2022/08/29 23:01:08 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] CUDA available: True numpy_random_seed: 387890681 GPU 0: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.10.0+cu111 OpenCV: 4.5.4 MMEngine: 0.0.1 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 1 ------------------------------------------------------------ 2022/08/29 23:01:09 - mmengine - INFO - Config: model = dict( type='DBNet', backbone=dict( type='mmdet.ResNet', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=-1, norm_cfg=dict(type='BN', requires_grad=True), norm_eval=False, style='pytorch', dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False), init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'), stage_with_dcn=(False, True, True, True)), neck=dict( type='FPNC', in_channels=[256, 512, 1024, 2048], lateral_channels=256, asf_cfg=dict(attention_type='ScaleChannelSpatial')), det_head=dict( type='DBHead', in_channels=256, module_loss=dict(type='DBModuleLoss'), postprocessor=dict( type='DBPostprocessor', text_repr_type='quad', epsilon_ratio=0.002)), data_preprocessor=dict( type='TextDetDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], bgr_to_rgb=True, pad_size_divisor=32)) train_pipeline = [ dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), dict( type='LoadOCRAnnotations', with_bbox=True, with_polygon=True, with_label=True), dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.12549019607843137, saturation=0.5), dict( type='ImgAugWrapper', args=[['Fliplr', 0.5], { 'cls': 'Affine', 'rotate': [-10, 10] }, ['Resize', [0.5, 3.0]]]), dict(type='RandomCrop', min_side_ratio=0.1), dict(type='Resize', scale=(640, 640), keep_ratio=True), dict(type='Pad', size=(640, 640)), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape')) ] test_pipeline = [ dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), dict(type='Resize', scale=(4068, 1024), keep_ratio=True), dict( type='LoadOCRAnnotations', with_polygon=True, with_bbox=True, with_label=True), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor', 'instances')) ] default_scope = 'mmocr' env_cfg = dict( cudnn_benchmark=True, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) randomness = dict(seed=None) default_hooks = dict( timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=5), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=20, out_dir=''), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffer=dict(type='SyncBuffersHook'), visualization=dict( type='VisualizationHook', interval=1, enable=False, show=False, draw_gt=False, draw_pred=False)) log_level = 'INFO' log_processor = dict(type='LogProcessor', window_size=10, by_epoch=True) load_from = '~/dbnet_pretrain/dbnetpp_r50dcnv2_fpnc_100k_iter_synthtext-20220502-db297554.pth' resume = False val_evaluator = dict(type='HmeanIOUMetric') test_evaluator = dict(type='HmeanIOUMetric') vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='TextDetLocalVisualizer', name='visualizer', vis_backends=[dict(type='LocalVisBackend')]) ic15_det_data_root = 'data/det/icdar2015' ic15_det_train = dict( type='OCRDataset', data_root='data/det/icdar2015', ann_file='instances_training.json', data_prefix=dict(img_path='imgs/'), filter_cfg=dict(filter_empty_gt=True, min_size=32), pipeline=None) ic15_det_test = dict( type='OCRDataset', data_root='data/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=None) optim_wrapper = dict( type='OptimWrapper', optimizer=dict(type='SGD', lr=0.007, momentum=0.9, weight_decay=0.0001)) train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=1200, val_interval=20) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [dict(type='PolyLR', power=0.9, eta_min=1e-07, end=1200)] train_list = [ dict( type='OCRDataset', data_root='data/det/icdar2015', ann_file='instances_training.json', data_prefix=dict(img_path='imgs/'), filter_cfg=dict(filter_empty_gt=True, min_size=32), pipeline=None) ] test_list = [ dict( type='OCRDataset', data_root='data/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=None) ] train_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/det/icdar2015', ann_file='instances_training.json', data_prefix=dict(img_path='imgs/'), filter_cfg=dict(filter_empty_gt=True, min_size=32), pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', color_type='color_ignore_orientation', file_client_args=dict(backend='petrel')), dict( type='LoadOCRAnnotations', with_bbox=True, with_polygon=True, with_label=True), dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.12549019607843137, saturation=0.5), dict( type='ImgAugWrapper', args=[['Fliplr', 0.5], { 'cls': 'Affine', 'rotate': [-10, 10] }, ['Resize', [0.5, 3.0]]]), dict(type='RandomCrop', min_side_ratio=0.1), dict(type='Resize', scale=(640, 640), keep_ratio=True), dict(type='Pad', size=(640, 640)), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape')) ])) val_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', color_type='color_ignore_orientation', file_client_args=dict(backend='petrel')), dict(type='Resize', scale=(4068, 1024), keep_ratio=True), dict( type='LoadOCRAnnotations', with_polygon=True, with_bbox=True, with_label=True), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor', 'instances')) ])) test_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', color_type='color_ignore_orientation', file_client_args=dict(backend='petrel')), dict(type='Resize', scale=(4068, 1024), keep_ratio=True), dict( type='LoadOCRAnnotations', with_polygon=True, with_bbox=True, with_label=True), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor', 'instances')) ])) launcher = 'slurm' work_dir = './work_dirs/dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015' Name of parameter - Initialization information backbone.conv1.weight - torch.Size([64, 3, 7, 7]): PretrainedInit: load from torchvision://resnet50 backbone.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.conv1.weight - torch.Size([64, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn2.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn2.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn3.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn3.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.downsample.0.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.downsample.1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.downsample.1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn2.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn2.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn3.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn3.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn2.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn2.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn3.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn3.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.conv1.weight - torch.Size([128, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.conv2.conv_offset.weight - torch.Size([27, 128, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.0.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.0.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.downsample.0.weight - torch.Size([512, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.downsample.1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.downsample.1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.conv2.conv_offset.weight - torch.Size([27, 128, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.1.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.1.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.conv2.conv_offset.weight - torch.Size([27, 128, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.2.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.2.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.conv2.conv_offset.weight - torch.Size([27, 128, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.3.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer2.3.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.conv1.weight - torch.Size([256, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.conv2.conv_offset.weight - torch.Size([27, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.0.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.0.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.downsample.0.weight - torch.Size([1024, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.downsample.1.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.downsample.1.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.conv2.conv_offset.weight - torch.Size([27, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.1.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.1.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.conv2.conv_offset.weight - torch.Size([27, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.2.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.2.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.conv2.conv_offset.weight - torch.Size([27, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.3.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.3.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.conv2.conv_offset.weight - torch.Size([27, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.4.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.4.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.conv2.conv_offset.weight - torch.Size([27, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.5.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer3.5.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.conv1.weight - torch.Size([512, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.conv2.conv_offset.weight - torch.Size([27, 512, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer4.0.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer4.0.bn2.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn2.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn3.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn3.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.downsample.0.weight - torch.Size([2048, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.downsample.1.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.downsample.1.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.conv2.conv_offset.weight - torch.Size([27, 512, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer4.1.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer4.1.bn2.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn2.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn3.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn3.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.conv2.conv_offset.weight - torch.Size([27, 512, 3, 3]): The value is the same before and after calling `init_weights` of DBNet backbone.layer4.2.conv2.conv_offset.bias - torch.Size([27]): The value is the same before and after calling `init_weights` of DBNet backbone.layer4.2.bn2.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn2.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn3.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn3.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 neck.lateral_convs.0.conv.weight - torch.Size([256, 256, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.lateral_convs.1.conv.weight - torch.Size([256, 512, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.lateral_convs.2.conv.weight - torch.Size([256, 1024, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.lateral_convs.3.conv.weight - torch.Size([256, 2048, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.0.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.1.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.2.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.3.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.asf_conv.conv.weight - torch.Size([256, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.asf_conv.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of DBNet neck.asf_attn.channel_wise.0.conv.weight - torch.Size([64, 256, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.channel_wise.1.conv.weight - torch.Size([256, 64, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.spatial_wise.0.conv.weight - torch.Size([1, 1, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.spatial_wise.1.conv.weight - torch.Size([1, 1, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.attention_wise.conv.weight - torch.Size([4, 256, 1, 1]): Initialized by user-defined `init_weights` in ConvModule det_head.binarize.0.weight - torch.Size([64, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.3.weight - torch.Size([64, 64, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.3.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.4.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.4.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.6.weight - torch.Size([64, 1, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.6.bias - torch.Size([1]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.0.weight - torch.Size([64, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.3.weight - torch.Size([64, 64, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.3.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.4.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.4.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.6.weight - torch.Size([64, 1, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.6.bias - torch.Size([1]): The value is the same before and after calling `init_weights` of DBNet 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer2.0.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer2.1.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer2.2.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer2.3.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer3.0.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer3.1.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer3.2.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer3.3.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer3.4.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer3.5.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer4.0.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer4.1.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - ModulatedDeformConvPack backbone.layer4.2.conv2 is upgraded to version 2. 2022/08/29 23:03:50 - mmengine - INFO - Load checkpoint from ~/dbnet_pretrain/dbnetpp_r50dcnv2_fpnc_100k_iter_synthtext-20220502-db297554.pth 2022/08/29 23:07:51 - mmengine - INFO - Epoch(train) [1][5/63] lr: 7.0000e-03 memory: 48191 data_time: 44.7305 loss_prob: 2.5510 loss_thr: 0.8340 loss_db: 0.3972 loss: 3.7822 time: 48.1235 2022/08/29 23:07:56 - mmengine - INFO - Epoch(train) [1][10/63] lr: 7.0000e-03 eta: 21 days, 12:14:40 time: 24.5863 data_time: 22.4611 memory: 16198 loss_prob: 2.5794 loss_thr: 0.8199 loss_db: 0.4274 loss: 3.8266 2022/08/29 23:08:00 - mmengine - INFO - Epoch(train) [1][15/63] lr: 7.0000e-03 eta: 21 days, 12:14:40 time: 0.9536 data_time: 0.1111 memory: 16198 loss_prob: 2.4690 loss_thr: 0.7896 loss_db: 0.4234 loss: 3.6821 2022/08/29 23:08:05 - mmengine - INFO - Epoch(train) [1][20/63] lr: 7.0000e-03 eta: 11 days, 3:54:09 time: 0.9350 data_time: 0.0347 memory: 16198 loss_prob: 2.4320 loss_thr: 0.7915 loss_db: 0.3954 loss: 3.6189 2022/08/29 23:08:11 - mmengine - INFO - Epoch(train) [1][25/63] lr: 7.0000e-03 eta: 11 days, 3:54:09 time: 1.0294 data_time: 0.0935 memory: 16198 loss_prob: 2.3868 loss_thr: 0.7945 loss_db: 0.3920 loss: 3.5733 2022/08/29 23:08:15 - mmengine - INFO - Epoch(train) [1][30/63] lr: 7.0000e-03 eta: 7 days, 17:29:11 time: 0.9873 data_time: 0.1020 memory: 16198 loss_prob: 2.2988 loss_thr: 0.8036 loss_db: 0.3862 loss: 3.4886 2022/08/29 23:08:20 - mmengine - INFO - Epoch(train) [1][35/63] lr: 7.0000e-03 eta: 7 days, 17:29:11 time: 0.9133 data_time: 0.0558 memory: 16198 loss_prob: 2.2099 loss_thr: 0.8021 loss_db: 0.3804 loss: 3.3924 2022/08/29 23:08:25 - mmengine - INFO - Epoch(train) [1][40/63] lr: 7.0000e-03 eta: 5 days, 23:57:58 time: 0.9281 data_time: 0.0947 memory: 16198 loss_prob: 2.1226 loss_thr: 0.7697 loss_db: 0.3763 loss: 3.2686 2022/08/29 23:08:31 - mmengine - INFO - Epoch(train) [1][45/63] lr: 7.0000e-03 eta: 5 days, 23:57:58 time: 1.0930 data_time: 0.1141 memory: 16198 loss_prob: 2.0017 loss_thr: 0.7527 loss_db: 0.3307 loss: 3.0850 2022/08/29 23:08:37 - mmengine - INFO - Epoch(train) [1][50/63] lr: 7.0000e-03 eta: 5 days, 0:16:59 time: 1.2212 data_time: 0.1276 memory: 16198 loss_prob: 1.9976 loss_thr: 0.7640 loss_db: 0.3226 loss: 3.0842 2022/08/29 23:08:43 - mmengine - INFO - Epoch(train) [1][55/63] lr: 7.0000e-03 eta: 5 days, 0:16:59 time: 1.1950 data_time: 0.1167 memory: 16198 loss_prob: 2.1050 loss_thr: 0.7759 loss_db: 0.3506 loss: 3.2315 2022/08/29 23:08:49 - mmengine - INFO - Epoch(train) [1][60/63] lr: 7.0000e-03 eta: 4 days, 8:21:49 time: 1.1841 data_time: 0.1050 memory: 16198 loss_prob: 1.9185 loss_thr: 0.7379 loss_db: 0.3187 loss: 2.9751 2022/08/29 23:09:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:09:10 - mmengine - INFO - Epoch(train) [2][5/63] lr: 6.9947e-03 eta: 4 days, 8:21:49 time: 2.3033 data_time: 0.3072 memory: 40923 loss_prob: 1.7161 loss_thr: 0.7264 loss_db: 0.2842 loss: 2.7267 2022/08/29 23:09:17 - mmengine - INFO - Epoch(train) [2][10/63] lr: 6.9947e-03 eta: 3 days, 18:03:43 time: 1.4956 data_time: 0.3597 memory: 16198 loss_prob: 1.6659 loss_thr: 0.7079 loss_db: 0.2765 loss: 2.6502 2022/08/29 23:09:23 - mmengine - INFO - Epoch(train) [2][15/63] lr: 6.9947e-03 eta: 3 days, 18:03:43 time: 1.2866 data_time: 0.1116 memory: 16198 loss_prob: 1.5919 loss_thr: 0.6617 loss_db: 0.2581 loss: 2.5117 2022/08/29 23:09:29 - mmengine - INFO - Epoch(train) [2][20/63] lr: 6.9947e-03 eta: 3 days, 10:19:50 time: 1.2384 data_time: 0.0998 memory: 16198 loss_prob: 1.7231 loss_thr: 0.6894 loss_db: 0.2881 loss: 2.7007 2022/08/29 23:09:34 - mmengine - INFO - Epoch(train) [2][25/63] lr: 6.9947e-03 eta: 3 days, 10:19:50 time: 1.0664 data_time: 0.1110 memory: 16198 loss_prob: 1.7726 loss_thr: 0.7073 loss_db: 0.3005 loss: 2.7804 2022/08/29 23:09:38 - mmengine - INFO - Epoch(train) [2][30/63] lr: 6.9947e-03 eta: 3 days, 3:37:23 time: 0.9555 data_time: 0.0926 memory: 16198 loss_prob: 1.8376 loss_thr: 0.7312 loss_db: 0.3085 loss: 2.8773 2022/08/29 23:09:43 - mmengine - INFO - Epoch(train) [2][35/63] lr: 6.9947e-03 eta: 3 days, 3:37:23 time: 0.9226 data_time: 0.0897 memory: 16198 loss_prob: 1.9728 loss_thr: 0.7469 loss_db: 0.3381 loss: 3.0577 2022/08/29 23:09:47 - mmengine - INFO - Epoch(train) [2][40/63] lr: 6.9947e-03 eta: 2 days, 22:03:45 time: 0.8794 data_time: 0.0531 memory: 16198 loss_prob: 1.9150 loss_thr: 0.7218 loss_db: 0.3226 loss: 2.9594 2022/08/29 23:09:52 - mmengine - INFO - Epoch(train) [2][45/63] lr: 6.9947e-03 eta: 2 days, 22:03:45 time: 0.9293 data_time: 0.0894 memory: 16198 loss_prob: 1.8196 loss_thr: 0.7170 loss_db: 0.3033 loss: 2.8399 2022/08/29 23:09:57 - mmengine - INFO - Epoch(train) [2][50/63] lr: 6.9947e-03 eta: 2 days, 17:39:19 time: 0.9708 data_time: 0.1040 memory: 16198 loss_prob: 1.8569 loss_thr: 0.7251 loss_db: 0.3179 loss: 2.8998 2022/08/29 23:10:02 - mmengine - INFO - Epoch(train) [2][55/63] lr: 6.9947e-03 eta: 2 days, 17:39:19 time: 0.9541 data_time: 0.0563 memory: 16198 loss_prob: 1.8856 loss_thr: 0.7250 loss_db: 0.3209 loss: 2.9314 2022/08/29 23:10:07 - mmengine - INFO - Epoch(train) [2][60/63] lr: 6.9947e-03 eta: 2 days, 14:01:07 time: 1.0028 data_time: 0.1063 memory: 16198 loss_prob: 1.8089 loss_thr: 0.7167 loss_db: 0.3122 loss: 2.8378 2022/08/29 23:10:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:10:16 - mmengine - INFO - Epoch(train) [3][5/63] lr: 6.9895e-03 eta: 2 days, 14:01:07 time: 1.0723 data_time: 0.2595 memory: 16198 loss_prob: 1.8164 loss_thr: 0.7218 loss_db: 0.3073 loss: 2.8454 2022/08/29 23:10:21 - mmengine - INFO - Epoch(train) [3][10/63] lr: 6.9895e-03 eta: 2 days, 9:49:20 time: 1.1299 data_time: 0.2911 memory: 16198 loss_prob: 1.8354 loss_thr: 0.7166 loss_db: 0.3004 loss: 2.8524 2022/08/29 23:10:26 - mmengine - INFO - Epoch(train) [3][15/63] lr: 6.9895e-03 eta: 2 days, 9:49:20 time: 1.0477 data_time: 0.0885 memory: 16198 loss_prob: 1.6503 loss_thr: 0.6683 loss_db: 0.2677 loss: 2.5863 2022/08/29 23:10:32 - mmengine - INFO - Epoch(train) [3][20/63] lr: 6.9895e-03 eta: 2 days, 7:24:07 time: 1.0778 data_time: 0.0970 memory: 16198 loss_prob: 1.5808 loss_thr: 0.6689 loss_db: 0.2608 loss: 2.5105 2022/08/29 23:10:36 - mmengine - INFO - Epoch(train) [3][25/63] lr: 6.9895e-03 eta: 2 days, 7:24:07 time: 0.9809 data_time: 0.0998 memory: 16198 loss_prob: 1.6704 loss_thr: 0.7071 loss_db: 0.2776 loss: 2.6551 2022/08/29 23:10:41 - mmengine - INFO - Epoch(train) [3][30/63] lr: 6.9895e-03 eta: 2 days, 5:03:54 time: 0.9091 data_time: 0.0545 memory: 16198 loss_prob: 1.7590 loss_thr: 0.6967 loss_db: 0.2858 loss: 2.7415 2022/08/29 23:10:46 - mmengine - INFO - Epoch(train) [3][35/63] lr: 6.9895e-03 eta: 2 days, 5:03:54 time: 0.9900 data_time: 0.0912 memory: 16198 loss_prob: 2.0377 loss_thr: 0.6853 loss_db: 0.3183 loss: 3.0413 2022/08/29 23:10:51 - mmengine - INFO - Epoch(train) [3][40/63] lr: 6.9895e-03 eta: 2 days, 3:05:27 time: 0.9737 data_time: 0.0896 memory: 16198 loss_prob: 2.1461 loss_thr: 0.7397 loss_db: 0.3482 loss: 3.2340 2022/08/29 23:10:55 - mmengine - INFO - Epoch(train) [3][45/63] lr: 6.9895e-03 eta: 2 days, 3:05:27 time: 0.9177 data_time: 0.0602 memory: 16198 loss_prob: 2.0166 loss_thr: 0.7598 loss_db: 0.3530 loss: 3.1294 2022/08/29 23:11:00 - mmengine - INFO - Epoch(train) [3][50/63] lr: 6.9895e-03 eta: 2 days, 1:20:13 time: 0.9707 data_time: 0.1078 memory: 16198 loss_prob: 1.9755 loss_thr: 0.7465 loss_db: 0.3431 loss: 3.0651 2022/08/29 23:11:05 - mmengine - INFO - Epoch(train) [3][55/63] lr: 6.9895e-03 eta: 2 days, 1:20:13 time: 0.9274 data_time: 0.0972 memory: 16198 loss_prob: 1.9026 loss_thr: 0.7595 loss_db: 0.3274 loss: 2.9895 2022/08/29 23:11:10 - mmengine - INFO - Epoch(train) [3][60/63] lr: 6.9895e-03 eta: 1 day, 23:46:45 time: 0.9775 data_time: 0.0514 memory: 16198 loss_prob: 1.7902 loss_thr: 0.7174 loss_db: 0.3026 loss: 2.8101 2022/08/29 23:11:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:11:21 - mmengine - INFO - Epoch(train) [4][5/63] lr: 6.9842e-03 eta: 1 day, 23:46:45 time: 1.2237 data_time: 0.3591 memory: 16198 loss_prob: 1.6519 loss_thr: 0.7127 loss_db: 0.2730 loss: 2.6376 2022/08/29 23:11:27 - mmengine - INFO - Epoch(train) [4][10/63] lr: 6.9842e-03 eta: 1 day, 22:06:47 time: 1.3898 data_time: 0.3620 memory: 16198 loss_prob: 1.8620 loss_thr: 0.7395 loss_db: 0.3189 loss: 2.9205 2022/08/29 23:11:32 - mmengine - INFO - Epoch(train) [4][15/63] lr: 6.9842e-03 eta: 1 day, 22:06:47 time: 1.0783 data_time: 0.0502 memory: 16198 loss_prob: 1.8167 loss_thr: 0.7437 loss_db: 0.3151 loss: 2.8755 2022/08/29 23:11:37 - mmengine - INFO - Epoch(train) [4][20/63] lr: 6.9842e-03 eta: 1 day, 20:54:39 time: 1.0080 data_time: 0.0542 memory: 16198 loss_prob: 1.6880 loss_thr: 0.7151 loss_db: 0.2903 loss: 2.6934 2022/08/29 23:11:41 - mmengine - INFO - Epoch(train) [4][25/63] lr: 6.9842e-03 eta: 1 day, 20:54:39 time: 0.9714 data_time: 0.0567 memory: 16198 loss_prob: 1.8697 loss_thr: 0.7282 loss_db: 0.3192 loss: 2.9172 2022/08/29 23:11:46 - mmengine - INFO - Epoch(train) [4][30/63] lr: 6.9842e-03 eta: 1 day, 19:43:47 time: 0.9153 data_time: 0.0327 memory: 16198 loss_prob: 2.1078 loss_thr: 0.7636 loss_db: 0.3554 loss: 3.2268 2022/08/29 23:11:51 - mmengine - INFO - Epoch(train) [4][35/63] lr: 6.9842e-03 eta: 1 day, 19:43:47 time: 0.9479 data_time: 0.0513 memory: 16198 loss_prob: 2.1182 loss_thr: 0.7604 loss_db: 0.3621 loss: 3.2408 2022/08/29 23:11:56 - mmengine - INFO - Epoch(train) [4][40/63] lr: 6.9842e-03 eta: 1 day, 18:43:42 time: 0.9994 data_time: 0.0555 memory: 16198 loss_prob: 1.9800 loss_thr: 0.7458 loss_db: 0.3438 loss: 3.0696 2022/08/29 23:12:01 - mmengine - INFO - Epoch(train) [4][45/63] lr: 6.9842e-03 eta: 1 day, 18:43:42 time: 1.0236 data_time: 0.0572 memory: 16198 loss_prob: 2.0124 loss_thr: 0.7545 loss_db: 0.3520 loss: 3.1190 2022/08/29 23:12:06 - mmengine - INFO - Epoch(train) [4][50/63] lr: 6.9842e-03 eta: 1 day, 17:47:50 time: 0.9845 data_time: 0.0556 memory: 16198 loss_prob: 2.0599 loss_thr: 0.7496 loss_db: 0.3508 loss: 3.1603 2022/08/29 23:12:10 - mmengine - INFO - Epoch(train) [4][55/63] lr: 6.9842e-03 eta: 1 day, 17:47:50 time: 0.9056 data_time: 0.0270 memory: 16198 loss_prob: 1.9499 loss_thr: 0.7479 loss_db: 0.3253 loss: 3.0232 2022/08/29 23:12:16 - mmengine - INFO - Epoch(train) [4][60/63] lr: 6.9842e-03 eta: 1 day, 16:57:26 time: 1.0039 data_time: 0.0434 memory: 16198 loss_prob: 1.9390 loss_thr: 0.7561 loss_db: 0.3307 loss: 3.0259 2022/08/29 23:12:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:12:26 - mmengine - INFO - Epoch(train) [5][5/63] lr: 6.9790e-03 eta: 1 day, 16:57:26 time: 1.2785 data_time: 0.3513 memory: 16198 loss_prob: 2.0483 loss_thr: 0.7495 loss_db: 0.3733 loss: 3.1710 2022/08/29 23:12:31 - mmengine - INFO - Epoch(train) [5][10/63] lr: 6.9790e-03 eta: 1 day, 15:55:30 time: 1.2605 data_time: 0.3665 memory: 16198 loss_prob: 1.8028 loss_thr: 0.7235 loss_db: 0.2999 loss: 2.8262 2022/08/29 23:12:35 - mmengine - INFO - Epoch(train) [5][15/63] lr: 6.9790e-03 eta: 1 day, 15:55:30 time: 0.9313 data_time: 0.0543 memory: 16198 loss_prob: 1.7258 loss_thr: 0.7128 loss_db: 0.2807 loss: 2.7192 2022/08/29 23:12:40 - mmengine - INFO - Epoch(train) [5][20/63] lr: 6.9790e-03 eta: 1 day, 15:11:48 time: 0.9677 data_time: 0.0373 memory: 16198 loss_prob: 1.8516 loss_thr: 0.6960 loss_db: 0.3155 loss: 2.8631 2022/08/29 23:12:46 - mmengine - INFO - Epoch(train) [5][25/63] lr: 6.9790e-03 eta: 1 day, 15:11:48 time: 1.0447 data_time: 0.0623 memory: 16198 loss_prob: 1.9584 loss_thr: 0.7399 loss_db: 0.3425 loss: 3.0408 2022/08/29 23:12:50 - mmengine - INFO - Epoch(train) [5][30/63] lr: 6.9790e-03 eta: 1 day, 14:30:38 time: 0.9557 data_time: 0.0555 memory: 16198 loss_prob: 1.8784 loss_thr: 0.7362 loss_db: 0.3247 loss: 2.9393 2022/08/29 23:12:55 - mmengine - INFO - Epoch(train) [5][35/63] lr: 6.9790e-03 eta: 1 day, 14:30:38 time: 0.8867 data_time: 0.0385 memory: 16198 loss_prob: 1.7812 loss_thr: 0.7191 loss_db: 0.3050 loss: 2.8053 2022/08/29 23:13:00 - mmengine - INFO - Epoch(train) [5][40/63] lr: 6.9790e-03 eta: 1 day, 13:53:42 time: 0.9884 data_time: 0.0509 memory: 16198 loss_prob: 1.8569 loss_thr: 0.7328 loss_db: 0.3244 loss: 2.9142 2022/08/29 23:13:04 - mmengine - INFO - Epoch(train) [5][45/63] lr: 6.9790e-03 eta: 1 day, 13:53:42 time: 0.9320 data_time: 0.0548 memory: 16198 loss_prob: 1.8428 loss_thr: 0.7208 loss_db: 0.3199 loss: 2.8834 2022/08/29 23:13:08 - mmengine - INFO - Epoch(train) [5][50/63] lr: 6.9790e-03 eta: 1 day, 13:13:17 time: 0.8464 data_time: 0.0385 memory: 16198 loss_prob: 1.8511 loss_thr: 0.7362 loss_db: 0.3206 loss: 2.9079 2022/08/29 23:13:13 - mmengine - INFO - Epoch(train) [5][55/63] lr: 6.9790e-03 eta: 1 day, 13:13:17 time: 0.8979 data_time: 0.0416 memory: 16198 loss_prob: 1.8113 loss_thr: 0.7327 loss_db: 0.3035 loss: 2.8475 2022/08/29 23:13:17 - mmengine - INFO - Epoch(train) [5][60/63] lr: 6.9790e-03 eta: 1 day, 12:35:37 time: 0.8502 data_time: 0.0462 memory: 16198 loss_prob: 1.6703 loss_thr: 0.7240 loss_db: 0.2735 loss: 2.6678 2022/08/29 23:13:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:13:28 - mmengine - INFO - Epoch(train) [6][5/63] lr: 6.9737e-03 eta: 1 day, 12:35:37 time: 1.2675 data_time: 0.3560 memory: 16198 loss_prob: 1.5761 loss_thr: 0.6771 loss_db: 0.2494 loss: 2.5026 2022/08/29 23:13:33 - mmengine - INFO - Epoch(train) [6][10/63] lr: 6.9737e-03 eta: 1 day, 12:02:54 time: 1.4370 data_time: 0.3838 memory: 16198 loss_prob: 1.6049 loss_thr: 0.6740 loss_db: 0.2611 loss: 2.5400 2022/08/29 23:13:39 - mmengine - INFO - Epoch(train) [6][15/63] lr: 6.9737e-03 eta: 1 day, 12:02:54 time: 1.0500 data_time: 0.0614 memory: 16198 loss_prob: 1.4917 loss_thr: 0.6548 loss_db: 0.2434 loss: 2.3899 2022/08/29 23:13:45 - mmengine - INFO - Epoch(train) [6][20/63] lr: 6.9737e-03 eta: 1 day, 11:40:28 time: 1.1324 data_time: 0.0552 memory: 16198 loss_prob: 1.4926 loss_thr: 0.6819 loss_db: 0.2377 loss: 2.4122 2022/08/29 23:13:49 - mmengine - INFO - Epoch(train) [6][25/63] lr: 6.9737e-03 eta: 1 day, 11:40:28 time: 1.0635 data_time: 0.0571 memory: 16198 loss_prob: 1.5110 loss_thr: 0.7140 loss_db: 0.2437 loss: 2.4688 2022/08/29 23:13:54 - mmengine - INFO - Epoch(train) [6][30/63] lr: 6.9737e-03 eta: 1 day, 11:12:18 time: 0.9398 data_time: 0.0562 memory: 16198 loss_prob: 1.6528 loss_thr: 0.7342 loss_db: 0.2711 loss: 2.6581 2022/08/29 23:13:59 - mmengine - INFO - Epoch(train) [6][35/63] lr: 6.9737e-03 eta: 1 day, 11:12:18 time: 0.9353 data_time: 0.0575 memory: 16198 loss_prob: 1.8470 loss_thr: 0.7270 loss_db: 0.3090 loss: 2.8830 2022/08/29 23:14:03 - mmengine - INFO - Epoch(train) [6][40/63] lr: 6.9737e-03 eta: 1 day, 10:45:38 time: 0.9373 data_time: 0.0403 memory: 16198 loss_prob: 1.7599 loss_thr: 0.6851 loss_db: 0.2976 loss: 2.7426 2022/08/29 23:14:08 - mmengine - INFO - Epoch(train) [6][45/63] lr: 6.9737e-03 eta: 1 day, 10:45:38 time: 0.9983 data_time: 0.0999 memory: 16198 loss_prob: 1.7787 loss_thr: 0.7036 loss_db: 0.3056 loss: 2.7879 2022/08/29 23:14:13 - mmengine - INFO - Epoch(train) [6][50/63] lr: 6.9737e-03 eta: 1 day, 10:22:45 time: 1.0047 data_time: 0.1040 memory: 16198 loss_prob: 1.8087 loss_thr: 0.7237 loss_db: 0.3102 loss: 2.8426 2022/08/29 23:14:19 - mmengine - INFO - Epoch(train) [6][55/63] lr: 6.9737e-03 eta: 1 day, 10:22:45 time: 1.0148 data_time: 0.0577 memory: 16198 loss_prob: 1.6324 loss_thr: 0.6672 loss_db: 0.2685 loss: 2.5680 2022/08/29 23:14:23 - mmengine - INFO - Epoch(train) [6][60/63] lr: 6.9737e-03 eta: 1 day, 10:00:59 time: 1.0024 data_time: 0.0591 memory: 16198 loss_prob: 1.7046 loss_thr: 0.6975 loss_db: 0.2861 loss: 2.6881 2022/08/29 23:14:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:14:34 - mmengine - INFO - Epoch(train) [7][5/63] lr: 6.9685e-03 eta: 1 day, 10:00:59 time: 1.2699 data_time: 0.3711 memory: 16198 loss_prob: 1.7762 loss_thr: 0.7304 loss_db: 0.2852 loss: 2.7918 2022/08/29 23:14:39 - mmengine - INFO - Epoch(train) [7][10/63] lr: 6.9685e-03 eta: 1 day, 9:33:20 time: 1.2712 data_time: 0.3777 memory: 16198 loss_prob: 1.7801 loss_thr: 0.7303 loss_db: 0.2894 loss: 2.7998 2022/08/29 23:14:43 - mmengine - INFO - Epoch(train) [7][15/63] lr: 6.9685e-03 eta: 1 day, 9:33:20 time: 0.9301 data_time: 0.0473 memory: 16198 loss_prob: 2.0237 loss_thr: 0.7553 loss_db: 0.3445 loss: 3.1235 2022/08/29 23:14:50 - mmengine - INFO - Epoch(train) [7][20/63] lr: 6.9685e-03 eta: 1 day, 9:16:13 time: 1.0712 data_time: 0.0385 memory: 16198 loss_prob: 1.9952 loss_thr: 0.7531 loss_db: 0.3444 loss: 3.0927 2022/08/29 23:14:55 - mmengine - INFO - Epoch(train) [7][25/63] lr: 6.9685e-03 eta: 1 day, 9:16:13 time: 1.1094 data_time: 0.0690 memory: 16198 loss_prob: 1.7586 loss_thr: 0.7048 loss_db: 0.2964 loss: 2.7598 2022/08/29 23:14:59 - mmengine - INFO - Epoch(train) [7][30/63] lr: 6.9685e-03 eta: 1 day, 8:55:46 time: 0.9354 data_time: 0.0528 memory: 16198 loss_prob: 1.7258 loss_thr: 0.6943 loss_db: 0.2871 loss: 2.7072 2022/08/29 23:15:03 - mmengine - INFO - Epoch(train) [7][35/63] lr: 6.9685e-03 eta: 1 day, 8:55:46 time: 0.8938 data_time: 0.0346 memory: 16198 loss_prob: 1.8205 loss_thr: 0.7045 loss_db: 0.3110 loss: 2.8361 2022/08/29 23:15:09 - mmengine - INFO - Epoch(train) [7][40/63] lr: 6.9685e-03 eta: 1 day, 8:37:10 time: 0.9648 data_time: 0.0541 memory: 16198 loss_prob: 1.7010 loss_thr: 0.6759 loss_db: 0.2837 loss: 2.6605 2022/08/29 23:15:13 - mmengine - INFO - Epoch(train) [7][45/63] lr: 6.9685e-03 eta: 1 day, 8:37:10 time: 0.9975 data_time: 0.0887 memory: 16198 loss_prob: 1.6478 loss_thr: 0.7066 loss_db: 0.2713 loss: 2.6257 2022/08/29 23:15:18 - mmengine - INFO - Epoch(train) [7][50/63] lr: 6.9685e-03 eta: 1 day, 8:18:37 time: 0.9375 data_time: 0.0870 memory: 16198 loss_prob: 1.6834 loss_thr: 0.7088 loss_db: 0.2800 loss: 2.6722 2022/08/29 23:15:23 - mmengine - INFO - Epoch(train) [7][55/63] lr: 6.9685e-03 eta: 1 day, 8:18:37 time: 0.9072 data_time: 0.0542 memory: 16198 loss_prob: 1.6445 loss_thr: 0.7071 loss_db: 0.2790 loss: 2.6306 2022/08/29 23:15:28 - mmengine - INFO - Epoch(train) [7][60/63] lr: 6.9685e-03 eta: 1 day, 8:03:20 time: 1.0218 data_time: 0.0411 memory: 16198 loss_prob: 1.6809 loss_thr: 0.7388 loss_db: 0.2812 loss: 2.7010 2022/08/29 23:15:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:15:39 - mmengine - INFO - Epoch(train) [8][5/63] lr: 6.9632e-03 eta: 1 day, 8:03:20 time: 1.3412 data_time: 0.3849 memory: 16198 loss_prob: 1.6864 loss_thr: 0.7085 loss_db: 0.2773 loss: 2.6722 2022/08/29 23:15:43 - mmengine - INFO - Epoch(train) [8][10/63] lr: 6.9632e-03 eta: 1 day, 7:42:43 time: 1.2653 data_time: 0.3904 memory: 16198 loss_prob: 1.6688 loss_thr: 0.6954 loss_db: 0.2739 loss: 2.6381 2022/08/29 23:15:48 - mmengine - INFO - Epoch(train) [8][15/63] lr: 6.9632e-03 eta: 1 day, 7:42:43 time: 0.9283 data_time: 0.0629 memory: 16198 loss_prob: 1.7950 loss_thr: 0.7125 loss_db: 0.2996 loss: 2.8071 2022/08/29 23:15:52 - mmengine - INFO - Epoch(train) [8][20/63] lr: 6.9632e-03 eta: 1 day, 7:25:45 time: 0.9042 data_time: 0.0377 memory: 16198 loss_prob: 1.8364 loss_thr: 0.7240 loss_db: 0.3071 loss: 2.8675 2022/08/29 23:15:58 - mmengine - INFO - Epoch(train) [8][25/63] lr: 6.9632e-03 eta: 1 day, 7:25:45 time: 0.9578 data_time: 0.0579 memory: 16198 loss_prob: 1.9262 loss_thr: 0.7092 loss_db: 0.3137 loss: 2.9490 2022/08/29 23:16:02 - mmengine - INFO - Epoch(train) [8][30/63] lr: 6.9632e-03 eta: 1 day, 7:10:39 time: 0.9470 data_time: 0.0539 memory: 16198 loss_prob: 1.9405 loss_thr: 0.6987 loss_db: 0.3264 loss: 2.9656 2022/08/29 23:16:07 - mmengine - INFO - Epoch(train) [8][35/63] lr: 6.9632e-03 eta: 1 day, 7:10:39 time: 0.9080 data_time: 0.0336 memory: 16198 loss_prob: 1.8212 loss_thr: 0.7099 loss_db: 0.3146 loss: 2.8457 2022/08/29 23:16:11 - mmengine - INFO - Epoch(train) [8][40/63] lr: 6.9632e-03 eta: 1 day, 6:55:09 time: 0.9082 data_time: 0.0499 memory: 16198 loss_prob: 1.6606 loss_thr: 0.6859 loss_db: 0.2783 loss: 2.6248 2022/08/29 23:16:16 - mmengine - INFO - Epoch(train) [8][45/63] lr: 6.9632e-03 eta: 1 day, 6:55:09 time: 0.9206 data_time: 0.0584 memory: 16198 loss_prob: 1.7681 loss_thr: 0.6961 loss_db: 0.3039 loss: 2.7681 2022/08/29 23:16:20 - mmengine - INFO - Epoch(train) [8][50/63] lr: 6.9632e-03 eta: 1 day, 6:40:37 time: 0.9211 data_time: 0.0425 memory: 16198 loss_prob: 1.7625 loss_thr: 0.7035 loss_db: 0.2962 loss: 2.7623 2022/08/29 23:16:25 - mmengine - INFO - Epoch(train) [8][55/63] lr: 6.9632e-03 eta: 1 day, 6:40:37 time: 0.9240 data_time: 0.0491 memory: 16198 loss_prob: 1.5882 loss_thr: 0.6795 loss_db: 0.2582 loss: 2.5258 2022/08/29 23:16:30 - mmengine - INFO - Epoch(train) [8][60/63] lr: 6.9632e-03 eta: 1 day, 6:27:48 time: 0.9674 data_time: 0.0623 memory: 16198 loss_prob: 1.6098 loss_thr: 0.6985 loss_db: 0.2654 loss: 2.5737 2022/08/29 23:16:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:16:41 - mmengine - INFO - Epoch(train) [9][5/63] lr: 6.9580e-03 eta: 1 day, 6:27:48 time: 1.2263 data_time: 0.3372 memory: 16198 loss_prob: 1.6166 loss_thr: 0.6861 loss_db: 0.2747 loss: 2.5775 2022/08/29 23:16:46 - mmengine - INFO - Epoch(train) [9][10/63] lr: 6.9580e-03 eta: 1 day, 6:15:37 time: 1.4111 data_time: 0.3658 memory: 16198 loss_prob: 1.6262 loss_thr: 0.6856 loss_db: 0.2760 loss: 2.5878 2022/08/29 23:16:51 - mmengine - INFO - Epoch(train) [9][15/63] lr: 6.9580e-03 eta: 1 day, 6:15:37 time: 1.0677 data_time: 0.0602 memory: 16198 loss_prob: 1.6613 loss_thr: 0.6982 loss_db: 0.2792 loss: 2.6387 2022/08/29 23:16:56 - mmengine - INFO - Epoch(train) [9][20/63] lr: 6.9580e-03 eta: 1 day, 6:04:14 time: 0.9845 data_time: 0.0482 memory: 16198 loss_prob: 1.6965 loss_thr: 0.6877 loss_db: 0.2882 loss: 2.6724 2022/08/29 23:17:00 - mmengine - INFO - Epoch(train) [9][25/63] lr: 6.9580e-03 eta: 1 day, 6:04:14 time: 0.9063 data_time: 0.0463 memory: 16198 loss_prob: 1.6346 loss_thr: 0.6859 loss_db: 0.2768 loss: 2.5973 2022/08/29 23:17:05 - mmengine - INFO - Epoch(train) [9][30/63] lr: 6.9580e-03 eta: 1 day, 5:51:33 time: 0.9107 data_time: 0.0301 memory: 16198 loss_prob: 1.5113 loss_thr: 0.6682 loss_db: 0.2458 loss: 2.4253 2022/08/29 23:17:09 - mmengine - INFO - Epoch(train) [9][35/63] lr: 6.9580e-03 eta: 1 day, 5:51:33 time: 0.9124 data_time: 0.0549 memory: 16198 loss_prob: 1.5140 loss_thr: 0.6474 loss_db: 0.2418 loss: 2.4032 2022/08/29 23:17:14 - mmengine - INFO - Epoch(train) [9][40/63] lr: 6.9580e-03 eta: 1 day, 5:37:55 time: 0.8495 data_time: 0.0493 memory: 16198 loss_prob: 1.5883 loss_thr: 0.6510 loss_db: 0.2568 loss: 2.4961 2022/08/29 23:17:18 - mmengine - INFO - Epoch(train) [9][45/63] lr: 6.9580e-03 eta: 1 day, 5:37:55 time: 0.8555 data_time: 0.0305 memory: 16198 loss_prob: 1.5566 loss_thr: 0.6782 loss_db: 0.2500 loss: 2.4849 2022/08/29 23:17:23 - mmengine - INFO - Epoch(train) [9][50/63] lr: 6.9580e-03 eta: 1 day, 5:26:11 time: 0.9123 data_time: 0.0609 memory: 16198 loss_prob: 1.5449 loss_thr: 0.6874 loss_db: 0.2496 loss: 2.4820 2022/08/29 23:17:27 - mmengine - INFO - Epoch(train) [9][55/63] lr: 6.9580e-03 eta: 1 day, 5:26:11 time: 0.9169 data_time: 0.0563 memory: 16198 loss_prob: 1.5898 loss_thr: 0.7011 loss_db: 0.2563 loss: 2.5472 2022/08/29 23:17:32 - mmengine - INFO - Epoch(train) [9][60/63] lr: 6.9580e-03 eta: 1 day, 5:14:59 time: 0.9173 data_time: 0.0327 memory: 16198 loss_prob: 1.6322 loss_thr: 0.6952 loss_db: 0.2743 loss: 2.6017 2022/08/29 23:17:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:17:43 - mmengine - INFO - Epoch(train) [10][5/63] lr: 6.9527e-03 eta: 1 day, 5:14:59 time: 1.3042 data_time: 0.3996 memory: 16198 loss_prob: 1.7111 loss_thr: 0.6903 loss_db: 0.2941 loss: 2.6955 2022/08/29 23:17:47 - mmengine - INFO - Epoch(train) [10][10/63] lr: 6.9527e-03 eta: 1 day, 5:02:48 time: 1.2765 data_time: 0.4018 memory: 16198 loss_prob: 1.6636 loss_thr: 0.7105 loss_db: 0.2777 loss: 2.6518 2022/08/29 23:17:52 - mmengine - INFO - Epoch(train) [10][15/63] lr: 6.9527e-03 eta: 1 day, 5:02:48 time: 0.8968 data_time: 0.0526 memory: 16198 loss_prob: 1.6590 loss_thr: 0.7156 loss_db: 0.2770 loss: 2.6516 2022/08/29 23:17:58 - mmengine - INFO - Epoch(train) [10][20/63] lr: 6.9527e-03 eta: 1 day, 4:55:00 time: 1.0382 data_time: 0.0346 memory: 16198 loss_prob: 1.6173 loss_thr: 0.6809 loss_db: 0.2722 loss: 2.5704 2022/08/29 23:18:02 - mmengine - INFO - Epoch(train) [10][25/63] lr: 6.9527e-03 eta: 1 day, 4:55:00 time: 1.0522 data_time: 0.0600 memory: 16198 loss_prob: 1.7876 loss_thr: 0.7095 loss_db: 0.3017 loss: 2.7989 2022/08/29 23:18:07 - mmengine - INFO - Epoch(train) [10][30/63] lr: 6.9527e-03 eta: 1 day, 4:44:40 time: 0.9050 data_time: 0.0452 memory: 16198 loss_prob: 1.7075 loss_thr: 0.6853 loss_db: 0.2864 loss: 2.6791 2022/08/29 23:18:11 - mmengine - INFO - Epoch(train) [10][35/63] lr: 6.9527e-03 eta: 1 day, 4:44:40 time: 0.8958 data_time: 0.0330 memory: 16198 loss_prob: 1.5049 loss_thr: 0.6402 loss_db: 0.2498 loss: 2.3949 2022/08/29 23:18:16 - mmengine - INFO - Epoch(train) [10][40/63] lr: 6.9527e-03 eta: 1 day, 4:34:25 time: 0.8932 data_time: 0.0527 memory: 16198 loss_prob: 1.6839 loss_thr: 0.6517 loss_db: 0.2822 loss: 2.6178 2022/08/29 23:18:20 - mmengine - INFO - Epoch(train) [10][45/63] lr: 6.9527e-03 eta: 1 day, 4:34:25 time: 0.9057 data_time: 0.0466 memory: 16198 loss_prob: 1.8664 loss_thr: 0.7008 loss_db: 0.3188 loss: 2.8860 2022/08/29 23:18:25 - mmengine - INFO - Epoch(train) [10][50/63] lr: 6.9527e-03 eta: 1 day, 4:25:33 time: 0.9449 data_time: 0.0420 memory: 16198 loss_prob: 1.9491 loss_thr: 0.7264 loss_db: 0.3342 loss: 3.0097 2022/08/29 23:18:30 - mmengine - INFO - Epoch(train) [10][55/63] lr: 6.9527e-03 eta: 1 day, 4:25:33 time: 0.9415 data_time: 0.0493 memory: 16198 loss_prob: 1.9471 loss_thr: 0.6986 loss_db: 0.3382 loss: 2.9839 2022/08/29 23:18:36 - mmengine - INFO - Epoch(train) [10][60/63] lr: 6.9527e-03 eta: 1 day, 4:19:08 time: 1.0547 data_time: 0.0543 memory: 16198 loss_prob: 1.8017 loss_thr: 0.7031 loss_db: 0.3078 loss: 2.8126 2022/08/29 23:18:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:18:48 - mmengine - INFO - Epoch(train) [11][5/63] lr: 6.9474e-03 eta: 1 day, 4:19:08 time: 1.4229 data_time: 0.4447 memory: 16198 loss_prob: 1.6887 loss_thr: 0.6954 loss_db: 0.2785 loss: 2.6626 2022/08/29 23:18:52 - mmengine - INFO - Epoch(train) [11][10/63] lr: 6.9474e-03 eta: 1 day, 4:09:07 time: 1.2700 data_time: 0.4595 memory: 16198 loss_prob: 2.0388 loss_thr: 0.7334 loss_db: 0.3599 loss: 3.1321 2022/08/29 23:18:57 - mmengine - INFO - Epoch(train) [11][15/63] lr: 6.9474e-03 eta: 1 day, 4:09:07 time: 0.9217 data_time: 0.0508 memory: 16198 loss_prob: 1.9680 loss_thr: 0.7238 loss_db: 0.3532 loss: 3.0450 2022/08/29 23:19:01 - mmengine - INFO - Epoch(train) [11][20/63] lr: 6.9474e-03 eta: 1 day, 4:00:37 time: 0.9211 data_time: 0.0343 memory: 16198 loss_prob: 1.5918 loss_thr: 0.6778 loss_db: 0.2696 loss: 2.5393 2022/08/29 23:19:06 - mmengine - INFO - Epoch(train) [11][25/63] lr: 6.9474e-03 eta: 1 day, 4:00:37 time: 0.8992 data_time: 0.0598 memory: 16198 loss_prob: 1.5812 loss_thr: 0.7082 loss_db: 0.2646 loss: 2.5539 2022/08/29 23:19:11 - mmengine - INFO - Epoch(train) [11][30/63] lr: 6.9474e-03 eta: 1 day, 3:52:59 time: 0.9537 data_time: 0.0474 memory: 16198 loss_prob: 1.7290 loss_thr: 0.7281 loss_db: 0.2942 loss: 2.7514 2022/08/29 23:19:16 - mmengine - INFO - Epoch(train) [11][35/63] lr: 6.9474e-03 eta: 1 day, 3:52:59 time: 0.9786 data_time: 0.0324 memory: 16198 loss_prob: 1.7000 loss_thr: 0.7314 loss_db: 0.2866 loss: 2.7180 2022/08/29 23:19:21 - mmengine - INFO - Epoch(train) [11][40/63] lr: 6.9474e-03 eta: 1 day, 3:46:21 time: 0.9960 data_time: 0.0610 memory: 16198 loss_prob: 1.6934 loss_thr: 0.7243 loss_db: 0.2856 loss: 2.7033 2022/08/29 23:19:27 - mmengine - INFO - Epoch(train) [11][45/63] lr: 6.9474e-03 eta: 1 day, 3:46:21 time: 1.1708 data_time: 0.0630 memory: 16198 loss_prob: 1.8387 loss_thr: 0.7015 loss_db: 0.3410 loss: 2.8812 2022/08/29 23:19:33 - mmengine - INFO - Epoch(train) [11][50/63] lr: 6.9474e-03 eta: 1 day, 3:45:01 time: 1.2733 data_time: 0.0649 memory: 16198 loss_prob: 2.0100 loss_thr: 0.7211 loss_db: 0.3764 loss: 3.1076 2022/08/29 23:19:40 - mmengine - INFO - Epoch(train) [11][55/63] lr: 6.9474e-03 eta: 1 day, 3:45:01 time: 1.2440 data_time: 0.0581 memory: 16198 loss_prob: 1.8532 loss_thr: 0.7214 loss_db: 0.3133 loss: 2.8880 2022/08/29 23:19:48 - mmengine - INFO - Epoch(train) [11][60/63] lr: 6.9474e-03 eta: 1 day, 3:47:08 time: 1.4628 data_time: 0.0536 memory: 16198 loss_prob: 1.7460 loss_thr: 0.6976 loss_db: 0.2959 loss: 2.7396 2022/08/29 23:19:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:20:04 - mmengine - INFO - Epoch(train) [12][5/63] lr: 6.9422e-03 eta: 1 day, 3:47:08 time: 1.9800 data_time: 0.3073 memory: 16198 loss_prob: 1.8895 loss_thr: 0.7526 loss_db: 0.3212 loss: 2.9633 2022/08/29 23:20:10 - mmengine - INFO - Epoch(train) [12][10/63] lr: 6.9422e-03 eta: 1 day, 3:48:33 time: 1.8326 data_time: 0.3285 memory: 16198 loss_prob: 1.7464 loss_thr: 0.7233 loss_db: 0.2929 loss: 2.7627 2022/08/29 23:20:16 - mmengine - INFO - Epoch(train) [12][15/63] lr: 6.9422e-03 eta: 1 day, 3:48:33 time: 1.1716 data_time: 0.0403 memory: 16198 loss_prob: 1.6816 loss_thr: 0.7042 loss_db: 0.2767 loss: 2.6625 2022/08/29 23:20:24 - mmengine - INFO - Epoch(train) [12][20/63] lr: 6.9422e-03 eta: 1 day, 3:48:54 time: 1.3688 data_time: 0.0437 memory: 16198 loss_prob: 1.7748 loss_thr: 0.7037 loss_db: 0.3010 loss: 2.7796 2022/08/29 23:20:31 - mmengine - INFO - Epoch(train) [12][25/63] lr: 6.9422e-03 eta: 1 day, 3:48:54 time: 1.4954 data_time: 0.0686 memory: 16198 loss_prob: 1.8046 loss_thr: 0.7051 loss_db: 0.3135 loss: 2.8231 2022/08/29 23:20:40 - mmengine - INFO - Epoch(train) [12][30/63] lr: 6.9422e-03 eta: 1 day, 3:52:56 time: 1.5843 data_time: 0.0598 memory: 16198 loss_prob: 1.8559 loss_thr: 0.7295 loss_db: 0.3139 loss: 2.8992 2022/08/29 23:20:47 - mmengine - INFO - Epoch(train) [12][35/63] lr: 6.9422e-03 eta: 1 day, 3:52:56 time: 1.6169 data_time: 0.0564 memory: 16198 loss_prob: 1.8242 loss_thr: 0.7026 loss_db: 0.3000 loss: 2.8268 2022/08/29 23:20:54 - mmengine - INFO - Epoch(train) [12][40/63] lr: 6.9422e-03 eta: 1 day, 3:53:18 time: 1.3744 data_time: 0.0555 memory: 16198 loss_prob: 1.7478 loss_thr: 0.6868 loss_db: 0.2924 loss: 2.7269 2022/08/29 23:20:58 - mmengine - INFO - Epoch(train) [12][45/63] lr: 6.9422e-03 eta: 1 day, 3:53:18 time: 1.0915 data_time: 0.0480 memory: 16198 loss_prob: 1.6796 loss_thr: 0.6865 loss_db: 0.2833 loss: 2.6494 2022/08/29 23:21:03 - mmengine - INFO - Epoch(train) [12][50/63] lr: 6.9422e-03 eta: 1 day, 3:45:51 time: 0.9108 data_time: 0.0612 memory: 16198 loss_prob: 1.6276 loss_thr: 0.6821 loss_db: 0.2662 loss: 2.5759 2022/08/29 23:21:07 - mmengine - INFO - Epoch(train) [12][55/63] lr: 6.9422e-03 eta: 1 day, 3:45:51 time: 0.9179 data_time: 0.0518 memory: 16198 loss_prob: 1.6453 loss_thr: 0.6825 loss_db: 0.2682 loss: 2.5960 2022/08/29 23:21:12 - mmengine - INFO - Epoch(train) [12][60/63] lr: 6.9422e-03 eta: 1 day, 3:38:42 time: 0.9172 data_time: 0.0301 memory: 16198 loss_prob: 1.7802 loss_thr: 0.6944 loss_db: 0.2947 loss: 2.7693 2022/08/29 23:21:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:21:22 - mmengine - INFO - Epoch(train) [13][5/63] lr: 6.9369e-03 eta: 1 day, 3:38:42 time: 1.2256 data_time: 0.3777 memory: 16198 loss_prob: 1.7924 loss_thr: 0.7243 loss_db: 0.2996 loss: 2.8163 2022/08/29 23:21:27 - mmengine - INFO - Epoch(train) [13][10/63] lr: 6.9369e-03 eta: 1 day, 3:31:55 time: 1.3299 data_time: 0.3933 memory: 16198 loss_prob: 1.9848 loss_thr: 0.7629 loss_db: 0.3428 loss: 3.0906 2022/08/29 23:21:31 - mmengine - INFO - Epoch(train) [13][15/63] lr: 6.9369e-03 eta: 1 day, 3:31:55 time: 0.9013 data_time: 0.0451 memory: 16198 loss_prob: 1.7959 loss_thr: 0.7255 loss_db: 0.3014 loss: 2.8229 2022/08/29 23:21:35 - mmengine - INFO - Epoch(train) [13][20/63] lr: 6.9369e-03 eta: 1 day, 3:23:10 time: 0.7937 data_time: 0.0233 memory: 16198 loss_prob: 1.5945 loss_thr: 0.6935 loss_db: 0.2615 loss: 2.5495 2022/08/29 23:21:40 - mmengine - INFO - Epoch(train) [13][25/63] lr: 6.9369e-03 eta: 1 day, 3:23:10 time: 0.8338 data_time: 0.0428 memory: 16198 loss_prob: 1.5551 loss_thr: 0.6772 loss_db: 0.2527 loss: 2.4849 2022/08/29 23:21:44 - mmengine - INFO - Epoch(train) [13][30/63] lr: 6.9369e-03 eta: 1 day, 3:15:12 time: 0.8295 data_time: 0.0303 memory: 16198 loss_prob: 1.4545 loss_thr: 0.6674 loss_db: 0.2339 loss: 2.3558 2022/08/29 23:21:48 - mmengine - INFO - Epoch(train) [13][35/63] lr: 6.9369e-03 eta: 1 day, 3:15:12 time: 0.8507 data_time: 0.0192 memory: 16198 loss_prob: 1.6421 loss_thr: 0.6998 loss_db: 0.2739 loss: 2.6159 2022/08/29 23:21:53 - mmengine - INFO - Epoch(train) [13][40/63] lr: 6.9369e-03 eta: 1 day, 3:08:44 time: 0.9129 data_time: 0.0323 memory: 16198 loss_prob: 1.8175 loss_thr: 0.7200 loss_db: 0.3011 loss: 2.8387 2022/08/29 23:21:57 - mmengine - INFO - Epoch(train) [13][45/63] lr: 6.9369e-03 eta: 1 day, 3:08:44 time: 0.8574 data_time: 0.0325 memory: 16198 loss_prob: 1.6473 loss_thr: 0.6841 loss_db: 0.2648 loss: 2.5962 2022/08/29 23:22:01 - mmengine - INFO - Epoch(train) [13][50/63] lr: 6.9369e-03 eta: 1 day, 3:01:17 time: 0.8380 data_time: 0.0293 memory: 16198 loss_prob: 1.6644 loss_thr: 0.6937 loss_db: 0.2788 loss: 2.6370 2022/08/29 23:22:05 - mmengine - INFO - Epoch(train) [13][55/63] lr: 6.9369e-03 eta: 1 day, 3:01:17 time: 0.8549 data_time: 0.0247 memory: 16198 loss_prob: 1.7575 loss_thr: 0.6969 loss_db: 0.3040 loss: 2.7583 2022/08/29 23:22:11 - mmengine - INFO - Epoch(train) [13][60/63] lr: 6.9369e-03 eta: 1 day, 2:55:45 time: 0.9531 data_time: 0.0352 memory: 16198 loss_prob: 1.8773 loss_thr: 0.6939 loss_db: 0.3370 loss: 2.9082 2022/08/29 23:22:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:22:19 - mmengine - INFO - Epoch(train) [14][5/63] lr: 6.9317e-03 eta: 1 day, 2:55:45 time: 0.9597 data_time: 0.1981 memory: 16198 loss_prob: 1.7350 loss_thr: 0.6756 loss_db: 0.3000 loss: 2.7106 2022/08/29 23:22:23 - mmengine - INFO - Epoch(train) [14][10/63] lr: 6.9317e-03 eta: 1 day, 2:45:47 time: 1.0405 data_time: 0.2183 memory: 16198 loss_prob: 1.5693 loss_thr: 0.6554 loss_db: 0.2545 loss: 2.4792 2022/08/29 23:22:28 - mmengine - INFO - Epoch(train) [14][15/63] lr: 6.9317e-03 eta: 1 day, 2:45:47 time: 0.8793 data_time: 0.0365 memory: 16198 loss_prob: 1.6430 loss_thr: 0.7006 loss_db: 0.2733 loss: 2.6169 2022/08/29 23:22:32 - mmengine - INFO - Epoch(train) [14][20/63] lr: 6.9317e-03 eta: 1 day, 2:39:31 time: 0.8818 data_time: 0.0277 memory: 16198 loss_prob: 1.6874 loss_thr: 0.7197 loss_db: 0.2795 loss: 2.6866 2022/08/29 23:22:37 - mmengine - INFO - Epoch(train) [14][25/63] lr: 6.9317e-03 eta: 1 day, 2:39:31 time: 0.9714 data_time: 0.0585 memory: 16198 loss_prob: 1.6925 loss_thr: 0.6889 loss_db: 0.2809 loss: 2.6623 2022/08/29 23:22:42 - mmengine - INFO - Epoch(train) [14][30/63] lr: 6.9317e-03 eta: 1 day, 2:35:02 time: 0.9917 data_time: 0.0519 memory: 16198 loss_prob: 1.6473 loss_thr: 0.6854 loss_db: 0.2743 loss: 2.6070 2022/08/29 23:22:47 - mmengine - INFO - Epoch(train) [14][35/63] lr: 6.9317e-03 eta: 1 day, 2:35:02 time: 0.9748 data_time: 0.0331 memory: 16198 loss_prob: 1.6176 loss_thr: 0.6931 loss_db: 0.2716 loss: 2.5824 2022/08/29 23:22:52 - mmengine - INFO - Epoch(train) [14][40/63] lr: 6.9317e-03 eta: 1 day, 2:30:27 time: 0.9796 data_time: 0.0530 memory: 16198 loss_prob: 1.6511 loss_thr: 0.6829 loss_db: 0.2751 loss: 2.6091 2022/08/29 23:22:56 - mmengine - INFO - Epoch(train) [14][45/63] lr: 6.9317e-03 eta: 1 day, 2:30:27 time: 0.9207 data_time: 0.0489 memory: 16198 loss_prob: 1.5938 loss_thr: 0.6654 loss_db: 0.2608 loss: 2.5201 2022/08/29 23:23:01 - mmengine - INFO - Epoch(train) [14][50/63] lr: 6.9317e-03 eta: 1 day, 2:25:02 time: 0.9138 data_time: 0.0458 memory: 16198 loss_prob: 1.7038 loss_thr: 0.6807 loss_db: 0.2772 loss: 2.6617 2022/08/29 23:23:05 - mmengine - INFO - Epoch(train) [14][55/63] lr: 6.9317e-03 eta: 1 day, 2:25:02 time: 0.9182 data_time: 0.0555 memory: 16198 loss_prob: 1.6084 loss_thr: 0.6576 loss_db: 0.2523 loss: 2.5182 2022/08/29 23:23:11 - mmengine - INFO - Epoch(train) [14][60/63] lr: 6.9317e-03 eta: 1 day, 2:21:16 time: 1.0214 data_time: 0.0475 memory: 16198 loss_prob: 1.3753 loss_thr: 0.6140 loss_db: 0.2110 loss: 2.2003 2022/08/29 23:23:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:23:21 - mmengine - INFO - Epoch(train) [15][5/63] lr: 6.9264e-03 eta: 1 day, 2:21:16 time: 1.2295 data_time: 0.3687 memory: 16198 loss_prob: 1.5359 loss_thr: 0.6441 loss_db: 0.2485 loss: 2.4286 2022/08/29 23:23:26 - mmengine - INFO - Epoch(train) [15][10/63] lr: 6.9264e-03 eta: 1 day, 2:14:45 time: 1.2039 data_time: 0.3696 memory: 16198 loss_prob: 1.5010 loss_thr: 0.6220 loss_db: 0.2407 loss: 2.3637 2022/08/29 23:23:31 - mmengine - INFO - Epoch(train) [15][15/63] lr: 6.9264e-03 eta: 1 day, 2:14:45 time: 0.9403 data_time: 0.0485 memory: 16198 loss_prob: 1.4203 loss_thr: 0.6472 loss_db: 0.2269 loss: 2.2944 2022/08/29 23:23:37 - mmengine - INFO - Epoch(train) [15][20/63] lr: 6.9264e-03 eta: 1 day, 2:12:40 time: 1.1284 data_time: 0.0367 memory: 16198 loss_prob: 1.5125 loss_thr: 0.6741 loss_db: 0.2505 loss: 2.4371 2022/08/29 23:23:44 - mmengine - INFO - Epoch(train) [15][25/63] lr: 6.9264e-03 eta: 1 day, 2:12:40 time: 1.3178 data_time: 0.0543 memory: 16198 loss_prob: 1.5731 loss_thr: 0.6783 loss_db: 0.2657 loss: 2.5171 2022/08/29 23:23:49 - mmengine - INFO - Epoch(train) [15][30/63] lr: 6.9264e-03 eta: 1 day, 2:11:43 time: 1.2093 data_time: 0.0541 memory: 16198 loss_prob: 1.5123 loss_thr: 0.7017 loss_db: 0.2507 loss: 2.4647 2022/08/29 23:23:54 - mmengine - INFO - Epoch(train) [15][35/63] lr: 6.9264e-03 eta: 1 day, 2:11:43 time: 0.9707 data_time: 0.0539 memory: 16198 loss_prob: 1.5792 loss_thr: 0.7142 loss_db: 0.2606 loss: 2.5540 2022/08/29 23:23:59 - mmengine - INFO - Epoch(train) [15][40/63] lr: 6.9264e-03 eta: 1 day, 2:07:22 time: 0.9559 data_time: 0.0527 memory: 16198 loss_prob: 1.7024 loss_thr: 0.6947 loss_db: 0.2822 loss: 2.6793 2022/08/29 23:24:03 - mmengine - INFO - Epoch(train) [15][45/63] lr: 6.9264e-03 eta: 1 day, 2:07:22 time: 0.9737 data_time: 0.0373 memory: 16198 loss_prob: 1.6721 loss_thr: 0.6994 loss_db: 0.2781 loss: 2.6496 2022/08/29 23:24:08 - mmengine - INFO - Epoch(train) [15][50/63] lr: 6.9264e-03 eta: 1 day, 2:02:54 time: 0.9410 data_time: 0.0502 memory: 16198 loss_prob: 1.5568 loss_thr: 0.7061 loss_db: 0.2590 loss: 2.5219 2022/08/29 23:24:13 - mmengine - INFO - Epoch(train) [15][55/63] lr: 6.9264e-03 eta: 1 day, 2:02:54 time: 0.9249 data_time: 0.0456 memory: 16198 loss_prob: 1.5901 loss_thr: 0.7022 loss_db: 0.2602 loss: 2.5525 2022/08/29 23:24:18 - mmengine - INFO - Epoch(train) [15][60/63] lr: 6.9264e-03 eta: 1 day, 1:59:04 time: 0.9805 data_time: 0.0505 memory: 16198 loss_prob: 1.6987 loss_thr: 0.7113 loss_db: 0.2840 loss: 2.6940 2022/08/29 23:24:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:24:28 - mmengine - INFO - Epoch(train) [16][5/63] lr: 6.9211e-03 eta: 1 day, 1:59:04 time: 1.2193 data_time: 0.3855 memory: 16198 loss_prob: 1.4916 loss_thr: 0.6385 loss_db: 0.2478 loss: 2.3779 2022/08/29 23:24:33 - mmengine - INFO - Epoch(train) [16][10/63] lr: 6.9211e-03 eta: 1 day, 1:54:15 time: 1.2801 data_time: 0.3916 memory: 16198 loss_prob: 1.5386 loss_thr: 0.6653 loss_db: 0.2551 loss: 2.4589 2022/08/29 23:24:38 - mmengine - INFO - Epoch(train) [16][15/63] lr: 6.9211e-03 eta: 1 day, 1:54:15 time: 0.9869 data_time: 0.0534 memory: 16198 loss_prob: 1.7507 loss_thr: 0.6650 loss_db: 0.2778 loss: 2.6935 2022/08/29 23:24:43 - mmengine - INFO - Epoch(train) [16][20/63] lr: 6.9211e-03 eta: 1 day, 1:50:08 time: 0.9460 data_time: 0.0344 memory: 16198 loss_prob: 1.7388 loss_thr: 0.6515 loss_db: 0.2748 loss: 2.6651 2022/08/29 23:24:47 - mmengine - INFO - Epoch(train) [16][25/63] lr: 6.9211e-03 eta: 1 day, 1:50:08 time: 0.9414 data_time: 0.0472 memory: 16198 loss_prob: 1.7012 loss_thr: 0.6684 loss_db: 0.2814 loss: 2.6510 2022/08/29 23:24:53 - mmengine - INFO - Epoch(train) [16][30/63] lr: 6.9211e-03 eta: 1 day, 1:46:51 time: 1.0062 data_time: 0.0451 memory: 16198 loss_prob: 1.5510 loss_thr: 0.6539 loss_db: 0.2494 loss: 2.4543 2022/08/29 23:24:58 - mmengine - INFO - Epoch(train) [16][35/63] lr: 6.9211e-03 eta: 1 day, 1:46:51 time: 1.0281 data_time: 0.0497 memory: 16198 loss_prob: 1.3264 loss_thr: 0.6474 loss_db: 0.2112 loss: 2.1850 2022/08/29 23:25:02 - mmengine - INFO - Epoch(train) [16][40/63] lr: 6.9211e-03 eta: 1 day, 1:43:15 time: 0.9748 data_time: 0.0482 memory: 16198 loss_prob: 1.3900 loss_thr: 0.6818 loss_db: 0.2255 loss: 2.2974 2022/08/29 23:25:07 - mmengine - INFO - Epoch(train) [16][45/63] lr: 6.9211e-03 eta: 1 day, 1:43:15 time: 0.9864 data_time: 0.0366 memory: 16198 loss_prob: 1.6192 loss_thr: 0.7051 loss_db: 0.2691 loss: 2.5935 2022/08/29 23:25:12 - mmengine - INFO - Epoch(train) [16][50/63] lr: 6.9211e-03 eta: 1 day, 1:39:45 time: 0.9772 data_time: 0.0574 memory: 16198 loss_prob: 1.6385 loss_thr: 0.6758 loss_db: 0.2711 loss: 2.5855 2022/08/29 23:25:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:25:17 - mmengine - INFO - Epoch(train) [16][55/63] lr: 6.9211e-03 eta: 1 day, 1:39:45 time: 0.9693 data_time: 0.0493 memory: 16198 loss_prob: 1.5889 loss_thr: 0.6847 loss_db: 0.2487 loss: 2.5223 2022/08/29 23:25:22 - mmengine - INFO - Epoch(train) [16][60/63] lr: 6.9211e-03 eta: 1 day, 1:35:56 time: 0.9469 data_time: 0.0325 memory: 16198 loss_prob: 1.5605 loss_thr: 0.6546 loss_db: 0.2426 loss: 2.4577 2022/08/29 23:25:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:25:32 - mmengine - INFO - Epoch(train) [17][5/63] lr: 6.9159e-03 eta: 1 day, 1:35:56 time: 1.2087 data_time: 0.3372 memory: 16198 loss_prob: 1.5927 loss_thr: 0.6541 loss_db: 0.2634 loss: 2.5102 2022/08/29 23:25:37 - mmengine - INFO - Epoch(train) [17][10/63] lr: 6.9159e-03 eta: 1 day, 1:31:16 time: 1.2455 data_time: 0.3524 memory: 16198 loss_prob: 1.6643 loss_thr: 0.6673 loss_db: 0.2739 loss: 2.6055 2022/08/29 23:25:41 - mmengine - INFO - Epoch(train) [17][15/63] lr: 6.9159e-03 eta: 1 day, 1:31:16 time: 0.9066 data_time: 0.0593 memory: 16198 loss_prob: 1.6110 loss_thr: 0.6689 loss_db: 0.2657 loss: 2.5456 2022/08/29 23:25:45 - mmengine - INFO - Epoch(train) [17][20/63] lr: 6.9159e-03 eta: 1 day, 1:26:31 time: 0.8561 data_time: 0.0284 memory: 16198 loss_prob: 1.4250 loss_thr: 0.6574 loss_db: 0.2334 loss: 2.3158 2022/08/29 23:25:49 - mmengine - INFO - Epoch(train) [17][25/63] lr: 6.9159e-03 eta: 1 day, 1:26:31 time: 0.8463 data_time: 0.0442 memory: 16198 loss_prob: 1.4632 loss_thr: 0.6461 loss_db: 0.2406 loss: 2.3499 2022/08/29 23:25:54 - mmengine - INFO - Epoch(train) [17][30/63] lr: 6.9159e-03 eta: 1 day, 1:22:26 time: 0.9038 data_time: 0.0506 memory: 16198 loss_prob: 1.5567 loss_thr: 0.6519 loss_db: 0.2552 loss: 2.4639 2022/08/29 23:25:58 - mmengine - INFO - Epoch(train) [17][35/63] lr: 6.9159e-03 eta: 1 day, 1:22:26 time: 0.8862 data_time: 0.0432 memory: 16198 loss_prob: 1.5438 loss_thr: 0.6506 loss_db: 0.2550 loss: 2.4494 2022/08/29 23:26:03 - mmengine - INFO - Epoch(train) [17][40/63] lr: 6.9159e-03 eta: 1 day, 1:18:06 time: 0.8776 data_time: 0.0489 memory: 16198 loss_prob: 1.4687 loss_thr: 0.6608 loss_db: 0.2451 loss: 2.3745 2022/08/29 23:26:08 - mmengine - INFO - Epoch(train) [17][45/63] lr: 6.9159e-03 eta: 1 day, 1:18:06 time: 0.9290 data_time: 0.0441 memory: 16198 loss_prob: 1.4982 loss_thr: 0.6608 loss_db: 0.2460 loss: 2.4049 2022/08/29 23:26:12 - mmengine - INFO - Epoch(train) [17][50/63] lr: 6.9159e-03 eta: 1 day, 1:14:34 time: 0.9369 data_time: 0.0386 memory: 16198 loss_prob: 1.4314 loss_thr: 0.6283 loss_db: 0.2340 loss: 2.2937 2022/08/29 23:26:18 - mmengine - INFO - Epoch(train) [17][55/63] lr: 6.9159e-03 eta: 1 day, 1:14:34 time: 1.0390 data_time: 0.0525 memory: 16198 loss_prob: 1.3673 loss_thr: 0.5969 loss_db: 0.2224 loss: 2.1867 2022/08/29 23:26:23 - mmengine - INFO - Epoch(train) [17][60/63] lr: 6.9159e-03 eta: 1 day, 1:12:21 time: 1.0468 data_time: 0.0465 memory: 16198 loss_prob: 1.3047 loss_thr: 0.6170 loss_db: 0.2082 loss: 2.1298 2022/08/29 23:26:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:26:33 - mmengine - INFO - Epoch(train) [18][5/63] lr: 6.9106e-03 eta: 1 day, 1:12:21 time: 1.2446 data_time: 0.3935 memory: 16198 loss_prob: 1.3011 loss_thr: 0.6306 loss_db: 0.2097 loss: 2.1414 2022/08/29 23:26:39 - mmengine - INFO - Epoch(train) [18][10/63] lr: 6.9106e-03 eta: 1 day, 1:09:47 time: 1.3822 data_time: 0.4184 memory: 16198 loss_prob: 1.4306 loss_thr: 0.6637 loss_db: 0.2360 loss: 2.3304 2022/08/29 23:26:44 - mmengine - INFO - Epoch(train) [18][15/63] lr: 6.9106e-03 eta: 1 day, 1:09:47 time: 1.0320 data_time: 0.0657 memory: 16198 loss_prob: 1.5539 loss_thr: 0.6920 loss_db: 0.2559 loss: 2.5018 2022/08/29 23:26:49 - mmengine - INFO - Epoch(train) [18][20/63] lr: 6.9106e-03 eta: 1 day, 1:06:44 time: 0.9661 data_time: 0.0544 memory: 16198 loss_prob: 1.5998 loss_thr: 0.6954 loss_db: 0.2710 loss: 2.5661 2022/08/29 23:26:53 - mmengine - INFO - Epoch(train) [18][25/63] lr: 6.9106e-03 eta: 1 day, 1:06:44 time: 0.9459 data_time: 0.0595 memory: 16198 loss_prob: 1.5841 loss_thr: 0.6647 loss_db: 0.2728 loss: 2.5215 2022/08/29 23:26:58 - mmengine - INFO - Epoch(train) [18][30/63] lr: 6.9106e-03 eta: 1 day, 1:02:59 time: 0.8980 data_time: 0.0332 memory: 16198 loss_prob: 1.5284 loss_thr: 0.6239 loss_db: 0.2524 loss: 2.4047 2022/08/29 23:27:02 - mmengine - INFO - Epoch(train) [18][35/63] lr: 6.9106e-03 eta: 1 day, 1:02:59 time: 0.8946 data_time: 0.0474 memory: 16198 loss_prob: 1.5464 loss_thr: 0.6595 loss_db: 0.2588 loss: 2.4648 2022/08/29 23:27:07 - mmengine - INFO - Epoch(train) [18][40/63] lr: 6.9106e-03 eta: 1 day, 0:59:40 time: 0.9312 data_time: 0.0546 memory: 16198 loss_prob: 1.4871 loss_thr: 0.6579 loss_db: 0.2513 loss: 2.3964 2022/08/29 23:27:11 - mmengine - INFO - Epoch(train) [18][45/63] lr: 6.9106e-03 eta: 1 day, 0:59:40 time: 0.9090 data_time: 0.0392 memory: 16198 loss_prob: 1.5298 loss_thr: 0.6738 loss_db: 0.2500 loss: 2.4536 2022/08/29 23:27:16 - mmengine - INFO - Epoch(train) [18][50/63] lr: 6.9106e-03 eta: 1 day, 0:56:23 time: 0.9296 data_time: 0.0627 memory: 16198 loss_prob: 1.6281 loss_thr: 0.6990 loss_db: 0.2675 loss: 2.5946 2022/08/29 23:27:21 - mmengine - INFO - Epoch(train) [18][55/63] lr: 6.9106e-03 eta: 1 day, 0:56:23 time: 0.9854 data_time: 0.0556 memory: 16198 loss_prob: 1.6516 loss_thr: 0.6897 loss_db: 0.2755 loss: 2.6168 2022/08/29 23:27:26 - mmengine - INFO - Epoch(train) [18][60/63] lr: 6.9106e-03 eta: 1 day, 0:53:24 time: 0.9526 data_time: 0.0312 memory: 16198 loss_prob: 1.5019 loss_thr: 0.6836 loss_db: 0.2484 loss: 2.4339 2022/08/29 23:27:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:27:37 - mmengine - INFO - Epoch(train) [19][5/63] lr: 6.9054e-03 eta: 1 day, 0:53:24 time: 1.3097 data_time: 0.3511 memory: 16198 loss_prob: 1.5171 loss_thr: 0.6715 loss_db: 0.2519 loss: 2.4405 2022/08/29 23:27:42 - mmengine - INFO - Epoch(train) [19][10/63] lr: 6.9054e-03 eta: 1 day, 0:50:07 time: 1.2853 data_time: 0.3568 memory: 16198 loss_prob: 1.5701 loss_thr: 0.6503 loss_db: 0.2602 loss: 2.4807 2022/08/29 23:27:46 - mmengine - INFO - Epoch(train) [19][15/63] lr: 6.9054e-03 eta: 1 day, 0:50:07 time: 0.9214 data_time: 0.0483 memory: 16198 loss_prob: 1.3375 loss_thr: 0.6225 loss_db: 0.2128 loss: 2.1728 2022/08/29 23:27:51 - mmengine - INFO - Epoch(train) [19][20/63] lr: 6.9054e-03 eta: 1 day, 0:47:26 time: 0.9704 data_time: 0.0904 memory: 16198 loss_prob: 1.3443 loss_thr: 0.6304 loss_db: 0.2150 loss: 2.1897 2022/08/29 23:27:56 - mmengine - INFO - Epoch(train) [19][25/63] lr: 6.9054e-03 eta: 1 day, 0:47:26 time: 0.9829 data_time: 0.1105 memory: 16198 loss_prob: 1.2820 loss_thr: 0.6076 loss_db: 0.2108 loss: 2.1004 2022/08/29 23:28:01 - mmengine - INFO - Epoch(train) [19][30/63] lr: 6.9054e-03 eta: 1 day, 0:44:52 time: 0.9771 data_time: 0.0550 memory: 16198 loss_prob: 1.3177 loss_thr: 0.6097 loss_db: 0.2188 loss: 2.1461 2022/08/29 23:28:06 - mmengine - INFO - Epoch(train) [19][35/63] lr: 6.9054e-03 eta: 1 day, 0:44:52 time: 0.9646 data_time: 0.0474 memory: 16198 loss_prob: 1.3779 loss_thr: 0.6159 loss_db: 0.2281 loss: 2.2219 2022/08/29 23:28:11 - mmengine - INFO - Epoch(train) [19][40/63] lr: 6.9054e-03 eta: 1 day, 0:42:06 time: 0.9538 data_time: 0.0481 memory: 16198 loss_prob: 1.3391 loss_thr: 0.6193 loss_db: 0.2185 loss: 2.1769 2022/08/29 23:28:15 - mmengine - INFO - Epoch(train) [19][45/63] lr: 6.9054e-03 eta: 1 day, 0:42:06 time: 0.9288 data_time: 0.0465 memory: 16198 loss_prob: 1.4039 loss_thr: 0.6281 loss_db: 0.2301 loss: 2.2621 2022/08/29 23:28:20 - mmengine - INFO - Epoch(train) [19][50/63] lr: 6.9054e-03 eta: 1 day, 0:38:43 time: 0.8896 data_time: 0.0377 memory: 16198 loss_prob: 1.4497 loss_thr: 0.6350 loss_db: 0.2377 loss: 2.3225 2022/08/29 23:28:25 - mmengine - INFO - Epoch(train) [19][55/63] lr: 6.9054e-03 eta: 1 day, 0:38:43 time: 0.9419 data_time: 0.0576 memory: 16198 loss_prob: 1.4866 loss_thr: 0.6608 loss_db: 0.2437 loss: 2.3910 2022/08/29 23:28:29 - mmengine - INFO - Epoch(train) [19][60/63] lr: 6.9054e-03 eta: 1 day, 0:35:35 time: 0.9102 data_time: 0.0563 memory: 16198 loss_prob: 1.4657 loss_thr: 0.6683 loss_db: 0.2425 loss: 2.3764 2022/08/29 23:28:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:28:40 - mmengine - INFO - Epoch(train) [20][5/63] lr: 6.9001e-03 eta: 1 day, 0:35:35 time: 1.3265 data_time: 0.4498 memory: 16198 loss_prob: 1.4597 loss_thr: 0.6595 loss_db: 0.2433 loss: 2.3625 2022/08/29 23:28:47 - mmengine - INFO - Epoch(train) [20][10/63] lr: 6.9001e-03 eta: 1 day, 0:35:35 time: 1.5728 data_time: 0.4766 memory: 16198 loss_prob: 1.4807 loss_thr: 0.6617 loss_db: 0.2442 loss: 2.3866 2022/08/29 23:28:52 - mmengine - INFO - Epoch(train) [20][15/63] lr: 6.9001e-03 eta: 1 day, 0:35:35 time: 1.1349 data_time: 0.0537 memory: 16198 loss_prob: 1.3303 loss_thr: 0.6761 loss_db: 0.2163 loss: 2.2227 2022/08/29 23:28:56 - mmengine - INFO - Epoch(train) [20][20/63] lr: 6.9001e-03 eta: 1 day, 0:33:07 time: 0.9665 data_time: 0.0518 memory: 16198 loss_prob: 1.4417 loss_thr: 0.6817 loss_db: 0.2373 loss: 2.3607 2022/08/29 23:29:01 - mmengine - INFO - Epoch(train) [20][25/63] lr: 6.9001e-03 eta: 1 day, 0:33:07 time: 0.9148 data_time: 0.0617 memory: 16198 loss_prob: 1.4121 loss_thr: 0.6446 loss_db: 0.2304 loss: 2.2872 2022/08/29 23:29:05 - mmengine - INFO - Epoch(train) [20][30/63] lr: 6.9001e-03 eta: 1 day, 0:30:00 time: 0.8999 data_time: 0.0295 memory: 16198 loss_prob: 1.3672 loss_thr: 0.6598 loss_db: 0.2204 loss: 2.2474 2022/08/29 23:29:10 - mmengine - INFO - Epoch(train) [20][35/63] lr: 6.9001e-03 eta: 1 day, 0:30:00 time: 0.9603 data_time: 0.0455 memory: 16198 loss_prob: 1.5281 loss_thr: 0.6898 loss_db: 0.2522 loss: 2.4701 2022/08/29 23:29:15 - mmengine - INFO - Epoch(train) [20][40/63] lr: 6.9001e-03 eta: 1 day, 0:27:32 time: 0.9601 data_time: 0.0520 memory: 16198 loss_prob: 1.6206 loss_thr: 0.6663 loss_db: 0.2667 loss: 2.5536 2022/08/29 23:29:19 - mmengine - INFO - Epoch(train) [20][45/63] lr: 6.9001e-03 eta: 1 day, 0:27:32 time: 0.8736 data_time: 0.0355 memory: 16198 loss_prob: 1.5646 loss_thr: 0.6719 loss_db: 0.2557 loss: 2.4922 2022/08/29 23:29:24 - mmengine - INFO - Epoch(train) [20][50/63] lr: 6.9001e-03 eta: 1 day, 0:24:37 time: 0.9103 data_time: 0.0645 memory: 16198 loss_prob: 1.4981 loss_thr: 0.6858 loss_db: 0.2459 loss: 2.4297 2022/08/29 23:29:28 - mmengine - INFO - Epoch(train) [20][55/63] lr: 6.9001e-03 eta: 1 day, 0:24:37 time: 0.8994 data_time: 0.0600 memory: 16198 loss_prob: 1.5106 loss_thr: 0.6774 loss_db: 0.2557 loss: 2.4437 2022/08/29 23:29:33 - mmengine - INFO - Epoch(train) [20][60/63] lr: 6.9001e-03 eta: 1 day, 0:21:11 time: 0.8531 data_time: 0.0399 memory: 16198 loss_prob: 1.3867 loss_thr: 0.6354 loss_db: 0.2317 loss: 2.2538 2022/08/29 23:29:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:29:36 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/08/29 23:33:35 - mmengine - INFO - Epoch(val) [20][5/32] eta: 1 day, 0:21:11 time: 46.9137 data_time: 44.3905 memory: 40873 2022/08/29 23:33:39 - mmengine - INFO - Epoch(val) [20][10/32] eta: 0:08:42 time: 23.7697 data_time: 22.2234 memory: 15734 2022/08/29 23:33:42 - mmengine - INFO - Epoch(val) [20][15/32] eta: 0:08:42 time: 0.6335 data_time: 0.0721 memory: 15734 2022/08/29 23:33:45 - mmengine - INFO - Epoch(val) [20][20/32] eta: 0:00:07 time: 0.6387 data_time: 0.0710 memory: 15734 2022/08/29 23:33:49 - mmengine - INFO - Epoch(val) [20][25/32] eta: 0:00:07 time: 0.7234 data_time: 0.0536 memory: 15734 2022/08/29 23:33:52 - mmengine - INFO - Epoch(val) [20][30/32] eta: 0:00:01 time: 0.7059 data_time: 0.0436 memory: 15734 2022/08/29 23:34:01 - mmengine - INFO - Evaluating hmean-iou... 2022/08/29 23:34:01 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7660, precision: 0.6336, hmean: 0.6935 2022/08/29 23:34:01 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7655, precision: 0.7371, hmean: 0.7511 2022/08/29 23:34:01 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7583, precision: 0.7955, hmean: 0.7764 2022/08/29 23:34:01 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7304, precision: 0.8317, hmean: 0.7777 2022/08/29 23:34:01 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6716, precision: 0.8897, hmean: 0.7654 2022/08/29 23:34:01 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2860, precision: 0.9690, hmean: 0.4416 2022/08/29 23:34:01 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/08/29 23:34:01 - mmengine - INFO - Epoch(val) [20][32/32] icdar/precision: 0.8317 icdar/recall: 0.7304 icdar/hmean: 0.7777 2022/08/29 23:34:09 - mmengine - INFO - Epoch(train) [21][5/63] lr: 6.8948e-03 eta: 0:00:01 time: 1.2915 data_time: 0.3363 memory: 35430 loss_prob: 1.4544 loss_thr: 0.6290 loss_db: 0.2390 loss: 2.3224 2022/08/29 23:34:13 - mmengine - INFO - Epoch(train) [21][10/63] lr: 6.8948e-03 eta: 1 day, 0:17:37 time: 1.1935 data_time: 0.3312 memory: 16202 loss_prob: 1.6650 loss_thr: 0.6455 loss_db: 0.2785 loss: 2.5890 2022/08/29 23:34:18 - mmengine - INFO - Epoch(train) [21][15/63] lr: 6.8948e-03 eta: 1 day, 0:17:37 time: 0.8585 data_time: 0.0413 memory: 16202 loss_prob: 1.5297 loss_thr: 0.6692 loss_db: 0.2558 loss: 2.4547 2022/08/29 23:34:22 - mmengine - INFO - Epoch(train) [21][20/63] lr: 6.8948e-03 eta: 1 day, 0:14:23 time: 0.8635 data_time: 0.0464 memory: 16202 loss_prob: 1.3933 loss_thr: 0.6406 loss_db: 0.2312 loss: 2.2651 2022/08/29 23:34:27 - mmengine - INFO - Epoch(train) [21][25/63] lr: 6.8948e-03 eta: 1 day, 0:14:23 time: 0.8814 data_time: 0.0388 memory: 16202 loss_prob: 1.4951 loss_thr: 0.6574 loss_db: 0.2457 loss: 2.3982 2022/08/29 23:34:32 - mmengine - INFO - Epoch(train) [21][30/63] lr: 6.8948e-03 eta: 1 day, 0:12:08 time: 0.9589 data_time: 0.0487 memory: 16202 loss_prob: 1.5122 loss_thr: 0.6810 loss_db: 0.2484 loss: 2.4417 2022/08/29 23:34:37 - mmengine - INFO - Epoch(train) [21][35/63] lr: 6.8948e-03 eta: 1 day, 0:12:08 time: 1.0102 data_time: 0.0600 memory: 16202 loss_prob: 1.4350 loss_thr: 0.6495 loss_db: 0.2403 loss: 2.3248 2022/08/29 23:34:41 - mmengine - INFO - Epoch(train) [21][40/63] lr: 6.8948e-03 eta: 1 day, 0:09:38 time: 0.9319 data_time: 0.0448 memory: 16202 loss_prob: 1.5186 loss_thr: 0.6477 loss_db: 0.2595 loss: 2.4258 2022/08/29 23:34:45 - mmengine - INFO - Epoch(train) [21][45/63] lr: 6.8948e-03 eta: 1 day, 0:09:38 time: 0.8674 data_time: 0.0453 memory: 16202 loss_prob: 1.5045 loss_thr: 0.6463 loss_db: 0.2504 loss: 2.4013 2022/08/29 23:34:50 - mmengine - INFO - Epoch(train) [21][50/63] lr: 6.8948e-03 eta: 1 day, 0:07:06 time: 0.9217 data_time: 0.0508 memory: 16202 loss_prob: 1.4817 loss_thr: 0.6732 loss_db: 0.2386 loss: 2.3936 2022/08/29 23:34:55 - mmengine - INFO - Epoch(train) [21][55/63] lr: 6.8948e-03 eta: 1 day, 0:07:06 time: 1.0112 data_time: 0.0670 memory: 16202 loss_prob: 1.5341 loss_thr: 0.6675 loss_db: 0.2483 loss: 2.4499 2022/08/29 23:35:00 - mmengine - INFO - Epoch(train) [21][60/63] lr: 6.8948e-03 eta: 1 day, 0:05:20 time: 1.0026 data_time: 0.0770 memory: 16202 loss_prob: 1.5022 loss_thr: 0.6482 loss_db: 0.2439 loss: 2.3942 2022/08/29 23:35:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:35:10 - mmengine - INFO - Epoch(train) [22][5/63] lr: 6.8896e-03 eta: 1 day, 0:05:20 time: 1.1106 data_time: 0.3408 memory: 16202 loss_prob: 1.5542 loss_thr: 0.6691 loss_db: 0.2537 loss: 2.4770 2022/08/29 23:35:14 - mmengine - INFO - Epoch(train) [22][10/63] lr: 6.8896e-03 eta: 1 day, 0:01:31 time: 1.1332 data_time: 0.3210 memory: 16202 loss_prob: 1.5305 loss_thr: 0.6777 loss_db: 0.2498 loss: 2.4580 2022/08/29 23:35:19 - mmengine - INFO - Epoch(train) [22][15/63] lr: 6.8896e-03 eta: 1 day, 0:01:31 time: 0.9209 data_time: 0.0960 memory: 16202 loss_prob: 1.4580 loss_thr: 0.6596 loss_db: 0.2433 loss: 2.3610 2022/08/29 23:35:24 - mmengine - INFO - Epoch(train) [22][20/63] lr: 6.8896e-03 eta: 23:59:19 time: 0.9475 data_time: 0.0910 memory: 16202 loss_prob: 1.3133 loss_thr: 0.6269 loss_db: 0.2174 loss: 2.1577 2022/08/29 23:35:28 - mmengine - INFO - Epoch(train) [22][25/63] lr: 6.8896e-03 eta: 23:59:19 time: 0.9396 data_time: 0.0828 memory: 16202 loss_prob: 1.4296 loss_thr: 0.6263 loss_db: 0.2375 loss: 2.2934 2022/08/29 23:35:33 - mmengine - INFO - Epoch(train) [22][30/63] lr: 6.8896e-03 eta: 23:57:35 time: 0.9948 data_time: 0.1119 memory: 16202 loss_prob: 1.6027 loss_thr: 0.6662 loss_db: 0.2672 loss: 2.5362 2022/08/29 23:35:38 - mmengine - INFO - Epoch(train) [22][35/63] lr: 6.8896e-03 eta: 23:57:35 time: 0.9809 data_time: 0.0882 memory: 16202 loss_prob: 1.5199 loss_thr: 0.6599 loss_db: 0.2494 loss: 2.4292 2022/08/29 23:35:42 - mmengine - INFO - Epoch(train) [22][40/63] lr: 6.8896e-03 eta: 23:55:01 time: 0.8990 data_time: 0.0506 memory: 16202 loss_prob: 1.4096 loss_thr: 0.6328 loss_db: 0.2301 loss: 2.2724 2022/08/29 23:35:47 - mmengine - INFO - Epoch(train) [22][45/63] lr: 6.8896e-03 eta: 23:55:01 time: 0.9068 data_time: 0.0923 memory: 16202 loss_prob: 1.3952 loss_thr: 0.6218 loss_db: 0.2281 loss: 2.2451 2022/08/29 23:35:52 - mmengine - INFO - Epoch(train) [22][50/63] lr: 6.8896e-03 eta: 23:52:48 time: 0.9365 data_time: 0.1087 memory: 16202 loss_prob: 1.4271 loss_thr: 0.6381 loss_db: 0.2296 loss: 2.2948 2022/08/29 23:35:57 - mmengine - INFO - Epoch(train) [22][55/63] lr: 6.8896e-03 eta: 23:52:48 time: 0.9886 data_time: 0.0701 memory: 16202 loss_prob: 1.3463 loss_thr: 0.6244 loss_db: 0.2142 loss: 2.1849 2022/08/29 23:36:02 - mmengine - INFO - Epoch(train) [22][60/63] lr: 6.8896e-03 eta: 23:51:13 time: 1.0016 data_time: 0.0907 memory: 16202 loss_prob: 1.3727 loss_thr: 0.6216 loss_db: 0.2224 loss: 2.2167 2022/08/29 23:36:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:36:11 - mmengine - INFO - Epoch(train) [23][5/63] lr: 6.8843e-03 eta: 23:51:13 time: 1.0755 data_time: 0.3039 memory: 16202 loss_prob: 1.5429 loss_thr: 0.6817 loss_db: 0.2515 loss: 2.4761 2022/08/29 23:36:17 - mmengine - INFO - Epoch(train) [23][10/63] lr: 6.8843e-03 eta: 23:48:32 time: 1.2307 data_time: 0.3347 memory: 16202 loss_prob: 1.4682 loss_thr: 0.6706 loss_db: 0.2375 loss: 2.3763 2022/08/29 23:36:22 - mmengine - INFO - Epoch(train) [23][15/63] lr: 6.8843e-03 eta: 23:48:32 time: 1.0872 data_time: 0.1027 memory: 16202 loss_prob: 1.4465 loss_thr: 0.6414 loss_db: 0.2372 loss: 2.3251 2022/08/29 23:36:27 - mmengine - INFO - Epoch(train) [23][20/63] lr: 6.8843e-03 eta: 23:46:57 time: 0.9967 data_time: 0.0978 memory: 16202 loss_prob: 1.4969 loss_thr: 0.6203 loss_db: 0.2481 loss: 2.3653 2022/08/29 23:36:31 - mmengine - INFO - Epoch(train) [23][25/63] lr: 6.8843e-03 eta: 23:46:57 time: 0.9382 data_time: 0.0844 memory: 16202 loss_prob: 1.4366 loss_thr: 0.6274 loss_db: 0.2350 loss: 2.2990 2022/08/29 23:36:36 - mmengine - INFO - Epoch(train) [23][30/63] lr: 6.8843e-03 eta: 23:44:49 time: 0.9318 data_time: 0.0443 memory: 16202 loss_prob: 1.3609 loss_thr: 0.6506 loss_db: 0.2199 loss: 2.2313 2022/08/29 23:36:41 - mmengine - INFO - Epoch(train) [23][35/63] lr: 6.8843e-03 eta: 23:44:49 time: 1.0023 data_time: 0.0990 memory: 16202 loss_prob: 1.3524 loss_thr: 0.6433 loss_db: 0.2209 loss: 2.2166 2022/08/29 23:36:46 - mmengine - INFO - Epoch(train) [23][40/63] lr: 6.8843e-03 eta: 23:43:13 time: 0.9905 data_time: 0.0976 memory: 16202 loss_prob: 1.2349 loss_thr: 0.6170 loss_db: 0.2019 loss: 2.0537 2022/08/29 23:36:50 - mmengine - INFO - Epoch(train) [23][45/63] lr: 6.8843e-03 eta: 23:43:13 time: 0.8880 data_time: 0.0549 memory: 16202 loss_prob: 1.2315 loss_thr: 0.6225 loss_db: 0.2014 loss: 2.0553 2022/08/29 23:36:55 - mmengine - INFO - Epoch(train) [23][50/63] lr: 6.8843e-03 eta: 23:41:16 time: 0.9459 data_time: 0.1053 memory: 16202 loss_prob: 1.2612 loss_thr: 0.6195 loss_db: 0.2047 loss: 2.0853 2022/08/29 23:37:00 - mmengine - INFO - Epoch(train) [23][55/63] lr: 6.8843e-03 eta: 23:41:16 time: 0.9629 data_time: 0.0943 memory: 16202 loss_prob: 1.3207 loss_thr: 0.6130 loss_db: 0.2150 loss: 2.1487 2022/08/29 23:37:05 - mmengine - INFO - Epoch(train) [23][60/63] lr: 6.8843e-03 eta: 23:39:12 time: 0.9304 data_time: 0.0557 memory: 16202 loss_prob: 1.3468 loss_thr: 0.6059 loss_db: 0.2217 loss: 2.1744 2022/08/29 23:37:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:37:15 - mmengine - INFO - Epoch(train) [24][5/63] lr: 6.8790e-03 eta: 23:39:12 time: 1.1961 data_time: 0.3325 memory: 16202 loss_prob: 1.3141 loss_thr: 0.6009 loss_db: 0.2110 loss: 2.1261 2022/08/29 23:37:20 - mmengine - INFO - Epoch(train) [24][10/63] lr: 6.8790e-03 eta: 23:37:14 time: 1.2903 data_time: 0.3642 memory: 16202 loss_prob: 1.2401 loss_thr: 0.6064 loss_db: 0.1977 loss: 2.0442 2022/08/29 23:37:25 - mmengine - INFO - Epoch(train) [24][15/63] lr: 6.8790e-03 eta: 23:37:14 time: 1.0114 data_time: 0.1142 memory: 16202 loss_prob: 1.3307 loss_thr: 0.6467 loss_db: 0.2165 loss: 2.1939 2022/08/29 23:37:30 - mmengine - INFO - Epoch(train) [24][20/63] lr: 6.8790e-03 eta: 23:35:22 time: 0.9472 data_time: 0.0785 memory: 16202 loss_prob: 1.4003 loss_thr: 0.6451 loss_db: 0.2302 loss: 2.2757 2022/08/29 23:37:35 - mmengine - INFO - Epoch(train) [24][25/63] lr: 6.8790e-03 eta: 23:35:22 time: 0.9814 data_time: 0.1090 memory: 16202 loss_prob: 1.3919 loss_thr: 0.6455 loss_db: 0.2277 loss: 2.2651 2022/08/29 23:37:40 - mmengine - INFO - Epoch(train) [24][30/63] lr: 6.8790e-03 eta: 23:34:03 time: 1.0113 data_time: 0.0776 memory: 16202 loss_prob: 1.4187 loss_thr: 0.6638 loss_db: 0.2354 loss: 2.3179 2022/08/29 23:37:45 - mmengine - INFO - Epoch(train) [24][35/63] lr: 6.8790e-03 eta: 23:34:03 time: 1.0115 data_time: 0.0938 memory: 16202 loss_prob: 1.3952 loss_thr: 0.6447 loss_db: 0.2374 loss: 2.2773 2022/08/29 23:37:49 - mmengine - INFO - Epoch(train) [24][40/63] lr: 6.8790e-03 eta: 23:32:04 time: 0.9292 data_time: 0.1018 memory: 16202 loss_prob: 1.3375 loss_thr: 0.6178 loss_db: 0.2174 loss: 2.1727 2022/08/29 23:37:53 - mmengine - INFO - Epoch(train) [24][45/63] lr: 6.8790e-03 eta: 23:32:04 time: 0.8627 data_time: 0.0594 memory: 16202 loss_prob: 1.4302 loss_thr: 0.6292 loss_db: 0.2269 loss: 2.2864 2022/08/29 23:38:01 - mmengine - INFO - Epoch(train) [24][50/63] lr: 6.8790e-03 eta: 23:32:20 time: 1.1979 data_time: 0.0942 memory: 16202 loss_prob: 1.3389 loss_thr: 0.6080 loss_db: 0.2213 loss: 2.1682 2022/08/29 23:38:06 - mmengine - INFO - Epoch(train) [24][55/63] lr: 6.8790e-03 eta: 23:32:20 time: 1.2615 data_time: 0.1022 memory: 16202 loss_prob: 1.3288 loss_thr: 0.6223 loss_db: 0.2189 loss: 2.1700 2022/08/29 23:38:12 - mmengine - INFO - Epoch(train) [24][60/63] lr: 6.8790e-03 eta: 23:31:47 time: 1.0997 data_time: 0.1013 memory: 16202 loss_prob: 1.3610 loss_thr: 0.6599 loss_db: 0.2203 loss: 2.2412 2022/08/29 23:38:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:38:21 - mmengine - INFO - Epoch(train) [25][5/63] lr: 6.8738e-03 eta: 23:31:47 time: 1.0148 data_time: 0.2831 memory: 16202 loss_prob: 1.2056 loss_thr: 0.5945 loss_db: 0.1967 loss: 1.9969 2022/08/29 23:38:25 - mmengine - INFO - Epoch(train) [25][10/63] lr: 6.8738e-03 eta: 23:28:18 time: 1.0871 data_time: 0.3201 memory: 16202 loss_prob: 1.2697 loss_thr: 0.6143 loss_db: 0.2072 loss: 2.0913 2022/08/29 23:38:30 - mmengine - INFO - Epoch(train) [25][15/63] lr: 6.8738e-03 eta: 23:28:18 time: 0.9233 data_time: 0.0903 memory: 16202 loss_prob: 1.3601 loss_thr: 0.6011 loss_db: 0.2228 loss: 2.1841 2022/08/29 23:38:34 - mmengine - INFO - Epoch(train) [25][20/63] lr: 6.8738e-03 eta: 23:26:25 time: 0.9301 data_time: 0.0479 memory: 16202 loss_prob: 1.4354 loss_thr: 0.6170 loss_db: 0.2380 loss: 2.2904 2022/08/29 23:38:40 - mmengine - INFO - Epoch(train) [25][25/63] lr: 6.8738e-03 eta: 23:26:25 time: 0.9667 data_time: 0.0573 memory: 16202 loss_prob: 1.5013 loss_thr: 0.6700 loss_db: 0.2475 loss: 2.4188 2022/08/29 23:38:44 - mmengine - INFO - Epoch(train) [25][30/63] lr: 6.8738e-03 eta: 23:24:51 time: 0.9683 data_time: 0.0487 memory: 16202 loss_prob: 1.4672 loss_thr: 0.6610 loss_db: 0.2359 loss: 2.3641 2022/08/29 23:38:49 - mmengine - INFO - Epoch(train) [25][35/63] lr: 6.8738e-03 eta: 23:24:51 time: 0.9340 data_time: 0.0342 memory: 16202 loss_prob: 1.4565 loss_thr: 0.6385 loss_db: 0.2324 loss: 2.3275 2022/08/29 23:38:54 - mmengine - INFO - Epoch(train) [25][40/63] lr: 6.8738e-03 eta: 23:23:24 time: 0.9787 data_time: 0.0535 memory: 16202 loss_prob: 1.4812 loss_thr: 0.6687 loss_db: 0.2465 loss: 2.3964 2022/08/29 23:38:59 - mmengine - INFO - Epoch(train) [25][45/63] lr: 6.8738e-03 eta: 23:23:24 time: 0.9978 data_time: 0.0514 memory: 16202 loss_prob: 1.4717 loss_thr: 0.6886 loss_db: 0.2490 loss: 2.4092 2022/08/29 23:39:03 - mmengine - INFO - Epoch(train) [25][50/63] lr: 6.8738e-03 eta: 23:21:44 time: 0.9504 data_time: 0.0480 memory: 16202 loss_prob: 1.5265 loss_thr: 0.6819 loss_db: 0.2484 loss: 2.4567 2022/08/29 23:39:09 - mmengine - INFO - Epoch(train) [25][55/63] lr: 6.8738e-03 eta: 23:21:44 time: 1.0071 data_time: 0.0605 memory: 16202 loss_prob: 1.4930 loss_thr: 0.6385 loss_db: 0.2397 loss: 2.3712 2022/08/29 23:39:14 - mmengine - INFO - Epoch(train) [25][60/63] lr: 6.8738e-03 eta: 23:20:40 time: 1.0258 data_time: 0.0614 memory: 16202 loss_prob: 1.4415 loss_thr: 0.6097 loss_db: 0.2303 loss: 2.2815 2022/08/29 23:39:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:39:24 - mmengine - INFO - Epoch(train) [26][5/63] lr: 6.8685e-03 eta: 23:20:40 time: 1.2210 data_time: 0.4128 memory: 16202 loss_prob: 1.3926 loss_thr: 0.6300 loss_db: 0.2211 loss: 2.2436 2022/08/29 23:39:29 - mmengine - INFO - Epoch(train) [26][10/63] lr: 6.8685e-03 eta: 23:18:49 time: 1.2694 data_time: 0.4135 memory: 16202 loss_prob: 1.3718 loss_thr: 0.6300 loss_db: 0.2257 loss: 2.2274 2022/08/29 23:39:33 - mmengine - INFO - Epoch(train) [26][15/63] lr: 6.8685e-03 eta: 23:18:49 time: 0.9033 data_time: 0.0440 memory: 16202 loss_prob: 1.2906 loss_thr: 0.6173 loss_db: 0.2138 loss: 2.1217 2022/08/29 23:39:38 - mmengine - INFO - Epoch(train) [26][20/63] lr: 6.8685e-03 eta: 23:17:04 time: 0.9315 data_time: 0.0334 memory: 16202 loss_prob: 1.3621 loss_thr: 0.6206 loss_db: 0.2248 loss: 2.2075 2022/08/29 23:39:43 - mmengine - INFO - Epoch(train) [26][25/63] lr: 6.8685e-03 eta: 23:17:04 time: 0.9575 data_time: 0.0609 memory: 16202 loss_prob: 1.3299 loss_thr: 0.6132 loss_db: 0.2186 loss: 2.1618 2022/08/29 23:39:48 - mmengine - INFO - Epoch(train) [26][30/63] lr: 6.8685e-03 eta: 23:15:23 time: 0.9386 data_time: 0.0533 memory: 16202 loss_prob: 1.3300 loss_thr: 0.6223 loss_db: 0.2178 loss: 2.1702 2022/08/29 23:39:52 - mmengine - INFO - Epoch(train) [26][35/63] lr: 6.8685e-03 eta: 23:15:23 time: 0.9121 data_time: 0.0353 memory: 16202 loss_prob: 1.3815 loss_thr: 0.6322 loss_db: 0.2275 loss: 2.2412 2022/08/29 23:39:57 - mmengine - INFO - Epoch(train) [26][40/63] lr: 6.8685e-03 eta: 23:13:33 time: 0.9162 data_time: 0.0535 memory: 16202 loss_prob: 1.3226 loss_thr: 0.6218 loss_db: 0.2190 loss: 2.1635 2022/08/29 23:40:02 - mmengine - INFO - Epoch(train) [26][45/63] lr: 6.8685e-03 eta: 23:13:33 time: 1.0409 data_time: 0.0574 memory: 16202 loss_prob: 1.3246 loss_thr: 0.6055 loss_db: 0.2208 loss: 2.1509 2022/08/29 23:40:07 - mmengine - INFO - Epoch(train) [26][50/63] lr: 6.8685e-03 eta: 23:12:39 time: 1.0368 data_time: 0.0737 memory: 16202 loss_prob: 1.3383 loss_thr: 0.6058 loss_db: 0.2178 loss: 2.1619 2022/08/29 23:40:12 - mmengine - INFO - Epoch(train) [26][55/63] lr: 6.8685e-03 eta: 23:12:39 time: 0.9217 data_time: 0.0604 memory: 16202 loss_prob: 1.3760 loss_thr: 0.6351 loss_db: 0.2254 loss: 2.2365 2022/08/29 23:40:17 - mmengine - INFO - Epoch(train) [26][60/63] lr: 6.8685e-03 eta: 23:11:22 time: 0.9828 data_time: 0.0414 memory: 16202 loss_prob: 1.4548 loss_thr: 0.6657 loss_db: 0.2437 loss: 2.3642 2022/08/29 23:40:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:40:27 - mmengine - INFO - Epoch(train) [27][5/63] lr: 6.8632e-03 eta: 23:11:22 time: 1.2206 data_time: 0.3522 memory: 16202 loss_prob: 1.5268 loss_thr: 0.7125 loss_db: 0.2503 loss: 2.4896 2022/08/29 23:40:32 - mmengine - INFO - Epoch(train) [27][10/63] lr: 6.8632e-03 eta: 23:09:31 time: 1.2523 data_time: 0.3616 memory: 16202 loss_prob: 1.4546 loss_thr: 0.6939 loss_db: 0.2422 loss: 2.3907 2022/08/29 23:40:37 - mmengine - INFO - Epoch(train) [27][15/63] lr: 6.8632e-03 eta: 23:09:31 time: 0.9915 data_time: 0.0513 memory: 16202 loss_prob: 1.3903 loss_thr: 0.6584 loss_db: 0.2333 loss: 2.2820 2022/08/29 23:40:42 - mmengine - INFO - Epoch(train) [27][20/63] lr: 6.8632e-03 eta: 23:08:16 time: 0.9856 data_time: 0.0399 memory: 16202 loss_prob: 1.3184 loss_thr: 0.6372 loss_db: 0.2213 loss: 2.1769 2022/08/29 23:40:47 - mmengine - INFO - Epoch(train) [27][25/63] lr: 6.8632e-03 eta: 23:08:16 time: 0.9406 data_time: 0.0701 memory: 16202 loss_prob: 1.4093 loss_thr: 0.6334 loss_db: 0.2360 loss: 2.2786 2022/08/29 23:40:51 - mmengine - INFO - Epoch(train) [27][30/63] lr: 6.8632e-03 eta: 23:06:41 time: 0.9372 data_time: 0.0533 memory: 16202 loss_prob: 1.4155 loss_thr: 0.6455 loss_db: 0.2368 loss: 2.2978 2022/08/29 23:40:56 - mmengine - INFO - Epoch(train) [27][35/63] lr: 6.8632e-03 eta: 23:06:41 time: 0.9102 data_time: 0.0421 memory: 16202 loss_prob: 1.3128 loss_thr: 0.6193 loss_db: 0.2168 loss: 2.1489 2022/08/29 23:41:01 - mmengine - INFO - Epoch(train) [27][40/63] lr: 6.8632e-03 eta: 23:05:20 time: 0.9674 data_time: 0.0569 memory: 16202 loss_prob: 1.2900 loss_thr: 0.5994 loss_db: 0.2150 loss: 2.1045 2022/08/29 23:41:06 - mmengine - INFO - Epoch(train) [27][45/63] lr: 6.8632e-03 eta: 23:05:20 time: 1.0121 data_time: 0.0444 memory: 16202 loss_prob: 1.2571 loss_thr: 0.5996 loss_db: 0.2070 loss: 2.0637 2022/08/29 23:41:10 - mmengine - INFO - Epoch(train) [27][50/63] lr: 6.8632e-03 eta: 23:03:59 time: 0.9657 data_time: 0.0590 memory: 16202 loss_prob: 1.2557 loss_thr: 0.6139 loss_db: 0.2033 loss: 2.0729 2022/08/29 23:41:15 - mmengine - INFO - Epoch(train) [27][55/63] lr: 6.8632e-03 eta: 23:03:59 time: 0.9076 data_time: 0.0532 memory: 16202 loss_prob: 1.3980 loss_thr: 0.6310 loss_db: 0.2271 loss: 2.2561 2022/08/29 23:41:20 - mmengine - INFO - Epoch(train) [27][60/63] lr: 6.8632e-03 eta: 23:02:16 time: 0.9119 data_time: 0.0374 memory: 16202 loss_prob: 1.6040 loss_thr: 0.6678 loss_db: 0.2677 loss: 2.5396 2022/08/29 23:41:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:41:30 - mmengine - INFO - Epoch(train) [28][5/63] lr: 6.8580e-03 eta: 23:02:16 time: 1.1797 data_time: 0.3363 memory: 16202 loss_prob: 1.3829 loss_thr: 0.6481 loss_db: 0.2360 loss: 2.2671 2022/08/29 23:41:35 - mmengine - INFO - Epoch(train) [28][10/63] lr: 6.8580e-03 eta: 23:00:35 time: 1.2590 data_time: 0.3376 memory: 16202 loss_prob: 1.2674 loss_thr: 0.5967 loss_db: 0.2075 loss: 2.0717 2022/08/29 23:41:40 - mmengine - INFO - Epoch(train) [28][15/63] lr: 6.8580e-03 eta: 23:00:35 time: 1.0139 data_time: 0.0472 memory: 16202 loss_prob: 1.3822 loss_thr: 0.6038 loss_db: 0.2284 loss: 2.2144 2022/08/29 23:41:44 - mmengine - INFO - Epoch(train) [28][20/63] lr: 6.8580e-03 eta: 22:59:02 time: 0.9299 data_time: 0.0521 memory: 16202 loss_prob: 1.2886 loss_thr: 0.6052 loss_db: 0.2136 loss: 2.1074 2022/08/29 23:41:48 - mmengine - INFO - Epoch(train) [28][25/63] lr: 6.8580e-03 eta: 22:59:02 time: 0.8666 data_time: 0.0460 memory: 16202 loss_prob: 1.3496 loss_thr: 0.6587 loss_db: 0.2276 loss: 2.2359 2022/08/29 23:41:53 - mmengine - INFO - Epoch(train) [28][30/63] lr: 6.8580e-03 eta: 22:57:19 time: 0.9057 data_time: 0.0421 memory: 16202 loss_prob: 1.4394 loss_thr: 0.6828 loss_db: 0.2428 loss: 2.3649 2022/08/29 23:41:58 - mmengine - INFO - Epoch(train) [28][35/63] lr: 6.8580e-03 eta: 22:57:19 time: 0.9806 data_time: 0.0810 memory: 16202 loss_prob: 1.3698 loss_thr: 0.6541 loss_db: 0.2229 loss: 2.2468 2022/08/29 23:42:06 - mmengine - INFO - Epoch(train) [28][40/63] lr: 6.8580e-03 eta: 22:58:07 time: 1.2580 data_time: 0.0687 memory: 16202 loss_prob: 1.2952 loss_thr: 0.6396 loss_db: 0.2100 loss: 2.1448 2022/08/29 23:42:14 - mmengine - INFO - Epoch(train) [28][45/63] lr: 6.8580e-03 eta: 22:58:07 time: 1.6210 data_time: 0.0554 memory: 16202 loss_prob: 1.3920 loss_thr: 0.6340 loss_db: 0.2256 loss: 2.2516 2022/08/29 23:42:20 - mmengine - INFO - Epoch(train) [28][50/63] lr: 6.8580e-03 eta: 23:00:13 time: 1.4439 data_time: 0.0538 memory: 16202 loss_prob: 1.3923 loss_thr: 0.6507 loss_db: 0.2229 loss: 2.2659 2022/08/29 23:42:26 - mmengine - INFO - Epoch(train) [28][55/63] lr: 6.8580e-03 eta: 23:00:13 time: 1.1528 data_time: 0.0459 memory: 16202 loss_prob: 1.3430 loss_thr: 0.6410 loss_db: 0.2186 loss: 2.2026 2022/08/29 23:42:31 - mmengine - INFO - Epoch(train) [28][60/63] lr: 6.8580e-03 eta: 23:00:06 time: 1.1332 data_time: 0.0474 memory: 16202 loss_prob: 1.4438 loss_thr: 0.6474 loss_db: 0.2361 loss: 2.3274 2022/08/29 23:42:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:42:44 - mmengine - INFO - Epoch(train) [29][5/63] lr: 6.8527e-03 eta: 23:00:06 time: 1.5128 data_time: 0.3234 memory: 16202 loss_prob: 1.3603 loss_thr: 0.6188 loss_db: 0.2146 loss: 2.1937 2022/08/29 23:42:52 - mmengine - INFO - Epoch(train) [29][10/63] lr: 6.8527e-03 eta: 23:01:29 time: 1.6915 data_time: 0.3319 memory: 16202 loss_prob: 1.4870 loss_thr: 0.6521 loss_db: 0.2362 loss: 2.3753 2022/08/29 23:42:59 - mmengine - INFO - Epoch(train) [29][15/63] lr: 6.8527e-03 eta: 23:01:29 time: 1.4523 data_time: 0.0605 memory: 16202 loss_prob: 1.5748 loss_thr: 0.6629 loss_db: 0.2550 loss: 2.4928 2022/08/29 23:43:07 - mmengine - INFO - Epoch(train) [29][20/63] lr: 6.8527e-03 eta: 23:04:27 time: 1.5793 data_time: 0.0533 memory: 16202 loss_prob: 1.5532 loss_thr: 0.6487 loss_db: 0.2574 loss: 2.4592 2022/08/29 23:43:15 - mmengine - INFO - Epoch(train) [29][25/63] lr: 6.8527e-03 eta: 23:04:27 time: 1.6704 data_time: 0.0573 memory: 16202 loss_prob: 1.3645 loss_thr: 0.5989 loss_db: 0.2267 loss: 2.1901 2022/08/29 23:43:21 - mmengine - INFO - Epoch(train) [29][30/63] lr: 6.8527e-03 eta: 23:05:37 time: 1.3239 data_time: 0.0585 memory: 16202 loss_prob: 1.2634 loss_thr: 0.5818 loss_db: 0.2109 loss: 2.0561 2022/08/29 23:43:25 - mmengine - INFO - Epoch(train) [29][35/63] lr: 6.8527e-03 eta: 23:05:37 time: 0.9442 data_time: 0.0525 memory: 16202 loss_prob: 1.3035 loss_thr: 0.6176 loss_db: 0.2162 loss: 2.1373 2022/08/29 23:43:29 - mmengine - INFO - Epoch(train) [29][40/63] lr: 6.8527e-03 eta: 23:03:34 time: 0.8519 data_time: 0.0316 memory: 16202 loss_prob: 1.3446 loss_thr: 0.6223 loss_db: 0.2203 loss: 2.1871 2022/08/29 23:43:34 - mmengine - INFO - Epoch(train) [29][45/63] lr: 6.8527e-03 eta: 23:03:34 time: 0.8890 data_time: 0.0467 memory: 16202 loss_prob: 1.3288 loss_thr: 0.6002 loss_db: 0.2198 loss: 2.1489 2022/08/29 23:43:38 - mmengine - INFO - Epoch(train) [29][50/63] lr: 6.8527e-03 eta: 23:02:04 time: 0.9311 data_time: 0.0496 memory: 16202 loss_prob: 1.2793 loss_thr: 0.6272 loss_db: 0.2130 loss: 2.1195 2022/08/29 23:43:43 - mmengine - INFO - Epoch(train) [29][55/63] lr: 6.8527e-03 eta: 23:02:04 time: 0.9449 data_time: 0.0369 memory: 16202 loss_prob: 1.3673 loss_thr: 0.6419 loss_db: 0.2272 loss: 2.2364 2022/08/29 23:43:47 - mmengine - INFO - Epoch(train) [29][60/63] lr: 6.8527e-03 eta: 23:00:17 time: 0.8888 data_time: 0.0507 memory: 16202 loss_prob: 1.4505 loss_thr: 0.6271 loss_db: 0.2389 loss: 2.3166 2022/08/29 23:43:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:43:59 - mmengine - INFO - Epoch(train) [30][5/63] lr: 6.8474e-03 eta: 23:00:17 time: 1.2849 data_time: 0.4120 memory: 16202 loss_prob: 1.4327 loss_thr: 0.6536 loss_db: 0.2341 loss: 2.3204 2022/08/29 23:44:03 - mmengine - INFO - Epoch(train) [30][10/63] lr: 6.8474e-03 eta: 22:59:05 time: 1.3161 data_time: 0.4291 memory: 16202 loss_prob: 1.2360 loss_thr: 0.6295 loss_db: 0.1990 loss: 2.0645 2022/08/29 23:44:08 - mmengine - INFO - Epoch(train) [30][15/63] lr: 6.8474e-03 eta: 22:59:05 time: 0.8986 data_time: 0.0531 memory: 16202 loss_prob: 1.2160 loss_thr: 0.6145 loss_db: 0.1954 loss: 2.0259 2022/08/29 23:44:12 - mmengine - INFO - Epoch(train) [30][20/63] lr: 6.8474e-03 eta: 22:57:35 time: 0.9251 data_time: 0.0441 memory: 16202 loss_prob: 1.2483 loss_thr: 0.6072 loss_db: 0.2033 loss: 2.0589 2022/08/29 23:44:17 - mmengine - INFO - Epoch(train) [30][25/63] lr: 6.8474e-03 eta: 22:57:35 time: 0.9281 data_time: 0.0604 memory: 16202 loss_prob: 1.3026 loss_thr: 0.5940 loss_db: 0.2130 loss: 2.1096 2022/08/29 23:44:21 - mmengine - INFO - Epoch(train) [30][30/63] lr: 6.8474e-03 eta: 22:55:54 time: 0.8937 data_time: 0.0455 memory: 16202 loss_prob: 1.3886 loss_thr: 0.6285 loss_db: 0.2298 loss: 2.2469 2022/08/29 23:44:26 - mmengine - INFO - Epoch(train) [30][35/63] lr: 6.8474e-03 eta: 22:55:54 time: 0.9371 data_time: 0.0364 memory: 16202 loss_prob: 1.5463 loss_thr: 0.6797 loss_db: 0.2641 loss: 2.4901 2022/08/29 23:44:32 - mmengine - INFO - Epoch(train) [30][40/63] lr: 6.8474e-03 eta: 22:55:30 time: 1.0871 data_time: 0.0579 memory: 16202 loss_prob: 1.4753 loss_thr: 0.6638 loss_db: 0.2525 loss: 2.3917 2022/08/29 23:44:37 - mmengine - INFO - Epoch(train) [30][45/63] lr: 6.8474e-03 eta: 22:55:30 time: 1.0638 data_time: 0.0586 memory: 16202 loss_prob: 1.3389 loss_thr: 0.6394 loss_db: 0.2196 loss: 2.1979 2022/08/29 23:44:41 - mmengine - INFO - Epoch(train) [30][50/63] lr: 6.8474e-03 eta: 22:53:59 time: 0.9169 data_time: 0.0545 memory: 16202 loss_prob: 1.3547 loss_thr: 0.6164 loss_db: 0.2194 loss: 2.1904 2022/08/29 23:44:46 - mmengine - INFO - Epoch(train) [30][55/63] lr: 6.8474e-03 eta: 22:53:59 time: 0.9093 data_time: 0.0518 memory: 16202 loss_prob: 1.4141 loss_thr: 0.5965 loss_db: 0.2306 loss: 2.2411 2022/08/29 23:44:52 - mmengine - INFO - Epoch(train) [30][60/63] lr: 6.8474e-03 eta: 22:53:25 time: 1.0583 data_time: 0.0403 memory: 16202 loss_prob: 1.4723 loss_thr: 0.5948 loss_db: 0.2341 loss: 2.3013 2022/08/29 23:44:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:45:03 - mmengine - INFO - Epoch(train) [31][5/63] lr: 6.8422e-03 eta: 22:53:25 time: 1.2760 data_time: 0.4134 memory: 16202 loss_prob: 1.6943 loss_thr: 0.6344 loss_db: 0.2823 loss: 2.6110 2022/08/29 23:45:08 - mmengine - INFO - Epoch(train) [31][10/63] lr: 6.8422e-03 eta: 22:52:21 time: 1.3266 data_time: 0.4175 memory: 16202 loss_prob: 1.6351 loss_thr: 0.6112 loss_db: 0.2742 loss: 2.5206 2022/08/29 23:45:12 - mmengine - INFO - Epoch(train) [31][15/63] lr: 6.8422e-03 eta: 22:52:21 time: 0.9824 data_time: 0.0514 memory: 16202 loss_prob: 1.4172 loss_thr: 0.6361 loss_db: 0.2307 loss: 2.2839 2022/08/29 23:45:17 - mmengine - INFO - Epoch(train) [31][20/63] lr: 6.8422e-03 eta: 22:50:49 time: 0.9080 data_time: 0.0366 memory: 16202 loss_prob: 1.3883 loss_thr: 0.6527 loss_db: 0.2335 loss: 2.2744 2022/08/29 23:45:22 - mmengine - INFO - Epoch(train) [31][25/63] lr: 6.8422e-03 eta: 22:50:49 time: 0.9079 data_time: 0.0568 memory: 16202 loss_prob: 1.2676 loss_thr: 0.6038 loss_db: 0.2117 loss: 2.0831 2022/08/29 23:45:27 - mmengine - INFO - Epoch(train) [31][30/63] lr: 6.8422e-03 eta: 22:50:03 time: 1.0239 data_time: 0.0459 memory: 16202 loss_prob: 1.2210 loss_thr: 0.6010 loss_db: 0.1978 loss: 2.0198 2022/08/29 23:45:32 - mmengine - INFO - Epoch(train) [31][35/63] lr: 6.8422e-03 eta: 22:50:03 time: 1.0117 data_time: 0.0533 memory: 16202 loss_prob: 1.2412 loss_thr: 0.6061 loss_db: 0.1983 loss: 2.0456 2022/08/29 23:45:36 - mmengine - INFO - Epoch(train) [31][40/63] lr: 6.8422e-03 eta: 22:48:32 time: 0.9081 data_time: 0.0521 memory: 16202 loss_prob: 1.3920 loss_thr: 0.6429 loss_db: 0.2260 loss: 2.2608 2022/08/29 23:45:42 - mmengine - INFO - Epoch(train) [31][45/63] lr: 6.8422e-03 eta: 22:48:32 time: 1.0084 data_time: 0.0881 memory: 16202 loss_prob: 1.3342 loss_thr: 0.6225 loss_db: 0.2170 loss: 2.1736 2022/08/29 23:45:47 - mmengine - INFO - Epoch(train) [31][50/63] lr: 6.8422e-03 eta: 22:47:58 time: 1.0534 data_time: 0.1090 memory: 16202 loss_prob: 1.3594 loss_thr: 0.5944 loss_db: 0.2219 loss: 2.1757 2022/08/29 23:45:51 - mmengine - INFO - Epoch(train) [31][55/63] lr: 6.8422e-03 eta: 22:47:58 time: 0.9177 data_time: 0.0490 memory: 16202 loss_prob: 1.4296 loss_thr: 0.6039 loss_db: 0.2323 loss: 2.2658 2022/08/29 23:45:55 - mmengine - INFO - Epoch(train) [31][60/63] lr: 6.8422e-03 eta: 22:46:16 time: 0.8737 data_time: 0.0338 memory: 16202 loss_prob: 1.3488 loss_thr: 0.6095 loss_db: 0.2170 loss: 2.1753 2022/08/29 23:45:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:46:06 - mmengine - INFO - Epoch(train) [32][5/63] lr: 6.8369e-03 eta: 22:46:16 time: 1.2065 data_time: 0.3482 memory: 16202 loss_prob: 1.2733 loss_thr: 0.5834 loss_db: 0.2101 loss: 2.0667 2022/08/29 23:46:10 - mmengine - INFO - Epoch(train) [32][10/63] lr: 6.8369e-03 eta: 22:44:54 time: 1.2683 data_time: 0.3668 memory: 16202 loss_prob: 1.2865 loss_thr: 0.6159 loss_db: 0.2160 loss: 2.1185 2022/08/29 23:46:15 - mmengine - INFO - Epoch(train) [32][15/63] lr: 6.8369e-03 eta: 22:44:54 time: 0.9088 data_time: 0.0583 memory: 16202 loss_prob: 1.2833 loss_thr: 0.6176 loss_db: 0.2141 loss: 2.1150 2022/08/29 23:46:20 - mmengine - INFO - Epoch(train) [32][20/63] lr: 6.8369e-03 eta: 22:43:29 time: 0.9132 data_time: 0.0421 memory: 16202 loss_prob: 1.2990 loss_thr: 0.6207 loss_db: 0.2107 loss: 2.1304 2022/08/29 23:46:24 - mmengine - INFO - Epoch(train) [32][25/63] lr: 6.8369e-03 eta: 22:43:29 time: 0.9212 data_time: 0.0587 memory: 16202 loss_prob: 1.3200 loss_thr: 0.6192 loss_db: 0.2115 loss: 2.1506 2022/08/29 23:46:29 - mmengine - INFO - Epoch(train) [32][30/63] lr: 6.8369e-03 eta: 22:42:03 time: 0.9103 data_time: 0.0539 memory: 16202 loss_prob: 1.4430 loss_thr: 0.6329 loss_db: 0.2348 loss: 2.3106 2022/08/29 23:46:34 - mmengine - INFO - Epoch(train) [32][35/63] lr: 6.8369e-03 eta: 22:42:03 time: 1.0309 data_time: 0.0462 memory: 16202 loss_prob: 1.4533 loss_thr: 0.6280 loss_db: 0.2402 loss: 2.3215 2022/08/29 23:46:39 - mmengine - INFO - Epoch(train) [32][40/63] lr: 6.8369e-03 eta: 22:41:16 time: 1.0128 data_time: 0.0526 memory: 16202 loss_prob: 1.3816 loss_thr: 0.5986 loss_db: 0.2262 loss: 2.2063 2022/08/29 23:46:43 - mmengine - INFO - Epoch(train) [32][45/63] lr: 6.8369e-03 eta: 22:41:16 time: 0.8735 data_time: 0.0472 memory: 16202 loss_prob: 1.3895 loss_thr: 0.6068 loss_db: 0.2199 loss: 2.2162 2022/08/29 23:46:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:46:47 - mmengine - INFO - Epoch(train) [32][50/63] lr: 6.8369e-03 eta: 22:39:25 time: 0.8358 data_time: 0.0352 memory: 16202 loss_prob: 1.3819 loss_thr: 0.6315 loss_db: 0.2165 loss: 2.2299 2022/08/29 23:46:52 - mmengine - INFO - Epoch(train) [32][55/63] lr: 6.8369e-03 eta: 22:39:25 time: 0.8648 data_time: 0.0444 memory: 16202 loss_prob: 1.5124 loss_thr: 0.6596 loss_db: 0.2454 loss: 2.4174 2022/08/29 23:46:56 - mmengine - INFO - Epoch(train) [32][60/63] lr: 6.8369e-03 eta: 22:37:55 time: 0.8935 data_time: 0.0489 memory: 16202 loss_prob: 1.4359 loss_thr: 0.6398 loss_db: 0.2354 loss: 2.3111 2022/08/29 23:46:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:47:06 - mmengine - INFO - Epoch(train) [33][5/63] lr: 6.8316e-03 eta: 22:37:55 time: 1.1897 data_time: 0.3241 memory: 16202 loss_prob: 1.3760 loss_thr: 0.6320 loss_db: 0.2302 loss: 2.2382 2022/08/29 23:47:12 - mmengine - INFO - Epoch(train) [33][10/63] lr: 6.8316e-03 eta: 22:37:06 time: 1.3452 data_time: 0.3481 memory: 16202 loss_prob: 1.3288 loss_thr: 0.6244 loss_db: 0.2138 loss: 2.1670 2022/08/29 23:47:16 - mmengine - INFO - Epoch(train) [33][15/63] lr: 6.8316e-03 eta: 22:37:06 time: 0.9785 data_time: 0.0504 memory: 16202 loss_prob: 1.3545 loss_thr: 0.6195 loss_db: 0.2190 loss: 2.1929 2022/08/29 23:47:22 - mmengine - INFO - Epoch(train) [33][20/63] lr: 6.8316e-03 eta: 22:36:16 time: 0.9974 data_time: 0.0401 memory: 16202 loss_prob: 1.4003 loss_thr: 0.6237 loss_db: 0.2317 loss: 2.2557 2022/08/29 23:47:26 - mmengine - INFO - Epoch(train) [33][25/63] lr: 6.8316e-03 eta: 22:36:16 time: 1.0332 data_time: 0.0510 memory: 16202 loss_prob: 1.3642 loss_thr: 0.6295 loss_db: 0.2238 loss: 2.2175 2022/08/29 23:47:31 - mmengine - INFO - Epoch(train) [33][30/63] lr: 6.8316e-03 eta: 22:34:55 time: 0.9116 data_time: 0.0421 memory: 16202 loss_prob: 1.3775 loss_thr: 0.6380 loss_db: 0.2237 loss: 2.2392 2022/08/29 23:47:35 - mmengine - INFO - Epoch(train) [33][35/63] lr: 6.8316e-03 eta: 22:34:55 time: 0.8845 data_time: 0.0372 memory: 16202 loss_prob: 1.4016 loss_thr: 0.6340 loss_db: 0.2249 loss: 2.2605 2022/08/29 23:47:41 - mmengine - INFO - Epoch(train) [33][40/63] lr: 6.8316e-03 eta: 22:34:08 time: 1.0040 data_time: 0.0507 memory: 16202 loss_prob: 1.3269 loss_thr: 0.6300 loss_db: 0.2154 loss: 2.1723 2022/08/29 23:47:45 - mmengine - INFO - Epoch(train) [33][45/63] lr: 6.8316e-03 eta: 22:34:08 time: 1.0240 data_time: 0.0497 memory: 16202 loss_prob: 1.2702 loss_thr: 0.6366 loss_db: 0.2094 loss: 2.1162 2022/08/29 23:47:50 - mmengine - INFO - Epoch(train) [33][50/63] lr: 6.8316e-03 eta: 22:33:07 time: 0.9660 data_time: 0.0496 memory: 16202 loss_prob: 1.4812 loss_thr: 0.6444 loss_db: 0.2508 loss: 2.3764 2022/08/29 23:47:55 - mmengine - INFO - Epoch(train) [33][55/63] lr: 6.8316e-03 eta: 22:33:07 time: 0.9568 data_time: 0.0526 memory: 16202 loss_prob: 1.5806 loss_thr: 0.6535 loss_db: 0.2656 loss: 2.4997 2022/08/29 23:48:00 - mmengine - INFO - Epoch(train) [33][60/63] lr: 6.8316e-03 eta: 22:32:17 time: 0.9942 data_time: 0.0439 memory: 16202 loss_prob: 1.4907 loss_thr: 0.6552 loss_db: 0.2349 loss: 2.3809 2022/08/29 23:48:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:48:13 - mmengine - INFO - Epoch(train) [34][5/63] lr: 6.8264e-03 eta: 22:32:17 time: 1.5192 data_time: 0.3688 memory: 16202 loss_prob: 1.3879 loss_thr: 0.6579 loss_db: 0.2256 loss: 2.2714 2022/08/29 23:48:19 - mmengine - INFO - Epoch(train) [34][10/63] lr: 6.8264e-03 eta: 22:33:14 time: 1.6381 data_time: 0.3816 memory: 16202 loss_prob: 1.4344 loss_thr: 0.6626 loss_db: 0.2332 loss: 2.3302 2022/08/29 23:48:24 - mmengine - INFO - Epoch(train) [34][15/63] lr: 6.8264e-03 eta: 22:33:14 time: 1.0829 data_time: 0.0676 memory: 16202 loss_prob: 1.3704 loss_thr: 0.6398 loss_db: 0.2216 loss: 2.2317 2022/08/29 23:48:28 - mmengine - INFO - Epoch(train) [34][20/63] lr: 6.8264e-03 eta: 22:32:04 time: 0.9341 data_time: 0.0598 memory: 16202 loss_prob: 1.2400 loss_thr: 0.6050 loss_db: 0.2018 loss: 2.0467 2022/08/29 23:48:33 - mmengine - INFO - Epoch(train) [34][25/63] lr: 6.8264e-03 eta: 22:32:04 time: 0.9817 data_time: 0.0580 memory: 16202 loss_prob: 1.3231 loss_thr: 0.6231 loss_db: 0.2148 loss: 2.1609 2022/08/29 23:48:38 - mmengine - INFO - Epoch(train) [34][30/63] lr: 6.8264e-03 eta: 22:30:49 time: 0.9222 data_time: 0.0275 memory: 16202 loss_prob: 1.4441 loss_thr: 0.6841 loss_db: 0.2391 loss: 2.3673 2022/08/29 23:48:43 - mmengine - INFO - Epoch(train) [34][35/63] lr: 6.8264e-03 eta: 22:30:49 time: 0.9611 data_time: 0.0507 memory: 16202 loss_prob: 1.5061 loss_thr: 0.6758 loss_db: 0.2526 loss: 2.4345 2022/08/29 23:48:48 - mmengine - INFO - Epoch(train) [34][40/63] lr: 6.8264e-03 eta: 22:30:04 time: 1.0052 data_time: 0.0592 memory: 16202 loss_prob: 1.5053 loss_thr: 0.6386 loss_db: 0.2527 loss: 2.3966 2022/08/29 23:48:52 - mmengine - INFO - Epoch(train) [34][45/63] lr: 6.8264e-03 eta: 22:30:04 time: 0.9136 data_time: 0.0499 memory: 16202 loss_prob: 1.4934 loss_thr: 0.6131 loss_db: 0.2495 loss: 2.3560 2022/08/29 23:48:56 - mmengine - INFO - Epoch(train) [34][50/63] lr: 6.8264e-03 eta: 22:28:33 time: 0.8699 data_time: 0.0507 memory: 16202 loss_prob: 1.4715 loss_thr: 0.6305 loss_db: 0.2448 loss: 2.3468 2022/08/29 23:49:02 - mmengine - INFO - Epoch(train) [34][55/63] lr: 6.8264e-03 eta: 22:28:33 time: 0.9619 data_time: 0.0357 memory: 16202 loss_prob: 1.4137 loss_thr: 0.6286 loss_db: 0.2336 loss: 2.2759 2022/08/29 23:49:06 - mmengine - INFO - Epoch(train) [34][60/63] lr: 6.8264e-03 eta: 22:27:49 time: 1.0059 data_time: 0.0525 memory: 16202 loss_prob: 1.3801 loss_thr: 0.6044 loss_db: 0.2226 loss: 2.2072 2022/08/29 23:49:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:49:17 - mmengine - INFO - Epoch(train) [35][5/63] lr: 6.8211e-03 eta: 22:27:49 time: 1.2086 data_time: 0.3395 memory: 16202 loss_prob: 1.3732 loss_thr: 0.5956 loss_db: 0.2280 loss: 2.1968 2022/08/29 23:49:22 - mmengine - INFO - Epoch(train) [35][10/63] lr: 6.8211e-03 eta: 22:26:44 time: 1.2810 data_time: 0.3773 memory: 16202 loss_prob: 1.2393 loss_thr: 0.5841 loss_db: 0.2049 loss: 2.0283 2022/08/29 23:49:27 - mmengine - INFO - Epoch(train) [35][15/63] lr: 6.8211e-03 eta: 22:26:44 time: 0.9536 data_time: 0.0600 memory: 16202 loss_prob: 1.3350 loss_thr: 0.6263 loss_db: 0.2112 loss: 2.1725 2022/08/29 23:49:32 - mmengine - INFO - Epoch(train) [35][20/63] lr: 6.8211e-03 eta: 22:26:01 time: 1.0057 data_time: 0.0335 memory: 16202 loss_prob: 1.2625 loss_thr: 0.6083 loss_db: 0.2019 loss: 2.0727 2022/08/29 23:49:36 - mmengine - INFO - Epoch(train) [35][25/63] lr: 6.8211e-03 eta: 22:26:01 time: 0.9726 data_time: 0.0605 memory: 16202 loss_prob: 1.1357 loss_thr: 0.5710 loss_db: 0.1851 loss: 1.8918 2022/08/29 23:49:41 - mmengine - INFO - Epoch(train) [35][30/63] lr: 6.8211e-03 eta: 22:24:58 time: 0.9469 data_time: 0.0548 memory: 16202 loss_prob: 1.2074 loss_thr: 0.6156 loss_db: 0.1977 loss: 2.0207 2022/08/29 23:49:46 - mmengine - INFO - Epoch(train) [35][35/63] lr: 6.8211e-03 eta: 22:24:58 time: 0.9681 data_time: 0.0367 memory: 16202 loss_prob: 1.2131 loss_thr: 0.6207 loss_db: 0.1971 loss: 2.0310 2022/08/29 23:49:51 - mmengine - INFO - Epoch(train) [35][40/63] lr: 6.8211e-03 eta: 22:23:58 time: 0.9528 data_time: 0.0494 memory: 16202 loss_prob: 1.3423 loss_thr: 0.6001 loss_db: 0.2096 loss: 2.1519 2022/08/29 23:49:55 - mmengine - INFO - Epoch(train) [35][45/63] lr: 6.8211e-03 eta: 22:23:58 time: 0.9237 data_time: 0.0509 memory: 16202 loss_prob: 1.3766 loss_thr: 0.6100 loss_db: 0.2200 loss: 2.2066 2022/08/29 23:50:00 - mmengine - INFO - Epoch(train) [35][50/63] lr: 6.8211e-03 eta: 22:23:03 time: 0.9666 data_time: 0.0438 memory: 16202 loss_prob: 1.2406 loss_thr: 0.6046 loss_db: 0.2027 loss: 2.0479 2022/08/29 23:50:05 - mmengine - INFO - Epoch(train) [35][55/63] lr: 6.8211e-03 eta: 22:23:03 time: 0.9493 data_time: 0.0443 memory: 16202 loss_prob: 1.2736 loss_thr: 0.6031 loss_db: 0.2044 loss: 2.0810 2022/08/29 23:50:09 - mmengine - INFO - Epoch(train) [35][60/63] lr: 6.8211e-03 eta: 22:21:45 time: 0.8978 data_time: 0.0470 memory: 16202 loss_prob: 1.2418 loss_thr: 0.5934 loss_db: 0.2015 loss: 2.0366 2022/08/29 23:50:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:50:19 - mmengine - INFO - Epoch(train) [36][5/63] lr: 6.8158e-03 eta: 22:21:45 time: 1.2154 data_time: 0.3633 memory: 16202 loss_prob: 1.2595 loss_thr: 0.6025 loss_db: 0.2105 loss: 2.0725 2022/08/29 23:50:25 - mmengine - INFO - Epoch(train) [36][10/63] lr: 6.8158e-03 eta: 22:20:43 time: 1.2820 data_time: 0.3906 memory: 16202 loss_prob: 1.3651 loss_thr: 0.6335 loss_db: 0.2182 loss: 2.2168 2022/08/29 23:50:30 - mmengine - INFO - Epoch(train) [36][15/63] lr: 6.8158e-03 eta: 22:20:43 time: 1.0252 data_time: 0.0584 memory: 16202 loss_prob: 1.3534 loss_thr: 0.6231 loss_db: 0.2141 loss: 2.1906 2022/08/29 23:50:35 - mmengine - INFO - Epoch(train) [36][20/63] lr: 6.8158e-03 eta: 22:20:14 time: 1.0413 data_time: 0.1083 memory: 16202 loss_prob: 1.2178 loss_thr: 0.6167 loss_db: 0.1964 loss: 2.0308 2022/08/29 23:50:40 - mmengine - INFO - Epoch(train) [36][25/63] lr: 6.8158e-03 eta: 22:20:14 time: 1.0110 data_time: 0.1069 memory: 16202 loss_prob: 1.1772 loss_thr: 0.6045 loss_db: 0.1918 loss: 1.9735 2022/08/29 23:50:45 - mmengine - INFO - Epoch(train) [36][30/63] lr: 6.8158e-03 eta: 22:19:20 time: 0.9652 data_time: 0.0537 memory: 16202 loss_prob: 1.1730 loss_thr: 0.5845 loss_db: 0.1894 loss: 1.9469 2022/08/29 23:50:49 - mmengine - INFO - Epoch(train) [36][35/63] lr: 6.8158e-03 eta: 22:19:20 time: 0.8870 data_time: 0.0544 memory: 16202 loss_prob: 1.1003 loss_thr: 0.5847 loss_db: 0.1796 loss: 1.8646 2022/08/29 23:50:53 - mmengine - INFO - Epoch(train) [36][40/63] lr: 6.8158e-03 eta: 22:17:37 time: 0.8129 data_time: 0.0286 memory: 16202 loss_prob: 1.1150 loss_thr: 0.5835 loss_db: 0.1845 loss: 1.8830 2022/08/29 23:50:57 - mmengine - INFO - Epoch(train) [36][45/63] lr: 6.8158e-03 eta: 22:17:37 time: 0.8267 data_time: 0.0477 memory: 16202 loss_prob: 1.2166 loss_thr: 0.5938 loss_db: 0.1990 loss: 2.0094 2022/08/29 23:51:01 - mmengine - INFO - Epoch(train) [36][50/63] lr: 6.8158e-03 eta: 22:16:04 time: 0.8420 data_time: 0.0605 memory: 16202 loss_prob: 1.2814 loss_thr: 0.6134 loss_db: 0.2067 loss: 2.1015 2022/08/29 23:51:05 - mmengine - INFO - Epoch(train) [36][55/63] lr: 6.8158e-03 eta: 22:16:04 time: 0.8261 data_time: 0.0346 memory: 16202 loss_prob: 1.2258 loss_thr: 0.6057 loss_db: 0.1965 loss: 2.0280 2022/08/29 23:51:09 - mmengine - INFO - Epoch(train) [36][60/63] lr: 6.8158e-03 eta: 22:14:30 time: 0.8366 data_time: 0.0292 memory: 16202 loss_prob: 1.3836 loss_thr: 0.6220 loss_db: 0.2164 loss: 2.2221 2022/08/29 23:51:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:51:19 - mmengine - INFO - Epoch(train) [37][5/63] lr: 6.8106e-03 eta: 22:14:30 time: 1.1352 data_time: 0.3255 memory: 16202 loss_prob: 1.4028 loss_thr: 0.6207 loss_db: 0.2137 loss: 2.2371 2022/08/29 23:51:24 - mmengine - INFO - Epoch(train) [37][10/63] lr: 6.8106e-03 eta: 22:13:13 time: 1.2230 data_time: 0.3459 memory: 16202 loss_prob: 1.2696 loss_thr: 0.6296 loss_db: 0.2029 loss: 2.1021 2022/08/29 23:51:28 - mmengine - INFO - Epoch(train) [37][15/63] lr: 6.8106e-03 eta: 22:13:13 time: 0.9069 data_time: 0.0462 memory: 16202 loss_prob: 1.3097 loss_thr: 0.6256 loss_db: 0.2114 loss: 2.1467 2022/08/29 23:51:33 - mmengine - INFO - Epoch(train) [37][20/63] lr: 6.8106e-03 eta: 22:12:15 time: 0.9460 data_time: 0.0327 memory: 16202 loss_prob: 1.2755 loss_thr: 0.6150 loss_db: 0.2005 loss: 2.0910 2022/08/29 23:51:38 - mmengine - INFO - Epoch(train) [37][25/63] lr: 6.8106e-03 eta: 22:12:15 time: 0.9819 data_time: 0.0585 memory: 16202 loss_prob: 1.1746 loss_thr: 0.5740 loss_db: 0.1857 loss: 1.9343 2022/08/29 23:51:42 - mmengine - INFO - Epoch(train) [37][30/63] lr: 6.8106e-03 eta: 22:11:04 time: 0.9004 data_time: 0.0553 memory: 16202 loss_prob: 1.1476 loss_thr: 0.5739 loss_db: 0.1858 loss: 1.9073 2022/08/29 23:51:47 - mmengine - INFO - Epoch(train) [37][35/63] lr: 6.8106e-03 eta: 22:11:04 time: 0.8650 data_time: 0.0383 memory: 16202 loss_prob: 1.1910 loss_thr: 0.5723 loss_db: 0.1951 loss: 1.9584 2022/08/29 23:51:52 - mmengine - INFO - Epoch(train) [37][40/63] lr: 6.8106e-03 eta: 22:10:07 time: 0.9447 data_time: 0.0372 memory: 16202 loss_prob: 1.3112 loss_thr: 0.5922 loss_db: 0.2143 loss: 2.1177 2022/08/29 23:51:56 - mmengine - INFO - Epoch(train) [37][45/63] lr: 6.8106e-03 eta: 22:10:07 time: 0.9589 data_time: 0.0356 memory: 16202 loss_prob: 1.2800 loss_thr: 0.6148 loss_db: 0.2085 loss: 2.1033 2022/08/29 23:52:00 - mmengine - INFO - Epoch(train) [37][50/63] lr: 6.8106e-03 eta: 22:08:42 time: 0.8536 data_time: 0.0285 memory: 16202 loss_prob: 1.2064 loss_thr: 0.6059 loss_db: 0.2011 loss: 2.0134 2022/08/29 23:52:05 - mmengine - INFO - Epoch(train) [37][55/63] lr: 6.8106e-03 eta: 22:08:42 time: 0.8297 data_time: 0.0265 memory: 16202 loss_prob: 1.2534 loss_thr: 0.6157 loss_db: 0.2058 loss: 2.0749 2022/08/29 23:52:09 - mmengine - INFO - Epoch(train) [37][60/63] lr: 6.8106e-03 eta: 22:07:16 time: 0.8510 data_time: 0.0340 memory: 16202 loss_prob: 1.2100 loss_thr: 0.5987 loss_db: 0.1992 loss: 2.0079 2022/08/29 23:52:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:52:17 - mmengine - INFO - Epoch(train) [38][5/63] lr: 6.8053e-03 eta: 22:07:16 time: 1.0235 data_time: 0.2366 memory: 16202 loss_prob: 1.0906 loss_thr: 0.5743 loss_db: 0.1776 loss: 1.8425 2022/08/29 23:52:22 - mmengine - INFO - Epoch(train) [38][10/63] lr: 6.8053e-03 eta: 22:05:06 time: 1.0415 data_time: 0.2391 memory: 16202 loss_prob: 1.1208 loss_thr: 0.5769 loss_db: 0.1830 loss: 1.8807 2022/08/29 23:52:26 - mmengine - INFO - Epoch(train) [38][15/63] lr: 6.8053e-03 eta: 22:05:06 time: 0.8697 data_time: 0.0248 memory: 16202 loss_prob: 1.2158 loss_thr: 0.5909 loss_db: 0.1973 loss: 2.0039 2022/08/29 23:52:30 - mmengine - INFO - Epoch(train) [38][20/63] lr: 6.8053e-03 eta: 22:03:48 time: 0.8700 data_time: 0.0238 memory: 16202 loss_prob: 1.3373 loss_thr: 0.6445 loss_db: 0.2184 loss: 2.2002 2022/08/29 23:52:35 - mmengine - INFO - Epoch(train) [38][25/63] lr: 6.8053e-03 eta: 22:03:48 time: 0.8723 data_time: 0.0389 memory: 16202 loss_prob: 1.2129 loss_thr: 0.5971 loss_db: 0.2003 loss: 2.0103 2022/08/29 23:52:40 - mmengine - INFO - Epoch(train) [38][30/63] lr: 6.8053e-03 eta: 22:03:13 time: 1.0070 data_time: 0.0335 memory: 16202 loss_prob: 1.0919 loss_thr: 0.5578 loss_db: 0.1758 loss: 1.8256 2022/08/29 23:52:45 - mmengine - INFO - Epoch(train) [38][35/63] lr: 6.8053e-03 eta: 22:03:13 time: 1.0169 data_time: 0.0602 memory: 16202 loss_prob: 1.1327 loss_thr: 0.5744 loss_db: 0.1808 loss: 1.8879 2022/08/29 23:52:50 - mmengine - INFO - Epoch(train) [38][40/63] lr: 6.8053e-03 eta: 22:02:13 time: 0.9231 data_time: 0.0593 memory: 16202 loss_prob: 1.1991 loss_thr: 0.5809 loss_db: 0.1932 loss: 1.9733 2022/08/29 23:52:54 - mmengine - INFO - Epoch(train) [38][45/63] lr: 6.8053e-03 eta: 22:02:13 time: 0.8901 data_time: 0.0319 memory: 16202 loss_prob: 1.2057 loss_thr: 0.5954 loss_db: 0.1915 loss: 1.9926 2022/08/29 23:53:00 - mmengine - INFO - Epoch(train) [38][50/63] lr: 6.8053e-03 eta: 22:01:54 time: 1.0567 data_time: 0.0571 memory: 16202 loss_prob: 1.1076 loss_thr: 0.5768 loss_db: 0.1760 loss: 1.8604 2022/08/29 23:53:06 - mmengine - INFO - Epoch(train) [38][55/63] lr: 6.8053e-03 eta: 22:01:54 time: 1.2406 data_time: 0.0501 memory: 16202 loss_prob: 1.0593 loss_thr: 0.5694 loss_db: 0.1704 loss: 1.7990 2022/08/29 23:53:15 - mmengine - INFO - Epoch(train) [38][60/63] lr: 6.8053e-03 eta: 22:03:32 time: 1.4399 data_time: 0.0729 memory: 16202 loss_prob: 1.0760 loss_thr: 0.6005 loss_db: 0.1738 loss: 1.8503 2022/08/29 23:53:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:53:30 - mmengine - INFO - Epoch(train) [39][5/63] lr: 6.8000e-03 eta: 22:03:32 time: 1.8493 data_time: 0.3570 memory: 16202 loss_prob: 1.3493 loss_thr: 0.6363 loss_db: 0.2138 loss: 2.1995 2022/08/29 23:53:38 - mmengine - INFO - Epoch(train) [39][10/63] lr: 6.8000e-03 eta: 22:05:13 time: 1.7873 data_time: 0.3954 memory: 16202 loss_prob: 1.2573 loss_thr: 0.6109 loss_db: 0.1988 loss: 2.0669 2022/08/29 23:53:47 - mmengine - INFO - Epoch(train) [39][15/63] lr: 6.8000e-03 eta: 22:05:13 time: 1.7057 data_time: 0.0582 memory: 16202 loss_prob: 1.2374 loss_thr: 0.5944 loss_db: 0.1938 loss: 2.0256 2022/08/29 23:53:55 - mmengine - INFO - Epoch(train) [39][20/63] lr: 6.8000e-03 eta: 22:08:09 time: 1.7027 data_time: 0.0494 memory: 16202 loss_prob: 1.1503 loss_thr: 0.5791 loss_db: 0.1868 loss: 1.9163 2022/08/29 23:54:02 - mmengine - INFO - Epoch(train) [39][25/63] lr: 6.8000e-03 eta: 22:08:09 time: 1.5208 data_time: 0.0587 memory: 16202 loss_prob: 1.1566 loss_thr: 0.5966 loss_db: 0.1907 loss: 1.9440 2022/08/29 23:54:10 - mmengine - INFO - Epoch(train) [39][30/63] lr: 6.8000e-03 eta: 22:09:49 time: 1.4581 data_time: 0.0482 memory: 16202 loss_prob: 1.2416 loss_thr: 0.6104 loss_db: 0.2008 loss: 2.0528 2022/08/29 23:54:18 - mmengine - INFO - Epoch(train) [39][35/63] lr: 6.8000e-03 eta: 22:09:49 time: 1.6168 data_time: 0.0743 memory: 16202 loss_prob: 1.1194 loss_thr: 0.5634 loss_db: 0.1816 loss: 1.8644 2022/08/29 23:54:27 - mmengine - INFO - Epoch(train) [39][40/63] lr: 6.8000e-03 eta: 22:12:40 time: 1.6942 data_time: 0.0752 memory: 16202 loss_prob: 1.2200 loss_thr: 0.5922 loss_db: 0.1981 loss: 2.0104 2022/08/29 23:54:31 - mmengine - INFO - Epoch(train) [39][45/63] lr: 6.8000e-03 eta: 22:12:40 time: 1.2673 data_time: 0.0531 memory: 16202 loss_prob: 1.3091 loss_thr: 0.6227 loss_db: 0.2122 loss: 2.1439 2022/08/29 23:54:36 - mmengine - INFO - Epoch(train) [39][50/63] lr: 6.8000e-03 eta: 22:11:45 time: 0.9458 data_time: 0.0591 memory: 16202 loss_prob: 1.1448 loss_thr: 0.5784 loss_db: 0.1885 loss: 1.9118 2022/08/29 23:54:41 - mmengine - INFO - Epoch(train) [39][55/63] lr: 6.8000e-03 eta: 22:11:45 time: 0.9799 data_time: 0.0490 memory: 16202 loss_prob: 1.1581 loss_thr: 0.6151 loss_db: 0.1962 loss: 1.9694 2022/08/29 23:54:46 - mmengine - INFO - Epoch(train) [39][60/63] lr: 6.8000e-03 eta: 22:10:48 time: 0.9369 data_time: 0.0359 memory: 16202 loss_prob: 1.2757 loss_thr: 0.6635 loss_db: 0.2147 loss: 2.1539 2022/08/29 23:54:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:54:56 - mmengine - INFO - Epoch(train) [40][5/63] lr: 6.7947e-03 eta: 22:10:48 time: 1.1860 data_time: 0.3785 memory: 16202 loss_prob: 1.1779 loss_thr: 0.6211 loss_db: 0.1955 loss: 1.9945 2022/08/29 23:55:01 - mmengine - INFO - Epoch(train) [40][10/63] lr: 6.7947e-03 eta: 22:09:49 time: 1.2693 data_time: 0.3952 memory: 16202 loss_prob: 1.1377 loss_thr: 0.5908 loss_db: 0.1851 loss: 1.9136 2022/08/29 23:55:05 - mmengine - INFO - Epoch(train) [40][15/63] lr: 6.7947e-03 eta: 22:09:49 time: 0.9213 data_time: 0.0584 memory: 16202 loss_prob: 1.0650 loss_thr: 0.5581 loss_db: 0.1711 loss: 1.7942 2022/08/29 23:55:09 - mmengine - INFO - Epoch(train) [40][20/63] lr: 6.7947e-03 eta: 22:08:33 time: 0.8687 data_time: 0.0366 memory: 16202 loss_prob: 1.1349 loss_thr: 0.5720 loss_db: 0.1861 loss: 1.8930 2022/08/29 23:55:14 - mmengine - INFO - Epoch(train) [40][25/63] lr: 6.7947e-03 eta: 22:08:33 time: 0.8380 data_time: 0.0567 memory: 16202 loss_prob: 1.2093 loss_thr: 0.5898 loss_db: 0.1946 loss: 1.9937 2022/08/29 23:55:18 - mmengine - INFO - Epoch(train) [40][30/63] lr: 6.7947e-03 eta: 22:07:16 time: 0.8659 data_time: 0.0629 memory: 16202 loss_prob: 1.1712 loss_thr: 0.5819 loss_db: 0.1872 loss: 1.9403 2022/08/29 23:55:22 - mmengine - INFO - Epoch(train) [40][35/63] lr: 6.7947e-03 eta: 22:07:16 time: 0.8474 data_time: 0.0409 memory: 16202 loss_prob: 1.2893 loss_thr: 0.5842 loss_db: 0.2078 loss: 2.0812 2022/08/29 23:55:26 - mmengine - INFO - Epoch(train) [40][40/63] lr: 6.7947e-03 eta: 22:05:49 time: 0.8311 data_time: 0.0417 memory: 16202 loss_prob: 1.3249 loss_thr: 0.5895 loss_db: 0.2112 loss: 2.1255 2022/08/29 23:55:31 - mmengine - INFO - Epoch(train) [40][45/63] lr: 6.7947e-03 eta: 22:05:49 time: 0.8886 data_time: 0.0529 memory: 16202 loss_prob: 1.2021 loss_thr: 0.5922 loss_db: 0.1943 loss: 1.9886 2022/08/29 23:55:35 - mmengine - INFO - Epoch(train) [40][50/63] lr: 6.7947e-03 eta: 22:04:47 time: 0.9130 data_time: 0.0460 memory: 16202 loss_prob: 1.3862 loss_thr: 0.6297 loss_db: 0.2258 loss: 2.2416 2022/08/29 23:55:40 - mmengine - INFO - Epoch(train) [40][55/63] lr: 6.7947e-03 eta: 22:04:47 time: 0.9328 data_time: 0.0502 memory: 16202 loss_prob: 1.3957 loss_thr: 0.6050 loss_db: 0.2254 loss: 2.2261 2022/08/29 23:55:44 - mmengine - INFO - Epoch(train) [40][60/63] lr: 6.7947e-03 eta: 22:03:45 time: 0.9091 data_time: 0.0546 memory: 16202 loss_prob: 1.2661 loss_thr: 0.5741 loss_db: 0.1989 loss: 2.0391 2022/08/29 23:55:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:55:47 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/08/29 23:55:56 - mmengine - INFO - Epoch(val) [40][5/32] eta: 22:03:45 time: 1.5989 data_time: 0.2370 memory: 16202 2022/08/29 23:56:00 - mmengine - INFO - Epoch(val) [40][10/32] eta: 0:00:19 time: 0.8976 data_time: 0.2735 memory: 15734 2022/08/29 23:56:03 - mmengine - INFO - Epoch(val) [40][15/32] eta: 0:00:19 time: 0.6789 data_time: 0.0570 memory: 15734 2022/08/29 23:56:06 - mmengine - INFO - Epoch(val) [40][20/32] eta: 0:00:07 time: 0.6164 data_time: 0.0591 memory: 15734 2022/08/29 23:56:10 - mmengine - INFO - Epoch(val) [40][25/32] eta: 0:00:07 time: 0.7176 data_time: 0.0577 memory: 15734 2022/08/29 23:56:13 - mmengine - INFO - Epoch(val) [40][30/32] eta: 0:00:01 time: 0.6953 data_time: 0.0301 memory: 15734 2022/08/29 23:56:14 - mmengine - INFO - Evaluating hmean-iou... 2022/08/29 23:56:14 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8021, precision: 0.6819, hmean: 0.7372 2022/08/29 23:56:14 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8016, precision: 0.7737, hmean: 0.7874 2022/08/29 23:56:14 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7867, precision: 0.8178, hmean: 0.8020 2022/08/29 23:56:14 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7631, precision: 0.8605, hmean: 0.8089 2022/08/29 23:56:14 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6933, precision: 0.9017, hmean: 0.7839 2022/08/29 23:56:14 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3067, precision: 0.9830, hmean: 0.4675 2022/08/29 23:56:14 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/08/29 23:56:14 - mmengine - INFO - Epoch(val) [40][32/32] icdar/precision: 0.8605 icdar/recall: 0.7631 icdar/hmean: 0.8089 2022/08/29 23:56:22 - mmengine - INFO - Epoch(train) [41][5/63] lr: 6.7895e-03 eta: 0:00:01 time: 1.2125 data_time: 0.4010 memory: 16201 loss_prob: 1.2038 loss_thr: 0.5831 loss_db: 0.1933 loss: 1.9802 2022/08/29 23:56:27 - mmengine - INFO - Epoch(train) [41][10/63] lr: 6.7895e-03 eta: 22:03:02 time: 1.3144 data_time: 0.4038 memory: 16201 loss_prob: 1.1212 loss_thr: 0.5876 loss_db: 0.1886 loss: 1.8974 2022/08/29 23:56:33 - mmengine - INFO - Epoch(train) [41][15/63] lr: 6.7895e-03 eta: 22:03:02 time: 1.0674 data_time: 0.0538 memory: 16201 loss_prob: 1.1808 loss_thr: 0.5801 loss_db: 0.1969 loss: 1.9578 2022/08/29 23:56:37 - mmengine - INFO - Epoch(train) [41][20/63] lr: 6.7895e-03 eta: 22:02:32 time: 1.0185 data_time: 0.0561 memory: 16201 loss_prob: 1.3913 loss_thr: 0.6075 loss_db: 0.2246 loss: 2.2234 2022/08/29 23:56:42 - mmengine - INFO - Epoch(train) [41][25/63] lr: 6.7895e-03 eta: 22:02:32 time: 0.8974 data_time: 0.0553 memory: 16201 loss_prob: 1.4570 loss_thr: 0.6510 loss_db: 0.2344 loss: 2.3424 2022/08/29 23:56:46 - mmengine - INFO - Epoch(train) [41][30/63] lr: 6.7895e-03 eta: 22:01:33 time: 0.9175 data_time: 0.0490 memory: 16201 loss_prob: 1.3453 loss_thr: 0.6148 loss_db: 0.2187 loss: 2.1788 2022/08/29 23:56:52 - mmengine - INFO - Epoch(train) [41][35/63] lr: 6.7895e-03 eta: 22:01:33 time: 1.0237 data_time: 0.0381 memory: 16201 loss_prob: 1.2098 loss_thr: 0.5700 loss_db: 0.2034 loss: 1.9832 2022/08/29 23:56:56 - mmengine - INFO - Epoch(train) [41][40/63] lr: 6.7895e-03 eta: 22:00:57 time: 1.0000 data_time: 0.0520 memory: 16201 loss_prob: 1.2118 loss_thr: 0.5762 loss_db: 0.1950 loss: 1.9830 2022/08/29 23:57:01 - mmengine - INFO - Epoch(train) [41][45/63] lr: 6.7895e-03 eta: 22:00:57 time: 0.8964 data_time: 0.0736 memory: 16201 loss_prob: 1.2626 loss_thr: 0.5805 loss_db: 0.1951 loss: 2.0382 2022/08/29 23:57:05 - mmengine - INFO - Epoch(train) [41][50/63] lr: 6.7895e-03 eta: 21:59:53 time: 0.8966 data_time: 0.0632 memory: 16201 loss_prob: 1.2409 loss_thr: 0.5758 loss_db: 0.2016 loss: 2.0184 2022/08/29 23:57:11 - mmengine - INFO - Epoch(train) [41][55/63] lr: 6.7895e-03 eta: 21:59:53 time: 1.0329 data_time: 0.0546 memory: 16201 loss_prob: 1.3229 loss_thr: 0.6093 loss_db: 0.2140 loss: 2.1461 2022/08/29 23:57:16 - mmengine - INFO - Epoch(train) [41][60/63] lr: 6.7895e-03 eta: 21:59:28 time: 1.0352 data_time: 0.0638 memory: 16201 loss_prob: 1.3464 loss_thr: 0.6323 loss_db: 0.2163 loss: 2.1951 2022/08/29 23:57:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:57:26 - mmengine - INFO - Epoch(train) [42][5/63] lr: 6.7842e-03 eta: 21:59:28 time: 1.1858 data_time: 0.3887 memory: 16201 loss_prob: 1.1590 loss_thr: 0.5843 loss_db: 0.1861 loss: 1.9295 2022/08/29 23:57:31 - mmengine - INFO - Epoch(train) [42][10/63] lr: 6.7842e-03 eta: 21:58:35 time: 1.2720 data_time: 0.3923 memory: 16201 loss_prob: 1.0933 loss_thr: 0.5562 loss_db: 0.1790 loss: 1.8285 2022/08/29 23:57:35 - mmengine - INFO - Epoch(train) [42][15/63] lr: 6.7842e-03 eta: 21:58:35 time: 0.9315 data_time: 0.0520 memory: 16201 loss_prob: 1.2053 loss_thr: 0.5821 loss_db: 0.1914 loss: 1.9788 2022/08/29 23:57:40 - mmengine - INFO - Epoch(train) [42][20/63] lr: 6.7842e-03 eta: 21:57:37 time: 0.9143 data_time: 0.0356 memory: 16201 loss_prob: 1.1825 loss_thr: 0.5918 loss_db: 0.1860 loss: 1.9603 2022/08/29 23:57:44 - mmengine - INFO - Epoch(train) [42][25/63] lr: 6.7842e-03 eta: 21:57:37 time: 0.8805 data_time: 0.0329 memory: 16201 loss_prob: 1.1289 loss_thr: 0.5922 loss_db: 0.1826 loss: 1.9038 2022/08/29 23:57:48 - mmengine - INFO - Epoch(train) [42][30/63] lr: 6.7842e-03 eta: 21:56:20 time: 0.8452 data_time: 0.0325 memory: 16201 loss_prob: 1.2262 loss_thr: 0.6537 loss_db: 0.1991 loss: 2.0790 2022/08/29 23:57:53 - mmengine - INFO - Epoch(train) [42][35/63] lr: 6.7842e-03 eta: 21:56:20 time: 0.8854 data_time: 0.0441 memory: 16201 loss_prob: 1.1612 loss_thr: 0.6171 loss_db: 0.1840 loss: 1.9623 2022/08/29 23:57:57 - mmengine - INFO - Epoch(train) [42][40/63] lr: 6.7842e-03 eta: 21:55:19 time: 0.9035 data_time: 0.0497 memory: 16201 loss_prob: 1.1475 loss_thr: 0.5810 loss_db: 0.1822 loss: 1.9107 2022/08/29 23:58:03 - mmengine - INFO - Epoch(train) [42][45/63] lr: 6.7842e-03 eta: 21:55:19 time: 0.9607 data_time: 0.0494 memory: 16201 loss_prob: 1.2050 loss_thr: 0.5986 loss_db: 0.1983 loss: 2.0020 2022/08/29 23:58:07 - mmengine - INFO - Epoch(train) [42][50/63] lr: 6.7842e-03 eta: 21:54:36 time: 0.9637 data_time: 0.0440 memory: 16201 loss_prob: 1.2516 loss_thr: 0.6073 loss_db: 0.2075 loss: 2.0665 2022/08/29 23:58:12 - mmengine - INFO - Epoch(train) [42][55/63] lr: 6.7842e-03 eta: 21:54:36 time: 0.8861 data_time: 0.0481 memory: 16201 loss_prob: 1.2444 loss_thr: 0.5942 loss_db: 0.2010 loss: 2.0397 2022/08/29 23:58:18 - mmengine - INFO - Epoch(train) [42][60/63] lr: 6.7842e-03 eta: 21:54:21 time: 1.0658 data_time: 0.0545 memory: 16201 loss_prob: 1.2342 loss_thr: 0.5953 loss_db: 0.1948 loss: 2.0244 2022/08/29 23:58:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:58:29 - mmengine - INFO - Epoch(train) [43][5/63] lr: 6.7789e-03 eta: 21:54:21 time: 1.3404 data_time: 0.4040 memory: 16201 loss_prob: 1.2206 loss_thr: 0.5863 loss_db: 0.1995 loss: 2.0065 2022/08/29 23:58:33 - mmengine - INFO - Epoch(train) [43][10/63] lr: 6.7789e-03 eta: 21:53:22 time: 1.2426 data_time: 0.4156 memory: 16201 loss_prob: 1.2517 loss_thr: 0.5830 loss_db: 0.2074 loss: 2.0421 2022/08/29 23:58:38 - mmengine - INFO - Epoch(train) [43][15/63] lr: 6.7789e-03 eta: 21:53:22 time: 0.9001 data_time: 0.0606 memory: 16201 loss_prob: 1.2387 loss_thr: 0.5893 loss_db: 0.2040 loss: 2.0319 2022/08/29 23:58:43 - mmengine - INFO - Epoch(train) [43][20/63] lr: 6.7789e-03 eta: 21:52:25 time: 0.9096 data_time: 0.0376 memory: 16201 loss_prob: 1.2687 loss_thr: 0.6369 loss_db: 0.2130 loss: 2.1185 2022/08/29 23:58:47 - mmengine - INFO - Epoch(train) [43][25/63] lr: 6.7789e-03 eta: 21:52:25 time: 0.9333 data_time: 0.0547 memory: 16201 loss_prob: 1.3004 loss_thr: 0.6411 loss_db: 0.2149 loss: 2.1564 2022/08/29 23:58:52 - mmengine - INFO - Epoch(train) [43][30/63] lr: 6.7789e-03 eta: 21:51:27 time: 0.9096 data_time: 0.0421 memory: 16201 loss_prob: 1.2365 loss_thr: 0.6002 loss_db: 0.2015 loss: 2.0382 2022/08/29 23:58:56 - mmengine - INFO - Epoch(train) [43][35/63] lr: 6.7789e-03 eta: 21:51:27 time: 0.8791 data_time: 0.0335 memory: 16201 loss_prob: 1.2281 loss_thr: 0.6057 loss_db: 0.2031 loss: 2.0369 2022/08/29 23:59:00 - mmengine - INFO - Epoch(train) [43][40/63] lr: 6.7789e-03 eta: 21:50:22 time: 0.8767 data_time: 0.0508 memory: 16201 loss_prob: 1.2226 loss_thr: 0.6244 loss_db: 0.2031 loss: 2.0502 2022/08/29 23:59:05 - mmengine - INFO - Epoch(train) [43][45/63] lr: 6.7789e-03 eta: 21:50:22 time: 0.9316 data_time: 0.0455 memory: 16201 loss_prob: 1.1390 loss_thr: 0.5936 loss_db: 0.1860 loss: 1.9187 2022/08/29 23:59:10 - mmengine - INFO - Epoch(train) [43][50/63] lr: 6.7789e-03 eta: 21:49:31 time: 0.9288 data_time: 0.0474 memory: 16201 loss_prob: 1.0846 loss_thr: 0.5568 loss_db: 0.1748 loss: 1.8162 2022/08/29 23:59:14 - mmengine - INFO - Epoch(train) [43][55/63] lr: 6.7789e-03 eta: 21:49:31 time: 0.8936 data_time: 0.0674 memory: 16201 loss_prob: 1.0695 loss_thr: 0.5591 loss_db: 0.1724 loss: 1.8011 2022/08/29 23:59:19 - mmengine - INFO - Epoch(train) [43][60/63] lr: 6.7789e-03 eta: 21:48:32 time: 0.9014 data_time: 0.0549 memory: 16201 loss_prob: 1.1583 loss_thr: 0.5780 loss_db: 0.1845 loss: 1.9209 2022/08/29 23:59:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/29 23:59:28 - mmengine - INFO - Epoch(train) [44][5/63] lr: 6.7737e-03 eta: 21:48:32 time: 1.1176 data_time: 0.2847 memory: 16201 loss_prob: 1.1674 loss_thr: 0.5735 loss_db: 0.1906 loss: 1.9316 2022/08/29 23:59:32 - mmengine - INFO - Epoch(train) [44][10/63] lr: 6.7737e-03 eta: 21:47:10 time: 1.1437 data_time: 0.3145 memory: 16201 loss_prob: 1.1983 loss_thr: 0.6175 loss_db: 0.1948 loss: 2.0106 2022/08/29 23:59:37 - mmengine - INFO - Epoch(train) [44][15/63] lr: 6.7737e-03 eta: 21:47:10 time: 0.8362 data_time: 0.0514 memory: 16201 loss_prob: 1.1694 loss_thr: 0.6262 loss_db: 0.1911 loss: 1.9867 2022/08/29 23:59:41 - mmengine - INFO - Epoch(train) [44][20/63] lr: 6.7737e-03 eta: 21:45:51 time: 0.8219 data_time: 0.0277 memory: 16201 loss_prob: 1.2344 loss_thr: 0.6507 loss_db: 0.2069 loss: 2.0920 2022/08/29 23:59:45 - mmengine - INFO - Epoch(train) [44][25/63] lr: 6.7737e-03 eta: 21:45:51 time: 0.8722 data_time: 0.0530 memory: 16201 loss_prob: 1.3064 loss_thr: 0.6320 loss_db: 0.2188 loss: 2.1572 2022/08/29 23:59:50 - mmengine - INFO - Epoch(train) [44][30/63] lr: 6.7737e-03 eta: 21:44:55 time: 0.9057 data_time: 0.0532 memory: 16201 loss_prob: 1.3376 loss_thr: 0.5966 loss_db: 0.2186 loss: 2.1528 2022/08/29 23:59:54 - mmengine - INFO - Epoch(train) [44][35/63] lr: 6.7737e-03 eta: 21:44:55 time: 0.8839 data_time: 0.0303 memory: 16201 loss_prob: 1.2534 loss_thr: 0.5672 loss_db: 0.1985 loss: 2.0191 2022/08/29 23:59:59 - mmengine - INFO - Epoch(train) [44][40/63] lr: 6.7737e-03 eta: 21:44:02 time: 0.9156 data_time: 0.0604 memory: 16201 loss_prob: 1.1247 loss_thr: 0.5660 loss_db: 0.1808 loss: 1.8714 2022/08/30 00:00:12 - mmengine - INFO - Epoch(train) [44][45/63] lr: 6.7737e-03 eta: 21:44:02 time: 1.7666 data_time: 0.0903 memory: 16201 loss_prob: 1.1769 loss_thr: 0.5887 loss_db: 0.1927 loss: 1.9582 2022/08/30 00:00:16 - mmengine - INFO - Epoch(train) [44][50/63] lr: 6.7737e-03 eta: 21:46:47 time: 1.7392 data_time: 0.0834 memory: 16201 loss_prob: 1.3639 loss_thr: 0.6444 loss_db: 0.2201 loss: 2.2283 2022/08/30 00:00:21 - mmengine - INFO - Epoch(train) [44][55/63] lr: 6.7737e-03 eta: 21:46:47 time: 0.8852 data_time: 0.0562 memory: 16201 loss_prob: 1.3146 loss_thr: 0.6336 loss_db: 0.2129 loss: 2.1612 2022/08/30 00:00:25 - mmengine - INFO - Epoch(train) [44][60/63] lr: 6.7737e-03 eta: 21:45:46 time: 0.8845 data_time: 0.0415 memory: 16201 loss_prob: 1.2637 loss_thr: 0.5866 loss_db: 0.2040 loss: 2.0543 2022/08/30 00:00:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:00:36 - mmengine - INFO - Epoch(train) [45][5/63] lr: 6.7684e-03 eta: 21:45:46 time: 1.2036 data_time: 0.3831 memory: 16201 loss_prob: 1.3096 loss_thr: 0.5969 loss_db: 0.2104 loss: 2.1169 2022/08/30 00:00:40 - mmengine - INFO - Epoch(train) [45][10/63] lr: 6.7684e-03 eta: 21:44:57 time: 1.2645 data_time: 0.3757 memory: 16201 loss_prob: 1.3402 loss_thr: 0.6198 loss_db: 0.2195 loss: 2.1794 2022/08/30 00:00:45 - mmengine - INFO - Epoch(train) [45][15/63] lr: 6.7684e-03 eta: 21:44:57 time: 0.9204 data_time: 0.0519 memory: 16201 loss_prob: 1.4571 loss_thr: 0.6432 loss_db: 0.2414 loss: 2.3417 2022/08/30 00:00:49 - mmengine - INFO - Epoch(train) [45][20/63] lr: 6.7684e-03 eta: 21:43:57 time: 0.8880 data_time: 0.0344 memory: 16201 loss_prob: 1.3743 loss_thr: 0.6078 loss_db: 0.2214 loss: 2.2035 2022/08/30 00:00:54 - mmengine - INFO - Epoch(train) [45][25/63] lr: 6.7684e-03 eta: 21:43:57 time: 0.9260 data_time: 0.0557 memory: 16201 loss_prob: 1.2253 loss_thr: 0.5946 loss_db: 0.1938 loss: 2.0138 2022/08/30 00:00:58 - mmengine - INFO - Epoch(train) [45][30/63] lr: 6.7684e-03 eta: 21:43:06 time: 0.9198 data_time: 0.0549 memory: 16201 loss_prob: 1.1944 loss_thr: 0.6155 loss_db: 0.1951 loss: 2.0050 2022/08/30 00:01:03 - mmengine - INFO - Epoch(train) [45][35/63] lr: 6.7684e-03 eta: 21:43:06 time: 0.9087 data_time: 0.0383 memory: 16201 loss_prob: 1.2171 loss_thr: 0.6317 loss_db: 0.2026 loss: 2.0514 2022/08/30 00:01:08 - mmengine - INFO - Epoch(train) [45][40/63] lr: 6.7684e-03 eta: 21:42:14 time: 0.9126 data_time: 0.0521 memory: 16201 loss_prob: 1.2286 loss_thr: 0.6345 loss_db: 0.2022 loss: 2.0654 2022/08/30 00:01:12 - mmengine - INFO - Epoch(train) [45][45/63] lr: 6.7684e-03 eta: 21:42:14 time: 0.8865 data_time: 0.0481 memory: 16201 loss_prob: 1.2310 loss_thr: 0.6134 loss_db: 0.2008 loss: 2.0453 2022/08/30 00:01:17 - mmengine - INFO - Epoch(train) [45][50/63] lr: 6.7684e-03 eta: 21:41:21 time: 0.9092 data_time: 0.0407 memory: 16201 loss_prob: 1.1662 loss_thr: 0.5801 loss_db: 0.1873 loss: 1.9336 2022/08/30 00:01:21 - mmengine - INFO - Epoch(train) [45][55/63] lr: 6.7684e-03 eta: 21:41:21 time: 0.9209 data_time: 0.0573 memory: 16201 loss_prob: 1.1890 loss_thr: 0.5844 loss_db: 0.1875 loss: 1.9610 2022/08/30 00:01:26 - mmengine - INFO - Epoch(train) [45][60/63] lr: 6.7684e-03 eta: 21:40:24 time: 0.8944 data_time: 0.0637 memory: 16201 loss_prob: 1.3078 loss_thr: 0.6311 loss_db: 0.2068 loss: 2.1458 2022/08/30 00:01:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:01:36 - mmengine - INFO - Epoch(train) [46][5/63] lr: 6.7631e-03 eta: 21:40:24 time: 1.2094 data_time: 0.3637 memory: 16201 loss_prob: 1.1431 loss_thr: 0.5922 loss_db: 0.1837 loss: 1.9189 2022/08/30 00:01:41 - mmengine - INFO - Epoch(train) [46][10/63] lr: 6.7631e-03 eta: 21:39:53 time: 1.3276 data_time: 0.3783 memory: 16201 loss_prob: 1.0792 loss_thr: 0.5727 loss_db: 0.1804 loss: 1.8324 2022/08/30 00:01:45 - mmengine - INFO - Epoch(train) [46][15/63] lr: 6.7631e-03 eta: 21:39:53 time: 0.9150 data_time: 0.0380 memory: 16201 loss_prob: 1.1145 loss_thr: 0.5781 loss_db: 0.1875 loss: 1.8801 2022/08/30 00:01:50 - mmengine - INFO - Epoch(train) [46][20/63] lr: 6.7631e-03 eta: 21:38:51 time: 0.8721 data_time: 0.0396 memory: 16201 loss_prob: 1.1853 loss_thr: 0.5610 loss_db: 0.1892 loss: 1.9354 2022/08/30 00:01:54 - mmengine - INFO - Epoch(train) [46][25/63] lr: 6.7631e-03 eta: 21:38:51 time: 0.9012 data_time: 0.0614 memory: 16201 loss_prob: 1.2346 loss_thr: 0.5594 loss_db: 0.1914 loss: 1.9854 2022/08/30 00:01:59 - mmengine - INFO - Epoch(train) [46][30/63] lr: 6.7631e-03 eta: 21:37:55 time: 0.8922 data_time: 0.0430 memory: 16201 loss_prob: 1.2219 loss_thr: 0.5762 loss_db: 0.1943 loss: 1.9924 2022/08/30 00:02:04 - mmengine - INFO - Epoch(train) [46][35/63] lr: 6.7631e-03 eta: 21:37:55 time: 0.9562 data_time: 0.0336 memory: 16201 loss_prob: 1.1634 loss_thr: 0.5650 loss_db: 0.1903 loss: 1.9186 2022/08/30 00:02:08 - mmengine - INFO - Epoch(train) [46][40/63] lr: 6.7631e-03 eta: 21:37:17 time: 0.9616 data_time: 0.0497 memory: 16201 loss_prob: 1.1817 loss_thr: 0.5760 loss_db: 0.1947 loss: 1.9524 2022/08/30 00:02:13 - mmengine - INFO - Epoch(train) [46][45/63] lr: 6.7631e-03 eta: 21:37:17 time: 0.8912 data_time: 0.0475 memory: 16201 loss_prob: 1.1808 loss_thr: 0.5848 loss_db: 0.1939 loss: 1.9595 2022/08/30 00:02:17 - mmengine - INFO - Epoch(train) [46][50/63] lr: 6.7631e-03 eta: 21:36:21 time: 0.8925 data_time: 0.0489 memory: 16201 loss_prob: 1.2956 loss_thr: 0.6354 loss_db: 0.2139 loss: 2.1449 2022/08/30 00:02:22 - mmengine - INFO - Epoch(train) [46][55/63] lr: 6.7631e-03 eta: 21:36:21 time: 0.9080 data_time: 0.0519 memory: 16201 loss_prob: 1.3109 loss_thr: 0.6404 loss_db: 0.2183 loss: 2.1697 2022/08/30 00:02:26 - mmengine - INFO - Epoch(train) [46][60/63] lr: 6.7631e-03 eta: 21:35:35 time: 0.9268 data_time: 0.0615 memory: 16201 loss_prob: 1.1821 loss_thr: 0.6080 loss_db: 0.1958 loss: 1.9859 2022/08/30 00:02:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:02:38 - mmengine - INFO - Epoch(train) [47][5/63] lr: 6.7578e-03 eta: 21:35:35 time: 1.3350 data_time: 0.5077 memory: 16201 loss_prob: 1.3541 loss_thr: 0.6435 loss_db: 0.2172 loss: 2.2148 2022/08/30 00:02:43 - mmengine - INFO - Epoch(train) [47][10/63] lr: 6.7578e-03 eta: 21:35:33 time: 1.4395 data_time: 0.5832 memory: 16201 loss_prob: 1.2212 loss_thr: 0.6038 loss_db: 0.1938 loss: 2.0188 2022/08/30 00:02:47 - mmengine - INFO - Epoch(train) [47][15/63] lr: 6.7578e-03 eta: 21:35:33 time: 0.9230 data_time: 0.0993 memory: 16201 loss_prob: 1.1938 loss_thr: 0.5679 loss_db: 0.1922 loss: 1.9539 2022/08/30 00:02:52 - mmengine - INFO - Epoch(train) [47][20/63] lr: 6.7578e-03 eta: 21:34:33 time: 0.8687 data_time: 0.0482 memory: 16201 loss_prob: 1.3274 loss_thr: 0.5784 loss_db: 0.2219 loss: 2.1277 2022/08/30 00:02:56 - mmengine - INFO - Epoch(train) [47][25/63] lr: 6.7578e-03 eta: 21:34:33 time: 0.9045 data_time: 0.1050 memory: 16201 loss_prob: 1.2935 loss_thr: 0.5803 loss_db: 0.2165 loss: 2.0902 2022/08/30 00:03:01 - mmengine - INFO - Epoch(train) [47][30/63] lr: 6.7578e-03 eta: 21:33:48 time: 0.9310 data_time: 0.0984 memory: 16201 loss_prob: 1.1830 loss_thr: 0.5954 loss_db: 0.1928 loss: 1.9712 2022/08/30 00:03:07 - mmengine - INFO - Epoch(train) [47][35/63] lr: 6.7578e-03 eta: 21:33:48 time: 1.0550 data_time: 0.0673 memory: 16201 loss_prob: 1.2305 loss_thr: 0.6286 loss_db: 0.2069 loss: 2.0661 2022/08/30 00:03:13 - mmengine - INFO - Epoch(train) [47][40/63] lr: 6.7578e-03 eta: 21:34:10 time: 1.2010 data_time: 0.1047 memory: 16201 loss_prob: 1.1899 loss_thr: 0.6153 loss_db: 0.2020 loss: 2.0072 2022/08/30 00:03:18 - mmengine - INFO - Epoch(train) [47][45/63] lr: 6.7578e-03 eta: 21:34:10 time: 1.0667 data_time: 0.1028 memory: 16201 loss_prob: 1.2509 loss_thr: 0.6361 loss_db: 0.2041 loss: 2.0911 2022/08/30 00:03:22 - mmengine - INFO - Epoch(train) [47][50/63] lr: 6.7578e-03 eta: 21:33:21 time: 0.9121 data_time: 0.1056 memory: 16201 loss_prob: 1.3486 loss_thr: 0.6390 loss_db: 0.2195 loss: 2.2071 2022/08/30 00:03:27 - mmengine - INFO - Epoch(train) [47][55/63] lr: 6.7578e-03 eta: 21:33:21 time: 0.9001 data_time: 0.0840 memory: 16201 loss_prob: 1.2157 loss_thr: 0.6046 loss_db: 0.2004 loss: 2.0207 2022/08/30 00:03:31 - mmengine - INFO - Epoch(train) [47][60/63] lr: 6.7578e-03 eta: 21:32:25 time: 0.8846 data_time: 0.0545 memory: 16201 loss_prob: 1.2655 loss_thr: 0.6156 loss_db: 0.2076 loss: 2.0888 2022/08/30 00:03:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:03:40 - mmengine - INFO - Epoch(train) [48][5/63] lr: 6.7526e-03 eta: 21:32:25 time: 1.0573 data_time: 0.3077 memory: 16201 loss_prob: 1.3244 loss_thr: 0.6424 loss_db: 0.2161 loss: 2.1829 2022/08/30 00:03:44 - mmengine - INFO - Epoch(train) [48][10/63] lr: 6.7526e-03 eta: 21:30:50 time: 1.0581 data_time: 0.2699 memory: 16201 loss_prob: 1.1929 loss_thr: 0.6209 loss_db: 0.1949 loss: 2.0087 2022/08/30 00:03:49 - mmengine - INFO - Epoch(train) [48][15/63] lr: 6.7526e-03 eta: 21:30:50 time: 0.9126 data_time: 0.0925 memory: 16201 loss_prob: 1.2047 loss_thr: 0.5971 loss_db: 0.1977 loss: 1.9995 2022/08/30 00:03:53 - mmengine - INFO - Epoch(train) [48][20/63] lr: 6.7526e-03 eta: 21:29:58 time: 0.8930 data_time: 0.0943 memory: 16201 loss_prob: 1.2203 loss_thr: 0.6021 loss_db: 0.2010 loss: 2.0234 2022/08/30 00:03:58 - mmengine - INFO - Epoch(train) [48][25/63] lr: 6.7526e-03 eta: 21:29:58 time: 0.8402 data_time: 0.0564 memory: 16201 loss_prob: 1.3498 loss_thr: 0.6205 loss_db: 0.2188 loss: 2.1891 2022/08/30 00:04:02 - mmengine - INFO - Epoch(train) [48][30/63] lr: 6.7526e-03 eta: 21:29:09 time: 0.9108 data_time: 0.0873 memory: 16201 loss_prob: 1.3033 loss_thr: 0.6176 loss_db: 0.2129 loss: 2.1338 2022/08/30 00:04:07 - mmengine - INFO - Epoch(train) [48][35/63] lr: 6.7526e-03 eta: 21:29:09 time: 0.9133 data_time: 0.0892 memory: 16201 loss_prob: 1.1545 loss_thr: 0.5959 loss_db: 0.1901 loss: 1.9405 2022/08/30 00:04:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:04:12 - mmengine - INFO - Epoch(train) [48][40/63] lr: 6.7526e-03 eta: 21:28:28 time: 0.9374 data_time: 0.0508 memory: 16201 loss_prob: 1.1812 loss_thr: 0.5930 loss_db: 0.1918 loss: 1.9660 2022/08/30 00:04:17 - mmengine - INFO - Epoch(train) [48][45/63] lr: 6.7526e-03 eta: 21:28:28 time: 1.0047 data_time: 0.0994 memory: 16201 loss_prob: 1.1984 loss_thr: 0.5900 loss_db: 0.1954 loss: 1.9839 2022/08/30 00:04:21 - mmengine - INFO - Epoch(train) [48][50/63] lr: 6.7526e-03 eta: 21:27:45 time: 0.9324 data_time: 0.1095 memory: 16201 loss_prob: 1.4066 loss_thr: 0.6273 loss_db: 0.2282 loss: 2.2621 2022/08/30 00:04:26 - mmengine - INFO - Epoch(train) [48][55/63] lr: 6.7526e-03 eta: 21:27:45 time: 0.9041 data_time: 0.0721 memory: 16201 loss_prob: 1.3221 loss_thr: 0.6144 loss_db: 0.2152 loss: 2.1517 2022/08/30 00:04:31 - mmengine - INFO - Epoch(train) [48][60/63] lr: 6.7526e-03 eta: 21:27:13 time: 0.9750 data_time: 0.1196 memory: 16201 loss_prob: 1.3756 loss_thr: 0.5955 loss_db: 0.2188 loss: 2.1899 2022/08/30 00:04:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:04:40 - mmengine - INFO - Epoch(train) [49][5/63] lr: 6.7473e-03 eta: 21:27:13 time: 1.0993 data_time: 0.2936 memory: 16201 loss_prob: 1.3676 loss_thr: 0.6130 loss_db: 0.2236 loss: 2.2042 2022/08/30 00:04:45 - mmengine - INFO - Epoch(train) [49][10/63] lr: 6.7473e-03 eta: 21:26:04 time: 1.1549 data_time: 0.3332 memory: 16201 loss_prob: 1.2092 loss_thr: 0.5831 loss_db: 0.2024 loss: 1.9947 2022/08/30 00:04:49 - mmengine - INFO - Epoch(train) [49][15/63] lr: 6.7473e-03 eta: 21:26:04 time: 0.9061 data_time: 0.0944 memory: 16201 loss_prob: 1.1490 loss_thr: 0.5588 loss_db: 0.1868 loss: 1.8946 2022/08/30 00:04:54 - mmengine - INFO - Epoch(train) [49][20/63] lr: 6.7473e-03 eta: 21:25:23 time: 0.9336 data_time: 0.0625 memory: 16201 loss_prob: 1.1480 loss_thr: 0.5970 loss_db: 0.1848 loss: 1.9298 2022/08/30 00:04:59 - mmengine - INFO - Epoch(train) [49][25/63] lr: 6.7473e-03 eta: 21:25:23 time: 0.9690 data_time: 0.0995 memory: 16201 loss_prob: 1.3175 loss_thr: 0.6264 loss_db: 0.2173 loss: 2.1612 2022/08/30 00:05:03 - mmengine - INFO - Epoch(train) [49][30/63] lr: 6.7473e-03 eta: 21:24:31 time: 0.8872 data_time: 0.0920 memory: 16201 loss_prob: 1.3400 loss_thr: 0.6051 loss_db: 0.2177 loss: 2.1628 2022/08/30 00:05:08 - mmengine - INFO - Epoch(train) [49][35/63] lr: 6.7473e-03 eta: 21:24:31 time: 0.8982 data_time: 0.0668 memory: 16201 loss_prob: 1.4991 loss_thr: 0.6185 loss_db: 0.2303 loss: 2.3479 2022/08/30 00:05:13 - mmengine - INFO - Epoch(train) [49][40/63] lr: 6.7473e-03 eta: 21:24:00 time: 0.9786 data_time: 0.1084 memory: 16201 loss_prob: 1.5217 loss_thr: 0.6285 loss_db: 0.2415 loss: 2.3917 2022/08/30 00:05:17 - mmengine - INFO - Epoch(train) [49][45/63] lr: 6.7473e-03 eta: 21:24:00 time: 0.9127 data_time: 0.1071 memory: 16201 loss_prob: 1.2195 loss_thr: 0.5863 loss_db: 0.2020 loss: 2.0078 2022/08/30 00:05:22 - mmengine - INFO - Epoch(train) [49][50/63] lr: 6.7473e-03 eta: 21:23:18 time: 0.9275 data_time: 0.0676 memory: 16201 loss_prob: 1.2456 loss_thr: 0.5723 loss_db: 0.2051 loss: 2.0230 2022/08/30 00:05:27 - mmengine - INFO - Epoch(train) [49][55/63] lr: 6.7473e-03 eta: 21:23:18 time: 0.9817 data_time: 0.0970 memory: 16201 loss_prob: 1.4920 loss_thr: 0.5889 loss_db: 0.2341 loss: 2.3150 2022/08/30 00:05:31 - mmengine - INFO - Epoch(train) [49][60/63] lr: 6.7473e-03 eta: 21:22:27 time: 0.8904 data_time: 0.0915 memory: 16201 loss_prob: 1.6971 loss_thr: 0.6098 loss_db: 0.2813 loss: 2.5882 2022/08/30 00:05:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:05:40 - mmengine - INFO - Epoch(train) [50][5/63] lr: 6.7420e-03 eta: 21:22:27 time: 1.0866 data_time: 0.2881 memory: 16201 loss_prob: 1.8137 loss_thr: 0.6655 loss_db: 0.3108 loss: 2.7900 2022/08/30 00:05:45 - mmengine - INFO - Epoch(train) [50][10/63] lr: 6.7420e-03 eta: 21:21:24 time: 1.1693 data_time: 0.3334 memory: 16201 loss_prob: 1.6508 loss_thr: 0.6663 loss_db: 0.2721 loss: 2.5892 2022/08/30 00:05:49 - mmengine - INFO - Epoch(train) [50][15/63] lr: 6.7420e-03 eta: 21:21:24 time: 0.8962 data_time: 0.0925 memory: 16201 loss_prob: 1.4254 loss_thr: 0.6185 loss_db: 0.2309 loss: 2.2748 2022/08/30 00:05:54 - mmengine - INFO - Epoch(train) [50][20/63] lr: 6.7420e-03 eta: 21:20:50 time: 0.9598 data_time: 0.0520 memory: 16201 loss_prob: 1.5014 loss_thr: 0.6278 loss_db: 0.2452 loss: 2.3743 2022/08/30 00:05:59 - mmengine - INFO - Epoch(train) [50][25/63] lr: 6.7420e-03 eta: 21:20:50 time: 1.0270 data_time: 0.0993 memory: 16201 loss_prob: 1.5088 loss_thr: 0.6367 loss_db: 0.2503 loss: 2.3958 2022/08/30 00:06:04 - mmengine - INFO - Epoch(train) [50][30/63] lr: 6.7420e-03 eta: 21:20:04 time: 0.9107 data_time: 0.0915 memory: 16201 loss_prob: 1.3580 loss_thr: 0.5902 loss_db: 0.2207 loss: 2.1690 2022/08/30 00:06:08 - mmengine - INFO - Epoch(train) [50][35/63] lr: 6.7420e-03 eta: 21:20:04 time: 0.8753 data_time: 0.0518 memory: 16201 loss_prob: 1.3517 loss_thr: 0.6055 loss_db: 0.2183 loss: 2.1756 2022/08/30 00:06:14 - mmengine - INFO - Epoch(train) [50][40/63] lr: 6.7420e-03 eta: 21:19:56 time: 1.0705 data_time: 0.0964 memory: 16201 loss_prob: 1.4770 loss_thr: 0.6432 loss_db: 0.2457 loss: 2.3659 2022/08/30 00:06:18 - mmengine - INFO - Epoch(train) [50][45/63] lr: 6.7420e-03 eta: 21:19:56 time: 1.0414 data_time: 0.0881 memory: 16201 loss_prob: 1.4470 loss_thr: 0.6397 loss_db: 0.2428 loss: 2.3295 2022/08/30 00:06:23 - mmengine - INFO - Epoch(train) [50][50/63] lr: 6.7420e-03 eta: 21:19:04 time: 0.8774 data_time: 0.0538 memory: 16201 loss_prob: 1.4066 loss_thr: 0.6258 loss_db: 0.2329 loss: 2.2653 2022/08/30 00:06:27 - mmengine - INFO - Epoch(train) [50][55/63] lr: 6.7420e-03 eta: 21:19:04 time: 0.8857 data_time: 0.0422 memory: 16201 loss_prob: 1.4891 loss_thr: 0.6268 loss_db: 0.2487 loss: 2.3646 2022/08/30 00:06:33 - mmengine - INFO - Epoch(train) [50][60/63] lr: 6.7420e-03 eta: 21:18:40 time: 1.0004 data_time: 0.0287 memory: 16201 loss_prob: 1.5016 loss_thr: 0.6363 loss_db: 0.2532 loss: 2.3912 2022/08/30 00:06:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:06:43 - mmengine - INFO - Epoch(train) [51][5/63] lr: 6.7367e-03 eta: 21:18:40 time: 1.2412 data_time: 0.3102 memory: 16201 loss_prob: 1.3742 loss_thr: 0.6257 loss_db: 0.2258 loss: 2.2256 2022/08/30 00:06:47 - mmengine - INFO - Epoch(train) [51][10/63] lr: 6.7367e-03 eta: 21:17:32 time: 1.1424 data_time: 0.3138 memory: 16201 loss_prob: 1.3320 loss_thr: 0.6099 loss_db: 0.2159 loss: 2.1578 2022/08/30 00:06:52 - mmengine - INFO - Epoch(train) [51][15/63] lr: 6.7367e-03 eta: 21:17:32 time: 0.9436 data_time: 0.0528 memory: 16201 loss_prob: 1.3446 loss_thr: 0.6226 loss_db: 0.2155 loss: 2.1828 2022/08/30 00:06:57 - mmengine - INFO - Epoch(train) [51][20/63] lr: 6.7367e-03 eta: 21:17:01 time: 0.9692 data_time: 0.0543 memory: 16201 loss_prob: 1.1770 loss_thr: 0.5735 loss_db: 0.1849 loss: 1.9353 2022/08/30 00:07:01 - mmengine - INFO - Epoch(train) [51][25/63] lr: 6.7367e-03 eta: 21:17:01 time: 0.8934 data_time: 0.0436 memory: 16201 loss_prob: 1.2140 loss_thr: 0.5873 loss_db: 0.1940 loss: 1.9953 2022/08/30 00:07:06 - mmengine - INFO - Epoch(train) [51][30/63] lr: 6.7367e-03 eta: 21:16:16 time: 0.9040 data_time: 0.0467 memory: 16201 loss_prob: 1.3331 loss_thr: 0.6093 loss_db: 0.2183 loss: 2.1607 2022/08/30 00:07:10 - mmengine - INFO - Epoch(train) [51][35/63] lr: 6.7367e-03 eta: 21:16:16 time: 0.9237 data_time: 0.0538 memory: 16201 loss_prob: 1.3611 loss_thr: 0.6055 loss_db: 0.2209 loss: 2.1875 2022/08/30 00:07:14 - mmengine - INFO - Epoch(train) [51][40/63] lr: 6.7367e-03 eta: 21:15:24 time: 0.8750 data_time: 0.0405 memory: 16201 loss_prob: 1.3766 loss_thr: 0.6493 loss_db: 0.2186 loss: 2.2445 2022/08/30 00:07:19 - mmengine - INFO - Epoch(train) [51][45/63] lr: 6.7367e-03 eta: 21:15:24 time: 0.8823 data_time: 0.0443 memory: 16201 loss_prob: 1.2926 loss_thr: 0.6399 loss_db: 0.2061 loss: 2.1385 2022/08/30 00:07:25 - mmengine - INFO - Epoch(train) [51][50/63] lr: 6.7367e-03 eta: 21:15:11 time: 1.0475 data_time: 0.0603 memory: 16201 loss_prob: 1.2811 loss_thr: 0.6331 loss_db: 0.2106 loss: 2.1248 2022/08/30 00:07:29 - mmengine - INFO - Epoch(train) [51][55/63] lr: 6.7367e-03 eta: 21:15:11 time: 1.0332 data_time: 0.0621 memory: 16201 loss_prob: 1.2946 loss_thr: 0.6493 loss_db: 0.2146 loss: 2.1585 2022/08/30 00:07:33 - mmengine - INFO - Epoch(train) [51][60/63] lr: 6.7367e-03 eta: 21:14:18 time: 0.8674 data_time: 0.0489 memory: 16201 loss_prob: 1.2594 loss_thr: 0.6263 loss_db: 0.2061 loss: 2.0918 2022/08/30 00:07:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:07:44 - mmengine - INFO - Epoch(train) [52][5/63] lr: 6.7315e-03 eta: 21:14:18 time: 1.1739 data_time: 0.3723 memory: 16201 loss_prob: 1.0860 loss_thr: 0.5750 loss_db: 0.1753 loss: 1.8363 2022/08/30 00:07:49 - mmengine - INFO - Epoch(train) [52][10/63] lr: 6.7315e-03 eta: 21:13:59 time: 1.3533 data_time: 0.3918 memory: 16201 loss_prob: 1.1777 loss_thr: 0.5890 loss_db: 0.1921 loss: 1.9588 2022/08/30 00:07:55 - mmengine - INFO - Epoch(train) [52][15/63] lr: 6.7315e-03 eta: 21:13:59 time: 1.1507 data_time: 0.0559 memory: 16201 loss_prob: 1.2010 loss_thr: 0.5835 loss_db: 0.1900 loss: 1.9744 2022/08/30 00:08:01 - mmengine - INFO - Epoch(train) [52][20/63] lr: 6.7315e-03 eta: 21:14:03 time: 1.1207 data_time: 0.0609 memory: 16201 loss_prob: 1.2534 loss_thr: 0.6104 loss_db: 0.1997 loss: 2.0635 2022/08/30 00:08:05 - mmengine - INFO - Epoch(train) [52][25/63] lr: 6.7315e-03 eta: 21:14:03 time: 0.9678 data_time: 0.0565 memory: 16201 loss_prob: 1.4206 loss_thr: 0.6134 loss_db: 0.2295 loss: 2.2635 2022/08/30 00:08:09 - mmengine - INFO - Epoch(train) [52][30/63] lr: 6.7315e-03 eta: 21:12:57 time: 0.8075 data_time: 0.0366 memory: 16201 loss_prob: 1.3840 loss_thr: 0.6171 loss_db: 0.2232 loss: 2.2243 2022/08/30 00:08:13 - mmengine - INFO - Epoch(train) [52][35/63] lr: 6.7315e-03 eta: 21:12:57 time: 0.7986 data_time: 0.0443 memory: 16201 loss_prob: 1.2678 loss_thr: 0.6285 loss_db: 0.2030 loss: 2.0993 2022/08/30 00:08:17 - mmengine - INFO - Epoch(train) [52][40/63] lr: 6.7315e-03 eta: 21:12:03 time: 0.8594 data_time: 0.0529 memory: 16201 loss_prob: 1.3091 loss_thr: 0.6156 loss_db: 0.2084 loss: 2.1331 2022/08/30 00:08:22 - mmengine - INFO - Epoch(train) [52][45/63] lr: 6.7315e-03 eta: 21:12:03 time: 0.8989 data_time: 0.0533 memory: 16201 loss_prob: 1.2736 loss_thr: 0.6221 loss_db: 0.2079 loss: 2.1037 2022/08/30 00:08:27 - mmengine - INFO - Epoch(train) [52][50/63] lr: 6.7315e-03 eta: 21:11:41 time: 1.0016 data_time: 0.0567 memory: 16201 loss_prob: 1.2258 loss_thr: 0.6260 loss_db: 0.2021 loss: 2.0539 2022/08/30 00:08:32 - mmengine - INFO - Epoch(train) [52][55/63] lr: 6.7315e-03 eta: 21:11:41 time: 0.9896 data_time: 0.0492 memory: 16201 loss_prob: 1.3187 loss_thr: 0.6227 loss_db: 0.2178 loss: 2.1591 2022/08/30 00:08:36 - mmengine - INFO - Epoch(train) [52][60/63] lr: 6.7315e-03 eta: 21:10:51 time: 0.8793 data_time: 0.0418 memory: 16201 loss_prob: 1.3023 loss_thr: 0.6025 loss_db: 0.2164 loss: 2.1212 2022/08/30 00:08:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:08:46 - mmengine - INFO - Epoch(train) [53][5/63] lr: 6.7262e-03 eta: 21:10:51 time: 1.2088 data_time: 0.3529 memory: 16201 loss_prob: 1.1923 loss_thr: 0.6230 loss_db: 0.1954 loss: 2.0107 2022/08/30 00:08:55 - mmengine - INFO - Epoch(train) [53][10/63] lr: 6.7262e-03 eta: 21:11:32 time: 1.6186 data_time: 0.3699 memory: 16201 loss_prob: 1.1699 loss_thr: 0.5913 loss_db: 0.1861 loss: 1.9473 2022/08/30 00:09:01 - mmengine - INFO - Epoch(train) [53][15/63] lr: 6.7262e-03 eta: 21:11:32 time: 1.4767 data_time: 0.0672 memory: 16201 loss_prob: 1.3785 loss_thr: 0.5742 loss_db: 0.2068 loss: 2.1594 2022/08/30 00:09:09 - mmengine - INFO - Epoch(train) [53][20/63] lr: 6.7262e-03 eta: 21:12:32 time: 1.3738 data_time: 0.0615 memory: 16201 loss_prob: 1.3440 loss_thr: 0.5940 loss_db: 0.2033 loss: 2.1412 2022/08/30 00:09:16 - mmengine - INFO - Epoch(train) [53][25/63] lr: 6.7262e-03 eta: 21:12:32 time: 1.5061 data_time: 0.0762 memory: 16201 loss_prob: 1.1557 loss_thr: 0.5714 loss_db: 0.1858 loss: 1.9130 2022/08/30 00:09:24 - mmengine - INFO - Epoch(train) [53][30/63] lr: 6.7262e-03 eta: 21:14:02 time: 1.5168 data_time: 0.0624 memory: 16201 loss_prob: 1.1834 loss_thr: 0.5942 loss_db: 0.1941 loss: 1.9717 2022/08/30 00:09:31 - mmengine - INFO - Epoch(train) [53][35/63] lr: 6.7262e-03 eta: 21:14:02 time: 1.4881 data_time: 0.0591 memory: 16201 loss_prob: 1.2910 loss_thr: 0.6521 loss_db: 0.2148 loss: 2.1579 2022/08/30 00:09:38 - mmengine - INFO - Epoch(train) [53][40/63] lr: 6.7262e-03 eta: 21:15:08 time: 1.4108 data_time: 0.0753 memory: 16201 loss_prob: 1.3314 loss_thr: 0.6505 loss_db: 0.2237 loss: 2.2056 2022/08/30 00:09:45 - mmengine - INFO - Epoch(train) [53][45/63] lr: 6.7262e-03 eta: 21:15:08 time: 1.3804 data_time: 0.0703 memory: 16201 loss_prob: 1.2608 loss_thr: 0.6474 loss_db: 0.2109 loss: 2.1190 2022/08/30 00:09:53 - mmengine - INFO - Epoch(train) [53][50/63] lr: 6.7262e-03 eta: 21:16:35 time: 1.5054 data_time: 0.0724 memory: 16201 loss_prob: 1.1756 loss_thr: 0.6308 loss_db: 0.1947 loss: 2.0010 2022/08/30 00:10:00 - mmengine - INFO - Epoch(train) [53][55/63] lr: 6.7262e-03 eta: 21:16:35 time: 1.5356 data_time: 0.0589 memory: 16201 loss_prob: 1.1533 loss_thr: 0.5673 loss_db: 0.1908 loss: 1.9114 2022/08/30 00:10:07 - mmengine - INFO - Epoch(train) [53][60/63] lr: 6.7262e-03 eta: 21:17:50 time: 1.4568 data_time: 0.0552 memory: 16201 loss_prob: 1.3169 loss_thr: 0.5994 loss_db: 0.2130 loss: 2.1293 2022/08/30 00:10:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:10:22 - mmengine - INFO - Epoch(train) [54][5/63] lr: 6.7209e-03 eta: 21:17:50 time: 1.7242 data_time: 0.3954 memory: 16201 loss_prob: 1.2254 loss_thr: 0.6141 loss_db: 0.1986 loss: 2.0381 2022/08/30 00:10:30 - mmengine - INFO - Epoch(train) [54][10/63] lr: 6.7209e-03 eta: 21:19:21 time: 1.8632 data_time: 0.4479 memory: 16201 loss_prob: 1.1535 loss_thr: 0.5968 loss_db: 0.1882 loss: 1.9384 2022/08/30 00:10:38 - mmengine - INFO - Epoch(train) [54][15/63] lr: 6.7209e-03 eta: 21:19:21 time: 1.5175 data_time: 0.0748 memory: 16201 loss_prob: 1.1751 loss_thr: 0.5786 loss_db: 0.1890 loss: 1.9427 2022/08/30 00:10:44 - mmengine - INFO - Epoch(train) [54][20/63] lr: 6.7209e-03 eta: 21:20:42 time: 1.4906 data_time: 0.0582 memory: 16201 loss_prob: 1.1326 loss_thr: 0.5849 loss_db: 0.1844 loss: 1.9019 2022/08/30 00:10:53 - mmengine - INFO - Epoch(train) [54][25/63] lr: 6.7209e-03 eta: 21:20:42 time: 1.5321 data_time: 0.0775 memory: 16201 loss_prob: 1.1692 loss_thr: 0.6274 loss_db: 0.1919 loss: 1.9885 2022/08/30 00:11:00 - mmengine - INFO - Epoch(train) [54][30/63] lr: 6.7209e-03 eta: 21:22:20 time: 1.5697 data_time: 0.0610 memory: 16201 loss_prob: 1.2687 loss_thr: 0.6369 loss_db: 0.2087 loss: 2.1143 2022/08/30 00:11:08 - mmengine - INFO - Epoch(train) [54][35/63] lr: 6.7209e-03 eta: 21:22:20 time: 1.5355 data_time: 0.0568 memory: 16201 loss_prob: 1.2380 loss_thr: 0.6157 loss_db: 0.2043 loss: 2.0579 2022/08/30 00:11:16 - mmengine - INFO - Epoch(train) [54][40/63] lr: 6.7209e-03 eta: 21:23:50 time: 1.5349 data_time: 0.0613 memory: 16201 loss_prob: 1.1263 loss_thr: 0.5946 loss_db: 0.1814 loss: 1.9024 2022/08/30 00:11:22 - mmengine - INFO - Epoch(train) [54][45/63] lr: 6.7209e-03 eta: 21:23:50 time: 1.3995 data_time: 0.0591 memory: 16201 loss_prob: 1.1416 loss_thr: 0.5977 loss_db: 0.1850 loss: 1.9243 2022/08/30 00:11:29 - mmengine - INFO - Epoch(train) [54][50/63] lr: 6.7209e-03 eta: 21:24:38 time: 1.3430 data_time: 0.0669 memory: 16201 loss_prob: 1.1227 loss_thr: 0.5918 loss_db: 0.1837 loss: 1.8982 2022/08/30 00:11:36 - mmengine - INFO - Epoch(train) [54][55/63] lr: 6.7209e-03 eta: 21:24:38 time: 1.3708 data_time: 0.0516 memory: 16201 loss_prob: 1.1500 loss_thr: 0.5858 loss_db: 0.1822 loss: 1.9179 2022/08/30 00:11:43 - mmengine - INFO - Epoch(train) [54][60/63] lr: 6.7209e-03 eta: 21:25:29 time: 1.3585 data_time: 0.0523 memory: 16201 loss_prob: 1.2927 loss_thr: 0.5813 loss_db: 0.2104 loss: 2.0844 2022/08/30 00:11:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:11:57 - mmengine - INFO - Epoch(train) [55][5/63] lr: 6.7156e-03 eta: 21:25:29 time: 1.6776 data_time: 0.3559 memory: 16201 loss_prob: 1.2838 loss_thr: 0.5934 loss_db: 0.2103 loss: 2.0876 2022/08/30 00:12:05 - mmengine - INFO - Epoch(train) [55][10/63] lr: 6.7156e-03 eta: 21:27:03 time: 1.8979 data_time: 0.4323 memory: 16201 loss_prob: 1.2130 loss_thr: 0.5987 loss_db: 0.2012 loss: 2.0129 2022/08/30 00:12:12 - mmengine - INFO - Epoch(train) [55][15/63] lr: 6.7156e-03 eta: 21:27:03 time: 1.5705 data_time: 0.1040 memory: 16201 loss_prob: 1.3762 loss_thr: 0.6128 loss_db: 0.2287 loss: 2.2177 2022/08/30 00:12:19 - mmengine - INFO - Epoch(train) [55][20/63] lr: 6.7156e-03 eta: 21:28:07 time: 1.4229 data_time: 0.0632 memory: 16201 loss_prob: 1.5021 loss_thr: 0.6252 loss_db: 0.2425 loss: 2.3698 2022/08/30 00:12:26 - mmengine - INFO - Epoch(train) [55][25/63] lr: 6.7156e-03 eta: 21:28:07 time: 1.3398 data_time: 0.0736 memory: 16201 loss_prob: 1.4277 loss_thr: 0.6357 loss_db: 0.2288 loss: 2.2922 2022/08/30 00:12:32 - mmengine - INFO - Epoch(train) [55][30/63] lr: 6.7156e-03 eta: 21:28:37 time: 1.2656 data_time: 0.0570 memory: 16201 loss_prob: 1.3170 loss_thr: 0.6398 loss_db: 0.2164 loss: 2.1731 2022/08/30 00:12:37 - mmengine - INFO - Epoch(train) [55][35/63] lr: 6.7156e-03 eta: 21:28:37 time: 1.1730 data_time: 0.0579 memory: 16201 loss_prob: 1.2252 loss_thr: 0.6044 loss_db: 0.2075 loss: 2.0371 2022/08/30 00:12:43 - mmengine - INFO - Epoch(train) [55][40/63] lr: 6.7156e-03 eta: 21:28:34 time: 1.1048 data_time: 0.0540 memory: 16201 loss_prob: 1.1326 loss_thr: 0.5815 loss_db: 0.1891 loss: 1.9032 2022/08/30 00:12:48 - mmengine - INFO - Epoch(train) [55][45/63] lr: 6.7156e-03 eta: 21:28:34 time: 1.0386 data_time: 0.0481 memory: 16201 loss_prob: 1.1828 loss_thr: 0.6271 loss_db: 0.1874 loss: 1.9974 2022/08/30 00:12:54 - mmengine - INFO - Epoch(train) [55][50/63] lr: 6.7156e-03 eta: 21:28:23 time: 1.0702 data_time: 0.0622 memory: 16201 loss_prob: 1.3911 loss_thr: 0.6404 loss_db: 0.2170 loss: 2.2485 2022/08/30 00:12:59 - mmengine - INFO - Epoch(train) [55][55/63] lr: 6.7156e-03 eta: 21:28:23 time: 1.1510 data_time: 0.0555 memory: 16201 loss_prob: 1.4065 loss_thr: 0.6101 loss_db: 0.2231 loss: 2.2397 2022/08/30 00:13:05 - mmengine - INFO - Epoch(train) [55][60/63] lr: 6.7156e-03 eta: 21:28:26 time: 1.1386 data_time: 0.0635 memory: 16201 loss_prob: 1.2033 loss_thr: 0.6044 loss_db: 0.1947 loss: 2.0023 2022/08/30 00:13:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:13:17 - mmengine - INFO - Epoch(train) [56][5/63] lr: 6.7103e-03 eta: 21:28:26 time: 1.4267 data_time: 0.3681 memory: 16201 loss_prob: 1.2475 loss_thr: 0.5996 loss_db: 0.1996 loss: 2.0467 2022/08/30 00:13:23 - mmengine - INFO - Epoch(train) [56][10/63] lr: 6.7103e-03 eta: 21:28:38 time: 1.5190 data_time: 0.3905 memory: 16201 loss_prob: 1.2362 loss_thr: 0.5899 loss_db: 0.1988 loss: 2.0249 2022/08/30 00:13:28 - mmengine - INFO - Epoch(train) [56][15/63] lr: 6.7103e-03 eta: 21:28:38 time: 1.1215 data_time: 0.0567 memory: 16201 loss_prob: 1.1759 loss_thr: 0.6102 loss_db: 0.1915 loss: 1.9776 2022/08/30 00:13:35 - mmengine - INFO - Epoch(train) [56][20/63] lr: 6.7103e-03 eta: 21:28:50 time: 1.1810 data_time: 0.0605 memory: 16201 loss_prob: 1.1274 loss_thr: 0.5863 loss_db: 0.1844 loss: 1.8981 2022/08/30 00:13:41 - mmengine - INFO - Epoch(train) [56][25/63] lr: 6.7103e-03 eta: 21:28:50 time: 1.2419 data_time: 0.0724 memory: 16201 loss_prob: 1.2718 loss_thr: 0.6118 loss_db: 0.2156 loss: 2.0993 2022/08/30 00:13:46 - mmengine - INFO - Epoch(train) [56][30/63] lr: 6.7103e-03 eta: 21:28:56 time: 1.1545 data_time: 0.0565 memory: 16201 loss_prob: 1.5010 loss_thr: 0.6733 loss_db: 0.2514 loss: 2.4258 2022/08/30 00:13:52 - mmengine - INFO - Epoch(train) [56][35/63] lr: 6.7103e-03 eta: 21:28:56 time: 1.1522 data_time: 0.0603 memory: 16201 loss_prob: 1.4173 loss_thr: 0.6364 loss_db: 0.2267 loss: 2.2804 2022/08/30 00:14:01 - mmengine - INFO - Epoch(train) [56][40/63] lr: 6.7103e-03 eta: 21:30:11 time: 1.4901 data_time: 0.0551 memory: 16201 loss_prob: 1.2683 loss_thr: 0.5984 loss_db: 0.2113 loss: 2.0780 2022/08/30 00:14:12 - mmengine - INFO - Epoch(train) [56][45/63] lr: 6.7103e-03 eta: 21:30:11 time: 1.9832 data_time: 0.0507 memory: 16201 loss_prob: 1.3026 loss_thr: 0.6157 loss_db: 0.2208 loss: 2.1391 2022/08/30 00:14:26 - mmengine - INFO - Epoch(train) [56][50/63] lr: 6.7103e-03 eta: 21:34:35 time: 2.4117 data_time: 0.0739 memory: 16201 loss_prob: 1.2307 loss_thr: 0.6001 loss_db: 0.2018 loss: 2.0326 2022/08/30 00:14:37 - mmengine - INFO - Epoch(train) [56][55/63] lr: 6.7103e-03 eta: 21:34:35 time: 2.5281 data_time: 0.0999 memory: 16201 loss_prob: 1.1932 loss_thr: 0.6004 loss_db: 0.1952 loss: 1.9887 2022/08/30 00:14:50 - mmengine - INFO - Epoch(train) [56][60/63] lr: 6.7103e-03 eta: 21:39:09 time: 2.4700 data_time: 0.0901 memory: 16201 loss_prob: 1.2329 loss_thr: 0.6004 loss_db: 0.2077 loss: 2.0410 2022/08/30 00:14:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:15:12 - mmengine - INFO - Epoch(train) [57][5/63] lr: 6.7051e-03 eta: 21:39:09 time: 2.6568 data_time: 0.5786 memory: 16201 loss_prob: 1.3100 loss_thr: 0.5972 loss_db: 0.2067 loss: 2.1140 2022/08/30 00:15:24 - mmengine - INFO - Epoch(train) [57][10/63] lr: 6.7051e-03 eta: 21:44:12 time: 2.9658 data_time: 0.5835 memory: 16201 loss_prob: 1.3369 loss_thr: 0.5971 loss_db: 0.2165 loss: 2.1505 2022/08/30 00:15:34 - mmengine - INFO - Epoch(train) [57][15/63] lr: 6.7051e-03 eta: 21:44:12 time: 2.1432 data_time: 0.0986 memory: 16201 loss_prob: 1.6099 loss_thr: 0.6322 loss_db: 0.2768 loss: 2.5189 2022/08/30 00:15:43 - mmengine - INFO - Epoch(train) [57][20/63] lr: 6.7051e-03 eta: 21:46:50 time: 1.9139 data_time: 0.0823 memory: 16201 loss_prob: 1.7767 loss_thr: 0.6486 loss_db: 0.3041 loss: 2.7294 2022/08/30 00:15:55 - mmengine - INFO - Epoch(train) [57][25/63] lr: 6.7051e-03 eta: 21:46:50 time: 2.1595 data_time: 0.0626 memory: 16201 loss_prob: 1.5296 loss_thr: 0.6262 loss_db: 0.2494 loss: 2.4052 2022/08/30 00:16:07 - mmengine - INFO - Epoch(train) [57][30/63] lr: 6.7051e-03 eta: 21:51:10 time: 2.4294 data_time: 0.0693 memory: 16201 loss_prob: 1.5776 loss_thr: 0.6560 loss_db: 0.2560 loss: 2.4895 2022/08/30 00:16:18 - mmengine - INFO - Epoch(train) [57][35/63] lr: 6.7051e-03 eta: 21:51:10 time: 2.2698 data_time: 0.0978 memory: 16201 loss_prob: 1.5927 loss_thr: 0.6670 loss_db: 0.2654 loss: 2.5251 2022/08/30 00:16:29 - mmengine - INFO - Epoch(train) [57][40/63] lr: 6.7051e-03 eta: 21:54:44 time: 2.2065 data_time: 0.0966 memory: 16201 loss_prob: 1.5316 loss_thr: 0.6874 loss_db: 0.2541 loss: 2.4731 2022/08/30 00:16:40 - mmengine - INFO - Epoch(train) [57][45/63] lr: 6.7051e-03 eta: 21:54:44 time: 2.1469 data_time: 0.0950 memory: 16201 loss_prob: 1.5740 loss_thr: 0.7124 loss_db: 0.2572 loss: 2.5437 2022/08/30 00:16:49 - mmengine - INFO - Epoch(train) [57][50/63] lr: 6.7051e-03 eta: 21:57:31 time: 1.9759 data_time: 0.0962 memory: 16201 loss_prob: 1.4045 loss_thr: 0.6618 loss_db: 0.2323 loss: 2.2985 2022/08/30 00:16:59 - mmengine - INFO - Epoch(train) [57][55/63] lr: 6.7051e-03 eta: 21:57:31 time: 1.9513 data_time: 0.0697 memory: 16201 loss_prob: 1.3400 loss_thr: 0.6193 loss_db: 0.2161 loss: 2.1754 2022/08/30 00:17:09 - mmengine - INFO - Epoch(train) [57][60/63] lr: 6.7051e-03 eta: 22:00:17 time: 1.9782 data_time: 0.0680 memory: 16201 loss_prob: 1.4091 loss_thr: 0.6203 loss_db: 0.2256 loss: 2.2550 2022/08/30 00:17:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:17:24 - mmengine - INFO - Epoch(train) [58][5/63] lr: 6.6998e-03 eta: 22:00:17 time: 1.8222 data_time: 0.3397 memory: 16201 loss_prob: 1.2897 loss_thr: 0.6135 loss_db: 0.2115 loss: 2.1146 2022/08/30 00:17:31 - mmengine - INFO - Epoch(train) [58][10/63] lr: 6.6998e-03 eta: 22:00:47 time: 1.6549 data_time: 0.3666 memory: 16201 loss_prob: 1.2023 loss_thr: 0.5917 loss_db: 0.1962 loss: 1.9902 2022/08/30 00:17:38 - mmengine - INFO - Epoch(train) [58][15/63] lr: 6.6998e-03 eta: 22:00:47 time: 1.4211 data_time: 0.0659 memory: 16201 loss_prob: 1.0993 loss_thr: 0.6000 loss_db: 0.1773 loss: 1.8766 2022/08/30 00:17:44 - mmengine - INFO - Epoch(train) [58][20/63] lr: 6.6998e-03 eta: 22:01:15 time: 1.2941 data_time: 0.0612 memory: 16201 loss_prob: 1.1322 loss_thr: 0.6091 loss_db: 0.1844 loss: 1.9257 2022/08/30 00:17:49 - mmengine - INFO - Epoch(train) [58][25/63] lr: 6.6998e-03 eta: 22:01:15 time: 1.1135 data_time: 0.0640 memory: 16201 loss_prob: 1.2380 loss_thr: 0.6303 loss_db: 0.2017 loss: 2.0700 2022/08/30 00:17:55 - mmengine - INFO - Epoch(train) [58][30/63] lr: 6.6998e-03 eta: 22:01:03 time: 1.0991 data_time: 0.0643 memory: 16201 loss_prob: 1.3835 loss_thr: 0.6541 loss_db: 0.2245 loss: 2.2620 2022/08/30 00:18:00 - mmengine - INFO - Epoch(train) [58][35/63] lr: 6.6998e-03 eta: 22:01:03 time: 1.1318 data_time: 0.0677 memory: 16201 loss_prob: 1.2810 loss_thr: 0.6118 loss_db: 0.2093 loss: 2.1022 2022/08/30 00:18:06 - mmengine - INFO - Epoch(train) [58][40/63] lr: 6.6998e-03 eta: 22:01:00 time: 1.1396 data_time: 0.0539 memory: 16201 loss_prob: 1.1676 loss_thr: 0.5794 loss_db: 0.1890 loss: 1.9360 2022/08/30 00:18:11 - mmengine - INFO - Epoch(train) [58][45/63] lr: 6.6998e-03 eta: 22:01:00 time: 1.1225 data_time: 0.0561 memory: 16201 loss_prob: 1.2194 loss_thr: 0.5883 loss_db: 0.1977 loss: 2.0054 2022/08/30 00:18:18 - mmengine - INFO - Epoch(train) [58][50/63] lr: 6.6998e-03 eta: 22:00:59 time: 1.1525 data_time: 0.0624 memory: 16201 loss_prob: 1.2276 loss_thr: 0.5896 loss_db: 0.2004 loss: 2.0176 2022/08/30 00:18:24 - mmengine - INFO - Epoch(train) [58][55/63] lr: 6.6998e-03 eta: 22:00:59 time: 1.2134 data_time: 0.0550 memory: 16201 loss_prob: 1.3532 loss_thr: 0.6026 loss_db: 0.2193 loss: 2.1751 2022/08/30 00:18:29 - mmengine - INFO - Epoch(train) [58][60/63] lr: 6.6998e-03 eta: 22:00:55 time: 1.1349 data_time: 0.0587 memory: 16201 loss_prob: 1.3591 loss_thr: 0.6143 loss_db: 0.2192 loss: 2.1925 2022/08/30 00:18:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:18:41 - mmengine - INFO - Epoch(train) [59][5/63] lr: 6.6945e-03 eta: 22:00:55 time: 1.4126 data_time: 0.4022 memory: 16201 loss_prob: 1.4979 loss_thr: 0.6068 loss_db: 0.2400 loss: 2.3446 2022/08/30 00:18:47 - mmengine - INFO - Epoch(train) [59][10/63] lr: 6.6945e-03 eta: 22:00:53 time: 1.4964 data_time: 0.4422 memory: 16201 loss_prob: 1.4444 loss_thr: 0.6177 loss_db: 0.2299 loss: 2.2920 2022/08/30 00:18:52 - mmengine - INFO - Epoch(train) [59][15/63] lr: 6.6945e-03 eta: 22:00:53 time: 1.1197 data_time: 0.0650 memory: 16201 loss_prob: 1.1436 loss_thr: 0.5806 loss_db: 0.1859 loss: 1.9101 2022/08/30 00:18:58 - mmengine - INFO - Epoch(train) [59][20/63] lr: 6.6945e-03 eta: 22:00:48 time: 1.1314 data_time: 0.0554 memory: 16201 loss_prob: 1.1570 loss_thr: 0.5613 loss_db: 0.1879 loss: 1.9062 2022/08/30 00:19:03 - mmengine - INFO - Epoch(train) [59][25/63] lr: 6.6945e-03 eta: 22:00:48 time: 1.1228 data_time: 0.0724 memory: 16201 loss_prob: 1.3566 loss_thr: 0.6048 loss_db: 0.2151 loss: 2.1765 2022/08/30 00:19:09 - mmengine - INFO - Epoch(train) [59][30/63] lr: 6.6945e-03 eta: 22:00:41 time: 1.1247 data_time: 0.0519 memory: 16201 loss_prob: 1.3715 loss_thr: 0.6144 loss_db: 0.2244 loss: 2.2102 2022/08/30 00:19:14 - mmengine - INFO - Epoch(train) [59][35/63] lr: 6.6945e-03 eta: 22:00:41 time: 1.1022 data_time: 0.0533 memory: 16201 loss_prob: 1.1772 loss_thr: 0.5841 loss_db: 0.1965 loss: 1.9578 2022/08/30 00:19:20 - mmengine - INFO - Epoch(train) [59][40/63] lr: 6.6945e-03 eta: 22:00:28 time: 1.0933 data_time: 0.0568 memory: 16201 loss_prob: 1.2018 loss_thr: 0.6051 loss_db: 0.1955 loss: 2.0024 2022/08/30 00:19:26 - mmengine - INFO - Epoch(train) [59][45/63] lr: 6.6945e-03 eta: 22:00:28 time: 1.1502 data_time: 0.0486 memory: 16201 loss_prob: 1.2236 loss_thr: 0.5648 loss_db: 0.2048 loss: 1.9932 2022/08/30 00:19:32 - mmengine - INFO - Epoch(train) [59][50/63] lr: 6.6945e-03 eta: 22:00:37 time: 1.2021 data_time: 0.0645 memory: 16201 loss_prob: 1.2635 loss_thr: 0.5785 loss_db: 0.2160 loss: 2.0580 2022/08/30 00:19:38 - mmengine - INFO - Epoch(train) [59][55/63] lr: 6.6945e-03 eta: 22:00:37 time: 1.1583 data_time: 0.0622 memory: 16201 loss_prob: 1.2606 loss_thr: 0.6291 loss_db: 0.2029 loss: 2.0926 2022/08/30 00:19:43 - mmengine - INFO - Epoch(train) [59][60/63] lr: 6.6945e-03 eta: 22:00:22 time: 1.0809 data_time: 0.0581 memory: 16201 loss_prob: 1.1741 loss_thr: 0.6024 loss_db: 0.1870 loss: 1.9635 2022/08/30 00:19:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:19:54 - mmengine - INFO - Epoch(train) [60][5/63] lr: 6.6892e-03 eta: 22:00:22 time: 1.3385 data_time: 0.2976 memory: 16201 loss_prob: 1.4014 loss_thr: 0.5989 loss_db: 0.2208 loss: 2.2212 2022/08/30 00:20:00 - mmengine - INFO - Epoch(train) [60][10/63] lr: 6.6892e-03 eta: 21:59:56 time: 1.3714 data_time: 0.3197 memory: 16201 loss_prob: 1.1408 loss_thr: 0.5881 loss_db: 0.1848 loss: 1.9136 2022/08/30 00:20:06 - mmengine - INFO - Epoch(train) [60][15/63] lr: 6.6892e-03 eta: 21:59:56 time: 1.1659 data_time: 0.0599 memory: 16201 loss_prob: 1.0609 loss_thr: 0.5572 loss_db: 0.1717 loss: 1.7897 2022/08/30 00:20:11 - mmengine - INFO - Epoch(train) [60][20/63] lr: 6.6892e-03 eta: 21:59:56 time: 1.1629 data_time: 0.0648 memory: 16201 loss_prob: 1.2021 loss_thr: 0.5631 loss_db: 0.1898 loss: 1.9551 2022/08/30 00:20:17 - mmengine - INFO - Epoch(train) [60][25/63] lr: 6.6892e-03 eta: 21:59:56 time: 1.0936 data_time: 0.0581 memory: 16201 loss_prob: 1.2615 loss_thr: 0.5872 loss_db: 0.2017 loss: 2.0505 2022/08/30 00:20:23 - mmengine - INFO - Epoch(train) [60][30/63] lr: 6.6892e-03 eta: 21:59:57 time: 1.1603 data_time: 0.0597 memory: 16201 loss_prob: 1.1504 loss_thr: 0.5888 loss_db: 0.1836 loss: 1.9228 2022/08/30 00:20:29 - mmengine - INFO - Epoch(train) [60][35/63] lr: 6.6892e-03 eta: 21:59:57 time: 1.2170 data_time: 0.0733 memory: 16201 loss_prob: 1.1759 loss_thr: 0.6122 loss_db: 0.1888 loss: 1.9769 2022/08/30 00:20:34 - mmengine - INFO - Epoch(train) [60][40/63] lr: 6.6892e-03 eta: 21:59:50 time: 1.1272 data_time: 0.0582 memory: 16201 loss_prob: 1.1351 loss_thr: 0.6002 loss_db: 0.1902 loss: 1.9255 2022/08/30 00:20:40 - mmengine - INFO - Epoch(train) [60][45/63] lr: 6.6892e-03 eta: 21:59:50 time: 1.1376 data_time: 0.0498 memory: 16201 loss_prob: 1.1329 loss_thr: 0.5816 loss_db: 0.1854 loss: 1.8999 2022/08/30 00:20:46 - mmengine - INFO - Epoch(train) [60][50/63] lr: 6.6892e-03 eta: 21:59:58 time: 1.1983 data_time: 0.0576 memory: 16201 loss_prob: 1.1134 loss_thr: 0.5799 loss_db: 0.1749 loss: 1.8683 2022/08/30 00:20:52 - mmengine - INFO - Epoch(train) [60][55/63] lr: 6.6892e-03 eta: 21:59:58 time: 1.1635 data_time: 0.0483 memory: 16201 loss_prob: 1.1190 loss_thr: 0.5888 loss_db: 0.1821 loss: 1.8899 2022/08/30 00:20:58 - mmengine - INFO - Epoch(train) [60][60/63] lr: 6.6892e-03 eta: 22:00:03 time: 1.1892 data_time: 0.0644 memory: 16201 loss_prob: 1.1469 loss_thr: 0.5797 loss_db: 0.1890 loss: 1.9156 2022/08/30 00:21:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:21:01 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/08/30 00:21:10 - mmengine - INFO - Epoch(val) [60][5/32] eta: 22:00:03 time: 0.6581 data_time: 0.1305 memory: 16201 2022/08/30 00:21:13 - mmengine - INFO - Epoch(val) [60][10/32] eta: 0:00:15 time: 0.7122 data_time: 0.1362 memory: 15734 2022/08/30 00:21:16 - mmengine - INFO - Epoch(val) [60][15/32] eta: 0:00:15 time: 0.6155 data_time: 0.0484 memory: 15734 2022/08/30 00:21:20 - mmengine - INFO - Epoch(val) [60][20/32] eta: 0:00:08 time: 0.7413 data_time: 0.0766 memory: 15734 2022/08/30 00:21:23 - mmengine - INFO - Epoch(val) [60][25/32] eta: 0:00:08 time: 0.7483 data_time: 0.0711 memory: 15734 2022/08/30 00:21:26 - mmengine - INFO - Epoch(val) [60][30/32] eta: 0:00:01 time: 0.6265 data_time: 0.0503 memory: 15734 2022/08/30 00:21:27 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 00:21:27 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8093, precision: 0.7494, hmean: 0.7782 2022/08/30 00:21:27 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8093, precision: 0.8062, hmean: 0.8078 2022/08/30 00:21:27 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8021, precision: 0.8470, hmean: 0.8239 2022/08/30 00:21:27 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7790, precision: 0.8713, hmean: 0.8226 2022/08/30 00:21:27 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7130, precision: 0.9080, hmean: 0.7988 2022/08/30 00:21:27 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3207, precision: 0.9652, hmean: 0.4814 2022/08/30 00:21:27 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/08/30 00:21:27 - mmengine - INFO - Epoch(val) [60][32/32] icdar/precision: 0.8470 icdar/recall: 0.8021 icdar/hmean: 0.8239 2022/08/30 00:21:39 - mmengine - INFO - Epoch(train) [61][5/63] lr: 6.6839e-03 eta: 0:00:01 time: 1.7004 data_time: 0.2742 memory: 16201 loss_prob: 1.2316 loss_thr: 0.6015 loss_db: 0.1999 loss: 2.0330 2022/08/30 00:21:49 - mmengine - INFO - Epoch(train) [61][10/63] lr: 6.6839e-03 eta: 22:02:07 time: 2.1619 data_time: 0.3069 memory: 16201 loss_prob: 1.1867 loss_thr: 0.5892 loss_db: 0.1983 loss: 1.9742 2022/08/30 00:21:56 - mmengine - INFO - Epoch(train) [61][15/63] lr: 6.6839e-03 eta: 22:02:07 time: 1.6666 data_time: 0.0546 memory: 16201 loss_prob: 1.1164 loss_thr: 0.5684 loss_db: 0.1831 loss: 1.8679 2022/08/30 00:22:07 - mmengine - INFO - Epoch(train) [61][20/63] lr: 6.6839e-03 eta: 22:04:12 time: 1.8252 data_time: 0.0468 memory: 16201 loss_prob: 1.1817 loss_thr: 0.5631 loss_db: 0.1889 loss: 1.9337 2022/08/30 00:22:18 - mmengine - INFO - Epoch(train) [61][25/63] lr: 6.6839e-03 eta: 22:04:12 time: 2.1933 data_time: 0.1017 memory: 16201 loss_prob: 1.3060 loss_thr: 0.6039 loss_db: 0.2112 loss: 2.1211 2022/08/30 00:22:29 - mmengine - INFO - Epoch(train) [61][30/63] lr: 6.6839e-03 eta: 22:07:25 time: 2.1919 data_time: 0.1006 memory: 16201 loss_prob: 1.1777 loss_thr: 0.5839 loss_db: 0.1955 loss: 1.9571 2022/08/30 00:22:39 - mmengine - INFO - Epoch(train) [61][35/63] lr: 6.6839e-03 eta: 22:07:25 time: 2.0700 data_time: 0.0872 memory: 16201 loss_prob: 1.0562 loss_thr: 0.5401 loss_db: 0.1732 loss: 1.7695 2022/08/30 00:22:48 - mmengine - INFO - Epoch(train) [61][40/63] lr: 6.6839e-03 eta: 22:09:36 time: 1.8625 data_time: 0.0686 memory: 16201 loss_prob: 1.1696 loss_thr: 0.5754 loss_db: 0.1870 loss: 1.9320 2022/08/30 00:22:58 - mmengine - INFO - Epoch(train) [61][45/63] lr: 6.6839e-03 eta: 22:09:36 time: 1.8974 data_time: 0.0662 memory: 16201 loss_prob: 1.2329 loss_thr: 0.6090 loss_db: 0.1971 loss: 2.0390 2022/08/30 00:23:08 - mmengine - INFO - Epoch(train) [61][50/63] lr: 6.6839e-03 eta: 22:12:14 time: 2.0165 data_time: 0.0844 memory: 16201 loss_prob: 1.1415 loss_thr: 0.6058 loss_db: 0.1847 loss: 1.9319 2022/08/30 00:23:18 - mmengine - INFO - Epoch(train) [61][55/63] lr: 6.6839e-03 eta: 22:12:14 time: 2.0783 data_time: 0.0741 memory: 16201 loss_prob: 1.2110 loss_thr: 0.6157 loss_db: 0.1987 loss: 2.0254 2022/08/30 00:23:28 - mmengine - INFO - Epoch(train) [61][60/63] lr: 6.6839e-03 eta: 22:14:58 time: 2.0516 data_time: 0.0925 memory: 16201 loss_prob: 1.2433 loss_thr: 0.6042 loss_db: 0.2045 loss: 2.0520 2022/08/30 00:23:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:23:47 - mmengine - INFO - Epoch(train) [62][5/63] lr: 6.6787e-03 eta: 22:14:58 time: 2.3116 data_time: 0.3531 memory: 16201 loss_prob: 1.1329 loss_thr: 0.5947 loss_db: 0.1876 loss: 1.9153 2022/08/30 00:23:59 - mmengine - INFO - Epoch(train) [62][10/63] lr: 6.6787e-03 eta: 22:17:54 time: 2.4705 data_time: 0.3941 memory: 16201 loss_prob: 1.1741 loss_thr: 0.6032 loss_db: 0.1884 loss: 1.9657 2022/08/30 00:24:08 - mmengine - INFO - Epoch(train) [62][15/63] lr: 6.6787e-03 eta: 22:17:54 time: 2.0483 data_time: 0.1035 memory: 16201 loss_prob: 1.2693 loss_thr: 0.6082 loss_db: 0.2066 loss: 2.0841 2022/08/30 00:24:18 - mmengine - INFO - Epoch(train) [62][20/63] lr: 6.6787e-03 eta: 22:20:17 time: 1.9527 data_time: 0.0682 memory: 16201 loss_prob: 1.2689 loss_thr: 0.6049 loss_db: 0.2081 loss: 2.0819 2022/08/30 00:24:29 - mmengine - INFO - Epoch(train) [62][25/63] lr: 6.6787e-03 eta: 22:20:17 time: 2.1171 data_time: 0.0810 memory: 16201 loss_prob: 1.2280 loss_thr: 0.5878 loss_db: 0.1981 loss: 2.0140 2022/08/30 00:24:40 - mmengine - INFO - Epoch(train) [62][30/63] lr: 6.6787e-03 eta: 22:23:20 time: 2.1690 data_time: 0.0794 memory: 16201 loss_prob: 1.1458 loss_thr: 0.5693 loss_db: 0.1865 loss: 1.9017 2022/08/30 00:24:52 - mmengine - INFO - Epoch(train) [62][35/63] lr: 6.6787e-03 eta: 22:23:20 time: 2.2879 data_time: 0.0989 memory: 16201 loss_prob: 1.1246 loss_thr: 0.5736 loss_db: 0.1835 loss: 1.8818 2022/08/30 00:25:03 - mmengine - INFO - Epoch(train) [62][40/63] lr: 6.6787e-03 eta: 22:26:42 time: 2.2806 data_time: 0.1181 memory: 16201 loss_prob: 1.1510 loss_thr: 0.5943 loss_db: 0.1833 loss: 1.9285 2022/08/30 00:25:15 - mmengine - INFO - Epoch(train) [62][45/63] lr: 6.6787e-03 eta: 22:26:42 time: 2.3308 data_time: 0.1180 memory: 16201 loss_prob: 1.1402 loss_thr: 0.5960 loss_db: 0.1862 loss: 1.9224 2022/08/30 00:25:28 - mmengine - INFO - Epoch(train) [62][50/63] lr: 6.6787e-03 eta: 22:30:48 time: 2.5215 data_time: 0.1253 memory: 16201 loss_prob: 1.1806 loss_thr: 0.5899 loss_db: 0.1941 loss: 1.9647 2022/08/30 00:25:41 - mmengine - INFO - Epoch(train) [62][55/63] lr: 6.6787e-03 eta: 22:30:48 time: 2.5709 data_time: 0.1059 memory: 16201 loss_prob: 1.1475 loss_thr: 0.5753 loss_db: 0.1852 loss: 1.9079 2022/08/30 00:25:52 - mmengine - INFO - Epoch(train) [62][60/63] lr: 6.6787e-03 eta: 22:34:21 time: 2.3484 data_time: 0.1020 memory: 16201 loss_prob: 1.0615 loss_thr: 0.5587 loss_db: 0.1761 loss: 1.7963 2022/08/30 00:25:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:26:08 - mmengine - INFO - Epoch(train) [63][5/63] lr: 6.6734e-03 eta: 22:34:21 time: 1.9847 data_time: 0.3036 memory: 16201 loss_prob: 1.2749 loss_thr: 0.6163 loss_db: 0.2085 loss: 2.0996 2022/08/30 00:26:19 - mmengine - INFO - Epoch(train) [63][10/63] lr: 6.6734e-03 eta: 22:36:15 time: 2.1775 data_time: 0.3295 memory: 16201 loss_prob: 1.1456 loss_thr: 0.6069 loss_db: 0.1911 loss: 1.9437 2022/08/30 00:26:28 - mmengine - INFO - Epoch(train) [63][15/63] lr: 6.6734e-03 eta: 22:36:15 time: 2.0642 data_time: 0.0983 memory: 16201 loss_prob: 1.0179 loss_thr: 0.5547 loss_db: 0.1686 loss: 1.7412 2022/08/30 00:26:40 - mmengine - INFO - Epoch(train) [63][20/63] lr: 6.6734e-03 eta: 22:39:04 time: 2.1219 data_time: 0.0807 memory: 16201 loss_prob: 1.0798 loss_thr: 0.5654 loss_db: 0.1719 loss: 1.8170 2022/08/30 00:26:50 - mmengine - INFO - Epoch(train) [63][25/63] lr: 6.6734e-03 eta: 22:39:04 time: 2.2003 data_time: 0.0977 memory: 16201 loss_prob: 1.1508 loss_thr: 0.5962 loss_db: 0.1849 loss: 1.9319 2022/08/30 00:27:03 - mmengine - INFO - Epoch(train) [63][30/63] lr: 6.6734e-03 eta: 22:42:25 time: 2.3067 data_time: 0.1039 memory: 16201 loss_prob: 1.1266 loss_thr: 0.5881 loss_db: 0.1861 loss: 1.9007 2022/08/30 00:27:15 - mmengine - INFO - Epoch(train) [63][35/63] lr: 6.6734e-03 eta: 22:42:25 time: 2.5100 data_time: 0.1144 memory: 16201 loss_prob: 1.1503 loss_thr: 0.5823 loss_db: 0.1860 loss: 1.9186 2022/08/30 00:27:26 - mmengine - INFO - Epoch(train) [63][40/63] lr: 6.6734e-03 eta: 22:45:37 time: 2.2602 data_time: 0.1064 memory: 16201 loss_prob: 1.2021 loss_thr: 0.5700 loss_db: 0.1888 loss: 1.9609 2022/08/30 00:27:37 - mmengine - INFO - Epoch(train) [63][45/63] lr: 6.6734e-03 eta: 22:45:37 time: 2.1781 data_time: 0.0744 memory: 16201 loss_prob: 1.1423 loss_thr: 0.5666 loss_db: 0.1813 loss: 1.8901 2022/08/30 00:27:48 - mmengine - INFO - Epoch(train) [63][50/63] lr: 6.6734e-03 eta: 22:48:34 time: 2.1868 data_time: 0.0850 memory: 16201 loss_prob: 1.1012 loss_thr: 0.5723 loss_db: 0.1812 loss: 1.8547 2022/08/30 00:28:01 - mmengine - INFO - Epoch(train) [63][55/63] lr: 6.6734e-03 eta: 22:48:34 time: 2.3123 data_time: 0.0947 memory: 16201 loss_prob: 1.1147 loss_thr: 0.5734 loss_db: 0.1836 loss: 1.8717 2022/08/30 00:28:10 - mmengine - INFO - Epoch(train) [63][60/63] lr: 6.6734e-03 eta: 22:51:49 time: 2.2877 data_time: 0.1080 memory: 16201 loss_prob: 1.1501 loss_thr: 0.5958 loss_db: 0.1903 loss: 1.9362 2022/08/30 00:28:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:28:30 - mmengine - INFO - Epoch(train) [64][5/63] lr: 6.6681e-03 eta: 22:51:49 time: 2.3318 data_time: 0.3841 memory: 16201 loss_prob: 1.2760 loss_thr: 0.6359 loss_db: 0.2118 loss: 2.1237 2022/08/30 00:28:40 - mmengine - INFO - Epoch(train) [64][10/63] lr: 6.6681e-03 eta: 22:54:16 time: 2.3930 data_time: 0.4197 memory: 16201 loss_prob: 1.3070 loss_thr: 0.6176 loss_db: 0.2119 loss: 2.1364 2022/08/30 00:28:50 - mmengine - INFO - Epoch(train) [64][15/63] lr: 6.6681e-03 eta: 22:54:16 time: 2.0426 data_time: 0.0810 memory: 16201 loss_prob: 1.1992 loss_thr: 0.6072 loss_db: 0.1968 loss: 2.0032 2022/08/30 00:29:01 - mmengine - INFO - Epoch(train) [64][20/63] lr: 6.6681e-03 eta: 22:57:03 time: 2.1472 data_time: 0.0787 memory: 16201 loss_prob: 1.1036 loss_thr: 0.5998 loss_db: 0.1832 loss: 1.8866 2022/08/30 00:29:14 - mmengine - INFO - Epoch(train) [64][25/63] lr: 6.6681e-03 eta: 22:57:03 time: 2.3520 data_time: 0.0987 memory: 16201 loss_prob: 1.0839 loss_thr: 0.5710 loss_db: 0.1800 loss: 1.8349 2022/08/30 00:29:25 - mmengine - INFO - Epoch(train) [64][30/63] lr: 6.6681e-03 eta: 23:00:36 time: 2.4083 data_time: 0.0959 memory: 16201 loss_prob: 1.0907 loss_thr: 0.5780 loss_db: 0.1785 loss: 1.8472 2022/08/30 00:29:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:29:37 - mmengine - INFO - Epoch(train) [64][35/63] lr: 6.6681e-03 eta: 23:00:36 time: 2.3211 data_time: 0.0980 memory: 16201 loss_prob: 1.0857 loss_thr: 0.5752 loss_db: 0.1732 loss: 1.8341 2022/08/30 00:29:48 - mmengine - INFO - Epoch(train) [64][40/63] lr: 6.6681e-03 eta: 23:03:49 time: 2.2998 data_time: 0.0809 memory: 16201 loss_prob: 1.0847 loss_thr: 0.5663 loss_db: 0.1762 loss: 1.8272 2022/08/30 00:29:59 - mmengine - INFO - Epoch(train) [64][45/63] lr: 6.6681e-03 eta: 23:03:49 time: 2.2300 data_time: 0.0877 memory: 16201 loss_prob: 1.1606 loss_thr: 0.5473 loss_db: 0.1883 loss: 1.8961 2022/08/30 00:30:10 - mmengine - INFO - Epoch(train) [64][50/63] lr: 6.6681e-03 eta: 23:06:37 time: 2.1703 data_time: 0.0978 memory: 16201 loss_prob: 1.2566 loss_thr: 0.5913 loss_db: 0.2005 loss: 2.0483 2022/08/30 00:30:18 - mmengine - INFO - Epoch(train) [64][55/63] lr: 6.6681e-03 eta: 23:06:37 time: 1.9323 data_time: 0.0757 memory: 16201 loss_prob: 1.2107 loss_thr: 0.6066 loss_db: 0.1941 loss: 2.0114 2022/08/30 00:30:28 - mmengine - INFO - Epoch(train) [64][60/63] lr: 6.6681e-03 eta: 23:08:13 time: 1.7684 data_time: 0.0645 memory: 16201 loss_prob: 1.0732 loss_thr: 0.5553 loss_db: 0.1752 loss: 1.8037 2022/08/30 00:30:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:30:46 - mmengine - INFO - Epoch(train) [65][5/63] lr: 6.6628e-03 eta: 23:08:13 time: 2.2146 data_time: 0.3753 memory: 16201 loss_prob: 1.1895 loss_thr: 0.5934 loss_db: 0.1924 loss: 1.9754 2022/08/30 00:30:55 - mmengine - INFO - Epoch(train) [65][10/63] lr: 6.6628e-03 eta: 23:10:02 time: 2.2124 data_time: 0.4269 memory: 16201 loss_prob: 1.2309 loss_thr: 0.6228 loss_db: 0.2046 loss: 2.0583 2022/08/30 00:31:06 - mmengine - INFO - Epoch(train) [65][15/63] lr: 6.6628e-03 eta: 23:10:02 time: 2.0101 data_time: 0.1142 memory: 16201 loss_prob: 1.1688 loss_thr: 0.5990 loss_db: 0.1967 loss: 1.9644 2022/08/30 00:31:15 - mmengine - INFO - Epoch(train) [65][20/63] lr: 6.6628e-03 eta: 23:12:27 time: 2.0514 data_time: 0.1123 memory: 16201 loss_prob: 1.1596 loss_thr: 0.5893 loss_db: 0.1935 loss: 1.9424 2022/08/30 00:31:27 - mmengine - INFO - Epoch(train) [65][25/63] lr: 6.6628e-03 eta: 23:12:27 time: 2.0469 data_time: 0.1318 memory: 16201 loss_prob: 1.2432 loss_thr: 0.5917 loss_db: 0.2096 loss: 2.0445 2022/08/30 00:31:36 - mmengine - INFO - Epoch(train) [65][30/63] lr: 6.6628e-03 eta: 23:14:53 time: 2.0657 data_time: 0.1250 memory: 16201 loss_prob: 1.2413 loss_thr: 0.5958 loss_db: 0.2075 loss: 2.0447 2022/08/30 00:31:46 - mmengine - INFO - Epoch(train) [65][35/63] lr: 6.6628e-03 eta: 23:14:53 time: 1.9114 data_time: 0.1185 memory: 16201 loss_prob: 1.1201 loss_thr: 0.6009 loss_db: 0.1859 loss: 1.9069 2022/08/30 00:31:55 - mmengine - INFO - Epoch(train) [65][40/63] lr: 6.6628e-03 eta: 23:16:50 time: 1.9001 data_time: 0.1183 memory: 16201 loss_prob: 1.0850 loss_thr: 0.5626 loss_db: 0.1788 loss: 1.8264 2022/08/30 00:32:05 - mmengine - INFO - Epoch(train) [65][45/63] lr: 6.6628e-03 eta: 23:16:50 time: 1.9793 data_time: 0.1164 memory: 16201 loss_prob: 1.1322 loss_thr: 0.5574 loss_db: 0.1853 loss: 1.8750 2022/08/30 00:32:16 - mmengine - INFO - Epoch(train) [65][50/63] lr: 6.6628e-03 eta: 23:19:21 time: 2.1026 data_time: 0.1270 memory: 16201 loss_prob: 1.0826 loss_thr: 0.5601 loss_db: 0.1783 loss: 1.8211 2022/08/30 00:32:26 - mmengine - INFO - Epoch(train) [65][55/63] lr: 6.6628e-03 eta: 23:19:21 time: 2.0954 data_time: 0.1563 memory: 16201 loss_prob: 1.2053 loss_thr: 0.5829 loss_db: 0.1939 loss: 1.9821 2022/08/30 00:32:37 - mmengine - INFO - Epoch(train) [65][60/63] lr: 6.6628e-03 eta: 23:22:01 time: 2.1577 data_time: 0.1524 memory: 16201 loss_prob: 1.3371 loss_thr: 0.6217 loss_db: 0.2112 loss: 2.1701 2022/08/30 00:32:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:32:55 - mmengine - INFO - Epoch(train) [66][5/63] lr: 6.6575e-03 eta: 23:22:01 time: 2.1758 data_time: 0.3965 memory: 16201 loss_prob: 1.2209 loss_thr: 0.5684 loss_db: 0.2024 loss: 1.9916 2022/08/30 00:33:05 - mmengine - INFO - Epoch(train) [66][10/63] lr: 6.6575e-03 eta: 23:24:08 time: 2.3465 data_time: 0.4218 memory: 16201 loss_prob: 1.2439 loss_thr: 0.5842 loss_db: 0.2014 loss: 2.0295 2022/08/30 00:33:16 - mmengine - INFO - Epoch(train) [66][15/63] lr: 6.6575e-03 eta: 23:24:08 time: 2.0754 data_time: 0.1250 memory: 16201 loss_prob: 1.1596 loss_thr: 0.5677 loss_db: 0.1899 loss: 1.9172 2022/08/30 00:33:26 - mmengine - INFO - Epoch(train) [66][20/63] lr: 6.6575e-03 eta: 23:26:33 time: 2.0778 data_time: 0.1166 memory: 16201 loss_prob: 1.1074 loss_thr: 0.5711 loss_db: 0.1865 loss: 1.8650 2022/08/30 00:33:38 - mmengine - INFO - Epoch(train) [66][25/63] lr: 6.6575e-03 eta: 23:26:33 time: 2.2022 data_time: 0.1313 memory: 16201 loss_prob: 1.0926 loss_thr: 0.5805 loss_db: 0.1760 loss: 1.8491 2022/08/30 00:33:49 - mmengine - INFO - Epoch(train) [66][30/63] lr: 6.6575e-03 eta: 23:29:34 time: 2.2933 data_time: 0.1118 memory: 16201 loss_prob: 1.1697 loss_thr: 0.5869 loss_db: 0.1882 loss: 1.9448 2022/08/30 00:34:01 - mmengine - INFO - Epoch(train) [66][35/63] lr: 6.6575e-03 eta: 23:29:34 time: 2.3243 data_time: 0.1596 memory: 16201 loss_prob: 1.2454 loss_thr: 0.5800 loss_db: 0.2061 loss: 2.0315 2022/08/30 00:34:12 - mmengine - INFO - Epoch(train) [66][40/63] lr: 6.6575e-03 eta: 23:32:39 time: 2.3252 data_time: 0.1589 memory: 16201 loss_prob: 1.1864 loss_thr: 0.5937 loss_db: 0.1943 loss: 1.9744 2022/08/30 00:34:24 - mmengine - INFO - Epoch(train) [66][45/63] lr: 6.6575e-03 eta: 23:32:39 time: 2.2858 data_time: 0.1916 memory: 16201 loss_prob: 1.1159 loss_thr: 0.6073 loss_db: 0.1858 loss: 1.9090 2022/08/30 00:34:36 - mmengine - INFO - Epoch(train) [66][50/63] lr: 6.6575e-03 eta: 23:35:45 time: 2.3310 data_time: 0.1751 memory: 16201 loss_prob: 1.0796 loss_thr: 0.5854 loss_db: 0.1755 loss: 1.8405 2022/08/30 00:34:47 - mmengine - INFO - Epoch(train) [66][55/63] lr: 6.6575e-03 eta: 23:35:45 time: 2.3163 data_time: 0.0893 memory: 16201 loss_prob: 1.1119 loss_thr: 0.5793 loss_db: 0.1784 loss: 1.8696 2022/08/30 00:34:57 - mmengine - INFO - Epoch(train) [66][60/63] lr: 6.6575e-03 eta: 23:38:09 time: 2.0969 data_time: 0.0945 memory: 16201 loss_prob: 1.1753 loss_thr: 0.5837 loss_db: 0.1935 loss: 1.9526 2022/08/30 00:35:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:35:19 - mmengine - INFO - Epoch(train) [67][5/63] lr: 6.6522e-03 eta: 23:38:09 time: 2.5569 data_time: 0.5101 memory: 16201 loss_prob: 1.2461 loss_thr: 0.5869 loss_db: 0.1970 loss: 2.0299 2022/08/30 00:35:30 - mmengine - INFO - Epoch(train) [67][10/63] lr: 6.6522e-03 eta: 23:41:29 time: 2.8019 data_time: 0.5663 memory: 16201 loss_prob: 1.1646 loss_thr: 0.5866 loss_db: 0.1797 loss: 1.9309 2022/08/30 00:35:40 - mmengine - INFO - Epoch(train) [67][15/63] lr: 6.6522e-03 eta: 23:41:29 time: 2.1398 data_time: 0.0996 memory: 16201 loss_prob: 1.1845 loss_thr: 0.6012 loss_db: 0.1893 loss: 1.9749 2022/08/30 00:35:50 - mmengine - INFO - Epoch(train) [67][20/63] lr: 6.6522e-03 eta: 23:43:26 time: 1.9505 data_time: 0.0642 memory: 16201 loss_prob: 1.1582 loss_thr: 0.5792 loss_db: 0.1920 loss: 1.9294 2022/08/30 00:35:59 - mmengine - INFO - Epoch(train) [67][25/63] lr: 6.6522e-03 eta: 23:43:26 time: 1.8522 data_time: 0.0915 memory: 16201 loss_prob: 1.1207 loss_thr: 0.5852 loss_db: 0.1853 loss: 1.8912 2022/08/30 00:36:07 - mmengine - INFO - Epoch(train) [67][30/63] lr: 6.6522e-03 eta: 23:44:52 time: 1.7710 data_time: 0.0767 memory: 16201 loss_prob: 1.1292 loss_thr: 0.5989 loss_db: 0.1896 loss: 1.9176 2022/08/30 00:36:19 - mmengine - INFO - Epoch(train) [67][35/63] lr: 6.6522e-03 eta: 23:44:52 time: 2.0776 data_time: 0.0617 memory: 16201 loss_prob: 1.0720 loss_thr: 0.5939 loss_db: 0.1777 loss: 1.8435 2022/08/30 00:36:31 - mmengine - INFO - Epoch(train) [67][40/63] lr: 6.6522e-03 eta: 23:47:52 time: 2.3263 data_time: 0.1109 memory: 16201 loss_prob: 1.2359 loss_thr: 0.6065 loss_db: 0.1951 loss: 2.0374 2022/08/30 00:36:42 - mmengine - INFO - Epoch(train) [67][45/63] lr: 6.6522e-03 eta: 23:47:52 time: 2.2435 data_time: 0.1173 memory: 16201 loss_prob: 1.1826 loss_thr: 0.5776 loss_db: 0.1900 loss: 1.9502 2022/08/30 00:36:53 - mmengine - INFO - Epoch(train) [67][50/63] lr: 6.6522e-03 eta: 23:50:31 time: 2.2088 data_time: 0.1020 memory: 16201 loss_prob: 1.1165 loss_thr: 0.5694 loss_db: 0.1838 loss: 1.8696 2022/08/30 00:37:04 - mmengine - INFO - Epoch(train) [67][55/63] lr: 6.6522e-03 eta: 23:50:31 time: 2.1829 data_time: 0.0960 memory: 16201 loss_prob: 1.1766 loss_thr: 0.5989 loss_db: 0.1920 loss: 1.9676 2022/08/30 00:37:15 - mmengine - INFO - Epoch(train) [67][60/63] lr: 6.6522e-03 eta: 23:53:11 time: 2.2196 data_time: 0.1074 memory: 16201 loss_prob: 1.0933 loss_thr: 0.5978 loss_db: 0.1795 loss: 1.8705 2022/08/30 00:37:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:37:39 - mmengine - INFO - Epoch(train) [68][5/63] lr: 6.6470e-03 eta: 23:53:11 time: 2.7982 data_time: 0.5830 memory: 16201 loss_prob: 1.0863 loss_thr: 0.5924 loss_db: 0.1774 loss: 1.8561 2022/08/30 00:37:51 - mmengine - INFO - Epoch(train) [68][10/63] lr: 6.6470e-03 eta: 23:56:54 time: 2.9764 data_time: 0.6692 memory: 16201 loss_prob: 1.0278 loss_thr: 0.5810 loss_db: 0.1715 loss: 1.7803 2022/08/30 00:38:02 - mmengine - INFO - Epoch(train) [68][15/63] lr: 6.6470e-03 eta: 23:56:54 time: 2.3291 data_time: 0.1670 memory: 16201 loss_prob: 1.0791 loss_thr: 0.5892 loss_db: 0.1766 loss: 1.8449 2022/08/30 00:38:14 - mmengine - INFO - Epoch(train) [68][20/63] lr: 6.6470e-03 eta: 23:59:43 time: 2.2884 data_time: 0.0798 memory: 16201 loss_prob: 1.0525 loss_thr: 0.5787 loss_db: 0.1702 loss: 1.8015 2022/08/30 00:38:26 - mmengine - INFO - Epoch(train) [68][25/63] lr: 6.6470e-03 eta: 23:59:43 time: 2.3650 data_time: 0.1072 memory: 16201 loss_prob: 1.0652 loss_thr: 0.5619 loss_db: 0.1726 loss: 1.7997 2022/08/30 00:38:37 - mmengine - INFO - Epoch(train) [68][30/63] lr: 6.6470e-03 eta: 1 day, 0:02:39 time: 2.3303 data_time: 0.1030 memory: 16201 loss_prob: 1.0877 loss_thr: 0.5586 loss_db: 0.1766 loss: 1.8229 2022/08/30 00:38:48 - mmengine - INFO - Epoch(train) [68][35/63] lr: 6.6470e-03 eta: 1 day, 0:02:39 time: 2.2338 data_time: 0.0911 memory: 16201 loss_prob: 1.0683 loss_thr: 0.5688 loss_db: 0.1769 loss: 1.8140 2022/08/30 00:38:59 - mmengine - INFO - Epoch(train) [68][40/63] lr: 6.6470e-03 eta: 1 day, 0:05:15 time: 2.2183 data_time: 0.0725 memory: 16201 loss_prob: 1.1414 loss_thr: 0.5964 loss_db: 0.1912 loss: 1.9290 2022/08/30 00:39:10 - mmengine - INFO - Epoch(train) [68][45/63] lr: 6.6470e-03 eta: 1 day, 0:05:15 time: 2.2340 data_time: 0.0830 memory: 16201 loss_prob: 1.2172 loss_thr: 0.6142 loss_db: 0.2020 loss: 2.0333 2022/08/30 00:39:20 - mmengine - INFO - Epoch(train) [68][50/63] lr: 6.6470e-03 eta: 1 day, 0:07:32 time: 2.1046 data_time: 0.1065 memory: 16201 loss_prob: 1.1487 loss_thr: 0.5878 loss_db: 0.1885 loss: 1.9250 2022/08/30 00:39:30 - mmengine - INFO - Epoch(train) [68][55/63] lr: 6.6470e-03 eta: 1 day, 0:07:32 time: 1.9836 data_time: 0.0774 memory: 16201 loss_prob: 1.1238 loss_thr: 0.5750 loss_db: 0.1841 loss: 1.8829 2022/08/30 00:39:41 - mmengine - INFO - Epoch(train) [68][60/63] lr: 6.6470e-03 eta: 1 day, 0:09:39 time: 2.0542 data_time: 0.0670 memory: 16201 loss_prob: 1.1494 loss_thr: 0.5901 loss_db: 0.1898 loss: 1.9292 2022/08/30 00:39:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:40:01 - mmengine - INFO - Epoch(train) [69][5/63] lr: 6.6417e-03 eta: 1 day, 0:09:39 time: 2.4061 data_time: 0.3306 memory: 16201 loss_prob: 1.1492 loss_thr: 0.5980 loss_db: 0.1976 loss: 1.9448 2022/08/30 00:40:10 - mmengine - INFO - Epoch(train) [69][10/63] lr: 6.6417e-03 eta: 1 day, 0:11:36 time: 2.3885 data_time: 0.3412 memory: 16201 loss_prob: 1.1990 loss_thr: 0.6012 loss_db: 0.1985 loss: 1.9987 2022/08/30 00:40:17 - mmengine - INFO - Epoch(train) [69][15/63] lr: 6.6417e-03 eta: 1 day, 0:11:36 time: 1.6449 data_time: 0.0694 memory: 16201 loss_prob: 1.1800 loss_thr: 0.6057 loss_db: 0.1942 loss: 1.9799 2022/08/30 00:40:27 - mmengine - INFO - Epoch(train) [69][20/63] lr: 6.6417e-03 eta: 1 day, 0:12:50 time: 1.7410 data_time: 0.0665 memory: 16201 loss_prob: 1.1988 loss_thr: 0.6263 loss_db: 0.1947 loss: 2.0197 2022/08/30 00:40:37 - mmengine - INFO - Epoch(train) [69][25/63] lr: 6.6417e-03 eta: 1 day, 0:12:50 time: 1.9646 data_time: 0.0690 memory: 16201 loss_prob: 1.2640 loss_thr: 0.6392 loss_db: 0.2032 loss: 2.1063 2022/08/30 00:40:49 - mmengine - INFO - Epoch(train) [69][30/63] lr: 6.6417e-03 eta: 1 day, 0:15:25 time: 2.2302 data_time: 0.0673 memory: 16201 loss_prob: 1.1718 loss_thr: 0.6061 loss_db: 0.1880 loss: 1.9659 2022/08/30 00:40:59 - mmengine - INFO - Epoch(train) [69][35/63] lr: 6.6417e-03 eta: 1 day, 0:15:25 time: 2.1863 data_time: 0.0903 memory: 16201 loss_prob: 1.1682 loss_thr: 0.5871 loss_db: 0.1861 loss: 1.9415 2022/08/30 00:41:09 - mmengine - INFO - Epoch(train) [69][40/63] lr: 6.6417e-03 eta: 1 day, 0:17:18 time: 1.9860 data_time: 0.0715 memory: 16201 loss_prob: 1.1630 loss_thr: 0.5794 loss_db: 0.1911 loss: 1.9334 2022/08/30 00:41:20 - mmengine - INFO - Epoch(train) [69][45/63] lr: 6.6417e-03 eta: 1 day, 0:17:18 time: 2.0765 data_time: 0.0784 memory: 16201 loss_prob: 1.1206 loss_thr: 0.5646 loss_db: 0.1841 loss: 1.8692 2022/08/30 00:41:29 - mmengine - INFO - Epoch(train) [69][50/63] lr: 6.6417e-03 eta: 1 day, 0:19:03 time: 1.9417 data_time: 0.0956 memory: 16201 loss_prob: 1.1929 loss_thr: 0.5703 loss_db: 0.1902 loss: 1.9535 2022/08/30 00:41:40 - mmengine - INFO - Epoch(train) [69][55/63] lr: 6.6417e-03 eta: 1 day, 0:19:03 time: 2.0209 data_time: 0.0736 memory: 16201 loss_prob: 1.2436 loss_thr: 0.6039 loss_db: 0.2018 loss: 2.0493 2022/08/30 00:41:51 - mmengine - INFO - Epoch(train) [69][60/63] lr: 6.6417e-03 eta: 1 day, 0:21:34 time: 2.2220 data_time: 0.0866 memory: 16201 loss_prob: 1.1911 loss_thr: 0.5994 loss_db: 0.1953 loss: 1.9857 2022/08/30 00:41:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:42:11 - mmengine - INFO - Epoch(train) [70][5/63] lr: 6.6364e-03 eta: 1 day, 0:21:34 time: 2.4344 data_time: 0.5541 memory: 16201 loss_prob: 1.1730 loss_thr: 0.5941 loss_db: 0.1928 loss: 1.9599 2022/08/30 00:42:22 - mmengine - INFO - Epoch(train) [70][10/63] lr: 6.6364e-03 eta: 1 day, 0:24:04 time: 2.6191 data_time: 0.5637 memory: 16201 loss_prob: 1.1620 loss_thr: 0.5848 loss_db: 0.1935 loss: 1.9404 2022/08/30 00:42:34 - mmengine - INFO - Epoch(train) [70][15/63] lr: 6.6364e-03 eta: 1 day, 0:24:04 time: 2.3673 data_time: 0.0958 memory: 16201 loss_prob: 1.1106 loss_thr: 0.5639 loss_db: 0.1866 loss: 1.8611 2022/08/30 00:42:45 - mmengine - INFO - Epoch(train) [70][20/63] lr: 6.6364e-03 eta: 1 day, 0:26:48 time: 2.3099 data_time: 0.0844 memory: 16201 loss_prob: 1.0288 loss_thr: 0.5441 loss_db: 0.1708 loss: 1.7437 2022/08/30 00:42:57 - mmengine - INFO - Epoch(train) [70][25/63] lr: 6.6364e-03 eta: 1 day, 0:26:48 time: 2.2309 data_time: 0.1188 memory: 16201 loss_prob: 1.0339 loss_thr: 0.5472 loss_db: 0.1710 loss: 1.7521 2022/08/30 00:43:07 - mmengine - INFO - Epoch(train) [70][30/63] lr: 6.6364e-03 eta: 1 day, 0:29:14 time: 2.2123 data_time: 0.0913 memory: 16201 loss_prob: 1.1471 loss_thr: 0.5715 loss_db: 0.1859 loss: 1.9044 2022/08/30 00:43:19 - mmengine - INFO - Epoch(train) [70][35/63] lr: 6.6364e-03 eta: 1 day, 0:29:14 time: 2.2325 data_time: 0.0817 memory: 16201 loss_prob: 1.2076 loss_thr: 0.5673 loss_db: 0.1948 loss: 1.9698 2022/08/30 00:43:29 - mmengine - INFO - Epoch(train) [70][40/63] lr: 6.6364e-03 eta: 1 day, 0:31:23 time: 2.1062 data_time: 0.0844 memory: 16201 loss_prob: 1.1392 loss_thr: 0.5642 loss_db: 0.1873 loss: 1.8907 2022/08/30 00:43:39 - mmengine - INFO - Epoch(train) [70][45/63] lr: 6.6364e-03 eta: 1 day, 0:31:23 time: 2.0000 data_time: 0.0757 memory: 16201 loss_prob: 1.1308 loss_thr: 0.6095 loss_db: 0.1856 loss: 1.9260 2022/08/30 00:43:49 - mmengine - INFO - Epoch(train) [70][50/63] lr: 6.6364e-03 eta: 1 day, 0:33:23 time: 2.0612 data_time: 0.0956 memory: 16201 loss_prob: 1.1379 loss_thr: 0.6198 loss_db: 0.1855 loss: 1.9432 2022/08/30 00:43:59 - mmengine - INFO - Epoch(train) [70][55/63] lr: 6.6364e-03 eta: 1 day, 0:33:23 time: 1.9563 data_time: 0.0841 memory: 16201 loss_prob: 1.1319 loss_thr: 0.6033 loss_db: 0.1828 loss: 1.9180 2022/08/30 00:44:09 - mmengine - INFO - Epoch(train) [70][60/63] lr: 6.6364e-03 eta: 1 day, 0:35:14 time: 2.0004 data_time: 0.0578 memory: 16201 loss_prob: 1.1090 loss_thr: 0.5755 loss_db: 0.1784 loss: 1.8629 2022/08/30 00:44:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:44:30 - mmengine - INFO - Epoch(train) [71][5/63] lr: 6.6311e-03 eta: 1 day, 0:35:14 time: 2.5053 data_time: 0.4270 memory: 16201 loss_prob: 1.0756 loss_thr: 0.5885 loss_db: 0.1763 loss: 1.8404 2022/08/30 00:44:43 - mmengine - INFO - Epoch(train) [71][10/63] lr: 6.6311e-03 eta: 1 day, 0:38:12 time: 2.8213 data_time: 0.4533 memory: 16201 loss_prob: 1.0940 loss_thr: 0.5802 loss_db: 0.1795 loss: 1.8537 2022/08/30 00:44:52 - mmengine - INFO - Epoch(train) [71][15/63] lr: 6.6311e-03 eta: 1 day, 0:38:12 time: 2.2052 data_time: 0.0978 memory: 16201 loss_prob: 1.1452 loss_thr: 0.5807 loss_db: 0.1852 loss: 1.9111 2022/08/30 00:45:03 - mmengine - INFO - Epoch(train) [71][20/63] lr: 6.6311e-03 eta: 1 day, 0:39:57 time: 1.9821 data_time: 0.0682 memory: 16201 loss_prob: 1.1617 loss_thr: 0.5923 loss_db: 0.1851 loss: 1.9391 2022/08/30 00:45:12 - mmengine - INFO - Epoch(train) [71][25/63] lr: 6.6311e-03 eta: 1 day, 0:39:57 time: 2.0520 data_time: 0.0867 memory: 16201 loss_prob: 1.0745 loss_thr: 0.5776 loss_db: 0.1759 loss: 1.8279 2022/08/30 00:45:22 - mmengine - INFO - Epoch(train) [71][30/63] lr: 6.6311e-03 eta: 1 day, 0:41:45 time: 1.9943 data_time: 0.0838 memory: 16201 loss_prob: 0.9888 loss_thr: 0.5425 loss_db: 0.1671 loss: 1.6983 2022/08/30 00:45:32 - mmengine - INFO - Epoch(train) [71][35/63] lr: 6.6311e-03 eta: 1 day, 0:41:45 time: 2.0183 data_time: 0.0795 memory: 16201 loss_prob: 1.0965 loss_thr: 0.5545 loss_db: 0.1819 loss: 1.8329 2022/08/30 00:45:44 - mmengine - INFO - Epoch(train) [71][40/63] lr: 6.6311e-03 eta: 1 day, 0:43:50 time: 2.1127 data_time: 0.0733 memory: 16201 loss_prob: 1.1454 loss_thr: 0.5754 loss_db: 0.1888 loss: 1.9096 2022/08/30 00:45:54 - mmengine - INFO - Epoch(train) [71][45/63] lr: 6.6311e-03 eta: 1 day, 0:43:50 time: 2.1281 data_time: 0.0743 memory: 16201 loss_prob: 1.1337 loss_thr: 0.5851 loss_db: 0.1856 loss: 1.9044 2022/08/30 00:46:05 - mmengine - INFO - Epoch(train) [71][50/63] lr: 6.6311e-03 eta: 1 day, 0:45:57 time: 2.1230 data_time: 0.0970 memory: 16201 loss_prob: 1.2052 loss_thr: 0.5955 loss_db: 0.1930 loss: 1.9937 2022/08/30 00:46:16 - mmengine - INFO - Epoch(train) [71][55/63] lr: 6.6311e-03 eta: 1 day, 0:45:57 time: 2.1869 data_time: 0.0760 memory: 16201 loss_prob: 1.2225 loss_thr: 0.5786 loss_db: 0.2007 loss: 2.0018 2022/08/30 00:46:25 - mmengine - INFO - Epoch(train) [71][60/63] lr: 6.6311e-03 eta: 1 day, 0:47:51 time: 2.0523 data_time: 0.0762 memory: 16201 loss_prob: 1.1942 loss_thr: 0.5768 loss_db: 0.1979 loss: 1.9690 2022/08/30 00:46:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:46:44 - mmengine - INFO - Epoch(train) [72][5/63] lr: 6.6258e-03 eta: 1 day, 0:47:51 time: 2.2159 data_time: 0.3856 memory: 16201 loss_prob: 1.2688 loss_thr: 0.6168 loss_db: 0.2053 loss: 2.0909 2022/08/30 00:46:56 - mmengine - INFO - Epoch(train) [72][10/63] lr: 6.6258e-03 eta: 1 day, 0:50:07 time: 2.5905 data_time: 0.5611 memory: 16201 loss_prob: 1.1953 loss_thr: 0.5907 loss_db: 0.1937 loss: 1.9797 2022/08/30 00:47:06 - mmengine - INFO - Epoch(train) [72][15/63] lr: 6.6258e-03 eta: 1 day, 0:50:07 time: 2.2139 data_time: 0.2518 memory: 16201 loss_prob: 1.1644 loss_thr: 0.5730 loss_db: 0.1880 loss: 1.9254 2022/08/30 00:47:17 - mmengine - INFO - Epoch(train) [72][20/63] lr: 6.6258e-03 eta: 1 day, 0:52:06 time: 2.0879 data_time: 0.1064 memory: 16201 loss_prob: 1.0652 loss_thr: 0.5707 loss_db: 0.1697 loss: 1.8056 2022/08/30 00:47:29 - mmengine - INFO - Epoch(train) [72][25/63] lr: 6.6258e-03 eta: 1 day, 0:52:06 time: 2.2573 data_time: 0.1140 memory: 16201 loss_prob: 1.1714 loss_thr: 0.5727 loss_db: 0.1873 loss: 1.9313 2022/08/30 00:47:39 - mmengine - INFO - Epoch(train) [72][30/63] lr: 6.6258e-03 eta: 1 day, 0:54:22 time: 2.2007 data_time: 0.0961 memory: 16201 loss_prob: 1.2769 loss_thr: 0.5875 loss_db: 0.2065 loss: 2.0710 2022/08/30 00:47:51 - mmengine - INFO - Epoch(train) [72][35/63] lr: 6.6258e-03 eta: 1 day, 0:54:22 time: 2.2634 data_time: 0.0620 memory: 16201 loss_prob: 1.2554 loss_thr: 0.5890 loss_db: 0.2063 loss: 2.0506 2022/08/30 00:48:02 - mmengine - INFO - Epoch(train) [72][40/63] lr: 6.6258e-03 eta: 1 day, 0:56:56 time: 2.3213 data_time: 0.0821 memory: 16201 loss_prob: 1.1648 loss_thr: 0.5754 loss_db: 0.1915 loss: 1.9317 2022/08/30 00:48:13 - mmengine - INFO - Epoch(train) [72][45/63] lr: 6.6258e-03 eta: 1 day, 0:56:56 time: 2.1382 data_time: 0.1070 memory: 16201 loss_prob: 1.1828 loss_thr: 0.5955 loss_db: 0.1934 loss: 1.9717 2022/08/30 00:48:22 - mmengine - INFO - Epoch(train) [72][50/63] lr: 6.6258e-03 eta: 1 day, 0:58:43 time: 2.0211 data_time: 0.0822 memory: 16201 loss_prob: 1.1956 loss_thr: 0.6148 loss_db: 0.1981 loss: 2.0085 2022/08/30 00:48:34 - mmengine - INFO - Epoch(train) [72][55/63] lr: 6.6258e-03 eta: 1 day, 0:58:43 time: 2.1130 data_time: 0.0723 memory: 16201 loss_prob: 1.3377 loss_thr: 0.6334 loss_db: 0.2142 loss: 2.1853 2022/08/30 00:48:44 - mmengine - INFO - Epoch(train) [72][60/63] lr: 6.6258e-03 eta: 1 day, 1:00:56 time: 2.1982 data_time: 0.0772 memory: 16201 loss_prob: 1.3062 loss_thr: 0.6002 loss_db: 0.2094 loss: 2.1158 2022/08/30 00:48:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:49:05 - mmengine - INFO - Epoch(train) [73][5/63] lr: 6.6205e-03 eta: 1 day, 1:00:56 time: 2.4743 data_time: 0.4630 memory: 16201 loss_prob: 1.0661 loss_thr: 0.5580 loss_db: 0.1759 loss: 1.8000 2022/08/30 00:49:15 - mmengine - INFO - Epoch(train) [73][10/63] lr: 6.6205e-03 eta: 1 day, 1:03:14 time: 2.6335 data_time: 0.5077 memory: 16201 loss_prob: 1.1524 loss_thr: 0.6129 loss_db: 0.1919 loss: 1.9571 2022/08/30 00:49:25 - mmengine - INFO - Epoch(train) [73][15/63] lr: 6.6205e-03 eta: 1 day, 1:03:14 time: 2.1040 data_time: 0.1139 memory: 16201 loss_prob: 1.2538 loss_thr: 0.6438 loss_db: 0.2052 loss: 2.1028 2022/08/30 00:49:35 - mmengine - INFO - Epoch(train) [73][20/63] lr: 6.6205e-03 eta: 1 day, 1:04:56 time: 2.0052 data_time: 0.0775 memory: 16201 loss_prob: 1.2200 loss_thr: 0.6081 loss_db: 0.1995 loss: 2.0277 2022/08/30 00:49:45 - mmengine - INFO - Epoch(train) [73][25/63] lr: 6.6205e-03 eta: 1 day, 1:04:56 time: 1.9398 data_time: 0.0653 memory: 16201 loss_prob: 1.1524 loss_thr: 0.5728 loss_db: 0.1923 loss: 1.9174 2022/08/30 00:49:53 - mmengine - INFO - Epoch(train) [73][30/63] lr: 6.6205e-03 eta: 1 day, 1:06:09 time: 1.8185 data_time: 0.0667 memory: 16201 loss_prob: 1.1797 loss_thr: 0.5867 loss_db: 0.1909 loss: 1.9573 2022/08/30 00:50:05 - mmengine - INFO - Epoch(train) [73][35/63] lr: 6.6205e-03 eta: 1 day, 1:06:09 time: 2.0650 data_time: 0.0698 memory: 16201 loss_prob: 1.1971 loss_thr: 0.5848 loss_db: 0.1930 loss: 1.9749 2022/08/30 00:50:16 - mmengine - INFO - Epoch(train) [73][40/63] lr: 6.6205e-03 eta: 1 day, 1:08:33 time: 2.2836 data_time: 0.0721 memory: 16201 loss_prob: 1.1578 loss_thr: 0.5517 loss_db: 0.1865 loss: 1.8960 2022/08/30 00:50:27 - mmengine - INFO - Epoch(train) [73][45/63] lr: 6.6205e-03 eta: 1 day, 1:08:33 time: 2.1240 data_time: 0.0871 memory: 16201 loss_prob: 1.2155 loss_thr: 0.5615 loss_db: 0.1946 loss: 1.9716 2022/08/30 00:50:37 - mmengine - INFO - Epoch(train) [73][50/63] lr: 6.6205e-03 eta: 1 day, 1:10:27 time: 2.0943 data_time: 0.0936 memory: 16201 loss_prob: 1.1339 loss_thr: 0.5558 loss_db: 0.1847 loss: 1.8743 2022/08/30 00:50:47 - mmengine - INFO - Epoch(train) [73][55/63] lr: 6.6205e-03 eta: 1 day, 1:10:27 time: 2.0845 data_time: 0.1039 memory: 16201 loss_prob: 1.0816 loss_thr: 0.5703 loss_db: 0.1751 loss: 1.8271 2022/08/30 00:50:58 - mmengine - INFO - Epoch(train) [73][60/63] lr: 6.6205e-03 eta: 1 day, 1:12:16 time: 2.0639 data_time: 0.0921 memory: 16201 loss_prob: 1.0925 loss_thr: 0.5786 loss_db: 0.1784 loss: 1.8495 2022/08/30 00:51:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:51:18 - mmengine - INFO - Epoch(train) [74][5/63] lr: 6.6152e-03 eta: 1 day, 1:12:16 time: 2.5271 data_time: 0.3695 memory: 16201 loss_prob: 1.0952 loss_thr: 0.5739 loss_db: 0.1804 loss: 1.8495 2022/08/30 00:51:30 - mmengine - INFO - Epoch(train) [74][10/63] lr: 6.6152e-03 eta: 1 day, 1:14:13 time: 2.5289 data_time: 0.3654 memory: 16201 loss_prob: 1.0536 loss_thr: 0.5654 loss_db: 0.1710 loss: 1.7901 2022/08/30 00:51:39 - mmengine - INFO - Epoch(train) [74][15/63] lr: 6.6152e-03 eta: 1 day, 1:14:13 time: 2.0975 data_time: 0.0920 memory: 16201 loss_prob: 0.9964 loss_thr: 0.5484 loss_db: 0.1624 loss: 1.7072 2022/08/30 00:51:49 - mmengine - INFO - Epoch(train) [74][20/63] lr: 6.6152e-03 eta: 1 day, 1:15:39 time: 1.9248 data_time: 0.0746 memory: 16201 loss_prob: 1.0548 loss_thr: 0.5635 loss_db: 0.1699 loss: 1.7882 2022/08/30 00:51:59 - mmengine - INFO - Epoch(train) [74][25/63] lr: 6.6152e-03 eta: 1 day, 1:15:39 time: 1.9474 data_time: 0.0552 memory: 16201 loss_prob: 1.1081 loss_thr: 0.5704 loss_db: 0.1755 loss: 1.8540 2022/08/30 00:52:09 - mmengine - INFO - Epoch(train) [74][30/63] lr: 6.6152e-03 eta: 1 day, 1:17:26 time: 2.0601 data_time: 0.0639 memory: 16201 loss_prob: 1.0717 loss_thr: 0.5560 loss_db: 0.1761 loss: 1.8038 2022/08/30 00:52:19 - mmengine - INFO - Epoch(train) [74][35/63] lr: 6.6152e-03 eta: 1 day, 1:17:26 time: 2.0210 data_time: 0.0641 memory: 16201 loss_prob: 1.1021 loss_thr: 0.5666 loss_db: 0.1834 loss: 1.8521 2022/08/30 00:52:28 - mmengine - INFO - Epoch(train) [74][40/63] lr: 6.6152e-03 eta: 1 day, 1:18:43 time: 1.8726 data_time: 0.0417 memory: 16201 loss_prob: 1.1493 loss_thr: 0.5998 loss_db: 0.1880 loss: 1.9371 2022/08/30 00:52:38 - mmengine - INFO - Epoch(train) [74][45/63] lr: 6.6152e-03 eta: 1 day, 1:18:43 time: 1.8459 data_time: 0.0517 memory: 16201 loss_prob: 1.1381 loss_thr: 0.6010 loss_db: 0.1830 loss: 1.9221 2022/08/30 00:52:48 - mmengine - INFO - Epoch(train) [74][50/63] lr: 6.6152e-03 eta: 1 day, 1:20:18 time: 1.9869 data_time: 0.0545 memory: 16201 loss_prob: 1.0810 loss_thr: 0.5726 loss_db: 0.1735 loss: 1.8272 2022/08/30 00:53:00 - mmengine - INFO - Epoch(train) [74][55/63] lr: 6.6152e-03 eta: 1 day, 1:20:18 time: 2.2397 data_time: 0.0713 memory: 16201 loss_prob: 1.0876 loss_thr: 0.5760 loss_db: 0.1753 loss: 1.8389 2022/08/30 00:53:11 - mmengine - INFO - Epoch(train) [74][60/63] lr: 6.6152e-03 eta: 1 day, 1:22:44 time: 2.3321 data_time: 0.1099 memory: 16201 loss_prob: 1.0621 loss_thr: 0.5743 loss_db: 0.1747 loss: 1.8110 2022/08/30 00:53:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:53:30 - mmengine - INFO - Epoch(train) [75][5/63] lr: 6.6100e-03 eta: 1 day, 1:22:44 time: 2.3133 data_time: 0.3987 memory: 16201 loss_prob: 1.0405 loss_thr: 0.5467 loss_db: 0.1722 loss: 1.7594 2022/08/30 00:53:42 - mmengine - INFO - Epoch(train) [75][10/63] lr: 6.6100e-03 eta: 1 day, 1:24:42 time: 2.5575 data_time: 0.4226 memory: 16201 loss_prob: 1.0558 loss_thr: 0.5683 loss_db: 0.1700 loss: 1.7942 2022/08/30 00:53:53 - mmengine - INFO - Epoch(train) [75][15/63] lr: 6.6100e-03 eta: 1 day, 1:24:42 time: 2.2937 data_time: 0.1032 memory: 16201 loss_prob: 1.0692 loss_thr: 0.5738 loss_db: 0.1735 loss: 1.8166 2022/08/30 00:54:04 - mmengine - INFO - Epoch(train) [75][20/63] lr: 6.6100e-03 eta: 1 day, 1:26:50 time: 2.2205 data_time: 0.0966 memory: 16201 loss_prob: 1.1829 loss_thr: 0.5888 loss_db: 0.1954 loss: 1.9670 2022/08/30 00:54:14 - mmengine - INFO - Epoch(train) [75][25/63] lr: 6.6100e-03 eta: 1 day, 1:26:50 time: 2.0979 data_time: 0.0972 memory: 16201 loss_prob: 1.1071 loss_thr: 0.5805 loss_db: 0.1820 loss: 1.8696 2022/08/30 00:54:23 - mmengine - INFO - Epoch(train) [75][30/63] lr: 6.6100e-03 eta: 1 day, 1:28:04 time: 1.8705 data_time: 0.0807 memory: 16201 loss_prob: 1.1680 loss_thr: 0.5809 loss_db: 0.1803 loss: 1.9292 2022/08/30 00:54:33 - mmengine - INFO - Epoch(train) [75][35/63] lr: 6.6100e-03 eta: 1 day, 1:28:04 time: 1.8845 data_time: 0.0667 memory: 16201 loss_prob: 1.1811 loss_thr: 0.5625 loss_db: 0.1827 loss: 1.9264 2022/08/30 00:54:45 - mmengine - INFO - Epoch(train) [75][40/63] lr: 6.6100e-03 eta: 1 day, 1:30:08 time: 2.1990 data_time: 0.0716 memory: 16201 loss_prob: 1.0424 loss_thr: 0.5681 loss_db: 0.1731 loss: 1.7836 2022/08/30 00:54:55 - mmengine - INFO - Epoch(train) [75][45/63] lr: 6.6100e-03 eta: 1 day, 1:30:08 time: 2.2230 data_time: 0.0987 memory: 16201 loss_prob: 1.1141 loss_thr: 0.5918 loss_db: 0.1839 loss: 1.8898 2022/08/30 00:55:06 - mmengine - INFO - Epoch(train) [75][50/63] lr: 6.6100e-03 eta: 1 day, 1:31:55 time: 2.0909 data_time: 0.1220 memory: 16201 loss_prob: 1.1000 loss_thr: 0.5756 loss_db: 0.1839 loss: 1.8596 2022/08/30 00:55:16 - mmengine - INFO - Epoch(train) [75][55/63] lr: 6.6100e-03 eta: 1 day, 1:31:55 time: 2.0678 data_time: 0.1130 memory: 16201 loss_prob: 1.2921 loss_thr: 0.6073 loss_db: 0.2142 loss: 2.1136 2022/08/30 00:55:26 - mmengine - INFO - Epoch(train) [75][60/63] lr: 6.6100e-03 eta: 1 day, 1:33:31 time: 2.0235 data_time: 0.1112 memory: 16201 loss_prob: 1.3405 loss_thr: 0.6038 loss_db: 0.2160 loss: 2.1602 2022/08/30 00:55:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:55:46 - mmengine - INFO - Epoch(train) [76][5/63] lr: 6.6047e-03 eta: 1 day, 1:33:31 time: 2.3040 data_time: 0.3949 memory: 16201 loss_prob: 1.2143 loss_thr: 0.5931 loss_db: 0.2076 loss: 2.0151 2022/08/30 00:55:57 - mmengine - INFO - Epoch(train) [76][10/63] lr: 6.6047e-03 eta: 1 day, 1:35:22 time: 2.5457 data_time: 0.4347 memory: 16201 loss_prob: 1.1582 loss_thr: 0.5899 loss_db: 0.1899 loss: 1.9381 2022/08/30 00:56:06 - mmengine - INFO - Epoch(train) [76][15/63] lr: 6.6047e-03 eta: 1 day, 1:35:22 time: 2.0291 data_time: 0.0916 memory: 16201 loss_prob: 1.0887 loss_thr: 0.5681 loss_db: 0.1802 loss: 1.8370 2022/08/30 00:56:17 - mmengine - INFO - Epoch(train) [76][20/63] lr: 6.6047e-03 eta: 1 day, 1:36:56 time: 2.0144 data_time: 0.0689 memory: 16201 loss_prob: 1.2752 loss_thr: 0.6124 loss_db: 0.2059 loss: 2.0935 2022/08/30 00:56:27 - mmengine - INFO - Epoch(train) [76][25/63] lr: 6.6047e-03 eta: 1 day, 1:36:56 time: 2.1091 data_time: 0.0815 memory: 16201 loss_prob: 1.2578 loss_thr: 0.5998 loss_db: 0.1973 loss: 2.0550 2022/08/30 00:56:39 - mmengine - INFO - Epoch(train) [76][30/63] lr: 6.6047e-03 eta: 1 day, 1:39:04 time: 2.2461 data_time: 0.0870 memory: 16201 loss_prob: 1.0230 loss_thr: 0.5472 loss_db: 0.1634 loss: 1.7337 2022/08/30 00:56:52 - mmengine - INFO - Epoch(train) [76][35/63] lr: 6.6047e-03 eta: 1 day, 1:39:04 time: 2.4627 data_time: 0.1044 memory: 16201 loss_prob: 1.0796 loss_thr: 0.5648 loss_db: 0.1761 loss: 1.8205 2022/08/30 00:57:02 - mmengine - INFO - Epoch(train) [76][40/63] lr: 6.6047e-03 eta: 1 day, 1:41:13 time: 2.2577 data_time: 0.0932 memory: 16201 loss_prob: 1.1152 loss_thr: 0.5861 loss_db: 0.1829 loss: 1.8842 2022/08/30 00:57:13 - mmengine - INFO - Epoch(train) [76][45/63] lr: 6.6047e-03 eta: 1 day, 1:41:13 time: 2.1270 data_time: 0.0746 memory: 16201 loss_prob: 1.0270 loss_thr: 0.5760 loss_db: 0.1665 loss: 1.7695 2022/08/30 00:57:23 - mmengine - INFO - Epoch(train) [76][50/63] lr: 6.6047e-03 eta: 1 day, 1:42:57 time: 2.1008 data_time: 0.0799 memory: 16201 loss_prob: 1.0423 loss_thr: 0.5868 loss_db: 0.1701 loss: 1.7993 2022/08/30 00:57:31 - mmengine - INFO - Epoch(train) [76][55/63] lr: 6.6047e-03 eta: 1 day, 1:42:57 time: 1.8072 data_time: 0.0452 memory: 16201 loss_prob: 1.0679 loss_thr: 0.5866 loss_db: 0.1771 loss: 1.8316 2022/08/30 00:57:40 - mmengine - INFO - Epoch(train) [76][60/63] lr: 6.6047e-03 eta: 1 day, 1:43:46 time: 1.7241 data_time: 0.0421 memory: 16201 loss_prob: 0.9482 loss_thr: 0.5412 loss_db: 0.1598 loss: 1.6491 2022/08/30 00:57:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:57:57 - mmengine - INFO - Epoch(train) [77][5/63] lr: 6.5994e-03 eta: 1 day, 1:43:46 time: 1.9683 data_time: 0.2685 memory: 16201 loss_prob: 1.0205 loss_thr: 0.5310 loss_db: 0.1661 loss: 1.7177 2022/08/30 00:58:06 - mmengine - INFO - Epoch(train) [77][10/63] lr: 6.5994e-03 eta: 1 day, 1:44:23 time: 2.0622 data_time: 0.2985 memory: 16201 loss_prob: 1.0688 loss_thr: 0.5656 loss_db: 0.1769 loss: 1.8114 2022/08/30 00:58:15 - mmengine - INFO - Epoch(train) [77][15/63] lr: 6.5994e-03 eta: 1 day, 1:44:23 time: 1.8120 data_time: 0.0507 memory: 16201 loss_prob: 1.0591 loss_thr: 0.5767 loss_db: 0.1770 loss: 1.8127 2022/08/30 00:58:23 - mmengine - INFO - Epoch(train) [77][20/63] lr: 6.5994e-03 eta: 1 day, 1:45:12 time: 1.7356 data_time: 0.0456 memory: 16201 loss_prob: 1.2321 loss_thr: 0.5981 loss_db: 0.1990 loss: 2.0292 2022/08/30 00:58:32 - mmengine - INFO - Epoch(train) [77][25/63] lr: 6.5994e-03 eta: 1 day, 1:45:12 time: 1.7766 data_time: 0.0456 memory: 16201 loss_prob: 1.2422 loss_thr: 0.5705 loss_db: 0.1991 loss: 2.0118 2022/08/30 00:58:40 - mmengine - INFO - Epoch(train) [77][30/63] lr: 6.5994e-03 eta: 1 day, 1:45:51 time: 1.6592 data_time: 0.0312 memory: 16201 loss_prob: 1.1447 loss_thr: 0.5469 loss_db: 0.1897 loss: 1.8813 2022/08/30 00:58:47 - mmengine - INFO - Epoch(train) [77][35/63] lr: 6.5994e-03 eta: 1 day, 1:45:51 time: 1.4087 data_time: 0.0352 memory: 16201 loss_prob: 1.1472 loss_thr: 0.5744 loss_db: 0.1862 loss: 1.9077 2022/08/30 00:58:55 - mmengine - INFO - Epoch(train) [77][40/63] lr: 6.5994e-03 eta: 1 day, 1:46:02 time: 1.4811 data_time: 0.0396 memory: 16201 loss_prob: 1.0224 loss_thr: 0.5713 loss_db: 0.1676 loss: 1.7613 2022/08/30 00:59:02 - mmengine - INFO - Epoch(train) [77][45/63] lr: 6.5994e-03 eta: 1 day, 1:46:02 time: 1.5768 data_time: 0.0422 memory: 16201 loss_prob: 1.0000 loss_thr: 0.5557 loss_db: 0.1635 loss: 1.7193 2022/08/30 00:59:11 - mmengine - INFO - Epoch(train) [77][50/63] lr: 6.5994e-03 eta: 1 day, 1:46:40 time: 1.6547 data_time: 0.0531 memory: 16201 loss_prob: 1.1725 loss_thr: 0.5650 loss_db: 0.1874 loss: 1.9248 2022/08/30 00:59:20 - mmengine - INFO - Epoch(train) [77][55/63] lr: 6.5994e-03 eta: 1 day, 1:46:40 time: 1.7579 data_time: 0.0465 memory: 16201 loss_prob: 1.1615 loss_thr: 0.5563 loss_db: 0.1840 loss: 1.9018 2022/08/30 00:59:28 - mmengine - INFO - Epoch(train) [77][60/63] lr: 6.5994e-03 eta: 1 day, 1:47:20 time: 1.6751 data_time: 0.0490 memory: 16201 loss_prob: 1.1699 loss_thr: 0.5610 loss_db: 0.1863 loss: 1.9172 2022/08/30 00:59:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 00:59:44 - mmengine - INFO - Epoch(train) [78][5/63] lr: 6.5941e-03 eta: 1 day, 1:47:20 time: 1.9252 data_time: 0.3481 memory: 16201 loss_prob: 1.1286 loss_thr: 0.5873 loss_db: 0.1831 loss: 1.8990 2022/08/30 00:59:54 - mmengine - INFO - Epoch(train) [78][10/63] lr: 6.5941e-03 eta: 1 day, 1:48:10 time: 2.1718 data_time: 0.3848 memory: 16201 loss_prob: 1.1021 loss_thr: 0.5783 loss_db: 0.1778 loss: 1.8582 2022/08/30 01:00:04 - mmengine - INFO - Epoch(train) [78][15/63] lr: 6.5941e-03 eta: 1 day, 1:48:10 time: 2.0048 data_time: 0.0907 memory: 16201 loss_prob: 1.1799 loss_thr: 0.5823 loss_db: 0.1891 loss: 1.9512 2022/08/30 01:00:14 - mmengine - INFO - Epoch(train) [78][20/63] lr: 6.5941e-03 eta: 1 day, 1:49:30 time: 1.9511 data_time: 0.0864 memory: 16201 loss_prob: 1.1419 loss_thr: 0.5821 loss_db: 0.1822 loss: 1.9062 2022/08/30 01:00:23 - mmengine - INFO - Epoch(train) [78][25/63] lr: 6.5941e-03 eta: 1 day, 1:49:30 time: 1.9055 data_time: 0.0892 memory: 16201 loss_prob: 1.1785 loss_thr: 0.5580 loss_db: 0.1954 loss: 1.9320 2022/08/30 01:00:33 - mmengine - INFO - Epoch(train) [78][30/63] lr: 6.5941e-03 eta: 1 day, 1:50:54 time: 1.9867 data_time: 0.0983 memory: 16201 loss_prob: 1.2395 loss_thr: 0.5620 loss_db: 0.1998 loss: 2.0013 2022/08/30 01:00:44 - mmengine - INFO - Epoch(train) [78][35/63] lr: 6.5941e-03 eta: 1 day, 1:50:54 time: 2.0326 data_time: 0.1040 memory: 16201 loss_prob: 1.2095 loss_thr: 0.5929 loss_db: 0.1878 loss: 1.9903 2022/08/30 01:00:54 - mmengine - INFO - Epoch(train) [78][40/63] lr: 6.5941e-03 eta: 1 day, 1:52:36 time: 2.1091 data_time: 0.0936 memory: 16201 loss_prob: 1.1699 loss_thr: 0.5779 loss_db: 0.1873 loss: 1.9352 2022/08/30 01:01:04 - mmengine - INFO - Epoch(train) [78][45/63] lr: 6.5941e-03 eta: 1 day, 1:52:36 time: 2.0306 data_time: 0.1340 memory: 16201 loss_prob: 1.1132 loss_thr: 0.5787 loss_db: 0.1837 loss: 1.8757 2022/08/30 01:01:14 - mmengine - INFO - Epoch(train) [78][50/63] lr: 6.5941e-03 eta: 1 day, 1:54:00 time: 1.9934 data_time: 0.1082 memory: 16201 loss_prob: 1.1328 loss_thr: 0.5778 loss_db: 0.1893 loss: 1.8999 2022/08/30 01:01:22 - mmengine - INFO - Epoch(train) [78][55/63] lr: 6.5941e-03 eta: 1 day, 1:54:00 time: 1.8391 data_time: 0.0965 memory: 16201 loss_prob: 1.2202 loss_thr: 0.6161 loss_db: 0.1995 loss: 2.0358 2022/08/30 01:01:32 - mmengine - INFO - Epoch(train) [78][60/63] lr: 6.5941e-03 eta: 1 day, 1:54:52 time: 1.7707 data_time: 0.1009 memory: 16201 loss_prob: 1.2650 loss_thr: 0.6421 loss_db: 0.2056 loss: 2.1126 2022/08/30 01:01:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:01:49 - mmengine - INFO - Epoch(train) [79][5/63] lr: 6.5888e-03 eta: 1 day, 1:54:52 time: 2.0233 data_time: 0.2971 memory: 16201 loss_prob: 1.0373 loss_thr: 0.5432 loss_db: 0.1673 loss: 1.7477 2022/08/30 01:01:58 - mmengine - INFO - Epoch(train) [79][10/63] lr: 6.5888e-03 eta: 1 day, 1:55:08 time: 1.9474 data_time: 0.3249 memory: 16201 loss_prob: 1.0529 loss_thr: 0.5657 loss_db: 0.1768 loss: 1.7954 2022/08/30 01:02:06 - mmengine - INFO - Epoch(train) [79][15/63] lr: 6.5888e-03 eta: 1 day, 1:55:08 time: 1.7417 data_time: 0.0992 memory: 16201 loss_prob: 1.0593 loss_thr: 0.5889 loss_db: 0.1795 loss: 1.8276 2022/08/30 01:02:16 - mmengine - INFO - Epoch(train) [79][20/63] lr: 6.5888e-03 eta: 1 day, 1:56:12 time: 1.8601 data_time: 0.0478 memory: 16201 loss_prob: 1.0849 loss_thr: 0.5940 loss_db: 0.1795 loss: 1.8584 2022/08/30 01:02:24 - mmengine - INFO - Epoch(train) [79][25/63] lr: 6.5888e-03 eta: 1 day, 1:56:12 time: 1.8415 data_time: 0.0681 memory: 16201 loss_prob: 1.0643 loss_thr: 0.5687 loss_db: 0.1737 loss: 1.8067 2022/08/30 01:02:34 - mmengine - INFO - Epoch(train) [79][30/63] lr: 6.5888e-03 eta: 1 day, 1:57:07 time: 1.8012 data_time: 0.0499 memory: 16201 loss_prob: 1.0089 loss_thr: 0.5696 loss_db: 0.1655 loss: 1.7441 2022/08/30 01:02:44 - mmengine - INFO - Epoch(train) [79][35/63] lr: 6.5888e-03 eta: 1 day, 1:57:07 time: 1.9315 data_time: 0.0366 memory: 16201 loss_prob: 1.0221 loss_thr: 0.5757 loss_db: 0.1699 loss: 1.7678 2022/08/30 01:02:53 - mmengine - INFO - Epoch(train) [79][40/63] lr: 6.5888e-03 eta: 1 day, 1:58:14 time: 1.8840 data_time: 0.0421 memory: 16201 loss_prob: 1.0532 loss_thr: 0.5577 loss_db: 0.1756 loss: 1.7865 2022/08/30 01:03:02 - mmengine - INFO - Epoch(train) [79][45/63] lr: 6.5888e-03 eta: 1 day, 1:58:14 time: 1.8639 data_time: 0.0344 memory: 16201 loss_prob: 1.0298 loss_thr: 0.5430 loss_db: 0.1717 loss: 1.7445 2022/08/30 01:03:10 - mmengine - INFO - Epoch(train) [79][50/63] lr: 6.5888e-03 eta: 1 day, 1:58:59 time: 1.7309 data_time: 0.0473 memory: 16201 loss_prob: 0.9728 loss_thr: 0.5374 loss_db: 0.1618 loss: 1.6721 2022/08/30 01:03:18 - mmengine - INFO - Epoch(train) [79][55/63] lr: 6.5888e-03 eta: 1 day, 1:58:59 time: 1.5878 data_time: 0.0471 memory: 16201 loss_prob: 1.0488 loss_thr: 0.5621 loss_db: 0.1692 loss: 1.7801 2022/08/30 01:03:25 - mmengine - INFO - Epoch(train) [79][60/63] lr: 6.5888e-03 eta: 1 day, 1:59:12 time: 1.5088 data_time: 0.0438 memory: 16201 loss_prob: 1.1486 loss_thr: 0.5893 loss_db: 0.1823 loss: 1.9202 2022/08/30 01:03:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:03:40 - mmengine - INFO - Epoch(train) [80][5/63] lr: 6.5835e-03 eta: 1 day, 1:59:12 time: 1.7153 data_time: 0.2694 memory: 16201 loss_prob: 1.0775 loss_thr: 0.5695 loss_db: 0.1738 loss: 1.8208 2022/08/30 01:03:49 - mmengine - INFO - Epoch(train) [80][10/63] lr: 6.5835e-03 eta: 1 day, 1:59:34 time: 1.9967 data_time: 0.2804 memory: 16201 loss_prob: 1.0246 loss_thr: 0.5532 loss_db: 0.1681 loss: 1.7459 2022/08/30 01:03:57 - mmengine - INFO - Epoch(train) [80][15/63] lr: 6.5835e-03 eta: 1 day, 1:59:34 time: 1.6682 data_time: 0.0386 memory: 16201 loss_prob: 0.9948 loss_thr: 0.5498 loss_db: 0.1674 loss: 1.7120 2022/08/30 01:04:07 - mmengine - INFO - Epoch(train) [80][20/63] lr: 6.5835e-03 eta: 1 day, 2:00:20 time: 1.7494 data_time: 0.0492 memory: 16201 loss_prob: 0.9935 loss_thr: 0.5584 loss_db: 0.1658 loss: 1.7178 2022/08/30 01:04:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:04:15 - mmengine - INFO - Epoch(train) [80][25/63] lr: 6.5835e-03 eta: 1 day, 2:00:20 time: 1.8617 data_time: 0.0484 memory: 16201 loss_prob: 1.0870 loss_thr: 0.5803 loss_db: 0.1775 loss: 1.8448 2022/08/30 01:04:24 - mmengine - INFO - Epoch(train) [80][30/63] lr: 6.5835e-03 eta: 1 day, 2:01:10 time: 1.7695 data_time: 0.0369 memory: 16201 loss_prob: 1.1636 loss_thr: 0.5802 loss_db: 0.1887 loss: 1.9325 2022/08/30 01:04:35 - mmengine - INFO - Epoch(train) [80][35/63] lr: 6.5835e-03 eta: 1 day, 2:01:10 time: 1.9328 data_time: 0.0567 memory: 16201 loss_prob: 1.0855 loss_thr: 0.5708 loss_db: 0.1757 loss: 1.8321 2022/08/30 01:04:43 - mmengine - INFO - Epoch(train) [80][40/63] lr: 6.5835e-03 eta: 1 day, 2:02:21 time: 1.9273 data_time: 0.0484 memory: 16201 loss_prob: 1.0290 loss_thr: 0.5691 loss_db: 0.1668 loss: 1.7649 2022/08/30 01:04:53 - mmengine - INFO - Epoch(train) [80][45/63] lr: 6.5835e-03 eta: 1 day, 2:02:21 time: 1.8536 data_time: 0.0435 memory: 16201 loss_prob: 1.0071 loss_thr: 0.5730 loss_db: 0.1627 loss: 1.7427 2022/08/30 01:05:02 - mmengine - INFO - Epoch(train) [80][50/63] lr: 6.5835e-03 eta: 1 day, 2:03:20 time: 1.8412 data_time: 0.0523 memory: 16201 loss_prob: 1.0336 loss_thr: 0.5777 loss_db: 0.1717 loss: 1.7830 2022/08/30 01:05:11 - mmengine - INFO - Epoch(train) [80][55/63] lr: 6.5835e-03 eta: 1 day, 2:03:20 time: 1.8124 data_time: 0.0361 memory: 16201 loss_prob: 1.0501 loss_thr: 0.5490 loss_db: 0.1738 loss: 1.7729 2022/08/30 01:05:20 - mmengine - INFO - Epoch(train) [80][60/63] lr: 6.5835e-03 eta: 1 day, 2:04:08 time: 1.7715 data_time: 0.0392 memory: 16201 loss_prob: 1.0926 loss_thr: 0.5650 loss_db: 0.1800 loss: 1.8376 2022/08/30 01:05:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:05:24 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/08/30 01:05:34 - mmengine - INFO - Epoch(val) [80][5/32] eta: 1 day, 2:04:08 time: 0.7534 data_time: 0.1612 memory: 16201 2022/08/30 01:05:37 - mmengine - INFO - Epoch(val) [80][10/32] eta: 0:00:18 time: 0.8501 data_time: 0.2045 memory: 15734 2022/08/30 01:05:40 - mmengine - INFO - Epoch(val) [80][15/32] eta: 0:00:18 time: 0.6679 data_time: 0.0631 memory: 15734 2022/08/30 01:05:44 - mmengine - INFO - Epoch(val) [80][20/32] eta: 0:00:08 time: 0.6928 data_time: 0.0796 memory: 15734 2022/08/30 01:05:48 - mmengine - INFO - Epoch(val) [80][25/32] eta: 0:00:08 time: 0.7959 data_time: 0.0877 memory: 15734 2022/08/30 01:05:51 - mmengine - INFO - Epoch(val) [80][30/32] eta: 0:00:01 time: 0.7439 data_time: 0.0434 memory: 15734 2022/08/30 01:05:52 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 01:05:52 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8267, precision: 0.7127, hmean: 0.7655 2022/08/30 01:05:52 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8267, precision: 0.7934, hmean: 0.8097 2022/08/30 01:05:52 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8185, precision: 0.8466, hmean: 0.8323 2022/08/30 01:05:52 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7939, precision: 0.8866, hmean: 0.8377 2022/08/30 01:05:52 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7130, precision: 0.9320, hmean: 0.8080 2022/08/30 01:05:52 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3356, precision: 0.9667, hmean: 0.4982 2022/08/30 01:05:52 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0010, precision: 1.0000, hmean: 0.0019 2022/08/30 01:05:52 - mmengine - INFO - Epoch(val) [80][32/32] icdar/precision: 0.8866 icdar/recall: 0.7939 icdar/hmean: 0.8377 2022/08/30 01:06:04 - mmengine - INFO - Epoch(train) [81][5/63] lr: 6.5782e-03 eta: 0:00:01 time: 1.8780 data_time: 0.2541 memory: 16201 loss_prob: 1.0494 loss_thr: 0.5506 loss_db: 0.1757 loss: 1.7758 2022/08/30 01:06:14 - mmengine - INFO - Epoch(train) [81][10/63] lr: 6.5782e-03 eta: 1 day, 2:04:51 time: 2.1556 data_time: 0.2640 memory: 16201 loss_prob: 1.0710 loss_thr: 0.5644 loss_db: 0.1797 loss: 1.8151 2022/08/30 01:06:23 - mmengine - INFO - Epoch(train) [81][15/63] lr: 6.5782e-03 eta: 1 day, 2:04:51 time: 1.9250 data_time: 0.0446 memory: 16201 loss_prob: 1.0901 loss_thr: 0.5750 loss_db: 0.1769 loss: 1.8420 2022/08/30 01:06:32 - mmengine - INFO - Epoch(train) [81][20/63] lr: 6.5782e-03 eta: 1 day, 2:05:46 time: 1.8221 data_time: 0.0574 memory: 16201 loss_prob: 0.9824 loss_thr: 0.5349 loss_db: 0.1595 loss: 1.6768 2022/08/30 01:06:40 - mmengine - INFO - Epoch(train) [81][25/63] lr: 6.5782e-03 eta: 1 day, 2:05:46 time: 1.6500 data_time: 0.0483 memory: 16201 loss_prob: 0.9930 loss_thr: 0.5314 loss_db: 0.1606 loss: 1.6850 2022/08/30 01:06:49 - mmengine - INFO - Epoch(train) [81][30/63] lr: 6.5782e-03 eta: 1 day, 2:06:25 time: 1.7080 data_time: 0.0473 memory: 16201 loss_prob: 0.9902 loss_thr: 0.5453 loss_db: 0.1614 loss: 1.6969 2022/08/30 01:06:58 - mmengine - INFO - Epoch(train) [81][35/63] lr: 6.5782e-03 eta: 1 day, 2:06:25 time: 1.8393 data_time: 0.0539 memory: 16201 loss_prob: 0.9677 loss_thr: 0.5293 loss_db: 0.1585 loss: 1.6555 2022/08/30 01:07:08 - mmengine - INFO - Epoch(train) [81][40/63] lr: 6.5782e-03 eta: 1 day, 2:07:21 time: 1.8332 data_time: 0.0376 memory: 16201 loss_prob: 0.9618 loss_thr: 0.5234 loss_db: 0.1580 loss: 1.6432 2022/08/30 01:07:17 - mmengine - INFO - Epoch(train) [81][45/63] lr: 6.5782e-03 eta: 1 day, 2:07:21 time: 1.8362 data_time: 0.0412 memory: 16201 loss_prob: 1.0309 loss_thr: 0.5534 loss_db: 0.1676 loss: 1.7520 2022/08/30 01:07:26 - mmengine - INFO - Epoch(train) [81][50/63] lr: 6.5782e-03 eta: 1 day, 2:08:12 time: 1.7972 data_time: 0.0494 memory: 16201 loss_prob: 1.0799 loss_thr: 0.5688 loss_db: 0.1738 loss: 1.8225 2022/08/30 01:07:35 - mmengine - INFO - Epoch(train) [81][55/63] lr: 6.5782e-03 eta: 1 day, 2:08:12 time: 1.8251 data_time: 0.0432 memory: 16201 loss_prob: 1.0330 loss_thr: 0.5516 loss_db: 0.1698 loss: 1.7544 2022/08/30 01:07:43 - mmengine - INFO - Epoch(train) [81][60/63] lr: 6.5782e-03 eta: 1 day, 2:08:57 time: 1.7563 data_time: 0.0483 memory: 16201 loss_prob: 1.0880 loss_thr: 0.5788 loss_db: 0.1781 loss: 1.8449 2022/08/30 01:07:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:07:59 - mmengine - INFO - Epoch(train) [82][5/63] lr: 6.5729e-03 eta: 1 day, 2:08:57 time: 1.8344 data_time: 0.2418 memory: 16201 loss_prob: 1.1133 loss_thr: 0.5748 loss_db: 0.1826 loss: 1.8707 2022/08/30 01:08:07 - mmengine - INFO - Epoch(train) [82][10/63] lr: 6.5729e-03 eta: 1 day, 2:09:03 time: 1.9057 data_time: 0.2618 memory: 16201 loss_prob: 1.0384 loss_thr: 0.5417 loss_db: 0.1724 loss: 1.7525 2022/08/30 01:08:16 - mmengine - INFO - Epoch(train) [82][15/63] lr: 6.5729e-03 eta: 1 day, 2:09:03 time: 1.7823 data_time: 0.0367 memory: 16201 loss_prob: 1.1568 loss_thr: 0.5756 loss_db: 0.1866 loss: 1.9190 2022/08/30 01:08:26 - mmengine - INFO - Epoch(train) [82][20/63] lr: 6.5729e-03 eta: 1 day, 2:10:12 time: 1.9357 data_time: 0.0435 memory: 16201 loss_prob: 1.1506 loss_thr: 0.5733 loss_db: 0.1834 loss: 1.9073 2022/08/30 01:08:35 - mmengine - INFO - Epoch(train) [82][25/63] lr: 6.5729e-03 eta: 1 day, 2:10:12 time: 1.9054 data_time: 0.0578 memory: 16201 loss_prob: 1.1288 loss_thr: 0.5696 loss_db: 0.1818 loss: 1.8802 2022/08/30 01:08:44 - mmengine - INFO - Epoch(train) [82][30/63] lr: 6.5729e-03 eta: 1 day, 2:11:04 time: 1.8107 data_time: 0.0345 memory: 16201 loss_prob: 1.0951 loss_thr: 0.5721 loss_db: 0.1818 loss: 1.8491 2022/08/30 01:08:54 - mmengine - INFO - Epoch(train) [82][35/63] lr: 6.5729e-03 eta: 1 day, 2:11:04 time: 1.9107 data_time: 0.0362 memory: 16201 loss_prob: 0.9736 loss_thr: 0.5349 loss_db: 0.1618 loss: 1.6703 2022/08/30 01:09:04 - mmengine - INFO - Epoch(train) [82][40/63] lr: 6.5729e-03 eta: 1 day, 2:12:18 time: 1.9783 data_time: 0.0424 memory: 16201 loss_prob: 0.9580 loss_thr: 0.5260 loss_db: 0.1553 loss: 1.6393 2022/08/30 01:09:14 - mmengine - INFO - Epoch(train) [82][45/63] lr: 6.5729e-03 eta: 1 day, 2:12:18 time: 1.9543 data_time: 0.0383 memory: 16201 loss_prob: 1.0958 loss_thr: 0.5576 loss_db: 0.1751 loss: 1.8285 2022/08/30 01:09:22 - mmengine - INFO - Epoch(train) [82][50/63] lr: 6.5729e-03 eta: 1 day, 2:13:07 time: 1.7942 data_time: 0.0451 memory: 16201 loss_prob: 1.1566 loss_thr: 0.6003 loss_db: 0.1868 loss: 1.9437 2022/08/30 01:09:32 - mmengine - INFO - Epoch(train) [82][55/63] lr: 6.5729e-03 eta: 1 day, 2:13:07 time: 1.7329 data_time: 0.0362 memory: 16201 loss_prob: 1.0843 loss_thr: 0.5928 loss_db: 0.1792 loss: 1.8563 2022/08/30 01:09:41 - mmengine - INFO - Epoch(train) [82][60/63] lr: 6.5729e-03 eta: 1 day, 2:14:11 time: 1.9090 data_time: 0.0578 memory: 16201 loss_prob: 1.0763 loss_thr: 0.5744 loss_db: 0.1760 loss: 1.8267 2022/08/30 01:09:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:09:57 - mmengine - INFO - Epoch(train) [83][5/63] lr: 6.5676e-03 eta: 1 day, 2:14:11 time: 2.0155 data_time: 0.2475 memory: 16201 loss_prob: 1.0236 loss_thr: 0.5730 loss_db: 0.1700 loss: 1.7666 2022/08/30 01:10:07 - mmengine - INFO - Epoch(train) [83][10/63] lr: 6.5676e-03 eta: 1 day, 2:14:44 time: 2.1132 data_time: 0.2809 memory: 16201 loss_prob: 1.0505 loss_thr: 0.5642 loss_db: 0.1706 loss: 1.7853 2022/08/30 01:10:15 - mmengine - INFO - Epoch(train) [83][15/63] lr: 6.5676e-03 eta: 1 day, 2:14:44 time: 1.7594 data_time: 0.0482 memory: 16201 loss_prob: 0.9980 loss_thr: 0.5404 loss_db: 0.1593 loss: 1.6977 2022/08/30 01:10:24 - mmengine - INFO - Epoch(train) [83][20/63] lr: 6.5676e-03 eta: 1 day, 2:15:31 time: 1.7853 data_time: 0.0608 memory: 16201 loss_prob: 0.9737 loss_thr: 0.5345 loss_db: 0.1572 loss: 1.6654 2022/08/30 01:10:34 - mmengine - INFO - Epoch(train) [83][25/63] lr: 6.5676e-03 eta: 1 day, 2:15:31 time: 1.9329 data_time: 0.0680 memory: 16201 loss_prob: 1.0654 loss_thr: 0.5489 loss_db: 0.1705 loss: 1.7847 2022/08/30 01:10:43 - mmengine - INFO - Epoch(train) [83][30/63] lr: 6.5676e-03 eta: 1 day, 2:16:26 time: 1.8454 data_time: 0.0436 memory: 16201 loss_prob: 1.1226 loss_thr: 0.5500 loss_db: 0.1773 loss: 1.8499 2022/08/30 01:10:53 - mmengine - INFO - Epoch(train) [83][35/63] lr: 6.5676e-03 eta: 1 day, 2:16:26 time: 1.8634 data_time: 0.0459 memory: 16201 loss_prob: 1.0854 loss_thr: 0.5499 loss_db: 0.1701 loss: 1.8055 2022/08/30 01:11:02 - mmengine - INFO - Epoch(train) [83][40/63] lr: 6.5676e-03 eta: 1 day, 2:17:23 time: 1.8652 data_time: 0.0443 memory: 16201 loss_prob: 1.0713 loss_thr: 0.5587 loss_db: 0.1718 loss: 1.8018 2022/08/30 01:11:11 - mmengine - INFO - Epoch(train) [83][45/63] lr: 6.5676e-03 eta: 1 day, 2:17:23 time: 1.7970 data_time: 0.0520 memory: 16201 loss_prob: 1.0579 loss_thr: 0.5584 loss_db: 0.1750 loss: 1.7914 2022/08/30 01:11:22 - mmengine - INFO - Epoch(train) [83][50/63] lr: 6.5676e-03 eta: 1 day, 2:18:43 time: 2.0353 data_time: 0.0562 memory: 16201 loss_prob: 1.0558 loss_thr: 0.5746 loss_db: 0.1785 loss: 1.8089 2022/08/30 01:11:31 - mmengine - INFO - Epoch(train) [83][55/63] lr: 6.5676e-03 eta: 1 day, 2:18:43 time: 2.0371 data_time: 0.0506 memory: 16201 loss_prob: 1.0743 loss_thr: 0.5843 loss_db: 0.1837 loss: 1.8423 2022/08/30 01:11:41 - mmengine - INFO - Epoch(train) [83][60/63] lr: 6.5676e-03 eta: 1 day, 2:19:50 time: 1.9445 data_time: 0.0858 memory: 16201 loss_prob: 1.1281 loss_thr: 0.5912 loss_db: 0.1865 loss: 1.9058 2022/08/30 01:11:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:11:57 - mmengine - INFO - Epoch(train) [84][5/63] lr: 6.5623e-03 eta: 1 day, 2:19:50 time: 1.8973 data_time: 0.2451 memory: 16201 loss_prob: 0.9793 loss_thr: 0.5899 loss_db: 0.1614 loss: 1.7306 2022/08/30 01:12:06 - mmengine - INFO - Epoch(train) [84][10/63] lr: 6.5623e-03 eta: 1 day, 2:20:13 time: 2.0584 data_time: 0.2640 memory: 16201 loss_prob: 1.0788 loss_thr: 0.5678 loss_db: 0.1808 loss: 1.8274 2022/08/30 01:12:15 - mmengine - INFO - Epoch(train) [84][15/63] lr: 6.5623e-03 eta: 1 day, 2:20:13 time: 1.7732 data_time: 0.0479 memory: 16201 loss_prob: 1.1746 loss_thr: 0.5514 loss_db: 0.1968 loss: 1.9228 2022/08/30 01:12:22 - mmengine - INFO - Epoch(train) [84][20/63] lr: 6.5623e-03 eta: 1 day, 2:20:31 time: 1.5782 data_time: 0.0403 memory: 16201 loss_prob: 1.2229 loss_thr: 0.5826 loss_db: 0.2032 loss: 2.0087 2022/08/30 01:12:31 - mmengine - INFO - Epoch(train) [84][25/63] lr: 6.5623e-03 eta: 1 day, 2:20:31 time: 1.5884 data_time: 0.0455 memory: 16201 loss_prob: 1.2529 loss_thr: 0.6034 loss_db: 0.2055 loss: 2.0617 2022/08/30 01:12:39 - mmengine - INFO - Epoch(train) [84][30/63] lr: 6.5623e-03 eta: 1 day, 2:21:06 time: 1.7124 data_time: 0.0461 memory: 16201 loss_prob: 1.1667 loss_thr: 0.5838 loss_db: 0.1902 loss: 1.9407 2022/08/30 01:12:48 - mmengine - INFO - Epoch(train) [84][35/63] lr: 6.5623e-03 eta: 1 day, 2:21:06 time: 1.7095 data_time: 0.0478 memory: 16201 loss_prob: 1.2521 loss_thr: 0.5729 loss_db: 0.2020 loss: 2.0269 2022/08/30 01:12:56 - mmengine - INFO - Epoch(train) [84][40/63] lr: 6.5623e-03 eta: 1 day, 2:21:40 time: 1.7049 data_time: 0.0413 memory: 16201 loss_prob: 1.3401 loss_thr: 0.6039 loss_db: 0.2106 loss: 2.1547 2022/08/30 01:13:05 - mmengine - INFO - Epoch(train) [84][45/63] lr: 6.5623e-03 eta: 1 day, 2:21:40 time: 1.7345 data_time: 0.0421 memory: 16201 loss_prob: 1.3781 loss_thr: 0.6044 loss_db: 0.2146 loss: 2.1971 2022/08/30 01:13:14 - mmengine - INFO - Epoch(train) [84][50/63] lr: 6.5623e-03 eta: 1 day, 2:22:16 time: 1.7209 data_time: 0.0560 memory: 16201 loss_prob: 1.3196 loss_thr: 0.5857 loss_db: 0.2079 loss: 2.1132 2022/08/30 01:13:20 - mmengine - INFO - Epoch(train) [84][55/63] lr: 6.5623e-03 eta: 1 day, 2:22:16 time: 1.5309 data_time: 0.0428 memory: 16201 loss_prob: 1.0943 loss_thr: 0.5822 loss_db: 0.1774 loss: 1.8540 2022/08/30 01:13:29 - mmengine - INFO - Epoch(train) [84][60/63] lr: 6.5623e-03 eta: 1 day, 2:22:29 time: 1.5451 data_time: 0.0337 memory: 16201 loss_prob: 1.1246 loss_thr: 0.5886 loss_db: 0.1805 loss: 1.8937 2022/08/30 01:13:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:13:44 - mmengine - INFO - Epoch(train) [85][5/63] lr: 6.5571e-03 eta: 1 day, 2:22:29 time: 1.7380 data_time: 0.2420 memory: 16201 loss_prob: 1.1270 loss_thr: 0.5365 loss_db: 0.1762 loss: 1.8396 2022/08/30 01:13:55 - mmengine - INFO - Epoch(train) [85][10/63] lr: 6.5571e-03 eta: 1 day, 2:22:59 time: 2.1190 data_time: 0.2623 memory: 16201 loss_prob: 1.0372 loss_thr: 0.5180 loss_db: 0.1587 loss: 1.7139 2022/08/30 01:14:04 - mmengine - INFO - Epoch(train) [85][15/63] lr: 6.5571e-03 eta: 1 day, 2:22:59 time: 2.0249 data_time: 0.0519 memory: 16201 loss_prob: 1.1022 loss_thr: 0.5776 loss_db: 0.1800 loss: 1.8598 2022/08/30 01:14:13 - mmengine - INFO - Epoch(train) [85][20/63] lr: 6.5571e-03 eta: 1 day, 2:23:44 time: 1.7888 data_time: 0.0441 memory: 16201 loss_prob: 1.0306 loss_thr: 0.5676 loss_db: 0.1737 loss: 1.7719 2022/08/30 01:14:21 - mmengine - INFO - Epoch(train) [85][25/63] lr: 6.5571e-03 eta: 1 day, 2:23:44 time: 1.6889 data_time: 0.0497 memory: 16201 loss_prob: 1.0975 loss_thr: 0.5659 loss_db: 0.1806 loss: 1.8440 2022/08/30 01:14:31 - mmengine - INFO - Epoch(train) [85][30/63] lr: 6.5571e-03 eta: 1 day, 2:24:31 time: 1.8122 data_time: 0.0401 memory: 16201 loss_prob: 1.1926 loss_thr: 0.6031 loss_db: 0.1940 loss: 1.9897 2022/08/30 01:14:39 - mmengine - INFO - Epoch(train) [85][35/63] lr: 6.5571e-03 eta: 1 day, 2:24:31 time: 1.8213 data_time: 0.0532 memory: 16201 loss_prob: 1.2053 loss_thr: 0.6064 loss_db: 0.1966 loss: 2.0083 2022/08/30 01:14:48 - mmengine - INFO - Epoch(train) [85][40/63] lr: 6.5571e-03 eta: 1 day, 2:25:02 time: 1.6909 data_time: 0.0548 memory: 16201 loss_prob: 1.2483 loss_thr: 0.5882 loss_db: 0.1980 loss: 2.0344 2022/08/30 01:14:55 - mmengine - INFO - Epoch(train) [85][45/63] lr: 6.5571e-03 eta: 1 day, 2:25:02 time: 1.6371 data_time: 0.0447 memory: 16201 loss_prob: 1.1817 loss_thr: 0.5739 loss_db: 0.1878 loss: 1.9434 2022/08/30 01:15:04 - mmengine - INFO - Epoch(train) [85][50/63] lr: 6.5571e-03 eta: 1 day, 2:25:22 time: 1.6064 data_time: 0.0524 memory: 16201 loss_prob: 1.1505 loss_thr: 0.5811 loss_db: 0.1883 loss: 1.9200 2022/08/30 01:15:12 - mmengine - INFO - Epoch(train) [85][55/63] lr: 6.5571e-03 eta: 1 day, 2:25:22 time: 1.6078 data_time: 0.0446 memory: 16201 loss_prob: 1.0965 loss_thr: 0.5661 loss_db: 0.1812 loss: 1.8438 2022/08/30 01:15:19 - mmengine - INFO - Epoch(train) [85][60/63] lr: 6.5571e-03 eta: 1 day, 2:25:33 time: 1.5446 data_time: 0.0414 memory: 16201 loss_prob: 1.0507 loss_thr: 0.5736 loss_db: 0.1705 loss: 1.7948 2022/08/30 01:15:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:15:35 - mmengine - INFO - Epoch(train) [86][5/63] lr: 6.5518e-03 eta: 1 day, 2:25:33 time: 1.9029 data_time: 0.2688 memory: 16201 loss_prob: 1.0110 loss_thr: 0.5438 loss_db: 0.1670 loss: 1.7218 2022/08/30 01:15:44 - mmengine - INFO - Epoch(train) [86][10/63] lr: 6.5518e-03 eta: 1 day, 2:25:55 time: 2.0594 data_time: 0.2727 memory: 16201 loss_prob: 1.1375 loss_thr: 0.5692 loss_db: 0.1852 loss: 1.8919 2022/08/30 01:15:52 - mmengine - INFO - Epoch(train) [86][15/63] lr: 6.5518e-03 eta: 1 day, 2:25:55 time: 1.6514 data_time: 0.0399 memory: 16201 loss_prob: 1.1503 loss_thr: 0.5670 loss_db: 0.1867 loss: 1.9040 2022/08/30 01:16:02 - mmengine - INFO - Epoch(train) [86][20/63] lr: 6.5518e-03 eta: 1 day, 2:26:39 time: 1.7982 data_time: 0.0439 memory: 16201 loss_prob: 1.0564 loss_thr: 0.5536 loss_db: 0.1746 loss: 1.7846 2022/08/30 01:16:11 - mmengine - INFO - Epoch(train) [86][25/63] lr: 6.5518e-03 eta: 1 day, 2:26:39 time: 1.9525 data_time: 0.0429 memory: 16201 loss_prob: 1.3227 loss_thr: 0.6055 loss_db: 0.2107 loss: 2.1389 2022/08/30 01:16:20 - mmengine - INFO - Epoch(train) [86][30/63] lr: 6.5518e-03 eta: 1 day, 2:27:34 time: 1.8823 data_time: 0.0398 memory: 16201 loss_prob: 1.2282 loss_thr: 0.5851 loss_db: 0.1959 loss: 2.0092 2022/08/30 01:16:29 - mmengine - INFO - Epoch(train) [86][35/63] lr: 6.5518e-03 eta: 1 day, 2:27:34 time: 1.7429 data_time: 0.0549 memory: 16201 loss_prob: 0.9520 loss_thr: 0.5451 loss_db: 0.1583 loss: 1.6555 2022/08/30 01:16:38 - mmengine - INFO - Epoch(train) [86][40/63] lr: 6.5518e-03 eta: 1 day, 2:28:09 time: 1.7247 data_time: 0.0399 memory: 16201 loss_prob: 1.0308 loss_thr: 0.5592 loss_db: 0.1699 loss: 1.7598 2022/08/30 01:16:47 - mmengine - INFO - Epoch(train) [86][45/63] lr: 6.5518e-03 eta: 1 day, 2:28:09 time: 1.8042 data_time: 0.0414 memory: 16201 loss_prob: 0.9934 loss_thr: 0.5378 loss_db: 0.1604 loss: 1.6916 2022/08/30 01:16:54 - mmengine - INFO - Epoch(train) [86][50/63] lr: 6.5518e-03 eta: 1 day, 2:28:32 time: 1.6400 data_time: 0.0556 memory: 16201 loss_prob: 0.9787 loss_thr: 0.5417 loss_db: 0.1564 loss: 1.6768 2022/08/30 01:17:01 - mmengine - INFO - Epoch(train) [86][55/63] lr: 6.5518e-03 eta: 1 day, 2:28:32 time: 1.4057 data_time: 0.0331 memory: 16201 loss_prob: 1.0015 loss_thr: 0.5510 loss_db: 0.1628 loss: 1.7153 2022/08/30 01:17:09 - mmengine - INFO - Epoch(train) [86][60/63] lr: 6.5518e-03 eta: 1 day, 2:28:35 time: 1.4872 data_time: 0.0347 memory: 16201 loss_prob: 0.9673 loss_thr: 0.5263 loss_db: 0.1580 loss: 1.6517 2022/08/30 01:17:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:17:22 - mmengine - INFO - Epoch(train) [87][5/63] lr: 6.5465e-03 eta: 1 day, 2:28:35 time: 1.6340 data_time: 0.2525 memory: 16201 loss_prob: 1.1542 loss_thr: 0.5768 loss_db: 0.1953 loss: 1.9263 2022/08/30 01:17:32 - mmengine - INFO - Epoch(train) [87][10/63] lr: 6.5465e-03 eta: 1 day, 2:28:46 time: 1.9862 data_time: 0.2648 memory: 16201 loss_prob: 1.0916 loss_thr: 0.5427 loss_db: 0.1825 loss: 1.8168 2022/08/30 01:17:41 - mmengine - INFO - Epoch(train) [87][15/63] lr: 6.5465e-03 eta: 1 day, 2:28:46 time: 1.8481 data_time: 0.0457 memory: 16201 loss_prob: 1.0285 loss_thr: 0.5398 loss_db: 0.1702 loss: 1.7385 2022/08/30 01:17:48 - mmengine - INFO - Epoch(train) [87][20/63] lr: 6.5465e-03 eta: 1 day, 2:29:04 time: 1.6034 data_time: 0.0560 memory: 16201 loss_prob: 1.0927 loss_thr: 0.5701 loss_db: 0.1777 loss: 1.8405 2022/08/30 01:17:56 - mmengine - INFO - Epoch(train) [87][25/63] lr: 6.5465e-03 eta: 1 day, 2:29:04 time: 1.5202 data_time: 0.0556 memory: 16201 loss_prob: 1.0738 loss_thr: 0.5691 loss_db: 0.1722 loss: 1.8152 2022/08/30 01:18:04 - mmengine - INFO - Epoch(train) [87][30/63] lr: 6.5465e-03 eta: 1 day, 2:29:20 time: 1.5938 data_time: 0.0428 memory: 16201 loss_prob: 1.0639 loss_thr: 0.5692 loss_db: 0.1712 loss: 1.8042 2022/08/30 01:18:13 - mmengine - INFO - Epoch(train) [87][35/63] lr: 6.5465e-03 eta: 1 day, 2:29:20 time: 1.7327 data_time: 0.0359 memory: 16201 loss_prob: 1.0902 loss_thr: 0.5631 loss_db: 0.1751 loss: 1.8284 2022/08/30 01:18:22 - mmengine - INFO - Epoch(train) [87][40/63] lr: 6.5465e-03 eta: 1 day, 2:30:05 time: 1.8150 data_time: 0.0361 memory: 16201 loss_prob: 1.1299 loss_thr: 0.5579 loss_db: 0.1854 loss: 1.8732 2022/08/30 01:18:31 - mmengine - INFO - Epoch(train) [87][45/63] lr: 6.5465e-03 eta: 1 day, 2:30:05 time: 1.7701 data_time: 0.0491 memory: 16201 loss_prob: 1.2739 loss_thr: 0.5630 loss_db: 0.2045 loss: 2.0414 2022/08/30 01:18:39 - mmengine - INFO - Epoch(train) [87][50/63] lr: 6.5465e-03 eta: 1 day, 2:30:37 time: 1.7145 data_time: 0.0570 memory: 16201 loss_prob: 1.2711 loss_thr: 0.5600 loss_db: 0.2016 loss: 2.0326 2022/08/30 01:18:49 - mmengine - INFO - Epoch(train) [87][55/63] lr: 6.5465e-03 eta: 1 day, 2:30:37 time: 1.7620 data_time: 0.0437 memory: 16201 loss_prob: 1.1407 loss_thr: 0.5744 loss_db: 0.1854 loss: 1.9005 2022/08/30 01:18:58 - mmengine - INFO - Epoch(train) [87][60/63] lr: 6.5465e-03 eta: 1 day, 2:31:23 time: 1.8210 data_time: 0.0527 memory: 16201 loss_prob: 1.0333 loss_thr: 0.5729 loss_db: 0.1734 loss: 1.7796 2022/08/30 01:19:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:19:13 - mmengine - INFO - Epoch(train) [88][5/63] lr: 6.5412e-03 eta: 1 day, 2:31:23 time: 1.8818 data_time: 0.2541 memory: 16201 loss_prob: 1.1119 loss_thr: 0.5961 loss_db: 0.1811 loss: 1.8892 2022/08/30 01:19:21 - mmengine - INFO - Epoch(train) [88][10/63] lr: 6.5412e-03 eta: 1 day, 2:31:12 time: 1.8261 data_time: 0.2772 memory: 16201 loss_prob: 0.9847 loss_thr: 0.5465 loss_db: 0.1594 loss: 1.6907 2022/08/30 01:19:30 - mmengine - INFO - Epoch(train) [88][15/63] lr: 6.5412e-03 eta: 1 day, 2:31:12 time: 1.7848 data_time: 0.0458 memory: 16201 loss_prob: 1.0598 loss_thr: 0.5487 loss_db: 0.1646 loss: 1.7731 2022/08/30 01:19:39 - mmengine - INFO - Epoch(train) [88][20/63] lr: 6.5412e-03 eta: 1 day, 2:31:58 time: 1.8303 data_time: 0.0361 memory: 16201 loss_prob: 1.2140 loss_thr: 0.5673 loss_db: 0.1950 loss: 1.9763 2022/08/30 01:19:48 - mmengine - INFO - Epoch(train) [88][25/63] lr: 6.5412e-03 eta: 1 day, 2:31:58 time: 1.7720 data_time: 0.0546 memory: 16201 loss_prob: 1.1328 loss_thr: 0.5713 loss_db: 0.1879 loss: 1.8920 2022/08/30 01:19:57 - mmengine - INFO - Epoch(train) [88][30/63] lr: 6.5412e-03 eta: 1 day, 2:32:36 time: 1.7707 data_time: 0.0371 memory: 16201 loss_prob: 1.1021 loss_thr: 0.5966 loss_db: 0.1802 loss: 1.8790 2022/08/30 01:20:06 - mmengine - INFO - Epoch(train) [88][35/63] lr: 6.5412e-03 eta: 1 day, 2:32:36 time: 1.8073 data_time: 0.0452 memory: 16201 loss_prob: 1.1551 loss_thr: 0.5869 loss_db: 0.1902 loss: 1.9322 2022/08/30 01:20:16 - mmengine - INFO - Epoch(train) [88][40/63] lr: 6.5412e-03 eta: 1 day, 2:33:30 time: 1.8949 data_time: 0.0459 memory: 16201 loss_prob: 1.1189 loss_thr: 0.5383 loss_db: 0.1822 loss: 1.8394 2022/08/30 01:20:25 - mmengine - INFO - Epoch(train) [88][45/63] lr: 6.5412e-03 eta: 1 day, 2:33:30 time: 1.8689 data_time: 0.0323 memory: 16201 loss_prob: 1.2054 loss_thr: 0.5705 loss_db: 0.1922 loss: 1.9680 2022/08/30 01:20:34 - mmengine - INFO - Epoch(train) [88][50/63] lr: 6.5412e-03 eta: 1 day, 2:34:15 time: 1.8276 data_time: 0.0560 memory: 16201 loss_prob: 1.2148 loss_thr: 0.6072 loss_db: 0.1967 loss: 2.0187 2022/08/30 01:20:44 - mmengine - INFO - Epoch(train) [88][55/63] lr: 6.5412e-03 eta: 1 day, 2:34:15 time: 1.9320 data_time: 0.0416 memory: 16201 loss_prob: 1.1695 loss_thr: 0.5907 loss_db: 0.1905 loss: 1.9507 2022/08/30 01:20:54 - mmengine - INFO - Epoch(train) [88][60/63] lr: 6.5412e-03 eta: 1 day, 2:35:21 time: 1.9970 data_time: 0.0325 memory: 16201 loss_prob: 1.1533 loss_thr: 0.5826 loss_db: 0.1847 loss: 1.9206 2022/08/30 01:20:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:21:10 - mmengine - INFO - Epoch(train) [89][5/63] lr: 6.5359e-03 eta: 1 day, 2:35:21 time: 1.9508 data_time: 0.2846 memory: 16201 loss_prob: 1.0180 loss_thr: 0.5307 loss_db: 0.1642 loss: 1.7129 2022/08/30 01:21:18 - mmengine - INFO - Epoch(train) [89][10/63] lr: 6.5359e-03 eta: 1 day, 2:35:28 time: 1.9676 data_time: 0.3030 memory: 16201 loss_prob: 1.0422 loss_thr: 0.5382 loss_db: 0.1686 loss: 1.7490 2022/08/30 01:21:26 - mmengine - INFO - Epoch(train) [89][15/63] lr: 6.5359e-03 eta: 1 day, 2:35:28 time: 1.5675 data_time: 0.0372 memory: 16201 loss_prob: 1.1226 loss_thr: 0.5760 loss_db: 0.1812 loss: 1.8797 2022/08/30 01:21:33 - mmengine - INFO - Epoch(train) [89][20/63] lr: 6.5359e-03 eta: 1 day, 2:35:31 time: 1.5031 data_time: 0.0428 memory: 16201 loss_prob: 1.1236 loss_thr: 0.5725 loss_db: 0.1845 loss: 1.8806 2022/08/30 01:21:41 - mmengine - INFO - Epoch(train) [89][25/63] lr: 6.5359e-03 eta: 1 day, 2:35:31 time: 1.5007 data_time: 0.0476 memory: 16201 loss_prob: 1.0253 loss_thr: 0.5492 loss_db: 0.1711 loss: 1.7456 2022/08/30 01:21:50 - mmengine - INFO - Epoch(train) [89][30/63] lr: 6.5359e-03 eta: 1 day, 2:36:01 time: 1.7150 data_time: 0.0330 memory: 16201 loss_prob: 1.0123 loss_thr: 0.5325 loss_db: 0.1629 loss: 1.7076 2022/08/30 01:21:58 - mmengine - INFO - Epoch(train) [89][35/63] lr: 6.5359e-03 eta: 1 day, 2:36:01 time: 1.7975 data_time: 0.0458 memory: 16201 loss_prob: 1.0236 loss_thr: 0.5477 loss_db: 0.1648 loss: 1.7361 2022/08/30 01:22:08 - mmengine - INFO - Epoch(train) [89][40/63] lr: 6.5359e-03 eta: 1 day, 2:36:40 time: 1.7853 data_time: 0.0370 memory: 16201 loss_prob: 1.0654 loss_thr: 0.5616 loss_db: 0.1753 loss: 1.8023 2022/08/30 01:22:17 - mmengine - INFO - Epoch(train) [89][45/63] lr: 6.5359e-03 eta: 1 day, 2:36:40 time: 1.8776 data_time: 0.0412 memory: 16201 loss_prob: 1.1454 loss_thr: 0.5619 loss_db: 0.1848 loss: 1.8921 2022/08/30 01:22:26 - mmengine - INFO - Epoch(train) [89][50/63] lr: 6.5359e-03 eta: 1 day, 2:37:21 time: 1.8046 data_time: 0.0520 memory: 16201 loss_prob: 1.1541 loss_thr: 0.5733 loss_db: 0.1852 loss: 1.9126 2022/08/30 01:22:35 - mmengine - INFO - Epoch(train) [89][55/63] lr: 6.5359e-03 eta: 1 day, 2:37:21 time: 1.7404 data_time: 0.0460 memory: 16201 loss_prob: 1.0163 loss_thr: 0.5381 loss_db: 0.1686 loss: 1.7229 2022/08/30 01:22:44 - mmengine - INFO - Epoch(train) [89][60/63] lr: 6.5359e-03 eta: 1 day, 2:38:01 time: 1.7979 data_time: 0.0491 memory: 16201 loss_prob: 0.9415 loss_thr: 0.5400 loss_db: 0.1556 loss: 1.6372 2022/08/30 01:22:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:23:00 - mmengine - INFO - Epoch(train) [90][5/63] lr: 6.5306e-03 eta: 1 day, 2:38:01 time: 1.9231 data_time: 0.2693 memory: 16201 loss_prob: 0.9997 loss_thr: 0.5536 loss_db: 0.1634 loss: 1.7166 2022/08/30 01:23:10 - mmengine - INFO - Epoch(train) [90][10/63] lr: 6.5306e-03 eta: 1 day, 2:38:19 time: 2.0702 data_time: 0.2781 memory: 16201 loss_prob: 1.0633 loss_thr: 0.5640 loss_db: 0.1763 loss: 1.8036 2022/08/30 01:23:18 - mmengine - INFO - Epoch(train) [90][15/63] lr: 6.5306e-03 eta: 1 day, 2:38:19 time: 1.8623 data_time: 0.0497 memory: 16201 loss_prob: 1.0095 loss_thr: 0.5541 loss_db: 0.1669 loss: 1.7305 2022/08/30 01:23:27 - mmengine - INFO - Epoch(train) [90][20/63] lr: 6.5306e-03 eta: 1 day, 2:38:55 time: 1.7670 data_time: 0.0515 memory: 16201 loss_prob: 0.9686 loss_thr: 0.5513 loss_db: 0.1581 loss: 1.6780 2022/08/30 01:23:34 - mmengine - INFO - Epoch(train) [90][25/63] lr: 6.5306e-03 eta: 1 day, 2:38:55 time: 1.6108 data_time: 0.0514 memory: 16201 loss_prob: 0.9604 loss_thr: 0.5519 loss_db: 0.1562 loss: 1.6684 2022/08/30 01:23:43 - mmengine - INFO - Epoch(train) [90][30/63] lr: 6.5306e-03 eta: 1 day, 2:39:11 time: 1.6112 data_time: 0.0418 memory: 16201 loss_prob: 0.9310 loss_thr: 0.5417 loss_db: 0.1535 loss: 1.6262 2022/08/30 01:23:52 - mmengine - INFO - Epoch(train) [90][35/63] lr: 6.5306e-03 eta: 1 day, 2:39:11 time: 1.7433 data_time: 0.0486 memory: 16201 loss_prob: 0.9491 loss_thr: 0.5385 loss_db: 0.1556 loss: 1.6432 2022/08/30 01:24:00 - mmengine - INFO - Epoch(train) [90][40/63] lr: 6.5306e-03 eta: 1 day, 2:39:31 time: 1.6426 data_time: 0.0418 memory: 16201 loss_prob: 0.9775 loss_thr: 0.5178 loss_db: 0.1574 loss: 1.6527 2022/08/30 01:24:09 - mmengine - INFO - Epoch(train) [90][45/63] lr: 6.5306e-03 eta: 1 day, 2:39:31 time: 1.7012 data_time: 0.0320 memory: 16201 loss_prob: 0.9746 loss_thr: 0.5044 loss_db: 0.1591 loss: 1.6381 2022/08/30 01:24:17 - mmengine - INFO - Epoch(train) [90][50/63] lr: 6.5306e-03 eta: 1 day, 2:40:04 time: 1.7493 data_time: 0.0557 memory: 16201 loss_prob: 0.9486 loss_thr: 0.5256 loss_db: 0.1544 loss: 1.6285 2022/08/30 01:24:26 - mmengine - INFO - Epoch(train) [90][55/63] lr: 6.5306e-03 eta: 1 day, 2:40:04 time: 1.7255 data_time: 0.0513 memory: 16201 loss_prob: 0.9843 loss_thr: 0.5704 loss_db: 0.1651 loss: 1.7199 2022/08/30 01:24:37 - mmengine - INFO - Epoch(train) [90][60/63] lr: 6.5306e-03 eta: 1 day, 2:41:01 time: 1.9499 data_time: 0.0497 memory: 16201 loss_prob: 1.0072 loss_thr: 0.5819 loss_db: 0.1688 loss: 1.7580 2022/08/30 01:24:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:24:50 - mmengine - INFO - Epoch(train) [91][5/63] lr: 6.5253e-03 eta: 1 day, 2:41:01 time: 1.7361 data_time: 0.2691 memory: 16201 loss_prob: 1.2196 loss_thr: 0.5813 loss_db: 0.1937 loss: 1.9946 2022/08/30 01:25:00 - mmengine - INFO - Epoch(train) [91][10/63] lr: 6.5253e-03 eta: 1 day, 2:41:01 time: 1.9288 data_time: 0.2907 memory: 16201 loss_prob: 1.2695 loss_thr: 0.5824 loss_db: 0.2074 loss: 2.0594 2022/08/30 01:25:09 - mmengine - INFO - Epoch(train) [91][15/63] lr: 6.5253e-03 eta: 1 day, 2:41:01 time: 1.8080 data_time: 0.0561 memory: 16201 loss_prob: 1.1636 loss_thr: 0.5592 loss_db: 0.1949 loss: 1.9176 2022/08/30 01:25:18 - mmengine - INFO - Epoch(train) [91][20/63] lr: 6.5253e-03 eta: 1 day, 2:41:40 time: 1.8063 data_time: 0.0514 memory: 16201 loss_prob: 1.0800 loss_thr: 0.5569 loss_db: 0.1752 loss: 1.8122 2022/08/30 01:25:26 - mmengine - INFO - Epoch(train) [91][25/63] lr: 6.5253e-03 eta: 1 day, 2:41:40 time: 1.7133 data_time: 0.0490 memory: 16201 loss_prob: 1.0296 loss_thr: 0.5652 loss_db: 0.1655 loss: 1.7603 2022/08/30 01:25:34 - mmengine - INFO - Epoch(train) [91][30/63] lr: 6.5253e-03 eta: 1 day, 2:41:54 time: 1.6002 data_time: 0.0384 memory: 16201 loss_prob: 1.0025 loss_thr: 0.5259 loss_db: 0.1668 loss: 1.6951 2022/08/30 01:25:43 - mmengine - INFO - Epoch(train) [91][35/63] lr: 6.5253e-03 eta: 1 day, 2:41:54 time: 1.7085 data_time: 0.0423 memory: 16201 loss_prob: 0.9796 loss_thr: 0.5260 loss_db: 0.1618 loss: 1.6675 2022/08/30 01:25:52 - mmengine - INFO - Epoch(train) [91][40/63] lr: 6.5253e-03 eta: 1 day, 2:42:28 time: 1.7590 data_time: 0.0359 memory: 16201 loss_prob: 0.9648 loss_thr: 0.5395 loss_db: 0.1592 loss: 1.6634 2022/08/30 01:26:00 - mmengine - INFO - Epoch(train) [91][45/63] lr: 6.5253e-03 eta: 1 day, 2:42:28 time: 1.7433 data_time: 0.0444 memory: 16201 loss_prob: 0.9476 loss_thr: 0.5367 loss_db: 0.1563 loss: 1.6406 2022/08/30 01:26:09 - mmengine - INFO - Epoch(train) [91][50/63] lr: 6.5253e-03 eta: 1 day, 2:42:58 time: 1.7412 data_time: 0.0491 memory: 16201 loss_prob: 1.0232 loss_thr: 0.5547 loss_db: 0.1670 loss: 1.7449 2022/08/30 01:26:17 - mmengine - INFO - Epoch(train) [91][55/63] lr: 6.5253e-03 eta: 1 day, 2:42:58 time: 1.7037 data_time: 0.0504 memory: 16201 loss_prob: 1.0639 loss_thr: 0.5565 loss_db: 0.1791 loss: 1.7996 2022/08/30 01:26:27 - mmengine - INFO - Epoch(train) [91][60/63] lr: 6.5253e-03 eta: 1 day, 2:43:32 time: 1.7632 data_time: 0.0944 memory: 16201 loss_prob: 1.0552 loss_thr: 0.5697 loss_db: 0.1732 loss: 1.7981 2022/08/30 01:26:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:26:45 - mmengine - INFO - Epoch(train) [92][5/63] lr: 6.5200e-03 eta: 1 day, 2:43:32 time: 2.1642 data_time: 0.2940 memory: 16201 loss_prob: 0.9600 loss_thr: 0.5528 loss_db: 0.1611 loss: 1.6740 2022/08/30 01:26:56 - mmengine - INFO - Epoch(train) [92][10/63] lr: 6.5200e-03 eta: 1 day, 2:44:20 time: 2.3361 data_time: 0.3400 memory: 16201 loss_prob: 1.2238 loss_thr: 0.6096 loss_db: 0.1988 loss: 2.0322 2022/08/30 01:27:05 - mmengine - INFO - Epoch(train) [92][15/63] lr: 6.5200e-03 eta: 1 day, 2:44:20 time: 2.0050 data_time: 0.1342 memory: 16201 loss_prob: 1.2788 loss_thr: 0.6004 loss_db: 0.2088 loss: 2.0880 2022/08/30 01:27:16 - mmengine - INFO - Epoch(train) [92][20/63] lr: 6.5200e-03 eta: 1 day, 2:45:29 time: 2.0552 data_time: 0.0982 memory: 16201 loss_prob: 1.0931 loss_thr: 0.5649 loss_db: 0.1826 loss: 1.8407 2022/08/30 01:27:26 - mmengine - INFO - Epoch(train) [92][25/63] lr: 6.5200e-03 eta: 1 day, 2:45:29 time: 2.1181 data_time: 0.0917 memory: 16201 loss_prob: 1.1143 loss_thr: 0.5921 loss_db: 0.1833 loss: 1.8897 2022/08/30 01:27:36 - mmengine - INFO - Epoch(train) [92][30/63] lr: 6.5200e-03 eta: 1 day, 2:46:22 time: 1.9349 data_time: 0.0881 memory: 16201 loss_prob: 1.1346 loss_thr: 0.5986 loss_db: 0.1878 loss: 1.9209 2022/08/30 01:27:44 - mmengine - INFO - Epoch(train) [92][35/63] lr: 6.5200e-03 eta: 1 day, 2:46:22 time: 1.7408 data_time: 0.0995 memory: 16201 loss_prob: 0.9770 loss_thr: 0.5410 loss_db: 0.1581 loss: 1.6761 2022/08/30 01:27:54 - mmengine - INFO - Epoch(train) [92][40/63] lr: 6.5200e-03 eta: 1 day, 2:47:01 time: 1.8105 data_time: 0.0929 memory: 16201 loss_prob: 0.9607 loss_thr: 0.5279 loss_db: 0.1512 loss: 1.6398 2022/08/30 01:28:04 - mmengine - INFO - Epoch(train) [92][45/63] lr: 6.5200e-03 eta: 1 day, 2:47:01 time: 2.0053 data_time: 0.0984 memory: 16201 loss_prob: 1.0250 loss_thr: 0.5608 loss_db: 0.1677 loss: 1.7534 2022/08/30 01:28:12 - mmengine - INFO - Epoch(train) [92][50/63] lr: 6.5200e-03 eta: 1 day, 2:47:41 time: 1.8297 data_time: 0.0987 memory: 16201 loss_prob: 1.0255 loss_thr: 0.5758 loss_db: 0.1702 loss: 1.7715 2022/08/30 01:28:22 - mmengine - INFO - Epoch(train) [92][55/63] lr: 6.5200e-03 eta: 1 day, 2:47:41 time: 1.8629 data_time: 0.1005 memory: 16201 loss_prob: 1.1047 loss_thr: 0.5700 loss_db: 0.1716 loss: 1.8462 2022/08/30 01:28:30 - mmengine - INFO - Epoch(train) [92][60/63] lr: 6.5200e-03 eta: 1 day, 2:48:19 time: 1.8103 data_time: 0.1312 memory: 16201 loss_prob: 1.1840 loss_thr: 0.5531 loss_db: 0.1836 loss: 1.9208 2022/08/30 01:28:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:28:46 - mmengine - INFO - Epoch(train) [93][5/63] lr: 6.5147e-03 eta: 1 day, 2:48:19 time: 1.9680 data_time: 0.2910 memory: 16201 loss_prob: 1.1513 loss_thr: 0.5721 loss_db: 0.1927 loss: 1.9160 2022/08/30 01:28:55 - mmengine - INFO - Epoch(train) [93][10/63] lr: 6.5147e-03 eta: 1 day, 2:48:25 time: 1.9948 data_time: 0.2833 memory: 16201 loss_prob: 1.1466 loss_thr: 0.5727 loss_db: 0.1888 loss: 1.9081 2022/08/30 01:29:04 - mmengine - INFO - Epoch(train) [93][15/63] lr: 6.5147e-03 eta: 1 day, 2:48:25 time: 1.7855 data_time: 0.0465 memory: 16201 loss_prob: 1.2006 loss_thr: 0.5434 loss_db: 0.1957 loss: 1.9396 2022/08/30 01:29:12 - mmengine - INFO - Epoch(train) [93][20/63] lr: 6.5147e-03 eta: 1 day, 2:48:54 time: 1.7420 data_time: 0.0483 memory: 16201 loss_prob: 1.0978 loss_thr: 0.5073 loss_db: 0.1740 loss: 1.7791 2022/08/30 01:29:21 - mmengine - INFO - Epoch(train) [93][25/63] lr: 6.5147e-03 eta: 1 day, 2:48:54 time: 1.7204 data_time: 0.0436 memory: 16201 loss_prob: 1.0455 loss_thr: 0.5257 loss_db: 0.1655 loss: 1.7368 2022/08/30 01:29:30 - mmengine - INFO - Epoch(train) [93][30/63] lr: 6.5147e-03 eta: 1 day, 2:49:31 time: 1.8115 data_time: 0.0456 memory: 16201 loss_prob: 1.0834 loss_thr: 0.5627 loss_db: 0.1755 loss: 1.8216 2022/08/30 01:29:38 - mmengine - INFO - Epoch(train) [93][35/63] lr: 6.5147e-03 eta: 1 day, 2:49:31 time: 1.6489 data_time: 0.0517 memory: 16201 loss_prob: 1.1153 loss_thr: 0.5733 loss_db: 0.1816 loss: 1.8702 2022/08/30 01:29:46 - mmengine - INFO - Epoch(train) [93][40/63] lr: 6.5147e-03 eta: 1 day, 2:49:45 time: 1.6148 data_time: 0.0464 memory: 16201 loss_prob: 1.0616 loss_thr: 0.5551 loss_db: 0.1727 loss: 1.7894 2022/08/30 01:29:56 - mmengine - INFO - Epoch(train) [93][45/63] lr: 6.5147e-03 eta: 1 day, 2:49:45 time: 1.7733 data_time: 0.0544 memory: 16201 loss_prob: 0.9602 loss_thr: 0.5303 loss_db: 0.1543 loss: 1.6448 2022/08/30 01:30:04 - mmengine - INFO - Epoch(train) [93][50/63] lr: 6.5147e-03 eta: 1 day, 2:50:14 time: 1.7428 data_time: 0.0540 memory: 16201 loss_prob: 0.9183 loss_thr: 0.5202 loss_db: 0.1502 loss: 1.5887 2022/08/30 01:30:14 - mmengine - INFO - Epoch(train) [93][55/63] lr: 6.5147e-03 eta: 1 day, 2:50:14 time: 1.7995 data_time: 0.0419 memory: 16201 loss_prob: 0.8962 loss_thr: 0.5240 loss_db: 0.1460 loss: 1.5662 2022/08/30 01:30:21 - mmengine - INFO - Epoch(train) [93][60/63] lr: 6.5147e-03 eta: 1 day, 2:50:45 time: 1.7583 data_time: 0.0468 memory: 16201 loss_prob: 0.9662 loss_thr: 0.5340 loss_db: 0.1552 loss: 1.6554 2022/08/30 01:30:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:30:36 - mmengine - INFO - Epoch(train) [94][5/63] lr: 6.5094e-03 eta: 1 day, 2:50:45 time: 1.7083 data_time: 0.2708 memory: 16201 loss_prob: 0.9744 loss_thr: 0.5530 loss_db: 0.1572 loss: 1.6846 2022/08/30 01:30:44 - mmengine - INFO - Epoch(train) [94][10/63] lr: 6.5094e-03 eta: 1 day, 2:50:34 time: 1.8635 data_time: 0.2900 memory: 16201 loss_prob: 0.9279 loss_thr: 0.5443 loss_db: 0.1552 loss: 1.6275 2022/08/30 01:30:52 - mmengine - INFO - Epoch(train) [94][15/63] lr: 6.5094e-03 eta: 1 day, 2:50:34 time: 1.6615 data_time: 0.0369 memory: 16201 loss_prob: 0.9506 loss_thr: 0.5358 loss_db: 0.1553 loss: 1.6417 2022/08/30 01:31:01 - mmengine - INFO - Epoch(train) [94][20/63] lr: 6.5094e-03 eta: 1 day, 2:50:53 time: 1.6595 data_time: 0.0396 memory: 16201 loss_prob: 0.9956 loss_thr: 0.5454 loss_db: 0.1620 loss: 1.7031 2022/08/30 01:31:10 - mmengine - INFO - Epoch(train) [94][25/63] lr: 6.5094e-03 eta: 1 day, 2:50:53 time: 1.7197 data_time: 0.0539 memory: 16201 loss_prob: 1.0437 loss_thr: 0.5753 loss_db: 0.1739 loss: 1.7930 2022/08/30 01:31:19 - mmengine - INFO - Epoch(train) [94][30/63] lr: 6.5094e-03 eta: 1 day, 2:51:26 time: 1.7868 data_time: 0.0380 memory: 16201 loss_prob: 1.0197 loss_thr: 0.5489 loss_db: 0.1676 loss: 1.7363 2022/08/30 01:31:26 - mmengine - INFO - Epoch(train) [94][35/63] lr: 6.5094e-03 eta: 1 day, 2:51:26 time: 1.6683 data_time: 0.0490 memory: 16201 loss_prob: 0.9884 loss_thr: 0.5482 loss_db: 0.1606 loss: 1.6972 2022/08/30 01:31:35 - mmengine - INFO - Epoch(train) [94][40/63] lr: 6.5094e-03 eta: 1 day, 2:51:42 time: 1.6357 data_time: 0.0480 memory: 16201 loss_prob: 1.0674 loss_thr: 0.5922 loss_db: 0.1737 loss: 1.8332 2022/08/30 01:31:43 - mmengine - INFO - Epoch(train) [94][45/63] lr: 6.5094e-03 eta: 1 day, 2:51:42 time: 1.7244 data_time: 0.0366 memory: 16201 loss_prob: 1.0984 loss_thr: 0.5677 loss_db: 0.1774 loss: 1.8436 2022/08/30 01:31:53 - mmengine - INFO - Epoch(train) [94][50/63] lr: 6.5094e-03 eta: 1 day, 2:52:18 time: 1.8112 data_time: 0.0533 memory: 16201 loss_prob: 0.9990 loss_thr: 0.5440 loss_db: 0.1627 loss: 1.7057 2022/08/30 01:32:04 - mmengine - INFO - Epoch(train) [94][55/63] lr: 6.5094e-03 eta: 1 day, 2:52:18 time: 2.0061 data_time: 0.0408 memory: 16201 loss_prob: 1.1144 loss_thr: 0.5786 loss_db: 0.1769 loss: 1.8700 2022/08/30 01:32:13 - mmengine - INFO - Epoch(train) [94][60/63] lr: 6.5094e-03 eta: 1 day, 2:53:12 time: 1.9668 data_time: 0.0431 memory: 16201 loss_prob: 1.2357 loss_thr: 0.6030 loss_db: 0.1976 loss: 2.0363 2022/08/30 01:32:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:32:28 - mmengine - INFO - Epoch(train) [95][5/63] lr: 6.5041e-03 eta: 1 day, 2:53:12 time: 1.8862 data_time: 0.2639 memory: 16201 loss_prob: 1.0849 loss_thr: 0.5593 loss_db: 0.1803 loss: 1.8245 2022/08/30 01:32:37 - mmengine - INFO - Epoch(train) [95][10/63] lr: 6.5041e-03 eta: 1 day, 2:53:12 time: 1.9572 data_time: 0.3039 memory: 16201 loss_prob: 1.0879 loss_thr: 0.5433 loss_db: 0.1835 loss: 1.8147 2022/08/30 01:32:47 - mmengine - INFO - Epoch(train) [95][15/63] lr: 6.5041e-03 eta: 1 day, 2:53:12 time: 1.8674 data_time: 0.0604 memory: 16201 loss_prob: 1.1396 loss_thr: 0.5522 loss_db: 0.1946 loss: 1.8864 2022/08/30 01:32:56 - mmengine - INFO - Epoch(train) [95][20/63] lr: 6.5041e-03 eta: 1 day, 2:53:55 time: 1.8793 data_time: 0.0496 memory: 16201 loss_prob: 1.2727 loss_thr: 0.6055 loss_db: 0.2030 loss: 2.0812 2022/08/30 01:33:05 - mmengine - INFO - Epoch(train) [95][25/63] lr: 6.5041e-03 eta: 1 day, 2:53:55 time: 1.7823 data_time: 0.0571 memory: 16201 loss_prob: 1.2381 loss_thr: 0.6078 loss_db: 0.1964 loss: 2.0424 2022/08/30 01:33:14 - mmengine - INFO - Epoch(train) [95][30/63] lr: 6.5041e-03 eta: 1 day, 2:54:33 time: 1.8352 data_time: 0.0352 memory: 16201 loss_prob: 1.0691 loss_thr: 0.5616 loss_db: 0.1810 loss: 1.8117 2022/08/30 01:33:22 - mmengine - INFO - Epoch(train) [95][35/63] lr: 6.5041e-03 eta: 1 day, 2:54:33 time: 1.6912 data_time: 0.0476 memory: 16201 loss_prob: 1.0936 loss_thr: 0.5727 loss_db: 0.1856 loss: 1.8519 2022/08/30 01:33:30 - mmengine - INFO - Epoch(train) [95][40/63] lr: 6.5041e-03 eta: 1 day, 2:54:41 time: 1.5788 data_time: 0.0430 memory: 16201 loss_prob: 1.1468 loss_thr: 0.5739 loss_db: 0.1911 loss: 1.9117 2022/08/30 01:33:39 - mmengine - INFO - Epoch(train) [95][45/63] lr: 6.5041e-03 eta: 1 day, 2:54:41 time: 1.7503 data_time: 0.0427 memory: 16201 loss_prob: 1.0780 loss_thr: 0.5598 loss_db: 0.1759 loss: 1.8137 2022/08/30 01:33:47 - mmengine - INFO - Epoch(train) [95][50/63] lr: 6.5041e-03 eta: 1 day, 2:55:08 time: 1.7415 data_time: 0.0568 memory: 16201 loss_prob: 1.0575 loss_thr: 0.5505 loss_db: 0.1692 loss: 1.7772 2022/08/30 01:33:57 - mmengine - INFO - Epoch(train) [95][55/63] lr: 6.5041e-03 eta: 1 day, 2:55:08 time: 1.7474 data_time: 0.0327 memory: 16201 loss_prob: 1.1055 loss_thr: 0.5677 loss_db: 0.1776 loss: 1.8508 2022/08/30 01:34:05 - mmengine - INFO - Epoch(train) [95][60/63] lr: 6.5041e-03 eta: 1 day, 2:55:45 time: 1.8242 data_time: 0.0396 memory: 16201 loss_prob: 1.0623 loss_thr: 0.5793 loss_db: 0.1721 loss: 1.8137 2022/08/30 01:34:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:34:23 - mmengine - INFO - Epoch(train) [96][5/63] lr: 6.4988e-03 eta: 1 day, 2:55:45 time: 2.1646 data_time: 0.2871 memory: 16201 loss_prob: 0.9263 loss_thr: 0.5321 loss_db: 0.1543 loss: 1.6127 2022/08/30 01:34:33 - mmengine - INFO - Epoch(train) [96][10/63] lr: 6.4988e-03 eta: 1 day, 2:56:23 time: 2.2964 data_time: 0.2979 memory: 16201 loss_prob: 1.0343 loss_thr: 0.5388 loss_db: 0.1703 loss: 1.7434 2022/08/30 01:34:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:34:42 - mmengine - INFO - Epoch(train) [96][15/63] lr: 6.4988e-03 eta: 1 day, 2:56:23 time: 1.9420 data_time: 0.0538 memory: 16201 loss_prob: 0.9652 loss_thr: 0.5105 loss_db: 0.1548 loss: 1.6306 2022/08/30 01:34:50 - mmengine - INFO - Epoch(train) [96][20/63] lr: 6.4988e-03 eta: 1 day, 2:56:43 time: 1.6810 data_time: 0.0545 memory: 16201 loss_prob: 0.9299 loss_thr: 0.5168 loss_db: 0.1500 loss: 1.5968 2022/08/30 01:34:59 - mmengine - INFO - Epoch(train) [96][25/63] lr: 6.4988e-03 eta: 1 day, 2:56:43 time: 1.6562 data_time: 0.0465 memory: 16201 loss_prob: 1.0666 loss_thr: 0.5583 loss_db: 0.1715 loss: 1.7964 2022/08/30 01:35:07 - mmengine - INFO - Epoch(train) [96][30/63] lr: 6.4988e-03 eta: 1 day, 2:57:02 time: 1.6803 data_time: 0.0395 memory: 16201 loss_prob: 1.0689 loss_thr: 0.5646 loss_db: 0.1755 loss: 1.8089 2022/08/30 01:35:15 - mmengine - INFO - Epoch(train) [96][35/63] lr: 6.4988e-03 eta: 1 day, 2:57:02 time: 1.6424 data_time: 0.0499 memory: 16201 loss_prob: 1.0565 loss_thr: 0.5546 loss_db: 0.1704 loss: 1.7815 2022/08/30 01:35:23 - mmengine - INFO - Epoch(train) [96][40/63] lr: 6.4988e-03 eta: 1 day, 2:57:18 time: 1.6533 data_time: 0.0483 memory: 16201 loss_prob: 1.0267 loss_thr: 0.5143 loss_db: 0.1648 loss: 1.7057 2022/08/30 01:35:32 - mmengine - INFO - Epoch(train) [96][45/63] lr: 6.4988e-03 eta: 1 day, 2:57:18 time: 1.6949 data_time: 0.0458 memory: 16201 loss_prob: 1.0226 loss_thr: 0.5524 loss_db: 0.1675 loss: 1.7425 2022/08/30 01:35:40 - mmengine - INFO - Epoch(train) [96][50/63] lr: 6.4988e-03 eta: 1 day, 2:57:34 time: 1.6579 data_time: 0.0602 memory: 16201 loss_prob: 0.9571 loss_thr: 0.5674 loss_db: 0.1570 loss: 1.6815 2022/08/30 01:35:50 - mmengine - INFO - Epoch(train) [96][55/63] lr: 6.4988e-03 eta: 1 day, 2:57:34 time: 1.8369 data_time: 0.0545 memory: 16201 loss_prob: 0.9923 loss_thr: 0.5245 loss_db: 0.1574 loss: 1.6743 2022/08/30 01:35:59 - mmengine - INFO - Epoch(train) [96][60/63] lr: 6.4988e-03 eta: 1 day, 2:58:16 time: 1.8842 data_time: 0.0521 memory: 16201 loss_prob: 1.0364 loss_thr: 0.5324 loss_db: 0.1646 loss: 1.7334 2022/08/30 01:36:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:36:16 - mmengine - INFO - Epoch(train) [97][5/63] lr: 6.4935e-03 eta: 1 day, 2:58:16 time: 1.9963 data_time: 0.2695 memory: 16201 loss_prob: 0.9310 loss_thr: 0.5458 loss_db: 0.1534 loss: 1.6302 2022/08/30 01:36:25 - mmengine - INFO - Epoch(train) [97][10/63] lr: 6.4935e-03 eta: 1 day, 2:58:30 time: 2.0911 data_time: 0.2732 memory: 16201 loss_prob: 1.1742 loss_thr: 0.5784 loss_db: 0.1979 loss: 1.9505 2022/08/30 01:36:34 - mmengine - INFO - Epoch(train) [97][15/63] lr: 6.4935e-03 eta: 1 day, 2:58:30 time: 1.7858 data_time: 0.0495 memory: 16201 loss_prob: 1.3274 loss_thr: 0.6072 loss_db: 0.2152 loss: 2.1499 2022/08/30 01:36:43 - mmengine - INFO - Epoch(train) [97][20/63] lr: 6.4935e-03 eta: 1 day, 2:59:05 time: 1.8274 data_time: 0.0390 memory: 16201 loss_prob: 1.0859 loss_thr: 0.5783 loss_db: 0.1713 loss: 1.8355 2022/08/30 01:36:52 - mmengine - INFO - Epoch(train) [97][25/63] lr: 6.4935e-03 eta: 1 day, 2:59:05 time: 1.7757 data_time: 0.0466 memory: 16201 loss_prob: 1.2167 loss_thr: 0.5833 loss_db: 0.1965 loss: 1.9965 2022/08/30 01:37:01 - mmengine - INFO - Epoch(train) [97][30/63] lr: 6.4935e-03 eta: 1 day, 2:59:35 time: 1.7773 data_time: 0.0381 memory: 16201 loss_prob: 1.4453 loss_thr: 0.6157 loss_db: 0.2358 loss: 2.2968 2022/08/30 01:37:10 - mmengine - INFO - Epoch(train) [97][35/63] lr: 6.4935e-03 eta: 1 day, 2:59:35 time: 1.8270 data_time: 0.0520 memory: 16201 loss_prob: 1.2837 loss_thr: 0.5955 loss_db: 0.2117 loss: 2.0909 2022/08/30 01:37:19 - mmengine - INFO - Epoch(train) [97][40/63] lr: 6.4935e-03 eta: 1 day, 3:00:05 time: 1.7814 data_time: 0.0462 memory: 16201 loss_prob: 1.1649 loss_thr: 0.5688 loss_db: 0.1892 loss: 1.9229 2022/08/30 01:37:28 - mmengine - INFO - Epoch(train) [97][45/63] lr: 6.4935e-03 eta: 1 day, 3:00:05 time: 1.8001 data_time: 0.0595 memory: 16201 loss_prob: 1.0555 loss_thr: 0.5252 loss_db: 0.1729 loss: 1.7536 2022/08/30 01:37:36 - mmengine - INFO - Epoch(train) [97][50/63] lr: 6.4935e-03 eta: 1 day, 3:00:34 time: 1.7756 data_time: 0.0661 memory: 16201 loss_prob: 1.0173 loss_thr: 0.5334 loss_db: 0.1699 loss: 1.7206 2022/08/30 01:37:46 - mmengine - INFO - Epoch(train) [97][55/63] lr: 6.4935e-03 eta: 1 day, 3:00:34 time: 1.7581 data_time: 0.0365 memory: 16201 loss_prob: 1.2329 loss_thr: 0.5939 loss_db: 0.1933 loss: 2.0200 2022/08/30 01:37:55 - mmengine - INFO - Epoch(train) [97][60/63] lr: 6.4935e-03 eta: 1 day, 3:01:11 time: 1.8485 data_time: 0.0403 memory: 16201 loss_prob: 1.1777 loss_thr: 0.5591 loss_db: 0.1848 loss: 1.9217 2022/08/30 01:38:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:38:13 - mmengine - INFO - Epoch(train) [98][5/63] lr: 6.4882e-03 eta: 1 day, 3:01:11 time: 2.1202 data_time: 0.2965 memory: 16201 loss_prob: 1.0202 loss_thr: 0.5262 loss_db: 0.1701 loss: 1.7165 2022/08/30 01:38:21 - mmengine - INFO - Epoch(train) [98][10/63] lr: 6.4882e-03 eta: 1 day, 3:01:24 time: 2.0921 data_time: 0.3197 memory: 16201 loss_prob: 1.0315 loss_thr: 0.5209 loss_db: 0.1761 loss: 1.7285 2022/08/30 01:38:31 - mmengine - INFO - Epoch(train) [98][15/63] lr: 6.4882e-03 eta: 1 day, 3:01:24 time: 1.7940 data_time: 0.0441 memory: 16201 loss_prob: 1.0112 loss_thr: 0.5207 loss_db: 0.1700 loss: 1.7019 2022/08/30 01:38:40 - mmengine - INFO - Epoch(train) [98][20/63] lr: 6.4882e-03 eta: 1 day, 3:01:58 time: 1.8274 data_time: 0.0768 memory: 16201 loss_prob: 1.0314 loss_thr: 0.5352 loss_db: 0.1645 loss: 1.7311 2022/08/30 01:38:49 - mmengine - INFO - Epoch(train) [98][25/63] lr: 6.4882e-03 eta: 1 day, 3:01:58 time: 1.7760 data_time: 0.0809 memory: 16201 loss_prob: 1.0947 loss_thr: 0.5476 loss_db: 0.1746 loss: 1.8169 2022/08/30 01:38:58 - mmengine - INFO - Epoch(train) [98][30/63] lr: 6.4882e-03 eta: 1 day, 3:02:27 time: 1.7812 data_time: 0.0411 memory: 16201 loss_prob: 1.1204 loss_thr: 0.5597 loss_db: 0.1800 loss: 1.8602 2022/08/30 01:39:05 - mmengine - INFO - Epoch(train) [98][35/63] lr: 6.4882e-03 eta: 1 day, 3:02:27 time: 1.6428 data_time: 0.0483 memory: 16201 loss_prob: 1.1416 loss_thr: 0.5800 loss_db: 0.1852 loss: 1.9068 2022/08/30 01:39:13 - mmengine - INFO - Epoch(train) [98][40/63] lr: 6.4882e-03 eta: 1 day, 3:02:30 time: 1.5546 data_time: 0.0482 memory: 16201 loss_prob: 1.2095 loss_thr: 0.5669 loss_db: 0.1946 loss: 1.9709 2022/08/30 01:39:20 - mmengine - INFO - Epoch(train) [98][45/63] lr: 6.4882e-03 eta: 1 day, 3:02:30 time: 1.4742 data_time: 0.0434 memory: 16201 loss_prob: 1.1849 loss_thr: 0.5690 loss_db: 0.1882 loss: 1.9421 2022/08/30 01:39:27 - mmengine - INFO - Epoch(train) [98][50/63] lr: 6.4882e-03 eta: 1 day, 3:02:19 time: 1.4229 data_time: 0.0335 memory: 16201 loss_prob: 1.0935 loss_thr: 0.5797 loss_db: 0.1816 loss: 1.8547 2022/08/30 01:39:35 - mmengine - INFO - Epoch(train) [98][55/63] lr: 6.4882e-03 eta: 1 day, 3:02:19 time: 1.4724 data_time: 0.0322 memory: 16201 loss_prob: 1.1328 loss_thr: 0.5640 loss_db: 0.1877 loss: 1.8846 2022/08/30 01:39:43 - mmengine - INFO - Epoch(train) [98][60/63] lr: 6.4882e-03 eta: 1 day, 3:02:23 time: 1.5687 data_time: 0.0436 memory: 16201 loss_prob: 1.1699 loss_thr: 0.5792 loss_db: 0.1896 loss: 1.9387 2022/08/30 01:39:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:39:59 - mmengine - INFO - Epoch(train) [99][5/63] lr: 6.4829e-03 eta: 1 day, 3:02:23 time: 1.8551 data_time: 0.2504 memory: 16201 loss_prob: 1.1249 loss_thr: 0.5793 loss_db: 0.1871 loss: 1.8913 2022/08/30 01:40:08 - mmengine - INFO - Epoch(train) [99][10/63] lr: 6.4829e-03 eta: 1 day, 3:02:41 time: 2.1422 data_time: 0.2639 memory: 16201 loss_prob: 1.1504 loss_thr: 0.5820 loss_db: 0.1913 loss: 1.9237 2022/08/30 01:40:18 - mmengine - INFO - Epoch(train) [99][15/63] lr: 6.4829e-03 eta: 1 day, 3:02:41 time: 1.9146 data_time: 0.0463 memory: 16201 loss_prob: 1.0131 loss_thr: 0.5435 loss_db: 0.1663 loss: 1.7229 2022/08/30 01:40:28 - mmengine - INFO - Epoch(train) [99][20/63] lr: 6.4829e-03 eta: 1 day, 3:03:35 time: 2.0120 data_time: 0.0513 memory: 16201 loss_prob: 1.0055 loss_thr: 0.5545 loss_db: 0.1653 loss: 1.7253 2022/08/30 01:40:37 - mmengine - INFO - Epoch(train) [99][25/63] lr: 6.4829e-03 eta: 1 day, 3:03:35 time: 1.9019 data_time: 0.0489 memory: 16201 loss_prob: 1.1322 loss_thr: 0.5848 loss_db: 0.1864 loss: 1.9034 2022/08/30 01:40:46 - mmengine - INFO - Epoch(train) [99][30/63] lr: 6.4829e-03 eta: 1 day, 3:03:58 time: 1.7307 data_time: 0.0417 memory: 16201 loss_prob: 1.1312 loss_thr: 0.5518 loss_db: 0.1837 loss: 1.8667 2022/08/30 01:40:55 - mmengine - INFO - Epoch(train) [99][35/63] lr: 6.4829e-03 eta: 1 day, 3:03:58 time: 1.7783 data_time: 0.0610 memory: 16201 loss_prob: 1.2562 loss_thr: 0.5725 loss_db: 0.2003 loss: 2.0291 2022/08/30 01:41:04 - mmengine - INFO - Epoch(train) [99][40/63] lr: 6.4829e-03 eta: 1 day, 3:04:29 time: 1.8069 data_time: 0.0475 memory: 16201 loss_prob: 1.2517 loss_thr: 0.6025 loss_db: 0.2005 loss: 2.0546 2022/08/30 01:41:13 - mmengine - INFO - Epoch(train) [99][45/63] lr: 6.4829e-03 eta: 1 day, 3:04:29 time: 1.8768 data_time: 0.0527 memory: 16201 loss_prob: 1.0422 loss_thr: 0.5878 loss_db: 0.1714 loss: 1.8014 2022/08/30 01:41:22 - mmengine - INFO - Epoch(train) [99][50/63] lr: 6.4829e-03 eta: 1 day, 3:04:57 time: 1.7873 data_time: 0.0465 memory: 16201 loss_prob: 0.9928 loss_thr: 0.5517 loss_db: 0.1637 loss: 1.7082 2022/08/30 01:41:30 - mmengine - INFO - Epoch(train) [99][55/63] lr: 6.4829e-03 eta: 1 day, 3:04:57 time: 1.7207 data_time: 0.0251 memory: 16201 loss_prob: 1.0297 loss_thr: 0.5277 loss_db: 0.1663 loss: 1.7237 2022/08/30 01:41:38 - mmengine - INFO - Epoch(train) [99][60/63] lr: 6.4829e-03 eta: 1 day, 3:05:09 time: 1.6339 data_time: 0.0370 memory: 16201 loss_prob: 1.0516 loss_thr: 0.5431 loss_db: 0.1706 loss: 1.7653 2022/08/30 01:41:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:41:54 - mmengine - INFO - Epoch(train) [100][5/63] lr: 6.4776e-03 eta: 1 day, 3:05:09 time: 1.9073 data_time: 0.2891 memory: 16201 loss_prob: 1.0658 loss_thr: 0.5574 loss_db: 0.1782 loss: 1.8014 2022/08/30 01:42:05 - mmengine - INFO - Epoch(train) [100][10/63] lr: 6.4776e-03 eta: 1 day, 3:05:31 time: 2.1909 data_time: 0.3003 memory: 16201 loss_prob: 1.1412 loss_thr: 0.5728 loss_db: 0.1915 loss: 1.9055 2022/08/30 01:42:13 - mmengine - INFO - Epoch(train) [100][15/63] lr: 6.4776e-03 eta: 1 day, 3:05:31 time: 1.8459 data_time: 0.0448 memory: 16201 loss_prob: 1.1696 loss_thr: 0.5432 loss_db: 0.1915 loss: 1.9042 2022/08/30 01:42:22 - mmengine - INFO - Epoch(train) [100][20/63] lr: 6.4776e-03 eta: 1 day, 3:05:53 time: 1.7332 data_time: 0.0406 memory: 16201 loss_prob: 1.2469 loss_thr: 0.5824 loss_db: 0.2025 loss: 2.0318 2022/08/30 01:42:32 - mmengine - INFO - Epoch(train) [100][25/63] lr: 6.4776e-03 eta: 1 day, 3:05:53 time: 1.8725 data_time: 0.0621 memory: 16201 loss_prob: 1.2561 loss_thr: 0.6188 loss_db: 0.2149 loss: 2.0897 2022/08/30 01:42:40 - mmengine - INFO - Epoch(train) [100][30/63] lr: 6.4776e-03 eta: 1 day, 3:06:23 time: 1.8083 data_time: 0.0455 memory: 16201 loss_prob: 1.3803 loss_thr: 0.6097 loss_db: 0.2408 loss: 2.2308 2022/08/30 01:42:50 - mmengine - INFO - Epoch(train) [100][35/63] lr: 6.4776e-03 eta: 1 day, 3:06:23 time: 1.8019 data_time: 0.0376 memory: 16201 loss_prob: 1.2607 loss_thr: 0.6014 loss_db: 0.2131 loss: 2.0752 2022/08/30 01:42:57 - mmengine - INFO - Epoch(train) [100][40/63] lr: 6.4776e-03 eta: 1 day, 3:06:44 time: 1.7174 data_time: 0.0465 memory: 16201 loss_prob: 1.2818 loss_thr: 0.6188 loss_db: 0.2158 loss: 2.1164 2022/08/30 01:43:08 - mmengine - INFO - Epoch(train) [100][45/63] lr: 6.4776e-03 eta: 1 day, 3:06:44 time: 1.8081 data_time: 0.0453 memory: 16201 loss_prob: 1.4282 loss_thr: 0.6214 loss_db: 0.2418 loss: 2.2914 2022/08/30 01:43:16 - mmengine - INFO - Epoch(train) [100][50/63] lr: 6.4776e-03 eta: 1 day, 3:07:21 time: 1.8728 data_time: 0.0566 memory: 16201 loss_prob: 1.3022 loss_thr: 0.5959 loss_db: 0.2124 loss: 2.1104 2022/08/30 01:43:25 - mmengine - INFO - Epoch(train) [100][55/63] lr: 6.4776e-03 eta: 1 day, 3:07:21 time: 1.7759 data_time: 0.0386 memory: 16201 loss_prob: 1.2445 loss_thr: 0.5862 loss_db: 0.2003 loss: 2.0310 2022/08/30 01:43:35 - mmengine - INFO - Epoch(train) [100][60/63] lr: 6.4776e-03 eta: 1 day, 3:08:01 time: 1.9049 data_time: 0.0439 memory: 16201 loss_prob: 1.2451 loss_thr: 0.5899 loss_db: 0.2043 loss: 2.0393 2022/08/30 01:43:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:43:40 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/08/30 01:43:49 - mmengine - INFO - Epoch(val) [100][5/32] eta: 1 day, 3:08:01 time: 0.7891 data_time: 0.1552 memory: 16201 2022/08/30 01:43:52 - mmengine - INFO - Epoch(val) [100][10/32] eta: 0:00:18 time: 0.8560 data_time: 0.2067 memory: 15734 2022/08/30 01:43:55 - mmengine - INFO - Epoch(val) [100][15/32] eta: 0:00:18 time: 0.6480 data_time: 0.0715 memory: 15734 2022/08/30 01:43:59 - mmengine - INFO - Epoch(val) [100][20/32] eta: 0:00:08 time: 0.6672 data_time: 0.0659 memory: 15734 2022/08/30 01:44:03 - mmengine - INFO - Epoch(val) [100][25/32] eta: 0:00:08 time: 0.7698 data_time: 0.0831 memory: 15734 2022/08/30 01:44:06 - mmengine - INFO - Epoch(val) [100][30/32] eta: 0:00:01 time: 0.7155 data_time: 0.0454 memory: 15734 2022/08/30 01:44:07 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 01:44:07 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7809, precision: 0.6615, hmean: 0.7163 2022/08/30 01:44:07 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7800, precision: 0.7545, hmean: 0.7670 2022/08/30 01:44:07 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7713, precision: 0.8022, hmean: 0.7865 2022/08/30 01:44:07 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7492, precision: 0.8447, hmean: 0.7941 2022/08/30 01:44:07 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6986, precision: 0.8821, hmean: 0.7797 2022/08/30 01:44:07 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4434, precision: 0.9341, hmean: 0.6014 2022/08/30 01:44:07 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0135, precision: 1.0000, hmean: 0.0266 2022/08/30 01:44:07 - mmengine - INFO - Epoch(val) [100][32/32] icdar/precision: 0.8447 icdar/recall: 0.7492 icdar/hmean: 0.7941 2022/08/30 01:44:19 - mmengine - INFO - Epoch(train) [101][5/63] lr: 6.4723e-03 eta: 0:00:01 time: 1.9680 data_time: 0.2713 memory: 16201 loss_prob: 1.3841 loss_thr: 0.6302 loss_db: 0.2336 loss: 2.2480 2022/08/30 01:44:28 - mmengine - INFO - Epoch(train) [101][10/63] lr: 6.4723e-03 eta: 1 day, 3:08:08 time: 2.0614 data_time: 0.2938 memory: 16201 loss_prob: 1.1434 loss_thr: 0.5709 loss_db: 0.1907 loss: 1.9049 2022/08/30 01:44:38 - mmengine - INFO - Epoch(train) [101][15/63] lr: 6.4723e-03 eta: 1 day, 3:08:08 time: 1.8514 data_time: 0.0403 memory: 16201 loss_prob: 1.2327 loss_thr: 0.5461 loss_db: 0.1997 loss: 1.9785 2022/08/30 01:44:47 - mmengine - INFO - Epoch(train) [101][20/63] lr: 6.4723e-03 eta: 1 day, 3:08:46 time: 1.8856 data_time: 0.0384 memory: 16201 loss_prob: 1.4333 loss_thr: 0.5961 loss_db: 0.2239 loss: 2.2533 2022/08/30 01:44:57 - mmengine - INFO - Epoch(train) [101][25/63] lr: 6.4723e-03 eta: 1 day, 3:08:46 time: 1.9802 data_time: 0.0558 memory: 16201 loss_prob: 1.4952 loss_thr: 0.6483 loss_db: 0.2318 loss: 2.3753 2022/08/30 01:45:05 - mmengine - INFO - Epoch(train) [101][30/63] lr: 6.4723e-03 eta: 1 day, 3:09:20 time: 1.8498 data_time: 0.0399 memory: 16201 loss_prob: 1.5861 loss_thr: 0.6678 loss_db: 0.2545 loss: 2.5083 2022/08/30 01:45:15 - mmengine - INFO - Epoch(train) [101][35/63] lr: 6.4723e-03 eta: 1 day, 3:09:20 time: 1.7831 data_time: 0.0404 memory: 16201 loss_prob: 1.4311 loss_thr: 0.6418 loss_db: 0.2339 loss: 2.3068 2022/08/30 01:45:23 - mmengine - INFO - Epoch(train) [101][40/63] lr: 6.4723e-03 eta: 1 day, 3:09:52 time: 1.8295 data_time: 0.0395 memory: 16201 loss_prob: 1.2239 loss_thr: 0.6181 loss_db: 0.1992 loss: 2.0412 2022/08/30 01:45:32 - mmengine - INFO - Epoch(train) [101][45/63] lr: 6.4723e-03 eta: 1 day, 3:09:52 time: 1.7283 data_time: 0.0343 memory: 16201 loss_prob: 1.1409 loss_thr: 0.5944 loss_db: 0.1791 loss: 1.9144 2022/08/30 01:45:41 - mmengine - INFO - Epoch(train) [101][50/63] lr: 6.4723e-03 eta: 1 day, 3:10:19 time: 1.7894 data_time: 0.0523 memory: 16201 loss_prob: 1.1190 loss_thr: 0.5737 loss_db: 0.1765 loss: 1.8692 2022/08/30 01:45:51 - mmengine - INFO - Epoch(train) [101][55/63] lr: 6.4723e-03 eta: 1 day, 3:10:19 time: 1.8536 data_time: 0.0431 memory: 16201 loss_prob: 1.1416 loss_thr: 0.5788 loss_db: 0.1847 loss: 1.9051 2022/08/30 01:46:00 - mmengine - INFO - Epoch(train) [101][60/63] lr: 6.4723e-03 eta: 1 day, 3:10:58 time: 1.9046 data_time: 0.0375 memory: 16201 loss_prob: 1.2735 loss_thr: 0.6026 loss_db: 0.2055 loss: 2.0816 2022/08/30 01:46:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:46:17 - mmengine - INFO - Epoch(train) [102][5/63] lr: 6.4670e-03 eta: 1 day, 3:10:58 time: 2.0680 data_time: 0.2452 memory: 16201 loss_prob: 1.1247 loss_thr: 0.5739 loss_db: 0.1825 loss: 1.8811 2022/08/30 01:46:26 - mmengine - INFO - Epoch(train) [102][10/63] lr: 6.4670e-03 eta: 1 day, 3:11:16 time: 2.1738 data_time: 0.2711 memory: 16201 loss_prob: 1.1486 loss_thr: 0.5753 loss_db: 0.1886 loss: 1.9126 2022/08/30 01:46:34 - mmengine - INFO - Epoch(train) [102][15/63] lr: 6.4670e-03 eta: 1 day, 3:11:16 time: 1.7442 data_time: 0.0482 memory: 16201 loss_prob: 1.1289 loss_thr: 0.5846 loss_db: 0.1809 loss: 1.8943 2022/08/30 01:46:44 - mmengine - INFO - Epoch(train) [102][20/63] lr: 6.4670e-03 eta: 1 day, 3:11:45 time: 1.8115 data_time: 0.0397 memory: 16201 loss_prob: 1.0679 loss_thr: 0.5649 loss_db: 0.1715 loss: 1.8044 2022/08/30 01:46:53 - mmengine - INFO - Epoch(train) [102][25/63] lr: 6.4670e-03 eta: 1 day, 3:11:45 time: 1.8540 data_time: 0.0513 memory: 16201 loss_prob: 1.0676 loss_thr: 0.5446 loss_db: 0.1728 loss: 1.7850 2022/08/30 01:47:01 - mmengine - INFO - Epoch(train) [102][30/63] lr: 6.4670e-03 eta: 1 day, 3:12:00 time: 1.6826 data_time: 0.0494 memory: 16201 loss_prob: 1.1938 loss_thr: 0.5568 loss_db: 0.1893 loss: 1.9399 2022/08/30 01:47:10 - mmengine - INFO - Epoch(train) [102][35/63] lr: 6.4670e-03 eta: 1 day, 3:12:00 time: 1.7114 data_time: 0.0629 memory: 16201 loss_prob: 1.1664 loss_thr: 0.5544 loss_db: 0.1839 loss: 1.9047 2022/08/30 01:47:18 - mmengine - INFO - Epoch(train) [102][40/63] lr: 6.4670e-03 eta: 1 day, 3:12:18 time: 1.7082 data_time: 0.0493 memory: 16201 loss_prob: 1.0750 loss_thr: 0.5630 loss_db: 0.1678 loss: 1.8059 2022/08/30 01:47:26 - mmengine - INFO - Epoch(train) [102][45/63] lr: 6.4670e-03 eta: 1 day, 3:12:18 time: 1.6326 data_time: 0.0414 memory: 16201 loss_prob: 1.0417 loss_thr: 0.5756 loss_db: 0.1668 loss: 1.7841 2022/08/30 01:47:34 - mmengine - INFO - Epoch(train) [102][50/63] lr: 6.4670e-03 eta: 1 day, 3:12:23 time: 1.5915 data_time: 0.0567 memory: 16201 loss_prob: 0.9893 loss_thr: 0.5582 loss_db: 0.1646 loss: 1.7121 2022/08/30 01:47:44 - mmengine - INFO - Epoch(train) [102][55/63] lr: 6.4670e-03 eta: 1 day, 3:12:23 time: 1.8012 data_time: 0.0448 memory: 16201 loss_prob: 1.0495 loss_thr: 0.5693 loss_db: 0.1727 loss: 1.7915 2022/08/30 01:47:52 - mmengine - INFO - Epoch(train) [102][60/63] lr: 6.4670e-03 eta: 1 day, 3:12:47 time: 1.7730 data_time: 0.0467 memory: 16201 loss_prob: 1.0358 loss_thr: 0.5638 loss_db: 0.1680 loss: 1.7677 2022/08/30 01:47:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:48:07 - mmengine - INFO - Epoch(train) [103][5/63] lr: 6.4617e-03 eta: 1 day, 3:12:47 time: 1.7590 data_time: 0.2531 memory: 16201 loss_prob: 1.0540 loss_thr: 0.5533 loss_db: 0.1748 loss: 1.7821 2022/08/30 01:48:16 - mmengine - INFO - Epoch(train) [103][10/63] lr: 6.4617e-03 eta: 1 day, 3:12:48 time: 2.0202 data_time: 0.2712 memory: 16201 loss_prob: 1.0572 loss_thr: 0.5520 loss_db: 0.1783 loss: 1.7875 2022/08/30 01:48:23 - mmengine - INFO - Epoch(train) [103][15/63] lr: 6.4617e-03 eta: 1 day, 3:12:48 time: 1.5764 data_time: 0.0383 memory: 16201 loss_prob: 1.0016 loss_thr: 0.5537 loss_db: 0.1641 loss: 1.7194 2022/08/30 01:48:31 - mmengine - INFO - Epoch(train) [103][20/63] lr: 6.4617e-03 eta: 1 day, 3:12:39 time: 1.4654 data_time: 0.0504 memory: 16201 loss_prob: 1.0958 loss_thr: 0.5762 loss_db: 0.1756 loss: 1.8476 2022/08/30 01:48:38 - mmengine - INFO - Epoch(train) [103][25/63] lr: 6.4617e-03 eta: 1 day, 3:12:39 time: 1.5031 data_time: 0.0513 memory: 16201 loss_prob: 1.0423 loss_thr: 0.5436 loss_db: 0.1738 loss: 1.7598 2022/08/30 01:48:46 - mmengine - INFO - Epoch(train) [103][30/63] lr: 6.4617e-03 eta: 1 day, 3:12:38 time: 1.5457 data_time: 0.0319 memory: 16201 loss_prob: 0.9826 loss_thr: 0.5169 loss_db: 0.1655 loss: 1.6649 2022/08/30 01:48:55 - mmengine - INFO - Epoch(train) [103][35/63] lr: 6.4617e-03 eta: 1 day, 3:12:38 time: 1.7206 data_time: 0.0463 memory: 16201 loss_prob: 1.0179 loss_thr: 0.5505 loss_db: 0.1663 loss: 1.7348 2022/08/30 01:49:05 - mmengine - INFO - Epoch(train) [103][40/63] lr: 6.4617e-03 eta: 1 day, 3:13:11 time: 1.8511 data_time: 0.0366 memory: 16201 loss_prob: 1.0357 loss_thr: 0.5876 loss_db: 0.1689 loss: 1.7921 2022/08/30 01:49:15 - mmengine - INFO - Epoch(train) [103][45/63] lr: 6.4617e-03 eta: 1 day, 3:13:11 time: 1.9355 data_time: 0.0491 memory: 16201 loss_prob: 1.0621 loss_thr: 0.5809 loss_db: 0.1740 loss: 1.8170 2022/08/30 01:49:23 - mmengine - INFO - Epoch(train) [103][50/63] lr: 6.4617e-03 eta: 1 day, 3:13:35 time: 1.7739 data_time: 0.0664 memory: 16201 loss_prob: 1.0852 loss_thr: 0.5535 loss_db: 0.1794 loss: 1.8180 2022/08/30 01:49:32 - mmengine - INFO - Epoch(train) [103][55/63] lr: 6.4617e-03 eta: 1 day, 3:13:35 time: 1.7314 data_time: 0.0382 memory: 16201 loss_prob: 1.1898 loss_thr: 0.5592 loss_db: 0.1928 loss: 1.9418 2022/08/30 01:49:41 - mmengine - INFO - Epoch(train) [103][60/63] lr: 6.4617e-03 eta: 1 day, 3:14:04 time: 1.8304 data_time: 0.0390 memory: 16201 loss_prob: 1.1736 loss_thr: 0.5773 loss_db: 0.1907 loss: 1.9416 2022/08/30 01:49:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:49:57 - mmengine - INFO - Epoch(train) [104][5/63] lr: 6.4564e-03 eta: 1 day, 3:14:04 time: 1.9100 data_time: 0.2839 memory: 16201 loss_prob: 1.0670 loss_thr: 0.5557 loss_db: 0.1777 loss: 1.8003 2022/08/30 01:50:07 - mmengine - INFO - Epoch(train) [104][10/63] lr: 6.4564e-03 eta: 1 day, 3:14:25 time: 2.2145 data_time: 0.3114 memory: 16201 loss_prob: 1.0182 loss_thr: 0.5224 loss_db: 0.1643 loss: 1.7049 2022/08/30 01:50:17 - mmengine - INFO - Epoch(train) [104][15/63] lr: 6.4564e-03 eta: 1 day, 3:14:25 time: 1.9392 data_time: 0.0484 memory: 16201 loss_prob: 0.9854 loss_thr: 0.5291 loss_db: 0.1620 loss: 1.6765 2022/08/30 01:50:26 - mmengine - INFO - Epoch(train) [104][20/63] lr: 6.4564e-03 eta: 1 day, 3:15:04 time: 1.9185 data_time: 0.0403 memory: 16201 loss_prob: 1.0555 loss_thr: 0.5755 loss_db: 0.1732 loss: 1.8041 2022/08/30 01:50:36 - mmengine - INFO - Epoch(train) [104][25/63] lr: 6.4564e-03 eta: 1 day, 3:15:04 time: 1.9079 data_time: 0.0591 memory: 16201 loss_prob: 1.0129 loss_thr: 0.5536 loss_db: 0.1661 loss: 1.7326 2022/08/30 01:50:45 - mmengine - INFO - Epoch(train) [104][30/63] lr: 6.4564e-03 eta: 1 day, 3:15:38 time: 1.8698 data_time: 0.0412 memory: 16201 loss_prob: 1.0317 loss_thr: 0.5546 loss_db: 0.1697 loss: 1.7561 2022/08/30 01:50:52 - mmengine - INFO - Epoch(train) [104][35/63] lr: 6.4564e-03 eta: 1 day, 3:15:38 time: 1.6639 data_time: 0.0448 memory: 16201 loss_prob: 1.0969 loss_thr: 0.5614 loss_db: 0.1805 loss: 1.8389 2022/08/30 01:51:02 - mmengine - INFO - Epoch(train) [104][40/63] lr: 6.4564e-03 eta: 1 day, 3:15:50 time: 1.6721 data_time: 0.0431 memory: 16201 loss_prob: 0.9903 loss_thr: 0.5371 loss_db: 0.1606 loss: 1.6880 2022/08/30 01:51:11 - mmengine - INFO - Epoch(train) [104][45/63] lr: 6.4564e-03 eta: 1 day, 3:15:50 time: 1.8524 data_time: 0.0369 memory: 16201 loss_prob: 0.9622 loss_thr: 0.5313 loss_db: 0.1542 loss: 1.6478 2022/08/30 01:51:21 - mmengine - INFO - Epoch(train) [104][50/63] lr: 6.4564e-03 eta: 1 day, 3:16:22 time: 1.8542 data_time: 0.0525 memory: 16201 loss_prob: 1.1398 loss_thr: 0.5457 loss_db: 0.1795 loss: 1.8650 2022/08/30 01:51:29 - mmengine - INFO - Epoch(train) [104][55/63] lr: 6.4564e-03 eta: 1 day, 3:16:22 time: 1.8059 data_time: 0.0468 memory: 16201 loss_prob: 1.2717 loss_thr: 0.5439 loss_db: 0.1952 loss: 2.0108 2022/08/30 01:51:37 - mmengine - INFO - Epoch(train) [104][60/63] lr: 6.4564e-03 eta: 1 day, 3:16:33 time: 1.6687 data_time: 0.0557 memory: 16201 loss_prob: 1.1044 loss_thr: 0.5422 loss_db: 0.1696 loss: 1.8162 2022/08/30 01:51:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:51:52 - mmengine - INFO - Epoch(train) [105][5/63] lr: 6.4511e-03 eta: 1 day, 3:16:33 time: 1.7516 data_time: 0.2543 memory: 16201 loss_prob: 1.0760 loss_thr: 0.5900 loss_db: 0.1790 loss: 1.8449 2022/08/30 01:52:00 - mmengine - INFO - Epoch(train) [105][10/63] lr: 6.4511e-03 eta: 1 day, 3:16:21 time: 1.9060 data_time: 0.2771 memory: 16201 loss_prob: 1.0746 loss_thr: 0.5843 loss_db: 0.1795 loss: 1.8384 2022/08/30 01:52:08 - mmengine - INFO - Epoch(train) [105][15/63] lr: 6.4511e-03 eta: 1 day, 3:16:21 time: 1.6383 data_time: 0.0498 memory: 16201 loss_prob: 0.9571 loss_thr: 0.5260 loss_db: 0.1594 loss: 1.6426 2022/08/30 01:52:17 - mmengine - INFO - Epoch(train) [105][20/63] lr: 6.4511e-03 eta: 1 day, 3:16:42 time: 1.7607 data_time: 0.0476 memory: 16201 loss_prob: 1.0024 loss_thr: 0.5409 loss_db: 0.1632 loss: 1.7065 2022/08/30 01:52:26 - mmengine - INFO - Epoch(train) [105][25/63] lr: 6.4511e-03 eta: 1 day, 3:16:42 time: 1.7705 data_time: 0.0453 memory: 16201 loss_prob: 1.0811 loss_thr: 0.5404 loss_db: 0.1704 loss: 1.7919 2022/08/30 01:52:35 - mmengine - INFO - Epoch(train) [105][30/63] lr: 6.4511e-03 eta: 1 day, 3:17:01 time: 1.7369 data_time: 0.0407 memory: 16201 loss_prob: 1.0634 loss_thr: 0.5434 loss_db: 0.1704 loss: 1.7773 2022/08/30 01:52:43 - mmengine - INFO - Epoch(train) [105][35/63] lr: 6.4511e-03 eta: 1 day, 3:17:01 time: 1.7401 data_time: 0.0528 memory: 16201 loss_prob: 0.9533 loss_thr: 0.5472 loss_db: 0.1606 loss: 1.6612 2022/08/30 01:52:52 - mmengine - INFO - Epoch(train) [105][40/63] lr: 6.4511e-03 eta: 1 day, 3:17:17 time: 1.7144 data_time: 0.0381 memory: 16201 loss_prob: 0.9694 loss_thr: 0.5382 loss_db: 0.1624 loss: 1.6700 2022/08/30 01:52:59 - mmengine - INFO - Epoch(train) [105][45/63] lr: 6.4511e-03 eta: 1 day, 3:17:17 time: 1.5375 data_time: 0.0326 memory: 16201 loss_prob: 1.2160 loss_thr: 0.5616 loss_db: 0.1999 loss: 1.9775 2022/08/30 01:53:06 - mmengine - INFO - Epoch(train) [105][50/63] lr: 6.4511e-03 eta: 1 day, 3:17:06 time: 1.4538 data_time: 0.0443 memory: 16201 loss_prob: 1.3148 loss_thr: 0.5783 loss_db: 0.2170 loss: 2.1102 2022/08/30 01:53:14 - mmengine - INFO - Epoch(train) [105][55/63] lr: 6.4511e-03 eta: 1 day, 3:17:06 time: 1.5021 data_time: 0.0446 memory: 16201 loss_prob: 1.1183 loss_thr: 0.5689 loss_db: 0.1829 loss: 1.8702 2022/08/30 01:53:23 - mmengine - INFO - Epoch(train) [105][60/63] lr: 6.4511e-03 eta: 1 day, 3:17:17 time: 1.6627 data_time: 0.0942 memory: 16201 loss_prob: 1.1404 loss_thr: 0.5778 loss_db: 0.1884 loss: 1.9065 2022/08/30 01:53:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:53:38 - mmengine - INFO - Epoch(train) [106][5/63] lr: 6.4458e-03 eta: 1 day, 3:17:17 time: 1.7625 data_time: 0.3153 memory: 16201 loss_prob: 1.2502 loss_thr: 0.5801 loss_db: 0.1963 loss: 2.0265 2022/08/30 01:53:47 - mmengine - INFO - Epoch(train) [106][10/63] lr: 6.4458e-03 eta: 1 day, 3:17:05 time: 1.9145 data_time: 0.3592 memory: 16201 loss_prob: 1.2527 loss_thr: 0.6039 loss_db: 0.1977 loss: 2.0542 2022/08/30 01:53:54 - mmengine - INFO - Epoch(train) [106][15/63] lr: 6.4458e-03 eta: 1 day, 3:17:05 time: 1.6412 data_time: 0.0925 memory: 16201 loss_prob: 1.1832 loss_thr: 0.6160 loss_db: 0.1926 loss: 1.9918 2022/08/30 01:54:05 - mmengine - INFO - Epoch(train) [106][20/63] lr: 6.4458e-03 eta: 1 day, 3:17:38 time: 1.8794 data_time: 0.0885 memory: 16201 loss_prob: 1.0291 loss_thr: 0.5834 loss_db: 0.1683 loss: 1.7807 2022/08/30 01:54:14 - mmengine - INFO - Epoch(train) [106][25/63] lr: 6.4458e-03 eta: 1 day, 3:17:38 time: 1.9534 data_time: 0.1257 memory: 16201 loss_prob: 1.0285 loss_thr: 0.5586 loss_db: 0.1701 loss: 1.7571 2022/08/30 01:54:22 - mmengine - INFO - Epoch(train) [106][30/63] lr: 6.4458e-03 eta: 1 day, 3:17:51 time: 1.6845 data_time: 0.0927 memory: 16201 loss_prob: 1.0910 loss_thr: 0.5474 loss_db: 0.1825 loss: 1.8209 2022/08/30 01:54:31 - mmengine - INFO - Epoch(train) [106][35/63] lr: 6.4458e-03 eta: 1 day, 3:17:51 time: 1.7688 data_time: 0.0865 memory: 16201 loss_prob: 1.4788 loss_thr: 0.5752 loss_db: 0.2387 loss: 2.2927 2022/08/30 01:54:39 - mmengine - INFO - Epoch(train) [106][40/63] lr: 6.4458e-03 eta: 1 day, 3:18:05 time: 1.7032 data_time: 0.0816 memory: 16201 loss_prob: 1.5197 loss_thr: 0.6059 loss_db: 0.2369 loss: 2.3625 2022/08/30 01:54:49 - mmengine - INFO - Epoch(train) [106][45/63] lr: 6.4458e-03 eta: 1 day, 3:18:05 time: 1.7525 data_time: 0.1061 memory: 16201 loss_prob: 1.3088 loss_thr: 0.5991 loss_db: 0.1984 loss: 2.1063 2022/08/30 01:54:58 - mmengine - INFO - Epoch(train) [106][50/63] lr: 6.4458e-03 eta: 1 day, 3:18:35 time: 1.8530 data_time: 0.1082 memory: 16201 loss_prob: 1.3051 loss_thr: 0.5888 loss_db: 0.2034 loss: 2.0973 2022/08/30 01:55:09 - mmengine - INFO - Epoch(train) [106][55/63] lr: 6.4458e-03 eta: 1 day, 3:18:35 time: 1.9837 data_time: 0.0809 memory: 16201 loss_prob: 1.2076 loss_thr: 0.5849 loss_db: 0.1988 loss: 1.9913 2022/08/30 01:55:19 - mmengine - INFO - Epoch(train) [106][60/63] lr: 6.4458e-03 eta: 1 day, 3:19:27 time: 2.0673 data_time: 0.1246 memory: 16201 loss_prob: 1.2227 loss_thr: 0.5883 loss_db: 0.1972 loss: 2.0083 2022/08/30 01:55:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:55:37 - mmengine - INFO - Epoch(train) [107][5/63] lr: 6.4405e-03 eta: 1 day, 3:19:27 time: 2.2503 data_time: 0.3096 memory: 16201 loss_prob: 1.2475 loss_thr: 0.5988 loss_db: 0.2005 loss: 2.0469 2022/08/30 01:55:47 - mmengine - INFO - Epoch(train) [107][10/63] lr: 6.4405e-03 eta: 1 day, 3:19:46 time: 2.2197 data_time: 0.3700 memory: 16201 loss_prob: 1.1455 loss_thr: 0.5743 loss_db: 0.1813 loss: 1.9010 2022/08/30 01:55:55 - mmengine - INFO - Epoch(train) [107][15/63] lr: 6.4405e-03 eta: 1 day, 3:19:46 time: 1.7852 data_time: 0.0884 memory: 16201 loss_prob: 1.0896 loss_thr: 0.5626 loss_db: 0.1721 loss: 1.8243 2022/08/30 01:56:05 - mmengine - INFO - Epoch(train) [107][20/63] lr: 6.4405e-03 eta: 1 day, 3:20:16 time: 1.8541 data_time: 0.0526 memory: 16201 loss_prob: 1.0487 loss_thr: 0.5605 loss_db: 0.1685 loss: 1.7777 2022/08/30 01:56:13 - mmengine - INFO - Epoch(train) [107][25/63] lr: 6.4405e-03 eta: 1 day, 3:20:16 time: 1.7866 data_time: 0.0698 memory: 16201 loss_prob: 1.1060 loss_thr: 0.5625 loss_db: 0.1779 loss: 1.8464 2022/08/30 01:56:22 - mmengine - INFO - Epoch(train) [107][30/63] lr: 6.4405e-03 eta: 1 day, 3:20:29 time: 1.7003 data_time: 0.0369 memory: 16201 loss_prob: 1.0687 loss_thr: 0.5674 loss_db: 0.1724 loss: 1.8085 2022/08/30 01:56:30 - mmengine - INFO - Epoch(train) [107][35/63] lr: 6.4405e-03 eta: 1 day, 3:20:29 time: 1.7213 data_time: 0.0379 memory: 16201 loss_prob: 1.0034 loss_thr: 0.5612 loss_db: 0.1662 loss: 1.7308 2022/08/30 01:56:38 - mmengine - INFO - Epoch(train) [107][40/63] lr: 6.4405e-03 eta: 1 day, 3:20:30 time: 1.5748 data_time: 0.0427 memory: 16201 loss_prob: 1.0005 loss_thr: 0.5478 loss_db: 0.1673 loss: 1.7156 2022/08/30 01:56:47 - mmengine - INFO - Epoch(train) [107][45/63] lr: 6.4405e-03 eta: 1 day, 3:20:30 time: 1.6377 data_time: 0.0464 memory: 16201 loss_prob: 1.0408 loss_thr: 0.5511 loss_db: 0.1684 loss: 1.7603 2022/08/30 01:56:56 - mmengine - INFO - Epoch(train) [107][50/63] lr: 6.4405e-03 eta: 1 day, 3:20:52 time: 1.7854 data_time: 0.0598 memory: 16201 loss_prob: 1.1626 loss_thr: 0.5669 loss_db: 0.1826 loss: 1.9120 2022/08/30 01:57:04 - mmengine - INFO - Epoch(train) [107][55/63] lr: 6.4405e-03 eta: 1 day, 3:20:52 time: 1.7126 data_time: 0.0402 memory: 16201 loss_prob: 1.1131 loss_thr: 0.5552 loss_db: 0.1779 loss: 1.8463 2022/08/30 01:57:11 - mmengine - INFO - Epoch(train) [107][60/63] lr: 6.4405e-03 eta: 1 day, 3:20:53 time: 1.5810 data_time: 0.0395 memory: 16201 loss_prob: 1.0293 loss_thr: 0.5406 loss_db: 0.1688 loss: 1.7387 2022/08/30 01:57:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:57:26 - mmengine - INFO - Epoch(train) [108][5/63] lr: 6.4352e-03 eta: 1 day, 3:20:53 time: 1.6773 data_time: 0.2647 memory: 16201 loss_prob: 0.9931 loss_thr: 0.5270 loss_db: 0.1597 loss: 1.6798 2022/08/30 01:57:34 - mmengine - INFO - Epoch(train) [108][10/63] lr: 6.4352e-03 eta: 1 day, 3:20:41 time: 1.9233 data_time: 0.2853 memory: 16201 loss_prob: 0.9647 loss_thr: 0.5319 loss_db: 0.1586 loss: 1.6552 2022/08/30 01:57:41 - mmengine - INFO - Epoch(train) [108][15/63] lr: 6.4352e-03 eta: 1 day, 3:20:41 time: 1.5279 data_time: 0.0435 memory: 16201 loss_prob: 0.9991 loss_thr: 0.5527 loss_db: 0.1648 loss: 1.7166 2022/08/30 01:57:49 - mmengine - INFO - Epoch(train) [108][20/63] lr: 6.4352e-03 eta: 1 day, 3:20:32 time: 1.4785 data_time: 0.0401 memory: 16201 loss_prob: 0.9918 loss_thr: 0.5540 loss_db: 0.1580 loss: 1.7038 2022/08/30 01:57:58 - mmengine - INFO - Epoch(train) [108][25/63] lr: 6.4352e-03 eta: 1 day, 3:20:32 time: 1.6807 data_time: 0.0401 memory: 16201 loss_prob: 0.9535 loss_thr: 0.5362 loss_db: 0.1531 loss: 1.6428 2022/08/30 01:58:06 - mmengine - INFO - Epoch(train) [108][30/63] lr: 6.4352e-03 eta: 1 day, 3:20:48 time: 1.7278 data_time: 0.0507 memory: 16201 loss_prob: 0.9143 loss_thr: 0.5411 loss_db: 0.1547 loss: 1.6101 2022/08/30 01:58:14 - mmengine - INFO - Epoch(train) [108][35/63] lr: 6.4352e-03 eta: 1 day, 3:20:48 time: 1.6426 data_time: 0.0635 memory: 16201 loss_prob: 1.0641 loss_thr: 0.5820 loss_db: 0.1767 loss: 1.8228 2022/08/30 01:58:22 - mmengine - INFO - Epoch(train) [108][40/63] lr: 6.4352e-03 eta: 1 day, 3:20:50 time: 1.5881 data_time: 0.0465 memory: 16201 loss_prob: 1.1364 loss_thr: 0.5918 loss_db: 0.1867 loss: 1.9149 2022/08/30 01:58:31 - mmengine - INFO - Epoch(train) [108][45/63] lr: 6.4352e-03 eta: 1 day, 3:20:50 time: 1.6788 data_time: 0.0454 memory: 16201 loss_prob: 1.1083 loss_thr: 0.5822 loss_db: 0.1835 loss: 1.8740 2022/08/30 01:58:40 - mmengine - INFO - Epoch(train) [108][50/63] lr: 6.4352e-03 eta: 1 day, 3:21:17 time: 1.8351 data_time: 0.0432 memory: 16201 loss_prob: 1.0508 loss_thr: 0.5648 loss_db: 0.1742 loss: 1.7899 2022/08/30 01:58:50 - mmengine - INFO - Epoch(train) [108][55/63] lr: 6.4352e-03 eta: 1 day, 3:21:17 time: 1.8644 data_time: 0.0469 memory: 16201 loss_prob: 0.9399 loss_thr: 0.5362 loss_db: 0.1573 loss: 1.6333 2022/08/30 01:58:58 - mmengine - INFO - Epoch(train) [108][60/63] lr: 6.4352e-03 eta: 1 day, 3:21:37 time: 1.7801 data_time: 0.0541 memory: 16201 loss_prob: 1.0321 loss_thr: 0.5723 loss_db: 0.1722 loss: 1.7766 2022/08/30 01:59:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 01:59:14 - mmengine - INFO - Epoch(train) [109][5/63] lr: 6.4299e-03 eta: 1 day, 3:21:37 time: 1.9418 data_time: 0.2827 memory: 16201 loss_prob: 1.0368 loss_thr: 0.5703 loss_db: 0.1719 loss: 1.7789 2022/08/30 01:59:22 - mmengine - INFO - Epoch(train) [109][10/63] lr: 6.4299e-03 eta: 1 day, 3:21:25 time: 1.9201 data_time: 0.2945 memory: 16201 loss_prob: 1.1274 loss_thr: 0.5659 loss_db: 0.1804 loss: 1.8737 2022/08/30 01:59:31 - mmengine - INFO - Epoch(train) [109][15/63] lr: 6.4299e-03 eta: 1 day, 3:21:25 time: 1.7160 data_time: 0.0390 memory: 16201 loss_prob: 1.1122 loss_thr: 0.5473 loss_db: 0.1792 loss: 1.8387 2022/08/30 01:59:40 - mmengine - INFO - Epoch(train) [109][20/63] lr: 6.4299e-03 eta: 1 day, 3:21:47 time: 1.7903 data_time: 0.0363 memory: 16201 loss_prob: 0.9467 loss_thr: 0.5419 loss_db: 0.1559 loss: 1.6445 2022/08/30 01:59:48 - mmengine - INFO - Epoch(train) [109][25/63] lr: 6.4299e-03 eta: 1 day, 3:21:47 time: 1.7096 data_time: 0.0405 memory: 16201 loss_prob: 0.9377 loss_thr: 0.5357 loss_db: 0.1550 loss: 1.6285 2022/08/30 01:59:57 - mmengine - INFO - Epoch(train) [109][30/63] lr: 6.4299e-03 eta: 1 day, 3:21:57 time: 1.6751 data_time: 0.0386 memory: 16201 loss_prob: 0.9861 loss_thr: 0.5394 loss_db: 0.1608 loss: 1.6863 2022/08/30 02:00:09 - mmengine - INFO - Epoch(train) [109][35/63] lr: 6.4299e-03 eta: 1 day, 3:21:57 time: 2.0985 data_time: 0.0573 memory: 16201 loss_prob: 0.9574 loss_thr: 0.5286 loss_db: 0.1519 loss: 1.6380 2022/08/30 02:00:18 - mmengine - INFO - Epoch(train) [109][40/63] lr: 6.4299e-03 eta: 1 day, 3:22:53 time: 2.1390 data_time: 0.0627 memory: 16201 loss_prob: 0.9405 loss_thr: 0.5118 loss_db: 0.1537 loss: 1.6060 2022/08/30 02:00:27 - mmengine - INFO - Epoch(train) [109][45/63] lr: 6.4299e-03 eta: 1 day, 3:22:53 time: 1.7920 data_time: 0.0601 memory: 16201 loss_prob: 1.0146 loss_thr: 0.5332 loss_db: 0.1692 loss: 1.7170 2022/08/30 02:00:35 - mmengine - INFO - Epoch(train) [109][50/63] lr: 6.4299e-03 eta: 1 day, 3:23:04 time: 1.6793 data_time: 0.0532 memory: 16201 loss_prob: 1.1645 loss_thr: 0.5989 loss_db: 0.1879 loss: 1.9513 2022/08/30 02:00:43 - mmengine - INFO - Epoch(train) [109][55/63] lr: 6.4299e-03 eta: 1 day, 3:23:04 time: 1.5833 data_time: 0.0438 memory: 16201 loss_prob: 1.2034 loss_thr: 0.6242 loss_db: 0.1986 loss: 2.0261 2022/08/30 02:00:52 - mmengine - INFO - Epoch(train) [109][60/63] lr: 6.4299e-03 eta: 1 day, 3:23:10 time: 1.6370 data_time: 0.0471 memory: 16201 loss_prob: 1.0772 loss_thr: 0.5862 loss_db: 0.1812 loss: 1.8446 2022/08/30 02:00:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:01:08 - mmengine - INFO - Epoch(train) [110][5/63] lr: 6.4246e-03 eta: 1 day, 3:23:10 time: 1.8743 data_time: 0.2648 memory: 16201 loss_prob: 1.0450 loss_thr: 0.5457 loss_db: 0.1647 loss: 1.7553 2022/08/30 02:01:17 - mmengine - INFO - Epoch(train) [110][10/63] lr: 6.4246e-03 eta: 1 day, 3:23:20 time: 2.1550 data_time: 0.2868 memory: 16201 loss_prob: 1.1159 loss_thr: 0.5963 loss_db: 0.1778 loss: 1.8900 2022/08/30 02:01:26 - mmengine - INFO - Epoch(train) [110][15/63] lr: 6.4246e-03 eta: 1 day, 3:23:20 time: 1.8146 data_time: 0.0569 memory: 16201 loss_prob: 1.0570 loss_thr: 0.5695 loss_db: 0.1721 loss: 1.7986 2022/08/30 02:01:37 - mmengine - INFO - Epoch(train) [110][20/63] lr: 6.4246e-03 eta: 1 day, 3:23:55 time: 1.9253 data_time: 0.0572 memory: 16201 loss_prob: 0.9676 loss_thr: 0.5346 loss_db: 0.1597 loss: 1.6618 2022/08/30 02:01:45 - mmengine - INFO - Epoch(train) [110][25/63] lr: 6.4246e-03 eta: 1 day, 3:23:55 time: 1.8831 data_time: 0.0516 memory: 16201 loss_prob: 1.0601 loss_thr: 0.5535 loss_db: 0.1698 loss: 1.7835 2022/08/30 02:01:53 - mmengine - INFO - Epoch(train) [110][30/63] lr: 6.4246e-03 eta: 1 day, 3:24:02 time: 1.6495 data_time: 0.0393 memory: 16201 loss_prob: 0.9933 loss_thr: 0.5249 loss_db: 0.1593 loss: 1.6775 2022/08/30 02:02:01 - mmengine - INFO - Epoch(train) [110][35/63] lr: 6.4246e-03 eta: 1 day, 3:24:02 time: 1.5972 data_time: 0.0473 memory: 16201 loss_prob: 1.0573 loss_thr: 0.5273 loss_db: 0.1749 loss: 1.7595 2022/08/30 02:02:08 - mmengine - INFO - Epoch(train) [110][40/63] lr: 6.4246e-03 eta: 1 day, 3:23:55 time: 1.5118 data_time: 0.0308 memory: 16201 loss_prob: 1.0350 loss_thr: 0.5420 loss_db: 0.1741 loss: 1.7510 2022/08/30 02:02:17 - mmengine - INFO - Epoch(train) [110][45/63] lr: 6.4246e-03 eta: 1 day, 3:23:55 time: 1.6150 data_time: 0.0333 memory: 16201 loss_prob: 1.0137 loss_thr: 0.5479 loss_db: 0.1691 loss: 1.7308 2022/08/30 02:02:25 - mmengine - INFO - Epoch(train) [110][50/63] lr: 6.4246e-03 eta: 1 day, 3:24:04 time: 1.6696 data_time: 0.0457 memory: 16201 loss_prob: 1.0993 loss_thr: 0.5689 loss_db: 0.1805 loss: 1.8486 2022/08/30 02:02:34 - mmengine - INFO - Epoch(train) [110][55/63] lr: 6.4246e-03 eta: 1 day, 3:24:04 time: 1.7368 data_time: 0.0370 memory: 16201 loss_prob: 1.0017 loss_thr: 0.5626 loss_db: 0.1653 loss: 1.7296 2022/08/30 02:02:43 - mmengine - INFO - Epoch(train) [110][60/63] lr: 6.4246e-03 eta: 1 day, 3:24:22 time: 1.7682 data_time: 0.0389 memory: 16201 loss_prob: 1.0160 loss_thr: 0.5661 loss_db: 0.1677 loss: 1.7498 2022/08/30 02:02:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:02:59 - mmengine - INFO - Epoch(train) [111][5/63] lr: 6.4193e-03 eta: 1 day, 3:24:22 time: 1.9694 data_time: 0.2941 memory: 16201 loss_prob: 0.9880 loss_thr: 0.5321 loss_db: 0.1606 loss: 1.6808 2022/08/30 02:03:08 - mmengine - INFO - Epoch(train) [111][10/63] lr: 6.4193e-03 eta: 1 day, 3:24:17 time: 2.0035 data_time: 0.3018 memory: 16201 loss_prob: 1.0050 loss_thr: 0.5387 loss_db: 0.1657 loss: 1.7095 2022/08/30 02:03:16 - mmengine - INFO - Epoch(train) [111][15/63] lr: 6.4193e-03 eta: 1 day, 3:24:17 time: 1.7090 data_time: 0.0406 memory: 16201 loss_prob: 0.9630 loss_thr: 0.5234 loss_db: 0.1569 loss: 1.6432 2022/08/30 02:03:25 - mmengine - INFO - Epoch(train) [111][20/63] lr: 6.4193e-03 eta: 1 day, 3:24:28 time: 1.6921 data_time: 0.0438 memory: 16201 loss_prob: 0.9262 loss_thr: 0.5344 loss_db: 0.1504 loss: 1.6110 2022/08/30 02:03:34 - mmengine - INFO - Epoch(train) [111][25/63] lr: 6.4193e-03 eta: 1 day, 3:24:28 time: 1.8275 data_time: 0.0494 memory: 16201 loss_prob: 0.9267 loss_thr: 0.5447 loss_db: 0.1529 loss: 1.6243 2022/08/30 02:03:44 - mmengine - INFO - Epoch(train) [111][30/63] lr: 6.4193e-03 eta: 1 day, 3:25:06 time: 1.9680 data_time: 0.0425 memory: 16201 loss_prob: 0.9229 loss_thr: 0.5286 loss_db: 0.1539 loss: 1.6054 2022/08/30 02:03:53 - mmengine - INFO - Epoch(train) [111][35/63] lr: 6.4193e-03 eta: 1 day, 3:25:06 time: 1.8337 data_time: 0.0433 memory: 16201 loss_prob: 0.9614 loss_thr: 0.5319 loss_db: 0.1600 loss: 1.6532 2022/08/30 02:04:00 - mmengine - INFO - Epoch(train) [111][40/63] lr: 6.4193e-03 eta: 1 day, 3:25:07 time: 1.5984 data_time: 0.0349 memory: 16201 loss_prob: 0.9256 loss_thr: 0.5131 loss_db: 0.1531 loss: 1.5918 2022/08/30 02:04:10 - mmengine - INFO - Epoch(train) [111][45/63] lr: 6.4193e-03 eta: 1 day, 3:25:07 time: 1.7501 data_time: 0.0444 memory: 16201 loss_prob: 0.9540 loss_thr: 0.5166 loss_db: 0.1569 loss: 1.6275 2022/08/30 02:04:20 - mmengine - INFO - Epoch(train) [111][50/63] lr: 6.4193e-03 eta: 1 day, 3:25:41 time: 1.9327 data_time: 0.0518 memory: 16201 loss_prob: 1.0835 loss_thr: 0.5466 loss_db: 0.1745 loss: 1.8046 2022/08/30 02:04:28 - mmengine - INFO - Epoch(train) [111][55/63] lr: 6.4193e-03 eta: 1 day, 3:25:41 time: 1.7995 data_time: 0.0384 memory: 16201 loss_prob: 1.0706 loss_thr: 0.5483 loss_db: 0.1736 loss: 1.7926 2022/08/30 02:04:37 - mmengine - INFO - Epoch(train) [111][60/63] lr: 6.4193e-03 eta: 1 day, 3:25:54 time: 1.7163 data_time: 0.0475 memory: 16201 loss_prob: 1.0508 loss_thr: 0.5440 loss_db: 0.1701 loss: 1.7650 2022/08/30 02:04:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:04:52 - mmengine - INFO - Epoch(train) [112][5/63] lr: 6.4140e-03 eta: 1 day, 3:25:54 time: 1.9099 data_time: 0.2706 memory: 16201 loss_prob: 0.9810 loss_thr: 0.5209 loss_db: 0.1632 loss: 1.6651 2022/08/30 02:04:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:05:01 - mmengine - INFO - Epoch(train) [112][10/63] lr: 6.4140e-03 eta: 1 day, 3:25:44 time: 1.9596 data_time: 0.2970 memory: 16201 loss_prob: 0.8834 loss_thr: 0.5080 loss_db: 0.1477 loss: 1.5390 2022/08/30 02:05:10 - mmengine - INFO - Epoch(train) [112][15/63] lr: 6.4140e-03 eta: 1 day, 3:25:44 time: 1.7377 data_time: 0.0486 memory: 16201 loss_prob: 0.9515 loss_thr: 0.5023 loss_db: 0.1555 loss: 1.6093 2022/08/30 02:05:19 - mmengine - INFO - Epoch(train) [112][20/63] lr: 6.4140e-03 eta: 1 day, 3:26:07 time: 1.8211 data_time: 0.0464 memory: 16201 loss_prob: 1.0006 loss_thr: 0.5117 loss_db: 0.1652 loss: 1.6774 2022/08/30 02:05:26 - mmengine - INFO - Epoch(train) [112][25/63] lr: 6.4140e-03 eta: 1 day, 3:26:07 time: 1.6180 data_time: 0.0932 memory: 16201 loss_prob: 0.9198 loss_thr: 0.5107 loss_db: 0.1538 loss: 1.5843 2022/08/30 02:05:35 - mmengine - INFO - Epoch(train) [112][30/63] lr: 6.4140e-03 eta: 1 day, 3:26:09 time: 1.6030 data_time: 0.0810 memory: 16201 loss_prob: 0.8898 loss_thr: 0.5145 loss_db: 0.1442 loss: 1.5485 2022/08/30 02:05:43 - mmengine - INFO - Epoch(train) [112][35/63] lr: 6.4140e-03 eta: 1 day, 3:26:09 time: 1.6566 data_time: 0.0490 memory: 16201 loss_prob: 0.9973 loss_thr: 0.5419 loss_db: 0.1565 loss: 1.6957 2022/08/30 02:05:51 - mmengine - INFO - Epoch(train) [112][40/63] lr: 6.4140e-03 eta: 1 day, 3:26:13 time: 1.6294 data_time: 0.0415 memory: 16201 loss_prob: 1.0955 loss_thr: 0.5718 loss_db: 0.1724 loss: 1.8396 2022/08/30 02:06:00 - mmengine - INFO - Epoch(train) [112][45/63] lr: 6.4140e-03 eta: 1 day, 3:26:13 time: 1.6975 data_time: 0.0372 memory: 16201 loss_prob: 1.0272 loss_thr: 0.5415 loss_db: 0.1653 loss: 1.7341 2022/08/30 02:06:10 - mmengine - INFO - Epoch(train) [112][50/63] lr: 6.4140e-03 eta: 1 day, 3:26:38 time: 1.8531 data_time: 0.0521 memory: 16201 loss_prob: 0.9690 loss_thr: 0.5184 loss_db: 0.1568 loss: 1.6441 2022/08/30 02:06:18 - mmengine - INFO - Epoch(train) [112][55/63] lr: 6.4140e-03 eta: 1 day, 3:26:38 time: 1.8159 data_time: 0.0459 memory: 16201 loss_prob: 1.0465 loss_thr: 0.5419 loss_db: 0.1760 loss: 1.7644 2022/08/30 02:06:27 - mmengine - INFO - Epoch(train) [112][60/63] lr: 6.4140e-03 eta: 1 day, 3:26:46 time: 1.6632 data_time: 0.0517 memory: 16201 loss_prob: 1.0403 loss_thr: 0.5409 loss_db: 0.1779 loss: 1.7591 2022/08/30 02:06:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:06:40 - mmengine - INFO - Epoch(train) [113][5/63] lr: 6.4087e-03 eta: 1 day, 3:26:46 time: 1.6382 data_time: 0.2768 memory: 16201 loss_prob: 1.0045 loss_thr: 0.5393 loss_db: 0.1661 loss: 1.7099 2022/08/30 02:06:47 - mmengine - INFO - Epoch(train) [113][10/63] lr: 6.4087e-03 eta: 1 day, 3:26:17 time: 1.7699 data_time: 0.2922 memory: 16201 loss_prob: 1.0011 loss_thr: 0.5547 loss_db: 0.1650 loss: 1.7209 2022/08/30 02:06:54 - mmengine - INFO - Epoch(train) [113][15/63] lr: 6.4087e-03 eta: 1 day, 3:26:17 time: 1.4410 data_time: 0.0388 memory: 16201 loss_prob: 1.0543 loss_thr: 0.5566 loss_db: 0.1731 loss: 1.7841 2022/08/30 02:07:03 - mmengine - INFO - Epoch(train) [113][20/63] lr: 6.4087e-03 eta: 1 day, 3:26:11 time: 1.5310 data_time: 0.0322 memory: 16201 loss_prob: 0.9616 loss_thr: 0.5234 loss_db: 0.1622 loss: 1.6472 2022/08/30 02:07:11 - mmengine - INFO - Epoch(train) [113][25/63] lr: 6.4087e-03 eta: 1 day, 3:26:11 time: 1.7471 data_time: 0.0404 memory: 16201 loss_prob: 0.9385 loss_thr: 0.5127 loss_db: 0.1583 loss: 1.6096 2022/08/30 02:07:20 - mmengine - INFO - Epoch(train) [113][30/63] lr: 6.4087e-03 eta: 1 day, 3:26:27 time: 1.7549 data_time: 0.0397 memory: 16201 loss_prob: 1.1012 loss_thr: 0.5652 loss_db: 0.1798 loss: 1.8463 2022/08/30 02:07:28 - mmengine - INFO - Epoch(train) [113][35/63] lr: 6.4087e-03 eta: 1 day, 3:26:27 time: 1.6783 data_time: 0.0469 memory: 16201 loss_prob: 1.1698 loss_thr: 0.5859 loss_db: 0.1896 loss: 1.9453 2022/08/30 02:07:37 - mmengine - INFO - Epoch(train) [113][40/63] lr: 6.4087e-03 eta: 1 day, 3:26:37 time: 1.6907 data_time: 0.0350 memory: 16201 loss_prob: 1.0401 loss_thr: 0.5623 loss_db: 0.1713 loss: 1.7737 2022/08/30 02:07:46 - mmengine - INFO - Epoch(train) [113][45/63] lr: 6.4087e-03 eta: 1 day, 3:26:37 time: 1.8143 data_time: 0.0363 memory: 16201 loss_prob: 0.9312 loss_thr: 0.5388 loss_db: 0.1542 loss: 1.6242 2022/08/30 02:07:54 - mmengine - INFO - Epoch(train) [113][50/63] lr: 6.4087e-03 eta: 1 day, 3:26:51 time: 1.7437 data_time: 0.0570 memory: 16201 loss_prob: 0.9821 loss_thr: 0.5398 loss_db: 0.1622 loss: 1.6841 2022/08/30 02:08:03 - mmengine - INFO - Epoch(train) [113][55/63] lr: 6.4087e-03 eta: 1 day, 3:26:51 time: 1.6777 data_time: 0.0395 memory: 16201 loss_prob: 1.0156 loss_thr: 0.5561 loss_db: 0.1673 loss: 1.7390 2022/08/30 02:08:11 - mmengine - INFO - Epoch(train) [113][60/63] lr: 6.4087e-03 eta: 1 day, 3:26:56 time: 1.6428 data_time: 0.0335 memory: 16201 loss_prob: 1.0058 loss_thr: 0.5691 loss_db: 0.1661 loss: 1.7410 2022/08/30 02:08:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:08:26 - mmengine - INFO - Epoch(train) [114][5/63] lr: 6.4034e-03 eta: 1 day, 3:26:56 time: 1.7860 data_time: 0.2667 memory: 16201 loss_prob: 1.0222 loss_thr: 0.5626 loss_db: 0.1664 loss: 1.7512 2022/08/30 02:08:34 - mmengine - INFO - Epoch(train) [114][10/63] lr: 6.4034e-03 eta: 1 day, 3:26:34 time: 1.8403 data_time: 0.2769 memory: 16201 loss_prob: 0.9134 loss_thr: 0.5303 loss_db: 0.1481 loss: 1.5918 2022/08/30 02:08:43 - mmengine - INFO - Epoch(train) [114][15/63] lr: 6.4034e-03 eta: 1 day, 3:26:34 time: 1.6655 data_time: 0.0458 memory: 16201 loss_prob: 0.8227 loss_thr: 0.4988 loss_db: 0.1361 loss: 1.4576 2022/08/30 02:08:52 - mmengine - INFO - Epoch(train) [114][20/63] lr: 6.4034e-03 eta: 1 day, 3:26:53 time: 1.7907 data_time: 0.0566 memory: 16201 loss_prob: 0.9009 loss_thr: 0.5178 loss_db: 0.1522 loss: 1.5709 2022/08/30 02:09:00 - mmengine - INFO - Epoch(train) [114][25/63] lr: 6.4034e-03 eta: 1 day, 3:26:53 time: 1.7880 data_time: 0.0407 memory: 16201 loss_prob: 1.0030 loss_thr: 0.5509 loss_db: 0.1641 loss: 1.7180 2022/08/30 02:09:08 - mmengine - INFO - Epoch(train) [114][30/63] lr: 6.4034e-03 eta: 1 day, 3:27:01 time: 1.6755 data_time: 0.0373 memory: 16201 loss_prob: 1.0439 loss_thr: 0.5647 loss_db: 0.1691 loss: 1.7776 2022/08/30 02:09:17 - mmengine - INFO - Epoch(train) [114][35/63] lr: 6.4034e-03 eta: 1 day, 3:27:01 time: 1.6645 data_time: 0.0560 memory: 16201 loss_prob: 1.1182 loss_thr: 0.5496 loss_db: 0.1770 loss: 1.8448 2022/08/30 02:09:27 - mmengine - INFO - Epoch(train) [114][40/63] lr: 6.4034e-03 eta: 1 day, 3:27:22 time: 1.8161 data_time: 0.0458 memory: 16201 loss_prob: 1.1080 loss_thr: 0.5550 loss_db: 0.1724 loss: 1.8353 2022/08/30 02:09:34 - mmengine - INFO - Epoch(train) [114][45/63] lr: 6.4034e-03 eta: 1 day, 3:27:22 time: 1.7286 data_time: 0.0485 memory: 16201 loss_prob: 0.9685 loss_thr: 0.5396 loss_db: 0.1596 loss: 1.6677 2022/08/30 02:09:43 - mmengine - INFO - Epoch(train) [114][50/63] lr: 6.4034e-03 eta: 1 day, 3:27:30 time: 1.6836 data_time: 0.0504 memory: 16201 loss_prob: 0.9023 loss_thr: 0.5195 loss_db: 0.1502 loss: 1.5719 2022/08/30 02:09:53 - mmengine - INFO - Epoch(train) [114][55/63] lr: 6.4034e-03 eta: 1 day, 3:27:30 time: 1.8450 data_time: 0.0355 memory: 16201 loss_prob: 0.8919 loss_thr: 0.5269 loss_db: 0.1411 loss: 1.5599 2022/08/30 02:10:02 - mmengine - INFO - Epoch(train) [114][60/63] lr: 6.4034e-03 eta: 1 day, 3:27:51 time: 1.8171 data_time: 0.0507 memory: 16201 loss_prob: 0.9982 loss_thr: 0.5442 loss_db: 0.1611 loss: 1.7035 2022/08/30 02:10:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:10:19 - mmengine - INFO - Epoch(train) [115][5/63] lr: 6.3981e-03 eta: 1 day, 3:27:51 time: 2.1094 data_time: 0.2606 memory: 16201 loss_prob: 0.9690 loss_thr: 0.5479 loss_db: 0.1606 loss: 1.6775 2022/08/30 02:10:28 - mmengine - INFO - Epoch(train) [115][10/63] lr: 6.3981e-03 eta: 1 day, 3:27:52 time: 2.0850 data_time: 0.2819 memory: 16201 loss_prob: 0.9844 loss_thr: 0.5584 loss_db: 0.1633 loss: 1.7061 2022/08/30 02:10:35 - mmengine - INFO - Epoch(train) [115][15/63] lr: 6.3981e-03 eta: 1 day, 3:27:52 time: 1.5772 data_time: 0.0463 memory: 16201 loss_prob: 0.9664 loss_thr: 0.5258 loss_db: 0.1589 loss: 1.6510 2022/08/30 02:10:44 - mmengine - INFO - Epoch(train) [115][20/63] lr: 6.3981e-03 eta: 1 day, 3:27:54 time: 1.6218 data_time: 0.0328 memory: 16201 loss_prob: 0.9072 loss_thr: 0.4983 loss_db: 0.1456 loss: 1.5511 2022/08/30 02:10:53 - mmengine - INFO - Epoch(train) [115][25/63] lr: 6.3981e-03 eta: 1 day, 3:27:54 time: 1.8134 data_time: 0.0457 memory: 16201 loss_prob: 0.9339 loss_thr: 0.5212 loss_db: 0.1483 loss: 1.6034 2022/08/30 02:11:01 - mmengine - INFO - Epoch(train) [115][30/63] lr: 6.3981e-03 eta: 1 day, 3:28:07 time: 1.7293 data_time: 0.0392 memory: 16201 loss_prob: 0.9524 loss_thr: 0.5327 loss_db: 0.1531 loss: 1.6382 2022/08/30 02:11:09 - mmengine - INFO - Epoch(train) [115][35/63] lr: 6.3981e-03 eta: 1 day, 3:28:07 time: 1.5632 data_time: 0.0376 memory: 16201 loss_prob: 0.9680 loss_thr: 0.5216 loss_db: 0.1613 loss: 1.6509 2022/08/30 02:11:16 - mmengine - INFO - Epoch(train) [115][40/63] lr: 6.3981e-03 eta: 1 day, 3:27:56 time: 1.4890 data_time: 0.0347 memory: 16201 loss_prob: 0.9342 loss_thr: 0.5111 loss_db: 0.1551 loss: 1.6004 2022/08/30 02:11:23 - mmengine - INFO - Epoch(train) [115][45/63] lr: 6.3981e-03 eta: 1 day, 3:27:56 time: 1.3941 data_time: 0.0326 memory: 16201 loss_prob: 0.9761 loss_thr: 0.5438 loss_db: 0.1561 loss: 1.6760 2022/08/30 02:11:32 - mmengine - INFO - Epoch(train) [115][50/63] lr: 6.3981e-03 eta: 1 day, 3:27:55 time: 1.5855 data_time: 0.0452 memory: 16201 loss_prob: 1.0471 loss_thr: 0.5755 loss_db: 0.1708 loss: 1.7934 2022/08/30 02:11:41 - mmengine - INFO - Epoch(train) [115][55/63] lr: 6.3981e-03 eta: 1 day, 3:27:55 time: 1.8174 data_time: 0.0326 memory: 16201 loss_prob: 1.1310 loss_thr: 0.5933 loss_db: 0.1796 loss: 1.9039 2022/08/30 02:11:49 - mmengine - INFO - Epoch(train) [115][60/63] lr: 6.3981e-03 eta: 1 day, 3:28:06 time: 1.7127 data_time: 0.0418 memory: 16201 loss_prob: 1.1470 loss_thr: 0.5786 loss_db: 0.1824 loss: 1.9080 2022/08/30 02:11:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:12:06 - mmengine - INFO - Epoch(train) [116][5/63] lr: 6.3927e-03 eta: 1 day, 3:28:06 time: 1.9400 data_time: 0.2937 memory: 16201 loss_prob: 0.9712 loss_thr: 0.5409 loss_db: 0.1572 loss: 1.6693 2022/08/30 02:12:15 - mmengine - INFO - Epoch(train) [116][10/63] lr: 6.3927e-03 eta: 1 day, 3:28:12 time: 2.1450 data_time: 0.3192 memory: 16201 loss_prob: 0.8620 loss_thr: 0.5211 loss_db: 0.1420 loss: 1.5251 2022/08/30 02:12:23 - mmengine - INFO - Epoch(train) [116][15/63] lr: 6.3927e-03 eta: 1 day, 3:28:12 time: 1.7206 data_time: 0.0424 memory: 16201 loss_prob: 0.9159 loss_thr: 0.5519 loss_db: 0.1514 loss: 1.6192 2022/08/30 02:12:32 - mmengine - INFO - Epoch(train) [116][20/63] lr: 6.3927e-03 eta: 1 day, 3:28:16 time: 1.6435 data_time: 0.0334 memory: 16201 loss_prob: 0.9433 loss_thr: 0.5608 loss_db: 0.1577 loss: 1.6619 2022/08/30 02:12:40 - mmengine - INFO - Epoch(train) [116][25/63] lr: 6.3927e-03 eta: 1 day, 3:28:16 time: 1.6909 data_time: 0.0414 memory: 16201 loss_prob: 0.9247 loss_thr: 0.5307 loss_db: 0.1561 loss: 1.6114 2022/08/30 02:12:49 - mmengine - INFO - Epoch(train) [116][30/63] lr: 6.3927e-03 eta: 1 day, 3:28:28 time: 1.7303 data_time: 0.0464 memory: 16201 loss_prob: 1.0321 loss_thr: 0.5496 loss_db: 0.1688 loss: 1.7506 2022/08/30 02:12:57 - mmengine - INFO - Epoch(train) [116][35/63] lr: 6.3927e-03 eta: 1 day, 3:28:28 time: 1.7189 data_time: 0.0608 memory: 16201 loss_prob: 0.9976 loss_thr: 0.5324 loss_db: 0.1625 loss: 1.6926 2022/08/30 02:13:06 - mmengine - INFO - Epoch(train) [116][40/63] lr: 6.3927e-03 eta: 1 day, 3:28:41 time: 1.7402 data_time: 0.0429 memory: 16201 loss_prob: 0.9932 loss_thr: 0.5605 loss_db: 0.1638 loss: 1.7174 2022/08/30 02:13:15 - mmengine - INFO - Epoch(train) [116][45/63] lr: 6.3927e-03 eta: 1 day, 3:28:41 time: 1.7725 data_time: 0.0321 memory: 16201 loss_prob: 0.9922 loss_thr: 0.5731 loss_db: 0.1633 loss: 1.7286 2022/08/30 02:13:24 - mmengine - INFO - Epoch(train) [116][50/63] lr: 6.3927e-03 eta: 1 day, 3:28:57 time: 1.7782 data_time: 0.0469 memory: 16201 loss_prob: 0.9234 loss_thr: 0.5254 loss_db: 0.1531 loss: 1.6019 2022/08/30 02:13:33 - mmengine - INFO - Epoch(train) [116][55/63] lr: 6.3927e-03 eta: 1 day, 3:28:57 time: 1.8166 data_time: 0.0325 memory: 16201 loss_prob: 0.9644 loss_thr: 0.5390 loss_db: 0.1585 loss: 1.6619 2022/08/30 02:13:42 - mmengine - INFO - Epoch(train) [116][60/63] lr: 6.3927e-03 eta: 1 day, 3:29:11 time: 1.7497 data_time: 0.0391 memory: 16201 loss_prob: 0.9922 loss_thr: 0.5416 loss_db: 0.1633 loss: 1.6972 2022/08/30 02:13:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:13:57 - mmengine - INFO - Epoch(train) [117][5/63] lr: 6.3874e-03 eta: 1 day, 3:29:11 time: 1.8494 data_time: 0.2539 memory: 16201 loss_prob: 0.9920 loss_thr: 0.5495 loss_db: 0.1647 loss: 1.7062 2022/08/30 02:14:06 - mmengine - INFO - Epoch(train) [117][10/63] lr: 6.3874e-03 eta: 1 day, 3:29:04 time: 2.0117 data_time: 0.2844 memory: 16201 loss_prob: 1.0028 loss_thr: 0.5553 loss_db: 0.1649 loss: 1.7230 2022/08/30 02:14:14 - mmengine - INFO - Epoch(train) [117][15/63] lr: 6.3874e-03 eta: 1 day, 3:29:04 time: 1.7001 data_time: 0.0449 memory: 16201 loss_prob: 1.0088 loss_thr: 0.5589 loss_db: 0.1678 loss: 1.7354 2022/08/30 02:14:23 - mmengine - INFO - Epoch(train) [117][20/63] lr: 6.3874e-03 eta: 1 day, 3:29:14 time: 1.7089 data_time: 0.0349 memory: 16201 loss_prob: 0.9799 loss_thr: 0.5676 loss_db: 0.1642 loss: 1.7116 2022/08/30 02:14:32 - mmengine - INFO - Epoch(train) [117][25/63] lr: 6.3874e-03 eta: 1 day, 3:29:14 time: 1.8687 data_time: 0.0382 memory: 16201 loss_prob: 0.9393 loss_thr: 0.5483 loss_db: 0.1591 loss: 1.6466 2022/08/30 02:14:41 - mmengine - INFO - Epoch(train) [117][30/63] lr: 6.3874e-03 eta: 1 day, 3:29:38 time: 1.8586 data_time: 0.0375 memory: 16201 loss_prob: 0.8822 loss_thr: 0.5114 loss_db: 0.1477 loss: 1.5413 2022/08/30 02:14:50 - mmengine - INFO - Epoch(train) [117][35/63] lr: 6.3874e-03 eta: 1 day, 3:29:38 time: 1.7813 data_time: 0.0513 memory: 16201 loss_prob: 0.9105 loss_thr: 0.5272 loss_db: 0.1485 loss: 1.5861 2022/08/30 02:14:59 - mmengine - INFO - Epoch(train) [117][40/63] lr: 6.3874e-03 eta: 1 day, 3:29:56 time: 1.8096 data_time: 0.0385 memory: 16201 loss_prob: 0.9747 loss_thr: 0.5643 loss_db: 0.1625 loss: 1.7015 2022/08/30 02:15:08 - mmengine - INFO - Epoch(train) [117][45/63] lr: 6.3874e-03 eta: 1 day, 3:29:56 time: 1.7466 data_time: 0.0365 memory: 16201 loss_prob: 0.9394 loss_thr: 0.5403 loss_db: 0.1581 loss: 1.6378 2022/08/30 02:15:18 - mmengine - INFO - Epoch(train) [117][50/63] lr: 6.3874e-03 eta: 1 day, 3:30:23 time: 1.8977 data_time: 0.0539 memory: 16201 loss_prob: 0.9977 loss_thr: 0.5312 loss_db: 0.1632 loss: 1.6921 2022/08/30 02:15:25 - mmengine - INFO - Epoch(train) [117][55/63] lr: 6.3874e-03 eta: 1 day, 3:30:23 time: 1.7520 data_time: 0.0502 memory: 16201 loss_prob: 0.9680 loss_thr: 0.5134 loss_db: 0.1591 loss: 1.6404 2022/08/30 02:15:34 - mmengine - INFO - Epoch(train) [117][60/63] lr: 6.3874e-03 eta: 1 day, 3:30:21 time: 1.5843 data_time: 0.0407 memory: 16201 loss_prob: 0.9276 loss_thr: 0.5053 loss_db: 0.1564 loss: 1.5892 2022/08/30 02:15:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:15:48 - mmengine - INFO - Epoch(train) [118][5/63] lr: 6.3821e-03 eta: 1 day, 3:30:21 time: 1.7660 data_time: 0.2546 memory: 16201 loss_prob: 0.9659 loss_thr: 0.5446 loss_db: 0.1614 loss: 1.6720 2022/08/30 02:15:55 - mmengine - INFO - Epoch(train) [118][10/63] lr: 6.3821e-03 eta: 1 day, 3:29:48 time: 1.7294 data_time: 0.2606 memory: 16201 loss_prob: 0.9788 loss_thr: 0.5295 loss_db: 0.1615 loss: 1.6698 2022/08/30 02:16:04 - mmengine - INFO - Epoch(train) [118][15/63] lr: 6.3821e-03 eta: 1 day, 3:29:48 time: 1.5898 data_time: 0.0451 memory: 16201 loss_prob: 0.9619 loss_thr: 0.5111 loss_db: 0.1592 loss: 1.6322 2022/08/30 02:16:13 - mmengine - INFO - Epoch(train) [118][20/63] lr: 6.3821e-03 eta: 1 day, 3:30:06 time: 1.7992 data_time: 0.0443 memory: 16201 loss_prob: 1.0431 loss_thr: 0.5657 loss_db: 0.1718 loss: 1.7806 2022/08/30 02:16:22 - mmengine - INFO - Epoch(train) [118][25/63] lr: 6.3821e-03 eta: 1 day, 3:30:06 time: 1.8100 data_time: 0.0420 memory: 16201 loss_prob: 0.9853 loss_thr: 0.5512 loss_db: 0.1661 loss: 1.7026 2022/08/30 02:16:30 - mmengine - INFO - Epoch(train) [118][30/63] lr: 6.3821e-03 eta: 1 day, 3:30:14 time: 1.7051 data_time: 0.0375 memory: 16201 loss_prob: 0.8902 loss_thr: 0.5241 loss_db: 0.1507 loss: 1.5651 2022/08/30 02:16:38 - mmengine - INFO - Epoch(train) [118][35/63] lr: 6.3821e-03 eta: 1 day, 3:30:14 time: 1.6118 data_time: 0.0426 memory: 16201 loss_prob: 0.9772 loss_thr: 0.5568 loss_db: 0.1672 loss: 1.7011 2022/08/30 02:16:47 - mmengine - INFO - Epoch(train) [118][40/63] lr: 6.3821e-03 eta: 1 day, 3:30:19 time: 1.6588 data_time: 0.0456 memory: 16201 loss_prob: 1.0130 loss_thr: 0.5722 loss_db: 0.1744 loss: 1.7596 2022/08/30 02:16:55 - mmengine - INFO - Epoch(train) [118][45/63] lr: 6.3821e-03 eta: 1 day, 3:30:19 time: 1.7274 data_time: 0.0492 memory: 16201 loss_prob: 0.9927 loss_thr: 0.5471 loss_db: 0.1654 loss: 1.7052 2022/08/30 02:17:05 - mmengine - INFO - Epoch(train) [118][50/63] lr: 6.3821e-03 eta: 1 day, 3:30:38 time: 1.8162 data_time: 0.0481 memory: 16201 loss_prob: 1.0083 loss_thr: 0.5351 loss_db: 0.1700 loss: 1.7134 2022/08/30 02:17:14 - mmengine - INFO - Epoch(train) [118][55/63] lr: 6.3821e-03 eta: 1 day, 3:30:38 time: 1.8230 data_time: 0.0378 memory: 16201 loss_prob: 0.9946 loss_thr: 0.5491 loss_db: 0.1717 loss: 1.7154 2022/08/30 02:17:23 - mmengine - INFO - Epoch(train) [118][60/63] lr: 6.3821e-03 eta: 1 day, 3:30:53 time: 1.7788 data_time: 0.0385 memory: 16201 loss_prob: 1.0247 loss_thr: 0.5453 loss_db: 0.1702 loss: 1.7402 2022/08/30 02:17:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:17:39 - mmengine - INFO - Epoch(train) [119][5/63] lr: 6.3768e-03 eta: 1 day, 3:30:53 time: 1.9512 data_time: 0.2589 memory: 16201 loss_prob: 1.1612 loss_thr: 0.5544 loss_db: 0.1900 loss: 1.9056 2022/08/30 02:17:48 - mmengine - INFO - Epoch(train) [119][10/63] lr: 6.3768e-03 eta: 1 day, 3:30:57 time: 2.1365 data_time: 0.2872 memory: 16201 loss_prob: 1.1326 loss_thr: 0.5536 loss_db: 0.1900 loss: 1.8762 2022/08/30 02:17:57 - mmengine - INFO - Epoch(train) [119][15/63] lr: 6.3768e-03 eta: 1 day, 3:30:57 time: 1.7466 data_time: 0.0427 memory: 16201 loss_prob: 1.0863 loss_thr: 0.5644 loss_db: 0.1868 loss: 1.8374 2022/08/30 02:18:05 - mmengine - INFO - Epoch(train) [119][20/63] lr: 6.3768e-03 eta: 1 day, 3:31:00 time: 1.6483 data_time: 0.0328 memory: 16201 loss_prob: 1.1616 loss_thr: 0.5641 loss_db: 0.1915 loss: 1.9172 2022/08/30 02:18:14 - mmengine - INFO - Epoch(train) [119][25/63] lr: 6.3768e-03 eta: 1 day, 3:31:00 time: 1.7043 data_time: 0.0458 memory: 16201 loss_prob: 1.2347 loss_thr: 0.5807 loss_db: 0.1991 loss: 2.0145 2022/08/30 02:18:24 - mmengine - INFO - Epoch(train) [119][30/63] lr: 6.3768e-03 eta: 1 day, 3:31:22 time: 1.8560 data_time: 0.0365 memory: 16201 loss_prob: 1.0559 loss_thr: 0.5509 loss_db: 0.1743 loss: 1.7811 2022/08/30 02:18:33 - mmengine - INFO - Epoch(train) [119][35/63] lr: 6.3768e-03 eta: 1 day, 3:31:22 time: 1.9117 data_time: 0.0480 memory: 16201 loss_prob: 0.9876 loss_thr: 0.5474 loss_db: 0.1658 loss: 1.7008 2022/08/30 02:18:42 - mmengine - INFO - Epoch(train) [119][40/63] lr: 6.3768e-03 eta: 1 day, 3:31:43 time: 1.8415 data_time: 0.0446 memory: 16201 loss_prob: 1.0930 loss_thr: 0.5892 loss_db: 0.1800 loss: 1.8623 2022/08/30 02:18:51 - mmengine - INFO - Epoch(train) [119][45/63] lr: 6.3768e-03 eta: 1 day, 3:31:43 time: 1.7696 data_time: 0.0446 memory: 16201 loss_prob: 1.0239 loss_thr: 0.5747 loss_db: 0.1676 loss: 1.7662 2022/08/30 02:18:59 - mmengine - INFO - Epoch(train) [119][50/63] lr: 6.3768e-03 eta: 1 day, 3:31:54 time: 1.7364 data_time: 0.0613 memory: 16201 loss_prob: 1.1535 loss_thr: 0.5965 loss_db: 0.1798 loss: 1.9298 2022/08/30 02:19:09 - mmengine - INFO - Epoch(train) [119][55/63] lr: 6.3768e-03 eta: 1 day, 3:31:54 time: 1.8366 data_time: 0.0373 memory: 16201 loss_prob: 1.1606 loss_thr: 0.5959 loss_db: 0.1796 loss: 1.9361 2022/08/30 02:19:18 - mmengine - INFO - Epoch(train) [119][60/63] lr: 6.3768e-03 eta: 1 day, 3:32:14 time: 1.8319 data_time: 0.0302 memory: 16201 loss_prob: 1.0270 loss_thr: 0.5646 loss_db: 0.1669 loss: 1.7585 2022/08/30 02:19:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:19:34 - mmengine - INFO - Epoch(train) [120][5/63] lr: 6.3715e-03 eta: 1 day, 3:32:14 time: 1.9740 data_time: 0.2600 memory: 16201 loss_prob: 1.1232 loss_thr: 0.5865 loss_db: 0.1885 loss: 1.8982 2022/08/30 02:19:43 - mmengine - INFO - Epoch(train) [120][10/63] lr: 6.3715e-03 eta: 1 day, 3:32:09 time: 2.0440 data_time: 0.2815 memory: 16201 loss_prob: 1.0481 loss_thr: 0.5617 loss_db: 0.1752 loss: 1.7850 2022/08/30 02:19:51 - mmengine - INFO - Epoch(train) [120][15/63] lr: 6.3715e-03 eta: 1 day, 3:32:09 time: 1.6903 data_time: 0.0405 memory: 16201 loss_prob: 0.9310 loss_thr: 0.5526 loss_db: 0.1551 loss: 1.6387 2022/08/30 02:19:59 - mmengine - INFO - Epoch(train) [120][20/63] lr: 6.3715e-03 eta: 1 day, 3:32:10 time: 1.6283 data_time: 0.0390 memory: 16201 loss_prob: 0.9469 loss_thr: 0.5707 loss_db: 0.1577 loss: 1.6753 2022/08/30 02:20:08 - mmengine - INFO - Epoch(train) [120][25/63] lr: 6.3715e-03 eta: 1 day, 3:32:10 time: 1.6678 data_time: 0.0530 memory: 16201 loss_prob: 1.0903 loss_thr: 0.6050 loss_db: 0.1769 loss: 1.8722 2022/08/30 02:20:16 - mmengine - INFO - Epoch(train) [120][30/63] lr: 6.3715e-03 eta: 1 day, 3:32:12 time: 1.6412 data_time: 0.0386 memory: 16201 loss_prob: 1.1999 loss_thr: 0.6364 loss_db: 0.1953 loss: 2.0316 2022/08/30 02:20:23 - mmengine - INFO - Epoch(train) [120][35/63] lr: 6.3715e-03 eta: 1 day, 3:32:12 time: 1.5562 data_time: 0.0394 memory: 16201 loss_prob: 1.1283 loss_thr: 0.5912 loss_db: 0.1881 loss: 1.9076 2022/08/30 02:20:30 - mmengine - INFO - Epoch(train) [120][40/63] lr: 6.3715e-03 eta: 1 day, 3:31:59 time: 1.4690 data_time: 0.0375 memory: 16201 loss_prob: 1.0970 loss_thr: 0.5617 loss_db: 0.1787 loss: 1.8374 2022/08/30 02:20:37 - mmengine - INFO - Epoch(train) [120][45/63] lr: 6.3715e-03 eta: 1 day, 3:31:59 time: 1.4087 data_time: 0.0340 memory: 16201 loss_prob: 1.0436 loss_thr: 0.5517 loss_db: 0.1687 loss: 1.7641 2022/08/30 02:20:46 - mmengine - INFO - Epoch(train) [120][50/63] lr: 6.3715e-03 eta: 1 day, 3:31:58 time: 1.6114 data_time: 0.0461 memory: 16201 loss_prob: 1.0158 loss_thr: 0.5506 loss_db: 0.1699 loss: 1.7363 2022/08/30 02:20:55 - mmengine - INFO - Epoch(train) [120][55/63] lr: 6.3715e-03 eta: 1 day, 3:31:58 time: 1.8103 data_time: 0.0471 memory: 16201 loss_prob: 1.0458 loss_thr: 0.5435 loss_db: 0.1720 loss: 1.7613 2022/08/30 02:21:04 - mmengine - INFO - Epoch(train) [120][60/63] lr: 6.3715e-03 eta: 1 day, 3:32:13 time: 1.7825 data_time: 0.0506 memory: 16201 loss_prob: 1.1317 loss_thr: 0.5528 loss_db: 0.1846 loss: 1.8691 2022/08/30 02:21:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:21:07 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/08/30 02:21:16 - mmengine - INFO - Epoch(val) [120][5/32] eta: 1 day, 3:32:13 time: 0.7142 data_time: 0.1427 memory: 16201 2022/08/30 02:21:20 - mmengine - INFO - Epoch(val) [120][10/32] eta: 0:00:17 time: 0.8168 data_time: 0.1921 memory: 15734 2022/08/30 02:21:23 - mmengine - INFO - Epoch(val) [120][15/32] eta: 0:00:17 time: 0.6782 data_time: 0.0740 memory: 15734 2022/08/30 02:21:27 - mmengine - INFO - Epoch(val) [120][20/32] eta: 0:00:08 time: 0.7359 data_time: 0.0780 memory: 15734 2022/08/30 02:21:30 - mmengine - INFO - Epoch(val) [120][25/32] eta: 0:00:08 time: 0.7683 data_time: 0.0861 memory: 15734 2022/08/30 02:21:34 - mmengine - INFO - Epoch(val) [120][30/32] eta: 0:00:01 time: 0.6613 data_time: 0.0329 memory: 15734 2022/08/30 02:21:34 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 02:21:34 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7824, precision: 0.7162, hmean: 0.7478 2022/08/30 02:21:34 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7805, precision: 0.8191, hmean: 0.7993 2022/08/30 02:21:34 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7650, precision: 0.8740, hmean: 0.8159 2022/08/30 02:21:34 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7203, precision: 0.9072, hmean: 0.8030 2022/08/30 02:21:34 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6052, precision: 0.9472, hmean: 0.7385 2022/08/30 02:21:34 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1998, precision: 0.9834, hmean: 0.3321 2022/08/30 02:21:34 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/08/30 02:21:34 - mmengine - INFO - Epoch(val) [120][32/32] icdar/precision: 0.8740 icdar/recall: 0.7650 icdar/hmean: 0.8159 2022/08/30 02:21:47 - mmengine - INFO - Epoch(train) [121][5/63] lr: 6.3662e-03 eta: 0:00:01 time: 1.7774 data_time: 0.2386 memory: 16201 loss_prob: 1.4678 loss_thr: 0.6127 loss_db: 0.2342 loss: 2.3147 2022/08/30 02:21:54 - mmengine - INFO - Epoch(train) [121][10/63] lr: 6.3662e-03 eta: 1 day, 3:32:02 time: 1.9787 data_time: 0.2615 memory: 16201 loss_prob: 1.1597 loss_thr: 0.5701 loss_db: 0.1920 loss: 1.9219 2022/08/30 02:22:03 - mmengine - INFO - Epoch(train) [121][15/63] lr: 6.3662e-03 eta: 1 day, 3:32:02 time: 1.6550 data_time: 0.0416 memory: 16201 loss_prob: 1.1594 loss_thr: 0.5620 loss_db: 0.1866 loss: 1.9080 2022/08/30 02:22:12 - mmengine - INFO - Epoch(train) [121][20/63] lr: 6.3662e-03 eta: 1 day, 3:32:12 time: 1.7348 data_time: 0.0339 memory: 16201 loss_prob: 1.2408 loss_thr: 0.5786 loss_db: 0.1966 loss: 2.0160 2022/08/30 02:22:19 - mmengine - INFO - Epoch(train) [121][25/63] lr: 6.3662e-03 eta: 1 day, 3:32:12 time: 1.5585 data_time: 0.0487 memory: 16201 loss_prob: 1.1827 loss_thr: 0.5927 loss_db: 0.1925 loss: 1.9679 2022/08/30 02:22:27 - mmengine - INFO - Epoch(train) [121][30/63] lr: 6.3662e-03 eta: 1 day, 3:32:03 time: 1.5164 data_time: 0.0384 memory: 16201 loss_prob: 1.1479 loss_thr: 0.5891 loss_db: 0.1934 loss: 1.9304 2022/08/30 02:22:34 - mmengine - INFO - Epoch(train) [121][35/63] lr: 6.3662e-03 eta: 1 day, 3:32:03 time: 1.5634 data_time: 0.0392 memory: 16201 loss_prob: 1.1612 loss_thr: 0.5818 loss_db: 0.1913 loss: 1.9342 2022/08/30 02:22:44 - mmengine - INFO - Epoch(train) [121][40/63] lr: 6.3662e-03 eta: 1 day, 3:32:12 time: 1.7301 data_time: 0.0434 memory: 16201 loss_prob: 1.1603 loss_thr: 0.5750 loss_db: 0.1855 loss: 1.9208 2022/08/30 02:22:53 - mmengine - INFO - Epoch(train) [121][45/63] lr: 6.3662e-03 eta: 1 day, 3:32:12 time: 1.8895 data_time: 0.0357 memory: 16201 loss_prob: 1.1615 loss_thr: 0.5863 loss_db: 0.1856 loss: 1.9334 2022/08/30 02:23:02 - mmengine - INFO - Epoch(train) [121][50/63] lr: 6.3662e-03 eta: 1 day, 3:32:27 time: 1.7881 data_time: 0.0550 memory: 16201 loss_prob: 1.1432 loss_thr: 0.5967 loss_db: 0.1854 loss: 1.9253 2022/08/30 02:23:11 - mmengine - INFO - Epoch(train) [121][55/63] lr: 6.3662e-03 eta: 1 day, 3:32:27 time: 1.7773 data_time: 0.0451 memory: 16201 loss_prob: 1.0379 loss_thr: 0.5623 loss_db: 0.1707 loss: 1.7709 2022/08/30 02:23:21 - mmengine - INFO - Epoch(train) [121][60/63] lr: 6.3662e-03 eta: 1 day, 3:32:49 time: 1.8608 data_time: 0.0485 memory: 16201 loss_prob: 0.9757 loss_thr: 0.5259 loss_db: 0.1613 loss: 1.6629 2022/08/30 02:23:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:23:37 - mmengine - INFO - Epoch(train) [122][5/63] lr: 6.3609e-03 eta: 1 day, 3:32:49 time: 2.0488 data_time: 0.2589 memory: 16201 loss_prob: 1.0058 loss_thr: 0.5326 loss_db: 0.1663 loss: 1.7048 2022/08/30 02:23:46 - mmengine - INFO - Epoch(train) [122][10/63] lr: 6.3609e-03 eta: 1 day, 3:32:41 time: 2.0197 data_time: 0.2845 memory: 16201 loss_prob: 1.0392 loss_thr: 0.5438 loss_db: 0.1695 loss: 1.7525 2022/08/30 02:23:56 - mmengine - INFO - Epoch(train) [122][15/63] lr: 6.3609e-03 eta: 1 day, 3:32:41 time: 1.8102 data_time: 0.0408 memory: 16201 loss_prob: 1.1868 loss_thr: 0.5707 loss_db: 0.1988 loss: 1.9564 2022/08/30 02:24:05 - mmengine - INFO - Epoch(train) [122][20/63] lr: 6.3609e-03 eta: 1 day, 3:33:12 time: 1.9758 data_time: 0.0352 memory: 16201 loss_prob: 1.1204 loss_thr: 0.5745 loss_db: 0.1917 loss: 1.8866 2022/08/30 02:24:15 - mmengine - INFO - Epoch(train) [122][25/63] lr: 6.3609e-03 eta: 1 day, 3:33:12 time: 1.9640 data_time: 0.0401 memory: 16201 loss_prob: 1.0624 loss_thr: 0.5618 loss_db: 0.1762 loss: 1.8004 2022/08/30 02:24:25 - mmengine - INFO - Epoch(train) [122][30/63] lr: 6.3609e-03 eta: 1 day, 3:33:39 time: 1.9314 data_time: 0.0389 memory: 16201 loss_prob: 1.1165 loss_thr: 0.5544 loss_db: 0.1852 loss: 1.8560 2022/08/30 02:24:34 - mmengine - INFO - Epoch(train) [122][35/63] lr: 6.3609e-03 eta: 1 day, 3:33:39 time: 1.8622 data_time: 0.0483 memory: 16201 loss_prob: 1.1070 loss_thr: 0.5642 loss_db: 0.1867 loss: 1.8580 2022/08/30 02:24:44 - mmengine - INFO - Epoch(train) [122][40/63] lr: 6.3609e-03 eta: 1 day, 3:34:07 time: 1.9346 data_time: 0.0490 memory: 16201 loss_prob: 1.1071 loss_thr: 0.5548 loss_db: 0.1863 loss: 1.8482 2022/08/30 02:24:53 - mmengine - INFO - Epoch(train) [122][45/63] lr: 6.3609e-03 eta: 1 day, 3:34:07 time: 1.8744 data_time: 0.0504 memory: 16201 loss_prob: 1.1601 loss_thr: 0.5658 loss_db: 0.1959 loss: 1.9218 2022/08/30 02:25:01 - mmengine - INFO - Epoch(train) [122][50/63] lr: 6.3609e-03 eta: 1 day, 3:34:10 time: 1.6663 data_time: 0.0479 memory: 16201 loss_prob: 1.0822 loss_thr: 0.5372 loss_db: 0.1756 loss: 1.7950 2022/08/30 02:25:08 - mmengine - INFO - Epoch(train) [122][55/63] lr: 6.3609e-03 eta: 1 day, 3:34:10 time: 1.5753 data_time: 0.0441 memory: 16201 loss_prob: 0.9845 loss_thr: 0.5035 loss_db: 0.1561 loss: 1.6441 2022/08/30 02:25:17 - mmengine - INFO - Epoch(train) [122][60/63] lr: 6.3609e-03 eta: 1 day, 3:34:07 time: 1.5841 data_time: 0.0354 memory: 16201 loss_prob: 1.0010 loss_thr: 0.5296 loss_db: 0.1639 loss: 1.6945 2022/08/30 02:25:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:25:32 - mmengine - INFO - Epoch(train) [123][5/63] lr: 6.3556e-03 eta: 1 day, 3:34:07 time: 1.8791 data_time: 0.2521 memory: 16201 loss_prob: 0.9623 loss_thr: 0.5168 loss_db: 0.1588 loss: 1.6378 2022/08/30 02:25:42 - mmengine - INFO - Epoch(train) [123][10/63] lr: 6.3556e-03 eta: 1 day, 3:34:14 time: 2.1982 data_time: 0.2770 memory: 16201 loss_prob: 0.8899 loss_thr: 0.4908 loss_db: 0.1434 loss: 1.5241 2022/08/30 02:25:50 - mmengine - INFO - Epoch(train) [123][15/63] lr: 6.3556e-03 eta: 1 day, 3:34:14 time: 1.7949 data_time: 0.0514 memory: 16201 loss_prob: 0.8674 loss_thr: 0.4953 loss_db: 0.1386 loss: 1.5013 2022/08/30 02:25:59 - mmengine - INFO - Epoch(train) [123][20/63] lr: 6.3556e-03 eta: 1 day, 3:34:23 time: 1.7278 data_time: 0.0404 memory: 16201 loss_prob: 1.0881 loss_thr: 0.5398 loss_db: 0.1793 loss: 1.8073 2022/08/30 02:26:08 - mmengine - INFO - Epoch(train) [123][25/63] lr: 6.3556e-03 eta: 1 day, 3:34:23 time: 1.8650 data_time: 0.0451 memory: 16201 loss_prob: 1.1110 loss_thr: 0.5581 loss_db: 0.1829 loss: 1.8520 2022/08/30 02:26:17 - mmengine - INFO - Epoch(train) [123][30/63] lr: 6.3556e-03 eta: 1 day, 3:34:35 time: 1.7662 data_time: 0.0461 memory: 16201 loss_prob: 1.0390 loss_thr: 0.5559 loss_db: 0.1644 loss: 1.7593 2022/08/30 02:26:26 - mmengine - INFO - Epoch(train) [123][35/63] lr: 6.3556e-03 eta: 1 day, 3:34:35 time: 1.7498 data_time: 0.0554 memory: 16201 loss_prob: 1.0821 loss_thr: 0.5605 loss_db: 0.1768 loss: 1.8195 2022/08/30 02:26:35 - mmengine - INFO - Epoch(train) [123][40/63] lr: 6.3556e-03 eta: 1 day, 3:34:54 time: 1.8401 data_time: 0.0379 memory: 16201 loss_prob: 1.0726 loss_thr: 0.5788 loss_db: 0.1739 loss: 1.8253 2022/08/30 02:26:44 - mmengine - INFO - Epoch(train) [123][45/63] lr: 6.3556e-03 eta: 1 day, 3:34:54 time: 1.8036 data_time: 0.0392 memory: 16201 loss_prob: 0.9995 loss_thr: 0.5584 loss_db: 0.1589 loss: 1.7168 2022/08/30 02:26:53 - mmengine - INFO - Epoch(train) [123][50/63] lr: 6.3556e-03 eta: 1 day, 3:35:03 time: 1.7397 data_time: 0.0580 memory: 16201 loss_prob: 1.0188 loss_thr: 0.5420 loss_db: 0.1631 loss: 1.7239 2022/08/30 02:27:01 - mmengine - INFO - Epoch(train) [123][55/63] lr: 6.3556e-03 eta: 1 day, 3:35:03 time: 1.7178 data_time: 0.0410 memory: 16201 loss_prob: 1.0720 loss_thr: 0.5429 loss_db: 0.1697 loss: 1.7846 2022/08/30 02:27:11 - mmengine - INFO - Epoch(train) [123][60/63] lr: 6.3556e-03 eta: 1 day, 3:35:22 time: 1.8497 data_time: 0.0560 memory: 16201 loss_prob: 1.0911 loss_thr: 0.5611 loss_db: 0.1700 loss: 1.8221 2022/08/30 02:27:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:27:27 - mmengine - INFO - Epoch(train) [124][5/63] lr: 6.3503e-03 eta: 1 day, 3:35:22 time: 1.8932 data_time: 0.3019 memory: 16201 loss_prob: 0.9927 loss_thr: 0.5531 loss_db: 0.1609 loss: 1.7067 2022/08/30 02:27:35 - mmengine - INFO - Epoch(train) [124][10/63] lr: 6.3503e-03 eta: 1 day, 3:35:11 time: 1.9899 data_time: 0.3125 memory: 16201 loss_prob: 0.9846 loss_thr: 0.5440 loss_db: 0.1600 loss: 1.6887 2022/08/30 02:27:44 - mmengine - INFO - Epoch(train) [124][15/63] lr: 6.3503e-03 eta: 1 day, 3:35:11 time: 1.7537 data_time: 0.0402 memory: 16201 loss_prob: 1.0084 loss_thr: 0.5560 loss_db: 0.1635 loss: 1.7279 2022/08/30 02:27:54 - mmengine - INFO - Epoch(train) [124][20/63] lr: 6.3503e-03 eta: 1 day, 3:35:35 time: 1.9103 data_time: 0.0545 memory: 16201 loss_prob: 1.0330 loss_thr: 0.5536 loss_db: 0.1733 loss: 1.7599 2022/08/30 02:28:03 - mmengine - INFO - Epoch(train) [124][25/63] lr: 6.3503e-03 eta: 1 day, 3:35:35 time: 1.8731 data_time: 0.0590 memory: 16201 loss_prob: 0.9352 loss_thr: 0.5202 loss_db: 0.1602 loss: 1.6156 2022/08/30 02:28:13 - mmengine - INFO - Epoch(train) [124][30/63] lr: 6.3503e-03 eta: 1 day, 3:35:55 time: 1.8604 data_time: 0.0406 memory: 16201 loss_prob: 0.8726 loss_thr: 0.5076 loss_db: 0.1438 loss: 1.5240 2022/08/30 02:28:21 - mmengine - INFO - Epoch(train) [124][35/63] lr: 6.3503e-03 eta: 1 day, 3:35:55 time: 1.7566 data_time: 0.0464 memory: 16201 loss_prob: 0.9343 loss_thr: 0.5449 loss_db: 0.1584 loss: 1.6376 2022/08/30 02:28:30 - mmengine - INFO - Epoch(train) [124][40/63] lr: 6.3503e-03 eta: 1 day, 3:36:07 time: 1.7658 data_time: 0.0402 memory: 16201 loss_prob: 0.9458 loss_thr: 0.5493 loss_db: 0.1610 loss: 1.6561 2022/08/30 02:28:39 - mmengine - INFO - Epoch(train) [124][45/63] lr: 6.3503e-03 eta: 1 day, 3:36:07 time: 1.7954 data_time: 0.0371 memory: 16201 loss_prob: 0.9748 loss_thr: 0.5588 loss_db: 0.1606 loss: 1.6942 2022/08/30 02:28:47 - mmengine - INFO - Epoch(train) [124][50/63] lr: 6.3503e-03 eta: 1 day, 3:36:13 time: 1.7075 data_time: 0.0424 memory: 16201 loss_prob: 0.9900 loss_thr: 0.5703 loss_db: 0.1657 loss: 1.7260 2022/08/30 02:28:55 - mmengine - INFO - Epoch(train) [124][55/63] lr: 6.3503e-03 eta: 1 day, 3:36:13 time: 1.6653 data_time: 0.0424 memory: 16201 loss_prob: 1.0393 loss_thr: 0.5706 loss_db: 0.1760 loss: 1.7860 2022/08/30 02:29:05 - mmengine - INFO - Epoch(train) [124][60/63] lr: 6.3503e-03 eta: 1 day, 3:36:23 time: 1.7523 data_time: 0.0557 memory: 16201 loss_prob: 1.0405 loss_thr: 0.5567 loss_db: 0.1744 loss: 1.7716 2022/08/30 02:29:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:29:21 - mmengine - INFO - Epoch(train) [125][5/63] lr: 6.3450e-03 eta: 1 day, 3:36:23 time: 1.9967 data_time: 0.2722 memory: 16201 loss_prob: 0.9732 loss_thr: 0.5533 loss_db: 0.1651 loss: 1.6915 2022/08/30 02:29:30 - mmengine - INFO - Epoch(train) [125][10/63] lr: 6.3450e-03 eta: 1 day, 3:36:10 time: 1.9706 data_time: 0.2845 memory: 16201 loss_prob: 0.9929 loss_thr: 0.5402 loss_db: 0.1692 loss: 1.7024 2022/08/30 02:29:37 - mmengine - INFO - Epoch(train) [125][15/63] lr: 6.3450e-03 eta: 1 day, 3:36:10 time: 1.5860 data_time: 0.0421 memory: 16201 loss_prob: 0.9528 loss_thr: 0.5280 loss_db: 0.1586 loss: 1.6394 2022/08/30 02:29:44 - mmengine - INFO - Epoch(train) [125][20/63] lr: 6.3450e-03 eta: 1 day, 3:35:55 time: 1.4638 data_time: 0.0418 memory: 16201 loss_prob: 0.9013 loss_thr: 0.4955 loss_db: 0.1467 loss: 1.5435 2022/08/30 02:29:53 - mmengine - INFO - Epoch(train) [125][25/63] lr: 6.3450e-03 eta: 1 day, 3:35:55 time: 1.5883 data_time: 0.0418 memory: 16201 loss_prob: 0.9671 loss_thr: 0.5130 loss_db: 0.1569 loss: 1.6370 2022/08/30 02:30:01 - mmengine - INFO - Epoch(train) [125][30/63] lr: 6.3450e-03 eta: 1 day, 3:35:56 time: 1.6442 data_time: 0.0380 memory: 16201 loss_prob: 0.9750 loss_thr: 0.5322 loss_db: 0.1605 loss: 1.6677 2022/08/30 02:30:11 - mmengine - INFO - Epoch(train) [125][35/63] lr: 6.3450e-03 eta: 1 day, 3:35:56 time: 1.7798 data_time: 0.0501 memory: 16201 loss_prob: 0.9294 loss_thr: 0.5284 loss_db: 0.1553 loss: 1.6131 2022/08/30 02:30:18 - mmengine - INFO - Epoch(train) [125][40/63] lr: 6.3450e-03 eta: 1 day, 3:36:03 time: 1.7192 data_time: 0.0389 memory: 16201 loss_prob: 0.9655 loss_thr: 0.5492 loss_db: 0.1597 loss: 1.6743 2022/08/30 02:30:28 - mmengine - INFO - Epoch(train) [125][45/63] lr: 6.3450e-03 eta: 1 day, 3:36:03 time: 1.7674 data_time: 0.0491 memory: 16201 loss_prob: 0.9160 loss_thr: 0.5275 loss_db: 0.1504 loss: 1.5939 2022/08/30 02:30:38 - mmengine - INFO - Epoch(train) [125][50/63] lr: 6.3450e-03 eta: 1 day, 3:36:33 time: 1.9830 data_time: 0.0602 memory: 16201 loss_prob: 0.9298 loss_thr: 0.5191 loss_db: 0.1519 loss: 1.6008 2022/08/30 02:30:47 - mmengine - INFO - Epoch(train) [125][55/63] lr: 6.3450e-03 eta: 1 day, 3:36:33 time: 1.8716 data_time: 0.0416 memory: 16201 loss_prob: 1.0181 loss_thr: 0.5506 loss_db: 0.1663 loss: 1.7350 2022/08/30 02:30:57 - mmengine - INFO - Epoch(train) [125][60/63] lr: 6.3450e-03 eta: 1 day, 3:36:55 time: 1.8912 data_time: 0.0488 memory: 16201 loss_prob: 0.9350 loss_thr: 0.5367 loss_db: 0.1550 loss: 1.6267 2022/08/30 02:31:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:31:12 - mmengine - INFO - Epoch(train) [126][5/63] lr: 6.3396e-03 eta: 1 day, 3:36:55 time: 1.8807 data_time: 0.2644 memory: 16201 loss_prob: 0.8791 loss_thr: 0.5192 loss_db: 0.1495 loss: 1.5478 2022/08/30 02:31:21 - mmengine - INFO - Epoch(train) [126][10/63] lr: 6.3396e-03 eta: 1 day, 3:36:36 time: 1.9155 data_time: 0.2991 memory: 16201 loss_prob: 0.9121 loss_thr: 0.5401 loss_db: 0.1566 loss: 1.6088 2022/08/30 02:31:29 - mmengine - INFO - Epoch(train) [126][15/63] lr: 6.3396e-03 eta: 1 day, 3:36:36 time: 1.7035 data_time: 0.0529 memory: 16201 loss_prob: 1.0271 loss_thr: 0.5835 loss_db: 0.1737 loss: 1.7843 2022/08/30 02:31:38 - mmengine - INFO - Epoch(train) [126][20/63] lr: 6.3396e-03 eta: 1 day, 3:36:46 time: 1.7554 data_time: 0.0335 memory: 16201 loss_prob: 1.0020 loss_thr: 0.5417 loss_db: 0.1636 loss: 1.7073 2022/08/30 02:31:46 - mmengine - INFO - Epoch(train) [126][25/63] lr: 6.3396e-03 eta: 1 day, 3:36:46 time: 1.7250 data_time: 0.0468 memory: 16201 loss_prob: 1.0196 loss_thr: 0.5312 loss_db: 0.1669 loss: 1.7177 2022/08/30 02:31:55 - mmengine - INFO - Epoch(train) [126][30/63] lr: 6.3396e-03 eta: 1 day, 3:36:53 time: 1.7219 data_time: 0.0401 memory: 16201 loss_prob: 1.1942 loss_thr: 0.5697 loss_db: 0.1899 loss: 1.9538 2022/08/30 02:32:05 - mmengine - INFO - Epoch(train) [126][35/63] lr: 6.3396e-03 eta: 1 day, 3:36:53 time: 1.8977 data_time: 0.0478 memory: 16201 loss_prob: 1.1418 loss_thr: 0.5564 loss_db: 0.1803 loss: 1.8785 2022/08/30 02:32:15 - mmengine - INFO - Epoch(train) [126][40/63] lr: 6.3396e-03 eta: 1 day, 3:37:22 time: 1.9765 data_time: 0.0474 memory: 16201 loss_prob: 0.9270 loss_thr: 0.5220 loss_db: 0.1539 loss: 1.6028 2022/08/30 02:32:24 - mmengine - INFO - Epoch(train) [126][45/63] lr: 6.3396e-03 eta: 1 day, 3:37:22 time: 1.8340 data_time: 0.0456 memory: 16201 loss_prob: 0.8932 loss_thr: 0.4975 loss_db: 0.1499 loss: 1.5406 2022/08/30 02:32:34 - mmengine - INFO - Epoch(train) [126][50/63] lr: 6.3396e-03 eta: 1 day, 3:37:41 time: 1.8705 data_time: 0.0578 memory: 16201 loss_prob: 0.9167 loss_thr: 0.5124 loss_db: 0.1529 loss: 1.5820 2022/08/30 02:32:43 - mmengine - INFO - Epoch(train) [126][55/63] lr: 6.3396e-03 eta: 1 day, 3:37:41 time: 1.8781 data_time: 0.0562 memory: 16201 loss_prob: 0.9459 loss_thr: 0.5414 loss_db: 0.1562 loss: 1.6436 2022/08/30 02:32:51 - mmengine - INFO - Epoch(train) [126][60/63] lr: 6.3396e-03 eta: 1 day, 3:37:51 time: 1.7510 data_time: 0.0472 memory: 16201 loss_prob: 1.0466 loss_thr: 0.5606 loss_db: 0.1707 loss: 1.7779 2022/08/30 02:32:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:33:07 - mmengine - INFO - Epoch(train) [127][5/63] lr: 6.3343e-03 eta: 1 day, 3:37:51 time: 1.9007 data_time: 0.2827 memory: 16201 loss_prob: 1.1554 loss_thr: 0.5595 loss_db: 0.1863 loss: 1.9011 2022/08/30 02:33:18 - mmengine - INFO - Epoch(train) [127][10/63] lr: 6.3343e-03 eta: 1 day, 3:37:59 time: 2.2327 data_time: 0.2972 memory: 16201 loss_prob: 1.0905 loss_thr: 0.5571 loss_db: 0.1788 loss: 1.8265 2022/08/30 02:33:28 - mmengine - INFO - Epoch(train) [127][15/63] lr: 6.3343e-03 eta: 1 day, 3:37:59 time: 2.0445 data_time: 0.0530 memory: 16201 loss_prob: 1.0183 loss_thr: 0.5680 loss_db: 0.1699 loss: 1.7562 2022/08/30 02:33:38 - mmengine - INFO - Epoch(train) [127][20/63] lr: 6.3343e-03 eta: 1 day, 3:38:31 time: 2.0238 data_time: 0.0601 memory: 16201 loss_prob: 1.1470 loss_thr: 0.5961 loss_db: 0.1949 loss: 1.9379 2022/08/30 02:33:47 - mmengine - INFO - Epoch(train) [127][25/63] lr: 6.3343e-03 eta: 1 day, 3:38:31 time: 1.9426 data_time: 0.0596 memory: 16201 loss_prob: 1.1970 loss_thr: 0.5964 loss_db: 0.1975 loss: 1.9909 2022/08/30 02:33:55 - mmengine - INFO - Epoch(train) [127][30/63] lr: 6.3343e-03 eta: 1 day, 3:38:33 time: 1.6597 data_time: 0.0388 memory: 16201 loss_prob: 0.9944 loss_thr: 0.5447 loss_db: 0.1625 loss: 1.7016 2022/08/30 02:34:03 - mmengine - INFO - Epoch(train) [127][35/63] lr: 6.3343e-03 eta: 1 day, 3:38:33 time: 1.5809 data_time: 0.0338 memory: 16201 loss_prob: 0.9405 loss_thr: 0.5082 loss_db: 0.1571 loss: 1.6057 2022/08/30 02:34:11 - mmengine - INFO - Epoch(train) [127][40/63] lr: 6.3343e-03 eta: 1 day, 3:38:27 time: 1.5745 data_time: 0.0405 memory: 16201 loss_prob: 0.9900 loss_thr: 0.5261 loss_db: 0.1632 loss: 1.6794 2022/08/30 02:34:19 - mmengine - INFO - Epoch(train) [127][45/63] lr: 6.3343e-03 eta: 1 day, 3:38:27 time: 1.6103 data_time: 0.0435 memory: 16201 loss_prob: 1.0522 loss_thr: 0.5743 loss_db: 0.1721 loss: 1.7986 2022/08/30 02:34:28 - mmengine - INFO - Epoch(train) [127][50/63] lr: 6.3343e-03 eta: 1 day, 3:38:34 time: 1.7329 data_time: 0.0486 memory: 16201 loss_prob: 1.0600 loss_thr: 0.5775 loss_db: 0.1740 loss: 1.8114 2022/08/30 02:34:37 - mmengine - INFO - Epoch(train) [127][55/63] lr: 6.3343e-03 eta: 1 day, 3:38:34 time: 1.7867 data_time: 0.0471 memory: 16201 loss_prob: 1.0046 loss_thr: 0.5433 loss_db: 0.1666 loss: 1.7145 2022/08/30 02:34:45 - mmengine - INFO - Epoch(train) [127][60/63] lr: 6.3343e-03 eta: 1 day, 3:38:34 time: 1.6515 data_time: 0.0429 memory: 16201 loss_prob: 0.9544 loss_thr: 0.5177 loss_db: 0.1600 loss: 1.6321 2022/08/30 02:34:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:34:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:35:01 - mmengine - INFO - Epoch(train) [128][5/63] lr: 6.3290e-03 eta: 1 day, 3:38:34 time: 1.9451 data_time: 0.2607 memory: 16201 loss_prob: 1.0459 loss_thr: 0.5557 loss_db: 0.1716 loss: 1.7732 2022/08/30 02:35:11 - mmengine - INFO - Epoch(train) [128][10/63] lr: 6.3290e-03 eta: 1 day, 3:38:34 time: 2.1345 data_time: 0.2707 memory: 16201 loss_prob: 0.8779 loss_thr: 0.4903 loss_db: 0.1438 loss: 1.5120 2022/08/30 02:35:21 - mmengine - INFO - Epoch(train) [128][15/63] lr: 6.3290e-03 eta: 1 day, 3:38:34 time: 1.9550 data_time: 0.0557 memory: 16201 loss_prob: 0.8430 loss_thr: 0.5071 loss_db: 0.1374 loss: 1.4875 2022/08/30 02:35:30 - mmengine - INFO - Epoch(train) [128][20/63] lr: 6.3290e-03 eta: 1 day, 3:38:48 time: 1.8133 data_time: 0.0570 memory: 16201 loss_prob: 0.9203 loss_thr: 0.5347 loss_db: 0.1530 loss: 1.6080 2022/08/30 02:35:37 - mmengine - INFO - Epoch(train) [128][25/63] lr: 6.3290e-03 eta: 1 day, 3:38:48 time: 1.6709 data_time: 0.0446 memory: 16201 loss_prob: 0.9916 loss_thr: 0.5229 loss_db: 0.1638 loss: 1.6784 2022/08/30 02:35:46 - mmengine - INFO - Epoch(train) [128][30/63] lr: 6.3290e-03 eta: 1 day, 3:38:44 time: 1.6014 data_time: 0.0338 memory: 16201 loss_prob: 1.0064 loss_thr: 0.5548 loss_db: 0.1650 loss: 1.7262 2022/08/30 02:35:54 - mmengine - INFO - Epoch(train) [128][35/63] lr: 6.3290e-03 eta: 1 day, 3:38:44 time: 1.6795 data_time: 0.0434 memory: 16201 loss_prob: 0.9005 loss_thr: 0.5342 loss_db: 0.1485 loss: 1.5832 2022/08/30 02:36:03 - mmengine - INFO - Epoch(train) [128][40/63] lr: 6.3290e-03 eta: 1 day, 3:38:52 time: 1.7483 data_time: 0.0415 memory: 16201 loss_prob: 0.8497 loss_thr: 0.5093 loss_db: 0.1418 loss: 1.5008 2022/08/30 02:36:12 - mmengine - INFO - Epoch(train) [128][45/63] lr: 6.3290e-03 eta: 1 day, 3:38:52 time: 1.8187 data_time: 0.0464 memory: 16201 loss_prob: 0.9627 loss_thr: 0.5502 loss_db: 0.1567 loss: 1.6697 2022/08/30 02:36:22 - mmengine - INFO - Epoch(train) [128][50/63] lr: 6.3290e-03 eta: 1 day, 3:39:09 time: 1.8451 data_time: 0.0451 memory: 16201 loss_prob: 1.0118 loss_thr: 0.5614 loss_db: 0.1632 loss: 1.7365 2022/08/30 02:36:30 - mmengine - INFO - Epoch(train) [128][55/63] lr: 6.3290e-03 eta: 1 day, 3:39:09 time: 1.8148 data_time: 0.0826 memory: 16201 loss_prob: 1.0133 loss_thr: 0.5576 loss_db: 0.1678 loss: 1.7388 2022/08/30 02:36:41 - mmengine - INFO - Epoch(train) [128][60/63] lr: 6.3290e-03 eta: 1 day, 3:39:34 time: 1.9455 data_time: 0.1032 memory: 16201 loss_prob: 1.1600 loss_thr: 0.5752 loss_db: 0.1828 loss: 1.9180 2022/08/30 02:36:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:36:55 - mmengine - INFO - Epoch(train) [129][5/63] lr: 6.3237e-03 eta: 1 day, 3:39:34 time: 1.8176 data_time: 0.2731 memory: 16201 loss_prob: 1.0665 loss_thr: 0.5480 loss_db: 0.1670 loss: 1.7815 2022/08/30 02:37:04 - mmengine - INFO - Epoch(train) [129][10/63] lr: 6.3237e-03 eta: 1 day, 3:39:14 time: 1.9107 data_time: 0.2965 memory: 16201 loss_prob: 0.8886 loss_thr: 0.5161 loss_db: 0.1479 loss: 1.5526 2022/08/30 02:37:11 - mmengine - INFO - Epoch(train) [129][15/63] lr: 6.3237e-03 eta: 1 day, 3:39:14 time: 1.6035 data_time: 0.0486 memory: 16201 loss_prob: 0.8819 loss_thr: 0.5140 loss_db: 0.1491 loss: 1.5451 2022/08/30 02:37:20 - mmengine - INFO - Epoch(train) [129][20/63] lr: 6.3237e-03 eta: 1 day, 3:39:09 time: 1.5952 data_time: 0.0423 memory: 16201 loss_prob: 0.8821 loss_thr: 0.5073 loss_db: 0.1433 loss: 1.5327 2022/08/30 02:37:27 - mmengine - INFO - Epoch(train) [129][25/63] lr: 6.3237e-03 eta: 1 day, 3:39:09 time: 1.5504 data_time: 0.0477 memory: 16201 loss_prob: 0.9020 loss_thr: 0.5214 loss_db: 0.1454 loss: 1.5689 2022/08/30 02:37:36 - mmengine - INFO - Epoch(train) [129][30/63] lr: 6.3237e-03 eta: 1 day, 3:39:09 time: 1.6408 data_time: 0.0342 memory: 16201 loss_prob: 0.8812 loss_thr: 0.5138 loss_db: 0.1490 loss: 1.5441 2022/08/30 02:37:44 - mmengine - INFO - Epoch(train) [129][35/63] lr: 6.3237e-03 eta: 1 day, 3:39:09 time: 1.7007 data_time: 0.0449 memory: 16201 loss_prob: 0.9083 loss_thr: 0.5098 loss_db: 0.1554 loss: 1.5735 2022/08/30 02:37:52 - mmengine - INFO - Epoch(train) [129][40/63] lr: 6.3237e-03 eta: 1 day, 3:39:00 time: 1.5521 data_time: 0.0360 memory: 16201 loss_prob: 0.9361 loss_thr: 0.5363 loss_db: 0.1565 loss: 1.6289 2022/08/30 02:38:00 - mmengine - INFO - Epoch(train) [129][45/63] lr: 6.3237e-03 eta: 1 day, 3:39:00 time: 1.6458 data_time: 0.0355 memory: 16201 loss_prob: 0.9622 loss_thr: 0.5574 loss_db: 0.1594 loss: 1.6789 2022/08/30 02:38:08 - mmengine - INFO - Epoch(train) [129][50/63] lr: 6.3237e-03 eta: 1 day, 3:39:01 time: 1.6636 data_time: 0.0564 memory: 16201 loss_prob: 1.0031 loss_thr: 0.5422 loss_db: 0.1681 loss: 1.7134 2022/08/30 02:38:16 - mmengine - INFO - Epoch(train) [129][55/63] lr: 6.3237e-03 eta: 1 day, 3:39:01 time: 1.6190 data_time: 0.0407 memory: 16201 loss_prob: 0.9858 loss_thr: 0.5191 loss_db: 0.1628 loss: 1.6677 2022/08/30 02:38:23 - mmengine - INFO - Epoch(train) [129][60/63] lr: 6.3237e-03 eta: 1 day, 3:38:50 time: 1.5139 data_time: 0.0277 memory: 16201 loss_prob: 0.9865 loss_thr: 0.5322 loss_db: 0.1631 loss: 1.6819 2022/08/30 02:38:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:38:37 - mmengine - INFO - Epoch(train) [130][5/63] lr: 6.3184e-03 eta: 1 day, 3:38:50 time: 1.6191 data_time: 0.2538 memory: 16201 loss_prob: 0.9436 loss_thr: 0.5504 loss_db: 0.1624 loss: 1.6563 2022/08/30 02:38:46 - mmengine - INFO - Epoch(train) [130][10/63] lr: 6.3184e-03 eta: 1 day, 3:38:22 time: 1.8159 data_time: 0.2791 memory: 16201 loss_prob: 0.9061 loss_thr: 0.5072 loss_db: 0.1501 loss: 1.5633 2022/08/30 02:38:55 - mmengine - INFO - Epoch(train) [130][15/63] lr: 6.3184e-03 eta: 1 day, 3:38:22 time: 1.8229 data_time: 0.0418 memory: 16201 loss_prob: 1.0063 loss_thr: 0.5442 loss_db: 0.1652 loss: 1.7157 2022/08/30 02:39:02 - mmengine - INFO - Epoch(train) [130][20/63] lr: 6.3184e-03 eta: 1 day, 3:38:20 time: 1.6251 data_time: 0.0394 memory: 16201 loss_prob: 0.9322 loss_thr: 0.5283 loss_db: 0.1567 loss: 1.6172 2022/08/30 02:39:10 - mmengine - INFO - Epoch(train) [130][25/63] lr: 6.3184e-03 eta: 1 day, 3:38:20 time: 1.5046 data_time: 0.0440 memory: 16201 loss_prob: 0.8692 loss_thr: 0.4980 loss_db: 0.1448 loss: 1.5120 2022/08/30 02:39:19 - mmengine - INFO - Epoch(train) [130][30/63] lr: 6.3184e-03 eta: 1 day, 3:38:21 time: 1.6647 data_time: 0.0341 memory: 16201 loss_prob: 0.9833 loss_thr: 0.5364 loss_db: 0.1580 loss: 1.6777 2022/08/30 02:39:28 - mmengine - INFO - Epoch(train) [130][35/63] lr: 6.3184e-03 eta: 1 day, 3:38:21 time: 1.8318 data_time: 0.0516 memory: 16201 loss_prob: 0.9354 loss_thr: 0.5221 loss_db: 0.1531 loss: 1.6107 2022/08/30 02:39:37 - mmengine - INFO - Epoch(train) [130][40/63] lr: 6.3184e-03 eta: 1 day, 3:38:35 time: 1.8310 data_time: 0.0491 memory: 16201 loss_prob: 0.8310 loss_thr: 0.5049 loss_db: 0.1389 loss: 1.4748 2022/08/30 02:39:45 - mmengine - INFO - Epoch(train) [130][45/63] lr: 6.3184e-03 eta: 1 day, 3:38:35 time: 1.6725 data_time: 0.0355 memory: 16201 loss_prob: 0.9100 loss_thr: 0.5338 loss_db: 0.1511 loss: 1.5949 2022/08/30 02:39:54 - mmengine - INFO - Epoch(train) [130][50/63] lr: 6.3184e-03 eta: 1 day, 3:38:38 time: 1.6831 data_time: 0.0459 memory: 16201 loss_prob: 1.0057 loss_thr: 0.5418 loss_db: 0.1653 loss: 1.7128 2022/08/30 02:40:02 - mmengine - INFO - Epoch(train) [130][55/63] lr: 6.3184e-03 eta: 1 day, 3:38:38 time: 1.7223 data_time: 0.0368 memory: 16201 loss_prob: 0.9575 loss_thr: 0.5589 loss_db: 0.1555 loss: 1.6719 2022/08/30 02:40:11 - mmengine - INFO - Epoch(train) [130][60/63] lr: 6.3184e-03 eta: 1 day, 3:38:47 time: 1.7637 data_time: 0.0452 memory: 16201 loss_prob: 0.9381 loss_thr: 0.5641 loss_db: 0.1566 loss: 1.6589 2022/08/30 02:40:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:40:26 - mmengine - INFO - Epoch(train) [131][5/63] lr: 6.3131e-03 eta: 1 day, 3:38:47 time: 1.7527 data_time: 0.2331 memory: 16201 loss_prob: 0.8874 loss_thr: 0.5286 loss_db: 0.1513 loss: 1.5673 2022/08/30 02:40:34 - mmengine - INFO - Epoch(train) [131][10/63] lr: 6.3131e-03 eta: 1 day, 3:38:24 time: 1.8827 data_time: 0.2453 memory: 16201 loss_prob: 0.8660 loss_thr: 0.5203 loss_db: 0.1469 loss: 1.5332 2022/08/30 02:40:42 - mmengine - INFO - Epoch(train) [131][15/63] lr: 6.3131e-03 eta: 1 day, 3:38:24 time: 1.6377 data_time: 0.0399 memory: 16201 loss_prob: 0.8336 loss_thr: 0.5037 loss_db: 0.1375 loss: 1.4748 2022/08/30 02:40:51 - mmengine - INFO - Epoch(train) [131][20/63] lr: 6.3131e-03 eta: 1 day, 3:38:25 time: 1.6665 data_time: 0.0460 memory: 16201 loss_prob: 0.9128 loss_thr: 0.5223 loss_db: 0.1483 loss: 1.5835 2022/08/30 02:40:59 - mmengine - INFO - Epoch(train) [131][25/63] lr: 6.3131e-03 eta: 1 day, 3:38:25 time: 1.7368 data_time: 0.0420 memory: 16201 loss_prob: 0.8995 loss_thr: 0.5272 loss_db: 0.1489 loss: 1.5755 2022/08/30 02:41:08 - mmengine - INFO - Epoch(train) [131][30/63] lr: 6.3131e-03 eta: 1 day, 3:38:29 time: 1.6997 data_time: 0.0383 memory: 16201 loss_prob: 0.8661 loss_thr: 0.5177 loss_db: 0.1447 loss: 1.5285 2022/08/30 02:41:16 - mmengine - INFO - Epoch(train) [131][35/63] lr: 6.3131e-03 eta: 1 day, 3:38:29 time: 1.6646 data_time: 0.0479 memory: 16201 loss_prob: 0.9798 loss_thr: 0.5324 loss_db: 0.1642 loss: 1.6765 2022/08/30 02:41:24 - mmengine - INFO - Epoch(train) [131][40/63] lr: 6.3131e-03 eta: 1 day, 3:38:29 time: 1.6624 data_time: 0.0356 memory: 16201 loss_prob: 0.9709 loss_thr: 0.5291 loss_db: 0.1642 loss: 1.6642 2022/08/30 02:41:34 - mmengine - INFO - Epoch(train) [131][45/63] lr: 6.3131e-03 eta: 1 day, 3:38:29 time: 1.8094 data_time: 0.0373 memory: 16201 loss_prob: 0.9039 loss_thr: 0.5059 loss_db: 0.1503 loss: 1.5600 2022/08/30 02:41:44 - mmengine - INFO - Epoch(train) [131][50/63] lr: 6.3131e-03 eta: 1 day, 3:38:54 time: 1.9621 data_time: 0.0391 memory: 16201 loss_prob: 0.9373 loss_thr: 0.5139 loss_db: 0.1520 loss: 1.6032 2022/08/30 02:41:53 - mmengine - INFO - Epoch(train) [131][55/63] lr: 6.3131e-03 eta: 1 day, 3:38:54 time: 1.9280 data_time: 0.0379 memory: 16201 loss_prob: 0.9968 loss_thr: 0.5438 loss_db: 0.1636 loss: 1.7042 2022/08/30 02:42:04 - mmengine - INFO - Epoch(train) [131][60/63] lr: 6.3131e-03 eta: 1 day, 3:39:25 time: 2.0368 data_time: 0.0479 memory: 16201 loss_prob: 0.9888 loss_thr: 0.5499 loss_db: 0.1662 loss: 1.7049 2022/08/30 02:42:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:42:21 - mmengine - INFO - Epoch(train) [132][5/63] lr: 6.3078e-03 eta: 1 day, 3:39:25 time: 1.9862 data_time: 0.2609 memory: 16201 loss_prob: 1.0885 loss_thr: 0.5510 loss_db: 0.1678 loss: 1.8073 2022/08/30 02:42:31 - mmengine - INFO - Epoch(train) [132][10/63] lr: 6.3078e-03 eta: 1 day, 3:39:35 time: 2.2826 data_time: 0.2675 memory: 16201 loss_prob: 1.0704 loss_thr: 0.5400 loss_db: 0.1633 loss: 1.7736 2022/08/30 02:42:40 - mmengine - INFO - Epoch(train) [132][15/63] lr: 6.3078e-03 eta: 1 day, 3:39:35 time: 1.9023 data_time: 0.0508 memory: 16201 loss_prob: 0.9135 loss_thr: 0.5375 loss_db: 0.1510 loss: 1.6020 2022/08/30 02:42:48 - mmengine - INFO - Epoch(train) [132][20/63] lr: 6.3078e-03 eta: 1 day, 3:39:34 time: 1.6465 data_time: 0.0517 memory: 16201 loss_prob: 0.9330 loss_thr: 0.5394 loss_db: 0.1556 loss: 1.6281 2022/08/30 02:42:56 - mmengine - INFO - Epoch(train) [132][25/63] lr: 6.3078e-03 eta: 1 day, 3:39:34 time: 1.6106 data_time: 0.0564 memory: 16201 loss_prob: 0.9203 loss_thr: 0.5285 loss_db: 0.1541 loss: 1.6030 2022/08/30 02:43:03 - mmengine - INFO - Epoch(train) [132][30/63] lr: 6.3078e-03 eta: 1 day, 3:39:18 time: 1.4696 data_time: 0.0386 memory: 16201 loss_prob: 0.9667 loss_thr: 0.5313 loss_db: 0.1564 loss: 1.6544 2022/08/30 02:43:10 - mmengine - INFO - Epoch(train) [132][35/63] lr: 6.3078e-03 eta: 1 day, 3:39:18 time: 1.4068 data_time: 0.0381 memory: 16201 loss_prob: 1.0380 loss_thr: 0.5202 loss_db: 0.1643 loss: 1.7225 2022/08/30 02:43:18 - mmengine - INFO - Epoch(train) [132][40/63] lr: 6.3078e-03 eta: 1 day, 3:39:05 time: 1.4960 data_time: 0.0392 memory: 16201 loss_prob: 1.0900 loss_thr: 0.5363 loss_db: 0.1719 loss: 1.7982 2022/08/30 02:43:27 - mmengine - INFO - Epoch(train) [132][45/63] lr: 6.3078e-03 eta: 1 day, 3:39:05 time: 1.6799 data_time: 0.0410 memory: 16201 loss_prob: 1.0394 loss_thr: 0.5511 loss_db: 0.1669 loss: 1.7575 2022/08/30 02:43:36 - mmengine - INFO - Epoch(train) [132][50/63] lr: 6.3078e-03 eta: 1 day, 3:39:20 time: 1.8512 data_time: 0.0551 memory: 16201 loss_prob: 1.0206 loss_thr: 0.5466 loss_db: 0.1618 loss: 1.7290 2022/08/30 02:43:44 - mmengine - INFO - Epoch(train) [132][55/63] lr: 6.3078e-03 eta: 1 day, 3:39:20 time: 1.7042 data_time: 0.0436 memory: 16201 loss_prob: 1.0174 loss_thr: 0.5412 loss_db: 0.1631 loss: 1.7217 2022/08/30 02:43:53 - mmengine - INFO - Epoch(train) [132][60/63] lr: 6.3078e-03 eta: 1 day, 3:39:19 time: 1.6493 data_time: 0.0636 memory: 16201 loss_prob: 0.9729 loss_thr: 0.5530 loss_db: 0.1622 loss: 1.6881 2022/08/30 02:43:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:44:08 - mmengine - INFO - Epoch(train) [133][5/63] lr: 6.3025e-03 eta: 1 day, 3:39:19 time: 1.8216 data_time: 0.2986 memory: 16201 loss_prob: 1.0411 loss_thr: 0.5351 loss_db: 0.1734 loss: 1.7496 2022/08/30 02:44:18 - mmengine - INFO - Epoch(train) [133][10/63] lr: 6.3025e-03 eta: 1 day, 3:39:13 time: 2.0789 data_time: 0.3304 memory: 16201 loss_prob: 1.0286 loss_thr: 0.5380 loss_db: 0.1718 loss: 1.7384 2022/08/30 02:44:26 - mmengine - INFO - Epoch(train) [133][15/63] lr: 6.3025e-03 eta: 1 day, 3:39:13 time: 1.8391 data_time: 0.0661 memory: 16201 loss_prob: 1.0889 loss_thr: 0.5467 loss_db: 0.1760 loss: 1.8116 2022/08/30 02:44:35 - mmengine - INFO - Epoch(train) [133][20/63] lr: 6.3025e-03 eta: 1 day, 3:39:16 time: 1.7003 data_time: 0.0292 memory: 16201 loss_prob: 1.2985 loss_thr: 0.5537 loss_db: 0.2118 loss: 2.0639 2022/08/30 02:44:43 - mmengine - INFO - Epoch(train) [133][25/63] lr: 6.3025e-03 eta: 1 day, 3:39:16 time: 1.7300 data_time: 0.0312 memory: 16201 loss_prob: 1.2563 loss_thr: 0.5653 loss_db: 0.2056 loss: 2.0271 2022/08/30 02:44:52 - mmengine - INFO - Epoch(train) [133][30/63] lr: 6.3025e-03 eta: 1 day, 3:39:20 time: 1.7235 data_time: 0.0457 memory: 16201 loss_prob: 1.1343 loss_thr: 0.5411 loss_db: 0.1880 loss: 1.8633 2022/08/30 02:45:00 - mmengine - INFO - Epoch(train) [133][35/63] lr: 6.3025e-03 eta: 1 day, 3:39:20 time: 1.6816 data_time: 0.0601 memory: 16201 loss_prob: 1.0752 loss_thr: 0.5459 loss_db: 0.1810 loss: 1.8022 2022/08/30 02:45:07 - mmengine - INFO - Epoch(train) [133][40/63] lr: 6.3025e-03 eta: 1 day, 3:39:11 time: 1.5498 data_time: 0.0383 memory: 16201 loss_prob: 1.0399 loss_thr: 0.5556 loss_db: 0.1734 loss: 1.7689 2022/08/30 02:45:17 - mmengine - INFO - Epoch(train) [133][45/63] lr: 6.3025e-03 eta: 1 day, 3:39:11 time: 1.7225 data_time: 0.0405 memory: 16201 loss_prob: 1.0116 loss_thr: 0.5384 loss_db: 0.1699 loss: 1.7200 2022/08/30 02:45:26 - mmengine - INFO - Epoch(train) [133][50/63] lr: 6.3025e-03 eta: 1 day, 3:39:29 time: 1.8846 data_time: 0.0564 memory: 16201 loss_prob: 1.0831 loss_thr: 0.5704 loss_db: 0.1780 loss: 1.8315 2022/08/30 02:45:35 - mmengine - INFO - Epoch(train) [133][55/63] lr: 6.3025e-03 eta: 1 day, 3:39:29 time: 1.7995 data_time: 0.0382 memory: 16201 loss_prob: 1.2917 loss_thr: 0.5737 loss_db: 0.2054 loss: 2.0708 2022/08/30 02:45:44 - mmengine - INFO - Epoch(train) [133][60/63] lr: 6.3025e-03 eta: 1 day, 3:39:41 time: 1.8123 data_time: 0.0517 memory: 16201 loss_prob: 1.3282 loss_thr: 0.5663 loss_db: 0.2134 loss: 2.1080 2022/08/30 02:45:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:45:59 - mmengine - INFO - Epoch(train) [134][5/63] lr: 6.2971e-03 eta: 1 day, 3:39:41 time: 1.7982 data_time: 0.2619 memory: 16201 loss_prob: 1.1167 loss_thr: 0.5631 loss_db: 0.1740 loss: 1.8538 2022/08/30 02:46:07 - mmengine - INFO - Epoch(train) [134][10/63] lr: 6.2971e-03 eta: 1 day, 3:39:13 time: 1.8156 data_time: 0.2711 memory: 16201 loss_prob: 1.0974 loss_thr: 0.5387 loss_db: 0.1797 loss: 1.8158 2022/08/30 02:46:15 - mmengine - INFO - Epoch(train) [134][15/63] lr: 6.2971e-03 eta: 1 day, 3:39:13 time: 1.5453 data_time: 0.0371 memory: 16201 loss_prob: 1.0882 loss_thr: 0.5432 loss_db: 0.1789 loss: 1.8103 2022/08/30 02:46:23 - mmengine - INFO - Epoch(train) [134][20/63] lr: 6.2971e-03 eta: 1 day, 3:39:07 time: 1.5972 data_time: 0.0423 memory: 16201 loss_prob: 1.1034 loss_thr: 0.5740 loss_db: 0.1786 loss: 1.8560 2022/08/30 02:46:32 - mmengine - INFO - Epoch(train) [134][25/63] lr: 6.2971e-03 eta: 1 day, 3:39:07 time: 1.7884 data_time: 0.0441 memory: 16201 loss_prob: 1.1315 loss_thr: 0.5694 loss_db: 0.1820 loss: 1.8829 2022/08/30 02:46:41 - mmengine - INFO - Epoch(train) [134][30/63] lr: 6.2971e-03 eta: 1 day, 3:39:22 time: 1.8510 data_time: 0.0365 memory: 16201 loss_prob: 1.1551 loss_thr: 0.5554 loss_db: 0.1856 loss: 1.8960 2022/08/30 02:46:50 - mmengine - INFO - Epoch(train) [134][35/63] lr: 6.2971e-03 eta: 1 day, 3:39:22 time: 1.7977 data_time: 0.0479 memory: 16201 loss_prob: 1.1235 loss_thr: 0.5525 loss_db: 0.1851 loss: 1.8610 2022/08/30 02:46:59 - mmengine - INFO - Epoch(train) [134][40/63] lr: 6.2971e-03 eta: 1 day, 3:39:34 time: 1.8163 data_time: 0.0536 memory: 16201 loss_prob: 1.0628 loss_thr: 0.5666 loss_db: 0.1787 loss: 1.8081 2022/08/30 02:47:09 - mmengine - INFO - Epoch(train) [134][45/63] lr: 6.2971e-03 eta: 1 day, 3:39:34 time: 1.9015 data_time: 0.0465 memory: 16201 loss_prob: 1.0019 loss_thr: 0.5333 loss_db: 0.1666 loss: 1.7018 2022/08/30 02:47:17 - mmengine - INFO - Epoch(train) [134][50/63] lr: 6.2971e-03 eta: 1 day, 3:39:40 time: 1.7509 data_time: 0.0495 memory: 16201 loss_prob: 0.8614 loss_thr: 0.4787 loss_db: 0.1397 loss: 1.4798 2022/08/30 02:47:24 - mmengine - INFO - Epoch(train) [134][55/63] lr: 6.2971e-03 eta: 1 day, 3:39:40 time: 1.5047 data_time: 0.0375 memory: 16201 loss_prob: 0.9020 loss_thr: 0.5098 loss_db: 0.1454 loss: 1.5573 2022/08/30 02:47:33 - mmengine - INFO - Epoch(train) [134][60/63] lr: 6.2971e-03 eta: 1 day, 3:39:35 time: 1.5980 data_time: 0.0382 memory: 16201 loss_prob: 1.1307 loss_thr: 0.5672 loss_db: 0.1820 loss: 1.8799 2022/08/30 02:47:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:47:48 - mmengine - INFO - Epoch(train) [135][5/63] lr: 6.2918e-03 eta: 1 day, 3:39:35 time: 1.8622 data_time: 0.2665 memory: 16201 loss_prob: 1.0427 loss_thr: 0.5754 loss_db: 0.1674 loss: 1.7855 2022/08/30 02:47:57 - mmengine - INFO - Epoch(train) [135][10/63] lr: 6.2918e-03 eta: 1 day, 3:39:22 time: 2.0051 data_time: 0.2752 memory: 16201 loss_prob: 0.9972 loss_thr: 0.5644 loss_db: 0.1632 loss: 1.7248 2022/08/30 02:48:05 - mmengine - INFO - Epoch(train) [135][15/63] lr: 6.2918e-03 eta: 1 day, 3:39:22 time: 1.6295 data_time: 0.0376 memory: 16201 loss_prob: 1.0462 loss_thr: 0.5603 loss_db: 0.1689 loss: 1.7754 2022/08/30 02:48:14 - mmengine - INFO - Epoch(train) [135][20/63] lr: 6.2918e-03 eta: 1 day, 3:39:22 time: 1.6810 data_time: 0.0454 memory: 16201 loss_prob: 1.0496 loss_thr: 0.5511 loss_db: 0.1716 loss: 1.7723 2022/08/30 02:48:23 - mmengine - INFO - Epoch(train) [135][25/63] lr: 6.2918e-03 eta: 1 day, 3:39:22 time: 1.8580 data_time: 0.0457 memory: 16201 loss_prob: 1.0331 loss_thr: 0.5454 loss_db: 0.1736 loss: 1.7521 2022/08/30 02:48:32 - mmengine - INFO - Epoch(train) [135][30/63] lr: 6.2918e-03 eta: 1 day, 3:39:34 time: 1.8197 data_time: 0.0459 memory: 16201 loss_prob: 0.9223 loss_thr: 0.5176 loss_db: 0.1513 loss: 1.5912 2022/08/30 02:48:43 - mmengine - INFO - Epoch(train) [135][35/63] lr: 6.2918e-03 eta: 1 day, 3:39:34 time: 1.9313 data_time: 0.0589 memory: 16201 loss_prob: 0.9445 loss_thr: 0.5287 loss_db: 0.1522 loss: 1.6254 2022/08/30 02:48:51 - mmengine - INFO - Epoch(train) [135][40/63] lr: 6.2918e-03 eta: 1 day, 3:39:51 time: 1.8862 data_time: 0.0491 memory: 16201 loss_prob: 1.0264 loss_thr: 0.5383 loss_db: 0.1708 loss: 1.7355 2022/08/30 02:49:01 - mmengine - INFO - Epoch(train) [135][45/63] lr: 6.2918e-03 eta: 1 day, 3:39:51 time: 1.8716 data_time: 0.0541 memory: 16201 loss_prob: 0.9392 loss_thr: 0.5119 loss_db: 0.1570 loss: 1.6080 2022/08/30 02:49:11 - mmengine - INFO - Epoch(train) [135][50/63] lr: 6.2918e-03 eta: 1 day, 3:40:18 time: 2.0145 data_time: 0.0664 memory: 16201 loss_prob: 0.8959 loss_thr: 0.5058 loss_db: 0.1464 loss: 1.5481 2022/08/30 02:49:21 - mmengine - INFO - Epoch(train) [135][55/63] lr: 6.2918e-03 eta: 1 day, 3:40:18 time: 1.9771 data_time: 0.0433 memory: 16201 loss_prob: 0.9293 loss_thr: 0.5262 loss_db: 0.1553 loss: 1.6108 2022/08/30 02:49:30 - mmengine - INFO - Epoch(train) [135][60/63] lr: 6.2918e-03 eta: 1 day, 3:40:34 time: 1.8654 data_time: 0.0423 memory: 16201 loss_prob: 0.9843 loss_thr: 0.5433 loss_db: 0.1652 loss: 1.6928 2022/08/30 02:49:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:49:46 - mmengine - INFO - Epoch(train) [136][5/63] lr: 6.2865e-03 eta: 1 day, 3:40:34 time: 1.9758 data_time: 0.2600 memory: 16201 loss_prob: 1.0262 loss_thr: 0.5553 loss_db: 0.1702 loss: 1.7517 2022/08/30 02:49:56 - mmengine - INFO - Epoch(train) [136][10/63] lr: 6.2865e-03 eta: 1 day, 3:40:31 time: 2.1473 data_time: 0.2815 memory: 16201 loss_prob: 1.0273 loss_thr: 0.5535 loss_db: 0.1705 loss: 1.7513 2022/08/30 02:50:05 - mmengine - INFO - Epoch(train) [136][15/63] lr: 6.2865e-03 eta: 1 day, 3:40:31 time: 1.8606 data_time: 0.0462 memory: 16201 loss_prob: 1.0196 loss_thr: 0.5326 loss_db: 0.1732 loss: 1.7254 2022/08/30 02:50:14 - mmengine - INFO - Epoch(train) [136][20/63] lr: 6.2865e-03 eta: 1 day, 3:40:46 time: 1.8574 data_time: 0.0410 memory: 16201 loss_prob: 0.9984 loss_thr: 0.5448 loss_db: 0.1657 loss: 1.7089 2022/08/30 02:50:23 - mmengine - INFO - Epoch(train) [136][25/63] lr: 6.2865e-03 eta: 1 day, 3:40:46 time: 1.7970 data_time: 0.0556 memory: 16201 loss_prob: 0.9955 loss_thr: 0.5598 loss_db: 0.1636 loss: 1.7190 2022/08/30 02:50:31 - mmengine - INFO - Epoch(train) [136][30/63] lr: 6.2865e-03 eta: 1 day, 3:40:49 time: 1.7163 data_time: 0.0562 memory: 16201 loss_prob: 1.2002 loss_thr: 0.5600 loss_db: 0.1909 loss: 1.9511 2022/08/30 02:50:41 - mmengine - INFO - Epoch(train) [136][35/63] lr: 6.2865e-03 eta: 1 day, 3:40:49 time: 1.7813 data_time: 0.0551 memory: 16201 loss_prob: 1.2461 loss_thr: 0.5480 loss_db: 0.1964 loss: 1.9906 2022/08/30 02:50:51 - mmengine - INFO - Epoch(train) [136][40/63] lr: 6.2865e-03 eta: 1 day, 3:41:09 time: 1.9235 data_time: 0.0395 memory: 16201 loss_prob: 1.0665 loss_thr: 0.5315 loss_db: 0.1751 loss: 1.7731 2022/08/30 02:51:00 - mmengine - INFO - Epoch(train) [136][45/63] lr: 6.2865e-03 eta: 1 day, 3:41:09 time: 1.9508 data_time: 0.0439 memory: 16201 loss_prob: 1.0856 loss_thr: 0.5619 loss_db: 0.1812 loss: 1.8288 2022/08/30 02:51:10 - mmengine - INFO - Epoch(train) [136][50/63] lr: 6.2865e-03 eta: 1 day, 3:41:27 time: 1.9153 data_time: 0.0621 memory: 16201 loss_prob: 1.0680 loss_thr: 0.5469 loss_db: 0.1794 loss: 1.7943 2022/08/30 02:51:19 - mmengine - INFO - Epoch(train) [136][55/63] lr: 6.2865e-03 eta: 1 day, 3:41:27 time: 1.8911 data_time: 0.0429 memory: 16201 loss_prob: 0.9323 loss_thr: 0.4995 loss_db: 0.1558 loss: 1.5876 2022/08/30 02:51:28 - mmengine - INFO - Epoch(train) [136][60/63] lr: 6.2865e-03 eta: 1 day, 3:41:40 time: 1.8430 data_time: 0.0474 memory: 16201 loss_prob: 0.9658 loss_thr: 0.5125 loss_db: 0.1578 loss: 1.6361 2022/08/30 02:51:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:51:41 - mmengine - INFO - Epoch(train) [137][5/63] lr: 6.2812e-03 eta: 1 day, 3:41:40 time: 1.6862 data_time: 0.2617 memory: 16201 loss_prob: 0.9409 loss_thr: 0.5188 loss_db: 0.1550 loss: 1.6148 2022/08/30 02:51:50 - mmengine - INFO - Epoch(train) [137][10/63] lr: 6.2812e-03 eta: 1 day, 3:41:13 time: 1.8278 data_time: 0.2789 memory: 16201 loss_prob: 1.0871 loss_thr: 0.5400 loss_db: 0.1788 loss: 1.8059 2022/08/30 02:51:57 - mmengine - INFO - Epoch(train) [137][15/63] lr: 6.2812e-03 eta: 1 day, 3:41:13 time: 1.5463 data_time: 0.0329 memory: 16201 loss_prob: 1.0136 loss_thr: 0.5176 loss_db: 0.1696 loss: 1.7007 2022/08/30 02:52:09 - mmengine - INFO - Epoch(train) [137][20/63] lr: 6.2812e-03 eta: 1 day, 3:41:27 time: 1.8614 data_time: 0.0361 memory: 16201 loss_prob: 0.9648 loss_thr: 0.5151 loss_db: 0.1626 loss: 1.6425 2022/08/30 02:52:17 - mmengine - INFO - Epoch(train) [137][25/63] lr: 6.2812e-03 eta: 1 day, 3:41:27 time: 2.0288 data_time: 0.0559 memory: 16201 loss_prob: 1.2601 loss_thr: 0.5841 loss_db: 0.2027 loss: 2.0470 2022/08/30 02:52:27 - mmengine - INFO - Epoch(train) [137][30/63] lr: 6.2812e-03 eta: 1 day, 3:41:40 time: 1.8376 data_time: 0.0487 memory: 16201 loss_prob: 1.1724 loss_thr: 0.5601 loss_db: 0.1898 loss: 1.9223 2022/08/30 02:52:37 - mmengine - INFO - Epoch(train) [137][35/63] lr: 6.2812e-03 eta: 1 day, 3:41:40 time: 1.9707 data_time: 0.0579 memory: 16201 loss_prob: 0.9435 loss_thr: 0.5045 loss_db: 0.1572 loss: 1.6053 2022/08/30 02:52:45 - mmengine - INFO - Epoch(train) [137][40/63] lr: 6.2812e-03 eta: 1 day, 3:41:48 time: 1.7941 data_time: 0.0389 memory: 16201 loss_prob: 0.9335 loss_thr: 0.5112 loss_db: 0.1568 loss: 1.6016 2022/08/30 02:52:55 - mmengine - INFO - Epoch(train) [137][45/63] lr: 6.2812e-03 eta: 1 day, 3:41:48 time: 1.8238 data_time: 0.0440 memory: 16201 loss_prob: 1.0423 loss_thr: 0.5298 loss_db: 0.1724 loss: 1.7445 2022/08/30 02:53:04 - mmengine - INFO - Epoch(train) [137][50/63] lr: 6.2812e-03 eta: 1 day, 3:42:03 time: 1.8658 data_time: 0.0721 memory: 16201 loss_prob: 1.1109 loss_thr: 0.5645 loss_db: 0.1813 loss: 1.8567 2022/08/30 02:53:12 - mmengine - INFO - Epoch(train) [137][55/63] lr: 6.2812e-03 eta: 1 day, 3:42:03 time: 1.7031 data_time: 0.0409 memory: 16201 loss_prob: 0.9847 loss_thr: 0.5664 loss_db: 0.1624 loss: 1.7134 2022/08/30 02:53:22 - mmengine - INFO - Epoch(train) [137][60/63] lr: 6.2812e-03 eta: 1 day, 3:42:14 time: 1.8186 data_time: 0.0360 memory: 16201 loss_prob: 0.9576 loss_thr: 0.5324 loss_db: 0.1537 loss: 1.6438 2022/08/30 02:53:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:53:38 - mmengine - INFO - Epoch(train) [138][5/63] lr: 6.2759e-03 eta: 1 day, 3:42:14 time: 1.8917 data_time: 0.2435 memory: 16201 loss_prob: 1.1315 loss_thr: 0.5651 loss_db: 0.1836 loss: 1.8802 2022/08/30 02:53:48 - mmengine - INFO - Epoch(train) [138][10/63] lr: 6.2759e-03 eta: 1 day, 3:42:13 time: 2.1785 data_time: 0.2646 memory: 16201 loss_prob: 1.1270 loss_thr: 0.5741 loss_db: 0.1878 loss: 1.8890 2022/08/30 02:53:56 - mmengine - INFO - Epoch(train) [138][15/63] lr: 6.2759e-03 eta: 1 day, 3:42:13 time: 1.8685 data_time: 0.0465 memory: 16201 loss_prob: 1.0767 loss_thr: 0.5587 loss_db: 0.1801 loss: 1.8155 2022/08/30 02:54:04 - mmengine - INFO - Epoch(train) [138][20/63] lr: 6.2759e-03 eta: 1 day, 3:42:10 time: 1.6421 data_time: 0.0461 memory: 16201 loss_prob: 1.0748 loss_thr: 0.5657 loss_db: 0.1779 loss: 1.8184 2022/08/30 02:54:14 - mmengine - INFO - Epoch(train) [138][25/63] lr: 6.2759e-03 eta: 1 day, 3:42:10 time: 1.7516 data_time: 0.0378 memory: 16201 loss_prob: 0.9592 loss_thr: 0.5378 loss_db: 0.1582 loss: 1.6551 2022/08/30 02:54:22 - mmengine - INFO - Epoch(train) [138][30/63] lr: 6.2759e-03 eta: 1 day, 3:42:18 time: 1.7923 data_time: 0.0306 memory: 16201 loss_prob: 0.8839 loss_thr: 0.5113 loss_db: 0.1487 loss: 1.5439 2022/08/30 02:54:31 - mmengine - INFO - Epoch(train) [138][35/63] lr: 6.2759e-03 eta: 1 day, 3:42:18 time: 1.7240 data_time: 0.0437 memory: 16201 loss_prob: 1.0392 loss_thr: 0.5483 loss_db: 0.1703 loss: 1.7579 2022/08/30 02:54:39 - mmengine - INFO - Epoch(train) [138][40/63] lr: 6.2759e-03 eta: 1 day, 3:42:18 time: 1.6719 data_time: 0.0377 memory: 16201 loss_prob: 1.0828 loss_thr: 0.5499 loss_db: 0.1698 loss: 1.8025 2022/08/30 02:54:47 - mmengine - INFO - Epoch(train) [138][45/63] lr: 6.2759e-03 eta: 1 day, 3:42:18 time: 1.5621 data_time: 0.0354 memory: 16201 loss_prob: 0.9595 loss_thr: 0.5280 loss_db: 0.1533 loss: 1.6408 2022/08/30 02:54:55 - mmengine - INFO - Epoch(train) [138][50/63] lr: 6.2759e-03 eta: 1 day, 3:42:11 time: 1.5931 data_time: 0.0424 memory: 16201 loss_prob: 0.9779 loss_thr: 0.5392 loss_db: 0.1642 loss: 1.6813 2022/08/30 02:55:02 - mmengine - INFO - Epoch(train) [138][55/63] lr: 6.2759e-03 eta: 1 day, 3:42:11 time: 1.5538 data_time: 0.0339 memory: 16201 loss_prob: 1.1229 loss_thr: 0.5800 loss_db: 0.1822 loss: 1.8852 2022/08/30 02:55:10 - mmengine - INFO - Epoch(train) [138][60/63] lr: 6.2759e-03 eta: 1 day, 3:41:59 time: 1.5383 data_time: 0.0393 memory: 16201 loss_prob: 1.0971 loss_thr: 0.5881 loss_db: 0.1739 loss: 1.8590 2022/08/30 02:55:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:55:25 - mmengine - INFO - Epoch(train) [139][5/63] lr: 6.2705e-03 eta: 1 day, 3:41:59 time: 1.8411 data_time: 0.2591 memory: 16201 loss_prob: 0.9293 loss_thr: 0.5390 loss_db: 0.1534 loss: 1.6217 2022/08/30 02:55:35 - mmengine - INFO - Epoch(train) [139][10/63] lr: 6.2705e-03 eta: 1 day, 3:41:46 time: 2.0205 data_time: 0.2906 memory: 16201 loss_prob: 0.9621 loss_thr: 0.5300 loss_db: 0.1615 loss: 1.6536 2022/08/30 02:55:44 - mmengine - INFO - Epoch(train) [139][15/63] lr: 6.2705e-03 eta: 1 day, 3:41:46 time: 1.8086 data_time: 0.0498 memory: 16201 loss_prob: 0.9782 loss_thr: 0.5570 loss_db: 0.1626 loss: 1.6978 2022/08/30 02:55:52 - mmengine - INFO - Epoch(train) [139][20/63] lr: 6.2705e-03 eta: 1 day, 3:41:53 time: 1.7641 data_time: 0.0398 memory: 16201 loss_prob: 0.9744 loss_thr: 0.5429 loss_db: 0.1604 loss: 1.6778 2022/08/30 02:56:00 - mmengine - INFO - Epoch(train) [139][25/63] lr: 6.2705e-03 eta: 1 day, 3:41:53 time: 1.6457 data_time: 0.0602 memory: 16201 loss_prob: 0.9606 loss_thr: 0.5178 loss_db: 0.1605 loss: 1.6389 2022/08/30 02:56:08 - mmengine - INFO - Epoch(train) [139][30/63] lr: 6.2705e-03 eta: 1 day, 3:41:48 time: 1.6227 data_time: 0.0424 memory: 16201 loss_prob: 0.9797 loss_thr: 0.5294 loss_db: 0.1633 loss: 1.6724 2022/08/30 02:56:17 - mmengine - INFO - Epoch(train) [139][35/63] lr: 6.2705e-03 eta: 1 day, 3:41:48 time: 1.7167 data_time: 0.0437 memory: 16201 loss_prob: 0.9874 loss_thr: 0.5334 loss_db: 0.1600 loss: 1.6808 2022/08/30 02:56:25 - mmengine - INFO - Epoch(train) [139][40/63] lr: 6.2705e-03 eta: 1 day, 3:41:47 time: 1.6790 data_time: 0.0515 memory: 16201 loss_prob: 0.9825 loss_thr: 0.5379 loss_db: 0.1643 loss: 1.6847 2022/08/30 02:56:32 - mmengine - INFO - Epoch(train) [139][45/63] lr: 6.2705e-03 eta: 1 day, 3:41:47 time: 1.5191 data_time: 0.0383 memory: 16201 loss_prob: 0.9796 loss_thr: 0.5151 loss_db: 0.1670 loss: 1.6617 2022/08/30 02:56:41 - mmengine - INFO - Epoch(train) [139][50/63] lr: 6.2705e-03 eta: 1 day, 3:41:35 time: 1.5320 data_time: 0.0504 memory: 16201 loss_prob: 1.0324 loss_thr: 0.5099 loss_db: 0.1699 loss: 1.7121 2022/08/30 02:56:47 - mmengine - INFO - Epoch(train) [139][55/63] lr: 6.2705e-03 eta: 1 day, 3:41:35 time: 1.4686 data_time: 0.0422 memory: 16201 loss_prob: 1.1101 loss_thr: 0.5477 loss_db: 0.1782 loss: 1.8361 2022/08/30 02:56:57 - mmengine - INFO - Epoch(train) [139][60/63] lr: 6.2705e-03 eta: 1 day, 3:41:30 time: 1.6190 data_time: 0.0467 memory: 16201 loss_prob: 1.0590 loss_thr: 0.5657 loss_db: 0.1748 loss: 1.7994 2022/08/30 02:57:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:57:12 - mmengine - INFO - Epoch(train) [140][5/63] lr: 6.2652e-03 eta: 1 day, 3:41:30 time: 1.9132 data_time: 0.2719 memory: 16201 loss_prob: 0.9662 loss_thr: 0.5432 loss_db: 0.1558 loss: 1.6651 2022/08/30 02:57:22 - mmengine - INFO - Epoch(train) [140][10/63] lr: 6.2652e-03 eta: 1 day, 3:41:29 time: 2.1820 data_time: 0.3015 memory: 16201 loss_prob: 1.0366 loss_thr: 0.5720 loss_db: 0.1672 loss: 1.7759 2022/08/30 02:57:31 - mmengine - INFO - Epoch(train) [140][15/63] lr: 6.2652e-03 eta: 1 day, 3:41:29 time: 1.8303 data_time: 0.0446 memory: 16201 loss_prob: 1.1181 loss_thr: 0.5801 loss_db: 0.1778 loss: 1.8759 2022/08/30 02:57:41 - mmengine - INFO - Epoch(train) [140][20/63] lr: 6.2652e-03 eta: 1 day, 3:41:50 time: 1.9569 data_time: 0.0393 memory: 16201 loss_prob: 0.9504 loss_thr: 0.5149 loss_db: 0.1533 loss: 1.6186 2022/08/30 02:57:51 - mmengine - INFO - Epoch(train) [140][25/63] lr: 6.2652e-03 eta: 1 day, 3:41:50 time: 2.0349 data_time: 0.0646 memory: 16201 loss_prob: 0.8732 loss_thr: 0.4855 loss_db: 0.1454 loss: 1.5040 2022/08/30 02:57:59 - mmengine - INFO - Epoch(train) [140][30/63] lr: 6.2652e-03 eta: 1 day, 3:41:57 time: 1.7841 data_time: 0.0383 memory: 16201 loss_prob: 0.8753 loss_thr: 0.4866 loss_db: 0.1463 loss: 1.5083 2022/08/30 02:58:08 - mmengine - INFO - Epoch(train) [140][35/63] lr: 6.2652e-03 eta: 1 day, 3:41:57 time: 1.7318 data_time: 0.0409 memory: 16201 loss_prob: 0.9113 loss_thr: 0.5055 loss_db: 0.1500 loss: 1.5668 2022/08/30 02:58:16 - mmengine - INFO - Epoch(train) [140][40/63] lr: 6.2652e-03 eta: 1 day, 3:41:56 time: 1.6770 data_time: 0.0445 memory: 16201 loss_prob: 0.8713 loss_thr: 0.5094 loss_db: 0.1429 loss: 1.5236 2022/08/30 02:58:25 - mmengine - INFO - Epoch(train) [140][45/63] lr: 6.2652e-03 eta: 1 day, 3:41:56 time: 1.6214 data_time: 0.0340 memory: 16201 loss_prob: 0.8885 loss_thr: 0.5086 loss_db: 0.1494 loss: 1.5465 2022/08/30 02:58:33 - mmengine - INFO - Epoch(train) [140][50/63] lr: 6.2652e-03 eta: 1 day, 3:42:00 time: 1.7419 data_time: 0.0459 memory: 16201 loss_prob: 0.9433 loss_thr: 0.5176 loss_db: 0.1568 loss: 1.6177 2022/08/30 02:58:41 - mmengine - INFO - Epoch(train) [140][55/63] lr: 6.2652e-03 eta: 1 day, 3:42:00 time: 1.6540 data_time: 0.0321 memory: 16201 loss_prob: 0.8901 loss_thr: 0.5125 loss_db: 0.1457 loss: 1.5483 2022/08/30 02:58:51 - mmengine - INFO - Epoch(train) [140][60/63] lr: 6.2652e-03 eta: 1 day, 3:42:02 time: 1.7112 data_time: 0.0406 memory: 16201 loss_prob: 0.9563 loss_thr: 0.5298 loss_db: 0.1575 loss: 1.6437 2022/08/30 02:58:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 02:58:55 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/08/30 02:59:05 - mmengine - INFO - Epoch(val) [140][5/32] eta: 1 day, 3:42:02 time: 0.7385 data_time: 0.1483 memory: 16201 2022/08/30 02:59:09 - mmengine - INFO - Epoch(val) [140][10/32] eta: 0:00:18 time: 0.8515 data_time: 0.2005 memory: 15734 2022/08/30 02:59:12 - mmengine - INFO - Epoch(val) [140][15/32] eta: 0:00:18 time: 0.7090 data_time: 0.0722 memory: 15734 2022/08/30 02:59:16 - mmengine - INFO - Epoch(val) [140][20/32] eta: 0:00:08 time: 0.6874 data_time: 0.0653 memory: 15734 2022/08/30 02:59:20 - mmengine - INFO - Epoch(val) [140][25/32] eta: 0:00:08 time: 0.8083 data_time: 0.0773 memory: 15734 2022/08/30 02:59:23 - mmengine - INFO - Epoch(val) [140][30/32] eta: 0:00:01 time: 0.7635 data_time: 0.0405 memory: 15734 2022/08/30 02:59:24 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 02:59:24 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8334, precision: 0.6617, hmean: 0.7377 2022/08/30 02:59:24 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8334, precision: 0.7325, hmean: 0.7797 2022/08/30 02:59:24 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8300, precision: 0.7826, hmean: 0.8056 2022/08/30 02:59:24 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8219, precision: 0.8319, hmean: 0.8268 2022/08/30 02:59:24 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7886, precision: 0.8745, hmean: 0.8294 2022/08/30 02:59:24 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5797, precision: 0.9406, hmean: 0.7173 2022/08/30 02:59:24 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0058, precision: 1.0000, hmean: 0.0115 2022/08/30 02:59:24 - mmengine - INFO - Epoch(val) [140][32/32] icdar/precision: 0.8745 icdar/recall: 0.7886 icdar/hmean: 0.8294 2022/08/30 02:59:35 - mmengine - INFO - Epoch(train) [141][5/63] lr: 6.2599e-03 eta: 0:00:01 time: 1.8840 data_time: 0.2590 memory: 16201 loss_prob: 0.9438 loss_thr: 0.5264 loss_db: 0.1528 loss: 1.6230 2022/08/30 02:59:44 - mmengine - INFO - Epoch(train) [141][10/63] lr: 6.2599e-03 eta: 1 day, 3:41:47 time: 2.0025 data_time: 0.2893 memory: 16201 loss_prob: 0.9582 loss_thr: 0.5429 loss_db: 0.1533 loss: 1.6543 2022/08/30 02:59:52 - mmengine - INFO - Epoch(train) [141][15/63] lr: 6.2599e-03 eta: 1 day, 3:41:47 time: 1.7448 data_time: 0.0548 memory: 16201 loss_prob: 0.9479 loss_thr: 0.5387 loss_db: 0.1573 loss: 1.6439 2022/08/30 03:00:02 - mmengine - INFO - Epoch(train) [141][20/63] lr: 6.2599e-03 eta: 1 day, 3:41:52 time: 1.7602 data_time: 0.0527 memory: 16201 loss_prob: 0.9496 loss_thr: 0.5346 loss_db: 0.1566 loss: 1.6408 2022/08/30 03:00:09 - mmengine - INFO - Epoch(train) [141][25/63] lr: 6.2599e-03 eta: 1 day, 3:41:52 time: 1.6239 data_time: 0.0545 memory: 16201 loss_prob: 0.9351 loss_thr: 0.5384 loss_db: 0.1532 loss: 1.6266 2022/08/30 03:00:18 - mmengine - INFO - Epoch(train) [141][30/63] lr: 6.2599e-03 eta: 1 day, 3:41:43 time: 1.5666 data_time: 0.0366 memory: 16201 loss_prob: 0.9145 loss_thr: 0.5218 loss_db: 0.1556 loss: 1.5919 2022/08/30 03:00:27 - mmengine - INFO - Epoch(train) [141][35/63] lr: 6.2599e-03 eta: 1 day, 3:41:43 time: 1.8874 data_time: 0.0359 memory: 16201 loss_prob: 0.9136 loss_thr: 0.5016 loss_db: 0.1560 loss: 1.5712 2022/08/30 03:00:36 - mmengine - INFO - Epoch(train) [141][40/63] lr: 6.2599e-03 eta: 1 day, 3:41:54 time: 1.8381 data_time: 0.0387 memory: 16201 loss_prob: 0.9135 loss_thr: 0.5030 loss_db: 0.1498 loss: 1.5663 2022/08/30 03:00:45 - mmengine - INFO - Epoch(train) [141][45/63] lr: 6.2599e-03 eta: 1 day, 3:41:54 time: 1.7270 data_time: 0.0441 memory: 16201 loss_prob: 0.8720 loss_thr: 0.5042 loss_db: 0.1437 loss: 1.5199 2022/08/30 03:00:55 - mmengine - INFO - Epoch(train) [141][50/63] lr: 6.2599e-03 eta: 1 day, 3:42:07 time: 1.8654 data_time: 0.0431 memory: 16201 loss_prob: 0.8885 loss_thr: 0.5027 loss_db: 0.1477 loss: 1.5390 2022/08/30 03:01:02 - mmengine - INFO - Epoch(train) [141][55/63] lr: 6.2599e-03 eta: 1 day, 3:42:07 time: 1.7514 data_time: 0.0651 memory: 16201 loss_prob: 0.9366 loss_thr: 0.5186 loss_db: 0.1546 loss: 1.6098 2022/08/30 03:01:11 - mmengine - INFO - Epoch(train) [141][60/63] lr: 6.2599e-03 eta: 1 day, 3:42:03 time: 1.6434 data_time: 0.0654 memory: 16201 loss_prob: 0.9308 loss_thr: 0.5316 loss_db: 0.1530 loss: 1.6154 2022/08/30 03:01:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:01:27 - mmengine - INFO - Epoch(train) [142][5/63] lr: 6.2546e-03 eta: 1 day, 3:42:03 time: 1.9541 data_time: 0.2427 memory: 16201 loss_prob: 0.8712 loss_thr: 0.4954 loss_db: 0.1440 loss: 1.5106 2022/08/30 03:01:36 - mmengine - INFO - Epoch(train) [142][10/63] lr: 6.2546e-03 eta: 1 day, 3:41:54 time: 2.0853 data_time: 0.2720 memory: 16201 loss_prob: 0.9672 loss_thr: 0.5219 loss_db: 0.1593 loss: 1.6484 2022/08/30 03:01:45 - mmengine - INFO - Epoch(train) [142][15/63] lr: 6.2546e-03 eta: 1 day, 3:41:54 time: 1.8018 data_time: 0.0499 memory: 16201 loss_prob: 1.0403 loss_thr: 0.5715 loss_db: 0.1727 loss: 1.7845 2022/08/30 03:01:55 - mmengine - INFO - Epoch(train) [142][20/63] lr: 6.2546e-03 eta: 1 day, 3:42:07 time: 1.8643 data_time: 0.0265 memory: 16201 loss_prob: 1.0233 loss_thr: 0.5606 loss_db: 0.1687 loss: 1.7526 2022/08/30 03:02:03 - mmengine - INFO - Epoch(train) [142][25/63] lr: 6.2546e-03 eta: 1 day, 3:42:07 time: 1.8310 data_time: 0.0275 memory: 16201 loss_prob: 0.8997 loss_thr: 0.4953 loss_db: 0.1479 loss: 1.5430 2022/08/30 03:02:12 - mmengine - INFO - Epoch(train) [142][30/63] lr: 6.2546e-03 eta: 1 day, 3:42:09 time: 1.7159 data_time: 0.0340 memory: 16201 loss_prob: 0.8324 loss_thr: 0.4952 loss_db: 0.1384 loss: 1.4660 2022/08/30 03:02:19 - mmengine - INFO - Epoch(train) [142][35/63] lr: 6.2546e-03 eta: 1 day, 3:42:09 time: 1.6074 data_time: 0.0505 memory: 16201 loss_prob: 0.8481 loss_thr: 0.5023 loss_db: 0.1435 loss: 1.4939 2022/08/30 03:02:28 - mmengine - INFO - Epoch(train) [142][40/63] lr: 6.2546e-03 eta: 1 day, 3:42:04 time: 1.6392 data_time: 0.0372 memory: 16201 loss_prob: 0.9050 loss_thr: 0.5080 loss_db: 0.1486 loss: 1.5616 2022/08/30 03:02:38 - mmengine - INFO - Epoch(train) [142][45/63] lr: 6.2546e-03 eta: 1 day, 3:42:04 time: 1.8464 data_time: 0.0466 memory: 16201 loss_prob: 0.9645 loss_thr: 0.5275 loss_db: 0.1577 loss: 1.6497 2022/08/30 03:02:47 - mmengine - INFO - Epoch(train) [142][50/63] lr: 6.2546e-03 eta: 1 day, 3:42:14 time: 1.8208 data_time: 0.0711 memory: 16201 loss_prob: 0.9725 loss_thr: 0.5318 loss_db: 0.1603 loss: 1.6646 2022/08/30 03:02:56 - mmengine - INFO - Epoch(train) [142][55/63] lr: 6.2546e-03 eta: 1 day, 3:42:14 time: 1.7888 data_time: 0.0447 memory: 16201 loss_prob: 0.9702 loss_thr: 0.5323 loss_db: 0.1559 loss: 1.6583 2022/08/30 03:03:05 - mmengine - INFO - Epoch(train) [142][60/63] lr: 6.2546e-03 eta: 1 day, 3:42:24 time: 1.8292 data_time: 0.0386 memory: 16201 loss_prob: 0.9345 loss_thr: 0.5202 loss_db: 0.1518 loss: 1.6065 2022/08/30 03:03:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:03:21 - mmengine - INFO - Epoch(train) [143][5/63] lr: 6.2493e-03 eta: 1 day, 3:42:24 time: 1.9504 data_time: 0.2548 memory: 16201 loss_prob: 0.8701 loss_thr: 0.4979 loss_db: 0.1419 loss: 1.5100 2022/08/30 03:03:30 - mmengine - INFO - Epoch(train) [143][10/63] lr: 6.2493e-03 eta: 1 day, 3:42:12 time: 2.0478 data_time: 0.3086 memory: 16201 loss_prob: 0.7657 loss_thr: 0.4910 loss_db: 0.1271 loss: 1.3839 2022/08/30 03:03:38 - mmengine - INFO - Epoch(train) [143][15/63] lr: 6.2493e-03 eta: 1 day, 3:42:12 time: 1.7488 data_time: 0.0800 memory: 16201 loss_prob: 0.7802 loss_thr: 0.4981 loss_db: 0.1310 loss: 1.4093 2022/08/30 03:03:46 - mmengine - INFO - Epoch(train) [143][20/63] lr: 6.2493e-03 eta: 1 day, 3:42:07 time: 1.6292 data_time: 0.0455 memory: 16201 loss_prob: 0.8525 loss_thr: 0.5228 loss_db: 0.1445 loss: 1.5198 2022/08/30 03:03:57 - mmengine - INFO - Epoch(train) [143][25/63] lr: 6.2493e-03 eta: 1 day, 3:42:07 time: 1.8936 data_time: 0.0419 memory: 16201 loss_prob: 0.9172 loss_thr: 0.5325 loss_db: 0.1534 loss: 1.6031 2022/08/30 03:04:06 - mmengine - INFO - Epoch(train) [143][30/63] lr: 6.2493e-03 eta: 1 day, 3:42:30 time: 2.0145 data_time: 0.0455 memory: 16201 loss_prob: 0.8742 loss_thr: 0.5170 loss_db: 0.1449 loss: 1.5361 2022/08/30 03:04:16 - mmengine - INFO - Epoch(train) [143][35/63] lr: 6.2493e-03 eta: 1 day, 3:42:30 time: 1.8840 data_time: 0.0498 memory: 16201 loss_prob: 0.8168 loss_thr: 0.5169 loss_db: 0.1347 loss: 1.4684 2022/08/30 03:04:25 - mmengine - INFO - Epoch(train) [143][40/63] lr: 6.2493e-03 eta: 1 day, 3:42:41 time: 1.8468 data_time: 0.0430 memory: 16201 loss_prob: 0.8192 loss_thr: 0.5038 loss_db: 0.1386 loss: 1.4616 2022/08/30 03:04:34 - mmengine - INFO - Epoch(train) [143][45/63] lr: 6.2493e-03 eta: 1 day, 3:42:41 time: 1.7874 data_time: 0.0494 memory: 16201 loss_prob: 0.8279 loss_thr: 0.5041 loss_db: 0.1392 loss: 1.4712 2022/08/30 03:04:43 - mmengine - INFO - Epoch(train) [143][50/63] lr: 6.2493e-03 eta: 1 day, 3:42:50 time: 1.8188 data_time: 0.0484 memory: 16201 loss_prob: 1.0443 loss_thr: 0.5457 loss_db: 0.1655 loss: 1.7555 2022/08/30 03:04:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:04:52 - mmengine - INFO - Epoch(train) [143][55/63] lr: 6.2493e-03 eta: 1 day, 3:42:50 time: 1.8716 data_time: 0.0446 memory: 16201 loss_prob: 1.0318 loss_thr: 0.5393 loss_db: 0.1647 loss: 1.7358 2022/08/30 03:05:01 - mmengine - INFO - Epoch(train) [143][60/63] lr: 6.2493e-03 eta: 1 day, 3:42:55 time: 1.7676 data_time: 0.0712 memory: 16201 loss_prob: 0.8847 loss_thr: 0.4826 loss_db: 0.1465 loss: 1.5138 2022/08/30 03:05:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:05:18 - mmengine - INFO - Epoch(train) [144][5/63] lr: 6.2439e-03 eta: 1 day, 3:42:55 time: 2.0162 data_time: 0.3093 memory: 16201 loss_prob: 1.1075 loss_thr: 0.5177 loss_db: 0.1707 loss: 1.7959 2022/08/30 03:05:27 - mmengine - INFO - Epoch(train) [144][10/63] lr: 6.2439e-03 eta: 1 day, 3:42:52 time: 2.1699 data_time: 0.3377 memory: 16201 loss_prob: 1.0171 loss_thr: 0.5182 loss_db: 0.1622 loss: 1.6975 2022/08/30 03:05:34 - mmengine - INFO - Epoch(train) [144][15/63] lr: 6.2439e-03 eta: 1 day, 3:42:52 time: 1.6309 data_time: 0.0586 memory: 16201 loss_prob: 1.0355 loss_thr: 0.5328 loss_db: 0.1738 loss: 1.7420 2022/08/30 03:05:43 - mmengine - INFO - Epoch(train) [144][20/63] lr: 6.2439e-03 eta: 1 day, 3:42:44 time: 1.5918 data_time: 0.0400 memory: 16201 loss_prob: 1.2121 loss_thr: 0.5714 loss_db: 0.2031 loss: 1.9866 2022/08/30 03:05:51 - mmengine - INFO - Epoch(train) [144][25/63] lr: 6.2439e-03 eta: 1 day, 3:42:44 time: 1.6942 data_time: 0.0478 memory: 16201 loss_prob: 1.1099 loss_thr: 0.5698 loss_db: 0.1843 loss: 1.8640 2022/08/30 03:06:00 - mmengine - INFO - Epoch(train) [144][30/63] lr: 6.2439e-03 eta: 1 day, 3:42:48 time: 1.7652 data_time: 0.0405 memory: 16201 loss_prob: 1.0859 loss_thr: 0.5702 loss_db: 0.1765 loss: 1.8326 2022/08/30 03:06:10 - mmengine - INFO - Epoch(train) [144][35/63] lr: 6.2439e-03 eta: 1 day, 3:42:48 time: 1.9051 data_time: 0.0382 memory: 16201 loss_prob: 1.0893 loss_thr: 0.5706 loss_db: 0.1784 loss: 1.8382 2022/08/30 03:06:20 - mmengine - INFO - Epoch(train) [144][40/63] lr: 6.2439e-03 eta: 1 day, 3:43:07 time: 1.9495 data_time: 0.0384 memory: 16201 loss_prob: 1.0078 loss_thr: 0.5527 loss_db: 0.1690 loss: 1.7295 2022/08/30 03:06:28 - mmengine - INFO - Epoch(train) [144][45/63] lr: 6.2439e-03 eta: 1 day, 3:43:07 time: 1.7948 data_time: 0.0357 memory: 16201 loss_prob: 1.0007 loss_thr: 0.5666 loss_db: 0.1680 loss: 1.7352 2022/08/30 03:06:37 - mmengine - INFO - Epoch(train) [144][50/63] lr: 6.2439e-03 eta: 1 day, 3:43:08 time: 1.7208 data_time: 0.0432 memory: 16201 loss_prob: 0.9596 loss_thr: 0.5479 loss_db: 0.1579 loss: 1.6654 2022/08/30 03:06:47 - mmengine - INFO - Epoch(train) [144][55/63] lr: 6.2439e-03 eta: 1 day, 3:43:08 time: 1.8294 data_time: 0.0482 memory: 16201 loss_prob: 0.9567 loss_thr: 0.5165 loss_db: 0.1581 loss: 1.6314 2022/08/30 03:06:56 - mmengine - INFO - Epoch(train) [144][60/63] lr: 6.2439e-03 eta: 1 day, 3:43:21 time: 1.8868 data_time: 0.0490 memory: 16201 loss_prob: 1.0375 loss_thr: 0.5514 loss_db: 0.1715 loss: 1.7604 2022/08/30 03:07:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:07:13 - mmengine - INFO - Epoch(train) [145][5/63] lr: 6.2386e-03 eta: 1 day, 3:43:21 time: 2.0585 data_time: 0.2649 memory: 16201 loss_prob: 1.1181 loss_thr: 0.5705 loss_db: 0.1920 loss: 1.8806 2022/08/30 03:07:24 - mmengine - INFO - Epoch(train) [145][10/63] lr: 6.2386e-03 eta: 1 day, 3:43:17 time: 2.1537 data_time: 0.2758 memory: 16201 loss_prob: 1.0030 loss_thr: 0.5313 loss_db: 0.1711 loss: 1.7053 2022/08/30 03:07:31 - mmengine - INFO - Epoch(train) [145][15/63] lr: 6.2386e-03 eta: 1 day, 3:43:17 time: 1.8263 data_time: 0.0485 memory: 16201 loss_prob: 0.9938 loss_thr: 0.5225 loss_db: 0.1656 loss: 1.6818 2022/08/30 03:07:41 - mmengine - INFO - Epoch(train) [145][20/63] lr: 6.2386e-03 eta: 1 day, 3:43:19 time: 1.7357 data_time: 0.0377 memory: 16201 loss_prob: 0.9542 loss_thr: 0.5213 loss_db: 0.1579 loss: 1.6334 2022/08/30 03:07:49 - mmengine - INFO - Epoch(train) [145][25/63] lr: 6.2386e-03 eta: 1 day, 3:43:19 time: 1.7615 data_time: 0.0434 memory: 16201 loss_prob: 0.9875 loss_thr: 0.5276 loss_db: 0.1624 loss: 1.6776 2022/08/30 03:07:57 - mmengine - INFO - Epoch(train) [145][30/63] lr: 6.2386e-03 eta: 1 day, 3:43:15 time: 1.6505 data_time: 0.0431 memory: 16201 loss_prob: 1.0041 loss_thr: 0.5326 loss_db: 0.1688 loss: 1.7055 2022/08/30 03:08:06 - mmengine - INFO - Epoch(train) [145][35/63] lr: 6.2386e-03 eta: 1 day, 3:43:15 time: 1.7468 data_time: 0.0514 memory: 16201 loss_prob: 1.0773 loss_thr: 0.5575 loss_db: 0.1804 loss: 1.8153 2022/08/30 03:08:14 - mmengine - INFO - Epoch(train) [145][40/63] lr: 6.2386e-03 eta: 1 day, 3:43:08 time: 1.6169 data_time: 0.0629 memory: 16201 loss_prob: 1.2239 loss_thr: 0.5762 loss_db: 0.1913 loss: 1.9914 2022/08/30 03:08:22 - mmengine - INFO - Epoch(train) [145][45/63] lr: 6.2386e-03 eta: 1 day, 3:43:08 time: 1.5957 data_time: 0.0433 memory: 16201 loss_prob: 1.0441 loss_thr: 0.5349 loss_db: 0.1632 loss: 1.7422 2022/08/30 03:08:31 - mmengine - INFO - Epoch(train) [145][50/63] lr: 6.2386e-03 eta: 1 day, 3:43:13 time: 1.7694 data_time: 0.0418 memory: 16201 loss_prob: 0.9483 loss_thr: 0.5679 loss_db: 0.1612 loss: 1.6774 2022/08/30 03:08:40 - mmengine - INFO - Epoch(train) [145][55/63] lr: 6.2386e-03 eta: 1 day, 3:43:13 time: 1.7130 data_time: 0.0485 memory: 16201 loss_prob: 1.0406 loss_thr: 0.5839 loss_db: 0.1713 loss: 1.7958 2022/08/30 03:08:48 - mmengine - INFO - Epoch(train) [145][60/63] lr: 6.2386e-03 eta: 1 day, 3:43:11 time: 1.6842 data_time: 0.0446 memory: 16201 loss_prob: 0.9085 loss_thr: 0.5107 loss_db: 0.1470 loss: 1.5662 2022/08/30 03:08:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:09:04 - mmengine - INFO - Epoch(train) [146][5/63] lr: 6.2333e-03 eta: 1 day, 3:43:11 time: 1.9527 data_time: 0.2793 memory: 16201 loss_prob: 0.9497 loss_thr: 0.5335 loss_db: 0.1557 loss: 1.6390 2022/08/30 03:09:14 - mmengine - INFO - Epoch(train) [146][10/63] lr: 6.2333e-03 eta: 1 day, 3:43:09 time: 2.1944 data_time: 0.2946 memory: 16201 loss_prob: 0.9720 loss_thr: 0.5430 loss_db: 0.1589 loss: 1.6739 2022/08/30 03:09:22 - mmengine - INFO - Epoch(train) [146][15/63] lr: 6.2333e-03 eta: 1 day, 3:43:09 time: 1.8365 data_time: 0.0465 memory: 16201 loss_prob: 0.8393 loss_thr: 0.4908 loss_db: 0.1382 loss: 1.4682 2022/08/30 03:09:33 - mmengine - INFO - Epoch(train) [146][20/63] lr: 6.2333e-03 eta: 1 day, 3:43:19 time: 1.8370 data_time: 0.0339 memory: 16201 loss_prob: 0.8035 loss_thr: 0.4878 loss_db: 0.1301 loss: 1.4214 2022/08/30 03:09:41 - mmengine - INFO - Epoch(train) [146][25/63] lr: 6.2333e-03 eta: 1 day, 3:43:19 time: 1.8558 data_time: 0.0429 memory: 16201 loss_prob: 0.8071 loss_thr: 0.4895 loss_db: 0.1342 loss: 1.4308 2022/08/30 03:09:51 - mmengine - INFO - Epoch(train) [146][30/63] lr: 6.2333e-03 eta: 1 day, 3:43:30 time: 1.8614 data_time: 0.0419 memory: 16201 loss_prob: 0.8377 loss_thr: 0.4894 loss_db: 0.1397 loss: 1.4668 2022/08/30 03:10:00 - mmengine - INFO - Epoch(train) [146][35/63] lr: 6.2333e-03 eta: 1 day, 3:43:30 time: 1.8993 data_time: 0.0560 memory: 16201 loss_prob: 0.8756 loss_thr: 0.5052 loss_db: 0.1423 loss: 1.5231 2022/08/30 03:10:08 - mmengine - INFO - Epoch(train) [146][40/63] lr: 6.2333e-03 eta: 1 day, 3:43:23 time: 1.6221 data_time: 0.0431 memory: 16201 loss_prob: 0.8519 loss_thr: 0.5053 loss_db: 0.1403 loss: 1.4975 2022/08/30 03:10:15 - mmengine - INFO - Epoch(train) [146][45/63] lr: 6.2333e-03 eta: 1 day, 3:43:23 time: 1.4935 data_time: 0.0304 memory: 16201 loss_prob: 0.8633 loss_thr: 0.5133 loss_db: 0.1423 loss: 1.5189 2022/08/30 03:10:22 - mmengine - INFO - Epoch(train) [146][50/63] lr: 6.2333e-03 eta: 1 day, 3:43:07 time: 1.4798 data_time: 0.0368 memory: 16201 loss_prob: 0.8740 loss_thr: 0.5170 loss_db: 0.1438 loss: 1.5348 2022/08/30 03:10:31 - mmengine - INFO - Epoch(train) [146][55/63] lr: 6.2333e-03 eta: 1 day, 3:43:07 time: 1.6000 data_time: 0.0363 memory: 16201 loss_prob: 0.8947 loss_thr: 0.5348 loss_db: 0.1463 loss: 1.5758 2022/08/30 03:10:40 - mmengine - INFO - Epoch(train) [146][60/63] lr: 6.2333e-03 eta: 1 day, 3:43:06 time: 1.7062 data_time: 0.0548 memory: 16201 loss_prob: 0.9590 loss_thr: 0.5577 loss_db: 0.1554 loss: 1.6721 2022/08/30 03:10:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:10:54 - mmengine - INFO - Epoch(train) [147][5/63] lr: 6.2280e-03 eta: 1 day, 3:43:06 time: 1.8221 data_time: 0.2655 memory: 16201 loss_prob: 1.0147 loss_thr: 0.5317 loss_db: 0.1728 loss: 1.7193 2022/08/30 03:11:04 - mmengine - INFO - Epoch(train) [147][10/63] lr: 6.2280e-03 eta: 1 day, 3:42:54 time: 2.0545 data_time: 0.2656 memory: 16201 loss_prob: 0.9686 loss_thr: 0.5389 loss_db: 0.1642 loss: 1.6717 2022/08/30 03:11:13 - mmengine - INFO - Epoch(train) [147][15/63] lr: 6.2280e-03 eta: 1 day, 3:42:54 time: 1.8486 data_time: 0.0571 memory: 16201 loss_prob: 0.8750 loss_thr: 0.5285 loss_db: 0.1422 loss: 1.5458 2022/08/30 03:11:23 - mmengine - INFO - Epoch(train) [147][20/63] lr: 6.2280e-03 eta: 1 day, 3:43:05 time: 1.8652 data_time: 0.0494 memory: 16201 loss_prob: 0.9964 loss_thr: 0.5419 loss_db: 0.1585 loss: 1.6968 2022/08/30 03:11:32 - mmengine - INFO - Epoch(train) [147][25/63] lr: 6.2280e-03 eta: 1 day, 3:43:05 time: 1.9172 data_time: 0.0548 memory: 16201 loss_prob: 1.0668 loss_thr: 0.5490 loss_db: 0.1714 loss: 1.7872 2022/08/30 03:11:41 - mmengine - INFO - Epoch(train) [147][30/63] lr: 6.2280e-03 eta: 1 day, 3:43:11 time: 1.7915 data_time: 0.0431 memory: 16201 loss_prob: 0.9263 loss_thr: 0.5095 loss_db: 0.1499 loss: 1.5858 2022/08/30 03:11:50 - mmengine - INFO - Epoch(train) [147][35/63] lr: 6.2280e-03 eta: 1 day, 3:43:11 time: 1.8036 data_time: 0.0389 memory: 16201 loss_prob: 1.0537 loss_thr: 0.5639 loss_db: 0.1672 loss: 1.7847 2022/08/30 03:12:00 - mmengine - INFO - Epoch(train) [147][40/63] lr: 6.2280e-03 eta: 1 day, 3:43:23 time: 1.8858 data_time: 0.0397 memory: 16201 loss_prob: 1.1109 loss_thr: 0.5821 loss_db: 0.1812 loss: 1.8742 2022/08/30 03:12:09 - mmengine - INFO - Epoch(train) [147][45/63] lr: 6.2280e-03 eta: 1 day, 3:43:23 time: 1.9005 data_time: 0.0388 memory: 16201 loss_prob: 0.9988 loss_thr: 0.5361 loss_db: 0.1706 loss: 1.7055 2022/08/30 03:12:18 - mmengine - INFO - Epoch(train) [147][50/63] lr: 6.2280e-03 eta: 1 day, 3:43:32 time: 1.8403 data_time: 0.0588 memory: 16201 loss_prob: 0.9650 loss_thr: 0.5166 loss_db: 0.1607 loss: 1.6423 2022/08/30 03:12:26 - mmengine - INFO - Epoch(train) [147][55/63] lr: 6.2280e-03 eta: 1 day, 3:43:32 time: 1.7136 data_time: 0.0549 memory: 16201 loss_prob: 0.8951 loss_thr: 0.4979 loss_db: 0.1461 loss: 1.5392 2022/08/30 03:12:36 - mmengine - INFO - Epoch(train) [147][60/63] lr: 6.2280e-03 eta: 1 day, 3:43:40 time: 1.8257 data_time: 0.0413 memory: 16201 loss_prob: 0.9844 loss_thr: 0.5216 loss_db: 0.1603 loss: 1.6663 2022/08/30 03:12:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:12:51 - mmengine - INFO - Epoch(train) [148][5/63] lr: 6.2227e-03 eta: 1 day, 3:43:40 time: 1.8353 data_time: 0.2647 memory: 16201 loss_prob: 1.0211 loss_thr: 0.5482 loss_db: 0.1656 loss: 1.7348 2022/08/30 03:12:59 - mmengine - INFO - Epoch(train) [148][10/63] lr: 6.2227e-03 eta: 1 day, 3:43:14 time: 1.8668 data_time: 0.2722 memory: 16201 loss_prob: 0.9528 loss_thr: 0.5251 loss_db: 0.1554 loss: 1.6333 2022/08/30 03:13:07 - mmengine - INFO - Epoch(train) [148][15/63] lr: 6.2227e-03 eta: 1 day, 3:43:14 time: 1.6446 data_time: 0.0407 memory: 16201 loss_prob: 0.9497 loss_thr: 0.5225 loss_db: 0.1615 loss: 1.6337 2022/08/30 03:13:16 - mmengine - INFO - Epoch(train) [148][20/63] lr: 6.2227e-03 eta: 1 day, 3:43:12 time: 1.6780 data_time: 0.0512 memory: 16201 loss_prob: 0.9429 loss_thr: 0.5146 loss_db: 0.1630 loss: 1.6206 2022/08/30 03:13:24 - mmengine - INFO - Epoch(train) [148][25/63] lr: 6.2227e-03 eta: 1 day, 3:43:12 time: 1.6738 data_time: 0.0499 memory: 16201 loss_prob: 1.0346 loss_thr: 0.5298 loss_db: 0.1727 loss: 1.7371 2022/08/30 03:13:33 - mmengine - INFO - Epoch(train) [148][30/63] lr: 6.2227e-03 eta: 1 day, 3:43:13 time: 1.7324 data_time: 0.0461 memory: 16201 loss_prob: 1.1230 loss_thr: 0.5664 loss_db: 0.1818 loss: 1.8711 2022/08/30 03:13:41 - mmengine - INFO - Epoch(train) [148][35/63] lr: 6.2227e-03 eta: 1 day, 3:43:13 time: 1.7102 data_time: 0.0422 memory: 16201 loss_prob: 1.0347 loss_thr: 0.5612 loss_db: 0.1692 loss: 1.7651 2022/08/30 03:13:50 - mmengine - INFO - Epoch(train) [148][40/63] lr: 6.2227e-03 eta: 1 day, 3:43:14 time: 1.7269 data_time: 0.0391 memory: 16201 loss_prob: 1.0109 loss_thr: 0.5355 loss_db: 0.1648 loss: 1.7112 2022/08/30 03:13:59 - mmengine - INFO - Epoch(train) [148][45/63] lr: 6.2227e-03 eta: 1 day, 3:43:14 time: 1.8150 data_time: 0.0489 memory: 16201 loss_prob: 1.0409 loss_thr: 0.5458 loss_db: 0.1706 loss: 1.7573 2022/08/30 03:14:07 - mmengine - INFO - Epoch(train) [148][50/63] lr: 6.2227e-03 eta: 1 day, 3:43:09 time: 1.6507 data_time: 0.0417 memory: 16201 loss_prob: 0.9622 loss_thr: 0.5474 loss_db: 0.1622 loss: 1.6718 2022/08/30 03:14:16 - mmengine - INFO - Epoch(train) [148][55/63] lr: 6.2227e-03 eta: 1 day, 3:43:09 time: 1.7156 data_time: 0.0369 memory: 16201 loss_prob: 0.8766 loss_thr: 0.5200 loss_db: 0.1475 loss: 1.5441 2022/08/30 03:14:24 - mmengine - INFO - Epoch(train) [148][60/63] lr: 6.2227e-03 eta: 1 day, 3:43:11 time: 1.7507 data_time: 0.0491 memory: 16201 loss_prob: 0.8861 loss_thr: 0.5215 loss_db: 0.1450 loss: 1.5526 2022/08/30 03:14:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:14:38 - mmengine - INFO - Epoch(train) [149][5/63] lr: 6.2173e-03 eta: 1 day, 3:43:11 time: 1.7011 data_time: 0.2522 memory: 16201 loss_prob: 0.9132 loss_thr: 0.4879 loss_db: 0.1477 loss: 1.5488 2022/08/30 03:14:46 - mmengine - INFO - Epoch(train) [149][10/63] lr: 6.2173e-03 eta: 1 day, 3:42:42 time: 1.8186 data_time: 0.2579 memory: 16201 loss_prob: 0.9603 loss_thr: 0.5224 loss_db: 0.1552 loss: 1.6380 2022/08/30 03:14:54 - mmengine - INFO - Epoch(train) [149][15/63] lr: 6.2173e-03 eta: 1 day, 3:42:42 time: 1.5428 data_time: 0.0355 memory: 16201 loss_prob: 0.9378 loss_thr: 0.5335 loss_db: 0.1540 loss: 1.6254 2022/08/30 03:15:00 - mmengine - INFO - Epoch(train) [149][20/63] lr: 6.2173e-03 eta: 1 day, 3:42:20 time: 1.4025 data_time: 0.0352 memory: 16201 loss_prob: 0.8927 loss_thr: 0.5111 loss_db: 0.1469 loss: 1.5507 2022/08/30 03:15:10 - mmengine - INFO - Epoch(train) [149][25/63] lr: 6.2173e-03 eta: 1 day, 3:42:20 time: 1.5949 data_time: 0.0514 memory: 16201 loss_prob: 0.9025 loss_thr: 0.5225 loss_db: 0.1485 loss: 1.5735 2022/08/30 03:15:19 - mmengine - INFO - Epoch(train) [149][30/63] lr: 6.2173e-03 eta: 1 day, 3:42:29 time: 1.8512 data_time: 0.0470 memory: 16201 loss_prob: 0.9542 loss_thr: 0.5373 loss_db: 0.1591 loss: 1.6506 2022/08/30 03:15:27 - mmengine - INFO - Epoch(train) [149][35/63] lr: 6.2173e-03 eta: 1 day, 3:42:29 time: 1.7902 data_time: 0.0450 memory: 16201 loss_prob: 0.9125 loss_thr: 0.5062 loss_db: 0.1527 loss: 1.5713 2022/08/30 03:15:37 - mmengine - INFO - Epoch(train) [149][40/63] lr: 6.2173e-03 eta: 1 day, 3:42:33 time: 1.7681 data_time: 0.0465 memory: 16201 loss_prob: 0.9771 loss_thr: 0.5233 loss_db: 0.1586 loss: 1.6589 2022/08/30 03:15:45 - mmengine - INFO - Epoch(train) [149][45/63] lr: 6.2173e-03 eta: 1 day, 3:42:33 time: 1.7163 data_time: 0.0467 memory: 16201 loss_prob: 0.9468 loss_thr: 0.5373 loss_db: 0.1537 loss: 1.6377 2022/08/30 03:15:53 - mmengine - INFO - Epoch(train) [149][50/63] lr: 6.2173e-03 eta: 1 day, 3:42:28 time: 1.6553 data_time: 0.0478 memory: 16201 loss_prob: 0.8381 loss_thr: 0.5212 loss_db: 0.1427 loss: 1.5020 2022/08/30 03:16:04 - mmengine - INFO - Epoch(train) [149][55/63] lr: 6.2173e-03 eta: 1 day, 3:42:28 time: 1.9012 data_time: 0.0458 memory: 16201 loss_prob: 0.8925 loss_thr: 0.5317 loss_db: 0.1490 loss: 1.5733 2022/08/30 03:16:12 - mmengine - INFO - Epoch(train) [149][60/63] lr: 6.2173e-03 eta: 1 day, 3:42:41 time: 1.9102 data_time: 0.0566 memory: 16201 loss_prob: 0.9577 loss_thr: 0.5441 loss_db: 0.1557 loss: 1.6575 2022/08/30 03:16:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:16:28 - mmengine - INFO - Epoch(train) [150][5/63] lr: 6.2120e-03 eta: 1 day, 3:42:41 time: 1.8339 data_time: 0.2673 memory: 16201 loss_prob: 0.9331 loss_thr: 0.5146 loss_db: 0.1591 loss: 1.6068 2022/08/30 03:16:38 - mmengine - INFO - Epoch(train) [150][10/63] lr: 6.2120e-03 eta: 1 day, 3:42:31 time: 2.0854 data_time: 0.2921 memory: 16201 loss_prob: 0.8415 loss_thr: 0.4807 loss_db: 0.1430 loss: 1.4652 2022/08/30 03:16:45 - mmengine - INFO - Epoch(train) [150][15/63] lr: 6.2120e-03 eta: 1 day, 3:42:31 time: 1.7757 data_time: 0.0532 memory: 16201 loss_prob: 0.9016 loss_thr: 0.4993 loss_db: 0.1473 loss: 1.5482 2022/08/30 03:16:55 - mmengine - INFO - Epoch(train) [150][20/63] lr: 6.2120e-03 eta: 1 day, 3:42:33 time: 1.7581 data_time: 0.0444 memory: 16201 loss_prob: 0.9460 loss_thr: 0.5189 loss_db: 0.1564 loss: 1.6213 2022/08/30 03:17:03 - mmengine - INFO - Epoch(train) [150][25/63] lr: 6.2120e-03 eta: 1 day, 3:42:33 time: 1.7525 data_time: 0.0436 memory: 16201 loss_prob: 0.8431 loss_thr: 0.5048 loss_db: 0.1421 loss: 1.4900 2022/08/30 03:17:11 - mmengine - INFO - Epoch(train) [150][30/63] lr: 6.2120e-03 eta: 1 day, 3:42:27 time: 1.6247 data_time: 0.0423 memory: 16201 loss_prob: 0.8134 loss_thr: 0.4950 loss_db: 0.1363 loss: 1.4448 2022/08/30 03:17:20 - mmengine - INFO - Epoch(train) [150][35/63] lr: 6.2120e-03 eta: 1 day, 3:42:27 time: 1.7216 data_time: 0.0495 memory: 16201 loss_prob: 0.8798 loss_thr: 0.5025 loss_db: 0.1453 loss: 1.5276 2022/08/30 03:17:28 - mmengine - INFO - Epoch(train) [150][40/63] lr: 6.2120e-03 eta: 1 day, 3:42:26 time: 1.7106 data_time: 0.0320 memory: 16201 loss_prob: 0.9262 loss_thr: 0.5172 loss_db: 0.1511 loss: 1.5945 2022/08/30 03:17:38 - mmengine - INFO - Epoch(train) [150][45/63] lr: 6.2120e-03 eta: 1 day, 3:42:26 time: 1.7727 data_time: 0.0426 memory: 16201 loss_prob: 0.8856 loss_thr: 0.5089 loss_db: 0.1450 loss: 1.5395 2022/08/30 03:17:47 - mmengine - INFO - Epoch(train) [150][50/63] lr: 6.2120e-03 eta: 1 day, 3:42:34 time: 1.8389 data_time: 0.0630 memory: 16201 loss_prob: 0.8865 loss_thr: 0.5073 loss_db: 0.1502 loss: 1.5440 2022/08/30 03:17:56 - mmengine - INFO - Epoch(train) [150][55/63] lr: 6.2120e-03 eta: 1 day, 3:42:34 time: 1.7879 data_time: 0.0423 memory: 16201 loss_prob: 0.9002 loss_thr: 0.5234 loss_db: 0.1521 loss: 1.5757 2022/08/30 03:18:04 - mmengine - INFO - Epoch(train) [150][60/63] lr: 6.2120e-03 eta: 1 day, 3:42:36 time: 1.7478 data_time: 0.0415 memory: 16201 loss_prob: 0.8535 loss_thr: 0.5152 loss_db: 0.1440 loss: 1.5127 2022/08/30 03:18:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:18:21 - mmengine - INFO - Epoch(train) [151][5/63] lr: 6.2067e-03 eta: 1 day, 3:42:36 time: 1.9957 data_time: 0.2541 memory: 16201 loss_prob: 0.8685 loss_thr: 0.5197 loss_db: 0.1455 loss: 1.5338 2022/08/30 03:18:30 - mmengine - INFO - Epoch(train) [151][10/63] lr: 6.2067e-03 eta: 1 day, 3:42:22 time: 2.0488 data_time: 0.2700 memory: 16201 loss_prob: 0.7916 loss_thr: 0.4811 loss_db: 0.1329 loss: 1.4056 2022/08/30 03:18:39 - mmengine - INFO - Epoch(train) [151][15/63] lr: 6.2067e-03 eta: 1 day, 3:42:22 time: 1.7585 data_time: 0.0362 memory: 16201 loss_prob: 0.8449 loss_thr: 0.4939 loss_db: 0.1397 loss: 1.4785 2022/08/30 03:18:46 - mmengine - INFO - Epoch(train) [151][20/63] lr: 6.2067e-03 eta: 1 day, 3:42:14 time: 1.6006 data_time: 0.0382 memory: 16201 loss_prob: 0.9278 loss_thr: 0.5184 loss_db: 0.1495 loss: 1.5957 2022/08/30 03:18:55 - mmengine - INFO - Epoch(train) [151][25/63] lr: 6.2067e-03 eta: 1 day, 3:42:14 time: 1.6942 data_time: 0.0362 memory: 16201 loss_prob: 0.9136 loss_thr: 0.5169 loss_db: 0.1517 loss: 1.5823 2022/08/30 03:19:03 - mmengine - INFO - Epoch(train) [151][30/63] lr: 6.2067e-03 eta: 1 day, 3:42:15 time: 1.7373 data_time: 0.0387 memory: 16201 loss_prob: 0.8913 loss_thr: 0.5130 loss_db: 0.1517 loss: 1.5559 2022/08/30 03:19:10 - mmengine - INFO - Epoch(train) [151][35/63] lr: 6.2067e-03 eta: 1 day, 3:42:15 time: 1.4956 data_time: 0.0492 memory: 16201 loss_prob: 0.8786 loss_thr: 0.5100 loss_db: 0.1463 loss: 1.5349 2022/08/30 03:19:18 - mmengine - INFO - Epoch(train) [151][40/63] lr: 6.2067e-03 eta: 1 day, 3:41:54 time: 1.4289 data_time: 0.0347 memory: 16201 loss_prob: 0.8830 loss_thr: 0.5159 loss_db: 0.1435 loss: 1.5424 2022/08/30 03:19:25 - mmengine - INFO - Epoch(train) [151][45/63] lr: 6.2067e-03 eta: 1 day, 3:41:54 time: 1.5029 data_time: 0.0371 memory: 16201 loss_prob: 0.8978 loss_thr: 0.5274 loss_db: 0.1437 loss: 1.5689 2022/08/30 03:19:36 - mmengine - INFO - Epoch(train) [151][50/63] lr: 6.2067e-03 eta: 1 day, 3:42:00 time: 1.8049 data_time: 0.0497 memory: 16201 loss_prob: 0.9087 loss_thr: 0.5237 loss_db: 0.1468 loss: 1.5792 2022/08/30 03:19:43 - mmengine - INFO - Epoch(train) [151][55/63] lr: 6.2067e-03 eta: 1 day, 3:42:00 time: 1.7947 data_time: 0.0392 memory: 16201 loss_prob: 0.8417 loss_thr: 0.4838 loss_db: 0.1397 loss: 1.4652 2022/08/30 03:19:52 - mmengine - INFO - Epoch(train) [151][60/63] lr: 6.2067e-03 eta: 1 day, 3:41:56 time: 1.6709 data_time: 0.0519 memory: 16201 loss_prob: 0.8543 loss_thr: 0.4908 loss_db: 0.1413 loss: 1.4864 2022/08/30 03:19:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:20:07 - mmengine - INFO - Epoch(train) [152][5/63] lr: 6.2014e-03 eta: 1 day, 3:41:56 time: 1.7551 data_time: 0.2624 memory: 16201 loss_prob: 0.9178 loss_thr: 0.5310 loss_db: 0.1537 loss: 1.6024 2022/08/30 03:20:16 - mmengine - INFO - Epoch(train) [152][10/63] lr: 6.2014e-03 eta: 1 day, 3:41:38 time: 1.9858 data_time: 0.2713 memory: 16201 loss_prob: 0.8652 loss_thr: 0.5363 loss_db: 0.1469 loss: 1.5483 2022/08/30 03:20:24 - mmengine - INFO - Epoch(train) [152][15/63] lr: 6.2014e-03 eta: 1 day, 3:41:38 time: 1.7027 data_time: 0.0451 memory: 16201 loss_prob: 0.9237 loss_thr: 0.5320 loss_db: 0.1523 loss: 1.6081 2022/08/30 03:20:32 - mmengine - INFO - Epoch(train) [152][20/63] lr: 6.2014e-03 eta: 1 day, 3:41:32 time: 1.6402 data_time: 0.0521 memory: 16201 loss_prob: 0.9416 loss_thr: 0.5239 loss_db: 0.1530 loss: 1.6185 2022/08/30 03:20:40 - mmengine - INFO - Epoch(train) [152][25/63] lr: 6.2014e-03 eta: 1 day, 3:41:32 time: 1.6648 data_time: 0.0571 memory: 16201 loss_prob: 0.8791 loss_thr: 0.4972 loss_db: 0.1444 loss: 1.5208 2022/08/30 03:20:49 - mmengine - INFO - Epoch(train) [152][30/63] lr: 6.2014e-03 eta: 1 day, 3:41:31 time: 1.7129 data_time: 0.0406 memory: 16201 loss_prob: 0.9227 loss_thr: 0.5066 loss_db: 0.1512 loss: 1.5805 2022/08/30 03:20:59 - mmengine - INFO - Epoch(train) [152][35/63] lr: 6.2014e-03 eta: 1 day, 3:41:31 time: 1.8211 data_time: 0.0396 memory: 16201 loss_prob: 0.8525 loss_thr: 0.5116 loss_db: 0.1404 loss: 1.5044 2022/08/30 03:21:07 - mmengine - INFO - Epoch(train) [152][40/63] lr: 6.2014e-03 eta: 1 day, 3:41:34 time: 1.7695 data_time: 0.0310 memory: 16201 loss_prob: 0.8850 loss_thr: 0.5123 loss_db: 0.1363 loss: 1.5336 2022/08/30 03:21:17 - mmengine - INFO - Epoch(train) [152][45/63] lr: 6.2014e-03 eta: 1 day, 3:41:34 time: 1.7931 data_time: 0.0306 memory: 16201 loss_prob: 0.9403 loss_thr: 0.5281 loss_db: 0.1454 loss: 1.6138 2022/08/30 03:21:26 - mmengine - INFO - Epoch(train) [152][50/63] lr: 6.2014e-03 eta: 1 day, 3:41:42 time: 1.8472 data_time: 0.0428 memory: 16201 loss_prob: 0.8766 loss_thr: 0.5227 loss_db: 0.1460 loss: 1.5452 2022/08/30 03:21:35 - mmengine - INFO - Epoch(train) [152][55/63] lr: 6.2014e-03 eta: 1 day, 3:41:42 time: 1.8171 data_time: 0.0367 memory: 16201 loss_prob: 0.8363 loss_thr: 0.5077 loss_db: 0.1396 loss: 1.4835 2022/08/30 03:21:44 - mmengine - INFO - Epoch(train) [152][60/63] lr: 6.2014e-03 eta: 1 day, 3:41:48 time: 1.8185 data_time: 0.0476 memory: 16201 loss_prob: 0.8469 loss_thr: 0.5328 loss_db: 0.1411 loss: 1.5207 2022/08/30 03:21:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:21:58 - mmengine - INFO - Epoch(train) [153][5/63] lr: 6.1960e-03 eta: 1 day, 3:41:48 time: 1.7913 data_time: 0.2503 memory: 16201 loss_prob: 0.8734 loss_thr: 0.5390 loss_db: 0.1461 loss: 1.5586 2022/08/30 03:22:05 - mmengine - INFO - Epoch(train) [153][10/63] lr: 6.1960e-03 eta: 1 day, 3:41:17 time: 1.7960 data_time: 0.2588 memory: 16201 loss_prob: 0.8498 loss_thr: 0.5109 loss_db: 0.1439 loss: 1.5046 2022/08/30 03:22:13 - mmengine - INFO - Epoch(train) [153][15/63] lr: 6.1960e-03 eta: 1 day, 3:41:17 time: 1.5137 data_time: 0.0416 memory: 16201 loss_prob: 0.8736 loss_thr: 0.4881 loss_db: 0.1439 loss: 1.5056 2022/08/30 03:22:23 - mmengine - INFO - Epoch(train) [153][20/63] lr: 6.1960e-03 eta: 1 day, 3:41:20 time: 1.7671 data_time: 0.0497 memory: 16201 loss_prob: 0.8877 loss_thr: 0.5049 loss_db: 0.1482 loss: 1.5409 2022/08/30 03:22:30 - mmengine - INFO - Epoch(train) [153][25/63] lr: 6.1960e-03 eta: 1 day, 3:41:20 time: 1.7185 data_time: 0.0549 memory: 16201 loss_prob: 0.8583 loss_thr: 0.5071 loss_db: 0.1482 loss: 1.5136 2022/08/30 03:22:38 - mmengine - INFO - Epoch(train) [153][30/63] lr: 6.1960e-03 eta: 1 day, 3:41:01 time: 1.4593 data_time: 0.0416 memory: 16201 loss_prob: 0.8596 loss_thr: 0.5154 loss_db: 0.1442 loss: 1.5192 2022/08/30 03:22:47 - mmengine - INFO - Epoch(train) [153][35/63] lr: 6.1960e-03 eta: 1 day, 3:41:01 time: 1.6558 data_time: 0.0399 memory: 16201 loss_prob: 0.9170 loss_thr: 0.5368 loss_db: 0.1540 loss: 1.6078 2022/08/30 03:22:56 - mmengine - INFO - Epoch(train) [153][40/63] lr: 6.1960e-03 eta: 1 day, 3:41:05 time: 1.7940 data_time: 0.0380 memory: 16201 loss_prob: 0.8977 loss_thr: 0.5274 loss_db: 0.1501 loss: 1.5752 2022/08/30 03:23:04 - mmengine - INFO - Epoch(train) [153][45/63] lr: 6.1960e-03 eta: 1 day, 3:41:05 time: 1.7427 data_time: 0.0445 memory: 16201 loss_prob: 0.8833 loss_thr: 0.5034 loss_db: 0.1426 loss: 1.5292 2022/08/30 03:23:11 - mmengine - INFO - Epoch(train) [153][50/63] lr: 6.1960e-03 eta: 1 day, 3:40:53 time: 1.5548 data_time: 0.0471 memory: 16201 loss_prob: 0.9268 loss_thr: 0.5020 loss_db: 0.1529 loss: 1.5816 2022/08/30 03:23:21 - mmengine - INFO - Epoch(train) [153][55/63] lr: 6.1960e-03 eta: 1 day, 3:40:53 time: 1.6365 data_time: 0.0375 memory: 16201 loss_prob: 0.9153 loss_thr: 0.5001 loss_db: 0.1578 loss: 1.5732 2022/08/30 03:23:30 - mmengine - INFO - Epoch(train) [153][60/63] lr: 6.1960e-03 eta: 1 day, 3:41:03 time: 1.8698 data_time: 0.0451 memory: 16201 loss_prob: 0.9643 loss_thr: 0.5093 loss_db: 0.1642 loss: 1.6378 2022/08/30 03:23:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:23:42 - mmengine - INFO - Epoch(train) [154][5/63] lr: 6.1907e-03 eta: 1 day, 3:41:03 time: 1.6329 data_time: 0.2572 memory: 16201 loss_prob: 0.9581 loss_thr: 0.5280 loss_db: 0.1610 loss: 1.6472 2022/08/30 03:23:51 - mmengine - INFO - Epoch(train) [154][10/63] lr: 6.1907e-03 eta: 1 day, 3:40:28 time: 1.7396 data_time: 0.2772 memory: 16201 loss_prob: 0.9736 loss_thr: 0.5171 loss_db: 0.1659 loss: 1.6566 2022/08/30 03:23:57 - mmengine - INFO - Epoch(train) [154][15/63] lr: 6.1907e-03 eta: 1 day, 3:40:28 time: 1.4821 data_time: 0.0403 memory: 16201 loss_prob: 0.9791 loss_thr: 0.5196 loss_db: 0.1627 loss: 1.6614 2022/08/30 03:24:04 - mmengine - INFO - Epoch(train) [154][20/63] lr: 6.1907e-03 eta: 1 day, 3:40:04 time: 1.3822 data_time: 0.0390 memory: 16201 loss_prob: 1.0243 loss_thr: 0.5572 loss_db: 0.1695 loss: 1.7510 2022/08/30 03:24:13 - mmengine - INFO - Epoch(train) [154][25/63] lr: 6.1907e-03 eta: 1 day, 3:40:04 time: 1.5542 data_time: 0.0572 memory: 16201 loss_prob: 1.0408 loss_thr: 0.5927 loss_db: 0.1737 loss: 1.8072 2022/08/30 03:24:21 - mmengine - INFO - Epoch(train) [154][30/63] lr: 6.1907e-03 eta: 1 day, 3:39:56 time: 1.6168 data_time: 0.0365 memory: 16201 loss_prob: 1.0606 loss_thr: 0.5790 loss_db: 0.1755 loss: 1.8151 2022/08/30 03:24:29 - mmengine - INFO - Epoch(train) [154][35/63] lr: 6.1907e-03 eta: 1 day, 3:39:56 time: 1.6193 data_time: 0.0432 memory: 16201 loss_prob: 1.0096 loss_thr: 0.5492 loss_db: 0.1646 loss: 1.7234 2022/08/30 03:24:38 - mmengine - INFO - Epoch(train) [154][40/63] lr: 6.1907e-03 eta: 1 day, 3:39:57 time: 1.7475 data_time: 0.0456 memory: 16201 loss_prob: 1.0249 loss_thr: 0.5481 loss_db: 0.1672 loss: 1.7402 2022/08/30 03:24:46 - mmengine - INFO - Epoch(train) [154][45/63] lr: 6.1907e-03 eta: 1 day, 3:39:57 time: 1.7028 data_time: 0.0336 memory: 16201 loss_prob: 1.0538 loss_thr: 0.5346 loss_db: 0.1748 loss: 1.7632 2022/08/30 03:24:55 - mmengine - INFO - Epoch(train) [154][50/63] lr: 6.1907e-03 eta: 1 day, 3:39:54 time: 1.6891 data_time: 0.0485 memory: 16201 loss_prob: 0.9701 loss_thr: 0.5277 loss_db: 0.1592 loss: 1.6571 2022/08/30 03:25:04 - mmengine - INFO - Epoch(train) [154][55/63] lr: 6.1907e-03 eta: 1 day, 3:39:54 time: 1.7510 data_time: 0.0360 memory: 16201 loss_prob: 0.9014 loss_thr: 0.5082 loss_db: 0.1464 loss: 1.5560 2022/08/30 03:25:13 - mmengine - INFO - Epoch(train) [154][60/63] lr: 6.1907e-03 eta: 1 day, 3:39:58 time: 1.7858 data_time: 0.0334 memory: 16201 loss_prob: 0.9196 loss_thr: 0.4863 loss_db: 0.1444 loss: 1.5503 2022/08/30 03:25:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:25:27 - mmengine - INFO - Epoch(train) [155][5/63] lr: 6.1854e-03 eta: 1 day, 3:39:58 time: 1.8264 data_time: 0.2413 memory: 16201 loss_prob: 0.9501 loss_thr: 0.5045 loss_db: 0.1500 loss: 1.6046 2022/08/30 03:25:37 - mmengine - INFO - Epoch(train) [155][10/63] lr: 6.1854e-03 eta: 1 day, 3:39:43 time: 2.0447 data_time: 0.2682 memory: 16201 loss_prob: 0.9480 loss_thr: 0.5162 loss_db: 0.1538 loss: 1.6180 2022/08/30 03:25:48 - mmengine - INFO - Epoch(train) [155][15/63] lr: 6.1854e-03 eta: 1 day, 3:39:43 time: 2.0373 data_time: 0.0520 memory: 16201 loss_prob: 1.0203 loss_thr: 0.5535 loss_db: 0.1728 loss: 1.7467 2022/08/30 03:25:56 - mmengine - INFO - Epoch(train) [155][20/63] lr: 6.1854e-03 eta: 1 day, 3:39:51 time: 1.8486 data_time: 0.0566 memory: 16201 loss_prob: 0.9524 loss_thr: 0.5382 loss_db: 0.1610 loss: 1.6516 2022/08/30 03:26:04 - mmengine - INFO - Epoch(train) [155][25/63] lr: 6.1854e-03 eta: 1 day, 3:39:51 time: 1.6799 data_time: 0.0581 memory: 16201 loss_prob: 0.9185 loss_thr: 0.5046 loss_db: 0.1516 loss: 1.5746 2022/08/30 03:26:15 - mmengine - INFO - Epoch(train) [155][30/63] lr: 6.1854e-03 eta: 1 day, 3:40:02 time: 1.8875 data_time: 0.0375 memory: 16201 loss_prob: 0.9888 loss_thr: 0.5217 loss_db: 0.1633 loss: 1.6739 2022/08/30 03:26:24 - mmengine - INFO - Epoch(train) [155][35/63] lr: 6.1854e-03 eta: 1 day, 3:40:02 time: 1.9119 data_time: 0.0487 memory: 16201 loss_prob: 0.9868 loss_thr: 0.5186 loss_db: 0.1605 loss: 1.6659 2022/08/30 03:26:33 - mmengine - INFO - Epoch(train) [155][40/63] lr: 6.1854e-03 eta: 1 day, 3:40:09 time: 1.8464 data_time: 0.0426 memory: 16201 loss_prob: 0.9830 loss_thr: 0.5097 loss_db: 0.1567 loss: 1.6494 2022/08/30 03:26:41 - mmengine - INFO - Epoch(train) [155][45/63] lr: 6.1854e-03 eta: 1 day, 3:40:09 time: 1.7710 data_time: 0.0453 memory: 16201 loss_prob: 0.9844 loss_thr: 0.5107 loss_db: 0.1598 loss: 1.6549 2022/08/30 03:26:51 - mmengine - INFO - Epoch(train) [155][50/63] lr: 6.1854e-03 eta: 1 day, 3:40:12 time: 1.7766 data_time: 0.0565 memory: 16201 loss_prob: 0.9947 loss_thr: 0.5505 loss_db: 0.1623 loss: 1.7075 2022/08/30 03:26:59 - mmengine - INFO - Epoch(train) [155][55/63] lr: 6.1854e-03 eta: 1 day, 3:40:12 time: 1.7958 data_time: 0.0470 memory: 16201 loss_prob: 0.9949 loss_thr: 0.5798 loss_db: 0.1622 loss: 1.7370 2022/08/30 03:27:07 - mmengine - INFO - Epoch(train) [155][60/63] lr: 6.1854e-03 eta: 1 day, 3:40:07 time: 1.6647 data_time: 0.0423 memory: 16201 loss_prob: 0.9600 loss_thr: 0.5240 loss_db: 0.1562 loss: 1.6402 2022/08/30 03:27:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:27:21 - mmengine - INFO - Epoch(train) [156][5/63] lr: 6.1801e-03 eta: 1 day, 3:40:07 time: 1.7461 data_time: 0.2607 memory: 16201 loss_prob: 0.9582 loss_thr: 0.5129 loss_db: 0.1550 loss: 1.6262 2022/08/30 03:27:32 - mmengine - INFO - Epoch(train) [156][10/63] lr: 6.1801e-03 eta: 1 day, 3:39:52 time: 2.0358 data_time: 0.2842 memory: 16201 loss_prob: 1.0318 loss_thr: 0.5349 loss_db: 0.1687 loss: 1.7354 2022/08/30 03:27:41 - mmengine - INFO - Epoch(train) [156][15/63] lr: 6.1801e-03 eta: 1 day, 3:39:52 time: 1.9245 data_time: 0.0532 memory: 16201 loss_prob: 0.9323 loss_thr: 0.5261 loss_db: 0.1564 loss: 1.6148 2022/08/30 03:27:49 - mmengine - INFO - Epoch(train) [156][20/63] lr: 6.1801e-03 eta: 1 day, 3:39:50 time: 1.7099 data_time: 0.0386 memory: 16201 loss_prob: 0.7828 loss_thr: 0.4803 loss_db: 0.1313 loss: 1.3944 2022/08/30 03:27:58 - mmengine - INFO - Epoch(train) [156][25/63] lr: 6.1801e-03 eta: 1 day, 3:39:50 time: 1.7226 data_time: 0.0531 memory: 16201 loss_prob: 0.7972 loss_thr: 0.4862 loss_db: 0.1328 loss: 1.4162 2022/08/30 03:28:06 - mmengine - INFO - Epoch(train) [156][30/63] lr: 6.1801e-03 eta: 1 day, 3:39:42 time: 1.6245 data_time: 0.0408 memory: 16201 loss_prob: 1.0828 loss_thr: 0.5347 loss_db: 0.1687 loss: 1.7863 2022/08/30 03:28:14 - mmengine - INFO - Epoch(train) [156][35/63] lr: 6.1801e-03 eta: 1 day, 3:39:42 time: 1.6125 data_time: 0.0404 memory: 16201 loss_prob: 1.0999 loss_thr: 0.5376 loss_db: 0.1704 loss: 1.8078 2022/08/30 03:28:21 - mmengine - INFO - Epoch(train) [156][40/63] lr: 6.1801e-03 eta: 1 day, 3:39:29 time: 1.5408 data_time: 0.0316 memory: 16201 loss_prob: 0.9826 loss_thr: 0.5578 loss_db: 0.1631 loss: 1.7035 2022/08/30 03:28:28 - mmengine - INFO - Epoch(train) [156][45/63] lr: 6.1801e-03 eta: 1 day, 3:39:29 time: 1.4038 data_time: 0.0322 memory: 16201 loss_prob: 0.9957 loss_thr: 0.5568 loss_db: 0.1654 loss: 1.7179 2022/08/30 03:28:36 - mmengine - INFO - Epoch(train) [156][50/63] lr: 6.1801e-03 eta: 1 day, 3:39:10 time: 1.4599 data_time: 0.0539 memory: 16201 loss_prob: 0.9645 loss_thr: 0.5366 loss_db: 0.1589 loss: 1.6599 2022/08/30 03:28:44 - mmengine - INFO - Epoch(train) [156][55/63] lr: 6.1801e-03 eta: 1 day, 3:39:10 time: 1.5998 data_time: 0.0411 memory: 16201 loss_prob: 0.9514 loss_thr: 0.5224 loss_db: 0.1562 loss: 1.6300 2022/08/30 03:28:53 - mmengine - INFO - Epoch(train) [156][60/63] lr: 6.1801e-03 eta: 1 day, 3:39:12 time: 1.7621 data_time: 0.0491 memory: 16201 loss_prob: 0.9841 loss_thr: 0.5168 loss_db: 0.1609 loss: 1.6618 2022/08/30 03:28:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:29:08 - mmengine - INFO - Epoch(train) [157][5/63] lr: 6.1747e-03 eta: 1 day, 3:39:12 time: 1.8458 data_time: 0.2486 memory: 16201 loss_prob: 0.9373 loss_thr: 0.5262 loss_db: 0.1515 loss: 1.6150 2022/08/30 03:29:17 - mmengine - INFO - Epoch(train) [157][10/63] lr: 6.1747e-03 eta: 1 day, 3:38:49 time: 1.9255 data_time: 0.2649 memory: 16201 loss_prob: 0.9309 loss_thr: 0.5202 loss_db: 0.1567 loss: 1.6078 2022/08/30 03:29:25 - mmengine - INFO - Epoch(train) [157][15/63] lr: 6.1747e-03 eta: 1 day, 3:38:49 time: 1.6799 data_time: 0.0391 memory: 16201 loss_prob: 0.9141 loss_thr: 0.5001 loss_db: 0.1511 loss: 1.5653 2022/08/30 03:29:34 - mmengine - INFO - Epoch(train) [157][20/63] lr: 6.1747e-03 eta: 1 day, 3:38:50 time: 1.7503 data_time: 0.0446 memory: 16201 loss_prob: 0.9092 loss_thr: 0.5033 loss_db: 0.1444 loss: 1.5569 2022/08/30 03:29:43 - mmengine - INFO - Epoch(train) [157][25/63] lr: 6.1747e-03 eta: 1 day, 3:38:50 time: 1.8251 data_time: 0.0511 memory: 16201 loss_prob: 0.9596 loss_thr: 0.5239 loss_db: 0.1623 loss: 1.6458 2022/08/30 03:29:51 - mmengine - INFO - Epoch(train) [157][30/63] lr: 6.1747e-03 eta: 1 day, 3:38:46 time: 1.6834 data_time: 0.0362 memory: 16201 loss_prob: 0.9644 loss_thr: 0.5304 loss_db: 0.1648 loss: 1.6596 2022/08/30 03:30:00 - mmengine - INFO - Epoch(train) [157][35/63] lr: 6.1747e-03 eta: 1 day, 3:38:46 time: 1.6152 data_time: 0.0409 memory: 16201 loss_prob: 0.8998 loss_thr: 0.5164 loss_db: 0.1468 loss: 1.5631 2022/08/30 03:30:08 - mmengine - INFO - Epoch(train) [157][40/63] lr: 6.1747e-03 eta: 1 day, 3:38:43 time: 1.7000 data_time: 0.0345 memory: 16201 loss_prob: 0.9054 loss_thr: 0.5527 loss_db: 0.1511 loss: 1.6092 2022/08/30 03:30:16 - mmengine - INFO - Epoch(train) [157][45/63] lr: 6.1747e-03 eta: 1 day, 3:38:43 time: 1.6409 data_time: 0.0351 memory: 16201 loss_prob: 0.9688 loss_thr: 0.5474 loss_db: 0.1656 loss: 1.6818 2022/08/30 03:30:25 - mmengine - INFO - Epoch(train) [157][50/63] lr: 6.1747e-03 eta: 1 day, 3:38:39 time: 1.6806 data_time: 0.0481 memory: 16201 loss_prob: 0.9085 loss_thr: 0.4911 loss_db: 0.1560 loss: 1.5556 2022/08/30 03:30:34 - mmengine - INFO - Epoch(train) [157][55/63] lr: 6.1747e-03 eta: 1 day, 3:38:39 time: 1.7940 data_time: 0.0450 memory: 16201 loss_prob: 0.8437 loss_thr: 0.4907 loss_db: 0.1416 loss: 1.4760 2022/08/30 03:30:43 - mmengine - INFO - Epoch(train) [157][60/63] lr: 6.1747e-03 eta: 1 day, 3:38:44 time: 1.8093 data_time: 0.0478 memory: 16201 loss_prob: 0.8933 loss_thr: 0.5002 loss_db: 0.1502 loss: 1.5436 2022/08/30 03:30:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:30:57 - mmengine - INFO - Epoch(train) [158][5/63] lr: 6.1694e-03 eta: 1 day, 3:38:44 time: 1.8032 data_time: 0.2681 memory: 16201 loss_prob: 0.9336 loss_thr: 0.5203 loss_db: 0.1534 loss: 1.6074 2022/08/30 03:31:05 - mmengine - INFO - Epoch(train) [158][10/63] lr: 6.1694e-03 eta: 1 day, 3:38:13 time: 1.8010 data_time: 0.2826 memory: 16201 loss_prob: 0.8923 loss_thr: 0.4908 loss_db: 0.1466 loss: 1.5297 2022/08/30 03:31:14 - mmengine - INFO - Epoch(train) [158][15/63] lr: 6.1694e-03 eta: 1 day, 3:38:13 time: 1.6587 data_time: 0.0490 memory: 16201 loss_prob: 0.8787 loss_thr: 0.5019 loss_db: 0.1446 loss: 1.5251 2022/08/30 03:31:24 - mmengine - INFO - Epoch(train) [158][20/63] lr: 6.1694e-03 eta: 1 day, 3:38:21 time: 1.8625 data_time: 0.1148 memory: 16201 loss_prob: 0.9661 loss_thr: 0.5349 loss_db: 0.1597 loss: 1.6607 2022/08/30 03:31:32 - mmengine - INFO - Epoch(train) [158][25/63] lr: 6.1694e-03 eta: 1 day, 3:38:21 time: 1.8434 data_time: 0.1112 memory: 16201 loss_prob: 0.9343 loss_thr: 0.5220 loss_db: 0.1516 loss: 1.6079 2022/08/30 03:31:43 - mmengine - INFO - Epoch(train) [158][30/63] lr: 6.1694e-03 eta: 1 day, 3:38:31 time: 1.8916 data_time: 0.0578 memory: 16201 loss_prob: 0.8435 loss_thr: 0.4926 loss_db: 0.1367 loss: 1.4728 2022/08/30 03:31:51 - mmengine - INFO - Epoch(train) [158][35/63] lr: 6.1694e-03 eta: 1 day, 3:38:31 time: 1.9147 data_time: 0.0725 memory: 16201 loss_prob: 0.8317 loss_thr: 0.4976 loss_db: 0.1416 loss: 1.4709 2022/08/30 03:32:01 - mmengine - INFO - Epoch(train) [158][40/63] lr: 6.1694e-03 eta: 1 day, 3:38:35 time: 1.8117 data_time: 0.0444 memory: 16201 loss_prob: 0.9232 loss_thr: 0.5236 loss_db: 0.1531 loss: 1.5999 2022/08/30 03:32:10 - mmengine - INFO - Epoch(train) [158][45/63] lr: 6.1694e-03 eta: 1 day, 3:38:35 time: 1.8722 data_time: 0.0369 memory: 16201 loss_prob: 0.9916 loss_thr: 0.5290 loss_db: 0.1535 loss: 1.6741 2022/08/30 03:32:18 - mmengine - INFO - Epoch(train) [158][50/63] lr: 6.1694e-03 eta: 1 day, 3:38:31 time: 1.6744 data_time: 0.0436 memory: 16201 loss_prob: 0.9148 loss_thr: 0.5064 loss_db: 0.1447 loss: 1.5659 2022/08/30 03:32:27 - mmengine - INFO - Epoch(train) [158][55/63] lr: 6.1694e-03 eta: 1 day, 3:38:31 time: 1.6666 data_time: 0.0388 memory: 16201 loss_prob: 0.8561 loss_thr: 0.4998 loss_db: 0.1406 loss: 1.4964 2022/08/30 03:32:35 - mmengine - INFO - Epoch(train) [158][60/63] lr: 6.1694e-03 eta: 1 day, 3:38:31 time: 1.7546 data_time: 0.0698 memory: 16201 loss_prob: 0.8685 loss_thr: 0.5327 loss_db: 0.1435 loss: 1.5447 2022/08/30 03:32:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:32:48 - mmengine - INFO - Epoch(train) [159][5/63] lr: 6.1641e-03 eta: 1 day, 3:38:31 time: 1.5782 data_time: 0.2632 memory: 16201 loss_prob: 0.8444 loss_thr: 0.5176 loss_db: 0.1367 loss: 1.4987 2022/08/30 03:32:55 - mmengine - INFO - Epoch(train) [159][10/63] lr: 6.1641e-03 eta: 1 day, 3:37:50 time: 1.6416 data_time: 0.2722 memory: 16201 loss_prob: 0.9691 loss_thr: 0.5476 loss_db: 0.1601 loss: 1.6768 2022/08/30 03:33:02 - mmengine - INFO - Epoch(train) [159][15/63] lr: 6.1641e-03 eta: 1 day, 3:37:50 time: 1.4537 data_time: 0.0372 memory: 16201 loss_prob: 0.9920 loss_thr: 0.5390 loss_db: 0.1655 loss: 1.6966 2022/08/30 03:33:12 - mmengine - INFO - Epoch(train) [159][20/63] lr: 6.1641e-03 eta: 1 day, 3:37:51 time: 1.7574 data_time: 0.0354 memory: 16201 loss_prob: 0.8495 loss_thr: 0.5025 loss_db: 0.1425 loss: 1.4946 2022/08/30 03:33:21 - mmengine - INFO - Epoch(train) [159][25/63] lr: 6.1641e-03 eta: 1 day, 3:37:51 time: 1.9056 data_time: 0.0470 memory: 16201 loss_prob: 0.8512 loss_thr: 0.5168 loss_db: 0.1457 loss: 1.5137 2022/08/30 03:33:29 - mmengine - INFO - Epoch(train) [159][30/63] lr: 6.1641e-03 eta: 1 day, 3:37:47 time: 1.6976 data_time: 0.0396 memory: 16201 loss_prob: 0.8812 loss_thr: 0.5218 loss_db: 0.1498 loss: 1.5528 2022/08/30 03:33:38 - mmengine - INFO - Epoch(train) [159][35/63] lr: 6.1641e-03 eta: 1 day, 3:37:47 time: 1.6475 data_time: 0.0389 memory: 16201 loss_prob: 0.8776 loss_thr: 0.5146 loss_db: 0.1423 loss: 1.5344 2022/08/30 03:33:47 - mmengine - INFO - Epoch(train) [159][40/63] lr: 6.1641e-03 eta: 1 day, 3:37:49 time: 1.7746 data_time: 0.0478 memory: 16201 loss_prob: 0.8681 loss_thr: 0.5180 loss_db: 0.1403 loss: 1.5264 2022/08/30 03:33:54 - mmengine - INFO - Epoch(train) [159][45/63] lr: 6.1641e-03 eta: 1 day, 3:37:49 time: 1.6000 data_time: 0.0506 memory: 16201 loss_prob: 0.8128 loss_thr: 0.5065 loss_db: 0.1367 loss: 1.4560 2022/08/30 03:33:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:34:02 - mmengine - INFO - Epoch(train) [159][50/63] lr: 6.1641e-03 eta: 1 day, 3:37:36 time: 1.5417 data_time: 0.0493 memory: 16201 loss_prob: 0.8161 loss_thr: 0.5041 loss_db: 0.1412 loss: 1.4614 2022/08/30 03:34:11 - mmengine - INFO - Epoch(train) [159][55/63] lr: 6.1641e-03 eta: 1 day, 3:37:36 time: 1.7046 data_time: 0.0377 memory: 16201 loss_prob: 0.8788 loss_thr: 0.5121 loss_db: 0.1477 loss: 1.5385 2022/08/30 03:34:20 - mmengine - INFO - Epoch(train) [159][60/63] lr: 6.1641e-03 eta: 1 day, 3:37:38 time: 1.7775 data_time: 0.0367 memory: 16201 loss_prob: 0.8641 loss_thr: 0.5031 loss_db: 0.1441 loss: 1.5113 2022/08/30 03:34:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:34:34 - mmengine - INFO - Epoch(train) [160][5/63] lr: 6.1587e-03 eta: 1 day, 3:37:38 time: 1.7888 data_time: 0.2693 memory: 16201 loss_prob: 0.8976 loss_thr: 0.5064 loss_db: 0.1575 loss: 1.5614 2022/08/30 03:34:44 - mmengine - INFO - Epoch(train) [160][10/63] lr: 6.1587e-03 eta: 1 day, 3:37:28 time: 2.1213 data_time: 0.2828 memory: 16201 loss_prob: 0.8420 loss_thr: 0.5137 loss_db: 0.1418 loss: 1.4974 2022/08/30 03:34:52 - mmengine - INFO - Epoch(train) [160][15/63] lr: 6.1587e-03 eta: 1 day, 3:37:28 time: 1.7749 data_time: 0.0468 memory: 16201 loss_prob: 0.8348 loss_thr: 0.5150 loss_db: 0.1377 loss: 1.4876 2022/08/30 03:35:01 - mmengine - INFO - Epoch(train) [160][20/63] lr: 6.1587e-03 eta: 1 day, 3:37:21 time: 1.6485 data_time: 0.0492 memory: 16201 loss_prob: 0.9368 loss_thr: 0.5282 loss_db: 0.1511 loss: 1.6161 2022/08/30 03:35:09 - mmengine - INFO - Epoch(train) [160][25/63] lr: 6.1587e-03 eta: 1 day, 3:37:21 time: 1.6977 data_time: 0.0496 memory: 16201 loss_prob: 0.9244 loss_thr: 0.5311 loss_db: 0.1540 loss: 1.6095 2022/08/30 03:35:19 - mmengine - INFO - Epoch(train) [160][30/63] lr: 6.1587e-03 eta: 1 day, 3:37:27 time: 1.8427 data_time: 0.0422 memory: 16201 loss_prob: 0.9619 loss_thr: 0.5358 loss_db: 0.1665 loss: 1.6642 2022/08/30 03:35:29 - mmengine - INFO - Epoch(train) [160][35/63] lr: 6.1587e-03 eta: 1 day, 3:37:27 time: 1.9877 data_time: 0.0549 memory: 16201 loss_prob: 0.9393 loss_thr: 0.5189 loss_db: 0.1545 loss: 1.6127 2022/08/30 03:35:38 - mmengine - INFO - Epoch(train) [160][40/63] lr: 6.1587e-03 eta: 1 day, 3:37:32 time: 1.8188 data_time: 0.0504 memory: 16201 loss_prob: 0.8489 loss_thr: 0.5095 loss_db: 0.1375 loss: 1.4960 2022/08/30 03:35:47 - mmengine - INFO - Epoch(train) [160][45/63] lr: 6.1587e-03 eta: 1 day, 3:37:32 time: 1.7699 data_time: 0.0479 memory: 16201 loss_prob: 0.8252 loss_thr: 0.5062 loss_db: 0.1403 loss: 1.4717 2022/08/30 03:35:58 - mmengine - INFO - Epoch(train) [160][50/63] lr: 6.1587e-03 eta: 1 day, 3:37:51 time: 2.0417 data_time: 0.0526 memory: 16201 loss_prob: 0.8642 loss_thr: 0.5132 loss_db: 0.1427 loss: 1.5201 2022/08/30 03:36:08 - mmengine - INFO - Epoch(train) [160][55/63] lr: 6.1587e-03 eta: 1 day, 3:37:51 time: 2.0947 data_time: 0.0604 memory: 16201 loss_prob: 0.9371 loss_thr: 0.5251 loss_db: 0.1524 loss: 1.6146 2022/08/30 03:36:18 - mmengine - INFO - Epoch(train) [160][60/63] lr: 6.1587e-03 eta: 1 day, 3:38:05 time: 1.9649 data_time: 0.0608 memory: 16201 loss_prob: 0.8968 loss_thr: 0.5178 loss_db: 0.1487 loss: 1.5633 2022/08/30 03:36:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:36:23 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/08/30 03:36:32 - mmengine - INFO - Epoch(val) [160][5/32] eta: 1 day, 3:38:05 time: 0.7392 data_time: 0.1587 memory: 16201 2022/08/30 03:36:35 - mmengine - INFO - Epoch(val) [160][10/32] eta: 0:00:18 time: 0.8293 data_time: 0.1858 memory: 15734 2022/08/30 03:36:39 - mmengine - INFO - Epoch(val) [160][15/32] eta: 0:00:18 time: 0.7056 data_time: 0.0816 memory: 15734 2022/08/30 03:36:43 - mmengine - INFO - Epoch(val) [160][20/32] eta: 0:00:09 time: 0.7671 data_time: 0.0888 memory: 15734 2022/08/30 03:36:46 - mmengine - INFO - Epoch(val) [160][25/32] eta: 0:00:09 time: 0.7500 data_time: 0.0692 memory: 15734 2022/08/30 03:36:50 - mmengine - INFO - Epoch(val) [160][30/32] eta: 0:00:01 time: 0.7306 data_time: 0.0972 memory: 15734 2022/08/30 03:36:51 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 03:36:51 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8368, precision: 0.7534, hmean: 0.7929 2022/08/30 03:36:51 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8363, precision: 0.8124, hmean: 0.8242 2022/08/30 03:36:51 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8310, precision: 0.8490, hmean: 0.8399 2022/08/30 03:36:51 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8180, precision: 0.8726, hmean: 0.8444 2022/08/30 03:36:51 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7814, precision: 0.9007, hmean: 0.8368 2022/08/30 03:36:51 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4983, precision: 0.9628, hmean: 0.6567 2022/08/30 03:36:51 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0024, precision: 1.0000, hmean: 0.0048 2022/08/30 03:36:51 - mmengine - INFO - Epoch(val) [160][32/32] icdar/precision: 0.8726 icdar/recall: 0.8180 icdar/hmean: 0.8444 2022/08/30 03:37:02 - mmengine - INFO - Epoch(train) [161][5/63] lr: 6.1534e-03 eta: 0:00:01 time: 2.0100 data_time: 0.3044 memory: 16201 loss_prob: 0.8332 loss_thr: 0.4871 loss_db: 0.1360 loss: 1.4564 2022/08/30 03:37:13 - mmengine - INFO - Epoch(train) [161][10/63] lr: 6.1534e-03 eta: 1 day, 3:37:57 time: 2.1619 data_time: 0.2917 memory: 16201 loss_prob: 0.7935 loss_thr: 0.4839 loss_db: 0.1335 loss: 1.4110 2022/08/30 03:37:21 - mmengine - INFO - Epoch(train) [161][15/63] lr: 6.1534e-03 eta: 1 day, 3:37:57 time: 1.9062 data_time: 0.0462 memory: 16201 loss_prob: 0.7910 loss_thr: 0.4800 loss_db: 0.1372 loss: 1.4082 2022/08/30 03:37:29 - mmengine - INFO - Epoch(train) [161][20/63] lr: 6.1534e-03 eta: 1 day, 3:37:50 time: 1.6403 data_time: 0.0391 memory: 16201 loss_prob: 0.8917 loss_thr: 0.4848 loss_db: 0.1442 loss: 1.5207 2022/08/30 03:37:38 - mmengine - INFO - Epoch(train) [161][25/63] lr: 6.1534e-03 eta: 1 day, 3:37:50 time: 1.6488 data_time: 0.0466 memory: 16201 loss_prob: 0.9403 loss_thr: 0.5160 loss_db: 0.1505 loss: 1.6068 2022/08/30 03:37:47 - mmengine - INFO - Epoch(train) [161][30/63] lr: 6.1534e-03 eta: 1 day, 3:37:52 time: 1.7864 data_time: 0.0332 memory: 16201 loss_prob: 0.9903 loss_thr: 0.5447 loss_db: 0.1686 loss: 1.7035 2022/08/30 03:37:58 - mmengine - INFO - Epoch(train) [161][35/63] lr: 6.1534e-03 eta: 1 day, 3:37:52 time: 1.9760 data_time: 0.0479 memory: 16201 loss_prob: 0.9815 loss_thr: 0.5282 loss_db: 0.1641 loss: 1.6737 2022/08/30 03:38:07 - mmengine - INFO - Epoch(train) [161][40/63] lr: 6.1534e-03 eta: 1 day, 3:38:04 time: 1.9370 data_time: 0.0560 memory: 16201 loss_prob: 0.9166 loss_thr: 0.5135 loss_db: 0.1459 loss: 1.5760 2022/08/30 03:38:16 - mmengine - INFO - Epoch(train) [161][45/63] lr: 6.1534e-03 eta: 1 day, 3:38:04 time: 1.8637 data_time: 0.0456 memory: 16201 loss_prob: 0.9418 loss_thr: 0.5280 loss_db: 0.1540 loss: 1.6238 2022/08/30 03:38:25 - mmengine - INFO - Epoch(train) [161][50/63] lr: 6.1534e-03 eta: 1 day, 3:38:08 time: 1.8203 data_time: 0.0532 memory: 16201 loss_prob: 0.8939 loss_thr: 0.5176 loss_db: 0.1502 loss: 1.5617 2022/08/30 03:38:34 - mmengine - INFO - Epoch(train) [161][55/63] lr: 6.1534e-03 eta: 1 day, 3:38:08 time: 1.7876 data_time: 0.0401 memory: 16201 loss_prob: 0.8897 loss_thr: 0.5182 loss_db: 0.1468 loss: 1.5547 2022/08/30 03:38:43 - mmengine - INFO - Epoch(train) [161][60/63] lr: 6.1534e-03 eta: 1 day, 3:38:14 time: 1.8531 data_time: 0.0438 memory: 16201 loss_prob: 0.8767 loss_thr: 0.5172 loss_db: 0.1470 loss: 1.5409 2022/08/30 03:38:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:39:01 - mmengine - INFO - Epoch(train) [162][5/63] lr: 6.1481e-03 eta: 1 day, 3:38:14 time: 2.0295 data_time: 0.2616 memory: 16201 loss_prob: 0.8059 loss_thr: 0.4897 loss_db: 0.1348 loss: 1.4304 2022/08/30 03:39:10 - mmengine - INFO - Epoch(train) [162][10/63] lr: 6.1481e-03 eta: 1 day, 3:38:06 time: 2.1549 data_time: 0.2899 memory: 16201 loss_prob: 0.8485 loss_thr: 0.5136 loss_db: 0.1442 loss: 1.5062 2022/08/30 03:39:17 - mmengine - INFO - Epoch(train) [162][15/63] lr: 6.1481e-03 eta: 1 day, 3:38:06 time: 1.6372 data_time: 0.0588 memory: 16201 loss_prob: 0.8426 loss_thr: 0.5181 loss_db: 0.1433 loss: 1.5040 2022/08/30 03:39:26 - mmengine - INFO - Epoch(train) [162][20/63] lr: 6.1481e-03 eta: 1 day, 3:37:57 time: 1.6169 data_time: 0.0511 memory: 16201 loss_prob: 0.7714 loss_thr: 0.4715 loss_db: 0.1294 loss: 1.3723 2022/08/30 03:39:33 - mmengine - INFO - Epoch(train) [162][25/63] lr: 6.1481e-03 eta: 1 day, 3:37:57 time: 1.6135 data_time: 0.0485 memory: 16201 loss_prob: 0.9058 loss_thr: 0.4936 loss_db: 0.1496 loss: 1.5491 2022/08/30 03:39:42 - mmengine - INFO - Epoch(train) [162][30/63] lr: 6.1481e-03 eta: 1 day, 3:37:49 time: 1.6317 data_time: 0.0345 memory: 16201 loss_prob: 0.9619 loss_thr: 0.5406 loss_db: 0.1602 loss: 1.6627 2022/08/30 03:39:51 - mmengine - INFO - Epoch(train) [162][35/63] lr: 6.1481e-03 eta: 1 day, 3:37:49 time: 1.7848 data_time: 0.0428 memory: 16201 loss_prob: 0.8333 loss_thr: 0.5164 loss_db: 0.1467 loss: 1.4963 2022/08/30 03:40:00 - mmengine - INFO - Epoch(train) [162][40/63] lr: 6.1481e-03 eta: 1 day, 3:37:49 time: 1.7544 data_time: 0.0392 memory: 16201 loss_prob: 0.8834 loss_thr: 0.5092 loss_db: 0.1525 loss: 1.5451 2022/08/30 03:40:09 - mmengine - INFO - Epoch(train) [162][45/63] lr: 6.1481e-03 eta: 1 day, 3:37:49 time: 1.7530 data_time: 0.0462 memory: 16201 loss_prob: 0.9000 loss_thr: 0.5201 loss_db: 0.1472 loss: 1.5673 2022/08/30 03:40:17 - mmengine - INFO - Epoch(train) [162][50/63] lr: 6.1481e-03 eta: 1 day, 3:37:46 time: 1.7065 data_time: 0.0449 memory: 16201 loss_prob: 0.8488 loss_thr: 0.5124 loss_db: 0.1400 loss: 1.5013 2022/08/30 03:40:25 - mmengine - INFO - Epoch(train) [162][55/63] lr: 6.1481e-03 eta: 1 day, 3:37:46 time: 1.6893 data_time: 0.0345 memory: 16201 loss_prob: 0.8382 loss_thr: 0.4914 loss_db: 0.1439 loss: 1.4735 2022/08/30 03:40:33 - mmengine - INFO - Epoch(train) [162][60/63] lr: 6.1481e-03 eta: 1 day, 3:37:39 time: 1.6533 data_time: 0.0473 memory: 16201 loss_prob: 0.8410 loss_thr: 0.4966 loss_db: 0.1400 loss: 1.4777 2022/08/30 03:40:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:40:48 - mmengine - INFO - Epoch(train) [163][5/63] lr: 6.1427e-03 eta: 1 day, 3:37:39 time: 1.8145 data_time: 0.2870 memory: 16201 loss_prob: 0.8631 loss_thr: 0.4909 loss_db: 0.1421 loss: 1.4961 2022/08/30 03:40:58 - mmengine - INFO - Epoch(train) [163][10/63] lr: 6.1427e-03 eta: 1 day, 3:37:24 time: 2.0463 data_time: 0.3072 memory: 16201 loss_prob: 0.8654 loss_thr: 0.4658 loss_db: 0.1409 loss: 1.4721 2022/08/30 03:41:06 - mmengine - INFO - Epoch(train) [163][15/63] lr: 6.1427e-03 eta: 1 day, 3:37:24 time: 1.7755 data_time: 0.0448 memory: 16201 loss_prob: 0.8915 loss_thr: 0.4912 loss_db: 0.1465 loss: 1.5292 2022/08/30 03:41:15 - mmengine - INFO - Epoch(train) [163][20/63] lr: 6.1427e-03 eta: 1 day, 3:37:20 time: 1.7039 data_time: 0.0357 memory: 16201 loss_prob: 0.8762 loss_thr: 0.4995 loss_db: 0.1454 loss: 1.5210 2022/08/30 03:41:24 - mmengine - INFO - Epoch(train) [163][25/63] lr: 6.1427e-03 eta: 1 day, 3:37:20 time: 1.7499 data_time: 0.0483 memory: 16201 loss_prob: 0.8488 loss_thr: 0.4947 loss_db: 0.1411 loss: 1.4846 2022/08/30 03:41:32 - mmengine - INFO - Epoch(train) [163][30/63] lr: 6.1427e-03 eta: 1 day, 3:37:16 time: 1.6912 data_time: 0.0334 memory: 16201 loss_prob: 0.8142 loss_thr: 0.4904 loss_db: 0.1381 loss: 1.4427 2022/08/30 03:41:39 - mmengine - INFO - Epoch(train) [163][35/63] lr: 6.1427e-03 eta: 1 day, 3:37:16 time: 1.5139 data_time: 0.0363 memory: 16201 loss_prob: 0.8549 loss_thr: 0.5011 loss_db: 0.1431 loss: 1.4991 2022/08/30 03:41:46 - mmengine - INFO - Epoch(train) [163][40/63] lr: 6.1427e-03 eta: 1 day, 3:36:54 time: 1.4110 data_time: 0.0380 memory: 16201 loss_prob: 0.8897 loss_thr: 0.5108 loss_db: 0.1484 loss: 1.5489 2022/08/30 03:41:53 - mmengine - INFO - Epoch(train) [163][45/63] lr: 6.1427e-03 eta: 1 day, 3:36:54 time: 1.4334 data_time: 0.0349 memory: 16201 loss_prob: 0.8917 loss_thr: 0.5142 loss_db: 0.1461 loss: 1.5520 2022/08/30 03:42:02 - mmengine - INFO - Epoch(train) [163][50/63] lr: 6.1427e-03 eta: 1 day, 3:36:42 time: 1.5849 data_time: 0.0556 memory: 16201 loss_prob: 0.8417 loss_thr: 0.4980 loss_db: 0.1378 loss: 1.4776 2022/08/30 03:42:10 - mmengine - INFO - Epoch(train) [163][55/63] lr: 6.1427e-03 eta: 1 day, 3:36:42 time: 1.6786 data_time: 0.0394 memory: 16201 loss_prob: 0.8352 loss_thr: 0.5160 loss_db: 0.1400 loss: 1.4912 2022/08/30 03:42:19 - mmengine - INFO - Epoch(train) [163][60/63] lr: 6.1427e-03 eta: 1 day, 3:36:39 time: 1.7022 data_time: 0.0421 memory: 16201 loss_prob: 0.9515 loss_thr: 0.5519 loss_db: 0.1588 loss: 1.6622 2022/08/30 03:42:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:42:34 - mmengine - INFO - Epoch(train) [164][5/63] lr: 6.1374e-03 eta: 1 day, 3:36:39 time: 1.8722 data_time: 0.2834 memory: 16201 loss_prob: 0.8509 loss_thr: 0.5064 loss_db: 0.1452 loss: 1.5025 2022/08/30 03:42:43 - mmengine - INFO - Epoch(train) [164][10/63] lr: 6.1374e-03 eta: 1 day, 3:36:20 time: 1.9897 data_time: 0.2953 memory: 16201 loss_prob: 0.8929 loss_thr: 0.5252 loss_db: 0.1486 loss: 1.5667 2022/08/30 03:42:51 - mmengine - INFO - Epoch(train) [164][15/63] lr: 6.1374e-03 eta: 1 day, 3:36:20 time: 1.7433 data_time: 0.0362 memory: 16201 loss_prob: 0.8174 loss_thr: 0.5054 loss_db: 0.1347 loss: 1.4575 2022/08/30 03:43:00 - mmengine - INFO - Epoch(train) [164][20/63] lr: 6.1374e-03 eta: 1 day, 3:36:19 time: 1.7561 data_time: 0.0359 memory: 16201 loss_prob: 1.0064 loss_thr: 0.5270 loss_db: 0.1555 loss: 1.6889 2022/08/30 03:43:10 - mmengine - INFO - Epoch(train) [164][25/63] lr: 6.1374e-03 eta: 1 day, 3:36:19 time: 1.8186 data_time: 0.0358 memory: 16201 loss_prob: 1.0179 loss_thr: 0.5263 loss_db: 0.1599 loss: 1.7040 2022/08/30 03:43:18 - mmengine - INFO - Epoch(train) [164][30/63] lr: 6.1374e-03 eta: 1 day, 3:36:23 time: 1.8260 data_time: 0.0495 memory: 16201 loss_prob: 0.8664 loss_thr: 0.5126 loss_db: 0.1454 loss: 1.5243 2022/08/30 03:43:28 - mmengine - INFO - Epoch(train) [164][35/63] lr: 6.1374e-03 eta: 1 day, 3:36:23 time: 1.8763 data_time: 0.0652 memory: 16201 loss_prob: 0.9078 loss_thr: 0.5544 loss_db: 0.1514 loss: 1.6136 2022/08/30 03:43:37 - mmengine - INFO - Epoch(train) [164][40/63] lr: 6.1374e-03 eta: 1 day, 3:36:27 time: 1.8126 data_time: 0.0367 memory: 16201 loss_prob: 0.8844 loss_thr: 0.5215 loss_db: 0.1505 loss: 1.5565 2022/08/30 03:43:45 - mmengine - INFO - Epoch(train) [164][45/63] lr: 6.1374e-03 eta: 1 day, 3:36:27 time: 1.6654 data_time: 0.0383 memory: 16201 loss_prob: 0.8617 loss_thr: 0.4911 loss_db: 0.1412 loss: 1.4940 2022/08/30 03:43:54 - mmengine - INFO - Epoch(train) [164][50/63] lr: 6.1374e-03 eta: 1 day, 3:36:28 time: 1.7850 data_time: 0.0610 memory: 16201 loss_prob: 0.8057 loss_thr: 0.4869 loss_db: 0.1307 loss: 1.4234 2022/08/30 03:44:02 - mmengine - INFO - Epoch(train) [164][55/63] lr: 6.1374e-03 eta: 1 day, 3:36:28 time: 1.7227 data_time: 0.0416 memory: 16201 loss_prob: 0.8266 loss_thr: 0.4814 loss_db: 0.1376 loss: 1.4456 2022/08/30 03:44:12 - mmengine - INFO - Epoch(train) [164][60/63] lr: 6.1374e-03 eta: 1 day, 3:36:27 time: 1.7470 data_time: 0.0542 memory: 16201 loss_prob: 0.8498 loss_thr: 0.4883 loss_db: 0.1409 loss: 1.4790 2022/08/30 03:44:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:44:28 - mmengine - INFO - Epoch(train) [165][5/63] lr: 6.1321e-03 eta: 1 day, 3:36:27 time: 1.9904 data_time: 0.2301 memory: 16201 loss_prob: 0.9387 loss_thr: 0.5221 loss_db: 0.1576 loss: 1.6184 2022/08/30 03:44:38 - mmengine - INFO - Epoch(train) [165][10/63] lr: 6.1321e-03 eta: 1 day, 3:36:11 time: 2.0447 data_time: 0.2567 memory: 16201 loss_prob: 0.9816 loss_thr: 0.5394 loss_db: 0.1592 loss: 1.6802 2022/08/30 03:44:45 - mmengine - INFO - Epoch(train) [165][15/63] lr: 6.1321e-03 eta: 1 day, 3:36:11 time: 1.7132 data_time: 0.0432 memory: 16201 loss_prob: 0.8837 loss_thr: 0.5209 loss_db: 0.1401 loss: 1.5447 2022/08/30 03:44:54 - mmengine - INFO - Epoch(train) [165][20/63] lr: 6.1321e-03 eta: 1 day, 3:36:02 time: 1.6228 data_time: 0.0467 memory: 16201 loss_prob: 0.8961 loss_thr: 0.5214 loss_db: 0.1475 loss: 1.5650 2022/08/30 03:45:04 - mmengine - INFO - Epoch(train) [165][25/63] lr: 6.1321e-03 eta: 1 day, 3:36:02 time: 1.8419 data_time: 0.0596 memory: 16201 loss_prob: 0.8858 loss_thr: 0.5088 loss_db: 0.1479 loss: 1.5425 2022/08/30 03:45:13 - mmengine - INFO - Epoch(train) [165][30/63] lr: 6.1321e-03 eta: 1 day, 3:36:10 time: 1.8854 data_time: 0.0367 memory: 16201 loss_prob: 0.8256 loss_thr: 0.4692 loss_db: 0.1387 loss: 1.4335 2022/08/30 03:45:22 - mmengine - INFO - Epoch(train) [165][35/63] lr: 6.1321e-03 eta: 1 day, 3:36:10 time: 1.7913 data_time: 0.0437 memory: 16201 loss_prob: 0.8114 loss_thr: 0.4661 loss_db: 0.1401 loss: 1.4176 2022/08/30 03:45:31 - mmengine - INFO - Epoch(train) [165][40/63] lr: 6.1321e-03 eta: 1 day, 3:36:14 time: 1.8310 data_time: 0.0454 memory: 16201 loss_prob: 0.8874 loss_thr: 0.5028 loss_db: 0.1498 loss: 1.5400 2022/08/30 03:45:38 - mmengine - INFO - Epoch(train) [165][45/63] lr: 6.1321e-03 eta: 1 day, 3:36:14 time: 1.6625 data_time: 0.0430 memory: 16201 loss_prob: 0.9016 loss_thr: 0.5107 loss_db: 0.1507 loss: 1.5630 2022/08/30 03:45:47 - mmengine - INFO - Epoch(train) [165][50/63] lr: 6.1321e-03 eta: 1 day, 3:36:03 time: 1.5937 data_time: 0.0534 memory: 16201 loss_prob: 0.8273 loss_thr: 0.4960 loss_db: 0.1395 loss: 1.4628 2022/08/30 03:45:55 - mmengine - INFO - Epoch(train) [165][55/63] lr: 6.1321e-03 eta: 1 day, 3:36:03 time: 1.6534 data_time: 0.0467 memory: 16201 loss_prob: 0.8070 loss_thr: 0.5014 loss_db: 0.1350 loss: 1.4433 2022/08/30 03:46:04 - mmengine - INFO - Epoch(train) [165][60/63] lr: 6.1321e-03 eta: 1 day, 3:35:59 time: 1.6962 data_time: 0.0461 memory: 16201 loss_prob: 0.8320 loss_thr: 0.5152 loss_db: 0.1399 loss: 1.4870 2022/08/30 03:46:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:46:17 - mmengine - INFO - Epoch(train) [166][5/63] lr: 6.1267e-03 eta: 1 day, 3:35:59 time: 1.6498 data_time: 0.2519 memory: 16201 loss_prob: 0.8601 loss_thr: 0.5000 loss_db: 0.1436 loss: 1.5038 2022/08/30 03:46:24 - mmengine - INFO - Epoch(train) [166][10/63] lr: 6.1267e-03 eta: 1 day, 3:35:21 time: 1.6956 data_time: 0.2705 memory: 16201 loss_prob: 0.7823 loss_thr: 0.4796 loss_db: 0.1291 loss: 1.3910 2022/08/30 03:46:31 - mmengine - INFO - Epoch(train) [166][15/63] lr: 6.1267e-03 eta: 1 day, 3:35:21 time: 1.3913 data_time: 0.0360 memory: 16201 loss_prob: 0.8424 loss_thr: 0.5006 loss_db: 0.1458 loss: 1.4889 2022/08/30 03:46:39 - mmengine - INFO - Epoch(train) [166][20/63] lr: 6.1267e-03 eta: 1 day, 3:35:01 time: 1.4410 data_time: 0.0404 memory: 16201 loss_prob: 0.8722 loss_thr: 0.4992 loss_db: 0.1490 loss: 1.5205 2022/08/30 03:46:48 - mmengine - INFO - Epoch(train) [166][25/63] lr: 6.1267e-03 eta: 1 day, 3:35:01 time: 1.7365 data_time: 0.0559 memory: 16201 loss_prob: 0.8039 loss_thr: 0.4837 loss_db: 0.1333 loss: 1.4209 2022/08/30 03:46:57 - mmengine - INFO - Epoch(train) [166][30/63] lr: 6.1267e-03 eta: 1 day, 3:35:02 time: 1.7924 data_time: 0.0385 memory: 16201 loss_prob: 0.8037 loss_thr: 0.4933 loss_db: 0.1359 loss: 1.4329 2022/08/30 03:47:07 - mmengine - INFO - Epoch(train) [166][35/63] lr: 6.1267e-03 eta: 1 day, 3:35:02 time: 1.8759 data_time: 0.0448 memory: 16201 loss_prob: 0.9899 loss_thr: 0.5124 loss_db: 0.1575 loss: 1.6598 2022/08/30 03:47:16 - mmengine - INFO - Epoch(train) [166][40/63] lr: 6.1267e-03 eta: 1 day, 3:35:14 time: 1.9461 data_time: 0.0395 memory: 16201 loss_prob: 1.0008 loss_thr: 0.5251 loss_db: 0.1613 loss: 1.6872 2022/08/30 03:47:25 - mmengine - INFO - Epoch(train) [166][45/63] lr: 6.1267e-03 eta: 1 day, 3:35:14 time: 1.8440 data_time: 0.0402 memory: 16201 loss_prob: 0.8671 loss_thr: 0.5101 loss_db: 0.1450 loss: 1.5222 2022/08/30 03:47:33 - mmengine - INFO - Epoch(train) [166][50/63] lr: 6.1267e-03 eta: 1 day, 3:35:11 time: 1.7320 data_time: 0.0616 memory: 16201 loss_prob: 0.8446 loss_thr: 0.5080 loss_db: 0.1357 loss: 1.4883 2022/08/30 03:47:41 - mmengine - INFO - Epoch(train) [166][55/63] lr: 6.1267e-03 eta: 1 day, 3:35:11 time: 1.6142 data_time: 0.0394 memory: 16201 loss_prob: 0.8040 loss_thr: 0.4880 loss_db: 0.1294 loss: 1.4214 2022/08/30 03:47:51 - mmengine - INFO - Epoch(train) [166][60/63] lr: 6.1267e-03 eta: 1 day, 3:35:09 time: 1.7261 data_time: 0.0456 memory: 16201 loss_prob: 0.8986 loss_thr: 0.4929 loss_db: 0.1442 loss: 1.5357 2022/08/30 03:47:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:48:06 - mmengine - INFO - Epoch(train) [167][5/63] lr: 6.1214e-03 eta: 1 day, 3:35:09 time: 1.8955 data_time: 0.2352 memory: 16201 loss_prob: 0.8358 loss_thr: 0.5149 loss_db: 0.1369 loss: 1.4876 2022/08/30 03:48:15 - mmengine - INFO - Epoch(train) [167][10/63] lr: 6.1214e-03 eta: 1 day, 3:34:49 time: 1.9865 data_time: 0.2559 memory: 16201 loss_prob: 0.8068 loss_thr: 0.5064 loss_db: 0.1362 loss: 1.4495 2022/08/30 03:48:24 - mmengine - INFO - Epoch(train) [167][15/63] lr: 6.1214e-03 eta: 1 day, 3:34:49 time: 1.7587 data_time: 0.0487 memory: 16201 loss_prob: 0.8193 loss_thr: 0.5011 loss_db: 0.1397 loss: 1.4601 2022/08/30 03:48:32 - mmengine - INFO - Epoch(train) [167][20/63] lr: 6.1214e-03 eta: 1 day, 3:34:46 time: 1.7225 data_time: 0.0424 memory: 16201 loss_prob: 0.8352 loss_thr: 0.5025 loss_db: 0.1389 loss: 1.4766 2022/08/30 03:48:41 - mmengine - INFO - Epoch(train) [167][25/63] lr: 6.1214e-03 eta: 1 day, 3:34:46 time: 1.6957 data_time: 0.0515 memory: 16201 loss_prob: 0.8842 loss_thr: 0.5049 loss_db: 0.1488 loss: 1.5380 2022/08/30 03:48:49 - mmengine - INFO - Epoch(train) [167][30/63] lr: 6.1214e-03 eta: 1 day, 3:34:42 time: 1.7012 data_time: 0.0413 memory: 16201 loss_prob: 0.8818 loss_thr: 0.4860 loss_db: 0.1478 loss: 1.5156 2022/08/30 03:48:58 - mmengine - INFO - Epoch(train) [167][35/63] lr: 6.1214e-03 eta: 1 day, 3:34:42 time: 1.7423 data_time: 0.0390 memory: 16201 loss_prob: 0.8424 loss_thr: 0.4834 loss_db: 0.1370 loss: 1.4628 2022/08/30 03:49:07 - mmengine - INFO - Epoch(train) [167][40/63] lr: 6.1214e-03 eta: 1 day, 3:34:41 time: 1.7499 data_time: 0.0503 memory: 16201 loss_prob: 0.8537 loss_thr: 0.5157 loss_db: 0.1407 loss: 1.5101 2022/08/30 03:49:16 - mmengine - INFO - Epoch(train) [167][45/63] lr: 6.1214e-03 eta: 1 day, 3:34:41 time: 1.7293 data_time: 0.0442 memory: 16201 loss_prob: 0.8907 loss_thr: 0.5243 loss_db: 0.1463 loss: 1.5614 2022/08/30 03:49:24 - mmengine - INFO - Epoch(train) [167][50/63] lr: 6.1214e-03 eta: 1 day, 3:34:39 time: 1.7378 data_time: 0.0442 memory: 16201 loss_prob: 0.8577 loss_thr: 0.4980 loss_db: 0.1401 loss: 1.4959 2022/08/30 03:49:33 - mmengine - INFO - Epoch(train) [167][55/63] lr: 6.1214e-03 eta: 1 day, 3:34:39 time: 1.7151 data_time: 0.0382 memory: 16201 loss_prob: 0.7966 loss_thr: 0.5035 loss_db: 0.1305 loss: 1.4307 2022/08/30 03:49:42 - mmengine - INFO - Epoch(train) [167][60/63] lr: 6.1214e-03 eta: 1 day, 3:34:38 time: 1.7630 data_time: 0.0421 memory: 16201 loss_prob: 0.8716 loss_thr: 0.5059 loss_db: 0.1423 loss: 1.5198 2022/08/30 03:49:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:49:57 - mmengine - INFO - Epoch(train) [168][5/63] lr: 6.1161e-03 eta: 1 day, 3:34:38 time: 1.8597 data_time: 0.2738 memory: 16201 loss_prob: 0.8909 loss_thr: 0.5225 loss_db: 0.1474 loss: 1.5608 2022/08/30 03:50:05 - mmengine - INFO - Epoch(train) [168][10/63] lr: 6.1161e-03 eta: 1 day, 3:34:14 time: 1.9098 data_time: 0.2801 memory: 16201 loss_prob: 0.8527 loss_thr: 0.5104 loss_db: 0.1404 loss: 1.5034 2022/08/30 03:50:13 - mmengine - INFO - Epoch(train) [168][15/63] lr: 6.1161e-03 eta: 1 day, 3:34:14 time: 1.6563 data_time: 0.0337 memory: 16201 loss_prob: 0.8254 loss_thr: 0.4781 loss_db: 0.1372 loss: 1.4407 2022/08/30 03:50:22 - mmengine - INFO - Epoch(train) [168][20/63] lr: 6.1161e-03 eta: 1 day, 3:34:12 time: 1.7408 data_time: 0.0340 memory: 16201 loss_prob: 0.8496 loss_thr: 0.4947 loss_db: 0.1441 loss: 1.4885 2022/08/30 03:50:31 - mmengine - INFO - Epoch(train) [168][25/63] lr: 6.1161e-03 eta: 1 day, 3:34:12 time: 1.7783 data_time: 0.0460 memory: 16201 loss_prob: 0.8292 loss_thr: 0.4979 loss_db: 0.1410 loss: 1.4682 2022/08/30 03:50:40 - mmengine - INFO - Epoch(train) [168][30/63] lr: 6.1161e-03 eta: 1 day, 3:34:13 time: 1.7999 data_time: 0.0385 memory: 16201 loss_prob: 0.8253 loss_thr: 0.5089 loss_db: 0.1397 loss: 1.4739 2022/08/30 03:50:48 - mmengine - INFO - Epoch(train) [168][35/63] lr: 6.1161e-03 eta: 1 day, 3:34:13 time: 1.6825 data_time: 0.0434 memory: 16201 loss_prob: 0.8157 loss_thr: 0.4950 loss_db: 0.1356 loss: 1.4462 2022/08/30 03:50:54 - mmengine - INFO - Epoch(train) [168][40/63] lr: 6.1161e-03 eta: 1 day, 3:33:49 time: 1.3806 data_time: 0.0364 memory: 16201 loss_prob: 0.8525 loss_thr: 0.4855 loss_db: 0.1413 loss: 1.4793 2022/08/30 03:51:01 - mmengine - INFO - Epoch(train) [168][45/63] lr: 6.1161e-03 eta: 1 day, 3:33:49 time: 1.3067 data_time: 0.0333 memory: 16201 loss_prob: 0.8566 loss_thr: 0.4934 loss_db: 0.1444 loss: 1.4944 2022/08/30 03:51:10 - mmengine - INFO - Epoch(train) [168][50/63] lr: 6.1161e-03 eta: 1 day, 3:33:35 time: 1.5480 data_time: 0.0484 memory: 16201 loss_prob: 0.8347 loss_thr: 0.4977 loss_db: 0.1407 loss: 1.4731 2022/08/30 03:51:18 - mmengine - INFO - Epoch(train) [168][55/63] lr: 6.1161e-03 eta: 1 day, 3:33:35 time: 1.7146 data_time: 0.0320 memory: 16201 loss_prob: 0.8641 loss_thr: 0.4944 loss_db: 0.1437 loss: 1.5023 2022/08/30 03:51:27 - mmengine - INFO - Epoch(train) [168][60/63] lr: 6.1161e-03 eta: 1 day, 3:33:35 time: 1.7623 data_time: 0.0440 memory: 16201 loss_prob: 0.9601 loss_thr: 0.5069 loss_db: 0.1532 loss: 1.6202 2022/08/30 03:51:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:51:43 - mmengine - INFO - Epoch(train) [169][5/63] lr: 6.1107e-03 eta: 1 day, 3:33:35 time: 1.8554 data_time: 0.2252 memory: 16201 loss_prob: 0.8591 loss_thr: 0.5142 loss_db: 0.1443 loss: 1.5177 2022/08/30 03:51:51 - mmengine - INFO - Epoch(train) [169][10/63] lr: 6.1107e-03 eta: 1 day, 3:33:14 time: 1.9722 data_time: 0.2439 memory: 16201 loss_prob: 0.8318 loss_thr: 0.5127 loss_db: 0.1425 loss: 1.4870 2022/08/30 03:52:00 - mmengine - INFO - Epoch(train) [169][15/63] lr: 6.1107e-03 eta: 1 day, 3:33:14 time: 1.7083 data_time: 0.0504 memory: 16201 loss_prob: 0.7870 loss_thr: 0.4854 loss_db: 0.1337 loss: 1.4061 2022/08/30 03:52:08 - mmengine - INFO - Epoch(train) [169][20/63] lr: 6.1107e-03 eta: 1 day, 3:33:10 time: 1.7162 data_time: 0.0549 memory: 16201 loss_prob: 0.8142 loss_thr: 0.4983 loss_db: 0.1365 loss: 1.4490 2022/08/30 03:52:18 - mmengine - INFO - Epoch(train) [169][25/63] lr: 6.1107e-03 eta: 1 day, 3:33:10 time: 1.7958 data_time: 0.0461 memory: 16201 loss_prob: 0.8585 loss_thr: 0.5315 loss_db: 0.1425 loss: 1.5326 2022/08/30 03:52:27 - mmengine - INFO - Epoch(train) [169][30/63] lr: 6.1107e-03 eta: 1 day, 3:33:12 time: 1.8058 data_time: 0.0438 memory: 16201 loss_prob: 0.7704 loss_thr: 0.4993 loss_db: 0.1301 loss: 1.3998 2022/08/30 03:52:36 - mmengine - INFO - Epoch(train) [169][35/63] lr: 6.1107e-03 eta: 1 day, 3:33:12 time: 1.8227 data_time: 0.0468 memory: 16201 loss_prob: 0.8224 loss_thr: 0.4882 loss_db: 0.1372 loss: 1.4478 2022/08/30 03:52:44 - mmengine - INFO - Epoch(train) [169][40/63] lr: 6.1107e-03 eta: 1 day, 3:33:13 time: 1.7914 data_time: 0.0401 memory: 16201 loss_prob: 0.8558 loss_thr: 0.5014 loss_db: 0.1413 loss: 1.4984 2022/08/30 03:52:52 - mmengine - INFO - Epoch(train) [169][45/63] lr: 6.1107e-03 eta: 1 day, 3:33:13 time: 1.6443 data_time: 0.0472 memory: 16201 loss_prob: 0.8710 loss_thr: 0.5078 loss_db: 0.1445 loss: 1.5233 2022/08/30 03:53:01 - mmengine - INFO - Epoch(train) [169][50/63] lr: 6.1107e-03 eta: 1 day, 3:33:07 time: 1.6781 data_time: 0.0492 memory: 16201 loss_prob: 0.9143 loss_thr: 0.5308 loss_db: 0.1535 loss: 1.5986 2022/08/30 03:53:10 - mmengine - INFO - Epoch(train) [169][55/63] lr: 6.1107e-03 eta: 1 day, 3:33:07 time: 1.7478 data_time: 0.0524 memory: 16201 loss_prob: 0.8476 loss_thr: 0.5065 loss_db: 0.1427 loss: 1.4968 2022/08/30 03:53:18 - mmengine - INFO - Epoch(train) [169][60/63] lr: 6.1107e-03 eta: 1 day, 3:33:04 time: 1.7188 data_time: 0.0629 memory: 16201 loss_prob: 0.8304 loss_thr: 0.4722 loss_db: 0.1336 loss: 1.4362 2022/08/30 03:53:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:53:33 - mmengine - INFO - Epoch(train) [170][5/63] lr: 6.1054e-03 eta: 1 day, 3:33:04 time: 1.7916 data_time: 0.2705 memory: 16201 loss_prob: 0.8836 loss_thr: 0.5060 loss_db: 0.1470 loss: 1.5365 2022/08/30 03:53:41 - mmengine - INFO - Epoch(train) [170][10/63] lr: 6.1054e-03 eta: 1 day, 3:32:40 time: 1.9199 data_time: 0.2672 memory: 16201 loss_prob: 0.8130 loss_thr: 0.5077 loss_db: 0.1360 loss: 1.4567 2022/08/30 03:53:50 - mmengine - INFO - Epoch(train) [170][15/63] lr: 6.1054e-03 eta: 1 day, 3:32:40 time: 1.7609 data_time: 0.0357 memory: 16201 loss_prob: 0.8813 loss_thr: 0.5346 loss_db: 0.1433 loss: 1.5592 2022/08/30 03:53:58 - mmengine - INFO - Epoch(train) [170][20/63] lr: 6.1054e-03 eta: 1 day, 3:32:33 time: 1.6660 data_time: 0.0410 memory: 16201 loss_prob: 0.9123 loss_thr: 0.5214 loss_db: 0.1501 loss: 1.5839 2022/08/30 03:54:06 - mmengine - INFO - Epoch(train) [170][25/63] lr: 6.1054e-03 eta: 1 day, 3:32:33 time: 1.5517 data_time: 0.0416 memory: 16201 loss_prob: 0.8073 loss_thr: 0.4880 loss_db: 0.1369 loss: 1.4322 2022/08/30 03:54:15 - mmengine - INFO - Epoch(train) [170][30/63] lr: 6.1054e-03 eta: 1 day, 3:32:31 time: 1.7508 data_time: 0.0401 memory: 16201 loss_prob: 0.7759 loss_thr: 0.4725 loss_db: 0.1277 loss: 1.3762 2022/08/30 03:54:23 - mmengine - INFO - Epoch(train) [170][35/63] lr: 6.1054e-03 eta: 1 day, 3:32:31 time: 1.6972 data_time: 0.0577 memory: 16201 loss_prob: 0.8196 loss_thr: 0.4821 loss_db: 0.1315 loss: 1.4332 2022/08/30 03:54:31 - mmengine - INFO - Epoch(train) [170][40/63] lr: 6.1054e-03 eta: 1 day, 3:32:20 time: 1.5842 data_time: 0.0478 memory: 16201 loss_prob: 0.8011 loss_thr: 0.4902 loss_db: 0.1338 loss: 1.4251 2022/08/30 03:54:41 - mmengine - INFO - Epoch(train) [170][45/63] lr: 6.1054e-03 eta: 1 day, 3:32:20 time: 1.7809 data_time: 0.0409 memory: 16201 loss_prob: 0.8089 loss_thr: 0.5139 loss_db: 0.1372 loss: 1.4600 2022/08/30 03:54:50 - mmengine - INFO - Epoch(train) [170][50/63] lr: 6.1054e-03 eta: 1 day, 3:32:24 time: 1.8518 data_time: 0.0518 memory: 16201 loss_prob: 0.8108 loss_thr: 0.5056 loss_db: 0.1344 loss: 1.4508 2022/08/30 03:54:59 - mmengine - INFO - Epoch(train) [170][55/63] lr: 6.1054e-03 eta: 1 day, 3:32:24 time: 1.7965 data_time: 0.0397 memory: 16201 loss_prob: 0.7985 loss_thr: 0.4918 loss_db: 0.1330 loss: 1.4233 2022/08/30 03:55:06 - mmengine - INFO - Epoch(train) [170][60/63] lr: 6.1054e-03 eta: 1 day, 3:32:16 time: 1.6500 data_time: 0.0458 memory: 16201 loss_prob: 0.8418 loss_thr: 0.5068 loss_db: 0.1438 loss: 1.4924 2022/08/30 03:55:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:55:19 - mmengine - INFO - Epoch(train) [171][5/63] lr: 6.1001e-03 eta: 1 day, 3:32:16 time: 1.6534 data_time: 0.2535 memory: 16201 loss_prob: 0.8053 loss_thr: 0.4899 loss_db: 0.1339 loss: 1.4291 2022/08/30 03:55:28 - mmengine - INFO - Epoch(train) [171][10/63] lr: 6.1001e-03 eta: 1 day, 3:31:50 time: 1.8862 data_time: 0.2736 memory: 16201 loss_prob: 0.8149 loss_thr: 0.4785 loss_db: 0.1338 loss: 1.4272 2022/08/30 03:55:38 - mmengine - INFO - Epoch(train) [171][15/63] lr: 6.1001e-03 eta: 1 day, 3:31:50 time: 1.8040 data_time: 0.0393 memory: 16201 loss_prob: 0.9432 loss_thr: 0.5149 loss_db: 0.1591 loss: 1.6173 2022/08/30 03:55:47 - mmengine - INFO - Epoch(train) [171][20/63] lr: 6.1001e-03 eta: 1 day, 3:31:57 time: 1.8933 data_time: 0.0393 memory: 16201 loss_prob: 0.8989 loss_thr: 0.5072 loss_db: 0.1493 loss: 1.5554 2022/08/30 03:55:57 - mmengine - INFO - Epoch(train) [171][25/63] lr: 6.1001e-03 eta: 1 day, 3:31:57 time: 1.9647 data_time: 0.0483 memory: 16201 loss_prob: 0.7617 loss_thr: 0.4692 loss_db: 0.1252 loss: 1.3561 2022/08/30 03:56:07 - mmengine - INFO - Epoch(train) [171][30/63] lr: 6.1001e-03 eta: 1 day, 3:32:08 time: 1.9590 data_time: 0.0465 memory: 16201 loss_prob: 0.8173 loss_thr: 0.5024 loss_db: 0.1383 loss: 1.4580 2022/08/30 03:56:15 - mmengine - INFO - Epoch(train) [171][35/63] lr: 6.1001e-03 eta: 1 day, 3:32:08 time: 1.7898 data_time: 0.0481 memory: 16201 loss_prob: 0.8602 loss_thr: 0.5292 loss_db: 0.1483 loss: 1.5378 2022/08/30 03:56:25 - mmengine - INFO - Epoch(train) [171][40/63] lr: 6.1001e-03 eta: 1 day, 3:32:07 time: 1.7619 data_time: 0.0409 memory: 16201 loss_prob: 0.8266 loss_thr: 0.5251 loss_db: 0.1424 loss: 1.4941 2022/08/30 03:56:33 - mmengine - INFO - Epoch(train) [171][45/63] lr: 6.1001e-03 eta: 1 day, 3:32:07 time: 1.7457 data_time: 0.0366 memory: 16201 loss_prob: 0.8347 loss_thr: 0.5025 loss_db: 0.1384 loss: 1.4756 2022/08/30 03:56:41 - mmengine - INFO - Epoch(train) [171][50/63] lr: 6.1001e-03 eta: 1 day, 3:31:59 time: 1.6495 data_time: 0.0500 memory: 16201 loss_prob: 0.8410 loss_thr: 0.4826 loss_db: 0.1386 loss: 1.4622 2022/08/30 03:56:50 - mmengine - INFO - Epoch(train) [171][55/63] lr: 6.1001e-03 eta: 1 day, 3:31:59 time: 1.7346 data_time: 0.0573 memory: 16201 loss_prob: 0.8211 loss_thr: 0.4810 loss_db: 0.1354 loss: 1.4376 2022/08/30 03:56:58 - mmengine - INFO - Epoch(train) [171][60/63] lr: 6.1001e-03 eta: 1 day, 3:31:53 time: 1.6951 data_time: 0.0467 memory: 16201 loss_prob: 0.8961 loss_thr: 0.4871 loss_db: 0.1444 loss: 1.5276 2022/08/30 03:57:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:57:15 - mmengine - INFO - Epoch(train) [172][5/63] lr: 6.0947e-03 eta: 1 day, 3:31:53 time: 2.0715 data_time: 0.2810 memory: 16201 loss_prob: 0.8375 loss_thr: 0.4787 loss_db: 0.1372 loss: 1.4534 2022/08/30 03:57:24 - mmengine - INFO - Epoch(train) [172][10/63] lr: 6.0947e-03 eta: 1 day, 3:31:40 time: 2.0893 data_time: 0.3100 memory: 16201 loss_prob: 0.8299 loss_thr: 0.5084 loss_db: 0.1379 loss: 1.4762 2022/08/30 03:57:32 - mmengine - INFO - Epoch(train) [172][15/63] lr: 6.0947e-03 eta: 1 day, 3:31:40 time: 1.6719 data_time: 0.0458 memory: 16201 loss_prob: 0.8518 loss_thr: 0.5141 loss_db: 0.1439 loss: 1.5097 2022/08/30 03:57:40 - mmengine - INFO - Epoch(train) [172][20/63] lr: 6.0947e-03 eta: 1 day, 3:31:32 time: 1.6500 data_time: 0.0398 memory: 16201 loss_prob: 0.9053 loss_thr: 0.5173 loss_db: 0.1491 loss: 1.5717 2022/08/30 03:57:50 - mmengine - INFO - Epoch(train) [172][25/63] lr: 6.0947e-03 eta: 1 day, 3:31:32 time: 1.8635 data_time: 0.0579 memory: 16201 loss_prob: 0.8523 loss_thr: 0.4951 loss_db: 0.1405 loss: 1.4878 2022/08/30 03:57:59 - mmengine - INFO - Epoch(train) [172][30/63] lr: 6.0947e-03 eta: 1 day, 3:31:38 time: 1.8937 data_time: 0.0399 memory: 16201 loss_prob: 0.7732 loss_thr: 0.4769 loss_db: 0.1329 loss: 1.3830 2022/08/30 03:58:09 - mmengine - INFO - Epoch(train) [172][35/63] lr: 6.0947e-03 eta: 1 day, 3:31:38 time: 1.8628 data_time: 0.0392 memory: 16201 loss_prob: 0.7727 loss_thr: 0.4941 loss_db: 0.1319 loss: 1.3987 2022/08/30 03:58:17 - mmengine - INFO - Epoch(train) [172][40/63] lr: 6.0947e-03 eta: 1 day, 3:31:37 time: 1.7688 data_time: 0.0454 memory: 16201 loss_prob: 0.8810 loss_thr: 0.5263 loss_db: 0.1413 loss: 1.5485 2022/08/30 03:58:28 - mmengine - INFO - Epoch(train) [172][45/63] lr: 6.0947e-03 eta: 1 day, 3:31:37 time: 1.9171 data_time: 0.0444 memory: 16201 loss_prob: 0.8816 loss_thr: 0.5159 loss_db: 0.1409 loss: 1.5385 2022/08/30 03:58:37 - mmengine - INFO - Epoch(train) [172][50/63] lr: 6.0947e-03 eta: 1 day, 3:31:48 time: 1.9601 data_time: 0.0580 memory: 16201 loss_prob: 0.8040 loss_thr: 0.4848 loss_db: 0.1361 loss: 1.4249 2022/08/30 03:58:45 - mmengine - INFO - Epoch(train) [172][55/63] lr: 6.0947e-03 eta: 1 day, 3:31:48 time: 1.6534 data_time: 0.0433 memory: 16201 loss_prob: 0.8030 loss_thr: 0.4639 loss_db: 0.1331 loss: 1.3999 2022/08/30 03:58:53 - mmengine - INFO - Epoch(train) [172][60/63] lr: 6.0947e-03 eta: 1 day, 3:31:40 time: 1.6548 data_time: 0.0503 memory: 16201 loss_prob: 0.8517 loss_thr: 0.4738 loss_db: 0.1384 loss: 1.4639 2022/08/30 03:58:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 03:59:08 - mmengine - INFO - Epoch(train) [173][5/63] lr: 6.0894e-03 eta: 1 day, 3:31:40 time: 1.8595 data_time: 0.2724 memory: 16201 loss_prob: 0.8560 loss_thr: 0.5116 loss_db: 0.1420 loss: 1.5096 2022/08/30 03:59:17 - mmengine - INFO - Epoch(train) [173][10/63] lr: 6.0894e-03 eta: 1 day, 3:31:15 time: 1.9044 data_time: 0.2898 memory: 16201 loss_prob: 0.8565 loss_thr: 0.5372 loss_db: 0.1400 loss: 1.5336 2022/08/30 03:59:24 - mmengine - INFO - Epoch(train) [173][15/63] lr: 6.0894e-03 eta: 1 day, 3:31:15 time: 1.5719 data_time: 0.0391 memory: 16201 loss_prob: 0.8540 loss_thr: 0.5224 loss_db: 0.1436 loss: 1.5199 2022/08/30 03:59:32 - mmengine - INFO - Epoch(train) [173][20/63] lr: 6.0894e-03 eta: 1 day, 3:31:01 time: 1.5620 data_time: 0.0297 memory: 16201 loss_prob: 0.7859 loss_thr: 0.4716 loss_db: 0.1327 loss: 1.3902 2022/08/30 03:59:40 - mmengine - INFO - Epoch(train) [173][25/63] lr: 6.0894e-03 eta: 1 day, 3:31:01 time: 1.5805 data_time: 0.0447 memory: 16201 loss_prob: 0.7526 loss_thr: 0.4527 loss_db: 0.1246 loss: 1.3298 2022/08/30 03:59:46 - mmengine - INFO - Epoch(train) [173][30/63] lr: 6.0894e-03 eta: 1 day, 3:30:39 time: 1.4041 data_time: 0.0351 memory: 16201 loss_prob: 0.8191 loss_thr: 0.4906 loss_db: 0.1386 loss: 1.4483 2022/08/30 03:59:55 - mmengine - INFO - Epoch(train) [173][35/63] lr: 6.0894e-03 eta: 1 day, 3:30:39 time: 1.5093 data_time: 0.0381 memory: 16201 loss_prob: 0.8489 loss_thr: 0.4839 loss_db: 0.1415 loss: 1.4743 2022/08/30 04:00:03 - mmengine - INFO - Epoch(train) [173][40/63] lr: 6.0894e-03 eta: 1 day, 3:30:31 time: 1.6553 data_time: 0.0454 memory: 16201 loss_prob: 0.8146 loss_thr: 0.4808 loss_db: 0.1355 loss: 1.4309 2022/08/30 04:00:11 - mmengine - INFO - Epoch(train) [173][45/63] lr: 6.0894e-03 eta: 1 day, 3:30:31 time: 1.6507 data_time: 0.0670 memory: 16201 loss_prob: 0.7675 loss_thr: 0.4772 loss_db: 0.1323 loss: 1.3770 2022/08/30 04:00:19 - mmengine - INFO - Epoch(train) [173][50/63] lr: 6.0894e-03 eta: 1 day, 3:30:20 time: 1.6021 data_time: 0.0731 memory: 16201 loss_prob: 0.8354 loss_thr: 0.4838 loss_db: 0.1416 loss: 1.4607 2022/08/30 04:00:28 - mmengine - INFO - Epoch(train) [173][55/63] lr: 6.0894e-03 eta: 1 day, 3:30:20 time: 1.6447 data_time: 0.0462 memory: 16201 loss_prob: 0.8870 loss_thr: 0.5003 loss_db: 0.1459 loss: 1.5332 2022/08/30 04:00:37 - mmengine - INFO - Epoch(train) [173][60/63] lr: 6.0894e-03 eta: 1 day, 3:30:19 time: 1.7676 data_time: 0.0441 memory: 16201 loss_prob: 0.8556 loss_thr: 0.5026 loss_db: 0.1430 loss: 1.5011 2022/08/30 04:00:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:00:54 - mmengine - INFO - Epoch(train) [174][5/63] lr: 6.0841e-03 eta: 1 day, 3:30:19 time: 1.9928 data_time: 0.2196 memory: 16201 loss_prob: 0.7653 loss_thr: 0.4988 loss_db: 0.1296 loss: 1.3937 2022/08/30 04:01:03 - mmengine - INFO - Epoch(train) [174][10/63] lr: 6.0841e-03 eta: 1 day, 3:30:13 time: 2.2251 data_time: 0.2672 memory: 16201 loss_prob: 0.7725 loss_thr: 0.4862 loss_db: 0.1301 loss: 1.3888 2022/08/30 04:01:11 - mmengine - INFO - Epoch(train) [174][15/63] lr: 6.0841e-03 eta: 1 day, 3:30:13 time: 1.7861 data_time: 0.0643 memory: 16201 loss_prob: 0.8201 loss_thr: 0.4883 loss_db: 0.1391 loss: 1.4475 2022/08/30 04:01:20 - mmengine - INFO - Epoch(train) [174][20/63] lr: 6.0841e-03 eta: 1 day, 3:30:09 time: 1.7239 data_time: 0.0353 memory: 16201 loss_prob: 0.8151 loss_thr: 0.4893 loss_db: 0.1371 loss: 1.4415 2022/08/30 04:01:30 - mmengine - INFO - Epoch(train) [174][25/63] lr: 6.0841e-03 eta: 1 day, 3:30:09 time: 1.8417 data_time: 0.0447 memory: 16201 loss_prob: 0.7578 loss_thr: 0.4528 loss_db: 0.1269 loss: 1.3375 2022/08/30 04:01:38 - mmengine - INFO - Epoch(train) [174][30/63] lr: 6.0841e-03 eta: 1 day, 3:30:07 time: 1.7665 data_time: 0.0390 memory: 16201 loss_prob: 0.7793 loss_thr: 0.4771 loss_db: 0.1294 loss: 1.3858 2022/08/30 04:01:46 - mmengine - INFO - Epoch(train) [174][35/63] lr: 6.0841e-03 eta: 1 day, 3:30:07 time: 1.6381 data_time: 0.0369 memory: 16201 loss_prob: 0.7866 loss_thr: 0.4990 loss_db: 0.1314 loss: 1.4170 2022/08/30 04:01:55 - mmengine - INFO - Epoch(train) [174][40/63] lr: 6.0841e-03 eta: 1 day, 3:30:05 time: 1.7537 data_time: 0.0396 memory: 16201 loss_prob: 0.7929 loss_thr: 0.4860 loss_db: 0.1348 loss: 1.4136 2022/08/30 04:02:04 - mmengine - INFO - Epoch(train) [174][45/63] lr: 6.0841e-03 eta: 1 day, 3:30:05 time: 1.7768 data_time: 0.0367 memory: 16201 loss_prob: 0.8864 loss_thr: 0.5155 loss_db: 0.1508 loss: 1.5527 2022/08/30 04:02:13 - mmengine - INFO - Epoch(train) [174][50/63] lr: 6.0841e-03 eta: 1 day, 3:30:01 time: 1.7212 data_time: 0.0477 memory: 16201 loss_prob: 0.8706 loss_thr: 0.5159 loss_db: 0.1451 loss: 1.5317 2022/08/30 04:02:21 - mmengine - INFO - Epoch(train) [174][55/63] lr: 6.0841e-03 eta: 1 day, 3:30:01 time: 1.6889 data_time: 0.0452 memory: 16201 loss_prob: 0.9511 loss_thr: 0.5149 loss_db: 0.1554 loss: 1.6214 2022/08/30 04:02:29 - mmengine - INFO - Epoch(train) [174][60/63] lr: 6.0841e-03 eta: 1 day, 3:29:51 time: 1.6107 data_time: 0.0348 memory: 16201 loss_prob: 0.9734 loss_thr: 0.5163 loss_db: 0.1620 loss: 1.6517 2022/08/30 04:02:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:02:45 - mmengine - INFO - Epoch(train) [175][5/63] lr: 6.0787e-03 eta: 1 day, 3:29:51 time: 1.9683 data_time: 0.2840 memory: 16201 loss_prob: 0.9942 loss_thr: 0.5290 loss_db: 0.1630 loss: 1.6862 2022/08/30 04:02:54 - mmengine - INFO - Epoch(train) [175][10/63] lr: 6.0787e-03 eta: 1 day, 3:29:33 time: 2.0341 data_time: 0.3052 memory: 16201 loss_prob: 0.9727 loss_thr: 0.5321 loss_db: 0.1599 loss: 1.6648 2022/08/30 04:03:03 - mmengine - INFO - Epoch(train) [175][15/63] lr: 6.0787e-03 eta: 1 day, 3:29:33 time: 1.7941 data_time: 0.0437 memory: 16201 loss_prob: 0.9577 loss_thr: 0.5247 loss_db: 0.1615 loss: 1.6439 2022/08/30 04:03:12 - mmengine - INFO - Epoch(train) [175][20/63] lr: 6.0787e-03 eta: 1 day, 3:29:37 time: 1.8520 data_time: 0.0554 memory: 16201 loss_prob: 0.8254 loss_thr: 0.4859 loss_db: 0.1409 loss: 1.4522 2022/08/30 04:03:20 - mmengine - INFO - Epoch(train) [175][25/63] lr: 6.0787e-03 eta: 1 day, 3:29:37 time: 1.6786 data_time: 0.0604 memory: 16201 loss_prob: 0.7826 loss_thr: 0.4859 loss_db: 0.1321 loss: 1.4007 2022/08/30 04:03:28 - mmengine - INFO - Epoch(train) [175][30/63] lr: 6.0787e-03 eta: 1 day, 3:29:24 time: 1.5659 data_time: 0.0304 memory: 16201 loss_prob: 0.9563 loss_thr: 0.5231 loss_db: 0.1529 loss: 1.6323 2022/08/30 04:03:35 - mmengine - INFO - Epoch(train) [175][35/63] lr: 6.0787e-03 eta: 1 day, 3:29:24 time: 1.5522 data_time: 0.0310 memory: 16201 loss_prob: 0.9584 loss_thr: 0.5262 loss_db: 0.1527 loss: 1.6373 2022/08/30 04:03:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:03:43 - mmengine - INFO - Epoch(train) [175][40/63] lr: 6.0787e-03 eta: 1 day, 3:29:05 time: 1.4693 data_time: 0.0323 memory: 16201 loss_prob: 0.8098 loss_thr: 0.4998 loss_db: 0.1365 loss: 1.4461 2022/08/30 04:03:49 - mmengine - INFO - Epoch(train) [175][45/63] lr: 6.0787e-03 eta: 1 day, 3:29:05 time: 1.3710 data_time: 0.0343 memory: 16201 loss_prob: 0.7945 loss_thr: 0.4940 loss_db: 0.1349 loss: 1.4233 2022/08/30 04:03:56 - mmengine - INFO - Epoch(train) [175][50/63] lr: 6.0787e-03 eta: 1 day, 3:28:39 time: 1.3645 data_time: 0.0429 memory: 16201 loss_prob: 0.8024 loss_thr: 0.4871 loss_db: 0.1317 loss: 1.4212 2022/08/30 04:04:04 - mmengine - INFO - Epoch(train) [175][55/63] lr: 6.0787e-03 eta: 1 day, 3:28:39 time: 1.4550 data_time: 0.0386 memory: 16201 loss_prob: 0.8486 loss_thr: 0.5018 loss_db: 0.1388 loss: 1.4892 2022/08/30 04:04:12 - mmengine - INFO - Epoch(train) [175][60/63] lr: 6.0787e-03 eta: 1 day, 3:28:27 time: 1.5761 data_time: 0.0378 memory: 16201 loss_prob: 0.8317 loss_thr: 0.4978 loss_db: 0.1404 loss: 1.4699 2022/08/30 04:04:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:04:27 - mmengine - INFO - Epoch(train) [176][5/63] lr: 6.0734e-03 eta: 1 day, 3:28:27 time: 1.8427 data_time: 0.2504 memory: 16201 loss_prob: 1.2178 loss_thr: 0.5238 loss_db: 0.1829 loss: 1.9245 2022/08/30 04:04:35 - mmengine - INFO - Epoch(train) [176][10/63] lr: 6.0734e-03 eta: 1 day, 3:28:03 time: 1.9256 data_time: 0.2810 memory: 16201 loss_prob: 0.9694 loss_thr: 0.5192 loss_db: 0.1649 loss: 1.6535 2022/08/30 04:04:43 - mmengine - INFO - Epoch(train) [176][15/63] lr: 6.0734e-03 eta: 1 day, 3:28:03 time: 1.5565 data_time: 0.0469 memory: 16201 loss_prob: 1.0804 loss_thr: 0.5280 loss_db: 0.1818 loss: 1.7901 2022/08/30 04:04:51 - mmengine - INFO - Epoch(train) [176][20/63] lr: 6.0734e-03 eta: 1 day, 3:27:48 time: 1.5367 data_time: 0.0429 memory: 16201 loss_prob: 1.0996 loss_thr: 0.5349 loss_db: 0.1811 loss: 1.8156 2022/08/30 04:04:58 - mmengine - INFO - Epoch(train) [176][25/63] lr: 6.0734e-03 eta: 1 day, 3:27:48 time: 1.5382 data_time: 0.0590 memory: 16201 loss_prob: 0.9899 loss_thr: 0.5395 loss_db: 0.1635 loss: 1.6928 2022/08/30 04:05:06 - mmengine - INFO - Epoch(train) [176][30/63] lr: 6.0734e-03 eta: 1 day, 3:27:30 time: 1.4879 data_time: 0.0393 memory: 16201 loss_prob: 0.9314 loss_thr: 0.5154 loss_db: 0.1534 loss: 1.6001 2022/08/30 04:05:13 - mmengine - INFO - Epoch(train) [176][35/63] lr: 6.0734e-03 eta: 1 day, 3:27:30 time: 1.4296 data_time: 0.0378 memory: 16201 loss_prob: 1.0471 loss_thr: 0.5152 loss_db: 0.1669 loss: 1.7292 2022/08/30 04:05:20 - mmengine - INFO - Epoch(train) [176][40/63] lr: 6.0734e-03 eta: 1 day, 3:27:10 time: 1.4498 data_time: 0.0345 memory: 16201 loss_prob: 1.0225 loss_thr: 0.5089 loss_db: 0.1642 loss: 1.6955 2022/08/30 04:05:28 - mmengine - INFO - Epoch(train) [176][45/63] lr: 6.0734e-03 eta: 1 day, 3:27:10 time: 1.5225 data_time: 0.0311 memory: 16201 loss_prob: 1.0189 loss_thr: 0.5211 loss_db: 0.1678 loss: 1.7078 2022/08/30 04:05:35 - mmengine - INFO - Epoch(train) [176][50/63] lr: 6.0734e-03 eta: 1 day, 3:26:50 time: 1.4570 data_time: 0.0421 memory: 16201 loss_prob: 1.0297 loss_thr: 0.5399 loss_db: 0.1643 loss: 1.7340 2022/08/30 04:05:42 - mmengine - INFO - Epoch(train) [176][55/63] lr: 6.0734e-03 eta: 1 day, 3:26:50 time: 1.4389 data_time: 0.0348 memory: 16201 loss_prob: 0.9916 loss_thr: 0.5331 loss_db: 0.1594 loss: 1.6841 2022/08/30 04:05:50 - mmengine - INFO - Epoch(train) [176][60/63] lr: 6.0734e-03 eta: 1 day, 3:26:34 time: 1.5072 data_time: 0.0368 memory: 16201 loss_prob: 0.9783 loss_thr: 0.5302 loss_db: 0.1627 loss: 1.6712 2022/08/30 04:05:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:06:04 - mmengine - INFO - Epoch(train) [177][5/63] lr: 6.0681e-03 eta: 1 day, 3:26:34 time: 1.7374 data_time: 0.2547 memory: 16201 loss_prob: 1.3344 loss_thr: 0.5552 loss_db: 0.2078 loss: 2.0974 2022/08/30 04:06:12 - mmengine - INFO - Epoch(train) [177][10/63] lr: 6.0681e-03 eta: 1 day, 3:26:02 time: 1.7963 data_time: 0.2753 memory: 16201 loss_prob: 1.0681 loss_thr: 0.5691 loss_db: 0.1738 loss: 1.8110 2022/08/30 04:06:20 - mmengine - INFO - Epoch(train) [177][15/63] lr: 6.0681e-03 eta: 1 day, 3:26:02 time: 1.5821 data_time: 0.0359 memory: 16201 loss_prob: 1.0118 loss_thr: 0.5569 loss_db: 0.1666 loss: 1.7354 2022/08/30 04:06:27 - mmengine - INFO - Epoch(train) [177][20/63] lr: 6.0681e-03 eta: 1 day, 3:25:48 time: 1.5450 data_time: 0.0339 memory: 16201 loss_prob: 1.0111 loss_thr: 0.5520 loss_db: 0.1702 loss: 1.7333 2022/08/30 04:06:35 - mmengine - INFO - Epoch(train) [177][25/63] lr: 6.0681e-03 eta: 1 day, 3:25:48 time: 1.4818 data_time: 0.0398 memory: 16201 loss_prob: 0.9314 loss_thr: 0.5172 loss_db: 0.1576 loss: 1.6063 2022/08/30 04:06:43 - mmengine - INFO - Epoch(train) [177][30/63] lr: 6.0681e-03 eta: 1 day, 3:25:33 time: 1.5444 data_time: 0.0359 memory: 16201 loss_prob: 0.9693 loss_thr: 0.5242 loss_db: 0.1718 loss: 1.6653 2022/08/30 04:06:50 - mmengine - INFO - Epoch(train) [177][35/63] lr: 6.0681e-03 eta: 1 day, 3:25:33 time: 1.5814 data_time: 0.0429 memory: 16201 loss_prob: 1.2300 loss_thr: 0.5438 loss_db: 0.1930 loss: 1.9668 2022/08/30 04:06:57 - mmengine - INFO - Epoch(train) [177][40/63] lr: 6.0681e-03 eta: 1 day, 3:25:13 time: 1.4501 data_time: 0.0340 memory: 16201 loss_prob: 1.2220 loss_thr: 0.5276 loss_db: 0.1789 loss: 1.9285 2022/08/30 04:07:04 - mmengine - INFO - Epoch(train) [177][45/63] lr: 6.0681e-03 eta: 1 day, 3:25:13 time: 1.3348 data_time: 0.0337 memory: 16201 loss_prob: 1.1374 loss_thr: 0.5267 loss_db: 0.1794 loss: 1.8434 2022/08/30 04:07:11 - mmengine - INFO - Epoch(train) [177][50/63] lr: 6.0681e-03 eta: 1 day, 3:24:50 time: 1.3841 data_time: 0.0423 memory: 16201 loss_prob: 1.1008 loss_thr: 0.5343 loss_db: 0.1756 loss: 1.8107 2022/08/30 04:07:18 - mmengine - INFO - Epoch(train) [177][55/63] lr: 6.0681e-03 eta: 1 day, 3:24:50 time: 1.4127 data_time: 0.0296 memory: 16201 loss_prob: 1.0155 loss_thr: 0.5404 loss_db: 0.1664 loss: 1.7223 2022/08/30 04:07:25 - mmengine - INFO - Epoch(train) [177][60/63] lr: 6.0681e-03 eta: 1 day, 3:24:29 time: 1.4414 data_time: 0.0397 memory: 16201 loss_prob: 1.2575 loss_thr: 0.5701 loss_db: 0.1997 loss: 2.0274 2022/08/30 04:07:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:07:40 - mmengine - INFO - Epoch(train) [178][5/63] lr: 6.0627e-03 eta: 1 day, 3:24:29 time: 1.7240 data_time: 0.2419 memory: 16201 loss_prob: 0.9952 loss_thr: 0.5139 loss_db: 0.1624 loss: 1.6715 2022/08/30 04:07:48 - mmengine - INFO - Epoch(train) [178][10/63] lr: 6.0627e-03 eta: 1 day, 3:24:00 time: 1.8319 data_time: 0.2620 memory: 16201 loss_prob: 0.9260 loss_thr: 0.5121 loss_db: 0.1523 loss: 1.5903 2022/08/30 04:07:55 - mmengine - INFO - Epoch(train) [178][15/63] lr: 6.0627e-03 eta: 1 day, 3:24:00 time: 1.5537 data_time: 0.0422 memory: 16201 loss_prob: 1.0292 loss_thr: 0.5269 loss_db: 0.1634 loss: 1.7195 2022/08/30 04:08:03 - mmengine - INFO - Epoch(train) [178][20/63] lr: 6.0627e-03 eta: 1 day, 3:23:44 time: 1.5194 data_time: 0.0296 memory: 16201 loss_prob: 1.1574 loss_thr: 0.5571 loss_db: 0.1842 loss: 1.8987 2022/08/30 04:08:10 - mmengine - INFO - Epoch(train) [178][25/63] lr: 6.0627e-03 eta: 1 day, 3:23:44 time: 1.5215 data_time: 0.0450 memory: 16201 loss_prob: 1.0434 loss_thr: 0.5445 loss_db: 0.1757 loss: 1.7636 2022/08/30 04:08:18 - mmengine - INFO - Epoch(train) [178][30/63] lr: 6.0627e-03 eta: 1 day, 3:23:28 time: 1.5153 data_time: 0.0452 memory: 16201 loss_prob: 0.9575 loss_thr: 0.5023 loss_db: 0.1597 loss: 1.6194 2022/08/30 04:08:25 - mmengine - INFO - Epoch(train) [178][35/63] lr: 6.0627e-03 eta: 1 day, 3:23:28 time: 1.4252 data_time: 0.0340 memory: 16201 loss_prob: 0.9977 loss_thr: 0.5301 loss_db: 0.1618 loss: 1.6895 2022/08/30 04:08:32 - mmengine - INFO - Epoch(train) [178][40/63] lr: 6.0627e-03 eta: 1 day, 3:23:06 time: 1.4172 data_time: 0.0327 memory: 16201 loss_prob: 0.9263 loss_thr: 0.5215 loss_db: 0.1504 loss: 1.5983 2022/08/30 04:08:40 - mmengine - INFO - Epoch(train) [178][45/63] lr: 6.0627e-03 eta: 1 day, 3:23:06 time: 1.5011 data_time: 0.0368 memory: 16201 loss_prob: 0.8902 loss_thr: 0.4917 loss_db: 0.1451 loss: 1.5270 2022/08/30 04:08:47 - mmengine - INFO - Epoch(train) [178][50/63] lr: 6.0627e-03 eta: 1 day, 3:22:47 time: 1.4603 data_time: 0.0389 memory: 16201 loss_prob: 0.9004 loss_thr: 0.5071 loss_db: 0.1479 loss: 1.5554 2022/08/30 04:08:54 - mmengine - INFO - Epoch(train) [178][55/63] lr: 6.0627e-03 eta: 1 day, 3:22:47 time: 1.3925 data_time: 0.0308 memory: 16201 loss_prob: 0.9741 loss_thr: 0.5509 loss_db: 0.1593 loss: 1.6842 2022/08/30 04:09:01 - mmengine - INFO - Epoch(train) [178][60/63] lr: 6.0627e-03 eta: 1 day, 3:22:27 time: 1.4607 data_time: 0.0294 memory: 16201 loss_prob: 0.9623 loss_thr: 0.5299 loss_db: 0.1555 loss: 1.6477 2022/08/30 04:09:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:09:15 - mmengine - INFO - Epoch(train) [179][5/63] lr: 6.0574e-03 eta: 1 day, 3:22:27 time: 1.6454 data_time: 0.2443 memory: 16201 loss_prob: 0.8783 loss_thr: 0.4919 loss_db: 0.1432 loss: 1.5135 2022/08/30 04:09:22 - mmengine - INFO - Epoch(train) [179][10/63] lr: 6.0574e-03 eta: 1 day, 3:21:49 time: 1.6622 data_time: 0.2624 memory: 16201 loss_prob: 0.9552 loss_thr: 0.5249 loss_db: 0.1548 loss: 1.6349 2022/08/30 04:09:30 - mmengine - INFO - Epoch(train) [179][15/63] lr: 6.0574e-03 eta: 1 day, 3:21:49 time: 1.5221 data_time: 0.0359 memory: 16201 loss_prob: 0.9888 loss_thr: 0.5389 loss_db: 0.1606 loss: 1.6883 2022/08/30 04:09:37 - mmengine - INFO - Epoch(train) [179][20/63] lr: 6.0574e-03 eta: 1 day, 3:21:30 time: 1.4714 data_time: 0.0373 memory: 16201 loss_prob: 0.9853 loss_thr: 0.5381 loss_db: 0.1620 loss: 1.6854 2022/08/30 04:09:44 - mmengine - INFO - Epoch(train) [179][25/63] lr: 6.0574e-03 eta: 1 day, 3:21:30 time: 1.4532 data_time: 0.0361 memory: 16201 loss_prob: 0.9458 loss_thr: 0.5232 loss_db: 0.1550 loss: 1.6240 2022/08/30 04:09:52 - mmengine - INFO - Epoch(train) [179][30/63] lr: 6.0574e-03 eta: 1 day, 3:21:12 time: 1.4908 data_time: 0.0350 memory: 16201 loss_prob: 0.8666 loss_thr: 0.5036 loss_db: 0.1461 loss: 1.5162 2022/08/30 04:09:59 - mmengine - INFO - Epoch(train) [179][35/63] lr: 6.0574e-03 eta: 1 day, 3:21:12 time: 1.4821 data_time: 0.0456 memory: 16201 loss_prob: 0.8042 loss_thr: 0.4829 loss_db: 0.1348 loss: 1.4219 2022/08/30 04:10:06 - mmengine - INFO - Epoch(train) [179][40/63] lr: 6.0574e-03 eta: 1 day, 3:20:49 time: 1.3941 data_time: 0.0370 memory: 16201 loss_prob: 0.7861 loss_thr: 0.4903 loss_db: 0.1298 loss: 1.4062 2022/08/30 04:10:13 - mmengine - INFO - Epoch(train) [179][45/63] lr: 6.0574e-03 eta: 1 day, 3:20:49 time: 1.3776 data_time: 0.0351 memory: 16201 loss_prob: 0.8751 loss_thr: 0.5213 loss_db: 0.1488 loss: 1.5452 2022/08/30 04:10:19 - mmengine - INFO - Epoch(train) [179][50/63] lr: 6.0574e-03 eta: 1 day, 3:20:26 time: 1.3819 data_time: 0.0509 memory: 16201 loss_prob: 0.8556 loss_thr: 0.5013 loss_db: 0.1447 loss: 1.5016 2022/08/30 04:10:27 - mmengine - INFO - Epoch(train) [179][55/63] lr: 6.0574e-03 eta: 1 day, 3:20:26 time: 1.4245 data_time: 0.0451 memory: 16201 loss_prob: 0.8075 loss_thr: 0.4851 loss_db: 0.1305 loss: 1.4230 2022/08/30 04:10:34 - mmengine - INFO - Epoch(train) [179][60/63] lr: 6.0574e-03 eta: 1 day, 3:20:09 time: 1.5013 data_time: 0.0365 memory: 16201 loss_prob: 0.8606 loss_thr: 0.5000 loss_db: 0.1429 loss: 1.5034 2022/08/30 04:10:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:10:47 - mmengine - INFO - Epoch(train) [180][5/63] lr: 6.0520e-03 eta: 1 day, 3:20:09 time: 1.5429 data_time: 0.2420 memory: 16201 loss_prob: 0.9250 loss_thr: 0.5235 loss_db: 0.1534 loss: 1.6019 2022/08/30 04:10:55 - mmengine - INFO - Epoch(train) [180][10/63] lr: 6.0520e-03 eta: 1 day, 3:19:33 time: 1.7102 data_time: 0.2518 memory: 16201 loss_prob: 0.8656 loss_thr: 0.5028 loss_db: 0.1441 loss: 1.5124 2022/08/30 04:11:01 - mmengine - INFO - Epoch(train) [180][15/63] lr: 6.0520e-03 eta: 1 day, 3:19:33 time: 1.4633 data_time: 0.0342 memory: 16201 loss_prob: 0.8836 loss_thr: 0.5184 loss_db: 0.1495 loss: 1.5515 2022/08/30 04:11:09 - mmengine - INFO - Epoch(train) [180][20/63] lr: 6.0520e-03 eta: 1 day, 3:19:14 time: 1.4708 data_time: 0.0298 memory: 16201 loss_prob: 0.8536 loss_thr: 0.5203 loss_db: 0.1417 loss: 1.5156 2022/08/30 04:11:18 - mmengine - INFO - Epoch(train) [180][25/63] lr: 6.0520e-03 eta: 1 day, 3:19:14 time: 1.6178 data_time: 0.0384 memory: 16201 loss_prob: 0.7611 loss_thr: 0.4753 loss_db: 0.1266 loss: 1.3630 2022/08/30 04:11:25 - mmengine - INFO - Epoch(train) [180][30/63] lr: 6.0520e-03 eta: 1 day, 3:19:01 time: 1.5599 data_time: 0.0311 memory: 16201 loss_prob: 0.7925 loss_thr: 0.4860 loss_db: 0.1309 loss: 1.4094 2022/08/30 04:11:32 - mmengine - INFO - Epoch(train) [180][35/63] lr: 6.0520e-03 eta: 1 day, 3:19:01 time: 1.4552 data_time: 0.0429 memory: 16201 loss_prob: 0.8857 loss_thr: 0.5296 loss_db: 0.1459 loss: 1.5611 2022/08/30 04:11:39 - mmengine - INFO - Epoch(train) [180][40/63] lr: 6.0520e-03 eta: 1 day, 3:18:40 time: 1.4348 data_time: 0.0369 memory: 16201 loss_prob: 0.9020 loss_thr: 0.5170 loss_db: 0.1498 loss: 1.5688 2022/08/30 04:11:46 - mmengine - INFO - Epoch(train) [180][45/63] lr: 6.0520e-03 eta: 1 day, 3:18:40 time: 1.4088 data_time: 0.0366 memory: 16201 loss_prob: 0.8687 loss_thr: 0.4812 loss_db: 0.1440 loss: 1.4938 2022/08/30 04:11:53 - mmengine - INFO - Epoch(train) [180][50/63] lr: 6.0520e-03 eta: 1 day, 3:18:13 time: 1.3224 data_time: 0.0561 memory: 16201 loss_prob: 0.9794 loss_thr: 0.4954 loss_db: 0.1531 loss: 1.6278 2022/08/30 04:12:00 - mmengine - INFO - Epoch(train) [180][55/63] lr: 6.0520e-03 eta: 1 day, 3:18:13 time: 1.3446 data_time: 0.0361 memory: 16201 loss_prob: 0.9619 loss_thr: 0.5132 loss_db: 0.1490 loss: 1.6241 2022/08/30 04:12:07 - mmengine - INFO - Epoch(train) [180][60/63] lr: 6.0520e-03 eta: 1 day, 3:17:50 time: 1.3927 data_time: 0.0330 memory: 16201 loss_prob: 0.9025 loss_thr: 0.5135 loss_db: 0.1440 loss: 1.5600 2022/08/30 04:12:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:12:09 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/08/30 04:12:18 - mmengine - INFO - Epoch(val) [180][5/32] eta: 1 day, 3:17:50 time: 0.7148 data_time: 0.1446 memory: 16201 2022/08/30 04:12:22 - mmengine - INFO - Epoch(val) [180][10/32] eta: 0:00:17 time: 0.7918 data_time: 0.1819 memory: 15734 2022/08/30 04:12:25 - mmengine - INFO - Epoch(val) [180][15/32] eta: 0:00:17 time: 0.6570 data_time: 0.0633 memory: 15734 2022/08/30 04:12:28 - mmengine - INFO - Epoch(val) [180][20/32] eta: 0:00:07 time: 0.6638 data_time: 0.0696 memory: 15734 2022/08/30 04:12:32 - mmengine - INFO - Epoch(val) [180][25/32] eta: 0:00:07 time: 0.7250 data_time: 0.0792 memory: 15734 2022/08/30 04:12:35 - mmengine - INFO - Epoch(val) [180][30/32] eta: 0:00:01 time: 0.6968 data_time: 0.0379 memory: 15734 2022/08/30 04:12:36 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 04:12:36 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8377, precision: 0.7529, hmean: 0.7931 2022/08/30 04:12:36 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8373, precision: 0.8077, hmean: 0.8222 2022/08/30 04:12:36 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8334, precision: 0.8456, hmean: 0.8395 2022/08/30 04:12:36 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8252, precision: 0.8692, hmean: 0.8466 2022/08/30 04:12:36 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7906, precision: 0.9007, hmean: 0.8421 2022/08/30 04:12:36 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5455, precision: 0.9457, hmean: 0.6919 2022/08/30 04:12:36 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0154, precision: 1.0000, hmean: 0.0303 2022/08/30 04:12:36 - mmengine - INFO - Epoch(val) [180][32/32] icdar/precision: 0.8692 icdar/recall: 0.8252 icdar/hmean: 0.8466 2022/08/30 04:12:46 - mmengine - INFO - Epoch(train) [181][5/63] lr: 6.0467e-03 eta: 0:00:01 time: 1.4950 data_time: 0.2344 memory: 16201 loss_prob: 0.8493 loss_thr: 0.4749 loss_db: 0.1426 loss: 1.4668 2022/08/30 04:12:53 - mmengine - INFO - Epoch(train) [181][10/63] lr: 6.0467e-03 eta: 1 day, 3:17:14 time: 1.7071 data_time: 0.2417 memory: 16201 loss_prob: 0.8274 loss_thr: 0.4823 loss_db: 0.1392 loss: 1.4489 2022/08/30 04:13:01 - mmengine - INFO - Epoch(train) [181][15/63] lr: 6.0467e-03 eta: 1 day, 3:17:14 time: 1.5142 data_time: 0.0337 memory: 16201 loss_prob: 0.7238 loss_thr: 0.4730 loss_db: 0.1240 loss: 1.3207 2022/08/30 04:13:08 - mmengine - INFO - Epoch(train) [181][20/63] lr: 6.0467e-03 eta: 1 day, 3:16:52 time: 1.4045 data_time: 0.0273 memory: 16201 loss_prob: 0.7345 loss_thr: 0.4735 loss_db: 0.1265 loss: 1.3345 2022/08/30 04:13:14 - mmengine - INFO - Epoch(train) [181][25/63] lr: 6.0467e-03 eta: 1 day, 3:16:52 time: 1.2486 data_time: 0.0346 memory: 16201 loss_prob: 0.8152 loss_thr: 0.5034 loss_db: 0.1396 loss: 1.4582 2022/08/30 04:13:21 - mmengine - INFO - Epoch(train) [181][30/63] lr: 6.0467e-03 eta: 1 day, 3:16:28 time: 1.3721 data_time: 0.0465 memory: 16201 loss_prob: 0.8437 loss_thr: 0.5039 loss_db: 0.1411 loss: 1.4887 2022/08/30 04:13:28 - mmengine - INFO - Epoch(train) [181][35/63] lr: 6.0467e-03 eta: 1 day, 3:16:28 time: 1.4217 data_time: 0.0370 memory: 16201 loss_prob: 0.8441 loss_thr: 0.4932 loss_db: 0.1395 loss: 1.4768 2022/08/30 04:13:35 - mmengine - INFO - Epoch(train) [181][40/63] lr: 6.0467e-03 eta: 1 day, 3:16:03 time: 1.3632 data_time: 0.0360 memory: 16201 loss_prob: 0.8525 loss_thr: 0.5022 loss_db: 0.1407 loss: 1.4954 2022/08/30 04:13:42 - mmengine - INFO - Epoch(train) [181][45/63] lr: 6.0467e-03 eta: 1 day, 3:16:03 time: 1.4421 data_time: 0.0386 memory: 16201 loss_prob: 0.8635 loss_thr: 0.5116 loss_db: 0.1437 loss: 1.5187 2022/08/30 04:13:50 - mmengine - INFO - Epoch(train) [181][50/63] lr: 6.0467e-03 eta: 1 day, 3:15:46 time: 1.5048 data_time: 0.0382 memory: 16201 loss_prob: 0.8617 loss_thr: 0.5003 loss_db: 0.1430 loss: 1.5050 2022/08/30 04:13:57 - mmengine - INFO - Epoch(train) [181][55/63] lr: 6.0467e-03 eta: 1 day, 3:15:46 time: 1.4812 data_time: 0.0430 memory: 16201 loss_prob: 0.7853 loss_thr: 0.4755 loss_db: 0.1294 loss: 1.3903 2022/08/30 04:14:04 - mmengine - INFO - Epoch(train) [181][60/63] lr: 6.0467e-03 eta: 1 day, 3:15:26 time: 1.4396 data_time: 0.0400 memory: 16201 loss_prob: 0.7692 loss_thr: 0.4701 loss_db: 0.1299 loss: 1.3692 2022/08/30 04:14:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:14:18 - mmengine - INFO - Epoch(train) [182][5/63] lr: 6.0414e-03 eta: 1 day, 3:15:26 time: 1.5992 data_time: 0.2517 memory: 16201 loss_prob: 0.8406 loss_thr: 0.4979 loss_db: 0.1431 loss: 1.4816 2022/08/30 04:14:26 - mmengine - INFO - Epoch(train) [182][10/63] lr: 6.0414e-03 eta: 1 day, 3:14:56 time: 1.8079 data_time: 0.2803 memory: 16201 loss_prob: 0.8697 loss_thr: 0.5347 loss_db: 0.1478 loss: 1.5523 2022/08/30 04:14:33 - mmengine - INFO - Epoch(train) [182][15/63] lr: 6.0414e-03 eta: 1 day, 3:14:56 time: 1.5650 data_time: 0.0608 memory: 16201 loss_prob: 0.8947 loss_thr: 0.5465 loss_db: 0.1491 loss: 1.5903 2022/08/30 04:14:42 - mmengine - INFO - Epoch(train) [182][20/63] lr: 6.0414e-03 eta: 1 day, 3:14:42 time: 1.5529 data_time: 0.0470 memory: 16201 loss_prob: 0.7921 loss_thr: 0.4950 loss_db: 0.1332 loss: 1.4203 2022/08/30 04:14:48 - mmengine - INFO - Epoch(train) [182][25/63] lr: 6.0414e-03 eta: 1 day, 3:14:42 time: 1.5170 data_time: 0.0405 memory: 16201 loss_prob: 0.8610 loss_thr: 0.4944 loss_db: 0.1450 loss: 1.5004 2022/08/30 04:14:56 - mmengine - INFO - Epoch(train) [182][30/63] lr: 6.0414e-03 eta: 1 day, 3:14:21 time: 1.4151 data_time: 0.0332 memory: 16201 loss_prob: 0.8554 loss_thr: 0.5133 loss_db: 0.1401 loss: 1.5088 2022/08/30 04:15:02 - mmengine - INFO - Epoch(train) [182][35/63] lr: 6.0414e-03 eta: 1 day, 3:14:21 time: 1.3966 data_time: 0.0518 memory: 16201 loss_prob: 0.7481 loss_thr: 0.4995 loss_db: 0.1247 loss: 1.3723 2022/08/30 04:15:10 - mmengine - INFO - Epoch(train) [182][40/63] lr: 6.0414e-03 eta: 1 day, 3:13:57 time: 1.3868 data_time: 0.0430 memory: 16201 loss_prob: 0.7715 loss_thr: 0.4858 loss_db: 0.1323 loss: 1.3896 2022/08/30 04:15:16 - mmengine - INFO - Epoch(train) [182][45/63] lr: 6.0414e-03 eta: 1 day, 3:13:57 time: 1.3851 data_time: 0.0398 memory: 16201 loss_prob: 0.8094 loss_thr: 0.4898 loss_db: 0.1387 loss: 1.4380 2022/08/30 04:15:23 - mmengine - INFO - Epoch(train) [182][50/63] lr: 6.0414e-03 eta: 1 day, 3:13:30 time: 1.3016 data_time: 0.0457 memory: 16201 loss_prob: 0.7609 loss_thr: 0.4684 loss_db: 0.1291 loss: 1.3585 2022/08/30 04:15:30 - mmengine - INFO - Epoch(train) [182][55/63] lr: 6.0414e-03 eta: 1 day, 3:13:30 time: 1.4034 data_time: 0.0336 memory: 16201 loss_prob: 0.7526 loss_thr: 0.4622 loss_db: 0.1267 loss: 1.3415 2022/08/30 04:15:38 - mmengine - INFO - Epoch(train) [182][60/63] lr: 6.0414e-03 eta: 1 day, 3:13:13 time: 1.5032 data_time: 0.0400 memory: 16201 loss_prob: 0.8289 loss_thr: 0.4966 loss_db: 0.1381 loss: 1.4636 2022/08/30 04:15:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:15:51 - mmengine - INFO - Epoch(train) [183][5/63] lr: 6.0360e-03 eta: 1 day, 3:13:13 time: 1.5675 data_time: 0.2423 memory: 16201 loss_prob: 0.8899 loss_thr: 0.5121 loss_db: 0.1532 loss: 1.5552 2022/08/30 04:15:58 - mmengine - INFO - Epoch(train) [183][10/63] lr: 6.0360e-03 eta: 1 day, 3:12:38 time: 1.7109 data_time: 0.2515 memory: 16201 loss_prob: 0.8240 loss_thr: 0.4917 loss_db: 0.1390 loss: 1.4547 2022/08/30 04:16:05 - mmengine - INFO - Epoch(train) [183][15/63] lr: 6.0360e-03 eta: 1 day, 3:12:38 time: 1.4853 data_time: 0.0344 memory: 16201 loss_prob: 0.7919 loss_thr: 0.4767 loss_db: 0.1289 loss: 1.3975 2022/08/30 04:16:12 - mmengine - INFO - Epoch(train) [183][20/63] lr: 6.0360e-03 eta: 1 day, 3:12:18 time: 1.4446 data_time: 0.0332 memory: 16201 loss_prob: 0.8613 loss_thr: 0.5092 loss_db: 0.1408 loss: 1.5114 2022/08/30 04:16:19 - mmengine - INFO - Epoch(train) [183][25/63] lr: 6.0360e-03 eta: 1 day, 3:12:18 time: 1.3972 data_time: 0.0452 memory: 16201 loss_prob: 0.8928 loss_thr: 0.5315 loss_db: 0.1467 loss: 1.5710 2022/08/30 04:16:26 - mmengine - INFO - Epoch(train) [183][30/63] lr: 6.0360e-03 eta: 1 day, 3:11:52 time: 1.3414 data_time: 0.0366 memory: 16201 loss_prob: 0.8475 loss_thr: 0.5109 loss_db: 0.1405 loss: 1.4989 2022/08/30 04:16:33 - mmengine - INFO - Epoch(train) [183][35/63] lr: 6.0360e-03 eta: 1 day, 3:11:52 time: 1.3466 data_time: 0.0344 memory: 16201 loss_prob: 0.8215 loss_thr: 0.4800 loss_db: 0.1349 loss: 1.4364 2022/08/30 04:16:39 - mmengine - INFO - Epoch(train) [183][40/63] lr: 6.0360e-03 eta: 1 day, 3:11:28 time: 1.3729 data_time: 0.0330 memory: 16201 loss_prob: 0.7891 loss_thr: 0.4617 loss_db: 0.1272 loss: 1.3781 2022/08/30 04:16:46 - mmengine - INFO - Epoch(train) [183][45/63] lr: 6.0360e-03 eta: 1 day, 3:11:28 time: 1.3262 data_time: 0.0327 memory: 16201 loss_prob: 0.7243 loss_thr: 0.4531 loss_db: 0.1244 loss: 1.3018 2022/08/30 04:16:54 - mmengine - INFO - Epoch(train) [183][50/63] lr: 6.0360e-03 eta: 1 day, 3:11:07 time: 1.4153 data_time: 0.0420 memory: 16201 loss_prob: 0.8095 loss_thr: 0.4802 loss_db: 0.1370 loss: 1.4266 2022/08/30 04:17:00 - mmengine - INFO - Epoch(train) [183][55/63] lr: 6.0360e-03 eta: 1 day, 3:11:07 time: 1.4207 data_time: 0.0283 memory: 16201 loss_prob: 0.8443 loss_thr: 0.4989 loss_db: 0.1413 loss: 1.4844 2022/08/30 04:17:08 - mmengine - INFO - Epoch(train) [183][60/63] lr: 6.0360e-03 eta: 1 day, 3:10:45 time: 1.4179 data_time: 0.0377 memory: 16201 loss_prob: 0.8452 loss_thr: 0.4833 loss_db: 0.1433 loss: 1.4719 2022/08/30 04:17:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:17:21 - mmengine - INFO - Epoch(train) [184][5/63] lr: 6.0307e-03 eta: 1 day, 3:10:45 time: 1.5811 data_time: 0.2513 memory: 16201 loss_prob: 0.8558 loss_thr: 0.4898 loss_db: 0.1419 loss: 1.4875 2022/08/30 04:17:28 - mmengine - INFO - Epoch(train) [184][10/63] lr: 6.0307e-03 eta: 1 day, 3:10:09 time: 1.6835 data_time: 0.2817 memory: 16201 loss_prob: 0.8659 loss_thr: 0.4898 loss_db: 0.1477 loss: 1.5034 2022/08/30 04:17:35 - mmengine - INFO - Epoch(train) [184][15/63] lr: 6.0307e-03 eta: 1 day, 3:10:09 time: 1.4599 data_time: 0.0526 memory: 16201 loss_prob: 0.8856 loss_thr: 0.4687 loss_db: 0.1446 loss: 1.4988 2022/08/30 04:17:43 - mmengine - INFO - Epoch(train) [184][20/63] lr: 6.0307e-03 eta: 1 day, 3:09:54 time: 1.5393 data_time: 0.0513 memory: 16201 loss_prob: 0.8669 loss_thr: 0.4934 loss_db: 0.1381 loss: 1.4985 2022/08/30 04:17:50 - mmengine - INFO - Epoch(train) [184][25/63] lr: 6.0307e-03 eta: 1 day, 3:09:54 time: 1.5030 data_time: 0.0532 memory: 16201 loss_prob: 0.8611 loss_thr: 0.5214 loss_db: 0.1464 loss: 1.5289 2022/08/30 04:17:58 - mmengine - INFO - Epoch(train) [184][30/63] lr: 6.0307e-03 eta: 1 day, 3:09:34 time: 1.4398 data_time: 0.0399 memory: 16201 loss_prob: 0.8463 loss_thr: 0.5061 loss_db: 0.1428 loss: 1.4952 2022/08/30 04:18:04 - mmengine - INFO - Epoch(train) [184][35/63] lr: 6.0307e-03 eta: 1 day, 3:09:34 time: 1.4245 data_time: 0.0345 memory: 16201 loss_prob: 0.8237 loss_thr: 0.5049 loss_db: 0.1346 loss: 1.4632 2022/08/30 04:18:11 - mmengine - INFO - Epoch(train) [184][40/63] lr: 6.0307e-03 eta: 1 day, 3:09:09 time: 1.3563 data_time: 0.0352 memory: 16201 loss_prob: 0.8120 loss_thr: 0.4908 loss_db: 0.1321 loss: 1.4349 2022/08/30 04:18:19 - mmengine - INFO - Epoch(train) [184][45/63] lr: 6.0307e-03 eta: 1 day, 3:09:09 time: 1.4641 data_time: 0.0384 memory: 16201 loss_prob: 0.7877 loss_thr: 0.4754 loss_db: 0.1294 loss: 1.3924 2022/08/30 04:18:26 - mmengine - INFO - Epoch(train) [184][50/63] lr: 6.0307e-03 eta: 1 day, 3:08:51 time: 1.4682 data_time: 0.0416 memory: 16201 loss_prob: 0.7955 loss_thr: 0.4742 loss_db: 0.1360 loss: 1.4056 2022/08/30 04:18:34 - mmengine - INFO - Epoch(train) [184][55/63] lr: 6.0307e-03 eta: 1 day, 3:08:51 time: 1.4973 data_time: 0.0373 memory: 16201 loss_prob: 0.8166 loss_thr: 0.4825 loss_db: 0.1364 loss: 1.4356 2022/08/30 04:18:41 - mmengine - INFO - Epoch(train) [184][60/63] lr: 6.0307e-03 eta: 1 day, 3:08:33 time: 1.4828 data_time: 0.0313 memory: 16201 loss_prob: 0.7737 loss_thr: 0.4933 loss_db: 0.1277 loss: 1.3947 2022/08/30 04:18:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:18:54 - mmengine - INFO - Epoch(train) [185][5/63] lr: 6.0253e-03 eta: 1 day, 3:08:33 time: 1.5764 data_time: 0.2865 memory: 16201 loss_prob: 0.9085 loss_thr: 0.5057 loss_db: 0.1552 loss: 1.5694 2022/08/30 04:19:01 - mmengine - INFO - Epoch(train) [185][10/63] lr: 6.0253e-03 eta: 1 day, 3:07:58 time: 1.6987 data_time: 0.2848 memory: 16201 loss_prob: 0.8238 loss_thr: 0.4914 loss_db: 0.1391 loss: 1.4543 2022/08/30 04:19:08 - mmengine - INFO - Epoch(train) [185][15/63] lr: 6.0253e-03 eta: 1 day, 3:07:58 time: 1.4780 data_time: 0.0340 memory: 16201 loss_prob: 0.8091 loss_thr: 0.4670 loss_db: 0.1374 loss: 1.4134 2022/08/30 04:19:17 - mmengine - INFO - Epoch(train) [185][20/63] lr: 6.0253e-03 eta: 1 day, 3:07:42 time: 1.5271 data_time: 0.0348 memory: 16201 loss_prob: 0.9044 loss_thr: 0.4838 loss_db: 0.1580 loss: 1.5462 2022/08/30 04:19:24 - mmengine - INFO - Epoch(train) [185][25/63] lr: 6.0253e-03 eta: 1 day, 3:07:42 time: 1.5205 data_time: 0.0378 memory: 16201 loss_prob: 0.9987 loss_thr: 0.5211 loss_db: 0.1672 loss: 1.6870 2022/08/30 04:19:31 - mmengine - INFO - Epoch(train) [185][30/63] lr: 6.0253e-03 eta: 1 day, 3:07:24 time: 1.4693 data_time: 0.0296 memory: 16201 loss_prob: 0.9395 loss_thr: 0.5112 loss_db: 0.1534 loss: 1.6041 2022/08/30 04:19:38 - mmengine - INFO - Epoch(train) [185][35/63] lr: 6.0253e-03 eta: 1 day, 3:07:24 time: 1.4614 data_time: 0.0395 memory: 16201 loss_prob: 0.8919 loss_thr: 0.4821 loss_db: 0.1491 loss: 1.5231 2022/08/30 04:19:45 - mmengine - INFO - Epoch(train) [185][40/63] lr: 6.0253e-03 eta: 1 day, 3:06:59 time: 1.3423 data_time: 0.0326 memory: 16201 loss_prob: 0.8955 loss_thr: 0.4783 loss_db: 0.1482 loss: 1.5220 2022/08/30 04:19:51 - mmengine - INFO - Epoch(train) [185][45/63] lr: 6.0253e-03 eta: 1 day, 3:06:59 time: 1.3159 data_time: 0.0318 memory: 16201 loss_prob: 0.8992 loss_thr: 0.5063 loss_db: 0.1455 loss: 1.5511 2022/08/30 04:19:59 - mmengine - INFO - Epoch(train) [185][50/63] lr: 6.0253e-03 eta: 1 day, 3:06:35 time: 1.3743 data_time: 0.0536 memory: 16201 loss_prob: 0.9101 loss_thr: 0.5252 loss_db: 0.1477 loss: 1.5830 2022/08/30 04:20:05 - mmengine - INFO - Epoch(train) [185][55/63] lr: 6.0253e-03 eta: 1 day, 3:06:35 time: 1.3535 data_time: 0.0380 memory: 16201 loss_prob: 0.8605 loss_thr: 0.4994 loss_db: 0.1426 loss: 1.5024 2022/08/30 04:20:12 - mmengine - INFO - Epoch(train) [185][60/63] lr: 6.0253e-03 eta: 1 day, 3:06:08 time: 1.3195 data_time: 0.0318 memory: 16201 loss_prob: 0.7536 loss_thr: 0.4576 loss_db: 0.1269 loss: 1.3382 2022/08/30 04:20:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:20:24 - mmengine - INFO - Epoch(train) [186][5/63] lr: 6.0200e-03 eta: 1 day, 3:06:08 time: 1.5273 data_time: 0.2330 memory: 16201 loss_prob: 0.8240 loss_thr: 0.4647 loss_db: 0.1367 loss: 1.4253 2022/08/30 04:20:31 - mmengine - INFO - Epoch(train) [186][10/63] lr: 6.0200e-03 eta: 1 day, 3:05:21 time: 1.4864 data_time: 0.2585 memory: 16201 loss_prob: 0.8886 loss_thr: 0.4869 loss_db: 0.1481 loss: 1.5236 2022/08/30 04:20:38 - mmengine - INFO - Epoch(train) [186][15/63] lr: 6.0200e-03 eta: 1 day, 3:05:21 time: 1.3426 data_time: 0.0338 memory: 16201 loss_prob: 0.8362 loss_thr: 0.4761 loss_db: 0.1430 loss: 1.4552 2022/08/30 04:20:44 - mmengine - INFO - Epoch(train) [186][20/63] lr: 6.0200e-03 eta: 1 day, 3:04:59 time: 1.3881 data_time: 0.0256 memory: 16201 loss_prob: 0.8367 loss_thr: 0.4728 loss_db: 0.1419 loss: 1.4514 2022/08/30 04:20:51 - mmengine - INFO - Epoch(train) [186][25/63] lr: 6.0200e-03 eta: 1 day, 3:04:59 time: 1.3580 data_time: 0.0393 memory: 16201 loss_prob: 0.9784 loss_thr: 0.5227 loss_db: 0.1588 loss: 1.6600 2022/08/30 04:20:58 - mmengine - INFO - Epoch(train) [186][30/63] lr: 6.0200e-03 eta: 1 day, 3:04:36 time: 1.4011 data_time: 0.0282 memory: 16201 loss_prob: 0.9256 loss_thr: 0.5218 loss_db: 0.1484 loss: 1.5959 2022/08/30 04:21:05 - mmengine - INFO - Epoch(train) [186][35/63] lr: 6.0200e-03 eta: 1 day, 3:04:36 time: 1.3974 data_time: 0.0280 memory: 16201 loss_prob: 0.8396 loss_thr: 0.4924 loss_db: 0.1391 loss: 1.4710 2022/08/30 04:21:12 - mmengine - INFO - Epoch(train) [186][40/63] lr: 6.0200e-03 eta: 1 day, 3:04:11 time: 1.3404 data_time: 0.0331 memory: 16201 loss_prob: 0.8943 loss_thr: 0.5071 loss_db: 0.1513 loss: 1.5527 2022/08/30 04:21:18 - mmengine - INFO - Epoch(train) [186][45/63] lr: 6.0200e-03 eta: 1 day, 3:04:11 time: 1.2800 data_time: 0.0320 memory: 16201 loss_prob: 0.7999 loss_thr: 0.5000 loss_db: 0.1354 loss: 1.4353 2022/08/30 04:21:25 - mmengine - INFO - Epoch(train) [186][50/63] lr: 6.0200e-03 eta: 1 day, 3:03:43 time: 1.2968 data_time: 0.0361 memory: 16201 loss_prob: 0.7688 loss_thr: 0.4838 loss_db: 0.1288 loss: 1.3814 2022/08/30 04:21:32 - mmengine - INFO - Epoch(train) [186][55/63] lr: 6.0200e-03 eta: 1 day, 3:03:43 time: 1.3398 data_time: 0.0360 memory: 16201 loss_prob: 0.8302 loss_thr: 0.4728 loss_db: 0.1373 loss: 1.4403 2022/08/30 04:21:39 - mmengine - INFO - Epoch(train) [186][60/63] lr: 6.0200e-03 eta: 1 day, 3:03:23 time: 1.4369 data_time: 0.0427 memory: 16201 loss_prob: 0.7778 loss_thr: 0.4708 loss_db: 0.1293 loss: 1.3780 2022/08/30 04:21:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:21:51 - mmengine - INFO - Epoch(train) [187][5/63] lr: 6.0146e-03 eta: 1 day, 3:03:23 time: 1.4945 data_time: 0.2421 memory: 16201 loss_prob: 0.8517 loss_thr: 0.5013 loss_db: 0.1434 loss: 1.4963 2022/08/30 04:21:58 - mmengine - INFO - Epoch(train) [187][10/63] lr: 6.0146e-03 eta: 1 day, 3:02:43 time: 1.6009 data_time: 0.2580 memory: 16201 loss_prob: 0.9407 loss_thr: 0.5234 loss_db: 0.1533 loss: 1.6173 2022/08/30 04:22:05 - mmengine - INFO - Epoch(train) [187][15/63] lr: 6.0146e-03 eta: 1 day, 3:02:43 time: 1.3885 data_time: 0.0357 memory: 16201 loss_prob: 0.8951 loss_thr: 0.5279 loss_db: 0.1490 loss: 1.5720 2022/08/30 04:22:12 - mmengine - INFO - Epoch(train) [187][20/63] lr: 6.0146e-03 eta: 1 day, 3:02:18 time: 1.3499 data_time: 0.0262 memory: 16201 loss_prob: 0.7761 loss_thr: 0.4811 loss_db: 0.1333 loss: 1.3905 2022/08/30 04:22:18 - mmengine - INFO - Epoch(train) [187][25/63] lr: 6.0146e-03 eta: 1 day, 3:02:18 time: 1.3358 data_time: 0.0290 memory: 16201 loss_prob: 0.7845 loss_thr: 0.4660 loss_db: 0.1308 loss: 1.3813 2022/08/30 04:22:25 - mmengine - INFO - Epoch(train) [187][30/63] lr: 6.0146e-03 eta: 1 day, 3:01:52 time: 1.3203 data_time: 0.0317 memory: 16201 loss_prob: 0.8373 loss_thr: 0.4905 loss_db: 0.1407 loss: 1.4684 2022/08/30 04:22:31 - mmengine - INFO - Epoch(train) [187][35/63] lr: 6.0146e-03 eta: 1 day, 3:01:52 time: 1.2657 data_time: 0.0379 memory: 16201 loss_prob: 0.8265 loss_thr: 0.4924 loss_db: 0.1359 loss: 1.4548 2022/08/30 04:22:38 - mmengine - INFO - Epoch(train) [187][40/63] lr: 6.0146e-03 eta: 1 day, 3:01:27 time: 1.3505 data_time: 0.0252 memory: 16201 loss_prob: 0.8462 loss_thr: 0.5111 loss_db: 0.1407 loss: 1.4979 2022/08/30 04:22:45 - mmengine - INFO - Epoch(train) [187][45/63] lr: 6.0146e-03 eta: 1 day, 3:01:27 time: 1.3992 data_time: 0.0311 memory: 16201 loss_prob: 1.3210 loss_thr: 0.5494 loss_db: 0.2004 loss: 2.0709 2022/08/30 04:22:52 - mmengine - INFO - Epoch(train) [187][50/63] lr: 6.0146e-03 eta: 1 day, 3:01:01 time: 1.3277 data_time: 0.0472 memory: 16201 loss_prob: 1.4075 loss_thr: 0.5355 loss_db: 0.2106 loss: 2.1536 2022/08/30 04:22:58 - mmengine - INFO - Epoch(train) [187][55/63] lr: 6.0146e-03 eta: 1 day, 3:01:01 time: 1.3028 data_time: 0.0322 memory: 16201 loss_prob: 1.0310 loss_thr: 0.4957 loss_db: 0.1616 loss: 1.6883 2022/08/30 04:23:05 - mmengine - INFO - Epoch(train) [187][60/63] lr: 6.0146e-03 eta: 1 day, 3:00:33 time: 1.2921 data_time: 0.0369 memory: 16201 loss_prob: 0.9339 loss_thr: 0.5001 loss_db: 0.1431 loss: 1.5772 2022/08/30 04:23:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:23:16 - mmengine - INFO - Epoch(train) [188][5/63] lr: 6.0093e-03 eta: 1 day, 3:00:33 time: 1.4182 data_time: 0.2199 memory: 16201 loss_prob: 0.8202 loss_thr: 0.5072 loss_db: 0.1399 loss: 1.4672 2022/08/30 04:23:24 - mmengine - INFO - Epoch(train) [188][10/63] lr: 6.0093e-03 eta: 1 day, 2:59:53 time: 1.6015 data_time: 0.2447 memory: 16201 loss_prob: 0.8463 loss_thr: 0.4891 loss_db: 0.1408 loss: 1.4762 2022/08/30 04:23:30 - mmengine - INFO - Epoch(train) [188][15/63] lr: 6.0093e-03 eta: 1 day, 2:59:53 time: 1.3333 data_time: 0.0388 memory: 16201 loss_prob: 0.9342 loss_thr: 0.5248 loss_db: 0.1521 loss: 1.6111 2022/08/30 04:23:36 - mmengine - INFO - Epoch(train) [188][20/63] lr: 6.0093e-03 eta: 1 day, 2:59:24 time: 1.2712 data_time: 0.0310 memory: 16201 loss_prob: 0.9164 loss_thr: 0.5315 loss_db: 0.1496 loss: 1.5974 2022/08/30 04:23:43 - mmengine - INFO - Epoch(train) [188][25/63] lr: 6.0093e-03 eta: 1 day, 2:59:24 time: 1.3050 data_time: 0.0378 memory: 16201 loss_prob: 0.7744 loss_thr: 0.4690 loss_db: 0.1292 loss: 1.3726 2022/08/30 04:23:49 - mmengine - INFO - Epoch(train) [188][30/63] lr: 6.0093e-03 eta: 1 day, 2:58:56 time: 1.2789 data_time: 0.0325 memory: 16201 loss_prob: 0.7272 loss_thr: 0.4443 loss_db: 0.1226 loss: 1.2941 2022/08/30 04:23:56 - mmengine - INFO - Epoch(train) [188][35/63] lr: 6.0093e-03 eta: 1 day, 2:58:56 time: 1.3406 data_time: 0.0315 memory: 16201 loss_prob: 0.8140 loss_thr: 0.4834 loss_db: 0.1367 loss: 1.4341 2022/08/30 04:24:02 - mmengine - INFO - Epoch(train) [188][40/63] lr: 6.0093e-03 eta: 1 day, 2:58:31 time: 1.3409 data_time: 0.0305 memory: 16201 loss_prob: 0.7977 loss_thr: 0.4604 loss_db: 0.1342 loss: 1.3923 2022/08/30 04:24:09 - mmengine - INFO - Epoch(train) [188][45/63] lr: 6.0093e-03 eta: 1 day, 2:58:31 time: 1.3114 data_time: 0.0334 memory: 16201 loss_prob: 0.8102 loss_thr: 0.4564 loss_db: 0.1365 loss: 1.4031 2022/08/30 04:24:16 - mmengine - INFO - Epoch(train) [188][50/63] lr: 6.0093e-03 eta: 1 day, 2:58:07 time: 1.3712 data_time: 0.0403 memory: 16201 loss_prob: 0.8385 loss_thr: 0.4912 loss_db: 0.1414 loss: 1.4711 2022/08/30 04:24:22 - mmengine - INFO - Epoch(train) [188][55/63] lr: 6.0093e-03 eta: 1 day, 2:58:07 time: 1.2902 data_time: 0.0344 memory: 16201 loss_prob: 0.8371 loss_thr: 0.4871 loss_db: 0.1399 loss: 1.4641 2022/08/30 04:24:28 - mmengine - INFO - Epoch(train) [188][60/63] lr: 6.0093e-03 eta: 1 day, 2:57:35 time: 1.1990 data_time: 0.0290 memory: 16201 loss_prob: 0.8450 loss_thr: 0.4946 loss_db: 0.1387 loss: 1.4784 2022/08/30 04:24:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:24:41 - mmengine - INFO - Epoch(train) [189][5/63] lr: 6.0040e-03 eta: 1 day, 2:57:35 time: 1.4759 data_time: 0.2175 memory: 16201 loss_prob: 0.7777 loss_thr: 0.4808 loss_db: 0.1274 loss: 1.3859 2022/08/30 04:24:48 - mmengine - INFO - Epoch(train) [189][10/63] lr: 6.0040e-03 eta: 1 day, 2:56:56 time: 1.6327 data_time: 0.2307 memory: 16201 loss_prob: 0.8516 loss_thr: 0.5130 loss_db: 0.1439 loss: 1.5084 2022/08/30 04:24:54 - mmengine - INFO - Epoch(train) [189][15/63] lr: 6.0040e-03 eta: 1 day, 2:56:56 time: 1.3668 data_time: 0.0392 memory: 16201 loss_prob: 0.9162 loss_thr: 0.5450 loss_db: 0.1554 loss: 1.6166 2022/08/30 04:25:01 - mmengine - INFO - Epoch(train) [189][20/63] lr: 6.0040e-03 eta: 1 day, 2:56:31 time: 1.3408 data_time: 0.0706 memory: 16201 loss_prob: 0.9031 loss_thr: 0.5243 loss_db: 0.1510 loss: 1.5784 2022/08/30 04:25:08 - mmengine - INFO - Epoch(train) [189][25/63] lr: 6.0040e-03 eta: 1 day, 2:56:31 time: 1.3939 data_time: 0.0656 memory: 16201 loss_prob: 0.8447 loss_thr: 0.4965 loss_db: 0.1409 loss: 1.4820 2022/08/30 04:25:15 - mmengine - INFO - Epoch(train) [189][30/63] lr: 6.0040e-03 eta: 1 day, 2:56:07 time: 1.3545 data_time: 0.0289 memory: 16201 loss_prob: 0.8368 loss_thr: 0.4740 loss_db: 0.1377 loss: 1.4485 2022/08/30 04:25:22 - mmengine - INFO - Epoch(train) [189][35/63] lr: 6.0040e-03 eta: 1 day, 2:56:07 time: 1.3680 data_time: 0.0313 memory: 16201 loss_prob: 0.8588 loss_thr: 0.4796 loss_db: 0.1412 loss: 1.4796 2022/08/30 04:25:29 - mmengine - INFO - Epoch(train) [189][40/63] lr: 6.0040e-03 eta: 1 day, 2:55:45 time: 1.3938 data_time: 0.0304 memory: 16201 loss_prob: 0.8750 loss_thr: 0.5148 loss_db: 0.1442 loss: 1.5340 2022/08/30 04:25:36 - mmengine - INFO - Epoch(train) [189][45/63] lr: 6.0040e-03 eta: 1 day, 2:55:45 time: 1.4097 data_time: 0.0306 memory: 16201 loss_prob: 0.9232 loss_thr: 0.5334 loss_db: 0.1562 loss: 1.6128 2022/08/30 04:25:43 - mmengine - INFO - Epoch(train) [189][50/63] lr: 6.0040e-03 eta: 1 day, 2:55:27 time: 1.4596 data_time: 0.0382 memory: 16201 loss_prob: 0.8736 loss_thr: 0.5143 loss_db: 0.1511 loss: 1.5390 2022/08/30 04:25:49 - mmengine - INFO - Epoch(train) [189][55/63] lr: 6.0040e-03 eta: 1 day, 2:55:27 time: 1.3405 data_time: 0.0341 memory: 16201 loss_prob: 0.8542 loss_thr: 0.5021 loss_db: 0.1466 loss: 1.5029 2022/08/30 04:25:56 - mmengine - INFO - Epoch(train) [189][60/63] lr: 6.0040e-03 eta: 1 day, 2:54:56 time: 1.2276 data_time: 0.0339 memory: 16201 loss_prob: 0.9346 loss_thr: 0.5244 loss_db: 0.1595 loss: 1.6186 2022/08/30 04:25:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:26:07 - mmengine - INFO - Epoch(train) [190][5/63] lr: 5.9986e-03 eta: 1 day, 2:54:56 time: 1.4334 data_time: 0.2400 memory: 16201 loss_prob: 0.9921 loss_thr: 0.5697 loss_db: 0.1689 loss: 1.7307 2022/08/30 04:26:14 - mmengine - INFO - Epoch(train) [190][10/63] lr: 5.9986e-03 eta: 1 day, 2:54:13 time: 1.5518 data_time: 0.2427 memory: 16201 loss_prob: 1.0081 loss_thr: 0.5528 loss_db: 0.1697 loss: 1.7306 2022/08/30 04:26:20 - mmengine - INFO - Epoch(train) [190][15/63] lr: 5.9986e-03 eta: 1 day, 2:54:13 time: 1.2794 data_time: 0.0361 memory: 16201 loss_prob: 1.1281 loss_thr: 0.5425 loss_db: 0.1825 loss: 1.8531 2022/08/30 04:26:28 - mmengine - INFO - Epoch(train) [190][20/63] lr: 5.9986e-03 eta: 1 day, 2:53:49 time: 1.3503 data_time: 0.0342 memory: 16201 loss_prob: 1.1216 loss_thr: 0.5505 loss_db: 0.1835 loss: 1.8555 2022/08/30 04:26:35 - mmengine - INFO - Epoch(train) [190][25/63] lr: 5.9986e-03 eta: 1 day, 2:53:49 time: 1.4541 data_time: 0.0358 memory: 16201 loss_prob: 1.1316 loss_thr: 0.5710 loss_db: 0.1918 loss: 1.8944 2022/08/30 04:26:41 - mmengine - INFO - Epoch(train) [190][30/63] lr: 5.9986e-03 eta: 1 day, 2:53:25 time: 1.3631 data_time: 0.0431 memory: 16201 loss_prob: 1.0957 loss_thr: 0.5652 loss_db: 0.1850 loss: 1.8459 2022/08/30 04:26:47 - mmengine - INFO - Epoch(train) [190][35/63] lr: 5.9986e-03 eta: 1 day, 2:53:25 time: 1.2615 data_time: 0.0399 memory: 16201 loss_prob: 0.9726 loss_thr: 0.5400 loss_db: 0.1585 loss: 1.6710 2022/08/30 04:26:54 - mmengine - INFO - Epoch(train) [190][40/63] lr: 5.9986e-03 eta: 1 day, 2:52:56 time: 1.2572 data_time: 0.0309 memory: 16201 loss_prob: 0.9728 loss_thr: 0.5077 loss_db: 0.1526 loss: 1.6331 2022/08/30 04:27:00 - mmengine - INFO - Epoch(train) [190][45/63] lr: 5.9986e-03 eta: 1 day, 2:52:56 time: 1.2804 data_time: 0.0378 memory: 16201 loss_prob: 1.0426 loss_thr: 0.5101 loss_db: 0.1586 loss: 1.7112 2022/08/30 04:27:07 - mmengine - INFO - Epoch(train) [190][50/63] lr: 5.9986e-03 eta: 1 day, 2:52:29 time: 1.3027 data_time: 0.0411 memory: 16201 loss_prob: 1.0123 loss_thr: 0.5231 loss_db: 0.1597 loss: 1.6951 2022/08/30 04:27:14 - mmengine - INFO - Epoch(train) [190][55/63] lr: 5.9986e-03 eta: 1 day, 2:52:29 time: 1.3259 data_time: 0.0282 memory: 16201 loss_prob: 0.8907 loss_thr: 0.5173 loss_db: 0.1523 loss: 1.5603 2022/08/30 04:27:21 - mmengine - INFO - Epoch(train) [190][60/63] lr: 5.9986e-03 eta: 1 day, 2:52:10 time: 1.4472 data_time: 0.0480 memory: 16201 loss_prob: 0.8733 loss_thr: 0.5173 loss_db: 0.1501 loss: 1.5407 2022/08/30 04:27:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:27:34 - mmengine - INFO - Epoch(train) [191][5/63] lr: 5.9933e-03 eta: 1 day, 2:52:10 time: 1.5677 data_time: 0.2325 memory: 16201 loss_prob: 0.9605 loss_thr: 0.5587 loss_db: 0.1631 loss: 1.6822 2022/08/30 04:27:42 - mmengine - INFO - Epoch(train) [191][10/63] lr: 5.9933e-03 eta: 1 day, 2:51:37 time: 1.7268 data_time: 0.2455 memory: 16201 loss_prob: 0.9149 loss_thr: 0.5230 loss_db: 0.1538 loss: 1.5918 2022/08/30 04:27:49 - mmengine - INFO - Epoch(train) [191][15/63] lr: 5.9933e-03 eta: 1 day, 2:51:37 time: 1.4524 data_time: 0.0326 memory: 16201 loss_prob: 0.8992 loss_thr: 0.5074 loss_db: 0.1502 loss: 1.5568 2022/08/30 04:27:55 - mmengine - INFO - Epoch(train) [191][20/63] lr: 5.9933e-03 eta: 1 day, 2:51:13 time: 1.3610 data_time: 0.0314 memory: 16201 loss_prob: 0.9140 loss_thr: 0.5106 loss_db: 0.1512 loss: 1.5757 2022/08/30 04:28:04 - mmengine - INFO - Epoch(train) [191][25/63] lr: 5.9933e-03 eta: 1 day, 2:51:13 time: 1.4871 data_time: 0.0415 memory: 16201 loss_prob: 0.8626 loss_thr: 0.4928 loss_db: 0.1417 loss: 1.4970 2022/08/30 04:28:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:28:10 - mmengine - INFO - Epoch(train) [191][30/63] lr: 5.9933e-03 eta: 1 day, 2:50:56 time: 1.4697 data_time: 0.0303 memory: 16201 loss_prob: 0.8760 loss_thr: 0.5019 loss_db: 0.1452 loss: 1.5231 2022/08/30 04:28:17 - mmengine - INFO - Epoch(train) [191][35/63] lr: 5.9933e-03 eta: 1 day, 2:50:56 time: 1.3091 data_time: 0.0288 memory: 16201 loss_prob: 0.8704 loss_thr: 0.5124 loss_db: 0.1458 loss: 1.5285 2022/08/30 04:28:24 - mmengine - INFO - Epoch(train) [191][40/63] lr: 5.9933e-03 eta: 1 day, 2:50:33 time: 1.3797 data_time: 0.0299 memory: 16201 loss_prob: 0.8510 loss_thr: 0.4939 loss_db: 0.1427 loss: 1.4876 2022/08/30 04:28:30 - mmengine - INFO - Epoch(train) [191][45/63] lr: 5.9933e-03 eta: 1 day, 2:50:33 time: 1.2983 data_time: 0.0319 memory: 16201 loss_prob: 0.8898 loss_thr: 0.5091 loss_db: 0.1530 loss: 1.5519 2022/08/30 04:28:37 - mmengine - INFO - Epoch(train) [191][50/63] lr: 5.9933e-03 eta: 1 day, 2:50:05 time: 1.2818 data_time: 0.0424 memory: 16201 loss_prob: 0.9052 loss_thr: 0.5342 loss_db: 0.1520 loss: 1.5914 2022/08/30 04:28:44 - mmengine - INFO - Epoch(train) [191][55/63] lr: 5.9933e-03 eta: 1 day, 2:50:05 time: 1.4043 data_time: 0.0319 memory: 16201 loss_prob: 0.8946 loss_thr: 0.5297 loss_db: 0.1461 loss: 1.5704 2022/08/30 04:28:50 - mmengine - INFO - Epoch(train) [191][60/63] lr: 5.9933e-03 eta: 1 day, 2:49:40 time: 1.3342 data_time: 0.0338 memory: 16201 loss_prob: 0.8397 loss_thr: 0.5001 loss_db: 0.1415 loss: 1.4813 2022/08/30 04:28:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:29:02 - mmengine - INFO - Epoch(train) [192][5/63] lr: 5.9879e-03 eta: 1 day, 2:49:40 time: 1.4280 data_time: 0.2114 memory: 16201 loss_prob: 0.8070 loss_thr: 0.4996 loss_db: 0.1378 loss: 1.4444 2022/08/30 04:29:09 - mmengine - INFO - Epoch(train) [192][10/63] lr: 5.9879e-03 eta: 1 day, 2:48:57 time: 1.5280 data_time: 0.2246 memory: 16201 loss_prob: 0.7984 loss_thr: 0.5018 loss_db: 0.1334 loss: 1.4336 2022/08/30 04:29:15 - mmengine - INFO - Epoch(train) [192][15/63] lr: 5.9879e-03 eta: 1 day, 2:48:57 time: 1.3473 data_time: 0.0321 memory: 16201 loss_prob: 0.7929 loss_thr: 0.4970 loss_db: 0.1313 loss: 1.4211 2022/08/30 04:29:21 - mmengine - INFO - Epoch(train) [192][20/63] lr: 5.9879e-03 eta: 1 day, 2:48:28 time: 1.2614 data_time: 0.0429 memory: 16201 loss_prob: 0.8078 loss_thr: 0.4898 loss_db: 0.1372 loss: 1.4347 2022/08/30 04:29:28 - mmengine - INFO - Epoch(train) [192][25/63] lr: 5.9879e-03 eta: 1 day, 2:48:28 time: 1.2987 data_time: 0.0434 memory: 16201 loss_prob: 0.8294 loss_thr: 0.4950 loss_db: 0.1375 loss: 1.4619 2022/08/30 04:29:35 - mmengine - INFO - Epoch(train) [192][30/63] lr: 5.9879e-03 eta: 1 day, 2:48:05 time: 1.3708 data_time: 0.0343 memory: 16201 loss_prob: 0.8402 loss_thr: 0.4916 loss_db: 0.1373 loss: 1.4692 2022/08/30 04:29:42 - mmengine - INFO - Epoch(train) [192][35/63] lr: 5.9879e-03 eta: 1 day, 2:48:05 time: 1.3768 data_time: 0.0309 memory: 16201 loss_prob: 0.8526 loss_thr: 0.4919 loss_db: 0.1431 loss: 1.4875 2022/08/30 04:29:49 - mmengine - INFO - Epoch(train) [192][40/63] lr: 5.9879e-03 eta: 1 day, 2:47:45 time: 1.4244 data_time: 0.0305 memory: 16201 loss_prob: 0.8263 loss_thr: 0.5032 loss_db: 0.1388 loss: 1.4682 2022/08/30 04:29:56 - mmengine - INFO - Epoch(train) [192][45/63] lr: 5.9879e-03 eta: 1 day, 2:47:45 time: 1.3803 data_time: 0.0381 memory: 16201 loss_prob: 0.8723 loss_thr: 0.5131 loss_db: 0.1448 loss: 1.5302 2022/08/30 04:30:02 - mmengine - INFO - Epoch(train) [192][50/63] lr: 5.9879e-03 eta: 1 day, 2:47:19 time: 1.3077 data_time: 0.0384 memory: 16201 loss_prob: 0.9973 loss_thr: 0.5387 loss_db: 0.1590 loss: 1.6951 2022/08/30 04:30:10 - mmengine - INFO - Epoch(train) [192][55/63] lr: 5.9879e-03 eta: 1 day, 2:47:19 time: 1.4075 data_time: 0.0321 memory: 16201 loss_prob: 0.9306 loss_thr: 0.5332 loss_db: 0.1506 loss: 1.6144 2022/08/30 04:30:18 - mmengine - INFO - Epoch(train) [192][60/63] lr: 5.9879e-03 eta: 1 day, 2:47:04 time: 1.5279 data_time: 0.0581 memory: 16201 loss_prob: 0.7774 loss_thr: 0.4796 loss_db: 0.1322 loss: 1.3891 2022/08/30 04:30:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:30:30 - mmengine - INFO - Epoch(train) [193][5/63] lr: 5.9826e-03 eta: 1 day, 2:47:04 time: 1.6115 data_time: 0.2418 memory: 16201 loss_prob: 0.9029 loss_thr: 0.5341 loss_db: 0.1497 loss: 1.5867 2022/08/30 04:30:37 - mmengine - INFO - Epoch(train) [193][10/63] lr: 5.9826e-03 eta: 1 day, 2:46:23 time: 1.5604 data_time: 0.2507 memory: 16201 loss_prob: 0.9395 loss_thr: 0.5421 loss_db: 0.1521 loss: 1.6336 2022/08/30 04:30:44 - mmengine - INFO - Epoch(train) [193][15/63] lr: 5.9826e-03 eta: 1 day, 2:46:23 time: 1.4030 data_time: 0.0360 memory: 16201 loss_prob: 0.9213 loss_thr: 0.5301 loss_db: 0.1519 loss: 1.6034 2022/08/30 04:30:51 - mmengine - INFO - Epoch(train) [193][20/63] lr: 5.9826e-03 eta: 1 day, 2:46:03 time: 1.4370 data_time: 0.0310 memory: 16201 loss_prob: 0.8150 loss_thr: 0.4874 loss_db: 0.1371 loss: 1.4395 2022/08/30 04:30:58 - mmengine - INFO - Epoch(train) [193][25/63] lr: 5.9826e-03 eta: 1 day, 2:46:03 time: 1.3352 data_time: 0.0435 memory: 16201 loss_prob: 0.7652 loss_thr: 0.4519 loss_db: 0.1275 loss: 1.3446 2022/08/30 04:31:05 - mmengine - INFO - Epoch(train) [193][30/63] lr: 5.9826e-03 eta: 1 day, 2:45:39 time: 1.3465 data_time: 0.0321 memory: 16201 loss_prob: 0.8164 loss_thr: 0.4856 loss_db: 0.1390 loss: 1.4409 2022/08/30 04:31:11 - mmengine - INFO - Epoch(train) [193][35/63] lr: 5.9826e-03 eta: 1 day, 2:45:39 time: 1.3387 data_time: 0.0289 memory: 16201 loss_prob: 0.8586 loss_thr: 0.4972 loss_db: 0.1452 loss: 1.5010 2022/08/30 04:31:18 - mmengine - INFO - Epoch(train) [193][40/63] lr: 5.9826e-03 eta: 1 day, 2:45:13 time: 1.3000 data_time: 0.0349 memory: 16201 loss_prob: 0.8650 loss_thr: 0.4895 loss_db: 0.1420 loss: 1.4964 2022/08/30 04:31:24 - mmengine - INFO - Epoch(train) [193][45/63] lr: 5.9826e-03 eta: 1 day, 2:45:13 time: 1.3050 data_time: 0.0311 memory: 16201 loss_prob: 0.8026 loss_thr: 0.4828 loss_db: 0.1341 loss: 1.4195 2022/08/30 04:31:31 - mmengine - INFO - Epoch(train) [193][50/63] lr: 5.9826e-03 eta: 1 day, 2:44:49 time: 1.3509 data_time: 0.0372 memory: 16201 loss_prob: 0.7821 loss_thr: 0.4789 loss_db: 0.1342 loss: 1.3951 2022/08/30 04:31:38 - mmengine - INFO - Epoch(train) [193][55/63] lr: 5.9826e-03 eta: 1 day, 2:44:49 time: 1.3708 data_time: 0.0302 memory: 16201 loss_prob: 0.8349 loss_thr: 0.4810 loss_db: 0.1383 loss: 1.4542 2022/08/30 04:31:44 - mmengine - INFO - Epoch(train) [193][60/63] lr: 5.9826e-03 eta: 1 day, 2:44:21 time: 1.2803 data_time: 0.0275 memory: 16201 loss_prob: 0.8009 loss_thr: 0.4793 loss_db: 0.1333 loss: 1.4136 2022/08/30 04:31:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:31:57 - mmengine - INFO - Epoch(train) [194][5/63] lr: 5.9772e-03 eta: 1 day, 2:44:21 time: 1.5763 data_time: 0.2332 memory: 16201 loss_prob: 0.8849 loss_thr: 0.5155 loss_db: 0.1476 loss: 1.5479 2022/08/30 04:32:04 - mmengine - INFO - Epoch(train) [194][10/63] lr: 5.9772e-03 eta: 1 day, 2:43:42 time: 1.6066 data_time: 0.2500 memory: 16201 loss_prob: 0.8895 loss_thr: 0.5250 loss_db: 0.1491 loss: 1.5637 2022/08/30 04:32:11 - mmengine - INFO - Epoch(train) [194][15/63] lr: 5.9772e-03 eta: 1 day, 2:43:42 time: 1.3090 data_time: 0.0318 memory: 16201 loss_prob: 0.8718 loss_thr: 0.5262 loss_db: 0.1472 loss: 1.5452 2022/08/30 04:32:17 - mmengine - INFO - Epoch(train) [194][20/63] lr: 5.9772e-03 eta: 1 day, 2:43:13 time: 1.2545 data_time: 0.0324 memory: 16201 loss_prob: 0.8342 loss_thr: 0.5268 loss_db: 0.1408 loss: 1.5019 2022/08/30 04:32:23 - mmengine - INFO - Epoch(train) [194][25/63] lr: 5.9772e-03 eta: 1 day, 2:43:13 time: 1.2348 data_time: 0.0375 memory: 16201 loss_prob: 0.8222 loss_thr: 0.5138 loss_db: 0.1380 loss: 1.4741 2022/08/30 04:32:31 - mmengine - INFO - Epoch(train) [194][30/63] lr: 5.9772e-03 eta: 1 day, 2:42:52 time: 1.4026 data_time: 0.0299 memory: 16201 loss_prob: 0.8563 loss_thr: 0.5170 loss_db: 0.1450 loss: 1.5183 2022/08/30 04:32:37 - mmengine - INFO - Epoch(train) [194][35/63] lr: 5.9772e-03 eta: 1 day, 2:42:52 time: 1.3592 data_time: 0.0385 memory: 16201 loss_prob: 0.8624 loss_thr: 0.5261 loss_db: 0.1432 loss: 1.5318 2022/08/30 04:32:43 - mmengine - INFO - Epoch(train) [194][40/63] lr: 5.9772e-03 eta: 1 day, 2:42:23 time: 1.2433 data_time: 0.0341 memory: 16201 loss_prob: 0.7962 loss_thr: 0.4929 loss_db: 0.1339 loss: 1.4231 2022/08/30 04:32:50 - mmengine - INFO - Epoch(train) [194][45/63] lr: 5.9772e-03 eta: 1 day, 2:42:23 time: 1.3464 data_time: 0.0302 memory: 16201 loss_prob: 0.8184 loss_thr: 0.4867 loss_db: 0.1402 loss: 1.4453 2022/08/30 04:32:56 - mmengine - INFO - Epoch(train) [194][50/63] lr: 5.9772e-03 eta: 1 day, 2:41:59 time: 1.3421 data_time: 0.0373 memory: 16201 loss_prob: 0.8400 loss_thr: 0.4942 loss_db: 0.1423 loss: 1.4765 2022/08/30 04:33:03 - mmengine - INFO - Epoch(train) [194][55/63] lr: 5.9772e-03 eta: 1 day, 2:41:59 time: 1.2667 data_time: 0.0308 memory: 16201 loss_prob: 0.7629 loss_thr: 0.4727 loss_db: 0.1268 loss: 1.3623 2022/08/30 04:33:10 - mmengine - INFO - Epoch(train) [194][60/63] lr: 5.9772e-03 eta: 1 day, 2:41:33 time: 1.3180 data_time: 0.0447 memory: 16201 loss_prob: 0.7254 loss_thr: 0.4625 loss_db: 0.1220 loss: 1.3099 2022/08/30 04:33:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:33:22 - mmengine - INFO - Epoch(train) [195][5/63] lr: 5.9719e-03 eta: 1 day, 2:41:33 time: 1.5239 data_time: 0.2392 memory: 16201 loss_prob: 0.8074 loss_thr: 0.4903 loss_db: 0.1353 loss: 1.4331 2022/08/30 04:33:28 - mmengine - INFO - Epoch(train) [195][10/63] lr: 5.9719e-03 eta: 1 day, 2:40:51 time: 1.5361 data_time: 0.2414 memory: 16201 loss_prob: 0.7744 loss_thr: 0.4713 loss_db: 0.1285 loss: 1.3741 2022/08/30 04:33:35 - mmengine - INFO - Epoch(train) [195][15/63] lr: 5.9719e-03 eta: 1 day, 2:40:51 time: 1.2938 data_time: 0.0315 memory: 16201 loss_prob: 0.7636 loss_thr: 0.4674 loss_db: 0.1291 loss: 1.3601 2022/08/30 04:33:41 - mmengine - INFO - Epoch(train) [195][20/63] lr: 5.9719e-03 eta: 1 day, 2:40:21 time: 1.2322 data_time: 0.0241 memory: 16201 loss_prob: 0.8219 loss_thr: 0.4765 loss_db: 0.1395 loss: 1.4380 2022/08/30 04:33:48 - mmengine - INFO - Epoch(train) [195][25/63] lr: 5.9719e-03 eta: 1 day, 2:40:21 time: 1.2820 data_time: 0.0344 memory: 16201 loss_prob: 0.8487 loss_thr: 0.4837 loss_db: 0.1443 loss: 1.4767 2022/08/30 04:33:54 - mmengine - INFO - Epoch(train) [195][30/63] lr: 5.9719e-03 eta: 1 day, 2:39:55 time: 1.3052 data_time: 0.0340 memory: 16201 loss_prob: 0.8708 loss_thr: 0.4879 loss_db: 0.1469 loss: 1.5056 2022/08/30 04:34:00 - mmengine - INFO - Epoch(train) [195][35/63] lr: 5.9719e-03 eta: 1 day, 2:39:55 time: 1.2854 data_time: 0.0344 memory: 16201 loss_prob: 0.8696 loss_thr: 0.4910 loss_db: 0.1448 loss: 1.5054 2022/08/30 04:34:07 - mmengine - INFO - Epoch(train) [195][40/63] lr: 5.9719e-03 eta: 1 day, 2:39:31 time: 1.3421 data_time: 0.0412 memory: 16201 loss_prob: 0.8127 loss_thr: 0.4909 loss_db: 0.1340 loss: 1.4377 2022/08/30 04:34:14 - mmengine - INFO - Epoch(train) [195][45/63] lr: 5.9719e-03 eta: 1 day, 2:39:31 time: 1.3838 data_time: 0.0407 memory: 16201 loss_prob: 0.7821 loss_thr: 0.4656 loss_db: 0.1294 loss: 1.3771 2022/08/30 04:34:21 - mmengine - INFO - Epoch(train) [195][50/63] lr: 5.9719e-03 eta: 1 day, 2:39:07 time: 1.3351 data_time: 0.0420 memory: 16201 loss_prob: 0.8009 loss_thr: 0.4717 loss_db: 0.1321 loss: 1.4048 2022/08/30 04:34:28 - mmengine - INFO - Epoch(train) [195][55/63] lr: 5.9719e-03 eta: 1 day, 2:39:07 time: 1.3209 data_time: 0.0296 memory: 16201 loss_prob: 0.8485 loss_thr: 0.5061 loss_db: 0.1420 loss: 1.4967 2022/08/30 04:34:35 - mmengine - INFO - Epoch(train) [195][60/63] lr: 5.9719e-03 eta: 1 day, 2:38:45 time: 1.3940 data_time: 0.0408 memory: 16201 loss_prob: 0.8099 loss_thr: 0.4843 loss_db: 0.1368 loss: 1.4311 2022/08/30 04:34:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:34:47 - mmengine - INFO - Epoch(train) [196][5/63] lr: 5.9665e-03 eta: 1 day, 2:38:45 time: 1.4534 data_time: 0.2165 memory: 16201 loss_prob: 0.8132 loss_thr: 0.4841 loss_db: 0.1363 loss: 1.4336 2022/08/30 04:34:53 - mmengine - INFO - Epoch(train) [196][10/63] lr: 5.9665e-03 eta: 1 day, 2:38:04 time: 1.5499 data_time: 0.2356 memory: 16201 loss_prob: 0.8349 loss_thr: 0.4635 loss_db: 0.1343 loss: 1.4327 2022/08/30 04:35:00 - mmengine - INFO - Epoch(train) [196][15/63] lr: 5.9665e-03 eta: 1 day, 2:38:04 time: 1.3524 data_time: 0.0321 memory: 16201 loss_prob: 0.8460 loss_thr: 0.4683 loss_db: 0.1365 loss: 1.4508 2022/08/30 04:35:07 - mmengine - INFO - Epoch(train) [196][20/63] lr: 5.9665e-03 eta: 1 day, 2:37:41 time: 1.3585 data_time: 0.0308 memory: 16201 loss_prob: 0.9238 loss_thr: 0.5020 loss_db: 0.1533 loss: 1.5792 2022/08/30 04:35:14 - mmengine - INFO - Epoch(train) [196][25/63] lr: 5.9665e-03 eta: 1 day, 2:37:41 time: 1.4032 data_time: 0.0364 memory: 16201 loss_prob: 0.9244 loss_thr: 0.4973 loss_db: 0.1551 loss: 1.5768 2022/08/30 04:35:21 - mmengine - INFO - Epoch(train) [196][30/63] lr: 5.9665e-03 eta: 1 day, 2:37:19 time: 1.3793 data_time: 0.0298 memory: 16201 loss_prob: 0.8168 loss_thr: 0.4607 loss_db: 0.1398 loss: 1.4173 2022/08/30 04:35:28 - mmengine - INFO - Epoch(train) [196][35/63] lr: 5.9665e-03 eta: 1 day, 2:37:19 time: 1.3927 data_time: 0.0359 memory: 16201 loss_prob: 0.7622 loss_thr: 0.4386 loss_db: 0.1265 loss: 1.3274 2022/08/30 04:35:35 - mmengine - INFO - Epoch(train) [196][40/63] lr: 5.9665e-03 eta: 1 day, 2:36:58 time: 1.4077 data_time: 0.0294 memory: 16201 loss_prob: 0.7834 loss_thr: 0.4680 loss_db: 0.1318 loss: 1.3832 2022/08/30 04:35:42 - mmengine - INFO - Epoch(train) [196][45/63] lr: 5.9665e-03 eta: 1 day, 2:36:58 time: 1.3845 data_time: 0.0317 memory: 16201 loss_prob: 0.8044 loss_thr: 0.4864 loss_db: 0.1360 loss: 1.4268 2022/08/30 04:35:49 - mmengine - INFO - Epoch(train) [196][50/63] lr: 5.9665e-03 eta: 1 day, 2:36:37 time: 1.4033 data_time: 0.0464 memory: 16201 loss_prob: 0.7998 loss_thr: 0.4828 loss_db: 0.1315 loss: 1.4141 2022/08/30 04:35:56 - mmengine - INFO - Epoch(train) [196][55/63] lr: 5.9665e-03 eta: 1 day, 2:36:37 time: 1.3637 data_time: 0.0300 memory: 16201 loss_prob: 0.8310 loss_thr: 0.5000 loss_db: 0.1360 loss: 1.4669 2022/08/30 04:36:02 - mmengine - INFO - Epoch(train) [196][60/63] lr: 5.9665e-03 eta: 1 day, 2:36:14 time: 1.3564 data_time: 0.0292 memory: 16201 loss_prob: 0.8238 loss_thr: 0.5093 loss_db: 0.1339 loss: 1.4670 2022/08/30 04:36:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:36:14 - mmengine - INFO - Epoch(train) [197][5/63] lr: 5.9612e-03 eta: 1 day, 2:36:14 time: 1.3910 data_time: 0.2228 memory: 16201 loss_prob: 0.8693 loss_thr: 0.5188 loss_db: 0.1460 loss: 1.5341 2022/08/30 04:36:21 - mmengine - INFO - Epoch(train) [197][10/63] lr: 5.9612e-03 eta: 1 day, 2:35:31 time: 1.5071 data_time: 0.2349 memory: 16201 loss_prob: 0.8665 loss_thr: 0.5128 loss_db: 0.1456 loss: 1.5249 2022/08/30 04:36:28 - mmengine - INFO - Epoch(train) [197][15/63] lr: 5.9612e-03 eta: 1 day, 2:35:31 time: 1.3809 data_time: 0.0477 memory: 16201 loss_prob: 0.9186 loss_thr: 0.5334 loss_db: 0.1505 loss: 1.6025 2022/08/30 04:36:35 - mmengine - INFO - Epoch(train) [197][20/63] lr: 5.9612e-03 eta: 1 day, 2:35:10 time: 1.4047 data_time: 0.0454 memory: 16201 loss_prob: 0.8454 loss_thr: 0.5089 loss_db: 0.1372 loss: 1.4915 2022/08/30 04:36:41 - mmengine - INFO - Epoch(train) [197][25/63] lr: 5.9612e-03 eta: 1 day, 2:35:10 time: 1.3322 data_time: 0.0309 memory: 16201 loss_prob: 0.8079 loss_thr: 0.5060 loss_db: 0.1345 loss: 1.4485 2022/08/30 04:36:48 - mmengine - INFO - Epoch(train) [197][30/63] lr: 5.9612e-03 eta: 1 day, 2:34:46 time: 1.3349 data_time: 0.0329 memory: 16201 loss_prob: 0.8026 loss_thr: 0.4950 loss_db: 0.1331 loss: 1.4307 2022/08/30 04:36:54 - mmengine - INFO - Epoch(train) [197][35/63] lr: 5.9612e-03 eta: 1 day, 2:34:46 time: 1.3367 data_time: 0.0320 memory: 16201 loss_prob: 0.8604 loss_thr: 0.4912 loss_db: 0.1377 loss: 1.4892 2022/08/30 04:37:01 - mmengine - INFO - Epoch(train) [197][40/63] lr: 5.9612e-03 eta: 1 day, 2:34:19 time: 1.2804 data_time: 0.0305 memory: 16201 loss_prob: 0.9862 loss_thr: 0.5127 loss_db: 0.1576 loss: 1.6565 2022/08/30 04:37:07 - mmengine - INFO - Epoch(train) [197][45/63] lr: 5.9612e-03 eta: 1 day, 2:34:19 time: 1.2725 data_time: 0.0328 memory: 16201 loss_prob: 0.9954 loss_thr: 0.5180 loss_db: 0.1607 loss: 1.6741 2022/08/30 04:37:14 - mmengine - INFO - Epoch(train) [197][50/63] lr: 5.9612e-03 eta: 1 day, 2:33:54 time: 1.3328 data_time: 0.0360 memory: 16201 loss_prob: 0.8439 loss_thr: 0.4766 loss_db: 0.1379 loss: 1.4584 2022/08/30 04:37:21 - mmengine - INFO - Epoch(train) [197][55/63] lr: 5.9612e-03 eta: 1 day, 2:33:54 time: 1.3976 data_time: 0.0355 memory: 16201 loss_prob: 0.7756 loss_thr: 0.4542 loss_db: 0.1323 loss: 1.3621 2022/08/30 04:37:28 - mmengine - INFO - Epoch(train) [197][60/63] lr: 5.9612e-03 eta: 1 day, 2:33:33 time: 1.3914 data_time: 0.0398 memory: 16201 loss_prob: 0.9244 loss_thr: 0.4996 loss_db: 0.1525 loss: 1.5765 2022/08/30 04:37:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:37:41 - mmengine - INFO - Epoch(train) [198][5/63] lr: 5.9558e-03 eta: 1 day, 2:33:33 time: 1.5851 data_time: 0.2295 memory: 16201 loss_prob: 0.7698 loss_thr: 0.4712 loss_db: 0.1335 loss: 1.3745 2022/08/30 04:37:48 - mmengine - INFO - Epoch(train) [198][10/63] lr: 5.9558e-03 eta: 1 day, 2:32:57 time: 1.6423 data_time: 0.2457 memory: 16201 loss_prob: 0.8455 loss_thr: 0.4974 loss_db: 0.1408 loss: 1.4836 2022/08/30 04:37:55 - mmengine - INFO - Epoch(train) [198][15/63] lr: 5.9558e-03 eta: 1 day, 2:32:57 time: 1.3676 data_time: 0.0341 memory: 16201 loss_prob: 0.8938 loss_thr: 0.5171 loss_db: 0.1476 loss: 1.5584 2022/08/30 04:38:01 - mmengine - INFO - Epoch(train) [198][20/63] lr: 5.9558e-03 eta: 1 day, 2:32:30 time: 1.2833 data_time: 0.0331 memory: 16201 loss_prob: 0.8171 loss_thr: 0.5150 loss_db: 0.1379 loss: 1.4700 2022/08/30 04:38:08 - mmengine - INFO - Epoch(train) [198][25/63] lr: 5.9558e-03 eta: 1 day, 2:32:30 time: 1.2677 data_time: 0.0380 memory: 16201 loss_prob: 0.8526 loss_thr: 0.5160 loss_db: 0.1402 loss: 1.5088 2022/08/30 04:38:14 - mmengine - INFO - Epoch(train) [198][30/63] lr: 5.9558e-03 eta: 1 day, 2:32:04 time: 1.3037 data_time: 0.0317 memory: 16201 loss_prob: 0.8802 loss_thr: 0.5083 loss_db: 0.1435 loss: 1.5320 2022/08/30 04:38:21 - mmengine - INFO - Epoch(train) [198][35/63] lr: 5.9558e-03 eta: 1 day, 2:32:04 time: 1.3199 data_time: 0.0399 memory: 16201 loss_prob: 0.8441 loss_thr: 0.4899 loss_db: 0.1411 loss: 1.4751 2022/08/30 04:38:27 - mmengine - INFO - Epoch(train) [198][40/63] lr: 5.9558e-03 eta: 1 day, 2:31:40 time: 1.3259 data_time: 0.0297 memory: 16201 loss_prob: 0.8495 loss_thr: 0.5062 loss_db: 0.1433 loss: 1.4990 2022/08/30 04:38:34 - mmengine - INFO - Epoch(train) [198][45/63] lr: 5.9558e-03 eta: 1 day, 2:31:40 time: 1.2967 data_time: 0.0326 memory: 16201 loss_prob: 0.8918 loss_thr: 0.5295 loss_db: 0.1497 loss: 1.5710 2022/08/30 04:38:40 - mmengine - INFO - Epoch(train) [198][50/63] lr: 5.9558e-03 eta: 1 day, 2:31:10 time: 1.2298 data_time: 0.0493 memory: 16201 loss_prob: 0.7770 loss_thr: 0.4732 loss_db: 0.1278 loss: 1.3780 2022/08/30 04:38:46 - mmengine - INFO - Epoch(train) [198][55/63] lr: 5.9558e-03 eta: 1 day, 2:31:10 time: 1.2501 data_time: 0.0334 memory: 16201 loss_prob: 0.8270 loss_thr: 0.4836 loss_db: 0.1336 loss: 1.4442 2022/08/30 04:38:53 - mmengine - INFO - Epoch(train) [198][60/63] lr: 5.9558e-03 eta: 1 day, 2:30:49 time: 1.3869 data_time: 0.0479 memory: 16201 loss_prob: 0.8920 loss_thr: 0.5001 loss_db: 0.1457 loss: 1.5378 2022/08/30 04:38:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:39:06 - mmengine - INFO - Epoch(train) [199][5/63] lr: 5.9505e-03 eta: 1 day, 2:30:49 time: 1.5175 data_time: 0.2272 memory: 16201 loss_prob: 0.8280 loss_thr: 0.4756 loss_db: 0.1404 loss: 1.4440 2022/08/30 04:39:13 - mmengine - INFO - Epoch(train) [199][10/63] lr: 5.9505e-03 eta: 1 day, 2:30:09 time: 1.5642 data_time: 0.2479 memory: 16201 loss_prob: 0.7317 loss_thr: 0.4474 loss_db: 0.1265 loss: 1.3055 2022/08/30 04:39:20 - mmengine - INFO - Epoch(train) [199][15/63] lr: 5.9505e-03 eta: 1 day, 2:30:09 time: 1.4117 data_time: 0.0412 memory: 16201 loss_prob: 0.7028 loss_thr: 0.4621 loss_db: 0.1196 loss: 1.2845 2022/08/30 04:39:26 - mmengine - INFO - Epoch(train) [199][20/63] lr: 5.9505e-03 eta: 1 day, 2:29:47 time: 1.3682 data_time: 0.0342 memory: 16201 loss_prob: 0.8749 loss_thr: 0.4984 loss_db: 0.1463 loss: 1.5197 2022/08/30 04:39:33 - mmengine - INFO - Epoch(train) [199][25/63] lr: 5.9505e-03 eta: 1 day, 2:29:47 time: 1.2297 data_time: 0.0441 memory: 16201 loss_prob: 0.8985 loss_thr: 0.5041 loss_db: 0.1480 loss: 1.5506 2022/08/30 04:39:39 - mmengine - INFO - Epoch(train) [199][30/63] lr: 5.9505e-03 eta: 1 day, 2:29:20 time: 1.2938 data_time: 0.0374 memory: 16201 loss_prob: 0.8141 loss_thr: 0.4958 loss_db: 0.1369 loss: 1.4467 2022/08/30 04:39:46 - mmengine - INFO - Epoch(train) [199][35/63] lr: 5.9505e-03 eta: 1 day, 2:29:20 time: 1.3050 data_time: 0.0305 memory: 16201 loss_prob: 0.7957 loss_thr: 0.4964 loss_db: 0.1342 loss: 1.4263 2022/08/30 04:39:52 - mmengine - INFO - Epoch(train) [199][40/63] lr: 5.9505e-03 eta: 1 day, 2:28:53 time: 1.2700 data_time: 0.0315 memory: 16201 loss_prob: 0.7807 loss_thr: 0.5156 loss_db: 0.1319 loss: 1.4282 2022/08/30 04:39:58 - mmengine - INFO - Epoch(train) [199][45/63] lr: 5.9505e-03 eta: 1 day, 2:28:53 time: 1.2749 data_time: 0.0339 memory: 16201 loss_prob: 0.8257 loss_thr: 0.5141 loss_db: 0.1410 loss: 1.4808 2022/08/30 04:40:05 - mmengine - INFO - Epoch(train) [199][50/63] lr: 5.9505e-03 eta: 1 day, 2:28:26 time: 1.2701 data_time: 0.0409 memory: 16201 loss_prob: 0.8119 loss_thr: 0.4848 loss_db: 0.1393 loss: 1.4360 2022/08/30 04:40:11 - mmengine - INFO - Epoch(train) [199][55/63] lr: 5.9505e-03 eta: 1 day, 2:28:26 time: 1.2716 data_time: 0.0282 memory: 16201 loss_prob: 0.8385 loss_thr: 0.4721 loss_db: 0.1330 loss: 1.4436 2022/08/30 04:40:18 - mmengine - INFO - Epoch(train) [199][60/63] lr: 5.9505e-03 eta: 1 day, 2:28:01 time: 1.3137 data_time: 0.0349 memory: 16201 loss_prob: 0.9038 loss_thr: 0.4896 loss_db: 0.1417 loss: 1.5352 2022/08/30 04:40:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:40:30 - mmengine - INFO - Epoch(train) [200][5/63] lr: 5.9451e-03 eta: 1 day, 2:28:01 time: 1.4818 data_time: 0.2296 memory: 16201 loss_prob: 0.8390 loss_thr: 0.5022 loss_db: 0.1415 loss: 1.4827 2022/08/30 04:40:36 - mmengine - INFO - Epoch(train) [200][10/63] lr: 5.9451e-03 eta: 1 day, 2:27:17 time: 1.4741 data_time: 0.2504 memory: 16201 loss_prob: 0.7861 loss_thr: 0.4736 loss_db: 0.1352 loss: 1.3949 2022/08/30 04:40:43 - mmengine - INFO - Epoch(train) [200][15/63] lr: 5.9451e-03 eta: 1 day, 2:27:17 time: 1.3615 data_time: 0.0342 memory: 16201 loss_prob: 0.7736 loss_thr: 0.4790 loss_db: 0.1298 loss: 1.3824 2022/08/30 04:40:49 - mmengine - INFO - Epoch(train) [200][20/63] lr: 5.9451e-03 eta: 1 day, 2:26:53 time: 1.3511 data_time: 0.0303 memory: 16201 loss_prob: 0.8534 loss_thr: 0.4873 loss_db: 0.1416 loss: 1.4822 2022/08/30 04:40:56 - mmengine - INFO - Epoch(train) [200][25/63] lr: 5.9451e-03 eta: 1 day, 2:26:53 time: 1.2718 data_time: 0.0429 memory: 16201 loss_prob: 0.8486 loss_thr: 0.4912 loss_db: 0.1422 loss: 1.4820 2022/08/30 04:41:03 - mmengine - INFO - Epoch(train) [200][30/63] lr: 5.9451e-03 eta: 1 day, 2:26:32 time: 1.3749 data_time: 0.0334 memory: 16201 loss_prob: 0.7708 loss_thr: 0.4733 loss_db: 0.1309 loss: 1.3750 2022/08/30 04:41:09 - mmengine - INFO - Epoch(train) [200][35/63] lr: 5.9451e-03 eta: 1 day, 2:26:32 time: 1.3329 data_time: 0.0284 memory: 16201 loss_prob: 0.8045 loss_thr: 0.4953 loss_db: 0.1339 loss: 1.4337 2022/08/30 04:41:16 - mmengine - INFO - Epoch(train) [200][40/63] lr: 5.9451e-03 eta: 1 day, 2:26:03 time: 1.2399 data_time: 0.0298 memory: 16201 loss_prob: 0.8312 loss_thr: 0.5198 loss_db: 0.1375 loss: 1.4885 2022/08/30 04:41:23 - mmengine - INFO - Epoch(train) [200][45/63] lr: 5.9451e-03 eta: 1 day, 2:26:03 time: 1.3389 data_time: 0.0264 memory: 16201 loss_prob: 0.7734 loss_thr: 0.4808 loss_db: 0.1299 loss: 1.3840 2022/08/30 04:41:29 - mmengine - INFO - Epoch(train) [200][50/63] lr: 5.9451e-03 eta: 1 day, 2:25:38 time: 1.3142 data_time: 0.0346 memory: 16201 loss_prob: 0.8119 loss_thr: 0.4806 loss_db: 0.1331 loss: 1.4256 2022/08/30 04:41:36 - mmengine - INFO - Epoch(train) [200][55/63] lr: 5.9451e-03 eta: 1 day, 2:25:38 time: 1.2775 data_time: 0.0322 memory: 16201 loss_prob: 0.8396 loss_thr: 0.4889 loss_db: 0.1393 loss: 1.4677 2022/08/30 04:41:42 - mmengine - INFO - Epoch(train) [200][60/63] lr: 5.9451e-03 eta: 1 day, 2:25:16 time: 1.3665 data_time: 0.0309 memory: 16201 loss_prob: 0.7981 loss_thr: 0.4723 loss_db: 0.1347 loss: 1.4051 2022/08/30 04:41:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:41:46 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/08/30 04:41:54 - mmengine - INFO - Epoch(val) [200][5/32] eta: 1 day, 2:25:16 time: 0.7270 data_time: 0.1363 memory: 16201 2022/08/30 04:41:58 - mmengine - INFO - Epoch(val) [200][10/32] eta: 0:00:17 time: 0.7938 data_time: 0.1762 memory: 15734 2022/08/30 04:42:01 - mmengine - INFO - Epoch(val) [200][15/32] eta: 0:00:17 time: 0.6622 data_time: 0.0686 memory: 15734 2022/08/30 04:42:04 - mmengine - INFO - Epoch(val) [200][20/32] eta: 0:00:07 time: 0.6539 data_time: 0.0714 memory: 15734 2022/08/30 04:42:08 - mmengine - INFO - Epoch(val) [200][25/32] eta: 0:00:07 time: 0.7353 data_time: 0.0861 memory: 15734 2022/08/30 04:42:11 - mmengine - INFO - Epoch(val) [200][30/32] eta: 0:00:01 time: 0.6695 data_time: 0.0339 memory: 15734 2022/08/30 04:42:12 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 04:42:12 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8382, precision: 0.7758, hmean: 0.8058 2022/08/30 04:42:12 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8377, precision: 0.8294, hmean: 0.8335 2022/08/30 04:42:12 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8310, precision: 0.8587, hmean: 0.8446 2022/08/30 04:42:12 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8146, precision: 0.8836, hmean: 0.8477 2022/08/30 04:42:12 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7814, precision: 0.9118, hmean: 0.8416 2022/08/30 04:42:12 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5816, precision: 0.9587, hmean: 0.7240 2022/08/30 04:42:12 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0226, precision: 1.0000, hmean: 0.0443 2022/08/30 04:42:12 - mmengine - INFO - Epoch(val) [200][32/32] icdar/precision: 0.8836 icdar/recall: 0.8146 icdar/hmean: 0.8477 2022/08/30 04:42:21 - mmengine - INFO - Epoch(train) [201][5/63] lr: 5.9398e-03 eta: 0:00:01 time: 1.5066 data_time: 0.2110 memory: 16201 loss_prob: 0.8414 loss_thr: 0.5015 loss_db: 0.1410 loss: 1.4839 2022/08/30 04:42:29 - mmengine - INFO - Epoch(train) [201][10/63] lr: 5.9398e-03 eta: 1 day, 2:24:41 time: 1.6495 data_time: 0.2243 memory: 16201 loss_prob: 0.7305 loss_thr: 0.4693 loss_db: 0.1219 loss: 1.3217 2022/08/30 04:42:35 - mmengine - INFO - Epoch(train) [201][15/63] lr: 5.9398e-03 eta: 1 day, 2:24:41 time: 1.4009 data_time: 0.0415 memory: 16201 loss_prob: 0.7244 loss_thr: 0.4645 loss_db: 0.1227 loss: 1.3117 2022/08/30 04:42:41 - mmengine - INFO - Epoch(train) [201][20/63] lr: 5.9398e-03 eta: 1 day, 2:24:15 time: 1.2937 data_time: 0.0343 memory: 16201 loss_prob: 0.7810 loss_thr: 0.4940 loss_db: 0.1323 loss: 1.4073 2022/08/30 04:42:48 - mmengine - INFO - Epoch(train) [201][25/63] lr: 5.9398e-03 eta: 1 day, 2:24:15 time: 1.3055 data_time: 0.0350 memory: 16201 loss_prob: 0.8700 loss_thr: 0.4987 loss_db: 0.1441 loss: 1.5128 2022/08/30 04:42:55 - mmengine - INFO - Epoch(train) [201][30/63] lr: 5.9398e-03 eta: 1 day, 2:23:52 time: 1.3567 data_time: 0.0373 memory: 16201 loss_prob: 0.8520 loss_thr: 0.4671 loss_db: 0.1413 loss: 1.4604 2022/08/30 04:43:02 - mmengine - INFO - Epoch(train) [201][35/63] lr: 5.9398e-03 eta: 1 day, 2:23:52 time: 1.3490 data_time: 0.0330 memory: 16201 loss_prob: 0.7623 loss_thr: 0.4593 loss_db: 0.1280 loss: 1.3497 2022/08/30 04:43:09 - mmengine - INFO - Epoch(train) [201][40/63] lr: 5.9398e-03 eta: 1 day, 2:23:31 time: 1.3845 data_time: 0.0330 memory: 16201 loss_prob: 0.7603 loss_thr: 0.4780 loss_db: 0.1290 loss: 1.3673 2022/08/30 04:43:16 - mmengine - INFO - Epoch(train) [201][45/63] lr: 5.9398e-03 eta: 1 day, 2:23:31 time: 1.3820 data_time: 0.0361 memory: 16201 loss_prob: 0.8059 loss_thr: 0.4951 loss_db: 0.1368 loss: 1.4379 2022/08/30 04:43:22 - mmengine - INFO - Epoch(train) [201][50/63] lr: 5.9398e-03 eta: 1 day, 2:23:04 time: 1.2870 data_time: 0.0447 memory: 16201 loss_prob: 0.7287 loss_thr: 0.4565 loss_db: 0.1229 loss: 1.3080 2022/08/30 04:43:28 - mmengine - INFO - Epoch(train) [201][55/63] lr: 5.9398e-03 eta: 1 day, 2:23:04 time: 1.2541 data_time: 0.0400 memory: 16201 loss_prob: 0.6789 loss_thr: 0.4475 loss_db: 0.1157 loss: 1.2421 2022/08/30 04:43:34 - mmengine - INFO - Epoch(train) [201][60/63] lr: 5.9398e-03 eta: 1 day, 2:22:38 time: 1.2697 data_time: 0.0318 memory: 16201 loss_prob: 0.7833 loss_thr: 0.5074 loss_db: 0.1313 loss: 1.4221 2022/08/30 04:43:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:43:47 - mmengine - INFO - Epoch(train) [202][5/63] lr: 5.9344e-03 eta: 1 day, 2:22:38 time: 1.4585 data_time: 0.2412 memory: 16201 loss_prob: 0.7409 loss_thr: 0.4845 loss_db: 0.1268 loss: 1.3522 2022/08/30 04:43:53 - mmengine - INFO - Epoch(train) [202][10/63] lr: 5.9344e-03 eta: 1 day, 2:21:58 time: 1.5588 data_time: 0.2485 memory: 16201 loss_prob: 0.7544 loss_thr: 0.4599 loss_db: 0.1267 loss: 1.3411 2022/08/30 04:44:00 - mmengine - INFO - Epoch(train) [202][15/63] lr: 5.9344e-03 eta: 1 day, 2:21:58 time: 1.2938 data_time: 0.0394 memory: 16201 loss_prob: 0.7573 loss_thr: 0.4575 loss_db: 0.1257 loss: 1.3405 2022/08/30 04:44:06 - mmengine - INFO - Epoch(train) [202][20/63] lr: 5.9344e-03 eta: 1 day, 2:21:32 time: 1.2944 data_time: 0.0430 memory: 16201 loss_prob: 0.7425 loss_thr: 0.4538 loss_db: 0.1268 loss: 1.3231 2022/08/30 04:44:13 - mmengine - INFO - Epoch(train) [202][25/63] lr: 5.9344e-03 eta: 1 day, 2:21:32 time: 1.3139 data_time: 0.0335 memory: 16201 loss_prob: 0.7819 loss_thr: 0.4748 loss_db: 0.1321 loss: 1.3888 2022/08/30 04:44:20 - mmengine - INFO - Epoch(train) [202][30/63] lr: 5.9344e-03 eta: 1 day, 2:21:09 time: 1.3367 data_time: 0.0321 memory: 16201 loss_prob: 0.8008 loss_thr: 0.5023 loss_db: 0.1331 loss: 1.4362 2022/08/30 04:44:27 - mmengine - INFO - Epoch(train) [202][35/63] lr: 5.9344e-03 eta: 1 day, 2:21:09 time: 1.3819 data_time: 0.0449 memory: 16201 loss_prob: 0.7689 loss_thr: 0.4877 loss_db: 0.1281 loss: 1.3847 2022/08/30 04:44:33 - mmengine - INFO - Epoch(train) [202][40/63] lr: 5.9344e-03 eta: 1 day, 2:20:47 time: 1.3730 data_time: 0.0304 memory: 16201 loss_prob: 0.7824 loss_thr: 0.4825 loss_db: 0.1312 loss: 1.3961 2022/08/30 04:44:40 - mmengine - INFO - Epoch(train) [202][45/63] lr: 5.9344e-03 eta: 1 day, 2:20:47 time: 1.3599 data_time: 0.0273 memory: 16201 loss_prob: 0.7693 loss_thr: 0.4662 loss_db: 0.1287 loss: 1.3643 2022/08/30 04:44:46 - mmengine - INFO - Epoch(train) [202][50/63] lr: 5.9344e-03 eta: 1 day, 2:20:21 time: 1.2996 data_time: 0.0387 memory: 16201 loss_prob: 0.7518 loss_thr: 0.4414 loss_db: 0.1257 loss: 1.3189 2022/08/30 04:44:52 - mmengine - INFO - Epoch(train) [202][55/63] lr: 5.9344e-03 eta: 1 day, 2:20:21 time: 1.2288 data_time: 0.0288 memory: 16201 loss_prob: 0.8619 loss_thr: 0.4903 loss_db: 0.1413 loss: 1.4936 2022/08/30 04:44:59 - mmengine - INFO - Epoch(train) [202][60/63] lr: 5.9344e-03 eta: 1 day, 2:19:55 time: 1.2843 data_time: 0.0276 memory: 16201 loss_prob: 0.8369 loss_thr: 0.5047 loss_db: 0.1385 loss: 1.4801 2022/08/30 04:45:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:45:11 - mmengine - INFO - Epoch(train) [203][5/63] lr: 5.9291e-03 eta: 1 day, 2:19:55 time: 1.5212 data_time: 0.2181 memory: 16201 loss_prob: 0.7651 loss_thr: 0.4631 loss_db: 0.1306 loss: 1.3588 2022/08/30 04:45:18 - mmengine - INFO - Epoch(train) [203][10/63] lr: 5.9291e-03 eta: 1 day, 2:19:18 time: 1.6045 data_time: 0.2320 memory: 16201 loss_prob: 0.7872 loss_thr: 0.4674 loss_db: 0.1337 loss: 1.3883 2022/08/30 04:45:25 - mmengine - INFO - Epoch(train) [203][15/63] lr: 5.9291e-03 eta: 1 day, 2:19:18 time: 1.3447 data_time: 0.0382 memory: 16201 loss_prob: 0.7775 loss_thr: 0.4641 loss_db: 0.1300 loss: 1.3716 2022/08/30 04:45:32 - mmengine - INFO - Epoch(train) [203][20/63] lr: 5.9291e-03 eta: 1 day, 2:18:56 time: 1.3698 data_time: 0.0358 memory: 16201 loss_prob: 0.7285 loss_thr: 0.4726 loss_db: 0.1238 loss: 1.3249 2022/08/30 04:45:39 - mmengine - INFO - Epoch(train) [203][25/63] lr: 5.9291e-03 eta: 1 day, 2:18:56 time: 1.3970 data_time: 0.0376 memory: 16201 loss_prob: 0.7301 loss_thr: 0.4756 loss_db: 0.1261 loss: 1.3318 2022/08/30 04:45:45 - mmengine - INFO - Epoch(train) [203][30/63] lr: 5.9291e-03 eta: 1 day, 2:18:35 time: 1.3710 data_time: 0.0375 memory: 16201 loss_prob: 0.7507 loss_thr: 0.4650 loss_db: 0.1253 loss: 1.3411 2022/08/30 04:45:51 - mmengine - INFO - Epoch(train) [203][35/63] lr: 5.9291e-03 eta: 1 day, 2:18:35 time: 1.2540 data_time: 0.0345 memory: 16201 loss_prob: 0.8373 loss_thr: 0.4932 loss_db: 0.1392 loss: 1.4697 2022/08/30 04:45:58 - mmengine - INFO - Epoch(train) [203][40/63] lr: 5.9291e-03 eta: 1 day, 2:18:09 time: 1.2990 data_time: 0.0267 memory: 16201 loss_prob: 0.8792 loss_thr: 0.5115 loss_db: 0.1503 loss: 1.5410 2022/08/30 04:46:05 - mmengine - INFO - Epoch(train) [203][45/63] lr: 5.9291e-03 eta: 1 day, 2:18:09 time: 1.3745 data_time: 0.0305 memory: 16201 loss_prob: 0.7726 loss_thr: 0.4781 loss_db: 0.1316 loss: 1.3823 2022/08/30 04:46:12 - mmengine - INFO - Epoch(train) [203][50/63] lr: 5.9291e-03 eta: 1 day, 2:17:45 time: 1.3172 data_time: 0.0364 memory: 16201 loss_prob: 0.8709 loss_thr: 0.4828 loss_db: 0.1355 loss: 1.4892 2022/08/30 04:46:18 - mmengine - INFO - Epoch(train) [203][55/63] lr: 5.9291e-03 eta: 1 day, 2:17:45 time: 1.2502 data_time: 0.0384 memory: 16201 loss_prob: 0.9332 loss_thr: 0.5075 loss_db: 0.1431 loss: 1.5837 2022/08/30 04:46:25 - mmengine - INFO - Epoch(train) [203][60/63] lr: 5.9291e-03 eta: 1 day, 2:17:20 time: 1.3052 data_time: 0.0431 memory: 16201 loss_prob: 0.7815 loss_thr: 0.4808 loss_db: 0.1293 loss: 1.3916 2022/08/30 04:46:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:46:37 - mmengine - INFO - Epoch(train) [204][5/63] lr: 5.9237e-03 eta: 1 day, 2:17:20 time: 1.5269 data_time: 0.2257 memory: 16201 loss_prob: 0.7453 loss_thr: 0.4759 loss_db: 0.1256 loss: 1.3468 2022/08/30 04:46:45 - mmengine - INFO - Epoch(train) [204][10/63] lr: 5.9237e-03 eta: 1 day, 2:16:47 time: 1.6790 data_time: 0.2361 memory: 16201 loss_prob: 0.7544 loss_thr: 0.4759 loss_db: 0.1330 loss: 1.3632 2022/08/30 04:46:51 - mmengine - INFO - Epoch(train) [204][15/63] lr: 5.9237e-03 eta: 1 day, 2:16:47 time: 1.3954 data_time: 0.0355 memory: 16201 loss_prob: 0.7033 loss_thr: 0.4531 loss_db: 0.1216 loss: 1.2780 2022/08/30 04:46:57 - mmengine - INFO - Epoch(train) [204][20/63] lr: 5.9237e-03 eta: 1 day, 2:16:19 time: 1.2611 data_time: 0.0391 memory: 16201 loss_prob: 0.7119 loss_thr: 0.4535 loss_db: 0.1189 loss: 1.2844 2022/08/30 04:47:04 - mmengine - INFO - Epoch(train) [204][25/63] lr: 5.9237e-03 eta: 1 day, 2:16:19 time: 1.2768 data_time: 0.0351 memory: 16201 loss_prob: 0.7773 loss_thr: 0.4726 loss_db: 0.1311 loss: 1.3810 2022/08/30 04:47:11 - mmengine - INFO - Epoch(train) [204][30/63] lr: 5.9237e-03 eta: 1 day, 2:15:56 time: 1.3296 data_time: 0.0379 memory: 16201 loss_prob: 0.7735 loss_thr: 0.4741 loss_db: 0.1306 loss: 1.3782 2022/08/30 04:47:17 - mmengine - INFO - Epoch(train) [204][35/63] lr: 5.9237e-03 eta: 1 day, 2:15:56 time: 1.3451 data_time: 0.0409 memory: 16201 loss_prob: 0.7506 loss_thr: 0.4771 loss_db: 0.1262 loss: 1.3540 2022/08/30 04:47:24 - mmengine - INFO - Epoch(train) [204][40/63] lr: 5.9237e-03 eta: 1 day, 2:15:34 time: 1.3637 data_time: 0.0303 memory: 16201 loss_prob: 0.9002 loss_thr: 0.4962 loss_db: 0.1494 loss: 1.5458 2022/08/30 04:47:31 - mmengine - INFO - Epoch(train) [204][45/63] lr: 5.9237e-03 eta: 1 day, 2:15:34 time: 1.3758 data_time: 0.0346 memory: 16201 loss_prob: 0.9606 loss_thr: 0.5152 loss_db: 0.1602 loss: 1.6360 2022/08/30 04:47:38 - mmengine - INFO - Epoch(train) [204][50/63] lr: 5.9237e-03 eta: 1 day, 2:15:11 time: 1.3454 data_time: 0.0341 memory: 16201 loss_prob: 0.9748 loss_thr: 0.4996 loss_db: 0.1602 loss: 1.6346 2022/08/30 04:47:44 - mmengine - INFO - Epoch(train) [204][55/63] lr: 5.9237e-03 eta: 1 day, 2:15:11 time: 1.2929 data_time: 0.0370 memory: 16201 loss_prob: 1.0422 loss_thr: 0.5125 loss_db: 0.1651 loss: 1.7199 2022/08/30 04:47:51 - mmengine - INFO - Epoch(train) [204][60/63] lr: 5.9237e-03 eta: 1 day, 2:14:47 time: 1.3331 data_time: 0.0418 memory: 16201 loss_prob: 0.9261 loss_thr: 0.5123 loss_db: 0.1512 loss: 1.5896 2022/08/30 04:47:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:48:03 - mmengine - INFO - Epoch(train) [205][5/63] lr: 5.9184e-03 eta: 1 day, 2:14:47 time: 1.5762 data_time: 0.2852 memory: 16201 loss_prob: 0.8068 loss_thr: 0.4576 loss_db: 0.1332 loss: 1.3975 2022/08/30 04:48:11 - mmengine - INFO - Epoch(train) [205][10/63] lr: 5.9184e-03 eta: 1 day, 2:14:11 time: 1.6148 data_time: 0.2449 memory: 16201 loss_prob: 0.7592 loss_thr: 0.4513 loss_db: 0.1266 loss: 1.3371 2022/08/30 04:48:17 - mmengine - INFO - Epoch(train) [205][15/63] lr: 5.9184e-03 eta: 1 day, 2:14:11 time: 1.3664 data_time: 0.0337 memory: 16201 loss_prob: 0.8720 loss_thr: 0.4844 loss_db: 0.1483 loss: 1.5048 2022/08/30 04:48:23 - mmengine - INFO - Epoch(train) [205][20/63] lr: 5.9184e-03 eta: 1 day, 2:13:44 time: 1.2627 data_time: 0.0309 memory: 16201 loss_prob: 0.8980 loss_thr: 0.5066 loss_db: 0.1513 loss: 1.5560 2022/08/30 04:48:30 - mmengine - INFO - Epoch(train) [205][25/63] lr: 5.9184e-03 eta: 1 day, 2:13:44 time: 1.3118 data_time: 0.0439 memory: 16201 loss_prob: 0.8442 loss_thr: 0.4989 loss_db: 0.1407 loss: 1.4837 2022/08/30 04:48:36 - mmengine - INFO - Epoch(train) [205][30/63] lr: 5.9184e-03 eta: 1 day, 2:13:19 time: 1.2992 data_time: 0.0307 memory: 16201 loss_prob: 0.8424 loss_thr: 0.4847 loss_db: 0.1403 loss: 1.4674 2022/08/30 04:48:43 - mmengine - INFO - Epoch(train) [205][35/63] lr: 5.9184e-03 eta: 1 day, 2:13:19 time: 1.3070 data_time: 0.0321 memory: 16201 loss_prob: 0.8516 loss_thr: 0.5047 loss_db: 0.1415 loss: 1.4978 2022/08/30 04:48:49 - mmengine - INFO - Epoch(train) [205][40/63] lr: 5.9184e-03 eta: 1 day, 2:12:55 time: 1.3147 data_time: 0.0372 memory: 16201 loss_prob: 0.9218 loss_thr: 0.5472 loss_db: 0.1531 loss: 1.6221 2022/08/30 04:48:56 - mmengine - INFO - Epoch(train) [205][45/63] lr: 5.9184e-03 eta: 1 day, 2:12:55 time: 1.2648 data_time: 0.0310 memory: 16201 loss_prob: 0.8920 loss_thr: 0.5067 loss_db: 0.1478 loss: 1.5465 2022/08/30 04:49:02 - mmengine - INFO - Epoch(train) [205][50/63] lr: 5.9184e-03 eta: 1 day, 2:12:29 time: 1.2955 data_time: 0.0380 memory: 16201 loss_prob: 0.8724 loss_thr: 0.4659 loss_db: 0.1433 loss: 1.4815 2022/08/30 04:49:09 - mmengine - INFO - Epoch(train) [205][55/63] lr: 5.9184e-03 eta: 1 day, 2:12:29 time: 1.3080 data_time: 0.0389 memory: 16201 loss_prob: 0.8722 loss_thr: 0.4833 loss_db: 0.1408 loss: 1.4963 2022/08/30 04:49:16 - mmengine - INFO - Epoch(train) [205][60/63] lr: 5.9184e-03 eta: 1 day, 2:12:07 time: 1.3562 data_time: 0.0389 memory: 16201 loss_prob: 0.8753 loss_thr: 0.5095 loss_db: 0.1395 loss: 1.5243 2022/08/30 04:49:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:49:28 - mmengine - INFO - Epoch(train) [206][5/63] lr: 5.9130e-03 eta: 1 day, 2:12:07 time: 1.4554 data_time: 0.2344 memory: 16201 loss_prob: 0.7727 loss_thr: 0.4835 loss_db: 0.1281 loss: 1.3843 2022/08/30 04:49:34 - mmengine - INFO - Epoch(train) [206][10/63] lr: 5.9130e-03 eta: 1 day, 2:11:24 time: 1.4669 data_time: 0.2590 memory: 16201 loss_prob: 0.6964 loss_thr: 0.4578 loss_db: 0.1184 loss: 1.2726 2022/08/30 04:49:40 - mmengine - INFO - Epoch(train) [206][15/63] lr: 5.9130e-03 eta: 1 day, 2:11:24 time: 1.2469 data_time: 0.0342 memory: 16201 loss_prob: 0.7520 loss_thr: 0.4581 loss_db: 0.1243 loss: 1.3343 2022/08/30 04:49:46 - mmengine - INFO - Epoch(train) [206][20/63] lr: 5.9130e-03 eta: 1 day, 2:10:56 time: 1.2468 data_time: 0.0294 memory: 16201 loss_prob: 0.7641 loss_thr: 0.4741 loss_db: 0.1276 loss: 1.3658 2022/08/30 04:49:53 - mmengine - INFO - Epoch(train) [206][25/63] lr: 5.9130e-03 eta: 1 day, 2:10:56 time: 1.2786 data_time: 0.0437 memory: 16201 loss_prob: 0.8311 loss_thr: 0.5094 loss_db: 0.1386 loss: 1.4791 2022/08/30 04:49:58 - mmengine - INFO - Epoch(train) [206][30/63] lr: 5.9130e-03 eta: 1 day, 2:10:28 time: 1.2320 data_time: 0.0297 memory: 16201 loss_prob: 0.9069 loss_thr: 0.5095 loss_db: 0.1470 loss: 1.5635 2022/08/30 04:50:05 - mmengine - INFO - Epoch(train) [206][35/63] lr: 5.9130e-03 eta: 1 day, 2:10:28 time: 1.2217 data_time: 0.0286 memory: 16201 loss_prob: 0.8367 loss_thr: 0.4799 loss_db: 0.1399 loss: 1.4565 2022/08/30 04:50:11 - mmengine - INFO - Epoch(train) [206][40/63] lr: 5.9130e-03 eta: 1 day, 2:10:01 time: 1.2491 data_time: 0.0307 memory: 16201 loss_prob: 0.7705 loss_thr: 0.4564 loss_db: 0.1320 loss: 1.3589 2022/08/30 04:50:18 - mmengine - INFO - Epoch(train) [206][45/63] lr: 5.9130e-03 eta: 1 day, 2:10:01 time: 1.3173 data_time: 0.0283 memory: 16201 loss_prob: 0.7906 loss_thr: 0.4688 loss_db: 0.1305 loss: 1.3899 2022/08/30 04:50:25 - mmengine - INFO - Epoch(train) [206][50/63] lr: 5.9130e-03 eta: 1 day, 2:09:43 time: 1.4383 data_time: 0.0404 memory: 16201 loss_prob: 0.7958 loss_thr: 0.4897 loss_db: 0.1297 loss: 1.4152 2022/08/30 04:50:32 - mmengine - INFO - Epoch(train) [206][55/63] lr: 5.9130e-03 eta: 1 day, 2:09:43 time: 1.3950 data_time: 0.0290 memory: 16201 loss_prob: 0.8054 loss_thr: 0.4716 loss_db: 0.1320 loss: 1.4090 2022/08/30 04:50:39 - mmengine - INFO - Epoch(train) [206][60/63] lr: 5.9130e-03 eta: 1 day, 2:09:20 time: 1.3454 data_time: 0.0268 memory: 16201 loss_prob: 0.8230 loss_thr: 0.4867 loss_db: 0.1366 loss: 1.4463 2022/08/30 04:50:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:50:51 - mmengine - INFO - Epoch(train) [207][5/63] lr: 5.9077e-03 eta: 1 day, 2:09:20 time: 1.4738 data_time: 0.2248 memory: 16201 loss_prob: 0.8360 loss_thr: 0.5263 loss_db: 0.1435 loss: 1.5058 2022/08/30 04:50:58 - mmengine - INFO - Epoch(train) [207][10/63] lr: 5.9077e-03 eta: 1 day, 2:08:41 time: 1.5470 data_time: 0.2432 memory: 16201 loss_prob: 0.8288 loss_thr: 0.4982 loss_db: 0.1414 loss: 1.4684 2022/08/30 04:51:05 - mmengine - INFO - Epoch(train) [207][15/63] lr: 5.9077e-03 eta: 1 day, 2:08:41 time: 1.4380 data_time: 0.0328 memory: 16201 loss_prob: 0.7901 loss_thr: 0.4783 loss_db: 0.1318 loss: 1.4002 2022/08/30 04:51:12 - mmengine - INFO - Epoch(train) [207][20/63] lr: 5.9077e-03 eta: 1 day, 2:08:21 time: 1.4067 data_time: 0.0342 memory: 16201 loss_prob: 0.8028 loss_thr: 0.4667 loss_db: 0.1264 loss: 1.3958 2022/08/30 04:51:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:51:19 - mmengine - INFO - Epoch(train) [207][25/63] lr: 5.9077e-03 eta: 1 day, 2:08:21 time: 1.3222 data_time: 0.0380 memory: 16201 loss_prob: 0.8795 loss_thr: 0.4901 loss_db: 0.1437 loss: 1.5133 2022/08/30 04:51:26 - mmengine - INFO - Epoch(train) [207][30/63] lr: 5.9077e-03 eta: 1 day, 2:08:00 time: 1.3839 data_time: 0.0292 memory: 16201 loss_prob: 0.8673 loss_thr: 0.5167 loss_db: 0.1480 loss: 1.5320 2022/08/30 04:51:32 - mmengine - INFO - Epoch(train) [207][35/63] lr: 5.9077e-03 eta: 1 day, 2:08:00 time: 1.3444 data_time: 0.0387 memory: 16201 loss_prob: 0.8022 loss_thr: 0.4859 loss_db: 0.1323 loss: 1.4204 2022/08/30 04:51:39 - mmengine - INFO - Epoch(train) [207][40/63] lr: 5.9077e-03 eta: 1 day, 2:07:37 time: 1.3290 data_time: 0.0338 memory: 16201 loss_prob: 0.8051 loss_thr: 0.4826 loss_db: 0.1299 loss: 1.4176 2022/08/30 04:51:46 - mmengine - INFO - Epoch(train) [207][45/63] lr: 5.9077e-03 eta: 1 day, 2:07:37 time: 1.3903 data_time: 0.0338 memory: 16201 loss_prob: 0.8311 loss_thr: 0.4833 loss_db: 0.1364 loss: 1.4508 2022/08/30 04:51:53 - mmengine - INFO - Epoch(train) [207][50/63] lr: 5.9077e-03 eta: 1 day, 2:07:16 time: 1.3811 data_time: 0.0422 memory: 16201 loss_prob: 0.8627 loss_thr: 0.4928 loss_db: 0.1442 loss: 1.4998 2022/08/30 04:51:59 - mmengine - INFO - Epoch(train) [207][55/63] lr: 5.9077e-03 eta: 1 day, 2:07:16 time: 1.3340 data_time: 0.0333 memory: 16201 loss_prob: 0.8240 loss_thr: 0.5018 loss_db: 0.1377 loss: 1.4635 2022/08/30 04:52:06 - mmengine - INFO - Epoch(train) [207][60/63] lr: 5.9077e-03 eta: 1 day, 2:06:54 time: 1.3626 data_time: 0.0396 memory: 16201 loss_prob: 0.7797 loss_thr: 0.4734 loss_db: 0.1305 loss: 1.3836 2022/08/30 04:52:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:52:18 - mmengine - INFO - Epoch(train) [208][5/63] lr: 5.9023e-03 eta: 1 day, 2:06:54 time: 1.4378 data_time: 0.2362 memory: 16201 loss_prob: 0.8835 loss_thr: 0.5151 loss_db: 0.1479 loss: 1.5465 2022/08/30 04:52:25 - mmengine - INFO - Epoch(train) [208][10/63] lr: 5.9023e-03 eta: 1 day, 2:06:17 time: 1.5751 data_time: 0.2540 memory: 16201 loss_prob: 0.8597 loss_thr: 0.5051 loss_db: 0.1443 loss: 1.5091 2022/08/30 04:52:31 - mmengine - INFO - Epoch(train) [208][15/63] lr: 5.9023e-03 eta: 1 day, 2:06:17 time: 1.3402 data_time: 0.0386 memory: 16201 loss_prob: 0.7856 loss_thr: 0.4740 loss_db: 0.1313 loss: 1.3908 2022/08/30 04:52:38 - mmengine - INFO - Epoch(train) [208][20/63] lr: 5.9023e-03 eta: 1 day, 2:05:53 time: 1.3243 data_time: 0.0325 memory: 16201 loss_prob: 0.7265 loss_thr: 0.4536 loss_db: 0.1224 loss: 1.3025 2022/08/30 04:52:46 - mmengine - INFO - Epoch(train) [208][25/63] lr: 5.9023e-03 eta: 1 day, 2:05:53 time: 1.4151 data_time: 0.0495 memory: 16201 loss_prob: 0.7384 loss_thr: 0.4627 loss_db: 0.1260 loss: 1.3271 2022/08/30 04:52:52 - mmengine - INFO - Epoch(train) [208][30/63] lr: 5.9023e-03 eta: 1 day, 2:05:32 time: 1.3716 data_time: 0.0361 memory: 16201 loss_prob: 0.8194 loss_thr: 0.5007 loss_db: 0.1390 loss: 1.4591 2022/08/30 04:52:59 - mmengine - INFO - Epoch(train) [208][35/63] lr: 5.9023e-03 eta: 1 day, 2:05:32 time: 1.3004 data_time: 0.0333 memory: 16201 loss_prob: 0.8145 loss_thr: 0.5067 loss_db: 0.1368 loss: 1.4580 2022/08/30 04:53:05 - mmengine - INFO - Epoch(train) [208][40/63] lr: 5.9023e-03 eta: 1 day, 2:05:10 time: 1.3605 data_time: 0.0386 memory: 16201 loss_prob: 0.7618 loss_thr: 0.4781 loss_db: 0.1276 loss: 1.3675 2022/08/30 04:53:12 - mmengine - INFO - Epoch(train) [208][45/63] lr: 5.9023e-03 eta: 1 day, 2:05:10 time: 1.3442 data_time: 0.0336 memory: 16201 loss_prob: 0.7919 loss_thr: 0.4776 loss_db: 0.1326 loss: 1.4021 2022/08/30 04:53:19 - mmengine - INFO - Epoch(train) [208][50/63] lr: 5.9023e-03 eta: 1 day, 2:04:48 time: 1.3537 data_time: 0.0418 memory: 16201 loss_prob: 0.7936 loss_thr: 0.4728 loss_db: 0.1333 loss: 1.3997 2022/08/30 04:53:25 - mmengine - INFO - Epoch(train) [208][55/63] lr: 5.9023e-03 eta: 1 day, 2:04:48 time: 1.3412 data_time: 0.0317 memory: 16201 loss_prob: 0.7553 loss_thr: 0.4698 loss_db: 0.1303 loss: 1.3555 2022/08/30 04:53:32 - mmengine - INFO - Epoch(train) [208][60/63] lr: 5.9023e-03 eta: 1 day, 2:04:25 time: 1.3404 data_time: 0.0325 memory: 16201 loss_prob: 0.7460 loss_thr: 0.4669 loss_db: 0.1278 loss: 1.3407 2022/08/30 04:53:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:53:44 - mmengine - INFO - Epoch(train) [209][5/63] lr: 5.8970e-03 eta: 1 day, 2:04:25 time: 1.4768 data_time: 0.2438 memory: 16201 loss_prob: 0.7965 loss_thr: 0.4824 loss_db: 0.1356 loss: 1.4144 2022/08/30 04:53:51 - mmengine - INFO - Epoch(train) [209][10/63] lr: 5.8970e-03 eta: 1 day, 2:03:49 time: 1.5963 data_time: 0.2681 memory: 16201 loss_prob: 0.7490 loss_thr: 0.4584 loss_db: 0.1296 loss: 1.3369 2022/08/30 04:53:58 - mmengine - INFO - Epoch(train) [209][15/63] lr: 5.8970e-03 eta: 1 day, 2:03:49 time: 1.3777 data_time: 0.0350 memory: 16201 loss_prob: 0.7241 loss_thr: 0.4471 loss_db: 0.1220 loss: 1.2931 2022/08/30 04:54:04 - mmengine - INFO - Epoch(train) [209][20/63] lr: 5.8970e-03 eta: 1 day, 2:03:25 time: 1.3262 data_time: 0.0298 memory: 16201 loss_prob: 0.7503 loss_thr: 0.4484 loss_db: 0.1318 loss: 1.3305 2022/08/30 04:54:10 - mmengine - INFO - Epoch(train) [209][25/63] lr: 5.8970e-03 eta: 1 day, 2:03:25 time: 1.2467 data_time: 0.0323 memory: 16201 loss_prob: 0.7729 loss_thr: 0.4639 loss_db: 0.1361 loss: 1.3729 2022/08/30 04:54:17 - mmengine - INFO - Epoch(train) [209][30/63] lr: 5.8970e-03 eta: 1 day, 2:03:00 time: 1.2940 data_time: 0.0304 memory: 16201 loss_prob: 0.8852 loss_thr: 0.5070 loss_db: 0.1496 loss: 1.5419 2022/08/30 04:54:24 - mmengine - INFO - Epoch(train) [209][35/63] lr: 5.8970e-03 eta: 1 day, 2:03:00 time: 1.3891 data_time: 0.0442 memory: 16201 loss_prob: 0.9544 loss_thr: 0.4954 loss_db: 0.1608 loss: 1.6106 2022/08/30 04:54:31 - mmengine - INFO - Epoch(train) [209][40/63] lr: 5.8970e-03 eta: 1 day, 2:02:40 time: 1.3887 data_time: 0.0319 memory: 16201 loss_prob: 1.0792 loss_thr: 0.5124 loss_db: 0.1736 loss: 1.7652 2022/08/30 04:54:38 - mmengine - INFO - Epoch(train) [209][45/63] lr: 5.8970e-03 eta: 1 day, 2:02:40 time: 1.3821 data_time: 0.0315 memory: 16201 loss_prob: 1.1503 loss_thr: 0.5568 loss_db: 0.1800 loss: 1.8870 2022/08/30 04:54:45 - mmengine - INFO - Epoch(train) [209][50/63] lr: 5.8970e-03 eta: 1 day, 2:02:18 time: 1.3550 data_time: 0.0462 memory: 16201 loss_prob: 1.0016 loss_thr: 0.5385 loss_db: 0.1636 loss: 1.7036 2022/08/30 04:54:52 - mmengine - INFO - Epoch(train) [209][55/63] lr: 5.8970e-03 eta: 1 day, 2:02:18 time: 1.3632 data_time: 0.0291 memory: 16201 loss_prob: 0.9426 loss_thr: 0.5079 loss_db: 0.1573 loss: 1.6078 2022/08/30 04:54:59 - mmengine - INFO - Epoch(train) [209][60/63] lr: 5.8970e-03 eta: 1 day, 2:01:59 time: 1.4061 data_time: 0.0280 memory: 16201 loss_prob: 0.9552 loss_thr: 0.5186 loss_db: 0.1574 loss: 1.6313 2022/08/30 04:55:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:55:11 - mmengine - INFO - Epoch(train) [210][5/63] lr: 5.8916e-03 eta: 1 day, 2:01:59 time: 1.5419 data_time: 0.2270 memory: 16201 loss_prob: 1.0587 loss_thr: 0.5351 loss_db: 0.1826 loss: 1.7763 2022/08/30 04:55:18 - mmengine - INFO - Epoch(train) [210][10/63] lr: 5.8916e-03 eta: 1 day, 2:01:23 time: 1.6103 data_time: 0.2401 memory: 16201 loss_prob: 1.0433 loss_thr: 0.5213 loss_db: 0.1713 loss: 1.7359 2022/08/30 04:55:26 - mmengine - INFO - Epoch(train) [210][15/63] lr: 5.8916e-03 eta: 1 day, 2:01:23 time: 1.4100 data_time: 0.0362 memory: 16201 loss_prob: 1.0463 loss_thr: 0.4830 loss_db: 0.1686 loss: 1.6978 2022/08/30 04:55:32 - mmengine - INFO - Epoch(train) [210][20/63] lr: 5.8916e-03 eta: 1 day, 2:01:01 time: 1.3594 data_time: 0.0407 memory: 16201 loss_prob: 1.0571 loss_thr: 0.4981 loss_db: 0.1707 loss: 1.7260 2022/08/30 04:55:38 - mmengine - INFO - Epoch(train) [210][25/63] lr: 5.8916e-03 eta: 1 day, 2:01:01 time: 1.2855 data_time: 0.0320 memory: 16201 loss_prob: 1.1285 loss_thr: 0.5446 loss_db: 0.1844 loss: 1.8574 2022/08/30 04:55:46 - mmengine - INFO - Epoch(train) [210][30/63] lr: 5.8916e-03 eta: 1 day, 2:00:45 time: 1.4786 data_time: 0.0362 memory: 16201 loss_prob: 1.0683 loss_thr: 0.5428 loss_db: 0.1760 loss: 1.7871 2022/08/30 04:55:53 - mmengine - INFO - Epoch(train) [210][35/63] lr: 5.8916e-03 eta: 1 day, 2:00:45 time: 1.4477 data_time: 0.0441 memory: 16201 loss_prob: 1.0725 loss_thr: 0.5324 loss_db: 0.1756 loss: 1.7805 2022/08/30 04:56:00 - mmengine - INFO - Epoch(train) [210][40/63] lr: 5.8916e-03 eta: 1 day, 2:00:25 time: 1.3932 data_time: 0.0317 memory: 16201 loss_prob: 1.1125 loss_thr: 0.5318 loss_db: 0.1909 loss: 1.8353 2022/08/30 04:56:06 - mmengine - INFO - Epoch(train) [210][45/63] lr: 5.8916e-03 eta: 1 day, 2:00:25 time: 1.3647 data_time: 0.0327 memory: 16201 loss_prob: 0.9348 loss_thr: 0.5134 loss_db: 0.1613 loss: 1.6095 2022/08/30 04:56:13 - mmengine - INFO - Epoch(train) [210][50/63] lr: 5.8916e-03 eta: 1 day, 2:00:00 time: 1.2811 data_time: 0.0372 memory: 16201 loss_prob: 0.8637 loss_thr: 0.5001 loss_db: 0.1452 loss: 1.5091 2022/08/30 04:56:20 - mmengine - INFO - Epoch(train) [210][55/63] lr: 5.8916e-03 eta: 1 day, 2:00:00 time: 1.3468 data_time: 0.0321 memory: 16201 loss_prob: 0.9493 loss_thr: 0.5041 loss_db: 0.1595 loss: 1.6128 2022/08/30 04:56:27 - mmengine - INFO - Epoch(train) [210][60/63] lr: 5.8916e-03 eta: 1 day, 1:59:37 time: 1.3386 data_time: 0.0352 memory: 16201 loss_prob: 1.0478 loss_thr: 0.5383 loss_db: 0.1689 loss: 1.7550 2022/08/30 04:56:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:56:39 - mmengine - INFO - Epoch(train) [211][5/63] lr: 5.8862e-03 eta: 1 day, 1:59:37 time: 1.4953 data_time: 0.2342 memory: 16201 loss_prob: 1.1474 loss_thr: 0.5614 loss_db: 0.1773 loss: 1.8862 2022/08/30 04:56:46 - mmengine - INFO - Epoch(train) [211][10/63] lr: 5.8862e-03 eta: 1 day, 1:58:58 time: 1.5449 data_time: 0.2485 memory: 16201 loss_prob: 1.0542 loss_thr: 0.5461 loss_db: 0.1703 loss: 1.7705 2022/08/30 04:56:52 - mmengine - INFO - Epoch(train) [211][15/63] lr: 5.8862e-03 eta: 1 day, 1:58:58 time: 1.3621 data_time: 0.0338 memory: 16201 loss_prob: 0.9593 loss_thr: 0.5250 loss_db: 0.1598 loss: 1.6441 2022/08/30 04:56:59 - mmengine - INFO - Epoch(train) [211][20/63] lr: 5.8862e-03 eta: 1 day, 1:58:37 time: 1.3655 data_time: 0.0352 memory: 16201 loss_prob: 0.9751 loss_thr: 0.5041 loss_db: 0.1554 loss: 1.6346 2022/08/30 04:57:06 - mmengine - INFO - Epoch(train) [211][25/63] lr: 5.8862e-03 eta: 1 day, 1:58:37 time: 1.3537 data_time: 0.0509 memory: 16201 loss_prob: 1.0714 loss_thr: 0.5165 loss_db: 0.1707 loss: 1.7586 2022/08/30 04:57:13 - mmengine - INFO - Epoch(train) [211][30/63] lr: 5.8862e-03 eta: 1 day, 1:58:14 time: 1.3370 data_time: 0.0349 memory: 16201 loss_prob: 1.0273 loss_thr: 0.5209 loss_db: 0.1668 loss: 1.7150 2022/08/30 04:57:20 - mmengine - INFO - Epoch(train) [211][35/63] lr: 5.8862e-03 eta: 1 day, 1:58:14 time: 1.4097 data_time: 0.0317 memory: 16201 loss_prob: 0.8793 loss_thr: 0.4922 loss_db: 0.1429 loss: 1.5145 2022/08/30 04:57:27 - mmengine - INFO - Epoch(train) [211][40/63] lr: 5.8862e-03 eta: 1 day, 1:57:55 time: 1.3952 data_time: 0.0337 memory: 16201 loss_prob: 0.8889 loss_thr: 0.5046 loss_db: 0.1459 loss: 1.5395 2022/08/30 04:57:34 - mmengine - INFO - Epoch(train) [211][45/63] lr: 5.8862e-03 eta: 1 day, 1:57:55 time: 1.4314 data_time: 0.0382 memory: 16201 loss_prob: 0.8712 loss_thr: 0.4983 loss_db: 0.1449 loss: 1.5145 2022/08/30 04:57:42 - mmengine - INFO - Epoch(train) [211][50/63] lr: 5.8862e-03 eta: 1 day, 1:57:39 time: 1.4805 data_time: 0.0517 memory: 16201 loss_prob: 0.7506 loss_thr: 0.4538 loss_db: 0.1272 loss: 1.3316 2022/08/30 04:57:49 - mmengine - INFO - Epoch(train) [211][55/63] lr: 5.8862e-03 eta: 1 day, 1:57:39 time: 1.4338 data_time: 0.0314 memory: 16201 loss_prob: 0.7495 loss_thr: 0.4827 loss_db: 0.1264 loss: 1.3587 2022/08/30 04:57:55 - mmengine - INFO - Epoch(train) [211][60/63] lr: 5.8862e-03 eta: 1 day, 1:57:17 time: 1.3587 data_time: 0.0273 memory: 16201 loss_prob: 0.8239 loss_thr: 0.5075 loss_db: 0.1383 loss: 1.4698 2022/08/30 04:57:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:58:08 - mmengine - INFO - Epoch(train) [212][5/63] lr: 5.8809e-03 eta: 1 day, 1:57:17 time: 1.4941 data_time: 0.2472 memory: 16201 loss_prob: 0.8273 loss_thr: 0.4825 loss_db: 0.1400 loss: 1.4498 2022/08/30 04:58:14 - mmengine - INFO - Epoch(train) [212][10/63] lr: 5.8809e-03 eta: 1 day, 1:56:41 time: 1.5998 data_time: 0.2686 memory: 16201 loss_prob: 0.7259 loss_thr: 0.4523 loss_db: 0.1214 loss: 1.2996 2022/08/30 04:58:20 - mmengine - INFO - Epoch(train) [212][15/63] lr: 5.8809e-03 eta: 1 day, 1:56:41 time: 1.2919 data_time: 0.0311 memory: 16201 loss_prob: 0.7185 loss_thr: 0.4709 loss_db: 0.1188 loss: 1.3082 2022/08/30 04:58:28 - mmengine - INFO - Epoch(train) [212][20/63] lr: 5.8809e-03 eta: 1 day, 1:56:19 time: 1.3381 data_time: 0.0320 memory: 16201 loss_prob: 0.7806 loss_thr: 0.4987 loss_db: 0.1316 loss: 1.4109 2022/08/30 04:58:35 - mmengine - INFO - Epoch(train) [212][25/63] lr: 5.8809e-03 eta: 1 day, 1:56:19 time: 1.4344 data_time: 0.0379 memory: 16201 loss_prob: 0.7742 loss_thr: 0.4841 loss_db: 0.1313 loss: 1.3896 2022/08/30 04:58:41 - mmengine - INFO - Epoch(train) [212][30/63] lr: 5.8809e-03 eta: 1 day, 1:55:57 time: 1.3483 data_time: 0.0277 memory: 16201 loss_prob: 0.7660 loss_thr: 0.4743 loss_db: 0.1314 loss: 1.3717 2022/08/30 04:58:48 - mmengine - INFO - Epoch(train) [212][35/63] lr: 5.8809e-03 eta: 1 day, 1:55:57 time: 1.2745 data_time: 0.0353 memory: 16201 loss_prob: 0.7765 loss_thr: 0.4743 loss_db: 0.1324 loss: 1.3832 2022/08/30 04:58:55 - mmengine - INFO - Epoch(train) [212][40/63] lr: 5.8809e-03 eta: 1 day, 1:55:34 time: 1.3344 data_time: 0.0314 memory: 16201 loss_prob: 0.8115 loss_thr: 0.4825 loss_db: 0.1348 loss: 1.4288 2022/08/30 04:59:01 - mmengine - INFO - Epoch(train) [212][45/63] lr: 5.8809e-03 eta: 1 day, 1:55:34 time: 1.3242 data_time: 0.0314 memory: 16201 loss_prob: 0.8740 loss_thr: 0.5100 loss_db: 0.1456 loss: 1.5295 2022/08/30 04:59:08 - mmengine - INFO - Epoch(train) [212][50/63] lr: 5.8809e-03 eta: 1 day, 1:55:11 time: 1.3378 data_time: 0.0465 memory: 16201 loss_prob: 0.8206 loss_thr: 0.4923 loss_db: 0.1385 loss: 1.4515 2022/08/30 04:59:14 - mmengine - INFO - Epoch(train) [212][55/63] lr: 5.8809e-03 eta: 1 day, 1:55:11 time: 1.3317 data_time: 0.0316 memory: 16201 loss_prob: 0.7981 loss_thr: 0.4742 loss_db: 0.1300 loss: 1.4023 2022/08/30 04:59:21 - mmengine - INFO - Epoch(train) [212][60/63] lr: 5.8809e-03 eta: 1 day, 1:54:48 time: 1.3172 data_time: 0.0335 memory: 16201 loss_prob: 0.8732 loss_thr: 0.4934 loss_db: 0.1426 loss: 1.5092 2022/08/30 04:59:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 04:59:33 - mmengine - INFO - Epoch(train) [213][5/63] lr: 5.8755e-03 eta: 1 day, 1:54:48 time: 1.5453 data_time: 0.2384 memory: 16201 loss_prob: 0.8151 loss_thr: 0.4883 loss_db: 0.1366 loss: 1.4400 2022/08/30 04:59:40 - mmengine - INFO - Epoch(train) [213][10/63] lr: 5.8755e-03 eta: 1 day, 1:54:10 time: 1.5585 data_time: 0.2589 memory: 16201 loss_prob: 0.8110 loss_thr: 0.4779 loss_db: 0.1374 loss: 1.4264 2022/08/30 04:59:47 - mmengine - INFO - Epoch(train) [213][15/63] lr: 5.8755e-03 eta: 1 day, 1:54:10 time: 1.3587 data_time: 0.0363 memory: 16201 loss_prob: 0.8255 loss_thr: 0.4981 loss_db: 0.1390 loss: 1.4627 2022/08/30 04:59:53 - mmengine - INFO - Epoch(train) [213][20/63] lr: 5.8755e-03 eta: 1 day, 1:53:48 time: 1.3349 data_time: 0.0292 memory: 16201 loss_prob: 0.8305 loss_thr: 0.4988 loss_db: 0.1381 loss: 1.4674 2022/08/30 05:00:00 - mmengine - INFO - Epoch(train) [213][25/63] lr: 5.8755e-03 eta: 1 day, 1:53:48 time: 1.2654 data_time: 0.0392 memory: 16201 loss_prob: 0.8312 loss_thr: 0.4940 loss_db: 0.1392 loss: 1.4645 2022/08/30 05:00:06 - mmengine - INFO - Epoch(train) [213][30/63] lr: 5.8755e-03 eta: 1 day, 1:53:23 time: 1.2975 data_time: 0.0304 memory: 16201 loss_prob: 0.8437 loss_thr: 0.4898 loss_db: 0.1392 loss: 1.4727 2022/08/30 05:00:12 - mmengine - INFO - Epoch(train) [213][35/63] lr: 5.8755e-03 eta: 1 day, 1:53:23 time: 1.2629 data_time: 0.0310 memory: 16201 loss_prob: 0.8608 loss_thr: 0.4815 loss_db: 0.1403 loss: 1.4826 2022/08/30 05:00:18 - mmengine - INFO - Epoch(train) [213][40/63] lr: 5.8755e-03 eta: 1 day, 1:52:57 time: 1.2410 data_time: 0.0303 memory: 16201 loss_prob: 0.7688 loss_thr: 0.4605 loss_db: 0.1295 loss: 1.3589 2022/08/30 05:00:25 - mmengine - INFO - Epoch(train) [213][45/63] lr: 5.8755e-03 eta: 1 day, 1:52:57 time: 1.3212 data_time: 0.0290 memory: 16201 loss_prob: 0.7008 loss_thr: 0.4472 loss_db: 0.1212 loss: 1.2691 2022/08/30 05:00:32 - mmengine - INFO - Epoch(train) [213][50/63] lr: 5.8755e-03 eta: 1 day, 1:52:34 time: 1.3295 data_time: 0.0437 memory: 16201 loss_prob: 0.7447 loss_thr: 0.4678 loss_db: 0.1280 loss: 1.3405 2022/08/30 05:00:38 - mmengine - INFO - Epoch(train) [213][55/63] lr: 5.8755e-03 eta: 1 day, 1:52:34 time: 1.3119 data_time: 0.0316 memory: 16201 loss_prob: 0.7372 loss_thr: 0.4634 loss_db: 0.1249 loss: 1.3254 2022/08/30 05:00:46 - mmengine - INFO - Epoch(train) [213][60/63] lr: 5.8755e-03 eta: 1 day, 1:52:13 time: 1.3735 data_time: 0.0345 memory: 16201 loss_prob: 0.7549 loss_thr: 0.4869 loss_db: 0.1283 loss: 1.3701 2022/08/30 05:00:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:00:58 - mmengine - INFO - Epoch(train) [214][5/63] lr: 5.8702e-03 eta: 1 day, 1:52:13 time: 1.4693 data_time: 0.2253 memory: 16201 loss_prob: 0.7828 loss_thr: 0.4907 loss_db: 0.1314 loss: 1.4049 2022/08/30 05:01:04 - mmengine - INFO - Epoch(train) [214][10/63] lr: 5.8702e-03 eta: 1 day, 1:51:35 time: 1.5439 data_time: 0.2373 memory: 16201 loss_prob: 0.7871 loss_thr: 0.4761 loss_db: 0.1260 loss: 1.3893 2022/08/30 05:01:11 - mmengine - INFO - Epoch(train) [214][15/63] lr: 5.8702e-03 eta: 1 day, 1:51:35 time: 1.3381 data_time: 0.0363 memory: 16201 loss_prob: 0.7711 loss_thr: 0.4647 loss_db: 0.1247 loss: 1.3605 2022/08/30 05:01:17 - mmengine - INFO - Epoch(train) [214][20/63] lr: 5.8702e-03 eta: 1 day, 1:51:11 time: 1.2989 data_time: 0.0368 memory: 16201 loss_prob: 0.7412 loss_thr: 0.4960 loss_db: 0.1254 loss: 1.3626 2022/08/30 05:01:25 - mmengine - INFO - Epoch(train) [214][25/63] lr: 5.8702e-03 eta: 1 day, 1:51:11 time: 1.3899 data_time: 0.0348 memory: 16201 loss_prob: 0.7920 loss_thr: 0.5144 loss_db: 0.1329 loss: 1.4393 2022/08/30 05:01:31 - mmengine - INFO - Epoch(train) [214][30/63] lr: 5.8702e-03 eta: 1 day, 1:50:51 time: 1.3989 data_time: 0.0401 memory: 16201 loss_prob: 0.8608 loss_thr: 0.5105 loss_db: 0.1393 loss: 1.5105 2022/08/30 05:01:38 - mmengine - INFO - Epoch(train) [214][35/63] lr: 5.8702e-03 eta: 1 day, 1:50:51 time: 1.2945 data_time: 0.0381 memory: 16201 loss_prob: 0.8544 loss_thr: 0.5094 loss_db: 0.1402 loss: 1.5039 2022/08/30 05:01:44 - mmengine - INFO - Epoch(train) [214][40/63] lr: 5.8702e-03 eta: 1 day, 1:50:26 time: 1.2824 data_time: 0.0310 memory: 16201 loss_prob: 0.8593 loss_thr: 0.5033 loss_db: 0.1458 loss: 1.5084 2022/08/30 05:01:51 - mmengine - INFO - Epoch(train) [214][45/63] lr: 5.8702e-03 eta: 1 day, 1:50:26 time: 1.3000 data_time: 0.0394 memory: 16201 loss_prob: 0.8625 loss_thr: 0.4973 loss_db: 0.1441 loss: 1.5038 2022/08/30 05:01:57 - mmengine - INFO - Epoch(train) [214][50/63] lr: 5.8702e-03 eta: 1 day, 1:50:02 time: 1.2873 data_time: 0.0376 memory: 16201 loss_prob: 0.7621 loss_thr: 0.4623 loss_db: 0.1269 loss: 1.3513 2022/08/30 05:02:04 - mmengine - INFO - Epoch(train) [214][55/63] lr: 5.8702e-03 eta: 1 day, 1:50:02 time: 1.3676 data_time: 0.0337 memory: 16201 loss_prob: 0.7179 loss_thr: 0.4497 loss_db: 0.1207 loss: 1.2883 2022/08/30 05:02:11 - mmengine - INFO - Epoch(train) [214][60/63] lr: 5.8702e-03 eta: 1 day, 1:49:42 time: 1.3850 data_time: 0.0378 memory: 16201 loss_prob: 0.7979 loss_thr: 0.4802 loss_db: 0.1382 loss: 1.4163 2022/08/30 05:02:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:02:23 - mmengine - INFO - Epoch(train) [215][5/63] lr: 5.8648e-03 eta: 1 day, 1:49:42 time: 1.5294 data_time: 0.2434 memory: 16201 loss_prob: 0.7477 loss_thr: 0.4768 loss_db: 0.1250 loss: 1.3495 2022/08/30 05:02:30 - mmengine - INFO - Epoch(train) [215][10/63] lr: 5.8648e-03 eta: 1 day, 1:49:04 time: 1.5551 data_time: 0.2527 memory: 16201 loss_prob: 0.7670 loss_thr: 0.4838 loss_db: 0.1295 loss: 1.3803 2022/08/30 05:02:37 - mmengine - INFO - Epoch(train) [215][15/63] lr: 5.8648e-03 eta: 1 day, 1:49:04 time: 1.3431 data_time: 0.0357 memory: 16201 loss_prob: 0.8303 loss_thr: 0.5207 loss_db: 0.1393 loss: 1.4903 2022/08/30 05:02:43 - mmengine - INFO - Epoch(train) [215][20/63] lr: 5.8648e-03 eta: 1 day, 1:48:38 time: 1.2536 data_time: 0.0323 memory: 16201 loss_prob: 0.7963 loss_thr: 0.4875 loss_db: 0.1335 loss: 1.4173 2022/08/30 05:02:49 - mmengine - INFO - Epoch(train) [215][25/63] lr: 5.8648e-03 eta: 1 day, 1:48:38 time: 1.2619 data_time: 0.0398 memory: 16201 loss_prob: 0.6874 loss_thr: 0.4477 loss_db: 0.1148 loss: 1.2499 2022/08/30 05:02:56 - mmengine - INFO - Epoch(train) [215][30/63] lr: 5.8648e-03 eta: 1 day, 1:48:16 time: 1.3370 data_time: 0.0388 memory: 16201 loss_prob: 0.7705 loss_thr: 0.4902 loss_db: 0.1230 loss: 1.3837 2022/08/30 05:03:03 - mmengine - INFO - Epoch(train) [215][35/63] lr: 5.8648e-03 eta: 1 day, 1:48:16 time: 1.3353 data_time: 0.0355 memory: 16201 loss_prob: 0.8195 loss_thr: 0.5040 loss_db: 0.1336 loss: 1.4570 2022/08/30 05:03:09 - mmengine - INFO - Epoch(train) [215][40/63] lr: 5.8648e-03 eta: 1 day, 1:47:52 time: 1.3123 data_time: 0.0353 memory: 16201 loss_prob: 0.8451 loss_thr: 0.5052 loss_db: 0.1397 loss: 1.4899 2022/08/30 05:03:16 - mmengine - INFO - Epoch(train) [215][45/63] lr: 5.8648e-03 eta: 1 day, 1:47:52 time: 1.3352 data_time: 0.0353 memory: 16201 loss_prob: 0.8826 loss_thr: 0.4971 loss_db: 0.1454 loss: 1.5251 2022/08/30 05:03:23 - mmengine - INFO - Epoch(train) [215][50/63] lr: 5.8648e-03 eta: 1 day, 1:47:32 time: 1.3879 data_time: 0.0388 memory: 16201 loss_prob: 0.8264 loss_thr: 0.4618 loss_db: 0.1402 loss: 1.4284 2022/08/30 05:03:30 - mmengine - INFO - Epoch(train) [215][55/63] lr: 5.8648e-03 eta: 1 day, 1:47:32 time: 1.3351 data_time: 0.0325 memory: 16201 loss_prob: 0.8191 loss_thr: 0.4653 loss_db: 0.1381 loss: 1.4225 2022/08/30 05:03:36 - mmengine - INFO - Epoch(train) [215][60/63] lr: 5.8648e-03 eta: 1 day, 1:47:07 time: 1.2706 data_time: 0.0294 memory: 16201 loss_prob: 0.7989 loss_thr: 0.4775 loss_db: 0.1329 loss: 1.4093 2022/08/30 05:03:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:03:48 - mmengine - INFO - Epoch(train) [216][5/63] lr: 5.8595e-03 eta: 1 day, 1:47:07 time: 1.4467 data_time: 0.2550 memory: 16201 loss_prob: 0.7744 loss_thr: 0.4837 loss_db: 0.1309 loss: 1.3890 2022/08/30 05:03:55 - mmengine - INFO - Epoch(train) [216][10/63] lr: 5.8595e-03 eta: 1 day, 1:46:34 time: 1.6431 data_time: 0.2756 memory: 16201 loss_prob: 0.8316 loss_thr: 0.4970 loss_db: 0.1434 loss: 1.4720 2022/08/30 05:04:01 - mmengine - INFO - Epoch(train) [216][15/63] lr: 5.8595e-03 eta: 1 day, 1:46:34 time: 1.3452 data_time: 0.0347 memory: 16201 loss_prob: 0.8437 loss_thr: 0.4856 loss_db: 0.1429 loss: 1.4723 2022/08/30 05:04:08 - mmengine - INFO - Epoch(train) [216][20/63] lr: 5.8595e-03 eta: 1 day, 1:46:12 time: 1.3441 data_time: 0.0277 memory: 16201 loss_prob: 0.8055 loss_thr: 0.4707 loss_db: 0.1320 loss: 1.4082 2022/08/30 05:04:15 - mmengine - INFO - Epoch(train) [216][25/63] lr: 5.8595e-03 eta: 1 day, 1:46:12 time: 1.3630 data_time: 0.0416 memory: 16201 loss_prob: 0.8487 loss_thr: 0.4969 loss_db: 0.1417 loss: 1.4873 2022/08/30 05:04:21 - mmengine - INFO - Epoch(train) [216][30/63] lr: 5.8595e-03 eta: 1 day, 1:45:46 time: 1.2470 data_time: 0.0322 memory: 16201 loss_prob: 0.8535 loss_thr: 0.4892 loss_db: 0.1461 loss: 1.4888 2022/08/30 05:04:27 - mmengine - INFO - Epoch(train) [216][35/63] lr: 5.8595e-03 eta: 1 day, 1:45:46 time: 1.2413 data_time: 0.0321 memory: 16201 loss_prob: 0.7472 loss_thr: 0.4652 loss_db: 0.1282 loss: 1.3405 2022/08/30 05:04:33 - mmengine - INFO - Epoch(train) [216][40/63] lr: 5.8595e-03 eta: 1 day, 1:45:19 time: 1.2486 data_time: 0.0352 memory: 16201 loss_prob: 0.6769 loss_thr: 0.4637 loss_db: 0.1146 loss: 1.2552 2022/08/30 05:04:41 - mmengine - INFO - Epoch(train) [216][45/63] lr: 5.8595e-03 eta: 1 day, 1:45:19 time: 1.3154 data_time: 0.0657 memory: 16201 loss_prob: 0.7305 loss_thr: 0.4561 loss_db: 0.1252 loss: 1.3118 2022/08/30 05:04:48 - mmengine - INFO - Epoch(train) [216][50/63] lr: 5.8595e-03 eta: 1 day, 1:45:01 time: 1.4236 data_time: 0.0722 memory: 16201 loss_prob: 0.8366 loss_thr: 0.4799 loss_db: 0.1403 loss: 1.4568 2022/08/30 05:04:54 - mmengine - INFO - Epoch(train) [216][55/63] lr: 5.8595e-03 eta: 1 day, 1:45:01 time: 1.3740 data_time: 0.0354 memory: 16201 loss_prob: 0.8208 loss_thr: 0.4828 loss_db: 0.1387 loss: 1.4423 2022/08/30 05:05:01 - mmengine - INFO - Epoch(train) [216][60/63] lr: 5.8595e-03 eta: 1 day, 1:44:39 time: 1.3293 data_time: 0.0492 memory: 16201 loss_prob: 0.8474 loss_thr: 0.4740 loss_db: 0.1442 loss: 1.4655 2022/08/30 05:05:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:05:13 - mmengine - INFO - Epoch(train) [217][5/63] lr: 5.8541e-03 eta: 1 day, 1:44:39 time: 1.4532 data_time: 0.2410 memory: 16201 loss_prob: 0.8976 loss_thr: 0.5093 loss_db: 0.1446 loss: 1.5515 2022/08/30 05:05:20 - mmengine - INFO - Epoch(train) [217][10/63] lr: 5.8541e-03 eta: 1 day, 1:44:04 time: 1.6035 data_time: 0.2697 memory: 16201 loss_prob: 0.8658 loss_thr: 0.5131 loss_db: 0.1452 loss: 1.5242 2022/08/30 05:05:27 - mmengine - INFO - Epoch(train) [217][15/63] lr: 5.8541e-03 eta: 1 day, 1:44:04 time: 1.3560 data_time: 0.0445 memory: 16201 loss_prob: 0.8107 loss_thr: 0.4943 loss_db: 0.1389 loss: 1.4440 2022/08/30 05:05:34 - mmengine - INFO - Epoch(train) [217][20/63] lr: 5.8541e-03 eta: 1 day, 1:43:42 time: 1.3552 data_time: 0.0319 memory: 16201 loss_prob: 0.8084 loss_thr: 0.4903 loss_db: 0.1331 loss: 1.4318 2022/08/30 05:05:40 - mmengine - INFO - Epoch(train) [217][25/63] lr: 5.8541e-03 eta: 1 day, 1:43:42 time: 1.3108 data_time: 0.0408 memory: 16201 loss_prob: 0.7890 loss_thr: 0.4789 loss_db: 0.1290 loss: 1.3969 2022/08/30 05:05:46 - mmengine - INFO - Epoch(train) [217][30/63] lr: 5.8541e-03 eta: 1 day, 1:43:16 time: 1.2388 data_time: 0.0310 memory: 16201 loss_prob: 0.8109 loss_thr: 0.4702 loss_db: 0.1333 loss: 1.4143 2022/08/30 05:05:53 - mmengine - INFO - Epoch(train) [217][35/63] lr: 5.8541e-03 eta: 1 day, 1:43:16 time: 1.3366 data_time: 0.0324 memory: 16201 loss_prob: 0.7983 loss_thr: 0.4755 loss_db: 0.1326 loss: 1.4065 2022/08/30 05:05:59 - mmengine - INFO - Epoch(train) [217][40/63] lr: 5.8541e-03 eta: 1 day, 1:42:53 time: 1.3221 data_time: 0.0325 memory: 16201 loss_prob: 0.7695 loss_thr: 0.4920 loss_db: 0.1278 loss: 1.3893 2022/08/30 05:06:06 - mmengine - INFO - Epoch(train) [217][45/63] lr: 5.8541e-03 eta: 1 day, 1:42:53 time: 1.2988 data_time: 0.0366 memory: 16201 loss_prob: 0.8183 loss_thr: 0.4979 loss_db: 0.1387 loss: 1.4549 2022/08/30 05:06:13 - mmengine - INFO - Epoch(train) [217][50/63] lr: 5.8541e-03 eta: 1 day, 1:42:33 time: 1.3866 data_time: 0.0444 memory: 16201 loss_prob: 0.8188 loss_thr: 0.4883 loss_db: 0.1383 loss: 1.4454 2022/08/30 05:06:20 - mmengine - INFO - Epoch(train) [217][55/63] lr: 5.8541e-03 eta: 1 day, 1:42:33 time: 1.3885 data_time: 0.0269 memory: 16201 loss_prob: 0.8062 loss_thr: 0.4813 loss_db: 0.1360 loss: 1.4235 2022/08/30 05:06:27 - mmengine - INFO - Epoch(train) [217][60/63] lr: 5.8541e-03 eta: 1 day, 1:42:13 time: 1.3786 data_time: 0.0333 memory: 16201 loss_prob: 0.7946 loss_thr: 0.4723 loss_db: 0.1359 loss: 1.4028 2022/08/30 05:06:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:06:38 - mmengine - INFO - Epoch(train) [218][5/63] lr: 5.8487e-03 eta: 1 day, 1:42:13 time: 1.4351 data_time: 0.2274 memory: 16201 loss_prob: 0.8694 loss_thr: 0.4998 loss_db: 0.1445 loss: 1.5136 2022/08/30 05:06:45 - mmengine - INFO - Epoch(train) [218][10/63] lr: 5.8487e-03 eta: 1 day, 1:41:38 time: 1.5966 data_time: 0.2372 memory: 16201 loss_prob: 0.8322 loss_thr: 0.4811 loss_db: 0.1380 loss: 1.4513 2022/08/30 05:06:52 - mmengine - INFO - Epoch(train) [218][15/63] lr: 5.8487e-03 eta: 1 day, 1:41:38 time: 1.3855 data_time: 0.0403 memory: 16201 loss_prob: 0.7735 loss_thr: 0.4762 loss_db: 0.1299 loss: 1.3796 2022/08/30 05:06:59 - mmengine - INFO - Epoch(train) [218][20/63] lr: 5.8487e-03 eta: 1 day, 1:41:15 time: 1.3177 data_time: 0.0423 memory: 16201 loss_prob: 0.7299 loss_thr: 0.4590 loss_db: 0.1242 loss: 1.3130 2022/08/30 05:07:06 - mmengine - INFO - Epoch(train) [218][25/63] lr: 5.8487e-03 eta: 1 day, 1:41:15 time: 1.3448 data_time: 0.0388 memory: 16201 loss_prob: 0.7614 loss_thr: 0.4655 loss_db: 0.1273 loss: 1.3543 2022/08/30 05:07:12 - mmengine - INFO - Epoch(train) [218][30/63] lr: 5.8487e-03 eta: 1 day, 1:40:53 time: 1.3380 data_time: 0.0368 memory: 16201 loss_prob: 0.8009 loss_thr: 0.4711 loss_db: 0.1332 loss: 1.4052 2022/08/30 05:07:18 - mmengine - INFO - Epoch(train) [218][35/63] lr: 5.8487e-03 eta: 1 day, 1:40:53 time: 1.2477 data_time: 0.0332 memory: 16201 loss_prob: 0.8204 loss_thr: 0.4789 loss_db: 0.1353 loss: 1.4346 2022/08/30 05:07:25 - mmengine - INFO - Epoch(train) [218][40/63] lr: 5.8487e-03 eta: 1 day, 1:40:30 time: 1.3157 data_time: 0.0371 memory: 16201 loss_prob: 0.8093 loss_thr: 0.4971 loss_db: 0.1362 loss: 1.4426 2022/08/30 05:07:31 - mmengine - INFO - Epoch(train) [218][45/63] lr: 5.8487e-03 eta: 1 day, 1:40:30 time: 1.3452 data_time: 0.0373 memory: 16201 loss_prob: 0.7693 loss_thr: 0.4894 loss_db: 0.1312 loss: 1.3898 2022/08/30 05:07:38 - mmengine - INFO - Epoch(train) [218][50/63] lr: 5.8487e-03 eta: 1 day, 1:40:06 time: 1.2820 data_time: 0.0339 memory: 16201 loss_prob: 0.7913 loss_thr: 0.4873 loss_db: 0.1324 loss: 1.4110 2022/08/30 05:07:46 - mmengine - INFO - Epoch(train) [218][55/63] lr: 5.8487e-03 eta: 1 day, 1:40:06 time: 1.4499 data_time: 0.0348 memory: 16201 loss_prob: 0.7924 loss_thr: 0.4981 loss_db: 0.1347 loss: 1.4252 2022/08/30 05:07:52 - mmengine - INFO - Epoch(train) [218][60/63] lr: 5.8487e-03 eta: 1 day, 1:39:47 time: 1.4143 data_time: 0.0415 memory: 16201 loss_prob: 0.8870 loss_thr: 0.5424 loss_db: 0.1519 loss: 1.5813 2022/08/30 05:07:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:08:04 - mmengine - INFO - Epoch(train) [219][5/63] lr: 5.8434e-03 eta: 1 day, 1:39:47 time: 1.4564 data_time: 0.2345 memory: 16201 loss_prob: 0.9247 loss_thr: 0.5181 loss_db: 0.1485 loss: 1.5914 2022/08/30 05:08:11 - mmengine - INFO - Epoch(train) [219][10/63] lr: 5.8434e-03 eta: 1 day, 1:39:09 time: 1.5120 data_time: 0.2418 memory: 16201 loss_prob: 0.7727 loss_thr: 0.4701 loss_db: 0.1293 loss: 1.3721 2022/08/30 05:08:17 - mmengine - INFO - Epoch(train) [219][15/63] lr: 5.8434e-03 eta: 1 day, 1:39:09 time: 1.3045 data_time: 0.0325 memory: 16201 loss_prob: 0.7319 loss_thr: 0.4800 loss_db: 0.1266 loss: 1.3385 2022/08/30 05:08:24 - mmengine - INFO - Epoch(train) [219][20/63] lr: 5.8434e-03 eta: 1 day, 1:38:46 time: 1.3212 data_time: 0.0339 memory: 16201 loss_prob: 0.7946 loss_thr: 0.4813 loss_db: 0.1349 loss: 1.4108 2022/08/30 05:08:31 - mmengine - INFO - Epoch(train) [219][25/63] lr: 5.8434e-03 eta: 1 day, 1:38:46 time: 1.3462 data_time: 0.0400 memory: 16201 loss_prob: 0.7613 loss_thr: 0.4435 loss_db: 0.1272 loss: 1.3320 2022/08/30 05:08:38 - mmengine - INFO - Epoch(train) [219][30/63] lr: 5.8434e-03 eta: 1 day, 1:38:25 time: 1.3620 data_time: 0.0326 memory: 16201 loss_prob: 0.7397 loss_thr: 0.4402 loss_db: 0.1252 loss: 1.3051 2022/08/30 05:08:44 - mmengine - INFO - Epoch(train) [219][35/63] lr: 5.8434e-03 eta: 1 day, 1:38:25 time: 1.3114 data_time: 0.0291 memory: 16201 loss_prob: 0.7371 loss_thr: 0.4412 loss_db: 0.1254 loss: 1.3038 2022/08/30 05:08:51 - mmengine - INFO - Epoch(train) [219][40/63] lr: 5.8434e-03 eta: 1 day, 1:38:02 time: 1.3204 data_time: 0.0283 memory: 16201 loss_prob: 0.7121 loss_thr: 0.4594 loss_db: 0.1194 loss: 1.2909 2022/08/30 05:08:58 - mmengine - INFO - Epoch(train) [219][45/63] lr: 5.8434e-03 eta: 1 day, 1:38:02 time: 1.3682 data_time: 0.0331 memory: 16201 loss_prob: 0.7344 loss_thr: 0.4667 loss_db: 0.1235 loss: 1.3246 2022/08/30 05:09:04 - mmengine - INFO - Epoch(train) [219][50/63] lr: 5.8434e-03 eta: 1 day, 1:37:40 time: 1.3153 data_time: 0.0402 memory: 16201 loss_prob: 0.7393 loss_thr: 0.4563 loss_db: 0.1234 loss: 1.3190 2022/08/30 05:09:10 - mmengine - INFO - Epoch(train) [219][55/63] lr: 5.8434e-03 eta: 1 day, 1:37:40 time: 1.2678 data_time: 0.0320 memory: 16201 loss_prob: 0.7564 loss_thr: 0.4618 loss_db: 0.1269 loss: 1.3451 2022/08/30 05:09:16 - mmengine - INFO - Epoch(train) [219][60/63] lr: 5.8434e-03 eta: 1 day, 1:37:13 time: 1.2334 data_time: 0.0322 memory: 16201 loss_prob: 0.8005 loss_thr: 0.4893 loss_db: 0.1368 loss: 1.4265 2022/08/30 05:09:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:09:28 - mmengine - INFO - Epoch(train) [220][5/63] lr: 5.8380e-03 eta: 1 day, 1:37:13 time: 1.4529 data_time: 0.2188 memory: 16201 loss_prob: 0.7725 loss_thr: 0.4777 loss_db: 0.1309 loss: 1.3810 2022/08/30 05:09:36 - mmengine - INFO - Epoch(train) [220][10/63] lr: 5.8380e-03 eta: 1 day, 1:36:40 time: 1.6398 data_time: 0.2366 memory: 16201 loss_prob: 0.7214 loss_thr: 0.4633 loss_db: 0.1214 loss: 1.3061 2022/08/30 05:09:43 - mmengine - INFO - Epoch(train) [220][15/63] lr: 5.8380e-03 eta: 1 day, 1:36:40 time: 1.4347 data_time: 0.0375 memory: 16201 loss_prob: 0.7698 loss_thr: 0.4796 loss_db: 0.1303 loss: 1.3797 2022/08/30 05:09:50 - mmengine - INFO - Epoch(train) [220][20/63] lr: 5.8380e-03 eta: 1 day, 1:36:21 time: 1.3868 data_time: 0.0333 memory: 16201 loss_prob: 0.8041 loss_thr: 0.4709 loss_db: 0.1339 loss: 1.4088 2022/08/30 05:09:57 - mmengine - INFO - Epoch(train) [220][25/63] lr: 5.8380e-03 eta: 1 day, 1:36:21 time: 1.4130 data_time: 0.0385 memory: 16201 loss_prob: 0.8117 loss_thr: 0.4710 loss_db: 0.1350 loss: 1.4177 2022/08/30 05:10:03 - mmengine - INFO - Epoch(train) [220][30/63] lr: 5.8380e-03 eta: 1 day, 1:35:58 time: 1.3300 data_time: 0.0389 memory: 16201 loss_prob: 0.7718 loss_thr: 0.4635 loss_db: 0.1301 loss: 1.3655 2022/08/30 05:10:10 - mmengine - INFO - Epoch(train) [220][35/63] lr: 5.8380e-03 eta: 1 day, 1:35:58 time: 1.2880 data_time: 0.0398 memory: 16201 loss_prob: 0.7492 loss_thr: 0.4589 loss_db: 0.1259 loss: 1.3341 2022/08/30 05:10:17 - mmengine - INFO - Epoch(train) [220][40/63] lr: 5.8380e-03 eta: 1 day, 1:35:37 time: 1.3467 data_time: 0.0318 memory: 16201 loss_prob: 0.7465 loss_thr: 0.4872 loss_db: 0.1254 loss: 1.3591 2022/08/30 05:10:24 - mmengine - INFO - Epoch(train) [220][45/63] lr: 5.8380e-03 eta: 1 day, 1:35:37 time: 1.4603 data_time: 0.0363 memory: 16201 loss_prob: 0.7711 loss_thr: 0.4911 loss_db: 0.1293 loss: 1.3915 2022/08/30 05:10:31 - mmengine - INFO - Epoch(train) [220][50/63] lr: 5.8380e-03 eta: 1 day, 1:35:22 time: 1.4837 data_time: 0.0469 memory: 16201 loss_prob: 0.7962 loss_thr: 0.4801 loss_db: 0.1360 loss: 1.4124 2022/08/30 05:10:38 - mmengine - INFO - Epoch(train) [220][55/63] lr: 5.8380e-03 eta: 1 day, 1:35:22 time: 1.3890 data_time: 0.0397 memory: 16201 loss_prob: 0.7328 loss_thr: 0.4704 loss_db: 0.1264 loss: 1.3297 2022/08/30 05:10:45 - mmengine - INFO - Epoch(train) [220][60/63] lr: 5.8380e-03 eta: 1 day, 1:35:01 time: 1.3602 data_time: 0.0319 memory: 16201 loss_prob: 0.7714 loss_thr: 0.4979 loss_db: 0.1286 loss: 1.3979 2022/08/30 05:10:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:10:48 - mmengine - INFO - Saving checkpoint at 220 epochs 2022/08/30 05:10:56 - mmengine - INFO - Epoch(val) [220][5/32] eta: 1 day, 1:35:01 time: 0.6818 data_time: 0.1435 memory: 16201 2022/08/30 05:11:00 - mmengine - INFO - Epoch(val) [220][10/32] eta: 0:00:17 time: 0.8021 data_time: 0.1829 memory: 15734 2022/08/30 05:11:03 - mmengine - INFO - Epoch(val) [220][15/32] eta: 0:00:17 time: 0.6669 data_time: 0.0571 memory: 15734 2022/08/30 05:11:07 - mmengine - INFO - Epoch(val) [220][20/32] eta: 0:00:08 time: 0.7150 data_time: 0.0688 memory: 15734 2022/08/30 05:11:10 - mmengine - INFO - Epoch(val) [220][25/32] eta: 0:00:08 time: 0.7350 data_time: 0.0690 memory: 15734 2022/08/30 05:11:13 - mmengine - INFO - Epoch(val) [220][30/32] eta: 0:00:01 time: 0.6158 data_time: 0.0269 memory: 15734 2022/08/30 05:11:14 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 05:11:14 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8219, precision: 0.7686, hmean: 0.7943 2022/08/30 05:11:14 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8214, precision: 0.8182, hmean: 0.8198 2022/08/30 05:11:14 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8185, precision: 0.8462, hmean: 0.8321 2022/08/30 05:11:14 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8031, precision: 0.8747, hmean: 0.8373 2022/08/30 05:11:14 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7689, precision: 0.9074, hmean: 0.8324 2022/08/30 05:11:14 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5455, precision: 0.9634, hmean: 0.6966 2022/08/30 05:11:14 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0318, precision: 1.0000, hmean: 0.0616 2022/08/30 05:11:14 - mmengine - INFO - Epoch(val) [220][32/32] icdar/precision: 0.8747 icdar/recall: 0.8031 icdar/hmean: 0.8373 2022/08/30 05:11:24 - mmengine - INFO - Epoch(train) [221][5/63] lr: 5.8327e-03 eta: 0:00:01 time: 1.5442 data_time: 0.2215 memory: 16201 loss_prob: 0.8444 loss_thr: 0.5130 loss_db: 0.1360 loss: 1.4934 2022/08/30 05:11:31 - mmengine - INFO - Epoch(train) [221][10/63] lr: 5.8327e-03 eta: 1 day, 1:34:28 time: 1.6397 data_time: 0.2286 memory: 16201 loss_prob: 0.7536 loss_thr: 0.4742 loss_db: 0.1256 loss: 1.3535 2022/08/30 05:11:37 - mmengine - INFO - Epoch(train) [221][15/63] lr: 5.8327e-03 eta: 1 day, 1:34:28 time: 1.3522 data_time: 0.0298 memory: 16201 loss_prob: 0.7279 loss_thr: 0.4587 loss_db: 0.1251 loss: 1.3117 2022/08/30 05:11:45 - mmengine - INFO - Epoch(train) [221][20/63] lr: 5.8327e-03 eta: 1 day, 1:34:08 time: 1.3832 data_time: 0.0304 memory: 16201 loss_prob: 0.7398 loss_thr: 0.4621 loss_db: 0.1237 loss: 1.3255 2022/08/30 05:11:52 - mmengine - INFO - Epoch(train) [221][25/63] lr: 5.8327e-03 eta: 1 day, 1:34:08 time: 1.4255 data_time: 0.0355 memory: 16201 loss_prob: 0.7422 loss_thr: 0.4608 loss_db: 0.1243 loss: 1.3272 2022/08/30 05:11:58 - mmengine - INFO - Epoch(train) [221][30/63] lr: 5.8327e-03 eta: 1 day, 1:33:47 time: 1.3548 data_time: 0.0336 memory: 16201 loss_prob: 0.6894 loss_thr: 0.4370 loss_db: 0.1184 loss: 1.2448 2022/08/30 05:12:05 - mmengine - INFO - Epoch(train) [221][35/63] lr: 5.8327e-03 eta: 1 day, 1:33:47 time: 1.3181 data_time: 0.0358 memory: 16201 loss_prob: 0.7241 loss_thr: 0.4496 loss_db: 0.1236 loss: 1.2973 2022/08/30 05:12:11 - mmengine - INFO - Epoch(train) [221][40/63] lr: 5.8327e-03 eta: 1 day, 1:33:26 time: 1.3335 data_time: 0.0315 memory: 16201 loss_prob: 0.8288 loss_thr: 0.4899 loss_db: 0.1399 loss: 1.4586 2022/08/30 05:12:18 - mmengine - INFO - Epoch(train) [221][45/63] lr: 5.8327e-03 eta: 1 day, 1:33:26 time: 1.3107 data_time: 0.0317 memory: 16201 loss_prob: 0.7920 loss_thr: 0.4820 loss_db: 0.1309 loss: 1.4049 2022/08/30 05:12:24 - mmengine - INFO - Epoch(train) [221][50/63] lr: 5.8327e-03 eta: 1 day, 1:33:02 time: 1.2884 data_time: 0.0479 memory: 16201 loss_prob: 0.7343 loss_thr: 0.4630 loss_db: 0.1243 loss: 1.3216 2022/08/30 05:12:30 - mmengine - INFO - Epoch(train) [221][55/63] lr: 5.8327e-03 eta: 1 day, 1:33:02 time: 1.2467 data_time: 0.0426 memory: 16201 loss_prob: 0.8068 loss_thr: 0.4886 loss_db: 0.1416 loss: 1.4370 2022/08/30 05:12:37 - mmengine - INFO - Epoch(train) [221][60/63] lr: 5.8327e-03 eta: 1 day, 1:32:37 time: 1.2779 data_time: 0.0309 memory: 16201 loss_prob: 0.8204 loss_thr: 0.5020 loss_db: 0.1408 loss: 1.4631 2022/08/30 05:12:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:12:49 - mmengine - INFO - Epoch(train) [222][5/63] lr: 5.8273e-03 eta: 1 day, 1:32:37 time: 1.4050 data_time: 0.2315 memory: 16201 loss_prob: 0.9769 loss_thr: 0.4961 loss_db: 0.1470 loss: 1.6199 2022/08/30 05:12:56 - mmengine - INFO - Epoch(train) [222][10/63] lr: 5.8273e-03 eta: 1 day, 1:32:00 time: 1.5442 data_time: 0.2391 memory: 16201 loss_prob: 0.9854 loss_thr: 0.4827 loss_db: 0.1485 loss: 1.6167 2022/08/30 05:13:02 - mmengine - INFO - Epoch(train) [222][15/63] lr: 5.8273e-03 eta: 1 day, 1:32:00 time: 1.3572 data_time: 0.0330 memory: 16201 loss_prob: 0.8658 loss_thr: 0.4937 loss_db: 0.1481 loss: 1.5076 2022/08/30 05:13:08 - mmengine - INFO - Epoch(train) [222][20/63] lr: 5.8273e-03 eta: 1 day, 1:31:37 time: 1.2953 data_time: 0.0335 memory: 16201 loss_prob: 1.0493 loss_thr: 0.5134 loss_db: 0.1710 loss: 1.7338 2022/08/30 05:13:15 - mmengine - INFO - Epoch(train) [222][25/63] lr: 5.8273e-03 eta: 1 day, 1:31:37 time: 1.2286 data_time: 0.0323 memory: 16201 loss_prob: 1.1009 loss_thr: 0.5443 loss_db: 0.1754 loss: 1.8206 2022/08/30 05:13:21 - mmengine - INFO - Epoch(train) [222][30/63] lr: 5.8273e-03 eta: 1 day, 1:31:12 time: 1.2650 data_time: 0.0285 memory: 16201 loss_prob: 0.9539 loss_thr: 0.5392 loss_db: 0.1628 loss: 1.6558 2022/08/30 05:13:28 - mmengine - INFO - Epoch(train) [222][35/63] lr: 5.8273e-03 eta: 1 day, 1:31:12 time: 1.3074 data_time: 0.0353 memory: 16201 loss_prob: 0.9460 loss_thr: 0.5142 loss_db: 0.1598 loss: 1.6200 2022/08/30 05:13:34 - mmengine - INFO - Epoch(train) [222][40/63] lr: 5.8273e-03 eta: 1 day, 1:30:47 time: 1.2685 data_time: 0.0338 memory: 16201 loss_prob: 0.9618 loss_thr: 0.5246 loss_db: 0.1575 loss: 1.6439 2022/08/30 05:13:41 - mmengine - INFO - Epoch(train) [222][45/63] lr: 5.8273e-03 eta: 1 day, 1:30:47 time: 1.3119 data_time: 0.0309 memory: 16201 loss_prob: 0.9023 loss_thr: 0.5222 loss_db: 0.1503 loss: 1.5748 2022/08/30 05:13:48 - mmengine - INFO - Epoch(train) [222][50/63] lr: 5.8273e-03 eta: 1 day, 1:30:29 time: 1.4224 data_time: 0.0399 memory: 16201 loss_prob: 0.8754 loss_thr: 0.5199 loss_db: 0.1479 loss: 1.5432 2022/08/30 05:13:54 - mmengine - INFO - Epoch(train) [222][55/63] lr: 5.8273e-03 eta: 1 day, 1:30:29 time: 1.3659 data_time: 0.0386 memory: 16201 loss_prob: 0.8579 loss_thr: 0.5021 loss_db: 0.1433 loss: 1.5034 2022/08/30 05:14:01 - mmengine - INFO - Epoch(train) [222][60/63] lr: 5.8273e-03 eta: 1 day, 1:30:08 time: 1.3318 data_time: 0.0349 memory: 16201 loss_prob: 0.9102 loss_thr: 0.5131 loss_db: 0.1508 loss: 1.5742 2022/08/30 05:14:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:14:14 - mmengine - INFO - Epoch(train) [223][5/63] lr: 5.8219e-03 eta: 1 day, 1:30:08 time: 1.5164 data_time: 0.2277 memory: 16201 loss_prob: 0.8736 loss_thr: 0.5016 loss_db: 0.1483 loss: 1.5236 2022/08/30 05:14:21 - mmengine - INFO - Epoch(train) [223][10/63] lr: 5.8219e-03 eta: 1 day, 1:29:35 time: 1.6417 data_time: 0.2309 memory: 16201 loss_prob: 0.8655 loss_thr: 0.5132 loss_db: 0.1450 loss: 1.5237 2022/08/30 05:14:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:14:28 - mmengine - INFO - Epoch(train) [223][15/63] lr: 5.8219e-03 eta: 1 day, 1:29:35 time: 1.4309 data_time: 0.0358 memory: 16201 loss_prob: 0.8106 loss_thr: 0.4944 loss_db: 0.1337 loss: 1.4388 2022/08/30 05:14:34 - mmengine - INFO - Epoch(train) [223][20/63] lr: 5.8219e-03 eta: 1 day, 1:29:14 time: 1.3411 data_time: 0.0426 memory: 16201 loss_prob: 0.8225 loss_thr: 0.4743 loss_db: 0.1387 loss: 1.4355 2022/08/30 05:14:41 - mmengine - INFO - Epoch(train) [223][25/63] lr: 5.8219e-03 eta: 1 day, 1:29:14 time: 1.3062 data_time: 0.0313 memory: 16201 loss_prob: 0.8719 loss_thr: 0.4850 loss_db: 0.1490 loss: 1.5059 2022/08/30 05:14:47 - mmengine - INFO - Epoch(train) [223][30/63] lr: 5.8219e-03 eta: 1 day, 1:28:51 time: 1.3161 data_time: 0.0320 memory: 16201 loss_prob: 0.8988 loss_thr: 0.5017 loss_db: 0.1489 loss: 1.5494 2022/08/30 05:14:54 - mmengine - INFO - Epoch(train) [223][35/63] lr: 5.8219e-03 eta: 1 day, 1:28:51 time: 1.2943 data_time: 0.0376 memory: 16201 loss_prob: 0.8823 loss_thr: 0.5097 loss_db: 0.1433 loss: 1.5352 2022/08/30 05:15:01 - mmengine - INFO - Epoch(train) [223][40/63] lr: 5.8219e-03 eta: 1 day, 1:28:29 time: 1.3275 data_time: 0.0297 memory: 16201 loss_prob: 0.8968 loss_thr: 0.5310 loss_db: 0.1469 loss: 1.5747 2022/08/30 05:15:08 - mmengine - INFO - Epoch(train) [223][45/63] lr: 5.8219e-03 eta: 1 day, 1:28:29 time: 1.3553 data_time: 0.0387 memory: 16201 loss_prob: 0.8904 loss_thr: 0.5236 loss_db: 0.1496 loss: 1.5636 2022/08/30 05:15:14 - mmengine - INFO - Epoch(train) [223][50/63] lr: 5.8219e-03 eta: 1 day, 1:28:06 time: 1.3090 data_time: 0.0358 memory: 16201 loss_prob: 0.8169 loss_thr: 0.4898 loss_db: 0.1372 loss: 1.4439 2022/08/30 05:15:22 - mmengine - INFO - Epoch(train) [223][55/63] lr: 5.8219e-03 eta: 1 day, 1:28:06 time: 1.4671 data_time: 0.0276 memory: 16201 loss_prob: 0.7904 loss_thr: 0.4737 loss_db: 0.1285 loss: 1.3926 2022/08/30 05:15:30 - mmengine - INFO - Epoch(train) [223][60/63] lr: 5.8219e-03 eta: 1 day, 1:27:57 time: 1.6121 data_time: 0.0470 memory: 16201 loss_prob: 0.7387 loss_thr: 0.4540 loss_db: 0.1239 loss: 1.3165 2022/08/30 05:15:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:15:43 - mmengine - INFO - Epoch(train) [224][5/63] lr: 5.8166e-03 eta: 1 day, 1:27:57 time: 1.6115 data_time: 0.2546 memory: 16201 loss_prob: 0.7306 loss_thr: 0.4598 loss_db: 0.1243 loss: 1.3147 2022/08/30 05:15:51 - mmengine - INFO - Epoch(train) [224][10/63] lr: 5.8166e-03 eta: 1 day, 1:27:30 time: 1.7704 data_time: 0.2661 memory: 16201 loss_prob: 0.8383 loss_thr: 0.4677 loss_db: 0.1321 loss: 1.4381 2022/08/30 05:15:58 - mmengine - INFO - Epoch(train) [224][15/63] lr: 5.8166e-03 eta: 1 day, 1:27:30 time: 1.5229 data_time: 0.0370 memory: 16201 loss_prob: 0.8908 loss_thr: 0.4854 loss_db: 0.1400 loss: 1.5162 2022/08/30 05:16:05 - mmengine - INFO - Epoch(train) [224][20/63] lr: 5.8166e-03 eta: 1 day, 1:27:11 time: 1.3965 data_time: 0.0371 memory: 16201 loss_prob: 0.7807 loss_thr: 0.4606 loss_db: 0.1278 loss: 1.3691 2022/08/30 05:16:13 - mmengine - INFO - Epoch(train) [224][25/63] lr: 5.8166e-03 eta: 1 day, 1:27:11 time: 1.4570 data_time: 0.0469 memory: 16201 loss_prob: 0.7948 loss_thr: 0.4885 loss_db: 0.1318 loss: 1.4151 2022/08/30 05:16:20 - mmengine - INFO - Epoch(train) [224][30/63] lr: 5.8166e-03 eta: 1 day, 1:26:55 time: 1.4592 data_time: 0.0342 memory: 16201 loss_prob: 0.8374 loss_thr: 0.5109 loss_db: 0.1415 loss: 1.4898 2022/08/30 05:16:26 - mmengine - INFO - Epoch(train) [224][35/63] lr: 5.8166e-03 eta: 1 day, 1:26:55 time: 1.2864 data_time: 0.0274 memory: 16201 loss_prob: 0.8206 loss_thr: 0.4947 loss_db: 0.1365 loss: 1.4519 2022/08/30 05:16:32 - mmengine - INFO - Epoch(train) [224][40/63] lr: 5.8166e-03 eta: 1 day, 1:26:30 time: 1.2578 data_time: 0.0292 memory: 16201 loss_prob: 0.7561 loss_thr: 0.4802 loss_db: 0.1251 loss: 1.3614 2022/08/30 05:16:39 - mmengine - INFO - Epoch(train) [224][45/63] lr: 5.8166e-03 eta: 1 day, 1:26:30 time: 1.2957 data_time: 0.0312 memory: 16201 loss_prob: 0.7423 loss_thr: 0.4629 loss_db: 0.1227 loss: 1.3279 2022/08/30 05:16:45 - mmengine - INFO - Epoch(train) [224][50/63] lr: 5.8166e-03 eta: 1 day, 1:26:07 time: 1.2894 data_time: 0.0382 memory: 16201 loss_prob: 0.8034 loss_thr: 0.4819 loss_db: 0.1350 loss: 1.4203 2022/08/30 05:16:53 - mmengine - INFO - Epoch(train) [224][55/63] lr: 5.8166e-03 eta: 1 day, 1:26:07 time: 1.3979 data_time: 0.0296 memory: 16201 loss_prob: 0.8209 loss_thr: 0.4935 loss_db: 0.1401 loss: 1.4546 2022/08/30 05:16:59 - mmengine - INFO - Epoch(train) [224][60/63] lr: 5.8166e-03 eta: 1 day, 1:25:48 time: 1.4121 data_time: 0.0306 memory: 16201 loss_prob: 0.7857 loss_thr: 0.4732 loss_db: 0.1323 loss: 1.3911 2022/08/30 05:17:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:17:11 - mmengine - INFO - Epoch(train) [225][5/63] lr: 5.8112e-03 eta: 1 day, 1:25:48 time: 1.3965 data_time: 0.2246 memory: 16201 loss_prob: 0.8371 loss_thr: 0.4971 loss_db: 0.1427 loss: 1.4769 2022/08/30 05:17:18 - mmengine - INFO - Epoch(train) [225][10/63] lr: 5.8112e-03 eta: 1 day, 1:25:15 time: 1.6091 data_time: 0.2437 memory: 16201 loss_prob: 0.8440 loss_thr: 0.5089 loss_db: 0.1441 loss: 1.4970 2022/08/30 05:17:25 - mmengine - INFO - Epoch(train) [225][15/63] lr: 5.8112e-03 eta: 1 day, 1:25:15 time: 1.4411 data_time: 0.0306 memory: 16201 loss_prob: 0.8152 loss_thr: 0.5051 loss_db: 0.1362 loss: 1.4565 2022/08/30 05:17:32 - mmengine - INFO - Epoch(train) [225][20/63] lr: 5.8112e-03 eta: 1 day, 1:24:55 time: 1.3777 data_time: 0.0350 memory: 16201 loss_prob: 0.7903 loss_thr: 0.4913 loss_db: 0.1287 loss: 1.4103 2022/08/30 05:17:39 - mmengine - INFO - Epoch(train) [225][25/63] lr: 5.8112e-03 eta: 1 day, 1:24:55 time: 1.4008 data_time: 0.0410 memory: 16201 loss_prob: 0.8502 loss_thr: 0.5111 loss_db: 0.1422 loss: 1.5035 2022/08/30 05:17:46 - mmengine - INFO - Epoch(train) [225][30/63] lr: 5.8112e-03 eta: 1 day, 1:24:36 time: 1.3981 data_time: 0.0273 memory: 16201 loss_prob: 0.8043 loss_thr: 0.4888 loss_db: 0.1375 loss: 1.4305 2022/08/30 05:17:53 - mmengine - INFO - Epoch(train) [225][35/63] lr: 5.8112e-03 eta: 1 day, 1:24:36 time: 1.3585 data_time: 0.0381 memory: 16201 loss_prob: 0.8330 loss_thr: 0.5003 loss_db: 0.1419 loss: 1.4753 2022/08/30 05:18:00 - mmengine - INFO - Epoch(train) [225][40/63] lr: 5.8112e-03 eta: 1 day, 1:24:16 time: 1.3546 data_time: 0.0312 memory: 16201 loss_prob: 0.8725 loss_thr: 0.5175 loss_db: 0.1483 loss: 1.5383 2022/08/30 05:18:07 - mmengine - INFO - Epoch(train) [225][45/63] lr: 5.8112e-03 eta: 1 day, 1:24:16 time: 1.3695 data_time: 0.0285 memory: 16201 loss_prob: 1.0288 loss_thr: 0.5322 loss_db: 0.1641 loss: 1.7251 2022/08/30 05:18:14 - mmengine - INFO - Epoch(train) [225][50/63] lr: 5.8112e-03 eta: 1 day, 1:23:57 time: 1.4031 data_time: 0.0415 memory: 16201 loss_prob: 0.9632 loss_thr: 0.5040 loss_db: 0.1535 loss: 1.6207 2022/08/30 05:18:20 - mmengine - INFO - Epoch(train) [225][55/63] lr: 5.8112e-03 eta: 1 day, 1:23:57 time: 1.3409 data_time: 0.0277 memory: 16201 loss_prob: 0.7521 loss_thr: 0.4675 loss_db: 0.1267 loss: 1.3463 2022/08/30 05:18:27 - mmengine - INFO - Epoch(train) [225][60/63] lr: 5.8112e-03 eta: 1 day, 1:23:35 time: 1.3204 data_time: 0.0282 memory: 16201 loss_prob: 0.8139 loss_thr: 0.4985 loss_db: 0.1347 loss: 1.4471 2022/08/30 05:18:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:18:40 - mmengine - INFO - Epoch(train) [226][5/63] lr: 5.8058e-03 eta: 1 day, 1:23:35 time: 1.5211 data_time: 0.2483 memory: 16201 loss_prob: 0.7358 loss_thr: 0.4443 loss_db: 0.1202 loss: 1.3003 2022/08/30 05:18:47 - mmengine - INFO - Epoch(train) [226][10/63] lr: 5.8058e-03 eta: 1 day, 1:23:06 time: 1.7217 data_time: 0.2709 memory: 16201 loss_prob: 0.7254 loss_thr: 0.4526 loss_db: 0.1228 loss: 1.3007 2022/08/30 05:18:54 - mmengine - INFO - Epoch(train) [226][15/63] lr: 5.8058e-03 eta: 1 day, 1:23:06 time: 1.4206 data_time: 0.0339 memory: 16201 loss_prob: 0.8423 loss_thr: 0.4935 loss_db: 0.1431 loss: 1.4788 2022/08/30 05:19:00 - mmengine - INFO - Epoch(train) [226][20/63] lr: 5.8058e-03 eta: 1 day, 1:22:43 time: 1.3026 data_time: 0.0324 memory: 16201 loss_prob: 0.8650 loss_thr: 0.5083 loss_db: 0.1434 loss: 1.5167 2022/08/30 05:19:07 - mmengine - INFO - Epoch(train) [226][25/63] lr: 5.8058e-03 eta: 1 day, 1:22:43 time: 1.2704 data_time: 0.0540 memory: 16201 loss_prob: 0.7957 loss_thr: 0.4871 loss_db: 0.1334 loss: 1.4162 2022/08/30 05:19:13 - mmengine - INFO - Epoch(train) [226][30/63] lr: 5.8058e-03 eta: 1 day, 1:22:20 time: 1.2998 data_time: 0.0375 memory: 16201 loss_prob: 0.8304 loss_thr: 0.4711 loss_db: 0.1362 loss: 1.4377 2022/08/30 05:19:20 - mmengine - INFO - Epoch(train) [226][35/63] lr: 5.8058e-03 eta: 1 day, 1:22:20 time: 1.3022 data_time: 0.0246 memory: 16201 loss_prob: 0.8903 loss_thr: 0.4755 loss_db: 0.1460 loss: 1.5118 2022/08/30 05:19:26 - mmengine - INFO - Epoch(train) [226][40/63] lr: 5.8058e-03 eta: 1 day, 1:21:57 time: 1.2893 data_time: 0.0310 memory: 16201 loss_prob: 0.9255 loss_thr: 0.5060 loss_db: 0.1507 loss: 1.5822 2022/08/30 05:19:34 - mmengine - INFO - Epoch(train) [226][45/63] lr: 5.8058e-03 eta: 1 day, 1:21:57 time: 1.4011 data_time: 0.0307 memory: 16201 loss_prob: 0.8691 loss_thr: 0.5168 loss_db: 0.1399 loss: 1.5259 2022/08/30 05:19:41 - mmengine - INFO - Epoch(train) [226][50/63] lr: 5.8058e-03 eta: 1 day, 1:21:40 time: 1.4367 data_time: 0.0427 memory: 16201 loss_prob: 0.8181 loss_thr: 0.4961 loss_db: 0.1370 loss: 1.4512 2022/08/30 05:19:47 - mmengine - INFO - Epoch(train) [226][55/63] lr: 5.8058e-03 eta: 1 day, 1:21:40 time: 1.3801 data_time: 0.0377 memory: 16201 loss_prob: 0.7725 loss_thr: 0.4760 loss_db: 0.1295 loss: 1.3780 2022/08/30 05:19:54 - mmengine - INFO - Epoch(train) [226][60/63] lr: 5.8058e-03 eta: 1 day, 1:21:20 time: 1.3810 data_time: 0.0320 memory: 16201 loss_prob: 0.7668 loss_thr: 0.4844 loss_db: 0.1275 loss: 1.3787 2022/08/30 05:19:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:20:07 - mmengine - INFO - Epoch(train) [227][5/63] lr: 5.8005e-03 eta: 1 day, 1:21:20 time: 1.5671 data_time: 0.2425 memory: 16201 loss_prob: 0.8754 loss_thr: 0.4914 loss_db: 0.1434 loss: 1.5103 2022/08/30 05:20:15 - mmengine - INFO - Epoch(train) [227][10/63] lr: 5.8005e-03 eta: 1 day, 1:20:50 time: 1.6883 data_time: 0.2703 memory: 16201 loss_prob: 0.8161 loss_thr: 0.4573 loss_db: 0.1316 loss: 1.4051 2022/08/30 05:20:22 - mmengine - INFO - Epoch(train) [227][15/63] lr: 5.8005e-03 eta: 1 day, 1:20:50 time: 1.4932 data_time: 0.0424 memory: 16201 loss_prob: 0.7851 loss_thr: 0.4616 loss_db: 0.1296 loss: 1.3762 2022/08/30 05:20:29 - mmengine - INFO - Epoch(train) [227][20/63] lr: 5.8005e-03 eta: 1 day, 1:20:34 time: 1.4478 data_time: 0.0311 memory: 16201 loss_prob: 0.7868 loss_thr: 0.4821 loss_db: 0.1339 loss: 1.4029 2022/08/30 05:20:36 - mmengine - INFO - Epoch(train) [227][25/63] lr: 5.8005e-03 eta: 1 day, 1:20:34 time: 1.4013 data_time: 0.0387 memory: 16201 loss_prob: 0.7770 loss_thr: 0.4754 loss_db: 0.1310 loss: 1.3834 2022/08/30 05:20:43 - mmengine - INFO - Epoch(train) [227][30/63] lr: 5.8005e-03 eta: 1 day, 1:20:15 time: 1.3955 data_time: 0.0304 memory: 16201 loss_prob: 0.8033 loss_thr: 0.4823 loss_db: 0.1346 loss: 1.4202 2022/08/30 05:20:50 - mmengine - INFO - Epoch(train) [227][35/63] lr: 5.8005e-03 eta: 1 day, 1:20:15 time: 1.4123 data_time: 0.0349 memory: 16201 loss_prob: 0.8287 loss_thr: 0.5049 loss_db: 0.1392 loss: 1.4728 2022/08/30 05:20:57 - mmengine - INFO - Epoch(train) [227][40/63] lr: 5.8005e-03 eta: 1 day, 1:19:55 time: 1.3695 data_time: 0.0329 memory: 16201 loss_prob: 0.8401 loss_thr: 0.4993 loss_db: 0.1403 loss: 1.4796 2022/08/30 05:21:04 - mmengine - INFO - Epoch(train) [227][45/63] lr: 5.8005e-03 eta: 1 day, 1:19:55 time: 1.3517 data_time: 0.0316 memory: 16201 loss_prob: 0.8576 loss_thr: 0.4917 loss_db: 0.1459 loss: 1.4953 2022/08/30 05:21:11 - mmengine - INFO - Epoch(train) [227][50/63] lr: 5.8005e-03 eta: 1 day, 1:19:35 time: 1.3715 data_time: 0.0422 memory: 16201 loss_prob: 0.8530 loss_thr: 0.4997 loss_db: 0.1444 loss: 1.4971 2022/08/30 05:21:17 - mmengine - INFO - Epoch(train) [227][55/63] lr: 5.8005e-03 eta: 1 day, 1:19:35 time: 1.3287 data_time: 0.0287 memory: 16201 loss_prob: 0.8136 loss_thr: 0.4984 loss_db: 0.1368 loss: 1.4488 2022/08/30 05:21:24 - mmengine - INFO - Epoch(train) [227][60/63] lr: 5.8005e-03 eta: 1 day, 1:19:13 time: 1.3046 data_time: 0.0276 memory: 16201 loss_prob: 0.8225 loss_thr: 0.4927 loss_db: 0.1397 loss: 1.4549 2022/08/30 05:21:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:21:36 - mmengine - INFO - Epoch(train) [228][5/63] lr: 5.7951e-03 eta: 1 day, 1:19:13 time: 1.4820 data_time: 0.2301 memory: 16201 loss_prob: 0.8238 loss_thr: 0.4900 loss_db: 0.1402 loss: 1.4539 2022/08/30 05:21:43 - mmengine - INFO - Epoch(train) [228][10/63] lr: 5.7951e-03 eta: 1 day, 1:18:41 time: 1.6577 data_time: 0.2556 memory: 16201 loss_prob: 0.7293 loss_thr: 0.4418 loss_db: 0.1209 loss: 1.2921 2022/08/30 05:21:50 - mmengine - INFO - Epoch(train) [228][15/63] lr: 5.7951e-03 eta: 1 day, 1:18:41 time: 1.4545 data_time: 0.0364 memory: 16201 loss_prob: 0.7012 loss_thr: 0.4275 loss_db: 0.1173 loss: 1.2459 2022/08/30 05:21:57 - mmengine - INFO - Epoch(train) [228][20/63] lr: 5.7951e-03 eta: 1 day, 1:18:22 time: 1.3689 data_time: 0.0276 memory: 16201 loss_prob: 0.7338 loss_thr: 0.4504 loss_db: 0.1258 loss: 1.3099 2022/08/30 05:22:04 - mmengine - INFO - Epoch(train) [228][25/63] lr: 5.7951e-03 eta: 1 day, 1:18:22 time: 1.3832 data_time: 0.0408 memory: 16201 loss_prob: 0.7841 loss_thr: 0.4774 loss_db: 0.1311 loss: 1.3927 2022/08/30 05:22:11 - mmengine - INFO - Epoch(train) [228][30/63] lr: 5.7951e-03 eta: 1 day, 1:18:02 time: 1.3760 data_time: 0.0312 memory: 16201 loss_prob: 0.7815 loss_thr: 0.4696 loss_db: 0.1294 loss: 1.3805 2022/08/30 05:22:18 - mmengine - INFO - Epoch(train) [228][35/63] lr: 5.7951e-03 eta: 1 day, 1:18:02 time: 1.3705 data_time: 0.0340 memory: 16201 loss_prob: 0.7911 loss_thr: 0.4781 loss_db: 0.1365 loss: 1.4057 2022/08/30 05:22:24 - mmengine - INFO - Epoch(train) [228][40/63] lr: 5.7951e-03 eta: 1 day, 1:17:40 time: 1.3313 data_time: 0.0338 memory: 16201 loss_prob: 0.7884 loss_thr: 0.4955 loss_db: 0.1359 loss: 1.4198 2022/08/30 05:22:30 - mmengine - INFO - Epoch(train) [228][45/63] lr: 5.7951e-03 eta: 1 day, 1:17:40 time: 1.2473 data_time: 0.0292 memory: 16201 loss_prob: 0.7724 loss_thr: 0.4782 loss_db: 0.1297 loss: 1.3802 2022/08/30 05:22:37 - mmengine - INFO - Epoch(train) [228][50/63] lr: 5.7951e-03 eta: 1 day, 1:17:18 time: 1.3067 data_time: 0.0411 memory: 16201 loss_prob: 0.7941 loss_thr: 0.4911 loss_db: 0.1308 loss: 1.4160 2022/08/30 05:22:43 - mmengine - INFO - Epoch(train) [228][55/63] lr: 5.7951e-03 eta: 1 day, 1:17:18 time: 1.2967 data_time: 0.0293 memory: 16201 loss_prob: 0.8119 loss_thr: 0.5021 loss_db: 0.1355 loss: 1.4495 2022/08/30 05:22:51 - mmengine - INFO - Epoch(train) [228][60/63] lr: 5.7951e-03 eta: 1 day, 1:16:57 time: 1.3550 data_time: 0.0297 memory: 16201 loss_prob: 0.8002 loss_thr: 0.4847 loss_db: 0.1352 loss: 1.4201 2022/08/30 05:22:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:23:03 - mmengine - INFO - Epoch(train) [229][5/63] lr: 5.7897e-03 eta: 1 day, 1:16:57 time: 1.4705 data_time: 0.2418 memory: 16201 loss_prob: 0.7311 loss_thr: 0.4615 loss_db: 0.1210 loss: 1.3136 2022/08/30 05:23:10 - mmengine - INFO - Epoch(train) [229][10/63] lr: 5.7897e-03 eta: 1 day, 1:16:23 time: 1.5666 data_time: 0.2591 memory: 16201 loss_prob: 0.7454 loss_thr: 0.4631 loss_db: 0.1235 loss: 1.3321 2022/08/30 05:23:17 - mmengine - INFO - Epoch(train) [229][15/63] lr: 5.7897e-03 eta: 1 day, 1:16:23 time: 1.3943 data_time: 0.0326 memory: 16201 loss_prob: 0.7515 loss_thr: 0.4863 loss_db: 0.1284 loss: 1.3661 2022/08/30 05:23:23 - mmengine - INFO - Epoch(train) [229][20/63] lr: 5.7897e-03 eta: 1 day, 1:16:00 time: 1.2962 data_time: 0.0364 memory: 16201 loss_prob: 0.7627 loss_thr: 0.4940 loss_db: 0.1295 loss: 1.3862 2022/08/30 05:23:30 - mmengine - INFO - Epoch(train) [229][25/63] lr: 5.7897e-03 eta: 1 day, 1:16:00 time: 1.3176 data_time: 0.0360 memory: 16201 loss_prob: 0.8286 loss_thr: 0.4720 loss_db: 0.1342 loss: 1.4348 2022/08/30 05:23:37 - mmengine - INFO - Epoch(train) [229][30/63] lr: 5.7897e-03 eta: 1 day, 1:15:40 time: 1.3820 data_time: 0.0409 memory: 16201 loss_prob: 0.8820 loss_thr: 0.4925 loss_db: 0.1450 loss: 1.5195 2022/08/30 05:23:43 - mmengine - INFO - Epoch(train) [229][35/63] lr: 5.7897e-03 eta: 1 day, 1:15:40 time: 1.3336 data_time: 0.0503 memory: 16201 loss_prob: 0.8344 loss_thr: 0.4881 loss_db: 0.1405 loss: 1.4630 2022/08/30 05:23:50 - mmengine - INFO - Epoch(train) [229][40/63] lr: 5.7897e-03 eta: 1 day, 1:15:20 time: 1.3593 data_time: 0.0310 memory: 16201 loss_prob: 0.7309 loss_thr: 0.4564 loss_db: 0.1231 loss: 1.3104 2022/08/30 05:23:57 - mmengine - INFO - Epoch(train) [229][45/63] lr: 5.7897e-03 eta: 1 day, 1:15:20 time: 1.3201 data_time: 0.0372 memory: 16201 loss_prob: 0.7440 loss_thr: 0.4673 loss_db: 0.1254 loss: 1.3367 2022/08/30 05:24:04 - mmengine - INFO - Epoch(train) [229][50/63] lr: 5.7897e-03 eta: 1 day, 1:15:00 time: 1.3541 data_time: 0.0473 memory: 16201 loss_prob: 0.8219 loss_thr: 0.5021 loss_db: 0.1375 loss: 1.4616 2022/08/30 05:24:10 - mmengine - INFO - Epoch(train) [229][55/63] lr: 5.7897e-03 eta: 1 day, 1:15:00 time: 1.3071 data_time: 0.0308 memory: 16201 loss_prob: 0.7558 loss_thr: 0.4828 loss_db: 0.1284 loss: 1.3671 2022/08/30 05:24:17 - mmengine - INFO - Epoch(train) [229][60/63] lr: 5.7897e-03 eta: 1 day, 1:14:39 time: 1.3383 data_time: 0.0325 memory: 16201 loss_prob: 0.7008 loss_thr: 0.4400 loss_db: 0.1189 loss: 1.2597 2022/08/30 05:24:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:24:30 - mmengine - INFO - Epoch(train) [230][5/63] lr: 5.7844e-03 eta: 1 day, 1:14:39 time: 1.6229 data_time: 0.2419 memory: 16201 loss_prob: 0.7821 loss_thr: 0.4528 loss_db: 0.1293 loss: 1.3643 2022/08/30 05:24:38 - mmengine - INFO - Epoch(train) [230][10/63] lr: 5.7844e-03 eta: 1 day, 1:14:07 time: 1.6405 data_time: 0.2513 memory: 16201 loss_prob: 0.7605 loss_thr: 0.4526 loss_db: 0.1297 loss: 1.3427 2022/08/30 05:24:44 - mmengine - INFO - Epoch(train) [230][15/63] lr: 5.7844e-03 eta: 1 day, 1:14:07 time: 1.3397 data_time: 0.0347 memory: 16201 loss_prob: 0.7178 loss_thr: 0.4491 loss_db: 0.1216 loss: 1.2886 2022/08/30 05:24:51 - mmengine - INFO - Epoch(train) [230][20/63] lr: 5.7844e-03 eta: 1 day, 1:13:46 time: 1.3397 data_time: 0.0333 memory: 16201 loss_prob: 0.7974 loss_thr: 0.4740 loss_db: 0.1279 loss: 1.3993 2022/08/30 05:24:58 - mmengine - INFO - Epoch(train) [230][25/63] lr: 5.7844e-03 eta: 1 day, 1:13:46 time: 1.3782 data_time: 0.0356 memory: 16201 loss_prob: 0.7978 loss_thr: 0.4770 loss_db: 0.1288 loss: 1.4036 2022/08/30 05:25:04 - mmengine - INFO - Epoch(train) [230][30/63] lr: 5.7844e-03 eta: 1 day, 1:13:24 time: 1.3286 data_time: 0.0350 memory: 16201 loss_prob: 0.7363 loss_thr: 0.4670 loss_db: 0.1243 loss: 1.3276 2022/08/30 05:25:11 - mmengine - INFO - Epoch(train) [230][35/63] lr: 5.7844e-03 eta: 1 day, 1:13:24 time: 1.3042 data_time: 0.0387 memory: 16201 loss_prob: 0.7167 loss_thr: 0.4647 loss_db: 0.1232 loss: 1.3047 2022/08/30 05:25:18 - mmengine - INFO - Epoch(train) [230][40/63] lr: 5.7844e-03 eta: 1 day, 1:13:04 time: 1.3408 data_time: 0.0310 memory: 16201 loss_prob: 0.6729 loss_thr: 0.4415 loss_db: 0.1155 loss: 1.2299 2022/08/30 05:25:24 - mmengine - INFO - Epoch(train) [230][45/63] lr: 5.7844e-03 eta: 1 day, 1:13:04 time: 1.3622 data_time: 0.0368 memory: 16201 loss_prob: 0.7045 loss_thr: 0.4606 loss_db: 0.1202 loss: 1.2853 2022/08/30 05:25:31 - mmengine - INFO - Epoch(train) [230][50/63] lr: 5.7844e-03 eta: 1 day, 1:12:43 time: 1.3534 data_time: 0.0420 memory: 16201 loss_prob: 0.7346 loss_thr: 0.4747 loss_db: 0.1263 loss: 1.3356 2022/08/30 05:25:38 - mmengine - INFO - Epoch(train) [230][55/63] lr: 5.7844e-03 eta: 1 day, 1:12:43 time: 1.4005 data_time: 0.0343 memory: 16201 loss_prob: 0.7141 loss_thr: 0.4479 loss_db: 0.1235 loss: 1.2856 2022/08/30 05:25:44 - mmengine - INFO - Epoch(train) [230][60/63] lr: 5.7844e-03 eta: 1 day, 1:12:22 time: 1.3317 data_time: 0.0389 memory: 16201 loss_prob: 0.6773 loss_thr: 0.4322 loss_db: 0.1149 loss: 1.2244 2022/08/30 05:25:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:25:56 - mmengine - INFO - Epoch(train) [231][5/63] lr: 5.7790e-03 eta: 1 day, 1:12:22 time: 1.4538 data_time: 0.2320 memory: 16201 loss_prob: 0.7089 loss_thr: 0.4535 loss_db: 0.1216 loss: 1.2839 2022/08/30 05:26:04 - mmengine - INFO - Epoch(train) [231][10/63] lr: 5.7790e-03 eta: 1 day, 1:11:51 time: 1.6493 data_time: 0.2527 memory: 16201 loss_prob: 0.7611 loss_thr: 0.4592 loss_db: 0.1316 loss: 1.3518 2022/08/30 05:26:10 - mmengine - INFO - Epoch(train) [231][15/63] lr: 5.7790e-03 eta: 1 day, 1:11:51 time: 1.3888 data_time: 0.0378 memory: 16201 loss_prob: 0.8582 loss_thr: 0.5146 loss_db: 0.1407 loss: 1.5136 2022/08/30 05:26:16 - mmengine - INFO - Epoch(train) [231][20/63] lr: 5.7790e-03 eta: 1 day, 1:11:25 time: 1.2332 data_time: 0.0336 memory: 16201 loss_prob: 0.8172 loss_thr: 0.4879 loss_db: 0.1359 loss: 1.4410 2022/08/30 05:26:23 - mmengine - INFO - Epoch(train) [231][25/63] lr: 5.7790e-03 eta: 1 day, 1:11:25 time: 1.2840 data_time: 0.0510 memory: 16201 loss_prob: 0.7891 loss_thr: 0.4810 loss_db: 0.1370 loss: 1.4071 2022/08/30 05:26:30 - mmengine - INFO - Epoch(train) [231][30/63] lr: 5.7790e-03 eta: 1 day, 1:11:07 time: 1.4009 data_time: 0.0403 memory: 16201 loss_prob: 0.7250 loss_thr: 0.4674 loss_db: 0.1241 loss: 1.3166 2022/08/30 05:26:38 - mmengine - INFO - Epoch(train) [231][35/63] lr: 5.7790e-03 eta: 1 day, 1:11:07 time: 1.4426 data_time: 0.0288 memory: 16201 loss_prob: 0.7102 loss_thr: 0.4613 loss_db: 0.1182 loss: 1.2896 2022/08/30 05:26:44 - mmengine - INFO - Epoch(train) [231][40/63] lr: 5.7790e-03 eta: 1 day, 1:10:48 time: 1.3953 data_time: 0.0329 memory: 16201 loss_prob: 0.7223 loss_thr: 0.4623 loss_db: 0.1200 loss: 1.3046 2022/08/30 05:26:51 - mmengine - INFO - Epoch(train) [231][45/63] lr: 5.7790e-03 eta: 1 day, 1:10:48 time: 1.3433 data_time: 0.0348 memory: 16201 loss_prob: 0.6914 loss_thr: 0.4389 loss_db: 0.1162 loss: 1.2464 2022/08/30 05:26:58 - mmengine - INFO - Epoch(train) [231][50/63] lr: 5.7790e-03 eta: 1 day, 1:10:28 time: 1.3532 data_time: 0.0401 memory: 16201 loss_prob: 0.7117 loss_thr: 0.4545 loss_db: 0.1219 loss: 1.2881 2022/08/30 05:27:05 - mmengine - INFO - Epoch(train) [231][55/63] lr: 5.7790e-03 eta: 1 day, 1:10:28 time: 1.3586 data_time: 0.0379 memory: 16201 loss_prob: 0.6949 loss_thr: 0.4394 loss_db: 0.1196 loss: 1.2539 2022/08/30 05:27:11 - mmengine - INFO - Epoch(train) [231][60/63] lr: 5.7790e-03 eta: 1 day, 1:10:06 time: 1.3206 data_time: 0.0327 memory: 16201 loss_prob: 0.7613 loss_thr: 0.4464 loss_db: 0.1236 loss: 1.3313 2022/08/30 05:27:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:27:24 - mmengine - INFO - Epoch(train) [232][5/63] lr: 5.7736e-03 eta: 1 day, 1:10:06 time: 1.5660 data_time: 0.2455 memory: 16201 loss_prob: 0.7874 loss_thr: 0.4763 loss_db: 0.1344 loss: 1.3981 2022/08/30 05:27:31 - mmengine - INFO - Epoch(train) [232][10/63] lr: 5.7736e-03 eta: 1 day, 1:09:30 time: 1.5314 data_time: 0.2446 memory: 16201 loss_prob: 0.7500 loss_thr: 0.4510 loss_db: 0.1313 loss: 1.3323 2022/08/30 05:27:38 - mmengine - INFO - Epoch(train) [232][15/63] lr: 5.7736e-03 eta: 1 day, 1:09:30 time: 1.3944 data_time: 0.0338 memory: 16201 loss_prob: 0.7177 loss_thr: 0.4221 loss_db: 0.1231 loss: 1.2629 2022/08/30 05:27:45 - mmengine - INFO - Epoch(train) [232][20/63] lr: 5.7736e-03 eta: 1 day, 1:09:13 time: 1.4245 data_time: 0.0304 memory: 16201 loss_prob: 0.7594 loss_thr: 0.4596 loss_db: 0.1200 loss: 1.3390 2022/08/30 05:27:51 - mmengine - INFO - Epoch(train) [232][25/63] lr: 5.7736e-03 eta: 1 day, 1:09:13 time: 1.2836 data_time: 0.0401 memory: 16201 loss_prob: 0.8564 loss_thr: 0.4950 loss_db: 0.1313 loss: 1.4826 2022/08/30 05:27:57 - mmengine - INFO - Epoch(train) [232][30/63] lr: 5.7736e-03 eta: 1 day, 1:08:47 time: 1.2198 data_time: 0.0299 memory: 16201 loss_prob: 0.8484 loss_thr: 0.4954 loss_db: 0.1366 loss: 1.4804 2022/08/30 05:28:05 - mmengine - INFO - Epoch(train) [232][35/63] lr: 5.7736e-03 eta: 1 day, 1:08:47 time: 1.3465 data_time: 0.0327 memory: 16201 loss_prob: 0.8344 loss_thr: 0.5011 loss_db: 0.1406 loss: 1.4761 2022/08/30 05:28:12 - mmengine - INFO - Epoch(train) [232][40/63] lr: 5.7736e-03 eta: 1 day, 1:08:30 time: 1.4431 data_time: 0.0312 memory: 16201 loss_prob: 0.8238 loss_thr: 0.4809 loss_db: 0.1364 loss: 1.4411 2022/08/30 05:28:19 - mmengine - INFO - Epoch(train) [232][45/63] lr: 5.7736e-03 eta: 1 day, 1:08:30 time: 1.4083 data_time: 0.0261 memory: 16201 loss_prob: 0.8021 loss_thr: 0.4706 loss_db: 0.1339 loss: 1.4066 2022/08/30 05:28:26 - mmengine - INFO - Epoch(train) [232][50/63] lr: 5.7736e-03 eta: 1 day, 1:08:12 time: 1.4040 data_time: 0.0635 memory: 16201 loss_prob: 0.7842 loss_thr: 0.4704 loss_db: 0.1342 loss: 1.3889 2022/08/30 05:28:33 - mmengine - INFO - Epoch(train) [232][55/63] lr: 5.7736e-03 eta: 1 day, 1:08:12 time: 1.4175 data_time: 0.0568 memory: 16201 loss_prob: 0.7223 loss_thr: 0.4479 loss_db: 0.1240 loss: 1.2942 2022/08/30 05:28:40 - mmengine - INFO - Epoch(train) [232][60/63] lr: 5.7736e-03 eta: 1 day, 1:07:54 time: 1.4015 data_time: 0.0371 memory: 16201 loss_prob: 0.7281 loss_thr: 0.4455 loss_db: 0.1203 loss: 1.2939 2022/08/30 05:28:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:28:52 - mmengine - INFO - Epoch(train) [233][5/63] lr: 5.7683e-03 eta: 1 day, 1:07:54 time: 1.4500 data_time: 0.2294 memory: 16201 loss_prob: 0.7314 loss_thr: 0.4515 loss_db: 0.1231 loss: 1.3061 2022/08/30 05:28:59 - mmengine - INFO - Epoch(train) [233][10/63] lr: 5.7683e-03 eta: 1 day, 1:07:22 time: 1.6293 data_time: 0.2448 memory: 16201 loss_prob: 0.9019 loss_thr: 0.4870 loss_db: 0.1511 loss: 1.5400 2022/08/30 05:29:06 - mmengine - INFO - Epoch(train) [233][15/63] lr: 5.7683e-03 eta: 1 day, 1:07:22 time: 1.4040 data_time: 0.0355 memory: 16201 loss_prob: 0.9865 loss_thr: 0.4877 loss_db: 0.1623 loss: 1.6365 2022/08/30 05:29:13 - mmengine - INFO - Epoch(train) [233][20/63] lr: 5.7683e-03 eta: 1 day, 1:07:05 time: 1.4122 data_time: 0.0348 memory: 16201 loss_prob: 1.1370 loss_thr: 0.5823 loss_db: 0.1811 loss: 1.9003 2022/08/30 05:29:20 - mmengine - INFO - Epoch(train) [233][25/63] lr: 5.7683e-03 eta: 1 day, 1:07:05 time: 1.4354 data_time: 0.0393 memory: 16201 loss_prob: 1.3305 loss_thr: 0.6208 loss_db: 0.2033 loss: 2.1546 2022/08/30 05:29:27 - mmengine - INFO - Epoch(train) [233][30/63] lr: 5.7683e-03 eta: 1 day, 1:06:45 time: 1.3691 data_time: 0.0373 memory: 16201 loss_prob: 1.3955 loss_thr: 0.5656 loss_db: 0.2159 loss: 2.1770 2022/08/30 05:29:35 - mmengine - INFO - Epoch(train) [233][35/63] lr: 5.7683e-03 eta: 1 day, 1:06:45 time: 1.4189 data_time: 0.0444 memory: 16201 loss_prob: 1.3468 loss_thr: 0.5778 loss_db: 0.2187 loss: 2.1432 2022/08/30 05:29:41 - mmengine - INFO - Epoch(train) [233][40/63] lr: 5.7683e-03 eta: 1 day, 1:06:27 time: 1.4026 data_time: 0.0348 memory: 16201 loss_prob: 1.2531 loss_thr: 0.5736 loss_db: 0.2002 loss: 2.0269 2022/08/30 05:29:48 - mmengine - INFO - Epoch(train) [233][45/63] lr: 5.7683e-03 eta: 1 day, 1:06:27 time: 1.3065 data_time: 0.0296 memory: 16201 loss_prob: 1.1822 loss_thr: 0.5949 loss_db: 0.1901 loss: 1.9672 2022/08/30 05:29:54 - mmengine - INFO - Epoch(train) [233][50/63] lr: 5.7683e-03 eta: 1 day, 1:06:04 time: 1.2970 data_time: 0.0430 memory: 16201 loss_prob: 1.1101 loss_thr: 0.5979 loss_db: 0.1836 loss: 1.8916 2022/08/30 05:30:01 - mmengine - INFO - Epoch(train) [233][55/63] lr: 5.7683e-03 eta: 1 day, 1:06:04 time: 1.3038 data_time: 0.0337 memory: 16201 loss_prob: 1.0929 loss_thr: 0.5793 loss_db: 0.1835 loss: 1.8556 2022/08/30 05:30:07 - mmengine - INFO - Epoch(train) [233][60/63] lr: 5.7683e-03 eta: 1 day, 1:05:43 time: 1.3220 data_time: 0.0265 memory: 16201 loss_prob: 1.0474 loss_thr: 0.5569 loss_db: 0.1717 loss: 1.7760 2022/08/30 05:30:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:30:20 - mmengine - INFO - Epoch(train) [234][5/63] lr: 5.7629e-03 eta: 1 day, 1:05:43 time: 1.4909 data_time: 0.2165 memory: 16201 loss_prob: 0.9087 loss_thr: 0.4983 loss_db: 0.1494 loss: 1.5564 2022/08/30 05:30:26 - mmengine - INFO - Epoch(train) [234][10/63] lr: 5.7629e-03 eta: 1 day, 1:05:08 time: 1.5518 data_time: 0.2362 memory: 16201 loss_prob: 0.8789 loss_thr: 0.4859 loss_db: 0.1497 loss: 1.5145 2022/08/30 05:30:33 - mmengine - INFO - Epoch(train) [234][15/63] lr: 5.7629e-03 eta: 1 day, 1:05:08 time: 1.3673 data_time: 0.0381 memory: 16201 loss_prob: 0.8600 loss_thr: 0.4745 loss_db: 0.1434 loss: 1.4779 2022/08/30 05:30:40 - mmengine - INFO - Epoch(train) [234][20/63] lr: 5.7629e-03 eta: 1 day, 1:04:50 time: 1.3997 data_time: 0.0395 memory: 16201 loss_prob: 0.9360 loss_thr: 0.5120 loss_db: 0.1535 loss: 1.6015 2022/08/30 05:30:47 - mmengine - INFO - Epoch(train) [234][25/63] lr: 5.7629e-03 eta: 1 day, 1:04:50 time: 1.3537 data_time: 0.0314 memory: 16201 loss_prob: 0.9539 loss_thr: 0.5252 loss_db: 0.1555 loss: 1.6346 2022/08/30 05:30:54 - mmengine - INFO - Epoch(train) [234][30/63] lr: 5.7629e-03 eta: 1 day, 1:04:29 time: 1.3368 data_time: 0.0278 memory: 16201 loss_prob: 0.9659 loss_thr: 0.5366 loss_db: 0.1581 loss: 1.6605 2022/08/30 05:31:00 - mmengine - INFO - Epoch(train) [234][35/63] lr: 5.7629e-03 eta: 1 day, 1:04:29 time: 1.3637 data_time: 0.0454 memory: 16201 loss_prob: 0.8751 loss_thr: 0.5183 loss_db: 0.1463 loss: 1.5397 2022/08/30 05:31:08 - mmengine - INFO - Epoch(train) [234][40/63] lr: 5.7629e-03 eta: 1 day, 1:04:10 time: 1.3982 data_time: 0.0321 memory: 16201 loss_prob: 0.8708 loss_thr: 0.5020 loss_db: 0.1434 loss: 1.5162 2022/08/30 05:31:15 - mmengine - INFO - Epoch(train) [234][45/63] lr: 5.7629e-03 eta: 1 day, 1:04:10 time: 1.4111 data_time: 0.0287 memory: 16201 loss_prob: 0.8950 loss_thr: 0.5055 loss_db: 0.1473 loss: 1.5478 2022/08/30 05:31:21 - mmengine - INFO - Epoch(train) [234][50/63] lr: 5.7629e-03 eta: 1 day, 1:03:51 time: 1.3668 data_time: 0.0368 memory: 16201 loss_prob: 0.8358 loss_thr: 0.4902 loss_db: 0.1391 loss: 1.4650 2022/08/30 05:31:28 - mmengine - INFO - Epoch(train) [234][55/63] lr: 5.7629e-03 eta: 1 day, 1:03:51 time: 1.3235 data_time: 0.0289 memory: 16201 loss_prob: 0.8469 loss_thr: 0.4917 loss_db: 0.1398 loss: 1.4784 2022/08/30 05:31:35 - mmengine - INFO - Epoch(train) [234][60/63] lr: 5.7629e-03 eta: 1 day, 1:03:31 time: 1.3719 data_time: 0.0359 memory: 16201 loss_prob: 0.8789 loss_thr: 0.5018 loss_db: 0.1500 loss: 1.5307 2022/08/30 05:31:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:31:48 - mmengine - INFO - Epoch(train) [235][5/63] lr: 5.7575e-03 eta: 1 day, 1:03:31 time: 1.6281 data_time: 0.2318 memory: 16201 loss_prob: 0.8232 loss_thr: 0.4753 loss_db: 0.1342 loss: 1.4327 2022/08/30 05:31:55 - mmengine - INFO - Epoch(train) [235][10/63] lr: 5.7575e-03 eta: 1 day, 1:03:02 time: 1.6928 data_time: 0.2438 memory: 16201 loss_prob: 0.8780 loss_thr: 0.4862 loss_db: 0.1460 loss: 1.5102 2022/08/30 05:32:02 - mmengine - INFO - Epoch(train) [235][15/63] lr: 5.7575e-03 eta: 1 day, 1:03:02 time: 1.4143 data_time: 0.0321 memory: 16201 loss_prob: 0.8237 loss_thr: 0.4780 loss_db: 0.1379 loss: 1.4396 2022/08/30 05:32:09 - mmengine - INFO - Epoch(train) [235][20/63] lr: 5.7575e-03 eta: 1 day, 1:02:42 time: 1.3367 data_time: 0.0295 memory: 16201 loss_prob: 0.7887 loss_thr: 0.4690 loss_db: 0.1283 loss: 1.3860 2022/08/30 05:32:16 - mmengine - INFO - Epoch(train) [235][25/63] lr: 5.7575e-03 eta: 1 day, 1:02:42 time: 1.3906 data_time: 0.0358 memory: 16201 loss_prob: 0.8296 loss_thr: 0.4880 loss_db: 0.1370 loss: 1.4546 2022/08/30 05:32:23 - mmengine - INFO - Epoch(train) [235][30/63] lr: 5.7575e-03 eta: 1 day, 1:02:27 time: 1.4811 data_time: 0.0328 memory: 16201 loss_prob: 0.9062 loss_thr: 0.4851 loss_db: 0.1536 loss: 1.5450 2022/08/30 05:32:30 - mmengine - INFO - Epoch(train) [235][35/63] lr: 5.7575e-03 eta: 1 day, 1:02:27 time: 1.4102 data_time: 0.0387 memory: 16201 loss_prob: 0.9013 loss_thr: 0.4844 loss_db: 0.1476 loss: 1.5333 2022/08/30 05:32:37 - mmengine - INFO - Epoch(train) [235][40/63] lr: 5.7575e-03 eta: 1 day, 1:02:08 time: 1.3971 data_time: 0.0292 memory: 16201 loss_prob: 0.8520 loss_thr: 0.5015 loss_db: 0.1376 loss: 1.4912 2022/08/30 05:32:44 - mmengine - INFO - Epoch(train) [235][45/63] lr: 5.7575e-03 eta: 1 day, 1:02:08 time: 1.3309 data_time: 0.0319 memory: 16201 loss_prob: 0.9100 loss_thr: 0.5144 loss_db: 0.1507 loss: 1.5751 2022/08/30 05:32:50 - mmengine - INFO - Epoch(train) [235][50/63] lr: 5.7575e-03 eta: 1 day, 1:01:46 time: 1.2962 data_time: 0.0435 memory: 16201 loss_prob: 1.1264 loss_thr: 0.5514 loss_db: 0.1720 loss: 1.8498 2022/08/30 05:32:58 - mmengine - INFO - Epoch(train) [235][55/63] lr: 5.7575e-03 eta: 1 day, 1:01:46 time: 1.4176 data_time: 0.0377 memory: 16201 loss_prob: 1.0995 loss_thr: 0.5318 loss_db: 0.1626 loss: 1.7939 2022/08/30 05:33:04 - mmengine - INFO - Epoch(train) [235][60/63] lr: 5.7575e-03 eta: 1 day, 1:01:26 time: 1.3601 data_time: 0.0434 memory: 16201 loss_prob: 0.9314 loss_thr: 0.5065 loss_db: 0.1527 loss: 1.5906 2022/08/30 05:33:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:33:17 - mmengine - INFO - Epoch(train) [236][5/63] lr: 5.7522e-03 eta: 1 day, 1:01:26 time: 1.4954 data_time: 0.2442 memory: 16201 loss_prob: 0.8146 loss_thr: 0.5085 loss_db: 0.1395 loss: 1.4627 2022/08/30 05:33:24 - mmengine - INFO - Epoch(train) [236][10/63] lr: 5.7522e-03 eta: 1 day, 1:00:57 time: 1.6924 data_time: 0.2680 memory: 16201 loss_prob: 0.7916 loss_thr: 0.4855 loss_db: 0.1320 loss: 1.4091 2022/08/30 05:33:30 - mmengine - INFO - Epoch(train) [236][15/63] lr: 5.7522e-03 eta: 1 day, 1:00:57 time: 1.3712 data_time: 0.0389 memory: 16201 loss_prob: 0.8266 loss_thr: 0.4656 loss_db: 0.1389 loss: 1.4311 2022/08/30 05:33:38 - mmengine - INFO - Epoch(train) [236][20/63] lr: 5.7522e-03 eta: 1 day, 1:00:39 time: 1.3954 data_time: 0.0283 memory: 16201 loss_prob: 0.8474 loss_thr: 0.4808 loss_db: 0.1469 loss: 1.4751 2022/08/30 05:33:45 - mmengine - INFO - Epoch(train) [236][25/63] lr: 5.7522e-03 eta: 1 day, 1:00:39 time: 1.4694 data_time: 0.0421 memory: 16201 loss_prob: 0.8694 loss_thr: 0.5059 loss_db: 0.1455 loss: 1.5209 2022/08/30 05:33:52 - mmengine - INFO - Epoch(train) [236][30/63] lr: 5.7522e-03 eta: 1 day, 1:00:22 time: 1.4235 data_time: 0.0340 memory: 16201 loss_prob: 0.8388 loss_thr: 0.5069 loss_db: 0.1368 loss: 1.4824 2022/08/30 05:33:59 - mmengine - INFO - Epoch(train) [236][35/63] lr: 5.7522e-03 eta: 1 day, 1:00:22 time: 1.3541 data_time: 0.0314 memory: 16201 loss_prob: 0.8746 loss_thr: 0.5232 loss_db: 0.1457 loss: 1.5436 2022/08/30 05:34:06 - mmengine - INFO - Epoch(train) [236][40/63] lr: 5.7522e-03 eta: 1 day, 1:00:03 time: 1.3911 data_time: 0.0321 memory: 16201 loss_prob: 0.7854 loss_thr: 0.4838 loss_db: 0.1328 loss: 1.4020 2022/08/30 05:34:13 - mmengine - INFO - Epoch(train) [236][45/63] lr: 5.7522e-03 eta: 1 day, 1:00:03 time: 1.3941 data_time: 0.0301 memory: 16201 loss_prob: 0.7166 loss_thr: 0.4428 loss_db: 0.1207 loss: 1.2802 2022/08/30 05:34:19 - mmengine - INFO - Epoch(train) [236][50/63] lr: 5.7522e-03 eta: 1 day, 0:59:41 time: 1.2946 data_time: 0.0415 memory: 16201 loss_prob: 0.8072 loss_thr: 0.4858 loss_db: 0.1372 loss: 1.4302 2022/08/30 05:34:26 - mmengine - INFO - Epoch(train) [236][55/63] lr: 5.7522e-03 eta: 1 day, 0:59:41 time: 1.3319 data_time: 0.0293 memory: 16201 loss_prob: 0.8972 loss_thr: 0.5181 loss_db: 0.1501 loss: 1.5654 2022/08/30 05:34:32 - mmengine - INFO - Epoch(train) [236][60/63] lr: 5.7522e-03 eta: 1 day, 0:59:21 time: 1.3493 data_time: 0.0384 memory: 16201 loss_prob: 0.8828 loss_thr: 0.4885 loss_db: 0.1437 loss: 1.5150 2022/08/30 05:34:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:34:44 - mmengine - INFO - Epoch(train) [237][5/63] lr: 5.7468e-03 eta: 1 day, 0:59:21 time: 1.4425 data_time: 0.2282 memory: 16201 loss_prob: 0.7927 loss_thr: 0.4655 loss_db: 0.1297 loss: 1.3880 2022/08/30 05:34:51 - mmengine - INFO - Epoch(train) [237][10/63] lr: 5.7468e-03 eta: 1 day, 0:58:43 time: 1.4810 data_time: 0.2394 memory: 16201 loss_prob: 0.7827 loss_thr: 0.4709 loss_db: 0.1325 loss: 1.3861 2022/08/30 05:34:57 - mmengine - INFO - Epoch(train) [237][15/63] lr: 5.7468e-03 eta: 1 day, 0:58:43 time: 1.3385 data_time: 0.0373 memory: 16201 loss_prob: 0.8659 loss_thr: 0.4828 loss_db: 0.1420 loss: 1.4908 2022/08/30 05:35:04 - mmengine - INFO - Epoch(train) [237][20/63] lr: 5.7468e-03 eta: 1 day, 0:58:23 time: 1.3486 data_time: 0.0443 memory: 16201 loss_prob: 0.8284 loss_thr: 0.4702 loss_db: 0.1335 loss: 1.4321 2022/08/30 05:35:11 - mmengine - INFO - Epoch(train) [237][25/63] lr: 5.7468e-03 eta: 1 day, 0:58:23 time: 1.3278 data_time: 0.0427 memory: 16201 loss_prob: 0.8356 loss_thr: 0.4806 loss_db: 0.1413 loss: 1.4574 2022/08/30 05:35:17 - mmengine - INFO - Epoch(train) [237][30/63] lr: 5.7468e-03 eta: 1 day, 0:58:03 time: 1.3512 data_time: 0.0321 memory: 16201 loss_prob: 0.8904 loss_thr: 0.4991 loss_db: 0.1498 loss: 1.5393 2022/08/30 05:35:25 - mmengine - INFO - Epoch(train) [237][35/63] lr: 5.7468e-03 eta: 1 day, 0:58:03 time: 1.4179 data_time: 0.0369 memory: 16201 loss_prob: 0.8506 loss_thr: 0.4850 loss_db: 0.1420 loss: 1.4776 2022/08/30 05:35:32 - mmengine - INFO - Epoch(train) [237][40/63] lr: 5.7468e-03 eta: 1 day, 0:57:48 time: 1.4799 data_time: 0.0383 memory: 16201 loss_prob: 0.8425 loss_thr: 0.4954 loss_db: 0.1447 loss: 1.4826 2022/08/30 05:35:39 - mmengine - INFO - Epoch(train) [237][45/63] lr: 5.7468e-03 eta: 1 day, 0:57:48 time: 1.3751 data_time: 0.0325 memory: 16201 loss_prob: 0.8443 loss_thr: 0.5075 loss_db: 0.1447 loss: 1.4965 2022/08/30 05:35:45 - mmengine - INFO - Epoch(train) [237][50/63] lr: 5.7468e-03 eta: 1 day, 0:57:25 time: 1.2803 data_time: 0.0384 memory: 16201 loss_prob: 0.8149 loss_thr: 0.4903 loss_db: 0.1377 loss: 1.4429 2022/08/30 05:35:52 - mmengine - INFO - Epoch(train) [237][55/63] lr: 5.7468e-03 eta: 1 day, 0:57:25 time: 1.3205 data_time: 0.0407 memory: 16201 loss_prob: 0.8469 loss_thr: 0.4922 loss_db: 0.1413 loss: 1.4803 2022/08/30 05:35:58 - mmengine - INFO - Epoch(train) [237][60/63] lr: 5.7468e-03 eta: 1 day, 0:57:04 time: 1.3276 data_time: 0.0387 memory: 16201 loss_prob: 0.8184 loss_thr: 0.4731 loss_db: 0.1355 loss: 1.4270 2022/08/30 05:36:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:36:11 - mmengine - INFO - Epoch(train) [238][5/63] lr: 5.7414e-03 eta: 1 day, 0:57:04 time: 1.5670 data_time: 0.2496 memory: 16201 loss_prob: 0.9113 loss_thr: 0.4995 loss_db: 0.1528 loss: 1.5636 2022/08/30 05:36:18 - mmengine - INFO - Epoch(train) [238][10/63] lr: 5.7414e-03 eta: 1 day, 0:56:33 time: 1.6404 data_time: 0.2727 memory: 16201 loss_prob: 0.8462 loss_thr: 0.4937 loss_db: 0.1424 loss: 1.4822 2022/08/30 05:36:25 - mmengine - INFO - Epoch(train) [238][15/63] lr: 5.7414e-03 eta: 1 day, 0:56:33 time: 1.3566 data_time: 0.0339 memory: 16201 loss_prob: 0.8700 loss_thr: 0.4935 loss_db: 0.1430 loss: 1.5065 2022/08/30 05:36:33 - mmengine - INFO - Epoch(train) [238][20/63] lr: 5.7414e-03 eta: 1 day, 0:56:16 time: 1.4147 data_time: 0.0277 memory: 16201 loss_prob: 0.8245 loss_thr: 0.4916 loss_db: 0.1376 loss: 1.4538 2022/08/30 05:36:39 - mmengine - INFO - Epoch(train) [238][25/63] lr: 5.7414e-03 eta: 1 day, 0:56:16 time: 1.4240 data_time: 0.0405 memory: 16201 loss_prob: 0.7773 loss_thr: 0.4832 loss_db: 0.1326 loss: 1.3931 2022/08/30 05:36:46 - mmengine - INFO - Epoch(train) [238][30/63] lr: 5.7414e-03 eta: 1 day, 0:55:55 time: 1.3272 data_time: 0.0285 memory: 16201 loss_prob: 0.7643 loss_thr: 0.4801 loss_db: 0.1307 loss: 1.3750 2022/08/30 05:36:52 - mmengine - INFO - Epoch(train) [238][35/63] lr: 5.7414e-03 eta: 1 day, 0:55:55 time: 1.3300 data_time: 0.0293 memory: 16201 loss_prob: 0.7750 loss_thr: 0.4730 loss_db: 0.1297 loss: 1.3777 2022/08/30 05:37:00 - mmengine - INFO - Epoch(train) [238][40/63] lr: 5.7414e-03 eta: 1 day, 0:55:36 time: 1.3689 data_time: 0.0315 memory: 16201 loss_prob: 1.0120 loss_thr: 0.4718 loss_db: 0.1478 loss: 1.6317 2022/08/30 05:37:07 - mmengine - INFO - Epoch(train) [238][45/63] lr: 5.7414e-03 eta: 1 day, 0:55:36 time: 1.4492 data_time: 0.0339 memory: 16201 loss_prob: 1.0292 loss_thr: 0.4952 loss_db: 0.1521 loss: 1.6765 2022/08/30 05:37:14 - mmengine - INFO - Epoch(train) [238][50/63] lr: 5.7414e-03 eta: 1 day, 0:55:20 time: 1.4509 data_time: 0.0431 memory: 16201 loss_prob: 0.7767 loss_thr: 0.4970 loss_db: 0.1309 loss: 1.4046 2022/08/30 05:37:21 - mmengine - INFO - Epoch(train) [238][55/63] lr: 5.7414e-03 eta: 1 day, 0:55:20 time: 1.3942 data_time: 0.0293 memory: 16201 loss_prob: 0.7905 loss_thr: 0.4886 loss_db: 0.1327 loss: 1.4118 2022/08/30 05:37:29 - mmengine - INFO - Epoch(train) [238][60/63] lr: 5.7414e-03 eta: 1 day, 0:55:04 time: 1.4600 data_time: 0.0314 memory: 16201 loss_prob: 0.8733 loss_thr: 0.4868 loss_db: 0.1476 loss: 1.5078 2022/08/30 05:37:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:37:41 - mmengine - INFO - Epoch(train) [239][5/63] lr: 5.7361e-03 eta: 1 day, 0:55:04 time: 1.4720 data_time: 0.2269 memory: 16201 loss_prob: 0.9360 loss_thr: 0.4957 loss_db: 0.1529 loss: 1.5846 2022/08/30 05:37:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:37:47 - mmengine - INFO - Epoch(train) [239][10/63] lr: 5.7361e-03 eta: 1 day, 0:54:29 time: 1.5432 data_time: 0.2400 memory: 16201 loss_prob: 0.9048 loss_thr: 0.4923 loss_db: 0.1448 loss: 1.5418 2022/08/30 05:37:54 - mmengine - INFO - Epoch(train) [239][15/63] lr: 5.7361e-03 eta: 1 day, 0:54:29 time: 1.3210 data_time: 0.0265 memory: 16201 loss_prob: 0.9194 loss_thr: 0.4981 loss_db: 0.1483 loss: 1.5658 2022/08/30 05:38:00 - mmengine - INFO - Epoch(train) [239][20/63] lr: 5.7361e-03 eta: 1 day, 0:54:08 time: 1.3303 data_time: 0.0273 memory: 16201 loss_prob: 0.8191 loss_thr: 0.4932 loss_db: 0.1389 loss: 1.4512 2022/08/30 05:38:08 - mmengine - INFO - Epoch(train) [239][25/63] lr: 5.7361e-03 eta: 1 day, 0:54:08 time: 1.3712 data_time: 0.0355 memory: 16201 loss_prob: 0.7956 loss_thr: 0.4783 loss_db: 0.1359 loss: 1.4098 2022/08/30 05:38:14 - mmengine - INFO - Epoch(train) [239][30/63] lr: 5.7361e-03 eta: 1 day, 0:53:49 time: 1.3642 data_time: 0.0282 memory: 16201 loss_prob: 0.7418 loss_thr: 0.4514 loss_db: 0.1244 loss: 1.3176 2022/08/30 05:38:21 - mmengine - INFO - Epoch(train) [239][35/63] lr: 5.7361e-03 eta: 1 day, 0:53:49 time: 1.3575 data_time: 0.0337 memory: 16201 loss_prob: 0.7074 loss_thr: 0.4322 loss_db: 0.1185 loss: 1.2581 2022/08/30 05:38:28 - mmengine - INFO - Epoch(train) [239][40/63] lr: 5.7361e-03 eta: 1 day, 0:53:31 time: 1.4074 data_time: 0.0282 memory: 16201 loss_prob: 0.7338 loss_thr: 0.4519 loss_db: 0.1246 loss: 1.3103 2022/08/30 05:38:35 - mmengine - INFO - Epoch(train) [239][45/63] lr: 5.7361e-03 eta: 1 day, 0:53:31 time: 1.4134 data_time: 0.0306 memory: 16201 loss_prob: 0.8495 loss_thr: 0.5107 loss_db: 0.1413 loss: 1.5016 2022/08/30 05:38:43 - mmengine - INFO - Epoch(train) [239][50/63] lr: 5.7361e-03 eta: 1 day, 0:53:17 time: 1.4870 data_time: 0.0422 memory: 16201 loss_prob: 0.9201 loss_thr: 0.5496 loss_db: 0.1535 loss: 1.6231 2022/08/30 05:38:50 - mmengine - INFO - Epoch(train) [239][55/63] lr: 5.7361e-03 eta: 1 day, 0:53:17 time: 1.4857 data_time: 0.0292 memory: 16201 loss_prob: 0.8804 loss_thr: 0.5140 loss_db: 0.1474 loss: 1.5418 2022/08/30 05:38:56 - mmengine - INFO - Epoch(train) [239][60/63] lr: 5.7361e-03 eta: 1 day, 0:52:56 time: 1.3343 data_time: 0.0325 memory: 16201 loss_prob: 0.8386 loss_thr: 0.4779 loss_db: 0.1381 loss: 1.4546 2022/08/30 05:39:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:39:09 - mmengine - INFO - Epoch(train) [240][5/63] lr: 5.7307e-03 eta: 1 day, 0:52:56 time: 1.5174 data_time: 0.2261 memory: 16201 loss_prob: 0.7940 loss_thr: 0.4876 loss_db: 0.1362 loss: 1.4179 2022/08/30 05:39:16 - mmengine - INFO - Epoch(train) [240][10/63] lr: 5.7307e-03 eta: 1 day, 0:52:27 time: 1.6741 data_time: 0.2525 memory: 16201 loss_prob: 0.6929 loss_thr: 0.4518 loss_db: 0.1177 loss: 1.2623 2022/08/30 05:39:23 - mmengine - INFO - Epoch(train) [240][15/63] lr: 5.7307e-03 eta: 1 day, 0:52:27 time: 1.3446 data_time: 0.0349 memory: 16201 loss_prob: 0.7122 loss_thr: 0.4689 loss_db: 0.1195 loss: 1.3006 2022/08/30 05:39:30 - mmengine - INFO - Epoch(train) [240][20/63] lr: 5.7307e-03 eta: 1 day, 0:52:06 time: 1.3288 data_time: 0.0280 memory: 16201 loss_prob: 0.7704 loss_thr: 0.4757 loss_db: 0.1273 loss: 1.3734 2022/08/30 05:39:37 - mmengine - INFO - Epoch(train) [240][25/63] lr: 5.7307e-03 eta: 1 day, 0:52:06 time: 1.3810 data_time: 0.0420 memory: 16201 loss_prob: 0.7372 loss_thr: 0.4639 loss_db: 0.1250 loss: 1.3261 2022/08/30 05:39:43 - mmengine - INFO - Epoch(train) [240][30/63] lr: 5.7307e-03 eta: 1 day, 0:51:46 time: 1.3574 data_time: 0.0279 memory: 16201 loss_prob: 0.7620 loss_thr: 0.4763 loss_db: 0.1294 loss: 1.3677 2022/08/30 05:39:49 - mmengine - INFO - Epoch(train) [240][35/63] lr: 5.7307e-03 eta: 1 day, 0:51:46 time: 1.2583 data_time: 0.0288 memory: 16201 loss_prob: 0.8109 loss_thr: 0.4997 loss_db: 0.1372 loss: 1.4478 2022/08/30 05:39:55 - mmengine - INFO - Epoch(train) [240][40/63] lr: 5.7307e-03 eta: 1 day, 0:51:20 time: 1.1829 data_time: 0.0333 memory: 16201 loss_prob: 0.7590 loss_thr: 0.4834 loss_db: 0.1317 loss: 1.3741 2022/08/30 05:40:02 - mmengine - INFO - Epoch(train) [240][45/63] lr: 5.7307e-03 eta: 1 day, 0:51:20 time: 1.2873 data_time: 0.0283 memory: 16201 loss_prob: 0.7749 loss_thr: 0.4706 loss_db: 0.1335 loss: 1.3791 2022/08/30 05:40:09 - mmengine - INFO - Epoch(train) [240][50/63] lr: 5.7307e-03 eta: 1 day, 0:51:00 time: 1.3641 data_time: 0.0411 memory: 16201 loss_prob: 0.8294 loss_thr: 0.4834 loss_db: 0.1397 loss: 1.4525 2022/08/30 05:40:15 - mmengine - INFO - Epoch(train) [240][55/63] lr: 5.7307e-03 eta: 1 day, 0:51:00 time: 1.3301 data_time: 0.0314 memory: 16201 loss_prob: 0.8006 loss_thr: 0.4724 loss_db: 0.1321 loss: 1.4050 2022/08/30 05:40:22 - mmengine - INFO - Epoch(train) [240][60/63] lr: 5.7307e-03 eta: 1 day, 0:50:41 time: 1.3543 data_time: 0.0296 memory: 16201 loss_prob: 0.7807 loss_thr: 0.4757 loss_db: 0.1307 loss: 1.3872 2022/08/30 05:40:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:40:26 - mmengine - INFO - Saving checkpoint at 240 epochs 2022/08/30 05:40:35 - mmengine - INFO - Epoch(val) [240][5/32] eta: 1 day, 0:50:41 time: 0.6910 data_time: 0.1406 memory: 16201 2022/08/30 05:40:38 - mmengine - INFO - Epoch(val) [240][10/32] eta: 0:00:17 time: 0.7829 data_time: 0.1828 memory: 15734 2022/08/30 05:40:41 - mmengine - INFO - Epoch(val) [240][15/32] eta: 0:00:17 time: 0.6486 data_time: 0.0620 memory: 15734 2022/08/30 05:40:45 - mmengine - INFO - Epoch(val) [240][20/32] eta: 0:00:08 time: 0.7168 data_time: 0.0622 memory: 15734 2022/08/30 05:40:49 - mmengine - INFO - Epoch(val) [240][25/32] eta: 0:00:08 time: 0.7311 data_time: 0.0691 memory: 15734 2022/08/30 05:40:51 - mmengine - INFO - Epoch(val) [240][30/32] eta: 0:00:01 time: 0.6084 data_time: 0.0299 memory: 15734 2022/08/30 05:40:52 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 05:40:52 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8416, precision: 0.7738, hmean: 0.8063 2022/08/30 05:40:52 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8416, precision: 0.8238, hmean: 0.8326 2022/08/30 05:40:52 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8334, precision: 0.8565, hmean: 0.8448 2022/08/30 05:40:52 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8195, precision: 0.8764, hmean: 0.8470 2022/08/30 05:40:52 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7867, precision: 0.9103, hmean: 0.8440 2022/08/30 05:40:52 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5725, precision: 0.9589, hmean: 0.7169 2022/08/30 05:40:52 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0217, precision: 0.9783, hmean: 0.0424 2022/08/30 05:40:52 - mmengine - INFO - Epoch(val) [240][32/32] icdar/precision: 0.8764 icdar/recall: 0.8195 icdar/hmean: 0.8470 2022/08/30 05:41:02 - mmengine - INFO - Epoch(train) [241][5/63] lr: 5.7253e-03 eta: 0:00:01 time: 1.5444 data_time: 0.2225 memory: 16201 loss_prob: 0.8895 loss_thr: 0.4952 loss_db: 0.1436 loss: 1.5283 2022/08/30 05:41:08 - mmengine - INFO - Epoch(train) [241][10/63] lr: 5.7253e-03 eta: 1 day, 0:50:07 time: 1.5714 data_time: 0.2331 memory: 16201 loss_prob: 0.8574 loss_thr: 0.4937 loss_db: 0.1434 loss: 1.4946 2022/08/30 05:41:15 - mmengine - INFO - Epoch(train) [241][15/63] lr: 5.7253e-03 eta: 1 day, 0:50:07 time: 1.3087 data_time: 0.0321 memory: 16201 loss_prob: 0.7789 loss_thr: 0.4672 loss_db: 0.1322 loss: 1.3783 2022/08/30 05:41:22 - mmengine - INFO - Epoch(train) [241][20/63] lr: 5.7253e-03 eta: 1 day, 0:49:47 time: 1.3496 data_time: 0.0353 memory: 16201 loss_prob: 0.6944 loss_thr: 0.4347 loss_db: 0.1175 loss: 1.2466 2022/08/30 05:41:28 - mmengine - INFO - Epoch(train) [241][25/63] lr: 5.7253e-03 eta: 1 day, 0:49:47 time: 1.3645 data_time: 0.0365 memory: 16201 loss_prob: 0.7216 loss_thr: 0.4689 loss_db: 0.1244 loss: 1.3149 2022/08/30 05:41:35 - mmengine - INFO - Epoch(train) [241][30/63] lr: 5.7253e-03 eta: 1 day, 0:49:26 time: 1.3082 data_time: 0.0328 memory: 16201 loss_prob: 0.7738 loss_thr: 0.5009 loss_db: 0.1332 loss: 1.4078 2022/08/30 05:41:41 - mmengine - INFO - Epoch(train) [241][35/63] lr: 5.7253e-03 eta: 1 day, 0:49:26 time: 1.2390 data_time: 0.0423 memory: 16201 loss_prob: 0.7868 loss_thr: 0.4939 loss_db: 0.1336 loss: 1.4142 2022/08/30 05:41:47 - mmengine - INFO - Epoch(train) [241][40/63] lr: 5.7253e-03 eta: 1 day, 0:49:03 time: 1.2733 data_time: 0.0381 memory: 16201 loss_prob: 0.7616 loss_thr: 0.4809 loss_db: 0.1290 loss: 1.3715 2022/08/30 05:41:54 - mmengine - INFO - Epoch(train) [241][45/63] lr: 5.7253e-03 eta: 1 day, 0:49:03 time: 1.2833 data_time: 0.0344 memory: 16201 loss_prob: 0.7596 loss_thr: 0.4782 loss_db: 0.1281 loss: 1.3659 2022/08/30 05:42:01 - mmengine - INFO - Epoch(train) [241][50/63] lr: 5.7253e-03 eta: 1 day, 0:48:42 time: 1.3272 data_time: 0.0474 memory: 16201 loss_prob: 0.8358 loss_thr: 0.5052 loss_db: 0.1398 loss: 1.4807 2022/08/30 05:42:07 - mmengine - INFO - Epoch(train) [241][55/63] lr: 5.7253e-03 eta: 1 day, 0:48:42 time: 1.2934 data_time: 0.0411 memory: 16201 loss_prob: 0.8973 loss_thr: 0.5109 loss_db: 0.1481 loss: 1.5563 2022/08/30 05:42:14 - mmengine - INFO - Epoch(train) [241][60/63] lr: 5.7253e-03 eta: 1 day, 0:48:23 time: 1.3597 data_time: 0.0359 memory: 16201 loss_prob: 0.9644 loss_thr: 0.5088 loss_db: 0.1649 loss: 1.6380 2022/08/30 05:42:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:42:27 - mmengine - INFO - Epoch(train) [242][5/63] lr: 5.7199e-03 eta: 1 day, 0:48:23 time: 1.5895 data_time: 0.2714 memory: 16201 loss_prob: 0.9381 loss_thr: 0.4953 loss_db: 0.1561 loss: 1.5895 2022/08/30 05:42:35 - mmengine - INFO - Epoch(train) [242][10/63] lr: 5.7199e-03 eta: 1 day, 0:47:54 time: 1.6900 data_time: 0.2629 memory: 16201 loss_prob: 1.0129 loss_thr: 0.5623 loss_db: 0.1612 loss: 1.7364 2022/08/30 05:42:42 - mmengine - INFO - Epoch(train) [242][15/63] lr: 5.7199e-03 eta: 1 day, 0:47:54 time: 1.4371 data_time: 0.0334 memory: 16201 loss_prob: 0.9038 loss_thr: 0.5192 loss_db: 0.1491 loss: 1.5720 2022/08/30 05:42:48 - mmengine - INFO - Epoch(train) [242][20/63] lr: 5.7199e-03 eta: 1 day, 0:47:34 time: 1.3449 data_time: 0.0353 memory: 16201 loss_prob: 0.8375 loss_thr: 0.4818 loss_db: 0.1375 loss: 1.4568 2022/08/30 05:42:55 - mmengine - INFO - Epoch(train) [242][25/63] lr: 5.7199e-03 eta: 1 day, 0:47:34 time: 1.3224 data_time: 0.0364 memory: 16201 loss_prob: 0.8887 loss_thr: 0.5010 loss_db: 0.1427 loss: 1.5324 2022/08/30 05:43:02 - mmengine - INFO - Epoch(train) [242][30/63] lr: 5.7199e-03 eta: 1 day, 0:47:17 time: 1.4261 data_time: 0.0315 memory: 16201 loss_prob: 0.8845 loss_thr: 0.4980 loss_db: 0.1475 loss: 1.5300 2022/08/30 05:43:09 - mmengine - INFO - Epoch(train) [242][35/63] lr: 5.7199e-03 eta: 1 day, 0:47:17 time: 1.4490 data_time: 0.0352 memory: 16201 loss_prob: 0.8475 loss_thr: 0.4933 loss_db: 0.1452 loss: 1.4861 2022/08/30 05:43:16 - mmengine - INFO - Epoch(train) [242][40/63] lr: 5.7199e-03 eta: 1 day, 0:46:59 time: 1.3881 data_time: 0.0311 memory: 16201 loss_prob: 0.8162 loss_thr: 0.4975 loss_db: 0.1389 loss: 1.4526 2022/08/30 05:43:23 - mmengine - INFO - Epoch(train) [242][45/63] lr: 5.7199e-03 eta: 1 day, 0:46:59 time: 1.3379 data_time: 0.0289 memory: 16201 loss_prob: 0.8560 loss_thr: 0.5050 loss_db: 0.1418 loss: 1.5028 2022/08/30 05:43:30 - mmengine - INFO - Epoch(train) [242][50/63] lr: 5.7199e-03 eta: 1 day, 0:46:40 time: 1.3747 data_time: 0.0410 memory: 16201 loss_prob: 0.8162 loss_thr: 0.4998 loss_db: 0.1384 loss: 1.4544 2022/08/30 05:43:36 - mmengine - INFO - Epoch(train) [242][55/63] lr: 5.7199e-03 eta: 1 day, 0:46:40 time: 1.3396 data_time: 0.0343 memory: 16201 loss_prob: 0.7906 loss_thr: 0.4909 loss_db: 0.1362 loss: 1.4177 2022/08/30 05:43:43 - mmengine - INFO - Epoch(train) [242][60/63] lr: 5.7199e-03 eta: 1 day, 0:46:19 time: 1.3160 data_time: 0.0307 memory: 16201 loss_prob: 0.8684 loss_thr: 0.4707 loss_db: 0.1391 loss: 1.4782 2022/08/30 05:43:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:43:55 - mmengine - INFO - Epoch(train) [243][5/63] lr: 5.7146e-03 eta: 1 day, 0:46:19 time: 1.4436 data_time: 0.2529 memory: 16201 loss_prob: 0.9468 loss_thr: 0.4703 loss_db: 0.1532 loss: 1.5703 2022/08/30 05:44:02 - mmengine - INFO - Epoch(train) [243][10/63] lr: 5.7146e-03 eta: 1 day, 0:45:47 time: 1.6095 data_time: 0.2640 memory: 16201 loss_prob: 0.8670 loss_thr: 0.4748 loss_db: 0.1501 loss: 1.4919 2022/08/30 05:44:08 - mmengine - INFO - Epoch(train) [243][15/63] lr: 5.7146e-03 eta: 1 day, 0:45:47 time: 1.3465 data_time: 0.0326 memory: 16201 loss_prob: 0.9131 loss_thr: 0.4845 loss_db: 0.1550 loss: 1.5526 2022/08/30 05:44:15 - mmengine - INFO - Epoch(train) [243][20/63] lr: 5.7146e-03 eta: 1 day, 0:45:24 time: 1.2610 data_time: 0.0317 memory: 16201 loss_prob: 0.8326 loss_thr: 0.4731 loss_db: 0.1369 loss: 1.4426 2022/08/30 05:44:22 - mmengine - INFO - Epoch(train) [243][25/63] lr: 5.7146e-03 eta: 1 day, 0:45:24 time: 1.3181 data_time: 0.0483 memory: 16201 loss_prob: 0.9113 loss_thr: 0.4974 loss_db: 0.1464 loss: 1.5551 2022/08/30 05:44:28 - mmengine - INFO - Epoch(train) [243][30/63] lr: 5.7146e-03 eta: 1 day, 0:45:04 time: 1.3369 data_time: 0.0377 memory: 16201 loss_prob: 1.0334 loss_thr: 0.5243 loss_db: 0.1662 loss: 1.7239 2022/08/30 05:44:35 - mmengine - INFO - Epoch(train) [243][35/63] lr: 5.7146e-03 eta: 1 day, 0:45:04 time: 1.3571 data_time: 0.0272 memory: 16201 loss_prob: 0.9694 loss_thr: 0.5280 loss_db: 0.1591 loss: 1.6566 2022/08/30 05:44:42 - mmengine - INFO - Epoch(train) [243][40/63] lr: 5.7146e-03 eta: 1 day, 0:44:45 time: 1.3680 data_time: 0.0299 memory: 16201 loss_prob: 0.8256 loss_thr: 0.5041 loss_db: 0.1377 loss: 1.4674 2022/08/30 05:44:48 - mmengine - INFO - Epoch(train) [243][45/63] lr: 5.7146e-03 eta: 1 day, 0:44:45 time: 1.2772 data_time: 0.0290 memory: 16201 loss_prob: 1.0050 loss_thr: 0.5443 loss_db: 0.1580 loss: 1.7074 2022/08/30 05:44:55 - mmengine - INFO - Epoch(train) [243][50/63] lr: 5.7146e-03 eta: 1 day, 0:44:24 time: 1.3149 data_time: 0.0381 memory: 16201 loss_prob: 1.0709 loss_thr: 0.5646 loss_db: 0.1716 loss: 1.8071 2022/08/30 05:45:01 - mmengine - INFO - Epoch(train) [243][55/63] lr: 5.7146e-03 eta: 1 day, 0:44:24 time: 1.3430 data_time: 0.0388 memory: 16201 loss_prob: 0.9177 loss_thr: 0.5100 loss_db: 0.1533 loss: 1.5809 2022/08/30 05:45:08 - mmengine - INFO - Epoch(train) [243][60/63] lr: 5.7146e-03 eta: 1 day, 0:44:03 time: 1.3227 data_time: 0.0410 memory: 16201 loss_prob: 0.8370 loss_thr: 0.4865 loss_db: 0.1358 loss: 1.4593 2022/08/30 05:45:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:45:21 - mmengine - INFO - Epoch(train) [244][5/63] lr: 5.7092e-03 eta: 1 day, 0:44:03 time: 1.4881 data_time: 0.2475 memory: 16201 loss_prob: 0.8534 loss_thr: 0.4746 loss_db: 0.1365 loss: 1.4645 2022/08/30 05:45:27 - mmengine - INFO - Epoch(train) [244][10/63] lr: 5.7092e-03 eta: 1 day, 0:43:27 time: 1.5022 data_time: 0.2642 memory: 16201 loss_prob: 0.8942 loss_thr: 0.5055 loss_db: 0.1455 loss: 1.5452 2022/08/30 05:45:32 - mmengine - INFO - Epoch(train) [244][15/63] lr: 5.7092e-03 eta: 1 day, 0:43:27 time: 1.1753 data_time: 0.0327 memory: 16201 loss_prob: 0.8407 loss_thr: 0.5055 loss_db: 0.1386 loss: 1.4848 2022/08/30 05:45:38 - mmengine - INFO - Epoch(train) [244][20/63] lr: 5.7092e-03 eta: 1 day, 0:43:01 time: 1.1875 data_time: 0.0326 memory: 16201 loss_prob: 0.8134 loss_thr: 0.4825 loss_db: 0.1325 loss: 1.4284 2022/08/30 05:45:45 - mmengine - INFO - Epoch(train) [244][25/63] lr: 5.7092e-03 eta: 1 day, 0:43:01 time: 1.2581 data_time: 0.0341 memory: 16201 loss_prob: 0.7943 loss_thr: 0.4974 loss_db: 0.1334 loss: 1.4251 2022/08/30 05:45:51 - mmengine - INFO - Epoch(train) [244][30/63] lr: 5.7092e-03 eta: 1 day, 0:42:38 time: 1.2679 data_time: 0.0352 memory: 16201 loss_prob: 0.7768 loss_thr: 0.4974 loss_db: 0.1315 loss: 1.4057 2022/08/30 05:45:57 - mmengine - INFO - Epoch(train) [244][35/63] lr: 5.7092e-03 eta: 1 day, 0:42:38 time: 1.2503 data_time: 0.0411 memory: 16201 loss_prob: 0.8324 loss_thr: 0.4888 loss_db: 0.1322 loss: 1.4533 2022/08/30 05:46:04 - mmengine - INFO - Epoch(train) [244][40/63] lr: 5.7092e-03 eta: 1 day, 0:42:15 time: 1.2650 data_time: 0.0326 memory: 16201 loss_prob: 0.8121 loss_thr: 0.4696 loss_db: 0.1286 loss: 1.4103 2022/08/30 05:46:10 - mmengine - INFO - Epoch(train) [244][45/63] lr: 5.7092e-03 eta: 1 day, 0:42:15 time: 1.2956 data_time: 0.0344 memory: 16201 loss_prob: 0.7673 loss_thr: 0.4567 loss_db: 0.1288 loss: 1.3529 2022/08/30 05:46:17 - mmengine - INFO - Epoch(train) [244][50/63] lr: 5.7092e-03 eta: 1 day, 0:41:56 time: 1.3609 data_time: 0.0410 memory: 16201 loss_prob: 0.8169 loss_thr: 0.4877 loss_db: 0.1386 loss: 1.4432 2022/08/30 05:46:24 - mmengine - INFO - Epoch(train) [244][55/63] lr: 5.7092e-03 eta: 1 day, 0:41:56 time: 1.3649 data_time: 0.0323 memory: 16201 loss_prob: 0.8402 loss_thr: 0.4924 loss_db: 0.1398 loss: 1.4724 2022/08/30 05:46:31 - mmengine - INFO - Epoch(train) [244][60/63] lr: 5.7092e-03 eta: 1 day, 0:41:35 time: 1.3243 data_time: 0.0347 memory: 16201 loss_prob: 1.0821 loss_thr: 0.5038 loss_db: 0.1647 loss: 1.7505 2022/08/30 05:46:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:46:44 - mmengine - INFO - Epoch(train) [245][5/63] lr: 5.7038e-03 eta: 1 day, 0:41:35 time: 1.5661 data_time: 0.2274 memory: 16201 loss_prob: 0.8252 loss_thr: 0.4912 loss_db: 0.1364 loss: 1.4528 2022/08/30 05:46:51 - mmengine - INFO - Epoch(train) [245][10/63] lr: 5.7038e-03 eta: 1 day, 0:41:04 time: 1.6177 data_time: 0.2426 memory: 16201 loss_prob: 0.8037 loss_thr: 0.4830 loss_db: 0.1339 loss: 1.4205 2022/08/30 05:46:58 - mmengine - INFO - Epoch(train) [245][15/63] lr: 5.7038e-03 eta: 1 day, 0:41:04 time: 1.3990 data_time: 0.0334 memory: 16201 loss_prob: 0.8605 loss_thr: 0.4900 loss_db: 0.1410 loss: 1.4916 2022/08/30 05:47:04 - mmengine - INFO - Epoch(train) [245][20/63] lr: 5.7038e-03 eta: 1 day, 0:40:45 time: 1.3671 data_time: 0.0344 memory: 16201 loss_prob: 0.8526 loss_thr: 0.4902 loss_db: 0.1370 loss: 1.4798 2022/08/30 05:47:11 - mmengine - INFO - Epoch(train) [245][25/63] lr: 5.7038e-03 eta: 1 day, 0:40:45 time: 1.2949 data_time: 0.0447 memory: 16201 loss_prob: 0.8290 loss_thr: 0.4983 loss_db: 0.1340 loss: 1.4613 2022/08/30 05:47:17 - mmengine - INFO - Epoch(train) [245][30/63] lr: 5.7038e-03 eta: 1 day, 0:40:23 time: 1.2849 data_time: 0.0330 memory: 16201 loss_prob: 0.8037 loss_thr: 0.5037 loss_db: 0.1319 loss: 1.4392 2022/08/30 05:47:24 - mmengine - INFO - Epoch(train) [245][35/63] lr: 5.7038e-03 eta: 1 day, 0:40:23 time: 1.3163 data_time: 0.0299 memory: 16201 loss_prob: 0.7674 loss_thr: 0.4910 loss_db: 0.1301 loss: 1.3886 2022/08/30 05:47:30 - mmengine - INFO - Epoch(train) [245][40/63] lr: 5.7038e-03 eta: 1 day, 0:40:01 time: 1.2996 data_time: 0.0325 memory: 16201 loss_prob: 0.7707 loss_thr: 0.4564 loss_db: 0.1288 loss: 1.3559 2022/08/30 05:47:37 - mmengine - INFO - Epoch(train) [245][45/63] lr: 5.7038e-03 eta: 1 day, 0:40:01 time: 1.3328 data_time: 0.0335 memory: 16201 loss_prob: 0.8179 loss_thr: 0.4667 loss_db: 0.1338 loss: 1.4184 2022/08/30 05:47:44 - mmengine - INFO - Epoch(train) [245][50/63] lr: 5.7038e-03 eta: 1 day, 0:39:42 time: 1.3590 data_time: 0.0405 memory: 16201 loss_prob: 0.7664 loss_thr: 0.4572 loss_db: 0.1253 loss: 1.3489 2022/08/30 05:47:51 - mmengine - INFO - Epoch(train) [245][55/63] lr: 5.7038e-03 eta: 1 day, 0:39:42 time: 1.3957 data_time: 0.0408 memory: 16201 loss_prob: 0.7943 loss_thr: 0.4564 loss_db: 0.1280 loss: 1.3787 2022/08/30 05:47:58 - mmengine - INFO - Epoch(train) [245][60/63] lr: 5.7038e-03 eta: 1 day, 0:39:24 time: 1.4000 data_time: 0.0373 memory: 16201 loss_prob: 0.8638 loss_thr: 0.4898 loss_db: 0.1412 loss: 1.4948 2022/08/30 05:48:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:48:11 - mmengine - INFO - Epoch(train) [246][5/63] lr: 5.6984e-03 eta: 1 day, 0:39:24 time: 1.5275 data_time: 0.2261 memory: 16201 loss_prob: 0.8426 loss_thr: 0.5045 loss_db: 0.1401 loss: 1.4872 2022/08/30 05:48:18 - mmengine - INFO - Epoch(train) [246][10/63] lr: 5.6984e-03 eta: 1 day, 0:38:55 time: 1.6648 data_time: 0.2355 memory: 16201 loss_prob: 0.8180 loss_thr: 0.4843 loss_db: 0.1385 loss: 1.4407 2022/08/30 05:48:26 - mmengine - INFO - Epoch(train) [246][15/63] lr: 5.6984e-03 eta: 1 day, 0:38:55 time: 1.4997 data_time: 0.0319 memory: 16201 loss_prob: 0.8055 loss_thr: 0.4922 loss_db: 0.1343 loss: 1.4321 2022/08/30 05:48:33 - mmengine - INFO - Epoch(train) [246][20/63] lr: 5.6984e-03 eta: 1 day, 0:38:40 time: 1.4575 data_time: 0.0546 memory: 16201 loss_prob: 0.8465 loss_thr: 0.4983 loss_db: 0.1404 loss: 1.4852 2022/08/30 05:48:40 - mmengine - INFO - Epoch(train) [246][25/63] lr: 5.6984e-03 eta: 1 day, 0:38:40 time: 1.4553 data_time: 0.0458 memory: 16201 loss_prob: 0.8804 loss_thr: 0.4905 loss_db: 0.1446 loss: 1.5155 2022/08/30 05:48:47 - mmengine - INFO - Epoch(train) [246][30/63] lr: 5.6984e-03 eta: 1 day, 0:38:22 time: 1.4093 data_time: 0.0291 memory: 16201 loss_prob: 0.7963 loss_thr: 0.4653 loss_db: 0.1323 loss: 1.3939 2022/08/30 05:48:53 - mmengine - INFO - Epoch(train) [246][35/63] lr: 5.6984e-03 eta: 1 day, 0:38:22 time: 1.3059 data_time: 0.0326 memory: 16201 loss_prob: 0.8443 loss_thr: 0.4883 loss_db: 0.1388 loss: 1.4714 2022/08/30 05:49:00 - mmengine - INFO - Epoch(train) [246][40/63] lr: 5.6984e-03 eta: 1 day, 0:38:02 time: 1.3198 data_time: 0.0298 memory: 16201 loss_prob: 0.9071 loss_thr: 0.5082 loss_db: 0.1478 loss: 1.5631 2022/08/30 05:49:06 - mmengine - INFO - Epoch(train) [246][45/63] lr: 5.6984e-03 eta: 1 day, 0:38:02 time: 1.2961 data_time: 0.0377 memory: 16201 loss_prob: 0.8042 loss_thr: 0.4797 loss_db: 0.1364 loss: 1.4203 2022/08/30 05:49:13 - mmengine - INFO - Epoch(train) [246][50/63] lr: 5.6984e-03 eta: 1 day, 0:37:37 time: 1.2287 data_time: 0.0342 memory: 16201 loss_prob: 0.7062 loss_thr: 0.4482 loss_db: 0.1197 loss: 1.2742 2022/08/30 05:49:19 - mmengine - INFO - Epoch(train) [246][55/63] lr: 5.6984e-03 eta: 1 day, 0:37:37 time: 1.2946 data_time: 0.0304 memory: 16201 loss_prob: 0.7553 loss_thr: 0.4564 loss_db: 0.1281 loss: 1.3398 2022/08/30 05:49:26 - mmengine - INFO - Epoch(train) [246][60/63] lr: 5.6984e-03 eta: 1 day, 0:37:16 time: 1.2987 data_time: 0.0398 memory: 16201 loss_prob: 0.8351 loss_thr: 0.4860 loss_db: 0.1410 loss: 1.4621 2022/08/30 05:49:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:49:38 - mmengine - INFO - Epoch(train) [247][5/63] lr: 5.6931e-03 eta: 1 day, 0:37:16 time: 1.4464 data_time: 0.2281 memory: 16201 loss_prob: 0.7582 loss_thr: 0.4635 loss_db: 0.1259 loss: 1.3475 2022/08/30 05:49:44 - mmengine - INFO - Epoch(train) [247][10/63] lr: 5.6931e-03 eta: 1 day, 0:36:40 time: 1.5012 data_time: 0.2354 memory: 16201 loss_prob: 0.7786 loss_thr: 0.4638 loss_db: 0.1311 loss: 1.3735 2022/08/30 05:49:50 - mmengine - INFO - Epoch(train) [247][15/63] lr: 5.6931e-03 eta: 1 day, 0:36:40 time: 1.2847 data_time: 0.0346 memory: 16201 loss_prob: 0.8222 loss_thr: 0.4911 loss_db: 0.1385 loss: 1.4519 2022/08/30 05:49:57 - mmengine - INFO - Epoch(train) [247][20/63] lr: 5.6931e-03 eta: 1 day, 0:36:17 time: 1.2541 data_time: 0.0359 memory: 16201 loss_prob: 0.8305 loss_thr: 0.4956 loss_db: 0.1378 loss: 1.4640 2022/08/30 05:50:03 - mmengine - INFO - Epoch(train) [247][25/63] lr: 5.6931e-03 eta: 1 day, 0:36:17 time: 1.2430 data_time: 0.0373 memory: 16201 loss_prob: 0.7650 loss_thr: 0.4515 loss_db: 0.1266 loss: 1.3431 2022/08/30 05:50:09 - mmengine - INFO - Epoch(train) [247][30/63] lr: 5.6931e-03 eta: 1 day, 0:35:54 time: 1.2536 data_time: 0.0394 memory: 16201 loss_prob: 0.8103 loss_thr: 0.5046 loss_db: 0.1334 loss: 1.4483 2022/08/30 05:50:16 - mmengine - INFO - Epoch(train) [247][35/63] lr: 5.6931e-03 eta: 1 day, 0:35:54 time: 1.3312 data_time: 0.0352 memory: 16201 loss_prob: 0.9486 loss_thr: 0.5511 loss_db: 0.1559 loss: 1.6556 2022/08/30 05:50:23 - mmengine - INFO - Epoch(train) [247][40/63] lr: 5.6931e-03 eta: 1 day, 0:35:34 time: 1.3331 data_time: 0.0334 memory: 16201 loss_prob: 0.9236 loss_thr: 0.5255 loss_db: 0.1486 loss: 1.5977 2022/08/30 05:50:29 - mmengine - INFO - Epoch(train) [247][45/63] lr: 5.6931e-03 eta: 1 day, 0:35:34 time: 1.2834 data_time: 0.0412 memory: 16201 loss_prob: 0.7929 loss_thr: 0.4927 loss_db: 0.1302 loss: 1.4158 2022/08/30 05:50:36 - mmengine - INFO - Epoch(train) [247][50/63] lr: 5.6931e-03 eta: 1 day, 0:35:13 time: 1.3306 data_time: 0.0330 memory: 16201 loss_prob: 0.7441 loss_thr: 0.4587 loss_db: 0.1266 loss: 1.3294 2022/08/30 05:50:42 - mmengine - INFO - Epoch(train) [247][55/63] lr: 5.6931e-03 eta: 1 day, 0:35:13 time: 1.3480 data_time: 0.0296 memory: 16201 loss_prob: 0.7967 loss_thr: 0.4660 loss_db: 0.1302 loss: 1.3929 2022/08/30 05:50:50 - mmengine - INFO - Epoch(train) [247][60/63] lr: 5.6931e-03 eta: 1 day, 0:34:57 time: 1.4355 data_time: 0.0416 memory: 16201 loss_prob: 0.8091 loss_thr: 0.4815 loss_db: 0.1301 loss: 1.4206 2022/08/30 05:50:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:51:02 - mmengine - INFO - Epoch(train) [248][5/63] lr: 5.6877e-03 eta: 1 day, 0:34:57 time: 1.4706 data_time: 0.2373 memory: 16201 loss_prob: 0.8967 loss_thr: 0.5109 loss_db: 0.1509 loss: 1.5584 2022/08/30 05:51:09 - mmengine - INFO - Epoch(train) [248][10/63] lr: 5.6877e-03 eta: 1 day, 0:34:21 time: 1.4841 data_time: 0.2454 memory: 16201 loss_prob: 0.7924 loss_thr: 0.4730 loss_db: 0.1375 loss: 1.4029 2022/08/30 05:51:15 - mmengine - INFO - Epoch(train) [248][15/63] lr: 5.6877e-03 eta: 1 day, 0:34:21 time: 1.2955 data_time: 0.0415 memory: 16201 loss_prob: 0.7985 loss_thr: 0.4764 loss_db: 0.1346 loss: 1.4095 2022/08/30 05:51:22 - mmengine - INFO - Epoch(train) [248][20/63] lr: 5.6877e-03 eta: 1 day, 0:34:02 time: 1.3459 data_time: 0.0441 memory: 16201 loss_prob: 0.8031 loss_thr: 0.4993 loss_db: 0.1350 loss: 1.4374 2022/08/30 05:51:28 - mmengine - INFO - Epoch(train) [248][25/63] lr: 5.6877e-03 eta: 1 day, 0:34:02 time: 1.2646 data_time: 0.0352 memory: 16201 loss_prob: 0.7331 loss_thr: 0.4798 loss_db: 0.1233 loss: 1.3362 2022/08/30 05:51:35 - mmengine - INFO - Epoch(train) [248][30/63] lr: 5.6877e-03 eta: 1 day, 0:33:42 time: 1.3389 data_time: 0.1029 memory: 16201 loss_prob: 0.6953 loss_thr: 0.4512 loss_db: 0.1178 loss: 1.2643 2022/08/30 05:51:42 - mmengine - INFO - Epoch(train) [248][35/63] lr: 5.6877e-03 eta: 1 day, 0:33:42 time: 1.3724 data_time: 0.1032 memory: 16201 loss_prob: 0.7079 loss_thr: 0.4655 loss_db: 0.1208 loss: 1.2942 2022/08/30 05:51:49 - mmengine - INFO - Epoch(train) [248][40/63] lr: 5.6877e-03 eta: 1 day, 0:33:23 time: 1.3766 data_time: 0.0309 memory: 16201 loss_prob: 0.7142 loss_thr: 0.4678 loss_db: 0.1204 loss: 1.3024 2022/08/30 05:51:56 - mmengine - INFO - Epoch(train) [248][45/63] lr: 5.6877e-03 eta: 1 day, 0:33:23 time: 1.4170 data_time: 0.0341 memory: 16201 loss_prob: 0.7051 loss_thr: 0.4622 loss_db: 0.1198 loss: 1.2872 2022/08/30 05:52:03 - mmengine - INFO - Epoch(train) [248][50/63] lr: 5.6877e-03 eta: 1 day, 0:33:05 time: 1.3767 data_time: 0.0378 memory: 16201 loss_prob: 0.7604 loss_thr: 0.4628 loss_db: 0.1352 loss: 1.3583 2022/08/30 05:52:10 - mmengine - INFO - Epoch(train) [248][55/63] lr: 5.6877e-03 eta: 1 day, 0:33:05 time: 1.3644 data_time: 0.0418 memory: 16201 loss_prob: 0.8770 loss_thr: 0.4759 loss_db: 0.1542 loss: 1.5071 2022/08/30 05:52:16 - mmengine - INFO - Epoch(train) [248][60/63] lr: 5.6877e-03 eta: 1 day, 0:32:43 time: 1.3009 data_time: 0.0420 memory: 16201 loss_prob: 1.0114 loss_thr: 0.5156 loss_db: 0.1661 loss: 1.6931 2022/08/30 05:52:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:52:28 - mmengine - INFO - Epoch(train) [249][5/63] lr: 5.6823e-03 eta: 1 day, 0:32:43 time: 1.4793 data_time: 0.2442 memory: 16201 loss_prob: 0.9881 loss_thr: 0.5416 loss_db: 0.1620 loss: 1.6916 2022/08/30 05:52:36 - mmengine - INFO - Epoch(train) [249][10/63] lr: 5.6823e-03 eta: 1 day, 0:32:14 time: 1.6525 data_time: 0.2460 memory: 16201 loss_prob: 0.9208 loss_thr: 0.4878 loss_db: 0.1507 loss: 1.5593 2022/08/30 05:52:42 - mmengine - INFO - Epoch(train) [249][15/63] lr: 5.6823e-03 eta: 1 day, 0:32:14 time: 1.3852 data_time: 0.0332 memory: 16201 loss_prob: 0.8997 loss_thr: 0.5030 loss_db: 0.1475 loss: 1.5503 2022/08/30 05:52:48 - mmengine - INFO - Epoch(train) [249][20/63] lr: 5.6823e-03 eta: 1 day, 0:31:50 time: 1.2221 data_time: 0.0400 memory: 16201 loss_prob: 0.8990 loss_thr: 0.5102 loss_db: 0.1483 loss: 1.5575 2022/08/30 05:52:54 - mmengine - INFO - Epoch(train) [249][25/63] lr: 5.6823e-03 eta: 1 day, 0:31:50 time: 1.2525 data_time: 0.0404 memory: 16201 loss_prob: 0.9505 loss_thr: 0.5178 loss_db: 0.1586 loss: 1.6270 2022/08/30 05:53:01 - mmengine - INFO - Epoch(train) [249][30/63] lr: 5.6823e-03 eta: 1 day, 0:31:29 time: 1.3005 data_time: 0.0291 memory: 16201 loss_prob: 0.9751 loss_thr: 0.5278 loss_db: 0.1575 loss: 1.6604 2022/08/30 05:53:08 - mmengine - INFO - Epoch(train) [249][35/63] lr: 5.6823e-03 eta: 1 day, 0:31:29 time: 1.3012 data_time: 0.0339 memory: 16201 loss_prob: 1.0368 loss_thr: 0.5110 loss_db: 0.1695 loss: 1.7173 2022/08/30 05:53:14 - mmengine - INFO - Epoch(train) [249][40/63] lr: 5.6823e-03 eta: 1 day, 0:31:07 time: 1.3057 data_time: 0.0319 memory: 16201 loss_prob: 1.0362 loss_thr: 0.5096 loss_db: 0.1705 loss: 1.7163 2022/08/30 05:53:21 - mmengine - INFO - Epoch(train) [249][45/63] lr: 5.6823e-03 eta: 1 day, 0:31:07 time: 1.3642 data_time: 0.0333 memory: 16201 loss_prob: 1.0148 loss_thr: 0.5231 loss_db: 0.1593 loss: 1.6972 2022/08/30 05:53:28 - mmengine - INFO - Epoch(train) [249][50/63] lr: 5.6823e-03 eta: 1 day, 0:30:51 time: 1.4153 data_time: 0.0364 memory: 16201 loss_prob: 1.0183 loss_thr: 0.5093 loss_db: 0.1637 loss: 1.6913 2022/08/30 05:53:35 - mmengine - INFO - Epoch(train) [249][55/63] lr: 5.6823e-03 eta: 1 day, 0:30:51 time: 1.3563 data_time: 0.0277 memory: 16201 loss_prob: 0.9901 loss_thr: 0.5244 loss_db: 0.1667 loss: 1.6812 2022/08/30 05:53:42 - mmengine - INFO - Epoch(train) [249][60/63] lr: 5.6823e-03 eta: 1 day, 0:30:30 time: 1.3217 data_time: 0.0292 memory: 16201 loss_prob: 0.9798 loss_thr: 0.5315 loss_db: 0.1658 loss: 1.6771 2022/08/30 05:53:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:53:54 - mmengine - INFO - Epoch(train) [250][5/63] lr: 5.6769e-03 eta: 1 day, 0:30:30 time: 1.5690 data_time: 0.2128 memory: 16201 loss_prob: 0.8939 loss_thr: 0.4776 loss_db: 0.1501 loss: 1.5216 2022/08/30 05:54:01 - mmengine - INFO - Epoch(train) [250][10/63] lr: 5.6769e-03 eta: 1 day, 0:29:58 time: 1.5652 data_time: 0.2248 memory: 16201 loss_prob: 0.9448 loss_thr: 0.5281 loss_db: 0.1572 loss: 1.6301 2022/08/30 05:54:08 - mmengine - INFO - Epoch(train) [250][15/63] lr: 5.6769e-03 eta: 1 day, 0:29:58 time: 1.3196 data_time: 0.0396 memory: 16201 loss_prob: 0.9938 loss_thr: 0.5173 loss_db: 0.1635 loss: 1.6746 2022/08/30 05:54:15 - mmengine - INFO - Epoch(train) [250][20/63] lr: 5.6769e-03 eta: 1 day, 0:29:38 time: 1.3365 data_time: 0.0392 memory: 16201 loss_prob: 0.9734 loss_thr: 0.4955 loss_db: 0.1634 loss: 1.6323 2022/08/30 05:54:21 - mmengine - INFO - Epoch(train) [250][25/63] lr: 5.6769e-03 eta: 1 day, 0:29:38 time: 1.3381 data_time: 0.0350 memory: 16201 loss_prob: 0.9710 loss_thr: 0.5074 loss_db: 0.1585 loss: 1.6369 2022/08/30 05:54:28 - mmengine - INFO - Epoch(train) [250][30/63] lr: 5.6769e-03 eta: 1 day, 0:29:19 time: 1.3604 data_time: 0.0337 memory: 16201 loss_prob: 0.9045 loss_thr: 0.4951 loss_db: 0.1466 loss: 1.5463 2022/08/30 05:54:35 - mmengine - INFO - Epoch(train) [250][35/63] lr: 5.6769e-03 eta: 1 day, 0:29:19 time: 1.4397 data_time: 0.0359 memory: 16201 loss_prob: 0.7932 loss_thr: 0.4808 loss_db: 0.1334 loss: 1.4075 2022/08/30 05:54:41 - mmengine - INFO - Epoch(train) [250][40/63] lr: 5.6769e-03 eta: 1 day, 0:28:58 time: 1.3251 data_time: 0.0314 memory: 16201 loss_prob: 0.7906 loss_thr: 0.4733 loss_db: 0.1340 loss: 1.3980 2022/08/30 05:54:48 - mmengine - INFO - Epoch(train) [250][45/63] lr: 5.6769e-03 eta: 1 day, 0:28:58 time: 1.2253 data_time: 0.0286 memory: 16201 loss_prob: 0.8763 loss_thr: 0.5082 loss_db: 0.1485 loss: 1.5330 2022/08/30 05:54:54 - mmengine - INFO - Epoch(train) [250][50/63] lr: 5.6769e-03 eta: 1 day, 0:28:37 time: 1.2942 data_time: 0.0329 memory: 16201 loss_prob: 0.9120 loss_thr: 0.5259 loss_db: 0.1519 loss: 1.5898 2022/08/30 05:55:02 - mmengine - INFO - Epoch(train) [250][55/63] lr: 5.6769e-03 eta: 1 day, 0:28:37 time: 1.3863 data_time: 0.0331 memory: 16201 loss_prob: 0.8365 loss_thr: 0.4923 loss_db: 0.1392 loss: 1.4680 2022/08/30 05:55:09 - mmengine - INFO - Epoch(train) [250][60/63] lr: 5.6769e-03 eta: 1 day, 0:28:22 time: 1.4749 data_time: 0.0474 memory: 16201 loss_prob: 0.8396 loss_thr: 0.4755 loss_db: 0.1370 loss: 1.4522 2022/08/30 05:55:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:55:21 - mmengine - INFO - Epoch(train) [251][5/63] lr: 5.6716e-03 eta: 1 day, 0:28:22 time: 1.4427 data_time: 0.2286 memory: 16201 loss_prob: 0.8688 loss_thr: 0.4915 loss_db: 0.1432 loss: 1.5034 2022/08/30 05:55:28 - mmengine - INFO - Epoch(train) [251][10/63] lr: 5.6716e-03 eta: 1 day, 0:27:51 time: 1.5914 data_time: 0.2422 memory: 16201 loss_prob: 0.7801 loss_thr: 0.4652 loss_db: 0.1302 loss: 1.3755 2022/08/30 05:55:35 - mmengine - INFO - Epoch(train) [251][15/63] lr: 5.6716e-03 eta: 1 day, 0:27:51 time: 1.4489 data_time: 0.0444 memory: 16201 loss_prob: 0.7293 loss_thr: 0.4561 loss_db: 0.1218 loss: 1.3072 2022/08/30 05:55:43 - mmengine - INFO - Epoch(train) [251][20/63] lr: 5.6716e-03 eta: 1 day, 0:27:35 time: 1.4455 data_time: 0.0326 memory: 16201 loss_prob: 0.7667 loss_thr: 0.4661 loss_db: 0.1289 loss: 1.3617 2022/08/30 05:55:50 - mmengine - INFO - Epoch(train) [251][25/63] lr: 5.6716e-03 eta: 1 day, 0:27:35 time: 1.4982 data_time: 0.0348 memory: 16201 loss_prob: 0.7343 loss_thr: 0.4496 loss_db: 0.1265 loss: 1.3103 2022/08/30 05:55:57 - mmengine - INFO - Epoch(train) [251][30/63] lr: 5.6716e-03 eta: 1 day, 0:27:17 time: 1.3873 data_time: 0.0370 memory: 16201 loss_prob: 0.7137 loss_thr: 0.4484 loss_db: 0.1227 loss: 1.2847 2022/08/30 05:56:04 - mmengine - INFO - Epoch(train) [251][35/63] lr: 5.6716e-03 eta: 1 day, 0:27:17 time: 1.3904 data_time: 0.0385 memory: 16201 loss_prob: 0.7416 loss_thr: 0.4537 loss_db: 0.1247 loss: 1.3200 2022/08/30 05:56:11 - mmengine - INFO - Epoch(train) [251][40/63] lr: 5.6716e-03 eta: 1 day, 0:27:01 time: 1.4402 data_time: 0.0303 memory: 16201 loss_prob: 0.7849 loss_thr: 0.4726 loss_db: 0.1310 loss: 1.3885 2022/08/30 05:56:17 - mmengine - INFO - Epoch(train) [251][45/63] lr: 5.6716e-03 eta: 1 day, 0:27:01 time: 1.3313 data_time: 0.0305 memory: 16201 loss_prob: 0.7930 loss_thr: 0.4730 loss_db: 0.1298 loss: 1.3958 2022/08/30 05:56:24 - mmengine - INFO - Epoch(train) [251][50/63] lr: 5.6716e-03 eta: 1 day, 0:26:40 time: 1.3088 data_time: 0.0362 memory: 16201 loss_prob: 0.7746 loss_thr: 0.4565 loss_db: 0.1290 loss: 1.3601 2022/08/30 05:56:31 - mmengine - INFO - Epoch(train) [251][55/63] lr: 5.6716e-03 eta: 1 day, 0:26:40 time: 1.3758 data_time: 0.0350 memory: 16201 loss_prob: 0.8296 loss_thr: 0.4909 loss_db: 0.1400 loss: 1.4605 2022/08/30 05:56:38 - mmengine - INFO - Epoch(train) [251][60/63] lr: 5.6716e-03 eta: 1 day, 0:26:22 time: 1.3795 data_time: 0.0315 memory: 16201 loss_prob: 0.8479 loss_thr: 0.5085 loss_db: 0.1443 loss: 1.5007 2022/08/30 05:56:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:56:50 - mmengine - INFO - Epoch(train) [252][5/63] lr: 5.6662e-03 eta: 1 day, 0:26:22 time: 1.4456 data_time: 0.2271 memory: 16201 loss_prob: 0.7805 loss_thr: 0.4670 loss_db: 0.1262 loss: 1.3737 2022/08/30 05:56:57 - mmengine - INFO - Epoch(train) [252][10/63] lr: 5.6662e-03 eta: 1 day, 0:25:50 time: 1.5655 data_time: 0.2482 memory: 16201 loss_prob: 0.7734 loss_thr: 0.4517 loss_db: 0.1318 loss: 1.3569 2022/08/30 05:57:04 - mmengine - INFO - Epoch(train) [252][15/63] lr: 5.6662e-03 eta: 1 day, 0:25:50 time: 1.4215 data_time: 0.0330 memory: 16201 loss_prob: 0.7852 loss_thr: 0.4730 loss_db: 0.1357 loss: 1.3938 2022/08/30 05:57:11 - mmengine - INFO - Epoch(train) [252][20/63] lr: 5.6662e-03 eta: 1 day, 0:25:32 time: 1.3798 data_time: 0.0264 memory: 16201 loss_prob: 0.7396 loss_thr: 0.4560 loss_db: 0.1237 loss: 1.3193 2022/08/30 05:57:17 - mmengine - INFO - Epoch(train) [252][25/63] lr: 5.6662e-03 eta: 1 day, 0:25:32 time: 1.3184 data_time: 0.0323 memory: 16201 loss_prob: 0.7218 loss_thr: 0.4555 loss_db: 0.1220 loss: 1.2992 2022/08/30 05:57:25 - mmengine - INFO - Epoch(train) [252][30/63] lr: 5.6662e-03 eta: 1 day, 0:25:15 time: 1.4128 data_time: 0.0277 memory: 16201 loss_prob: 0.8101 loss_thr: 0.5021 loss_db: 0.1340 loss: 1.4461 2022/08/30 05:57:32 - mmengine - INFO - Epoch(train) [252][35/63] lr: 5.6662e-03 eta: 1 day, 0:25:15 time: 1.5126 data_time: 0.0353 memory: 16201 loss_prob: 0.9277 loss_thr: 0.5297 loss_db: 0.1503 loss: 1.6077 2022/08/30 05:57:39 - mmengine - INFO - Epoch(train) [252][40/63] lr: 5.6662e-03 eta: 1 day, 0:25:00 time: 1.4541 data_time: 0.0281 memory: 16201 loss_prob: 0.8494 loss_thr: 0.4971 loss_db: 0.1408 loss: 1.4873 2022/08/30 05:57:46 - mmengine - INFO - Epoch(train) [252][45/63] lr: 5.6662e-03 eta: 1 day, 0:25:00 time: 1.3760 data_time: 0.0278 memory: 16201 loss_prob: 0.7994 loss_thr: 0.4825 loss_db: 0.1348 loss: 1.4167 2022/08/30 05:57:53 - mmengine - INFO - Epoch(train) [252][50/63] lr: 5.6662e-03 eta: 1 day, 0:24:40 time: 1.3417 data_time: 0.0435 memory: 16201 loss_prob: 0.8187 loss_thr: 0.4889 loss_db: 0.1377 loss: 1.4453 2022/08/30 05:57:59 - mmengine - INFO - Epoch(train) [252][55/63] lr: 5.6662e-03 eta: 1 day, 0:24:40 time: 1.2604 data_time: 0.0313 memory: 16201 loss_prob: 0.8941 loss_thr: 0.5082 loss_db: 0.1465 loss: 1.5488 2022/08/30 05:58:05 - mmengine - INFO - Epoch(train) [252][60/63] lr: 5.6662e-03 eta: 1 day, 0:24:18 time: 1.2697 data_time: 0.0274 memory: 16201 loss_prob: 0.9066 loss_thr: 0.5153 loss_db: 0.1497 loss: 1.5715 2022/08/30 05:58:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:58:17 - mmengine - INFO - Epoch(train) [253][5/63] lr: 5.6608e-03 eta: 1 day, 0:24:18 time: 1.4453 data_time: 0.2203 memory: 16201 loss_prob: 0.8188 loss_thr: 0.4778 loss_db: 0.1393 loss: 1.4359 2022/08/30 05:58:25 - mmengine - INFO - Epoch(train) [253][10/63] lr: 5.6608e-03 eta: 1 day, 0:23:49 time: 1.6529 data_time: 0.2287 memory: 16201 loss_prob: 0.7603 loss_thr: 0.4673 loss_db: 0.1306 loss: 1.3582 2022/08/30 05:58:32 - mmengine - INFO - Epoch(train) [253][15/63] lr: 5.6608e-03 eta: 1 day, 0:23:49 time: 1.4262 data_time: 0.0331 memory: 16201 loss_prob: 0.8119 loss_thr: 0.4832 loss_db: 0.1397 loss: 1.4348 2022/08/30 05:58:38 - mmengine - INFO - Epoch(train) [253][20/63] lr: 5.6608e-03 eta: 1 day, 0:23:27 time: 1.2866 data_time: 0.0361 memory: 16201 loss_prob: 0.7762 loss_thr: 0.4686 loss_db: 0.1306 loss: 1.3753 2022/08/30 05:58:45 - mmengine - INFO - Epoch(train) [253][25/63] lr: 5.6608e-03 eta: 1 day, 0:23:27 time: 1.3313 data_time: 0.0367 memory: 16201 loss_prob: 0.6691 loss_thr: 0.4303 loss_db: 0.1120 loss: 1.2115 2022/08/30 05:58:51 - mmengine - INFO - Epoch(train) [253][30/63] lr: 5.6608e-03 eta: 1 day, 0:23:07 time: 1.3312 data_time: 0.0315 memory: 16201 loss_prob: 0.6921 loss_thr: 0.4403 loss_db: 0.1187 loss: 1.2511 2022/08/30 05:58:58 - mmengine - INFO - Epoch(train) [253][35/63] lr: 5.6608e-03 eta: 1 day, 0:23:07 time: 1.2885 data_time: 0.0296 memory: 16201 loss_prob: 0.8330 loss_thr: 0.4814 loss_db: 0.1427 loss: 1.4571 2022/08/30 05:59:04 - mmengine - INFO - Epoch(train) [253][40/63] lr: 5.6608e-03 eta: 1 day, 0:22:47 time: 1.3173 data_time: 0.0286 memory: 16201 loss_prob: 0.9118 loss_thr: 0.5129 loss_db: 0.1540 loss: 1.5787 2022/08/30 05:59:12 - mmengine - INFO - Epoch(train) [253][45/63] lr: 5.6608e-03 eta: 1 day, 0:22:47 time: 1.4107 data_time: 0.0366 memory: 16201 loss_prob: 0.7988 loss_thr: 0.5008 loss_db: 0.1382 loss: 1.4378 2022/08/30 05:59:19 - mmengine - INFO - Epoch(train) [253][50/63] lr: 5.6608e-03 eta: 1 day, 0:22:32 time: 1.4619 data_time: 0.0434 memory: 16201 loss_prob: 0.8251 loss_thr: 0.5120 loss_db: 0.1419 loss: 1.4791 2022/08/30 05:59:26 - mmengine - INFO - Epoch(train) [253][55/63] lr: 5.6608e-03 eta: 1 day, 0:22:32 time: 1.4331 data_time: 0.0333 memory: 16201 loss_prob: 0.9538 loss_thr: 0.5304 loss_db: 0.1556 loss: 1.6398 2022/08/30 05:59:33 - mmengine - INFO - Epoch(train) [253][60/63] lr: 5.6608e-03 eta: 1 day, 0:22:15 time: 1.4049 data_time: 0.0300 memory: 16201 loss_prob: 0.9318 loss_thr: 0.5140 loss_db: 0.1513 loss: 1.5971 2022/08/30 05:59:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 05:59:46 - mmengine - INFO - Epoch(train) [254][5/63] lr: 5.6554e-03 eta: 1 day, 0:22:15 time: 1.5597 data_time: 0.2387 memory: 16201 loss_prob: 0.8608 loss_thr: 0.4778 loss_db: 0.1455 loss: 1.4841 2022/08/30 05:59:53 - mmengine - INFO - Epoch(train) [254][10/63] lr: 5.6554e-03 eta: 1 day, 0:21:45 time: 1.6403 data_time: 0.2487 memory: 16201 loss_prob: 0.8207 loss_thr: 0.4738 loss_db: 0.1334 loss: 1.4279 2022/08/30 06:00:00 - mmengine - INFO - Epoch(train) [254][15/63] lr: 5.6554e-03 eta: 1 day, 0:21:45 time: 1.3403 data_time: 0.0351 memory: 16201 loss_prob: 0.7988 loss_thr: 0.4707 loss_db: 0.1313 loss: 1.4008 2022/08/30 06:00:11 - mmengine - INFO - Epoch(train) [254][20/63] lr: 5.6554e-03 eta: 1 day, 0:21:42 time: 1.7797 data_time: 0.0393 memory: 16201 loss_prob: 0.7749 loss_thr: 0.4669 loss_db: 0.1306 loss: 1.3723 2022/08/30 06:00:17 - mmengine - INFO - Epoch(train) [254][25/63] lr: 5.6554e-03 eta: 1 day, 0:21:42 time: 1.7620 data_time: 0.0512 memory: 16201 loss_prob: 0.8434 loss_thr: 0.4707 loss_db: 0.1453 loss: 1.4594 2022/08/30 06:00:24 - mmengine - INFO - Epoch(train) [254][30/63] lr: 5.6554e-03 eta: 1 day, 0:21:23 time: 1.3579 data_time: 0.0374 memory: 16201 loss_prob: 0.8989 loss_thr: 0.4881 loss_db: 0.1553 loss: 1.5424 2022/08/30 06:00:31 - mmengine - INFO - Epoch(train) [254][35/63] lr: 5.6554e-03 eta: 1 day, 0:21:23 time: 1.3960 data_time: 0.0290 memory: 16201 loss_prob: 0.8506 loss_thr: 0.4936 loss_db: 0.1437 loss: 1.4879 2022/08/30 06:00:38 - mmengine - INFO - Epoch(train) [254][40/63] lr: 5.6554e-03 eta: 1 day, 0:21:04 time: 1.3571 data_time: 0.0311 memory: 16201 loss_prob: 0.8002 loss_thr: 0.4932 loss_db: 0.1338 loss: 1.4272 2022/08/30 06:00:45 - mmengine - INFO - Epoch(train) [254][45/63] lr: 5.6554e-03 eta: 1 day, 0:21:04 time: 1.3317 data_time: 0.0350 memory: 16201 loss_prob: 0.8315 loss_thr: 0.4949 loss_db: 0.1467 loss: 1.4731 2022/08/30 06:00:52 - mmengine - INFO - Epoch(train) [254][50/63] lr: 5.6554e-03 eta: 1 day, 0:20:48 time: 1.4239 data_time: 0.0453 memory: 16201 loss_prob: 0.8208 loss_thr: 0.4825 loss_db: 0.1426 loss: 1.4459 2022/08/30 06:00:58 - mmengine - INFO - Epoch(train) [254][55/63] lr: 5.6554e-03 eta: 1 day, 0:20:48 time: 1.3785 data_time: 0.0402 memory: 16201 loss_prob: 0.8829 loss_thr: 0.4963 loss_db: 0.1481 loss: 1.5273 2022/08/30 06:01:04 - mmengine - INFO - Epoch(train) [254][60/63] lr: 5.6554e-03 eta: 1 day, 0:20:24 time: 1.2274 data_time: 0.0270 memory: 16201 loss_prob: 0.9646 loss_thr: 0.5097 loss_db: 0.1630 loss: 1.6373 2022/08/30 06:01:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:01:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:01:16 - mmengine - INFO - Epoch(train) [255][5/63] lr: 5.6500e-03 eta: 1 day, 0:20:24 time: 1.4305 data_time: 0.2265 memory: 16201 loss_prob: 0.8603 loss_thr: 0.5013 loss_db: 0.1420 loss: 1.5036 2022/08/30 06:01:24 - mmengine - INFO - Epoch(train) [255][10/63] lr: 5.6500e-03 eta: 1 day, 0:19:53 time: 1.5968 data_time: 0.2278 memory: 16201 loss_prob: 0.8053 loss_thr: 0.4710 loss_db: 0.1401 loss: 1.4165 2022/08/30 06:01:31 - mmengine - INFO - Epoch(train) [255][15/63] lr: 5.6500e-03 eta: 1 day, 0:19:53 time: 1.4626 data_time: 0.0374 memory: 16201 loss_prob: 0.8131 loss_thr: 0.4832 loss_db: 0.1388 loss: 1.4350 2022/08/30 06:01:38 - mmengine - INFO - Epoch(train) [255][20/63] lr: 5.6500e-03 eta: 1 day, 0:19:36 time: 1.4027 data_time: 0.0454 memory: 16201 loss_prob: 0.8669 loss_thr: 0.5029 loss_db: 0.1399 loss: 1.5098 2022/08/30 06:01:44 - mmengine - INFO - Epoch(train) [255][25/63] lr: 5.6500e-03 eta: 1 day, 0:19:36 time: 1.3207 data_time: 0.0363 memory: 16201 loss_prob: 0.9050 loss_thr: 0.5110 loss_db: 0.1553 loss: 1.5713 2022/08/30 06:01:51 - mmengine - INFO - Epoch(train) [255][30/63] lr: 5.6500e-03 eta: 1 day, 0:19:17 time: 1.3550 data_time: 0.0325 memory: 16201 loss_prob: 0.9259 loss_thr: 0.5158 loss_db: 0.1614 loss: 1.6031 2022/08/30 06:01:58 - mmengine - INFO - Epoch(train) [255][35/63] lr: 5.6500e-03 eta: 1 day, 0:19:17 time: 1.3641 data_time: 0.0413 memory: 16201 loss_prob: 0.8356 loss_thr: 0.4870 loss_db: 0.1385 loss: 1.4611 2022/08/30 06:02:05 - mmengine - INFO - Epoch(train) [255][40/63] lr: 5.6500e-03 eta: 1 day, 0:18:58 time: 1.3541 data_time: 0.0340 memory: 16201 loss_prob: 0.7840 loss_thr: 0.4689 loss_db: 0.1326 loss: 1.3856 2022/08/30 06:02:12 - mmengine - INFO - Epoch(train) [255][45/63] lr: 5.6500e-03 eta: 1 day, 0:18:58 time: 1.3715 data_time: 0.0404 memory: 16201 loss_prob: 0.8826 loss_thr: 0.4866 loss_db: 0.1462 loss: 1.5154 2022/08/30 06:02:18 - mmengine - INFO - Epoch(train) [255][50/63] lr: 5.6500e-03 eta: 1 day, 0:18:38 time: 1.3263 data_time: 0.0424 memory: 16201 loss_prob: 1.0503 loss_thr: 0.5275 loss_db: 0.1782 loss: 1.7560 2022/08/30 06:02:24 - mmengine - INFO - Epoch(train) [255][55/63] lr: 5.6500e-03 eta: 1 day, 0:18:38 time: 1.2324 data_time: 0.0299 memory: 16201 loss_prob: 1.0758 loss_thr: 0.5461 loss_db: 0.1844 loss: 1.8063 2022/08/30 06:02:31 - mmengine - INFO - Epoch(train) [255][60/63] lr: 5.6500e-03 eta: 1 day, 0:18:18 time: 1.3118 data_time: 0.0411 memory: 16201 loss_prob: 1.0404 loss_thr: 0.5427 loss_db: 0.1684 loss: 1.7515 2022/08/30 06:02:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:02:43 - mmengine - INFO - Epoch(train) [256][5/63] lr: 5.6447e-03 eta: 1 day, 0:18:18 time: 1.4972 data_time: 0.2289 memory: 16201 loss_prob: 0.9001 loss_thr: 0.4968 loss_db: 0.1494 loss: 1.5463 2022/08/30 06:02:49 - mmengine - INFO - Epoch(train) [256][10/63] lr: 5.6447e-03 eta: 1 day, 0:17:44 time: 1.5305 data_time: 0.2428 memory: 16201 loss_prob: 0.9561 loss_thr: 0.4967 loss_db: 0.1560 loss: 1.6089 2022/08/30 06:02:57 - mmengine - INFO - Epoch(train) [256][15/63] lr: 5.6447e-03 eta: 1 day, 0:17:44 time: 1.3414 data_time: 0.0398 memory: 16201 loss_prob: 0.9535 loss_thr: 0.5068 loss_db: 0.1564 loss: 1.6167 2022/08/30 06:03:03 - mmengine - INFO - Epoch(train) [256][20/63] lr: 5.6447e-03 eta: 1 day, 0:17:27 time: 1.3846 data_time: 0.0311 memory: 16201 loss_prob: 0.8754 loss_thr: 0.5050 loss_db: 0.1454 loss: 1.5258 2022/08/30 06:03:10 - mmengine - INFO - Epoch(train) [256][25/63] lr: 5.6447e-03 eta: 1 day, 0:17:27 time: 1.3792 data_time: 0.0389 memory: 16201 loss_prob: 0.8265 loss_thr: 0.4803 loss_db: 0.1364 loss: 1.4432 2022/08/30 06:03:17 - mmengine - INFO - Epoch(train) [256][30/63] lr: 5.6447e-03 eta: 1 day, 0:17:08 time: 1.3627 data_time: 0.0390 memory: 16201 loss_prob: 0.7739 loss_thr: 0.4654 loss_db: 0.1311 loss: 1.3705 2022/08/30 06:03:24 - mmengine - INFO - Epoch(train) [256][35/63] lr: 5.6447e-03 eta: 1 day, 0:17:08 time: 1.3622 data_time: 0.0338 memory: 16201 loss_prob: 0.9691 loss_thr: 0.4863 loss_db: 0.1476 loss: 1.6030 2022/08/30 06:03:31 - mmengine - INFO - Epoch(train) [256][40/63] lr: 5.6447e-03 eta: 1 day, 0:16:51 time: 1.4133 data_time: 0.0349 memory: 16201 loss_prob: 1.0011 loss_thr: 0.5058 loss_db: 0.1493 loss: 1.6562 2022/08/30 06:03:38 - mmengine - INFO - Epoch(train) [256][45/63] lr: 5.6447e-03 eta: 1 day, 0:16:51 time: 1.3854 data_time: 0.0428 memory: 16201 loss_prob: 0.8046 loss_thr: 0.4729 loss_db: 0.1324 loss: 1.4100 2022/08/30 06:03:44 - mmengine - INFO - Epoch(train) [256][50/63] lr: 5.6447e-03 eta: 1 day, 0:16:30 time: 1.3031 data_time: 0.0376 memory: 16201 loss_prob: 0.8196 loss_thr: 0.4695 loss_db: 0.1396 loss: 1.4288 2022/08/30 06:03:51 - mmengine - INFO - Epoch(train) [256][55/63] lr: 5.6447e-03 eta: 1 day, 0:16:30 time: 1.3257 data_time: 0.0280 memory: 16201 loss_prob: 0.8206 loss_thr: 0.4771 loss_db: 0.1386 loss: 1.4362 2022/08/30 06:03:58 - mmengine - INFO - Epoch(train) [256][60/63] lr: 5.6447e-03 eta: 1 day, 0:16:11 time: 1.3479 data_time: 0.0310 memory: 16201 loss_prob: 0.7921 loss_thr: 0.4672 loss_db: 0.1312 loss: 1.3905 2022/08/30 06:04:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:04:10 - mmengine - INFO - Epoch(train) [257][5/63] lr: 5.6393e-03 eta: 1 day, 0:16:11 time: 1.4881 data_time: 0.2321 memory: 16201 loss_prob: 0.8301 loss_thr: 0.4974 loss_db: 0.1387 loss: 1.4662 2022/08/30 06:04:17 - mmengine - INFO - Epoch(train) [257][10/63] lr: 5.6393e-03 eta: 1 day, 0:15:41 time: 1.6104 data_time: 0.2468 memory: 16201 loss_prob: 0.8039 loss_thr: 0.4873 loss_db: 0.1373 loss: 1.4285 2022/08/30 06:04:23 - mmengine - INFO - Epoch(train) [257][15/63] lr: 5.6393e-03 eta: 1 day, 0:15:41 time: 1.2921 data_time: 0.0340 memory: 16201 loss_prob: 0.8149 loss_thr: 0.4978 loss_db: 0.1393 loss: 1.4521 2022/08/30 06:04:30 - mmengine - INFO - Epoch(train) [257][20/63] lr: 5.6393e-03 eta: 1 day, 0:15:17 time: 1.2237 data_time: 0.0317 memory: 16201 loss_prob: 0.9039 loss_thr: 0.5212 loss_db: 0.1519 loss: 1.5770 2022/08/30 06:04:37 - mmengine - INFO - Epoch(train) [257][25/63] lr: 5.6393e-03 eta: 1 day, 0:15:17 time: 1.3859 data_time: 0.0419 memory: 16201 loss_prob: 0.8979 loss_thr: 0.5069 loss_db: 0.1523 loss: 1.5572 2022/08/30 06:04:44 - mmengine - INFO - Epoch(train) [257][30/63] lr: 5.6393e-03 eta: 1 day, 0:15:01 time: 1.4152 data_time: 0.0372 memory: 16201 loss_prob: 0.8463 loss_thr: 0.4890 loss_db: 0.1440 loss: 1.4793 2022/08/30 06:04:50 - mmengine - INFO - Epoch(train) [257][35/63] lr: 5.6393e-03 eta: 1 day, 0:15:01 time: 1.3213 data_time: 0.0392 memory: 16201 loss_prob: 0.8769 loss_thr: 0.4935 loss_db: 0.1450 loss: 1.5154 2022/08/30 06:04:58 - mmengine - INFO - Epoch(train) [257][40/63] lr: 5.6393e-03 eta: 1 day, 0:14:44 time: 1.4221 data_time: 0.0367 memory: 16201 loss_prob: 0.9002 loss_thr: 0.5000 loss_db: 0.1478 loss: 1.5480 2022/08/30 06:05:05 - mmengine - INFO - Epoch(train) [257][45/63] lr: 5.6393e-03 eta: 1 day, 0:14:44 time: 1.5147 data_time: 0.0319 memory: 16201 loss_prob: 0.8550 loss_thr: 0.4923 loss_db: 0.1430 loss: 1.4904 2022/08/30 06:05:12 - mmengine - INFO - Epoch(train) [257][50/63] lr: 5.6393e-03 eta: 1 day, 0:14:27 time: 1.4041 data_time: 0.0347 memory: 16201 loss_prob: 0.7412 loss_thr: 0.4511 loss_db: 0.1247 loss: 1.3170 2022/08/30 06:05:19 - mmengine - INFO - Epoch(train) [257][55/63] lr: 5.6393e-03 eta: 1 day, 0:14:27 time: 1.3414 data_time: 0.0270 memory: 16201 loss_prob: 0.7491 loss_thr: 0.4594 loss_db: 0.1262 loss: 1.3347 2022/08/30 06:05:25 - mmengine - INFO - Epoch(train) [257][60/63] lr: 5.6393e-03 eta: 1 day, 0:14:06 time: 1.2940 data_time: 0.0336 memory: 16201 loss_prob: 0.7859 loss_thr: 0.4720 loss_db: 0.1306 loss: 1.3884 2022/08/30 06:05:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:05:37 - mmengine - INFO - Epoch(train) [258][5/63] lr: 5.6339e-03 eta: 1 day, 0:14:06 time: 1.4574 data_time: 0.2182 memory: 16201 loss_prob: 0.7642 loss_thr: 0.4491 loss_db: 0.1287 loss: 1.3420 2022/08/30 06:05:44 - mmengine - INFO - Epoch(train) [258][10/63] lr: 5.6339e-03 eta: 1 day, 0:13:35 time: 1.5885 data_time: 0.2321 memory: 16201 loss_prob: 0.7226 loss_thr: 0.4397 loss_db: 0.1204 loss: 1.2827 2022/08/30 06:05:52 - mmengine - INFO - Epoch(train) [258][15/63] lr: 5.6339e-03 eta: 1 day, 0:13:35 time: 1.5118 data_time: 0.0293 memory: 16201 loss_prob: 0.7394 loss_thr: 0.4647 loss_db: 0.1246 loss: 1.3287 2022/08/30 06:05:59 - mmengine - INFO - Epoch(train) [258][20/63] lr: 5.6339e-03 eta: 1 day, 0:13:23 time: 1.5382 data_time: 0.0312 memory: 16201 loss_prob: 0.7963 loss_thr: 0.4823 loss_db: 0.1363 loss: 1.4149 2022/08/30 06:06:07 - mmengine - INFO - Epoch(train) [258][25/63] lr: 5.6339e-03 eta: 1 day, 0:13:23 time: 1.4388 data_time: 0.0415 memory: 16201 loss_prob: 0.7842 loss_thr: 0.4522 loss_db: 0.1354 loss: 1.3718 2022/08/30 06:06:13 - mmengine - INFO - Epoch(train) [258][30/63] lr: 5.6339e-03 eta: 1 day, 0:13:06 time: 1.4005 data_time: 0.0300 memory: 16201 loss_prob: 0.7954 loss_thr: 0.4534 loss_db: 0.1332 loss: 1.3820 2022/08/30 06:06:21 - mmengine - INFO - Epoch(train) [258][35/63] lr: 5.6339e-03 eta: 1 day, 0:13:06 time: 1.4069 data_time: 0.0362 memory: 16201 loss_prob: 0.8039 loss_thr: 0.4746 loss_db: 0.1307 loss: 1.4092 2022/08/30 06:06:27 - mmengine - INFO - Epoch(train) [258][40/63] lr: 5.6339e-03 eta: 1 day, 0:12:47 time: 1.3625 data_time: 0.0383 memory: 16201 loss_prob: 0.8859 loss_thr: 0.5093 loss_db: 0.1426 loss: 1.5377 2022/08/30 06:06:33 - mmengine - INFO - Epoch(train) [258][45/63] lr: 5.6339e-03 eta: 1 day, 0:12:47 time: 1.2677 data_time: 0.0316 memory: 16201 loss_prob: 0.8275 loss_thr: 0.4941 loss_db: 0.1357 loss: 1.4574 2022/08/30 06:06:41 - mmengine - INFO - Epoch(train) [258][50/63] lr: 5.6339e-03 eta: 1 day, 0:12:29 time: 1.3663 data_time: 0.0398 memory: 16201 loss_prob: 0.7148 loss_thr: 0.4594 loss_db: 0.1198 loss: 1.2940 2022/08/30 06:06:48 - mmengine - INFO - Epoch(train) [258][55/63] lr: 5.6339e-03 eta: 1 day, 0:12:29 time: 1.4123 data_time: 0.0330 memory: 16201 loss_prob: 0.7135 loss_thr: 0.4502 loss_db: 0.1203 loss: 1.2840 2022/08/30 06:06:55 - mmengine - INFO - Epoch(train) [258][60/63] lr: 5.6339e-03 eta: 1 day, 0:12:12 time: 1.4005 data_time: 0.0345 memory: 16201 loss_prob: 0.7189 loss_thr: 0.4495 loss_db: 0.1212 loss: 1.2896 2022/08/30 06:06:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:07:07 - mmengine - INFO - Epoch(train) [259][5/63] lr: 5.6285e-03 eta: 1 day, 0:12:12 time: 1.5625 data_time: 0.2243 memory: 16201 loss_prob: 0.7939 loss_thr: 0.5025 loss_db: 0.1331 loss: 1.4295 2022/08/30 06:07:14 - mmengine - INFO - Epoch(train) [259][10/63] lr: 5.6285e-03 eta: 1 day, 0:11:38 time: 1.5085 data_time: 0.2419 memory: 16201 loss_prob: 0.7945 loss_thr: 0.5161 loss_db: 0.1331 loss: 1.4436 2022/08/30 06:07:21 - mmengine - INFO - Epoch(train) [259][15/63] lr: 5.6285e-03 eta: 1 day, 0:11:38 time: 1.3512 data_time: 0.0359 memory: 16201 loss_prob: 0.7064 loss_thr: 0.4636 loss_db: 0.1168 loss: 1.2868 2022/08/30 06:07:27 - mmengine - INFO - Epoch(train) [259][20/63] lr: 5.6285e-03 eta: 1 day, 0:11:20 time: 1.3842 data_time: 0.0334 memory: 16201 loss_prob: 0.6874 loss_thr: 0.4541 loss_db: 0.1151 loss: 1.2566 2022/08/30 06:07:35 - mmengine - INFO - Epoch(train) [259][25/63] lr: 5.6285e-03 eta: 1 day, 0:11:20 time: 1.4230 data_time: 0.0327 memory: 16201 loss_prob: 0.7475 loss_thr: 0.4804 loss_db: 0.1273 loss: 1.3552 2022/08/30 06:07:42 - mmengine - INFO - Epoch(train) [259][30/63] lr: 5.6285e-03 eta: 1 day, 0:11:04 time: 1.4205 data_time: 0.0284 memory: 16201 loss_prob: 0.6955 loss_thr: 0.4650 loss_db: 0.1183 loss: 1.2788 2022/08/30 06:07:48 - mmengine - INFO - Epoch(train) [259][35/63] lr: 5.6285e-03 eta: 1 day, 0:11:04 time: 1.3353 data_time: 0.0347 memory: 16201 loss_prob: 0.7170 loss_thr: 0.4558 loss_db: 0.1189 loss: 1.2917 2022/08/30 06:07:55 - mmengine - INFO - Epoch(train) [259][40/63] lr: 5.6285e-03 eta: 1 day, 0:10:45 time: 1.3601 data_time: 0.0293 memory: 16201 loss_prob: 0.7970 loss_thr: 0.4711 loss_db: 0.1322 loss: 1.4003 2022/08/30 06:08:02 - mmengine - INFO - Epoch(train) [259][45/63] lr: 5.6285e-03 eta: 1 day, 0:10:45 time: 1.3994 data_time: 0.0309 memory: 16201 loss_prob: 0.7250 loss_thr: 0.4601 loss_db: 0.1223 loss: 1.3074 2022/08/30 06:08:09 - mmengine - INFO - Epoch(train) [259][50/63] lr: 5.6285e-03 eta: 1 day, 0:10:28 time: 1.3890 data_time: 0.0440 memory: 16201 loss_prob: 0.7439 loss_thr: 0.4704 loss_db: 0.1255 loss: 1.3398 2022/08/30 06:08:16 - mmengine - INFO - Epoch(train) [259][55/63] lr: 5.6285e-03 eta: 1 day, 0:10:28 time: 1.4233 data_time: 0.0338 memory: 16201 loss_prob: 0.8252 loss_thr: 0.4813 loss_db: 0.1386 loss: 1.4452 2022/08/30 06:08:23 - mmengine - INFO - Epoch(train) [259][60/63] lr: 5.6285e-03 eta: 1 day, 0:10:09 time: 1.3618 data_time: 0.0319 memory: 16201 loss_prob: 0.7988 loss_thr: 0.4808 loss_db: 0.1351 loss: 1.4148 2022/08/30 06:08:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:08:35 - mmengine - INFO - Epoch(train) [260][5/63] lr: 5.6231e-03 eta: 1 day, 0:10:09 time: 1.5049 data_time: 0.2348 memory: 16201 loss_prob: 0.7433 loss_thr: 0.4682 loss_db: 0.1243 loss: 1.3358 2022/08/30 06:08:43 - mmengine - INFO - Epoch(train) [260][10/63] lr: 5.6231e-03 eta: 1 day, 0:09:43 time: 1.6926 data_time: 0.2580 memory: 16201 loss_prob: 0.7062 loss_thr: 0.4383 loss_db: 0.1220 loss: 1.2665 2022/08/30 06:08:50 - mmengine - INFO - Epoch(train) [260][15/63] lr: 5.6231e-03 eta: 1 day, 0:09:43 time: 1.5098 data_time: 0.0400 memory: 16201 loss_prob: 0.7680 loss_thr: 0.4757 loss_db: 0.1299 loss: 1.3736 2022/08/30 06:08:57 - mmengine - INFO - Epoch(train) [260][20/63] lr: 5.6231e-03 eta: 1 day, 0:09:28 time: 1.4653 data_time: 0.0313 memory: 16201 loss_prob: 0.7686 loss_thr: 0.4808 loss_db: 0.1289 loss: 1.3783 2022/08/30 06:09:04 - mmengine - INFO - Epoch(train) [260][25/63] lr: 5.6231e-03 eta: 1 day, 0:09:28 time: 1.3963 data_time: 0.0393 memory: 16201 loss_prob: 0.7924 loss_thr: 0.4917 loss_db: 0.1358 loss: 1.4199 2022/08/30 06:09:11 - mmengine - INFO - Epoch(train) [260][30/63] lr: 5.6231e-03 eta: 1 day, 0:09:08 time: 1.3353 data_time: 0.0271 memory: 16201 loss_prob: 0.7611 loss_thr: 0.4655 loss_db: 0.1313 loss: 1.3579 2022/08/30 06:09:18 - mmengine - INFO - Epoch(train) [260][35/63] lr: 5.6231e-03 eta: 1 day, 0:09:08 time: 1.3899 data_time: 0.0313 memory: 16201 loss_prob: 0.6789 loss_thr: 0.4385 loss_db: 0.1149 loss: 1.2322 2022/08/30 06:09:25 - mmengine - INFO - Epoch(train) [260][40/63] lr: 5.6231e-03 eta: 1 day, 0:08:53 time: 1.4460 data_time: 0.0341 memory: 16201 loss_prob: 0.7487 loss_thr: 0.4751 loss_db: 0.1245 loss: 1.3483 2022/08/30 06:09:32 - mmengine - INFO - Epoch(train) [260][45/63] lr: 5.6231e-03 eta: 1 day, 0:08:53 time: 1.3690 data_time: 0.0297 memory: 16201 loss_prob: 0.7931 loss_thr: 0.4781 loss_db: 0.1318 loss: 1.4030 2022/08/30 06:09:39 - mmengine - INFO - Epoch(train) [260][50/63] lr: 5.6231e-03 eta: 1 day, 0:08:36 time: 1.3959 data_time: 0.0397 memory: 16201 loss_prob: 0.7361 loss_thr: 0.4592 loss_db: 0.1243 loss: 1.3197 2022/08/30 06:09:47 - mmengine - INFO - Epoch(train) [260][55/63] lr: 5.6231e-03 eta: 1 day, 0:08:36 time: 1.5172 data_time: 0.0334 memory: 16201 loss_prob: 0.7511 loss_thr: 0.4704 loss_db: 0.1264 loss: 1.3478 2022/08/30 06:09:54 - mmengine - INFO - Epoch(train) [260][60/63] lr: 5.6231e-03 eta: 1 day, 0:08:22 time: 1.4837 data_time: 0.0309 memory: 16201 loss_prob: 0.7776 loss_thr: 0.4574 loss_db: 0.1290 loss: 1.3640 2022/08/30 06:09:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:09:57 - mmengine - INFO - Saving checkpoint at 260 epochs 2022/08/30 06:10:07 - mmengine - INFO - Epoch(val) [260][5/32] eta: 1 day, 0:08:22 time: 0.6967 data_time: 0.1300 memory: 16201 2022/08/30 06:10:11 - mmengine - INFO - Epoch(val) [260][10/32] eta: 0:00:17 time: 0.7894 data_time: 0.1792 memory: 15734 2022/08/30 06:10:14 - mmengine - INFO - Epoch(val) [260][15/32] eta: 0:00:17 time: 0.6411 data_time: 0.0653 memory: 15734 2022/08/30 06:10:17 - mmengine - INFO - Epoch(val) [260][20/32] eta: 0:00:08 time: 0.6720 data_time: 0.0606 memory: 15734 2022/08/30 06:10:21 - mmengine - INFO - Epoch(val) [260][25/32] eta: 0:00:08 time: 0.7067 data_time: 0.0682 memory: 15734 2022/08/30 06:10:24 - mmengine - INFO - Epoch(val) [260][30/32] eta: 0:00:01 time: 0.6229 data_time: 0.0264 memory: 15734 2022/08/30 06:10:24 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 06:10:24 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8618, precision: 0.7521, hmean: 0.8032 2022/08/30 06:10:24 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8618, precision: 0.8067, hmean: 0.8333 2022/08/30 06:10:24 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8584, precision: 0.8395, hmean: 0.8488 2022/08/30 06:10:24 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8483, precision: 0.8766, hmean: 0.8622 2022/08/30 06:10:24 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8146, precision: 0.9043, hmean: 0.8571 2022/08/30 06:10:24 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6009, precision: 0.9600, hmean: 0.7391 2022/08/30 06:10:24 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0188, precision: 1.0000, hmean: 0.0369 2022/08/30 06:10:24 - mmengine - INFO - Epoch(val) [260][32/32] icdar/precision: 0.8766 icdar/recall: 0.8483 icdar/hmean: 0.8622 2022/08/30 06:10:34 - mmengine - INFO - Epoch(train) [261][5/63] lr: 5.6177e-03 eta: 0:00:01 time: 1.5594 data_time: 0.2327 memory: 16201 loss_prob: 0.7373 loss_thr: 0.4376 loss_db: 0.1227 loss: 1.2977 2022/08/30 06:10:41 - mmengine - INFO - Epoch(train) [261][10/63] lr: 5.6177e-03 eta: 1 day, 0:07:52 time: 1.6263 data_time: 0.2442 memory: 16201 loss_prob: 0.7014 loss_thr: 0.4322 loss_db: 0.1156 loss: 1.2492 2022/08/30 06:10:49 - mmengine - INFO - Epoch(train) [261][15/63] lr: 5.6177e-03 eta: 1 day, 0:07:52 time: 1.4585 data_time: 0.0298 memory: 16201 loss_prob: 0.7365 loss_thr: 0.4528 loss_db: 0.1218 loss: 1.3111 2022/08/30 06:10:56 - mmengine - INFO - Epoch(train) [261][20/63] lr: 5.6177e-03 eta: 1 day, 0:07:41 time: 1.5646 data_time: 0.0330 memory: 16201 loss_prob: 0.7031 loss_thr: 0.4584 loss_db: 0.1213 loss: 1.2828 2022/08/30 06:11:04 - mmengine - INFO - Epoch(train) [261][25/63] lr: 5.6177e-03 eta: 1 day, 0:07:41 time: 1.5784 data_time: 0.0454 memory: 16201 loss_prob: 0.7142 loss_thr: 0.4487 loss_db: 0.1234 loss: 1.2863 2022/08/30 06:11:12 - mmengine - INFO - Epoch(train) [261][30/63] lr: 5.6177e-03 eta: 1 day, 0:07:28 time: 1.5184 data_time: 0.0319 memory: 16201 loss_prob: 0.6860 loss_thr: 0.4257 loss_db: 0.1161 loss: 1.2278 2022/08/30 06:11:19 - mmengine - INFO - Epoch(train) [261][35/63] lr: 5.6177e-03 eta: 1 day, 0:07:28 time: 1.4817 data_time: 0.0361 memory: 16201 loss_prob: 0.7080 loss_thr: 0.4453 loss_db: 0.1179 loss: 1.2713 2022/08/30 06:11:26 - mmengine - INFO - Epoch(train) [261][40/63] lr: 5.6177e-03 eta: 1 day, 0:07:11 time: 1.3969 data_time: 0.0337 memory: 16201 loss_prob: 0.7338 loss_thr: 0.4655 loss_db: 0.1238 loss: 1.3232 2022/08/30 06:11:32 - mmengine - INFO - Epoch(train) [261][45/63] lr: 5.6177e-03 eta: 1 day, 0:07:11 time: 1.3140 data_time: 0.0309 memory: 16201 loss_prob: 0.8419 loss_thr: 0.4669 loss_db: 0.1417 loss: 1.4505 2022/08/30 06:11:39 - mmengine - INFO - Epoch(train) [261][50/63] lr: 5.6177e-03 eta: 1 day, 0:06:52 time: 1.3383 data_time: 0.0405 memory: 16201 loss_prob: 0.8485 loss_thr: 0.4589 loss_db: 0.1388 loss: 1.4462 2022/08/30 06:11:46 - mmengine - INFO - Epoch(train) [261][55/63] lr: 5.6177e-03 eta: 1 day, 0:06:52 time: 1.3436 data_time: 0.0240 memory: 16201 loss_prob: 0.9000 loss_thr: 0.4843 loss_db: 0.1447 loss: 1.5290 2022/08/30 06:11:53 - mmengine - INFO - Epoch(train) [261][60/63] lr: 5.6177e-03 eta: 1 day, 0:06:33 time: 1.3582 data_time: 0.0309 memory: 16201 loss_prob: 0.9220 loss_thr: 0.4949 loss_db: 0.1546 loss: 1.5716 2022/08/30 06:11:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:12:06 - mmengine - INFO - Epoch(train) [262][5/63] lr: 5.6124e-03 eta: 1 day, 0:06:33 time: 1.6154 data_time: 0.2305 memory: 16201 loss_prob: 0.7664 loss_thr: 0.4483 loss_db: 0.1299 loss: 1.3446 2022/08/30 06:12:13 - mmengine - INFO - Epoch(train) [262][10/63] lr: 5.6124e-03 eta: 1 day, 0:06:07 time: 1.7121 data_time: 0.2413 memory: 16201 loss_prob: 0.7879 loss_thr: 0.4665 loss_db: 0.1339 loss: 1.3883 2022/08/30 06:12:20 - mmengine - INFO - Epoch(train) [262][15/63] lr: 5.6124e-03 eta: 1 day, 0:06:07 time: 1.3803 data_time: 0.0342 memory: 16201 loss_prob: 0.8275 loss_thr: 0.5012 loss_db: 0.1435 loss: 1.4722 2022/08/30 06:12:27 - mmengine - INFO - Epoch(train) [262][20/63] lr: 5.6124e-03 eta: 1 day, 0:05:48 time: 1.3555 data_time: 0.0413 memory: 16201 loss_prob: 0.8286 loss_thr: 0.5088 loss_db: 0.1411 loss: 1.4785 2022/08/30 06:12:34 - mmengine - INFO - Epoch(train) [262][25/63] lr: 5.6124e-03 eta: 1 day, 0:05:48 time: 1.3782 data_time: 0.0386 memory: 16201 loss_prob: 0.7560 loss_thr: 0.4682 loss_db: 0.1247 loss: 1.3489 2022/08/30 06:12:41 - mmengine - INFO - Epoch(train) [262][30/63] lr: 5.6124e-03 eta: 1 day, 0:05:30 time: 1.3723 data_time: 0.0258 memory: 16201 loss_prob: 0.8470 loss_thr: 0.4692 loss_db: 0.1328 loss: 1.4490 2022/08/30 06:12:48 - mmengine - INFO - Epoch(train) [262][35/63] lr: 5.6124e-03 eta: 1 day, 0:05:30 time: 1.3773 data_time: 0.0286 memory: 16201 loss_prob: 0.8799 loss_thr: 0.4662 loss_db: 0.1422 loss: 1.4882 2022/08/30 06:12:55 - mmengine - INFO - Epoch(train) [262][40/63] lr: 5.6124e-03 eta: 1 day, 0:05:13 time: 1.3818 data_time: 0.0298 memory: 16201 loss_prob: 0.9309 loss_thr: 0.4627 loss_db: 0.1538 loss: 1.5474 2022/08/30 06:13:02 - mmengine - INFO - Epoch(train) [262][45/63] lr: 5.6124e-03 eta: 1 day, 0:05:13 time: 1.4021 data_time: 0.0347 memory: 16201 loss_prob: 0.9941 loss_thr: 0.5012 loss_db: 0.1592 loss: 1.6545 2022/08/30 06:13:09 - mmengine - INFO - Epoch(train) [262][50/63] lr: 5.6124e-03 eta: 1 day, 0:04:58 time: 1.4698 data_time: 0.0393 memory: 16201 loss_prob: 0.8847 loss_thr: 0.4974 loss_db: 0.1427 loss: 1.5247 2022/08/30 06:13:16 - mmengine - INFO - Epoch(train) [262][55/63] lr: 5.6124e-03 eta: 1 day, 0:04:58 time: 1.4257 data_time: 0.0356 memory: 16201 loss_prob: 0.7862 loss_thr: 0.4621 loss_db: 0.1316 loss: 1.3800 2022/08/30 06:13:23 - mmengine - INFO - Epoch(train) [262][60/63] lr: 5.6124e-03 eta: 1 day, 0:04:41 time: 1.4115 data_time: 0.0350 memory: 16201 loss_prob: 0.7828 loss_thr: 0.4692 loss_db: 0.1323 loss: 1.3842 2022/08/30 06:13:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:13:36 - mmengine - INFO - Epoch(train) [263][5/63] lr: 5.6070e-03 eta: 1 day, 0:04:41 time: 1.5315 data_time: 0.2334 memory: 16201 loss_prob: 1.0307 loss_thr: 0.5409 loss_db: 0.1652 loss: 1.7368 2022/08/30 06:13:43 - mmengine - INFO - Epoch(train) [263][10/63] lr: 5.6070e-03 eta: 1 day, 0:04:12 time: 1.6060 data_time: 0.2498 memory: 16201 loss_prob: 0.8576 loss_thr: 0.4952 loss_db: 0.1406 loss: 1.4933 2022/08/30 06:13:50 - mmengine - INFO - Epoch(train) [263][15/63] lr: 5.6070e-03 eta: 1 day, 0:04:12 time: 1.3876 data_time: 0.0303 memory: 16201 loss_prob: 0.9560 loss_thr: 0.5235 loss_db: 0.1532 loss: 1.6327 2022/08/30 06:13:56 - mmengine - INFO - Epoch(train) [263][20/63] lr: 5.6070e-03 eta: 1 day, 0:03:53 time: 1.3496 data_time: 0.0309 memory: 16201 loss_prob: 0.9813 loss_thr: 0.5312 loss_db: 0.1562 loss: 1.6687 2022/08/30 06:14:04 - mmengine - INFO - Epoch(train) [263][25/63] lr: 5.6070e-03 eta: 1 day, 0:03:53 time: 1.3853 data_time: 0.0306 memory: 16201 loss_prob: 0.9124 loss_thr: 0.5132 loss_db: 0.1511 loss: 1.5767 2022/08/30 06:14:11 - mmengine - INFO - Epoch(train) [263][30/63] lr: 5.6070e-03 eta: 1 day, 0:03:38 time: 1.4627 data_time: 0.0263 memory: 16201 loss_prob: 0.8584 loss_thr: 0.4942 loss_db: 0.1443 loss: 1.4969 2022/08/30 06:14:19 - mmengine - INFO - Epoch(train) [263][35/63] lr: 5.6070e-03 eta: 1 day, 0:03:38 time: 1.5032 data_time: 0.0715 memory: 16201 loss_prob: 0.8191 loss_thr: 0.4879 loss_db: 0.1383 loss: 1.4453 2022/08/30 06:14:26 - mmengine - INFO - Epoch(train) [263][40/63] lr: 5.6070e-03 eta: 1 day, 0:03:26 time: 1.5423 data_time: 0.0598 memory: 16201 loss_prob: 0.7545 loss_thr: 0.4667 loss_db: 0.1298 loss: 1.3510 2022/08/30 06:14:34 - mmengine - INFO - Epoch(train) [263][45/63] lr: 5.6070e-03 eta: 1 day, 0:03:26 time: 1.5188 data_time: 0.0293 memory: 16201 loss_prob: 0.7673 loss_thr: 0.4441 loss_db: 0.1295 loss: 1.3408 2022/08/30 06:14:41 - mmengine - INFO - Epoch(train) [263][50/63] lr: 5.6070e-03 eta: 1 day, 0:03:11 time: 1.4466 data_time: 0.0474 memory: 16201 loss_prob: 0.8627 loss_thr: 0.4687 loss_db: 0.1424 loss: 1.4738 2022/08/30 06:14:48 - mmengine - INFO - Epoch(train) [263][55/63] lr: 5.6070e-03 eta: 1 day, 0:03:11 time: 1.3684 data_time: 0.0463 memory: 16201 loss_prob: 0.8669 loss_thr: 0.4945 loss_db: 0.1450 loss: 1.5064 2022/08/30 06:14:54 - mmengine - INFO - Epoch(train) [263][60/63] lr: 5.6070e-03 eta: 1 day, 0:02:51 time: 1.3344 data_time: 0.0396 memory: 16201 loss_prob: 0.7968 loss_thr: 0.4898 loss_db: 0.1350 loss: 1.4215 2022/08/30 06:14:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:15:07 - mmengine - INFO - Epoch(train) [264][5/63] lr: 5.6016e-03 eta: 1 day, 0:02:51 time: 1.5081 data_time: 0.2274 memory: 16201 loss_prob: 0.8451 loss_thr: 0.5006 loss_db: 0.1415 loss: 1.4872 2022/08/30 06:15:13 - mmengine - INFO - Epoch(train) [264][10/63] lr: 5.6016e-03 eta: 1 day, 0:02:20 time: 1.5533 data_time: 0.2504 memory: 16201 loss_prob: 0.8189 loss_thr: 0.4922 loss_db: 0.1384 loss: 1.4495 2022/08/30 06:15:20 - mmengine - INFO - Epoch(train) [264][15/63] lr: 5.6016e-03 eta: 1 day, 0:02:20 time: 1.2907 data_time: 0.0334 memory: 16201 loss_prob: 0.8191 loss_thr: 0.4903 loss_db: 0.1381 loss: 1.4475 2022/08/30 06:15:28 - mmengine - INFO - Epoch(train) [264][20/63] lr: 5.6016e-03 eta: 1 day, 0:02:04 time: 1.4341 data_time: 0.0347 memory: 16201 loss_prob: 0.7868 loss_thr: 0.4831 loss_db: 0.1311 loss: 1.4010 2022/08/30 06:15:35 - mmengine - INFO - Epoch(train) [264][25/63] lr: 5.6016e-03 eta: 1 day, 0:02:04 time: 1.4888 data_time: 0.0376 memory: 16201 loss_prob: 0.8158 loss_thr: 0.5037 loss_db: 0.1368 loss: 1.4563 2022/08/30 06:15:42 - mmengine - INFO - Epoch(train) [264][30/63] lr: 5.6016e-03 eta: 1 day, 0:01:48 time: 1.4302 data_time: 0.0295 memory: 16201 loss_prob: 0.8726 loss_thr: 0.5288 loss_db: 0.1490 loss: 1.5505 2022/08/30 06:15:49 - mmengine - INFO - Epoch(train) [264][35/63] lr: 5.6016e-03 eta: 1 day, 0:01:48 time: 1.4133 data_time: 0.0372 memory: 16201 loss_prob: 0.8187 loss_thr: 0.4974 loss_db: 0.1407 loss: 1.4569 2022/08/30 06:15:56 - mmengine - INFO - Epoch(train) [264][40/63] lr: 5.6016e-03 eta: 1 day, 0:01:29 time: 1.3517 data_time: 0.0297 memory: 16201 loss_prob: 0.7613 loss_thr: 0.4722 loss_db: 0.1303 loss: 1.3639 2022/08/30 06:16:03 - mmengine - INFO - Epoch(train) [264][45/63] lr: 5.6016e-03 eta: 1 day, 0:01:29 time: 1.4219 data_time: 0.0335 memory: 16201 loss_prob: 0.7207 loss_thr: 0.4617 loss_db: 0.1210 loss: 1.3034 2022/08/30 06:16:10 - mmengine - INFO - Epoch(train) [264][50/63] lr: 5.6016e-03 eta: 1 day, 0:01:13 time: 1.4237 data_time: 0.0437 memory: 16201 loss_prob: 0.8280 loss_thr: 0.4877 loss_db: 0.1316 loss: 1.4473 2022/08/30 06:16:16 - mmengine - INFO - Epoch(train) [264][55/63] lr: 5.6016e-03 eta: 1 day, 0:01:13 time: 1.3163 data_time: 0.0296 memory: 16201 loss_prob: 0.9453 loss_thr: 0.4946 loss_db: 0.1505 loss: 1.5904 2022/08/30 06:16:24 - mmengine - INFO - Epoch(train) [264][60/63] lr: 5.6016e-03 eta: 1 day, 0:00:55 time: 1.3781 data_time: 0.0299 memory: 16201 loss_prob: 0.8458 loss_thr: 0.4727 loss_db: 0.1402 loss: 1.4587 2022/08/30 06:16:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:16:37 - mmengine - INFO - Epoch(train) [265][5/63] lr: 5.5962e-03 eta: 1 day, 0:00:55 time: 1.5888 data_time: 0.2283 memory: 16201 loss_prob: 0.7848 loss_thr: 0.4722 loss_db: 0.1366 loss: 1.3937 2022/08/30 06:16:43 - mmengine - INFO - Epoch(train) [265][10/63] lr: 5.5962e-03 eta: 1 day, 0:00:26 time: 1.6079 data_time: 0.2476 memory: 16201 loss_prob: 0.7872 loss_thr: 0.4736 loss_db: 0.1386 loss: 1.3994 2022/08/30 06:16:49 - mmengine - INFO - Epoch(train) [265][15/63] lr: 5.5962e-03 eta: 1 day, 0:00:26 time: 1.2817 data_time: 0.0335 memory: 16201 loss_prob: 0.8103 loss_thr: 0.4760 loss_db: 0.1397 loss: 1.4260 2022/08/30 06:16:57 - mmengine - INFO - Epoch(train) [265][20/63] lr: 5.5962e-03 eta: 1 day, 0:00:07 time: 1.3632 data_time: 0.0295 memory: 16201 loss_prob: 0.7750 loss_thr: 0.4605 loss_db: 0.1311 loss: 1.3666 2022/08/30 06:17:04 - mmengine - INFO - Epoch(train) [265][25/63] lr: 5.5962e-03 eta: 1 day, 0:00:07 time: 1.4610 data_time: 0.0400 memory: 16201 loss_prob: 0.8287 loss_thr: 0.4849 loss_db: 0.1414 loss: 1.4550 2022/08/30 06:17:11 - mmengine - INFO - Epoch(train) [265][30/63] lr: 5.5962e-03 eta: 23:59:50 time: 1.4018 data_time: 0.0301 memory: 16201 loss_prob: 0.8841 loss_thr: 0.5213 loss_db: 0.1462 loss: 1.5517 2022/08/30 06:17:17 - mmengine - INFO - Epoch(train) [265][35/63] lr: 5.5962e-03 eta: 23:59:50 time: 1.3282 data_time: 0.0333 memory: 16201 loss_prob: 0.8398 loss_thr: 0.5023 loss_db: 0.1363 loss: 1.4784 2022/08/30 06:17:24 - mmengine - INFO - Epoch(train) [265][40/63] lr: 5.5962e-03 eta: 23:59:33 time: 1.3867 data_time: 0.0339 memory: 16201 loss_prob: 0.8275 loss_thr: 0.4860 loss_db: 0.1360 loss: 1.4495 2022/08/30 06:17:31 - mmengine - INFO - Epoch(train) [265][45/63] lr: 5.5962e-03 eta: 23:59:33 time: 1.3551 data_time: 0.0279 memory: 16201 loss_prob: 0.8068 loss_thr: 0.4870 loss_db: 0.1343 loss: 1.4281 2022/08/30 06:17:39 - mmengine - INFO - Epoch(train) [265][50/63] lr: 5.5962e-03 eta: 23:59:17 time: 1.4220 data_time: 0.0387 memory: 16201 loss_prob: 0.7691 loss_thr: 0.4742 loss_db: 0.1282 loss: 1.3715 2022/08/30 06:17:46 - mmengine - INFO - Epoch(train) [265][55/63] lr: 5.5962e-03 eta: 23:59:17 time: 1.5452 data_time: 0.0335 memory: 16201 loss_prob: 0.7303 loss_thr: 0.4624 loss_db: 0.1217 loss: 1.3144 2022/08/30 06:17:53 - mmengine - INFO - Epoch(train) [265][60/63] lr: 5.5962e-03 eta: 23:59:00 time: 1.4128 data_time: 0.0303 memory: 16201 loss_prob: 0.7217 loss_thr: 0.4572 loss_db: 0.1233 loss: 1.3022 2022/08/30 06:17:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:18:06 - mmengine - INFO - Epoch(train) [266][5/63] lr: 5.5908e-03 eta: 23:59:00 time: 1.5336 data_time: 0.2388 memory: 16201 loss_prob: 0.7595 loss_thr: 0.4662 loss_db: 0.1280 loss: 1.3537 2022/08/30 06:18:14 - mmengine - INFO - Epoch(train) [266][10/63] lr: 5.5908e-03 eta: 23:58:34 time: 1.7075 data_time: 0.2524 memory: 16201 loss_prob: 0.8077 loss_thr: 0.4711 loss_db: 0.1304 loss: 1.4091 2022/08/30 06:18:21 - mmengine - INFO - Epoch(train) [266][15/63] lr: 5.5908e-03 eta: 23:58:34 time: 1.5701 data_time: 0.0353 memory: 16201 loss_prob: 0.8335 loss_thr: 0.4769 loss_db: 0.1362 loss: 1.4465 2022/08/30 06:18:28 - mmengine - INFO - Epoch(train) [266][20/63] lr: 5.5908e-03 eta: 23:58:19 time: 1.4441 data_time: 0.0320 memory: 16201 loss_prob: 0.7297 loss_thr: 0.4461 loss_db: 0.1237 loss: 1.2995 2022/08/30 06:18:35 - mmengine - INFO - Epoch(train) [266][25/63] lr: 5.5908e-03 eta: 23:58:19 time: 1.3756 data_time: 0.0289 memory: 16201 loss_prob: 0.7498 loss_thr: 0.4585 loss_db: 0.1254 loss: 1.3337 2022/08/30 06:18:43 - mmengine - INFO - Epoch(train) [266][30/63] lr: 5.5908e-03 eta: 23:58:04 time: 1.4672 data_time: 0.0344 memory: 16201 loss_prob: 0.8071 loss_thr: 0.4819 loss_db: 0.1310 loss: 1.4200 2022/08/30 06:18:51 - mmengine - INFO - Epoch(train) [266][35/63] lr: 5.5908e-03 eta: 23:58:04 time: 1.5435 data_time: 0.0401 memory: 16201 loss_prob: 0.7960 loss_thr: 0.4728 loss_db: 0.1319 loss: 1.4008 2022/08/30 06:18:57 - mmengine - INFO - Epoch(train) [266][40/63] lr: 5.5908e-03 eta: 23:57:50 time: 1.4759 data_time: 0.0318 memory: 16201 loss_prob: 0.8006 loss_thr: 0.4818 loss_db: 0.1335 loss: 1.4159 2022/08/30 06:19:06 - mmengine - INFO - Epoch(train) [266][45/63] lr: 5.5908e-03 eta: 23:57:50 time: 1.4915 data_time: 0.0324 memory: 16201 loss_prob: 0.8463 loss_thr: 0.4850 loss_db: 0.1404 loss: 1.4717 2022/08/30 06:19:13 - mmengine - INFO - Epoch(train) [266][50/63] lr: 5.5908e-03 eta: 23:57:37 time: 1.5170 data_time: 0.0365 memory: 16201 loss_prob: 0.8117 loss_thr: 0.4993 loss_db: 0.1402 loss: 1.4512 2022/08/30 06:19:20 - mmengine - INFO - Epoch(train) [266][55/63] lr: 5.5908e-03 eta: 23:57:37 time: 1.4757 data_time: 0.0357 memory: 16201 loss_prob: 0.7772 loss_thr: 0.5072 loss_db: 0.1310 loss: 1.4154 2022/08/30 06:19:27 - mmengine - INFO - Epoch(train) [266][60/63] lr: 5.5908e-03 eta: 23:57:22 time: 1.4603 data_time: 0.0320 memory: 16201 loss_prob: 0.8082 loss_thr: 0.4955 loss_db: 0.1347 loss: 1.4385 2022/08/30 06:19:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:19:40 - mmengine - INFO - Epoch(train) [267][5/63] lr: 5.5854e-03 eta: 23:57:22 time: 1.5455 data_time: 0.2258 memory: 16201 loss_prob: 0.7446 loss_thr: 0.4622 loss_db: 0.1277 loss: 1.3344 2022/08/30 06:19:47 - mmengine - INFO - Epoch(train) [267][10/63] lr: 5.5854e-03 eta: 23:56:55 time: 1.6842 data_time: 0.2332 memory: 16201 loss_prob: 0.7759 loss_thr: 0.4674 loss_db: 0.1320 loss: 1.3753 2022/08/30 06:19:54 - mmengine - INFO - Epoch(train) [267][15/63] lr: 5.5854e-03 eta: 23:56:55 time: 1.3795 data_time: 0.0331 memory: 16201 loss_prob: 0.8050 loss_thr: 0.4786 loss_db: 0.1338 loss: 1.4174 2022/08/30 06:20:01 - mmengine - INFO - Epoch(train) [267][20/63] lr: 5.5854e-03 eta: 23:56:38 time: 1.3880 data_time: 0.0314 memory: 16201 loss_prob: 0.7538 loss_thr: 0.4552 loss_db: 0.1269 loss: 1.3358 2022/08/30 06:20:08 - mmengine - INFO - Epoch(train) [267][25/63] lr: 5.5854e-03 eta: 23:56:38 time: 1.4512 data_time: 0.0338 memory: 16201 loss_prob: 0.6969 loss_thr: 0.4416 loss_db: 0.1200 loss: 1.2585 2022/08/30 06:20:15 - mmengine - INFO - Epoch(train) [267][30/63] lr: 5.5854e-03 eta: 23:56:21 time: 1.3923 data_time: 0.0278 memory: 16201 loss_prob: 0.7113 loss_thr: 0.4574 loss_db: 0.1220 loss: 1.2907 2022/08/30 06:20:22 - mmengine - INFO - Epoch(train) [267][35/63] lr: 5.5854e-03 eta: 23:56:21 time: 1.3661 data_time: 0.0298 memory: 16201 loss_prob: 0.7580 loss_thr: 0.4690 loss_db: 0.1267 loss: 1.3537 2022/08/30 06:20:29 - mmengine - INFO - Epoch(train) [267][40/63] lr: 5.5854e-03 eta: 23:56:03 time: 1.3840 data_time: 0.0356 memory: 16201 loss_prob: 0.7668 loss_thr: 0.4861 loss_db: 0.1288 loss: 1.3817 2022/08/30 06:20:36 - mmengine - INFO - Epoch(train) [267][45/63] lr: 5.5854e-03 eta: 23:56:03 time: 1.3941 data_time: 0.0366 memory: 16201 loss_prob: 0.8004 loss_thr: 0.4871 loss_db: 0.1350 loss: 1.4225 2022/08/30 06:20:42 - mmengine - INFO - Epoch(train) [267][50/63] lr: 5.5854e-03 eta: 23:55:44 time: 1.3489 data_time: 0.0343 memory: 16201 loss_prob: 0.7640 loss_thr: 0.4702 loss_db: 0.1280 loss: 1.3623 2022/08/30 06:20:49 - mmengine - INFO - Epoch(train) [267][55/63] lr: 5.5854e-03 eta: 23:55:44 time: 1.3385 data_time: 0.0287 memory: 16201 loss_prob: 0.7361 loss_thr: 0.4589 loss_db: 0.1234 loss: 1.3184 2022/08/30 06:20:57 - mmengine - INFO - Epoch(train) [267][60/63] lr: 5.5854e-03 eta: 23:55:29 time: 1.4492 data_time: 0.0406 memory: 16201 loss_prob: 0.7261 loss_thr: 0.4450 loss_db: 0.1227 loss: 1.2939 2022/08/30 06:21:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:21:11 - mmengine - INFO - Epoch(train) [268][5/63] lr: 5.5800e-03 eta: 23:55:29 time: 1.6570 data_time: 0.2150 memory: 16201 loss_prob: 0.6383 loss_thr: 0.4263 loss_db: 0.1099 loss: 1.1745 2022/08/30 06:21:18 - mmengine - INFO - Epoch(train) [268][10/63] lr: 5.5800e-03 eta: 23:55:05 time: 1.7538 data_time: 0.2317 memory: 16201 loss_prob: 0.7147 loss_thr: 0.4557 loss_db: 0.1229 loss: 1.2934 2022/08/30 06:21:25 - mmengine - INFO - Epoch(train) [268][15/63] lr: 5.5800e-03 eta: 23:55:05 time: 1.4209 data_time: 0.0349 memory: 16201 loss_prob: 0.7766 loss_thr: 0.4640 loss_db: 0.1312 loss: 1.3717 2022/08/30 06:21:31 - mmengine - INFO - Epoch(train) [268][20/63] lr: 5.5800e-03 eta: 23:54:46 time: 1.3316 data_time: 0.0328 memory: 16201 loss_prob: 0.7713 loss_thr: 0.4467 loss_db: 0.1274 loss: 1.3454 2022/08/30 06:21:38 - mmengine - INFO - Epoch(train) [268][25/63] lr: 5.5800e-03 eta: 23:54:46 time: 1.3001 data_time: 0.0411 memory: 16201 loss_prob: 0.7620 loss_thr: 0.4629 loss_db: 0.1265 loss: 1.3515 2022/08/30 06:21:45 - mmengine - INFO - Epoch(train) [268][30/63] lr: 5.5800e-03 eta: 23:54:27 time: 1.3499 data_time: 0.0294 memory: 16201 loss_prob: 0.7283 loss_thr: 0.4613 loss_db: 0.1225 loss: 1.3121 2022/08/30 06:21:52 - mmengine - INFO - Epoch(train) [268][35/63] lr: 5.5800e-03 eta: 23:54:27 time: 1.3880 data_time: 0.0289 memory: 16201 loss_prob: 0.7025 loss_thr: 0.4449 loss_db: 0.1190 loss: 1.2664 2022/08/30 06:21:58 - mmengine - INFO - Epoch(train) [268][40/63] lr: 5.5800e-03 eta: 23:54:08 time: 1.3322 data_time: 0.0314 memory: 16201 loss_prob: 0.6986 loss_thr: 0.4446 loss_db: 0.1187 loss: 1.2619 2022/08/30 06:22:06 - mmengine - INFO - Epoch(train) [268][45/63] lr: 5.5800e-03 eta: 23:54:08 time: 1.3898 data_time: 0.0331 memory: 16201 loss_prob: 0.7012 loss_thr: 0.4404 loss_db: 0.1181 loss: 1.2596 2022/08/30 06:22:13 - mmengine - INFO - Epoch(train) [268][50/63] lr: 5.5800e-03 eta: 23:53:52 time: 1.4282 data_time: 0.0437 memory: 16201 loss_prob: 0.7834 loss_thr: 0.4941 loss_db: 0.1322 loss: 1.4097 2022/08/30 06:22:19 - mmengine - INFO - Epoch(train) [268][55/63] lr: 5.5800e-03 eta: 23:53:52 time: 1.3453 data_time: 0.0360 memory: 16201 loss_prob: 0.7673 loss_thr: 0.4919 loss_db: 0.1304 loss: 1.3897 2022/08/30 06:22:25 - mmengine - INFO - Epoch(train) [268][60/63] lr: 5.5800e-03 eta: 23:53:31 time: 1.2888 data_time: 0.0294 memory: 16201 loss_prob: 0.7021 loss_thr: 0.4464 loss_db: 0.1197 loss: 1.2681 2022/08/30 06:22:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:22:38 - mmengine - INFO - Epoch(train) [269][5/63] lr: 5.5746e-03 eta: 23:53:31 time: 1.4775 data_time: 0.2313 memory: 16201 loss_prob: 0.8403 loss_thr: 0.5057 loss_db: 0.1406 loss: 1.4866 2022/08/30 06:22:45 - mmengine - INFO - Epoch(train) [269][10/63] lr: 5.5746e-03 eta: 23:53:01 time: 1.5942 data_time: 0.2423 memory: 16201 loss_prob: 0.8376 loss_thr: 0.5001 loss_db: 0.1372 loss: 1.4748 2022/08/30 06:22:51 - mmengine - INFO - Epoch(train) [269][15/63] lr: 5.5746e-03 eta: 23:53:01 time: 1.3557 data_time: 0.0377 memory: 16201 loss_prob: 0.7472 loss_thr: 0.4744 loss_db: 0.1301 loss: 1.3517 2022/08/30 06:22:58 - mmengine - INFO - Epoch(train) [269][20/63] lr: 5.5746e-03 eta: 23:52:42 time: 1.3456 data_time: 0.0437 memory: 16201 loss_prob: 0.6856 loss_thr: 0.4470 loss_db: 0.1204 loss: 1.2530 2022/08/30 06:23:05 - mmengine - INFO - Epoch(train) [269][25/63] lr: 5.5746e-03 eta: 23:52:42 time: 1.3847 data_time: 0.0425 memory: 16201 loss_prob: 0.7391 loss_thr: 0.4786 loss_db: 0.1251 loss: 1.3429 2022/08/30 06:23:12 - mmengine - INFO - Epoch(train) [269][30/63] lr: 5.5746e-03 eta: 23:52:23 time: 1.3247 data_time: 0.0403 memory: 16201 loss_prob: 0.7502 loss_thr: 0.4816 loss_db: 0.1290 loss: 1.3609 2022/08/30 06:23:19 - mmengine - INFO - Epoch(train) [269][35/63] lr: 5.5746e-03 eta: 23:52:23 time: 1.3377 data_time: 0.0418 memory: 16201 loss_prob: 0.7462 loss_thr: 0.4607 loss_db: 0.1258 loss: 1.3328 2022/08/30 06:23:25 - mmengine - INFO - Epoch(train) [269][40/63] lr: 5.5746e-03 eta: 23:52:04 time: 1.3541 data_time: 0.0316 memory: 16201 loss_prob: 0.7545 loss_thr: 0.4723 loss_db: 0.1246 loss: 1.3514 2022/08/30 06:23:32 - mmengine - INFO - Epoch(train) [269][45/63] lr: 5.5746e-03 eta: 23:52:04 time: 1.3522 data_time: 0.0370 memory: 16201 loss_prob: 0.6698 loss_thr: 0.4432 loss_db: 0.1130 loss: 1.2260 2022/08/30 06:23:39 - mmengine - INFO - Epoch(train) [269][50/63] lr: 5.5746e-03 eta: 23:51:47 time: 1.3858 data_time: 0.0445 memory: 16201 loss_prob: 0.6535 loss_thr: 0.4296 loss_db: 0.1124 loss: 1.1955 2022/08/30 06:23:46 - mmengine - INFO - Epoch(train) [269][55/63] lr: 5.5746e-03 eta: 23:51:47 time: 1.3592 data_time: 0.0309 memory: 16201 loss_prob: 0.7117 loss_thr: 0.4570 loss_db: 0.1211 loss: 1.2898 2022/08/30 06:23:52 - mmengine - INFO - Epoch(train) [269][60/63] lr: 5.5746e-03 eta: 23:51:28 time: 1.3304 data_time: 0.0289 memory: 16201 loss_prob: 0.8011 loss_thr: 0.4695 loss_db: 0.1303 loss: 1.4009 2022/08/30 06:23:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:24:05 - mmengine - INFO - Epoch(train) [270][5/63] lr: 5.5693e-03 eta: 23:51:28 time: 1.4846 data_time: 0.2108 memory: 16201 loss_prob: 0.7185 loss_thr: 0.4664 loss_db: 0.1219 loss: 1.3068 2022/08/30 06:24:12 - mmengine - INFO - Epoch(train) [270][10/63] lr: 5.5693e-03 eta: 23:51:00 time: 1.6387 data_time: 0.2236 memory: 16201 loss_prob: 0.7454 loss_thr: 0.4710 loss_db: 0.1312 loss: 1.3476 2022/08/30 06:24:18 - mmengine - INFO - Epoch(train) [270][15/63] lr: 5.5693e-03 eta: 23:51:00 time: 1.2910 data_time: 0.0339 memory: 16201 loss_prob: 0.8339 loss_thr: 0.5064 loss_db: 0.1411 loss: 1.4814 2022/08/30 06:24:25 - mmengine - INFO - Epoch(train) [270][20/63] lr: 5.5693e-03 eta: 23:50:40 time: 1.3274 data_time: 0.0356 memory: 16201 loss_prob: 0.8045 loss_thr: 0.4768 loss_db: 0.1328 loss: 1.4141 2022/08/30 06:24:32 - mmengine - INFO - Epoch(train) [270][25/63] lr: 5.5693e-03 eta: 23:50:40 time: 1.4237 data_time: 0.0346 memory: 16201 loss_prob: 0.7270 loss_thr: 0.4497 loss_db: 0.1225 loss: 1.2992 2022/08/30 06:24:39 - mmengine - INFO - Epoch(train) [270][30/63] lr: 5.5693e-03 eta: 23:50:23 time: 1.3841 data_time: 0.0314 memory: 16201 loss_prob: 0.7015 loss_thr: 0.4512 loss_db: 0.1164 loss: 1.2691 2022/08/30 06:24:46 - mmengine - INFO - Epoch(train) [270][35/63] lr: 5.5693e-03 eta: 23:50:23 time: 1.4186 data_time: 0.0388 memory: 16201 loss_prob: 0.7278 loss_thr: 0.4506 loss_db: 0.1203 loss: 1.2988 2022/08/30 06:24:53 - mmengine - INFO - Epoch(train) [270][40/63] lr: 5.5693e-03 eta: 23:50:06 time: 1.4118 data_time: 0.0334 memory: 16201 loss_prob: 0.6860 loss_thr: 0.4373 loss_db: 0.1167 loss: 1.2400 2022/08/30 06:24:59 - mmengine - INFO - Epoch(train) [270][45/63] lr: 5.5693e-03 eta: 23:50:06 time: 1.2893 data_time: 0.0329 memory: 16201 loss_prob: 0.6698 loss_thr: 0.4368 loss_db: 0.1144 loss: 1.2211 2022/08/30 06:25:05 - mmengine - INFO - Epoch(train) [270][50/63] lr: 5.5693e-03 eta: 23:49:44 time: 1.2402 data_time: 0.0372 memory: 16201 loss_prob: 0.7305 loss_thr: 0.4535 loss_db: 0.1214 loss: 1.3054 2022/08/30 06:25:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:25:12 - mmengine - INFO - Epoch(train) [270][55/63] lr: 5.5693e-03 eta: 23:49:44 time: 1.2884 data_time: 0.0321 memory: 16201 loss_prob: 0.6648 loss_thr: 0.4197 loss_db: 0.1135 loss: 1.1979 2022/08/30 06:25:19 - mmengine - INFO - Epoch(train) [270][60/63] lr: 5.5693e-03 eta: 23:49:26 time: 1.3746 data_time: 0.0404 memory: 16201 loss_prob: 0.6620 loss_thr: 0.4260 loss_db: 0.1137 loss: 1.2016 2022/08/30 06:25:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:25:31 - mmengine - INFO - Epoch(train) [271][5/63] lr: 5.5639e-03 eta: 23:49:26 time: 1.4675 data_time: 0.2260 memory: 16201 loss_prob: 0.7220 loss_thr: 0.4570 loss_db: 0.1215 loss: 1.3005 2022/08/30 06:25:38 - mmengine - INFO - Epoch(train) [271][10/63] lr: 5.5639e-03 eta: 23:48:55 time: 1.5597 data_time: 0.2415 memory: 16201 loss_prob: 0.6961 loss_thr: 0.4439 loss_db: 0.1168 loss: 1.2567 2022/08/30 06:25:44 - mmengine - INFO - Epoch(train) [271][15/63] lr: 5.5639e-03 eta: 23:48:55 time: 1.3570 data_time: 0.0349 memory: 16201 loss_prob: 0.6780 loss_thr: 0.4411 loss_db: 0.1152 loss: 1.2344 2022/08/30 06:25:51 - mmengine - INFO - Epoch(train) [271][20/63] lr: 5.5639e-03 eta: 23:48:37 time: 1.3610 data_time: 0.0379 memory: 16201 loss_prob: 0.6763 loss_thr: 0.4360 loss_db: 0.1131 loss: 1.2253 2022/08/30 06:25:58 - mmengine - INFO - Epoch(train) [271][25/63] lr: 5.5639e-03 eta: 23:48:37 time: 1.3783 data_time: 0.0470 memory: 16201 loss_prob: 0.7769 loss_thr: 0.4801 loss_db: 0.1261 loss: 1.3832 2022/08/30 06:26:05 - mmengine - INFO - Epoch(train) [271][30/63] lr: 5.5639e-03 eta: 23:48:19 time: 1.3620 data_time: 0.0304 memory: 16201 loss_prob: 0.8250 loss_thr: 0.4938 loss_db: 0.1394 loss: 1.4583 2022/08/30 06:26:12 - mmengine - INFO - Epoch(train) [271][35/63] lr: 5.5639e-03 eta: 23:48:19 time: 1.3336 data_time: 0.0298 memory: 16201 loss_prob: 0.6972 loss_thr: 0.4341 loss_db: 0.1214 loss: 1.2527 2022/08/30 06:26:18 - mmengine - INFO - Epoch(train) [271][40/63] lr: 5.5639e-03 eta: 23:48:00 time: 1.3230 data_time: 0.0308 memory: 16201 loss_prob: 0.7219 loss_thr: 0.4314 loss_db: 0.1174 loss: 1.2706 2022/08/30 06:26:25 - mmengine - INFO - Epoch(train) [271][45/63] lr: 5.5639e-03 eta: 23:48:00 time: 1.3347 data_time: 0.0306 memory: 16201 loss_prob: 0.7625 loss_thr: 0.4775 loss_db: 0.1251 loss: 1.3652 2022/08/30 06:26:31 - mmengine - INFO - Epoch(train) [271][50/63] lr: 5.5639e-03 eta: 23:47:40 time: 1.3249 data_time: 0.0433 memory: 16201 loss_prob: 0.7606 loss_thr: 0.4726 loss_db: 0.1294 loss: 1.3626 2022/08/30 06:26:38 - mmengine - INFO - Epoch(train) [271][55/63] lr: 5.5639e-03 eta: 23:47:40 time: 1.2933 data_time: 0.0290 memory: 16201 loss_prob: 0.7933 loss_thr: 0.4566 loss_db: 0.1357 loss: 1.3855 2022/08/30 06:26:45 - mmengine - INFO - Epoch(train) [271][60/63] lr: 5.5639e-03 eta: 23:47:20 time: 1.3076 data_time: 0.0457 memory: 16201 loss_prob: 0.7478 loss_thr: 0.4681 loss_db: 0.1280 loss: 1.3438 2022/08/30 06:26:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:26:56 - mmengine - INFO - Epoch(train) [272][5/63] lr: 5.5585e-03 eta: 23:47:20 time: 1.3936 data_time: 0.2293 memory: 16201 loss_prob: 0.7466 loss_thr: 0.4488 loss_db: 0.1273 loss: 1.3227 2022/08/30 06:27:03 - mmengine - INFO - Epoch(train) [272][10/63] lr: 5.5585e-03 eta: 23:46:48 time: 1.5149 data_time: 0.2442 memory: 16201 loss_prob: 0.7018 loss_thr: 0.4452 loss_db: 0.1182 loss: 1.2651 2022/08/30 06:27:10 - mmengine - INFO - Epoch(train) [272][15/63] lr: 5.5585e-03 eta: 23:46:48 time: 1.3733 data_time: 0.0350 memory: 16201 loss_prob: 0.6993 loss_thr: 0.4491 loss_db: 0.1188 loss: 1.2672 2022/08/30 06:27:17 - mmengine - INFO - Epoch(train) [272][20/63] lr: 5.5585e-03 eta: 23:46:31 time: 1.3780 data_time: 0.0359 memory: 16201 loss_prob: 0.7042 loss_thr: 0.4406 loss_db: 0.1183 loss: 1.2632 2022/08/30 06:27:23 - mmengine - INFO - Epoch(train) [272][25/63] lr: 5.5585e-03 eta: 23:46:31 time: 1.2890 data_time: 0.0337 memory: 16201 loss_prob: 0.7324 loss_thr: 0.4453 loss_db: 0.1214 loss: 1.2992 2022/08/30 06:27:30 - mmengine - INFO - Epoch(train) [272][30/63] lr: 5.5585e-03 eta: 23:46:10 time: 1.2816 data_time: 0.0373 memory: 16201 loss_prob: 0.7278 loss_thr: 0.4628 loss_db: 0.1227 loss: 1.3133 2022/08/30 06:27:36 - mmengine - INFO - Epoch(train) [272][35/63] lr: 5.5585e-03 eta: 23:46:10 time: 1.3579 data_time: 0.0421 memory: 16201 loss_prob: 0.7218 loss_thr: 0.4662 loss_db: 0.1220 loss: 1.3100 2022/08/30 06:27:44 - mmengine - INFO - Epoch(train) [272][40/63] lr: 5.5585e-03 eta: 23:45:54 time: 1.4242 data_time: 0.0345 memory: 16201 loss_prob: 0.7890 loss_thr: 0.4961 loss_db: 0.1310 loss: 1.4161 2022/08/30 06:27:50 - mmengine - INFO - Epoch(train) [272][45/63] lr: 5.5585e-03 eta: 23:45:54 time: 1.4036 data_time: 0.0330 memory: 16201 loss_prob: 0.7463 loss_thr: 0.4740 loss_db: 0.1247 loss: 1.3450 2022/08/30 06:27:57 - mmengine - INFO - Epoch(train) [272][50/63] lr: 5.5585e-03 eta: 23:45:34 time: 1.3196 data_time: 0.0439 memory: 16201 loss_prob: 0.6916 loss_thr: 0.4400 loss_db: 0.1182 loss: 1.2498 2022/08/30 06:28:03 - mmengine - INFO - Epoch(train) [272][55/63] lr: 5.5585e-03 eta: 23:45:34 time: 1.2642 data_time: 0.0375 memory: 16201 loss_prob: 0.7093 loss_thr: 0.4560 loss_db: 0.1225 loss: 1.2878 2022/08/30 06:28:10 - mmengine - INFO - Epoch(train) [272][60/63] lr: 5.5585e-03 eta: 23:45:14 time: 1.2902 data_time: 0.0291 memory: 16201 loss_prob: 0.7082 loss_thr: 0.4621 loss_db: 0.1222 loss: 1.2924 2022/08/30 06:28:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:28:22 - mmengine - INFO - Epoch(train) [273][5/63] lr: 5.5531e-03 eta: 23:45:14 time: 1.4638 data_time: 0.2209 memory: 16201 loss_prob: 0.7578 loss_thr: 0.4577 loss_db: 0.1291 loss: 1.3447 2022/08/30 06:28:29 - mmengine - INFO - Epoch(train) [273][10/63] lr: 5.5531e-03 eta: 23:44:45 time: 1.6148 data_time: 0.2342 memory: 16201 loss_prob: 0.7202 loss_thr: 0.4487 loss_db: 0.1244 loss: 1.2933 2022/08/30 06:28:36 - mmengine - INFO - Epoch(train) [273][15/63] lr: 5.5531e-03 eta: 23:44:45 time: 1.4091 data_time: 0.0313 memory: 16201 loss_prob: 0.6467 loss_thr: 0.4287 loss_db: 0.1120 loss: 1.1873 2022/08/30 06:28:42 - mmengine - INFO - Epoch(train) [273][20/63] lr: 5.5531e-03 eta: 23:44:26 time: 1.3336 data_time: 0.0285 memory: 16201 loss_prob: 0.6460 loss_thr: 0.4162 loss_db: 0.1104 loss: 1.1726 2022/08/30 06:28:49 - mmengine - INFO - Epoch(train) [273][25/63] lr: 5.5531e-03 eta: 23:44:26 time: 1.3232 data_time: 0.0322 memory: 16201 loss_prob: 0.6536 loss_thr: 0.4150 loss_db: 0.1119 loss: 1.1806 2022/08/30 06:28:56 - mmengine - INFO - Epoch(train) [273][30/63] lr: 5.5531e-03 eta: 23:44:07 time: 1.3325 data_time: 0.0330 memory: 16201 loss_prob: 0.6661 loss_thr: 0.4303 loss_db: 0.1138 loss: 1.2103 2022/08/30 06:29:03 - mmengine - INFO - Epoch(train) [273][35/63] lr: 5.5531e-03 eta: 23:44:07 time: 1.3232 data_time: 0.0382 memory: 16201 loss_prob: 0.7352 loss_thr: 0.4414 loss_db: 0.1187 loss: 1.2953 2022/08/30 06:29:09 - mmengine - INFO - Epoch(train) [273][40/63] lr: 5.5531e-03 eta: 23:43:47 time: 1.3197 data_time: 0.0298 memory: 16201 loss_prob: 0.7667 loss_thr: 0.4667 loss_db: 0.1255 loss: 1.3589 2022/08/30 06:29:16 - mmengine - INFO - Epoch(train) [273][45/63] lr: 5.5531e-03 eta: 23:43:47 time: 1.3556 data_time: 0.0322 memory: 16201 loss_prob: 0.6853 loss_thr: 0.4484 loss_db: 0.1190 loss: 1.2526 2022/08/30 06:29:23 - mmengine - INFO - Epoch(train) [273][50/63] lr: 5.5531e-03 eta: 23:43:31 time: 1.4072 data_time: 0.0405 memory: 16201 loss_prob: 0.6771 loss_thr: 0.4317 loss_db: 0.1169 loss: 1.2256 2022/08/30 06:29:30 - mmengine - INFO - Epoch(train) [273][55/63] lr: 5.5531e-03 eta: 23:43:31 time: 1.4091 data_time: 0.0333 memory: 16201 loss_prob: 0.6797 loss_thr: 0.4345 loss_db: 0.1149 loss: 1.2291 2022/08/30 06:29:37 - mmengine - INFO - Epoch(train) [273][60/63] lr: 5.5531e-03 eta: 23:43:14 time: 1.3940 data_time: 0.0407 memory: 16201 loss_prob: 0.6594 loss_thr: 0.4215 loss_db: 0.1102 loss: 1.1911 2022/08/30 06:29:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:29:49 - mmengine - INFO - Epoch(train) [274][5/63] lr: 5.5477e-03 eta: 23:43:14 time: 1.4616 data_time: 0.2088 memory: 16201 loss_prob: 0.7056 loss_thr: 0.4430 loss_db: 0.1164 loss: 1.2650 2022/08/30 06:29:56 - mmengine - INFO - Epoch(train) [274][10/63] lr: 5.5477e-03 eta: 23:42:45 time: 1.5977 data_time: 0.2291 memory: 16201 loss_prob: 0.7350 loss_thr: 0.4645 loss_db: 0.1233 loss: 1.3228 2022/08/30 06:30:04 - mmengine - INFO - Epoch(train) [274][15/63] lr: 5.5477e-03 eta: 23:42:45 time: 1.4694 data_time: 0.0406 memory: 16201 loss_prob: 0.8217 loss_thr: 0.4855 loss_db: 0.1412 loss: 1.4483 2022/08/30 06:30:10 - mmengine - INFO - Epoch(train) [274][20/63] lr: 5.5477e-03 eta: 23:42:29 time: 1.4185 data_time: 0.0342 memory: 16201 loss_prob: 0.8161 loss_thr: 0.4774 loss_db: 0.1384 loss: 1.4319 2022/08/30 06:30:17 - mmengine - INFO - Epoch(train) [274][25/63] lr: 5.5477e-03 eta: 23:42:29 time: 1.3302 data_time: 0.0362 memory: 16201 loss_prob: 0.7466 loss_thr: 0.4559 loss_db: 0.1258 loss: 1.3283 2022/08/30 06:30:23 - mmengine - INFO - Epoch(train) [274][30/63] lr: 5.5477e-03 eta: 23:42:09 time: 1.3278 data_time: 0.0359 memory: 16201 loss_prob: 0.7676 loss_thr: 0.4507 loss_db: 0.1272 loss: 1.3454 2022/08/30 06:30:30 - mmengine - INFO - Epoch(train) [274][35/63] lr: 5.5477e-03 eta: 23:42:09 time: 1.2900 data_time: 0.0369 memory: 16201 loss_prob: 0.7772 loss_thr: 0.4541 loss_db: 0.1291 loss: 1.3605 2022/08/30 06:30:36 - mmengine - INFO - Epoch(train) [274][40/63] lr: 5.5477e-03 eta: 23:41:50 time: 1.3074 data_time: 0.0353 memory: 16201 loss_prob: 0.7698 loss_thr: 0.4727 loss_db: 0.1298 loss: 1.3723 2022/08/30 06:30:44 - mmengine - INFO - Epoch(train) [274][45/63] lr: 5.5477e-03 eta: 23:41:50 time: 1.3893 data_time: 0.0317 memory: 16201 loss_prob: 0.7396 loss_thr: 0.4696 loss_db: 0.1239 loss: 1.3331 2022/08/30 06:30:51 - mmengine - INFO - Epoch(train) [274][50/63] lr: 5.5477e-03 eta: 23:41:33 time: 1.4133 data_time: 0.0416 memory: 16201 loss_prob: 0.7133 loss_thr: 0.4549 loss_db: 0.1241 loss: 1.2923 2022/08/30 06:30:58 - mmengine - INFO - Epoch(train) [274][55/63] lr: 5.5477e-03 eta: 23:41:33 time: 1.3937 data_time: 0.0389 memory: 16201 loss_prob: 0.7048 loss_thr: 0.4462 loss_db: 0.1242 loss: 1.2752 2022/08/30 06:31:05 - mmengine - INFO - Epoch(train) [274][60/63] lr: 5.5477e-03 eta: 23:41:17 time: 1.3995 data_time: 0.0298 memory: 16201 loss_prob: 0.6737 loss_thr: 0.4400 loss_db: 0.1158 loss: 1.2295 2022/08/30 06:31:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:31:17 - mmengine - INFO - Epoch(train) [275][5/63] lr: 5.5423e-03 eta: 23:41:17 time: 1.4962 data_time: 0.2443 memory: 16201 loss_prob: 0.7178 loss_thr: 0.4587 loss_db: 0.1254 loss: 1.3019 2022/08/30 06:31:23 - mmengine - INFO - Epoch(train) [275][10/63] lr: 5.5423e-03 eta: 23:40:46 time: 1.5560 data_time: 0.2596 memory: 16201 loss_prob: 0.6851 loss_thr: 0.4427 loss_db: 0.1176 loss: 1.2454 2022/08/30 06:31:30 - mmengine - INFO - Epoch(train) [275][15/63] lr: 5.5423e-03 eta: 23:40:46 time: 1.2795 data_time: 0.0336 memory: 16201 loss_prob: 0.6456 loss_thr: 0.4275 loss_db: 0.1085 loss: 1.1815 2022/08/30 06:31:37 - mmengine - INFO - Epoch(train) [275][20/63] lr: 5.5423e-03 eta: 23:40:28 time: 1.3698 data_time: 0.0338 memory: 16201 loss_prob: 0.6791 loss_thr: 0.4478 loss_db: 0.1143 loss: 1.2413 2022/08/30 06:31:42 - mmengine - INFO - Epoch(train) [275][25/63] lr: 5.5423e-03 eta: 23:40:28 time: 1.2923 data_time: 0.0362 memory: 16201 loss_prob: 0.6854 loss_thr: 0.4472 loss_db: 0.1176 loss: 1.2501 2022/08/30 06:31:49 - mmengine - INFO - Epoch(train) [275][30/63] lr: 5.5423e-03 eta: 23:40:05 time: 1.1909 data_time: 0.0300 memory: 16201 loss_prob: 0.7304 loss_thr: 0.4685 loss_db: 0.1234 loss: 1.3223 2022/08/30 06:31:55 - mmengine - INFO - Epoch(train) [275][35/63] lr: 5.5423e-03 eta: 23:40:05 time: 1.2700 data_time: 0.0360 memory: 16201 loss_prob: 0.7466 loss_thr: 0.4670 loss_db: 0.1222 loss: 1.3359 2022/08/30 06:32:02 - mmengine - INFO - Epoch(train) [275][40/63] lr: 5.5423e-03 eta: 23:39:45 time: 1.3264 data_time: 0.0349 memory: 16201 loss_prob: 0.6718 loss_thr: 0.4304 loss_db: 0.1131 loss: 1.2153 2022/08/30 06:32:09 - mmengine - INFO - Epoch(train) [275][45/63] lr: 5.5423e-03 eta: 23:39:45 time: 1.3327 data_time: 0.0347 memory: 16201 loss_prob: 0.6873 loss_thr: 0.4410 loss_db: 0.1195 loss: 1.2477 2022/08/30 06:32:15 - mmengine - INFO - Epoch(train) [275][50/63] lr: 5.5423e-03 eta: 23:39:27 time: 1.3484 data_time: 0.0405 memory: 16201 loss_prob: 0.7189 loss_thr: 0.4556 loss_db: 0.1213 loss: 1.2959 2022/08/30 06:32:22 - mmengine - INFO - Epoch(train) [275][55/63] lr: 5.5423e-03 eta: 23:39:27 time: 1.3257 data_time: 0.0281 memory: 16201 loss_prob: 0.6867 loss_thr: 0.4340 loss_db: 0.1160 loss: 1.2367 2022/08/30 06:32:28 - mmengine - INFO - Epoch(train) [275][60/63] lr: 5.5423e-03 eta: 23:39:07 time: 1.2929 data_time: 0.0300 memory: 16201 loss_prob: 0.6855 loss_thr: 0.4425 loss_db: 0.1173 loss: 1.2453 2022/08/30 06:32:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:32:41 - mmengine - INFO - Epoch(train) [276][5/63] lr: 5.5369e-03 eta: 23:39:07 time: 1.4987 data_time: 0.2337 memory: 16201 loss_prob: 0.7249 loss_thr: 0.4559 loss_db: 0.1223 loss: 1.3031 2022/08/30 06:32:47 - mmengine - INFO - Epoch(train) [276][10/63] lr: 5.5369e-03 eta: 23:38:35 time: 1.5182 data_time: 0.2491 memory: 16201 loss_prob: 0.6668 loss_thr: 0.4265 loss_db: 0.1139 loss: 1.2072 2022/08/30 06:32:54 - mmengine - INFO - Epoch(train) [276][15/63] lr: 5.5369e-03 eta: 23:38:35 time: 1.2990 data_time: 0.0310 memory: 16201 loss_prob: 0.6521 loss_thr: 0.4204 loss_db: 0.1116 loss: 1.1841 2022/08/30 06:33:00 - mmengine - INFO - Epoch(train) [276][20/63] lr: 5.5369e-03 eta: 23:38:15 time: 1.2912 data_time: 0.0281 memory: 16201 loss_prob: 0.6942 loss_thr: 0.4531 loss_db: 0.1185 loss: 1.2658 2022/08/30 06:33:07 - mmengine - INFO - Epoch(train) [276][25/63] lr: 5.5369e-03 eta: 23:38:15 time: 1.2826 data_time: 0.0425 memory: 16201 loss_prob: 0.6953 loss_thr: 0.4573 loss_db: 0.1191 loss: 1.2717 2022/08/30 06:33:14 - mmengine - INFO - Epoch(train) [276][30/63] lr: 5.5369e-03 eta: 23:37:57 time: 1.3581 data_time: 0.0298 memory: 16201 loss_prob: 0.6633 loss_thr: 0.4382 loss_db: 0.1141 loss: 1.2156 2022/08/30 06:33:20 - mmengine - INFO - Epoch(train) [276][35/63] lr: 5.5369e-03 eta: 23:37:57 time: 1.3800 data_time: 0.0306 memory: 16201 loss_prob: 0.6935 loss_thr: 0.4531 loss_db: 0.1179 loss: 1.2645 2022/08/30 06:33:27 - mmengine - INFO - Epoch(train) [276][40/63] lr: 5.5369e-03 eta: 23:37:37 time: 1.3199 data_time: 0.0337 memory: 16201 loss_prob: 0.7556 loss_thr: 0.4662 loss_db: 0.1283 loss: 1.3500 2022/08/30 06:33:34 - mmengine - INFO - Epoch(train) [276][45/63] lr: 5.5369e-03 eta: 23:37:37 time: 1.3388 data_time: 0.0351 memory: 16201 loss_prob: 0.7567 loss_thr: 0.4550 loss_db: 0.1271 loss: 1.3387 2022/08/30 06:33:41 - mmengine - INFO - Epoch(train) [276][50/63] lr: 5.5369e-03 eta: 23:37:22 time: 1.4306 data_time: 0.0485 memory: 16201 loss_prob: 0.7919 loss_thr: 0.4721 loss_db: 0.1296 loss: 1.3937 2022/08/30 06:33:48 - mmengine - INFO - Epoch(train) [276][55/63] lr: 5.5369e-03 eta: 23:37:22 time: 1.4491 data_time: 0.0478 memory: 16201 loss_prob: 0.7254 loss_thr: 0.4638 loss_db: 0.1219 loss: 1.3111 2022/08/30 06:33:55 - mmengine - INFO - Epoch(train) [276][60/63] lr: 5.5369e-03 eta: 23:37:02 time: 1.3245 data_time: 0.0466 memory: 16201 loss_prob: 0.7050 loss_thr: 0.4559 loss_db: 0.1229 loss: 1.2838 2022/08/30 06:33:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:34:06 - mmengine - INFO - Epoch(train) [277][5/63] lr: 5.5315e-03 eta: 23:37:02 time: 1.4251 data_time: 0.2271 memory: 16201 loss_prob: 0.7759 loss_thr: 0.4630 loss_db: 0.1297 loss: 1.3686 2022/08/30 06:34:13 - mmengine - INFO - Epoch(train) [277][10/63] lr: 5.5315e-03 eta: 23:36:31 time: 1.5132 data_time: 0.2461 memory: 16201 loss_prob: 0.7309 loss_thr: 0.4512 loss_db: 0.1217 loss: 1.3038 2022/08/30 06:34:20 - mmengine - INFO - Epoch(train) [277][15/63] lr: 5.5315e-03 eta: 23:36:31 time: 1.3987 data_time: 0.0343 memory: 16201 loss_prob: 0.7294 loss_thr: 0.4513 loss_db: 0.1252 loss: 1.3060 2022/08/30 06:34:28 - mmengine - INFO - Epoch(train) [277][20/63] lr: 5.5315e-03 eta: 23:36:16 time: 1.4619 data_time: 0.0327 memory: 16201 loss_prob: 0.7205 loss_thr: 0.4521 loss_db: 0.1248 loss: 1.2974 2022/08/30 06:34:35 - mmengine - INFO - Epoch(train) [277][25/63] lr: 5.5315e-03 eta: 23:36:16 time: 1.4397 data_time: 0.0425 memory: 16201 loss_prob: 0.7166 loss_thr: 0.4520 loss_db: 0.1204 loss: 1.2890 2022/08/30 06:34:41 - mmengine - INFO - Epoch(train) [277][30/63] lr: 5.5315e-03 eta: 23:35:57 time: 1.3371 data_time: 0.0416 memory: 16201 loss_prob: 0.7138 loss_thr: 0.4501 loss_db: 0.1195 loss: 1.2835 2022/08/30 06:34:48 - mmengine - INFO - Epoch(train) [277][35/63] lr: 5.5315e-03 eta: 23:35:57 time: 1.3141 data_time: 0.0394 memory: 16201 loss_prob: 0.7124 loss_thr: 0.4500 loss_db: 0.1237 loss: 1.2860 2022/08/30 06:34:54 - mmengine - INFO - Epoch(train) [277][40/63] lr: 5.5315e-03 eta: 23:35:38 time: 1.3051 data_time: 0.0319 memory: 16201 loss_prob: 0.7011 loss_thr: 0.4394 loss_db: 0.1251 loss: 1.2656 2022/08/30 06:35:01 - mmengine - INFO - Epoch(train) [277][45/63] lr: 5.5315e-03 eta: 23:35:38 time: 1.3086 data_time: 0.0303 memory: 16201 loss_prob: 0.7316 loss_thr: 0.4578 loss_db: 0.1260 loss: 1.3154 2022/08/30 06:35:08 - mmengine - INFO - Epoch(train) [277][50/63] lr: 5.5315e-03 eta: 23:35:20 time: 1.3740 data_time: 0.0402 memory: 16201 loss_prob: 0.7794 loss_thr: 0.4673 loss_db: 0.1333 loss: 1.3800 2022/08/30 06:35:14 - mmengine - INFO - Epoch(train) [277][55/63] lr: 5.5315e-03 eta: 23:35:20 time: 1.3354 data_time: 0.0355 memory: 16201 loss_prob: 0.7244 loss_thr: 0.4416 loss_db: 0.1251 loss: 1.2911 2022/08/30 06:35:21 - mmengine - INFO - Epoch(train) [277][60/63] lr: 5.5315e-03 eta: 23:34:59 time: 1.2768 data_time: 0.0358 memory: 16201 loss_prob: 0.6818 loss_thr: 0.4400 loss_db: 0.1142 loss: 1.2360 2022/08/30 06:35:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:35:33 - mmengine - INFO - Epoch(train) [278][5/63] lr: 5.5261e-03 eta: 23:34:59 time: 1.4986 data_time: 0.2394 memory: 16201 loss_prob: 0.6771 loss_thr: 0.4432 loss_db: 0.1169 loss: 1.2372 2022/08/30 06:35:40 - mmengine - INFO - Epoch(train) [278][10/63] lr: 5.5261e-03 eta: 23:34:31 time: 1.6106 data_time: 0.2543 memory: 16201 loss_prob: 0.5819 loss_thr: 0.3997 loss_db: 0.1015 loss: 1.0831 2022/08/30 06:35:47 - mmengine - INFO - Epoch(train) [278][15/63] lr: 5.5261e-03 eta: 23:34:31 time: 1.3459 data_time: 0.0308 memory: 16201 loss_prob: 0.5616 loss_thr: 0.3813 loss_db: 0.0974 loss: 1.0403 2022/08/30 06:35:53 - mmengine - INFO - Epoch(train) [278][20/63] lr: 5.5261e-03 eta: 23:34:10 time: 1.2791 data_time: 0.0362 memory: 16201 loss_prob: 0.6882 loss_thr: 0.4382 loss_db: 0.1191 loss: 1.2455 2022/08/30 06:35:59 - mmengine - INFO - Epoch(train) [278][25/63] lr: 5.5261e-03 eta: 23:34:10 time: 1.2435 data_time: 0.0376 memory: 16201 loss_prob: 0.7077 loss_thr: 0.4567 loss_db: 0.1215 loss: 1.2859 2022/08/30 06:36:06 - mmengine - INFO - Epoch(train) [278][30/63] lr: 5.5261e-03 eta: 23:33:51 time: 1.3205 data_time: 0.0323 memory: 16201 loss_prob: 0.7295 loss_thr: 0.4719 loss_db: 0.1194 loss: 1.3209 2022/08/30 06:36:13 - mmengine - INFO - Epoch(train) [278][35/63] lr: 5.5261e-03 eta: 23:33:51 time: 1.3442 data_time: 0.0439 memory: 16201 loss_prob: 0.7579 loss_thr: 0.4623 loss_db: 0.1269 loss: 1.3472 2022/08/30 06:36:19 - mmengine - INFO - Epoch(train) [278][40/63] lr: 5.5261e-03 eta: 23:33:31 time: 1.2999 data_time: 0.0305 memory: 16201 loss_prob: 0.7004 loss_thr: 0.4369 loss_db: 0.1215 loss: 1.2589 2022/08/30 06:36:26 - mmengine - INFO - Epoch(train) [278][45/63] lr: 5.5261e-03 eta: 23:33:31 time: 1.2985 data_time: 0.0321 memory: 16201 loss_prob: 0.6870 loss_thr: 0.4479 loss_db: 0.1164 loss: 1.2514 2022/08/30 06:36:33 - mmengine - INFO - Epoch(train) [278][50/63] lr: 5.5261e-03 eta: 23:33:15 time: 1.4183 data_time: 0.0452 memory: 16201 loss_prob: 0.7129 loss_thr: 0.4526 loss_db: 0.1234 loss: 1.2889 2022/08/30 06:36:39 - mmengine - INFO - Epoch(train) [278][55/63] lr: 5.5261e-03 eta: 23:33:15 time: 1.3969 data_time: 0.0326 memory: 16201 loss_prob: 0.7455 loss_thr: 0.4635 loss_db: 0.1297 loss: 1.3387 2022/08/30 06:36:46 - mmengine - INFO - Epoch(train) [278][60/63] lr: 5.5261e-03 eta: 23:32:55 time: 1.2894 data_time: 0.0291 memory: 16201 loss_prob: 0.7196 loss_thr: 0.4495 loss_db: 0.1207 loss: 1.2898 2022/08/30 06:36:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:36:59 - mmengine - INFO - Epoch(train) [279][5/63] lr: 5.5207e-03 eta: 23:32:55 time: 1.5399 data_time: 0.2532 memory: 16201 loss_prob: 0.6894 loss_thr: 0.4450 loss_db: 0.1186 loss: 1.2530 2022/08/30 06:37:05 - mmengine - INFO - Epoch(train) [279][10/63] lr: 5.5207e-03 eta: 23:32:25 time: 1.5614 data_time: 0.2737 memory: 16201 loss_prob: 0.7057 loss_thr: 0.4363 loss_db: 0.1214 loss: 1.2635 2022/08/30 06:37:13 - mmengine - INFO - Epoch(train) [279][15/63] lr: 5.5207e-03 eta: 23:32:25 time: 1.3347 data_time: 0.0307 memory: 16201 loss_prob: 0.7194 loss_thr: 0.4453 loss_db: 0.1238 loss: 1.2885 2022/08/30 06:37:20 - mmengine - INFO - Epoch(train) [279][20/63] lr: 5.5207e-03 eta: 23:32:10 time: 1.4494 data_time: 0.0338 memory: 16201 loss_prob: 0.8933 loss_thr: 0.4655 loss_db: 0.1390 loss: 1.4977 2022/08/30 06:37:27 - mmengine - INFO - Epoch(train) [279][25/63] lr: 5.5207e-03 eta: 23:32:10 time: 1.4297 data_time: 0.0509 memory: 16201 loss_prob: 0.9399 loss_thr: 0.4837 loss_db: 0.1437 loss: 1.5673 2022/08/30 06:37:34 - mmengine - INFO - Epoch(train) [279][30/63] lr: 5.5207e-03 eta: 23:31:53 time: 1.4044 data_time: 0.0344 memory: 16201 loss_prob: 0.8292 loss_thr: 0.4608 loss_db: 0.1384 loss: 1.4284 2022/08/30 06:37:40 - mmengine - INFO - Epoch(train) [279][35/63] lr: 5.5207e-03 eta: 23:31:53 time: 1.3157 data_time: 0.0277 memory: 16201 loss_prob: 0.8359 loss_thr: 0.4663 loss_db: 0.1427 loss: 1.4449 2022/08/30 06:37:46 - mmengine - INFO - Epoch(train) [279][40/63] lr: 5.5207e-03 eta: 23:31:30 time: 1.2041 data_time: 0.0294 memory: 16201 loss_prob: 0.7112 loss_thr: 0.4536 loss_db: 0.1207 loss: 1.2855 2022/08/30 06:37:53 - mmengine - INFO - Epoch(train) [279][45/63] lr: 5.5207e-03 eta: 23:31:30 time: 1.2955 data_time: 0.0321 memory: 16201 loss_prob: 0.7205 loss_thr: 0.4490 loss_db: 0.1191 loss: 1.2886 2022/08/30 06:38:00 - mmengine - INFO - Epoch(train) [279][50/63] lr: 5.5207e-03 eta: 23:31:13 time: 1.3696 data_time: 0.0450 memory: 16201 loss_prob: 0.8079 loss_thr: 0.4657 loss_db: 0.1346 loss: 1.4082 2022/08/30 06:38:06 - mmengine - INFO - Epoch(train) [279][55/63] lr: 5.5207e-03 eta: 23:31:13 time: 1.3180 data_time: 0.0301 memory: 16201 loss_prob: 0.7742 loss_thr: 0.4621 loss_db: 0.1324 loss: 1.3687 2022/08/30 06:38:13 - mmengine - INFO - Epoch(train) [279][60/63] lr: 5.5207e-03 eta: 23:30:55 time: 1.3638 data_time: 0.0279 memory: 16201 loss_prob: 0.7583 loss_thr: 0.4714 loss_db: 0.1286 loss: 1.3583 2022/08/30 06:38:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:38:26 - mmengine - INFO - Epoch(train) [280][5/63] lr: 5.5153e-03 eta: 23:30:55 time: 1.4901 data_time: 0.2276 memory: 16201 loss_prob: 0.8889 loss_thr: 0.5043 loss_db: 0.1424 loss: 1.5356 2022/08/30 06:38:32 - mmengine - INFO - Epoch(train) [280][10/63] lr: 5.5153e-03 eta: 23:30:24 time: 1.5291 data_time: 0.2427 memory: 16201 loss_prob: 0.8737 loss_thr: 0.4782 loss_db: 0.1445 loss: 1.4965 2022/08/30 06:38:38 - mmengine - INFO - Epoch(train) [280][15/63] lr: 5.5153e-03 eta: 23:30:24 time: 1.2794 data_time: 0.0359 memory: 16201 loss_prob: 0.8081 loss_thr: 0.4626 loss_db: 0.1364 loss: 1.4071 2022/08/30 06:38:46 - mmengine - INFO - Epoch(train) [280][20/63] lr: 5.5153e-03 eta: 23:30:08 time: 1.4109 data_time: 0.0388 memory: 16201 loss_prob: 0.7432 loss_thr: 0.4578 loss_db: 0.1222 loss: 1.3233 2022/08/30 06:38:52 - mmengine - INFO - Epoch(train) [280][25/63] lr: 5.5153e-03 eta: 23:30:08 time: 1.3993 data_time: 0.0373 memory: 16201 loss_prob: 0.7565 loss_thr: 0.4577 loss_db: 0.1286 loss: 1.3428 2022/08/30 06:38:59 - mmengine - INFO - Epoch(train) [280][30/63] lr: 5.5153e-03 eta: 23:29:49 time: 1.3219 data_time: 0.0355 memory: 16201 loss_prob: 0.8127 loss_thr: 0.4777 loss_db: 0.1385 loss: 1.4289 2022/08/30 06:39:06 - mmengine - INFO - Epoch(train) [280][35/63] lr: 5.5153e-03 eta: 23:29:49 time: 1.3362 data_time: 0.0356 memory: 16201 loss_prob: 0.7881 loss_thr: 0.4751 loss_db: 0.1330 loss: 1.3962 2022/08/30 06:39:12 - mmengine - INFO - Epoch(train) [280][40/63] lr: 5.5153e-03 eta: 23:29:29 time: 1.2908 data_time: 0.0315 memory: 16201 loss_prob: 0.7065 loss_thr: 0.4336 loss_db: 0.1182 loss: 1.2583 2022/08/30 06:39:19 - mmengine - INFO - Epoch(train) [280][45/63] lr: 5.5153e-03 eta: 23:29:29 time: 1.3119 data_time: 0.0367 memory: 16201 loss_prob: 0.6726 loss_thr: 0.4186 loss_db: 0.1127 loss: 1.2040 2022/08/30 06:39:26 - mmengine - INFO - Epoch(train) [280][50/63] lr: 5.5153e-03 eta: 23:29:10 time: 1.3385 data_time: 0.0354 memory: 16201 loss_prob: 0.7365 loss_thr: 0.4612 loss_db: 0.1251 loss: 1.3228 2022/08/30 06:39:33 - mmengine - INFO - Epoch(train) [280][55/63] lr: 5.5153e-03 eta: 23:29:10 time: 1.3757 data_time: 0.0405 memory: 16201 loss_prob: 0.8366 loss_thr: 0.4773 loss_db: 0.1377 loss: 1.4516 2022/08/30 06:39:40 - mmengine - INFO - Epoch(train) [280][60/63] lr: 5.5153e-03 eta: 23:28:54 time: 1.4156 data_time: 0.0443 memory: 16201 loss_prob: 0.7681 loss_thr: 0.4405 loss_db: 0.1233 loss: 1.3318 2022/08/30 06:39:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:39:43 - mmengine - INFO - Saving checkpoint at 280 epochs 2022/08/30 06:39:51 - mmengine - INFO - Epoch(val) [280][5/32] eta: 23:28:54 time: 0.6934 data_time: 0.1408 memory: 16201 2022/08/30 06:39:55 - mmengine - INFO - Epoch(val) [280][10/32] eta: 0:00:17 time: 0.7972 data_time: 0.1910 memory: 15734 2022/08/30 06:39:58 - mmengine - INFO - Epoch(val) [280][15/32] eta: 0:00:17 time: 0.6543 data_time: 0.0666 memory: 15734 2022/08/30 06:40:02 - mmengine - INFO - Epoch(val) [280][20/32] eta: 0:00:09 time: 0.7549 data_time: 0.1368 memory: 15734 2022/08/30 06:40:06 - mmengine - INFO - Epoch(val) [280][25/32] eta: 0:00:09 time: 0.7814 data_time: 0.1400 memory: 15734 2022/08/30 06:40:09 - mmengine - INFO - Epoch(val) [280][30/32] eta: 0:00:01 time: 0.6363 data_time: 0.0303 memory: 15734 2022/08/30 06:40:10 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 06:40:10 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8483, precision: 0.7658, hmean: 0.8049 2022/08/30 06:40:10 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8479, precision: 0.8256, hmean: 0.8366 2022/08/30 06:40:10 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8416, precision: 0.8535, hmean: 0.8475 2022/08/30 06:40:10 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8296, precision: 0.8800, hmean: 0.8540 2022/08/30 06:40:10 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7939, precision: 0.9126, hmean: 0.8491 2022/08/30 06:40:10 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6225, precision: 0.9500, hmean: 0.7522 2022/08/30 06:40:10 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0221, precision: 1.0000, hmean: 0.0433 2022/08/30 06:40:10 - mmengine - INFO - Epoch(val) [280][32/32] icdar/precision: 0.8800 icdar/recall: 0.8296 icdar/hmean: 0.8540 2022/08/30 06:40:19 - mmengine - INFO - Epoch(train) [281][5/63] lr: 5.5099e-03 eta: 0:00:01 time: 1.5302 data_time: 0.2328 memory: 16201 loss_prob: 0.7206 loss_thr: 0.4503 loss_db: 0.1196 loss: 1.2906 2022/08/30 06:40:25 - mmengine - INFO - Epoch(train) [281][10/63] lr: 5.5099e-03 eta: 23:28:25 time: 1.5788 data_time: 0.2373 memory: 16201 loss_prob: 0.6335 loss_thr: 0.4354 loss_db: 0.1104 loss: 1.1793 2022/08/30 06:40:33 - mmengine - INFO - Epoch(train) [281][15/63] lr: 5.5099e-03 eta: 23:28:25 time: 1.3919 data_time: 0.0428 memory: 16201 loss_prob: 0.6828 loss_thr: 0.4419 loss_db: 0.1176 loss: 1.2423 2022/08/30 06:40:40 - mmengine - INFO - Epoch(train) [281][20/63] lr: 5.5099e-03 eta: 23:28:09 time: 1.4159 data_time: 0.0410 memory: 16201 loss_prob: 0.7866 loss_thr: 0.4371 loss_db: 0.1257 loss: 1.3493 2022/08/30 06:40:46 - mmengine - INFO - Epoch(train) [281][25/63] lr: 5.5099e-03 eta: 23:28:09 time: 1.3412 data_time: 0.0292 memory: 16201 loss_prob: 0.7211 loss_thr: 0.4266 loss_db: 0.1138 loss: 1.2614 2022/08/30 06:40:53 - mmengine - INFO - Epoch(train) [281][30/63] lr: 5.5099e-03 eta: 23:27:51 time: 1.3561 data_time: 0.0318 memory: 16201 loss_prob: 0.6696 loss_thr: 0.4364 loss_db: 0.1145 loss: 1.2205 2022/08/30 06:40:59 - mmengine - INFO - Epoch(train) [281][35/63] lr: 5.5099e-03 eta: 23:27:51 time: 1.3231 data_time: 0.0431 memory: 16201 loss_prob: 0.7506 loss_thr: 0.4660 loss_db: 0.1262 loss: 1.3428 2022/08/30 06:41:06 - mmengine - INFO - Epoch(train) [281][40/63] lr: 5.5099e-03 eta: 23:27:29 time: 1.2486 data_time: 0.0319 memory: 16201 loss_prob: 0.7790 loss_thr: 0.4734 loss_db: 0.1297 loss: 1.3822 2022/08/30 06:41:13 - mmengine - INFO - Epoch(train) [281][45/63] lr: 5.5099e-03 eta: 23:27:29 time: 1.3370 data_time: 0.0303 memory: 16201 loss_prob: 0.7787 loss_thr: 0.4685 loss_db: 0.1290 loss: 1.3761 2022/08/30 06:41:20 - mmengine - INFO - Epoch(train) [281][50/63] lr: 5.5099e-03 eta: 23:27:13 time: 1.4006 data_time: 0.0404 memory: 16201 loss_prob: 0.7335 loss_thr: 0.4496 loss_db: 0.1195 loss: 1.3025 2022/08/30 06:41:26 - mmengine - INFO - Epoch(train) [281][55/63] lr: 5.5099e-03 eta: 23:27:13 time: 1.3105 data_time: 0.0310 memory: 16201 loss_prob: 0.6911 loss_thr: 0.4390 loss_db: 0.1162 loss: 1.2462 2022/08/30 06:41:32 - mmengine - INFO - Epoch(train) [281][60/63] lr: 5.5099e-03 eta: 23:26:52 time: 1.2745 data_time: 0.0332 memory: 16201 loss_prob: 0.7033 loss_thr: 0.4422 loss_db: 0.1200 loss: 1.2655 2022/08/30 06:41:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:41:45 - mmengine - INFO - Epoch(train) [282][5/63] lr: 5.5045e-03 eta: 23:26:52 time: 1.4693 data_time: 0.2383 memory: 16201 loss_prob: 0.6999 loss_thr: 0.4555 loss_db: 0.1162 loss: 1.2716 2022/08/30 06:41:52 - mmengine - INFO - Epoch(train) [282][10/63] lr: 5.5045e-03 eta: 23:26:23 time: 1.5905 data_time: 0.2551 memory: 16201 loss_prob: 0.6501 loss_thr: 0.4170 loss_db: 0.1099 loss: 1.1770 2022/08/30 06:41:58 - mmengine - INFO - Epoch(train) [282][15/63] lr: 5.5045e-03 eta: 23:26:23 time: 1.3079 data_time: 0.0403 memory: 16201 loss_prob: 0.6905 loss_thr: 0.4368 loss_db: 0.1195 loss: 1.2467 2022/08/30 06:42:04 - mmengine - INFO - Epoch(train) [282][20/63] lr: 5.5045e-03 eta: 23:26:02 time: 1.2350 data_time: 0.0312 memory: 16201 loss_prob: 0.6985 loss_thr: 0.4532 loss_db: 0.1177 loss: 1.2694 2022/08/30 06:42:10 - mmengine - INFO - Epoch(train) [282][25/63] lr: 5.5045e-03 eta: 23:26:02 time: 1.2621 data_time: 0.0409 memory: 16201 loss_prob: 0.6875 loss_thr: 0.4611 loss_db: 0.1165 loss: 1.2651 2022/08/30 06:42:18 - mmengine - INFO - Epoch(train) [282][30/63] lr: 5.5045e-03 eta: 23:25:44 time: 1.3577 data_time: 0.0354 memory: 16201 loss_prob: 0.6425 loss_thr: 0.4423 loss_db: 0.1120 loss: 1.1967 2022/08/30 06:42:24 - mmengine - INFO - Epoch(train) [282][35/63] lr: 5.5045e-03 eta: 23:25:44 time: 1.3761 data_time: 0.0341 memory: 16201 loss_prob: 0.6301 loss_thr: 0.4096 loss_db: 0.1089 loss: 1.1486 2022/08/30 06:42:30 - mmengine - INFO - Epoch(train) [282][40/63] lr: 5.5045e-03 eta: 23:25:23 time: 1.2822 data_time: 0.0346 memory: 16201 loss_prob: 0.7181 loss_thr: 0.4456 loss_db: 0.1224 loss: 1.2861 2022/08/30 06:42:37 - mmengine - INFO - Epoch(train) [282][45/63] lr: 5.5045e-03 eta: 23:25:23 time: 1.3155 data_time: 0.0318 memory: 16201 loss_prob: 0.7624 loss_thr: 0.4651 loss_db: 0.1288 loss: 1.3564 2022/08/30 06:42:44 - mmengine - INFO - Epoch(train) [282][50/63] lr: 5.5045e-03 eta: 23:25:05 time: 1.3333 data_time: 0.0410 memory: 16201 loss_prob: 0.7344 loss_thr: 0.4476 loss_db: 0.1234 loss: 1.3054 2022/08/30 06:42:50 - mmengine - INFO - Epoch(train) [282][55/63] lr: 5.5045e-03 eta: 23:25:05 time: 1.2733 data_time: 0.0370 memory: 16201 loss_prob: 0.7322 loss_thr: 0.4563 loss_db: 0.1233 loss: 1.3119 2022/08/30 06:42:57 - mmengine - INFO - Epoch(train) [282][60/63] lr: 5.5045e-03 eta: 23:24:45 time: 1.2939 data_time: 0.0417 memory: 16201 loss_prob: 0.7322 loss_thr: 0.4541 loss_db: 0.1235 loss: 1.3098 2022/08/30 06:43:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:43:09 - mmengine - INFO - Epoch(train) [283][5/63] lr: 5.4991e-03 eta: 23:24:45 time: 1.4624 data_time: 0.2361 memory: 16201 loss_prob: 0.8108 loss_thr: 0.5200 loss_db: 0.1364 loss: 1.4672 2022/08/30 06:43:15 - mmengine - INFO - Epoch(train) [283][10/63] lr: 5.4991e-03 eta: 23:24:16 time: 1.5737 data_time: 0.2565 memory: 16201 loss_prob: 0.8255 loss_thr: 0.5094 loss_db: 0.1400 loss: 1.4749 2022/08/30 06:43:22 - mmengine - INFO - Epoch(train) [283][15/63] lr: 5.4991e-03 eta: 23:24:16 time: 1.2850 data_time: 0.0384 memory: 16201 loss_prob: 0.7820 loss_thr: 0.4783 loss_db: 0.1352 loss: 1.3955 2022/08/30 06:43:28 - mmengine - INFO - Epoch(train) [283][20/63] lr: 5.4991e-03 eta: 23:23:54 time: 1.2439 data_time: 0.0319 memory: 16201 loss_prob: 0.7926 loss_thr: 0.4549 loss_db: 0.1319 loss: 1.3794 2022/08/30 06:43:35 - mmengine - INFO - Epoch(train) [283][25/63] lr: 5.4991e-03 eta: 23:23:54 time: 1.2862 data_time: 0.0444 memory: 16201 loss_prob: 0.8271 loss_thr: 0.4568 loss_db: 0.1396 loss: 1.4236 2022/08/30 06:43:41 - mmengine - INFO - Epoch(train) [283][30/63] lr: 5.4991e-03 eta: 23:23:33 time: 1.2684 data_time: 0.0307 memory: 16201 loss_prob: 0.7479 loss_thr: 0.4498 loss_db: 0.1324 loss: 1.3301 2022/08/30 06:43:47 - mmengine - INFO - Epoch(train) [283][35/63] lr: 5.4991e-03 eta: 23:23:33 time: 1.2935 data_time: 0.0280 memory: 16201 loss_prob: 0.7258 loss_thr: 0.4520 loss_db: 0.1205 loss: 1.2983 2022/08/30 06:43:54 - mmengine - INFO - Epoch(train) [283][40/63] lr: 5.4991e-03 eta: 23:23:14 time: 1.2970 data_time: 0.0294 memory: 16201 loss_prob: 0.7268 loss_thr: 0.4429 loss_db: 0.1179 loss: 1.2876 2022/08/30 06:44:00 - mmengine - INFO - Epoch(train) [283][45/63] lr: 5.4991e-03 eta: 23:23:14 time: 1.2302 data_time: 0.0310 memory: 16201 loss_prob: 0.7017 loss_thr: 0.4588 loss_db: 0.1183 loss: 1.2789 2022/08/30 06:44:06 - mmengine - INFO - Epoch(train) [283][50/63] lr: 5.4991e-03 eta: 23:22:53 time: 1.2628 data_time: 0.0441 memory: 16201 loss_prob: 0.7079 loss_thr: 0.4605 loss_db: 0.1231 loss: 1.2914 2022/08/30 06:44:12 - mmengine - INFO - Epoch(train) [283][55/63] lr: 5.4991e-03 eta: 23:22:53 time: 1.2489 data_time: 0.0292 memory: 16201 loss_prob: 0.7252 loss_thr: 0.4666 loss_db: 0.1234 loss: 1.3152 2022/08/30 06:44:19 - mmengine - INFO - Epoch(train) [283][60/63] lr: 5.4991e-03 eta: 23:22:31 time: 1.2491 data_time: 0.0290 memory: 16201 loss_prob: 0.6800 loss_thr: 0.4384 loss_db: 0.1146 loss: 1.2329 2022/08/30 06:44:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:44:30 - mmengine - INFO - Epoch(train) [284][5/63] lr: 5.4937e-03 eta: 23:22:31 time: 1.3890 data_time: 0.2201 memory: 16201 loss_prob: 0.6735 loss_thr: 0.4359 loss_db: 0.1165 loss: 1.2259 2022/08/30 06:44:37 - mmengine - INFO - Epoch(train) [284][10/63] lr: 5.4937e-03 eta: 23:22:01 time: 1.5258 data_time: 0.2303 memory: 16201 loss_prob: 0.7154 loss_thr: 0.4414 loss_db: 0.1218 loss: 1.2786 2022/08/30 06:44:45 - mmengine - INFO - Epoch(train) [284][15/63] lr: 5.4937e-03 eta: 23:22:01 time: 1.4591 data_time: 0.0349 memory: 16201 loss_prob: 0.7051 loss_thr: 0.4442 loss_db: 0.1173 loss: 1.2665 2022/08/30 06:44:51 - mmengine - INFO - Epoch(train) [284][20/63] lr: 5.4937e-03 eta: 23:21:43 time: 1.3721 data_time: 0.0389 memory: 16201 loss_prob: 0.7017 loss_thr: 0.4562 loss_db: 0.1194 loss: 1.2773 2022/08/30 06:44:57 - mmengine - INFO - Epoch(train) [284][25/63] lr: 5.4937e-03 eta: 23:21:43 time: 1.2786 data_time: 0.0326 memory: 16201 loss_prob: 0.7514 loss_thr: 0.4727 loss_db: 0.1286 loss: 1.3526 2022/08/30 06:45:03 - mmengine - INFO - Epoch(train) [284][30/63] lr: 5.4937e-03 eta: 23:21:22 time: 1.2525 data_time: 0.0339 memory: 16201 loss_prob: 0.7177 loss_thr: 0.4562 loss_db: 0.1209 loss: 1.2948 2022/08/30 06:45:10 - mmengine - INFO - Epoch(train) [284][35/63] lr: 5.4937e-03 eta: 23:21:22 time: 1.2679 data_time: 0.0326 memory: 16201 loss_prob: 0.6712 loss_thr: 0.4544 loss_db: 0.1133 loss: 1.2390 2022/08/30 06:45:17 - mmengine - INFO - Epoch(train) [284][40/63] lr: 5.4937e-03 eta: 23:21:04 time: 1.3375 data_time: 0.0307 memory: 16201 loss_prob: 0.7134 loss_thr: 0.4685 loss_db: 0.1206 loss: 1.3026 2022/08/30 06:45:23 - mmengine - INFO - Epoch(train) [284][45/63] lr: 5.4937e-03 eta: 23:21:04 time: 1.2662 data_time: 0.0367 memory: 16201 loss_prob: 0.6953 loss_thr: 0.4527 loss_db: 0.1170 loss: 1.2651 2022/08/30 06:45:29 - mmengine - INFO - Epoch(train) [284][50/63] lr: 5.4937e-03 eta: 23:20:43 time: 1.2736 data_time: 0.0337 memory: 16201 loss_prob: 0.7035 loss_thr: 0.4471 loss_db: 0.1205 loss: 1.2710 2022/08/30 06:45:35 - mmengine - INFO - Epoch(train) [284][55/63] lr: 5.4937e-03 eta: 23:20:43 time: 1.2668 data_time: 0.0357 memory: 16201 loss_prob: 0.6584 loss_thr: 0.4218 loss_db: 0.1137 loss: 1.1940 2022/08/30 06:45:42 - mmengine - INFO - Epoch(train) [284][60/63] lr: 5.4937e-03 eta: 23:20:23 time: 1.2831 data_time: 0.0394 memory: 16201 loss_prob: 0.7087 loss_thr: 0.4367 loss_db: 0.1192 loss: 1.2645 2022/08/30 06:45:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:45:55 - mmengine - INFO - Epoch(train) [285][5/63] lr: 5.4883e-03 eta: 23:20:23 time: 1.5214 data_time: 0.2456 memory: 16201 loss_prob: 0.8671 loss_thr: 0.4379 loss_db: 0.1300 loss: 1.4349 2022/08/30 06:46:02 - mmengine - INFO - Epoch(train) [285][10/63] lr: 5.4883e-03 eta: 23:19:57 time: 1.6748 data_time: 0.2521 memory: 16201 loss_prob: 0.7201 loss_thr: 0.4377 loss_db: 0.1177 loss: 1.2755 2022/08/30 06:46:09 - mmengine - INFO - Epoch(train) [285][15/63] lr: 5.4883e-03 eta: 23:19:57 time: 1.3924 data_time: 0.0350 memory: 16201 loss_prob: 0.7427 loss_thr: 0.4687 loss_db: 0.1239 loss: 1.3353 2022/08/30 06:46:16 - mmengine - INFO - Epoch(train) [285][20/63] lr: 5.4883e-03 eta: 23:19:39 time: 1.3362 data_time: 0.0365 memory: 16201 loss_prob: 0.6841 loss_thr: 0.4389 loss_db: 0.1197 loss: 1.2426 2022/08/30 06:46:23 - mmengine - INFO - Epoch(train) [285][25/63] lr: 5.4883e-03 eta: 23:19:39 time: 1.3803 data_time: 0.0321 memory: 16201 loss_prob: 0.6815 loss_thr: 0.4302 loss_db: 0.1177 loss: 1.2294 2022/08/30 06:46:29 - mmengine - INFO - Epoch(train) [285][30/63] lr: 5.4883e-03 eta: 23:19:21 time: 1.3551 data_time: 0.0313 memory: 16201 loss_prob: 0.6832 loss_thr: 0.4350 loss_db: 0.1146 loss: 1.2327 2022/08/30 06:46:35 - mmengine - INFO - Epoch(train) [285][35/63] lr: 5.4883e-03 eta: 23:19:21 time: 1.2646 data_time: 0.0408 memory: 16201 loss_prob: 0.6428 loss_thr: 0.4357 loss_db: 0.1080 loss: 1.1865 2022/08/30 06:46:42 - mmengine - INFO - Epoch(train) [285][40/63] lr: 5.4883e-03 eta: 23:19:02 time: 1.3093 data_time: 0.0369 memory: 16201 loss_prob: 0.6279 loss_thr: 0.4295 loss_db: 0.1075 loss: 1.1649 2022/08/30 06:46:49 - mmengine - INFO - Epoch(train) [285][45/63] lr: 5.4883e-03 eta: 23:19:02 time: 1.3312 data_time: 0.0473 memory: 16201 loss_prob: 0.7038 loss_thr: 0.4315 loss_db: 0.1184 loss: 1.2538 2022/08/30 06:46:55 - mmengine - INFO - Epoch(train) [285][50/63] lr: 5.4883e-03 eta: 23:18:40 time: 1.2354 data_time: 0.0453 memory: 16201 loss_prob: 0.7710 loss_thr: 0.4708 loss_db: 0.1278 loss: 1.3696 2022/08/30 06:47:01 - mmengine - INFO - Epoch(train) [285][55/63] lr: 5.4883e-03 eta: 23:18:40 time: 1.2438 data_time: 0.0303 memory: 16201 loss_prob: 0.7396 loss_thr: 0.4857 loss_db: 0.1242 loss: 1.3495 2022/08/30 06:47:08 - mmengine - INFO - Epoch(train) [285][60/63] lr: 5.4883e-03 eta: 23:18:22 time: 1.3503 data_time: 0.0431 memory: 16201 loss_prob: 0.7038 loss_thr: 0.4685 loss_db: 0.1196 loss: 1.2919 2022/08/30 06:47:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:47:20 - mmengine - INFO - Epoch(train) [286][5/63] lr: 5.4829e-03 eta: 23:18:22 time: 1.4229 data_time: 0.2157 memory: 16201 loss_prob: 0.6916 loss_thr: 0.4445 loss_db: 0.1152 loss: 1.2513 2022/08/30 06:47:27 - mmengine - INFO - Epoch(train) [286][10/63] lr: 5.4829e-03 eta: 23:17:54 time: 1.5920 data_time: 0.2275 memory: 16201 loss_prob: 0.7064 loss_thr: 0.4438 loss_db: 0.1150 loss: 1.2653 2022/08/30 06:47:34 - mmengine - INFO - Epoch(train) [286][15/63] lr: 5.4829e-03 eta: 23:17:54 time: 1.4194 data_time: 0.0410 memory: 16201 loss_prob: 0.6559 loss_thr: 0.4273 loss_db: 0.1098 loss: 1.1930 2022/08/30 06:47:40 - mmengine - INFO - Epoch(train) [286][20/63] lr: 5.4829e-03 eta: 23:17:36 time: 1.3461 data_time: 0.0381 memory: 16201 loss_prob: 0.6676 loss_thr: 0.4315 loss_db: 0.1157 loss: 1.2148 2022/08/30 06:47:47 - mmengine - INFO - Epoch(train) [286][25/63] lr: 5.4829e-03 eta: 23:17:36 time: 1.3322 data_time: 0.0349 memory: 16201 loss_prob: 0.6404 loss_thr: 0.4228 loss_db: 0.1117 loss: 1.1749 2022/08/30 06:47:54 - mmengine - INFO - Epoch(train) [286][30/63] lr: 5.4829e-03 eta: 23:17:17 time: 1.3302 data_time: 0.0328 memory: 16201 loss_prob: 0.6576 loss_thr: 0.4234 loss_db: 0.1084 loss: 1.1894 2022/08/30 06:48:00 - mmengine - INFO - Epoch(train) [286][35/63] lr: 5.4829e-03 eta: 23:17:17 time: 1.3279 data_time: 0.0322 memory: 16201 loss_prob: 0.7361 loss_thr: 0.4383 loss_db: 0.1213 loss: 1.2957 2022/08/30 06:48:07 - mmengine - INFO - Epoch(train) [286][40/63] lr: 5.4829e-03 eta: 23:16:59 time: 1.3591 data_time: 0.0354 memory: 16201 loss_prob: 0.7881 loss_thr: 0.4608 loss_db: 0.1332 loss: 1.3821 2022/08/30 06:48:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:48:14 - mmengine - INFO - Epoch(train) [286][45/63] lr: 5.4829e-03 eta: 23:16:59 time: 1.3399 data_time: 0.0372 memory: 16201 loss_prob: 0.7532 loss_thr: 0.4596 loss_db: 0.1300 loss: 1.3428 2022/08/30 06:48:20 - mmengine - INFO - Epoch(train) [286][50/63] lr: 5.4829e-03 eta: 23:16:40 time: 1.3008 data_time: 0.0409 memory: 16201 loss_prob: 0.7571 loss_thr: 0.4627 loss_db: 0.1304 loss: 1.3502 2022/08/30 06:48:27 - mmengine - INFO - Epoch(train) [286][55/63] lr: 5.4829e-03 eta: 23:16:40 time: 1.3010 data_time: 0.0385 memory: 16201 loss_prob: 0.8602 loss_thr: 0.4848 loss_db: 0.1387 loss: 1.4836 2022/08/30 06:48:33 - mmengine - INFO - Epoch(train) [286][60/63] lr: 5.4829e-03 eta: 23:16:21 time: 1.3199 data_time: 0.0352 memory: 16201 loss_prob: 0.7997 loss_thr: 0.4678 loss_db: 0.1294 loss: 1.3970 2022/08/30 06:48:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:48:46 - mmengine - INFO - Epoch(train) [287][5/63] lr: 5.4775e-03 eta: 23:16:21 time: 1.5140 data_time: 0.2435 memory: 16201 loss_prob: 0.7086 loss_thr: 0.4452 loss_db: 0.1209 loss: 1.2747 2022/08/30 06:48:53 - mmengine - INFO - Epoch(train) [287][10/63] lr: 5.4775e-03 eta: 23:15:53 time: 1.6124 data_time: 0.2569 memory: 16201 loss_prob: 0.7212 loss_thr: 0.4302 loss_db: 0.1195 loss: 1.2709 2022/08/30 06:48:59 - mmengine - INFO - Epoch(train) [287][15/63] lr: 5.4775e-03 eta: 23:15:53 time: 1.2977 data_time: 0.0328 memory: 16201 loss_prob: 0.7434 loss_thr: 0.4343 loss_db: 0.1235 loss: 1.3012 2022/08/30 06:49:05 - mmengine - INFO - Epoch(train) [287][20/63] lr: 5.4775e-03 eta: 23:15:32 time: 1.2287 data_time: 0.0277 memory: 16201 loss_prob: 0.7465 loss_thr: 0.4592 loss_db: 0.1270 loss: 1.3327 2022/08/30 06:49:11 - mmengine - INFO - Epoch(train) [287][25/63] lr: 5.4775e-03 eta: 23:15:32 time: 1.2165 data_time: 0.0456 memory: 16201 loss_prob: 0.7399 loss_thr: 0.4435 loss_db: 0.1278 loss: 1.3111 2022/08/30 06:49:18 - mmengine - INFO - Epoch(train) [287][30/63] lr: 5.4775e-03 eta: 23:15:12 time: 1.3056 data_time: 0.0345 memory: 16201 loss_prob: 0.7022 loss_thr: 0.4319 loss_db: 0.1187 loss: 1.2529 2022/08/30 06:49:25 - mmengine - INFO - Epoch(train) [287][35/63] lr: 5.4775e-03 eta: 23:15:12 time: 1.4069 data_time: 0.0318 memory: 16201 loss_prob: 0.7786 loss_thr: 0.4807 loss_db: 0.1320 loss: 1.3913 2022/08/30 06:49:32 - mmengine - INFO - Epoch(train) [287][40/63] lr: 5.4775e-03 eta: 23:14:54 time: 1.3444 data_time: 0.0334 memory: 16201 loss_prob: 0.7760 loss_thr: 0.4713 loss_db: 0.1328 loss: 1.3800 2022/08/30 06:49:38 - mmengine - INFO - Epoch(train) [287][45/63] lr: 5.4775e-03 eta: 23:14:54 time: 1.2354 data_time: 0.0291 memory: 16201 loss_prob: 0.6992 loss_thr: 0.4375 loss_db: 0.1207 loss: 1.2575 2022/08/30 06:49:44 - mmengine - INFO - Epoch(train) [287][50/63] lr: 5.4775e-03 eta: 23:14:33 time: 1.2350 data_time: 0.0409 memory: 16201 loss_prob: 0.6236 loss_thr: 0.4042 loss_db: 0.1084 loss: 1.1362 2022/08/30 06:49:51 - mmengine - INFO - Epoch(train) [287][55/63] lr: 5.4775e-03 eta: 23:14:33 time: 1.2963 data_time: 0.0290 memory: 16201 loss_prob: 0.6656 loss_thr: 0.4235 loss_db: 0.1115 loss: 1.2006 2022/08/30 06:49:57 - mmengine - INFO - Epoch(train) [287][60/63] lr: 5.4775e-03 eta: 23:14:14 time: 1.3220 data_time: 0.0321 memory: 16201 loss_prob: 0.7307 loss_thr: 0.4494 loss_db: 0.1215 loss: 1.3017 2022/08/30 06:50:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:50:09 - mmengine - INFO - Epoch(train) [288][5/63] lr: 5.4721e-03 eta: 23:14:14 time: 1.4442 data_time: 0.2446 memory: 16201 loss_prob: 0.6922 loss_thr: 0.4355 loss_db: 0.1176 loss: 1.2453 2022/08/30 06:50:15 - mmengine - INFO - Epoch(train) [288][10/63] lr: 5.4721e-03 eta: 23:13:42 time: 1.4723 data_time: 0.2605 memory: 16201 loss_prob: 0.6852 loss_thr: 0.4286 loss_db: 0.1163 loss: 1.2301 2022/08/30 06:50:21 - mmengine - INFO - Epoch(train) [288][15/63] lr: 5.4721e-03 eta: 23:13:42 time: 1.2312 data_time: 0.0284 memory: 16201 loss_prob: 0.7322 loss_thr: 0.4370 loss_db: 0.1236 loss: 1.2927 2022/08/30 06:50:28 - mmengine - INFO - Epoch(train) [288][20/63] lr: 5.4721e-03 eta: 23:13:21 time: 1.2770 data_time: 0.0355 memory: 16201 loss_prob: 0.7053 loss_thr: 0.4460 loss_db: 0.1201 loss: 1.2715 2022/08/30 06:50:34 - mmengine - INFO - Epoch(train) [288][25/63] lr: 5.4721e-03 eta: 23:13:21 time: 1.3074 data_time: 0.0395 memory: 16201 loss_prob: 0.6519 loss_thr: 0.4432 loss_db: 0.1119 loss: 1.2070 2022/08/30 06:50:41 - mmengine - INFO - Epoch(train) [288][30/63] lr: 5.4721e-03 eta: 23:13:05 time: 1.3921 data_time: 0.0266 memory: 16201 loss_prob: 0.6700 loss_thr: 0.4513 loss_db: 0.1137 loss: 1.2349 2022/08/30 06:50:49 - mmengine - INFO - Epoch(train) [288][35/63] lr: 5.4721e-03 eta: 23:13:05 time: 1.4558 data_time: 0.0354 memory: 16201 loss_prob: 0.6277 loss_thr: 0.4427 loss_db: 0.1076 loss: 1.1779 2022/08/30 06:50:55 - mmengine - INFO - Epoch(train) [288][40/63] lr: 5.4721e-03 eta: 23:12:48 time: 1.3764 data_time: 0.0332 memory: 16201 loss_prob: 0.6286 loss_thr: 0.4491 loss_db: 0.1070 loss: 1.1847 2022/08/30 06:51:02 - mmengine - INFO - Epoch(train) [288][45/63] lr: 5.4721e-03 eta: 23:12:48 time: 1.2930 data_time: 0.0326 memory: 16201 loss_prob: 0.6791 loss_thr: 0.4524 loss_db: 0.1155 loss: 1.2469 2022/08/30 06:51:08 - mmengine - INFO - Epoch(train) [288][50/63] lr: 5.4721e-03 eta: 23:12:28 time: 1.2900 data_time: 0.0422 memory: 16201 loss_prob: 0.7266 loss_thr: 0.4611 loss_db: 0.1230 loss: 1.3107 2022/08/30 06:51:14 - mmengine - INFO - Epoch(train) [288][55/63] lr: 5.4721e-03 eta: 23:12:28 time: 1.1740 data_time: 0.0323 memory: 16201 loss_prob: 0.6972 loss_thr: 0.4519 loss_db: 0.1173 loss: 1.2664 2022/08/30 06:51:21 - mmengine - INFO - Epoch(train) [288][60/63] lr: 5.4721e-03 eta: 23:12:09 time: 1.3204 data_time: 0.0340 memory: 16201 loss_prob: 0.6417 loss_thr: 0.4151 loss_db: 0.1103 loss: 1.1670 2022/08/30 06:51:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:51:33 - mmengine - INFO - Epoch(train) [289][5/63] lr: 5.4667e-03 eta: 23:12:09 time: 1.5217 data_time: 0.2359 memory: 16201 loss_prob: 0.6567 loss_thr: 0.4369 loss_db: 0.1128 loss: 1.2064 2022/08/30 06:51:40 - mmengine - INFO - Epoch(train) [289][10/63] lr: 5.4667e-03 eta: 23:11:38 time: 1.4970 data_time: 0.2465 memory: 16201 loss_prob: 0.6558 loss_thr: 0.4279 loss_db: 0.1130 loss: 1.1968 2022/08/30 06:51:46 - mmengine - INFO - Epoch(train) [289][15/63] lr: 5.4667e-03 eta: 23:11:38 time: 1.3211 data_time: 0.0339 memory: 16201 loss_prob: 0.6188 loss_thr: 0.4127 loss_db: 0.1067 loss: 1.1382 2022/08/30 06:51:52 - mmengine - INFO - Epoch(train) [289][20/63] lr: 5.4667e-03 eta: 23:11:17 time: 1.2581 data_time: 0.0354 memory: 16201 loss_prob: 0.6430 loss_thr: 0.4443 loss_db: 0.1127 loss: 1.2000 2022/08/30 06:51:58 - mmengine - INFO - Epoch(train) [289][25/63] lr: 5.4667e-03 eta: 23:11:17 time: 1.2080 data_time: 0.0361 memory: 16201 loss_prob: 0.7079 loss_thr: 0.4538 loss_db: 0.1167 loss: 1.2784 2022/08/30 06:52:05 - mmengine - INFO - Epoch(train) [289][30/63] lr: 5.4667e-03 eta: 23:10:58 time: 1.2936 data_time: 0.0299 memory: 16201 loss_prob: 0.6572 loss_thr: 0.4267 loss_db: 0.1071 loss: 1.1910 2022/08/30 06:52:12 - mmengine - INFO - Epoch(train) [289][35/63] lr: 5.4667e-03 eta: 23:10:58 time: 1.3072 data_time: 0.0346 memory: 16201 loss_prob: 0.6345 loss_thr: 0.4313 loss_db: 0.1082 loss: 1.1739 2022/08/30 06:52:18 - mmengine - INFO - Epoch(train) [289][40/63] lr: 5.4667e-03 eta: 23:10:37 time: 1.2628 data_time: 0.0321 memory: 16201 loss_prob: 0.6774 loss_thr: 0.4353 loss_db: 0.1135 loss: 1.2261 2022/08/30 06:52:24 - mmengine - INFO - Epoch(train) [289][45/63] lr: 5.4667e-03 eta: 23:10:37 time: 1.2032 data_time: 0.0322 memory: 16201 loss_prob: 0.7357 loss_thr: 0.4628 loss_db: 0.1209 loss: 1.3194 2022/08/30 06:52:30 - mmengine - INFO - Epoch(train) [289][50/63] lr: 5.4667e-03 eta: 23:10:16 time: 1.2434 data_time: 0.0383 memory: 16201 loss_prob: 0.6776 loss_thr: 0.4416 loss_db: 0.1146 loss: 1.2338 2022/08/30 06:52:37 - mmengine - INFO - Epoch(train) [289][55/63] lr: 5.4667e-03 eta: 23:10:16 time: 1.3692 data_time: 0.0392 memory: 16201 loss_prob: 0.5949 loss_thr: 0.4060 loss_db: 0.1039 loss: 1.1048 2022/08/30 06:52:44 - mmengine - INFO - Epoch(train) [289][60/63] lr: 5.4667e-03 eta: 23:09:58 time: 1.3302 data_time: 0.0396 memory: 16201 loss_prob: 0.6036 loss_thr: 0.4018 loss_db: 0.1031 loss: 1.1085 2022/08/30 06:52:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:52:55 - mmengine - INFO - Epoch(train) [290][5/63] lr: 5.4613e-03 eta: 23:09:58 time: 1.4171 data_time: 0.2179 memory: 16201 loss_prob: 0.6788 loss_thr: 0.4384 loss_db: 0.1150 loss: 1.2322 2022/08/30 06:53:02 - mmengine - INFO - Epoch(train) [290][10/63] lr: 5.4613e-03 eta: 23:09:28 time: 1.5538 data_time: 0.2306 memory: 16201 loss_prob: 0.7093 loss_thr: 0.4594 loss_db: 0.1213 loss: 1.2899 2022/08/30 06:53:08 - mmengine - INFO - Epoch(train) [290][15/63] lr: 5.4613e-03 eta: 23:09:28 time: 1.3265 data_time: 0.0348 memory: 16201 loss_prob: 0.7053 loss_thr: 0.4632 loss_db: 0.1202 loss: 1.2887 2022/08/30 06:53:15 - mmengine - INFO - Epoch(train) [290][20/63] lr: 5.4613e-03 eta: 23:09:08 time: 1.2574 data_time: 0.0383 memory: 16201 loss_prob: 0.6695 loss_thr: 0.4456 loss_db: 0.1153 loss: 1.2304 2022/08/30 06:53:22 - mmengine - INFO - Epoch(train) [290][25/63] lr: 5.4613e-03 eta: 23:09:08 time: 1.3180 data_time: 0.0331 memory: 16201 loss_prob: 0.6804 loss_thr: 0.4483 loss_db: 0.1181 loss: 1.2468 2022/08/30 06:53:28 - mmengine - INFO - Epoch(train) [290][30/63] lr: 5.4613e-03 eta: 23:08:49 time: 1.3374 data_time: 0.0315 memory: 16201 loss_prob: 0.8251 loss_thr: 0.4511 loss_db: 0.1412 loss: 1.4174 2022/08/30 06:53:34 - mmengine - INFO - Epoch(train) [290][35/63] lr: 5.4613e-03 eta: 23:08:49 time: 1.2666 data_time: 0.0360 memory: 16201 loss_prob: 0.9213 loss_thr: 0.4549 loss_db: 0.1578 loss: 1.5339 2022/08/30 06:53:41 - mmengine - INFO - Epoch(train) [290][40/63] lr: 5.4613e-03 eta: 23:08:30 time: 1.2996 data_time: 0.0279 memory: 16201 loss_prob: 0.7662 loss_thr: 0.4382 loss_db: 0.1305 loss: 1.3348 2022/08/30 06:53:47 - mmengine - INFO - Epoch(train) [290][45/63] lr: 5.4613e-03 eta: 23:08:30 time: 1.3158 data_time: 0.0301 memory: 16201 loss_prob: 0.6792 loss_thr: 0.4150 loss_db: 0.1169 loss: 1.2111 2022/08/30 06:53:54 - mmengine - INFO - Epoch(train) [290][50/63] lr: 5.4613e-03 eta: 23:08:10 time: 1.2669 data_time: 0.0331 memory: 16201 loss_prob: 0.7172 loss_thr: 0.4242 loss_db: 0.1214 loss: 1.2628 2022/08/30 06:54:00 - mmengine - INFO - Epoch(train) [290][55/63] lr: 5.4613e-03 eta: 23:08:10 time: 1.2325 data_time: 0.0324 memory: 16201 loss_prob: 0.7046 loss_thr: 0.4222 loss_db: 0.1147 loss: 1.2415 2022/08/30 06:54:07 - mmengine - INFO - Epoch(train) [290][60/63] lr: 5.4613e-03 eta: 23:07:50 time: 1.2934 data_time: 0.0376 memory: 16201 loss_prob: 0.7381 loss_thr: 0.4449 loss_db: 0.1236 loss: 1.3066 2022/08/30 06:54:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:54:19 - mmengine - INFO - Epoch(train) [291][5/63] lr: 5.4559e-03 eta: 23:07:50 time: 1.5284 data_time: 0.2450 memory: 16201 loss_prob: 0.7170 loss_thr: 0.4574 loss_db: 0.1221 loss: 1.2965 2022/08/30 06:54:26 - mmengine - INFO - Epoch(train) [291][10/63] lr: 5.4559e-03 eta: 23:07:23 time: 1.6129 data_time: 0.2532 memory: 16201 loss_prob: 0.6868 loss_thr: 0.4479 loss_db: 0.1175 loss: 1.2523 2022/08/30 06:54:32 - mmengine - INFO - Epoch(train) [291][15/63] lr: 5.4559e-03 eta: 23:07:23 time: 1.2900 data_time: 0.0317 memory: 16201 loss_prob: 0.7120 loss_thr: 0.4431 loss_db: 0.1169 loss: 1.2720 2022/08/30 06:54:38 - mmengine - INFO - Epoch(train) [291][20/63] lr: 5.4559e-03 eta: 23:07:02 time: 1.2450 data_time: 0.0351 memory: 16201 loss_prob: 0.6575 loss_thr: 0.4072 loss_db: 0.1089 loss: 1.1736 2022/08/30 06:54:45 - mmengine - INFO - Epoch(train) [291][25/63] lr: 5.4559e-03 eta: 23:07:02 time: 1.3020 data_time: 0.0303 memory: 16201 loss_prob: 0.6630 loss_thr: 0.4238 loss_db: 0.1140 loss: 1.2009 2022/08/30 06:54:51 - mmengine - INFO - Epoch(train) [291][30/63] lr: 5.4559e-03 eta: 23:06:42 time: 1.2871 data_time: 0.0301 memory: 16201 loss_prob: 0.7150 loss_thr: 0.4560 loss_db: 0.1229 loss: 1.2938 2022/08/30 06:54:58 - mmengine - INFO - Epoch(train) [291][35/63] lr: 5.4559e-03 eta: 23:06:42 time: 1.2557 data_time: 0.0409 memory: 16201 loss_prob: 0.6851 loss_thr: 0.4428 loss_db: 0.1175 loss: 1.2454 2022/08/30 06:55:04 - mmengine - INFO - Epoch(train) [291][40/63] lr: 5.4559e-03 eta: 23:06:22 time: 1.2704 data_time: 0.0311 memory: 16201 loss_prob: 0.6820 loss_thr: 0.4361 loss_db: 0.1165 loss: 1.2346 2022/08/30 06:55:11 - mmengine - INFO - Epoch(train) [291][45/63] lr: 5.4559e-03 eta: 23:06:22 time: 1.3113 data_time: 0.0335 memory: 16201 loss_prob: 0.6589 loss_thr: 0.4199 loss_db: 0.1114 loss: 1.1903 2022/08/30 06:55:17 - mmengine - INFO - Epoch(train) [291][50/63] lr: 5.4559e-03 eta: 23:06:02 time: 1.2811 data_time: 0.0377 memory: 16201 loss_prob: 0.6194 loss_thr: 0.4152 loss_db: 0.1048 loss: 1.1395 2022/08/30 06:55:24 - mmengine - INFO - Epoch(train) [291][55/63] lr: 5.4559e-03 eta: 23:06:02 time: 1.3019 data_time: 0.0301 memory: 16201 loss_prob: 0.6527 loss_thr: 0.4426 loss_db: 0.1118 loss: 1.2071 2022/08/30 06:55:29 - mmengine - INFO - Epoch(train) [291][60/63] lr: 5.4559e-03 eta: 23:05:42 time: 1.2661 data_time: 0.0336 memory: 16201 loss_prob: 0.6563 loss_thr: 0.4358 loss_db: 0.1120 loss: 1.2041 2022/08/30 06:55:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:55:41 - mmengine - INFO - Epoch(train) [292][5/63] lr: 5.4505e-03 eta: 23:05:42 time: 1.3531 data_time: 0.2240 memory: 16201 loss_prob: 0.6684 loss_thr: 0.4401 loss_db: 0.1145 loss: 1.2231 2022/08/30 06:55:47 - mmengine - INFO - Epoch(train) [292][10/63] lr: 5.4505e-03 eta: 23:05:09 time: 1.4533 data_time: 0.2462 memory: 16201 loss_prob: 0.7068 loss_thr: 0.4501 loss_db: 0.1206 loss: 1.2774 2022/08/30 06:55:54 - mmengine - INFO - Epoch(train) [292][15/63] lr: 5.4505e-03 eta: 23:05:09 time: 1.3457 data_time: 0.0421 memory: 16201 loss_prob: 0.6521 loss_thr: 0.4265 loss_db: 0.1133 loss: 1.1919 2022/08/30 06:56:00 - mmengine - INFO - Epoch(train) [292][20/63] lr: 5.4505e-03 eta: 23:04:50 time: 1.3112 data_time: 0.0289 memory: 16201 loss_prob: 0.6596 loss_thr: 0.4388 loss_db: 0.1111 loss: 1.2096 2022/08/30 06:56:06 - mmengine - INFO - Epoch(train) [292][25/63] lr: 5.4505e-03 eta: 23:04:50 time: 1.2353 data_time: 0.0433 memory: 16201 loss_prob: 0.6976 loss_thr: 0.4525 loss_db: 0.1166 loss: 1.2667 2022/08/30 06:56:14 - mmengine - INFO - Epoch(train) [292][30/63] lr: 5.4505e-03 eta: 23:04:33 time: 1.3598 data_time: 0.0361 memory: 16201 loss_prob: 0.6797 loss_thr: 0.4298 loss_db: 0.1168 loss: 1.2263 2022/08/30 06:56:20 - mmengine - INFO - Epoch(train) [292][35/63] lr: 5.4505e-03 eta: 23:04:33 time: 1.3777 data_time: 0.0322 memory: 16201 loss_prob: 0.7105 loss_thr: 0.4508 loss_db: 0.1212 loss: 1.2825 2022/08/30 06:56:27 - mmengine - INFO - Epoch(train) [292][40/63] lr: 5.4505e-03 eta: 23:04:15 time: 1.3288 data_time: 0.0345 memory: 16201 loss_prob: 0.7344 loss_thr: 0.4538 loss_db: 0.1233 loss: 1.3115 2022/08/30 06:56:34 - mmengine - INFO - Epoch(train) [292][45/63] lr: 5.4505e-03 eta: 23:04:15 time: 1.3593 data_time: 0.0288 memory: 16201 loss_prob: 0.6851 loss_thr: 0.4237 loss_db: 0.1137 loss: 1.2225 2022/08/30 06:56:40 - mmengine - INFO - Epoch(train) [292][50/63] lr: 5.4505e-03 eta: 23:03:57 time: 1.3457 data_time: 0.0396 memory: 16201 loss_prob: 0.6895 loss_thr: 0.4567 loss_db: 0.1180 loss: 1.2642 2022/08/30 06:56:46 - mmengine - INFO - Epoch(train) [292][55/63] lr: 5.4505e-03 eta: 23:03:57 time: 1.2252 data_time: 0.0406 memory: 16201 loss_prob: 0.7646 loss_thr: 0.4758 loss_db: 0.1302 loss: 1.3706 2022/08/30 06:56:54 - mmengine - INFO - Epoch(train) [292][60/63] lr: 5.4505e-03 eta: 23:03:38 time: 1.3229 data_time: 0.0322 memory: 16201 loss_prob: 0.7446 loss_thr: 0.4445 loss_db: 0.1245 loss: 1.3136 2022/08/30 06:56:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:57:06 - mmengine - INFO - Epoch(train) [293][5/63] lr: 5.4451e-03 eta: 23:03:38 time: 1.4704 data_time: 0.2424 memory: 16201 loss_prob: 0.6278 loss_thr: 0.4167 loss_db: 0.1102 loss: 1.1547 2022/08/30 06:57:12 - mmengine - INFO - Epoch(train) [293][10/63] lr: 5.4451e-03 eta: 23:03:08 time: 1.5256 data_time: 0.2451 memory: 16201 loss_prob: 0.6555 loss_thr: 0.4256 loss_db: 0.1099 loss: 1.1910 2022/08/30 06:57:19 - mmengine - INFO - Epoch(train) [293][15/63] lr: 5.4451e-03 eta: 23:03:08 time: 1.3475 data_time: 0.0369 memory: 16201 loss_prob: 0.6909 loss_thr: 0.4533 loss_db: 0.1155 loss: 1.2596 2022/08/30 06:57:25 - mmengine - INFO - Epoch(train) [293][20/63] lr: 5.4451e-03 eta: 23:02:49 time: 1.2912 data_time: 0.0467 memory: 16201 loss_prob: 0.6933 loss_thr: 0.4660 loss_db: 0.1189 loss: 1.2782 2022/08/30 06:57:32 - mmengine - INFO - Epoch(train) [293][25/63] lr: 5.4451e-03 eta: 23:02:49 time: 1.2983 data_time: 0.0381 memory: 16201 loss_prob: 0.7459 loss_thr: 0.4628 loss_db: 0.1281 loss: 1.3368 2022/08/30 06:57:39 - mmengine - INFO - Epoch(train) [293][30/63] lr: 5.4451e-03 eta: 23:02:33 time: 1.3949 data_time: 0.0322 memory: 16201 loss_prob: 0.7390 loss_thr: 0.4550 loss_db: 0.1273 loss: 1.3214 2022/08/30 06:57:46 - mmengine - INFO - Epoch(train) [293][35/63] lr: 5.4451e-03 eta: 23:02:33 time: 1.3728 data_time: 0.0408 memory: 16201 loss_prob: 0.7091 loss_thr: 0.4406 loss_db: 0.1222 loss: 1.2718 2022/08/30 06:57:52 - mmengine - INFO - Epoch(train) [293][40/63] lr: 5.4451e-03 eta: 23:02:14 time: 1.3248 data_time: 0.0289 memory: 16201 loss_prob: 0.6999 loss_thr: 0.4323 loss_db: 0.1169 loss: 1.2491 2022/08/30 06:57:59 - mmengine - INFO - Epoch(train) [293][45/63] lr: 5.4451e-03 eta: 23:02:14 time: 1.2984 data_time: 0.0296 memory: 16201 loss_prob: 0.7147 loss_thr: 0.4414 loss_db: 0.1183 loss: 1.2744 2022/08/30 06:58:05 - mmengine - INFO - Epoch(train) [293][50/63] lr: 5.4451e-03 eta: 23:01:54 time: 1.2581 data_time: 0.0328 memory: 16201 loss_prob: 0.8337 loss_thr: 0.4807 loss_db: 0.1355 loss: 1.4499 2022/08/30 06:58:12 - mmengine - INFO - Epoch(train) [293][55/63] lr: 5.4451e-03 eta: 23:01:54 time: 1.2618 data_time: 0.0310 memory: 16201 loss_prob: 0.8391 loss_thr: 0.4830 loss_db: 0.1390 loss: 1.4612 2022/08/30 06:58:18 - mmengine - INFO - Epoch(train) [293][60/63] lr: 5.4451e-03 eta: 23:01:34 time: 1.2869 data_time: 0.0475 memory: 16201 loss_prob: 0.7067 loss_thr: 0.4438 loss_db: 0.1209 loss: 1.2714 2022/08/30 06:58:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:58:30 - mmengine - INFO - Epoch(train) [294][5/63] lr: 5.4397e-03 eta: 23:01:34 time: 1.4544 data_time: 0.2269 memory: 16201 loss_prob: 0.7393 loss_thr: 0.4552 loss_db: 0.1248 loss: 1.3193 2022/08/30 06:58:37 - mmengine - INFO - Epoch(train) [294][10/63] lr: 5.4397e-03 eta: 23:01:04 time: 1.5341 data_time: 0.2381 memory: 16201 loss_prob: 0.7388 loss_thr: 0.4531 loss_db: 0.1251 loss: 1.3171 2022/08/30 06:58:43 - mmengine - INFO - Epoch(train) [294][15/63] lr: 5.4397e-03 eta: 23:01:04 time: 1.3138 data_time: 0.0395 memory: 16201 loss_prob: 0.7972 loss_thr: 0.4661 loss_db: 0.1387 loss: 1.4020 2022/08/30 06:58:49 - mmengine - INFO - Epoch(train) [294][20/63] lr: 5.4397e-03 eta: 23:00:45 time: 1.2822 data_time: 0.0352 memory: 16201 loss_prob: 0.7588 loss_thr: 0.4534 loss_db: 0.1340 loss: 1.3463 2022/08/30 06:58:56 - mmengine - INFO - Epoch(train) [294][25/63] lr: 5.4397e-03 eta: 23:00:45 time: 1.3016 data_time: 0.0390 memory: 16201 loss_prob: 0.7419 loss_thr: 0.4535 loss_db: 0.1275 loss: 1.3229 2022/08/30 06:59:03 - mmengine - INFO - Epoch(train) [294][30/63] lr: 5.4397e-03 eta: 23:00:29 time: 1.4045 data_time: 0.0425 memory: 16201 loss_prob: 0.7431 loss_thr: 0.4570 loss_db: 0.1252 loss: 1.3254 2022/08/30 06:59:10 - mmengine - INFO - Epoch(train) [294][35/63] lr: 5.4397e-03 eta: 23:00:29 time: 1.3380 data_time: 0.0371 memory: 16201 loss_prob: 0.6995 loss_thr: 0.4522 loss_db: 0.1178 loss: 1.2694 2022/08/30 06:59:16 - mmengine - INFO - Epoch(train) [294][40/63] lr: 5.4397e-03 eta: 23:00:09 time: 1.2845 data_time: 0.0312 memory: 16201 loss_prob: 0.7092 loss_thr: 0.4573 loss_db: 0.1217 loss: 1.2882 2022/08/30 06:59:22 - mmengine - INFO - Epoch(train) [294][45/63] lr: 5.4397e-03 eta: 23:00:09 time: 1.2408 data_time: 0.0298 memory: 16201 loss_prob: 0.7262 loss_thr: 0.4357 loss_db: 0.1242 loss: 1.2861 2022/08/30 06:59:28 - mmengine - INFO - Epoch(train) [294][50/63] lr: 5.4397e-03 eta: 22:59:47 time: 1.2124 data_time: 0.0354 memory: 16201 loss_prob: 0.7786 loss_thr: 0.4483 loss_db: 0.1305 loss: 1.3573 2022/08/30 06:59:35 - mmengine - INFO - Epoch(train) [294][55/63] lr: 5.4397e-03 eta: 22:59:47 time: 1.2776 data_time: 0.0368 memory: 16201 loss_prob: 0.7257 loss_thr: 0.4546 loss_db: 0.1248 loss: 1.3050 2022/08/30 06:59:42 - mmengine - INFO - Epoch(train) [294][60/63] lr: 5.4397e-03 eta: 22:59:30 time: 1.3693 data_time: 0.0361 memory: 16201 loss_prob: 0.7183 loss_thr: 0.4480 loss_db: 0.1243 loss: 1.2906 2022/08/30 06:59:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 06:59:54 - mmengine - INFO - Epoch(train) [295][5/63] lr: 5.4343e-03 eta: 22:59:30 time: 1.5113 data_time: 0.2340 memory: 16201 loss_prob: 0.7657 loss_thr: 0.4508 loss_db: 0.1260 loss: 1.3425 2022/08/30 07:00:01 - mmengine - INFO - Epoch(train) [295][10/63] lr: 5.4343e-03 eta: 22:59:00 time: 1.5228 data_time: 0.2462 memory: 16201 loss_prob: 0.7038 loss_thr: 0.4376 loss_db: 0.1161 loss: 1.2574 2022/08/30 07:00:07 - mmengine - INFO - Epoch(train) [295][15/63] lr: 5.4343e-03 eta: 22:59:00 time: 1.2519 data_time: 0.0323 memory: 16201 loss_prob: 0.6723 loss_thr: 0.4224 loss_db: 0.1167 loss: 1.2113 2022/08/30 07:00:13 - mmengine - INFO - Epoch(train) [295][20/63] lr: 5.4343e-03 eta: 22:58:40 time: 1.2560 data_time: 0.0288 memory: 16201 loss_prob: 0.7912 loss_thr: 0.4446 loss_db: 0.1331 loss: 1.3689 2022/08/30 07:00:20 - mmengine - INFO - Epoch(train) [295][25/63] lr: 5.4343e-03 eta: 22:58:40 time: 1.3029 data_time: 0.0397 memory: 16201 loss_prob: 0.7740 loss_thr: 0.4429 loss_db: 0.1318 loss: 1.3488 2022/08/30 07:00:27 - mmengine - INFO - Epoch(train) [295][30/63] lr: 5.4343e-03 eta: 22:58:22 time: 1.3420 data_time: 0.0315 memory: 16201 loss_prob: 0.6592 loss_thr: 0.4123 loss_db: 0.1134 loss: 1.1848 2022/08/30 07:00:33 - mmengine - INFO - Epoch(train) [295][35/63] lr: 5.4343e-03 eta: 22:58:22 time: 1.3304 data_time: 0.0287 memory: 16201 loss_prob: 0.6830 loss_thr: 0.4236 loss_db: 0.1125 loss: 1.2192 2022/08/30 07:00:40 - mmengine - INFO - Epoch(train) [295][40/63] lr: 5.4343e-03 eta: 22:58:03 time: 1.3098 data_time: 0.0318 memory: 16201 loss_prob: 0.6910 loss_thr: 0.4392 loss_db: 0.1161 loss: 1.2463 2022/08/30 07:00:46 - mmengine - INFO - Epoch(train) [295][45/63] lr: 5.4343e-03 eta: 22:58:03 time: 1.2717 data_time: 0.0285 memory: 16201 loss_prob: 0.6790 loss_thr: 0.4476 loss_db: 0.1162 loss: 1.2429 2022/08/30 07:00:52 - mmengine - INFO - Epoch(train) [295][50/63] lr: 5.4343e-03 eta: 22:57:42 time: 1.2436 data_time: 0.0354 memory: 16201 loss_prob: 0.6850 loss_thr: 0.4468 loss_db: 0.1168 loss: 1.2485 2022/08/30 07:00:58 - mmengine - INFO - Epoch(train) [295][55/63] lr: 5.4343e-03 eta: 22:57:42 time: 1.2412 data_time: 0.0364 memory: 16201 loss_prob: 0.7874 loss_thr: 0.4731 loss_db: 0.1352 loss: 1.3958 2022/08/30 07:01:05 - mmengine - INFO - Epoch(train) [295][60/63] lr: 5.4343e-03 eta: 22:57:23 time: 1.2788 data_time: 0.0318 memory: 16201 loss_prob: 0.8380 loss_thr: 0.4761 loss_db: 0.1412 loss: 1.4553 2022/08/30 07:01:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:01:17 - mmengine - INFO - Epoch(train) [296][5/63] lr: 5.4289e-03 eta: 22:57:23 time: 1.4403 data_time: 0.2168 memory: 16201 loss_prob: 0.7328 loss_thr: 0.4440 loss_db: 0.1221 loss: 1.2988 2022/08/30 07:01:24 - mmengine - INFO - Epoch(train) [296][10/63] lr: 5.4289e-03 eta: 22:56:55 time: 1.5936 data_time: 0.2331 memory: 16201 loss_prob: 0.7543 loss_thr: 0.4498 loss_db: 0.1246 loss: 1.3287 2022/08/30 07:01:30 - mmengine - INFO - Epoch(train) [296][15/63] lr: 5.4289e-03 eta: 22:56:55 time: 1.2714 data_time: 0.0345 memory: 16201 loss_prob: 0.7208 loss_thr: 0.4519 loss_db: 0.1188 loss: 1.2916 2022/08/30 07:01:36 - mmengine - INFO - Epoch(train) [296][20/63] lr: 5.4289e-03 eta: 22:56:32 time: 1.1882 data_time: 0.0343 memory: 16201 loss_prob: 0.6949 loss_thr: 0.4385 loss_db: 0.1162 loss: 1.2496 2022/08/30 07:01:43 - mmengine - INFO - Epoch(train) [296][25/63] lr: 5.4289e-03 eta: 22:56:32 time: 1.2918 data_time: 0.0379 memory: 16201 loss_prob: 0.7214 loss_thr: 0.4364 loss_db: 0.1213 loss: 1.2791 2022/08/30 07:01:49 - mmengine - INFO - Epoch(train) [296][30/63] lr: 5.4289e-03 eta: 22:56:14 time: 1.3223 data_time: 0.0359 memory: 16201 loss_prob: 0.7274 loss_thr: 0.4574 loss_db: 0.1199 loss: 1.3047 2022/08/30 07:01:56 - mmengine - INFO - Epoch(train) [296][35/63] lr: 5.4289e-03 eta: 22:56:14 time: 1.3385 data_time: 0.0336 memory: 16201 loss_prob: 0.6952 loss_thr: 0.4559 loss_db: 0.1160 loss: 1.2672 2022/08/30 07:02:04 - mmengine - INFO - Epoch(train) [296][40/63] lr: 5.4289e-03 eta: 22:56:01 time: 1.4994 data_time: 0.0874 memory: 16201 loss_prob: 0.8139 loss_thr: 0.4981 loss_db: 0.1332 loss: 1.4452 2022/08/30 07:02:11 - mmengine - INFO - Epoch(train) [296][45/63] lr: 5.4289e-03 eta: 22:56:01 time: 1.5328 data_time: 0.0995 memory: 16201 loss_prob: 0.8314 loss_thr: 0.5082 loss_db: 0.1381 loss: 1.4777 2022/08/30 07:02:18 - mmengine - INFO - Epoch(train) [296][50/63] lr: 5.4289e-03 eta: 22:55:44 time: 1.3557 data_time: 0.0431 memory: 16201 loss_prob: 0.7155 loss_thr: 0.4293 loss_db: 0.1164 loss: 1.2612 2022/08/30 07:02:24 - mmengine - INFO - Epoch(train) [296][55/63] lr: 5.4289e-03 eta: 22:55:44 time: 1.2236 data_time: 0.0336 memory: 16201 loss_prob: 0.7131 loss_thr: 0.4201 loss_db: 0.1148 loss: 1.2480 2022/08/30 07:02:31 - mmengine - INFO - Epoch(train) [296][60/63] lr: 5.4289e-03 eta: 22:55:24 time: 1.2774 data_time: 0.0324 memory: 16201 loss_prob: 0.7159 loss_thr: 0.4602 loss_db: 0.1220 loss: 1.2982 2022/08/30 07:02:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:02:42 - mmengine - INFO - Epoch(train) [297][5/63] lr: 5.4235e-03 eta: 22:55:24 time: 1.4712 data_time: 0.2259 memory: 16201 loss_prob: 0.7066 loss_thr: 0.4501 loss_db: 0.1189 loss: 1.2755 2022/08/30 07:02:48 - mmengine - INFO - Epoch(train) [297][10/63] lr: 5.4235e-03 eta: 22:54:53 time: 1.4740 data_time: 0.2461 memory: 16201 loss_prob: 0.7393 loss_thr: 0.4382 loss_db: 0.1350 loss: 1.3126 2022/08/30 07:02:56 - mmengine - INFO - Epoch(train) [297][15/63] lr: 5.4235e-03 eta: 22:54:53 time: 1.3151 data_time: 0.0382 memory: 16201 loss_prob: 0.7794 loss_thr: 0.4655 loss_db: 0.1410 loss: 1.3859 2022/08/30 07:03:02 - mmengine - INFO - Epoch(train) [297][20/63] lr: 5.4235e-03 eta: 22:54:36 time: 1.3715 data_time: 0.0297 memory: 16201 loss_prob: 0.7626 loss_thr: 0.4703 loss_db: 0.1249 loss: 1.3577 2022/08/30 07:03:09 - mmengine - INFO - Epoch(train) [297][25/63] lr: 5.4235e-03 eta: 22:54:36 time: 1.3453 data_time: 0.0423 memory: 16201 loss_prob: 1.0649 loss_thr: 0.4886 loss_db: 0.1652 loss: 1.7187 2022/08/30 07:03:16 - mmengine - INFO - Epoch(train) [297][30/63] lr: 5.4235e-03 eta: 22:54:19 time: 1.3619 data_time: 0.0303 memory: 16201 loss_prob: 1.3187 loss_thr: 0.5233 loss_db: 0.1970 loss: 2.0390 2022/08/30 07:03:23 - mmengine - INFO - Epoch(train) [297][35/63] lr: 5.4235e-03 eta: 22:54:19 time: 1.4061 data_time: 0.0283 memory: 16201 loss_prob: 1.2893 loss_thr: 0.5358 loss_db: 0.2028 loss: 2.0278 2022/08/30 07:03:29 - mmengine - INFO - Epoch(train) [297][40/63] lr: 5.4235e-03 eta: 22:54:00 time: 1.2970 data_time: 0.0302 memory: 16201 loss_prob: 1.0548 loss_thr: 0.5257 loss_db: 0.1736 loss: 1.7541 2022/08/30 07:03:36 - mmengine - INFO - Epoch(train) [297][45/63] lr: 5.4235e-03 eta: 22:54:00 time: 1.3017 data_time: 0.0287 memory: 16201 loss_prob: 0.8951 loss_thr: 0.5158 loss_db: 0.1478 loss: 1.5587 2022/08/30 07:03:42 - mmengine - INFO - Epoch(train) [297][50/63] lr: 5.4235e-03 eta: 22:53:42 time: 1.3606 data_time: 0.0379 memory: 16201 loss_prob: 0.9963 loss_thr: 0.5267 loss_db: 0.1639 loss: 1.6869 2022/08/30 07:03:48 - mmengine - INFO - Epoch(train) [297][55/63] lr: 5.4235e-03 eta: 22:53:42 time: 1.2450 data_time: 0.0270 memory: 16201 loss_prob: 0.9641 loss_thr: 0.5241 loss_db: 0.1574 loss: 1.6457 2022/08/30 07:03:56 - mmengine - INFO - Epoch(train) [297][60/63] lr: 5.4235e-03 eta: 22:53:24 time: 1.3316 data_time: 0.0280 memory: 16201 loss_prob: 0.8762 loss_thr: 0.5096 loss_db: 0.1451 loss: 1.5309 2022/08/30 07:03:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:04:08 - mmengine - INFO - Epoch(train) [298][5/63] lr: 5.4181e-03 eta: 22:53:24 time: 1.4962 data_time: 0.2490 memory: 16201 loss_prob: 0.8578 loss_thr: 0.4865 loss_db: 0.1497 loss: 1.4940 2022/08/30 07:04:16 - mmengine - INFO - Epoch(train) [298][10/63] lr: 5.4181e-03 eta: 22:53:00 time: 1.6895 data_time: 0.2670 memory: 16201 loss_prob: 0.8525 loss_thr: 0.4703 loss_db: 0.1410 loss: 1.4638 2022/08/30 07:04:22 - mmengine - INFO - Epoch(train) [298][15/63] lr: 5.4181e-03 eta: 22:53:00 time: 1.3795 data_time: 0.0352 memory: 16201 loss_prob: 0.9796 loss_thr: 0.4926 loss_db: 0.1628 loss: 1.6350 2022/08/30 07:04:29 - mmengine - INFO - Epoch(train) [298][20/63] lr: 5.4181e-03 eta: 22:52:41 time: 1.3100 data_time: 0.0286 memory: 16201 loss_prob: 0.9119 loss_thr: 0.4946 loss_db: 0.1509 loss: 1.5573 2022/08/30 07:04:36 - mmengine - INFO - Epoch(train) [298][25/63] lr: 5.4181e-03 eta: 22:52:41 time: 1.3613 data_time: 0.0400 memory: 16201 loss_prob: 0.8991 loss_thr: 0.4911 loss_db: 0.1462 loss: 1.5364 2022/08/30 07:04:42 - mmengine - INFO - Epoch(train) [298][30/63] lr: 5.4181e-03 eta: 22:52:23 time: 1.3237 data_time: 0.0297 memory: 16201 loss_prob: 0.8665 loss_thr: 0.4960 loss_db: 0.1453 loss: 1.5078 2022/08/30 07:04:49 - mmengine - INFO - Epoch(train) [298][35/63] lr: 5.4181e-03 eta: 22:52:23 time: 1.3264 data_time: 0.0343 memory: 16201 loss_prob: 0.8432 loss_thr: 0.4829 loss_db: 0.1421 loss: 1.4682 2022/08/30 07:04:56 - mmengine - INFO - Epoch(train) [298][40/63] lr: 5.4181e-03 eta: 22:52:05 time: 1.3534 data_time: 0.0369 memory: 16201 loss_prob: 0.8815 loss_thr: 0.4931 loss_db: 0.1439 loss: 1.5185 2022/08/30 07:05:02 - mmengine - INFO - Epoch(train) [298][45/63] lr: 5.4181e-03 eta: 22:52:05 time: 1.3324 data_time: 0.0307 memory: 16201 loss_prob: 0.8128 loss_thr: 0.4898 loss_db: 0.1367 loss: 1.4394 2022/08/30 07:05:09 - mmengine - INFO - Epoch(train) [298][50/63] lr: 5.4181e-03 eta: 22:51:47 time: 1.3134 data_time: 0.0418 memory: 16201 loss_prob: 0.8060 loss_thr: 0.4820 loss_db: 0.1395 loss: 1.4275 2022/08/30 07:05:15 - mmengine - INFO - Epoch(train) [298][55/63] lr: 5.4181e-03 eta: 22:51:47 time: 1.3216 data_time: 0.0293 memory: 16201 loss_prob: 0.8681 loss_thr: 0.4953 loss_db: 0.1456 loss: 1.5091 2022/08/30 07:05:22 - mmengine - INFO - Epoch(train) [298][60/63] lr: 5.4181e-03 eta: 22:51:28 time: 1.3217 data_time: 0.0312 memory: 16201 loss_prob: 0.9073 loss_thr: 0.5079 loss_db: 0.1466 loss: 1.5617 2022/08/30 07:05:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:05:34 - mmengine - INFO - Epoch(train) [299][5/63] lr: 5.4127e-03 eta: 22:51:28 time: 1.4978 data_time: 0.2242 memory: 16201 loss_prob: 0.8490 loss_thr: 0.4843 loss_db: 0.1440 loss: 1.4773 2022/08/30 07:05:41 - mmengine - INFO - Epoch(train) [299][10/63] lr: 5.4127e-03 eta: 22:51:01 time: 1.6098 data_time: 0.2470 memory: 16201 loss_prob: 0.9041 loss_thr: 0.5053 loss_db: 0.1539 loss: 1.5632 2022/08/30 07:05:48 - mmengine - INFO - Epoch(train) [299][15/63] lr: 5.4127e-03 eta: 22:51:01 time: 1.3659 data_time: 0.0416 memory: 16201 loss_prob: 0.8698 loss_thr: 0.4982 loss_db: 0.1428 loss: 1.5108 2022/08/30 07:05:55 - mmengine - INFO - Epoch(train) [299][20/63] lr: 5.4127e-03 eta: 22:50:44 time: 1.3642 data_time: 0.0383 memory: 16201 loss_prob: 0.8785 loss_thr: 0.4960 loss_db: 0.1428 loss: 1.5173 2022/08/30 07:06:02 - mmengine - INFO - Epoch(train) [299][25/63] lr: 5.4127e-03 eta: 22:50:44 time: 1.3657 data_time: 0.0390 memory: 16201 loss_prob: 0.8226 loss_thr: 0.4911 loss_db: 0.1365 loss: 1.4502 2022/08/30 07:06:08 - mmengine - INFO - Epoch(train) [299][30/63] lr: 5.4127e-03 eta: 22:50:26 time: 1.3277 data_time: 0.0319 memory: 16201 loss_prob: 0.8204 loss_thr: 0.4874 loss_db: 0.1426 loss: 1.4504 2022/08/30 07:06:14 - mmengine - INFO - Epoch(train) [299][35/63] lr: 5.4127e-03 eta: 22:50:26 time: 1.2880 data_time: 0.0311 memory: 16201 loss_prob: 0.7961 loss_thr: 0.4613 loss_db: 0.1357 loss: 1.3930 2022/08/30 07:06:21 - mmengine - INFO - Epoch(train) [299][40/63] lr: 5.4127e-03 eta: 22:50:07 time: 1.2793 data_time: 0.0320 memory: 16201 loss_prob: 0.8401 loss_thr: 0.4800 loss_db: 0.1339 loss: 1.4539 2022/08/30 07:06:28 - mmengine - INFO - Epoch(train) [299][45/63] lr: 5.4127e-03 eta: 22:50:07 time: 1.3369 data_time: 0.0373 memory: 16201 loss_prob: 0.8973 loss_thr: 0.5043 loss_db: 0.1465 loss: 1.5481 2022/08/30 07:06:35 - mmengine - INFO - Epoch(train) [299][50/63] lr: 5.4127e-03 eta: 22:49:50 time: 1.3706 data_time: 0.0424 memory: 16201 loss_prob: 0.8583 loss_thr: 0.4862 loss_db: 0.1427 loss: 1.4872 2022/08/30 07:06:41 - mmengine - INFO - Epoch(train) [299][55/63] lr: 5.4127e-03 eta: 22:49:50 time: 1.3379 data_time: 0.0303 memory: 16201 loss_prob: 0.8341 loss_thr: 0.4827 loss_db: 0.1345 loss: 1.4513 2022/08/30 07:06:47 - mmengine - INFO - Epoch(train) [299][60/63] lr: 5.4127e-03 eta: 22:49:30 time: 1.2653 data_time: 0.0315 memory: 16201 loss_prob: 0.8471 loss_thr: 0.4929 loss_db: 0.1369 loss: 1.4768 2022/08/30 07:06:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:06:59 - mmengine - INFO - Epoch(train) [300][5/63] lr: 5.4073e-03 eta: 22:49:30 time: 1.4264 data_time: 0.2173 memory: 16201 loss_prob: 0.8727 loss_thr: 0.4696 loss_db: 0.1440 loss: 1.4863 2022/08/30 07:07:06 - mmengine - INFO - Epoch(train) [300][10/63] lr: 5.4073e-03 eta: 22:49:01 time: 1.5570 data_time: 0.2333 memory: 16201 loss_prob: 0.8411 loss_thr: 0.4646 loss_db: 0.1361 loss: 1.4418 2022/08/30 07:07:13 - mmengine - INFO - Epoch(train) [300][15/63] lr: 5.4073e-03 eta: 22:49:01 time: 1.3574 data_time: 0.0336 memory: 16201 loss_prob: 0.7516 loss_thr: 0.4640 loss_db: 0.1231 loss: 1.3387 2022/08/30 07:07:19 - mmengine - INFO - Epoch(train) [300][20/63] lr: 5.4073e-03 eta: 22:48:44 time: 1.3561 data_time: 0.0365 memory: 16201 loss_prob: 0.7958 loss_thr: 0.4749 loss_db: 0.1331 loss: 1.4039 2022/08/30 07:07:26 - mmengine - INFO - Epoch(train) [300][25/63] lr: 5.4073e-03 eta: 22:48:44 time: 1.3536 data_time: 0.0313 memory: 16201 loss_prob: 0.9865 loss_thr: 0.4942 loss_db: 0.1618 loss: 1.6425 2022/08/30 07:07:33 - mmengine - INFO - Epoch(train) [300][30/63] lr: 5.4073e-03 eta: 22:48:29 time: 1.4308 data_time: 0.0340 memory: 16201 loss_prob: 1.4145 loss_thr: 0.5414 loss_db: 0.2187 loss: 2.1746 2022/08/30 07:07:41 - mmengine - INFO - Epoch(train) [300][35/63] lr: 5.4073e-03 eta: 22:48:29 time: 1.4624 data_time: 0.0395 memory: 16201 loss_prob: 1.6070 loss_thr: 0.6083 loss_db: 0.2346 loss: 2.4499 2022/08/30 07:07:48 - mmengine - INFO - Epoch(train) [300][40/63] lr: 5.4073e-03 eta: 22:48:14 time: 1.4239 data_time: 0.0307 memory: 16201 loss_prob: 1.2876 loss_thr: 0.5755 loss_db: 0.1939 loss: 2.0570 2022/08/30 07:07:54 - mmengine - INFO - Epoch(train) [300][45/63] lr: 5.4073e-03 eta: 22:48:14 time: 1.3695 data_time: 0.0345 memory: 16201 loss_prob: 1.2745 loss_thr: 0.5705 loss_db: 0.2123 loss: 2.0573 2022/08/30 07:08:01 - mmengine - INFO - Epoch(train) [300][50/63] lr: 5.4073e-03 eta: 22:47:56 time: 1.3207 data_time: 0.0335 memory: 16201 loss_prob: 1.4056 loss_thr: 0.5853 loss_db: 0.2250 loss: 2.2159 2022/08/30 07:08:08 - mmengine - INFO - Epoch(train) [300][55/63] lr: 5.4073e-03 eta: 22:47:56 time: 1.3184 data_time: 0.0343 memory: 16201 loss_prob: 1.2380 loss_thr: 0.5572 loss_db: 0.1971 loss: 1.9922 2022/08/30 07:08:15 - mmengine - INFO - Epoch(train) [300][60/63] lr: 5.4073e-03 eta: 22:47:40 time: 1.4143 data_time: 0.0366 memory: 16201 loss_prob: 1.1887 loss_thr: 0.5672 loss_db: 0.1911 loss: 1.9470 2022/08/30 07:08:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:08:18 - mmengine - INFO - Saving checkpoint at 300 epochs 2022/08/30 07:08:27 - mmengine - INFO - Epoch(val) [300][5/32] eta: 22:47:40 time: 0.7063 data_time: 0.1340 memory: 16201 2022/08/30 07:08:31 - mmengine - INFO - Epoch(val) [300][10/32] eta: 0:00:17 time: 0.8078 data_time: 0.1777 memory: 15734 2022/08/30 07:08:34 - mmengine - INFO - Epoch(val) [300][15/32] eta: 0:00:17 time: 0.6713 data_time: 0.0603 memory: 15734 2022/08/30 07:08:38 - mmengine - INFO - Epoch(val) [300][20/32] eta: 0:00:08 time: 0.7394 data_time: 0.0745 memory: 15734 2022/08/30 07:08:42 - mmengine - INFO - Epoch(val) [300][25/32] eta: 0:00:08 time: 0.7657 data_time: 0.0801 memory: 15734 2022/08/30 07:08:45 - mmengine - INFO - Epoch(val) [300][30/32] eta: 0:00:01 time: 0.6505 data_time: 0.0335 memory: 15734 2022/08/30 07:08:46 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 07:08:46 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7920, precision: 0.6342, hmean: 0.7043 2022/08/30 07:08:46 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7920, precision: 0.7450, hmean: 0.7678 2022/08/30 07:08:46 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7766, precision: 0.8037, hmean: 0.7899 2022/08/30 07:08:46 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7477, precision: 0.8500, hmean: 0.7956 2022/08/30 07:08:46 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6808, precision: 0.8989, hmean: 0.7748 2022/08/30 07:08:46 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3385, precision: 0.9398, hmean: 0.4977 2022/08/30 07:08:46 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0039, precision: 1.0000, hmean: 0.0077 2022/08/30 07:08:46 - mmengine - INFO - Epoch(val) [300][32/32] icdar/precision: 0.8500 icdar/recall: 0.7477 icdar/hmean: 0.7956 2022/08/30 07:08:56 - mmengine - INFO - Epoch(train) [301][5/63] lr: 5.4019e-03 eta: 0:00:01 time: 1.6506 data_time: 0.2253 memory: 16201 loss_prob: 1.0302 loss_thr: 0.5345 loss_db: 0.1673 loss: 1.7319 2022/08/30 07:09:03 - mmengine - INFO - Epoch(train) [301][10/63] lr: 5.4019e-03 eta: 22:47:17 time: 1.7346 data_time: 0.2394 memory: 16201 loss_prob: 1.0175 loss_thr: 0.5392 loss_db: 0.1669 loss: 1.7236 2022/08/30 07:09:10 - mmengine - INFO - Epoch(train) [301][15/63] lr: 5.4019e-03 eta: 22:47:17 time: 1.4190 data_time: 0.0351 memory: 16201 loss_prob: 1.0761 loss_thr: 0.5532 loss_db: 0.1822 loss: 1.8114 2022/08/30 07:09:18 - mmengine - INFO - Epoch(train) [301][20/63] lr: 5.4019e-03 eta: 22:47:02 time: 1.4451 data_time: 0.0322 memory: 16201 loss_prob: 1.1132 loss_thr: 0.5602 loss_db: 0.1840 loss: 1.8574 2022/08/30 07:09:24 - mmengine - INFO - Epoch(train) [301][25/63] lr: 5.4019e-03 eta: 22:47:02 time: 1.4300 data_time: 0.0343 memory: 16201 loss_prob: 1.1438 loss_thr: 0.5642 loss_db: 0.1862 loss: 1.8943 2022/08/30 07:09:31 - mmengine - INFO - Epoch(train) [301][30/63] lr: 5.4019e-03 eta: 22:46:44 time: 1.3221 data_time: 0.0282 memory: 16201 loss_prob: 1.0383 loss_thr: 0.5400 loss_db: 0.1724 loss: 1.7506 2022/08/30 07:09:38 - mmengine - INFO - Epoch(train) [301][35/63] lr: 5.4019e-03 eta: 22:46:44 time: 1.3946 data_time: 0.0392 memory: 16201 loss_prob: 1.0690 loss_thr: 0.5189 loss_db: 0.1797 loss: 1.7676 2022/08/30 07:09:46 - mmengine - INFO - Epoch(train) [301][40/63] lr: 5.4019e-03 eta: 22:46:31 time: 1.4942 data_time: 0.0329 memory: 16201 loss_prob: 1.0681 loss_thr: 0.5039 loss_db: 0.1794 loss: 1.7513 2022/08/30 07:09:52 - mmengine - INFO - Epoch(train) [301][45/63] lr: 5.4019e-03 eta: 22:46:31 time: 1.3731 data_time: 0.0306 memory: 16201 loss_prob: 0.9845 loss_thr: 0.5034 loss_db: 0.1622 loss: 1.6501 2022/08/30 07:09:59 - mmengine - INFO - Epoch(train) [301][50/63] lr: 5.4019e-03 eta: 22:46:13 time: 1.3361 data_time: 0.0390 memory: 16201 loss_prob: 1.0092 loss_thr: 0.5183 loss_db: 0.1652 loss: 1.6927 2022/08/30 07:10:06 - mmengine - INFO - Epoch(train) [301][55/63] lr: 5.4019e-03 eta: 22:46:13 time: 1.4041 data_time: 0.0287 memory: 16201 loss_prob: 1.0063 loss_thr: 0.5170 loss_db: 0.1623 loss: 1.6856 2022/08/30 07:10:13 - mmengine - INFO - Epoch(train) [301][60/63] lr: 5.4019e-03 eta: 22:45:57 time: 1.3732 data_time: 0.0386 memory: 16201 loss_prob: 0.9600 loss_thr: 0.5009 loss_db: 0.1562 loss: 1.6171 2022/08/30 07:10:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:10:25 - mmengine - INFO - Epoch(train) [302][5/63] lr: 5.3965e-03 eta: 22:45:57 time: 1.5393 data_time: 0.2326 memory: 16201 loss_prob: 0.9656 loss_thr: 0.5106 loss_db: 0.1589 loss: 1.6350 2022/08/30 07:10:34 - mmengine - INFO - Epoch(train) [302][10/63] lr: 5.3965e-03 eta: 22:45:34 time: 1.7433 data_time: 0.2523 memory: 16201 loss_prob: 0.9767 loss_thr: 0.5168 loss_db: 0.1647 loss: 1.6582 2022/08/30 07:10:41 - mmengine - INFO - Epoch(train) [302][15/63] lr: 5.3965e-03 eta: 22:45:34 time: 1.5324 data_time: 0.0386 memory: 16201 loss_prob: 0.8458 loss_thr: 0.4904 loss_db: 0.1388 loss: 1.4750 2022/08/30 07:10:47 - mmengine - INFO - Epoch(train) [302][20/63] lr: 5.3965e-03 eta: 22:45:15 time: 1.3020 data_time: 0.0325 memory: 16201 loss_prob: 0.7685 loss_thr: 0.4655 loss_db: 0.1274 loss: 1.3613 2022/08/30 07:10:55 - mmengine - INFO - Epoch(train) [302][25/63] lr: 5.3965e-03 eta: 22:45:15 time: 1.4190 data_time: 0.0363 memory: 16201 loss_prob: 0.9537 loss_thr: 0.5130 loss_db: 0.1580 loss: 1.6246 2022/08/30 07:11:02 - mmengine - INFO - Epoch(train) [302][30/63] lr: 5.3965e-03 eta: 22:45:01 time: 1.4630 data_time: 0.0320 memory: 16201 loss_prob: 1.0379 loss_thr: 0.5227 loss_db: 0.1687 loss: 1.7293 2022/08/30 07:11:09 - mmengine - INFO - Epoch(train) [302][35/63] lr: 5.3965e-03 eta: 22:45:01 time: 1.3561 data_time: 0.0361 memory: 16201 loss_prob: 0.9777 loss_thr: 0.5059 loss_db: 0.1571 loss: 1.6407 2022/08/30 07:11:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:11:16 - mmengine - INFO - Epoch(train) [302][40/63] lr: 5.3965e-03 eta: 22:44:45 time: 1.4016 data_time: 0.0304 memory: 16201 loss_prob: 1.0336 loss_thr: 0.5329 loss_db: 0.1647 loss: 1.7312 2022/08/30 07:11:23 - mmengine - INFO - Epoch(train) [302][45/63] lr: 5.3965e-03 eta: 22:44:45 time: 1.4144 data_time: 0.0322 memory: 16201 loss_prob: 0.9190 loss_thr: 0.5046 loss_db: 0.1518 loss: 1.5754 2022/08/30 07:11:30 - mmengine - INFO - Epoch(train) [302][50/63] lr: 5.3965e-03 eta: 22:44:30 time: 1.4105 data_time: 0.0362 memory: 16201 loss_prob: 0.8050 loss_thr: 0.4675 loss_db: 0.1359 loss: 1.4084 2022/08/30 07:11:37 - mmengine - INFO - Epoch(train) [302][55/63] lr: 5.3965e-03 eta: 22:44:30 time: 1.3906 data_time: 0.0261 memory: 16201 loss_prob: 0.9491 loss_thr: 0.5043 loss_db: 0.1563 loss: 1.6097 2022/08/30 07:11:43 - mmengine - INFO - Epoch(train) [302][60/63] lr: 5.3965e-03 eta: 22:44:12 time: 1.3390 data_time: 0.0376 memory: 16201 loss_prob: 0.8909 loss_thr: 0.4824 loss_db: 0.1463 loss: 1.5197 2022/08/30 07:11:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:11:56 - mmengine - INFO - Epoch(train) [303][5/63] lr: 5.3911e-03 eta: 22:44:12 time: 1.4697 data_time: 0.2278 memory: 16201 loss_prob: 0.8191 loss_thr: 0.4763 loss_db: 0.1369 loss: 1.4324 2022/08/30 07:12:02 - mmengine - INFO - Epoch(train) [303][10/63] lr: 5.3911e-03 eta: 22:43:44 time: 1.5758 data_time: 0.2452 memory: 16201 loss_prob: 0.9069 loss_thr: 0.5050 loss_db: 0.1528 loss: 1.5647 2022/08/30 07:12:09 - mmengine - INFO - Epoch(train) [303][15/63] lr: 5.3911e-03 eta: 22:43:44 time: 1.2826 data_time: 0.0332 memory: 16201 loss_prob: 0.8899 loss_thr: 0.4807 loss_db: 0.1473 loss: 1.5179 2022/08/30 07:12:15 - mmengine - INFO - Epoch(train) [303][20/63] lr: 5.3911e-03 eta: 22:43:25 time: 1.2816 data_time: 0.0270 memory: 16201 loss_prob: 0.8179 loss_thr: 0.4563 loss_db: 0.1326 loss: 1.4068 2022/08/30 07:12:22 - mmengine - INFO - Epoch(train) [303][25/63] lr: 5.3911e-03 eta: 22:43:25 time: 1.3275 data_time: 0.0436 memory: 16201 loss_prob: 0.7935 loss_thr: 0.4400 loss_db: 0.1349 loss: 1.3684 2022/08/30 07:12:28 - mmengine - INFO - Epoch(train) [303][30/63] lr: 5.3911e-03 eta: 22:43:07 time: 1.3461 data_time: 0.0325 memory: 16201 loss_prob: 0.8399 loss_thr: 0.4761 loss_db: 0.1419 loss: 1.4579 2022/08/30 07:12:35 - mmengine - INFO - Epoch(train) [303][35/63] lr: 5.3911e-03 eta: 22:43:07 time: 1.3134 data_time: 0.0317 memory: 16201 loss_prob: 0.9036 loss_thr: 0.5132 loss_db: 0.1475 loss: 1.5644 2022/08/30 07:12:41 - mmengine - INFO - Epoch(train) [303][40/63] lr: 5.3911e-03 eta: 22:42:49 time: 1.3079 data_time: 0.0346 memory: 16201 loss_prob: 0.8515 loss_thr: 0.4985 loss_db: 0.1416 loss: 1.4916 2022/08/30 07:12:48 - mmengine - INFO - Epoch(train) [303][45/63] lr: 5.3911e-03 eta: 22:42:49 time: 1.2681 data_time: 0.0370 memory: 16201 loss_prob: 0.7741 loss_thr: 0.4714 loss_db: 0.1286 loss: 1.3741 2022/08/30 07:12:54 - mmengine - INFO - Epoch(train) [303][50/63] lr: 5.3911e-03 eta: 22:42:30 time: 1.2950 data_time: 0.0468 memory: 16201 loss_prob: 0.8154 loss_thr: 0.4621 loss_db: 0.1303 loss: 1.4078 2022/08/30 07:13:01 - mmengine - INFO - Epoch(train) [303][55/63] lr: 5.3911e-03 eta: 22:42:30 time: 1.3383 data_time: 0.0404 memory: 16201 loss_prob: 0.8809 loss_thr: 0.4745 loss_db: 0.1421 loss: 1.4976 2022/08/30 07:13:08 - mmengine - INFO - Epoch(train) [303][60/63] lr: 5.3911e-03 eta: 22:42:13 time: 1.3692 data_time: 0.0440 memory: 16201 loss_prob: 0.8247 loss_thr: 0.4780 loss_db: 0.1375 loss: 1.4403 2022/08/30 07:13:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:13:20 - mmengine - INFO - Epoch(train) [304][5/63] lr: 5.3857e-03 eta: 22:42:13 time: 1.4937 data_time: 0.2233 memory: 16201 loss_prob: 0.8325 loss_thr: 0.4865 loss_db: 0.1435 loss: 1.4624 2022/08/30 07:13:28 - mmengine - INFO - Epoch(train) [304][10/63] lr: 5.3857e-03 eta: 22:41:48 time: 1.6814 data_time: 0.2424 memory: 16201 loss_prob: 0.8941 loss_thr: 0.5064 loss_db: 0.1521 loss: 1.5526 2022/08/30 07:13:35 - mmengine - INFO - Epoch(train) [304][15/63] lr: 5.3857e-03 eta: 22:41:48 time: 1.4204 data_time: 0.0361 memory: 16201 loss_prob: 0.8294 loss_thr: 0.5043 loss_db: 0.1382 loss: 1.4719 2022/08/30 07:13:41 - mmengine - INFO - Epoch(train) [304][20/63] lr: 5.3857e-03 eta: 22:41:30 time: 1.3241 data_time: 0.0334 memory: 16201 loss_prob: 0.9950 loss_thr: 0.5299 loss_db: 0.1698 loss: 1.6946 2022/08/30 07:13:48 - mmengine - INFO - Epoch(train) [304][25/63] lr: 5.3857e-03 eta: 22:41:30 time: 1.3306 data_time: 0.0322 memory: 16201 loss_prob: 1.0668 loss_thr: 0.5036 loss_db: 0.1795 loss: 1.7498 2022/08/30 07:13:54 - mmengine - INFO - Epoch(train) [304][30/63] lr: 5.3857e-03 eta: 22:41:12 time: 1.3266 data_time: 0.0392 memory: 16201 loss_prob: 1.0742 loss_thr: 0.4838 loss_db: 0.1751 loss: 1.7331 2022/08/30 07:14:01 - mmengine - INFO - Epoch(train) [304][35/63] lr: 5.3857e-03 eta: 22:41:12 time: 1.2861 data_time: 0.0470 memory: 16201 loss_prob: 1.1851 loss_thr: 0.5204 loss_db: 0.1855 loss: 1.8910 2022/08/30 07:14:07 - mmengine - INFO - Epoch(train) [304][40/63] lr: 5.3857e-03 eta: 22:40:54 time: 1.3067 data_time: 0.0330 memory: 16201 loss_prob: 1.1903 loss_thr: 0.5606 loss_db: 0.1911 loss: 1.9420 2022/08/30 07:14:14 - mmengine - INFO - Epoch(train) [304][45/63] lr: 5.3857e-03 eta: 22:40:54 time: 1.2962 data_time: 0.0295 memory: 16201 loss_prob: 1.0758 loss_thr: 0.5431 loss_db: 0.1835 loss: 1.8024 2022/08/30 07:14:21 - mmengine - INFO - Epoch(train) [304][50/63] lr: 5.3857e-03 eta: 22:40:35 time: 1.3139 data_time: 0.0398 memory: 16201 loss_prob: 1.0277 loss_thr: 0.5159 loss_db: 0.1663 loss: 1.7099 2022/08/30 07:14:27 - mmengine - INFO - Epoch(train) [304][55/63] lr: 5.3857e-03 eta: 22:40:35 time: 1.3098 data_time: 0.0399 memory: 16201 loss_prob: 1.1372 loss_thr: 0.5672 loss_db: 0.1819 loss: 1.8863 2022/08/30 07:14:33 - mmengine - INFO - Epoch(train) [304][60/63] lr: 5.3857e-03 eta: 22:40:16 time: 1.2846 data_time: 0.0467 memory: 16201 loss_prob: 1.1140 loss_thr: 0.5660 loss_db: 0.1814 loss: 1.8614 2022/08/30 07:14:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:14:46 - mmengine - INFO - Epoch(train) [305][5/63] lr: 5.3803e-03 eta: 22:40:16 time: 1.4826 data_time: 0.2266 memory: 16201 loss_prob: 0.9785 loss_thr: 0.5196 loss_db: 0.1596 loss: 1.6577 2022/08/30 07:14:53 - mmengine - INFO - Epoch(train) [305][10/63] lr: 5.3803e-03 eta: 22:39:49 time: 1.6022 data_time: 0.2343 memory: 16201 loss_prob: 1.0021 loss_thr: 0.5605 loss_db: 0.1623 loss: 1.7249 2022/08/30 07:15:00 - mmengine - INFO - Epoch(train) [305][15/63] lr: 5.3803e-03 eta: 22:39:49 time: 1.3959 data_time: 0.0314 memory: 16201 loss_prob: 0.8899 loss_thr: 0.5446 loss_db: 0.1491 loss: 1.5837 2022/08/30 07:15:06 - mmengine - INFO - Epoch(train) [305][20/63] lr: 5.3803e-03 eta: 22:39:32 time: 1.3682 data_time: 0.0380 memory: 16201 loss_prob: 0.9210 loss_thr: 0.5215 loss_db: 0.1570 loss: 1.5994 2022/08/30 07:15:13 - mmengine - INFO - Epoch(train) [305][25/63] lr: 5.3803e-03 eta: 22:39:32 time: 1.3073 data_time: 0.0341 memory: 16201 loss_prob: 0.9207 loss_thr: 0.5151 loss_db: 0.1517 loss: 1.5875 2022/08/30 07:15:19 - mmengine - INFO - Epoch(train) [305][30/63] lr: 5.3803e-03 eta: 22:39:14 time: 1.2963 data_time: 0.0342 memory: 16201 loss_prob: 0.8484 loss_thr: 0.4813 loss_db: 0.1373 loss: 1.4670 2022/08/30 07:15:25 - mmengine - INFO - Epoch(train) [305][35/63] lr: 5.3803e-03 eta: 22:39:14 time: 1.2196 data_time: 0.0406 memory: 16201 loss_prob: 0.8452 loss_thr: 0.4786 loss_db: 0.1422 loss: 1.4660 2022/08/30 07:15:32 - mmengine - INFO - Epoch(train) [305][40/63] lr: 5.3803e-03 eta: 22:38:53 time: 1.2251 data_time: 0.0286 memory: 16201 loss_prob: 0.9321 loss_thr: 0.4988 loss_db: 0.1569 loss: 1.5877 2022/08/30 07:15:39 - mmengine - INFO - Epoch(train) [305][45/63] lr: 5.3803e-03 eta: 22:38:53 time: 1.3850 data_time: 0.0305 memory: 16201 loss_prob: 0.9298 loss_thr: 0.4863 loss_db: 0.1572 loss: 1.5733 2022/08/30 07:15:45 - mmengine - INFO - Epoch(train) [305][50/63] lr: 5.3803e-03 eta: 22:38:35 time: 1.3310 data_time: 0.0383 memory: 16201 loss_prob: 0.8771 loss_thr: 0.4865 loss_db: 0.1490 loss: 1.5126 2022/08/30 07:15:51 - mmengine - INFO - Epoch(train) [305][55/63] lr: 5.3803e-03 eta: 22:38:35 time: 1.2670 data_time: 0.0321 memory: 16201 loss_prob: 0.8605 loss_thr: 0.4802 loss_db: 0.1411 loss: 1.4817 2022/08/30 07:15:59 - mmengine - INFO - Epoch(train) [305][60/63] lr: 5.3803e-03 eta: 22:38:19 time: 1.3820 data_time: 0.0349 memory: 16201 loss_prob: 0.8422 loss_thr: 0.4718 loss_db: 0.1397 loss: 1.4537 2022/08/30 07:16:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:16:11 - mmengine - INFO - Epoch(train) [306][5/63] lr: 5.3749e-03 eta: 22:38:19 time: 1.4529 data_time: 0.2563 memory: 16201 loss_prob: 0.9019 loss_thr: 0.5018 loss_db: 0.1463 loss: 1.5500 2022/08/30 07:16:17 - mmengine - INFO - Epoch(train) [306][10/63] lr: 5.3749e-03 eta: 22:37:49 time: 1.5233 data_time: 0.2664 memory: 16201 loss_prob: 0.7838 loss_thr: 0.4754 loss_db: 0.1309 loss: 1.3901 2022/08/30 07:16:24 - mmengine - INFO - Epoch(train) [306][15/63] lr: 5.3749e-03 eta: 22:37:49 time: 1.2725 data_time: 0.0284 memory: 16201 loss_prob: 0.8167 loss_thr: 0.4824 loss_db: 0.1378 loss: 1.4369 2022/08/30 07:16:31 - mmengine - INFO - Epoch(train) [306][20/63] lr: 5.3749e-03 eta: 22:37:32 time: 1.3292 data_time: 0.0299 memory: 16201 loss_prob: 0.8932 loss_thr: 0.5105 loss_db: 0.1471 loss: 1.5507 2022/08/30 07:16:37 - mmengine - INFO - Epoch(train) [306][25/63] lr: 5.3749e-03 eta: 22:37:32 time: 1.3449 data_time: 0.0423 memory: 16201 loss_prob: 0.8881 loss_thr: 0.5030 loss_db: 0.1426 loss: 1.5337 2022/08/30 07:16:44 - mmengine - INFO - Epoch(train) [306][30/63] lr: 5.3749e-03 eta: 22:37:14 time: 1.3368 data_time: 0.0303 memory: 16201 loss_prob: 0.8350 loss_thr: 0.4777 loss_db: 0.1418 loss: 1.4545 2022/08/30 07:16:51 - mmengine - INFO - Epoch(train) [306][35/63] lr: 5.3749e-03 eta: 22:37:14 time: 1.3840 data_time: 0.0288 memory: 16201 loss_prob: 0.8423 loss_thr: 0.4789 loss_db: 0.1417 loss: 1.4629 2022/08/30 07:16:58 - mmengine - INFO - Epoch(train) [306][40/63] lr: 5.3749e-03 eta: 22:36:57 time: 1.3712 data_time: 0.0310 memory: 16201 loss_prob: 0.7649 loss_thr: 0.4582 loss_db: 0.1227 loss: 1.3457 2022/08/30 07:17:04 - mmengine - INFO - Epoch(train) [306][45/63] lr: 5.3749e-03 eta: 22:36:57 time: 1.3534 data_time: 0.0314 memory: 16201 loss_prob: 0.9436 loss_thr: 0.4969 loss_db: 0.1481 loss: 1.5886 2022/08/30 07:17:10 - mmengine - INFO - Epoch(train) [306][50/63] lr: 5.3749e-03 eta: 22:36:38 time: 1.2811 data_time: 0.0385 memory: 16201 loss_prob: 1.0521 loss_thr: 0.5239 loss_db: 0.1695 loss: 1.7455 2022/08/30 07:17:17 - mmengine - INFO - Epoch(train) [306][55/63] lr: 5.3749e-03 eta: 22:36:38 time: 1.2361 data_time: 0.0283 memory: 16201 loss_prob: 0.8322 loss_thr: 0.4720 loss_db: 0.1419 loss: 1.4461 2022/08/30 07:17:24 - mmengine - INFO - Epoch(train) [306][60/63] lr: 5.3749e-03 eta: 22:36:20 time: 1.3242 data_time: 0.0260 memory: 16201 loss_prob: 0.7881 loss_thr: 0.4734 loss_db: 0.1308 loss: 1.3923 2022/08/30 07:17:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:17:36 - mmengine - INFO - Epoch(train) [307][5/63] lr: 5.3694e-03 eta: 22:36:20 time: 1.4586 data_time: 0.2302 memory: 16201 loss_prob: 0.8465 loss_thr: 0.4863 loss_db: 0.1405 loss: 1.4733 2022/08/30 07:17:43 - mmengine - INFO - Epoch(train) [307][10/63] lr: 5.3694e-03 eta: 22:35:52 time: 1.5638 data_time: 0.2447 memory: 16201 loss_prob: 0.9148 loss_thr: 0.4943 loss_db: 0.1517 loss: 1.5608 2022/08/30 07:17:48 - mmengine - INFO - Epoch(train) [307][15/63] lr: 5.3694e-03 eta: 22:35:52 time: 1.2634 data_time: 0.0349 memory: 16201 loss_prob: 0.8658 loss_thr: 0.4840 loss_db: 0.1485 loss: 1.4982 2022/08/30 07:17:54 - mmengine - INFO - Epoch(train) [307][20/63] lr: 5.3694e-03 eta: 22:35:29 time: 1.1638 data_time: 0.0338 memory: 16201 loss_prob: 0.8668 loss_thr: 0.4680 loss_db: 0.1446 loss: 1.4794 2022/08/30 07:18:01 - mmengine - INFO - Epoch(train) [307][25/63] lr: 5.3694e-03 eta: 22:35:29 time: 1.2796 data_time: 0.0414 memory: 16201 loss_prob: 0.9349 loss_thr: 0.4739 loss_db: 0.1479 loss: 1.5566 2022/08/30 07:18:08 - mmengine - INFO - Epoch(train) [307][30/63] lr: 5.3694e-03 eta: 22:35:12 time: 1.3400 data_time: 0.0308 memory: 16201 loss_prob: 0.8483 loss_thr: 0.4684 loss_db: 0.1368 loss: 1.4535 2022/08/30 07:18:14 - mmengine - INFO - Epoch(train) [307][35/63] lr: 5.3694e-03 eta: 22:35:12 time: 1.2913 data_time: 0.0328 memory: 16201 loss_prob: 0.8629 loss_thr: 0.4860 loss_db: 0.1429 loss: 1.4918 2022/08/30 07:18:21 - mmengine - INFO - Epoch(train) [307][40/63] lr: 5.3694e-03 eta: 22:34:53 time: 1.2955 data_time: 0.0370 memory: 16201 loss_prob: 0.8154 loss_thr: 0.4723 loss_db: 0.1341 loss: 1.4218 2022/08/30 07:18:27 - mmengine - INFO - Epoch(train) [307][45/63] lr: 5.3694e-03 eta: 22:34:53 time: 1.2974 data_time: 0.0386 memory: 16201 loss_prob: 0.7971 loss_thr: 0.4483 loss_db: 0.1364 loss: 1.3818 2022/08/30 07:18:34 - mmengine - INFO - Epoch(train) [307][50/63] lr: 5.3694e-03 eta: 22:34:34 time: 1.2907 data_time: 0.0400 memory: 16201 loss_prob: 1.1014 loss_thr: 0.5068 loss_db: 0.1791 loss: 1.7872 2022/08/30 07:18:40 - mmengine - INFO - Epoch(train) [307][55/63] lr: 5.3694e-03 eta: 22:34:34 time: 1.2989 data_time: 0.0411 memory: 16201 loss_prob: 1.1056 loss_thr: 0.5335 loss_db: 0.1729 loss: 1.8120 2022/08/30 07:18:46 - mmengine - INFO - Epoch(train) [307][60/63] lr: 5.3694e-03 eta: 22:34:15 time: 1.2837 data_time: 0.0444 memory: 16201 loss_prob: 0.9445 loss_thr: 0.5128 loss_db: 0.1507 loss: 1.6079 2022/08/30 07:18:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:18:58 - mmengine - INFO - Epoch(train) [308][5/63] lr: 5.3640e-03 eta: 22:34:15 time: 1.4123 data_time: 0.2390 memory: 16201 loss_prob: 0.8583 loss_thr: 0.4992 loss_db: 0.1422 loss: 1.4996 2022/08/30 07:19:05 - mmengine - INFO - Epoch(train) [308][10/63] lr: 5.3640e-03 eta: 22:33:45 time: 1.4923 data_time: 0.2550 memory: 16201 loss_prob: 0.8920 loss_thr: 0.4893 loss_db: 0.1437 loss: 1.5250 2022/08/30 07:19:11 - mmengine - INFO - Epoch(train) [308][15/63] lr: 5.3640e-03 eta: 22:33:45 time: 1.3353 data_time: 0.0334 memory: 16201 loss_prob: 0.8679 loss_thr: 0.4897 loss_db: 0.1414 loss: 1.4990 2022/08/30 07:19:18 - mmengine - INFO - Epoch(train) [308][20/63] lr: 5.3640e-03 eta: 22:33:29 time: 1.3701 data_time: 0.0292 memory: 16201 loss_prob: 0.8247 loss_thr: 0.4980 loss_db: 0.1389 loss: 1.4615 2022/08/30 07:19:24 - mmengine - INFO - Epoch(train) [308][25/63] lr: 5.3640e-03 eta: 22:33:29 time: 1.2688 data_time: 0.0325 memory: 16201 loss_prob: 0.7752 loss_thr: 0.4742 loss_db: 0.1317 loss: 1.3811 2022/08/30 07:19:31 - mmengine - INFO - Epoch(train) [308][30/63] lr: 5.3640e-03 eta: 22:33:08 time: 1.2243 data_time: 0.0326 memory: 16201 loss_prob: 0.8219 loss_thr: 0.4750 loss_db: 0.1350 loss: 1.4320 2022/08/30 07:19:38 - mmengine - INFO - Epoch(train) [308][35/63] lr: 5.3640e-03 eta: 22:33:08 time: 1.3559 data_time: 0.0416 memory: 16201 loss_prob: 0.7995 loss_thr: 0.4682 loss_db: 0.1295 loss: 1.3972 2022/08/30 07:19:44 - mmengine - INFO - Epoch(train) [308][40/63] lr: 5.3640e-03 eta: 22:32:51 time: 1.3746 data_time: 0.0331 memory: 16201 loss_prob: 0.7790 loss_thr: 0.4614 loss_db: 0.1262 loss: 1.3665 2022/08/30 07:19:51 - mmengine - INFO - Epoch(train) [308][45/63] lr: 5.3640e-03 eta: 22:32:51 time: 1.3384 data_time: 0.0318 memory: 16201 loss_prob: 0.8205 loss_thr: 0.4688 loss_db: 0.1335 loss: 1.4228 2022/08/30 07:19:58 - mmengine - INFO - Epoch(train) [308][50/63] lr: 5.3640e-03 eta: 22:32:34 time: 1.3328 data_time: 0.0424 memory: 16201 loss_prob: 0.8263 loss_thr: 0.4807 loss_db: 0.1361 loss: 1.4431 2022/08/30 07:20:04 - mmengine - INFO - Epoch(train) [308][55/63] lr: 5.3640e-03 eta: 22:32:34 time: 1.3014 data_time: 0.0294 memory: 16201 loss_prob: 0.7995 loss_thr: 0.4854 loss_db: 0.1347 loss: 1.4195 2022/08/30 07:20:11 - mmengine - INFO - Epoch(train) [308][60/63] lr: 5.3640e-03 eta: 22:32:16 time: 1.3200 data_time: 0.0292 memory: 16201 loss_prob: 0.8412 loss_thr: 0.4991 loss_db: 0.1401 loss: 1.4804 2022/08/30 07:20:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:20:23 - mmengine - INFO - Epoch(train) [309][5/63] lr: 5.3586e-03 eta: 22:32:16 time: 1.4396 data_time: 0.2098 memory: 16201 loss_prob: 0.8019 loss_thr: 0.4785 loss_db: 0.1369 loss: 1.4173 2022/08/30 07:20:30 - mmengine - INFO - Epoch(train) [309][10/63] lr: 5.3586e-03 eta: 22:31:48 time: 1.5618 data_time: 0.2253 memory: 16201 loss_prob: 0.7020 loss_thr: 0.4502 loss_db: 0.1196 loss: 1.2718 2022/08/30 07:20:37 - mmengine - INFO - Epoch(train) [309][15/63] lr: 5.3586e-03 eta: 22:31:48 time: 1.4628 data_time: 0.0319 memory: 16201 loss_prob: 0.7330 loss_thr: 0.4656 loss_db: 0.1265 loss: 1.3251 2022/08/30 07:20:44 - mmengine - INFO - Epoch(train) [309][20/63] lr: 5.3586e-03 eta: 22:31:32 time: 1.3900 data_time: 0.0311 memory: 16201 loss_prob: 0.8268 loss_thr: 0.4925 loss_db: 0.1386 loss: 1.4579 2022/08/30 07:20:50 - mmengine - INFO - Epoch(train) [309][25/63] lr: 5.3586e-03 eta: 22:31:32 time: 1.2912 data_time: 0.0335 memory: 16201 loss_prob: 0.7792 loss_thr: 0.4688 loss_db: 0.1285 loss: 1.3765 2022/08/30 07:20:57 - mmengine - INFO - Epoch(train) [309][30/63] lr: 5.3586e-03 eta: 22:31:14 time: 1.3369 data_time: 0.0306 memory: 16201 loss_prob: 0.6587 loss_thr: 0.4327 loss_db: 0.1118 loss: 1.2032 2022/08/30 07:21:04 - mmengine - INFO - Epoch(train) [309][35/63] lr: 5.3586e-03 eta: 22:31:14 time: 1.4190 data_time: 0.0378 memory: 16201 loss_prob: 0.7234 loss_thr: 0.4597 loss_db: 0.1253 loss: 1.3084 2022/08/30 07:21:10 - mmengine - INFO - Epoch(train) [309][40/63] lr: 5.3586e-03 eta: 22:30:56 time: 1.3008 data_time: 0.0313 memory: 16201 loss_prob: 0.8085 loss_thr: 0.4786 loss_db: 0.1355 loss: 1.4226 2022/08/30 07:21:17 - mmengine - INFO - Epoch(train) [309][45/63] lr: 5.3586e-03 eta: 22:30:56 time: 1.2487 data_time: 0.0291 memory: 16201 loss_prob: 0.7804 loss_thr: 0.4745 loss_db: 0.1303 loss: 1.3851 2022/08/30 07:21:23 - mmengine - INFO - Epoch(train) [309][50/63] lr: 5.3586e-03 eta: 22:30:37 time: 1.2914 data_time: 0.0390 memory: 16201 loss_prob: 0.7947 loss_thr: 0.4937 loss_db: 0.1364 loss: 1.4247 2022/08/30 07:21:30 - mmengine - INFO - Epoch(train) [309][55/63] lr: 5.3586e-03 eta: 22:30:37 time: 1.2777 data_time: 0.0337 memory: 16201 loss_prob: 0.7985 loss_thr: 0.4902 loss_db: 0.1334 loss: 1.4220 2022/08/30 07:21:36 - mmengine - INFO - Epoch(train) [309][60/63] lr: 5.3586e-03 eta: 22:30:19 time: 1.3217 data_time: 0.0408 memory: 16201 loss_prob: 0.9677 loss_thr: 0.4932 loss_db: 0.1612 loss: 1.6221 2022/08/30 07:21:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:21:49 - mmengine - INFO - Epoch(train) [310][5/63] lr: 5.3532e-03 eta: 22:30:19 time: 1.5391 data_time: 0.2297 memory: 16201 loss_prob: 0.9445 loss_thr: 0.4980 loss_db: 0.1504 loss: 1.5928 2022/08/30 07:21:58 - mmengine - INFO - Epoch(train) [310][10/63] lr: 5.3532e-03 eta: 22:30:00 time: 1.8726 data_time: 0.2416 memory: 16201 loss_prob: 0.9068 loss_thr: 0.4739 loss_db: 0.1493 loss: 1.5300 2022/08/30 07:22:06 - mmengine - INFO - Epoch(train) [310][15/63] lr: 5.3532e-03 eta: 22:30:00 time: 1.7366 data_time: 0.0363 memory: 16201 loss_prob: 0.8463 loss_thr: 0.4900 loss_db: 0.1421 loss: 1.4784 2022/08/30 07:22:20 - mmengine - INFO - Epoch(train) [310][20/63] lr: 5.3532e-03 eta: 22:30:05 time: 2.1146 data_time: 0.0534 memory: 16201 loss_prob: 0.9039 loss_thr: 0.5251 loss_db: 0.1477 loss: 1.5767 2022/08/30 07:22:33 - mmengine - INFO - Epoch(train) [310][25/63] lr: 5.3532e-03 eta: 22:30:05 time: 2.6759 data_time: 0.0669 memory: 16201 loss_prob: 0.8257 loss_thr: 0.4702 loss_db: 0.1391 loss: 1.4349 2022/08/30 07:22:45 - mmengine - INFO - Epoch(train) [310][30/63] lr: 5.3532e-03 eta: 22:30:23 time: 2.5868 data_time: 0.0600 memory: 16201 loss_prob: 0.8433 loss_thr: 0.4526 loss_db: 0.1360 loss: 1.4319 2022/08/30 07:23:01 - mmengine - INFO - Epoch(train) [310][35/63] lr: 5.3532e-03 eta: 22:30:23 time: 2.7729 data_time: 0.0543 memory: 16201 loss_prob: 0.8006 loss_thr: 0.4528 loss_db: 0.1268 loss: 1.3802 2022/08/30 07:23:15 - mmengine - INFO - Epoch(train) [310][40/63] lr: 5.3532e-03 eta: 22:30:53 time: 2.9718 data_time: 0.0534 memory: 16201 loss_prob: 0.7563 loss_thr: 0.4652 loss_db: 0.1306 loss: 1.3521 2022/08/30 07:23:29 - mmengine - INFO - Epoch(train) [310][45/63] lr: 5.3532e-03 eta: 22:30:53 time: 2.7948 data_time: 0.0765 memory: 16201 loss_prob: 0.8127 loss_thr: 0.4869 loss_db: 0.1399 loss: 1.4394 2022/08/30 07:23:43 - mmengine - INFO - Epoch(train) [310][50/63] lr: 5.3532e-03 eta: 22:31:18 time: 2.8263 data_time: 0.0866 memory: 16201 loss_prob: 0.8193 loss_thr: 0.4735 loss_db: 0.1350 loss: 1.4278 2022/08/30 07:23:56 - mmengine - INFO - Epoch(train) [310][55/63] lr: 5.3532e-03 eta: 22:31:18 time: 2.7173 data_time: 0.0720 memory: 16201 loss_prob: 0.8476 loss_thr: 0.4840 loss_db: 0.1374 loss: 1.4689 2022/08/30 07:24:08 - mmengine - INFO - Epoch(train) [310][60/63] lr: 5.3532e-03 eta: 22:31:34 time: 2.4996 data_time: 0.0783 memory: 16201 loss_prob: 0.8603 loss_thr: 0.5007 loss_db: 0.1436 loss: 1.5046 2022/08/30 07:24:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:24:34 - mmengine - INFO - Epoch(train) [311][5/63] lr: 5.3478e-03 eta: 22:31:34 time: 2.9478 data_time: 0.2874 memory: 16201 loss_prob: 0.8621 loss_thr: 0.4863 loss_db: 0.1409 loss: 1.4893 2022/08/30 07:24:48 - mmengine - INFO - Epoch(train) [311][10/63] lr: 5.3478e-03 eta: 22:31:50 time: 3.0979 data_time: 0.2892 memory: 16201 loss_prob: 0.8911 loss_thr: 0.4970 loss_db: 0.1475 loss: 1.5356 2022/08/30 07:25:00 - mmengine - INFO - Epoch(train) [311][15/63] lr: 5.3478e-03 eta: 22:31:50 time: 2.6414 data_time: 0.0605 memory: 16201 loss_prob: 0.8289 loss_thr: 0.4566 loss_db: 0.1409 loss: 1.4264 2022/08/30 07:25:12 - mmengine - INFO - Epoch(train) [311][20/63] lr: 5.3478e-03 eta: 22:32:05 time: 2.4754 data_time: 0.0649 memory: 16201 loss_prob: 0.8397 loss_thr: 0.4587 loss_db: 0.1422 loss: 1.4406 2022/08/30 07:25:26 - mmengine - INFO - Epoch(train) [311][25/63] lr: 5.3478e-03 eta: 22:32:05 time: 2.6424 data_time: 0.0660 memory: 16201 loss_prob: 0.8154 loss_thr: 0.4786 loss_db: 0.1387 loss: 1.4327 2022/08/30 07:25:40 - mmengine - INFO - Epoch(train) [311][30/63] lr: 5.3478e-03 eta: 22:32:28 time: 2.7397 data_time: 0.0677 memory: 16201 loss_prob: 0.7673 loss_thr: 0.4879 loss_db: 0.1327 loss: 1.3879 2022/08/30 07:25:52 - mmengine - INFO - Epoch(train) [311][35/63] lr: 5.3478e-03 eta: 22:32:28 time: 2.6011 data_time: 0.0696 memory: 16201 loss_prob: 0.7513 loss_thr: 0.4730 loss_db: 0.1299 loss: 1.3543 2022/08/30 07:26:06 - mmengine - INFO - Epoch(train) [311][40/63] lr: 5.3478e-03 eta: 22:32:47 time: 2.6432 data_time: 0.1124 memory: 16201 loss_prob: 0.7583 loss_thr: 0.4515 loss_db: 0.1276 loss: 1.3375 2022/08/30 07:26:19 - mmengine - INFO - Epoch(train) [311][45/63] lr: 5.3478e-03 eta: 22:32:47 time: 2.6409 data_time: 0.1022 memory: 16201 loss_prob: 0.7823 loss_thr: 0.4655 loss_db: 0.1286 loss: 1.3764 2022/08/30 07:26:32 - mmengine - INFO - Epoch(train) [311][50/63] lr: 5.3478e-03 eta: 22:33:06 time: 2.6143 data_time: 0.0558 memory: 16201 loss_prob: 0.7602 loss_thr: 0.4636 loss_db: 0.1254 loss: 1.3492 2022/08/30 07:26:47 - mmengine - INFO - Epoch(train) [311][55/63] lr: 5.3478e-03 eta: 22:33:06 time: 2.8555 data_time: 0.0618 memory: 16201 loss_prob: 0.7957 loss_thr: 0.4853 loss_db: 0.1347 loss: 1.4157 2022/08/30 07:26:59 - mmengine - INFO - Epoch(train) [311][60/63] lr: 5.3478e-03 eta: 22:33:26 time: 2.6293 data_time: 0.0576 memory: 16201 loss_prob: 0.7612 loss_thr: 0.4845 loss_db: 0.1299 loss: 1.3756 2022/08/30 07:27:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:27:22 - mmengine - INFO - Epoch(train) [312][5/63] lr: 5.3424e-03 eta: 22:33:26 time: 2.7794 data_time: 0.2802 memory: 16201 loss_prob: 0.7527 loss_thr: 0.4801 loss_db: 0.1266 loss: 1.3594 2022/08/30 07:27:34 - mmengine - INFO - Epoch(train) [312][10/63] lr: 5.3424e-03 eta: 22:33:33 time: 2.7935 data_time: 0.2844 memory: 16201 loss_prob: 0.6903 loss_thr: 0.4673 loss_db: 0.1137 loss: 1.2713 2022/08/30 07:27:49 - mmengine - INFO - Epoch(train) [312][15/63] lr: 5.3424e-03 eta: 22:33:33 time: 2.6976 data_time: 0.0453 memory: 16201 loss_prob: 0.7497 loss_thr: 0.4672 loss_db: 0.1258 loss: 1.3427 2022/08/30 07:28:01 - mmengine - INFO - Epoch(train) [312][20/63] lr: 5.3424e-03 eta: 22:33:54 time: 2.7017 data_time: 0.0520 memory: 16201 loss_prob: 0.7967 loss_thr: 0.4627 loss_db: 0.1335 loss: 1.3929 2022/08/30 07:28:14 - mmengine - INFO - Epoch(train) [312][25/63] lr: 5.3424e-03 eta: 22:33:54 time: 2.4761 data_time: 0.0755 memory: 16201 loss_prob: 0.7137 loss_thr: 0.4433 loss_db: 0.1180 loss: 1.2749 2022/08/30 07:28:26 - mmengine - INFO - Epoch(train) [312][30/63] lr: 5.3424e-03 eta: 22:34:09 time: 2.5073 data_time: 0.0580 memory: 16201 loss_prob: 0.6553 loss_thr: 0.4207 loss_db: 0.1117 loss: 1.1877 2022/08/30 07:28:39 - mmengine - INFO - Epoch(train) [312][35/63] lr: 5.3424e-03 eta: 22:34:09 time: 2.5467 data_time: 0.0536 memory: 16201 loss_prob: 0.6476 loss_thr: 0.4071 loss_db: 0.1098 loss: 1.1645 2022/08/30 07:28:54 - mmengine - INFO - Epoch(train) [312][40/63] lr: 5.3424e-03 eta: 22:34:33 time: 2.7911 data_time: 0.0545 memory: 16201 loss_prob: 0.6879 loss_thr: 0.4251 loss_db: 0.1149 loss: 1.2279 2022/08/30 07:29:07 - mmengine - INFO - Epoch(train) [312][45/63] lr: 5.3424e-03 eta: 22:34:33 time: 2.7641 data_time: 0.0461 memory: 16201 loss_prob: 0.7317 loss_thr: 0.4496 loss_db: 0.1221 loss: 1.3035 2022/08/30 07:29:20 - mmengine - INFO - Epoch(train) [312][50/63] lr: 5.3424e-03 eta: 22:34:52 time: 2.6299 data_time: 0.0556 memory: 16201 loss_prob: 0.7137 loss_thr: 0.4359 loss_db: 0.1207 loss: 1.2703 2022/08/30 07:29:33 - mmengine - INFO - Epoch(train) [312][55/63] lr: 5.3424e-03 eta: 22:34:52 time: 2.6131 data_time: 0.0433 memory: 16201 loss_prob: 0.7160 loss_thr: 0.4364 loss_db: 0.1218 loss: 1.2742 2022/08/30 07:29:47 - mmengine - INFO - Epoch(train) [312][60/63] lr: 5.3424e-03 eta: 22:35:12 time: 2.6670 data_time: 0.0417 memory: 16201 loss_prob: 0.7068 loss_thr: 0.4476 loss_db: 0.1181 loss: 1.2726 2022/08/30 07:29:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:30:10 - mmengine - INFO - Epoch(train) [313][5/63] lr: 5.3370e-03 eta: 22:35:12 time: 2.8017 data_time: 0.2659 memory: 16201 loss_prob: 0.7472 loss_thr: 0.4953 loss_db: 0.1206 loss: 1.3631 2022/08/30 07:30:22 - mmengine - INFO - Epoch(train) [313][10/63] lr: 5.3370e-03 eta: 22:35:22 time: 2.9015 data_time: 0.2780 memory: 16201 loss_prob: 0.7632 loss_thr: 0.4875 loss_db: 0.1295 loss: 1.3801 2022/08/30 07:30:36 - mmengine - INFO - Epoch(train) [313][15/63] lr: 5.3370e-03 eta: 22:35:22 time: 2.5304 data_time: 0.0527 memory: 16201 loss_prob: 0.7611 loss_thr: 0.4766 loss_db: 0.1319 loss: 1.3697 2022/08/30 07:30:47 - mmengine - INFO - Epoch(train) [313][20/63] lr: 5.3370e-03 eta: 22:35:38 time: 2.5402 data_time: 0.0651 memory: 16201 loss_prob: 0.7030 loss_thr: 0.4597 loss_db: 0.1185 loss: 1.2812 2022/08/30 07:31:00 - mmengine - INFO - Epoch(train) [313][25/63] lr: 5.3370e-03 eta: 22:35:38 time: 2.4543 data_time: 0.0636 memory: 16201 loss_prob: 0.7224 loss_thr: 0.4634 loss_db: 0.1195 loss: 1.3053 2022/08/30 07:31:14 - mmengine - INFO - Epoch(train) [313][30/63] lr: 5.3370e-03 eta: 22:35:58 time: 2.6649 data_time: 0.0549 memory: 16201 loss_prob: 0.8345 loss_thr: 0.4546 loss_db: 0.1381 loss: 1.4272 2022/08/30 07:31:28 - mmengine - INFO - Epoch(train) [313][35/63] lr: 5.3370e-03 eta: 22:35:58 time: 2.7929 data_time: 0.0731 memory: 16201 loss_prob: 0.7715 loss_thr: 0.4200 loss_db: 0.1293 loss: 1.3208 2022/08/30 07:31:42 - mmengine - INFO - Epoch(train) [313][40/63] lr: 5.3370e-03 eta: 22:36:22 time: 2.7909 data_time: 0.0551 memory: 16201 loss_prob: 0.7134 loss_thr: 0.4281 loss_db: 0.1142 loss: 1.2557 2022/08/30 07:31:55 - mmengine - INFO - Epoch(train) [313][45/63] lr: 5.3370e-03 eta: 22:36:22 time: 2.6509 data_time: 0.0534 memory: 16201 loss_prob: 0.7951 loss_thr: 0.4766 loss_db: 0.1296 loss: 1.4012 2022/08/30 07:32:08 - mmengine - INFO - Epoch(train) [313][50/63] lr: 5.3370e-03 eta: 22:36:39 time: 2.5970 data_time: 0.0718 memory: 16201 loss_prob: 0.8536 loss_thr: 0.4924 loss_db: 0.1462 loss: 1.4923 2022/08/30 07:32:22 - mmengine - INFO - Epoch(train) [313][55/63] lr: 5.3370e-03 eta: 22:36:39 time: 2.7139 data_time: 0.0569 memory: 16201 loss_prob: 0.8316 loss_thr: 0.4718 loss_db: 0.1397 loss: 1.4431 2022/08/30 07:32:37 - mmengine - INFO - Epoch(train) [313][60/63] lr: 5.3370e-03 eta: 22:37:05 time: 2.8595 data_time: 0.0550 memory: 16201 loss_prob: 0.7599 loss_thr: 0.4353 loss_db: 0.1330 loss: 1.3283 2022/08/30 07:32:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:32:56 - mmengine - INFO - Epoch(train) [314][5/63] lr: 5.3315e-03 eta: 22:37:05 time: 2.5165 data_time: 0.2923 memory: 16201 loss_prob: 0.6749 loss_thr: 0.4306 loss_db: 0.1128 loss: 1.2183 2022/08/30 07:33:11 - mmengine - INFO - Epoch(train) [314][10/63] lr: 5.3315e-03 eta: 22:37:12 time: 2.8283 data_time: 0.2953 memory: 16201 loss_prob: 0.7366 loss_thr: 0.4585 loss_db: 0.1256 loss: 1.3207 2022/08/30 07:33:24 - mmengine - INFO - Epoch(train) [314][15/63] lr: 5.3315e-03 eta: 22:37:12 time: 2.7721 data_time: 0.0618 memory: 16201 loss_prob: 0.7960 loss_thr: 0.4820 loss_db: 0.1336 loss: 1.4116 2022/08/30 07:33:38 - mmengine - INFO - Epoch(train) [314][20/63] lr: 5.3315e-03 eta: 22:37:33 time: 2.6943 data_time: 0.0675 memory: 16201 loss_prob: 0.7456 loss_thr: 0.4512 loss_db: 0.1261 loss: 1.3229 2022/08/30 07:33:52 - mmengine - INFO - Epoch(train) [314][25/63] lr: 5.3315e-03 eta: 22:37:33 time: 2.7840 data_time: 0.0768 memory: 16201 loss_prob: 0.6711 loss_thr: 0.4212 loss_db: 0.1127 loss: 1.2050 2022/08/30 07:34:05 - mmengine - INFO - Epoch(train) [314][30/63] lr: 5.3315e-03 eta: 22:37:53 time: 2.6914 data_time: 0.0609 memory: 16201 loss_prob: 0.6832 loss_thr: 0.4376 loss_db: 0.1106 loss: 1.2314 2022/08/30 07:34:16 - mmengine - INFO - Epoch(train) [314][35/63] lr: 5.3315e-03 eta: 22:37:53 time: 2.3722 data_time: 0.0771 memory: 16201 loss_prob: 0.7385 loss_thr: 0.4651 loss_db: 0.1231 loss: 1.3266 2022/08/30 07:34:29 - mmengine - INFO - Epoch(train) [314][40/63] lr: 5.3315e-03 eta: 22:38:05 time: 2.4202 data_time: 0.0708 memory: 16201 loss_prob: 0.7369 loss_thr: 0.4653 loss_db: 0.1247 loss: 1.3269 2022/08/30 07:34:42 - mmengine - INFO - Epoch(train) [314][45/63] lr: 5.3315e-03 eta: 22:38:05 time: 2.5877 data_time: 0.0530 memory: 16201 loss_prob: 0.6858 loss_thr: 0.4396 loss_db: 0.1152 loss: 1.2406 2022/08/30 07:34:54 - mmengine - INFO - Epoch(train) [314][50/63] lr: 5.3315e-03 eta: 22:38:22 time: 2.5555 data_time: 0.0628 memory: 16201 loss_prob: 0.7261 loss_thr: 0.4614 loss_db: 0.1255 loss: 1.3131 2022/08/30 07:35:08 - mmengine - INFO - Epoch(train) [314][55/63] lr: 5.3315e-03 eta: 22:38:22 time: 2.6536 data_time: 0.0589 memory: 16201 loss_prob: 0.7173 loss_thr: 0.4566 loss_db: 0.1235 loss: 1.2974 2022/08/30 07:35:22 - mmengine - INFO - Epoch(train) [314][60/63] lr: 5.3315e-03 eta: 22:38:44 time: 2.7486 data_time: 0.0661 memory: 16201 loss_prob: 0.6653 loss_thr: 0.4345 loss_db: 0.1125 loss: 1.2123 2022/08/30 07:35:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:35:48 - mmengine - INFO - Epoch(train) [315][5/63] lr: 5.3261e-03 eta: 22:38:44 time: 3.2617 data_time: 0.2766 memory: 16201 loss_prob: 0.7193 loss_thr: 0.4410 loss_db: 0.1227 loss: 1.2830 2022/08/30 07:36:02 - mmengine - INFO - Epoch(train) [315][10/63] lr: 5.3261e-03 eta: 22:39:01 time: 3.2031 data_time: 0.2873 memory: 16201 loss_prob: 0.7185 loss_thr: 0.4391 loss_db: 0.1240 loss: 1.2816 2022/08/30 07:36:14 - mmengine - INFO - Epoch(train) [315][15/63] lr: 5.3261e-03 eta: 22:39:01 time: 2.5816 data_time: 0.0615 memory: 16201 loss_prob: 0.6869 loss_thr: 0.4451 loss_db: 0.1174 loss: 1.2494 2022/08/30 07:36:28 - mmengine - INFO - Epoch(train) [315][20/63] lr: 5.3261e-03 eta: 22:39:18 time: 2.5652 data_time: 0.0525 memory: 16201 loss_prob: 0.6627 loss_thr: 0.4401 loss_db: 0.1094 loss: 1.2122 2022/08/30 07:36:40 - mmengine - INFO - Epoch(train) [315][25/63] lr: 5.3261e-03 eta: 22:39:18 time: 2.5704 data_time: 0.0554 memory: 16201 loss_prob: 0.7070 loss_thr: 0.4384 loss_db: 0.1197 loss: 1.2652 2022/08/30 07:36:53 - mmengine - INFO - Epoch(train) [315][30/63] lr: 5.3261e-03 eta: 22:39:34 time: 2.5532 data_time: 0.0526 memory: 16201 loss_prob: 0.7670 loss_thr: 0.4617 loss_db: 0.1309 loss: 1.3596 2022/08/30 07:37:05 - mmengine - INFO - Epoch(train) [315][35/63] lr: 5.3261e-03 eta: 22:39:34 time: 2.5623 data_time: 0.0785 memory: 16201 loss_prob: 0.7260 loss_thr: 0.4593 loss_db: 0.1224 loss: 1.3076 2022/08/30 07:37:19 - mmengine - INFO - Epoch(train) [315][40/63] lr: 5.3261e-03 eta: 22:39:50 time: 2.5655 data_time: 0.0721 memory: 16201 loss_prob: 0.7071 loss_thr: 0.4533 loss_db: 0.1216 loss: 1.2821 2022/08/30 07:37:31 - mmengine - INFO - Epoch(train) [315][45/63] lr: 5.3261e-03 eta: 22:39:50 time: 2.6017 data_time: 0.0490 memory: 16201 loss_prob: 0.6569 loss_thr: 0.4284 loss_db: 0.1159 loss: 1.2013 2022/08/30 07:37:46 - mmengine - INFO - Epoch(train) [315][50/63] lr: 5.3261e-03 eta: 22:40:12 time: 2.7349 data_time: 0.0627 memory: 16201 loss_prob: 0.6374 loss_thr: 0.4204 loss_db: 0.1109 loss: 1.1686 2022/08/30 07:38:00 - mmengine - INFO - Epoch(train) [315][55/63] lr: 5.3261e-03 eta: 22:40:12 time: 2.8221 data_time: 0.0808 memory: 16201 loss_prob: 0.7068 loss_thr: 0.4506 loss_db: 0.1188 loss: 1.2761 2022/08/30 07:38:13 - mmengine - INFO - Epoch(train) [315][60/63] lr: 5.3261e-03 eta: 22:40:30 time: 2.6503 data_time: 0.0612 memory: 16201 loss_prob: 0.7476 loss_thr: 0.4589 loss_db: 0.1260 loss: 1.3325 2022/08/30 07:38:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:38:35 - mmengine - INFO - Epoch(train) [316][5/63] lr: 5.3207e-03 eta: 22:40:30 time: 2.7897 data_time: 0.2719 memory: 16201 loss_prob: 0.7620 loss_thr: 0.4722 loss_db: 0.1313 loss: 1.3656 2022/08/30 07:38:48 - mmengine - INFO - Epoch(train) [316][10/63] lr: 5.3207e-03 eta: 22:40:38 time: 2.8497 data_time: 0.2839 memory: 16201 loss_prob: 0.6842 loss_thr: 0.4330 loss_db: 0.1174 loss: 1.2346 2022/08/30 07:38:59 - mmengine - INFO - Epoch(train) [316][15/63] lr: 5.3207e-03 eta: 22:40:38 time: 2.4185 data_time: 0.0532 memory: 16201 loss_prob: 0.6651 loss_thr: 0.4380 loss_db: 0.1134 loss: 1.2165 2022/08/30 07:39:14 - mmengine - INFO - Epoch(train) [316][20/63] lr: 5.3207e-03 eta: 22:40:54 time: 2.5601 data_time: 0.0571 memory: 16201 loss_prob: 0.7068 loss_thr: 0.4747 loss_db: 0.1219 loss: 1.3034 2022/08/30 07:39:27 - mmengine - INFO - Epoch(train) [316][25/63] lr: 5.3207e-03 eta: 22:40:54 time: 2.7611 data_time: 0.0753 memory: 16201 loss_prob: 0.7327 loss_thr: 0.4816 loss_db: 0.1265 loss: 1.3408 2022/08/30 07:39:40 - mmengine - INFO - Epoch(train) [316][30/63] lr: 5.3207e-03 eta: 22:41:12 time: 2.6409 data_time: 0.0665 memory: 16201 loss_prob: 0.7191 loss_thr: 0.4482 loss_db: 0.1220 loss: 1.2893 2022/08/30 07:39:53 - mmengine - INFO - Epoch(train) [316][35/63] lr: 5.3207e-03 eta: 22:41:12 time: 2.6501 data_time: 0.0657 memory: 16201 loss_prob: 0.7009 loss_thr: 0.4340 loss_db: 0.1190 loss: 1.2539 2022/08/30 07:40:06 - mmengine - INFO - Epoch(train) [316][40/63] lr: 5.3207e-03 eta: 22:41:30 time: 2.6156 data_time: 0.0568 memory: 16201 loss_prob: 0.6730 loss_thr: 0.4223 loss_db: 0.1167 loss: 1.2120 2022/08/30 07:40:22 - mmengine - INFO - Epoch(train) [316][45/63] lr: 5.3207e-03 eta: 22:41:30 time: 2.8233 data_time: 0.0503 memory: 16201 loss_prob: 0.7044 loss_thr: 0.4539 loss_db: 0.1212 loss: 1.2795 2022/08/30 07:40:35 - mmengine - INFO - Epoch(train) [316][50/63] lr: 5.3207e-03 eta: 22:41:55 time: 2.8909 data_time: 0.0681 memory: 16201 loss_prob: 0.6825 loss_thr: 0.4535 loss_db: 0.1152 loss: 1.2512 2022/08/30 07:40:49 - mmengine - INFO - Epoch(train) [316][55/63] lr: 5.3207e-03 eta: 22:41:55 time: 2.7026 data_time: 0.0522 memory: 16201 loss_prob: 0.6253 loss_thr: 0.4328 loss_db: 0.1068 loss: 1.1649 2022/08/30 07:41:03 - mmengine - INFO - Epoch(train) [316][60/63] lr: 5.3207e-03 eta: 22:42:16 time: 2.7495 data_time: 0.0535 memory: 16201 loss_prob: 0.6891 loss_thr: 0.4447 loss_db: 0.1160 loss: 1.2498 2022/08/30 07:41:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:41:23 - mmengine - INFO - Epoch(train) [317][5/63] lr: 5.3153e-03 eta: 22:42:16 time: 2.6256 data_time: 0.2802 memory: 16201 loss_prob: 0.7174 loss_thr: 0.4279 loss_db: 0.1163 loss: 1.2616 2022/08/30 07:41:37 - mmengine - INFO - Epoch(train) [317][10/63] lr: 5.3153e-03 eta: 22:42:22 time: 2.8108 data_time: 0.2821 memory: 16201 loss_prob: 0.6563 loss_thr: 0.3955 loss_db: 0.1065 loss: 1.1583 2022/08/30 07:41:49 - mmengine - INFO - Epoch(train) [317][15/63] lr: 5.3153e-03 eta: 22:42:22 time: 2.5774 data_time: 0.0553 memory: 16201 loss_prob: 0.6656 loss_thr: 0.4005 loss_db: 0.1105 loss: 1.1766 2022/08/30 07:42:03 - mmengine - INFO - Epoch(train) [317][20/63] lr: 5.3153e-03 eta: 22:42:41 time: 2.6644 data_time: 0.0595 memory: 16201 loss_prob: 0.6546 loss_thr: 0.4192 loss_db: 0.1114 loss: 1.1853 2022/08/30 07:42:15 - mmengine - INFO - Epoch(train) [317][25/63] lr: 5.3153e-03 eta: 22:42:41 time: 2.6571 data_time: 0.0685 memory: 16201 loss_prob: 0.7115 loss_thr: 0.4501 loss_db: 0.1203 loss: 1.2819 2022/08/30 07:42:29 - mmengine - INFO - Epoch(train) [317][30/63] lr: 5.3153e-03 eta: 22:42:56 time: 2.5401 data_time: 0.0569 memory: 16201 loss_prob: 0.7278 loss_thr: 0.4665 loss_db: 0.1246 loss: 1.3189 2022/08/30 07:42:43 - mmengine - INFO - Epoch(train) [317][35/63] lr: 5.3153e-03 eta: 22:42:56 time: 2.7370 data_time: 0.0564 memory: 16201 loss_prob: 0.7185 loss_thr: 0.4441 loss_db: 0.1230 loss: 1.2856 2022/08/30 07:42:55 - mmengine - INFO - Epoch(train) [317][40/63] lr: 5.3153e-03 eta: 22:43:14 time: 2.6411 data_time: 0.0586 memory: 16201 loss_prob: 0.6794 loss_thr: 0.4247 loss_db: 0.1162 loss: 1.2203 2022/08/30 07:43:09 - mmengine - INFO - Epoch(train) [317][45/63] lr: 5.3153e-03 eta: 22:43:14 time: 2.5970 data_time: 0.0637 memory: 16201 loss_prob: 0.6678 loss_thr: 0.4315 loss_db: 0.1116 loss: 1.2109 2022/08/30 07:43:22 - mmengine - INFO - Epoch(train) [317][50/63] lr: 5.3153e-03 eta: 22:43:33 time: 2.6527 data_time: 0.0744 memory: 16201 loss_prob: 0.6970 loss_thr: 0.4442 loss_db: 0.1145 loss: 1.2557 2022/08/30 07:43:35 - mmengine - INFO - Epoch(train) [317][55/63] lr: 5.3153e-03 eta: 22:43:33 time: 2.6607 data_time: 0.0639 memory: 16201 loss_prob: 0.7076 loss_thr: 0.4537 loss_db: 0.1195 loss: 1.2808 2022/08/30 07:43:48 - mmengine - INFO - Epoch(train) [317][60/63] lr: 5.3153e-03 eta: 22:43:50 time: 2.6142 data_time: 0.0626 memory: 16201 loss_prob: 0.6858 loss_thr: 0.4419 loss_db: 0.1171 loss: 1.2448 2022/08/30 07:43:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:44:11 - mmengine - INFO - Epoch(train) [318][5/63] lr: 5.3099e-03 eta: 22:43:50 time: 2.9500 data_time: 0.2894 memory: 16201 loss_prob: 0.6929 loss_thr: 0.4684 loss_db: 0.1175 loss: 1.2788 2022/08/30 07:44:23 - mmengine - INFO - Epoch(train) [318][10/63] lr: 5.3099e-03 eta: 22:43:57 time: 2.8410 data_time: 0.3109 memory: 16201 loss_prob: 0.7027 loss_thr: 0.4620 loss_db: 0.1194 loss: 1.2841 2022/08/30 07:44:36 - mmengine - INFO - Epoch(train) [318][15/63] lr: 5.3099e-03 eta: 22:43:57 time: 2.5166 data_time: 0.0552 memory: 16201 loss_prob: 0.6997 loss_thr: 0.4298 loss_db: 0.1148 loss: 1.2443 2022/08/30 07:44:50 - mmengine - INFO - Epoch(train) [318][20/63] lr: 5.3099e-03 eta: 22:44:14 time: 2.6405 data_time: 0.0470 memory: 16201 loss_prob: 0.7108 loss_thr: 0.4240 loss_db: 0.1172 loss: 1.2520 2022/08/30 07:45:01 - mmengine - INFO - Epoch(train) [318][25/63] lr: 5.3099e-03 eta: 22:44:14 time: 2.5227 data_time: 0.0655 memory: 16201 loss_prob: 0.6711 loss_thr: 0.4210 loss_db: 0.1146 loss: 1.2067 2022/08/30 07:45:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:45:13 - mmengine - INFO - Epoch(train) [318][30/63] lr: 5.3099e-03 eta: 22:44:25 time: 2.3661 data_time: 0.0604 memory: 16201 loss_prob: 0.7165 loss_thr: 0.4301 loss_db: 0.1210 loss: 1.2676 2022/08/30 07:45:26 - mmengine - INFO - Epoch(train) [318][35/63] lr: 5.3099e-03 eta: 22:44:25 time: 2.4794 data_time: 0.0583 memory: 16201 loss_prob: 0.7231 loss_thr: 0.4484 loss_db: 0.1212 loss: 1.2926 2022/08/30 07:45:39 - mmengine - INFO - Epoch(train) [318][40/63] lr: 5.3099e-03 eta: 22:44:40 time: 2.5567 data_time: 0.0499 memory: 16201 loss_prob: 0.6441 loss_thr: 0.4058 loss_db: 0.1089 loss: 1.1588 2022/08/30 07:45:52 - mmengine - INFO - Epoch(train) [318][45/63] lr: 5.3099e-03 eta: 22:44:40 time: 2.5723 data_time: 0.0554 memory: 16201 loss_prob: 0.6693 loss_thr: 0.4133 loss_db: 0.1126 loss: 1.1951 2022/08/30 07:46:04 - mmengine - INFO - Epoch(train) [318][50/63] lr: 5.3099e-03 eta: 22:44:55 time: 2.5462 data_time: 0.0634 memory: 16201 loss_prob: 0.6652 loss_thr: 0.4378 loss_db: 0.1134 loss: 1.2164 2022/08/30 07:46:18 - mmengine - INFO - Epoch(train) [318][55/63] lr: 5.3099e-03 eta: 22:44:55 time: 2.6869 data_time: 0.0574 memory: 16201 loss_prob: 0.6396 loss_thr: 0.4307 loss_db: 0.1116 loss: 1.1820 2022/08/30 07:46:31 - mmengine - INFO - Epoch(train) [318][60/63] lr: 5.3099e-03 eta: 22:45:14 time: 2.7014 data_time: 0.0618 memory: 16201 loss_prob: 0.6828 loss_thr: 0.4250 loss_db: 0.1129 loss: 1.2207 2022/08/30 07:46:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:46:52 - mmengine - INFO - Epoch(train) [319][5/63] lr: 5.3045e-03 eta: 22:45:14 time: 2.6493 data_time: 0.2667 memory: 16201 loss_prob: 0.6888 loss_thr: 0.4377 loss_db: 0.1147 loss: 1.2412 2022/08/30 07:47:05 - mmengine - INFO - Epoch(train) [319][10/63] lr: 5.3045e-03 eta: 22:45:20 time: 2.7943 data_time: 0.2641 memory: 16201 loss_prob: 0.7357 loss_thr: 0.4599 loss_db: 0.1236 loss: 1.3191 2022/08/30 07:47:18 - mmengine - INFO - Epoch(train) [319][15/63] lr: 5.3045e-03 eta: 22:45:20 time: 2.5296 data_time: 0.0634 memory: 16201 loss_prob: 0.7457 loss_thr: 0.4555 loss_db: 0.1230 loss: 1.3241 2022/08/30 07:47:31 - mmengine - INFO - Epoch(train) [319][20/63] lr: 5.3045e-03 eta: 22:45:36 time: 2.6171 data_time: 0.0653 memory: 16201 loss_prob: 0.7119 loss_thr: 0.4513 loss_db: 0.1206 loss: 1.2838 2022/08/30 07:47:44 - mmengine - INFO - Epoch(train) [319][25/63] lr: 5.3045e-03 eta: 22:45:36 time: 2.6417 data_time: 0.0610 memory: 16201 loss_prob: 0.6930 loss_thr: 0.4405 loss_db: 0.1188 loss: 1.2523 2022/08/30 07:47:56 - mmengine - INFO - Epoch(train) [319][30/63] lr: 5.3045e-03 eta: 22:45:51 time: 2.5184 data_time: 0.0629 memory: 16201 loss_prob: 0.6452 loss_thr: 0.4208 loss_db: 0.1112 loss: 1.1772 2022/08/30 07:48:10 - mmengine - INFO - Epoch(train) [319][35/63] lr: 5.3045e-03 eta: 22:45:51 time: 2.5778 data_time: 0.0611 memory: 16201 loss_prob: 0.6504 loss_thr: 0.4315 loss_db: 0.1138 loss: 1.1956 2022/08/30 07:48:24 - mmengine - INFO - Epoch(train) [319][40/63] lr: 5.3045e-03 eta: 22:46:11 time: 2.7567 data_time: 0.0603 memory: 16201 loss_prob: 0.6572 loss_thr: 0.4355 loss_db: 0.1130 loss: 1.2057 2022/08/30 07:48:36 - mmengine - INFO - Epoch(train) [319][45/63] lr: 5.3045e-03 eta: 22:46:11 time: 2.6289 data_time: 0.0684 memory: 16201 loss_prob: 0.7402 loss_thr: 0.4524 loss_db: 0.1217 loss: 1.3143 2022/08/30 07:48:48 - mmengine - INFO - Epoch(train) [319][50/63] lr: 5.3045e-03 eta: 22:46:22 time: 2.3950 data_time: 0.0679 memory: 16201 loss_prob: 0.7411 loss_thr: 0.4608 loss_db: 0.1245 loss: 1.3264 2022/08/30 07:49:02 - mmengine - INFO - Epoch(train) [319][55/63] lr: 5.3045e-03 eta: 22:46:22 time: 2.6290 data_time: 0.0637 memory: 16201 loss_prob: 0.6094 loss_thr: 0.4235 loss_db: 0.1047 loss: 1.1376 2022/08/30 07:49:16 - mmengine - INFO - Epoch(train) [319][60/63] lr: 5.3045e-03 eta: 22:46:44 time: 2.8223 data_time: 0.0626 memory: 16201 loss_prob: 0.6871 loss_thr: 0.4568 loss_db: 0.1144 loss: 1.2583 2022/08/30 07:49:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:49:37 - mmengine - INFO - Epoch(train) [320][5/63] lr: 5.2990e-03 eta: 22:46:44 time: 2.7103 data_time: 0.3022 memory: 16201 loss_prob: 0.7231 loss_thr: 0.4727 loss_db: 0.1239 loss: 1.3197 2022/08/30 07:49:51 - mmengine - INFO - Epoch(train) [320][10/63] lr: 5.2990e-03 eta: 22:46:52 time: 2.8953 data_time: 0.3055 memory: 16201 loss_prob: 0.6601 loss_thr: 0.4230 loss_db: 0.1087 loss: 1.1919 2022/08/30 07:50:04 - mmengine - INFO - Epoch(train) [320][15/63] lr: 5.2990e-03 eta: 22:46:52 time: 2.6477 data_time: 0.0683 memory: 16201 loss_prob: 0.6936 loss_thr: 0.4316 loss_db: 0.1154 loss: 1.2406 2022/08/30 07:50:18 - mmengine - INFO - Epoch(train) [320][20/63] lr: 5.2990e-03 eta: 22:47:09 time: 2.6402 data_time: 0.0771 memory: 16201 loss_prob: 0.7549 loss_thr: 0.4603 loss_db: 0.1289 loss: 1.3441 2022/08/30 07:50:32 - mmengine - INFO - Epoch(train) [320][25/63] lr: 5.2990e-03 eta: 22:47:09 time: 2.8212 data_time: 0.0621 memory: 16201 loss_prob: 0.7049 loss_thr: 0.4530 loss_db: 0.1207 loss: 1.2786 2022/08/30 07:50:46 - mmengine - INFO - Epoch(train) [320][30/63] lr: 5.2990e-03 eta: 22:47:31 time: 2.8202 data_time: 0.0614 memory: 16201 loss_prob: 0.6277 loss_thr: 0.4192 loss_db: 0.1077 loss: 1.1546 2022/08/30 07:50:59 - mmengine - INFO - Epoch(train) [320][35/63] lr: 5.2990e-03 eta: 22:47:31 time: 2.7169 data_time: 0.0793 memory: 16201 loss_prob: 0.6957 loss_thr: 0.4434 loss_db: 0.1187 loss: 1.2578 2022/08/30 07:51:14 - mmengine - INFO - Epoch(train) [320][40/63] lr: 5.2990e-03 eta: 22:47:52 time: 2.7702 data_time: 0.0616 memory: 16201 loss_prob: 0.6833 loss_thr: 0.4387 loss_db: 0.1191 loss: 1.2412 2022/08/30 07:51:26 - mmengine - INFO - Epoch(train) [320][45/63] lr: 5.2990e-03 eta: 22:47:52 time: 2.6622 data_time: 0.0590 memory: 16201 loss_prob: 0.6615 loss_thr: 0.4264 loss_db: 0.1139 loss: 1.2018 2022/08/30 07:51:39 - mmengine - INFO - Epoch(train) [320][50/63] lr: 5.2990e-03 eta: 22:48:07 time: 2.5513 data_time: 0.0649 memory: 16201 loss_prob: 0.6946 loss_thr: 0.4562 loss_db: 0.1159 loss: 1.2668 2022/08/30 07:51:53 - mmengine - INFO - Epoch(train) [320][55/63] lr: 5.2990e-03 eta: 22:48:07 time: 2.7178 data_time: 0.0570 memory: 16201 loss_prob: 0.6957 loss_thr: 0.4556 loss_db: 0.1201 loss: 1.2714 2022/08/30 07:52:06 - mmengine - INFO - Epoch(train) [320][60/63] lr: 5.2990e-03 eta: 22:48:25 time: 2.6742 data_time: 0.0596 memory: 16201 loss_prob: 0.6811 loss_thr: 0.4380 loss_db: 0.1197 loss: 1.2387 2022/08/30 07:52:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:52:12 - mmengine - INFO - Saving checkpoint at 320 epochs 2022/08/30 07:52:21 - mmengine - INFO - Epoch(val) [320][5/32] eta: 22:48:25 time: 0.7262 data_time: 0.1572 memory: 16201 2022/08/30 07:52:25 - mmengine - INFO - Epoch(val) [320][10/32] eta: 0:00:17 time: 0.8067 data_time: 0.1958 memory: 15734 2022/08/30 07:52:28 - mmengine - INFO - Epoch(val) [320][15/32] eta: 0:00:17 time: 0.6553 data_time: 0.0630 memory: 15734 2022/08/30 07:52:31 - mmengine - INFO - Epoch(val) [320][20/32] eta: 0:00:07 time: 0.6463 data_time: 0.0593 memory: 15734 2022/08/30 07:52:35 - mmengine - INFO - Epoch(val) [320][25/32] eta: 0:00:07 time: 0.7105 data_time: 0.0637 memory: 15734 2022/08/30 07:52:38 - mmengine - INFO - Epoch(val) [320][30/32] eta: 0:00:01 time: 0.6826 data_time: 0.0451 memory: 15734 2022/08/30 07:52:39 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 07:52:39 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8185, precision: 0.7944, hmean: 0.8063 2022/08/30 07:52:39 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8180, precision: 0.8386, hmean: 0.8282 2022/08/30 07:52:39 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8137, precision: 0.8707, hmean: 0.8412 2022/08/30 07:52:39 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8002, precision: 0.8921, hmean: 0.8437 2022/08/30 07:52:39 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7689, precision: 0.9152, hmean: 0.8357 2022/08/30 07:52:39 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6081, precision: 0.9496, hmean: 0.7414 2022/08/30 07:52:39 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0448, precision: 0.9894, hmean: 0.0857 2022/08/30 07:52:39 - mmengine - INFO - Epoch(val) [320][32/32] icdar/precision: 0.8921 icdar/recall: 0.8002 icdar/hmean: 0.8437 2022/08/30 07:52:54 - mmengine - INFO - Epoch(train) [321][5/63] lr: 5.2936e-03 eta: 0:00:01 time: 2.6364 data_time: 0.2757 memory: 16201 loss_prob: 0.7237 loss_thr: 0.4751 loss_db: 0.1205 loss: 1.3193 2022/08/30 07:53:06 - mmengine - INFO - Epoch(train) [321][10/63] lr: 5.2936e-03 eta: 22:48:27 time: 2.7002 data_time: 0.2878 memory: 16201 loss_prob: 0.7155 loss_thr: 0.4649 loss_db: 0.1226 loss: 1.3030 2022/08/30 07:53:19 - mmengine - INFO - Epoch(train) [321][15/63] lr: 5.2936e-03 eta: 22:48:27 time: 2.4669 data_time: 0.0566 memory: 16201 loss_prob: 0.7205 loss_thr: 0.4477 loss_db: 0.1230 loss: 1.2912 2022/08/30 07:53:32 - mmengine - INFO - Epoch(train) [321][20/63] lr: 5.2936e-03 eta: 22:48:44 time: 2.6231 data_time: 0.0672 memory: 16201 loss_prob: 0.7324 loss_thr: 0.4506 loss_db: 0.1224 loss: 1.3054 2022/08/30 07:53:45 - mmengine - INFO - Epoch(train) [321][25/63] lr: 5.2936e-03 eta: 22:48:44 time: 2.5685 data_time: 0.0794 memory: 16201 loss_prob: 0.6389 loss_thr: 0.4139 loss_db: 0.1091 loss: 1.1619 2022/08/30 07:53:58 - mmengine - INFO - Epoch(train) [321][30/63] lr: 5.2936e-03 eta: 22:48:59 time: 2.5876 data_time: 0.0501 memory: 16201 loss_prob: 0.6199 loss_thr: 0.4003 loss_db: 0.1074 loss: 1.1275 2022/08/30 07:54:11 - mmengine - INFO - Epoch(train) [321][35/63] lr: 5.2936e-03 eta: 22:48:59 time: 2.6275 data_time: 0.0665 memory: 16201 loss_prob: 0.6917 loss_thr: 0.4400 loss_db: 0.1158 loss: 1.2476 2022/08/30 07:54:24 - mmengine - INFO - Epoch(train) [321][40/63] lr: 5.2936e-03 eta: 22:49:14 time: 2.5850 data_time: 0.0603 memory: 16201 loss_prob: 0.7327 loss_thr: 0.4693 loss_db: 0.1204 loss: 1.3223 2022/08/30 07:54:39 - mmengine - INFO - Epoch(train) [321][45/63] lr: 5.2936e-03 eta: 22:49:14 time: 2.7977 data_time: 0.0545 memory: 16201 loss_prob: 0.7317 loss_thr: 0.4433 loss_db: 0.1237 loss: 1.2987 2022/08/30 07:54:53 - mmengine - INFO - Epoch(train) [321][50/63] lr: 5.2936e-03 eta: 22:49:39 time: 2.9265 data_time: 0.0694 memory: 16201 loss_prob: 0.7210 loss_thr: 0.4401 loss_db: 0.1227 loss: 1.2838 2022/08/30 07:55:05 - mmengine - INFO - Epoch(train) [321][55/63] lr: 5.2936e-03 eta: 22:49:39 time: 2.6230 data_time: 0.0432 memory: 16201 loss_prob: 0.7118 loss_thr: 0.4590 loss_db: 0.1204 loss: 1.2912 2022/08/30 07:55:17 - mmengine - INFO - Epoch(train) [321][60/63] lr: 5.2936e-03 eta: 22:49:48 time: 2.3633 data_time: 0.0436 memory: 16201 loss_prob: 0.6625 loss_thr: 0.4239 loss_db: 0.1138 loss: 1.2002 2022/08/30 07:55:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:55:40 - mmengine - INFO - Epoch(train) [322][5/63] lr: 5.2882e-03 eta: 22:49:48 time: 2.7263 data_time: 0.2820 memory: 16201 loss_prob: 0.6690 loss_thr: 0.4488 loss_db: 0.1135 loss: 1.2312 2022/08/30 07:55:54 - mmengine - INFO - Epoch(train) [322][10/63] lr: 5.2882e-03 eta: 22:50:00 time: 3.0581 data_time: 0.2994 memory: 16201 loss_prob: 0.7339 loss_thr: 0.4602 loss_db: 0.1254 loss: 1.3195 2022/08/30 07:56:07 - mmengine - INFO - Epoch(train) [322][15/63] lr: 5.2882e-03 eta: 22:50:00 time: 2.7323 data_time: 0.0522 memory: 16201 loss_prob: 0.7521 loss_thr: 0.4601 loss_db: 0.1266 loss: 1.3388 2022/08/30 07:56:21 - mmengine - INFO - Epoch(train) [322][20/63] lr: 5.2882e-03 eta: 22:50:20 time: 2.7430 data_time: 0.0801 memory: 16201 loss_prob: 0.8102 loss_thr: 0.4825 loss_db: 0.1275 loss: 1.4202 2022/08/30 07:56:34 - mmengine - INFO - Epoch(train) [322][25/63] lr: 5.2882e-03 eta: 22:50:20 time: 2.7040 data_time: 0.0890 memory: 16201 loss_prob: 0.8619 loss_thr: 0.5172 loss_db: 0.1397 loss: 1.5188 2022/08/30 07:56:48 - mmengine - INFO - Epoch(train) [322][30/63] lr: 5.2882e-03 eta: 22:50:36 time: 2.6336 data_time: 0.0690 memory: 16201 loss_prob: 0.8139 loss_thr: 0.5042 loss_db: 0.1400 loss: 1.4581 2022/08/30 07:57:01 - mmengine - INFO - Epoch(train) [322][35/63] lr: 5.2882e-03 eta: 22:50:36 time: 2.6422 data_time: 0.0741 memory: 16201 loss_prob: 0.7853 loss_thr: 0.4666 loss_db: 0.1298 loss: 1.3818 2022/08/30 07:57:13 - mmengine - INFO - Epoch(train) [322][40/63] lr: 5.2882e-03 eta: 22:50:50 time: 2.5386 data_time: 0.0654 memory: 16201 loss_prob: 0.7675 loss_thr: 0.4623 loss_db: 0.1275 loss: 1.3572 2022/08/30 07:57:26 - mmengine - INFO - Epoch(train) [322][45/63] lr: 5.2882e-03 eta: 22:50:50 time: 2.5545 data_time: 0.0543 memory: 16201 loss_prob: 0.7758 loss_thr: 0.4637 loss_db: 0.1313 loss: 1.3708 2022/08/30 07:57:40 - mmengine - INFO - Epoch(train) [322][50/63] lr: 5.2882e-03 eta: 22:51:08 time: 2.6931 data_time: 0.0549 memory: 16201 loss_prob: 0.7807 loss_thr: 0.4440 loss_db: 0.1291 loss: 1.3538 2022/08/30 07:57:54 - mmengine - INFO - Epoch(train) [322][55/63] lr: 5.2882e-03 eta: 22:51:08 time: 2.7486 data_time: 0.0689 memory: 16201 loss_prob: 0.7512 loss_thr: 0.4391 loss_db: 0.1220 loss: 1.3123 2022/08/30 07:58:07 - mmengine - INFO - Epoch(train) [322][60/63] lr: 5.2882e-03 eta: 22:51:26 time: 2.7041 data_time: 0.0707 memory: 16201 loss_prob: 0.7922 loss_thr: 0.4592 loss_db: 0.1290 loss: 1.3804 2022/08/30 07:58:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 07:58:30 - mmengine - INFO - Epoch(train) [323][5/63] lr: 5.2828e-03 eta: 22:51:26 time: 2.8765 data_time: 0.2660 memory: 16201 loss_prob: 0.8089 loss_thr: 0.4894 loss_db: 0.1338 loss: 1.4321 2022/08/30 07:58:44 - mmengine - INFO - Epoch(train) [323][10/63] lr: 5.2828e-03 eta: 22:51:38 time: 3.0638 data_time: 0.2853 memory: 16201 loss_prob: 0.7752 loss_thr: 0.5002 loss_db: 0.1303 loss: 1.4057 2022/08/30 07:58:58 - mmengine - INFO - Epoch(train) [323][15/63] lr: 5.2828e-03 eta: 22:51:38 time: 2.7133 data_time: 0.0559 memory: 16201 loss_prob: 0.7339 loss_thr: 0.4815 loss_db: 0.1255 loss: 1.3410 2022/08/30 07:59:10 - mmengine - INFO - Epoch(train) [323][20/63] lr: 5.2828e-03 eta: 22:51:55 time: 2.6666 data_time: 0.0573 memory: 16201 loss_prob: 0.6635 loss_thr: 0.4475 loss_db: 0.1155 loss: 1.2265 2022/08/30 07:59:24 - mmengine - INFO - Epoch(train) [323][25/63] lr: 5.2828e-03 eta: 22:51:55 time: 2.6546 data_time: 0.0609 memory: 16201 loss_prob: 0.6604 loss_thr: 0.4403 loss_db: 0.1134 loss: 1.2142 2022/08/30 07:59:37 - mmengine - INFO - Epoch(train) [323][30/63] lr: 5.2828e-03 eta: 22:52:11 time: 2.6300 data_time: 0.0525 memory: 16201 loss_prob: 0.6629 loss_thr: 0.4455 loss_db: 0.1112 loss: 1.2196 2022/08/30 07:59:49 - mmengine - INFO - Epoch(train) [323][35/63] lr: 5.2828e-03 eta: 22:52:11 time: 2.4594 data_time: 0.0778 memory: 16201 loss_prob: 0.6704 loss_thr: 0.4436 loss_db: 0.1156 loss: 1.2296 2022/08/30 08:00:01 - mmengine - INFO - Epoch(train) [323][40/63] lr: 5.2828e-03 eta: 22:52:23 time: 2.4693 data_time: 0.0632 memory: 16201 loss_prob: 0.6448 loss_thr: 0.4321 loss_db: 0.1110 loss: 1.1879 2022/08/30 08:00:13 - mmengine - INFO - Epoch(train) [323][45/63] lr: 5.2828e-03 eta: 22:52:23 time: 2.4692 data_time: 0.0760 memory: 16201 loss_prob: 0.5958 loss_thr: 0.4195 loss_db: 0.1018 loss: 1.1171 2022/08/30 08:00:27 - mmengine - INFO - Epoch(train) [323][50/63] lr: 5.2828e-03 eta: 22:52:37 time: 2.5384 data_time: 0.0802 memory: 16201 loss_prob: 0.5924 loss_thr: 0.4371 loss_db: 0.1036 loss: 1.1332 2022/08/30 08:00:40 - mmengine - INFO - Epoch(train) [323][55/63] lr: 5.2828e-03 eta: 22:52:37 time: 2.6394 data_time: 0.0479 memory: 16201 loss_prob: 0.6827 loss_thr: 0.4730 loss_db: 0.1149 loss: 1.2705 2022/08/30 08:00:50 - mmengine - INFO - Epoch(train) [323][60/63] lr: 5.2828e-03 eta: 22:52:45 time: 2.3374 data_time: 0.0549 memory: 16201 loss_prob: 0.7617 loss_thr: 0.4641 loss_db: 0.1227 loss: 1.3485 2022/08/30 08:00:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:01:13 - mmengine - INFO - Epoch(train) [324][5/63] lr: 5.2774e-03 eta: 22:52:45 time: 2.6312 data_time: 0.2794 memory: 16201 loss_prob: 0.6557 loss_thr: 0.4619 loss_db: 0.1123 loss: 1.2299 2022/08/30 08:01:26 - mmengine - INFO - Epoch(train) [324][10/63] lr: 5.2774e-03 eta: 22:52:52 time: 2.9183 data_time: 0.2988 memory: 16201 loss_prob: 0.6488 loss_thr: 0.4551 loss_db: 0.1121 loss: 1.2161 2022/08/30 08:01:38 - mmengine - INFO - Epoch(train) [324][15/63] lr: 5.2774e-03 eta: 22:52:52 time: 2.5345 data_time: 0.0651 memory: 16201 loss_prob: 0.6829 loss_thr: 0.4362 loss_db: 0.1167 loss: 1.2358 2022/08/30 08:01:52 - mmengine - INFO - Epoch(train) [324][20/63] lr: 5.2774e-03 eta: 22:53:07 time: 2.5794 data_time: 0.0656 memory: 16201 loss_prob: 0.6214 loss_thr: 0.3967 loss_db: 0.1059 loss: 1.1240 2022/08/30 08:02:04 - mmengine - INFO - Epoch(train) [324][25/63] lr: 5.2774e-03 eta: 22:53:07 time: 2.6361 data_time: 0.0650 memory: 16201 loss_prob: 0.6546 loss_thr: 0.4230 loss_db: 0.1106 loss: 1.1883 2022/08/30 08:02:17 - mmengine - INFO - Epoch(train) [324][30/63] lr: 5.2774e-03 eta: 22:53:20 time: 2.5254 data_time: 0.0622 memory: 16201 loss_prob: 0.7189 loss_thr: 0.4586 loss_db: 0.1209 loss: 1.2985 2022/08/30 08:02:29 - mmengine - INFO - Epoch(train) [324][35/63] lr: 5.2774e-03 eta: 22:53:20 time: 2.4381 data_time: 0.0711 memory: 16201 loss_prob: 0.6982 loss_thr: 0.4216 loss_db: 0.1178 loss: 1.2376 2022/08/30 08:02:43 - mmengine - INFO - Epoch(train) [324][40/63] lr: 5.2774e-03 eta: 22:53:34 time: 2.5607 data_time: 0.0539 memory: 16201 loss_prob: 0.6977 loss_thr: 0.4298 loss_db: 0.1200 loss: 1.2476 2022/08/30 08:02:56 - mmengine - INFO - Epoch(train) [324][45/63] lr: 5.2774e-03 eta: 22:53:34 time: 2.7346 data_time: 0.0483 memory: 16201 loss_prob: 0.6889 loss_thr: 0.4449 loss_db: 0.1160 loss: 1.2499 2022/08/30 08:03:11 - mmengine - INFO - Epoch(train) [324][50/63] lr: 5.2774e-03 eta: 22:53:54 time: 2.7980 data_time: 0.0606 memory: 16201 loss_prob: 0.7010 loss_thr: 0.4499 loss_db: 0.1175 loss: 1.2684 2022/08/30 08:03:24 - mmengine - INFO - Epoch(train) [324][55/63] lr: 5.2774e-03 eta: 22:53:54 time: 2.7801 data_time: 0.0568 memory: 16201 loss_prob: 0.7986 loss_thr: 0.4893 loss_db: 0.1326 loss: 1.4205 2022/08/30 08:03:37 - mmengine - INFO - Epoch(train) [324][60/63] lr: 5.2774e-03 eta: 22:54:10 time: 2.6498 data_time: 0.0587 memory: 16201 loss_prob: 0.7974 loss_thr: 0.4763 loss_db: 0.1335 loss: 1.4072 2022/08/30 08:03:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:04:01 - mmengine - INFO - Epoch(train) [325][5/63] lr: 5.2719e-03 eta: 22:54:10 time: 2.8166 data_time: 0.2909 memory: 16201 loss_prob: 0.7226 loss_thr: 0.4433 loss_db: 0.1251 loss: 1.2909 2022/08/30 08:04:15 - mmengine - INFO - Epoch(train) [325][10/63] lr: 5.2719e-03 eta: 22:54:23 time: 3.1265 data_time: 0.3044 memory: 16201 loss_prob: 0.6764 loss_thr: 0.4398 loss_db: 0.1148 loss: 1.2310 2022/08/30 08:04:28 - mmengine - INFO - Epoch(train) [325][15/63] lr: 5.2719e-03 eta: 22:54:23 time: 2.6573 data_time: 0.0592 memory: 16201 loss_prob: 0.6499 loss_thr: 0.4397 loss_db: 0.1115 loss: 1.2012 2022/08/30 08:04:40 - mmengine - INFO - Epoch(train) [325][20/63] lr: 5.2719e-03 eta: 22:54:35 time: 2.4917 data_time: 0.0602 memory: 16201 loss_prob: 0.6326 loss_thr: 0.4307 loss_db: 0.1103 loss: 1.1736 2022/08/30 08:04:52 - mmengine - INFO - Epoch(train) [325][25/63] lr: 5.2719e-03 eta: 22:54:35 time: 2.3943 data_time: 0.0666 memory: 16201 loss_prob: 0.6943 loss_thr: 0.4403 loss_db: 0.1190 loss: 1.2535 2022/08/30 08:05:05 - mmengine - INFO - Epoch(train) [325][30/63] lr: 5.2719e-03 eta: 22:54:48 time: 2.5471 data_time: 0.0524 memory: 16201 loss_prob: 0.6506 loss_thr: 0.4007 loss_db: 0.1103 loss: 1.1616 2022/08/30 08:05:17 - mmengine - INFO - Epoch(train) [325][35/63] lr: 5.2719e-03 eta: 22:54:48 time: 2.5646 data_time: 0.0612 memory: 16201 loss_prob: 0.6398 loss_thr: 0.4244 loss_db: 0.1092 loss: 1.1735 2022/08/30 08:05:30 - mmengine - INFO - Epoch(train) [325][40/63] lr: 5.2719e-03 eta: 22:55:00 time: 2.4724 data_time: 0.0617 memory: 16201 loss_prob: 0.7243 loss_thr: 0.4566 loss_db: 0.1241 loss: 1.3050 2022/08/30 08:05:41 - mmengine - INFO - Epoch(train) [325][45/63] lr: 5.2719e-03 eta: 22:55:00 time: 2.3913 data_time: 0.0593 memory: 16201 loss_prob: 0.7089 loss_thr: 0.4386 loss_db: 0.1229 loss: 1.2705 2022/08/30 08:05:54 - mmengine - INFO - Epoch(train) [325][50/63] lr: 5.2719e-03 eta: 22:55:10 time: 2.4441 data_time: 0.0656 memory: 16201 loss_prob: 0.7119 loss_thr: 0.4465 loss_db: 0.1209 loss: 1.2792 2022/08/30 08:06:08 - mmengine - INFO - Epoch(train) [325][55/63] lr: 5.2719e-03 eta: 22:55:10 time: 2.6280 data_time: 0.0521 memory: 16201 loss_prob: 0.6818 loss_thr: 0.4226 loss_db: 0.1115 loss: 1.2159 2022/08/30 08:06:20 - mmengine - INFO - Epoch(train) [325][60/63] lr: 5.2719e-03 eta: 22:55:24 time: 2.5696 data_time: 0.0548 memory: 16201 loss_prob: 0.6898 loss_thr: 0.4287 loss_db: 0.1170 loss: 1.2355 2022/08/30 08:06:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:06:42 - mmengine - INFO - Epoch(train) [326][5/63] lr: 5.2665e-03 eta: 22:55:24 time: 2.6944 data_time: 0.2746 memory: 16201 loss_prob: 0.7199 loss_thr: 0.4524 loss_db: 0.1232 loss: 1.2955 2022/08/30 08:06:56 - mmengine - INFO - Epoch(train) [326][10/63] lr: 5.2665e-03 eta: 22:55:32 time: 2.9566 data_time: 0.2910 memory: 16201 loss_prob: 0.7040 loss_thr: 0.4513 loss_db: 0.1191 loss: 1.2745 2022/08/30 08:07:08 - mmengine - INFO - Epoch(train) [326][15/63] lr: 5.2665e-03 eta: 22:55:32 time: 2.5674 data_time: 0.0589 memory: 16201 loss_prob: 0.6795 loss_thr: 0.4260 loss_db: 0.1136 loss: 1.2191 2022/08/30 08:07:22 - mmengine - INFO - Epoch(train) [326][20/63] lr: 5.2665e-03 eta: 22:55:46 time: 2.5700 data_time: 0.0548 memory: 16201 loss_prob: 0.6415 loss_thr: 0.4137 loss_db: 0.1077 loss: 1.1629 2022/08/30 08:07:33 - mmengine - INFO - Epoch(train) [326][25/63] lr: 5.2665e-03 eta: 22:55:46 time: 2.4527 data_time: 0.0763 memory: 16201 loss_prob: 0.6130 loss_thr: 0.4044 loss_db: 0.1044 loss: 1.1218 2022/08/30 08:07:48 - mmengine - INFO - Epoch(train) [326][30/63] lr: 5.2665e-03 eta: 22:56:00 time: 2.5942 data_time: 0.0663 memory: 16201 loss_prob: 0.7723 loss_thr: 0.3991 loss_db: 0.1300 loss: 1.3014 2022/08/30 08:08:01 - mmengine - INFO - Epoch(train) [326][35/63] lr: 5.2665e-03 eta: 22:56:00 time: 2.8229 data_time: 0.0619 memory: 16201 loss_prob: 0.8100 loss_thr: 0.4175 loss_db: 0.1317 loss: 1.3592 2022/08/30 08:08:15 - mmengine - INFO - Epoch(train) [326][40/63] lr: 5.2665e-03 eta: 22:56:18 time: 2.7021 data_time: 0.0603 memory: 16201 loss_prob: 0.6931 loss_thr: 0.4177 loss_db: 0.1104 loss: 1.2211 2022/08/30 08:08:27 - mmengine - INFO - Epoch(train) [326][45/63] lr: 5.2665e-03 eta: 22:56:18 time: 2.6420 data_time: 0.0456 memory: 16201 loss_prob: 0.7719 loss_thr: 0.4567 loss_db: 0.1253 loss: 1.3539 2022/08/30 08:08:42 - mmengine - INFO - Epoch(train) [326][50/63] lr: 5.2665e-03 eta: 22:56:34 time: 2.6809 data_time: 0.0763 memory: 16201 loss_prob: 0.8077 loss_thr: 0.4633 loss_db: 0.1344 loss: 1.4054 2022/08/30 08:08:52 - mmengine - INFO - Epoch(train) [326][55/63] lr: 5.2665e-03 eta: 22:56:34 time: 2.4285 data_time: 0.0816 memory: 16201 loss_prob: 0.9265 loss_thr: 0.4812 loss_db: 0.1551 loss: 1.5628 2022/08/30 08:09:05 - mmengine - INFO - Epoch(train) [326][60/63] lr: 5.2665e-03 eta: 22:56:42 time: 2.3489 data_time: 0.0536 memory: 16201 loss_prob: 0.9311 loss_thr: 0.5002 loss_db: 0.1551 loss: 1.5864 2022/08/30 08:09:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:09:27 - mmengine - INFO - Epoch(train) [327][5/63] lr: 5.2611e-03 eta: 22:56:42 time: 2.7915 data_time: 0.2985 memory: 16201 loss_prob: 0.8163 loss_thr: 0.4732 loss_db: 0.1365 loss: 1.4260 2022/08/30 08:09:41 - mmengine - INFO - Epoch(train) [327][10/63] lr: 5.2611e-03 eta: 22:56:47 time: 2.8741 data_time: 0.3062 memory: 16201 loss_prob: 0.7966 loss_thr: 0.4786 loss_db: 0.1388 loss: 1.4139 2022/08/30 08:09:55 - mmengine - INFO - Epoch(train) [327][15/63] lr: 5.2611e-03 eta: 22:56:47 time: 2.7611 data_time: 0.0708 memory: 16201 loss_prob: 0.7801 loss_thr: 0.4709 loss_db: 0.1328 loss: 1.3838 2022/08/30 08:10:07 - mmengine - INFO - Epoch(train) [327][20/63] lr: 5.2611e-03 eta: 22:57:03 time: 2.6585 data_time: 0.0558 memory: 16201 loss_prob: 0.8323 loss_thr: 0.4741 loss_db: 0.1345 loss: 1.4409 2022/08/30 08:10:20 - mmengine - INFO - Epoch(train) [327][25/63] lr: 5.2611e-03 eta: 22:57:03 time: 2.5405 data_time: 0.0821 memory: 16201 loss_prob: 0.8245 loss_thr: 0.4753 loss_db: 0.1339 loss: 1.4338 2022/08/30 08:10:32 - mmengine - INFO - Epoch(train) [327][30/63] lr: 5.2611e-03 eta: 22:57:16 time: 2.5206 data_time: 0.0688 memory: 16201 loss_prob: 0.7656 loss_thr: 0.4846 loss_db: 0.1272 loss: 1.3773 2022/08/30 08:10:46 - mmengine - INFO - Epoch(train) [327][35/63] lr: 5.2611e-03 eta: 22:57:16 time: 2.6185 data_time: 0.0592 memory: 16201 loss_prob: 0.7386 loss_thr: 0.4710 loss_db: 0.1243 loss: 1.3339 2022/08/30 08:11:01 - mmengine - INFO - Epoch(train) [327][40/63] lr: 5.2611e-03 eta: 22:57:37 time: 2.8524 data_time: 0.0536 memory: 16201 loss_prob: 0.6859 loss_thr: 0.4297 loss_db: 0.1183 loss: 1.2339 2022/08/30 08:11:14 - mmengine - INFO - Epoch(train) [327][45/63] lr: 5.2611e-03 eta: 22:57:37 time: 2.7800 data_time: 0.0608 memory: 16201 loss_prob: 0.7378 loss_thr: 0.4500 loss_db: 0.1325 loss: 1.3203 2022/08/30 08:11:25 - mmengine - INFO - Epoch(train) [327][50/63] lr: 5.2611e-03 eta: 22:57:47 time: 2.4374 data_time: 0.0730 memory: 16201 loss_prob: 0.7700 loss_thr: 0.4772 loss_db: 0.1364 loss: 1.3836 2022/08/30 08:11:38 - mmengine - INFO - Epoch(train) [327][55/63] lr: 5.2611e-03 eta: 22:57:47 time: 2.4098 data_time: 0.0578 memory: 16201 loss_prob: 0.7832 loss_thr: 0.4756 loss_db: 0.1315 loss: 1.3903 2022/08/30 08:11:51 - mmengine - INFO - Epoch(train) [327][60/63] lr: 5.2611e-03 eta: 22:57:59 time: 2.5266 data_time: 0.0647 memory: 16201 loss_prob: 0.7895 loss_thr: 0.4551 loss_db: 0.1329 loss: 1.3776 2022/08/30 08:11:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:12:13 - mmengine - INFO - Epoch(train) [328][5/63] lr: 5.2557e-03 eta: 22:57:59 time: 2.5786 data_time: 0.2559 memory: 16201 loss_prob: 0.7629 loss_thr: 0.4790 loss_db: 0.1284 loss: 1.3703 2022/08/30 08:12:27 - mmengine - INFO - Epoch(train) [328][10/63] lr: 5.2557e-03 eta: 22:58:07 time: 2.9768 data_time: 0.3589 memory: 16201 loss_prob: 0.8327 loss_thr: 0.4939 loss_db: 0.1427 loss: 1.4693 2022/08/30 08:12:41 - mmengine - INFO - Epoch(train) [328][15/63] lr: 5.2557e-03 eta: 22:58:07 time: 2.8561 data_time: 0.1382 memory: 16201 loss_prob: 0.7246 loss_thr: 0.4538 loss_db: 0.1236 loss: 1.3020 2022/08/30 08:12:55 - mmengine - INFO - Epoch(train) [328][20/63] lr: 5.2557e-03 eta: 22:58:25 time: 2.7675 data_time: 0.0529 memory: 16201 loss_prob: 0.6209 loss_thr: 0.4155 loss_db: 0.1048 loss: 1.1412 2022/08/30 08:13:08 - mmengine - INFO - Epoch(train) [328][25/63] lr: 5.2557e-03 eta: 22:58:25 time: 2.7279 data_time: 0.0527 memory: 16201 loss_prob: 0.6519 loss_thr: 0.4299 loss_db: 0.1114 loss: 1.1932 2022/08/30 08:13:21 - mmengine - INFO - Epoch(train) [328][30/63] lr: 5.2557e-03 eta: 22:58:39 time: 2.5836 data_time: 0.0551 memory: 16201 loss_prob: 0.6705 loss_thr: 0.4389 loss_db: 0.1169 loss: 1.2264 2022/08/30 08:13:36 - mmengine - INFO - Epoch(train) [328][35/63] lr: 5.2557e-03 eta: 22:58:39 time: 2.7194 data_time: 0.0691 memory: 16201 loss_prob: 0.6433 loss_thr: 0.4260 loss_db: 0.1100 loss: 1.1794 2022/08/30 08:13:48 - mmengine - INFO - Epoch(train) [328][40/63] lr: 5.2557e-03 eta: 22:58:56 time: 2.7100 data_time: 0.0488 memory: 16201 loss_prob: 0.6868 loss_thr: 0.4474 loss_db: 0.1151 loss: 1.2492 2022/08/30 08:13:59 - mmengine - INFO - Epoch(train) [328][45/63] lr: 5.2557e-03 eta: 22:58:56 time: 2.3683 data_time: 0.0529 memory: 16201 loss_prob: 0.7465 loss_thr: 0.4961 loss_db: 0.1270 loss: 1.3695 2022/08/30 08:14:13 - mmengine - INFO - Epoch(train) [328][50/63] lr: 5.2557e-03 eta: 22:59:07 time: 2.4786 data_time: 0.0774 memory: 16201 loss_prob: 0.7530 loss_thr: 0.4738 loss_db: 0.1266 loss: 1.3533 2022/08/30 08:14:26 - mmengine - INFO - Epoch(train) [328][55/63] lr: 5.2557e-03 eta: 22:59:07 time: 2.6834 data_time: 0.0589 memory: 16201 loss_prob: 0.7004 loss_thr: 0.4200 loss_db: 0.1162 loss: 1.2366 2022/08/30 08:14:38 - mmengine - INFO - Epoch(train) [328][60/63] lr: 5.2557e-03 eta: 22:59:20 time: 2.5531 data_time: 0.0519 memory: 16201 loss_prob: 0.6844 loss_thr: 0.4354 loss_db: 0.1158 loss: 1.2356 2022/08/30 08:14:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:15:02 - mmengine - INFO - Epoch(train) [329][5/63] lr: 5.2502e-03 eta: 22:59:20 time: 2.8036 data_time: 0.2924 memory: 16201 loss_prob: 0.7614 loss_thr: 0.4675 loss_db: 0.1268 loss: 1.3556 2022/08/30 08:15:14 - mmengine - INFO - Epoch(train) [329][10/63] lr: 5.2502e-03 eta: 22:59:24 time: 2.8582 data_time: 0.2897 memory: 16201 loss_prob: 0.7070 loss_thr: 0.4459 loss_db: 0.1178 loss: 1.2707 2022/08/30 08:15:28 - mmengine - INFO - Epoch(train) [329][15/63] lr: 5.2502e-03 eta: 22:59:24 time: 2.6240 data_time: 0.0652 memory: 16201 loss_prob: 0.6724 loss_thr: 0.4469 loss_db: 0.1137 loss: 1.2329 2022/08/30 08:15:42 - mmengine - INFO - Epoch(train) [329][20/63] lr: 5.2502e-03 eta: 22:59:42 time: 2.7467 data_time: 0.0795 memory: 16201 loss_prob: 0.7049 loss_thr: 0.4582 loss_db: 0.1198 loss: 1.2829 2022/08/30 08:15:54 - mmengine - INFO - Epoch(train) [329][25/63] lr: 5.2502e-03 eta: 22:59:42 time: 2.5591 data_time: 0.0858 memory: 16201 loss_prob: 0.7001 loss_thr: 0.4495 loss_db: 0.1178 loss: 1.2673 2022/08/30 08:16:06 - mmengine - INFO - Epoch(train) [329][30/63] lr: 5.2502e-03 eta: 22:59:50 time: 2.3743 data_time: 0.0747 memory: 16201 loss_prob: 0.6504 loss_thr: 0.4245 loss_db: 0.1111 loss: 1.1860 2022/08/30 08:16:18 - mmengine - INFO - Epoch(train) [329][35/63] lr: 5.2502e-03 eta: 22:59:50 time: 2.4361 data_time: 0.0506 memory: 16201 loss_prob: 0.6943 loss_thr: 0.4282 loss_db: 0.1186 loss: 1.2411 2022/08/30 08:16:31 - mmengine - INFO - Epoch(train) [329][40/63] lr: 5.2502e-03 eta: 23:00:03 time: 2.5803 data_time: 0.0595 memory: 16201 loss_prob: 0.7040 loss_thr: 0.4410 loss_db: 0.1194 loss: 1.2644 2022/08/30 08:16:45 - mmengine - INFO - Epoch(train) [329][45/63] lr: 5.2502e-03 eta: 23:00:03 time: 2.6659 data_time: 0.0726 memory: 16201 loss_prob: 0.6562 loss_thr: 0.4146 loss_db: 0.1122 loss: 1.1829 2022/08/30 08:16:58 - mmengine - INFO - Epoch(train) [329][50/63] lr: 5.2502e-03 eta: 23:00:19 time: 2.6544 data_time: 0.0699 memory: 16201 loss_prob: 0.6730 loss_thr: 0.4189 loss_db: 0.1146 loss: 1.2065 2022/08/30 08:17:11 - mmengine - INFO - Epoch(train) [329][55/63] lr: 5.2502e-03 eta: 23:00:19 time: 2.6683 data_time: 0.0670 memory: 16201 loss_prob: 0.6593 loss_thr: 0.4389 loss_db: 0.1139 loss: 1.2121 2022/08/30 08:17:25 - mmengine - INFO - Epoch(train) [329][60/63] lr: 5.2502e-03 eta: 23:00:36 time: 2.7185 data_time: 0.0758 memory: 16201 loss_prob: 0.6341 loss_thr: 0.4217 loss_db: 0.1084 loss: 1.1642 2022/08/30 08:17:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:17:50 - mmengine - INFO - Epoch(train) [330][5/63] lr: 5.2448e-03 eta: 23:00:36 time: 3.0911 data_time: 0.2990 memory: 16201 loss_prob: 0.6958 loss_thr: 0.4604 loss_db: 0.1200 loss: 1.2762 2022/08/30 08:18:03 - mmengine - INFO - Epoch(train) [330][10/63] lr: 5.2448e-03 eta: 23:00:46 time: 3.0896 data_time: 0.3042 memory: 16201 loss_prob: 0.7603 loss_thr: 0.4603 loss_db: 0.1273 loss: 1.3478 2022/08/30 08:18:17 - mmengine - INFO - Epoch(train) [330][15/63] lr: 5.2448e-03 eta: 23:00:46 time: 2.7413 data_time: 0.0484 memory: 16201 loss_prob: 0.8121 loss_thr: 0.4696 loss_db: 0.1336 loss: 1.4153 2022/08/30 08:18:31 - mmengine - INFO - Epoch(train) [330][20/63] lr: 5.2448e-03 eta: 23:01:04 time: 2.7636 data_time: 0.0474 memory: 16201 loss_prob: 0.8605 loss_thr: 0.4680 loss_db: 0.1382 loss: 1.4667 2022/08/30 08:18:45 - mmengine - INFO - Epoch(train) [330][25/63] lr: 5.2448e-03 eta: 23:01:04 time: 2.7436 data_time: 0.0619 memory: 16201 loss_prob: 0.8361 loss_thr: 0.4614 loss_db: 0.1341 loss: 1.4316 2022/08/30 08:18:58 - mmengine - INFO - Epoch(train) [330][30/63] lr: 5.2448e-03 eta: 23:01:21 time: 2.7240 data_time: 0.0523 memory: 16201 loss_prob: 0.8155 loss_thr: 0.4794 loss_db: 0.1364 loss: 1.4314 2022/08/30 08:19:11 - mmengine - INFO - Epoch(train) [330][35/63] lr: 5.2448e-03 eta: 23:01:21 time: 2.6787 data_time: 0.0578 memory: 16201 loss_prob: 0.8294 loss_thr: 0.4919 loss_db: 0.1411 loss: 1.4624 2022/08/30 08:19:24 - mmengine - INFO - Epoch(train) [330][40/63] lr: 5.2448e-03 eta: 23:01:33 time: 2.5489 data_time: 0.0483 memory: 16201 loss_prob: 0.7203 loss_thr: 0.4701 loss_db: 0.1248 loss: 1.3152 2022/08/30 08:19:37 - mmengine - INFO - Epoch(train) [330][45/63] lr: 5.2448e-03 eta: 23:01:33 time: 2.5341 data_time: 0.0476 memory: 16201 loss_prob: 0.6820 loss_thr: 0.4380 loss_db: 0.1186 loss: 1.2386 2022/08/30 08:19:49 - mmengine - INFO - Epoch(train) [330][50/63] lr: 5.2448e-03 eta: 23:01:45 time: 2.5313 data_time: 0.0711 memory: 16201 loss_prob: 0.6614 loss_thr: 0.4108 loss_db: 0.1128 loss: 1.1850 2022/08/30 08:20:03 - mmengine - INFO - Epoch(train) [330][55/63] lr: 5.2448e-03 eta: 23:01:45 time: 2.6049 data_time: 0.0541 memory: 16201 loss_prob: 0.6652 loss_thr: 0.4129 loss_db: 0.1095 loss: 1.1875 2022/08/30 08:20:17 - mmengine - INFO - Epoch(train) [330][60/63] lr: 5.2448e-03 eta: 23:02:03 time: 2.7935 data_time: 0.0554 memory: 16201 loss_prob: 0.6773 loss_thr: 0.4135 loss_db: 0.1143 loss: 1.2051 2022/08/30 08:20:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:20:36 - mmengine - INFO - Epoch(train) [331][5/63] lr: 5.2394e-03 eta: 23:02:03 time: 2.4740 data_time: 0.2971 memory: 16201 loss_prob: 0.7000 loss_thr: 0.4143 loss_db: 0.1169 loss: 1.2311 2022/08/30 08:20:50 - mmengine - INFO - Epoch(train) [331][10/63] lr: 5.2394e-03 eta: 23:02:07 time: 2.8603 data_time: 0.3260 memory: 16201 loss_prob: 0.7369 loss_thr: 0.4721 loss_db: 0.1242 loss: 1.3332 2022/08/30 08:21:04 - mmengine - INFO - Epoch(train) [331][15/63] lr: 5.2394e-03 eta: 23:02:07 time: 2.8183 data_time: 0.0559 memory: 16201 loss_prob: 0.7123 loss_thr: 0.4755 loss_db: 0.1246 loss: 1.3124 2022/08/30 08:21:18 - mmengine - INFO - Epoch(train) [331][20/63] lr: 5.2394e-03 eta: 23:02:25 time: 2.7764 data_time: 0.0513 memory: 16201 loss_prob: 0.6862 loss_thr: 0.4486 loss_db: 0.1194 loss: 1.2542 2022/08/30 08:21:32 - mmengine - INFO - Epoch(train) [331][25/63] lr: 5.2394e-03 eta: 23:02:25 time: 2.7724 data_time: 0.0794 memory: 16201 loss_prob: 0.6935 loss_thr: 0.4343 loss_db: 0.1154 loss: 1.2432 2022/08/30 08:21:45 - mmengine - INFO - Epoch(train) [331][30/63] lr: 5.2394e-03 eta: 23:02:41 time: 2.6672 data_time: 0.0569 memory: 16201 loss_prob: 0.6818 loss_thr: 0.4220 loss_db: 0.1150 loss: 1.2188 2022/08/30 08:21:57 - mmengine - INFO - Epoch(train) [331][35/63] lr: 5.2394e-03 eta: 23:02:41 time: 2.5287 data_time: 0.0419 memory: 16201 loss_prob: 0.6862 loss_thr: 0.4213 loss_db: 0.1180 loss: 1.2256 2022/08/30 08:22:10 - mmengine - INFO - Epoch(train) [331][40/63] lr: 5.2394e-03 eta: 23:02:52 time: 2.5321 data_time: 0.0426 memory: 16201 loss_prob: 0.6968 loss_thr: 0.4400 loss_db: 0.1188 loss: 1.2556 2022/08/30 08:22:23 - mmengine - INFO - Epoch(train) [331][45/63] lr: 5.2394e-03 eta: 23:02:52 time: 2.5463 data_time: 0.0625 memory: 16201 loss_prob: 0.7168 loss_thr: 0.4583 loss_db: 0.1223 loss: 1.2974 2022/08/30 08:22:36 - mmengine - INFO - Epoch(train) [331][50/63] lr: 5.2394e-03 eta: 23:03:06 time: 2.6103 data_time: 0.0801 memory: 16201 loss_prob: 0.7110 loss_thr: 0.4499 loss_db: 0.1179 loss: 1.2789 2022/08/30 08:22:50 - mmengine - INFO - Epoch(train) [331][55/63] lr: 5.2394e-03 eta: 23:03:06 time: 2.7428 data_time: 0.0536 memory: 16201 loss_prob: 0.6929 loss_thr: 0.4435 loss_db: 0.1132 loss: 1.2496 2022/08/30 08:23:03 - mmengine - INFO - Epoch(train) [331][60/63] lr: 5.2394e-03 eta: 23:03:21 time: 2.6597 data_time: 0.0668 memory: 16201 loss_prob: 0.7155 loss_thr: 0.4689 loss_db: 0.1188 loss: 1.3032 2022/08/30 08:23:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:23:23 - mmengine - INFO - Epoch(train) [332][5/63] lr: 5.2340e-03 eta: 23:03:21 time: 2.6864 data_time: 0.2631 memory: 16201 loss_prob: 0.7691 loss_thr: 0.4679 loss_db: 0.1255 loss: 1.3625 2022/08/30 08:23:36 - mmengine - INFO - Epoch(train) [332][10/63] lr: 5.2340e-03 eta: 23:03:20 time: 2.6941 data_time: 0.2910 memory: 16201 loss_prob: 0.6900 loss_thr: 0.4420 loss_db: 0.1186 loss: 1.2506 2022/08/30 08:23:50 - mmengine - INFO - Epoch(train) [332][15/63] lr: 5.2340e-03 eta: 23:03:20 time: 2.6540 data_time: 0.0606 memory: 16201 loss_prob: 0.6870 loss_thr: 0.4419 loss_db: 0.1216 loss: 1.2504 2022/08/30 08:24:02 - mmengine - INFO - Epoch(train) [332][20/63] lr: 5.2340e-03 eta: 23:03:35 time: 2.6637 data_time: 0.0628 memory: 16201 loss_prob: 0.6688 loss_thr: 0.4244 loss_db: 0.1165 loss: 1.2098 2022/08/30 08:24:16 - mmengine - INFO - Epoch(train) [332][25/63] lr: 5.2340e-03 eta: 23:03:35 time: 2.6620 data_time: 0.0571 memory: 16201 loss_prob: 0.7211 loss_thr: 0.4315 loss_db: 0.1192 loss: 1.2718 2022/08/30 08:24:30 - mmengine - INFO - Epoch(train) [332][30/63] lr: 5.2340e-03 eta: 23:03:52 time: 2.7542 data_time: 0.0522 memory: 16201 loss_prob: 0.7105 loss_thr: 0.4484 loss_db: 0.1159 loss: 1.2748 2022/08/30 08:24:43 - mmengine - INFO - Epoch(train) [332][35/63] lr: 5.2340e-03 eta: 23:03:52 time: 2.6583 data_time: 0.0732 memory: 16201 loss_prob: 0.6114 loss_thr: 0.4277 loss_db: 0.1035 loss: 1.1426 2022/08/30 08:24:57 - mmengine - INFO - Epoch(train) [332][40/63] lr: 5.2340e-03 eta: 23:04:09 time: 2.7332 data_time: 0.0606 memory: 16201 loss_prob: 0.6269 loss_thr: 0.4297 loss_db: 0.1091 loss: 1.1657 2022/08/30 08:25:13 - mmengine - INFO - Epoch(train) [332][45/63] lr: 5.2340e-03 eta: 23:04:09 time: 2.9429 data_time: 0.0620 memory: 16201 loss_prob: 0.7357 loss_thr: 0.4633 loss_db: 0.1236 loss: 1.3226 2022/08/30 08:25:25 - mmengine - INFO - Epoch(train) [332][50/63] lr: 5.2340e-03 eta: 23:04:27 time: 2.7866 data_time: 0.0734 memory: 16201 loss_prob: 0.7419 loss_thr: 0.4572 loss_db: 0.1205 loss: 1.3196 2022/08/30 08:25:39 - mmengine - INFO - Epoch(train) [332][55/63] lr: 5.2340e-03 eta: 23:04:27 time: 2.6162 data_time: 0.0567 memory: 16201 loss_prob: 0.7032 loss_thr: 0.4451 loss_db: 0.1191 loss: 1.2673 2022/08/30 08:25:51 - mmengine - INFO - Epoch(train) [332][60/63] lr: 5.2340e-03 eta: 23:04:39 time: 2.5712 data_time: 0.0628 memory: 16201 loss_prob: 0.7415 loss_thr: 0.4445 loss_db: 0.1318 loss: 1.3179 2022/08/30 08:25:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:26:13 - mmengine - INFO - Epoch(train) [333][5/63] lr: 5.2285e-03 eta: 23:04:39 time: 2.6538 data_time: 0.2930 memory: 16201 loss_prob: 0.7070 loss_thr: 0.4487 loss_db: 0.1193 loss: 1.2751 2022/08/30 08:26:26 - mmengine - INFO - Epoch(train) [333][10/63] lr: 5.2285e-03 eta: 23:04:41 time: 2.7920 data_time: 0.3147 memory: 16201 loss_prob: 0.6972 loss_thr: 0.4275 loss_db: 0.1173 loss: 1.2420 2022/08/30 08:26:39 - mmengine - INFO - Epoch(train) [333][15/63] lr: 5.2285e-03 eta: 23:04:41 time: 2.6522 data_time: 0.0549 memory: 16201 loss_prob: 0.7297 loss_thr: 0.4265 loss_db: 0.1249 loss: 1.2811 2022/08/30 08:26:51 - mmengine - INFO - Epoch(train) [333][20/63] lr: 5.2285e-03 eta: 23:04:50 time: 2.4451 data_time: 0.0700 memory: 16201 loss_prob: 0.6709 loss_thr: 0.4441 loss_db: 0.1148 loss: 1.2298 2022/08/30 08:27:04 - mmengine - INFO - Epoch(train) [333][25/63] lr: 5.2285e-03 eta: 23:04:50 time: 2.5114 data_time: 0.0894 memory: 16201 loss_prob: 0.6415 loss_thr: 0.4245 loss_db: 0.1097 loss: 1.1758 2022/08/30 08:27:17 - mmengine - INFO - Epoch(train) [333][30/63] lr: 5.2285e-03 eta: 23:05:03 time: 2.6138 data_time: 0.0535 memory: 16201 loss_prob: 0.6716 loss_thr: 0.4114 loss_db: 0.1155 loss: 1.1984 2022/08/30 08:27:30 - mmengine - INFO - Epoch(train) [333][35/63] lr: 5.2285e-03 eta: 23:05:03 time: 2.6047 data_time: 0.0471 memory: 16201 loss_prob: 0.7743 loss_thr: 0.4342 loss_db: 0.1304 loss: 1.3389 2022/08/30 08:27:45 - mmengine - INFO - Epoch(train) [333][40/63] lr: 5.2285e-03 eta: 23:05:22 time: 2.8305 data_time: 0.0589 memory: 16201 loss_prob: 0.8263 loss_thr: 0.4408 loss_db: 0.1371 loss: 1.4043 2022/08/30 08:27:59 - mmengine - INFO - Epoch(train) [333][45/63] lr: 5.2285e-03 eta: 23:05:22 time: 2.8468 data_time: 0.0609 memory: 16201 loss_prob: 0.7692 loss_thr: 0.4357 loss_db: 0.1266 loss: 1.3314 2022/08/30 08:28:11 - mmengine - INFO - Epoch(train) [333][50/63] lr: 5.2285e-03 eta: 23:05:34 time: 2.5736 data_time: 0.0742 memory: 16201 loss_prob: 0.7628 loss_thr: 0.4529 loss_db: 0.1272 loss: 1.3429 2022/08/30 08:28:25 - mmengine - INFO - Epoch(train) [333][55/63] lr: 5.2285e-03 eta: 23:05:34 time: 2.6326 data_time: 0.0698 memory: 16201 loss_prob: 0.8363 loss_thr: 0.4881 loss_db: 0.1372 loss: 1.4617 2022/08/30 08:28:37 - mmengine - INFO - Epoch(train) [333][60/63] lr: 5.2285e-03 eta: 23:05:48 time: 2.6359 data_time: 0.0594 memory: 16201 loss_prob: 0.7919 loss_thr: 0.4730 loss_db: 0.1273 loss: 1.3921 2022/08/30 08:28:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:29:00 - mmengine - INFO - Epoch(train) [334][5/63] lr: 5.2231e-03 eta: 23:05:48 time: 2.7454 data_time: 0.2910 memory: 16201 loss_prob: 0.6801 loss_thr: 0.4489 loss_db: 0.1173 loss: 1.2462 2022/08/30 08:29:13 - mmengine - INFO - Epoch(train) [334][10/63] lr: 5.2231e-03 eta: 23:05:51 time: 2.8406 data_time: 0.3171 memory: 16201 loss_prob: 0.6545 loss_thr: 0.4369 loss_db: 0.1140 loss: 1.2053 2022/08/30 08:29:27 - mmengine - INFO - Epoch(train) [334][15/63] lr: 5.2231e-03 eta: 23:05:51 time: 2.7860 data_time: 0.0547 memory: 16201 loss_prob: 0.7163 loss_thr: 0.4488 loss_db: 0.1192 loss: 1.2843 2022/08/30 08:29:40 - mmengine - INFO - Epoch(train) [334][20/63] lr: 5.2231e-03 eta: 23:06:06 time: 2.6966 data_time: 0.0481 memory: 16201 loss_prob: 0.7992 loss_thr: 0.4911 loss_db: 0.1275 loss: 1.4177 2022/08/30 08:29:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:29:53 - mmengine - INFO - Epoch(train) [334][25/63] lr: 5.2231e-03 eta: 23:06:06 time: 2.5398 data_time: 0.0615 memory: 16201 loss_prob: 0.7500 loss_thr: 0.4776 loss_db: 0.1235 loss: 1.3511 2022/08/30 08:30:04 - mmengine - INFO - Epoch(train) [334][30/63] lr: 5.2231e-03 eta: 23:06:15 time: 2.4461 data_time: 0.0520 memory: 16201 loss_prob: 0.7496 loss_thr: 0.4651 loss_db: 0.1267 loss: 1.3414 2022/08/30 08:30:17 - mmengine - INFO - Epoch(train) [334][35/63] lr: 5.2231e-03 eta: 23:06:15 time: 2.4421 data_time: 0.0658 memory: 16201 loss_prob: 0.7666 loss_thr: 0.4642 loss_db: 0.1274 loss: 1.3582 2022/08/30 08:30:29 - mmengine - INFO - Epoch(train) [334][40/63] lr: 5.2231e-03 eta: 23:06:25 time: 2.4949 data_time: 0.0576 memory: 16201 loss_prob: 0.7030 loss_thr: 0.4378 loss_db: 0.1211 loss: 1.2619 2022/08/30 08:30:43 - mmengine - INFO - Epoch(train) [334][45/63] lr: 5.2231e-03 eta: 23:06:25 time: 2.5431 data_time: 0.0610 memory: 16201 loss_prob: 0.7282 loss_thr: 0.4452 loss_db: 0.1260 loss: 1.2994 2022/08/30 08:30:56 - mmengine - INFO - Epoch(train) [334][50/63] lr: 5.2231e-03 eta: 23:06:41 time: 2.7542 data_time: 0.0831 memory: 16201 loss_prob: 0.6949 loss_thr: 0.4166 loss_db: 0.1191 loss: 1.2306 2022/08/30 08:31:10 - mmengine - INFO - Epoch(train) [334][55/63] lr: 5.2231e-03 eta: 23:06:41 time: 2.7433 data_time: 0.0525 memory: 16201 loss_prob: 0.6754 loss_thr: 0.4077 loss_db: 0.1165 loss: 1.1996 2022/08/30 08:31:24 - mmengine - INFO - Epoch(train) [334][60/63] lr: 5.2231e-03 eta: 23:06:57 time: 2.7252 data_time: 0.0502 memory: 16201 loss_prob: 0.6846 loss_thr: 0.4310 loss_db: 0.1167 loss: 1.2323 2022/08/30 08:31:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:31:45 - mmengine - INFO - Epoch(train) [335][5/63] lr: 5.2177e-03 eta: 23:06:57 time: 2.6046 data_time: 0.3087 memory: 16201 loss_prob: 0.6615 loss_thr: 0.4201 loss_db: 0.1117 loss: 1.1933 2022/08/30 08:31:57 - mmengine - INFO - Epoch(train) [335][10/63] lr: 5.2177e-03 eta: 23:06:58 time: 2.7880 data_time: 0.3292 memory: 16201 loss_prob: 0.7135 loss_thr: 0.4532 loss_db: 0.1229 loss: 1.2896 2022/08/30 08:32:10 - mmengine - INFO - Epoch(train) [335][15/63] lr: 5.2177e-03 eta: 23:06:58 time: 2.5391 data_time: 0.0479 memory: 16201 loss_prob: 0.6944 loss_thr: 0.4260 loss_db: 0.1197 loss: 1.2402 2022/08/30 08:32:24 - mmengine - INFO - Epoch(train) [335][20/63] lr: 5.2177e-03 eta: 23:07:12 time: 2.6556 data_time: 0.0552 memory: 16201 loss_prob: 0.6748 loss_thr: 0.4062 loss_db: 0.1140 loss: 1.1950 2022/08/30 08:32:39 - mmengine - INFO - Epoch(train) [335][25/63] lr: 5.2177e-03 eta: 23:07:12 time: 2.8288 data_time: 0.0751 memory: 16201 loss_prob: 0.6568 loss_thr: 0.4198 loss_db: 0.1142 loss: 1.1908 2022/08/30 08:32:53 - mmengine - INFO - Epoch(train) [335][30/63] lr: 5.2177e-03 eta: 23:07:33 time: 2.9082 data_time: 0.0565 memory: 16201 loss_prob: 0.6218 loss_thr: 0.4129 loss_db: 0.1090 loss: 1.1436 2022/08/30 08:33:06 - mmengine - INFO - Epoch(train) [335][35/63] lr: 5.2177e-03 eta: 23:07:33 time: 2.7451 data_time: 0.0619 memory: 16201 loss_prob: 0.6800 loss_thr: 0.4211 loss_db: 0.1160 loss: 1.2171 2022/08/30 08:33:20 - mmengine - INFO - Epoch(train) [335][40/63] lr: 5.2177e-03 eta: 23:07:48 time: 2.6910 data_time: 0.0629 memory: 16201 loss_prob: 0.6891 loss_thr: 0.4257 loss_db: 0.1199 loss: 1.2347 2022/08/30 08:33:34 - mmengine - INFO - Epoch(train) [335][45/63] lr: 5.2177e-03 eta: 23:07:48 time: 2.7456 data_time: 0.0661 memory: 16201 loss_prob: 0.6183 loss_thr: 0.4108 loss_db: 0.1083 loss: 1.1375 2022/08/30 08:33:47 - mmengine - INFO - Epoch(train) [335][50/63] lr: 5.2177e-03 eta: 23:08:02 time: 2.6726 data_time: 0.0784 memory: 16201 loss_prob: 0.6474 loss_thr: 0.4205 loss_db: 0.1086 loss: 1.1764 2022/08/30 08:33:59 - mmengine - INFO - Epoch(train) [335][55/63] lr: 5.2177e-03 eta: 23:08:02 time: 2.4850 data_time: 0.0628 memory: 16201 loss_prob: 0.7131 loss_thr: 0.4484 loss_db: 0.1199 loss: 1.2814 2022/08/30 08:34:14 - mmengine - INFO - Epoch(train) [335][60/63] lr: 5.2177e-03 eta: 23:08:18 time: 2.7208 data_time: 0.0621 memory: 16201 loss_prob: 0.7120 loss_thr: 0.4576 loss_db: 0.1243 loss: 1.2939 2022/08/30 08:34:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:34:34 - mmengine - INFO - Epoch(train) [336][5/63] lr: 5.2123e-03 eta: 23:08:18 time: 2.6974 data_time: 0.2827 memory: 16201 loss_prob: 0.6772 loss_thr: 0.4313 loss_db: 0.1171 loss: 1.2256 2022/08/30 08:34:48 - mmengine - INFO - Epoch(train) [336][10/63] lr: 5.2123e-03 eta: 23:08:19 time: 2.7927 data_time: 0.2797 memory: 16201 loss_prob: 0.7462 loss_thr: 0.4430 loss_db: 0.1246 loss: 1.3138 2022/08/30 08:35:03 - mmengine - INFO - Epoch(train) [336][15/63] lr: 5.2123e-03 eta: 23:08:19 time: 2.8277 data_time: 0.0569 memory: 16201 loss_prob: 0.7533 loss_thr: 0.4462 loss_db: 0.1260 loss: 1.3254 2022/08/30 08:35:16 - mmengine - INFO - Epoch(train) [336][20/63] lr: 5.2123e-03 eta: 23:08:37 time: 2.8387 data_time: 0.0596 memory: 16201 loss_prob: 0.6877 loss_thr: 0.4197 loss_db: 0.1159 loss: 1.2233 2022/08/30 08:35:29 - mmengine - INFO - Epoch(train) [336][25/63] lr: 5.2123e-03 eta: 23:08:37 time: 2.5979 data_time: 0.0635 memory: 16201 loss_prob: 0.6726 loss_thr: 0.4358 loss_db: 0.1137 loss: 1.2221 2022/08/30 08:35:41 - mmengine - INFO - Epoch(train) [336][30/63] lr: 5.2123e-03 eta: 23:08:46 time: 2.4700 data_time: 0.0583 memory: 16201 loss_prob: 0.6494 loss_thr: 0.4355 loss_db: 0.1121 loss: 1.1971 2022/08/30 08:35:55 - mmengine - INFO - Epoch(train) [336][35/63] lr: 5.2123e-03 eta: 23:08:46 time: 2.6281 data_time: 0.0534 memory: 16201 loss_prob: 0.6656 loss_thr: 0.4203 loss_db: 0.1144 loss: 1.2002 2022/08/30 08:36:07 - mmengine - INFO - Epoch(train) [336][40/63] lr: 5.2123e-03 eta: 23:09:00 time: 2.6526 data_time: 0.0519 memory: 16201 loss_prob: 0.6755 loss_thr: 0.4222 loss_db: 0.1130 loss: 1.2107 2022/08/30 08:36:21 - mmengine - INFO - Epoch(train) [336][45/63] lr: 5.2123e-03 eta: 23:09:00 time: 2.5606 data_time: 0.0637 memory: 16201 loss_prob: 0.6470 loss_thr: 0.4243 loss_db: 0.1102 loss: 1.1815 2022/08/30 08:36:34 - mmengine - INFO - Epoch(train) [336][50/63] lr: 5.2123e-03 eta: 23:09:13 time: 2.6555 data_time: 0.0703 memory: 16201 loss_prob: 0.6077 loss_thr: 0.4155 loss_db: 0.1064 loss: 1.1296 2022/08/30 08:36:50 - mmengine - INFO - Epoch(train) [336][55/63] lr: 5.2123e-03 eta: 23:09:13 time: 2.9514 data_time: 0.0513 memory: 16201 loss_prob: 0.5982 loss_thr: 0.4062 loss_db: 0.1022 loss: 1.1066 2022/08/30 08:37:03 - mmengine - INFO - Epoch(train) [336][60/63] lr: 5.2123e-03 eta: 23:09:35 time: 2.9541 data_time: 0.0525 memory: 16201 loss_prob: 0.6457 loss_thr: 0.4272 loss_db: 0.1095 loss: 1.1825 2022/08/30 08:37:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:37:25 - mmengine - INFO - Epoch(train) [337][5/63] lr: 5.2068e-03 eta: 23:09:35 time: 2.7871 data_time: 0.2836 memory: 16201 loss_prob: 0.6483 loss_thr: 0.4267 loss_db: 0.1125 loss: 1.1875 2022/08/30 08:37:38 - mmengine - INFO - Epoch(train) [337][10/63] lr: 5.2068e-03 eta: 23:09:36 time: 2.8206 data_time: 0.2902 memory: 16201 loss_prob: 0.6586 loss_thr: 0.4392 loss_db: 0.1120 loss: 1.2098 2022/08/30 08:37:53 - mmengine - INFO - Epoch(train) [337][15/63] lr: 5.2068e-03 eta: 23:09:36 time: 2.8011 data_time: 0.0494 memory: 16201 loss_prob: 0.7033 loss_thr: 0.4419 loss_db: 0.1205 loss: 1.2658 2022/08/30 08:38:06 - mmengine - INFO - Epoch(train) [337][20/63] lr: 5.2068e-03 eta: 23:09:53 time: 2.8020 data_time: 0.0612 memory: 16201 loss_prob: 0.7120 loss_thr: 0.4540 loss_db: 0.1249 loss: 1.2909 2022/08/30 08:38:18 - mmengine - INFO - Epoch(train) [337][25/63] lr: 5.2068e-03 eta: 23:09:53 time: 2.5033 data_time: 0.0678 memory: 16201 loss_prob: 0.6592 loss_thr: 0.4451 loss_db: 0.1120 loss: 1.2163 2022/08/30 08:38:31 - mmengine - INFO - Epoch(train) [337][30/63] lr: 5.2068e-03 eta: 23:10:03 time: 2.5276 data_time: 0.0600 memory: 16201 loss_prob: 0.6562 loss_thr: 0.4260 loss_db: 0.1082 loss: 1.1905 2022/08/30 08:38:44 - mmengine - INFO - Epoch(train) [337][35/63] lr: 5.2068e-03 eta: 23:10:03 time: 2.6412 data_time: 0.0589 memory: 16201 loss_prob: 0.9675 loss_thr: 0.4636 loss_db: 0.1519 loss: 1.5830 2022/08/30 08:38:55 - mmengine - INFO - Epoch(train) [337][40/63] lr: 5.2068e-03 eta: 23:10:10 time: 2.4017 data_time: 0.0545 memory: 16201 loss_prob: 0.9530 loss_thr: 0.4625 loss_db: 0.1508 loss: 1.5663 2022/08/30 08:39:09 - mmengine - INFO - Epoch(train) [337][45/63] lr: 5.2068e-03 eta: 23:10:10 time: 2.4539 data_time: 0.0607 memory: 16201 loss_prob: 0.6518 loss_thr: 0.4116 loss_db: 0.1089 loss: 1.1722 2022/08/30 08:39:22 - mmengine - INFO - Epoch(train) [337][50/63] lr: 5.2068e-03 eta: 23:10:26 time: 2.7271 data_time: 0.0676 memory: 16201 loss_prob: 0.8720 loss_thr: 0.4081 loss_db: 0.1440 loss: 1.4241 2022/08/30 08:39:36 - mmengine - INFO - Epoch(train) [337][55/63] lr: 5.2068e-03 eta: 23:10:26 time: 2.6981 data_time: 0.0522 memory: 16201 loss_prob: 0.9714 loss_thr: 0.4403 loss_db: 0.1577 loss: 1.5694 2022/08/30 08:39:50 - mmengine - INFO - Epoch(train) [337][60/63] lr: 5.2068e-03 eta: 23:10:42 time: 2.7793 data_time: 0.0527 memory: 16201 loss_prob: 0.8741 loss_thr: 0.4804 loss_db: 0.1398 loss: 1.4943 2022/08/30 08:39:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:40:12 - mmengine - INFO - Epoch(train) [338][5/63] lr: 5.2014e-03 eta: 23:10:42 time: 2.8488 data_time: 0.2983 memory: 16201 loss_prob: 0.8148 loss_thr: 0.4732 loss_db: 0.1396 loss: 1.4275 2022/08/30 08:40:27 - mmengine - INFO - Epoch(train) [338][10/63] lr: 5.2014e-03 eta: 23:10:46 time: 2.9318 data_time: 0.3106 memory: 16201 loss_prob: 0.7370 loss_thr: 0.4347 loss_db: 0.1269 loss: 1.2986 2022/08/30 08:40:41 - mmengine - INFO - Epoch(train) [338][15/63] lr: 5.2014e-03 eta: 23:10:46 time: 2.8544 data_time: 0.0741 memory: 16201 loss_prob: 0.7105 loss_thr: 0.4465 loss_db: 0.1172 loss: 1.2742 2022/08/30 08:40:55 - mmengine - INFO - Epoch(train) [338][20/63] lr: 5.2014e-03 eta: 23:11:03 time: 2.7869 data_time: 0.0698 memory: 16201 loss_prob: 0.7188 loss_thr: 0.4535 loss_db: 0.1200 loss: 1.2923 2022/08/30 08:41:07 - mmengine - INFO - Epoch(train) [338][25/63] lr: 5.2014e-03 eta: 23:11:03 time: 2.6357 data_time: 0.0683 memory: 16201 loss_prob: 0.7965 loss_thr: 0.4374 loss_db: 0.1259 loss: 1.3598 2022/08/30 08:41:21 - mmengine - INFO - Epoch(train) [338][30/63] lr: 5.2014e-03 eta: 23:11:14 time: 2.5875 data_time: 0.0654 memory: 16201 loss_prob: 0.7888 loss_thr: 0.4403 loss_db: 0.1240 loss: 1.3531 2022/08/30 08:41:35 - mmengine - INFO - Epoch(train) [338][35/63] lr: 5.2014e-03 eta: 23:11:14 time: 2.8380 data_time: 0.0577 memory: 16201 loss_prob: 0.7237 loss_thr: 0.4483 loss_db: 0.1193 loss: 1.2912 2022/08/30 08:41:48 - mmengine - INFO - Epoch(train) [338][40/63] lr: 5.2014e-03 eta: 23:11:29 time: 2.7268 data_time: 0.0561 memory: 16201 loss_prob: 0.7321 loss_thr: 0.4514 loss_db: 0.1218 loss: 1.3054 2022/08/30 08:42:01 - mmengine - INFO - Epoch(train) [338][45/63] lr: 5.2014e-03 eta: 23:11:29 time: 2.5305 data_time: 0.0703 memory: 16201 loss_prob: 0.6997 loss_thr: 0.4288 loss_db: 0.1176 loss: 1.2461 2022/08/30 08:42:14 - mmengine - INFO - Epoch(train) [338][50/63] lr: 5.2014e-03 eta: 23:11:42 time: 2.6181 data_time: 0.0585 memory: 16201 loss_prob: 0.6805 loss_thr: 0.4128 loss_db: 0.1134 loss: 1.2067 2022/08/30 08:42:28 - mmengine - INFO - Epoch(train) [338][55/63] lr: 5.2014e-03 eta: 23:11:42 time: 2.7623 data_time: 0.0521 memory: 16201 loss_prob: 0.7032 loss_thr: 0.4306 loss_db: 0.1204 loss: 1.2542 2022/08/30 08:42:40 - mmengine - INFO - Epoch(train) [338][60/63] lr: 5.2014e-03 eta: 23:11:54 time: 2.6215 data_time: 0.0665 memory: 16201 loss_prob: 0.6742 loss_thr: 0.4362 loss_db: 0.1156 loss: 1.2260 2022/08/30 08:42:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:43:00 - mmengine - INFO - Epoch(train) [339][5/63] lr: 5.1960e-03 eta: 23:11:54 time: 2.4328 data_time: 0.2963 memory: 16201 loss_prob: 0.6143 loss_thr: 0.4253 loss_db: 0.1047 loss: 1.1443 2022/08/30 08:43:13 - mmengine - INFO - Epoch(train) [339][10/63] lr: 5.1960e-03 eta: 23:11:52 time: 2.6902 data_time: 0.3034 memory: 16201 loss_prob: 0.6468 loss_thr: 0.4333 loss_db: 0.1120 loss: 1.1921 2022/08/30 08:43:26 - mmengine - INFO - Epoch(train) [339][15/63] lr: 5.1960e-03 eta: 23:11:52 time: 2.5948 data_time: 0.0487 memory: 16201 loss_prob: 0.6121 loss_thr: 0.4247 loss_db: 0.1053 loss: 1.1421 2022/08/30 08:43:40 - mmengine - INFO - Epoch(train) [339][20/63] lr: 5.1960e-03 eta: 23:12:05 time: 2.6517 data_time: 0.0591 memory: 16201 loss_prob: 0.6208 loss_thr: 0.4285 loss_db: 0.1061 loss: 1.1554 2022/08/30 08:43:52 - mmengine - INFO - Epoch(train) [339][25/63] lr: 5.1960e-03 eta: 23:12:05 time: 2.5559 data_time: 0.0801 memory: 16201 loss_prob: 0.7124 loss_thr: 0.4589 loss_db: 0.1216 loss: 1.2930 2022/08/30 08:44:06 - mmengine - INFO - Epoch(train) [339][30/63] lr: 5.1960e-03 eta: 23:12:17 time: 2.6194 data_time: 0.0520 memory: 16201 loss_prob: 0.7529 loss_thr: 0.4705 loss_db: 0.1291 loss: 1.3525 2022/08/30 08:44:20 - mmengine - INFO - Epoch(train) [339][35/63] lr: 5.1960e-03 eta: 23:12:17 time: 2.8027 data_time: 0.0514 memory: 16201 loss_prob: 0.7026 loss_thr: 0.4408 loss_db: 0.1207 loss: 1.2641 2022/08/30 08:44:32 - mmengine - INFO - Epoch(train) [339][40/63] lr: 5.1960e-03 eta: 23:12:30 time: 2.6688 data_time: 0.0618 memory: 16201 loss_prob: 0.7353 loss_thr: 0.4416 loss_db: 0.1246 loss: 1.3014 2022/08/30 08:44:46 - mmengine - INFO - Epoch(train) [339][45/63] lr: 5.1960e-03 eta: 23:12:30 time: 2.6261 data_time: 0.0599 memory: 16201 loss_prob: 0.6921 loss_thr: 0.4244 loss_db: 0.1165 loss: 1.2330 2022/08/30 08:44:59 - mmengine - INFO - Epoch(train) [339][50/63] lr: 5.1960e-03 eta: 23:12:43 time: 2.6628 data_time: 0.0791 memory: 16201 loss_prob: 0.6507 loss_thr: 0.4169 loss_db: 0.1083 loss: 1.1758 2022/08/30 08:45:11 - mmengine - INFO - Epoch(train) [339][55/63] lr: 5.1960e-03 eta: 23:12:43 time: 2.4701 data_time: 0.0610 memory: 16201 loss_prob: 0.6591 loss_thr: 0.4347 loss_db: 0.1122 loss: 1.2060 2022/08/30 08:45:24 - mmengine - INFO - Epoch(train) [339][60/63] lr: 5.1960e-03 eta: 23:12:51 time: 2.4463 data_time: 0.0512 memory: 16201 loss_prob: 0.6306 loss_thr: 0.4270 loss_db: 0.1093 loss: 1.1669 2022/08/30 08:45:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:45:46 - mmengine - INFO - Epoch(train) [340][5/63] lr: 5.1905e-03 eta: 23:12:51 time: 2.6642 data_time: 0.2742 memory: 16201 loss_prob: 0.7567 loss_thr: 0.4628 loss_db: 0.1279 loss: 1.3474 2022/08/30 08:45:58 - mmengine - INFO - Epoch(train) [340][10/63] lr: 5.1905e-03 eta: 23:12:50 time: 2.7443 data_time: 0.2946 memory: 16201 loss_prob: 0.6605 loss_thr: 0.4234 loss_db: 0.1153 loss: 1.1992 2022/08/30 08:46:11 - mmengine - INFO - Epoch(train) [340][15/63] lr: 5.1905e-03 eta: 23:12:50 time: 2.5249 data_time: 0.0609 memory: 16201 loss_prob: 0.5990 loss_thr: 0.4174 loss_db: 0.1045 loss: 1.1210 2022/08/30 08:46:24 - mmengine - INFO - Epoch(train) [340][20/63] lr: 5.1905e-03 eta: 23:13:00 time: 2.5761 data_time: 0.0671 memory: 16201 loss_prob: 0.6071 loss_thr: 0.4220 loss_db: 0.1034 loss: 1.1325 2022/08/30 08:46:38 - mmengine - INFO - Epoch(train) [340][25/63] lr: 5.1905e-03 eta: 23:13:00 time: 2.6455 data_time: 0.0752 memory: 16201 loss_prob: 0.6544 loss_thr: 0.4388 loss_db: 0.1113 loss: 1.2045 2022/08/30 08:46:50 - mmengine - INFO - Epoch(train) [340][30/63] lr: 5.1905e-03 eta: 23:13:12 time: 2.6208 data_time: 0.0519 memory: 16201 loss_prob: 0.7072 loss_thr: 0.4503 loss_db: 0.1210 loss: 1.2786 2022/08/30 08:47:05 - mmengine - INFO - Epoch(train) [340][35/63] lr: 5.1905e-03 eta: 23:13:12 time: 2.7434 data_time: 0.0733 memory: 16201 loss_prob: 0.6649 loss_thr: 0.4277 loss_db: 0.1120 loss: 1.2046 2022/08/30 08:47:20 - mmengine - INFO - Epoch(train) [340][40/63] lr: 5.1905e-03 eta: 23:13:33 time: 2.9773 data_time: 0.0698 memory: 16201 loss_prob: 0.6463 loss_thr: 0.4160 loss_db: 0.1075 loss: 1.1698 2022/08/30 08:47:34 - mmengine - INFO - Epoch(train) [340][45/63] lr: 5.1905e-03 eta: 23:13:33 time: 2.8750 data_time: 0.0610 memory: 16201 loss_prob: 0.6589 loss_thr: 0.4233 loss_db: 0.1090 loss: 1.1912 2022/08/30 08:47:49 - mmengine - INFO - Epoch(train) [340][50/63] lr: 5.1905e-03 eta: 23:13:53 time: 2.9135 data_time: 0.0833 memory: 16201 loss_prob: 0.6211 loss_thr: 0.4069 loss_db: 0.1044 loss: 1.1324 2022/08/30 08:48:03 - mmengine - INFO - Epoch(train) [340][55/63] lr: 5.1905e-03 eta: 23:13:53 time: 2.9512 data_time: 0.0617 memory: 16201 loss_prob: 0.6875 loss_thr: 0.4455 loss_db: 0.1158 loss: 1.2488 2022/08/30 08:48:17 - mmengine - INFO - Epoch(train) [340][60/63] lr: 5.1905e-03 eta: 23:14:08 time: 2.7592 data_time: 0.0581 memory: 16201 loss_prob: 0.7017 loss_thr: 0.4676 loss_db: 0.1186 loss: 1.2879 2022/08/30 08:48:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:48:24 - mmengine - INFO - Saving checkpoint at 340 epochs 2022/08/30 08:48:33 - mmengine - INFO - Epoch(val) [340][5/32] eta: 23:14:08 time: 0.7034 data_time: 0.1583 memory: 16201 2022/08/30 08:48:36 - mmengine - INFO - Epoch(val) [340][10/32] eta: 0:00:16 time: 0.7711 data_time: 0.1706 memory: 15734 2022/08/30 08:48:39 - mmengine - INFO - Epoch(val) [340][15/32] eta: 0:00:16 time: 0.6675 data_time: 0.0696 memory: 15734 2022/08/30 08:48:44 - mmengine - INFO - Epoch(val) [340][20/32] eta: 0:00:09 time: 0.7577 data_time: 0.1041 memory: 15734 2022/08/30 08:48:47 - mmengine - INFO - Epoch(val) [340][25/32] eta: 0:00:09 time: 0.7693 data_time: 0.0820 memory: 15734 2022/08/30 08:48:50 - mmengine - INFO - Epoch(val) [340][30/32] eta: 0:00:01 time: 0.6533 data_time: 0.0341 memory: 15734 2022/08/30 08:48:51 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 08:48:51 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8377, precision: 0.7775, hmean: 0.8065 2022/08/30 08:48:51 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8373, precision: 0.8157, hmean: 0.8263 2022/08/30 08:48:51 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8353, precision: 0.8410, hmean: 0.8382 2022/08/30 08:48:51 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8305, precision: 0.8625, hmean: 0.8462 2022/08/30 08:48:51 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8098, precision: 0.8843, hmean: 0.8454 2022/08/30 08:48:51 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6822, precision: 0.9329, hmean: 0.7881 2022/08/30 08:48:51 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0462, precision: 0.9697, hmean: 0.0882 2022/08/30 08:48:51 - mmengine - INFO - Epoch(val) [340][32/32] icdar/precision: 0.8625 icdar/recall: 0.8305 icdar/hmean: 0.8462 2022/08/30 08:49:07 - mmengine - INFO - Epoch(train) [341][5/63] lr: 5.1851e-03 eta: 0:00:01 time: 2.8979 data_time: 0.3049 memory: 16201 loss_prob: 0.6478 loss_thr: 0.4311 loss_db: 0.1128 loss: 1.1917 2022/08/30 08:49:19 - mmengine - INFO - Epoch(train) [341][10/63] lr: 5.1851e-03 eta: 23:14:09 time: 2.8320 data_time: 0.3100 memory: 16201 loss_prob: 0.6589 loss_thr: 0.4263 loss_db: 0.1121 loss: 1.1973 2022/08/30 08:49:30 - mmengine - INFO - Epoch(train) [341][15/63] lr: 5.1851e-03 eta: 23:14:09 time: 2.2863 data_time: 0.0550 memory: 16201 loss_prob: 0.6912 loss_thr: 0.4537 loss_db: 0.1148 loss: 1.2597 2022/08/30 08:49:43 - mmengine - INFO - Epoch(train) [341][20/63] lr: 5.1851e-03 eta: 23:14:14 time: 2.3712 data_time: 0.0563 memory: 16201 loss_prob: 0.6727 loss_thr: 0.4494 loss_db: 0.1134 loss: 1.2355 2022/08/30 08:49:57 - mmengine - INFO - Epoch(train) [341][25/63] lr: 5.1851e-03 eta: 23:14:14 time: 2.6856 data_time: 0.0856 memory: 16201 loss_prob: 0.6500 loss_thr: 0.4329 loss_db: 0.1125 loss: 1.1953 2022/08/30 08:50:09 - mmengine - INFO - Epoch(train) [341][30/63] lr: 5.1851e-03 eta: 23:14:25 time: 2.6008 data_time: 0.0693 memory: 16201 loss_prob: 0.6672 loss_thr: 0.4210 loss_db: 0.1141 loss: 1.2023 2022/08/30 08:50:23 - mmengine - INFO - Epoch(train) [341][35/63] lr: 5.1851e-03 eta: 23:14:25 time: 2.6156 data_time: 0.0497 memory: 16201 loss_prob: 0.6578 loss_thr: 0.4176 loss_db: 0.1112 loss: 1.1866 2022/08/30 08:50:36 - mmengine - INFO - Epoch(train) [341][40/63] lr: 5.1851e-03 eta: 23:14:38 time: 2.6462 data_time: 0.0507 memory: 16201 loss_prob: 0.7047 loss_thr: 0.4547 loss_db: 0.1209 loss: 1.2802 2022/08/30 08:50:49 - mmengine - INFO - Epoch(train) [341][45/63] lr: 5.1851e-03 eta: 23:14:38 time: 2.6121 data_time: 0.0538 memory: 16201 loss_prob: 0.6780 loss_thr: 0.4373 loss_db: 0.1161 loss: 1.2314 2022/08/30 08:51:03 - mmengine - INFO - Epoch(train) [341][50/63] lr: 5.1851e-03 eta: 23:14:53 time: 2.7541 data_time: 0.1072 memory: 16201 loss_prob: 0.6136 loss_thr: 0.3990 loss_db: 0.1065 loss: 1.1191 2022/08/30 08:51:17 - mmengine - INFO - Epoch(train) [341][55/63] lr: 5.1851e-03 eta: 23:14:53 time: 2.7774 data_time: 0.1218 memory: 16201 loss_prob: 0.6523 loss_thr: 0.4292 loss_db: 0.1157 loss: 1.1971 2022/08/30 08:51:28 - mmengine - INFO - Epoch(train) [341][60/63] lr: 5.1851e-03 eta: 23:15:01 time: 2.4856 data_time: 0.0606 memory: 16201 loss_prob: 0.7029 loss_thr: 0.4620 loss_db: 0.1200 loss: 1.2849 2022/08/30 08:51:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:51:49 - mmengine - INFO - Epoch(train) [342][5/63] lr: 5.1797e-03 eta: 23:15:01 time: 2.5892 data_time: 0.3006 memory: 16201 loss_prob: 0.5915 loss_thr: 0.4038 loss_db: 0.0999 loss: 1.0952 2022/08/30 08:52:02 - mmengine - INFO - Epoch(train) [342][10/63] lr: 5.1797e-03 eta: 23:14:58 time: 2.7121 data_time: 0.2958 memory: 16201 loss_prob: 0.5547 loss_thr: 0.3850 loss_db: 0.0957 loss: 1.0354 2022/08/30 08:52:17 - mmengine - INFO - Epoch(train) [342][15/63] lr: 5.1797e-03 eta: 23:14:58 time: 2.7357 data_time: 0.0586 memory: 16201 loss_prob: 0.6013 loss_thr: 0.4002 loss_db: 0.1034 loss: 1.1049 2022/08/30 08:52:29 - mmengine - INFO - Epoch(train) [342][20/63] lr: 5.1797e-03 eta: 23:15:10 time: 2.6391 data_time: 0.0657 memory: 16201 loss_prob: 0.6711 loss_thr: 0.4155 loss_db: 0.1130 loss: 1.1995 2022/08/30 08:52:41 - mmengine - INFO - Epoch(train) [342][25/63] lr: 5.1797e-03 eta: 23:15:10 time: 2.4458 data_time: 0.0600 memory: 16201 loss_prob: 0.6852 loss_thr: 0.4324 loss_db: 0.1166 loss: 1.2342 2022/08/30 08:52:53 - mmengine - INFO - Epoch(train) [342][30/63] lr: 5.1797e-03 eta: 23:15:17 time: 2.4301 data_time: 0.0572 memory: 16201 loss_prob: 0.6717 loss_thr: 0.4403 loss_db: 0.1151 loss: 1.2272 2022/08/30 08:53:06 - mmengine - INFO - Epoch(train) [342][35/63] lr: 5.1797e-03 eta: 23:15:17 time: 2.5233 data_time: 0.0578 memory: 16201 loss_prob: 0.6384 loss_thr: 0.4149 loss_db: 0.1091 loss: 1.1623 2022/08/30 08:53:21 - mmengine - INFO - Epoch(train) [342][40/63] lr: 5.1797e-03 eta: 23:15:32 time: 2.7657 data_time: 0.0478 memory: 16201 loss_prob: 0.6760 loss_thr: 0.4349 loss_db: 0.1144 loss: 1.2253 2022/08/30 08:53:33 - mmengine - INFO - Epoch(train) [342][45/63] lr: 5.1797e-03 eta: 23:15:32 time: 2.6962 data_time: 0.0601 memory: 16201 loss_prob: 0.7555 loss_thr: 0.4442 loss_db: 0.1242 loss: 1.3240 2022/08/30 08:53:47 - mmengine - INFO - Epoch(train) [342][50/63] lr: 5.1797e-03 eta: 23:15:43 time: 2.5898 data_time: 0.0635 memory: 16201 loss_prob: 0.6627 loss_thr: 0.4069 loss_db: 0.1116 loss: 1.1812 2022/08/30 08:54:01 - mmengine - INFO - Epoch(train) [342][55/63] lr: 5.1797e-03 eta: 23:15:43 time: 2.8242 data_time: 0.0473 memory: 16201 loss_prob: 0.6232 loss_thr: 0.4165 loss_db: 0.1079 loss: 1.1475 2022/08/30 08:54:15 - mmengine - INFO - Epoch(train) [342][60/63] lr: 5.1797e-03 eta: 23:16:00 time: 2.8555 data_time: 0.0564 memory: 16201 loss_prob: 0.6835 loss_thr: 0.4321 loss_db: 0.1182 loss: 1.2339 2022/08/30 08:54:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:54:35 - mmengine - INFO - Epoch(train) [343][5/63] lr: 5.1742e-03 eta: 23:16:00 time: 2.6261 data_time: 0.3164 memory: 16201 loss_prob: 0.5680 loss_thr: 0.3847 loss_db: 0.0986 loss: 1.0514 2022/08/30 08:54:50 - mmengine - INFO - Epoch(train) [343][10/63] lr: 5.1742e-03 eta: 23:15:59 time: 2.7594 data_time: 0.3218 memory: 16201 loss_prob: 0.6146 loss_thr: 0.3990 loss_db: 0.1064 loss: 1.1200 2022/08/30 08:55:03 - mmengine - INFO - Epoch(train) [343][15/63] lr: 5.1742e-03 eta: 23:15:59 time: 2.7760 data_time: 0.0581 memory: 16201 loss_prob: 0.6269 loss_thr: 0.4074 loss_db: 0.1090 loss: 1.1433 2022/08/30 08:55:16 - mmengine - INFO - Epoch(train) [343][20/63] lr: 5.1742e-03 eta: 23:16:12 time: 2.6772 data_time: 0.0654 memory: 16201 loss_prob: 0.6057 loss_thr: 0.4159 loss_db: 0.1058 loss: 1.1274 2022/08/30 08:55:29 - mmengine - INFO - Epoch(train) [343][25/63] lr: 5.1742e-03 eta: 23:16:12 time: 2.6387 data_time: 0.0756 memory: 16201 loss_prob: 0.6568 loss_thr: 0.4297 loss_db: 0.1138 loss: 1.2003 2022/08/30 08:55:41 - mmengine - INFO - Epoch(train) [343][30/63] lr: 5.1742e-03 eta: 23:16:18 time: 2.4344 data_time: 0.0497 memory: 16201 loss_prob: 0.7320 loss_thr: 0.4526 loss_db: 0.1221 loss: 1.3066 2022/08/30 08:55:52 - mmengine - INFO - Epoch(train) [343][35/63] lr: 5.1742e-03 eta: 23:16:18 time: 2.3158 data_time: 0.0651 memory: 16201 loss_prob: 0.6826 loss_thr: 0.4373 loss_db: 0.1153 loss: 1.2353 2022/08/30 08:56:07 - mmengine - INFO - Epoch(train) [343][40/63] lr: 5.1742e-03 eta: 23:16:29 time: 2.5991 data_time: 0.0686 memory: 16201 loss_prob: 0.6284 loss_thr: 0.4238 loss_db: 0.1089 loss: 1.1611 2022/08/30 08:56:20 - mmengine - INFO - Epoch(train) [343][45/63] lr: 5.1742e-03 eta: 23:16:29 time: 2.7948 data_time: 0.0698 memory: 16201 loss_prob: 0.6471 loss_thr: 0.4350 loss_db: 0.1092 loss: 1.1913 2022/08/30 08:56:33 - mmengine - INFO - Epoch(train) [343][50/63] lr: 5.1742e-03 eta: 23:16:42 time: 2.6751 data_time: 0.0769 memory: 16201 loss_prob: 0.6477 loss_thr: 0.4260 loss_db: 0.1091 loss: 1.1828 2022/08/30 08:56:48 - mmengine - INFO - Epoch(train) [343][55/63] lr: 5.1742e-03 eta: 23:16:42 time: 2.7666 data_time: 0.0498 memory: 16201 loss_prob: 0.6738 loss_thr: 0.4293 loss_db: 0.1129 loss: 1.2160 2022/08/30 08:57:03 - mmengine - INFO - Epoch(train) [343][60/63] lr: 5.1742e-03 eta: 23:17:01 time: 2.9349 data_time: 0.0638 memory: 16201 loss_prob: 0.6425 loss_thr: 0.4175 loss_db: 0.1068 loss: 1.1669 2022/08/30 08:57:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 08:57:27 - mmengine - INFO - Epoch(train) [344][5/63] lr: 5.1688e-03 eta: 23:17:01 time: 3.0988 data_time: 0.2817 memory: 16201 loss_prob: 0.6347 loss_thr: 0.3996 loss_db: 0.1056 loss: 1.1399 2022/08/30 08:57:41 - mmengine - INFO - Epoch(train) [344][10/63] lr: 5.1688e-03 eta: 23:17:06 time: 3.0578 data_time: 0.2900 memory: 16201 loss_prob: 0.6080 loss_thr: 0.3936 loss_db: 0.1023 loss: 1.1040 2022/08/30 08:57:55 - mmengine - INFO - Epoch(train) [344][15/63] lr: 5.1688e-03 eta: 23:17:06 time: 2.7760 data_time: 0.0575 memory: 16201 loss_prob: 0.6844 loss_thr: 0.4366 loss_db: 0.1189 loss: 1.2399 2022/08/30 08:58:08 - mmengine - INFO - Epoch(train) [344][20/63] lr: 5.1688e-03 eta: 23:17:21 time: 2.7618 data_time: 0.0666 memory: 16201 loss_prob: 0.7104 loss_thr: 0.4568 loss_db: 0.1248 loss: 1.2920 2022/08/30 08:58:21 - mmengine - INFO - Epoch(train) [344][25/63] lr: 5.1688e-03 eta: 23:17:21 time: 2.6196 data_time: 0.0581 memory: 16201 loss_prob: 0.7563 loss_thr: 0.4817 loss_db: 0.1260 loss: 1.3640 2022/08/30 08:58:33 - mmengine - INFO - Epoch(train) [344][30/63] lr: 5.1688e-03 eta: 23:17:28 time: 2.4519 data_time: 0.0618 memory: 16201 loss_prob: 0.7094 loss_thr: 0.4434 loss_db: 0.1155 loss: 1.2683 2022/08/30 08:58:46 - mmengine - INFO - Epoch(train) [344][35/63] lr: 5.1688e-03 eta: 23:17:28 time: 2.5015 data_time: 0.0800 memory: 16201 loss_prob: 0.6010 loss_thr: 0.3930 loss_db: 0.1017 loss: 1.0956 2022/08/30 08:58:56 - mmengine - INFO - Epoch(train) [344][40/63] lr: 5.1688e-03 eta: 23:17:30 time: 2.2615 data_time: 0.0619 memory: 16201 loss_prob: 0.6027 loss_thr: 0.3990 loss_db: 0.1043 loss: 1.1059 2022/08/30 08:59:11 - mmengine - INFO - Epoch(train) [344][45/63] lr: 5.1688e-03 eta: 23:17:30 time: 2.4625 data_time: 0.0565 memory: 16201 loss_prob: 0.6703 loss_thr: 0.4126 loss_db: 0.1115 loss: 1.1944 2022/08/30 08:59:24 - mmengine - INFO - Epoch(train) [344][50/63] lr: 5.1688e-03 eta: 23:17:46 time: 2.8024 data_time: 0.0571 memory: 16201 loss_prob: 0.7189 loss_thr: 0.4380 loss_db: 0.1160 loss: 1.2729 2022/08/30 08:59:36 - mmengine - INFO - Epoch(train) [344][55/63] lr: 5.1688e-03 eta: 23:17:46 time: 2.5413 data_time: 0.0489 memory: 16201 loss_prob: 0.7103 loss_thr: 0.4660 loss_db: 0.1177 loss: 1.2941 2022/08/30 08:59:49 - mmengine - INFO - Epoch(train) [344][60/63] lr: 5.1688e-03 eta: 23:17:55 time: 2.5431 data_time: 0.0602 memory: 16201 loss_prob: 0.6607 loss_thr: 0.4405 loss_db: 0.1144 loss: 1.2155 2022/08/30 08:59:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:00:13 - mmengine - INFO - Epoch(train) [345][5/63] lr: 5.1634e-03 eta: 23:17:55 time: 2.9365 data_time: 0.2795 memory: 16201 loss_prob: 0.5934 loss_thr: 0.3999 loss_db: 0.1025 loss: 1.0958 2022/08/30 09:00:26 - mmengine - INFO - Epoch(train) [345][10/63] lr: 5.1634e-03 eta: 23:17:57 time: 2.9490 data_time: 0.2899 memory: 16201 loss_prob: 0.5881 loss_thr: 0.3994 loss_db: 0.0963 loss: 1.0838 2022/08/30 09:00:39 - mmengine - INFO - Epoch(train) [345][15/63] lr: 5.1634e-03 eta: 23:17:57 time: 2.6696 data_time: 0.0562 memory: 16201 loss_prob: 0.5677 loss_thr: 0.3884 loss_db: 0.0972 loss: 1.0532 2022/08/30 09:00:54 - mmengine - INFO - Epoch(train) [345][20/63] lr: 5.1634e-03 eta: 23:18:13 time: 2.8256 data_time: 0.0572 memory: 16201 loss_prob: 0.6018 loss_thr: 0.4071 loss_db: 0.1063 loss: 1.1153 2022/08/30 09:01:08 - mmengine - INFO - Epoch(train) [345][25/63] lr: 5.1634e-03 eta: 23:18:13 time: 2.8633 data_time: 0.0606 memory: 16201 loss_prob: 0.6205 loss_thr: 0.4228 loss_db: 0.1074 loss: 1.1507 2022/08/30 09:01:21 - mmengine - INFO - Epoch(train) [345][30/63] lr: 5.1634e-03 eta: 23:18:27 time: 2.7151 data_time: 0.0526 memory: 16201 loss_prob: 0.6192 loss_thr: 0.4122 loss_db: 0.1066 loss: 1.1380 2022/08/30 09:01:34 - mmengine - INFO - Epoch(train) [345][35/63] lr: 5.1634e-03 eta: 23:18:27 time: 2.6177 data_time: 0.0713 memory: 16201 loss_prob: 0.7289 loss_thr: 0.4420 loss_db: 0.1183 loss: 1.2892 2022/08/30 09:01:47 - mmengine - INFO - Epoch(train) [345][40/63] lr: 5.1634e-03 eta: 23:18:35 time: 2.5232 data_time: 0.0539 memory: 16201 loss_prob: 0.7761 loss_thr: 0.4732 loss_db: 0.1255 loss: 1.3749 2022/08/30 09:02:01 - mmengine - INFO - Epoch(train) [345][45/63] lr: 5.1634e-03 eta: 23:18:35 time: 2.7150 data_time: 0.0547 memory: 16201 loss_prob: 0.7188 loss_thr: 0.4706 loss_db: 0.1240 loss: 1.3134 2022/08/30 09:02:14 - mmengine - INFO - Epoch(train) [345][50/63] lr: 5.1634e-03 eta: 23:18:49 time: 2.7402 data_time: 0.0799 memory: 16201 loss_prob: 0.6523 loss_thr: 0.4330 loss_db: 0.1133 loss: 1.1986 2022/08/30 09:02:26 - mmengine - INFO - Epoch(train) [345][55/63] lr: 5.1634e-03 eta: 23:18:49 time: 2.4908 data_time: 0.0621 memory: 16201 loss_prob: 0.6284 loss_thr: 0.4143 loss_db: 0.1106 loss: 1.1533 2022/08/30 09:02:38 - mmengine - INFO - Epoch(train) [345][60/63] lr: 5.1634e-03 eta: 23:18:53 time: 2.3669 data_time: 0.0588 memory: 16201 loss_prob: 0.7126 loss_thr: 0.4354 loss_db: 0.1199 loss: 1.2680 2022/08/30 09:02:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:03:01 - mmengine - INFO - Epoch(train) [346][5/63] lr: 5.1579e-03 eta: 23:18:53 time: 2.7411 data_time: 0.2774 memory: 16201 loss_prob: 0.6889 loss_thr: 0.4465 loss_db: 0.1185 loss: 1.2539 2022/08/30 09:03:14 - mmengine - INFO - Epoch(train) [346][10/63] lr: 5.1579e-03 eta: 23:18:55 time: 2.9248 data_time: 0.3033 memory: 16201 loss_prob: 0.6683 loss_thr: 0.4523 loss_db: 0.1159 loss: 1.2365 2022/08/30 09:03:27 - mmengine - INFO - Epoch(train) [346][15/63] lr: 5.1579e-03 eta: 23:18:55 time: 2.5781 data_time: 0.0644 memory: 16201 loss_prob: 0.6983 loss_thr: 0.4663 loss_db: 0.1178 loss: 1.2825 2022/08/30 09:03:41 - mmengine - INFO - Epoch(train) [346][20/63] lr: 5.1579e-03 eta: 23:19:07 time: 2.6412 data_time: 0.0609 memory: 16201 loss_prob: 0.6321 loss_thr: 0.4209 loss_db: 0.1053 loss: 1.1584 2022/08/30 09:03:56 - mmengine - INFO - Epoch(train) [346][25/63] lr: 5.1579e-03 eta: 23:19:07 time: 2.9014 data_time: 0.0661 memory: 16201 loss_prob: 0.6018 loss_thr: 0.3882 loss_db: 0.1035 loss: 1.0935 2022/08/30 09:04:12 - mmengine - INFO - Epoch(train) [346][30/63] lr: 5.1579e-03 eta: 23:19:29 time: 3.1065 data_time: 0.0743 memory: 16201 loss_prob: 0.6374 loss_thr: 0.4121 loss_db: 0.1109 loss: 1.1604 2022/08/30 09:04:27 - mmengine - INFO - Epoch(train) [346][35/63] lr: 5.1579e-03 eta: 23:19:29 time: 3.0631 data_time: 0.0825 memory: 16201 loss_prob: 0.6527 loss_thr: 0.4265 loss_db: 0.1132 loss: 1.1924 2022/08/30 09:04:41 - mmengine - INFO - Epoch(train) [346][40/63] lr: 5.1579e-03 eta: 23:19:48 time: 2.9421 data_time: 0.0663 memory: 16201 loss_prob: 0.7225 loss_thr: 0.4384 loss_db: 0.1266 loss: 1.2874 2022/08/30 09:04:55 - mmengine - INFO - Epoch(train) [346][45/63] lr: 5.1579e-03 eta: 23:19:48 time: 2.7912 data_time: 0.0688 memory: 16201 loss_prob: 0.7592 loss_thr: 0.4475 loss_db: 0.1292 loss: 1.3359 2022/08/30 09:05:10 - mmengine - INFO - Epoch(train) [346][50/63] lr: 5.1579e-03 eta: 23:20:04 time: 2.8481 data_time: 0.0851 memory: 16201 loss_prob: 0.7416 loss_thr: 0.4387 loss_db: 0.1236 loss: 1.3039 2022/08/30 09:05:23 - mmengine - INFO - Epoch(train) [346][55/63] lr: 5.1579e-03 eta: 23:20:04 time: 2.8557 data_time: 0.0768 memory: 16201 loss_prob: 0.7235 loss_thr: 0.4409 loss_db: 0.1227 loss: 1.2872 2022/08/30 09:05:36 - mmengine - INFO - Epoch(train) [346][60/63] lr: 5.1579e-03 eta: 23:20:14 time: 2.5930 data_time: 0.0667 memory: 16201 loss_prob: 0.6823 loss_thr: 0.4436 loss_db: 0.1158 loss: 1.2417 2022/08/30 09:05:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:05:58 - mmengine - INFO - Epoch(train) [347][5/63] lr: 5.1525e-03 eta: 23:20:14 time: 2.7285 data_time: 0.2913 memory: 16201 loss_prob: 0.6715 loss_thr: 0.4504 loss_db: 0.1172 loss: 1.2391 2022/08/30 09:06:10 - mmengine - INFO - Epoch(train) [347][10/63] lr: 5.1525e-03 eta: 23:20:13 time: 2.8315 data_time: 0.2991 memory: 16201 loss_prob: 0.6590 loss_thr: 0.4327 loss_db: 0.1111 loss: 1.2028 2022/08/30 09:06:25 - mmengine - INFO - Epoch(train) [347][15/63] lr: 5.1525e-03 eta: 23:20:13 time: 2.6930 data_time: 0.0590 memory: 16201 loss_prob: 0.6462 loss_thr: 0.4309 loss_db: 0.1071 loss: 1.1842 2022/08/30 09:06:36 - mmengine - INFO - Epoch(train) [347][20/63] lr: 5.1525e-03 eta: 23:20:23 time: 2.5801 data_time: 0.0637 memory: 16201 loss_prob: 0.6184 loss_thr: 0.4186 loss_db: 0.1034 loss: 1.1404 2022/08/30 09:06:51 - mmengine - INFO - Epoch(train) [347][25/63] lr: 5.1525e-03 eta: 23:20:23 time: 2.6367 data_time: 0.0738 memory: 16201 loss_prob: 0.6238 loss_thr: 0.4077 loss_db: 0.1060 loss: 1.1375 2022/08/30 09:07:05 - mmengine - INFO - Epoch(train) [347][30/63] lr: 5.1525e-03 eta: 23:20:40 time: 2.9018 data_time: 0.0655 memory: 16201 loss_prob: 0.6674 loss_thr: 0.4229 loss_db: 0.1136 loss: 1.2039 2022/08/30 09:07:18 - mmengine - INFO - Epoch(train) [347][35/63] lr: 5.1525e-03 eta: 23:20:40 time: 2.6574 data_time: 0.0641 memory: 16201 loss_prob: 0.6890 loss_thr: 0.4461 loss_db: 0.1188 loss: 1.2538 2022/08/30 09:07:32 - mmengine - INFO - Epoch(train) [347][40/63] lr: 5.1525e-03 eta: 23:20:52 time: 2.6853 data_time: 0.0490 memory: 16201 loss_prob: 0.6466 loss_thr: 0.4417 loss_db: 0.1131 loss: 1.2014 2022/08/30 09:07:46 - mmengine - INFO - Epoch(train) [347][45/63] lr: 5.1525e-03 eta: 23:20:52 time: 2.8284 data_time: 0.0552 memory: 16201 loss_prob: 0.6155 loss_thr: 0.4327 loss_db: 0.1064 loss: 1.1546 2022/08/30 09:08:01 - mmengine - INFO - Epoch(train) [347][50/63] lr: 5.1525e-03 eta: 23:21:08 time: 2.8585 data_time: 0.0711 memory: 16201 loss_prob: 0.6008 loss_thr: 0.4160 loss_db: 0.1024 loss: 1.1192 2022/08/30 09:08:14 - mmengine - INFO - Epoch(train) [347][55/63] lr: 5.1525e-03 eta: 23:21:08 time: 2.7710 data_time: 0.0553 memory: 16201 loss_prob: 0.7022 loss_thr: 0.4373 loss_db: 0.1209 loss: 1.2605 2022/08/30 09:08:27 - mmengine - INFO - Epoch(train) [347][60/63] lr: 5.1525e-03 eta: 23:21:19 time: 2.6403 data_time: 0.0647 memory: 16201 loss_prob: 0.7421 loss_thr: 0.4562 loss_db: 0.1259 loss: 1.3242 2022/08/30 09:08:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:08:49 - mmengine - INFO - Epoch(train) [348][5/63] lr: 5.1471e-03 eta: 23:21:19 time: 2.6507 data_time: 0.2873 memory: 16201 loss_prob: 0.6333 loss_thr: 0.4115 loss_db: 0.1076 loss: 1.1523 2022/08/30 09:09:03 - mmengine - INFO - Epoch(train) [348][10/63] lr: 5.1471e-03 eta: 23:21:19 time: 2.8527 data_time: 0.3003 memory: 16201 loss_prob: 0.6298 loss_thr: 0.4050 loss_db: 0.1070 loss: 1.1418 2022/08/30 09:09:17 - mmengine - INFO - Epoch(train) [348][15/63] lr: 5.1471e-03 eta: 23:21:19 time: 2.7691 data_time: 0.0535 memory: 16201 loss_prob: 0.6434 loss_thr: 0.4304 loss_db: 0.1092 loss: 1.1831 2022/08/30 09:09:30 - mmengine - INFO - Epoch(train) [348][20/63] lr: 5.1471e-03 eta: 23:21:31 time: 2.6977 data_time: 0.0640 memory: 16201 loss_prob: 0.6686 loss_thr: 0.4471 loss_db: 0.1149 loss: 1.2306 2022/08/30 09:09:42 - mmengine - INFO - Epoch(train) [348][25/63] lr: 5.1471e-03 eta: 23:21:31 time: 2.4862 data_time: 0.0539 memory: 16201 loss_prob: 0.6645 loss_thr: 0.4184 loss_db: 0.1153 loss: 1.1982 2022/08/30 09:09:56 - mmengine - INFO - Epoch(train) [348][30/63] lr: 5.1471e-03 eta: 23:21:40 time: 2.5675 data_time: 0.0499 memory: 16201 loss_prob: 0.6291 loss_thr: 0.3973 loss_db: 0.1082 loss: 1.1346 2022/08/30 09:10:10 - mmengine - INFO - Epoch(train) [348][35/63] lr: 5.1471e-03 eta: 23:21:40 time: 2.8336 data_time: 0.0670 memory: 16201 loss_prob: 0.6649 loss_thr: 0.4234 loss_db: 0.1126 loss: 1.2009 2022/08/30 09:10:23 - mmengine - INFO - Epoch(train) [348][40/63] lr: 5.1471e-03 eta: 23:21:52 time: 2.6806 data_time: 0.0486 memory: 16201 loss_prob: 0.7785 loss_thr: 0.4458 loss_db: 0.1283 loss: 1.3527 2022/08/30 09:10:37 - mmengine - INFO - Epoch(train) [348][45/63] lr: 5.1471e-03 eta: 23:21:52 time: 2.6958 data_time: 0.0565 memory: 16201 loss_prob: 0.7900 loss_thr: 0.4406 loss_db: 0.1278 loss: 1.3584 2022/08/30 09:10:49 - mmengine - INFO - Epoch(train) [348][50/63] lr: 5.1471e-03 eta: 23:22:03 time: 2.6514 data_time: 0.0745 memory: 16201 loss_prob: 0.7846 loss_thr: 0.4461 loss_db: 0.1285 loss: 1.3592 2022/08/30 09:11:04 - mmengine - INFO - Epoch(train) [348][55/63] lr: 5.1471e-03 eta: 23:22:03 time: 2.6493 data_time: 0.0580 memory: 16201 loss_prob: 0.7960 loss_thr: 0.4464 loss_db: 0.1354 loss: 1.3777 2022/08/30 09:11:18 - mmengine - INFO - Epoch(train) [348][60/63] lr: 5.1471e-03 eta: 23:22:18 time: 2.8208 data_time: 0.0560 memory: 16201 loss_prob: 0.9763 loss_thr: 0.4698 loss_db: 0.1516 loss: 1.5976 2022/08/30 09:11:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:11:40 - mmengine - INFO - Epoch(train) [349][5/63] lr: 5.1416e-03 eta: 23:22:18 time: 2.8876 data_time: 0.2998 memory: 16201 loss_prob: 0.8855 loss_thr: 0.4894 loss_db: 0.1505 loss: 1.5253 2022/08/30 09:11:55 - mmengine - INFO - Epoch(train) [349][10/63] lr: 5.1416e-03 eta: 23:22:22 time: 3.0492 data_time: 0.3017 memory: 16201 loss_prob: 0.7189 loss_thr: 0.4467 loss_db: 0.1211 loss: 1.2867 2022/08/30 09:12:08 - mmengine - INFO - Epoch(train) [349][15/63] lr: 5.1416e-03 eta: 23:22:22 time: 2.7981 data_time: 0.0548 memory: 16201 loss_prob: 0.6857 loss_thr: 0.4385 loss_db: 0.1174 loss: 1.2417 2022/08/30 09:12:21 - mmengine - INFO - Epoch(train) [349][20/63] lr: 5.1416e-03 eta: 23:22:32 time: 2.6244 data_time: 0.0602 memory: 16201 loss_prob: 0.7170 loss_thr: 0.4477 loss_db: 0.1211 loss: 1.2858 2022/08/30 09:12:36 - mmengine - INFO - Epoch(train) [349][25/63] lr: 5.1416e-03 eta: 23:22:32 time: 2.8008 data_time: 0.0745 memory: 16201 loss_prob: 0.7355 loss_thr: 0.4534 loss_db: 0.1244 loss: 1.3133 2022/08/30 09:12:50 - mmengine - INFO - Epoch(train) [349][30/63] lr: 5.1416e-03 eta: 23:22:49 time: 2.8993 data_time: 0.0620 memory: 16201 loss_prob: 0.7729 loss_thr: 0.4639 loss_db: 0.1278 loss: 1.3647 2022/08/30 09:13:04 - mmengine - INFO - Epoch(train) [349][35/63] lr: 5.1416e-03 eta: 23:22:49 time: 2.7809 data_time: 0.0618 memory: 16201 loss_prob: 0.8059 loss_thr: 0.4753 loss_db: 0.1299 loss: 1.4111 2022/08/30 09:13:17 - mmengine - INFO - Epoch(train) [349][40/63] lr: 5.1416e-03 eta: 23:23:02 time: 2.7381 data_time: 0.0494 memory: 16201 loss_prob: 0.7883 loss_thr: 0.4617 loss_db: 0.1324 loss: 1.3824 2022/08/30 09:13:31 - mmengine - INFO - Epoch(train) [349][45/63] lr: 5.1416e-03 eta: 23:23:02 time: 2.6595 data_time: 0.0587 memory: 16201 loss_prob: 0.7395 loss_thr: 0.4630 loss_db: 0.1259 loss: 1.3284 2022/08/30 09:13:42 - mmengine - INFO - Epoch(train) [349][50/63] lr: 5.1416e-03 eta: 23:23:09 time: 2.5207 data_time: 0.0883 memory: 16201 loss_prob: 0.7261 loss_thr: 0.4639 loss_db: 0.1217 loss: 1.3117 2022/08/30 09:13:57 - mmengine - INFO - Epoch(train) [349][55/63] lr: 5.1416e-03 eta: 23:23:09 time: 2.5957 data_time: 0.0719 memory: 16201 loss_prob: 0.7081 loss_thr: 0.4397 loss_db: 0.1202 loss: 1.2680 2022/08/30 09:14:10 - mmengine - INFO - Epoch(train) [349][60/63] lr: 5.1416e-03 eta: 23:23:23 time: 2.7805 data_time: 0.0710 memory: 16201 loss_prob: 0.6978 loss_thr: 0.4380 loss_db: 0.1216 loss: 1.2573 2022/08/30 09:14:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:14:34 - mmengine - INFO - Epoch(train) [350][5/63] lr: 5.1362e-03 eta: 23:23:23 time: 2.7898 data_time: 0.2824 memory: 16201 loss_prob: 0.6440 loss_thr: 0.4148 loss_db: 0.1096 loss: 1.1684 2022/08/30 09:14:48 - mmengine - INFO - Epoch(train) [350][10/63] lr: 5.1362e-03 eta: 23:23:28 time: 3.0552 data_time: 0.3067 memory: 16201 loss_prob: 0.6354 loss_thr: 0.4136 loss_db: 0.1105 loss: 1.1595 2022/08/30 09:14:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:15:03 - mmengine - INFO - Epoch(train) [350][15/63] lr: 5.1362e-03 eta: 23:23:28 time: 2.8840 data_time: 0.0606 memory: 16201 loss_prob: 0.6661 loss_thr: 0.4376 loss_db: 0.1157 loss: 1.2194 2022/08/30 09:15:18 - mmengine - INFO - Epoch(train) [350][20/63] lr: 5.1362e-03 eta: 23:23:46 time: 2.9656 data_time: 0.0599 memory: 16201 loss_prob: 0.7345 loss_thr: 0.4398 loss_db: 0.1199 loss: 1.2941 2022/08/30 09:15:33 - mmengine - INFO - Epoch(train) [350][25/63] lr: 5.1362e-03 eta: 23:23:46 time: 3.0441 data_time: 0.0651 memory: 16201 loss_prob: 0.6941 loss_thr: 0.4184 loss_db: 0.1121 loss: 1.2247 2022/08/30 09:15:48 - mmengine - INFO - Epoch(train) [350][30/63] lr: 5.1362e-03 eta: 23:24:04 time: 2.9835 data_time: 0.0499 memory: 16201 loss_prob: 0.6463 loss_thr: 0.4178 loss_db: 0.1094 loss: 1.1735 2022/08/30 09:16:01 - mmengine - INFO - Epoch(train) [350][35/63] lr: 5.1362e-03 eta: 23:24:04 time: 2.7725 data_time: 0.0685 memory: 16201 loss_prob: 0.7371 loss_thr: 0.4698 loss_db: 0.1288 loss: 1.3357 2022/08/30 09:16:14 - mmengine - INFO - Epoch(train) [350][40/63] lr: 5.1362e-03 eta: 23:24:14 time: 2.6272 data_time: 0.0519 memory: 16201 loss_prob: 0.7022 loss_thr: 0.4426 loss_db: 0.1202 loss: 1.2650 2022/08/30 09:16:28 - mmengine - INFO - Epoch(train) [350][45/63] lr: 5.1362e-03 eta: 23:24:14 time: 2.7069 data_time: 0.0606 memory: 16201 loss_prob: 0.6292 loss_thr: 0.3976 loss_db: 0.1060 loss: 1.1328 2022/08/30 09:16:42 - mmengine - INFO - Epoch(train) [350][50/63] lr: 5.1362e-03 eta: 23:24:29 time: 2.8050 data_time: 0.0866 memory: 16201 loss_prob: 0.6707 loss_thr: 0.4361 loss_db: 0.1149 loss: 1.2217 2022/08/30 09:16:54 - mmengine - INFO - Epoch(train) [350][55/63] lr: 5.1362e-03 eta: 23:24:29 time: 2.6135 data_time: 0.0564 memory: 16201 loss_prob: 0.6871 loss_thr: 0.4548 loss_db: 0.1182 loss: 1.2601 2022/08/30 09:17:08 - mmengine - INFO - Epoch(train) [350][60/63] lr: 5.1362e-03 eta: 23:24:37 time: 2.5762 data_time: 0.0620 memory: 16201 loss_prob: 0.6833 loss_thr: 0.4504 loss_db: 0.1179 loss: 1.2516 2022/08/30 09:17:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:17:31 - mmengine - INFO - Epoch(train) [351][5/63] lr: 5.1307e-03 eta: 23:24:37 time: 2.8693 data_time: 0.3084 memory: 16201 loss_prob: 0.6726 loss_thr: 0.4689 loss_db: 0.1147 loss: 1.2562 2022/08/30 09:17:46 - mmengine - INFO - Epoch(train) [351][10/63] lr: 5.1307e-03 eta: 23:24:43 time: 3.1255 data_time: 0.3213 memory: 16201 loss_prob: 0.7118 loss_thr: 0.4531 loss_db: 0.1175 loss: 1.2824 2022/08/30 09:17:57 - mmengine - INFO - Epoch(train) [351][15/63] lr: 5.1307e-03 eta: 23:24:43 time: 2.6237 data_time: 0.0477 memory: 16201 loss_prob: 0.6917 loss_thr: 0.4184 loss_db: 0.1154 loss: 1.2255 2022/08/30 09:18:12 - mmengine - INFO - Epoch(train) [351][20/63] lr: 5.1307e-03 eta: 23:24:53 time: 2.6423 data_time: 0.0510 memory: 16201 loss_prob: 0.6831 loss_thr: 0.4268 loss_db: 0.1182 loss: 1.2281 2022/08/30 09:18:24 - mmengine - INFO - Epoch(train) [351][25/63] lr: 5.1307e-03 eta: 23:24:53 time: 2.7074 data_time: 0.0509 memory: 16201 loss_prob: 0.6781 loss_thr: 0.4372 loss_db: 0.1164 loss: 1.2318 2022/08/30 09:18:38 - mmengine - INFO - Epoch(train) [351][30/63] lr: 5.1307e-03 eta: 23:25:01 time: 2.5555 data_time: 0.0475 memory: 16201 loss_prob: 0.6313 loss_thr: 0.4265 loss_db: 0.1094 loss: 1.1673 2022/08/30 09:18:49 - mmengine - INFO - Epoch(train) [351][35/63] lr: 5.1307e-03 eta: 23:25:01 time: 2.4430 data_time: 0.0684 memory: 16201 loss_prob: 0.6099 loss_thr: 0.4079 loss_db: 0.1074 loss: 1.1251 2022/08/30 09:19:03 - mmengine - INFO - Epoch(train) [351][40/63] lr: 5.1307e-03 eta: 23:25:08 time: 2.4935 data_time: 0.0477 memory: 16201 loss_prob: 0.5999 loss_thr: 0.4104 loss_db: 0.1034 loss: 1.1137 2022/08/30 09:19:15 - mmengine - INFO - Epoch(train) [351][45/63] lr: 5.1307e-03 eta: 23:25:08 time: 2.6392 data_time: 0.0487 memory: 16201 loss_prob: 0.6207 loss_thr: 0.4289 loss_db: 0.1059 loss: 1.1555 2022/08/30 09:19:28 - mmengine - INFO - Epoch(train) [351][50/63] lr: 5.1307e-03 eta: 23:25:15 time: 2.5375 data_time: 0.0752 memory: 16201 loss_prob: 0.7071 loss_thr: 0.4519 loss_db: 0.1202 loss: 1.2792 2022/08/30 09:19:42 - mmengine - INFO - Epoch(train) [351][55/63] lr: 5.1307e-03 eta: 23:25:15 time: 2.7005 data_time: 0.0534 memory: 16201 loss_prob: 0.7117 loss_thr: 0.4472 loss_db: 0.1213 loss: 1.2803 2022/08/30 09:19:58 - mmengine - INFO - Epoch(train) [351][60/63] lr: 5.1307e-03 eta: 23:25:33 time: 2.9739 data_time: 0.0523 memory: 16201 loss_prob: 0.6076 loss_thr: 0.4018 loss_db: 0.1040 loss: 1.1134 2022/08/30 09:20:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:20:19 - mmengine - INFO - Epoch(train) [352][5/63] lr: 5.1253e-03 eta: 23:25:33 time: 2.7376 data_time: 0.2657 memory: 16201 loss_prob: 0.6544 loss_thr: 0.4162 loss_db: 0.1142 loss: 1.1848 2022/08/30 09:20:31 - mmengine - INFO - Epoch(train) [352][10/63] lr: 5.1253e-03 eta: 23:25:29 time: 2.7302 data_time: 0.2858 memory: 16201 loss_prob: 0.7184 loss_thr: 0.4575 loss_db: 0.1244 loss: 1.3003 2022/08/30 09:20:45 - mmengine - INFO - Epoch(train) [352][15/63] lr: 5.1253e-03 eta: 23:25:29 time: 2.6556 data_time: 0.0469 memory: 16201 loss_prob: 0.6894 loss_thr: 0.4365 loss_db: 0.1184 loss: 1.2443 2022/08/30 09:21:00 - mmengine - INFO - Epoch(train) [352][20/63] lr: 5.1253e-03 eta: 23:25:45 time: 2.8956 data_time: 0.0416 memory: 16201 loss_prob: 0.6057 loss_thr: 0.4060 loss_db: 0.1049 loss: 1.1166 2022/08/30 09:21:14 - mmengine - INFO - Epoch(train) [352][25/63] lr: 5.1253e-03 eta: 23:25:45 time: 2.8150 data_time: 0.0565 memory: 16201 loss_prob: 0.6443 loss_thr: 0.4352 loss_db: 0.1091 loss: 1.1886 2022/08/30 09:21:25 - mmengine - INFO - Epoch(train) [352][30/63] lr: 5.1253e-03 eta: 23:25:51 time: 2.4630 data_time: 0.0508 memory: 16201 loss_prob: 0.6872 loss_thr: 0.4516 loss_db: 0.1173 loss: 1.2560 2022/08/30 09:21:39 - mmengine - INFO - Epoch(train) [352][35/63] lr: 5.1253e-03 eta: 23:25:51 time: 2.5027 data_time: 0.0635 memory: 16201 loss_prob: 0.6725 loss_thr: 0.4408 loss_db: 0.1168 loss: 1.2301 2022/08/30 09:21:50 - mmengine - INFO - Epoch(train) [352][40/63] lr: 5.1253e-03 eta: 23:25:57 time: 2.4963 data_time: 0.0547 memory: 16201 loss_prob: 0.6374 loss_thr: 0.4136 loss_db: 0.1093 loss: 1.1603 2022/08/30 09:22:02 - mmengine - INFO - Epoch(train) [352][45/63] lr: 5.1253e-03 eta: 23:25:57 time: 2.3529 data_time: 0.0492 memory: 16201 loss_prob: 0.5959 loss_thr: 0.3847 loss_db: 0.1039 loss: 1.0846 2022/08/30 09:22:16 - mmengine - INFO - Epoch(train) [352][50/63] lr: 5.1253e-03 eta: 23:26:07 time: 2.6400 data_time: 0.0779 memory: 16201 loss_prob: 0.6579 loss_thr: 0.4236 loss_db: 0.1143 loss: 1.1958 2022/08/30 09:22:31 - mmengine - INFO - Epoch(train) [352][55/63] lr: 5.1253e-03 eta: 23:26:07 time: 2.8411 data_time: 0.0566 memory: 16201 loss_prob: 0.6718 loss_thr: 0.4367 loss_db: 0.1125 loss: 1.2211 2022/08/30 09:22:44 - mmengine - INFO - Epoch(train) [352][60/63] lr: 5.1253e-03 eta: 23:26:20 time: 2.7580 data_time: 0.0481 memory: 16201 loss_prob: 0.6431 loss_thr: 0.4350 loss_db: 0.1079 loss: 1.1859 2022/08/30 09:22:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:23:06 - mmengine - INFO - Epoch(train) [353][5/63] lr: 5.1199e-03 eta: 23:26:20 time: 2.8376 data_time: 0.2751 memory: 16201 loss_prob: 0.6384 loss_thr: 0.4161 loss_db: 0.1121 loss: 1.1667 2022/08/30 09:23:19 - mmengine - INFO - Epoch(train) [353][10/63] lr: 5.1199e-03 eta: 23:26:19 time: 2.8586 data_time: 0.2961 memory: 16201 loss_prob: 0.6053 loss_thr: 0.3889 loss_db: 0.1050 loss: 1.0993 2022/08/30 09:23:34 - mmengine - INFO - Epoch(train) [353][15/63] lr: 5.1199e-03 eta: 23:26:19 time: 2.7503 data_time: 0.0638 memory: 16201 loss_prob: 0.6247 loss_thr: 0.3911 loss_db: 0.1053 loss: 1.1211 2022/08/30 09:23:49 - mmengine - INFO - Epoch(train) [353][20/63] lr: 5.1199e-03 eta: 23:26:37 time: 2.9819 data_time: 0.0608 memory: 16201 loss_prob: 0.6459 loss_thr: 0.4229 loss_db: 0.1121 loss: 1.1809 2022/08/30 09:24:02 - mmengine - INFO - Epoch(train) [353][25/63] lr: 5.1199e-03 eta: 23:26:37 time: 2.7972 data_time: 0.0748 memory: 16201 loss_prob: 0.6484 loss_thr: 0.4344 loss_db: 0.1125 loss: 1.1953 2022/08/30 09:24:15 - mmengine - INFO - Epoch(train) [353][30/63] lr: 5.1199e-03 eta: 23:26:44 time: 2.5668 data_time: 0.0565 memory: 16201 loss_prob: 0.6352 loss_thr: 0.4177 loss_db: 0.1098 loss: 1.1627 2022/08/30 09:24:28 - mmengine - INFO - Epoch(train) [353][35/63] lr: 5.1199e-03 eta: 23:26:44 time: 2.5858 data_time: 0.0500 memory: 16201 loss_prob: 0.6072 loss_thr: 0.4080 loss_db: 0.1063 loss: 1.1215 2022/08/30 09:24:41 - mmengine - INFO - Epoch(train) [353][40/63] lr: 5.1199e-03 eta: 23:26:55 time: 2.6613 data_time: 0.0529 memory: 16201 loss_prob: 0.6382 loss_thr: 0.4320 loss_db: 0.1099 loss: 1.1802 2022/08/30 09:24:55 - mmengine - INFO - Epoch(train) [353][45/63] lr: 5.1199e-03 eta: 23:26:55 time: 2.7383 data_time: 0.0551 memory: 16201 loss_prob: 0.6638 loss_thr: 0.4522 loss_db: 0.1135 loss: 1.2296 2022/08/30 09:25:08 - mmengine - INFO - Epoch(train) [353][50/63] lr: 5.1199e-03 eta: 23:27:06 time: 2.6998 data_time: 0.0692 memory: 16201 loss_prob: 0.6465 loss_thr: 0.4389 loss_db: 0.1108 loss: 1.1962 2022/08/30 09:25:20 - mmengine - INFO - Epoch(train) [353][55/63] lr: 5.1199e-03 eta: 23:27:06 time: 2.5129 data_time: 0.0644 memory: 16201 loss_prob: 0.6783 loss_thr: 0.4472 loss_db: 0.1163 loss: 1.2418 2022/08/30 09:25:33 - mmengine - INFO - Epoch(train) [353][60/63] lr: 5.1199e-03 eta: 23:27:11 time: 2.4526 data_time: 0.0584 memory: 16201 loss_prob: 0.6905 loss_thr: 0.4599 loss_db: 0.1192 loss: 1.2696 2022/08/30 09:25:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:25:56 - mmengine - INFO - Epoch(train) [354][5/63] lr: 5.1144e-03 eta: 23:27:11 time: 2.7224 data_time: 0.2847 memory: 16201 loss_prob: 0.6030 loss_thr: 0.3952 loss_db: 0.1064 loss: 1.1046 2022/08/30 09:26:08 - mmengine - INFO - Epoch(train) [354][10/63] lr: 5.1144e-03 eta: 23:27:06 time: 2.7192 data_time: 0.2872 memory: 16201 loss_prob: 0.5513 loss_thr: 0.3617 loss_db: 0.0948 loss: 1.0077 2022/08/30 09:26:21 - mmengine - INFO - Epoch(train) [354][15/63] lr: 5.1144e-03 eta: 23:27:06 time: 2.5321 data_time: 0.0667 memory: 16201 loss_prob: 0.6582 loss_thr: 0.4206 loss_db: 0.1097 loss: 1.1885 2022/08/30 09:26:35 - mmengine - INFO - Epoch(train) [354][20/63] lr: 5.1144e-03 eta: 23:27:17 time: 2.6992 data_time: 0.0544 memory: 16201 loss_prob: 0.7174 loss_thr: 0.4519 loss_db: 0.1210 loss: 1.2902 2022/08/30 09:26:47 - mmengine - INFO - Epoch(train) [354][25/63] lr: 5.1144e-03 eta: 23:27:17 time: 2.6376 data_time: 0.0714 memory: 16201 loss_prob: 0.6779 loss_thr: 0.4476 loss_db: 0.1161 loss: 1.2416 2022/08/30 09:27:02 - mmengine - INFO - Epoch(train) [354][30/63] lr: 5.1144e-03 eta: 23:27:28 time: 2.7058 data_time: 0.0782 memory: 16201 loss_prob: 0.6415 loss_thr: 0.4492 loss_db: 0.1099 loss: 1.2006 2022/08/30 09:27:13 - mmengine - INFO - Epoch(train) [354][35/63] lr: 5.1144e-03 eta: 23:27:28 time: 2.5174 data_time: 0.0573 memory: 16201 loss_prob: 0.6155 loss_thr: 0.4167 loss_db: 0.1066 loss: 1.1388 2022/08/30 09:27:26 - mmengine - INFO - Epoch(train) [354][40/63] lr: 5.1144e-03 eta: 23:27:34 time: 2.4882 data_time: 0.0555 memory: 16201 loss_prob: 0.6380 loss_thr: 0.4087 loss_db: 0.1099 loss: 1.1566 2022/08/30 09:27:39 - mmengine - INFO - Epoch(train) [354][45/63] lr: 5.1144e-03 eta: 23:27:34 time: 2.6609 data_time: 0.0614 memory: 16201 loss_prob: 0.6333 loss_thr: 0.4218 loss_db: 0.1066 loss: 1.1617 2022/08/30 09:27:53 - mmengine - INFO - Epoch(train) [354][50/63] lr: 5.1144e-03 eta: 23:27:44 time: 2.6633 data_time: 0.0699 memory: 16201 loss_prob: 0.5989 loss_thr: 0.4027 loss_db: 0.1029 loss: 1.1045 2022/08/30 09:28:07 - mmengine - INFO - Epoch(train) [354][55/63] lr: 5.1144e-03 eta: 23:27:44 time: 2.7562 data_time: 0.0668 memory: 16201 loss_prob: 0.6096 loss_thr: 0.3904 loss_db: 0.1045 loss: 1.1044 2022/08/30 09:28:18 - mmengine - INFO - Epoch(train) [354][60/63] lr: 5.1144e-03 eta: 23:27:50 time: 2.5246 data_time: 0.0621 memory: 16201 loss_prob: 0.6362 loss_thr: 0.4016 loss_db: 0.1046 loss: 1.1423 2022/08/30 09:28:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:28:41 - mmengine - INFO - Epoch(train) [355][5/63] lr: 5.1090e-03 eta: 23:27:50 time: 2.6626 data_time: 0.3068 memory: 16201 loss_prob: 0.7039 loss_thr: 0.4284 loss_db: 0.1172 loss: 1.2496 2022/08/30 09:28:51 - mmengine - INFO - Epoch(train) [355][10/63] lr: 5.1090e-03 eta: 23:27:42 time: 2.5675 data_time: 0.3208 memory: 16201 loss_prob: 0.6366 loss_thr: 0.4098 loss_db: 0.1100 loss: 1.1564 2022/08/30 09:29:05 - mmengine - INFO - Epoch(train) [355][15/63] lr: 5.1090e-03 eta: 23:27:42 time: 2.4680 data_time: 0.0682 memory: 16201 loss_prob: 0.6023 loss_thr: 0.4046 loss_db: 0.1046 loss: 1.1115 2022/08/30 09:29:19 - mmengine - INFO - Epoch(train) [355][20/63] lr: 5.1090e-03 eta: 23:27:55 time: 2.7858 data_time: 0.0662 memory: 16201 loss_prob: 0.6563 loss_thr: 0.4190 loss_db: 0.1111 loss: 1.1863 2022/08/30 09:29:31 - mmengine - INFO - Epoch(train) [355][25/63] lr: 5.1090e-03 eta: 23:27:55 time: 2.5389 data_time: 0.0610 memory: 16201 loss_prob: 0.6642 loss_thr: 0.4150 loss_db: 0.1129 loss: 1.1921 2022/08/30 09:29:43 - mmengine - INFO - Epoch(train) [355][30/63] lr: 5.1090e-03 eta: 23:27:57 time: 2.3529 data_time: 0.0595 memory: 16201 loss_prob: 0.6487 loss_thr: 0.4129 loss_db: 0.1106 loss: 1.1722 2022/08/30 09:29:57 - mmengine - INFO - Epoch(train) [355][35/63] lr: 5.1090e-03 eta: 23:27:57 time: 2.6197 data_time: 0.0737 memory: 16201 loss_prob: 0.6469 loss_thr: 0.4146 loss_db: 0.1085 loss: 1.1700 2022/08/30 09:30:10 - mmengine - INFO - Epoch(train) [355][40/63] lr: 5.1090e-03 eta: 23:28:09 time: 2.7532 data_time: 0.0545 memory: 16201 loss_prob: 0.6051 loss_thr: 0.4032 loss_db: 0.1032 loss: 1.1115 2022/08/30 09:30:24 - mmengine - INFO - Epoch(train) [355][45/63] lr: 5.1090e-03 eta: 23:28:09 time: 2.6803 data_time: 0.0507 memory: 16201 loss_prob: 0.6632 loss_thr: 0.4168 loss_db: 0.1102 loss: 1.1903 2022/08/30 09:30:38 - mmengine - INFO - Epoch(train) [355][50/63] lr: 5.1090e-03 eta: 23:28:23 time: 2.8180 data_time: 0.0591 memory: 16201 loss_prob: 0.7336 loss_thr: 0.4416 loss_db: 0.1203 loss: 1.2954 2022/08/30 09:30:50 - mmengine - INFO - Epoch(train) [355][55/63] lr: 5.1090e-03 eta: 23:28:23 time: 2.6139 data_time: 0.0515 memory: 16201 loss_prob: 0.6747 loss_thr: 0.4268 loss_db: 0.1158 loss: 1.2173 2022/08/30 09:31:04 - mmengine - INFO - Epoch(train) [355][60/63] lr: 5.1090e-03 eta: 23:28:30 time: 2.5583 data_time: 0.0718 memory: 16201 loss_prob: 0.6089 loss_thr: 0.3937 loss_db: 0.1066 loss: 1.1092 2022/08/30 09:31:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:31:26 - mmengine - INFO - Epoch(train) [356][5/63] lr: 5.1035e-03 eta: 23:28:30 time: 2.7196 data_time: 0.3141 memory: 16201 loss_prob: 0.6010 loss_thr: 0.4079 loss_db: 0.1030 loss: 1.1118 2022/08/30 09:31:37 - mmengine - INFO - Epoch(train) [356][10/63] lr: 5.1035e-03 eta: 23:28:26 time: 2.7639 data_time: 0.3278 memory: 16201 loss_prob: 0.6245 loss_thr: 0.4246 loss_db: 0.1079 loss: 1.1570 2022/08/30 09:31:52 - mmengine - INFO - Epoch(train) [356][15/63] lr: 5.1035e-03 eta: 23:28:26 time: 2.5905 data_time: 0.0637 memory: 16201 loss_prob: 0.6449 loss_thr: 0.4188 loss_db: 0.1102 loss: 1.1740 2022/08/30 09:32:06 - mmengine - INFO - Epoch(train) [356][20/63] lr: 5.1035e-03 eta: 23:28:40 time: 2.8519 data_time: 0.0512 memory: 16201 loss_prob: 0.6348 loss_thr: 0.3917 loss_db: 0.1072 loss: 1.1337 2022/08/30 09:32:20 - mmengine - INFO - Epoch(train) [356][25/63] lr: 5.1035e-03 eta: 23:28:40 time: 2.7857 data_time: 0.0731 memory: 16201 loss_prob: 0.6272 loss_thr: 0.4021 loss_db: 0.1046 loss: 1.1340 2022/08/30 09:32:33 - mmengine - INFO - Epoch(train) [356][30/63] lr: 5.1035e-03 eta: 23:28:52 time: 2.7393 data_time: 0.0598 memory: 16201 loss_prob: 0.5903 loss_thr: 0.4126 loss_db: 0.1013 loss: 1.1041 2022/08/30 09:32:47 - mmengine - INFO - Epoch(train) [356][35/63] lr: 5.1035e-03 eta: 23:28:52 time: 2.6966 data_time: 0.0542 memory: 16201 loss_prob: 0.5829 loss_thr: 0.3999 loss_db: 0.1026 loss: 1.0854 2022/08/30 09:32:59 - mmengine - INFO - Epoch(train) [356][40/63] lr: 5.1035e-03 eta: 23:28:59 time: 2.5790 data_time: 0.0530 memory: 16201 loss_prob: 0.6154 loss_thr: 0.4123 loss_db: 0.1041 loss: 1.1318 2022/08/30 09:33:11 - mmengine - INFO - Epoch(train) [356][45/63] lr: 5.1035e-03 eta: 23:28:59 time: 2.4025 data_time: 0.0520 memory: 16201 loss_prob: 0.6248 loss_thr: 0.4252 loss_db: 0.1058 loss: 1.1558 2022/08/30 09:33:24 - mmengine - INFO - Epoch(train) [356][50/63] lr: 5.1035e-03 eta: 23:29:05 time: 2.5099 data_time: 0.0833 memory: 16201 loss_prob: 0.6482 loss_thr: 0.4355 loss_db: 0.1137 loss: 1.1974 2022/08/30 09:33:36 - mmengine - INFO - Epoch(train) [356][55/63] lr: 5.1035e-03 eta: 23:29:05 time: 2.5467 data_time: 0.0619 memory: 16201 loss_prob: 0.6557 loss_thr: 0.4278 loss_db: 0.1116 loss: 1.1952 2022/08/30 09:33:48 - mmengine - INFO - Epoch(train) [356][60/63] lr: 5.1035e-03 eta: 23:29:09 time: 2.4297 data_time: 0.0501 memory: 16201 loss_prob: 0.6408 loss_thr: 0.4191 loss_db: 0.1067 loss: 1.1666 2022/08/30 09:33:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:34:12 - mmengine - INFO - Epoch(train) [357][5/63] lr: 5.0981e-03 eta: 23:29:09 time: 2.8240 data_time: 0.2660 memory: 16201 loss_prob: 0.7364 loss_thr: 0.4613 loss_db: 0.1285 loss: 1.3261 2022/08/30 09:34:24 - mmengine - INFO - Epoch(train) [357][10/63] lr: 5.0981e-03 eta: 23:29:08 time: 2.8721 data_time: 0.2958 memory: 16201 loss_prob: 0.7311 loss_thr: 0.4395 loss_db: 0.1231 loss: 1.2938 2022/08/30 09:34:36 - mmengine - INFO - Epoch(train) [357][15/63] lr: 5.0981e-03 eta: 23:29:08 time: 2.4780 data_time: 0.0695 memory: 16201 loss_prob: 0.7227 loss_thr: 0.4515 loss_db: 0.1221 loss: 1.2963 2022/08/30 09:34:49 - mmengine - INFO - Epoch(train) [357][20/63] lr: 5.0981e-03 eta: 23:29:15 time: 2.5751 data_time: 0.0659 memory: 16201 loss_prob: 0.6944 loss_thr: 0.4253 loss_db: 0.1178 loss: 1.2375 2022/08/30 09:35:03 - mmengine - INFO - Epoch(train) [357][25/63] lr: 5.0981e-03 eta: 23:29:15 time: 2.6679 data_time: 0.0696 memory: 16201 loss_prob: 0.6538 loss_thr: 0.3933 loss_db: 0.1108 loss: 1.1579 2022/08/30 09:35:16 - mmengine - INFO - Epoch(train) [357][30/63] lr: 5.0981e-03 eta: 23:29:24 time: 2.6356 data_time: 0.0651 memory: 16201 loss_prob: 0.6634 loss_thr: 0.4300 loss_db: 0.1139 loss: 1.2073 2022/08/30 09:35:29 - mmengine - INFO - Epoch(train) [357][35/63] lr: 5.0981e-03 eta: 23:29:24 time: 2.5483 data_time: 0.0588 memory: 16201 loss_prob: 0.6677 loss_thr: 0.4437 loss_db: 0.1148 loss: 1.2262 2022/08/30 09:35:40 - mmengine - INFO - Epoch(train) [357][40/63] lr: 5.0981e-03 eta: 23:29:27 time: 2.3992 data_time: 0.0468 memory: 16201 loss_prob: 0.6077 loss_thr: 0.4130 loss_db: 0.1057 loss: 1.1264 2022/08/30 09:35:54 - mmengine - INFO - Epoch(train) [357][45/63] lr: 5.0981e-03 eta: 23:29:27 time: 2.5205 data_time: 0.0508 memory: 16201 loss_prob: 0.6370 loss_thr: 0.4289 loss_db: 0.1104 loss: 1.1763 2022/08/30 09:36:09 - mmengine - INFO - Epoch(train) [357][50/63] lr: 5.0981e-03 eta: 23:29:44 time: 2.9709 data_time: 0.0678 memory: 16201 loss_prob: 0.6556 loss_thr: 0.4312 loss_db: 0.1122 loss: 1.1991 2022/08/30 09:36:21 - mmengine - INFO - Epoch(train) [357][55/63] lr: 5.0981e-03 eta: 23:29:44 time: 2.6833 data_time: 0.0671 memory: 16201 loss_prob: 0.6606 loss_thr: 0.4290 loss_db: 0.1111 loss: 1.2007 2022/08/30 09:36:36 - mmengine - INFO - Epoch(train) [357][60/63] lr: 5.0981e-03 eta: 23:29:52 time: 2.6238 data_time: 0.0568 memory: 16201 loss_prob: 0.6631 loss_thr: 0.4296 loss_db: 0.1135 loss: 1.2063 2022/08/30 09:36:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:36:57 - mmengine - INFO - Epoch(train) [358][5/63] lr: 5.0927e-03 eta: 23:29:52 time: 2.7183 data_time: 0.2723 memory: 16201 loss_prob: 0.5951 loss_thr: 0.4190 loss_db: 0.1040 loss: 1.1181 2022/08/30 09:37:11 - mmengine - INFO - Epoch(train) [358][10/63] lr: 5.0927e-03 eta: 23:29:52 time: 2.9430 data_time: 0.2923 memory: 16201 loss_prob: 0.6134 loss_thr: 0.3998 loss_db: 0.1058 loss: 1.1190 2022/08/30 09:37:24 - mmengine - INFO - Epoch(train) [358][15/63] lr: 5.0927e-03 eta: 23:29:52 time: 2.6925 data_time: 0.0760 memory: 16201 loss_prob: 0.6768 loss_thr: 0.4243 loss_db: 0.1159 loss: 1.2169 2022/08/30 09:37:36 - mmengine - INFO - Epoch(train) [358][20/63] lr: 5.0927e-03 eta: 23:29:58 time: 2.5242 data_time: 0.0684 memory: 16201 loss_prob: 0.7342 loss_thr: 0.4583 loss_db: 0.1255 loss: 1.3181 2022/08/30 09:37:50 - mmengine - INFO - Epoch(train) [358][25/63] lr: 5.0927e-03 eta: 23:29:58 time: 2.5661 data_time: 0.0676 memory: 16201 loss_prob: 0.6656 loss_thr: 0.4363 loss_db: 0.1128 loss: 1.2147 2022/08/30 09:38:01 - mmengine - INFO - Epoch(train) [358][30/63] lr: 5.0927e-03 eta: 23:30:04 time: 2.5146 data_time: 0.0614 memory: 16201 loss_prob: 0.6713 loss_thr: 0.4239 loss_db: 0.1126 loss: 1.2078 2022/08/30 09:38:16 - mmengine - INFO - Epoch(train) [358][35/63] lr: 5.0927e-03 eta: 23:30:04 time: 2.6482 data_time: 0.0585 memory: 16201 loss_prob: 0.6688 loss_thr: 0.4230 loss_db: 0.1122 loss: 1.2040 2022/08/30 09:38:29 - mmengine - INFO - Epoch(train) [358][40/63] lr: 5.0927e-03 eta: 23:30:16 time: 2.7870 data_time: 0.0616 memory: 16201 loss_prob: 0.6416 loss_thr: 0.4225 loss_db: 0.1100 loss: 1.1740 2022/08/30 09:38:43 - mmengine - INFO - Epoch(train) [358][45/63] lr: 5.0927e-03 eta: 23:30:16 time: 2.6694 data_time: 0.0652 memory: 16201 loss_prob: 0.6408 loss_thr: 0.4097 loss_db: 0.1108 loss: 1.1613 2022/08/30 09:38:55 - mmengine - INFO - Epoch(train) [358][50/63] lr: 5.0927e-03 eta: 23:30:24 time: 2.6051 data_time: 0.0714 memory: 16201 loss_prob: 0.6664 loss_thr: 0.4295 loss_db: 0.1135 loss: 1.2094 2022/08/30 09:39:08 - mmengine - INFO - Epoch(train) [358][55/63] lr: 5.0927e-03 eta: 23:30:24 time: 2.5278 data_time: 0.0549 memory: 16201 loss_prob: 0.7019 loss_thr: 0.4448 loss_db: 0.1190 loss: 1.2657 2022/08/30 09:39:23 - mmengine - INFO - Epoch(train) [358][60/63] lr: 5.0927e-03 eta: 23:30:35 time: 2.7658 data_time: 0.0470 memory: 16201 loss_prob: 0.6286 loss_thr: 0.4245 loss_db: 0.1066 loss: 1.1597 2022/08/30 09:39:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:39:45 - mmengine - INFO - Epoch(train) [359][5/63] lr: 5.0872e-03 eta: 23:30:35 time: 2.7345 data_time: 0.2794 memory: 16201 loss_prob: 0.8899 loss_thr: 0.4783 loss_db: 0.1375 loss: 1.5057 2022/08/30 09:39:59 - mmengine - INFO - Epoch(train) [359][10/63] lr: 5.0872e-03 eta: 23:30:36 time: 2.9669 data_time: 0.2979 memory: 16201 loss_prob: 0.8592 loss_thr: 0.4785 loss_db: 0.1349 loss: 1.4726 2022/08/30 09:40:11 - mmengine - INFO - Epoch(train) [359][15/63] lr: 5.0872e-03 eta: 23:30:36 time: 2.5918 data_time: 0.0583 memory: 16201 loss_prob: 0.6482 loss_thr: 0.4563 loss_db: 0.1127 loss: 1.2171 2022/08/30 09:40:26 - mmengine - INFO - Epoch(train) [359][20/63] lr: 5.0872e-03 eta: 23:30:44 time: 2.6213 data_time: 0.0610 memory: 16201 loss_prob: 0.6098 loss_thr: 0.4308 loss_db: 0.1054 loss: 1.1460 2022/08/30 09:40:40 - mmengine - INFO - Epoch(train) [359][25/63] lr: 5.0872e-03 eta: 23:30:44 time: 2.9044 data_time: 0.0729 memory: 16201 loss_prob: 0.6257 loss_thr: 0.4106 loss_db: 0.1085 loss: 1.1448 2022/08/30 09:40:53 - mmengine - INFO - Epoch(train) [359][30/63] lr: 5.0872e-03 eta: 23:30:54 time: 2.7176 data_time: 0.0629 memory: 16201 loss_prob: 0.6799 loss_thr: 0.4255 loss_db: 0.1154 loss: 1.2208 2022/08/30 09:41:07 - mmengine - INFO - Epoch(train) [359][35/63] lr: 5.0872e-03 eta: 23:30:54 time: 2.7264 data_time: 0.0722 memory: 16201 loss_prob: 0.7630 loss_thr: 0.4232 loss_db: 0.1311 loss: 1.3172 2022/08/30 09:41:20 - mmengine - INFO - Epoch(train) [359][40/63] lr: 5.0872e-03 eta: 23:31:04 time: 2.7131 data_time: 0.0664 memory: 16201 loss_prob: 0.7860 loss_thr: 0.4262 loss_db: 0.1395 loss: 1.3517 2022/08/30 09:41:36 - mmengine - INFO - Epoch(train) [359][45/63] lr: 5.0872e-03 eta: 23:31:04 time: 2.8900 data_time: 0.0696 memory: 16201 loss_prob: 0.7309 loss_thr: 0.4600 loss_db: 0.1226 loss: 1.3136 2022/08/30 09:41:50 - mmengine - INFO - Epoch(train) [359][50/63] lr: 5.0872e-03 eta: 23:31:21 time: 2.9816 data_time: 0.0669 memory: 16201 loss_prob: 0.6753 loss_thr: 0.4420 loss_db: 0.1110 loss: 1.2283 2022/08/30 09:42:02 - mmengine - INFO - Epoch(train) [359][55/63] lr: 5.0872e-03 eta: 23:31:21 time: 2.5852 data_time: 0.0615 memory: 16201 loss_prob: 0.6407 loss_thr: 0.3941 loss_db: 0.1101 loss: 1.1449 2022/08/30 09:42:15 - mmengine - INFO - Epoch(train) [359][60/63] lr: 5.0872e-03 eta: 23:31:26 time: 2.4788 data_time: 0.0869 memory: 16201 loss_prob: 0.6495 loss_thr: 0.3979 loss_db: 0.1107 loss: 1.1581 2022/08/30 09:42:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:42:37 - mmengine - INFO - Epoch(train) [360][5/63] lr: 5.0818e-03 eta: 23:31:26 time: 2.7600 data_time: 0.2833 memory: 16201 loss_prob: 0.7737 loss_thr: 0.4285 loss_db: 0.1309 loss: 1.3331 2022/08/30 09:42:52 - mmengine - INFO - Epoch(train) [360][10/63] lr: 5.0818e-03 eta: 23:31:27 time: 3.0249 data_time: 0.2904 memory: 16201 loss_prob: 0.7365 loss_thr: 0.4304 loss_db: 0.1219 loss: 1.2889 2022/08/30 09:43:06 - mmengine - INFO - Epoch(train) [360][15/63] lr: 5.0818e-03 eta: 23:31:27 time: 2.9067 data_time: 0.0547 memory: 16201 loss_prob: 0.6851 loss_thr: 0.4345 loss_db: 0.1150 loss: 1.2346 2022/08/30 09:43:19 - mmengine - INFO - Epoch(train) [360][20/63] lr: 5.0818e-03 eta: 23:31:36 time: 2.6893 data_time: 0.0531 memory: 16201 loss_prob: 0.6406 loss_thr: 0.4491 loss_db: 0.1094 loss: 1.1990 2022/08/30 09:43:32 - mmengine - INFO - Epoch(train) [360][25/63] lr: 5.0818e-03 eta: 23:31:36 time: 2.5659 data_time: 0.0718 memory: 16201 loss_prob: 0.6636 loss_thr: 0.4476 loss_db: 0.1137 loss: 1.2249 2022/08/30 09:43:45 - mmengine - INFO - Epoch(train) [360][30/63] lr: 5.0818e-03 eta: 23:31:45 time: 2.6338 data_time: 0.0607 memory: 16201 loss_prob: 0.7123 loss_thr: 0.4515 loss_db: 0.1217 loss: 1.2856 2022/08/30 09:43:57 - mmengine - INFO - Epoch(train) [360][35/63] lr: 5.0818e-03 eta: 23:31:45 time: 2.5044 data_time: 0.0648 memory: 16201 loss_prob: 0.6947 loss_thr: 0.4496 loss_db: 0.1193 loss: 1.2636 2022/08/30 09:44:11 - mmengine - INFO - Epoch(train) [360][40/63] lr: 5.0818e-03 eta: 23:31:51 time: 2.5610 data_time: 0.0588 memory: 16201 loss_prob: 0.6945 loss_thr: 0.4526 loss_db: 0.1211 loss: 1.2682 2022/08/30 09:44:25 - mmengine - INFO - Epoch(train) [360][45/63] lr: 5.0818e-03 eta: 23:31:51 time: 2.7564 data_time: 0.0485 memory: 16201 loss_prob: 0.7258 loss_thr: 0.4501 loss_db: 0.1247 loss: 1.3005 2022/08/30 09:44:38 - mmengine - INFO - Epoch(train) [360][50/63] lr: 5.0818e-03 eta: 23:32:00 time: 2.6826 data_time: 0.0622 memory: 16201 loss_prob: 0.6904 loss_thr: 0.4264 loss_db: 0.1174 loss: 1.2342 2022/08/30 09:44:52 - mmengine - INFO - Epoch(train) [360][55/63] lr: 5.0818e-03 eta: 23:32:00 time: 2.7289 data_time: 0.0526 memory: 16201 loss_prob: 0.6960 loss_thr: 0.4294 loss_db: 0.1183 loss: 1.2437 2022/08/30 09:45:06 - mmengine - INFO - Epoch(train) [360][60/63] lr: 5.0818e-03 eta: 23:32:12 time: 2.7621 data_time: 0.0615 memory: 16201 loss_prob: 0.6624 loss_thr: 0.4294 loss_db: 0.1119 loss: 1.2037 2022/08/30 09:45:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:45:12 - mmengine - INFO - Saving checkpoint at 360 epochs 2022/08/30 09:45:21 - mmengine - INFO - Epoch(val) [360][5/32] eta: 23:32:12 time: 0.6997 data_time: 0.1441 memory: 16201 2022/08/30 09:45:25 - mmengine - INFO - Epoch(val) [360][10/32] eta: 0:00:17 time: 0.8038 data_time: 0.1944 memory: 15734 2022/08/30 09:45:28 - mmengine - INFO - Epoch(val) [360][15/32] eta: 0:00:17 time: 0.6772 data_time: 0.0706 memory: 15734 2022/08/30 09:45:32 - mmengine - INFO - Epoch(val) [360][20/32] eta: 0:00:08 time: 0.7196 data_time: 0.0727 memory: 15734 2022/08/30 09:45:36 - mmengine - INFO - Epoch(val) [360][25/32] eta: 0:00:08 time: 0.7462 data_time: 0.0878 memory: 15734 2022/08/30 09:45:39 - mmengine - INFO - Epoch(val) [360][30/32] eta: 0:00:01 time: 0.6807 data_time: 0.0385 memory: 15734 2022/08/30 09:45:40 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 09:45:40 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8546, precision: 0.7816, hmean: 0.8165 2022/08/30 09:45:40 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8541, precision: 0.8156, hmean: 0.8344 2022/08/30 09:45:40 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8527, precision: 0.8449, hmean: 0.8488 2022/08/30 09:45:40 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8469, precision: 0.8691, hmean: 0.8578 2022/08/30 09:45:40 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8238, precision: 0.8977, hmean: 0.8592 2022/08/30 09:45:40 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6875, precision: 0.9352, hmean: 0.7925 2022/08/30 09:45:40 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0631, precision: 1.0000, hmean: 0.1187 2022/08/30 09:45:40 - mmengine - INFO - Epoch(val) [360][32/32] icdar/precision: 0.8977 icdar/recall: 0.8238 icdar/hmean: 0.8592 2022/08/30 09:45:54 - mmengine - INFO - Epoch(train) [361][5/63] lr: 5.0763e-03 eta: 0:00:01 time: 2.6754 data_time: 0.2843 memory: 16201 loss_prob: 0.6632 loss_thr: 0.4128 loss_db: 0.1176 loss: 1.1937 2022/08/30 09:46:08 - mmengine - INFO - Epoch(train) [361][10/63] lr: 5.0763e-03 eta: 23:32:07 time: 2.7821 data_time: 0.2936 memory: 16201 loss_prob: 0.7411 loss_thr: 0.4312 loss_db: 0.1229 loss: 1.2952 2022/08/30 09:46:22 - mmengine - INFO - Epoch(train) [361][15/63] lr: 5.0763e-03 eta: 23:32:07 time: 2.8388 data_time: 0.0516 memory: 16201 loss_prob: 0.6690 loss_thr: 0.4065 loss_db: 0.1105 loss: 1.1860 2022/08/30 09:46:34 - mmengine - INFO - Epoch(train) [361][20/63] lr: 5.0763e-03 eta: 23:32:15 time: 2.6487 data_time: 0.0637 memory: 16201 loss_prob: 0.5788 loss_thr: 0.3857 loss_db: 0.0999 loss: 1.0644 2022/08/30 09:46:47 - mmengine - INFO - Epoch(train) [361][25/63] lr: 5.0763e-03 eta: 23:32:15 time: 2.5264 data_time: 0.0885 memory: 16201 loss_prob: 0.6835 loss_thr: 0.4071 loss_db: 0.1149 loss: 1.2056 2022/08/30 09:47:02 - mmengine - INFO - Epoch(train) [361][30/63] lr: 5.0763e-03 eta: 23:32:26 time: 2.7293 data_time: 0.0642 memory: 16201 loss_prob: 0.6941 loss_thr: 0.4055 loss_db: 0.1170 loss: 1.2165 2022/08/30 09:47:14 - mmengine - INFO - Epoch(train) [361][35/63] lr: 5.0763e-03 eta: 23:32:26 time: 2.6172 data_time: 0.0598 memory: 16201 loss_prob: 0.6759 loss_thr: 0.4187 loss_db: 0.1132 loss: 1.2077 2022/08/30 09:47:26 - mmengine - INFO - Epoch(train) [361][40/63] lr: 5.0763e-03 eta: 23:32:30 time: 2.4879 data_time: 0.0526 memory: 16201 loss_prob: 0.7005 loss_thr: 0.4378 loss_db: 0.1161 loss: 1.2544 2022/08/30 09:47:40 - mmengine - INFO - Epoch(train) [361][45/63] lr: 5.0763e-03 eta: 23:32:30 time: 2.6396 data_time: 0.0615 memory: 16201 loss_prob: 0.6502 loss_thr: 0.4140 loss_db: 0.1101 loss: 1.1743 2022/08/30 09:47:54 - mmengine - INFO - Epoch(train) [361][50/63] lr: 5.0763e-03 eta: 23:32:42 time: 2.7955 data_time: 0.0697 memory: 16201 loss_prob: 0.6112 loss_thr: 0.4130 loss_db: 0.1069 loss: 1.1311 2022/08/30 09:48:07 - mmengine - INFO - Epoch(train) [361][55/63] lr: 5.0763e-03 eta: 23:32:42 time: 2.7503 data_time: 0.0446 memory: 16201 loss_prob: 0.6217 loss_thr: 0.4273 loss_db: 0.1076 loss: 1.1566 2022/08/30 09:48:20 - mmengine - INFO - Epoch(train) [361][60/63] lr: 5.0763e-03 eta: 23:32:48 time: 2.5623 data_time: 0.0597 memory: 16201 loss_prob: 0.6449 loss_thr: 0.4267 loss_db: 0.1083 loss: 1.1799 2022/08/30 09:48:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:48:44 - mmengine - INFO - Epoch(train) [362][5/63] lr: 5.0709e-03 eta: 23:32:48 time: 2.8862 data_time: 0.3064 memory: 16201 loss_prob: 0.5908 loss_thr: 0.4006 loss_db: 0.1016 loss: 1.0930 2022/08/30 09:48:57 - mmengine - INFO - Epoch(train) [362][10/63] lr: 5.0709e-03 eta: 23:32:48 time: 2.9724 data_time: 0.3104 memory: 16201 loss_prob: 0.6282 loss_thr: 0.4077 loss_db: 0.1104 loss: 1.1464 2022/08/30 09:49:10 - mmengine - INFO - Epoch(train) [362][15/63] lr: 5.0709e-03 eta: 23:32:48 time: 2.6380 data_time: 0.0505 memory: 16201 loss_prob: 0.6179 loss_thr: 0.4103 loss_db: 0.1066 loss: 1.1348 2022/08/30 09:49:23 - mmengine - INFO - Epoch(train) [362][20/63] lr: 5.0709e-03 eta: 23:32:55 time: 2.6005 data_time: 0.0698 memory: 16201 loss_prob: 0.5736 loss_thr: 0.3913 loss_db: 0.0969 loss: 1.0618 2022/08/30 09:49:36 - mmengine - INFO - Epoch(train) [362][25/63] lr: 5.0709e-03 eta: 23:32:55 time: 2.6303 data_time: 0.0637 memory: 16201 loss_prob: 0.6117 loss_thr: 0.3995 loss_db: 0.1058 loss: 1.1170 2022/08/30 09:49:50 - mmengine - INFO - Epoch(train) [362][30/63] lr: 5.0709e-03 eta: 23:33:04 time: 2.6963 data_time: 0.0502 memory: 16201 loss_prob: 0.6623 loss_thr: 0.4284 loss_db: 0.1123 loss: 1.2030 2022/08/30 09:50:04 - mmengine - INFO - Epoch(train) [362][35/63] lr: 5.0709e-03 eta: 23:33:04 time: 2.7084 data_time: 0.0677 memory: 16201 loss_prob: 0.6377 loss_thr: 0.4108 loss_db: 0.1083 loss: 1.1568 2022/08/30 09:50:16 - mmengine - INFO - Epoch(train) [362][40/63] lr: 5.0709e-03 eta: 23:33:13 time: 2.6558 data_time: 0.0592 memory: 16201 loss_prob: 0.6252 loss_thr: 0.4172 loss_db: 0.1058 loss: 1.1482 2022/08/30 09:50:28 - mmengine - INFO - Epoch(train) [362][45/63] lr: 5.0709e-03 eta: 23:33:13 time: 2.4819 data_time: 0.0597 memory: 16201 loss_prob: 0.6415 loss_thr: 0.4501 loss_db: 0.1091 loss: 1.2007 2022/08/30 09:50:42 - mmengine - INFO - Epoch(train) [362][50/63] lr: 5.0709e-03 eta: 23:33:18 time: 2.5417 data_time: 0.0666 memory: 16201 loss_prob: 0.6331 loss_thr: 0.4382 loss_db: 0.1098 loss: 1.1811 2022/08/30 09:50:54 - mmengine - INFO - Epoch(train) [362][55/63] lr: 5.0709e-03 eta: 23:33:18 time: 2.6055 data_time: 0.0587 memory: 16201 loss_prob: 0.7667 loss_thr: 0.4362 loss_db: 0.1224 loss: 1.3254 2022/08/30 09:51:09 - mmengine - INFO - Epoch(train) [362][60/63] lr: 5.0709e-03 eta: 23:33:28 time: 2.6978 data_time: 0.0733 memory: 16201 loss_prob: 0.7603 loss_thr: 0.4278 loss_db: 0.1217 loss: 1.3098 2022/08/30 09:51:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:51:32 - mmengine - INFO - Epoch(train) [363][5/63] lr: 5.0654e-03 eta: 23:33:28 time: 2.8497 data_time: 0.2774 memory: 16201 loss_prob: 0.7208 loss_thr: 0.4504 loss_db: 0.1207 loss: 1.2919 2022/08/30 09:51:47 - mmengine - INFO - Epoch(train) [363][10/63] lr: 5.0654e-03 eta: 23:33:30 time: 3.1016 data_time: 0.2790 memory: 16201 loss_prob: 0.7562 loss_thr: 0.4552 loss_db: 0.1258 loss: 1.3372 2022/08/30 09:52:02 - mmengine - INFO - Epoch(train) [363][15/63] lr: 5.0654e-03 eta: 23:33:30 time: 3.0179 data_time: 0.0673 memory: 16201 loss_prob: 0.6512 loss_thr: 0.4225 loss_db: 0.1111 loss: 1.1848 2022/08/30 09:52:15 - mmengine - INFO - Epoch(train) [363][20/63] lr: 5.0654e-03 eta: 23:33:43 time: 2.8491 data_time: 0.0765 memory: 16201 loss_prob: 0.6346 loss_thr: 0.4139 loss_db: 0.1085 loss: 1.1571 2022/08/30 09:52:26 - mmengine - INFO - Epoch(train) [363][25/63] lr: 5.0654e-03 eta: 23:33:43 time: 2.4712 data_time: 0.0710 memory: 16201 loss_prob: 0.6906 loss_thr: 0.4326 loss_db: 0.1160 loss: 1.2391 2022/08/30 09:52:41 - mmengine - INFO - Epoch(train) [363][30/63] lr: 5.0654e-03 eta: 23:33:49 time: 2.5515 data_time: 0.0541 memory: 16201 loss_prob: 0.6798 loss_thr: 0.4226 loss_db: 0.1150 loss: 1.2173 2022/08/30 09:52:53 - mmengine - INFO - Epoch(train) [363][35/63] lr: 5.0654e-03 eta: 23:33:49 time: 2.6681 data_time: 0.0723 memory: 16201 loss_prob: 0.6466 loss_thr: 0.4120 loss_db: 0.1106 loss: 1.1692 2022/08/30 09:53:08 - mmengine - INFO - Epoch(train) [363][40/63] lr: 5.0654e-03 eta: 23:33:58 time: 2.6982 data_time: 0.0571 memory: 16201 loss_prob: 0.7006 loss_thr: 0.4306 loss_db: 0.1151 loss: 1.2463 2022/08/30 09:53:21 - mmengine - INFO - Epoch(train) [363][45/63] lr: 5.0654e-03 eta: 23:33:58 time: 2.7751 data_time: 0.0538 memory: 16201 loss_prob: 0.7203 loss_thr: 0.4173 loss_db: 0.1216 loss: 1.2591 2022/08/30 09:53:34 - mmengine - INFO - Epoch(train) [363][50/63] lr: 5.0654e-03 eta: 23:34:06 time: 2.6730 data_time: 0.0660 memory: 16201 loss_prob: 0.6547 loss_thr: 0.3999 loss_db: 0.1144 loss: 1.1689 2022/08/30 09:53:48 - mmengine - INFO - Epoch(train) [363][55/63] lr: 5.0654e-03 eta: 23:34:06 time: 2.7097 data_time: 0.0612 memory: 16201 loss_prob: 0.6224 loss_thr: 0.4084 loss_db: 0.1075 loss: 1.1383 2022/08/30 09:54:02 - mmengine - INFO - Epoch(train) [363][60/63] lr: 5.0654e-03 eta: 23:34:17 time: 2.7844 data_time: 0.0703 memory: 16201 loss_prob: 0.6269 loss_thr: 0.4074 loss_db: 0.1074 loss: 1.1417 2022/08/30 09:54:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:54:25 - mmengine - INFO - Epoch(train) [364][5/63] lr: 5.0600e-03 eta: 23:34:17 time: 2.8059 data_time: 0.2716 memory: 16201 loss_prob: 0.6397 loss_thr: 0.4194 loss_db: 0.1114 loss: 1.1705 2022/08/30 09:54:38 - mmengine - INFO - Epoch(train) [364][10/63] lr: 5.0600e-03 eta: 23:34:13 time: 2.8189 data_time: 0.2932 memory: 16201 loss_prob: 0.6773 loss_thr: 0.4292 loss_db: 0.1139 loss: 1.2204 2022/08/30 09:54:51 - mmengine - INFO - Epoch(train) [364][15/63] lr: 5.0600e-03 eta: 23:34:13 time: 2.6120 data_time: 0.0506 memory: 16201 loss_prob: 0.7326 loss_thr: 0.4517 loss_db: 0.1208 loss: 1.3051 2022/08/30 09:55:03 - mmengine - INFO - Epoch(train) [364][20/63] lr: 5.0600e-03 eta: 23:34:17 time: 2.4814 data_time: 0.0513 memory: 16201 loss_prob: 0.7260 loss_thr: 0.4419 loss_db: 0.1216 loss: 1.2896 2022/08/30 09:55:15 - mmengine - INFO - Epoch(train) [364][25/63] lr: 5.0600e-03 eta: 23:34:17 time: 2.3856 data_time: 0.0694 memory: 16201 loss_prob: 0.7188 loss_thr: 0.4331 loss_db: 0.1238 loss: 1.2757 2022/08/30 09:55:29 - mmengine - INFO - Epoch(train) [364][30/63] lr: 5.0600e-03 eta: 23:34:23 time: 2.5923 data_time: 0.0583 memory: 16201 loss_prob: 0.7460 loss_thr: 0.4384 loss_db: 0.1272 loss: 1.3115 2022/08/30 09:55:42 - mmengine - INFO - Epoch(train) [364][35/63] lr: 5.0600e-03 eta: 23:34:23 time: 2.7146 data_time: 0.0728 memory: 16201 loss_prob: 0.6899 loss_thr: 0.4234 loss_db: 0.1144 loss: 1.2278 2022/08/30 09:55:58 - mmengine - INFO - Epoch(train) [364][40/63] lr: 5.0600e-03 eta: 23:34:38 time: 2.9520 data_time: 0.0587 memory: 16201 loss_prob: 0.6552 loss_thr: 0.4173 loss_db: 0.1130 loss: 1.1855 2022/08/30 09:56:12 - mmengine - INFO - Epoch(train) [364][45/63] lr: 5.0600e-03 eta: 23:34:38 time: 2.9139 data_time: 0.0490 memory: 16201 loss_prob: 0.6547 loss_thr: 0.4227 loss_db: 0.1139 loss: 1.1913 2022/08/30 09:56:26 - mmengine - INFO - Epoch(train) [364][50/63] lr: 5.0600e-03 eta: 23:34:49 time: 2.7648 data_time: 0.0732 memory: 16201 loss_prob: 0.6535 loss_thr: 0.4063 loss_db: 0.1114 loss: 1.1712 2022/08/30 09:56:39 - mmengine - INFO - Epoch(train) [364][55/63] lr: 5.0600e-03 eta: 23:34:49 time: 2.7295 data_time: 0.0516 memory: 16201 loss_prob: 0.7003 loss_thr: 0.4224 loss_db: 0.1203 loss: 1.2430 2022/08/30 09:56:53 - mmengine - INFO - Epoch(train) [364][60/63] lr: 5.0600e-03 eta: 23:34:57 time: 2.6926 data_time: 0.0528 memory: 16201 loss_prob: 0.6887 loss_thr: 0.4454 loss_db: 0.1196 loss: 1.2537 2022/08/30 09:56:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 09:57:15 - mmengine - INFO - Epoch(train) [365][5/63] lr: 5.0545e-03 eta: 23:34:57 time: 2.8314 data_time: 0.2901 memory: 16201 loss_prob: 0.7162 loss_thr: 0.4611 loss_db: 0.1213 loss: 1.2986 2022/08/30 09:57:28 - mmengine - INFO - Epoch(train) [365][10/63] lr: 5.0545e-03 eta: 23:34:56 time: 2.9578 data_time: 0.3218 memory: 16201 loss_prob: 0.6529 loss_thr: 0.4166 loss_db: 0.1109 loss: 1.1805 2022/08/30 09:57:41 - mmengine - INFO - Epoch(train) [365][15/63] lr: 5.0545e-03 eta: 23:34:56 time: 2.6528 data_time: 0.0725 memory: 16201 loss_prob: 0.6496 loss_thr: 0.4083 loss_db: 0.1112 loss: 1.1692 2022/08/30 09:57:56 - mmengine - INFO - Epoch(train) [365][20/63] lr: 5.0545e-03 eta: 23:35:06 time: 2.7468 data_time: 0.0647 memory: 16201 loss_prob: 0.7258 loss_thr: 0.4494 loss_db: 0.1235 loss: 1.2987 2022/08/30 09:58:09 - mmengine - INFO - Epoch(train) [365][25/63] lr: 5.0545e-03 eta: 23:35:06 time: 2.7932 data_time: 0.0621 memory: 16201 loss_prob: 0.6855 loss_thr: 0.4346 loss_db: 0.1182 loss: 1.2383 2022/08/30 09:58:23 - mmengine - INFO - Epoch(train) [365][30/63] lr: 5.0545e-03 eta: 23:35:16 time: 2.7278 data_time: 0.0398 memory: 16201 loss_prob: 0.6070 loss_thr: 0.4045 loss_db: 0.1050 loss: 1.1166 2022/08/30 09:58:37 - mmengine - INFO - Epoch(train) [365][35/63] lr: 5.0545e-03 eta: 23:35:16 time: 2.7351 data_time: 0.0473 memory: 16201 loss_prob: 0.6562 loss_thr: 0.4256 loss_db: 0.1108 loss: 1.1927 2022/08/30 09:58:50 - mmengine - INFO - Epoch(train) [365][40/63] lr: 5.0545e-03 eta: 23:35:25 time: 2.7198 data_time: 0.0462 memory: 16201 loss_prob: 0.7107 loss_thr: 0.4452 loss_db: 0.1189 loss: 1.2748 2022/08/30 09:59:05 - mmengine - INFO - Epoch(train) [365][45/63] lr: 5.0545e-03 eta: 23:35:25 time: 2.7809 data_time: 0.0575 memory: 16201 loss_prob: 0.6664 loss_thr: 0.4169 loss_db: 0.1114 loss: 1.1947 2022/08/30 09:59:17 - mmengine - INFO - Epoch(train) [365][50/63] lr: 5.0545e-03 eta: 23:35:33 time: 2.6734 data_time: 0.0826 memory: 16201 loss_prob: 0.6926 loss_thr: 0.4304 loss_db: 0.1147 loss: 1.2377 2022/08/30 09:59:30 - mmengine - INFO - Epoch(train) [365][55/63] lr: 5.0545e-03 eta: 23:35:33 time: 2.5723 data_time: 0.0494 memory: 16201 loss_prob: 0.6404 loss_thr: 0.4204 loss_db: 0.1072 loss: 1.1680 2022/08/30 09:59:44 - mmengine - INFO - Epoch(train) [365][60/63] lr: 5.0545e-03 eta: 23:35:43 time: 2.7557 data_time: 0.0416 memory: 16201 loss_prob: 0.6240 loss_thr: 0.4126 loss_db: 0.1072 loss: 1.1438 2022/08/30 09:59:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:00:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:00:06 - mmengine - INFO - Epoch(train) [366][5/63] lr: 5.0491e-03 eta: 23:35:43 time: 2.7045 data_time: 0.2720 memory: 16201 loss_prob: 0.6288 loss_thr: 0.4169 loss_db: 0.1089 loss: 1.1546 2022/08/30 10:00:21 - mmengine - INFO - Epoch(train) [366][10/63] lr: 5.0491e-03 eta: 23:35:47 time: 3.1930 data_time: 0.3028 memory: 16201 loss_prob: 0.6363 loss_thr: 0.4106 loss_db: 0.1085 loss: 1.1555 2022/08/30 10:00:34 - mmengine - INFO - Epoch(train) [366][15/63] lr: 5.0491e-03 eta: 23:35:47 time: 2.8514 data_time: 0.0573 memory: 16201 loss_prob: 0.6914 loss_thr: 0.4272 loss_db: 0.1185 loss: 1.2372 2022/08/30 10:00:49 - mmengine - INFO - Epoch(train) [366][20/63] lr: 5.0491e-03 eta: 23:35:57 time: 2.7750 data_time: 0.0525 memory: 16201 loss_prob: 0.6285 loss_thr: 0.4132 loss_db: 0.1089 loss: 1.1506 2022/08/30 10:01:04 - mmengine - INFO - Epoch(train) [366][25/63] lr: 5.0491e-03 eta: 23:35:57 time: 2.9641 data_time: 0.0676 memory: 16201 loss_prob: 0.5832 loss_thr: 0.3921 loss_db: 0.0996 loss: 1.0749 2022/08/30 10:01:16 - mmengine - INFO - Epoch(train) [366][30/63] lr: 5.0491e-03 eta: 23:36:06 time: 2.7280 data_time: 0.0515 memory: 16201 loss_prob: 0.7122 loss_thr: 0.4345 loss_db: 0.1166 loss: 1.2634 2022/08/30 10:01:25 - mmengine - INFO - Epoch(train) [366][35/63] lr: 5.0491e-03 eta: 23:36:06 time: 2.0878 data_time: 0.0436 memory: 16201 loss_prob: 0.7869 loss_thr: 0.4564 loss_db: 0.1261 loss: 1.3694 2022/08/30 10:01:29 - mmengine - INFO - Epoch(train) [366][40/63] lr: 5.0491e-03 eta: 23:35:45 time: 1.3613 data_time: 0.0258 memory: 16201 loss_prob: 0.7295 loss_thr: 0.4415 loss_db: 0.1197 loss: 1.2908 2022/08/30 10:01:34 - mmengine - INFO - Epoch(train) [366][45/63] lr: 5.0491e-03 eta: 23:35:45 time: 0.9217 data_time: 0.0244 memory: 16201 loss_prob: 0.7032 loss_thr: 0.4416 loss_db: 0.1175 loss: 1.2624 2022/08/30 10:01:39 - mmengine - INFO - Epoch(train) [366][50/63] lr: 5.0491e-03 eta: 23:35:13 time: 0.9268 data_time: 0.0358 memory: 16201 loss_prob: 0.6655 loss_thr: 0.4419 loss_db: 0.1157 loss: 1.2231 2022/08/30 10:01:44 - mmengine - INFO - Epoch(train) [366][55/63] lr: 5.0491e-03 eta: 23:35:13 time: 1.0118 data_time: 0.0210 memory: 16201 loss_prob: 0.6453 loss_thr: 0.4376 loss_db: 0.1137 loss: 1.1966 2022/08/30 10:01:49 - mmengine - INFO - Epoch(train) [366][60/63] lr: 5.0491e-03 eta: 23:34:42 time: 0.9772 data_time: 0.0221 memory: 16201 loss_prob: 0.6562 loss_thr: 0.4224 loss_db: 0.1122 loss: 1.1908 2022/08/30 10:01:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:01:58 - mmengine - INFO - Epoch(train) [367][5/63] lr: 5.0436e-03 eta: 23:34:42 time: 1.1079 data_time: 0.2156 memory: 16201 loss_prob: 0.6618 loss_thr: 0.4385 loss_db: 0.1137 loss: 1.2140 2022/08/30 10:02:03 - mmengine - INFO - Epoch(train) [367][10/63] lr: 5.0436e-03 eta: 23:34:00 time: 1.1782 data_time: 0.2263 memory: 16201 loss_prob: 0.7916 loss_thr: 0.4486 loss_db: 0.1287 loss: 1.3690 2022/08/30 10:02:08 - mmengine - INFO - Epoch(train) [367][15/63] lr: 5.0436e-03 eta: 23:34:00 time: 1.0244 data_time: 0.0233 memory: 16201 loss_prob: 0.7971 loss_thr: 0.4350 loss_db: 0.1234 loss: 1.3555 2022/08/30 10:02:13 - mmengine - INFO - Epoch(train) [367][20/63] lr: 5.0436e-03 eta: 23:33:30 time: 1.0070 data_time: 0.0312 memory: 16201 loss_prob: 0.6814 loss_thr: 0.4054 loss_db: 0.1065 loss: 1.1933 2022/08/30 10:02:17 - mmengine - INFO - Epoch(train) [367][25/63] lr: 5.0436e-03 eta: 23:33:30 time: 0.8875 data_time: 0.0287 memory: 16201 loss_prob: 0.6976 loss_thr: 0.4132 loss_db: 0.1138 loss: 1.2246 2022/08/30 10:02:23 - mmengine - INFO - Epoch(train) [367][30/63] lr: 5.0436e-03 eta: 23:32:59 time: 0.9828 data_time: 0.0244 memory: 16201 loss_prob: 0.6307 loss_thr: 0.4033 loss_db: 0.1082 loss: 1.1421 2022/08/30 10:02:28 - mmengine - INFO - Epoch(train) [367][35/63] lr: 5.0436e-03 eta: 23:32:59 time: 1.0902 data_time: 0.0370 memory: 16201 loss_prob: 0.6001 loss_thr: 0.3920 loss_db: 0.1021 loss: 1.0942 2022/08/30 10:02:33 - mmengine - INFO - Epoch(train) [367][40/63] lr: 5.0436e-03 eta: 23:32:30 time: 1.0466 data_time: 0.0257 memory: 16201 loss_prob: 0.6095 loss_thr: 0.4029 loss_db: 0.1032 loss: 1.1156 2022/08/30 10:02:38 - mmengine - INFO - Epoch(train) [367][45/63] lr: 5.0436e-03 eta: 23:32:30 time: 1.0062 data_time: 0.0252 memory: 16201 loss_prob: 0.5865 loss_thr: 0.4060 loss_db: 0.1003 loss: 1.0927 2022/08/30 10:02:43 - mmengine - INFO - Epoch(train) [367][50/63] lr: 5.0436e-03 eta: 23:32:00 time: 0.9841 data_time: 0.0322 memory: 16201 loss_prob: 0.6119 loss_thr: 0.4058 loss_db: 0.1044 loss: 1.1221 2022/08/30 10:02:48 - mmengine - INFO - Epoch(train) [367][55/63] lr: 5.0436e-03 eta: 23:32:00 time: 1.0330 data_time: 0.0229 memory: 16201 loss_prob: 0.6301 loss_thr: 0.4035 loss_db: 0.1061 loss: 1.1397 2022/08/30 10:02:53 - mmengine - INFO - Epoch(train) [367][60/63] lr: 5.0436e-03 eta: 23:31:31 time: 1.0310 data_time: 0.0302 memory: 16201 loss_prob: 0.6266 loss_thr: 0.4089 loss_db: 0.1055 loss: 1.1410 2022/08/30 10:02:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:03:02 - mmengine - INFO - Epoch(train) [368][5/63] lr: 5.0382e-03 eta: 23:31:31 time: 1.0673 data_time: 0.2140 memory: 16201 loss_prob: 0.6451 loss_thr: 0.4138 loss_db: 0.1125 loss: 1.1714 2022/08/30 10:03:08 - mmengine - INFO - Epoch(train) [368][10/63] lr: 5.0382e-03 eta: 23:30:49 time: 1.1831 data_time: 0.2280 memory: 16201 loss_prob: 0.6499 loss_thr: 0.4140 loss_db: 0.1106 loss: 1.1746 2022/08/30 10:03:14 - mmengine - INFO - Epoch(train) [368][15/63] lr: 5.0382e-03 eta: 23:30:49 time: 1.1223 data_time: 0.0259 memory: 16201 loss_prob: 0.6575 loss_thr: 0.4318 loss_db: 0.1127 loss: 1.2019 2022/08/30 10:03:18 - mmengine - INFO - Epoch(train) [368][20/63] lr: 5.0382e-03 eta: 23:30:21 time: 1.0898 data_time: 0.0261 memory: 16201 loss_prob: 0.8192 loss_thr: 0.4335 loss_db: 0.1372 loss: 1.3900 2022/08/30 10:03:24 - mmengine - INFO - Epoch(train) [368][25/63] lr: 5.0382e-03 eta: 23:30:21 time: 1.0377 data_time: 0.0310 memory: 16201 loss_prob: 0.8384 loss_thr: 0.4368 loss_db: 0.1403 loss: 1.4154 2022/08/30 10:03:29 - mmengine - INFO - Epoch(train) [368][30/63] lr: 5.0382e-03 eta: 23:29:52 time: 1.0715 data_time: 0.0245 memory: 16201 loss_prob: 0.8970 loss_thr: 0.4746 loss_db: 0.1396 loss: 1.5113 2022/08/30 10:03:34 - mmengine - INFO - Epoch(train) [368][35/63] lr: 5.0382e-03 eta: 23:29:52 time: 1.0316 data_time: 0.0340 memory: 16201 loss_prob: 0.9614 loss_thr: 0.4957 loss_db: 0.1450 loss: 1.6020 2022/08/30 10:03:38 - mmengine - INFO - Epoch(train) [368][40/63] lr: 5.0382e-03 eta: 23:29:20 time: 0.8956 data_time: 0.0283 memory: 16201 loss_prob: 0.7755 loss_thr: 0.4560 loss_db: 0.1238 loss: 1.3553 2022/08/30 10:03:43 - mmengine - INFO - Epoch(train) [368][45/63] lr: 5.0382e-03 eta: 23:29:20 time: 0.8709 data_time: 0.0295 memory: 16201 loss_prob: 0.7362 loss_thr: 0.4261 loss_db: 0.1219 loss: 1.2841 2022/08/30 10:03:48 - mmengine - INFO - Epoch(train) [368][50/63] lr: 5.0382e-03 eta: 23:28:51 time: 1.0342 data_time: 0.0334 memory: 16201 loss_prob: 0.7961 loss_thr: 0.4450 loss_db: 0.1327 loss: 1.3738 2022/08/30 10:03:54 - mmengine - INFO - Epoch(train) [368][55/63] lr: 5.0382e-03 eta: 23:28:51 time: 1.0648 data_time: 0.0218 memory: 16201 loss_prob: 0.7645 loss_thr: 0.4457 loss_db: 0.1281 loss: 1.3382 2022/08/30 10:03:58 - mmengine - INFO - Epoch(train) [368][60/63] lr: 5.0382e-03 eta: 23:28:20 time: 0.9617 data_time: 0.0282 memory: 16201 loss_prob: 0.7441 loss_thr: 0.4295 loss_db: 0.1255 loss: 1.2990 2022/08/30 10:04:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:04:07 - mmengine - INFO - Epoch(train) [369][5/63] lr: 5.0327e-03 eta: 23:28:20 time: 1.0411 data_time: 0.2046 memory: 16201 loss_prob: 0.7650 loss_thr: 0.4305 loss_db: 0.1290 loss: 1.3245 2022/08/30 10:04:12 - mmengine - INFO - Epoch(train) [369][10/63] lr: 5.0327e-03 eta: 23:27:39 time: 1.2060 data_time: 0.2235 memory: 16201 loss_prob: 0.7001 loss_thr: 0.4180 loss_db: 0.1214 loss: 1.2394 2022/08/30 10:04:17 - mmengine - INFO - Epoch(train) [369][15/63] lr: 5.0327e-03 eta: 23:27:39 time: 1.0290 data_time: 0.0307 memory: 16201 loss_prob: 0.6545 loss_thr: 0.4163 loss_db: 0.1133 loss: 1.1842 2022/08/30 10:04:23 - mmengine - INFO - Epoch(train) [369][20/63] lr: 5.0327e-03 eta: 23:27:11 time: 1.0704 data_time: 0.0262 memory: 16201 loss_prob: 0.6676 loss_thr: 0.4297 loss_db: 0.1130 loss: 1.2103 2022/08/30 10:04:27 - mmengine - INFO - Epoch(train) [369][25/63] lr: 5.0327e-03 eta: 23:27:11 time: 0.9625 data_time: 0.0339 memory: 16201 loss_prob: 0.7112 loss_thr: 0.4524 loss_db: 0.1237 loss: 1.2873 2022/08/30 10:04:32 - mmengine - INFO - Epoch(train) [369][30/63] lr: 5.0327e-03 eta: 23:26:38 time: 0.8723 data_time: 0.0199 memory: 16201 loss_prob: 0.6960 loss_thr: 0.4345 loss_db: 0.1215 loss: 1.2520 2022/08/30 10:04:37 - mmengine - INFO - Epoch(train) [369][35/63] lr: 5.0327e-03 eta: 23:26:38 time: 1.0145 data_time: 0.0290 memory: 16201 loss_prob: 0.7304 loss_thr: 0.4532 loss_db: 0.1213 loss: 1.3049 2022/08/30 10:04:42 - mmengine - INFO - Epoch(train) [369][40/63] lr: 5.0327e-03 eta: 23:26:09 time: 1.0297 data_time: 0.0297 memory: 16201 loss_prob: 0.7380 loss_thr: 0.4648 loss_db: 0.1217 loss: 1.3245 2022/08/30 10:04:47 - mmengine - INFO - Epoch(train) [369][45/63] lr: 5.0327e-03 eta: 23:26:09 time: 1.0329 data_time: 0.0252 memory: 16201 loss_prob: 0.7236 loss_thr: 0.4426 loss_db: 0.1182 loss: 1.2844 2022/08/30 10:04:52 - mmengine - INFO - Epoch(train) [369][50/63] lr: 5.0327e-03 eta: 23:25:39 time: 0.9936 data_time: 0.0349 memory: 16201 loss_prob: 0.7921 loss_thr: 0.4453 loss_db: 0.1214 loss: 1.3588 2022/08/30 10:04:57 - mmengine - INFO - Epoch(train) [369][55/63] lr: 5.0327e-03 eta: 23:25:39 time: 0.9895 data_time: 0.0202 memory: 16201 loss_prob: 0.7216 loss_thr: 0.4428 loss_db: 0.1148 loss: 1.2792 2022/08/30 10:05:03 - mmengine - INFO - Epoch(train) [369][60/63] lr: 5.0327e-03 eta: 23:25:11 time: 1.0920 data_time: 0.0259 memory: 16201 loss_prob: 0.6259 loss_thr: 0.4120 loss_db: 0.1057 loss: 1.1436 2022/08/30 10:05:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:05:11 - mmengine - INFO - Epoch(train) [370][5/63] lr: 5.0273e-03 eta: 23:25:11 time: 1.0379 data_time: 0.2084 memory: 16201 loss_prob: 0.6644 loss_thr: 0.4270 loss_db: 0.1137 loss: 1.2052 2022/08/30 10:05:16 - mmengine - INFO - Epoch(train) [370][10/63] lr: 5.0273e-03 eta: 23:24:27 time: 1.0765 data_time: 0.2180 memory: 16201 loss_prob: 0.6948 loss_thr: 0.4492 loss_db: 0.1179 loss: 1.2620 2022/08/30 10:05:21 - mmengine - INFO - Epoch(train) [370][15/63] lr: 5.0273e-03 eta: 23:24:27 time: 0.9801 data_time: 0.0254 memory: 16201 loss_prob: 0.7217 loss_thr: 0.4380 loss_db: 0.1219 loss: 1.2817 2022/08/30 10:05:27 - mmengine - INFO - Epoch(train) [370][20/63] lr: 5.0273e-03 eta: 23:23:59 time: 1.0960 data_time: 0.0246 memory: 16201 loss_prob: 0.7326 loss_thr: 0.4354 loss_db: 0.1216 loss: 1.2895 2022/08/30 10:05:31 - mmengine - INFO - Epoch(train) [370][25/63] lr: 5.0273e-03 eta: 23:23:59 time: 1.0101 data_time: 0.0264 memory: 16201 loss_prob: 0.6593 loss_thr: 0.4284 loss_db: 0.1125 loss: 1.2002 2022/08/30 10:05:36 - mmengine - INFO - Epoch(train) [370][30/63] lr: 5.0273e-03 eta: 23:23:29 time: 0.9775 data_time: 0.0262 memory: 16201 loss_prob: 0.6594 loss_thr: 0.4467 loss_db: 0.1131 loss: 1.2192 2022/08/30 10:05:43 - mmengine - INFO - Epoch(train) [370][35/63] lr: 5.0273e-03 eta: 23:23:29 time: 1.1511 data_time: 0.0262 memory: 16201 loss_prob: 0.6551 loss_thr: 0.4285 loss_db: 0.1113 loss: 1.1949 2022/08/30 10:05:47 - mmengine - INFO - Epoch(train) [370][40/63] lr: 5.0273e-03 eta: 23:23:01 time: 1.0967 data_time: 0.0253 memory: 16201 loss_prob: 0.6594 loss_thr: 0.4233 loss_db: 0.1120 loss: 1.1947 2022/08/30 10:05:52 - mmengine - INFO - Epoch(train) [370][45/63] lr: 5.0273e-03 eta: 23:23:01 time: 0.9936 data_time: 0.0482 memory: 16201 loss_prob: 0.6601 loss_thr: 0.4331 loss_db: 0.1130 loss: 1.2062 2022/08/30 10:05:57 - mmengine - INFO - Epoch(train) [370][50/63] lr: 5.0273e-03 eta: 23:22:31 time: 0.9915 data_time: 0.0441 memory: 16201 loss_prob: 0.7603 loss_thr: 0.4438 loss_db: 0.1250 loss: 1.3290 2022/08/30 10:06:02 - mmengine - INFO - Epoch(train) [370][55/63] lr: 5.0273e-03 eta: 23:22:31 time: 0.9636 data_time: 0.0280 memory: 16201 loss_prob: 0.7584 loss_thr: 0.4431 loss_db: 0.1242 loss: 1.3257 2022/08/30 10:06:08 - mmengine - INFO - Epoch(train) [370][60/63] lr: 5.0273e-03 eta: 23:22:03 time: 1.0423 data_time: 0.0311 memory: 16201 loss_prob: 0.6508 loss_thr: 0.4039 loss_db: 0.1120 loss: 1.1668 2022/08/30 10:06:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:06:17 - mmengine - INFO - Epoch(train) [371][5/63] lr: 5.0218e-03 eta: 23:22:03 time: 1.2258 data_time: 0.2194 memory: 16201 loss_prob: 0.6128 loss_thr: 0.3969 loss_db: 0.1005 loss: 1.1102 2022/08/30 10:06:23 - mmengine - INFO - Epoch(train) [371][10/63] lr: 5.0218e-03 eta: 23:21:23 time: 1.2502 data_time: 0.2195 memory: 16201 loss_prob: 0.6620 loss_thr: 0.4131 loss_db: 0.1089 loss: 1.1840 2022/08/30 10:06:28 - mmengine - INFO - Epoch(train) [371][15/63] lr: 5.0218e-03 eta: 23:21:23 time: 1.0194 data_time: 0.0242 memory: 16201 loss_prob: 0.6683 loss_thr: 0.4202 loss_db: 0.1133 loss: 1.2018 2022/08/30 10:06:32 - mmengine - INFO - Epoch(train) [371][20/63] lr: 5.0218e-03 eta: 23:20:52 time: 0.9638 data_time: 0.0257 memory: 16201 loss_prob: 0.6394 loss_thr: 0.4194 loss_db: 0.1088 loss: 1.1675 2022/08/30 10:06:37 - mmengine - INFO - Epoch(train) [371][25/63] lr: 5.0218e-03 eta: 23:20:52 time: 0.9955 data_time: 0.0317 memory: 16201 loss_prob: 0.6165 loss_thr: 0.4134 loss_db: 0.1054 loss: 1.1352 2022/08/30 10:06:42 - mmengine - INFO - Epoch(train) [371][30/63] lr: 5.0218e-03 eta: 23:20:22 time: 0.9760 data_time: 0.0289 memory: 16201 loss_prob: 0.6376 loss_thr: 0.4062 loss_db: 0.1071 loss: 1.1509 2022/08/30 10:06:48 - mmengine - INFO - Epoch(train) [371][35/63] lr: 5.0218e-03 eta: 23:20:22 time: 1.0483 data_time: 0.0263 memory: 16201 loss_prob: 0.6722 loss_thr: 0.4243 loss_db: 0.1135 loss: 1.2101 2022/08/30 10:06:53 - mmengine - INFO - Epoch(train) [371][40/63] lr: 5.0218e-03 eta: 23:19:54 time: 1.0692 data_time: 0.0284 memory: 16201 loss_prob: 0.6295 loss_thr: 0.4376 loss_db: 0.1059 loss: 1.1730 2022/08/30 10:06:58 - mmengine - INFO - Epoch(train) [371][45/63] lr: 5.0218e-03 eta: 23:19:54 time: 1.0055 data_time: 0.0336 memory: 16201 loss_prob: 0.6367 loss_thr: 0.4443 loss_db: 0.1092 loss: 1.1901 2022/08/30 10:07:03 - mmengine - INFO - Epoch(train) [371][50/63] lr: 5.0218e-03 eta: 23:19:24 time: 0.9987 data_time: 0.0367 memory: 16201 loss_prob: 0.6425 loss_thr: 0.4294 loss_db: 0.1111 loss: 1.1831 2022/08/30 10:07:07 - mmengine - INFO - Epoch(train) [371][55/63] lr: 5.0218e-03 eta: 23:19:24 time: 0.9290 data_time: 0.0226 memory: 16201 loss_prob: 0.6465 loss_thr: 0.4126 loss_db: 0.1096 loss: 1.1687 2022/08/30 10:07:13 - mmengine - INFO - Epoch(train) [371][60/63] lr: 5.0218e-03 eta: 23:18:54 time: 0.9837 data_time: 0.0213 memory: 16201 loss_prob: 0.6338 loss_thr: 0.4086 loss_db: 0.1062 loss: 1.1486 2022/08/30 10:07:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:07:22 - mmengine - INFO - Epoch(train) [372][5/63] lr: 5.0164e-03 eta: 23:18:54 time: 1.1811 data_time: 0.2138 memory: 16201 loss_prob: 0.6192 loss_thr: 0.4188 loss_db: 0.1079 loss: 1.1459 2022/08/30 10:07:28 - mmengine - INFO - Epoch(train) [372][10/63] lr: 5.0164e-03 eta: 23:18:15 time: 1.2835 data_time: 0.2147 memory: 16201 loss_prob: 0.6111 loss_thr: 0.3982 loss_db: 0.1064 loss: 1.1156 2022/08/30 10:07:33 - mmengine - INFO - Epoch(train) [372][15/63] lr: 5.0164e-03 eta: 23:18:15 time: 1.1006 data_time: 0.0262 memory: 16201 loss_prob: 0.6048 loss_thr: 0.3904 loss_db: 0.1002 loss: 1.0953 2022/08/30 10:07:38 - mmengine - INFO - Epoch(train) [372][20/63] lr: 5.0164e-03 eta: 23:17:47 time: 1.0734 data_time: 0.0265 memory: 16201 loss_prob: 0.6251 loss_thr: 0.4345 loss_db: 0.1047 loss: 1.1643 2022/08/30 10:07:44 - mmengine - INFO - Epoch(train) [372][25/63] lr: 5.0164e-03 eta: 23:17:47 time: 1.0086 data_time: 0.0324 memory: 16201 loss_prob: 0.6239 loss_thr: 0.4605 loss_db: 0.1106 loss: 1.1951 2022/08/30 10:07:48 - mmengine - INFO - Epoch(train) [372][30/63] lr: 5.0164e-03 eta: 23:17:18 time: 1.0086 data_time: 0.0268 memory: 16201 loss_prob: 0.6176 loss_thr: 0.4416 loss_db: 0.1077 loss: 1.1668 2022/08/30 10:07:53 - mmengine - INFO - Epoch(train) [372][35/63] lr: 5.0164e-03 eta: 23:17:18 time: 0.9485 data_time: 0.0258 memory: 16201 loss_prob: 0.6393 loss_thr: 0.4236 loss_db: 0.1070 loss: 1.1699 2022/08/30 10:07:58 - mmengine - INFO - Epoch(train) [372][40/63] lr: 5.0164e-03 eta: 23:16:47 time: 0.9347 data_time: 0.0300 memory: 16201 loss_prob: 0.6485 loss_thr: 0.4238 loss_db: 0.1092 loss: 1.1815 2022/08/30 10:08:02 - mmengine - INFO - Epoch(train) [372][45/63] lr: 5.0164e-03 eta: 23:16:47 time: 0.9320 data_time: 0.0241 memory: 16201 loss_prob: 0.6667 loss_thr: 0.4126 loss_db: 0.1130 loss: 1.1923 2022/08/30 10:08:07 - mmengine - INFO - Epoch(train) [372][50/63] lr: 5.0164e-03 eta: 23:16:17 time: 0.9611 data_time: 0.0293 memory: 16201 loss_prob: 0.7056 loss_thr: 0.4238 loss_db: 0.1196 loss: 1.2491 2022/08/30 10:08:14 - mmengine - INFO - Epoch(train) [372][55/63] lr: 5.0164e-03 eta: 23:16:17 time: 1.1118 data_time: 0.0336 memory: 16201 loss_prob: 0.7103 loss_thr: 0.4378 loss_db: 0.1204 loss: 1.2685 2022/08/30 10:08:19 - mmengine - INFO - Epoch(train) [372][60/63] lr: 5.0164e-03 eta: 23:15:50 time: 1.1425 data_time: 0.0345 memory: 16201 loss_prob: 0.6646 loss_thr: 0.4253 loss_db: 0.1105 loss: 1.2004 2022/08/30 10:08:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:08:28 - mmengine - INFO - Epoch(train) [373][5/63] lr: 5.0109e-03 eta: 23:15:50 time: 1.1713 data_time: 0.2209 memory: 16201 loss_prob: 0.6467 loss_thr: 0.4146 loss_db: 0.1106 loss: 1.1719 2022/08/30 10:08:33 - mmengine - INFO - Epoch(train) [373][10/63] lr: 5.0109e-03 eta: 23:15:09 time: 1.1799 data_time: 0.2311 memory: 16201 loss_prob: 0.6830 loss_thr: 0.4213 loss_db: 0.1199 loss: 1.2242 2022/08/30 10:08:38 - mmengine - INFO - Epoch(train) [373][15/63] lr: 5.0109e-03 eta: 23:15:09 time: 1.0146 data_time: 0.0258 memory: 16201 loss_prob: 0.6576 loss_thr: 0.4179 loss_db: 0.1158 loss: 1.1912 2022/08/30 10:08:43 - mmengine - INFO - Epoch(train) [373][20/63] lr: 5.0109e-03 eta: 23:14:40 time: 1.0001 data_time: 0.0289 memory: 16201 loss_prob: 0.6963 loss_thr: 0.4365 loss_db: 0.1192 loss: 1.2520 2022/08/30 10:08:48 - mmengine - INFO - Epoch(train) [373][25/63] lr: 5.0109e-03 eta: 23:14:40 time: 0.9860 data_time: 0.0267 memory: 16201 loss_prob: 0.6980 loss_thr: 0.4276 loss_db: 0.1154 loss: 1.2410 2022/08/30 10:08:53 - mmengine - INFO - Epoch(train) [373][30/63] lr: 5.0109e-03 eta: 23:14:10 time: 1.0119 data_time: 0.0174 memory: 16201 loss_prob: 0.6723 loss_thr: 0.4273 loss_db: 0.1117 loss: 1.2113 2022/08/30 10:08:59 - mmengine - INFO - Epoch(train) [373][35/63] lr: 5.0109e-03 eta: 23:14:10 time: 1.0315 data_time: 0.0333 memory: 16201 loss_prob: 0.6461 loss_thr: 0.4265 loss_db: 0.1124 loss: 1.1851 2022/08/30 10:09:04 - mmengine - INFO - Epoch(train) [373][40/63] lr: 5.0109e-03 eta: 23:13:42 time: 1.0258 data_time: 0.0285 memory: 16201 loss_prob: 0.6541 loss_thr: 0.4238 loss_db: 0.1132 loss: 1.1911 2022/08/30 10:09:09 - mmengine - INFO - Epoch(train) [373][45/63] lr: 5.0109e-03 eta: 23:13:42 time: 0.9924 data_time: 0.0252 memory: 16201 loss_prob: 0.6458 loss_thr: 0.4094 loss_db: 0.1084 loss: 1.1637 2022/08/30 10:09:13 - mmengine - INFO - Epoch(train) [373][50/63] lr: 5.0109e-03 eta: 23:13:12 time: 0.9825 data_time: 0.0333 memory: 16201 loss_prob: 0.6658 loss_thr: 0.4118 loss_db: 0.1136 loss: 1.1912 2022/08/30 10:09:19 - mmengine - INFO - Epoch(train) [373][55/63] lr: 5.0109e-03 eta: 23:13:12 time: 1.0141 data_time: 0.0236 memory: 16201 loss_prob: 0.6740 loss_thr: 0.4235 loss_db: 0.1174 loss: 1.2149 2022/08/30 10:09:23 - mmengine - INFO - Epoch(train) [373][60/63] lr: 5.0109e-03 eta: 23:12:42 time: 0.9984 data_time: 0.0287 memory: 16201 loss_prob: 0.5566 loss_thr: 0.3733 loss_db: 0.0959 loss: 1.0258 2022/08/30 10:09:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:09:33 - mmengine - INFO - Epoch(train) [374][5/63] lr: 5.0055e-03 eta: 23:12:42 time: 1.1227 data_time: 0.2000 memory: 16201 loss_prob: 0.5683 loss_thr: 0.3839 loss_db: 0.0982 loss: 1.0504 2022/08/30 10:09:37 - mmengine - INFO - Epoch(train) [374][10/63] lr: 5.0055e-03 eta: 23:12:00 time: 1.1239 data_time: 0.2102 memory: 16201 loss_prob: 0.5919 loss_thr: 0.4018 loss_db: 0.1032 loss: 1.0969 2022/08/30 10:09:43 - mmengine - INFO - Epoch(train) [374][15/63] lr: 5.0055e-03 eta: 23:12:00 time: 0.9930 data_time: 0.0265 memory: 16201 loss_prob: 0.5737 loss_thr: 0.4041 loss_db: 0.0987 loss: 1.0765 2022/08/30 10:09:47 - mmengine - INFO - Epoch(train) [374][20/63] lr: 5.0055e-03 eta: 23:11:31 time: 1.0027 data_time: 0.0219 memory: 16201 loss_prob: 0.6376 loss_thr: 0.4266 loss_db: 0.1100 loss: 1.1742 2022/08/30 10:09:53 - mmengine - INFO - Epoch(train) [374][25/63] lr: 5.0055e-03 eta: 23:11:31 time: 0.9829 data_time: 0.0314 memory: 16201 loss_prob: 0.6558 loss_thr: 0.4170 loss_db: 0.1147 loss: 1.1875 2022/08/30 10:09:57 - mmengine - INFO - Epoch(train) [374][30/63] lr: 5.0055e-03 eta: 23:11:01 time: 0.9670 data_time: 0.0294 memory: 16201 loss_prob: 0.6510 loss_thr: 0.4177 loss_db: 0.1116 loss: 1.1803 2022/08/30 10:10:01 - mmengine - INFO - Epoch(train) [374][35/63] lr: 5.0055e-03 eta: 23:11:01 time: 0.8823 data_time: 0.0267 memory: 16201 loss_prob: 0.7147 loss_thr: 0.4471 loss_db: 0.1237 loss: 1.2854 2022/08/30 10:10:06 - mmengine - INFO - Epoch(train) [374][40/63] lr: 5.0055e-03 eta: 23:10:28 time: 0.8651 data_time: 0.0278 memory: 16201 loss_prob: 0.7361 loss_thr: 0.4547 loss_db: 0.1279 loss: 1.3187 2022/08/30 10:10:11 - mmengine - INFO - Epoch(train) [374][45/63] lr: 5.0055e-03 eta: 23:10:28 time: 0.9340 data_time: 0.0242 memory: 16201 loss_prob: 0.6467 loss_thr: 0.4121 loss_db: 0.1097 loss: 1.1686 2022/08/30 10:10:15 - mmengine - INFO - Epoch(train) [374][50/63] lr: 5.0055e-03 eta: 23:09:58 time: 0.9366 data_time: 0.0285 memory: 16201 loss_prob: 0.6599 loss_thr: 0.4147 loss_db: 0.1092 loss: 1.1837 2022/08/30 10:10:21 - mmengine - INFO - Epoch(train) [374][55/63] lr: 5.0055e-03 eta: 23:09:58 time: 0.9842 data_time: 0.0319 memory: 16201 loss_prob: 0.6866 loss_thr: 0.4310 loss_db: 0.1140 loss: 1.2316 2022/08/30 10:10:25 - mmengine - INFO - Epoch(train) [374][60/63] lr: 5.0055e-03 eta: 23:09:28 time: 0.9929 data_time: 0.0254 memory: 16201 loss_prob: 0.6097 loss_thr: 0.3935 loss_db: 0.1048 loss: 1.1080 2022/08/30 10:10:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:10:34 - mmengine - INFO - Epoch(train) [375][5/63] lr: 5.0000e-03 eta: 23:09:28 time: 1.0845 data_time: 0.2153 memory: 16201 loss_prob: 0.6230 loss_thr: 0.4170 loss_db: 0.1059 loss: 1.1460 2022/08/30 10:10:39 - mmengine - INFO - Epoch(train) [375][10/63] lr: 5.0000e-03 eta: 23:08:48 time: 1.2073 data_time: 0.2148 memory: 16201 loss_prob: 0.6168 loss_thr: 0.4230 loss_db: 0.1044 loss: 1.1442 2022/08/30 10:10:45 - mmengine - INFO - Epoch(train) [375][15/63] lr: 5.0000e-03 eta: 23:08:48 time: 1.0833 data_time: 0.0271 memory: 16201 loss_prob: 0.5962 loss_thr: 0.3968 loss_db: 0.1008 loss: 1.0939 2022/08/30 10:10:50 - mmengine - INFO - Epoch(train) [375][20/63] lr: 5.0000e-03 eta: 23:08:19 time: 1.0386 data_time: 0.0317 memory: 16201 loss_prob: 0.5967 loss_thr: 0.3790 loss_db: 0.1002 loss: 1.0759 2022/08/30 10:10:54 - mmengine - INFO - Epoch(train) [375][25/63] lr: 5.0000e-03 eta: 23:08:19 time: 0.9254 data_time: 0.0245 memory: 16201 loss_prob: 0.6668 loss_thr: 0.4101 loss_db: 0.1141 loss: 1.1910 2022/08/30 10:11:00 - mmengine - INFO - Epoch(train) [375][30/63] lr: 5.0000e-03 eta: 23:07:50 time: 1.0066 data_time: 0.0203 memory: 16201 loss_prob: 0.8816 loss_thr: 0.4355 loss_db: 0.1414 loss: 1.4586 2022/08/30 10:11:05 - mmengine - INFO - Epoch(train) [375][35/63] lr: 5.0000e-03 eta: 23:07:50 time: 1.0360 data_time: 0.0353 memory: 16201 loss_prob: 1.0167 loss_thr: 0.4271 loss_db: 0.1588 loss: 1.6026 2022/08/30 10:11:09 - mmengine - INFO - Epoch(train) [375][40/63] lr: 5.0000e-03 eta: 23:07:20 time: 0.9569 data_time: 0.0306 memory: 16201 loss_prob: 0.9094 loss_thr: 0.4206 loss_db: 0.1469 loss: 1.4768 2022/08/30 10:11:14 - mmengine - INFO - Epoch(train) [375][45/63] lr: 5.0000e-03 eta: 23:07:20 time: 0.9351 data_time: 0.0230 memory: 16201 loss_prob: 0.8148 loss_thr: 0.4387 loss_db: 0.1309 loss: 1.3844 2022/08/30 10:11:19 - mmengine - INFO - Epoch(train) [375][50/63] lr: 5.0000e-03 eta: 23:06:50 time: 0.9704 data_time: 0.0266 memory: 16201 loss_prob: 0.8636 loss_thr: 0.4654 loss_db: 0.1410 loss: 1.4700 2022/08/30 10:11:24 - mmengine - INFO - Epoch(train) [375][55/63] lr: 5.0000e-03 eta: 23:06:50 time: 1.0226 data_time: 0.0318 memory: 16201 loss_prob: 0.8163 loss_thr: 0.4438 loss_db: 0.1372 loss: 1.3972 2022/08/30 10:11:30 - mmengine - INFO - Epoch(train) [375][60/63] lr: 5.0000e-03 eta: 23:06:22 time: 1.0516 data_time: 0.0345 memory: 16201 loss_prob: 0.7267 loss_thr: 0.4150 loss_db: 0.1211 loss: 1.2628 2022/08/30 10:11:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:11:40 - mmengine - INFO - Epoch(train) [376][5/63] lr: 4.9946e-03 eta: 23:06:22 time: 1.2216 data_time: 0.2245 memory: 16201 loss_prob: 0.9350 loss_thr: 0.4749 loss_db: 0.1521 loss: 1.5621 2022/08/30 10:11:45 - mmengine - INFO - Epoch(train) [376][10/63] lr: 4.9946e-03 eta: 23:05:44 time: 1.3022 data_time: 0.2435 memory: 16201 loss_prob: 0.7103 loss_thr: 0.4502 loss_db: 0.1231 loss: 1.2835 2022/08/30 10:11:51 - mmengine - INFO - Epoch(train) [376][15/63] lr: 4.9946e-03 eta: 23:05:44 time: 1.0913 data_time: 0.0329 memory: 16201 loss_prob: 0.7356 loss_thr: 0.4567 loss_db: 0.1235 loss: 1.3158 2022/08/30 10:11:55 - mmengine - INFO - Epoch(train) [376][20/63] lr: 4.9946e-03 eta: 23:05:15 time: 0.9766 data_time: 0.0306 memory: 16201 loss_prob: 0.7189 loss_thr: 0.4264 loss_db: 0.1205 loss: 1.2658 2022/08/30 10:12:00 - mmengine - INFO - Epoch(train) [376][25/63] lr: 4.9946e-03 eta: 23:05:15 time: 0.9353 data_time: 0.0370 memory: 16201 loss_prob: 0.7775 loss_thr: 0.4673 loss_db: 0.1272 loss: 1.3720 2022/08/30 10:12:06 - mmengine - INFO - Epoch(train) [376][30/63] lr: 4.9946e-03 eta: 23:04:48 time: 1.1170 data_time: 0.0229 memory: 16201 loss_prob: 0.7922 loss_thr: 0.4756 loss_db: 0.1294 loss: 1.3973 2022/08/30 10:12:11 - mmengine - INFO - Epoch(train) [376][35/63] lr: 4.9946e-03 eta: 23:04:48 time: 1.1062 data_time: 0.0295 memory: 16201 loss_prob: 0.6314 loss_thr: 0.3947 loss_db: 0.1087 loss: 1.1348 2022/08/30 10:12:16 - mmengine - INFO - Epoch(train) [376][40/63] lr: 4.9946e-03 eta: 23:04:18 time: 0.9645 data_time: 0.0357 memory: 16201 loss_prob: 0.6788 loss_thr: 0.4162 loss_db: 0.1157 loss: 1.2106 2022/08/30 10:12:22 - mmengine - INFO - Epoch(train) [376][45/63] lr: 4.9946e-03 eta: 23:04:18 time: 1.0601 data_time: 0.0258 memory: 16201 loss_prob: 0.8755 loss_thr: 0.4818 loss_db: 0.1420 loss: 1.4993 2022/08/30 10:12:27 - mmengine - INFO - Epoch(train) [376][50/63] lr: 4.9946e-03 eta: 23:03:51 time: 1.0963 data_time: 0.0864 memory: 16201 loss_prob: 0.9099 loss_thr: 0.4953 loss_db: 0.1472 loss: 1.5525 2022/08/30 10:12:32 - mmengine - INFO - Epoch(train) [376][55/63] lr: 4.9946e-03 eta: 23:03:51 time: 0.9624 data_time: 0.0888 memory: 16201 loss_prob: 0.8306 loss_thr: 0.4747 loss_db: 0.1358 loss: 1.4411 2022/08/30 10:12:35 - mmengine - INFO - Epoch(train) [376][60/63] lr: 4.9946e-03 eta: 23:03:19 time: 0.8527 data_time: 0.0267 memory: 16201 loss_prob: 0.7110 loss_thr: 0.4280 loss_db: 0.1167 loss: 1.2557 2022/08/30 10:12:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:12:46 - mmengine - INFO - Epoch(train) [377][5/63] lr: 4.9891e-03 eta: 23:03:19 time: 1.1485 data_time: 0.2774 memory: 16201 loss_prob: 0.7369 loss_thr: 0.4352 loss_db: 0.1189 loss: 1.2911 2022/08/30 10:12:50 - mmengine - INFO - Epoch(train) [377][10/63] lr: 4.9891e-03 eta: 23:02:37 time: 1.1230 data_time: 0.2750 memory: 16201 loss_prob: 0.7241 loss_thr: 0.4337 loss_db: 0.1174 loss: 1.2752 2022/08/30 10:12:55 - mmengine - INFO - Epoch(train) [377][15/63] lr: 4.9891e-03 eta: 23:02:37 time: 0.9043 data_time: 0.0645 memory: 16201 loss_prob: 0.6433 loss_thr: 0.4088 loss_db: 0.1103 loss: 1.1624 2022/08/30 10:13:01 - mmengine - INFO - Epoch(train) [377][20/63] lr: 4.9891e-03 eta: 23:02:10 time: 1.1059 data_time: 0.1506 memory: 16201 loss_prob: 0.6517 loss_thr: 0.4099 loss_db: 0.1115 loss: 1.1731 2022/08/30 10:13:08 - mmengine - INFO - Epoch(train) [377][25/63] lr: 4.9891e-03 eta: 23:02:10 time: 1.3095 data_time: 0.3887 memory: 16201 loss_prob: 0.6752 loss_thr: 0.4152 loss_db: 0.1120 loss: 1.2024 2022/08/30 10:13:14 - mmengine - INFO - Epoch(train) [377][30/63] lr: 4.9891e-03 eta: 23:01:47 time: 1.2908 data_time: 0.3818 memory: 16201 loss_prob: 0.7340 loss_thr: 0.4348 loss_db: 0.1226 loss: 1.2914 2022/08/30 10:13:20 - mmengine - INFO - Epoch(train) [377][35/63] lr: 4.9891e-03 eta: 23:01:47 time: 1.1971 data_time: 0.2822 memory: 16201 loss_prob: 0.7204 loss_thr: 0.4457 loss_db: 0.1229 loss: 1.2890 2022/08/30 10:13:25 - mmengine - INFO - Epoch(train) [377][40/63] lr: 4.9891e-03 eta: 23:01:22 time: 1.1542 data_time: 0.2888 memory: 16201 loss_prob: 0.6836 loss_thr: 0.4429 loss_db: 0.1135 loss: 1.2399 2022/08/30 10:13:32 - mmengine - INFO - Epoch(train) [377][45/63] lr: 4.9891e-03 eta: 23:01:22 time: 1.2227 data_time: 0.3349 memory: 16201 loss_prob: 0.7423 loss_thr: 0.4497 loss_db: 0.1208 loss: 1.3128 2022/08/30 10:13:36 - mmengine - INFO - Epoch(train) [377][50/63] lr: 4.9891e-03 eta: 23:00:55 time: 1.0922 data_time: 0.2118 memory: 16201 loss_prob: 0.7396 loss_thr: 0.4357 loss_db: 0.1237 loss: 1.2990 2022/08/30 10:13:43 - mmengine - INFO - Epoch(train) [377][55/63] lr: 4.9891e-03 eta: 23:00:55 time: 1.1420 data_time: 0.2119 memory: 16201 loss_prob: 0.6807 loss_thr: 0.4212 loss_db: 0.1165 loss: 1.2184 2022/08/30 10:13:49 - mmengine - INFO - Epoch(train) [377][60/63] lr: 4.9891e-03 eta: 23:00:32 time: 1.2825 data_time: 0.3424 memory: 16201 loss_prob: 0.6555 loss_thr: 0.4202 loss_db: 0.1115 loss: 1.1873 2022/08/30 10:13:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:13:59 - mmengine - INFO - Epoch(train) [378][5/63] lr: 4.9837e-03 eta: 23:00:32 time: 1.1764 data_time: 0.2980 memory: 16201 loss_prob: 0.6602 loss_thr: 0.4540 loss_db: 0.1123 loss: 1.2265 2022/08/30 10:14:04 - mmengine - INFO - Epoch(train) [378][10/63] lr: 4.9837e-03 eta: 22:59:51 time: 1.1738 data_time: 0.2452 memory: 16201 loss_prob: 0.6355 loss_thr: 0.4190 loss_db: 0.1092 loss: 1.1637 2022/08/30 10:14:09 - mmengine - INFO - Epoch(train) [378][15/63] lr: 4.9837e-03 eta: 22:59:51 time: 1.0013 data_time: 0.0422 memory: 16201 loss_prob: 0.6063 loss_thr: 0.4014 loss_db: 0.1034 loss: 1.1111 2022/08/30 10:14:14 - mmengine - INFO - Epoch(train) [378][20/63] lr: 4.9837e-03 eta: 22:59:21 time: 0.9423 data_time: 0.0402 memory: 16201 loss_prob: 0.6241 loss_thr: 0.4094 loss_db: 0.1055 loss: 1.1391 2022/08/30 10:14:18 - mmengine - INFO - Epoch(train) [378][25/63] lr: 4.9837e-03 eta: 22:59:21 time: 0.8580 data_time: 0.0505 memory: 16201 loss_prob: 0.6973 loss_thr: 0.4210 loss_db: 0.1183 loss: 1.2366 2022/08/30 10:14:23 - mmengine - INFO - Epoch(train) [378][30/63] lr: 4.9837e-03 eta: 22:58:51 time: 0.9457 data_time: 0.0481 memory: 16201 loss_prob: 0.7390 loss_thr: 0.4436 loss_db: 0.1237 loss: 1.3064 2022/08/30 10:14:28 - mmengine - INFO - Epoch(train) [378][35/63] lr: 4.9837e-03 eta: 22:58:51 time: 1.0228 data_time: 0.0544 memory: 16201 loss_prob: 0.7169 loss_thr: 0.4608 loss_db: 0.1195 loss: 1.2973 2022/08/30 10:14:34 - mmengine - INFO - Epoch(train) [378][40/63] lr: 4.9837e-03 eta: 22:58:23 time: 1.0643 data_time: 0.0404 memory: 16201 loss_prob: 0.7257 loss_thr: 0.4495 loss_db: 0.1187 loss: 1.2939 2022/08/30 10:14:39 - mmengine - INFO - Epoch(train) [378][45/63] lr: 4.9837e-03 eta: 22:58:23 time: 1.0428 data_time: 0.0416 memory: 16201 loss_prob: 0.7121 loss_thr: 0.4309 loss_db: 0.1172 loss: 1.2602 2022/08/30 10:14:43 - mmengine - INFO - Epoch(train) [378][50/63] lr: 4.9837e-03 eta: 22:57:53 time: 0.9505 data_time: 0.0446 memory: 16201 loss_prob: 0.6518 loss_thr: 0.4309 loss_db: 0.1081 loss: 1.1909 2022/08/30 10:14:47 - mmengine - INFO - Epoch(train) [378][55/63] lr: 4.9837e-03 eta: 22:57:53 time: 0.8884 data_time: 0.0248 memory: 16201 loss_prob: 0.6472 loss_thr: 0.4326 loss_db: 0.1074 loss: 1.1872 2022/08/30 10:14:53 - mmengine - INFO - Epoch(train) [378][60/63] lr: 4.9837e-03 eta: 22:57:24 time: 0.9819 data_time: 0.0497 memory: 16201 loss_prob: 0.7624 loss_thr: 0.4575 loss_db: 0.1263 loss: 1.3462 2022/08/30 10:14:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:15:03 - mmengine - INFO - Epoch(train) [379][5/63] lr: 4.9782e-03 eta: 22:57:24 time: 1.1637 data_time: 0.2294 memory: 16201 loss_prob: 0.7030 loss_thr: 0.4417 loss_db: 0.1178 loss: 1.2626 2022/08/30 10:15:08 - mmengine - INFO - Epoch(train) [379][10/63] lr: 4.9782e-03 eta: 22:56:45 time: 1.2207 data_time: 0.2456 memory: 16201 loss_prob: 0.7434 loss_thr: 0.4478 loss_db: 0.1220 loss: 1.3133 2022/08/30 10:15:13 - mmengine - INFO - Epoch(train) [379][15/63] lr: 4.9782e-03 eta: 22:56:45 time: 0.9282 data_time: 0.0385 memory: 16201 loss_prob: 0.7453 loss_thr: 0.4582 loss_db: 0.1264 loss: 1.3299 2022/08/30 10:15:17 - mmengine - INFO - Epoch(train) [379][20/63] lr: 4.9782e-03 eta: 22:56:14 time: 0.8885 data_time: 0.0277 memory: 16201 loss_prob: 0.6551 loss_thr: 0.4303 loss_db: 0.1141 loss: 1.1994 2022/08/30 10:15:22 - mmengine - INFO - Epoch(train) [379][25/63] lr: 4.9782e-03 eta: 22:56:14 time: 0.9143 data_time: 0.0394 memory: 16201 loss_prob: 0.5904 loss_thr: 0.3949 loss_db: 0.1010 loss: 1.0863 2022/08/30 10:15:26 - mmengine - INFO - Epoch(train) [379][30/63] lr: 4.9782e-03 eta: 22:55:42 time: 0.8543 data_time: 0.0349 memory: 16201 loss_prob: 0.6254 loss_thr: 0.3971 loss_db: 0.1045 loss: 1.1269 2022/08/30 10:15:30 - mmengine - INFO - Epoch(train) [379][35/63] lr: 4.9782e-03 eta: 22:55:42 time: 0.8781 data_time: 0.0319 memory: 16201 loss_prob: 0.6375 loss_thr: 0.4083 loss_db: 0.1083 loss: 1.1540 2022/08/30 10:15:36 - mmengine - INFO - Epoch(train) [379][40/63] lr: 4.9782e-03 eta: 22:55:13 time: 1.0365 data_time: 0.0457 memory: 16201 loss_prob: 0.6165 loss_thr: 0.4087 loss_db: 0.1047 loss: 1.1299 2022/08/30 10:15:40 - mmengine - INFO - Epoch(train) [379][45/63] lr: 4.9782e-03 eta: 22:55:13 time: 1.0034 data_time: 0.0522 memory: 16201 loss_prob: 0.6165 loss_thr: 0.4058 loss_db: 0.1042 loss: 1.1265 2022/08/30 10:15:44 - mmengine - INFO - Epoch(train) [379][50/63] lr: 4.9782e-03 eta: 22:54:41 time: 0.8363 data_time: 0.0392 memory: 16201 loss_prob: 0.6100 loss_thr: 0.3926 loss_db: 0.1045 loss: 1.1071 2022/08/30 10:15:50 - mmengine - INFO - Epoch(train) [379][55/63] lr: 4.9782e-03 eta: 22:54:41 time: 0.9573 data_time: 0.0616 memory: 16201 loss_prob: 0.6216 loss_thr: 0.4070 loss_db: 0.1086 loss: 1.1372 2022/08/30 10:15:55 - mmengine - INFO - Epoch(train) [379][60/63] lr: 4.9782e-03 eta: 22:54:13 time: 1.0287 data_time: 0.0654 memory: 16201 loss_prob: 0.6303 loss_thr: 0.4313 loss_db: 0.1107 loss: 1.1722 2022/08/30 10:15:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:16:05 - mmengine - INFO - Epoch(train) [380][5/63] lr: 4.9727e-03 eta: 22:54:13 time: 1.2046 data_time: 0.2285 memory: 16201 loss_prob: 0.6238 loss_thr: 0.4207 loss_db: 0.1046 loss: 1.1491 2022/08/30 10:16:11 - mmengine - INFO - Epoch(train) [380][10/63] lr: 4.9727e-03 eta: 22:53:35 time: 1.2890 data_time: 0.2418 memory: 16201 loss_prob: 0.6333 loss_thr: 0.4166 loss_db: 0.1062 loss: 1.1561 2022/08/30 10:16:15 - mmengine - INFO - Epoch(train) [380][15/63] lr: 4.9727e-03 eta: 22:53:35 time: 0.9835 data_time: 0.0368 memory: 16201 loss_prob: 0.6765 loss_thr: 0.4328 loss_db: 0.1140 loss: 1.2233 2022/08/30 10:16:19 - mmengine - INFO - Epoch(train) [380][20/63] lr: 4.9727e-03 eta: 22:53:03 time: 0.8354 data_time: 0.0269 memory: 16201 loss_prob: 0.6764 loss_thr: 0.4305 loss_db: 0.1164 loss: 1.2233 2022/08/30 10:16:24 - mmengine - INFO - Epoch(train) [380][25/63] lr: 4.9727e-03 eta: 22:53:03 time: 0.9204 data_time: 0.0469 memory: 16201 loss_prob: 0.6567 loss_thr: 0.4196 loss_db: 0.1113 loss: 1.1876 2022/08/30 10:16:29 - mmengine - INFO - Epoch(train) [380][30/63] lr: 4.9727e-03 eta: 22:52:34 time: 0.9914 data_time: 0.0347 memory: 16201 loss_prob: 0.6002 loss_thr: 0.3973 loss_db: 0.1007 loss: 1.0983 2022/08/30 10:16:33 - mmengine - INFO - Epoch(train) [380][35/63] lr: 4.9727e-03 eta: 22:52:34 time: 0.8863 data_time: 0.0249 memory: 16201 loss_prob: 0.5958 loss_thr: 0.4011 loss_db: 0.1028 loss: 1.0997 2022/08/30 10:16:37 - mmengine - INFO - Epoch(train) [380][40/63] lr: 4.9727e-03 eta: 22:52:01 time: 0.8089 data_time: 0.0357 memory: 16201 loss_prob: 0.6721 loss_thr: 0.4394 loss_db: 0.1164 loss: 1.2279 2022/08/30 10:16:41 - mmengine - INFO - Epoch(train) [380][45/63] lr: 4.9727e-03 eta: 22:52:01 time: 0.8137 data_time: 0.0318 memory: 16201 loss_prob: 0.6219 loss_thr: 0.4149 loss_db: 0.1075 loss: 1.1442 2022/08/30 10:16:45 - mmengine - INFO - Epoch(train) [380][50/63] lr: 4.9727e-03 eta: 22:51:28 time: 0.7921 data_time: 0.0279 memory: 16201 loss_prob: 0.6225 loss_thr: 0.4045 loss_db: 0.1049 loss: 1.1319 2022/08/30 10:16:49 - mmengine - INFO - Epoch(train) [380][55/63] lr: 4.9727e-03 eta: 22:51:28 time: 0.7916 data_time: 0.0388 memory: 16201 loss_prob: 0.6543 loss_thr: 0.4259 loss_db: 0.1133 loss: 1.1935 2022/08/30 10:16:53 - mmengine - INFO - Epoch(train) [380][60/63] lr: 4.9727e-03 eta: 22:50:55 time: 0.8164 data_time: 0.0455 memory: 16201 loss_prob: 0.6300 loss_thr: 0.4127 loss_db: 0.1085 loss: 1.1513 2022/08/30 10:16:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:16:56 - mmengine - INFO - Saving checkpoint at 380 epochs 2022/08/30 10:17:08 - mmengine - INFO - Epoch(val) [380][5/32] eta: 22:50:55 time: 0.6478 data_time: 0.1173 memory: 16201 2022/08/30 10:17:11 - mmengine - INFO - Epoch(val) [380][10/32] eta: 0:00:14 time: 0.6815 data_time: 0.1455 memory: 15734 2022/08/30 10:17:14 - mmengine - INFO - Epoch(val) [380][15/32] eta: 0:00:14 time: 0.5747 data_time: 0.0494 memory: 15734 2022/08/30 10:17:17 - mmengine - INFO - Epoch(val) [380][20/32] eta: 0:00:06 time: 0.5644 data_time: 0.0454 memory: 15734 2022/08/30 10:17:21 - mmengine - INFO - Epoch(val) [380][25/32] eta: 0:00:06 time: 0.6522 data_time: 0.0548 memory: 15734 2022/08/30 10:17:23 - mmengine - INFO - Epoch(val) [380][30/32] eta: 0:00:01 time: 0.6210 data_time: 0.0272 memory: 15734 2022/08/30 10:17:24 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 10:17:24 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8382, precision: 0.7990, hmean: 0.8181 2022/08/30 10:17:24 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8382, precision: 0.8480, hmean: 0.8431 2022/08/30 10:17:24 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8329, precision: 0.8742, hmean: 0.8531 2022/08/30 10:17:24 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8228, precision: 0.8976, hmean: 0.8586 2022/08/30 10:17:24 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7910, precision: 0.9210, hmean: 0.8511 2022/08/30 10:17:24 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6336, precision: 0.9516, hmean: 0.7607 2022/08/30 10:17:24 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0501, precision: 0.9720, hmean: 0.0952 2022/08/30 10:17:24 - mmengine - INFO - Epoch(val) [380][32/32] icdar/precision: 0.8976 icdar/recall: 0.8228 icdar/hmean: 0.8586 2022/08/30 10:17:30 - mmengine - INFO - Epoch(train) [381][5/63] lr: 4.9673e-03 eta: 0:00:01 time: 1.0517 data_time: 0.3145 memory: 16201 loss_prob: 0.6471 loss_thr: 0.4043 loss_db: 0.1074 loss: 1.1588 2022/08/30 10:17:34 - mmengine - INFO - Epoch(train) [381][10/63] lr: 4.9673e-03 eta: 22:50:11 time: 0.9835 data_time: 0.2058 memory: 16201 loss_prob: 0.6364 loss_thr: 0.4076 loss_db: 0.1082 loss: 1.1521 2022/08/30 10:17:38 - mmengine - INFO - Epoch(train) [381][15/63] lr: 4.9673e-03 eta: 22:50:11 time: 0.7914 data_time: 0.0350 memory: 16201 loss_prob: 0.6560 loss_thr: 0.4196 loss_db: 0.1131 loss: 1.1888 2022/08/30 10:17:42 - mmengine - INFO - Epoch(train) [381][20/63] lr: 4.9673e-03 eta: 22:49:39 time: 0.8403 data_time: 0.0349 memory: 16201 loss_prob: 0.6454 loss_thr: 0.4231 loss_db: 0.1114 loss: 1.1799 2022/08/30 10:17:46 - mmengine - INFO - Epoch(train) [381][25/63] lr: 4.9673e-03 eta: 22:49:39 time: 0.8384 data_time: 0.0317 memory: 16201 loss_prob: 0.6151 loss_thr: 0.4161 loss_db: 0.1063 loss: 1.1375 2022/08/30 10:17:50 - mmengine - INFO - Epoch(train) [381][30/63] lr: 4.9673e-03 eta: 22:49:06 time: 0.7924 data_time: 0.0363 memory: 16201 loss_prob: 0.5749 loss_thr: 0.3982 loss_db: 0.0969 loss: 1.0699 2022/08/30 10:17:54 - mmengine - INFO - Epoch(train) [381][35/63] lr: 4.9673e-03 eta: 22:49:06 time: 0.7764 data_time: 0.0339 memory: 16201 loss_prob: 0.5627 loss_thr: 0.3981 loss_db: 0.0928 loss: 1.0535 2022/08/30 10:17:58 - mmengine - INFO - Epoch(train) [381][40/63] lr: 4.9673e-03 eta: 22:48:32 time: 0.7569 data_time: 0.0233 memory: 16201 loss_prob: 0.5882 loss_thr: 0.4162 loss_db: 0.0988 loss: 1.1032 2022/08/30 10:18:03 - mmengine - INFO - Epoch(train) [381][45/63] lr: 4.9673e-03 eta: 22:48:32 time: 0.8383 data_time: 0.0353 memory: 16201 loss_prob: 0.6204 loss_thr: 0.4336 loss_db: 0.1068 loss: 1.1609 2022/08/30 10:18:06 - mmengine - INFO - Epoch(train) [381][50/63] lr: 4.9673e-03 eta: 22:48:00 time: 0.8554 data_time: 0.0435 memory: 16201 loss_prob: 0.6367 loss_thr: 0.4318 loss_db: 0.1073 loss: 1.1758 2022/08/30 10:18:10 - mmengine - INFO - Epoch(train) [381][55/63] lr: 4.9673e-03 eta: 22:48:00 time: 0.7742 data_time: 0.0223 memory: 16201 loss_prob: 0.6676 loss_thr: 0.4417 loss_db: 0.1112 loss: 1.2205 2022/08/30 10:18:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:18:14 - mmengine - INFO - Epoch(train) [381][60/63] lr: 4.9673e-03 eta: 22:47:27 time: 0.7851 data_time: 0.0305 memory: 16201 loss_prob: 0.6814 loss_thr: 0.4518 loss_db: 0.1188 loss: 1.2521 2022/08/30 10:18:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:18:22 - mmengine - INFO - Epoch(train) [382][5/63] lr: 4.9618e-03 eta: 22:47:27 time: 0.9345 data_time: 0.1901 memory: 16201 loss_prob: 0.5836 loss_thr: 0.4107 loss_db: 0.1012 loss: 1.0955 2022/08/30 10:18:26 - mmengine - INFO - Epoch(train) [382][10/63] lr: 4.9618e-03 eta: 22:46:43 time: 0.9609 data_time: 0.2085 memory: 16201 loss_prob: 0.6231 loss_thr: 0.4269 loss_db: 0.1059 loss: 1.1558 2022/08/30 10:18:30 - mmengine - INFO - Epoch(train) [382][15/63] lr: 4.9618e-03 eta: 22:46:43 time: 0.8104 data_time: 0.0359 memory: 16201 loss_prob: 0.6507 loss_thr: 0.4345 loss_db: 0.1086 loss: 1.1938 2022/08/30 10:18:34 - mmengine - INFO - Epoch(train) [382][20/63] lr: 4.9618e-03 eta: 22:46:10 time: 0.8301 data_time: 0.0303 memory: 16201 loss_prob: 0.6500 loss_thr: 0.4387 loss_db: 0.1121 loss: 1.2007 2022/08/30 10:18:38 - mmengine - INFO - Epoch(train) [382][25/63] lr: 4.9618e-03 eta: 22:46:10 time: 0.8162 data_time: 0.0400 memory: 16201 loss_prob: 0.6568 loss_thr: 0.4387 loss_db: 0.1141 loss: 1.2096 2022/08/30 10:18:42 - mmengine - INFO - Epoch(train) [382][30/63] lr: 4.9618e-03 eta: 22:45:38 time: 0.8061 data_time: 0.0321 memory: 16201 loss_prob: 0.6245 loss_thr: 0.4246 loss_db: 0.1060 loss: 1.1551 2022/08/30 10:18:46 - mmengine - INFO - Epoch(train) [382][35/63] lr: 4.9618e-03 eta: 22:45:38 time: 0.7993 data_time: 0.0273 memory: 16201 loss_prob: 0.5512 loss_thr: 0.4053 loss_db: 0.0956 loss: 1.0521 2022/08/30 10:18:50 - mmengine - INFO - Epoch(train) [382][40/63] lr: 4.9618e-03 eta: 22:45:04 time: 0.7802 data_time: 0.0313 memory: 16201 loss_prob: 0.6032 loss_thr: 0.4111 loss_db: 0.1052 loss: 1.1196 2022/08/30 10:18:54 - mmengine - INFO - Epoch(train) [382][45/63] lr: 4.9618e-03 eta: 22:45:04 time: 0.7855 data_time: 0.0328 memory: 16201 loss_prob: 0.6531 loss_thr: 0.4119 loss_db: 0.1088 loss: 1.1738 2022/08/30 10:18:58 - mmengine - INFO - Epoch(train) [382][50/63] lr: 4.9618e-03 eta: 22:44:32 time: 0.8203 data_time: 0.0282 memory: 16201 loss_prob: 0.6032 loss_thr: 0.3923 loss_db: 0.1006 loss: 1.0961 2022/08/30 10:19:03 - mmengine - INFO - Epoch(train) [382][55/63] lr: 4.9618e-03 eta: 22:44:32 time: 0.8320 data_time: 0.0308 memory: 16201 loss_prob: 0.5188 loss_thr: 0.3661 loss_db: 0.0909 loss: 0.9758 2022/08/30 10:19:06 - mmengine - INFO - Epoch(train) [382][60/63] lr: 4.9618e-03 eta: 22:43:59 time: 0.8037 data_time: 0.0343 memory: 16201 loss_prob: 0.5628 loss_thr: 0.3866 loss_db: 0.0976 loss: 1.0470 2022/08/30 10:19:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:19:15 - mmengine - INFO - Epoch(train) [383][5/63] lr: 4.9564e-03 eta: 22:43:59 time: 0.9638 data_time: 0.2046 memory: 16201 loss_prob: 0.5817 loss_thr: 0.3778 loss_db: 0.0994 loss: 1.0589 2022/08/30 10:19:18 - mmengine - INFO - Epoch(train) [383][10/63] lr: 4.9564e-03 eta: 22:43:16 time: 1.0020 data_time: 0.2176 memory: 16201 loss_prob: 0.6165 loss_thr: 0.3762 loss_db: 0.1046 loss: 1.0973 2022/08/30 10:19:23 - mmengine - INFO - Epoch(train) [383][15/63] lr: 4.9564e-03 eta: 22:43:16 time: 0.8130 data_time: 0.0370 memory: 16201 loss_prob: 0.6310 loss_thr: 0.3969 loss_db: 0.1074 loss: 1.1354 2022/08/30 10:19:26 - mmengine - INFO - Epoch(train) [383][20/63] lr: 4.9564e-03 eta: 22:42:43 time: 0.7985 data_time: 0.0259 memory: 16201 loss_prob: 0.6062 loss_thr: 0.4174 loss_db: 0.1005 loss: 1.1242 2022/08/30 10:19:31 - mmengine - INFO - Epoch(train) [383][25/63] lr: 4.9564e-03 eta: 22:42:43 time: 0.7875 data_time: 0.0383 memory: 16201 loss_prob: 0.5925 loss_thr: 0.3979 loss_db: 0.0997 loss: 1.0901 2022/08/30 10:19:35 - mmengine - INFO - Epoch(train) [383][30/63] lr: 4.9564e-03 eta: 22:42:11 time: 0.8108 data_time: 0.0371 memory: 16201 loss_prob: 0.5803 loss_thr: 0.3913 loss_db: 0.1003 loss: 1.0719 2022/08/30 10:19:38 - mmengine - INFO - Epoch(train) [383][35/63] lr: 4.9564e-03 eta: 22:42:11 time: 0.7847 data_time: 0.0208 memory: 16201 loss_prob: 0.5752 loss_thr: 0.4017 loss_db: 0.0989 loss: 1.0758 2022/08/30 10:19:43 - mmengine - INFO - Epoch(train) [383][40/63] lr: 4.9564e-03 eta: 22:41:38 time: 0.8037 data_time: 0.0335 memory: 16201 loss_prob: 0.5698 loss_thr: 0.3952 loss_db: 0.0961 loss: 1.0612 2022/08/30 10:19:47 - mmengine - INFO - Epoch(train) [383][45/63] lr: 4.9564e-03 eta: 22:41:38 time: 0.8157 data_time: 0.0363 memory: 16201 loss_prob: 0.6471 loss_thr: 0.4356 loss_db: 0.1096 loss: 1.1923 2022/08/30 10:19:50 - mmengine - INFO - Epoch(train) [383][50/63] lr: 4.9564e-03 eta: 22:41:05 time: 0.7816 data_time: 0.0271 memory: 16201 loss_prob: 0.6800 loss_thr: 0.4497 loss_db: 0.1167 loss: 1.2464 2022/08/30 10:19:55 - mmengine - INFO - Epoch(train) [383][55/63] lr: 4.9564e-03 eta: 22:41:05 time: 0.8217 data_time: 0.0425 memory: 16201 loss_prob: 0.6115 loss_thr: 0.4192 loss_db: 0.1059 loss: 1.1366 2022/08/30 10:19:59 - mmengine - INFO - Epoch(train) [383][60/63] lr: 4.9564e-03 eta: 22:40:33 time: 0.8160 data_time: 0.0419 memory: 16201 loss_prob: 0.5805 loss_thr: 0.3969 loss_db: 0.0972 loss: 1.0746 2022/08/30 10:20:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:20:06 - mmengine - INFO - Epoch(train) [384][5/63] lr: 4.9509e-03 eta: 22:40:33 time: 0.8902 data_time: 0.1608 memory: 16201 loss_prob: 0.5841 loss_thr: 0.3981 loss_db: 0.0996 loss: 1.0818 2022/08/30 10:20:12 - mmengine - INFO - Epoch(train) [384][10/63] lr: 4.9509e-03 eta: 22:39:53 time: 1.1772 data_time: 0.4040 memory: 16201 loss_prob: 0.5953 loss_thr: 0.4026 loss_db: 0.1017 loss: 1.0995 2022/08/30 10:20:17 - mmengine - INFO - Epoch(train) [384][15/63] lr: 4.9509e-03 eta: 22:39:53 time: 1.0589 data_time: 0.2846 memory: 16201 loss_prob: 0.6141 loss_thr: 0.4023 loss_db: 0.1080 loss: 1.1244 2022/08/30 10:20:23 - mmengine - INFO - Epoch(train) [384][20/63] lr: 4.9509e-03 eta: 22:39:26 time: 1.0553 data_time: 0.2944 memory: 16201 loss_prob: 0.6281 loss_thr: 0.4134 loss_db: 0.1092 loss: 1.1508 2022/08/30 10:20:27 - mmengine - INFO - Epoch(train) [384][25/63] lr: 4.9509e-03 eta: 22:39:26 time: 1.0229 data_time: 0.2795 memory: 16201 loss_prob: 0.6369 loss_thr: 0.4306 loss_db: 0.1105 loss: 1.1780 2022/08/30 10:20:32 - mmengine - INFO - Epoch(train) [384][30/63] lr: 4.9509e-03 eta: 22:38:57 time: 0.9378 data_time: 0.1751 memory: 16201 loss_prob: 0.7399 loss_thr: 0.4170 loss_db: 0.1258 loss: 1.2827 2022/08/30 10:20:37 - mmengine - INFO - Epoch(train) [384][35/63] lr: 4.9509e-03 eta: 22:38:57 time: 1.0339 data_time: 0.2622 memory: 16201 loss_prob: 0.8444 loss_thr: 0.4302 loss_db: 0.1401 loss: 1.4146 2022/08/30 10:20:41 - mmengine - INFO - Epoch(train) [384][40/63] lr: 4.9509e-03 eta: 22:38:25 time: 0.8656 data_time: 0.1154 memory: 16201 loss_prob: 0.9455 loss_thr: 0.4805 loss_db: 0.1509 loss: 1.5769 2022/08/30 10:20:45 - mmengine - INFO - Epoch(train) [384][45/63] lr: 4.9509e-03 eta: 22:38:25 time: 0.7836 data_time: 0.0309 memory: 16201 loss_prob: 0.9316 loss_thr: 0.4992 loss_db: 0.1500 loss: 1.5809 2022/08/30 10:20:49 - mmengine - INFO - Epoch(train) [384][50/63] lr: 4.9509e-03 eta: 22:37:53 time: 0.7955 data_time: 0.0362 memory: 16201 loss_prob: 0.7831 loss_thr: 0.4620 loss_db: 0.1324 loss: 1.3775 2022/08/30 10:20:53 - mmengine - INFO - Epoch(train) [384][55/63] lr: 4.9509e-03 eta: 22:37:53 time: 0.8204 data_time: 0.0303 memory: 16201 loss_prob: 0.7145 loss_thr: 0.4261 loss_db: 0.1216 loss: 1.2622 2022/08/30 10:20:57 - mmengine - INFO - Epoch(train) [384][60/63] lr: 4.9509e-03 eta: 22:37:20 time: 0.8135 data_time: 0.0303 memory: 16201 loss_prob: 0.7398 loss_thr: 0.4433 loss_db: 0.1283 loss: 1.3114 2022/08/30 10:20:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:21:05 - mmengine - INFO - Epoch(train) [385][5/63] lr: 4.9454e-03 eta: 22:37:20 time: 0.9116 data_time: 0.2026 memory: 16201 loss_prob: 0.7335 loss_thr: 0.4382 loss_db: 0.1294 loss: 1.3011 2022/08/30 10:21:09 - mmengine - INFO - Epoch(train) [385][10/63] lr: 4.9454e-03 eta: 22:36:37 time: 0.9693 data_time: 0.2087 memory: 16201 loss_prob: 0.6802 loss_thr: 0.4220 loss_db: 0.1061 loss: 1.2083 2022/08/30 10:21:13 - mmengine - INFO - Epoch(train) [385][15/63] lr: 4.9454e-03 eta: 22:36:37 time: 0.8044 data_time: 0.0407 memory: 16201 loss_prob: 0.6913 loss_thr: 0.4211 loss_db: 0.1096 loss: 1.2220 2022/08/30 10:21:17 - mmengine - INFO - Epoch(train) [385][20/63] lr: 4.9454e-03 eta: 22:36:04 time: 0.7945 data_time: 0.0283 memory: 16201 loss_prob: 0.7352 loss_thr: 0.4355 loss_db: 0.1250 loss: 1.2957 2022/08/30 10:21:21 - mmengine - INFO - Epoch(train) [385][25/63] lr: 4.9454e-03 eta: 22:36:04 time: 0.7957 data_time: 0.0251 memory: 16201 loss_prob: 0.6831 loss_thr: 0.4185 loss_db: 0.1159 loss: 1.2175 2022/08/30 10:21:25 - mmengine - INFO - Epoch(train) [385][30/63] lr: 4.9454e-03 eta: 22:35:32 time: 0.8009 data_time: 0.0379 memory: 16201 loss_prob: 0.6537 loss_thr: 0.4094 loss_db: 0.1129 loss: 1.1760 2022/08/30 10:21:28 - mmengine - INFO - Epoch(train) [385][35/63] lr: 4.9454e-03 eta: 22:35:32 time: 0.7754 data_time: 0.0291 memory: 16201 loss_prob: 0.7743 loss_thr: 0.4541 loss_db: 0.1304 loss: 1.3587 2022/08/30 10:21:33 - mmengine - INFO - Epoch(train) [385][40/63] lr: 4.9454e-03 eta: 22:35:00 time: 0.8358 data_time: 0.0287 memory: 16201 loss_prob: 0.7554 loss_thr: 0.4588 loss_db: 0.1262 loss: 1.3404 2022/08/30 10:21:37 - mmengine - INFO - Epoch(train) [385][45/63] lr: 4.9454e-03 eta: 22:35:00 time: 0.8378 data_time: 0.0359 memory: 16201 loss_prob: 0.6640 loss_thr: 0.4271 loss_db: 0.1160 loss: 1.2071 2022/08/30 10:21:41 - mmengine - INFO - Epoch(train) [385][50/63] lr: 4.9454e-03 eta: 22:34:27 time: 0.7619 data_time: 0.0302 memory: 16201 loss_prob: 0.6894 loss_thr: 0.4492 loss_db: 0.1198 loss: 1.2585 2022/08/30 10:21:45 - mmengine - INFO - Epoch(train) [385][55/63] lr: 4.9454e-03 eta: 22:34:27 time: 0.7782 data_time: 0.0328 memory: 16201 loss_prob: 0.6940 loss_thr: 0.4469 loss_db: 0.1164 loss: 1.2573 2022/08/30 10:21:49 - mmengine - INFO - Epoch(train) [385][60/63] lr: 4.9454e-03 eta: 22:33:54 time: 0.7921 data_time: 0.0309 memory: 16201 loss_prob: 0.7011 loss_thr: 0.4331 loss_db: 0.1153 loss: 1.2494 2022/08/30 10:21:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:21:57 - mmengine - INFO - Epoch(train) [386][5/63] lr: 4.9400e-03 eta: 22:33:54 time: 1.0195 data_time: 0.1975 memory: 16201 loss_prob: 0.7150 loss_thr: 0.4531 loss_db: 0.1231 loss: 1.2912 2022/08/30 10:22:01 - mmengine - INFO - Epoch(train) [386][10/63] lr: 4.9400e-03 eta: 22:33:11 time: 0.9798 data_time: 0.2108 memory: 16201 loss_prob: 0.6730 loss_thr: 0.4422 loss_db: 0.1168 loss: 1.2320 2022/08/30 10:22:05 - mmengine - INFO - Epoch(train) [386][15/63] lr: 4.9400e-03 eta: 22:33:11 time: 0.7993 data_time: 0.0386 memory: 16201 loss_prob: 0.7068 loss_thr: 0.4406 loss_db: 0.1113 loss: 1.2588 2022/08/30 10:22:09 - mmengine - INFO - Epoch(train) [386][20/63] lr: 4.9400e-03 eta: 22:32:38 time: 0.7887 data_time: 0.0299 memory: 16201 loss_prob: 0.7582 loss_thr: 0.4313 loss_db: 0.1189 loss: 1.3085 2022/08/30 10:22:14 - mmengine - INFO - Epoch(train) [386][25/63] lr: 4.9400e-03 eta: 22:32:38 time: 0.8402 data_time: 0.0391 memory: 16201 loss_prob: 0.7111 loss_thr: 0.4087 loss_db: 0.1217 loss: 1.2416 2022/08/30 10:22:17 - mmengine - INFO - Epoch(train) [386][30/63] lr: 4.9400e-03 eta: 22:32:07 time: 0.8352 data_time: 0.0388 memory: 16201 loss_prob: 0.7038 loss_thr: 0.4244 loss_db: 0.1188 loss: 1.2471 2022/08/30 10:22:21 - mmengine - INFO - Epoch(train) [386][35/63] lr: 4.9400e-03 eta: 22:32:07 time: 0.7841 data_time: 0.0307 memory: 16201 loss_prob: 0.7269 loss_thr: 0.4428 loss_db: 0.1204 loss: 1.2900 2022/08/30 10:22:25 - mmengine - INFO - Epoch(train) [386][40/63] lr: 4.9400e-03 eta: 22:31:34 time: 0.7932 data_time: 0.0344 memory: 16201 loss_prob: 0.7050 loss_thr: 0.4328 loss_db: 0.1179 loss: 1.2557 2022/08/30 10:22:29 - mmengine - INFO - Epoch(train) [386][45/63] lr: 4.9400e-03 eta: 22:31:34 time: 0.8045 data_time: 0.0337 memory: 16201 loss_prob: 0.6655 loss_thr: 0.4195 loss_db: 0.1102 loss: 1.1952 2022/08/30 10:22:34 - mmengine - INFO - Epoch(train) [386][50/63] lr: 4.9400e-03 eta: 22:31:03 time: 0.8283 data_time: 0.0279 memory: 16201 loss_prob: 0.6262 loss_thr: 0.4134 loss_db: 0.1061 loss: 1.1457 2022/08/30 10:22:38 - mmengine - INFO - Epoch(train) [386][55/63] lr: 4.9400e-03 eta: 22:31:03 time: 0.8200 data_time: 0.0345 memory: 16201 loss_prob: 0.6400 loss_thr: 0.4268 loss_db: 0.1086 loss: 1.1754 2022/08/30 10:22:42 - mmengine - INFO - Epoch(train) [386][60/63] lr: 4.9400e-03 eta: 22:30:30 time: 0.7939 data_time: 0.0346 memory: 16201 loss_prob: 0.6541 loss_thr: 0.4368 loss_db: 0.1101 loss: 1.2011 2022/08/30 10:22:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:22:49 - mmengine - INFO - Epoch(train) [387][5/63] lr: 4.9345e-03 eta: 22:30:30 time: 0.9000 data_time: 0.1724 memory: 16201 loss_prob: 0.6746 loss_thr: 0.4208 loss_db: 0.1168 loss: 1.2123 2022/08/30 10:22:54 - mmengine - INFO - Epoch(train) [387][10/63] lr: 4.9345e-03 eta: 22:29:48 time: 1.0346 data_time: 0.2754 memory: 16201 loss_prob: 0.6394 loss_thr: 0.4025 loss_db: 0.1131 loss: 1.1551 2022/08/30 10:22:58 - mmengine - INFO - Epoch(train) [387][15/63] lr: 4.9345e-03 eta: 22:29:48 time: 0.8901 data_time: 0.1290 memory: 16201 loss_prob: 0.6269 loss_thr: 0.4185 loss_db: 0.1086 loss: 1.1539 2022/08/30 10:23:02 - mmengine - INFO - Epoch(train) [387][20/63] lr: 4.9345e-03 eta: 22:29:17 time: 0.8408 data_time: 0.0284 memory: 16201 loss_prob: 0.6253 loss_thr: 0.4207 loss_db: 0.1070 loss: 1.1530 2022/08/30 10:23:06 - mmengine - INFO - Epoch(train) [387][25/63] lr: 4.9345e-03 eta: 22:29:17 time: 0.8467 data_time: 0.0438 memory: 16201 loss_prob: 0.6081 loss_thr: 0.4359 loss_db: 0.1064 loss: 1.1504 2022/08/30 10:23:10 - mmengine - INFO - Epoch(train) [387][30/63] lr: 4.9345e-03 eta: 22:28:44 time: 0.7867 data_time: 0.0327 memory: 16201 loss_prob: 0.6336 loss_thr: 0.4348 loss_db: 0.1078 loss: 1.1761 2022/08/30 10:23:14 - mmengine - INFO - Epoch(train) [387][35/63] lr: 4.9345e-03 eta: 22:28:44 time: 0.7777 data_time: 0.0220 memory: 16201 loss_prob: 0.6125 loss_thr: 0.4036 loss_db: 0.1023 loss: 1.1184 2022/08/30 10:23:18 - mmengine - INFO - Epoch(train) [387][40/63] lr: 4.9345e-03 eta: 22:28:12 time: 0.7856 data_time: 0.0339 memory: 16201 loss_prob: 0.6191 loss_thr: 0.4089 loss_db: 0.1085 loss: 1.1365 2022/08/30 10:23:23 - mmengine - INFO - Epoch(train) [387][45/63] lr: 4.9345e-03 eta: 22:28:12 time: 0.8490 data_time: 0.0364 memory: 16201 loss_prob: 0.6056 loss_thr: 0.4069 loss_db: 0.1065 loss: 1.1190 2022/08/30 10:23:26 - mmengine - INFO - Epoch(train) [387][50/63] lr: 4.9345e-03 eta: 22:27:41 time: 0.8369 data_time: 0.0316 memory: 16201 loss_prob: 0.5852 loss_thr: 0.4069 loss_db: 0.0985 loss: 1.0906 2022/08/30 10:23:33 - mmengine - INFO - Epoch(train) [387][55/63] lr: 4.9345e-03 eta: 22:27:41 time: 1.0464 data_time: 0.2924 memory: 16201 loss_prob: 0.6727 loss_thr: 0.4275 loss_db: 0.1123 loss: 1.2125 2022/08/30 10:23:39 - mmengine - INFO - Epoch(train) [387][60/63] lr: 4.9345e-03 eta: 22:27:17 time: 1.2261 data_time: 0.4274 memory: 16201 loss_prob: 0.6458 loss_thr: 0.4132 loss_db: 0.1112 loss: 1.1702 2022/08/30 10:23:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:23:49 - mmengine - INFO - Epoch(train) [388][5/63] lr: 4.9291e-03 eta: 22:27:17 time: 1.2092 data_time: 0.4715 memory: 16201 loss_prob: 0.6682 loss_thr: 0.4289 loss_db: 0.1122 loss: 1.2093 2022/08/30 10:23:53 - mmengine - INFO - Epoch(train) [388][10/63] lr: 4.9291e-03 eta: 22:26:34 time: 0.9722 data_time: 0.2165 memory: 16201 loss_prob: 0.6700 loss_thr: 0.4282 loss_db: 0.1120 loss: 1.2101 2022/08/30 10:23:57 - mmengine - INFO - Epoch(train) [388][15/63] lr: 4.9291e-03 eta: 22:26:34 time: 0.7937 data_time: 0.0345 memory: 16201 loss_prob: 0.6267 loss_thr: 0.4041 loss_db: 0.1079 loss: 1.1387 2022/08/30 10:24:02 - mmengine - INFO - Epoch(train) [388][20/63] lr: 4.9291e-03 eta: 22:26:03 time: 0.8403 data_time: 0.0245 memory: 16201 loss_prob: 0.5844 loss_thr: 0.3995 loss_db: 0.1005 loss: 1.0844 2022/08/30 10:24:06 - mmengine - INFO - Epoch(train) [388][25/63] lr: 4.9291e-03 eta: 22:26:03 time: 0.8310 data_time: 0.0326 memory: 16201 loss_prob: 0.5999 loss_thr: 0.4145 loss_db: 0.1029 loss: 1.1173 2022/08/30 10:24:09 - mmengine - INFO - Epoch(train) [388][30/63] lr: 4.9291e-03 eta: 22:25:30 time: 0.7691 data_time: 0.0343 memory: 16201 loss_prob: 0.6251 loss_thr: 0.4299 loss_db: 0.1091 loss: 1.1640 2022/08/30 10:24:13 - mmengine - INFO - Epoch(train) [388][35/63] lr: 4.9291e-03 eta: 22:25:30 time: 0.7898 data_time: 0.0342 memory: 16201 loss_prob: 0.6144 loss_thr: 0.4275 loss_db: 0.1066 loss: 1.1484 2022/08/30 10:24:17 - mmengine - INFO - Epoch(train) [388][40/63] lr: 4.9291e-03 eta: 22:24:58 time: 0.8034 data_time: 0.0338 memory: 16201 loss_prob: 0.6642 loss_thr: 0.4239 loss_db: 0.1106 loss: 1.1986 2022/08/30 10:24:22 - mmengine - INFO - Epoch(train) [388][45/63] lr: 4.9291e-03 eta: 22:24:58 time: 0.8087 data_time: 0.0334 memory: 16201 loss_prob: 0.6629 loss_thr: 0.4213 loss_db: 0.1108 loss: 1.1951 2022/08/30 10:24:25 - mmengine - INFO - Epoch(train) [388][50/63] lr: 4.9291e-03 eta: 22:24:26 time: 0.7980 data_time: 0.0340 memory: 16201 loss_prob: 0.5702 loss_thr: 0.3966 loss_db: 0.0996 loss: 1.0664 2022/08/30 10:24:29 - mmengine - INFO - Epoch(train) [388][55/63] lr: 4.9291e-03 eta: 22:24:26 time: 0.7806 data_time: 0.0297 memory: 16201 loss_prob: 0.6602 loss_thr: 0.4346 loss_db: 0.1107 loss: 1.2055 2022/08/30 10:24:33 - mmengine - INFO - Epoch(train) [388][60/63] lr: 4.9291e-03 eta: 22:23:54 time: 0.7942 data_time: 0.0314 memory: 16201 loss_prob: 0.7156 loss_thr: 0.4537 loss_db: 0.1191 loss: 1.2884 2022/08/30 10:24:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:24:41 - mmengine - INFO - Epoch(train) [389][5/63] lr: 4.9236e-03 eta: 22:23:54 time: 0.8974 data_time: 0.1763 memory: 16201 loss_prob: 0.6499 loss_thr: 0.4167 loss_db: 0.1119 loss: 1.1785 2022/08/30 10:24:45 - mmengine - INFO - Epoch(train) [389][10/63] lr: 4.9236e-03 eta: 22:23:11 time: 0.9715 data_time: 0.2010 memory: 16201 loss_prob: 0.6392 loss_thr: 0.4232 loss_db: 0.1109 loss: 1.1733 2022/08/30 10:24:49 - mmengine - INFO - Epoch(train) [389][15/63] lr: 4.9236e-03 eta: 22:23:11 time: 0.8297 data_time: 0.0372 memory: 16201 loss_prob: 0.6836 loss_thr: 0.4336 loss_db: 0.1163 loss: 1.2335 2022/08/30 10:24:53 - mmengine - INFO - Epoch(train) [389][20/63] lr: 4.9236e-03 eta: 22:22:39 time: 0.8181 data_time: 0.0226 memory: 16201 loss_prob: 0.6676 loss_thr: 0.4189 loss_db: 0.1119 loss: 1.1985 2022/08/30 10:24:57 - mmengine - INFO - Epoch(train) [389][25/63] lr: 4.9236e-03 eta: 22:22:39 time: 0.8151 data_time: 0.0444 memory: 16201 loss_prob: 0.6687 loss_thr: 0.4048 loss_db: 0.1074 loss: 1.1809 2022/08/30 10:25:01 - mmengine - INFO - Epoch(train) [389][30/63] lr: 4.9236e-03 eta: 22:22:08 time: 0.8172 data_time: 0.0348 memory: 16201 loss_prob: 0.6753 loss_thr: 0.4134 loss_db: 0.1122 loss: 1.2009 2022/08/30 10:25:05 - mmengine - INFO - Epoch(train) [389][35/63] lr: 4.9236e-03 eta: 22:22:08 time: 0.7957 data_time: 0.0224 memory: 16201 loss_prob: 0.6309 loss_thr: 0.4115 loss_db: 0.1103 loss: 1.1527 2022/08/30 10:25:09 - mmengine - INFO - Epoch(train) [389][40/63] lr: 4.9236e-03 eta: 22:21:35 time: 0.7770 data_time: 0.0337 memory: 16201 loss_prob: 0.5901 loss_thr: 0.4020 loss_db: 0.1012 loss: 1.0933 2022/08/30 10:25:13 - mmengine - INFO - Epoch(train) [389][45/63] lr: 4.9236e-03 eta: 22:21:35 time: 0.7924 data_time: 0.0407 memory: 16201 loss_prob: 0.6131 loss_thr: 0.4105 loss_db: 0.1022 loss: 1.1259 2022/08/30 10:25:17 - mmengine - INFO - Epoch(train) [389][50/63] lr: 4.9236e-03 eta: 22:21:03 time: 0.7920 data_time: 0.0377 memory: 16201 loss_prob: 0.6666 loss_thr: 0.4149 loss_db: 0.1081 loss: 1.1896 2022/08/30 10:25:21 - mmengine - INFO - Epoch(train) [389][55/63] lr: 4.9236e-03 eta: 22:21:03 time: 0.8136 data_time: 0.0325 memory: 16201 loss_prob: 0.6688 loss_thr: 0.4266 loss_db: 0.1122 loss: 1.2076 2022/08/30 10:25:25 - mmengine - INFO - Epoch(train) [389][60/63] lr: 4.9236e-03 eta: 22:20:32 time: 0.8230 data_time: 0.0356 memory: 16201 loss_prob: 0.6410 loss_thr: 0.4234 loss_db: 0.1113 loss: 1.1757 2022/08/30 10:25:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:25:33 - mmengine - INFO - Epoch(train) [390][5/63] lr: 4.9181e-03 eta: 22:20:32 time: 0.9111 data_time: 0.1950 memory: 16201 loss_prob: 0.6533 loss_thr: 0.4377 loss_db: 0.1108 loss: 1.2018 2022/08/30 10:25:37 - mmengine - INFO - Epoch(train) [390][10/63] lr: 4.9181e-03 eta: 22:19:49 time: 0.9629 data_time: 0.2128 memory: 16201 loss_prob: 0.6392 loss_thr: 0.4336 loss_db: 0.1101 loss: 1.1830 2022/08/30 10:25:41 - mmengine - INFO - Epoch(train) [390][15/63] lr: 4.9181e-03 eta: 22:19:49 time: 0.8444 data_time: 0.0358 memory: 16201 loss_prob: 0.6156 loss_thr: 0.4236 loss_db: 0.1062 loss: 1.1455 2022/08/30 10:25:45 - mmengine - INFO - Epoch(train) [390][20/63] lr: 4.9181e-03 eta: 22:19:18 time: 0.8483 data_time: 0.0281 memory: 16201 loss_prob: 0.5787 loss_thr: 0.4099 loss_db: 0.0979 loss: 1.0866 2022/08/30 10:25:49 - mmengine - INFO - Epoch(train) [390][25/63] lr: 4.9181e-03 eta: 22:19:18 time: 0.7941 data_time: 0.0383 memory: 16201 loss_prob: 0.6177 loss_thr: 0.4174 loss_db: 0.1032 loss: 1.1382 2022/08/30 10:25:53 - mmengine - INFO - Epoch(train) [390][30/63] lr: 4.9181e-03 eta: 22:18:46 time: 0.8007 data_time: 0.0320 memory: 16201 loss_prob: 0.6984 loss_thr: 0.4214 loss_db: 0.1102 loss: 1.2300 2022/08/30 10:25:57 - mmengine - INFO - Epoch(train) [390][35/63] lr: 4.9181e-03 eta: 22:18:46 time: 0.7926 data_time: 0.0260 memory: 16201 loss_prob: 0.6763 loss_thr: 0.4052 loss_db: 0.1083 loss: 1.1898 2022/08/30 10:26:01 - mmengine - INFO - Epoch(train) [390][40/63] lr: 4.9181e-03 eta: 22:18:14 time: 0.7968 data_time: 0.0357 memory: 16201 loss_prob: 0.6188 loss_thr: 0.3972 loss_db: 0.1079 loss: 1.1238 2022/08/30 10:26:05 - mmengine - INFO - Epoch(train) [390][45/63] lr: 4.9181e-03 eta: 22:18:14 time: 0.7961 data_time: 0.0341 memory: 16201 loss_prob: 0.5812 loss_thr: 0.3848 loss_db: 0.1023 loss: 1.0683 2022/08/30 10:26:09 - mmengine - INFO - Epoch(train) [390][50/63] lr: 4.9181e-03 eta: 22:17:42 time: 0.7831 data_time: 0.0273 memory: 16201 loss_prob: 0.5592 loss_thr: 0.3782 loss_db: 0.0958 loss: 1.0331 2022/08/30 10:26:13 - mmengine - INFO - Epoch(train) [390][55/63] lr: 4.9181e-03 eta: 22:17:42 time: 0.8008 data_time: 0.0344 memory: 16201 loss_prob: 0.5856 loss_thr: 0.3801 loss_db: 0.0974 loss: 1.0631 2022/08/30 10:26:17 - mmengine - INFO - Epoch(train) [390][60/63] lr: 4.9181e-03 eta: 22:17:11 time: 0.8139 data_time: 0.0376 memory: 16201 loss_prob: 0.5723 loss_thr: 0.3775 loss_db: 0.0960 loss: 1.0457 2022/08/30 10:26:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:26:25 - mmengine - INFO - Epoch(train) [391][5/63] lr: 4.9127e-03 eta: 22:17:11 time: 0.9207 data_time: 0.1969 memory: 16201 loss_prob: 0.5598 loss_thr: 0.3870 loss_db: 0.0974 loss: 1.0442 2022/08/30 10:26:29 - mmengine - INFO - Epoch(train) [391][10/63] lr: 4.9127e-03 eta: 22:16:28 time: 0.9669 data_time: 0.2088 memory: 16201 loss_prob: 0.6071 loss_thr: 0.4025 loss_db: 0.1016 loss: 1.1112 2022/08/30 10:26:33 - mmengine - INFO - Epoch(train) [391][15/63] lr: 4.9127e-03 eta: 22:16:28 time: 0.8180 data_time: 0.0330 memory: 16201 loss_prob: 0.6111 loss_thr: 0.4155 loss_db: 0.1028 loss: 1.1295 2022/08/30 10:26:37 - mmengine - INFO - Epoch(train) [391][20/63] lr: 4.9127e-03 eta: 22:15:57 time: 0.8218 data_time: 0.0288 memory: 16201 loss_prob: 0.5775 loss_thr: 0.4024 loss_db: 0.0996 loss: 1.0794 2022/08/30 10:26:41 - mmengine - INFO - Epoch(train) [391][25/63] lr: 4.9127e-03 eta: 22:15:57 time: 0.7910 data_time: 0.0362 memory: 16201 loss_prob: 0.6185 loss_thr: 0.4158 loss_db: 0.1091 loss: 1.1434 2022/08/30 10:26:46 - mmengine - INFO - Epoch(train) [391][30/63] lr: 4.9127e-03 eta: 22:15:27 time: 0.8971 data_time: 0.1581 memory: 16201 loss_prob: 0.6559 loss_thr: 0.4246 loss_db: 0.1151 loss: 1.1956 2022/08/30 10:26:51 - mmengine - INFO - Epoch(train) [391][35/63] lr: 4.9127e-03 eta: 22:15:27 time: 0.9810 data_time: 0.1680 memory: 16201 loss_prob: 0.6257 loss_thr: 0.3971 loss_db: 0.1073 loss: 1.1301 2022/08/30 10:26:55 - mmengine - INFO - Epoch(train) [391][40/63] lr: 4.9127e-03 eta: 22:14:57 time: 0.8674 data_time: 0.0395 memory: 16201 loss_prob: 0.5809 loss_thr: 0.3848 loss_db: 0.1000 loss: 1.0657 2022/08/30 10:26:59 - mmengine - INFO - Epoch(train) [391][45/63] lr: 4.9127e-03 eta: 22:14:57 time: 0.7898 data_time: 0.0228 memory: 16201 loss_prob: 0.5915 loss_thr: 0.4042 loss_db: 0.1013 loss: 1.0970 2022/08/30 10:27:03 - mmengine - INFO - Epoch(train) [391][50/63] lr: 4.9127e-03 eta: 22:14:25 time: 0.8040 data_time: 0.0261 memory: 16201 loss_prob: 0.5936 loss_thr: 0.4080 loss_db: 0.1014 loss: 1.1030 2022/08/30 10:27:07 - mmengine - INFO - Epoch(train) [391][55/63] lr: 4.9127e-03 eta: 22:14:25 time: 0.8142 data_time: 0.0289 memory: 16201 loss_prob: 0.5993 loss_thr: 0.3957 loss_db: 0.1003 loss: 1.0953 2022/08/30 10:27:11 - mmengine - INFO - Epoch(train) [391][60/63] lr: 4.9127e-03 eta: 22:13:53 time: 0.7928 data_time: 0.0304 memory: 16201 loss_prob: 0.6628 loss_thr: 0.4160 loss_db: 0.1130 loss: 1.1918 2022/08/30 10:27:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:27:18 - mmengine - INFO - Epoch(train) [392][5/63] lr: 4.9072e-03 eta: 22:13:53 time: 0.9314 data_time: 0.2051 memory: 16201 loss_prob: 0.6361 loss_thr: 0.4484 loss_db: 0.1103 loss: 1.1948 2022/08/30 10:27:22 - mmengine - INFO - Epoch(train) [392][10/63] lr: 4.9072e-03 eta: 22:13:11 time: 0.9781 data_time: 0.2164 memory: 16201 loss_prob: 0.6213 loss_thr: 0.4360 loss_db: 0.1080 loss: 1.1652 2022/08/30 10:27:26 - mmengine - INFO - Epoch(train) [392][15/63] lr: 4.9072e-03 eta: 22:13:11 time: 0.7758 data_time: 0.0231 memory: 16201 loss_prob: 0.6416 loss_thr: 0.4245 loss_db: 0.1116 loss: 1.1776 2022/08/30 10:27:30 - mmengine - INFO - Epoch(train) [392][20/63] lr: 4.9072e-03 eta: 22:12:39 time: 0.7780 data_time: 0.0195 memory: 16201 loss_prob: 0.6703 loss_thr: 0.4250 loss_db: 0.1149 loss: 1.2102 2022/08/30 10:27:35 - mmengine - INFO - Epoch(train) [392][25/63] lr: 4.9072e-03 eta: 22:12:39 time: 0.8468 data_time: 0.0423 memory: 16201 loss_prob: 0.6129 loss_thr: 0.3971 loss_db: 0.1057 loss: 1.1157 2022/08/30 10:27:39 - mmengine - INFO - Epoch(train) [392][30/63] lr: 4.9072e-03 eta: 22:12:08 time: 0.8410 data_time: 0.0415 memory: 16201 loss_prob: 0.6198 loss_thr: 0.3945 loss_db: 0.1066 loss: 1.1210 2022/08/30 10:27:42 - mmengine - INFO - Epoch(train) [392][35/63] lr: 4.9072e-03 eta: 22:12:08 time: 0.7815 data_time: 0.0234 memory: 16201 loss_prob: 0.6332 loss_thr: 0.4252 loss_db: 0.1093 loss: 1.1677 2022/08/30 10:27:47 - mmengine - INFO - Epoch(train) [392][40/63] lr: 4.9072e-03 eta: 22:11:37 time: 0.8015 data_time: 0.0319 memory: 16201 loss_prob: 0.6145 loss_thr: 0.4227 loss_db: 0.1062 loss: 1.1434 2022/08/30 10:27:51 - mmengine - INFO - Epoch(train) [392][45/63] lr: 4.9072e-03 eta: 22:11:37 time: 0.8123 data_time: 0.0414 memory: 16201 loss_prob: 0.6361 loss_thr: 0.4059 loss_db: 0.1096 loss: 1.1515 2022/08/30 10:27:54 - mmengine - INFO - Epoch(train) [392][50/63] lr: 4.9072e-03 eta: 22:11:05 time: 0.7882 data_time: 0.0339 memory: 16201 loss_prob: 0.6633 loss_thr: 0.4076 loss_db: 0.1133 loss: 1.1842 2022/08/30 10:27:58 - mmengine - INFO - Epoch(train) [392][55/63] lr: 4.9072e-03 eta: 22:11:05 time: 0.7776 data_time: 0.0255 memory: 16201 loss_prob: 0.6265 loss_thr: 0.4012 loss_db: 0.1062 loss: 1.1339 2022/08/30 10:28:03 - mmengine - INFO - Epoch(train) [392][60/63] lr: 4.9072e-03 eta: 22:10:34 time: 0.8302 data_time: 0.0289 memory: 16201 loss_prob: 0.6158 loss_thr: 0.4076 loss_db: 0.1063 loss: 1.1297 2022/08/30 10:28:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:28:10 - mmengine - INFO - Epoch(train) [393][5/63] lr: 4.9017e-03 eta: 22:10:34 time: 0.9231 data_time: 0.1976 memory: 16201 loss_prob: 0.6133 loss_thr: 0.3996 loss_db: 0.1049 loss: 1.1178 2022/08/30 10:28:14 - mmengine - INFO - Epoch(train) [393][10/63] lr: 4.9017e-03 eta: 22:09:52 time: 0.9744 data_time: 0.2060 memory: 16201 loss_prob: 0.5804 loss_thr: 0.3968 loss_db: 0.0978 loss: 1.0750 2022/08/30 10:28:18 - mmengine - INFO - Epoch(train) [393][15/63] lr: 4.9017e-03 eta: 22:09:52 time: 0.7981 data_time: 0.0269 memory: 16201 loss_prob: 0.6042 loss_thr: 0.3993 loss_db: 0.1069 loss: 1.1104 2022/08/30 10:28:23 - mmengine - INFO - Epoch(train) [393][20/63] lr: 4.9017e-03 eta: 22:09:21 time: 0.8615 data_time: 0.0190 memory: 16201 loss_prob: 0.5805 loss_thr: 0.3909 loss_db: 0.1043 loss: 1.0757 2022/08/30 10:28:27 - mmengine - INFO - Epoch(train) [393][25/63] lr: 4.9017e-03 eta: 22:09:21 time: 0.8725 data_time: 0.0332 memory: 16201 loss_prob: 0.6150 loss_thr: 0.4272 loss_db: 0.1035 loss: 1.1458 2022/08/30 10:28:31 - mmengine - INFO - Epoch(train) [393][30/63] lr: 4.9017e-03 eta: 22:08:50 time: 0.7874 data_time: 0.0238 memory: 16201 loss_prob: 0.6316 loss_thr: 0.4270 loss_db: 0.1047 loss: 1.1633 2022/08/30 10:28:35 - mmengine - INFO - Epoch(train) [393][35/63] lr: 4.9017e-03 eta: 22:08:50 time: 0.7816 data_time: 0.0204 memory: 16201 loss_prob: 0.6033 loss_thr: 0.4102 loss_db: 0.1056 loss: 1.1190 2022/08/30 10:28:39 - mmengine - INFO - Epoch(train) [393][40/63] lr: 4.9017e-03 eta: 22:08:18 time: 0.7876 data_time: 0.0268 memory: 16201 loss_prob: 0.6132 loss_thr: 0.4046 loss_db: 0.1060 loss: 1.1237 2022/08/30 10:28:43 - mmengine - INFO - Epoch(train) [393][45/63] lr: 4.9017e-03 eta: 22:08:18 time: 0.8019 data_time: 0.0245 memory: 16201 loss_prob: 0.6117 loss_thr: 0.3980 loss_db: 0.1036 loss: 1.1133 2022/08/30 10:28:47 - mmengine - INFO - Epoch(train) [393][50/63] lr: 4.9017e-03 eta: 22:07:47 time: 0.8095 data_time: 0.0291 memory: 16201 loss_prob: 0.6289 loss_thr: 0.4070 loss_db: 0.1103 loss: 1.1462 2022/08/30 10:28:51 - mmengine - INFO - Epoch(train) [393][55/63] lr: 4.9017e-03 eta: 22:07:47 time: 0.7907 data_time: 0.0240 memory: 16201 loss_prob: 0.6315 loss_thr: 0.4085 loss_db: 0.1098 loss: 1.1499 2022/08/30 10:28:55 - mmengine - INFO - Epoch(train) [393][60/63] lr: 4.9017e-03 eta: 22:07:16 time: 0.8261 data_time: 0.0211 memory: 16201 loss_prob: 0.6189 loss_thr: 0.4043 loss_db: 0.1047 loss: 1.1278 2022/08/30 10:28:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:29:03 - mmengine - INFO - Epoch(train) [394][5/63] lr: 4.8963e-03 eta: 22:07:16 time: 0.8957 data_time: 0.1721 memory: 16201 loss_prob: 0.6656 loss_thr: 0.4141 loss_db: 0.1151 loss: 1.1948 2022/08/30 10:29:07 - mmengine - INFO - Epoch(train) [394][10/63] lr: 4.8963e-03 eta: 22:06:33 time: 0.9488 data_time: 0.1860 memory: 16201 loss_prob: 0.6383 loss_thr: 0.4219 loss_db: 0.1113 loss: 1.1714 2022/08/30 10:29:11 - mmengine - INFO - Epoch(train) [394][15/63] lr: 4.8963e-03 eta: 22:06:33 time: 0.7959 data_time: 0.0279 memory: 16201 loss_prob: 0.6911 loss_thr: 0.4513 loss_db: 0.1205 loss: 1.2629 2022/08/30 10:29:15 - mmengine - INFO - Epoch(train) [394][20/63] lr: 4.8963e-03 eta: 22:06:02 time: 0.8210 data_time: 0.0202 memory: 16201 loss_prob: 0.6910 loss_thr: 0.4433 loss_db: 0.1187 loss: 1.2530 2022/08/30 10:29:19 - mmengine - INFO - Epoch(train) [394][25/63] lr: 4.8963e-03 eta: 22:06:02 time: 0.8271 data_time: 0.0348 memory: 16201 loss_prob: 0.6379 loss_thr: 0.4165 loss_db: 0.1072 loss: 1.1615 2022/08/30 10:29:23 - mmengine - INFO - Epoch(train) [394][30/63] lr: 4.8963e-03 eta: 22:05:31 time: 0.8028 data_time: 0.0296 memory: 16201 loss_prob: 0.6614 loss_thr: 0.4306 loss_db: 0.1119 loss: 1.2038 2022/08/30 10:29:27 - mmengine - INFO - Epoch(train) [394][35/63] lr: 4.8963e-03 eta: 22:05:31 time: 0.8107 data_time: 0.0272 memory: 16201 loss_prob: 0.6219 loss_thr: 0.4201 loss_db: 0.1078 loss: 1.1498 2022/08/30 10:29:31 - mmengine - INFO - Epoch(train) [394][40/63] lr: 4.8963e-03 eta: 22:05:00 time: 0.8266 data_time: 0.0469 memory: 16201 loss_prob: 0.5850 loss_thr: 0.3983 loss_db: 0.1019 loss: 1.0852 2022/08/30 10:29:35 - mmengine - INFO - Epoch(train) [394][45/63] lr: 4.8963e-03 eta: 22:05:00 time: 0.8132 data_time: 0.0426 memory: 16201 loss_prob: 0.6009 loss_thr: 0.3869 loss_db: 0.1021 loss: 1.0900 2022/08/30 10:29:39 - mmengine - INFO - Epoch(train) [394][50/63] lr: 4.8963e-03 eta: 22:04:29 time: 0.7881 data_time: 0.0294 memory: 16201 loss_prob: 0.6396 loss_thr: 0.4317 loss_db: 0.1086 loss: 1.1799 2022/08/30 10:29:43 - mmengine - INFO - Epoch(train) [394][55/63] lr: 4.8963e-03 eta: 22:04:29 time: 0.8081 data_time: 0.0380 memory: 16201 loss_prob: 0.6468 loss_thr: 0.4490 loss_db: 0.1095 loss: 1.2053 2022/08/30 10:29:47 - mmengine - INFO - Epoch(train) [394][60/63] lr: 4.8963e-03 eta: 22:03:58 time: 0.8144 data_time: 0.0404 memory: 16201 loss_prob: 0.6328 loss_thr: 0.4194 loss_db: 0.1096 loss: 1.1617 2022/08/30 10:29:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:29:55 - mmengine - INFO - Epoch(train) [395][5/63] lr: 4.8908e-03 eta: 22:03:58 time: 0.8992 data_time: 0.1708 memory: 16201 loss_prob: 0.6428 loss_thr: 0.4031 loss_db: 0.1117 loss: 1.1576 2022/08/30 10:29:59 - mmengine - INFO - Epoch(train) [395][10/63] lr: 4.8908e-03 eta: 22:03:15 time: 0.9634 data_time: 0.1895 memory: 16201 loss_prob: 0.6116 loss_thr: 0.4002 loss_db: 0.1079 loss: 1.1197 2022/08/30 10:30:03 - mmengine - INFO - Epoch(train) [395][15/63] lr: 4.8908e-03 eta: 22:03:15 time: 0.8138 data_time: 0.0374 memory: 16201 loss_prob: 0.5637 loss_thr: 0.4068 loss_db: 0.1002 loss: 1.0707 2022/08/30 10:30:07 - mmengine - INFO - Epoch(train) [395][20/63] lr: 4.8908e-03 eta: 22:02:44 time: 0.7851 data_time: 0.0270 memory: 16201 loss_prob: 0.5929 loss_thr: 0.4213 loss_db: 0.1035 loss: 1.1178 2022/08/30 10:30:11 - mmengine - INFO - Epoch(train) [395][25/63] lr: 4.8908e-03 eta: 22:02:44 time: 0.7800 data_time: 0.0342 memory: 16201 loss_prob: 0.5897 loss_thr: 0.3891 loss_db: 0.1005 loss: 1.0793 2022/08/30 10:30:15 - mmengine - INFO - Epoch(train) [395][30/63] lr: 4.8908e-03 eta: 22:02:12 time: 0.7882 data_time: 0.0340 memory: 16201 loss_prob: 0.6348 loss_thr: 0.4077 loss_db: 0.1082 loss: 1.1507 2022/08/30 10:30:18 - mmengine - INFO - Epoch(train) [395][35/63] lr: 4.8908e-03 eta: 22:02:12 time: 0.7814 data_time: 0.0266 memory: 16201 loss_prob: 0.6704 loss_thr: 0.4268 loss_db: 0.1141 loss: 1.2113 2022/08/30 10:30:23 - mmengine - INFO - Epoch(train) [395][40/63] lr: 4.8908e-03 eta: 22:01:42 time: 0.8208 data_time: 0.0361 memory: 16201 loss_prob: 0.6191 loss_thr: 0.4082 loss_db: 0.1042 loss: 1.1315 2022/08/30 10:30:27 - mmengine - INFO - Epoch(train) [395][45/63] lr: 4.8908e-03 eta: 22:01:42 time: 0.8411 data_time: 0.0429 memory: 16201 loss_prob: 0.6303 loss_thr: 0.4082 loss_db: 0.1057 loss: 1.1442 2022/08/30 10:30:31 - mmengine - INFO - Epoch(train) [395][50/63] lr: 4.8908e-03 eta: 22:01:10 time: 0.7970 data_time: 0.0264 memory: 16201 loss_prob: 0.6387 loss_thr: 0.3983 loss_db: 0.1100 loss: 1.1470 2022/08/30 10:30:35 - mmengine - INFO - Epoch(train) [395][55/63] lr: 4.8908e-03 eta: 22:01:10 time: 0.7894 data_time: 0.0290 memory: 16201 loss_prob: 0.5891 loss_thr: 0.3983 loss_db: 0.1015 loss: 1.0889 2022/08/30 10:30:39 - mmengine - INFO - Epoch(train) [395][60/63] lr: 4.8908e-03 eta: 22:00:39 time: 0.8036 data_time: 0.0339 memory: 16201 loss_prob: 0.5809 loss_thr: 0.3984 loss_db: 0.0971 loss: 1.0764 2022/08/30 10:30:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:30:46 - mmengine - INFO - Epoch(train) [396][5/63] lr: 4.8853e-03 eta: 22:00:39 time: 0.9274 data_time: 0.1685 memory: 16201 loss_prob: 0.5588 loss_thr: 0.3921 loss_db: 0.0962 loss: 1.0471 2022/08/30 10:30:50 - mmengine - INFO - Epoch(train) [396][10/63] lr: 4.8853e-03 eta: 21:59:57 time: 0.9487 data_time: 0.1786 memory: 16201 loss_prob: 0.5449 loss_thr: 0.3841 loss_db: 0.0954 loss: 1.0244 2022/08/30 10:30:55 - mmengine - INFO - Epoch(train) [396][15/63] lr: 4.8853e-03 eta: 21:59:57 time: 0.8032 data_time: 0.0293 memory: 16201 loss_prob: 0.5587 loss_thr: 0.3950 loss_db: 0.0955 loss: 1.0491 2022/08/30 10:30:58 - mmengine - INFO - Epoch(train) [396][20/63] lr: 4.8853e-03 eta: 21:59:25 time: 0.7820 data_time: 0.0193 memory: 16201 loss_prob: 0.5552 loss_thr: 0.4016 loss_db: 0.0975 loss: 1.0544 2022/08/30 10:31:02 - mmengine - INFO - Epoch(train) [396][25/63] lr: 4.8853e-03 eta: 21:59:25 time: 0.7962 data_time: 0.0311 memory: 16201 loss_prob: 0.6039 loss_thr: 0.4002 loss_db: 0.1057 loss: 1.1098 2022/08/30 10:31:06 - mmengine - INFO - Epoch(train) [396][30/63] lr: 4.8853e-03 eta: 21:58:55 time: 0.8202 data_time: 0.0363 memory: 16201 loss_prob: 0.6628 loss_thr: 0.4183 loss_db: 0.1103 loss: 1.1915 2022/08/30 10:31:10 - mmengine - INFO - Epoch(train) [396][35/63] lr: 4.8853e-03 eta: 21:58:55 time: 0.7869 data_time: 0.0226 memory: 16201 loss_prob: 0.6448 loss_thr: 0.4184 loss_db: 0.1099 loss: 1.1732 2022/08/30 10:31:15 - mmengine - INFO - Epoch(train) [396][40/63] lr: 4.8853e-03 eta: 21:58:24 time: 0.8230 data_time: 0.0311 memory: 16201 loss_prob: 0.5803 loss_thr: 0.3815 loss_db: 0.1021 loss: 1.0639 2022/08/30 10:31:19 - mmengine - INFO - Epoch(train) [396][45/63] lr: 4.8853e-03 eta: 21:58:24 time: 0.8464 data_time: 0.0410 memory: 16201 loss_prob: 0.5619 loss_thr: 0.3744 loss_db: 0.0968 loss: 1.0331 2022/08/30 10:31:23 - mmengine - INFO - Epoch(train) [396][50/63] lr: 4.8853e-03 eta: 21:57:53 time: 0.8053 data_time: 0.0265 memory: 16201 loss_prob: 0.5752 loss_thr: 0.3806 loss_db: 0.0986 loss: 1.0545 2022/08/30 10:31:27 - mmengine - INFO - Epoch(train) [396][55/63] lr: 4.8853e-03 eta: 21:57:53 time: 0.7915 data_time: 0.0340 memory: 16201 loss_prob: 0.5913 loss_thr: 0.3889 loss_db: 0.1021 loss: 1.0823 2022/08/30 10:31:31 - mmengine - INFO - Epoch(train) [396][60/63] lr: 4.8853e-03 eta: 21:57:22 time: 0.7935 data_time: 0.0387 memory: 16201 loss_prob: 0.6420 loss_thr: 0.4227 loss_db: 0.1114 loss: 1.1762 2022/08/30 10:31:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:31:38 - mmengine - INFO - Epoch(train) [397][5/63] lr: 4.8799e-03 eta: 21:57:22 time: 0.9183 data_time: 0.1838 memory: 16201 loss_prob: 0.5682 loss_thr: 0.3927 loss_db: 0.0994 loss: 1.0602 2022/08/30 10:31:42 - mmengine - INFO - Epoch(train) [397][10/63] lr: 4.8799e-03 eta: 21:56:40 time: 0.9600 data_time: 0.1925 memory: 16201 loss_prob: 0.5851 loss_thr: 0.3988 loss_db: 0.1014 loss: 1.0853 2022/08/30 10:31:46 - mmengine - INFO - Epoch(train) [397][15/63] lr: 4.8799e-03 eta: 21:56:40 time: 0.7997 data_time: 0.0360 memory: 16201 loss_prob: 0.6154 loss_thr: 0.4127 loss_db: 0.1079 loss: 1.1360 2022/08/30 10:31:50 - mmengine - INFO - Epoch(train) [397][20/63] lr: 4.8799e-03 eta: 21:56:09 time: 0.7895 data_time: 0.0280 memory: 16201 loss_prob: 0.5956 loss_thr: 0.3922 loss_db: 0.1052 loss: 1.0930 2022/08/30 10:31:55 - mmengine - INFO - Epoch(train) [397][25/63] lr: 4.8799e-03 eta: 21:56:09 time: 0.8782 data_time: 0.0454 memory: 16201 loss_prob: 0.5933 loss_thr: 0.3799 loss_db: 0.0991 loss: 1.0723 2022/08/30 10:31:59 - mmengine - INFO - Epoch(train) [397][30/63] lr: 4.8799e-03 eta: 21:55:39 time: 0.8769 data_time: 0.0439 memory: 16201 loss_prob: 0.6745 loss_thr: 0.4095 loss_db: 0.1101 loss: 1.1942 2022/08/30 10:32:03 - mmengine - INFO - Epoch(train) [397][35/63] lr: 4.8799e-03 eta: 21:55:39 time: 0.7808 data_time: 0.0248 memory: 16201 loss_prob: 0.7003 loss_thr: 0.4278 loss_db: 0.1173 loss: 1.2453 2022/08/30 10:32:07 - mmengine - INFO - Epoch(train) [397][40/63] lr: 4.8799e-03 eta: 21:55:08 time: 0.7870 data_time: 0.0235 memory: 16201 loss_prob: 0.6571 loss_thr: 0.4052 loss_db: 0.1098 loss: 1.1721 2022/08/30 10:32:11 - mmengine - INFO - Epoch(train) [397][45/63] lr: 4.8799e-03 eta: 21:55:08 time: 0.8115 data_time: 0.0300 memory: 16201 loss_prob: 0.6144 loss_thr: 0.3858 loss_db: 0.1031 loss: 1.1033 2022/08/30 10:32:15 - mmengine - INFO - Epoch(train) [397][50/63] lr: 4.8799e-03 eta: 21:54:38 time: 0.8249 data_time: 0.0379 memory: 16201 loss_prob: 0.6086 loss_thr: 0.4092 loss_db: 0.1055 loss: 1.1233 2022/08/30 10:32:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:32:19 - mmengine - INFO - Epoch(train) [397][55/63] lr: 4.8799e-03 eta: 21:54:38 time: 0.8031 data_time: 0.0263 memory: 16201 loss_prob: 0.5672 loss_thr: 0.3965 loss_db: 0.0967 loss: 1.0604 2022/08/30 10:32:23 - mmengine - INFO - Epoch(train) [397][60/63] lr: 4.8799e-03 eta: 21:54:06 time: 0.7706 data_time: 0.0208 memory: 16201 loss_prob: 0.5794 loss_thr: 0.3930 loss_db: 0.0968 loss: 1.0691 2022/08/30 10:32:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:32:30 - mmengine - INFO - Epoch(train) [398][5/63] lr: 4.8744e-03 eta: 21:54:06 time: 0.8555 data_time: 0.1517 memory: 16201 loss_prob: 0.5923 loss_thr: 0.3964 loss_db: 0.1004 loss: 1.0891 2022/08/30 10:32:34 - mmengine - INFO - Epoch(train) [398][10/63] lr: 4.8744e-03 eta: 21:53:24 time: 0.9374 data_time: 0.1759 memory: 16201 loss_prob: 0.5388 loss_thr: 0.3790 loss_db: 0.0921 loss: 1.0100 2022/08/30 10:32:38 - mmengine - INFO - Epoch(train) [398][15/63] lr: 4.8744e-03 eta: 21:53:24 time: 0.7937 data_time: 0.0366 memory: 16201 loss_prob: 0.5591 loss_thr: 0.3905 loss_db: 0.0938 loss: 1.0433 2022/08/30 10:32:42 - mmengine - INFO - Epoch(train) [398][20/63] lr: 4.8744e-03 eta: 21:52:52 time: 0.7815 data_time: 0.0164 memory: 16201 loss_prob: 0.5662 loss_thr: 0.3848 loss_db: 0.0954 loss: 1.0463 2022/08/30 10:32:46 - mmengine - INFO - Epoch(train) [398][25/63] lr: 4.8744e-03 eta: 21:52:52 time: 0.8336 data_time: 0.0359 memory: 16201 loss_prob: 0.5679 loss_thr: 0.3891 loss_db: 0.0976 loss: 1.0547 2022/08/30 10:32:50 - mmengine - INFO - Epoch(train) [398][30/63] lr: 4.8744e-03 eta: 21:52:22 time: 0.8123 data_time: 0.0288 memory: 16201 loss_prob: 0.5731 loss_thr: 0.4012 loss_db: 0.1005 loss: 1.0748 2022/08/30 10:32:54 - mmengine - INFO - Epoch(train) [398][35/63] lr: 4.8744e-03 eta: 21:52:22 time: 0.7848 data_time: 0.0216 memory: 16201 loss_prob: 0.5728 loss_thr: 0.4015 loss_db: 0.0996 loss: 1.0739 2022/08/30 10:32:58 - mmengine - INFO - Epoch(train) [398][40/63] lr: 4.8744e-03 eta: 21:51:51 time: 0.7985 data_time: 0.0358 memory: 16201 loss_prob: 0.5988 loss_thr: 0.4078 loss_db: 0.1044 loss: 1.1110 2022/08/30 10:33:02 - mmengine - INFO - Epoch(train) [398][45/63] lr: 4.8744e-03 eta: 21:51:51 time: 0.8081 data_time: 0.0316 memory: 16201 loss_prob: 0.6052 loss_thr: 0.3996 loss_db: 0.1047 loss: 1.1096 2022/08/30 10:33:06 - mmengine - INFO - Epoch(train) [398][50/63] lr: 4.8744e-03 eta: 21:51:20 time: 0.7944 data_time: 0.0249 memory: 16201 loss_prob: 0.6853 loss_thr: 0.4068 loss_db: 0.1137 loss: 1.2058 2022/08/30 10:33:10 - mmengine - INFO - Epoch(train) [398][55/63] lr: 4.8744e-03 eta: 21:51:20 time: 0.7829 data_time: 0.0250 memory: 16201 loss_prob: 0.6841 loss_thr: 0.4022 loss_db: 0.1124 loss: 1.1986 2022/08/30 10:33:14 - mmengine - INFO - Epoch(train) [398][60/63] lr: 4.8744e-03 eta: 21:50:50 time: 0.8331 data_time: 0.0305 memory: 16201 loss_prob: 0.6171 loss_thr: 0.4001 loss_db: 0.1032 loss: 1.1204 2022/08/30 10:33:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:33:22 - mmengine - INFO - Epoch(train) [399][5/63] lr: 4.8689e-03 eta: 21:50:50 time: 0.9212 data_time: 0.1574 memory: 16201 loss_prob: 0.5826 loss_thr: 0.4010 loss_db: 0.1012 loss: 1.0849 2022/08/30 10:33:26 - mmengine - INFO - Epoch(train) [399][10/63] lr: 4.8689e-03 eta: 21:50:08 time: 0.9393 data_time: 0.1652 memory: 16201 loss_prob: 0.5683 loss_thr: 0.3803 loss_db: 0.0992 loss: 1.0477 2022/08/30 10:33:30 - mmengine - INFO - Epoch(train) [399][15/63] lr: 4.8689e-03 eta: 21:50:08 time: 0.7794 data_time: 0.0233 memory: 16201 loss_prob: 0.5968 loss_thr: 0.4028 loss_db: 0.1028 loss: 1.1024 2022/08/30 10:33:34 - mmengine - INFO - Epoch(train) [399][20/63] lr: 4.8689e-03 eta: 21:49:37 time: 0.8038 data_time: 0.0247 memory: 16201 loss_prob: 0.6562 loss_thr: 0.4368 loss_db: 0.1082 loss: 1.2012 2022/08/30 10:33:38 - mmengine - INFO - Epoch(train) [399][25/63] lr: 4.8689e-03 eta: 21:49:37 time: 0.8083 data_time: 0.0327 memory: 16201 loss_prob: 0.6211 loss_thr: 0.4238 loss_db: 0.1043 loss: 1.1491 2022/08/30 10:33:42 - mmengine - INFO - Epoch(train) [399][30/63] lr: 4.8689e-03 eta: 21:49:06 time: 0.7980 data_time: 0.0312 memory: 16201 loss_prob: 0.5594 loss_thr: 0.3866 loss_db: 0.0992 loss: 1.0452 2022/08/30 10:33:46 - mmengine - INFO - Epoch(train) [399][35/63] lr: 4.8689e-03 eta: 21:49:06 time: 0.8007 data_time: 0.0379 memory: 16201 loss_prob: 0.5564 loss_thr: 0.3796 loss_db: 0.0966 loss: 1.0326 2022/08/30 10:33:50 - mmengine - INFO - Epoch(train) [399][40/63] lr: 4.8689e-03 eta: 21:48:35 time: 0.7926 data_time: 0.0380 memory: 16201 loss_prob: 0.5827 loss_thr: 0.4020 loss_db: 0.0994 loss: 1.0841 2022/08/30 10:33:54 - mmengine - INFO - Epoch(train) [399][45/63] lr: 4.8689e-03 eta: 21:48:35 time: 0.8340 data_time: 0.0281 memory: 16201 loss_prob: 0.6020 loss_thr: 0.4005 loss_db: 0.1032 loss: 1.1058 2022/08/30 10:33:58 - mmengine - INFO - Epoch(train) [399][50/63] lr: 4.8689e-03 eta: 21:48:06 time: 0.8468 data_time: 0.0261 memory: 16201 loss_prob: 0.5567 loss_thr: 0.3767 loss_db: 0.0956 loss: 1.0289 2022/08/30 10:34:02 - mmengine - INFO - Epoch(train) [399][55/63] lr: 4.8689e-03 eta: 21:48:06 time: 0.8082 data_time: 0.0352 memory: 16201 loss_prob: 0.5616 loss_thr: 0.3824 loss_db: 0.0959 loss: 1.0399 2022/08/30 10:34:06 - mmengine - INFO - Epoch(train) [399][60/63] lr: 4.8689e-03 eta: 21:47:35 time: 0.7921 data_time: 0.0388 memory: 16201 loss_prob: 0.6316 loss_thr: 0.4200 loss_db: 0.1077 loss: 1.1593 2022/08/30 10:34:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:34:14 - mmengine - INFO - Epoch(train) [400][5/63] lr: 4.8635e-03 eta: 21:47:35 time: 0.9168 data_time: 0.1948 memory: 16201 loss_prob: 0.6244 loss_thr: 0.4267 loss_db: 0.1084 loss: 1.1594 2022/08/30 10:34:18 - mmengine - INFO - Epoch(train) [400][10/63] lr: 4.8635e-03 eta: 21:46:54 time: 0.9824 data_time: 0.2116 memory: 16201 loss_prob: 0.6039 loss_thr: 0.4186 loss_db: 0.1052 loss: 1.1277 2022/08/30 10:34:22 - mmengine - INFO - Epoch(train) [400][15/63] lr: 4.8635e-03 eta: 21:46:54 time: 0.8134 data_time: 0.0415 memory: 16201 loss_prob: 0.6073 loss_thr: 0.4143 loss_db: 0.1039 loss: 1.1254 2022/08/30 10:34:26 - mmengine - INFO - Epoch(train) [400][20/63] lr: 4.8635e-03 eta: 21:46:23 time: 0.8151 data_time: 0.0364 memory: 16201 loss_prob: 0.6035 loss_thr: 0.4114 loss_db: 0.1051 loss: 1.1199 2022/08/30 10:34:30 - mmengine - INFO - Epoch(train) [400][25/63] lr: 4.8635e-03 eta: 21:46:23 time: 0.8193 data_time: 0.0469 memory: 16201 loss_prob: 0.6314 loss_thr: 0.4195 loss_db: 0.1108 loss: 1.1617 2022/08/30 10:34:34 - mmengine - INFO - Epoch(train) [400][30/63] lr: 4.8635e-03 eta: 21:45:53 time: 0.8128 data_time: 0.0338 memory: 16201 loss_prob: 0.6076 loss_thr: 0.4041 loss_db: 0.1046 loss: 1.1163 2022/08/30 10:34:38 - mmengine - INFO - Epoch(train) [400][35/63] lr: 4.8635e-03 eta: 21:45:53 time: 0.8119 data_time: 0.0315 memory: 16201 loss_prob: 0.5194 loss_thr: 0.3648 loss_db: 0.0893 loss: 0.9734 2022/08/30 10:34:43 - mmengine - INFO - Epoch(train) [400][40/63] lr: 4.8635e-03 eta: 21:45:23 time: 0.8399 data_time: 0.0510 memory: 16201 loss_prob: 0.6040 loss_thr: 0.4060 loss_db: 0.1053 loss: 1.1152 2022/08/30 10:34:47 - mmengine - INFO - Epoch(train) [400][45/63] lr: 4.8635e-03 eta: 21:45:23 time: 0.8812 data_time: 0.0894 memory: 16201 loss_prob: 0.6553 loss_thr: 0.4427 loss_db: 0.1134 loss: 1.2114 2022/08/30 10:34:51 - mmengine - INFO - Epoch(train) [400][50/63] lr: 4.8635e-03 eta: 21:44:53 time: 0.8372 data_time: 0.0725 memory: 16201 loss_prob: 0.6031 loss_thr: 0.4036 loss_db: 0.1019 loss: 1.1085 2022/08/30 10:34:55 - mmengine - INFO - Epoch(train) [400][55/63] lr: 4.8635e-03 eta: 21:44:53 time: 0.7918 data_time: 0.0301 memory: 16201 loss_prob: 0.5819 loss_thr: 0.3719 loss_db: 0.0976 loss: 1.0515 2022/08/30 10:34:59 - mmengine - INFO - Epoch(train) [400][60/63] lr: 4.8635e-03 eta: 21:44:22 time: 0.7905 data_time: 0.0262 memory: 16201 loss_prob: 0.6109 loss_thr: 0.3935 loss_db: 0.1011 loss: 1.1056 2022/08/30 10:35:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:35:01 - mmengine - INFO - Saving checkpoint at 400 epochs 2022/08/30 10:35:10 - mmengine - INFO - Epoch(val) [400][5/32] eta: 21:44:22 time: 0.6554 data_time: 0.1226 memory: 16201 2022/08/30 10:35:13 - mmengine - INFO - Epoch(val) [400][10/32] eta: 0:00:15 time: 0.7219 data_time: 0.1337 memory: 15734 2022/08/30 10:35:16 - mmengine - INFO - Epoch(val) [400][15/32] eta: 0:00:15 time: 0.6008 data_time: 0.0448 memory: 15734 2022/08/30 10:35:19 - mmengine - INFO - Epoch(val) [400][20/32] eta: 0:00:07 time: 0.6237 data_time: 0.0669 memory: 15734 2022/08/30 10:35:22 - mmengine - INFO - Epoch(val) [400][25/32] eta: 0:00:07 time: 0.6685 data_time: 0.0530 memory: 15734 2022/08/30 10:35:25 - mmengine - INFO - Epoch(val) [400][30/32] eta: 0:00:01 time: 0.6292 data_time: 0.0261 memory: 15734 2022/08/30 10:35:26 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 10:35:26 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8613, precision: 0.7632, hmean: 0.8093 2022/08/30 10:35:26 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8613, precision: 0.8128, hmean: 0.8364 2022/08/30 10:35:26 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8599, precision: 0.8405, hmean: 0.8501 2022/08/30 10:35:26 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8546, precision: 0.8617, hmean: 0.8581 2022/08/30 10:35:26 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8387, precision: 0.8897, hmean: 0.8634 2022/08/30 10:35:26 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7342, precision: 0.9265, hmean: 0.8192 2022/08/30 10:35:26 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1151, precision: 0.9755, hmean: 0.2059 2022/08/30 10:35:26 - mmengine - INFO - Epoch(val) [400][32/32] icdar/precision: 0.8897 icdar/recall: 0.8387 icdar/hmean: 0.8634 2022/08/30 10:35:32 - mmengine - INFO - Epoch(train) [401][5/63] lr: 4.8580e-03 eta: 0:00:01 time: 0.9019 data_time: 0.1688 memory: 16201 loss_prob: 0.6228 loss_thr: 0.4132 loss_db: 0.1061 loss: 1.1422 2022/08/30 10:35:36 - mmengine - INFO - Epoch(train) [401][10/63] lr: 4.8580e-03 eta: 21:43:41 time: 0.9629 data_time: 0.1715 memory: 16201 loss_prob: 0.6553 loss_thr: 0.4286 loss_db: 0.1126 loss: 1.1965 2022/08/30 10:35:40 - mmengine - INFO - Epoch(train) [401][15/63] lr: 4.8580e-03 eta: 21:43:41 time: 0.8073 data_time: 0.0206 memory: 16201 loss_prob: 0.6695 loss_thr: 0.4140 loss_db: 0.1121 loss: 1.1956 2022/08/30 10:35:44 - mmengine - INFO - Epoch(train) [401][20/63] lr: 4.8580e-03 eta: 21:43:11 time: 0.8166 data_time: 0.0361 memory: 16201 loss_prob: 0.6331 loss_thr: 0.4058 loss_db: 0.1061 loss: 1.1450 2022/08/30 10:35:48 - mmengine - INFO - Epoch(train) [401][25/63] lr: 4.8580e-03 eta: 21:43:11 time: 0.8048 data_time: 0.0360 memory: 16201 loss_prob: 0.5364 loss_thr: 0.3659 loss_db: 0.0944 loss: 0.9967 2022/08/30 10:35:52 - mmengine - INFO - Epoch(train) [401][30/63] lr: 4.8580e-03 eta: 21:42:40 time: 0.8024 data_time: 0.0218 memory: 16201 loss_prob: 0.5376 loss_thr: 0.3476 loss_db: 0.0920 loss: 0.9772 2022/08/30 10:35:56 - mmengine - INFO - Epoch(train) [401][35/63] lr: 4.8580e-03 eta: 21:42:40 time: 0.8005 data_time: 0.0322 memory: 16201 loss_prob: 0.6110 loss_thr: 0.3997 loss_db: 0.1051 loss: 1.1158 2022/08/30 10:36:00 - mmengine - INFO - Epoch(train) [401][40/63] lr: 4.8580e-03 eta: 21:42:09 time: 0.7776 data_time: 0.0324 memory: 16201 loss_prob: 0.6014 loss_thr: 0.4103 loss_db: 0.1044 loss: 1.1162 2022/08/30 10:36:04 - mmengine - INFO - Epoch(train) [401][45/63] lr: 4.8580e-03 eta: 21:42:09 time: 0.7917 data_time: 0.0310 memory: 16201 loss_prob: 0.6544 loss_thr: 0.4420 loss_db: 0.1100 loss: 1.2064 2022/08/30 10:36:08 - mmengine - INFO - Epoch(train) [401][50/63] lr: 4.8580e-03 eta: 21:41:39 time: 0.8002 data_time: 0.0439 memory: 16201 loss_prob: 0.6573 loss_thr: 0.4420 loss_db: 0.1130 loss: 1.2123 2022/08/30 10:36:12 - mmengine - INFO - Epoch(train) [401][55/63] lr: 4.8580e-03 eta: 21:41:39 time: 0.7947 data_time: 0.0345 memory: 16201 loss_prob: 0.6088 loss_thr: 0.4148 loss_db: 0.1078 loss: 1.1313 2022/08/30 10:36:16 - mmengine - INFO - Epoch(train) [401][60/63] lr: 4.8580e-03 eta: 21:41:09 time: 0.8291 data_time: 0.0262 memory: 16201 loss_prob: 0.5991 loss_thr: 0.4118 loss_db: 0.1065 loss: 1.1173 2022/08/30 10:36:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:36:23 - mmengine - INFO - Epoch(train) [402][5/63] lr: 4.8525e-03 eta: 21:41:09 time: 0.9248 data_time: 0.1923 memory: 16201 loss_prob: 0.6083 loss_thr: 0.3999 loss_db: 0.1028 loss: 1.1109 2022/08/30 10:36:27 - mmengine - INFO - Epoch(train) [402][10/63] lr: 4.8525e-03 eta: 21:40:28 time: 0.9441 data_time: 0.1844 memory: 16201 loss_prob: 0.5631 loss_thr: 0.3808 loss_db: 0.0979 loss: 1.0419 2022/08/30 10:36:32 - mmengine - INFO - Epoch(train) [402][15/63] lr: 4.8525e-03 eta: 21:40:28 time: 0.8233 data_time: 0.0280 memory: 16201 loss_prob: 0.5650 loss_thr: 0.3931 loss_db: 0.0987 loss: 1.0568 2022/08/30 10:36:36 - mmengine - INFO - Epoch(train) [402][20/63] lr: 4.8525e-03 eta: 21:39:58 time: 0.8380 data_time: 0.0258 memory: 16201 loss_prob: 0.5612 loss_thr: 0.3887 loss_db: 0.0963 loss: 1.0463 2022/08/30 10:36:40 - mmengine - INFO - Epoch(train) [402][25/63] lr: 4.8525e-03 eta: 21:39:58 time: 0.8166 data_time: 0.0295 memory: 16201 loss_prob: 0.5535 loss_thr: 0.3741 loss_db: 0.0930 loss: 1.0205 2022/08/30 10:36:44 - mmengine - INFO - Epoch(train) [402][30/63] lr: 4.8525e-03 eta: 21:39:27 time: 0.8004 data_time: 0.0368 memory: 16201 loss_prob: 0.5885 loss_thr: 0.3916 loss_db: 0.0994 loss: 1.0796 2022/08/30 10:36:48 - mmengine - INFO - Epoch(train) [402][35/63] lr: 4.8525e-03 eta: 21:39:27 time: 0.7885 data_time: 0.0367 memory: 16201 loss_prob: 0.5757 loss_thr: 0.3944 loss_db: 0.0997 loss: 1.0699 2022/08/30 10:36:52 - mmengine - INFO - Epoch(train) [402][40/63] lr: 4.8525e-03 eta: 21:38:58 time: 0.8369 data_time: 0.0237 memory: 16201 loss_prob: 0.5665 loss_thr: 0.3904 loss_db: 0.0967 loss: 1.0536 2022/08/30 10:36:56 - mmengine - INFO - Epoch(train) [402][45/63] lr: 4.8525e-03 eta: 21:38:58 time: 0.8581 data_time: 0.0381 memory: 16201 loss_prob: 0.5764 loss_thr: 0.3925 loss_db: 0.1002 loss: 1.0690 2022/08/30 10:37:00 - mmengine - INFO - Epoch(train) [402][50/63] lr: 4.8525e-03 eta: 21:38:27 time: 0.8007 data_time: 0.0451 memory: 16201 loss_prob: 0.5651 loss_thr: 0.3867 loss_db: 0.0997 loss: 1.0515 2022/08/30 10:37:04 - mmengine - INFO - Epoch(train) [402][55/63] lr: 4.8525e-03 eta: 21:38:27 time: 0.7676 data_time: 0.0239 memory: 16201 loss_prob: 0.5604 loss_thr: 0.3755 loss_db: 0.0953 loss: 1.0311 2022/08/30 10:37:08 - mmengine - INFO - Epoch(train) [402][60/63] lr: 4.8525e-03 eta: 21:37:57 time: 0.7853 data_time: 0.0402 memory: 16201 loss_prob: 0.5718 loss_thr: 0.3762 loss_db: 0.0993 loss: 1.0473 2022/08/30 10:37:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:37:16 - mmengine - INFO - Epoch(train) [403][5/63] lr: 4.8470e-03 eta: 21:37:57 time: 0.8999 data_time: 0.1714 memory: 16201 loss_prob: 0.5649 loss_thr: 0.3871 loss_db: 0.0959 loss: 1.0479 2022/08/30 10:37:20 - mmengine - INFO - Epoch(train) [403][10/63] lr: 4.8470e-03 eta: 21:37:16 time: 0.9760 data_time: 0.1961 memory: 16201 loss_prob: 0.5575 loss_thr: 0.3982 loss_db: 0.0962 loss: 1.0519 2022/08/30 10:37:24 - mmengine - INFO - Epoch(train) [403][15/63] lr: 4.8470e-03 eta: 21:37:16 time: 0.8307 data_time: 0.0391 memory: 16201 loss_prob: 0.5803 loss_thr: 0.4034 loss_db: 0.1004 loss: 1.0841 2022/08/30 10:37:28 - mmengine - INFO - Epoch(train) [403][20/63] lr: 4.8470e-03 eta: 21:36:46 time: 0.8087 data_time: 0.0215 memory: 16201 loss_prob: 0.6212 loss_thr: 0.4144 loss_db: 0.1065 loss: 1.1422 2022/08/30 10:37:32 - mmengine - INFO - Epoch(train) [403][25/63] lr: 4.8470e-03 eta: 21:36:46 time: 0.8023 data_time: 0.0381 memory: 16201 loss_prob: 0.6147 loss_thr: 0.4087 loss_db: 0.1047 loss: 1.1281 2022/08/30 10:37:36 - mmengine - INFO - Epoch(train) [403][30/63] lr: 4.8470e-03 eta: 21:36:16 time: 0.8026 data_time: 0.0352 memory: 16201 loss_prob: 0.5551 loss_thr: 0.3796 loss_db: 0.0958 loss: 1.0305 2022/08/30 10:37:40 - mmengine - INFO - Epoch(train) [403][35/63] lr: 4.8470e-03 eta: 21:36:16 time: 0.8214 data_time: 0.0509 memory: 16201 loss_prob: 0.5918 loss_thr: 0.4018 loss_db: 0.1037 loss: 1.0973 2022/08/30 10:37:44 - mmengine - INFO - Epoch(train) [403][40/63] lr: 4.8470e-03 eta: 21:35:46 time: 0.8255 data_time: 0.0545 memory: 16201 loss_prob: 0.6417 loss_thr: 0.4429 loss_db: 0.1106 loss: 1.1952 2022/08/30 10:37:48 - mmengine - INFO - Epoch(train) [403][45/63] lr: 4.8470e-03 eta: 21:35:46 time: 0.7926 data_time: 0.0274 memory: 16201 loss_prob: 0.6257 loss_thr: 0.4207 loss_db: 0.1071 loss: 1.1535 2022/08/30 10:37:52 - mmengine - INFO - Epoch(train) [403][50/63] lr: 4.8470e-03 eta: 21:35:16 time: 0.8032 data_time: 0.0237 memory: 16201 loss_prob: 0.6450 loss_thr: 0.3892 loss_db: 0.1069 loss: 1.1411 2022/08/30 10:37:56 - mmengine - INFO - Epoch(train) [403][55/63] lr: 4.8470e-03 eta: 21:35:16 time: 0.7991 data_time: 0.0282 memory: 16201 loss_prob: 0.6216 loss_thr: 0.3860 loss_db: 0.1022 loss: 1.1097 2022/08/30 10:38:00 - mmengine - INFO - Epoch(train) [403][60/63] lr: 4.8470e-03 eta: 21:34:45 time: 0.7763 data_time: 0.0260 memory: 16201 loss_prob: 0.5825 loss_thr: 0.3912 loss_db: 0.0987 loss: 1.0724 2022/08/30 10:38:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:38:08 - mmengine - INFO - Epoch(train) [404][5/63] lr: 4.8416e-03 eta: 21:34:45 time: 0.9340 data_time: 0.1707 memory: 16201 loss_prob: 0.6434 loss_thr: 0.4301 loss_db: 0.1094 loss: 1.1830 2022/08/30 10:38:12 - mmengine - INFO - Epoch(train) [404][10/63] lr: 4.8416e-03 eta: 21:34:04 time: 0.9777 data_time: 0.2076 memory: 16201 loss_prob: 0.5871 loss_thr: 0.3832 loss_db: 0.1042 loss: 1.0745 2022/08/30 10:38:16 - mmengine - INFO - Epoch(train) [404][15/63] lr: 4.8416e-03 eta: 21:34:04 time: 0.8229 data_time: 0.0519 memory: 16201 loss_prob: 0.5273 loss_thr: 0.3560 loss_db: 0.0923 loss: 0.9756 2022/08/30 10:38:20 - mmengine - INFO - Epoch(train) [404][20/63] lr: 4.8416e-03 eta: 21:33:34 time: 0.8032 data_time: 0.0292 memory: 16201 loss_prob: 0.5566 loss_thr: 0.3895 loss_db: 0.0961 loss: 1.0422 2022/08/30 10:38:24 - mmengine - INFO - Epoch(train) [404][25/63] lr: 4.8416e-03 eta: 21:33:34 time: 0.8325 data_time: 0.0512 memory: 16201 loss_prob: 0.6514 loss_thr: 0.4225 loss_db: 0.1127 loss: 1.1866 2022/08/30 10:38:28 - mmengine - INFO - Epoch(train) [404][30/63] lr: 4.8416e-03 eta: 21:33:04 time: 0.8044 data_time: 0.0345 memory: 16201 loss_prob: 0.7371 loss_thr: 0.4347 loss_db: 0.1269 loss: 1.2987 2022/08/30 10:38:32 - mmengine - INFO - Epoch(train) [404][35/63] lr: 4.8416e-03 eta: 21:33:04 time: 0.7828 data_time: 0.0204 memory: 16201 loss_prob: 0.6872 loss_thr: 0.4160 loss_db: 0.1186 loss: 1.2218 2022/08/30 10:38:36 - mmengine - INFO - Epoch(train) [404][40/63] lr: 4.8416e-03 eta: 21:32:34 time: 0.8004 data_time: 0.0298 memory: 16201 loss_prob: 0.6705 loss_thr: 0.4340 loss_db: 0.1140 loss: 1.2185 2022/08/30 10:38:40 - mmengine - INFO - Epoch(train) [404][45/63] lr: 4.8416e-03 eta: 21:32:34 time: 0.7961 data_time: 0.0264 memory: 16201 loss_prob: 0.6140 loss_thr: 0.4008 loss_db: 0.1039 loss: 1.1187 2022/08/30 10:38:45 - mmengine - INFO - Epoch(train) [404][50/63] lr: 4.8416e-03 eta: 21:32:05 time: 0.8410 data_time: 0.0266 memory: 16201 loss_prob: 0.6175 loss_thr: 0.3861 loss_db: 0.1069 loss: 1.1104 2022/08/30 10:38:49 - mmengine - INFO - Epoch(train) [404][55/63] lr: 4.8416e-03 eta: 21:32:05 time: 0.8380 data_time: 0.0274 memory: 16201 loss_prob: 0.7070 loss_thr: 0.4003 loss_db: 0.1184 loss: 1.2257 2022/08/30 10:38:52 - mmengine - INFO - Epoch(train) [404][60/63] lr: 4.8416e-03 eta: 21:31:34 time: 0.7763 data_time: 0.0254 memory: 16201 loss_prob: 0.7437 loss_thr: 0.4286 loss_db: 0.1225 loss: 1.2947 2022/08/30 10:38:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:38:59 - mmengine - INFO - Epoch(train) [405][5/63] lr: 4.8361e-03 eta: 21:31:34 time: 0.8497 data_time: 0.1488 memory: 16201 loss_prob: 0.6869 loss_thr: 0.4334 loss_db: 0.1169 loss: 1.2372 2022/08/30 10:39:04 - mmengine - INFO - Epoch(train) [405][10/63] lr: 4.8361e-03 eta: 21:30:53 time: 0.9374 data_time: 0.1803 memory: 16201 loss_prob: 0.6751 loss_thr: 0.4188 loss_db: 0.1112 loss: 1.2051 2022/08/30 10:39:07 - mmengine - INFO - Epoch(train) [405][15/63] lr: 4.8361e-03 eta: 21:30:53 time: 0.7999 data_time: 0.0403 memory: 16201 loss_prob: 0.6517 loss_thr: 0.3970 loss_db: 0.1072 loss: 1.1559 2022/08/30 10:39:12 - mmengine - INFO - Epoch(train) [405][20/63] lr: 4.8361e-03 eta: 21:30:22 time: 0.7900 data_time: 0.0262 memory: 16201 loss_prob: 0.6266 loss_thr: 0.4148 loss_db: 0.1046 loss: 1.1460 2022/08/30 10:39:16 - mmengine - INFO - Epoch(train) [405][25/63] lr: 4.8361e-03 eta: 21:30:22 time: 0.8211 data_time: 0.0472 memory: 16201 loss_prob: 0.6024 loss_thr: 0.4192 loss_db: 0.1033 loss: 1.1249 2022/08/30 10:39:20 - mmengine - INFO - Epoch(train) [405][30/63] lr: 4.8361e-03 eta: 21:29:52 time: 0.7972 data_time: 0.0318 memory: 16201 loss_prob: 0.6129 loss_thr: 0.4005 loss_db: 0.1049 loss: 1.1183 2022/08/30 10:39:24 - mmengine - INFO - Epoch(train) [405][35/63] lr: 4.8361e-03 eta: 21:29:52 time: 0.7923 data_time: 0.0288 memory: 16201 loss_prob: 0.6057 loss_thr: 0.3952 loss_db: 0.1038 loss: 1.1047 2022/08/30 10:39:28 - mmengine - INFO - Epoch(train) [405][40/63] lr: 4.8361e-03 eta: 21:29:22 time: 0.8059 data_time: 0.0368 memory: 16201 loss_prob: 0.5773 loss_thr: 0.3976 loss_db: 0.0997 loss: 1.0746 2022/08/30 10:39:32 - mmengine - INFO - Epoch(train) [405][45/63] lr: 4.8361e-03 eta: 21:29:22 time: 0.8046 data_time: 0.0284 memory: 16201 loss_prob: 0.6025 loss_thr: 0.4092 loss_db: 0.1036 loss: 1.1153 2022/08/30 10:39:36 - mmengine - INFO - Epoch(train) [405][50/63] lr: 4.8361e-03 eta: 21:28:52 time: 0.8061 data_time: 0.0286 memory: 16201 loss_prob: 0.5983 loss_thr: 0.4080 loss_db: 0.1033 loss: 1.1096 2022/08/30 10:39:39 - mmengine - INFO - Epoch(train) [405][55/63] lr: 4.8361e-03 eta: 21:28:52 time: 0.7869 data_time: 0.0267 memory: 16201 loss_prob: 0.5780 loss_thr: 0.3825 loss_db: 0.0984 loss: 1.0590 2022/08/30 10:39:44 - mmengine - INFO - Epoch(train) [405][60/63] lr: 4.8361e-03 eta: 21:28:23 time: 0.8146 data_time: 0.0245 memory: 16201 loss_prob: 0.6002 loss_thr: 0.3968 loss_db: 0.1031 loss: 1.1001 2022/08/30 10:39:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:39:51 - mmengine - INFO - Epoch(train) [406][5/63] lr: 4.8306e-03 eta: 21:28:23 time: 0.9084 data_time: 0.1746 memory: 16201 loss_prob: 0.5887 loss_thr: 0.3945 loss_db: 0.1008 loss: 1.0840 2022/08/30 10:39:55 - mmengine - INFO - Epoch(train) [406][10/63] lr: 4.8306e-03 eta: 21:27:42 time: 0.9671 data_time: 0.1916 memory: 16201 loss_prob: 0.7589 loss_thr: 0.4079 loss_db: 0.1245 loss: 1.2913 2022/08/30 10:39:59 - mmengine - INFO - Epoch(train) [406][15/63] lr: 4.8306e-03 eta: 21:27:42 time: 0.7965 data_time: 0.0363 memory: 16201 loss_prob: 0.7755 loss_thr: 0.4176 loss_db: 0.1247 loss: 1.3179 2022/08/30 10:40:03 - mmengine - INFO - Epoch(train) [406][20/63] lr: 4.8306e-03 eta: 21:27:12 time: 0.7883 data_time: 0.0255 memory: 16201 loss_prob: 0.6029 loss_thr: 0.4049 loss_db: 0.0993 loss: 1.1071 2022/08/30 10:40:07 - mmengine - INFO - Epoch(train) [406][25/63] lr: 4.8306e-03 eta: 21:27:12 time: 0.8099 data_time: 0.0301 memory: 16201 loss_prob: 0.6095 loss_thr: 0.4118 loss_db: 0.1046 loss: 1.1259 2022/08/30 10:40:11 - mmengine - INFO - Epoch(train) [406][30/63] lr: 4.8306e-03 eta: 21:26:42 time: 0.7885 data_time: 0.0274 memory: 16201 loss_prob: 0.6269 loss_thr: 0.4186 loss_db: 0.1099 loss: 1.1554 2022/08/30 10:40:16 - mmengine - INFO - Epoch(train) [406][35/63] lr: 4.8306e-03 eta: 21:26:42 time: 0.8140 data_time: 0.0269 memory: 16201 loss_prob: 0.6906 loss_thr: 0.4414 loss_db: 0.1191 loss: 1.2511 2022/08/30 10:40:20 - mmengine - INFO - Epoch(train) [406][40/63] lr: 4.8306e-03 eta: 21:26:13 time: 0.8405 data_time: 0.0497 memory: 16201 loss_prob: 0.6477 loss_thr: 0.4097 loss_db: 0.1104 loss: 1.1678 2022/08/30 10:40:23 - mmengine - INFO - Epoch(train) [406][45/63] lr: 4.8306e-03 eta: 21:26:13 time: 0.7941 data_time: 0.0461 memory: 16201 loss_prob: 0.5499 loss_thr: 0.3634 loss_db: 0.0953 loss: 1.0086 2022/08/30 10:40:27 - mmengine - INFO - Epoch(train) [406][50/63] lr: 4.8306e-03 eta: 21:25:42 time: 0.7742 data_time: 0.0230 memory: 16201 loss_prob: 0.5589 loss_thr: 0.3708 loss_db: 0.0984 loss: 1.0281 2022/08/30 10:40:31 - mmengine - INFO - Epoch(train) [406][55/63] lr: 4.8306e-03 eta: 21:25:42 time: 0.7976 data_time: 0.0325 memory: 16201 loss_prob: 0.6010 loss_thr: 0.4027 loss_db: 0.1058 loss: 1.1095 2022/08/30 10:40:36 - mmengine - INFO - Epoch(train) [406][60/63] lr: 4.8306e-03 eta: 21:25:13 time: 0.8160 data_time: 0.0351 memory: 16201 loss_prob: 0.6199 loss_thr: 0.4118 loss_db: 0.1068 loss: 1.1384 2022/08/30 10:40:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:40:43 - mmengine - INFO - Epoch(train) [407][5/63] lr: 4.8251e-03 eta: 21:25:13 time: 0.9016 data_time: 0.1674 memory: 16201 loss_prob: 0.5908 loss_thr: 0.3901 loss_db: 0.1027 loss: 1.0836 2022/08/30 10:40:47 - mmengine - INFO - Epoch(train) [407][10/63] lr: 4.8251e-03 eta: 21:24:33 time: 0.9791 data_time: 0.1916 memory: 16201 loss_prob: 0.5974 loss_thr: 0.3913 loss_db: 0.1039 loss: 1.0925 2022/08/30 10:40:51 - mmengine - INFO - Epoch(train) [407][15/63] lr: 4.8251e-03 eta: 21:24:33 time: 0.8065 data_time: 0.0457 memory: 16201 loss_prob: 0.5773 loss_thr: 0.3830 loss_db: 0.1001 loss: 1.0604 2022/08/30 10:40:55 - mmengine - INFO - Epoch(train) [407][20/63] lr: 4.8251e-03 eta: 21:24:03 time: 0.8234 data_time: 0.0234 memory: 16201 loss_prob: 0.5581 loss_thr: 0.3859 loss_db: 0.0959 loss: 1.0398 2022/08/30 10:41:00 - mmengine - INFO - Epoch(train) [407][25/63] lr: 4.8251e-03 eta: 21:24:03 time: 0.8430 data_time: 0.0386 memory: 16201 loss_prob: 0.5823 loss_thr: 0.3898 loss_db: 0.1017 loss: 1.0737 2022/08/30 10:41:03 - mmengine - INFO - Epoch(train) [407][30/63] lr: 4.8251e-03 eta: 21:23:33 time: 0.8000 data_time: 0.0378 memory: 16201 loss_prob: 0.6125 loss_thr: 0.3889 loss_db: 0.1078 loss: 1.1092 2022/08/30 10:41:07 - mmengine - INFO - Epoch(train) [407][35/63] lr: 4.8251e-03 eta: 21:23:33 time: 0.7809 data_time: 0.0240 memory: 16201 loss_prob: 0.5998 loss_thr: 0.3954 loss_db: 0.1029 loss: 1.0981 2022/08/30 10:41:11 - mmengine - INFO - Epoch(train) [407][40/63] lr: 4.8251e-03 eta: 21:23:03 time: 0.7848 data_time: 0.0268 memory: 16201 loss_prob: 0.6176 loss_thr: 0.4234 loss_db: 0.1060 loss: 1.1470 2022/08/30 10:41:16 - mmengine - INFO - Epoch(train) [407][45/63] lr: 4.8251e-03 eta: 21:23:03 time: 0.8221 data_time: 0.0311 memory: 16201 loss_prob: 0.6410 loss_thr: 0.4258 loss_db: 0.1126 loss: 1.1795 2022/08/30 10:41:20 - mmengine - INFO - Epoch(train) [407][50/63] lr: 4.8251e-03 eta: 21:22:34 time: 0.8233 data_time: 0.0331 memory: 16201 loss_prob: 0.6632 loss_thr: 0.4273 loss_db: 0.1138 loss: 1.2043 2022/08/30 10:41:24 - mmengine - INFO - Epoch(train) [407][55/63] lr: 4.8251e-03 eta: 21:22:34 time: 0.7909 data_time: 0.0300 memory: 16201 loss_prob: 0.6671 loss_thr: 0.4260 loss_db: 0.1116 loss: 1.2048 2022/08/30 10:41:27 - mmengine - INFO - Epoch(train) [407][60/63] lr: 4.8251e-03 eta: 21:22:03 time: 0.7738 data_time: 0.0212 memory: 16201 loss_prob: 0.5938 loss_thr: 0.3927 loss_db: 0.1012 loss: 1.0877 2022/08/30 10:41:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:41:35 - mmengine - INFO - Epoch(train) [408][5/63] lr: 4.8197e-03 eta: 21:22:03 time: 0.8826 data_time: 0.1547 memory: 16201 loss_prob: 0.6086 loss_thr: 0.3987 loss_db: 0.1033 loss: 1.1105 2022/08/30 10:41:39 - mmengine - INFO - Epoch(train) [408][10/63] lr: 4.8197e-03 eta: 21:21:23 time: 0.9607 data_time: 0.1937 memory: 16201 loss_prob: 0.6718 loss_thr: 0.4236 loss_db: 0.1177 loss: 1.2131 2022/08/30 10:41:43 - mmengine - INFO - Epoch(train) [408][15/63] lr: 4.8197e-03 eta: 21:21:23 time: 0.8274 data_time: 0.0554 memory: 16201 loss_prob: 0.6297 loss_thr: 0.3996 loss_db: 0.1095 loss: 1.1388 2022/08/30 10:41:47 - mmengine - INFO - Epoch(train) [408][20/63] lr: 4.8197e-03 eta: 21:20:53 time: 0.7968 data_time: 0.0265 memory: 16201 loss_prob: 0.5788 loss_thr: 0.3920 loss_db: 0.0985 loss: 1.0693 2022/08/30 10:41:51 - mmengine - INFO - Epoch(train) [408][25/63] lr: 4.8197e-03 eta: 21:20:53 time: 0.8159 data_time: 0.0301 memory: 16201 loss_prob: 0.6349 loss_thr: 0.4214 loss_db: 0.1109 loss: 1.1672 2022/08/30 10:41:55 - mmengine - INFO - Epoch(train) [408][30/63] lr: 4.8197e-03 eta: 21:20:24 time: 0.8191 data_time: 0.0239 memory: 16201 loss_prob: 0.6282 loss_thr: 0.3973 loss_db: 0.1091 loss: 1.1347 2022/08/30 10:41:59 - mmengine - INFO - Epoch(train) [408][35/63] lr: 4.8197e-03 eta: 21:20:24 time: 0.7851 data_time: 0.0196 memory: 16201 loss_prob: 0.5680 loss_thr: 0.3735 loss_db: 0.0971 loss: 1.0386 2022/08/30 10:42:03 - mmengine - INFO - Epoch(train) [408][40/63] lr: 4.8197e-03 eta: 21:19:54 time: 0.7818 data_time: 0.0230 memory: 16201 loss_prob: 0.6131 loss_thr: 0.3993 loss_db: 0.1042 loss: 1.1166 2022/08/30 10:42:07 - mmengine - INFO - Epoch(train) [408][45/63] lr: 4.8197e-03 eta: 21:19:54 time: 0.7960 data_time: 0.0291 memory: 16201 loss_prob: 0.6045 loss_thr: 0.3875 loss_db: 0.1026 loss: 1.0946 2022/08/30 10:42:11 - mmengine - INFO - Epoch(train) [408][50/63] lr: 4.8197e-03 eta: 21:19:24 time: 0.7882 data_time: 0.0253 memory: 16201 loss_prob: 0.6071 loss_thr: 0.3822 loss_db: 0.0999 loss: 1.0892 2022/08/30 10:42:15 - mmengine - INFO - Epoch(train) [408][55/63] lr: 4.8197e-03 eta: 21:19:24 time: 0.8034 data_time: 0.0324 memory: 16201 loss_prob: 0.5778 loss_thr: 0.3936 loss_db: 0.0973 loss: 1.0687 2022/08/30 10:42:19 - mmengine - INFO - Epoch(train) [408][60/63] lr: 4.8197e-03 eta: 21:18:55 time: 0.8403 data_time: 0.0423 memory: 16201 loss_prob: 0.5466 loss_thr: 0.3909 loss_db: 0.0972 loss: 1.0347 2022/08/30 10:42:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:42:26 - mmengine - INFO - Epoch(train) [409][5/63] lr: 4.8142e-03 eta: 21:18:55 time: 0.8912 data_time: 0.1553 memory: 16201 loss_prob: 0.5935 loss_thr: 0.3990 loss_db: 0.1016 loss: 1.0941 2022/08/30 10:42:30 - mmengine - INFO - Epoch(train) [409][10/63] lr: 4.8142e-03 eta: 21:18:14 time: 0.9371 data_time: 0.1730 memory: 16201 loss_prob: 0.6043 loss_thr: 0.4000 loss_db: 0.1063 loss: 1.1107 2022/08/30 10:42:35 - mmengine - INFO - Epoch(train) [409][15/63] lr: 4.8142e-03 eta: 21:18:14 time: 0.8512 data_time: 0.0386 memory: 16201 loss_prob: 0.6244 loss_thr: 0.4133 loss_db: 0.1095 loss: 1.1473 2022/08/30 10:42:39 - mmengine - INFO - Epoch(train) [409][20/63] lr: 4.8142e-03 eta: 21:17:45 time: 0.8341 data_time: 0.0296 memory: 16201 loss_prob: 0.6818 loss_thr: 0.4204 loss_db: 0.1111 loss: 1.2133 2022/08/30 10:42:43 - mmengine - INFO - Epoch(train) [409][25/63] lr: 4.8142e-03 eta: 21:17:45 time: 0.7951 data_time: 0.0342 memory: 16201 loss_prob: 0.6974 loss_thr: 0.4060 loss_db: 0.1130 loss: 1.2164 2022/08/30 10:42:47 - mmengine - INFO - Epoch(train) [409][30/63] lr: 4.8142e-03 eta: 21:17:16 time: 0.7955 data_time: 0.0294 memory: 16201 loss_prob: 0.7303 loss_thr: 0.4071 loss_db: 0.1191 loss: 1.2565 2022/08/30 10:42:51 - mmengine - INFO - Epoch(train) [409][35/63] lr: 4.8142e-03 eta: 21:17:16 time: 0.7795 data_time: 0.0245 memory: 16201 loss_prob: 0.7358 loss_thr: 0.4329 loss_db: 0.1164 loss: 1.2851 2022/08/30 10:42:55 - mmengine - INFO - Epoch(train) [409][40/63] lr: 4.8142e-03 eta: 21:16:46 time: 0.8253 data_time: 0.0292 memory: 16201 loss_prob: 0.6393 loss_thr: 0.4273 loss_db: 0.1052 loss: 1.1719 2022/08/30 10:42:59 - mmengine - INFO - Epoch(train) [409][45/63] lr: 4.8142e-03 eta: 21:16:46 time: 0.8227 data_time: 0.0266 memory: 16201 loss_prob: 0.6666 loss_thr: 0.4242 loss_db: 0.1155 loss: 1.2063 2022/08/30 10:43:03 - mmengine - INFO - Epoch(train) [409][50/63] lr: 4.8142e-03 eta: 21:16:16 time: 0.7849 data_time: 0.0204 memory: 16201 loss_prob: 0.6987 loss_thr: 0.4359 loss_db: 0.1215 loss: 1.2561 2022/08/30 10:43:07 - mmengine - INFO - Epoch(train) [409][55/63] lr: 4.8142e-03 eta: 21:16:16 time: 0.7912 data_time: 0.0342 memory: 16201 loss_prob: 0.6614 loss_thr: 0.4298 loss_db: 0.1157 loss: 1.2070 2022/08/30 10:43:11 - mmengine - INFO - Epoch(train) [409][60/63] lr: 4.8142e-03 eta: 21:15:47 time: 0.7863 data_time: 0.0333 memory: 16201 loss_prob: 0.6235 loss_thr: 0.4239 loss_db: 0.1090 loss: 1.1564 2022/08/30 10:43:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:43:20 - mmengine - INFO - Epoch(train) [410][5/63] lr: 4.8087e-03 eta: 21:15:47 time: 1.0584 data_time: 0.2355 memory: 16201 loss_prob: 0.5697 loss_thr: 0.3929 loss_db: 0.0976 loss: 1.0601 2022/08/30 10:43:24 - mmengine - INFO - Epoch(train) [410][10/63] lr: 4.8087e-03 eta: 21:15:08 time: 1.0344 data_time: 0.2588 memory: 16201 loss_prob: 0.6588 loss_thr: 0.4240 loss_db: 0.1132 loss: 1.1961 2022/08/30 10:43:28 - mmengine - INFO - Epoch(train) [410][15/63] lr: 4.8087e-03 eta: 21:15:08 time: 0.8145 data_time: 0.0366 memory: 16201 loss_prob: 0.6270 loss_thr: 0.4096 loss_db: 0.1075 loss: 1.1441 2022/08/30 10:43:32 - mmengine - INFO - Epoch(train) [410][20/63] lr: 4.8087e-03 eta: 21:14:38 time: 0.7930 data_time: 0.0156 memory: 16201 loss_prob: 0.6184 loss_thr: 0.3922 loss_db: 0.1043 loss: 1.1150 2022/08/30 10:43:36 - mmengine - INFO - Epoch(train) [410][25/63] lr: 4.8087e-03 eta: 21:14:38 time: 0.8079 data_time: 0.0435 memory: 16201 loss_prob: 0.6273 loss_thr: 0.4006 loss_db: 0.1043 loss: 1.1322 2022/08/30 10:43:40 - mmengine - INFO - Epoch(train) [410][30/63] lr: 4.8087e-03 eta: 21:14:09 time: 0.8029 data_time: 0.0409 memory: 16201 loss_prob: 0.5598 loss_thr: 0.3962 loss_db: 0.0965 loss: 1.0525 2022/08/30 10:43:44 - mmengine - INFO - Epoch(train) [410][35/63] lr: 4.8087e-03 eta: 21:14:09 time: 0.7878 data_time: 0.0239 memory: 16201 loss_prob: 0.6108 loss_thr: 0.4248 loss_db: 0.1046 loss: 1.1402 2022/08/30 10:43:48 - mmengine - INFO - Epoch(train) [410][40/63] lr: 4.8087e-03 eta: 21:13:39 time: 0.7947 data_time: 0.0302 memory: 16201 loss_prob: 0.6580 loss_thr: 0.4452 loss_db: 0.1118 loss: 1.2150 2022/08/30 10:43:52 - mmengine - INFO - Epoch(train) [410][45/63] lr: 4.8087e-03 eta: 21:13:39 time: 0.7935 data_time: 0.0304 memory: 16201 loss_prob: 0.6482 loss_thr: 0.4321 loss_db: 0.1118 loss: 1.1921 2022/08/30 10:43:56 - mmengine - INFO - Epoch(train) [410][50/63] lr: 4.8087e-03 eta: 21:13:10 time: 0.8080 data_time: 0.0295 memory: 16201 loss_prob: 0.6316 loss_thr: 0.4131 loss_db: 0.1059 loss: 1.1506 2022/08/30 10:44:00 - mmengine - INFO - Epoch(train) [410][55/63] lr: 4.8087e-03 eta: 21:13:10 time: 0.8103 data_time: 0.0481 memory: 16201 loss_prob: 0.6491 loss_thr: 0.4069 loss_db: 0.1033 loss: 1.1593 2022/08/30 10:44:04 - mmengine - INFO - Epoch(train) [410][60/63] lr: 4.8087e-03 eta: 21:12:41 time: 0.8557 data_time: 0.0481 memory: 16201 loss_prob: 0.6168 loss_thr: 0.3925 loss_db: 0.1018 loss: 1.1110 2022/08/30 10:44:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:44:12 - mmengine - INFO - Epoch(train) [411][5/63] lr: 4.8032e-03 eta: 21:12:41 time: 0.8914 data_time: 0.1650 memory: 16201 loss_prob: 0.5681 loss_thr: 0.3811 loss_db: 0.1002 loss: 1.0494 2022/08/30 10:44:16 - mmengine - INFO - Epoch(train) [411][10/63] lr: 4.8032e-03 eta: 21:12:01 time: 0.9315 data_time: 0.1786 memory: 16201 loss_prob: 0.5941 loss_thr: 0.3966 loss_db: 0.1007 loss: 1.0913 2022/08/30 10:44:19 - mmengine - INFO - Epoch(train) [411][15/63] lr: 4.8032e-03 eta: 21:12:01 time: 0.7772 data_time: 0.0266 memory: 16201 loss_prob: 0.6639 loss_thr: 0.4326 loss_db: 0.1132 loss: 1.2097 2022/08/30 10:44:24 - mmengine - INFO - Epoch(train) [411][20/63] lr: 4.8032e-03 eta: 21:11:31 time: 0.7876 data_time: 0.0216 memory: 16201 loss_prob: 0.6034 loss_thr: 0.3952 loss_db: 0.1051 loss: 1.1037 2022/08/30 10:44:27 - mmengine - INFO - Epoch(train) [411][25/63] lr: 4.8032e-03 eta: 21:11:31 time: 0.7960 data_time: 0.0341 memory: 16201 loss_prob: 0.6931 loss_thr: 0.3979 loss_db: 0.1136 loss: 1.2046 2022/08/30 10:44:31 - mmengine - INFO - Epoch(train) [411][30/63] lr: 4.8032e-03 eta: 21:11:02 time: 0.7845 data_time: 0.0289 memory: 16201 loss_prob: 0.7334 loss_thr: 0.4108 loss_db: 0.1181 loss: 1.2623 2022/08/30 10:44:35 - mmengine - INFO - Epoch(train) [411][35/63] lr: 4.8032e-03 eta: 21:11:02 time: 0.8051 data_time: 0.0318 memory: 16201 loss_prob: 0.6029 loss_thr: 0.3877 loss_db: 0.1032 loss: 1.0939 2022/08/30 10:44:40 - mmengine - INFO - Epoch(train) [411][40/63] lr: 4.8032e-03 eta: 21:10:32 time: 0.8160 data_time: 0.0394 memory: 16201 loss_prob: 0.5558 loss_thr: 0.3716 loss_db: 0.0953 loss: 1.0226 2022/08/30 10:44:44 - mmengine - INFO - Epoch(train) [411][45/63] lr: 4.8032e-03 eta: 21:10:32 time: 0.8221 data_time: 0.0320 memory: 16201 loss_prob: 0.5439 loss_thr: 0.3703 loss_db: 0.0921 loss: 1.0063 2022/08/30 10:44:48 - mmengine - INFO - Epoch(train) [411][50/63] lr: 4.8032e-03 eta: 21:10:03 time: 0.8200 data_time: 0.0300 memory: 16201 loss_prob: 0.6081 loss_thr: 0.3994 loss_db: 0.1059 loss: 1.1134 2022/08/30 10:44:52 - mmengine - INFO - Epoch(train) [411][55/63] lr: 4.8032e-03 eta: 21:10:03 time: 0.7906 data_time: 0.0267 memory: 16201 loss_prob: 0.6762 loss_thr: 0.4206 loss_db: 0.1137 loss: 1.2105 2022/08/30 10:44:56 - mmengine - INFO - Epoch(train) [411][60/63] lr: 4.8032e-03 eta: 21:09:34 time: 0.7834 data_time: 0.0211 memory: 16201 loss_prob: 0.6196 loss_thr: 0.4056 loss_db: 0.1026 loss: 1.1278 2022/08/30 10:44:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:45:03 - mmengine - INFO - Epoch(train) [412][5/63] lr: 4.7977e-03 eta: 21:09:34 time: 0.8736 data_time: 0.1584 memory: 16201 loss_prob: 0.6594 loss_thr: 0.4038 loss_db: 0.1105 loss: 1.1737 2022/08/30 10:45:07 - mmengine - INFO - Epoch(train) [412][10/63] lr: 4.7977e-03 eta: 21:08:54 time: 0.9479 data_time: 0.1828 memory: 16201 loss_prob: 0.6581 loss_thr: 0.4101 loss_db: 0.1104 loss: 1.1786 2022/08/30 10:45:11 - mmengine - INFO - Epoch(train) [412][15/63] lr: 4.7977e-03 eta: 21:08:54 time: 0.8024 data_time: 0.0363 memory: 16201 loss_prob: 0.5882 loss_thr: 0.3944 loss_db: 0.1012 loss: 1.0838 2022/08/30 10:45:15 - mmengine - INFO - Epoch(train) [412][20/63] lr: 4.7977e-03 eta: 21:08:24 time: 0.7828 data_time: 0.0200 memory: 16201 loss_prob: 0.5516 loss_thr: 0.3937 loss_db: 0.0971 loss: 1.0424 2022/08/30 10:45:19 - mmengine - INFO - Epoch(train) [412][25/63] lr: 4.7977e-03 eta: 21:08:24 time: 0.8144 data_time: 0.0388 memory: 16201 loss_prob: 0.5700 loss_thr: 0.3961 loss_db: 0.1004 loss: 1.0665 2022/08/30 10:45:23 - mmengine - INFO - Epoch(train) [412][30/63] lr: 4.7977e-03 eta: 21:07:56 time: 0.8450 data_time: 0.0377 memory: 16201 loss_prob: 0.5612 loss_thr: 0.3738 loss_db: 0.0975 loss: 1.0326 2022/08/30 10:45:27 - mmengine - INFO - Epoch(train) [412][35/63] lr: 4.7977e-03 eta: 21:07:56 time: 0.8224 data_time: 0.0300 memory: 16201 loss_prob: 0.5859 loss_thr: 0.3872 loss_db: 0.1024 loss: 1.0755 2022/08/30 10:45:31 - mmengine - INFO - Epoch(train) [412][40/63] lr: 4.7977e-03 eta: 21:07:26 time: 0.7894 data_time: 0.0342 memory: 16201 loss_prob: 0.5983 loss_thr: 0.4089 loss_db: 0.1064 loss: 1.1136 2022/08/30 10:45:35 - mmengine - INFO - Epoch(train) [412][45/63] lr: 4.7977e-03 eta: 21:07:26 time: 0.8016 data_time: 0.0361 memory: 16201 loss_prob: 0.5948 loss_thr: 0.4086 loss_db: 0.1035 loss: 1.1069 2022/08/30 10:45:39 - mmengine - INFO - Epoch(train) [412][50/63] lr: 4.7977e-03 eta: 21:06:57 time: 0.7891 data_time: 0.0294 memory: 16201 loss_prob: 0.6026 loss_thr: 0.4156 loss_db: 0.1008 loss: 1.1191 2022/08/30 10:45:43 - mmengine - INFO - Epoch(train) [412][55/63] lr: 4.7977e-03 eta: 21:06:57 time: 0.8035 data_time: 0.0234 memory: 16201 loss_prob: 0.6122 loss_thr: 0.4122 loss_db: 0.1029 loss: 1.1273 2022/08/30 10:45:47 - mmengine - INFO - Epoch(train) [412][60/63] lr: 4.7977e-03 eta: 21:06:28 time: 0.8244 data_time: 0.0298 memory: 16201 loss_prob: 0.6157 loss_thr: 0.3994 loss_db: 0.1046 loss: 1.1197 2022/08/30 10:45:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:45:55 - mmengine - INFO - Epoch(train) [413][5/63] lr: 4.7923e-03 eta: 21:06:28 time: 0.9258 data_time: 0.1754 memory: 16201 loss_prob: 0.5680 loss_thr: 0.3818 loss_db: 0.0980 loss: 1.0479 2022/08/30 10:45:59 - mmengine - INFO - Epoch(train) [413][10/63] lr: 4.7923e-03 eta: 21:05:48 time: 0.9685 data_time: 0.1844 memory: 16201 loss_prob: 0.5211 loss_thr: 0.3672 loss_db: 0.0915 loss: 0.9798 2022/08/30 10:46:03 - mmengine - INFO - Epoch(train) [413][15/63] lr: 4.7923e-03 eta: 21:05:48 time: 0.8048 data_time: 0.0311 memory: 16201 loss_prob: 0.5365 loss_thr: 0.3750 loss_db: 0.0958 loss: 1.0074 2022/08/30 10:46:07 - mmengine - INFO - Epoch(train) [413][20/63] lr: 4.7923e-03 eta: 21:05:19 time: 0.8123 data_time: 0.0230 memory: 16201 loss_prob: 0.5752 loss_thr: 0.3777 loss_db: 0.1000 loss: 1.0529 2022/08/30 10:46:11 - mmengine - INFO - Epoch(train) [413][25/63] lr: 4.7923e-03 eta: 21:05:19 time: 0.8172 data_time: 0.0435 memory: 16201 loss_prob: 0.5992 loss_thr: 0.3757 loss_db: 0.1023 loss: 1.0772 2022/08/30 10:46:15 - mmengine - INFO - Epoch(train) [413][30/63] lr: 4.7923e-03 eta: 21:04:50 time: 0.7975 data_time: 0.0355 memory: 16201 loss_prob: 0.5848 loss_thr: 0.3706 loss_db: 0.0983 loss: 1.0536 2022/08/30 10:46:19 - mmengine - INFO - Epoch(train) [413][35/63] lr: 4.7923e-03 eta: 21:04:50 time: 0.7929 data_time: 0.0224 memory: 16201 loss_prob: 0.5459 loss_thr: 0.3727 loss_db: 0.0933 loss: 1.0118 2022/08/30 10:46:24 - mmengine - INFO - Epoch(train) [413][40/63] lr: 4.7923e-03 eta: 21:04:22 time: 0.8563 data_time: 0.0549 memory: 16201 loss_prob: 0.5435 loss_thr: 0.3779 loss_db: 0.0960 loss: 1.0173 2022/08/30 10:46:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:46:28 - mmengine - INFO - Epoch(train) [413][45/63] lr: 4.7923e-03 eta: 21:04:22 time: 0.8967 data_time: 0.1030 memory: 16201 loss_prob: 0.5419 loss_thr: 0.3768 loss_db: 0.0930 loss: 1.0118 2022/08/30 10:46:32 - mmengine - INFO - Epoch(train) [413][50/63] lr: 4.7923e-03 eta: 21:03:53 time: 0.8334 data_time: 0.0751 memory: 16201 loss_prob: 0.5451 loss_thr: 0.3920 loss_db: 0.0927 loss: 1.0299 2022/08/30 10:46:36 - mmengine - INFO - Epoch(train) [413][55/63] lr: 4.7923e-03 eta: 21:03:53 time: 0.7972 data_time: 0.0373 memory: 16201 loss_prob: 0.5982 loss_thr: 0.4070 loss_db: 0.1034 loss: 1.1087 2022/08/30 10:46:40 - mmengine - INFO - Epoch(train) [413][60/63] lr: 4.7923e-03 eta: 21:03:24 time: 0.7956 data_time: 0.0392 memory: 16201 loss_prob: 0.6292 loss_thr: 0.4124 loss_db: 0.1107 loss: 1.1523 2022/08/30 10:46:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:46:48 - mmengine - INFO - Epoch(train) [414][5/63] lr: 4.7868e-03 eta: 21:03:24 time: 0.9163 data_time: 0.1760 memory: 16201 loss_prob: 0.6441 loss_thr: 0.4071 loss_db: 0.1123 loss: 1.1635 2022/08/30 10:46:52 - mmengine - INFO - Epoch(train) [414][10/63] lr: 4.7868e-03 eta: 21:02:45 time: 0.9674 data_time: 0.1937 memory: 16201 loss_prob: 0.6169 loss_thr: 0.3870 loss_db: 0.1029 loss: 1.1069 2022/08/30 10:46:56 - mmengine - INFO - Epoch(train) [414][15/63] lr: 4.7868e-03 eta: 21:02:45 time: 0.8276 data_time: 0.0377 memory: 16201 loss_prob: 0.6258 loss_thr: 0.4012 loss_db: 0.1052 loss: 1.1322 2022/08/30 10:47:00 - mmengine - INFO - Epoch(train) [414][20/63] lr: 4.7868e-03 eta: 21:02:16 time: 0.8194 data_time: 0.0206 memory: 16201 loss_prob: 0.5490 loss_thr: 0.3899 loss_db: 0.0957 loss: 1.0346 2022/08/30 10:47:04 - mmengine - INFO - Epoch(train) [414][25/63] lr: 4.7868e-03 eta: 21:02:16 time: 0.8152 data_time: 0.0361 memory: 16201 loss_prob: 0.5156 loss_thr: 0.3590 loss_db: 0.0887 loss: 0.9633 2022/08/30 10:47:08 - mmengine - INFO - Epoch(train) [414][30/63] lr: 4.7868e-03 eta: 21:01:47 time: 0.7970 data_time: 0.0336 memory: 16201 loss_prob: 0.5460 loss_thr: 0.3638 loss_db: 0.0929 loss: 1.0026 2022/08/30 10:47:12 - mmengine - INFO - Epoch(train) [414][35/63] lr: 4.7868e-03 eta: 21:01:47 time: 0.7953 data_time: 0.0226 memory: 16201 loss_prob: 0.5263 loss_thr: 0.3649 loss_db: 0.0921 loss: 0.9833 2022/08/30 10:47:16 - mmengine - INFO - Epoch(train) [414][40/63] lr: 4.7868e-03 eta: 21:01:18 time: 0.8014 data_time: 0.0281 memory: 16201 loss_prob: 0.4954 loss_thr: 0.3534 loss_db: 0.0878 loss: 0.9366 2022/08/30 10:47:20 - mmengine - INFO - Epoch(train) [414][45/63] lr: 4.7868e-03 eta: 21:01:18 time: 0.7856 data_time: 0.0308 memory: 16201 loss_prob: 0.4976 loss_thr: 0.3506 loss_db: 0.0869 loss: 0.9351 2022/08/30 10:47:24 - mmengine - INFO - Epoch(train) [414][50/63] lr: 4.7868e-03 eta: 21:00:49 time: 0.8181 data_time: 0.0321 memory: 16201 loss_prob: 0.5466 loss_thr: 0.3700 loss_db: 0.0937 loss: 1.0103 2022/08/30 10:47:28 - mmengine - INFO - Epoch(train) [414][55/63] lr: 4.7868e-03 eta: 21:00:49 time: 0.8147 data_time: 0.0308 memory: 16201 loss_prob: 0.6049 loss_thr: 0.3992 loss_db: 0.1030 loss: 1.1071 2022/08/30 10:47:32 - mmengine - INFO - Epoch(train) [414][60/63] lr: 4.7868e-03 eta: 21:00:19 time: 0.7786 data_time: 0.0263 memory: 16201 loss_prob: 0.5952 loss_thr: 0.3949 loss_db: 0.1003 loss: 1.0904 2022/08/30 10:47:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:47:40 - mmengine - INFO - Epoch(train) [415][5/63] lr: 4.7813e-03 eta: 21:00:19 time: 0.9244 data_time: 0.1747 memory: 16201 loss_prob: 0.5139 loss_thr: 0.3574 loss_db: 0.0901 loss: 0.9614 2022/08/30 10:47:44 - mmengine - INFO - Epoch(train) [415][10/63] lr: 4.7813e-03 eta: 20:59:40 time: 0.9695 data_time: 0.1855 memory: 16201 loss_prob: 0.6063 loss_thr: 0.3991 loss_db: 0.1006 loss: 1.1060 2022/08/30 10:47:48 - mmengine - INFO - Epoch(train) [415][15/63] lr: 4.7813e-03 eta: 20:59:40 time: 0.7813 data_time: 0.0244 memory: 16201 loss_prob: 0.6657 loss_thr: 0.4124 loss_db: 0.1096 loss: 1.1877 2022/08/30 10:47:52 - mmengine - INFO - Epoch(train) [415][20/63] lr: 4.7813e-03 eta: 20:59:12 time: 0.8163 data_time: 0.0242 memory: 16201 loss_prob: 0.5769 loss_thr: 0.3787 loss_db: 0.1006 loss: 1.0562 2022/08/30 10:47:56 - mmengine - INFO - Epoch(train) [415][25/63] lr: 4.7813e-03 eta: 20:59:12 time: 0.8291 data_time: 0.0322 memory: 16201 loss_prob: 0.5640 loss_thr: 0.3854 loss_db: 0.0973 loss: 1.0467 2022/08/30 10:48:00 - mmengine - INFO - Epoch(train) [415][30/63] lr: 4.7813e-03 eta: 20:58:42 time: 0.7816 data_time: 0.0294 memory: 16201 loss_prob: 0.5512 loss_thr: 0.3962 loss_db: 0.0951 loss: 1.0426 2022/08/30 10:48:04 - mmengine - INFO - Epoch(train) [415][35/63] lr: 4.7813e-03 eta: 20:58:42 time: 0.8429 data_time: 0.0282 memory: 16201 loss_prob: 0.5599 loss_thr: 0.3903 loss_db: 0.0972 loss: 1.0474 2022/08/30 10:48:08 - mmengine - INFO - Epoch(train) [415][40/63] lr: 4.7813e-03 eta: 20:58:14 time: 0.8471 data_time: 0.0273 memory: 16201 loss_prob: 0.5998 loss_thr: 0.3851 loss_db: 0.1036 loss: 1.0886 2022/08/30 10:48:12 - mmengine - INFO - Epoch(train) [415][45/63] lr: 4.7813e-03 eta: 20:58:14 time: 0.7842 data_time: 0.0289 memory: 16201 loss_prob: 0.5386 loss_thr: 0.3540 loss_db: 0.0932 loss: 0.9858 2022/08/30 10:48:16 - mmengine - INFO - Epoch(train) [415][50/63] lr: 4.7813e-03 eta: 20:57:45 time: 0.8063 data_time: 0.0323 memory: 16201 loss_prob: 0.5163 loss_thr: 0.3639 loss_db: 0.0900 loss: 0.9701 2022/08/30 10:48:20 - mmengine - INFO - Epoch(train) [415][55/63] lr: 4.7813e-03 eta: 20:57:45 time: 0.8365 data_time: 0.0591 memory: 16201 loss_prob: 0.5746 loss_thr: 0.4095 loss_db: 0.1000 loss: 1.0842 2022/08/30 10:48:24 - mmengine - INFO - Epoch(train) [415][60/63] lr: 4.7813e-03 eta: 20:57:17 time: 0.8283 data_time: 0.0598 memory: 16201 loss_prob: 0.6169 loss_thr: 0.4089 loss_db: 0.1083 loss: 1.1341 2022/08/30 10:48:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:48:32 - mmengine - INFO - Epoch(train) [416][5/63] lr: 4.7758e-03 eta: 20:57:17 time: 0.8979 data_time: 0.1698 memory: 16201 loss_prob: 0.6124 loss_thr: 0.4166 loss_db: 0.1052 loss: 1.1342 2022/08/30 10:48:36 - mmengine - INFO - Epoch(train) [416][10/63] lr: 4.7758e-03 eta: 20:56:37 time: 0.9416 data_time: 0.1801 memory: 16201 loss_prob: 0.5698 loss_thr: 0.3966 loss_db: 0.0995 loss: 1.0659 2022/08/30 10:48:40 - mmengine - INFO - Epoch(train) [416][15/63] lr: 4.7758e-03 eta: 20:56:37 time: 0.7947 data_time: 0.0296 memory: 16201 loss_prob: 0.6146 loss_thr: 0.4057 loss_db: 0.1054 loss: 1.1257 2022/08/30 10:48:44 - mmengine - INFO - Epoch(train) [416][20/63] lr: 4.7758e-03 eta: 20:56:08 time: 0.7922 data_time: 0.0261 memory: 16201 loss_prob: 0.6064 loss_thr: 0.3915 loss_db: 0.1011 loss: 1.0989 2022/08/30 10:48:48 - mmengine - INFO - Epoch(train) [416][25/63] lr: 4.7758e-03 eta: 20:56:08 time: 0.8167 data_time: 0.0440 memory: 16201 loss_prob: 0.5767 loss_thr: 0.3759 loss_db: 0.0998 loss: 1.0524 2022/08/30 10:48:52 - mmengine - INFO - Epoch(train) [416][30/63] lr: 4.7758e-03 eta: 20:55:39 time: 0.7913 data_time: 0.0295 memory: 16201 loss_prob: 0.5562 loss_thr: 0.3597 loss_db: 0.0975 loss: 1.0134 2022/08/30 10:48:56 - mmengine - INFO - Epoch(train) [416][35/63] lr: 4.7758e-03 eta: 20:55:39 time: 0.8233 data_time: 0.0190 memory: 16201 loss_prob: 0.5091 loss_thr: 0.3486 loss_db: 0.0875 loss: 0.9452 2022/08/30 10:49:00 - mmengine - INFO - Epoch(train) [416][40/63] lr: 4.7758e-03 eta: 20:55:11 time: 0.8679 data_time: 0.0467 memory: 16201 loss_prob: 0.5068 loss_thr: 0.3505 loss_db: 0.0854 loss: 0.9427 2022/08/30 10:49:04 - mmengine - INFO - Epoch(train) [416][45/63] lr: 4.7758e-03 eta: 20:55:11 time: 0.8297 data_time: 0.0497 memory: 16201 loss_prob: 0.5621 loss_thr: 0.3722 loss_db: 0.0952 loss: 1.0295 2022/08/30 10:49:09 - mmengine - INFO - Epoch(train) [416][50/63] lr: 4.7758e-03 eta: 20:54:43 time: 0.8059 data_time: 0.0334 memory: 16201 loss_prob: 0.5543 loss_thr: 0.3807 loss_db: 0.0956 loss: 1.0307 2022/08/30 10:49:12 - mmengine - INFO - Epoch(train) [416][55/63] lr: 4.7758e-03 eta: 20:54:43 time: 0.7958 data_time: 0.0337 memory: 16201 loss_prob: 0.5348 loss_thr: 0.3773 loss_db: 0.0938 loss: 1.0060 2022/08/30 10:49:16 - mmengine - INFO - Epoch(train) [416][60/63] lr: 4.7758e-03 eta: 20:54:13 time: 0.7835 data_time: 0.0287 memory: 16201 loss_prob: 0.5592 loss_thr: 0.3929 loss_db: 0.0980 loss: 1.0501 2022/08/30 10:49:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:49:25 - mmengine - INFO - Epoch(train) [417][5/63] lr: 4.7703e-03 eta: 20:54:13 time: 0.9754 data_time: 0.1937 memory: 16201 loss_prob: 0.5812 loss_thr: 0.3887 loss_db: 0.0979 loss: 1.0679 2022/08/30 10:49:29 - mmengine - INFO - Epoch(train) [417][10/63] lr: 4.7703e-03 eta: 20:53:37 time: 1.0975 data_time: 0.2219 memory: 16201 loss_prob: 0.5354 loss_thr: 0.3761 loss_db: 0.0935 loss: 1.0050 2022/08/30 10:49:34 - mmengine - INFO - Epoch(train) [417][15/63] lr: 4.7703e-03 eta: 20:53:37 time: 0.9798 data_time: 0.0511 memory: 16201 loss_prob: 0.5458 loss_thr: 0.3879 loss_db: 0.0955 loss: 1.0292 2022/08/30 10:49:39 - mmengine - INFO - Epoch(train) [417][20/63] lr: 4.7703e-03 eta: 20:53:11 time: 0.9743 data_time: 0.0291 memory: 16201 loss_prob: 0.5256 loss_thr: 0.3754 loss_db: 0.0912 loss: 0.9922 2022/08/30 10:49:44 - mmengine - INFO - Epoch(train) [417][25/63] lr: 4.7703e-03 eta: 20:53:11 time: 0.9327 data_time: 0.0352 memory: 16201 loss_prob: 0.5237 loss_thr: 0.3727 loss_db: 0.0924 loss: 0.9888 2022/08/30 10:49:48 - mmengine - INFO - Epoch(train) [417][30/63] lr: 4.7703e-03 eta: 20:52:44 time: 0.8955 data_time: 0.0343 memory: 16201 loss_prob: 0.5552 loss_thr: 0.3829 loss_db: 0.0976 loss: 1.0358 2022/08/30 10:49:53 - mmengine - INFO - Epoch(train) [417][35/63] lr: 4.7703e-03 eta: 20:52:44 time: 0.9552 data_time: 0.0448 memory: 16201 loss_prob: 0.5671 loss_thr: 0.3914 loss_db: 0.0969 loss: 1.0555 2022/08/30 10:49:58 - mmengine - INFO - Epoch(train) [417][40/63] lr: 4.7703e-03 eta: 20:52:19 time: 0.9844 data_time: 0.0532 memory: 16201 loss_prob: 0.5906 loss_thr: 0.4052 loss_db: 0.1015 loss: 1.0973 2022/08/30 10:50:02 - mmengine - INFO - Epoch(train) [417][45/63] lr: 4.7703e-03 eta: 20:52:19 time: 0.8961 data_time: 0.0346 memory: 16201 loss_prob: 0.5937 loss_thr: 0.4028 loss_db: 0.1039 loss: 1.1005 2022/08/30 10:50:06 - mmengine - INFO - Epoch(train) [417][50/63] lr: 4.7703e-03 eta: 20:51:51 time: 0.8657 data_time: 0.0323 memory: 16201 loss_prob: 0.6001 loss_thr: 0.4108 loss_db: 0.1047 loss: 1.1156 2022/08/30 10:50:11 - mmengine - INFO - Epoch(train) [417][55/63] lr: 4.7703e-03 eta: 20:51:51 time: 0.8467 data_time: 0.0370 memory: 16201 loss_prob: 0.5583 loss_thr: 0.3822 loss_db: 0.0976 loss: 1.0380 2022/08/30 10:50:16 - mmengine - INFO - Epoch(train) [417][60/63] lr: 4.7703e-03 eta: 20:51:25 time: 0.9293 data_time: 0.0415 memory: 16201 loss_prob: 0.5539 loss_thr: 0.3757 loss_db: 0.0971 loss: 1.0268 2022/08/30 10:50:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:50:24 - mmengine - INFO - Epoch(train) [418][5/63] lr: 4.7649e-03 eta: 20:51:25 time: 1.0103 data_time: 0.1958 memory: 16201 loss_prob: 0.5669 loss_thr: 0.3905 loss_db: 0.0973 loss: 1.0548 2022/08/30 10:50:28 - mmengine - INFO - Epoch(train) [418][10/63] lr: 4.7649e-03 eta: 20:50:48 time: 1.0428 data_time: 0.2087 memory: 16201 loss_prob: 0.5834 loss_thr: 0.3974 loss_db: 0.1008 loss: 1.0816 2022/08/30 10:50:33 - mmengine - INFO - Epoch(train) [418][15/63] lr: 4.7649e-03 eta: 20:50:48 time: 0.8923 data_time: 0.0328 memory: 16201 loss_prob: 0.5486 loss_thr: 0.3832 loss_db: 0.0951 loss: 1.0269 2022/08/30 10:50:38 - mmengine - INFO - Epoch(train) [418][20/63] lr: 4.7649e-03 eta: 20:50:22 time: 0.9345 data_time: 0.0188 memory: 16201 loss_prob: 0.4860 loss_thr: 0.3558 loss_db: 0.0844 loss: 0.9262 2022/08/30 10:50:42 - mmengine - INFO - Epoch(train) [418][25/63] lr: 4.7649e-03 eta: 20:50:22 time: 0.9196 data_time: 0.0426 memory: 16201 loss_prob: 0.5592 loss_thr: 0.3694 loss_db: 0.0941 loss: 1.0226 2022/08/30 10:50:46 - mmengine - INFO - Epoch(train) [418][30/63] lr: 4.7649e-03 eta: 20:49:54 time: 0.8596 data_time: 0.0442 memory: 16201 loss_prob: 0.5909 loss_thr: 0.3810 loss_db: 0.0990 loss: 1.0708 2022/08/30 10:50:51 - mmengine - INFO - Epoch(train) [418][35/63] lr: 4.7649e-03 eta: 20:49:54 time: 0.8629 data_time: 0.0445 memory: 16201 loss_prob: 0.5652 loss_thr: 0.3788 loss_db: 0.0975 loss: 1.0415 2022/08/30 10:50:56 - mmengine - INFO - Epoch(train) [418][40/63] lr: 4.7649e-03 eta: 20:49:28 time: 0.9631 data_time: 0.0616 memory: 16201 loss_prob: 0.6043 loss_thr: 0.4023 loss_db: 0.1040 loss: 1.1105 2022/08/30 10:51:00 - mmengine - INFO - Epoch(train) [418][45/63] lr: 4.7649e-03 eta: 20:49:28 time: 0.9398 data_time: 0.0499 memory: 16201 loss_prob: 0.6488 loss_thr: 0.4192 loss_db: 0.1103 loss: 1.1783 2022/08/30 10:51:05 - mmengine - INFO - Epoch(train) [418][50/63] lr: 4.7649e-03 eta: 20:49:02 time: 0.9247 data_time: 0.0381 memory: 16201 loss_prob: 0.6051 loss_thr: 0.3963 loss_db: 0.1051 loss: 1.1066 2022/08/30 10:51:10 - mmengine - INFO - Epoch(train) [418][55/63] lr: 4.7649e-03 eta: 20:49:02 time: 0.9631 data_time: 0.0408 memory: 16201 loss_prob: 0.5697 loss_thr: 0.3869 loss_db: 0.0990 loss: 1.0555 2022/08/30 10:51:15 - mmengine - INFO - Epoch(train) [418][60/63] lr: 4.7649e-03 eta: 20:48:36 time: 0.9423 data_time: 0.0402 memory: 16201 loss_prob: 0.5796 loss_thr: 0.3930 loss_db: 0.0994 loss: 1.0720 2022/08/30 10:51:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:51:23 - mmengine - INFO - Epoch(train) [419][5/63] lr: 4.7594e-03 eta: 20:48:36 time: 0.9952 data_time: 0.2049 memory: 16201 loss_prob: 0.5426 loss_thr: 0.3708 loss_db: 0.0966 loss: 1.0100 2022/08/30 10:51:27 - mmengine - INFO - Epoch(train) [419][10/63] lr: 4.7594e-03 eta: 20:47:58 time: 1.0240 data_time: 0.2128 memory: 16201 loss_prob: 0.6058 loss_thr: 0.3839 loss_db: 0.1023 loss: 1.0920 2022/08/30 10:51:32 - mmengine - INFO - Epoch(train) [419][15/63] lr: 4.7594e-03 eta: 20:47:58 time: 0.8964 data_time: 0.0296 memory: 16201 loss_prob: 0.6253 loss_thr: 0.3936 loss_db: 0.1027 loss: 1.1215 2022/08/30 10:51:36 - mmengine - INFO - Epoch(train) [419][20/63] lr: 4.7594e-03 eta: 20:47:31 time: 0.8936 data_time: 0.0395 memory: 16201 loss_prob: 0.6469 loss_thr: 0.4095 loss_db: 0.1080 loss: 1.1645 2022/08/30 10:51:41 - mmengine - INFO - Epoch(train) [419][25/63] lr: 4.7594e-03 eta: 20:47:31 time: 0.9292 data_time: 0.1000 memory: 16201 loss_prob: 0.6294 loss_thr: 0.4048 loss_db: 0.1074 loss: 1.1416 2022/08/30 10:51:45 - mmengine - INFO - Epoch(train) [419][30/63] lr: 4.7594e-03 eta: 20:47:05 time: 0.9313 data_time: 0.0820 memory: 16201 loss_prob: 0.5880 loss_thr: 0.4045 loss_db: 0.1022 loss: 1.0947 2022/08/30 10:51:50 - mmengine - INFO - Epoch(train) [419][35/63] lr: 4.7594e-03 eta: 20:47:05 time: 0.9127 data_time: 0.0291 memory: 16201 loss_prob: 0.5767 loss_thr: 0.3906 loss_db: 0.1000 loss: 1.0674 2022/08/30 10:51:55 - mmengine - INFO - Epoch(train) [419][40/63] lr: 4.7594e-03 eta: 20:46:39 time: 0.9204 data_time: 0.0284 memory: 16201 loss_prob: 0.5933 loss_thr: 0.3934 loss_db: 0.1004 loss: 1.0871 2022/08/30 10:51:59 - mmengine - INFO - Epoch(train) [419][45/63] lr: 4.7594e-03 eta: 20:46:39 time: 0.9265 data_time: 0.0252 memory: 16201 loss_prob: 0.5813 loss_thr: 0.3916 loss_db: 0.0977 loss: 1.0706 2022/08/30 10:52:05 - mmengine - INFO - Epoch(train) [419][50/63] lr: 4.7594e-03 eta: 20:46:15 time: 1.0517 data_time: 0.0433 memory: 16201 loss_prob: 0.5124 loss_thr: 0.3648 loss_db: 0.0873 loss: 0.9646 2022/08/30 10:52:10 - mmengine - INFO - Epoch(train) [419][55/63] lr: 4.7594e-03 eta: 20:46:15 time: 1.0823 data_time: 0.0522 memory: 16201 loss_prob: 0.5437 loss_thr: 0.3903 loss_db: 0.0917 loss: 1.0258 2022/08/30 10:52:15 - mmengine - INFO - Epoch(train) [419][60/63] lr: 4.7594e-03 eta: 20:45:49 time: 0.9592 data_time: 0.0370 memory: 16201 loss_prob: 0.5649 loss_thr: 0.4036 loss_db: 0.0990 loss: 1.0675 2022/08/30 10:52:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:52:24 - mmengine - INFO - Epoch(train) [420][5/63] lr: 4.7539e-03 eta: 20:45:49 time: 1.0718 data_time: 0.1977 memory: 16201 loss_prob: 0.5466 loss_thr: 0.3558 loss_db: 0.0942 loss: 0.9965 2022/08/30 10:52:28 - mmengine - INFO - Epoch(train) [420][10/63] lr: 4.7539e-03 eta: 20:45:13 time: 1.0770 data_time: 0.2190 memory: 16201 loss_prob: 0.5770 loss_thr: 0.3820 loss_db: 0.0967 loss: 1.0556 2022/08/30 10:52:32 - mmengine - INFO - Epoch(train) [420][15/63] lr: 4.7539e-03 eta: 20:45:13 time: 0.8610 data_time: 0.0391 memory: 16201 loss_prob: 0.5676 loss_thr: 0.3776 loss_db: 0.0970 loss: 1.0422 2022/08/30 10:52:36 - mmengine - INFO - Epoch(train) [420][20/63] lr: 4.7539e-03 eta: 20:44:45 time: 0.8467 data_time: 0.0305 memory: 16201 loss_prob: 0.6172 loss_thr: 0.3833 loss_db: 0.1064 loss: 1.1069 2022/08/30 10:52:41 - mmengine - INFO - Epoch(train) [420][25/63] lr: 4.7539e-03 eta: 20:44:45 time: 0.8848 data_time: 0.0472 memory: 16201 loss_prob: 0.6496 loss_thr: 0.3977 loss_db: 0.1107 loss: 1.1580 2022/08/30 10:52:45 - mmengine - INFO - Epoch(train) [420][30/63] lr: 4.7539e-03 eta: 20:44:18 time: 0.8839 data_time: 0.0372 memory: 16201 loss_prob: 0.5878 loss_thr: 0.3814 loss_db: 0.1008 loss: 1.0700 2022/08/30 10:52:49 - mmengine - INFO - Epoch(train) [420][35/63] lr: 4.7539e-03 eta: 20:44:18 time: 0.8206 data_time: 0.0238 memory: 16201 loss_prob: 0.5826 loss_thr: 0.3897 loss_db: 0.1000 loss: 1.0723 2022/08/30 10:52:54 - mmengine - INFO - Epoch(train) [420][40/63] lr: 4.7539e-03 eta: 20:43:52 time: 0.9122 data_time: 0.0362 memory: 16201 loss_prob: 0.5678 loss_thr: 0.3878 loss_db: 0.0969 loss: 1.0525 2022/08/30 10:52:58 - mmengine - INFO - Epoch(train) [420][45/63] lr: 4.7539e-03 eta: 20:43:52 time: 0.9187 data_time: 0.0350 memory: 16201 loss_prob: 0.5565 loss_thr: 0.3914 loss_db: 0.0968 loss: 1.0446 2022/08/30 10:53:02 - mmengine - INFO - Epoch(train) [420][50/63] lr: 4.7539e-03 eta: 20:43:23 time: 0.8072 data_time: 0.0331 memory: 16201 loss_prob: 0.5985 loss_thr: 0.4054 loss_db: 0.1029 loss: 1.1067 2022/08/30 10:53:06 - mmengine - INFO - Epoch(train) [420][55/63] lr: 4.7539e-03 eta: 20:43:23 time: 0.7812 data_time: 0.0305 memory: 16201 loss_prob: 0.6159 loss_thr: 0.4070 loss_db: 0.1038 loss: 1.1268 2022/08/30 10:53:11 - mmengine - INFO - Epoch(train) [420][60/63] lr: 4.7539e-03 eta: 20:42:55 time: 0.8395 data_time: 0.0332 memory: 16201 loss_prob: 0.6054 loss_thr: 0.3968 loss_db: 0.1037 loss: 1.1059 2022/08/30 10:53:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:53:13 - mmengine - INFO - Saving checkpoint at 420 epochs 2022/08/30 10:53:21 - mmengine - INFO - Epoch(val) [420][5/32] eta: 20:42:55 time: 0.6351 data_time: 0.1304 memory: 16201 2022/08/30 10:53:24 - mmengine - INFO - Epoch(val) [420][10/32] eta: 0:00:15 time: 0.7171 data_time: 0.1584 memory: 15734 2022/08/30 10:53:27 - mmengine - INFO - Epoch(val) [420][15/32] eta: 0:00:15 time: 0.6048 data_time: 0.0466 memory: 15734 2022/08/30 10:53:30 - mmengine - INFO - Epoch(val) [420][20/32] eta: 0:00:07 time: 0.6055 data_time: 0.0512 memory: 15734 2022/08/30 10:53:34 - mmengine - INFO - Epoch(val) [420][25/32] eta: 0:00:07 time: 0.6869 data_time: 0.0765 memory: 15734 2022/08/30 10:53:37 - mmengine - INFO - Epoch(val) [420][30/32] eta: 0:00:01 time: 0.6459 data_time: 0.0466 memory: 15734 2022/08/30 10:53:37 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 10:53:37 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8503, precision: 0.7658, hmean: 0.8058 2022/08/30 10:53:37 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8503, precision: 0.8038, hmean: 0.8264 2022/08/30 10:53:37 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8483, precision: 0.8394, hmean: 0.8439 2022/08/30 10:53:37 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8426, precision: 0.8668, hmean: 0.8545 2022/08/30 10:53:37 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8238, precision: 0.8958, hmean: 0.8583 2022/08/30 10:53:37 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6736, precision: 0.9408, hmean: 0.7851 2022/08/30 10:53:37 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0843, precision: 0.9831, hmean: 0.1552 2022/08/30 10:53:37 - mmengine - INFO - Epoch(val) [420][32/32] icdar/precision: 0.8958 icdar/recall: 0.8238 icdar/hmean: 0.8583 2022/08/30 10:53:43 - mmengine - INFO - Epoch(train) [421][5/63] lr: 4.7484e-03 eta: 0:00:01 time: 0.9650 data_time: 0.1618 memory: 16201 loss_prob: 0.5552 loss_thr: 0.3607 loss_db: 0.0935 loss: 1.0094 2022/08/30 10:53:47 - mmengine - INFO - Epoch(train) [421][10/63] lr: 4.7484e-03 eta: 20:42:17 time: 0.9528 data_time: 0.1707 memory: 16201 loss_prob: 0.5865 loss_thr: 0.3833 loss_db: 0.1044 loss: 1.0742 2022/08/30 10:53:51 - mmengine - INFO - Epoch(train) [421][15/63] lr: 4.7484e-03 eta: 20:42:17 time: 0.8018 data_time: 0.0279 memory: 16201 loss_prob: 0.6054 loss_thr: 0.4000 loss_db: 0.1058 loss: 1.1112 2022/08/30 10:53:56 - mmengine - INFO - Epoch(train) [421][20/63] lr: 4.7484e-03 eta: 20:41:49 time: 0.8414 data_time: 0.0353 memory: 16201 loss_prob: 0.6008 loss_thr: 0.3868 loss_db: 0.1016 loss: 1.0892 2022/08/30 10:53:59 - mmengine - INFO - Epoch(train) [421][25/63] lr: 4.7484e-03 eta: 20:41:49 time: 0.8235 data_time: 0.0343 memory: 16201 loss_prob: 0.6296 loss_thr: 0.4053 loss_db: 0.1043 loss: 1.1392 2022/08/30 10:54:04 - mmengine - INFO - Epoch(train) [421][30/63] lr: 4.7484e-03 eta: 20:41:22 time: 0.8527 data_time: 0.0874 memory: 16201 loss_prob: 0.6207 loss_thr: 0.4212 loss_db: 0.1019 loss: 1.1438 2022/08/30 10:54:08 - mmengine - INFO - Epoch(train) [421][35/63] lr: 4.7484e-03 eta: 20:41:22 time: 0.8775 data_time: 0.1010 memory: 16201 loss_prob: 0.5618 loss_thr: 0.3920 loss_db: 0.0948 loss: 1.0486 2022/08/30 10:54:12 - mmengine - INFO - Epoch(train) [421][40/63] lr: 4.7484e-03 eta: 20:40:53 time: 0.8079 data_time: 0.0302 memory: 16201 loss_prob: 0.5524 loss_thr: 0.3780 loss_db: 0.0964 loss: 1.0268 2022/08/30 10:54:16 - mmengine - INFO - Epoch(train) [421][45/63] lr: 4.7484e-03 eta: 20:40:53 time: 0.8260 data_time: 0.0316 memory: 16201 loss_prob: 0.5999 loss_thr: 0.3932 loss_db: 0.1024 loss: 1.0954 2022/08/30 10:54:21 - mmengine - INFO - Epoch(train) [421][50/63] lr: 4.7484e-03 eta: 20:40:26 time: 0.8375 data_time: 0.0497 memory: 16201 loss_prob: 0.5670 loss_thr: 0.3848 loss_db: 0.0971 loss: 1.0489 2022/08/30 10:54:24 - mmengine - INFO - Epoch(train) [421][55/63] lr: 4.7484e-03 eta: 20:40:26 time: 0.7998 data_time: 0.0328 memory: 16201 loss_prob: 0.5589 loss_thr: 0.3858 loss_db: 0.0973 loss: 1.0419 2022/08/30 10:54:28 - mmengine - INFO - Epoch(train) [421][60/63] lr: 4.7484e-03 eta: 20:39:57 time: 0.7813 data_time: 0.0241 memory: 16201 loss_prob: 0.6159 loss_thr: 0.4111 loss_db: 0.1037 loss: 1.1307 2022/08/30 10:54:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:54:36 - mmengine - INFO - Epoch(train) [422][5/63] lr: 4.7429e-03 eta: 20:39:57 time: 0.9358 data_time: 0.1809 memory: 16201 loss_prob: 0.5530 loss_thr: 0.3534 loss_db: 0.0941 loss: 1.0005 2022/08/30 10:54:40 - mmengine - INFO - Epoch(train) [422][10/63] lr: 4.7429e-03 eta: 20:39:19 time: 0.9876 data_time: 0.1978 memory: 16201 loss_prob: 0.5151 loss_thr: 0.3425 loss_db: 0.0900 loss: 0.9476 2022/08/30 10:54:45 - mmengine - INFO - Epoch(train) [422][15/63] lr: 4.7429e-03 eta: 20:39:19 time: 0.8548 data_time: 0.0542 memory: 16201 loss_prob: 0.5833 loss_thr: 0.3777 loss_db: 0.0992 loss: 1.0602 2022/08/30 10:54:49 - mmengine - INFO - Epoch(train) [422][20/63] lr: 4.7429e-03 eta: 20:38:51 time: 0.8440 data_time: 0.0428 memory: 16201 loss_prob: 0.5922 loss_thr: 0.3933 loss_db: 0.0998 loss: 1.0853 2022/08/30 10:54:53 - mmengine - INFO - Epoch(train) [422][25/63] lr: 4.7429e-03 eta: 20:38:51 time: 0.7897 data_time: 0.0260 memory: 16201 loss_prob: 0.5483 loss_thr: 0.3899 loss_db: 0.0953 loss: 1.0335 2022/08/30 10:54:57 - mmengine - INFO - Epoch(train) [422][30/63] lr: 4.7429e-03 eta: 20:38:23 time: 0.8057 data_time: 0.0301 memory: 16201 loss_prob: 0.5712 loss_thr: 0.3999 loss_db: 0.0999 loss: 1.0711 2022/08/30 10:55:01 - mmengine - INFO - Epoch(train) [422][35/63] lr: 4.7429e-03 eta: 20:38:23 time: 0.8668 data_time: 0.0363 memory: 16201 loss_prob: 0.5751 loss_thr: 0.4117 loss_db: 0.1011 loss: 1.0879 2022/08/30 10:55:05 - mmengine - INFO - Epoch(train) [422][40/63] lr: 4.7429e-03 eta: 20:37:56 time: 0.8439 data_time: 0.0305 memory: 16201 loss_prob: 0.5945 loss_thr: 0.3996 loss_db: 0.1042 loss: 1.0984 2022/08/30 10:55:10 - mmengine - INFO - Epoch(train) [422][45/63] lr: 4.7429e-03 eta: 20:37:56 time: 0.8278 data_time: 0.0404 memory: 16201 loss_prob: 0.6420 loss_thr: 0.4158 loss_db: 0.1072 loss: 1.1650 2022/08/30 10:55:14 - mmengine - INFO - Epoch(train) [422][50/63] lr: 4.7429e-03 eta: 20:37:29 time: 0.8721 data_time: 0.0346 memory: 16201 loss_prob: 0.7820 loss_thr: 0.4389 loss_db: 0.1198 loss: 1.3407 2022/08/30 10:55:18 - mmengine - INFO - Epoch(train) [422][55/63] lr: 4.7429e-03 eta: 20:37:29 time: 0.8409 data_time: 0.0307 memory: 16201 loss_prob: 0.7510 loss_thr: 0.4331 loss_db: 0.1216 loss: 1.3057 2022/08/30 10:55:22 - mmengine - INFO - Epoch(train) [422][60/63] lr: 4.7429e-03 eta: 20:37:01 time: 0.8217 data_time: 0.0426 memory: 16201 loss_prob: 0.6558 loss_thr: 0.4355 loss_db: 0.1148 loss: 1.2061 2022/08/30 10:55:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:55:31 - mmengine - INFO - Epoch(train) [423][5/63] lr: 4.7374e-03 eta: 20:37:01 time: 1.0498 data_time: 0.2582 memory: 16201 loss_prob: 0.5703 loss_thr: 0.4071 loss_db: 0.0990 loss: 1.0765 2022/08/30 10:55:35 - mmengine - INFO - Epoch(train) [423][10/63] lr: 4.7374e-03 eta: 20:36:24 time: 1.0355 data_time: 0.2511 memory: 16201 loss_prob: 0.5684 loss_thr: 0.3992 loss_db: 0.0977 loss: 1.0653 2022/08/30 10:55:39 - mmengine - INFO - Epoch(train) [423][15/63] lr: 4.7374e-03 eta: 20:36:24 time: 0.8046 data_time: 0.0297 memory: 16201 loss_prob: 0.6318 loss_thr: 0.3993 loss_db: 0.1047 loss: 1.1358 2022/08/30 10:55:43 - mmengine - INFO - Epoch(train) [423][20/63] lr: 4.7374e-03 eta: 20:35:55 time: 0.7901 data_time: 0.0219 memory: 16201 loss_prob: 0.6356 loss_thr: 0.3911 loss_db: 0.1076 loss: 1.1343 2022/08/30 10:55:47 - mmengine - INFO - Epoch(train) [423][25/63] lr: 4.7374e-03 eta: 20:35:55 time: 0.8210 data_time: 0.0353 memory: 16201 loss_prob: 0.5950 loss_thr: 0.3926 loss_db: 0.1041 loss: 1.0918 2022/08/30 10:55:51 - mmengine - INFO - Epoch(train) [423][30/63] lr: 4.7374e-03 eta: 20:35:27 time: 0.8171 data_time: 0.0319 memory: 16201 loss_prob: 0.5606 loss_thr: 0.3735 loss_db: 0.0953 loss: 1.0294 2022/08/30 10:55:55 - mmengine - INFO - Epoch(train) [423][35/63] lr: 4.7374e-03 eta: 20:35:27 time: 0.7964 data_time: 0.0274 memory: 16201 loss_prob: 0.5877 loss_thr: 0.3913 loss_db: 0.0996 loss: 1.0786 2022/08/30 10:56:00 - mmengine - INFO - Epoch(train) [423][40/63] lr: 4.7374e-03 eta: 20:35:01 time: 0.8838 data_time: 0.0447 memory: 16201 loss_prob: 0.6199 loss_thr: 0.4118 loss_db: 0.1074 loss: 1.1391 2022/08/30 10:56:04 - mmengine - INFO - Epoch(train) [423][45/63] lr: 4.7374e-03 eta: 20:35:01 time: 0.8781 data_time: 0.0444 memory: 16201 loss_prob: 0.5735 loss_thr: 0.3784 loss_db: 0.0980 loss: 1.0499 2022/08/30 10:56:08 - mmengine - INFO - Epoch(train) [423][50/63] lr: 4.7374e-03 eta: 20:34:32 time: 0.7995 data_time: 0.0319 memory: 16201 loss_prob: 0.5889 loss_thr: 0.3984 loss_db: 0.1001 loss: 1.0874 2022/08/30 10:56:12 - mmengine - INFO - Epoch(train) [423][55/63] lr: 4.7374e-03 eta: 20:34:32 time: 0.8130 data_time: 0.0424 memory: 16201 loss_prob: 0.6191 loss_thr: 0.4222 loss_db: 0.1081 loss: 1.1495 2022/08/30 10:56:17 - mmengine - INFO - Epoch(train) [423][60/63] lr: 4.7374e-03 eta: 20:34:04 time: 0.8135 data_time: 0.0447 memory: 16201 loss_prob: 0.5938 loss_thr: 0.3976 loss_db: 0.1045 loss: 1.0958 2022/08/30 10:56:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:56:24 - mmengine - INFO - Epoch(train) [424][5/63] lr: 4.7319e-03 eta: 20:34:04 time: 0.9503 data_time: 0.2085 memory: 16201 loss_prob: 0.5458 loss_thr: 0.3832 loss_db: 0.0943 loss: 1.0234 2022/08/30 10:56:29 - mmengine - INFO - Epoch(train) [424][10/63] lr: 4.7319e-03 eta: 20:33:27 time: 0.9990 data_time: 0.2097 memory: 16201 loss_prob: 0.5499 loss_thr: 0.3795 loss_db: 0.0978 loss: 1.0273 2022/08/30 10:56:33 - mmengine - INFO - Epoch(train) [424][15/63] lr: 4.7319e-03 eta: 20:33:27 time: 0.8338 data_time: 0.0568 memory: 16201 loss_prob: 0.5537 loss_thr: 0.3794 loss_db: 0.0962 loss: 1.0294 2022/08/30 10:56:37 - mmengine - INFO - Epoch(train) [424][20/63] lr: 4.7319e-03 eta: 20:32:59 time: 0.7933 data_time: 0.0317 memory: 16201 loss_prob: 0.5501 loss_thr: 0.3785 loss_db: 0.0936 loss: 1.0222 2022/08/30 10:56:41 - mmengine - INFO - Epoch(train) [424][25/63] lr: 4.7319e-03 eta: 20:32:59 time: 0.8114 data_time: 0.0420 memory: 16201 loss_prob: 0.5565 loss_thr: 0.3895 loss_db: 0.0963 loss: 1.0423 2022/08/30 10:56:45 - mmengine - INFO - Epoch(train) [424][30/63] lr: 4.7319e-03 eta: 20:32:31 time: 0.8032 data_time: 0.0322 memory: 16201 loss_prob: 0.5628 loss_thr: 0.3763 loss_db: 0.0971 loss: 1.0363 2022/08/30 10:56:49 - mmengine - INFO - Epoch(train) [424][35/63] lr: 4.7319e-03 eta: 20:32:31 time: 0.7952 data_time: 0.0226 memory: 16201 loss_prob: 0.5768 loss_thr: 0.3750 loss_db: 0.0981 loss: 1.0499 2022/08/30 10:56:53 - mmengine - INFO - Epoch(train) [424][40/63] lr: 4.7319e-03 eta: 20:32:02 time: 0.8026 data_time: 0.0369 memory: 16201 loss_prob: 0.5742 loss_thr: 0.3840 loss_db: 0.1002 loss: 1.0583 2022/08/30 10:56:57 - mmengine - INFO - Epoch(train) [424][45/63] lr: 4.7319e-03 eta: 20:32:02 time: 0.8213 data_time: 0.0410 memory: 16201 loss_prob: 0.5608 loss_thr: 0.3826 loss_db: 0.0993 loss: 1.0426 2022/08/30 10:57:01 - mmengine - INFO - Epoch(train) [424][50/63] lr: 4.7319e-03 eta: 20:31:35 time: 0.8285 data_time: 0.0332 memory: 16201 loss_prob: 0.5370 loss_thr: 0.3726 loss_db: 0.0933 loss: 1.0030 2022/08/30 10:57:05 - mmengine - INFO - Epoch(train) [424][55/63] lr: 4.7319e-03 eta: 20:31:35 time: 0.8070 data_time: 0.0273 memory: 16201 loss_prob: 0.5834 loss_thr: 0.3938 loss_db: 0.1011 loss: 1.0783 2022/08/30 10:57:09 - mmengine - INFO - Epoch(train) [424][60/63] lr: 4.7319e-03 eta: 20:31:07 time: 0.7917 data_time: 0.0240 memory: 16201 loss_prob: 0.6394 loss_thr: 0.4139 loss_db: 0.1071 loss: 1.1603 2022/08/30 10:57:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:57:16 - mmengine - INFO - Epoch(train) [425][5/63] lr: 4.7265e-03 eta: 20:31:07 time: 0.9124 data_time: 0.1811 memory: 16201 loss_prob: 0.5744 loss_thr: 0.3874 loss_db: 0.0996 loss: 1.0614 2022/08/30 10:57:20 - mmengine - INFO - Epoch(train) [425][10/63] lr: 4.7265e-03 eta: 20:30:29 time: 0.9672 data_time: 0.1977 memory: 16201 loss_prob: 0.5843 loss_thr: 0.3917 loss_db: 0.1005 loss: 1.0765 2022/08/30 10:57:25 - mmengine - INFO - Epoch(train) [425][15/63] lr: 4.7265e-03 eta: 20:30:29 time: 0.8370 data_time: 0.0301 memory: 16201 loss_prob: 0.5839 loss_thr: 0.3919 loss_db: 0.1013 loss: 1.0771 2022/08/30 10:57:29 - mmengine - INFO - Epoch(train) [425][20/63] lr: 4.7265e-03 eta: 20:30:01 time: 0.8249 data_time: 0.0312 memory: 16201 loss_prob: 0.6353 loss_thr: 0.4068 loss_db: 0.1090 loss: 1.1511 2022/08/30 10:57:33 - mmengine - INFO - Epoch(train) [425][25/63] lr: 4.7265e-03 eta: 20:30:01 time: 0.7909 data_time: 0.0374 memory: 16201 loss_prob: 0.5968 loss_thr: 0.3857 loss_db: 0.1013 loss: 1.0837 2022/08/30 10:57:37 - mmengine - INFO - Epoch(train) [425][30/63] lr: 4.7265e-03 eta: 20:29:33 time: 0.7981 data_time: 0.0239 memory: 16201 loss_prob: 0.5553 loss_thr: 0.3825 loss_db: 0.0946 loss: 1.0324 2022/08/30 10:57:41 - mmengine - INFO - Epoch(train) [425][35/63] lr: 4.7265e-03 eta: 20:29:33 time: 0.7824 data_time: 0.0195 memory: 16201 loss_prob: 0.5951 loss_thr: 0.4130 loss_db: 0.1015 loss: 1.1096 2022/08/30 10:57:45 - mmengine - INFO - Epoch(train) [425][40/63] lr: 4.7265e-03 eta: 20:29:05 time: 0.8177 data_time: 0.0267 memory: 16201 loss_prob: 0.5779 loss_thr: 0.4006 loss_db: 0.1000 loss: 1.0785 2022/08/30 10:57:49 - mmengine - INFO - Epoch(train) [425][45/63] lr: 4.7265e-03 eta: 20:29:05 time: 0.8384 data_time: 0.0372 memory: 16201 loss_prob: 0.5760 loss_thr: 0.3917 loss_db: 0.1008 loss: 1.0685 2022/08/30 10:57:53 - mmengine - INFO - Epoch(train) [425][50/63] lr: 4.7265e-03 eta: 20:28:37 time: 0.8044 data_time: 0.0339 memory: 16201 loss_prob: 0.5870 loss_thr: 0.4098 loss_db: 0.1049 loss: 1.1017 2022/08/30 10:57:58 - mmengine - INFO - Epoch(train) [425][55/63] lr: 4.7265e-03 eta: 20:28:37 time: 0.8721 data_time: 0.0446 memory: 16201 loss_prob: 0.5621 loss_thr: 0.3912 loss_db: 0.1005 loss: 1.0539 2022/08/30 10:58:02 - mmengine - INFO - Epoch(train) [425][60/63] lr: 4.7265e-03 eta: 20:28:11 time: 0.8801 data_time: 0.0510 memory: 16201 loss_prob: 0.5785 loss_thr: 0.3764 loss_db: 0.1008 loss: 1.0558 2022/08/30 10:58:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:58:09 - mmengine - INFO - Epoch(train) [426][5/63] lr: 4.7210e-03 eta: 20:28:11 time: 0.8989 data_time: 0.1761 memory: 16201 loss_prob: 0.5232 loss_thr: 0.3574 loss_db: 0.0916 loss: 0.9722 2022/08/30 10:58:13 - mmengine - INFO - Epoch(train) [426][10/63] lr: 4.7210e-03 eta: 20:27:32 time: 0.9461 data_time: 0.1842 memory: 16201 loss_prob: 0.5385 loss_thr: 0.3654 loss_db: 0.0922 loss: 0.9962 2022/08/30 10:58:17 - mmengine - INFO - Epoch(train) [426][15/63] lr: 4.7210e-03 eta: 20:27:32 time: 0.7811 data_time: 0.0282 memory: 16201 loss_prob: 0.5750 loss_thr: 0.3895 loss_db: 0.1001 loss: 1.0646 2022/08/30 10:58:21 - mmengine - INFO - Epoch(train) [426][20/63] lr: 4.7210e-03 eta: 20:27:05 time: 0.8029 data_time: 0.0202 memory: 16201 loss_prob: 0.6751 loss_thr: 0.4141 loss_db: 0.1154 loss: 1.2046 2022/08/30 10:58:25 - mmengine - INFO - Epoch(train) [426][25/63] lr: 4.7210e-03 eta: 20:27:05 time: 0.8124 data_time: 0.0362 memory: 16201 loss_prob: 0.6860 loss_thr: 0.4284 loss_db: 0.1151 loss: 1.2295 2022/08/30 10:58:29 - mmengine - INFO - Epoch(train) [426][30/63] lr: 4.7210e-03 eta: 20:26:36 time: 0.7797 data_time: 0.0278 memory: 16201 loss_prob: 0.5944 loss_thr: 0.3958 loss_db: 0.1034 loss: 1.0936 2022/08/30 10:58:33 - mmengine - INFO - Epoch(train) [426][35/63] lr: 4.7210e-03 eta: 20:26:36 time: 0.7909 data_time: 0.0223 memory: 16201 loss_prob: 0.5508 loss_thr: 0.3669 loss_db: 0.0987 loss: 1.0164 2022/08/30 10:58:37 - mmengine - INFO - Epoch(train) [426][40/63] lr: 4.7210e-03 eta: 20:26:09 time: 0.8360 data_time: 0.0458 memory: 16201 loss_prob: 0.5694 loss_thr: 0.3832 loss_db: 0.1011 loss: 1.0537 2022/08/30 10:58:41 - mmengine - INFO - Epoch(train) [426][45/63] lr: 4.7210e-03 eta: 20:26:09 time: 0.8239 data_time: 0.0449 memory: 16201 loss_prob: 0.5877 loss_thr: 0.3945 loss_db: 0.1015 loss: 1.0837 2022/08/30 10:58:45 - mmengine - INFO - Epoch(train) [426][50/63] lr: 4.7210e-03 eta: 20:25:41 time: 0.7801 data_time: 0.0299 memory: 16201 loss_prob: 0.5595 loss_thr: 0.3876 loss_db: 0.0963 loss: 1.0435 2022/08/30 10:58:49 - mmengine - INFO - Epoch(train) [426][55/63] lr: 4.7210e-03 eta: 20:25:41 time: 0.7906 data_time: 0.0431 memory: 16201 loss_prob: 0.5516 loss_thr: 0.3710 loss_db: 0.0960 loss: 1.0185 2022/08/30 10:58:53 - mmengine - INFO - Epoch(train) [426][60/63] lr: 4.7210e-03 eta: 20:25:13 time: 0.8208 data_time: 0.0470 memory: 16201 loss_prob: 0.5573 loss_thr: 0.3701 loss_db: 0.0950 loss: 1.0225 2022/08/30 10:58:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:59:01 - mmengine - INFO - Epoch(train) [427][5/63] lr: 4.7155e-03 eta: 20:25:13 time: 0.9547 data_time: 0.2218 memory: 16201 loss_prob: 0.5577 loss_thr: 0.3777 loss_db: 0.0966 loss: 1.0321 2022/08/30 10:59:05 - mmengine - INFO - Epoch(train) [427][10/63] lr: 4.7155e-03 eta: 20:24:36 time: 1.0052 data_time: 0.2373 memory: 16201 loss_prob: 0.6096 loss_thr: 0.3961 loss_db: 0.1027 loss: 1.1084 2022/08/30 10:59:09 - mmengine - INFO - Epoch(train) [427][15/63] lr: 4.7155e-03 eta: 20:24:36 time: 0.7920 data_time: 0.0314 memory: 16201 loss_prob: 0.5986 loss_thr: 0.3909 loss_db: 0.1002 loss: 1.0898 2022/08/30 10:59:13 - mmengine - INFO - Epoch(train) [427][20/63] lr: 4.7155e-03 eta: 20:24:08 time: 0.7794 data_time: 0.0229 memory: 16201 loss_prob: 0.5401 loss_thr: 0.3844 loss_db: 0.0954 loss: 1.0199 2022/08/30 10:59:17 - mmengine - INFO - Epoch(train) [427][25/63] lr: 4.7155e-03 eta: 20:24:08 time: 0.8088 data_time: 0.0418 memory: 16201 loss_prob: 0.5799 loss_thr: 0.4028 loss_db: 0.1023 loss: 1.0850 2022/08/30 10:59:21 - mmengine - INFO - Epoch(train) [427][30/63] lr: 4.7155e-03 eta: 20:23:40 time: 0.8035 data_time: 0.0329 memory: 16201 loss_prob: 0.5773 loss_thr: 0.3821 loss_db: 0.0982 loss: 1.0577 2022/08/30 10:59:25 - mmengine - INFO - Epoch(train) [427][35/63] lr: 4.7155e-03 eta: 20:23:40 time: 0.8087 data_time: 0.0217 memory: 16201 loss_prob: 0.5692 loss_thr: 0.3901 loss_db: 0.0974 loss: 1.0567 2022/08/30 10:59:29 - mmengine - INFO - Epoch(train) [427][40/63] lr: 4.7155e-03 eta: 20:23:12 time: 0.8078 data_time: 0.0290 memory: 16201 loss_prob: 0.5586 loss_thr: 0.3970 loss_db: 0.0977 loss: 1.0533 2022/08/30 10:59:33 - mmengine - INFO - Epoch(train) [427][45/63] lr: 4.7155e-03 eta: 20:23:12 time: 0.7821 data_time: 0.0276 memory: 16201 loss_prob: 0.5489 loss_thr: 0.3815 loss_db: 0.0962 loss: 1.0266 2022/08/30 10:59:37 - mmengine - INFO - Epoch(train) [427][50/63] lr: 4.7155e-03 eta: 20:22:44 time: 0.7875 data_time: 0.0289 memory: 16201 loss_prob: 0.5384 loss_thr: 0.3768 loss_db: 0.0922 loss: 1.0074 2022/08/30 10:59:41 - mmengine - INFO - Epoch(train) [427][55/63] lr: 4.7155e-03 eta: 20:22:44 time: 0.7918 data_time: 0.0308 memory: 16201 loss_prob: 0.5758 loss_thr: 0.4024 loss_db: 0.0986 loss: 1.0769 2022/08/30 10:59:46 - mmengine - INFO - Epoch(train) [427][60/63] lr: 4.7155e-03 eta: 20:22:17 time: 0.8540 data_time: 0.0384 memory: 16201 loss_prob: 0.6519 loss_thr: 0.4238 loss_db: 0.1110 loss: 1.1867 2022/08/30 10:59:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 10:59:54 - mmengine - INFO - Epoch(train) [428][5/63] lr: 4.7100e-03 eta: 20:22:17 time: 0.9936 data_time: 0.2543 memory: 16201 loss_prob: 0.5670 loss_thr: 0.3698 loss_db: 0.0980 loss: 1.0347 2022/08/30 10:59:58 - mmengine - INFO - Epoch(train) [428][10/63] lr: 4.7100e-03 eta: 20:21:41 time: 1.0490 data_time: 0.2715 memory: 16201 loss_prob: 0.5102 loss_thr: 0.3557 loss_db: 0.0914 loss: 0.9573 2022/08/30 11:00:02 - mmengine - INFO - Epoch(train) [428][15/63] lr: 4.7100e-03 eta: 20:21:41 time: 0.8026 data_time: 0.0348 memory: 16201 loss_prob: 0.5840 loss_thr: 0.4062 loss_db: 0.1017 loss: 1.0920 2022/08/30 11:00:06 - mmengine - INFO - Epoch(train) [428][20/63] lr: 4.7100e-03 eta: 20:21:13 time: 0.7841 data_time: 0.0339 memory: 16201 loss_prob: 0.6467 loss_thr: 0.4359 loss_db: 0.1109 loss: 1.1936 2022/08/30 11:00:11 - mmengine - INFO - Epoch(train) [428][25/63] lr: 4.7100e-03 eta: 20:21:13 time: 0.8425 data_time: 0.0872 memory: 16201 loss_prob: 0.5867 loss_thr: 0.4040 loss_db: 0.1002 loss: 1.0909 2022/08/30 11:00:15 - mmengine - INFO - Epoch(train) [428][30/63] lr: 4.7100e-03 eta: 20:20:46 time: 0.8489 data_time: 0.0728 memory: 16201 loss_prob: 0.5649 loss_thr: 0.3900 loss_db: 0.0974 loss: 1.0523 2022/08/30 11:00:18 - mmengine - INFO - Epoch(train) [428][35/63] lr: 4.7100e-03 eta: 20:20:46 time: 0.7856 data_time: 0.0225 memory: 16201 loss_prob: 0.6205 loss_thr: 0.4088 loss_db: 0.1081 loss: 1.1373 2022/08/30 11:00:23 - mmengine - INFO - Epoch(train) [428][40/63] lr: 4.7100e-03 eta: 20:20:18 time: 0.7928 data_time: 0.0454 memory: 16201 loss_prob: 0.6008 loss_thr: 0.4018 loss_db: 0.1034 loss: 1.1061 2022/08/30 11:00:27 - mmengine - INFO - Epoch(train) [428][45/63] lr: 4.7100e-03 eta: 20:20:18 time: 0.8209 data_time: 0.0527 memory: 16201 loss_prob: 0.6300 loss_thr: 0.3914 loss_db: 0.1059 loss: 1.1273 2022/08/30 11:00:31 - mmengine - INFO - Epoch(train) [428][50/63] lr: 4.7100e-03 eta: 20:19:51 time: 0.7990 data_time: 0.0308 memory: 16201 loss_prob: 0.6718 loss_thr: 0.3996 loss_db: 0.1126 loss: 1.1841 2022/08/30 11:00:35 - mmengine - INFO - Epoch(train) [428][55/63] lr: 4.7100e-03 eta: 20:19:51 time: 0.8221 data_time: 0.0319 memory: 16201 loss_prob: 0.5979 loss_thr: 0.3943 loss_db: 0.0998 loss: 1.0920 2022/08/30 11:00:39 - mmengine - INFO - Epoch(train) [428][60/63] lr: 4.7100e-03 eta: 20:19:23 time: 0.8351 data_time: 0.0351 memory: 16201 loss_prob: 0.5228 loss_thr: 0.3806 loss_db: 0.0890 loss: 0.9924 2022/08/30 11:00:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:00:46 - mmengine - INFO - Epoch(train) [429][5/63] lr: 4.7045e-03 eta: 20:19:23 time: 0.9030 data_time: 0.1644 memory: 16201 loss_prob: 0.5333 loss_thr: 0.3746 loss_db: 0.0953 loss: 1.0033 2022/08/30 11:00:51 - mmengine - INFO - Epoch(train) [429][10/63] lr: 4.7045e-03 eta: 20:18:46 time: 0.9681 data_time: 0.1991 memory: 16201 loss_prob: 0.5773 loss_thr: 0.3814 loss_db: 0.1009 loss: 1.0595 2022/08/30 11:00:55 - mmengine - INFO - Epoch(train) [429][15/63] lr: 4.7045e-03 eta: 20:18:46 time: 0.8483 data_time: 0.0512 memory: 16201 loss_prob: 0.5883 loss_thr: 0.3890 loss_db: 0.1012 loss: 1.0786 2022/08/30 11:00:59 - mmengine - INFO - Epoch(train) [429][20/63] lr: 4.7045e-03 eta: 20:18:19 time: 0.8307 data_time: 0.0363 memory: 16201 loss_prob: 0.5825 loss_thr: 0.3898 loss_db: 0.1015 loss: 1.0738 2022/08/30 11:01:03 - mmengine - INFO - Epoch(train) [429][25/63] lr: 4.7045e-03 eta: 20:18:19 time: 0.8056 data_time: 0.0526 memory: 16201 loss_prob: 0.5736 loss_thr: 0.3840 loss_db: 0.0995 loss: 1.0571 2022/08/30 11:01:07 - mmengine - INFO - Epoch(train) [429][30/63] lr: 4.7045e-03 eta: 20:17:51 time: 0.8147 data_time: 0.0395 memory: 16201 loss_prob: 0.5717 loss_thr: 0.3858 loss_db: 0.0995 loss: 1.0570 2022/08/30 11:01:11 - mmengine - INFO - Epoch(train) [429][35/63] lr: 4.7045e-03 eta: 20:17:51 time: 0.8101 data_time: 0.0256 memory: 16201 loss_prob: 0.5488 loss_thr: 0.3744 loss_db: 0.0954 loss: 1.0186 2022/08/30 11:01:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:01:15 - mmengine - INFO - Epoch(train) [429][40/63] lr: 4.7045e-03 eta: 20:17:24 time: 0.8153 data_time: 0.0392 memory: 16201 loss_prob: 0.5513 loss_thr: 0.3719 loss_db: 0.0950 loss: 1.0182 2022/08/30 11:01:19 - mmengine - INFO - Epoch(train) [429][45/63] lr: 4.7045e-03 eta: 20:17:24 time: 0.8118 data_time: 0.0380 memory: 16201 loss_prob: 0.5384 loss_thr: 0.3593 loss_db: 0.0933 loss: 0.9910 2022/08/30 11:01:23 - mmengine - INFO - Epoch(train) [429][50/63] lr: 4.7045e-03 eta: 20:16:56 time: 0.7806 data_time: 0.0214 memory: 16201 loss_prob: 0.5015 loss_thr: 0.3423 loss_db: 0.0863 loss: 0.9301 2022/08/30 11:01:27 - mmengine - INFO - Epoch(train) [429][55/63] lr: 4.7045e-03 eta: 20:16:56 time: 0.7986 data_time: 0.0295 memory: 16201 loss_prob: 0.5706 loss_thr: 0.3797 loss_db: 0.0964 loss: 1.0467 2022/08/30 11:01:31 - mmengine - INFO - Epoch(train) [429][60/63] lr: 4.7045e-03 eta: 20:16:28 time: 0.8073 data_time: 0.0371 memory: 16201 loss_prob: 0.6121 loss_thr: 0.4017 loss_db: 0.1049 loss: 1.1187 2022/08/30 11:01:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:01:41 - mmengine - INFO - Epoch(train) [430][5/63] lr: 4.6990e-03 eta: 20:16:28 time: 1.1131 data_time: 0.3585 memory: 16201 loss_prob: 0.5767 loss_thr: 0.3783 loss_db: 0.0984 loss: 1.0535 2022/08/30 11:01:45 - mmengine - INFO - Epoch(train) [430][10/63] lr: 4.6990e-03 eta: 20:15:55 time: 1.2033 data_time: 0.3649 memory: 16201 loss_prob: 0.5262 loss_thr: 0.3621 loss_db: 0.0911 loss: 0.9795 2022/08/30 11:01:49 - mmengine - INFO - Epoch(train) [430][15/63] lr: 4.6990e-03 eta: 20:15:55 time: 0.8519 data_time: 0.0305 memory: 16201 loss_prob: 0.5417 loss_thr: 0.3708 loss_db: 0.0969 loss: 1.0093 2022/08/30 11:01:53 - mmengine - INFO - Epoch(train) [430][20/63] lr: 4.6990e-03 eta: 20:15:28 time: 0.8043 data_time: 0.0301 memory: 16201 loss_prob: 0.5759 loss_thr: 0.3772 loss_db: 0.0978 loss: 1.0509 2022/08/30 11:01:57 - mmengine - INFO - Epoch(train) [430][25/63] lr: 4.6990e-03 eta: 20:15:28 time: 0.8023 data_time: 0.0344 memory: 16201 loss_prob: 0.5702 loss_thr: 0.3790 loss_db: 0.0952 loss: 1.0444 2022/08/30 11:02:01 - mmengine - INFO - Epoch(train) [430][30/63] lr: 4.6990e-03 eta: 20:15:00 time: 0.7918 data_time: 0.0291 memory: 16201 loss_prob: 0.4946 loss_thr: 0.3591 loss_db: 0.0884 loss: 0.9421 2022/08/30 11:02:05 - mmengine - INFO - Epoch(train) [430][35/63] lr: 4.6990e-03 eta: 20:15:00 time: 0.8098 data_time: 0.0398 memory: 16201 loss_prob: 0.5204 loss_thr: 0.3726 loss_db: 0.0929 loss: 0.9860 2022/08/30 11:02:09 - mmengine - INFO - Epoch(train) [430][40/63] lr: 4.6990e-03 eta: 20:14:33 time: 0.8156 data_time: 0.0398 memory: 16201 loss_prob: 0.6064 loss_thr: 0.4142 loss_db: 0.1051 loss: 1.1257 2022/08/30 11:02:13 - mmengine - INFO - Epoch(train) [430][45/63] lr: 4.6990e-03 eta: 20:14:33 time: 0.7888 data_time: 0.0249 memory: 16201 loss_prob: 0.5818 loss_thr: 0.4046 loss_db: 0.0992 loss: 1.0857 2022/08/30 11:02:17 - mmengine - INFO - Epoch(train) [430][50/63] lr: 4.6990e-03 eta: 20:14:05 time: 0.8011 data_time: 0.0237 memory: 16201 loss_prob: 0.5278 loss_thr: 0.3794 loss_db: 0.0905 loss: 0.9977 2022/08/30 11:02:21 - mmengine - INFO - Epoch(train) [430][55/63] lr: 4.6990e-03 eta: 20:14:05 time: 0.8167 data_time: 0.0419 memory: 16201 loss_prob: 0.5266 loss_thr: 0.3652 loss_db: 0.0892 loss: 0.9809 2022/08/30 11:02:25 - mmengine - INFO - Epoch(train) [430][60/63] lr: 4.6990e-03 eta: 20:13:38 time: 0.8084 data_time: 0.0447 memory: 16201 loss_prob: 0.5554 loss_thr: 0.3797 loss_db: 0.0951 loss: 1.0302 2022/08/30 11:02:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:02:33 - mmengine - INFO - Epoch(train) [431][5/63] lr: 4.6935e-03 eta: 20:13:38 time: 0.8901 data_time: 0.1683 memory: 16201 loss_prob: 0.5873 loss_thr: 0.3906 loss_db: 0.1002 loss: 1.0781 2022/08/30 11:02:37 - mmengine - INFO - Epoch(train) [431][10/63] lr: 4.6935e-03 eta: 20:13:01 time: 0.9812 data_time: 0.2145 memory: 16201 loss_prob: 0.5196 loss_thr: 0.3563 loss_db: 0.0901 loss: 0.9660 2022/08/30 11:02:41 - mmengine - INFO - Epoch(train) [431][15/63] lr: 4.6935e-03 eta: 20:13:01 time: 0.8473 data_time: 0.0718 memory: 16201 loss_prob: 0.5525 loss_thr: 0.3737 loss_db: 0.0974 loss: 1.0236 2022/08/30 11:02:45 - mmengine - INFO - Epoch(train) [431][20/63] lr: 4.6935e-03 eta: 20:12:33 time: 0.8014 data_time: 0.0281 memory: 16201 loss_prob: 0.6149 loss_thr: 0.4078 loss_db: 0.1068 loss: 1.1295 2022/08/30 11:02:49 - mmengine - INFO - Epoch(train) [431][25/63] lr: 4.6935e-03 eta: 20:12:33 time: 0.8213 data_time: 0.0356 memory: 16201 loss_prob: 0.6180 loss_thr: 0.4239 loss_db: 0.1040 loss: 1.1460 2022/08/30 11:02:53 - mmengine - INFO - Epoch(train) [431][30/63] lr: 4.6935e-03 eta: 20:12:06 time: 0.8126 data_time: 0.0395 memory: 16201 loss_prob: 0.5965 loss_thr: 0.4139 loss_db: 0.1031 loss: 1.1135 2022/08/30 11:02:57 - mmengine - INFO - Epoch(train) [431][35/63] lr: 4.6935e-03 eta: 20:12:06 time: 0.7910 data_time: 0.0383 memory: 16201 loss_prob: 0.5953 loss_thr: 0.3988 loss_db: 0.1031 loss: 1.0971 2022/08/30 11:03:01 - mmengine - INFO - Epoch(train) [431][40/63] lr: 4.6935e-03 eta: 20:11:39 time: 0.7944 data_time: 0.0360 memory: 16201 loss_prob: 0.5707 loss_thr: 0.3830 loss_db: 0.0974 loss: 1.0511 2022/08/30 11:03:06 - mmengine - INFO - Epoch(train) [431][45/63] lr: 4.6935e-03 eta: 20:11:39 time: 0.8299 data_time: 0.0324 memory: 16201 loss_prob: 0.5175 loss_thr: 0.3620 loss_db: 0.0903 loss: 0.9698 2022/08/30 11:03:10 - mmengine - INFO - Epoch(train) [431][50/63] lr: 4.6935e-03 eta: 20:11:12 time: 0.8383 data_time: 0.0295 memory: 16201 loss_prob: 0.5249 loss_thr: 0.3808 loss_db: 0.0927 loss: 0.9984 2022/08/30 11:03:14 - mmengine - INFO - Epoch(train) [431][55/63] lr: 4.6935e-03 eta: 20:11:12 time: 0.8059 data_time: 0.0299 memory: 16201 loss_prob: 0.5447 loss_thr: 0.3889 loss_db: 0.0955 loss: 1.0291 2022/08/30 11:03:18 - mmengine - INFO - Epoch(train) [431][60/63] lr: 4.6935e-03 eta: 20:10:44 time: 0.8105 data_time: 0.0404 memory: 16201 loss_prob: 0.5355 loss_thr: 0.3700 loss_db: 0.0935 loss: 0.9989 2022/08/30 11:03:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:03:25 - mmengine - INFO - Epoch(train) [432][5/63] lr: 4.6880e-03 eta: 20:10:44 time: 0.8733 data_time: 0.1677 memory: 16201 loss_prob: 0.5007 loss_thr: 0.3563 loss_db: 0.0861 loss: 0.9432 2022/08/30 11:03:29 - mmengine - INFO - Epoch(train) [432][10/63] lr: 4.6880e-03 eta: 20:10:07 time: 0.9246 data_time: 0.1811 memory: 16201 loss_prob: 0.5324 loss_thr: 0.3677 loss_db: 0.0932 loss: 0.9933 2022/08/30 11:03:33 - mmengine - INFO - Epoch(train) [432][15/63] lr: 4.6880e-03 eta: 20:10:07 time: 0.7925 data_time: 0.0263 memory: 16201 loss_prob: 0.5306 loss_thr: 0.3549 loss_db: 0.0901 loss: 0.9756 2022/08/30 11:03:37 - mmengine - INFO - Epoch(train) [432][20/63] lr: 4.6880e-03 eta: 20:09:40 time: 0.8484 data_time: 0.0278 memory: 16201 loss_prob: 0.5816 loss_thr: 0.3787 loss_db: 0.0995 loss: 1.0598 2022/08/30 11:03:42 - mmengine - INFO - Epoch(train) [432][25/63] lr: 4.6880e-03 eta: 20:09:40 time: 0.8654 data_time: 0.0481 memory: 16201 loss_prob: 0.5617 loss_thr: 0.3835 loss_db: 0.0985 loss: 1.0437 2022/08/30 11:03:45 - mmengine - INFO - Epoch(train) [432][30/63] lr: 4.6880e-03 eta: 20:09:13 time: 0.8063 data_time: 0.0401 memory: 16201 loss_prob: 0.4900 loss_thr: 0.3556 loss_db: 0.0852 loss: 0.9308 2022/08/30 11:03:49 - mmengine - INFO - Epoch(train) [432][35/63] lr: 4.6880e-03 eta: 20:09:13 time: 0.7898 data_time: 0.0283 memory: 16201 loss_prob: 0.5399 loss_thr: 0.3851 loss_db: 0.0948 loss: 1.0198 2022/08/30 11:03:54 - mmengine - INFO - Epoch(train) [432][40/63] lr: 4.6880e-03 eta: 20:08:46 time: 0.8181 data_time: 0.0519 memory: 16201 loss_prob: 0.5228 loss_thr: 0.3709 loss_db: 0.0912 loss: 0.9848 2022/08/30 11:03:58 - mmengine - INFO - Epoch(train) [432][45/63] lr: 4.6880e-03 eta: 20:08:46 time: 0.8123 data_time: 0.0518 memory: 16201 loss_prob: 0.4798 loss_thr: 0.3469 loss_db: 0.0822 loss: 0.9089 2022/08/30 11:04:02 - mmengine - INFO - Epoch(train) [432][50/63] lr: 4.6880e-03 eta: 20:08:18 time: 0.7875 data_time: 0.0286 memory: 16201 loss_prob: 0.5265 loss_thr: 0.3668 loss_db: 0.0918 loss: 0.9852 2022/08/30 11:04:06 - mmengine - INFO - Epoch(train) [432][55/63] lr: 4.6880e-03 eta: 20:08:18 time: 0.8297 data_time: 0.0297 memory: 16201 loss_prob: 0.5453 loss_thr: 0.3775 loss_db: 0.0952 loss: 1.0180 2022/08/30 11:04:10 - mmengine - INFO - Epoch(train) [432][60/63] lr: 4.6880e-03 eta: 20:07:51 time: 0.8281 data_time: 0.0320 memory: 16201 loss_prob: 0.5877 loss_thr: 0.3948 loss_db: 0.0994 loss: 1.0820 2022/08/30 11:04:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:04:17 - mmengine - INFO - Epoch(train) [433][5/63] lr: 4.6825e-03 eta: 20:07:51 time: 0.9208 data_time: 0.1871 memory: 16201 loss_prob: 0.6006 loss_thr: 0.4050 loss_db: 0.1059 loss: 1.1115 2022/08/30 11:04:22 - mmengine - INFO - Epoch(train) [433][10/63] lr: 4.6825e-03 eta: 20:07:14 time: 0.9658 data_time: 0.2074 memory: 16201 loss_prob: 0.5422 loss_thr: 0.3779 loss_db: 0.0957 loss: 1.0158 2022/08/30 11:04:26 - mmengine - INFO - Epoch(train) [433][15/63] lr: 4.6825e-03 eta: 20:07:14 time: 0.8474 data_time: 0.0401 memory: 16201 loss_prob: 0.5146 loss_thr: 0.3731 loss_db: 0.0894 loss: 0.9771 2022/08/30 11:04:30 - mmengine - INFO - Epoch(train) [433][20/63] lr: 4.6825e-03 eta: 20:06:48 time: 0.8390 data_time: 0.0237 memory: 16201 loss_prob: 0.5028 loss_thr: 0.3627 loss_db: 0.0887 loss: 0.9542 2022/08/30 11:04:34 - mmengine - INFO - Epoch(train) [433][25/63] lr: 4.6825e-03 eta: 20:06:48 time: 0.7853 data_time: 0.0268 memory: 16201 loss_prob: 0.5121 loss_thr: 0.3526 loss_db: 0.0902 loss: 0.9549 2022/08/30 11:04:38 - mmengine - INFO - Epoch(train) [433][30/63] lr: 4.6825e-03 eta: 20:06:20 time: 0.7860 data_time: 0.0371 memory: 16201 loss_prob: 0.5576 loss_thr: 0.3832 loss_db: 0.0977 loss: 1.0385 2022/08/30 11:04:42 - mmengine - INFO - Epoch(train) [433][35/63] lr: 4.6825e-03 eta: 20:06:20 time: 0.7856 data_time: 0.0394 memory: 16201 loss_prob: 0.6146 loss_thr: 0.4042 loss_db: 0.1071 loss: 1.1260 2022/08/30 11:04:46 - mmengine - INFO - Epoch(train) [433][40/63] lr: 4.6825e-03 eta: 20:05:53 time: 0.7999 data_time: 0.0367 memory: 16201 loss_prob: 0.6060 loss_thr: 0.3821 loss_db: 0.1051 loss: 1.0932 2022/08/30 11:04:50 - mmengine - INFO - Epoch(train) [433][45/63] lr: 4.6825e-03 eta: 20:05:53 time: 0.8103 data_time: 0.0384 memory: 16201 loss_prob: 0.5797 loss_thr: 0.3778 loss_db: 0.0991 loss: 1.0566 2022/08/30 11:04:54 - mmengine - INFO - Epoch(train) [433][50/63] lr: 4.6825e-03 eta: 20:05:25 time: 0.7948 data_time: 0.0276 memory: 16201 loss_prob: 0.6085 loss_thr: 0.4125 loss_db: 0.1039 loss: 1.1248 2022/08/30 11:04:58 - mmengine - INFO - Epoch(train) [433][55/63] lr: 4.6825e-03 eta: 20:05:25 time: 0.8262 data_time: 0.0378 memory: 16201 loss_prob: 0.5673 loss_thr: 0.4039 loss_db: 0.1006 loss: 1.0718 2022/08/30 11:05:02 - mmengine - INFO - Epoch(train) [433][60/63] lr: 4.6825e-03 eta: 20:04:59 time: 0.8344 data_time: 0.0443 memory: 16201 loss_prob: 0.5385 loss_thr: 0.3844 loss_db: 0.0959 loss: 1.0188 2022/08/30 11:05:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:05:10 - mmengine - INFO - Epoch(train) [434][5/63] lr: 4.6770e-03 eta: 20:04:59 time: 0.9270 data_time: 0.1920 memory: 16201 loss_prob: 0.5976 loss_thr: 0.3942 loss_db: 0.1005 loss: 1.0923 2022/08/30 11:05:14 - mmengine - INFO - Epoch(train) [434][10/63] lr: 4.6770e-03 eta: 20:04:22 time: 0.9739 data_time: 0.2087 memory: 16201 loss_prob: 0.5958 loss_thr: 0.3930 loss_db: 0.0990 loss: 1.0878 2022/08/30 11:05:18 - mmengine - INFO - Epoch(train) [434][15/63] lr: 4.6770e-03 eta: 20:04:22 time: 0.8204 data_time: 0.0347 memory: 16201 loss_prob: 0.5481 loss_thr: 0.3799 loss_db: 0.0931 loss: 1.0212 2022/08/30 11:05:22 - mmengine - INFO - Epoch(train) [434][20/63] lr: 4.6770e-03 eta: 20:03:55 time: 0.8155 data_time: 0.0292 memory: 16201 loss_prob: 0.5331 loss_thr: 0.3841 loss_db: 0.0932 loss: 1.0104 2022/08/30 11:05:26 - mmengine - INFO - Epoch(train) [434][25/63] lr: 4.6770e-03 eta: 20:03:55 time: 0.8354 data_time: 0.0662 memory: 16201 loss_prob: 0.5431 loss_thr: 0.3794 loss_db: 0.0914 loss: 1.0139 2022/08/30 11:05:30 - mmengine - INFO - Epoch(train) [434][30/63] lr: 4.6770e-03 eta: 20:03:28 time: 0.8417 data_time: 0.0542 memory: 16201 loss_prob: 0.5752 loss_thr: 0.3799 loss_db: 0.0949 loss: 1.0501 2022/08/30 11:05:34 - mmengine - INFO - Epoch(train) [434][35/63] lr: 4.6770e-03 eta: 20:03:28 time: 0.7972 data_time: 0.0199 memory: 16201 loss_prob: 0.5530 loss_thr: 0.3723 loss_db: 0.0952 loss: 1.0204 2022/08/30 11:05:38 - mmengine - INFO - Epoch(train) [434][40/63] lr: 4.6770e-03 eta: 20:03:01 time: 0.7834 data_time: 0.0310 memory: 16201 loss_prob: 0.5188 loss_thr: 0.3542 loss_db: 0.0888 loss: 0.9619 2022/08/30 11:05:42 - mmengine - INFO - Epoch(train) [434][45/63] lr: 4.6770e-03 eta: 20:03:01 time: 0.7776 data_time: 0.0303 memory: 16201 loss_prob: 0.5052 loss_thr: 0.3572 loss_db: 0.0877 loss: 0.9502 2022/08/30 11:05:46 - mmengine - INFO - Epoch(train) [434][50/63] lr: 4.6770e-03 eta: 20:02:34 time: 0.8123 data_time: 0.0291 memory: 16201 loss_prob: 0.5436 loss_thr: 0.3804 loss_db: 0.0965 loss: 1.0205 2022/08/30 11:05:50 - mmengine - INFO - Epoch(train) [434][55/63] lr: 4.6770e-03 eta: 20:02:34 time: 0.8285 data_time: 0.0349 memory: 16201 loss_prob: 0.5090 loss_thr: 0.3589 loss_db: 0.0894 loss: 0.9574 2022/08/30 11:05:55 - mmengine - INFO - Epoch(train) [434][60/63] lr: 4.6770e-03 eta: 20:02:07 time: 0.8301 data_time: 0.0342 memory: 16201 loss_prob: 0.4978 loss_thr: 0.3473 loss_db: 0.0848 loss: 0.9299 2022/08/30 11:05:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:06:02 - mmengine - INFO - Epoch(train) [435][5/63] lr: 4.6715e-03 eta: 20:02:07 time: 0.9390 data_time: 0.1624 memory: 16201 loss_prob: 0.6091 loss_thr: 0.3872 loss_db: 0.1077 loss: 1.1039 2022/08/30 11:06:06 - mmengine - INFO - Epoch(train) [435][10/63] lr: 4.6715e-03 eta: 20:01:30 time: 0.9531 data_time: 0.1831 memory: 16201 loss_prob: 0.6121 loss_thr: 0.3990 loss_db: 0.1055 loss: 1.1166 2022/08/30 11:06:10 - mmengine - INFO - Epoch(train) [435][15/63] lr: 4.6715e-03 eta: 20:01:30 time: 0.7956 data_time: 0.0324 memory: 16201 loss_prob: 0.5426 loss_thr: 0.3619 loss_db: 0.0950 loss: 0.9995 2022/08/30 11:06:14 - mmengine - INFO - Epoch(train) [435][20/63] lr: 4.6715e-03 eta: 20:01:03 time: 0.7876 data_time: 0.0202 memory: 16201 loss_prob: 0.5082 loss_thr: 0.3464 loss_db: 0.0889 loss: 0.9435 2022/08/30 11:06:18 - mmengine - INFO - Epoch(train) [435][25/63] lr: 4.6715e-03 eta: 20:01:03 time: 0.8342 data_time: 0.0658 memory: 16201 loss_prob: 0.5740 loss_thr: 0.3891 loss_db: 0.0998 loss: 1.0629 2022/08/30 11:06:22 - mmengine - INFO - Epoch(train) [435][30/63] lr: 4.6715e-03 eta: 20:00:36 time: 0.8147 data_time: 0.0643 memory: 16201 loss_prob: 0.6029 loss_thr: 0.4029 loss_db: 0.1039 loss: 1.1097 2022/08/30 11:06:26 - mmengine - INFO - Epoch(train) [435][35/63] lr: 4.6715e-03 eta: 20:00:36 time: 0.7780 data_time: 0.0308 memory: 16201 loss_prob: 0.5888 loss_thr: 0.3887 loss_db: 0.1002 loss: 1.0778 2022/08/30 11:06:30 - mmengine - INFO - Epoch(train) [435][40/63] lr: 4.6715e-03 eta: 20:00:09 time: 0.8048 data_time: 0.0300 memory: 16201 loss_prob: 0.5792 loss_thr: 0.3834 loss_db: 0.1015 loss: 1.0641 2022/08/30 11:06:34 - mmengine - INFO - Epoch(train) [435][45/63] lr: 4.6715e-03 eta: 20:00:09 time: 0.8287 data_time: 0.0256 memory: 16201 loss_prob: 0.5646 loss_thr: 0.3752 loss_db: 0.0957 loss: 1.0356 2022/08/30 11:06:39 - mmengine - INFO - Epoch(train) [435][50/63] lr: 4.6715e-03 eta: 19:59:42 time: 0.8301 data_time: 0.0344 memory: 16201 loss_prob: 0.5297 loss_thr: 0.3656 loss_db: 0.0891 loss: 0.9845 2022/08/30 11:06:43 - mmengine - INFO - Epoch(train) [435][55/63] lr: 4.6715e-03 eta: 19:59:42 time: 0.8270 data_time: 0.0492 memory: 16201 loss_prob: 0.5252 loss_thr: 0.3687 loss_db: 0.0918 loss: 0.9857 2022/08/30 11:06:47 - mmengine - INFO - Epoch(train) [435][60/63] lr: 4.6715e-03 eta: 19:59:15 time: 0.8175 data_time: 0.0448 memory: 16201 loss_prob: 0.5480 loss_thr: 0.3682 loss_db: 0.0950 loss: 1.0111 2022/08/30 11:06:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:06:55 - mmengine - INFO - Epoch(train) [436][5/63] lr: 4.6660e-03 eta: 19:59:15 time: 0.9365 data_time: 0.1955 memory: 16201 loss_prob: 0.6163 loss_thr: 0.3913 loss_db: 0.1065 loss: 1.1141 2022/08/30 11:06:59 - mmengine - INFO - Epoch(train) [436][10/63] lr: 4.6660e-03 eta: 19:58:39 time: 0.9833 data_time: 0.2140 memory: 16201 loss_prob: 0.5839 loss_thr: 0.3806 loss_db: 0.1013 loss: 1.0658 2022/08/30 11:07:03 - mmengine - INFO - Epoch(train) [436][15/63] lr: 4.6660e-03 eta: 19:58:39 time: 0.8168 data_time: 0.0516 memory: 16201 loss_prob: 0.6865 loss_thr: 0.4189 loss_db: 0.1204 loss: 1.2259 2022/08/30 11:07:07 - mmengine - INFO - Epoch(train) [436][20/63] lr: 4.6660e-03 eta: 19:58:13 time: 0.8548 data_time: 0.0365 memory: 16201 loss_prob: 0.7048 loss_thr: 0.4334 loss_db: 0.1244 loss: 1.2626 2022/08/30 11:07:11 - mmengine - INFO - Epoch(train) [436][25/63] lr: 4.6660e-03 eta: 19:58:13 time: 0.8668 data_time: 0.0516 memory: 16201 loss_prob: 0.6479 loss_thr: 0.3997 loss_db: 0.1088 loss: 1.1565 2022/08/30 11:07:16 - mmengine - INFO - Epoch(train) [436][30/63] lr: 4.6660e-03 eta: 19:57:46 time: 0.8154 data_time: 0.0624 memory: 16201 loss_prob: 0.6930 loss_thr: 0.4108 loss_db: 0.1149 loss: 1.2188 2022/08/30 11:07:20 - mmengine - INFO - Epoch(train) [436][35/63] lr: 4.6660e-03 eta: 19:57:46 time: 0.8143 data_time: 0.0472 memory: 16201 loss_prob: 0.6062 loss_thr: 0.3896 loss_db: 0.1059 loss: 1.1017 2022/08/30 11:07:24 - mmengine - INFO - Epoch(train) [436][40/63] lr: 4.6660e-03 eta: 19:57:19 time: 0.8029 data_time: 0.0311 memory: 16201 loss_prob: 0.5292 loss_thr: 0.3616 loss_db: 0.0923 loss: 0.9830 2022/08/30 11:07:28 - mmengine - INFO - Epoch(train) [436][45/63] lr: 4.6660e-03 eta: 19:57:19 time: 0.7968 data_time: 0.0401 memory: 16201 loss_prob: 0.5846 loss_thr: 0.3986 loss_db: 0.1008 loss: 1.0840 2022/08/30 11:07:32 - mmengine - INFO - Epoch(train) [436][50/63] lr: 4.6660e-03 eta: 19:56:53 time: 0.8199 data_time: 0.0396 memory: 16201 loss_prob: 0.5529 loss_thr: 0.3852 loss_db: 0.0965 loss: 1.0346 2022/08/30 11:07:36 - mmengine - INFO - Epoch(train) [436][55/63] lr: 4.6660e-03 eta: 19:56:53 time: 0.8806 data_time: 0.0486 memory: 16201 loss_prob: 0.4999 loss_thr: 0.3678 loss_db: 0.0881 loss: 0.9558 2022/08/30 11:07:40 - mmengine - INFO - Epoch(train) [436][60/63] lr: 4.6660e-03 eta: 19:56:27 time: 0.8559 data_time: 0.0424 memory: 16201 loss_prob: 0.6300 loss_thr: 0.4243 loss_db: 0.1095 loss: 1.1637 2022/08/30 11:07:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:07:48 - mmengine - INFO - Epoch(train) [437][5/63] lr: 4.6605e-03 eta: 19:56:27 time: 0.9086 data_time: 0.1613 memory: 16201 loss_prob: 0.6377 loss_thr: 0.4125 loss_db: 0.1087 loss: 1.1590 2022/08/30 11:07:52 - mmengine - INFO - Epoch(train) [437][10/63] lr: 4.6605e-03 eta: 19:55:50 time: 0.9469 data_time: 0.1740 memory: 16201 loss_prob: 0.5857 loss_thr: 0.3786 loss_db: 0.1015 loss: 1.0657 2022/08/30 11:07:56 - mmengine - INFO - Epoch(train) [437][15/63] lr: 4.6605e-03 eta: 19:55:50 time: 0.8038 data_time: 0.0356 memory: 16201 loss_prob: 0.5851 loss_thr: 0.3785 loss_db: 0.1011 loss: 1.0647 2022/08/30 11:08:00 - mmengine - INFO - Epoch(train) [437][20/63] lr: 4.6605e-03 eta: 19:55:23 time: 0.7934 data_time: 0.0365 memory: 16201 loss_prob: 0.5523 loss_thr: 0.3795 loss_db: 0.0958 loss: 1.0276 2022/08/30 11:08:04 - mmengine - INFO - Epoch(train) [437][25/63] lr: 4.6605e-03 eta: 19:55:23 time: 0.7790 data_time: 0.0354 memory: 16201 loss_prob: 0.5614 loss_thr: 0.3823 loss_db: 0.0951 loss: 1.0388 2022/08/30 11:08:08 - mmengine - INFO - Epoch(train) [437][30/63] lr: 4.6605e-03 eta: 19:54:56 time: 0.8175 data_time: 0.0310 memory: 16201 loss_prob: 0.5510 loss_thr: 0.3716 loss_db: 0.0944 loss: 1.0170 2022/08/30 11:08:12 - mmengine - INFO - Epoch(train) [437][35/63] lr: 4.6605e-03 eta: 19:54:56 time: 0.8277 data_time: 0.0260 memory: 16201 loss_prob: 0.5530 loss_thr: 0.3725 loss_db: 0.0911 loss: 1.0167 2022/08/30 11:08:16 - mmengine - INFO - Epoch(train) [437][40/63] lr: 4.6605e-03 eta: 19:54:29 time: 0.8071 data_time: 0.0321 memory: 16201 loss_prob: 0.5668 loss_thr: 0.3792 loss_db: 0.0944 loss: 1.0405 2022/08/30 11:08:20 - mmengine - INFO - Epoch(train) [437][45/63] lr: 4.6605e-03 eta: 19:54:29 time: 0.8024 data_time: 0.0344 memory: 16201 loss_prob: 0.5906 loss_thr: 0.3818 loss_db: 0.1014 loss: 1.0738 2022/08/30 11:08:24 - mmengine - INFO - Epoch(train) [437][50/63] lr: 4.6605e-03 eta: 19:54:02 time: 0.7901 data_time: 0.0220 memory: 16201 loss_prob: 0.6339 loss_thr: 0.3918 loss_db: 0.1051 loss: 1.1308 2022/08/30 11:08:29 - mmengine - INFO - Epoch(train) [437][55/63] lr: 4.6605e-03 eta: 19:54:02 time: 0.8627 data_time: 0.0505 memory: 16201 loss_prob: 0.6380 loss_thr: 0.4015 loss_db: 0.1074 loss: 1.1470 2022/08/30 11:08:33 - mmengine - INFO - Epoch(train) [437][60/63] lr: 4.6605e-03 eta: 19:53:36 time: 0.8594 data_time: 0.0527 memory: 16201 loss_prob: 0.6593 loss_thr: 0.4175 loss_db: 0.1145 loss: 1.1913 2022/08/30 11:08:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:08:40 - mmengine - INFO - Epoch(train) [438][5/63] lr: 4.6550e-03 eta: 19:53:36 time: 0.9237 data_time: 0.1940 memory: 16201 loss_prob: 0.6007 loss_thr: 0.4072 loss_db: 0.1039 loss: 1.1119 2022/08/30 11:08:44 - mmengine - INFO - Epoch(train) [438][10/63] lr: 4.6550e-03 eta: 19:53:00 time: 0.9687 data_time: 0.2083 memory: 16201 loss_prob: 0.5710 loss_thr: 0.3872 loss_db: 0.0988 loss: 1.0569 2022/08/30 11:08:48 - mmengine - INFO - Epoch(train) [438][15/63] lr: 4.6550e-03 eta: 19:53:00 time: 0.8024 data_time: 0.0330 memory: 16201 loss_prob: 0.5843 loss_thr: 0.3861 loss_db: 0.0984 loss: 1.0688 2022/08/30 11:08:52 - mmengine - INFO - Epoch(train) [438][20/63] lr: 4.6550e-03 eta: 19:52:33 time: 0.7937 data_time: 0.0236 memory: 16201 loss_prob: 0.5755 loss_thr: 0.3879 loss_db: 0.1000 loss: 1.0634 2022/08/30 11:08:56 - mmengine - INFO - Epoch(train) [438][25/63] lr: 4.6550e-03 eta: 19:52:33 time: 0.8050 data_time: 0.0355 memory: 16201 loss_prob: 0.5534 loss_thr: 0.3885 loss_db: 0.0995 loss: 1.0413 2022/08/30 11:09:00 - mmengine - INFO - Epoch(train) [438][30/63] lr: 4.6550e-03 eta: 19:52:06 time: 0.8084 data_time: 0.0259 memory: 16201 loss_prob: 0.5194 loss_thr: 0.3683 loss_db: 0.0902 loss: 0.9779 2022/08/30 11:09:04 - mmengine - INFO - Epoch(train) [438][35/63] lr: 4.6550e-03 eta: 19:52:06 time: 0.7880 data_time: 0.0187 memory: 16201 loss_prob: 0.5304 loss_thr: 0.3664 loss_db: 0.0911 loss: 0.9879 2022/08/30 11:09:08 - mmengine - INFO - Epoch(train) [438][40/63] lr: 4.6550e-03 eta: 19:51:39 time: 0.7941 data_time: 0.0324 memory: 16201 loss_prob: 0.5708 loss_thr: 0.3838 loss_db: 0.1001 loss: 1.0547 2022/08/30 11:09:12 - mmengine - INFO - Epoch(train) [438][45/63] lr: 4.6550e-03 eta: 19:51:39 time: 0.7949 data_time: 0.0300 memory: 16201 loss_prob: 0.6337 loss_thr: 0.3991 loss_db: 0.1047 loss: 1.1374 2022/08/30 11:09:16 - mmengine - INFO - Epoch(train) [438][50/63] lr: 4.6550e-03 eta: 19:51:12 time: 0.7841 data_time: 0.0229 memory: 16201 loss_prob: 0.6492 loss_thr: 0.4100 loss_db: 0.1056 loss: 1.1648 2022/08/30 11:09:20 - mmengine - INFO - Epoch(train) [438][55/63] lr: 4.6550e-03 eta: 19:51:12 time: 0.8041 data_time: 0.0408 memory: 16201 loss_prob: 0.6006 loss_thr: 0.3966 loss_db: 0.1028 loss: 1.1000 2022/08/30 11:09:24 - mmengine - INFO - Epoch(train) [438][60/63] lr: 4.6550e-03 eta: 19:50:45 time: 0.8150 data_time: 0.0405 memory: 16201 loss_prob: 0.6018 loss_thr: 0.4043 loss_db: 0.1040 loss: 1.1100 2022/08/30 11:09:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:09:32 - mmengine - INFO - Epoch(train) [439][5/63] lr: 4.6495e-03 eta: 19:50:45 time: 0.9122 data_time: 0.1679 memory: 16201 loss_prob: 0.5844 loss_thr: 0.4208 loss_db: 0.1014 loss: 1.1066 2022/08/30 11:09:36 - mmengine - INFO - Epoch(train) [439][10/63] lr: 4.6495e-03 eta: 19:50:09 time: 0.9559 data_time: 0.1766 memory: 16201 loss_prob: 0.5823 loss_thr: 0.4022 loss_db: 0.1025 loss: 1.0869 2022/08/30 11:09:40 - mmengine - INFO - Epoch(train) [439][15/63] lr: 4.6495e-03 eta: 19:50:09 time: 0.8215 data_time: 0.0376 memory: 16201 loss_prob: 0.5401 loss_thr: 0.3640 loss_db: 0.0938 loss: 0.9979 2022/08/30 11:09:44 - mmengine - INFO - Epoch(train) [439][20/63] lr: 4.6495e-03 eta: 19:49:42 time: 0.8075 data_time: 0.0316 memory: 16201 loss_prob: 0.5574 loss_thr: 0.3741 loss_db: 0.0947 loss: 1.0261 2022/08/30 11:09:48 - mmengine - INFO - Epoch(train) [439][25/63] lr: 4.6495e-03 eta: 19:49:42 time: 0.8157 data_time: 0.0376 memory: 16201 loss_prob: 0.5713 loss_thr: 0.3818 loss_db: 0.0987 loss: 1.0518 2022/08/30 11:09:52 - mmengine - INFO - Epoch(train) [439][30/63] lr: 4.6495e-03 eta: 19:49:16 time: 0.8166 data_time: 0.0336 memory: 16201 loss_prob: 0.5149 loss_thr: 0.3534 loss_db: 0.0915 loss: 0.9598 2022/08/30 11:09:56 - mmengine - INFO - Epoch(train) [439][35/63] lr: 4.6495e-03 eta: 19:49:16 time: 0.7946 data_time: 0.0204 memory: 16201 loss_prob: 0.5383 loss_thr: 0.3708 loss_db: 0.0940 loss: 1.0031 2022/08/30 11:10:00 - mmengine - INFO - Epoch(train) [439][40/63] lr: 4.6495e-03 eta: 19:48:49 time: 0.8142 data_time: 0.0408 memory: 16201 loss_prob: 0.5466 loss_thr: 0.3667 loss_db: 0.0945 loss: 1.0078 2022/08/30 11:10:04 - mmengine - INFO - Epoch(train) [439][45/63] lr: 4.6495e-03 eta: 19:48:49 time: 0.8305 data_time: 0.0578 memory: 16201 loss_prob: 0.5590 loss_thr: 0.3630 loss_db: 0.0946 loss: 1.0166 2022/08/30 11:10:08 - mmengine - INFO - Epoch(train) [439][50/63] lr: 4.6495e-03 eta: 19:48:22 time: 0.8030 data_time: 0.0366 memory: 16201 loss_prob: 0.5689 loss_thr: 0.3843 loss_db: 0.0979 loss: 1.0511 2022/08/30 11:10:12 - mmengine - INFO - Epoch(train) [439][55/63] lr: 4.6495e-03 eta: 19:48:22 time: 0.7961 data_time: 0.0320 memory: 16201 loss_prob: 0.5277 loss_thr: 0.3649 loss_db: 0.0935 loss: 0.9861 2022/08/30 11:10:16 - mmengine - INFO - Epoch(train) [439][60/63] lr: 4.6495e-03 eta: 19:47:56 time: 0.8164 data_time: 0.0430 memory: 16201 loss_prob: 0.5015 loss_thr: 0.3535 loss_db: 0.0870 loss: 0.9420 2022/08/30 11:10:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:10:24 - mmengine - INFO - Epoch(train) [440][5/63] lr: 4.6440e-03 eta: 19:47:56 time: 0.9061 data_time: 0.1704 memory: 16201 loss_prob: 0.5777 loss_thr: 0.4011 loss_db: 0.1027 loss: 1.0815 2022/08/30 11:10:28 - mmengine - INFO - Epoch(train) [440][10/63] lr: 4.6440e-03 eta: 19:47:20 time: 0.9486 data_time: 0.1789 memory: 16201 loss_prob: 0.6548 loss_thr: 0.4193 loss_db: 0.1078 loss: 1.1820 2022/08/30 11:10:32 - mmengine - INFO - Epoch(train) [440][15/63] lr: 4.6440e-03 eta: 19:47:20 time: 0.8120 data_time: 0.0335 memory: 16201 loss_prob: 0.6601 loss_thr: 0.4163 loss_db: 0.1106 loss: 1.1871 2022/08/30 11:10:36 - mmengine - INFO - Epoch(train) [440][20/63] lr: 4.6440e-03 eta: 19:46:53 time: 0.8137 data_time: 0.0267 memory: 16201 loss_prob: 0.5856 loss_thr: 0.4000 loss_db: 0.1028 loss: 1.0884 2022/08/30 11:10:40 - mmengine - INFO - Epoch(train) [440][25/63] lr: 4.6440e-03 eta: 19:46:53 time: 0.8230 data_time: 0.0421 memory: 16201 loss_prob: 0.5949 loss_thr: 0.3757 loss_db: 0.1047 loss: 1.0752 2022/08/30 11:10:44 - mmengine - INFO - Epoch(train) [440][30/63] lr: 4.6440e-03 eta: 19:46:26 time: 0.7990 data_time: 0.0300 memory: 16201 loss_prob: 0.6683 loss_thr: 0.3918 loss_db: 0.1183 loss: 1.1784 2022/08/30 11:10:48 - mmengine - INFO - Epoch(train) [440][35/63] lr: 4.6440e-03 eta: 19:46:26 time: 0.7967 data_time: 0.0179 memory: 16201 loss_prob: 0.7754 loss_thr: 0.4009 loss_db: 0.1358 loss: 1.3121 2022/08/30 11:10:52 - mmengine - INFO - Epoch(train) [440][40/63] lr: 4.6440e-03 eta: 19:46:00 time: 0.8182 data_time: 0.0359 memory: 16201 loss_prob: 0.8246 loss_thr: 0.4070 loss_db: 0.1369 loss: 1.3685 2022/08/30 11:10:56 - mmengine - INFO - Epoch(train) [440][45/63] lr: 4.6440e-03 eta: 19:46:00 time: 0.8156 data_time: 0.0367 memory: 16201 loss_prob: 0.7047 loss_thr: 0.4048 loss_db: 0.1155 loss: 1.2250 2022/08/30 11:11:00 - mmengine - INFO - Epoch(train) [440][50/63] lr: 4.6440e-03 eta: 19:45:33 time: 0.7902 data_time: 0.0217 memory: 16201 loss_prob: 0.6518 loss_thr: 0.3847 loss_db: 0.1113 loss: 1.1478 2022/08/30 11:11:04 - mmengine - INFO - Epoch(train) [440][55/63] lr: 4.6440e-03 eta: 19:45:33 time: 0.8032 data_time: 0.0372 memory: 16201 loss_prob: 0.6485 loss_thr: 0.4020 loss_db: 0.1093 loss: 1.1598 2022/08/30 11:11:09 - mmengine - INFO - Epoch(train) [440][60/63] lr: 4.6440e-03 eta: 19:45:07 time: 0.8259 data_time: 0.0500 memory: 16201 loss_prob: 0.6478 loss_thr: 0.4252 loss_db: 0.1084 loss: 1.1813 2022/08/30 11:11:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:11:10 - mmengine - INFO - Saving checkpoint at 440 epochs 2022/08/30 11:11:18 - mmengine - INFO - Epoch(val) [440][5/32] eta: 19:45:07 time: 0.5945 data_time: 0.0724 memory: 16201 2022/08/30 11:11:21 - mmengine - INFO - Epoch(val) [440][10/32] eta: 0:00:14 time: 0.6482 data_time: 0.0833 memory: 15734 2022/08/30 11:11:24 - mmengine - INFO - Epoch(val) [440][15/32] eta: 0:00:14 time: 0.5868 data_time: 0.0383 memory: 15734 2022/08/30 11:11:28 - mmengine - INFO - Epoch(val) [440][20/32] eta: 0:00:07 time: 0.6325 data_time: 0.0546 memory: 15734 2022/08/30 11:11:30 - mmengine - INFO - Epoch(val) [440][25/32] eta: 0:00:07 time: 0.6265 data_time: 0.0424 memory: 15734 2022/08/30 11:11:33 - mmengine - INFO - Epoch(val) [440][30/32] eta: 0:00:01 time: 0.5660 data_time: 0.0209 memory: 15734 2022/08/30 11:11:34 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 11:11:34 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8286, precision: 0.7608, hmean: 0.7933 2022/08/30 11:11:34 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8286, precision: 0.8246, hmean: 0.8266 2022/08/30 11:11:34 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8238, precision: 0.8559, hmean: 0.8395 2022/08/30 11:11:34 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8132, precision: 0.8765, hmean: 0.8437 2022/08/30 11:11:34 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7882, precision: 0.9034, hmean: 0.8419 2022/08/30 11:11:34 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6654, precision: 0.9376, hmean: 0.7784 2022/08/30 11:11:34 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0655, precision: 0.9784, hmean: 0.1227 2022/08/30 11:11:34 - mmengine - INFO - Epoch(val) [440][32/32] icdar/precision: 0.8765 icdar/recall: 0.8132 icdar/hmean: 0.8437 2022/08/30 11:11:40 - mmengine - INFO - Epoch(train) [441][5/63] lr: 4.6385e-03 eta: 0:00:01 time: 0.9315 data_time: 0.1819 memory: 16201 loss_prob: 0.6121 loss_thr: 0.3924 loss_db: 0.1060 loss: 1.1105 2022/08/30 11:11:44 - mmengine - INFO - Epoch(train) [441][10/63] lr: 4.6385e-03 eta: 19:44:31 time: 0.9863 data_time: 0.1870 memory: 16201 loss_prob: 0.6693 loss_thr: 0.3984 loss_db: 0.1120 loss: 1.1797 2022/08/30 11:11:48 - mmengine - INFO - Epoch(train) [441][15/63] lr: 4.6385e-03 eta: 19:44:31 time: 0.8072 data_time: 0.0271 memory: 16201 loss_prob: 0.6718 loss_thr: 0.4208 loss_db: 0.1142 loss: 1.2069 2022/08/30 11:11:52 - mmengine - INFO - Epoch(train) [441][20/63] lr: 4.6385e-03 eta: 19:44:05 time: 0.8018 data_time: 0.0278 memory: 16201 loss_prob: 0.6537 loss_thr: 0.4233 loss_db: 0.1117 loss: 1.1887 2022/08/30 11:11:56 - mmengine - INFO - Epoch(train) [441][25/63] lr: 4.6385e-03 eta: 19:44:05 time: 0.8262 data_time: 0.0297 memory: 16201 loss_prob: 0.6691 loss_thr: 0.4251 loss_db: 0.1132 loss: 1.2073 2022/08/30 11:12:00 - mmengine - INFO - Epoch(train) [441][30/63] lr: 4.6385e-03 eta: 19:43:38 time: 0.8337 data_time: 0.0218 memory: 16201 loss_prob: 0.6469 loss_thr: 0.4195 loss_db: 0.1111 loss: 1.1775 2022/08/30 11:12:04 - mmengine - INFO - Epoch(train) [441][35/63] lr: 4.6385e-03 eta: 19:43:38 time: 0.8130 data_time: 0.0332 memory: 16201 loss_prob: 0.6926 loss_thr: 0.4141 loss_db: 0.1142 loss: 1.2209 2022/08/30 11:12:08 - mmengine - INFO - Epoch(train) [441][40/63] lr: 4.6385e-03 eta: 19:43:12 time: 0.7910 data_time: 0.0338 memory: 16201 loss_prob: 0.6344 loss_thr: 0.3881 loss_db: 0.1040 loss: 1.1265 2022/08/30 11:12:12 - mmengine - INFO - Epoch(train) [441][45/63] lr: 4.6385e-03 eta: 19:43:12 time: 0.7748 data_time: 0.0238 memory: 16201 loss_prob: 0.5478 loss_thr: 0.3810 loss_db: 0.0932 loss: 1.0220 2022/08/30 11:12:16 - mmengine - INFO - Epoch(train) [441][50/63] lr: 4.6385e-03 eta: 19:42:45 time: 0.7999 data_time: 0.0414 memory: 16201 loss_prob: 0.6022 loss_thr: 0.4050 loss_db: 0.1019 loss: 1.1092 2022/08/30 11:12:20 - mmengine - INFO - Epoch(train) [441][55/63] lr: 4.6385e-03 eta: 19:42:45 time: 0.8116 data_time: 0.0381 memory: 16201 loss_prob: 0.6047 loss_thr: 0.4022 loss_db: 0.1038 loss: 1.1107 2022/08/30 11:12:24 - mmengine - INFO - Epoch(train) [441][60/63] lr: 4.6385e-03 eta: 19:42:18 time: 0.7802 data_time: 0.0226 memory: 16201 loss_prob: 0.5799 loss_thr: 0.3961 loss_db: 0.1000 loss: 1.0760 2022/08/30 11:12:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:12:32 - mmengine - INFO - Epoch(train) [442][5/63] lr: 4.6330e-03 eta: 19:42:18 time: 0.9281 data_time: 0.1606 memory: 16201 loss_prob: 0.5979 loss_thr: 0.3956 loss_db: 0.1015 loss: 1.0950 2022/08/30 11:12:36 - mmengine - INFO - Epoch(train) [442][10/63] lr: 4.6330e-03 eta: 19:41:42 time: 0.9310 data_time: 0.1568 memory: 16201 loss_prob: 0.5347 loss_thr: 0.3769 loss_db: 0.0922 loss: 1.0037 2022/08/30 11:12:40 - mmengine - INFO - Epoch(train) [442][15/63] lr: 4.6330e-03 eta: 19:41:42 time: 0.8113 data_time: 0.0476 memory: 16201 loss_prob: 0.5854 loss_thr: 0.4006 loss_db: 0.1032 loss: 1.0892 2022/08/30 11:12:44 - mmengine - INFO - Epoch(train) [442][20/63] lr: 4.6330e-03 eta: 19:41:15 time: 0.8164 data_time: 0.0476 memory: 16201 loss_prob: 0.5906 loss_thr: 0.3965 loss_db: 0.1043 loss: 1.0914 2022/08/30 11:12:48 - mmengine - INFO - Epoch(train) [442][25/63] lr: 4.6330e-03 eta: 19:41:15 time: 0.8474 data_time: 0.0241 memory: 16201 loss_prob: 0.5584 loss_thr: 0.3735 loss_db: 0.0960 loss: 1.0279 2022/08/30 11:12:52 - mmengine - INFO - Epoch(train) [442][30/63] lr: 4.6330e-03 eta: 19:40:50 time: 0.8479 data_time: 0.0292 memory: 16201 loss_prob: 0.5687 loss_thr: 0.3754 loss_db: 0.0976 loss: 1.0417 2022/08/30 11:12:56 - mmengine - INFO - Epoch(train) [442][35/63] lr: 4.6330e-03 eta: 19:40:50 time: 0.7999 data_time: 0.0372 memory: 16201 loss_prob: 0.5570 loss_thr: 0.3730 loss_db: 0.0961 loss: 1.0261 2022/08/30 11:13:00 - mmengine - INFO - Epoch(train) [442][40/63] lr: 4.6330e-03 eta: 19:40:23 time: 0.7917 data_time: 0.0282 memory: 16201 loss_prob: 0.5599 loss_thr: 0.3849 loss_db: 0.0961 loss: 1.0409 2022/08/30 11:13:04 - mmengine - INFO - Epoch(train) [442][45/63] lr: 4.6330e-03 eta: 19:40:23 time: 0.7990 data_time: 0.0352 memory: 16201 loss_prob: 0.5840 loss_thr: 0.3988 loss_db: 0.1018 loss: 1.0845 2022/08/30 11:13:09 - mmengine - INFO - Epoch(train) [442][50/63] lr: 4.6330e-03 eta: 19:39:58 time: 0.8757 data_time: 0.0358 memory: 16201 loss_prob: 0.5716 loss_thr: 0.3879 loss_db: 0.0999 loss: 1.0594 2022/08/30 11:13:13 - mmengine - INFO - Epoch(train) [442][55/63] lr: 4.6330e-03 eta: 19:39:58 time: 0.8493 data_time: 0.0207 memory: 16201 loss_prob: 0.5778 loss_thr: 0.3890 loss_db: 0.1008 loss: 1.0676 2022/08/30 11:13:17 - mmengine - INFO - Epoch(train) [442][60/63] lr: 4.6330e-03 eta: 19:39:31 time: 0.7902 data_time: 0.0357 memory: 16201 loss_prob: 0.5969 loss_thr: 0.4025 loss_db: 0.1044 loss: 1.1038 2022/08/30 11:13:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:13:25 - mmengine - INFO - Epoch(train) [443][5/63] lr: 4.6275e-03 eta: 19:39:31 time: 0.9443 data_time: 0.2094 memory: 16201 loss_prob: 0.5892 loss_thr: 0.4123 loss_db: 0.1019 loss: 1.1034 2022/08/30 11:13:29 - mmengine - INFO - Epoch(train) [443][10/63] lr: 4.6275e-03 eta: 19:38:56 time: 0.9857 data_time: 0.2159 memory: 16201 loss_prob: 0.5857 loss_thr: 0.3981 loss_db: 0.1002 loss: 1.0839 2022/08/30 11:13:33 - mmengine - INFO - Epoch(train) [443][15/63] lr: 4.6275e-03 eta: 19:38:56 time: 0.8346 data_time: 0.0284 memory: 16201 loss_prob: 0.5400 loss_thr: 0.3783 loss_db: 0.0944 loss: 1.0128 2022/08/30 11:13:37 - mmengine - INFO - Epoch(train) [443][20/63] lr: 4.6275e-03 eta: 19:38:30 time: 0.8280 data_time: 0.0218 memory: 16201 loss_prob: 0.6177 loss_thr: 0.3917 loss_db: 0.1079 loss: 1.1173 2022/08/30 11:13:41 - mmengine - INFO - Epoch(train) [443][25/63] lr: 4.6275e-03 eta: 19:38:30 time: 0.7889 data_time: 0.0331 memory: 16201 loss_prob: 0.6894 loss_thr: 0.3962 loss_db: 0.1193 loss: 1.2049 2022/08/30 11:13:45 - mmengine - INFO - Epoch(train) [443][30/63] lr: 4.6275e-03 eta: 19:38:03 time: 0.7911 data_time: 0.0297 memory: 16201 loss_prob: 0.6230 loss_thr: 0.3994 loss_db: 0.1078 loss: 1.1302 2022/08/30 11:13:49 - mmengine - INFO - Epoch(train) [443][35/63] lr: 4.6275e-03 eta: 19:38:03 time: 0.8220 data_time: 0.0349 memory: 16201 loss_prob: 0.5544 loss_thr: 0.3818 loss_db: 0.0951 loss: 1.0314 2022/08/30 11:13:53 - mmengine - INFO - Epoch(train) [443][40/63] lr: 4.6275e-03 eta: 19:37:37 time: 0.8192 data_time: 0.0332 memory: 16201 loss_prob: 0.5744 loss_thr: 0.3813 loss_db: 0.0977 loss: 1.0534 2022/08/30 11:13:57 - mmengine - INFO - Epoch(train) [443][45/63] lr: 4.6275e-03 eta: 19:37:37 time: 0.7943 data_time: 0.0279 memory: 16201 loss_prob: 0.6184 loss_thr: 0.3979 loss_db: 0.1063 loss: 1.1226 2022/08/30 11:14:01 - mmengine - INFO - Epoch(train) [443][50/63] lr: 4.6275e-03 eta: 19:37:10 time: 0.8006 data_time: 0.0335 memory: 16201 loss_prob: 0.6117 loss_thr: 0.4059 loss_db: 0.1066 loss: 1.1242 2022/08/30 11:14:05 - mmengine - INFO - Epoch(train) [443][55/63] lr: 4.6275e-03 eta: 19:37:10 time: 0.7981 data_time: 0.0282 memory: 16201 loss_prob: 0.5962 loss_thr: 0.3917 loss_db: 0.1020 loss: 1.0900 2022/08/30 11:14:09 - mmengine - INFO - Epoch(train) [443][60/63] lr: 4.6275e-03 eta: 19:36:44 time: 0.7919 data_time: 0.0270 memory: 16201 loss_prob: 0.5536 loss_thr: 0.3639 loss_db: 0.0959 loss: 1.0134 2022/08/30 11:14:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:14:16 - mmengine - INFO - Epoch(train) [444][5/63] lr: 4.6220e-03 eta: 19:36:44 time: 0.8841 data_time: 0.1728 memory: 16201 loss_prob: 0.6227 loss_thr: 0.4363 loss_db: 0.1098 loss: 1.1689 2022/08/30 11:14:21 - mmengine - INFO - Epoch(train) [444][10/63] lr: 4.6220e-03 eta: 19:36:08 time: 0.9575 data_time: 0.1928 memory: 16201 loss_prob: 0.5758 loss_thr: 0.3915 loss_db: 0.0992 loss: 1.0664 2022/08/30 11:14:24 - mmengine - INFO - Epoch(train) [444][15/63] lr: 4.6220e-03 eta: 19:36:08 time: 0.8018 data_time: 0.0302 memory: 16201 loss_prob: 0.5374 loss_thr: 0.3495 loss_db: 0.0904 loss: 0.9772 2022/08/30 11:14:29 - mmengine - INFO - Epoch(train) [444][20/63] lr: 4.6220e-03 eta: 19:35:42 time: 0.8173 data_time: 0.0232 memory: 16201 loss_prob: 0.5889 loss_thr: 0.3893 loss_db: 0.1004 loss: 1.0786 2022/08/30 11:14:33 - mmengine - INFO - Epoch(train) [444][25/63] lr: 4.6220e-03 eta: 19:35:42 time: 0.8420 data_time: 0.0490 memory: 16201 loss_prob: 0.6117 loss_thr: 0.4088 loss_db: 0.1046 loss: 1.1251 2022/08/30 11:14:37 - mmengine - INFO - Epoch(train) [444][30/63] lr: 4.6220e-03 eta: 19:35:16 time: 0.8171 data_time: 0.0366 memory: 16201 loss_prob: 0.6559 loss_thr: 0.4223 loss_db: 0.1126 loss: 1.1908 2022/08/30 11:14:41 - mmengine - INFO - Epoch(train) [444][35/63] lr: 4.6220e-03 eta: 19:35:16 time: 0.8132 data_time: 0.0204 memory: 16201 loss_prob: 0.6580 loss_thr: 0.4163 loss_db: 0.1152 loss: 1.1894 2022/08/30 11:14:45 - mmengine - INFO - Epoch(train) [444][40/63] lr: 4.6220e-03 eta: 19:34:49 time: 0.8004 data_time: 0.0307 memory: 16201 loss_prob: 0.6166 loss_thr: 0.3919 loss_db: 0.1070 loss: 1.1155 2022/08/30 11:14:49 - mmengine - INFO - Epoch(train) [444][45/63] lr: 4.6220e-03 eta: 19:34:49 time: 0.8420 data_time: 0.0393 memory: 16201 loss_prob: 0.6181 loss_thr: 0.3825 loss_db: 0.1045 loss: 1.1051 2022/08/30 11:14:53 - mmengine - INFO - Epoch(train) [444][50/63] lr: 4.6220e-03 eta: 19:34:24 time: 0.8282 data_time: 0.0334 memory: 16201 loss_prob: 0.6126 loss_thr: 0.4033 loss_db: 0.1058 loss: 1.1217 2022/08/30 11:14:57 - mmengine - INFO - Epoch(train) [444][55/63] lr: 4.6220e-03 eta: 19:34:24 time: 0.7632 data_time: 0.0248 memory: 16201 loss_prob: 0.6008 loss_thr: 0.4038 loss_db: 0.1051 loss: 1.1098 2022/08/30 11:15:01 - mmengine - INFO - Epoch(train) [444][60/63] lr: 4.6220e-03 eta: 19:33:57 time: 0.7963 data_time: 0.0295 memory: 16201 loss_prob: 0.6102 loss_thr: 0.4121 loss_db: 0.1032 loss: 1.1255 2022/08/30 11:15:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:15:09 - mmengine - INFO - Epoch(train) [445][5/63] lr: 4.6165e-03 eta: 19:33:57 time: 0.9399 data_time: 0.1901 memory: 16201 loss_prob: 0.5463 loss_thr: 0.3966 loss_db: 0.0949 loss: 1.0378 2022/08/30 11:15:13 - mmengine - INFO - Epoch(train) [445][10/63] lr: 4.6165e-03 eta: 19:33:21 time: 0.9479 data_time: 0.1912 memory: 16201 loss_prob: 0.5813 loss_thr: 0.3884 loss_db: 0.1018 loss: 1.0715 2022/08/30 11:15:18 - mmengine - INFO - Epoch(train) [445][15/63] lr: 4.6165e-03 eta: 19:33:21 time: 0.9072 data_time: 0.0341 memory: 16201 loss_prob: 0.6113 loss_thr: 0.4114 loss_db: 0.1058 loss: 1.1285 2022/08/30 11:15:22 - mmengine - INFO - Epoch(train) [445][20/63] lr: 4.6165e-03 eta: 19:32:57 time: 0.9030 data_time: 0.0249 memory: 16201 loss_prob: 0.6027 loss_thr: 0.4073 loss_db: 0.1067 loss: 1.1166 2022/08/30 11:15:27 - mmengine - INFO - Epoch(train) [445][25/63] lr: 4.6165e-03 eta: 19:32:57 time: 0.9014 data_time: 0.0547 memory: 16201 loss_prob: 0.6086 loss_thr: 0.3964 loss_db: 0.1045 loss: 1.1094 2022/08/30 11:15:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:15:32 - mmengine - INFO - Epoch(train) [445][30/63] lr: 4.6165e-03 eta: 19:32:34 time: 1.0131 data_time: 0.0479 memory: 16201 loss_prob: 0.5599 loss_thr: 0.3854 loss_db: 0.0951 loss: 1.0405 2022/08/30 11:15:37 - mmengine - INFO - Epoch(train) [445][35/63] lr: 4.6165e-03 eta: 19:32:34 time: 0.9652 data_time: 0.0306 memory: 16201 loss_prob: 0.5580 loss_thr: 0.3918 loss_db: 0.0949 loss: 1.0447 2022/08/30 11:15:42 - mmengine - INFO - Epoch(train) [445][40/63] lr: 4.6165e-03 eta: 19:32:11 time: 0.9995 data_time: 0.0374 memory: 16201 loss_prob: 0.6671 loss_thr: 0.4250 loss_db: 0.1090 loss: 1.2011 2022/08/30 11:15:47 - mmengine - INFO - Epoch(train) [445][45/63] lr: 4.6165e-03 eta: 19:32:11 time: 1.0507 data_time: 0.0404 memory: 16201 loss_prob: 0.6619 loss_thr: 0.4209 loss_db: 0.1091 loss: 1.1919 2022/08/30 11:15:52 - mmengine - INFO - Epoch(train) [445][50/63] lr: 4.6165e-03 eta: 19:31:48 time: 0.9715 data_time: 0.0504 memory: 16201 loss_prob: 0.5594 loss_thr: 0.3780 loss_db: 0.0970 loss: 1.0343 2022/08/30 11:15:57 - mmengine - INFO - Epoch(train) [445][55/63] lr: 4.6165e-03 eta: 19:31:48 time: 1.0012 data_time: 0.0433 memory: 16201 loss_prob: 0.5183 loss_thr: 0.3582 loss_db: 0.0920 loss: 0.9686 2022/08/30 11:16:02 - mmengine - INFO - Epoch(train) [445][60/63] lr: 4.6165e-03 eta: 19:31:25 time: 1.0158 data_time: 0.0512 memory: 16201 loss_prob: 0.5495 loss_thr: 0.3767 loss_db: 0.0971 loss: 1.0232 2022/08/30 11:16:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:16:11 - mmengine - INFO - Epoch(train) [446][5/63] lr: 4.6110e-03 eta: 19:31:25 time: 1.1300 data_time: 0.2302 memory: 16201 loss_prob: 0.5489 loss_thr: 0.3751 loss_db: 0.0952 loss: 1.0191 2022/08/30 11:16:17 - mmengine - INFO - Epoch(train) [446][10/63] lr: 4.6110e-03 eta: 19:30:55 time: 1.2770 data_time: 0.2493 memory: 16201 loss_prob: 0.5537 loss_thr: 0.3796 loss_db: 0.0952 loss: 1.0285 2022/08/30 11:16:22 - mmengine - INFO - Epoch(train) [446][15/63] lr: 4.6110e-03 eta: 19:30:55 time: 1.0534 data_time: 0.0317 memory: 16201 loss_prob: 0.5243 loss_thr: 0.3740 loss_db: 0.0937 loss: 0.9920 2022/08/30 11:16:27 - mmengine - INFO - Epoch(train) [446][20/63] lr: 4.6110e-03 eta: 19:30:32 time: 1.0009 data_time: 0.0483 memory: 16201 loss_prob: 0.5734 loss_thr: 0.3859 loss_db: 0.1001 loss: 1.0594 2022/08/30 11:16:32 - mmengine - INFO - Epoch(train) [446][25/63] lr: 4.6110e-03 eta: 19:30:32 time: 0.9612 data_time: 0.0573 memory: 16201 loss_prob: 0.6804 loss_thr: 0.4111 loss_db: 0.1167 loss: 1.2082 2022/08/30 11:16:37 - mmengine - INFO - Epoch(train) [446][30/63] lr: 4.6110e-03 eta: 19:30:09 time: 0.9834 data_time: 0.0271 memory: 16201 loss_prob: 0.6311 loss_thr: 0.3890 loss_db: 0.1101 loss: 1.1302 2022/08/30 11:16:42 - mmengine - INFO - Epoch(train) [446][35/63] lr: 4.6110e-03 eta: 19:30:09 time: 1.0254 data_time: 0.0461 memory: 16201 loss_prob: 0.5030 loss_thr: 0.3376 loss_db: 0.0879 loss: 0.9285 2022/08/30 11:16:46 - mmengine - INFO - Epoch(train) [446][40/63] lr: 4.6110e-03 eta: 19:29:45 time: 0.9472 data_time: 0.0371 memory: 16201 loss_prob: 0.5337 loss_thr: 0.3597 loss_db: 0.0906 loss: 0.9840 2022/08/30 11:16:52 - mmengine - INFO - Epoch(train) [446][45/63] lr: 4.6110e-03 eta: 19:29:45 time: 0.9770 data_time: 0.0214 memory: 16201 loss_prob: 0.6187 loss_thr: 0.4198 loss_db: 0.1053 loss: 1.1438 2022/08/30 11:16:58 - mmengine - INFO - Epoch(train) [446][50/63] lr: 4.6110e-03 eta: 19:29:25 time: 1.1193 data_time: 0.0667 memory: 16201 loss_prob: 0.6213 loss_thr: 0.4102 loss_db: 0.1068 loss: 1.1383 2022/08/30 11:17:03 - mmengine - INFO - Epoch(train) [446][55/63] lr: 4.6110e-03 eta: 19:29:25 time: 1.1111 data_time: 0.0569 memory: 16201 loss_prob: 0.6091 loss_thr: 0.4113 loss_db: 0.1025 loss: 1.1228 2022/08/30 11:17:08 - mmengine - INFO - Epoch(train) [446][60/63] lr: 4.6110e-03 eta: 19:29:03 time: 1.0831 data_time: 0.0286 memory: 16201 loss_prob: 0.5971 loss_thr: 0.4108 loss_db: 0.1046 loss: 1.1126 2022/08/30 11:17:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:17:18 - mmengine - INFO - Epoch(train) [447][5/63] lr: 4.6055e-03 eta: 19:29:03 time: 1.2152 data_time: 0.1841 memory: 16201 loss_prob: 0.6088 loss_thr: 0.3988 loss_db: 0.1082 loss: 1.1158 2022/08/30 11:17:23 - mmengine - INFO - Epoch(train) [447][10/63] lr: 4.6055e-03 eta: 19:28:33 time: 1.2473 data_time: 0.2066 memory: 16201 loss_prob: 0.5610 loss_thr: 0.3794 loss_db: 0.0974 loss: 1.0378 2022/08/30 11:17:28 - mmengine - INFO - Epoch(train) [447][15/63] lr: 4.6055e-03 eta: 19:28:33 time: 0.9879 data_time: 0.0388 memory: 16201 loss_prob: 0.8125 loss_thr: 0.4216 loss_db: 0.1360 loss: 1.3701 2022/08/30 11:17:33 - mmengine - INFO - Epoch(train) [447][20/63] lr: 4.6055e-03 eta: 19:28:09 time: 0.9396 data_time: 0.0274 memory: 16201 loss_prob: 1.0328 loss_thr: 0.4522 loss_db: 0.1851 loss: 1.6701 2022/08/30 11:17:37 - mmengine - INFO - Epoch(train) [447][25/63] lr: 4.6055e-03 eta: 19:28:09 time: 0.9224 data_time: 0.0325 memory: 16201 loss_prob: 0.8026 loss_thr: 0.4115 loss_db: 0.1438 loss: 1.3580 2022/08/30 11:17:42 - mmengine - INFO - Epoch(train) [447][30/63] lr: 4.6055e-03 eta: 19:27:45 time: 0.9365 data_time: 0.0281 memory: 16201 loss_prob: 0.7659 loss_thr: 0.4501 loss_db: 0.1216 loss: 1.3377 2022/08/30 11:17:47 - mmengine - INFO - Epoch(train) [447][35/63] lr: 4.6055e-03 eta: 19:27:45 time: 0.9785 data_time: 0.0266 memory: 16201 loss_prob: 1.0475 loss_thr: 0.4841 loss_db: 0.1517 loss: 1.6834 2022/08/30 11:17:52 - mmengine - INFO - Epoch(train) [447][40/63] lr: 4.6055e-03 eta: 19:27:23 time: 1.0484 data_time: 0.0270 memory: 16201 loss_prob: 1.0324 loss_thr: 0.4771 loss_db: 0.1538 loss: 1.6634 2022/08/30 11:17:58 - mmengine - INFO - Epoch(train) [447][45/63] lr: 4.6055e-03 eta: 19:27:23 time: 1.1145 data_time: 0.0278 memory: 16201 loss_prob: 0.8609 loss_thr: 0.4682 loss_db: 0.1405 loss: 1.4696 2022/08/30 11:18:03 - mmengine - INFO - Epoch(train) [447][50/63] lr: 4.6055e-03 eta: 19:27:01 time: 1.0492 data_time: 0.0321 memory: 16201 loss_prob: 0.8110 loss_thr: 0.4648 loss_db: 0.1297 loss: 1.4054 2022/08/30 11:18:08 - mmengine - INFO - Epoch(train) [447][55/63] lr: 4.6055e-03 eta: 19:27:01 time: 0.9978 data_time: 0.0289 memory: 16201 loss_prob: 0.7570 loss_thr: 0.4670 loss_db: 0.1268 loss: 1.3507 2022/08/30 11:18:14 - mmengine - INFO - Epoch(train) [447][60/63] lr: 4.6055e-03 eta: 19:26:40 time: 1.0898 data_time: 0.0400 memory: 16201 loss_prob: 0.7552 loss_thr: 0.4589 loss_db: 0.1272 loss: 1.3413 2022/08/30 11:18:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:18:24 - mmengine - INFO - Epoch(train) [448][5/63] lr: 4.6000e-03 eta: 19:26:40 time: 1.2015 data_time: 0.1868 memory: 16201 loss_prob: 0.6571 loss_thr: 0.4111 loss_db: 0.1107 loss: 1.1789 2022/08/30 11:18:29 - mmengine - INFO - Epoch(train) [448][10/63] lr: 4.6000e-03 eta: 19:26:09 time: 1.2313 data_time: 0.1991 memory: 16201 loss_prob: 0.6033 loss_thr: 0.3974 loss_db: 0.1015 loss: 1.1022 2022/08/30 11:18:34 - mmengine - INFO - Epoch(train) [448][15/63] lr: 4.6000e-03 eta: 19:26:09 time: 0.9947 data_time: 0.0331 memory: 16201 loss_prob: 0.5914 loss_thr: 0.3959 loss_db: 0.1012 loss: 1.0885 2022/08/30 11:18:40 - mmengine - INFO - Epoch(train) [448][20/63] lr: 4.6000e-03 eta: 19:25:47 time: 1.0699 data_time: 0.0236 memory: 16201 loss_prob: 0.5677 loss_thr: 0.3924 loss_db: 0.0981 loss: 1.0582 2022/08/30 11:18:44 - mmengine - INFO - Epoch(train) [448][25/63] lr: 4.6000e-03 eta: 19:25:47 time: 1.0754 data_time: 0.0395 memory: 16201 loss_prob: 0.5687 loss_thr: 0.3884 loss_db: 0.0958 loss: 1.0529 2022/08/30 11:18:49 - mmengine - INFO - Epoch(train) [448][30/63] lr: 4.6000e-03 eta: 19:25:24 time: 0.9614 data_time: 0.0362 memory: 16201 loss_prob: 0.6191 loss_thr: 0.4008 loss_db: 0.1064 loss: 1.1263 2022/08/30 11:18:55 - mmengine - INFO - Epoch(train) [448][35/63] lr: 4.6000e-03 eta: 19:25:24 time: 1.1038 data_time: 0.0734 memory: 16201 loss_prob: 0.6254 loss_thr: 0.3984 loss_db: 0.1085 loss: 1.1323 2022/08/30 11:19:01 - mmengine - INFO - Epoch(train) [448][40/63] lr: 4.6000e-03 eta: 19:25:04 time: 1.1663 data_time: 0.0899 memory: 16201 loss_prob: 0.6363 loss_thr: 0.4097 loss_db: 0.1056 loss: 1.1515 2022/08/30 11:19:06 - mmengine - INFO - Epoch(train) [448][45/63] lr: 4.6000e-03 eta: 19:25:04 time: 1.0113 data_time: 0.0385 memory: 16201 loss_prob: 0.6773 loss_thr: 0.4308 loss_db: 0.1117 loss: 1.2198 2022/08/30 11:19:11 - mmengine - INFO - Epoch(train) [448][50/63] lr: 4.6000e-03 eta: 19:24:42 time: 1.0387 data_time: 0.0321 memory: 16201 loss_prob: 0.5878 loss_thr: 0.3921 loss_db: 0.1009 loss: 1.0807 2022/08/30 11:19:16 - mmengine - INFO - Epoch(train) [448][55/63] lr: 4.6000e-03 eta: 19:24:42 time: 1.0313 data_time: 0.0284 memory: 16201 loss_prob: 0.5675 loss_thr: 0.3679 loss_db: 0.0981 loss: 1.0335 2022/08/30 11:19:21 - mmengine - INFO - Epoch(train) [448][60/63] lr: 4.6000e-03 eta: 19:24:19 time: 0.9725 data_time: 0.0341 memory: 16201 loss_prob: 0.6245 loss_thr: 0.4011 loss_db: 0.1063 loss: 1.1319 2022/08/30 11:19:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:19:29 - mmengine - INFO - Epoch(train) [449][5/63] lr: 4.5945e-03 eta: 19:24:19 time: 0.9979 data_time: 0.1755 memory: 16201 loss_prob: 0.6692 loss_thr: 0.4279 loss_db: 0.1137 loss: 1.2108 2022/08/30 11:19:33 - mmengine - INFO - Epoch(train) [449][10/63] lr: 4.5945e-03 eta: 19:23:43 time: 0.9502 data_time: 0.1802 memory: 16201 loss_prob: 0.6073 loss_thr: 0.3993 loss_db: 0.1022 loss: 1.1088 2022/08/30 11:19:37 - mmengine - INFO - Epoch(train) [449][15/63] lr: 4.5945e-03 eta: 19:23:43 time: 0.8471 data_time: 0.0273 memory: 16201 loss_prob: 0.6518 loss_thr: 0.3920 loss_db: 0.1175 loss: 1.1614 2022/08/30 11:19:41 - mmengine - INFO - Epoch(train) [449][20/63] lr: 4.5945e-03 eta: 19:23:18 time: 0.8439 data_time: 0.0238 memory: 16201 loss_prob: 0.6512 loss_thr: 0.3907 loss_db: 0.1164 loss: 1.1583 2022/08/30 11:19:45 - mmengine - INFO - Epoch(train) [449][25/63] lr: 4.5945e-03 eta: 19:23:18 time: 0.7826 data_time: 0.0315 memory: 16201 loss_prob: 0.5950 loss_thr: 0.3927 loss_db: 0.1009 loss: 1.0886 2022/08/30 11:19:49 - mmengine - INFO - Epoch(train) [449][30/63] lr: 4.5945e-03 eta: 19:22:52 time: 0.7882 data_time: 0.0330 memory: 16201 loss_prob: 0.6043 loss_thr: 0.4067 loss_db: 0.1055 loss: 1.1164 2022/08/30 11:19:53 - mmengine - INFO - Epoch(train) [449][35/63] lr: 4.5945e-03 eta: 19:22:52 time: 0.7891 data_time: 0.0287 memory: 16201 loss_prob: 0.6193 loss_thr: 0.4096 loss_db: 0.1087 loss: 1.1376 2022/08/30 11:19:58 - mmengine - INFO - Epoch(train) [449][40/63] lr: 4.5945e-03 eta: 19:22:27 time: 0.8715 data_time: 0.0469 memory: 16201 loss_prob: 0.5975 loss_thr: 0.4049 loss_db: 0.1017 loss: 1.1042 2022/08/30 11:20:02 - mmengine - INFO - Epoch(train) [449][45/63] lr: 4.5945e-03 eta: 19:22:27 time: 0.8681 data_time: 0.0473 memory: 16201 loss_prob: 0.5670 loss_thr: 0.3818 loss_db: 0.0973 loss: 1.0461 2022/08/30 11:20:06 - mmengine - INFO - Epoch(train) [449][50/63] lr: 4.5945e-03 eta: 19:22:01 time: 0.7867 data_time: 0.0284 memory: 16201 loss_prob: 0.5695 loss_thr: 0.3645 loss_db: 0.0995 loss: 1.0335 2022/08/30 11:20:10 - mmengine - INFO - Epoch(train) [449][55/63] lr: 4.5945e-03 eta: 19:22:01 time: 0.7948 data_time: 0.0275 memory: 16201 loss_prob: 0.5961 loss_thr: 0.3799 loss_db: 0.1016 loss: 1.0776 2022/08/30 11:20:14 - mmengine - INFO - Epoch(train) [449][60/63] lr: 4.5945e-03 eta: 19:21:35 time: 0.7932 data_time: 0.0233 memory: 16201 loss_prob: 0.6790 loss_thr: 0.4123 loss_db: 0.1103 loss: 1.2016 2022/08/30 11:20:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:20:22 - mmengine - INFO - Epoch(train) [450][5/63] lr: 4.5890e-03 eta: 19:21:35 time: 0.9785 data_time: 0.1610 memory: 16201 loss_prob: 0.5429 loss_thr: 0.3684 loss_db: 0.0943 loss: 1.0056 2022/08/30 11:20:26 - mmengine - INFO - Epoch(train) [450][10/63] lr: 4.5890e-03 eta: 19:20:59 time: 0.9216 data_time: 0.1770 memory: 16201 loss_prob: 0.5017 loss_thr: 0.3730 loss_db: 0.0884 loss: 0.9631 2022/08/30 11:20:30 - mmengine - INFO - Epoch(train) [450][15/63] lr: 4.5890e-03 eta: 19:20:59 time: 0.7802 data_time: 0.0272 memory: 16201 loss_prob: 0.5202 loss_thr: 0.3770 loss_db: 0.0905 loss: 0.9878 2022/08/30 11:20:34 - mmengine - INFO - Epoch(train) [450][20/63] lr: 4.5890e-03 eta: 19:20:32 time: 0.7663 data_time: 0.0169 memory: 16201 loss_prob: 0.5741 loss_thr: 0.3879 loss_db: 0.0994 loss: 1.0614 2022/08/30 11:20:38 - mmengine - INFO - Epoch(train) [450][25/63] lr: 4.5890e-03 eta: 19:20:32 time: 0.8565 data_time: 0.0380 memory: 16201 loss_prob: 0.5690 loss_thr: 0.3840 loss_db: 0.0970 loss: 1.0499 2022/08/30 11:20:42 - mmengine - INFO - Epoch(train) [450][30/63] lr: 4.5890e-03 eta: 19:20:07 time: 0.8517 data_time: 0.0335 memory: 16201 loss_prob: 0.5682 loss_thr: 0.3804 loss_db: 0.0978 loss: 1.0464 2022/08/30 11:20:46 - mmengine - INFO - Epoch(train) [450][35/63] lr: 4.5890e-03 eta: 19:20:07 time: 0.7784 data_time: 0.0243 memory: 16201 loss_prob: 0.5980 loss_thr: 0.3936 loss_db: 0.1056 loss: 1.0972 2022/08/30 11:20:50 - mmengine - INFO - Epoch(train) [450][40/63] lr: 4.5890e-03 eta: 19:19:41 time: 0.8051 data_time: 0.0327 memory: 16201 loss_prob: 0.6854 loss_thr: 0.4401 loss_db: 0.1158 loss: 1.2412 2022/08/30 11:20:54 - mmengine - INFO - Epoch(train) [450][45/63] lr: 4.5890e-03 eta: 19:19:41 time: 0.8000 data_time: 0.0286 memory: 16201 loss_prob: 0.6708 loss_thr: 0.4437 loss_db: 0.1116 loss: 1.2260 2022/08/30 11:20:58 - mmengine - INFO - Epoch(train) [450][50/63] lr: 4.5890e-03 eta: 19:19:15 time: 0.7892 data_time: 0.0304 memory: 16201 loss_prob: 0.5942 loss_thr: 0.4153 loss_db: 0.1042 loss: 1.1137 2022/08/30 11:21:02 - mmengine - INFO - Epoch(train) [450][55/63] lr: 4.5890e-03 eta: 19:19:15 time: 0.8113 data_time: 0.0432 memory: 16201 loss_prob: 0.5947 loss_thr: 0.4020 loss_db: 0.1046 loss: 1.1013 2022/08/30 11:21:06 - mmengine - INFO - Epoch(train) [450][60/63] lr: 4.5890e-03 eta: 19:18:50 time: 0.8106 data_time: 0.0397 memory: 16201 loss_prob: 0.6029 loss_thr: 0.3966 loss_db: 0.1025 loss: 1.1021 2022/08/30 11:21:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:21:14 - mmengine - INFO - Epoch(train) [451][5/63] lr: 4.5835e-03 eta: 19:18:50 time: 0.8991 data_time: 0.1746 memory: 16201 loss_prob: 0.6380 loss_thr: 0.4134 loss_db: 0.1107 loss: 1.1621 2022/08/30 11:21:18 - mmengine - INFO - Epoch(train) [451][10/63] lr: 4.5835e-03 eta: 19:18:15 time: 0.9544 data_time: 0.1806 memory: 16201 loss_prob: 0.6055 loss_thr: 0.4108 loss_db: 0.1062 loss: 1.1224 2022/08/30 11:21:21 - mmengine - INFO - Epoch(train) [451][15/63] lr: 4.5835e-03 eta: 19:18:15 time: 0.7829 data_time: 0.0249 memory: 16201 loss_prob: 0.6493 loss_thr: 0.4093 loss_db: 0.1102 loss: 1.1688 2022/08/30 11:21:25 - mmengine - INFO - Epoch(train) [451][20/63] lr: 4.5835e-03 eta: 19:17:48 time: 0.7775 data_time: 0.0225 memory: 16201 loss_prob: 0.6782 loss_thr: 0.4219 loss_db: 0.1129 loss: 1.2130 2022/08/30 11:21:30 - mmengine - INFO - Epoch(train) [451][25/63] lr: 4.5835e-03 eta: 19:17:48 time: 0.8220 data_time: 0.0458 memory: 16201 loss_prob: 0.8100 loss_thr: 0.4309 loss_db: 0.1403 loss: 1.3812 2022/08/30 11:21:34 - mmengine - INFO - Epoch(train) [451][30/63] lr: 4.5835e-03 eta: 19:17:23 time: 0.8078 data_time: 0.0439 memory: 16201 loss_prob: 0.7794 loss_thr: 0.4252 loss_db: 0.1367 loss: 1.3413 2022/08/30 11:21:37 - mmengine - INFO - Epoch(train) [451][35/63] lr: 4.5835e-03 eta: 19:17:23 time: 0.7750 data_time: 0.0200 memory: 16201 loss_prob: 0.6608 loss_thr: 0.4086 loss_db: 0.1161 loss: 1.1855 2022/08/30 11:21:41 - mmengine - INFO - Epoch(train) [451][40/63] lr: 4.5835e-03 eta: 19:16:56 time: 0.7867 data_time: 0.0272 memory: 16201 loss_prob: 0.6604 loss_thr: 0.4085 loss_db: 0.1141 loss: 1.1831 2022/08/30 11:21:45 - mmengine - INFO - Epoch(train) [451][45/63] lr: 4.5835e-03 eta: 19:16:56 time: 0.7990 data_time: 0.0337 memory: 16201 loss_prob: 0.6160 loss_thr: 0.3998 loss_db: 0.1042 loss: 1.1200 2022/08/30 11:21:49 - mmengine - INFO - Epoch(train) [451][50/63] lr: 4.5835e-03 eta: 19:16:30 time: 0.7834 data_time: 0.0251 memory: 16201 loss_prob: 0.7669 loss_thr: 0.4317 loss_db: 0.1250 loss: 1.3236 2022/08/30 11:21:53 - mmengine - INFO - Epoch(train) [451][55/63] lr: 4.5835e-03 eta: 19:16:30 time: 0.7688 data_time: 0.0326 memory: 16201 loss_prob: 0.8164 loss_thr: 0.4607 loss_db: 0.1345 loss: 1.4116 2022/08/30 11:21:57 - mmengine - INFO - Epoch(train) [451][60/63] lr: 4.5835e-03 eta: 19:16:05 time: 0.8116 data_time: 0.0465 memory: 16201 loss_prob: 0.6365 loss_thr: 0.4136 loss_db: 0.1085 loss: 1.1586 2022/08/30 11:21:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:22:05 - mmengine - INFO - Epoch(train) [452][5/63] lr: 4.5780e-03 eta: 19:16:05 time: 0.9514 data_time: 0.2100 memory: 16201 loss_prob: 0.6608 loss_thr: 0.4113 loss_db: 0.1130 loss: 1.1851 2022/08/30 11:22:09 - mmengine - INFO - Epoch(train) [452][10/63] lr: 4.5780e-03 eta: 19:15:30 time: 0.9756 data_time: 0.2125 memory: 16201 loss_prob: 0.6934 loss_thr: 0.4195 loss_db: 0.1177 loss: 1.2306 2022/08/30 11:22:13 - mmengine - INFO - Epoch(train) [452][15/63] lr: 4.5780e-03 eta: 19:15:30 time: 0.8030 data_time: 0.0299 memory: 16201 loss_prob: 0.6535 loss_thr: 0.4122 loss_db: 0.1117 loss: 1.1774 2022/08/30 11:22:18 - mmengine - INFO - Epoch(train) [452][20/63] lr: 4.5780e-03 eta: 19:15:06 time: 0.8944 data_time: 0.0266 memory: 16201 loss_prob: 0.5759 loss_thr: 0.3697 loss_db: 0.0989 loss: 1.0446 2022/08/30 11:22:22 - mmengine - INFO - Epoch(train) [452][25/63] lr: 4.5780e-03 eta: 19:15:06 time: 0.8746 data_time: 0.0334 memory: 16201 loss_prob: 0.6331 loss_thr: 0.4053 loss_db: 0.1083 loss: 1.1468 2022/08/30 11:22:26 - mmengine - INFO - Epoch(train) [452][30/63] lr: 4.5780e-03 eta: 19:14:40 time: 0.7710 data_time: 0.0235 memory: 16201 loss_prob: 0.6990 loss_thr: 0.4276 loss_db: 0.1175 loss: 1.2442 2022/08/30 11:22:30 - mmengine - INFO - Epoch(train) [452][35/63] lr: 4.5780e-03 eta: 19:14:40 time: 0.7725 data_time: 0.0233 memory: 16201 loss_prob: 0.6653 loss_thr: 0.4038 loss_db: 0.1138 loss: 1.1829 2022/08/30 11:22:34 - mmengine - INFO - Epoch(train) [452][40/63] lr: 4.5780e-03 eta: 19:14:14 time: 0.8065 data_time: 0.0303 memory: 16201 loss_prob: 0.6398 loss_thr: 0.4222 loss_db: 0.1089 loss: 1.1709 2022/08/30 11:22:38 - mmengine - INFO - Epoch(train) [452][45/63] lr: 4.5780e-03 eta: 19:14:14 time: 0.8153 data_time: 0.0343 memory: 16201 loss_prob: 0.5953 loss_thr: 0.4041 loss_db: 0.1026 loss: 1.1020 2022/08/30 11:22:42 - mmengine - INFO - Epoch(train) [452][50/63] lr: 4.5780e-03 eta: 19:13:48 time: 0.7801 data_time: 0.0275 memory: 16201 loss_prob: 0.5879 loss_thr: 0.4004 loss_db: 0.1046 loss: 1.0929 2022/08/30 11:22:46 - mmengine - INFO - Epoch(train) [452][55/63] lr: 4.5780e-03 eta: 19:13:48 time: 0.7844 data_time: 0.0326 memory: 16201 loss_prob: 0.5455 loss_thr: 0.3830 loss_db: 0.0945 loss: 1.0230 2022/08/30 11:22:50 - mmengine - INFO - Epoch(train) [452][60/63] lr: 4.5780e-03 eta: 19:13:22 time: 0.8142 data_time: 0.0385 memory: 16201 loss_prob: 0.4987 loss_thr: 0.3495 loss_db: 0.0856 loss: 0.9337 2022/08/30 11:22:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:22:57 - mmengine - INFO - Epoch(train) [453][5/63] lr: 4.5725e-03 eta: 19:13:22 time: 0.8947 data_time: 0.1690 memory: 16201 loss_prob: 0.5543 loss_thr: 0.3892 loss_db: 0.0962 loss: 1.0398 2022/08/30 11:23:01 - mmengine - INFO - Epoch(train) [453][10/63] lr: 4.5725e-03 eta: 19:12:47 time: 0.9123 data_time: 0.1717 memory: 16201 loss_prob: 0.5354 loss_thr: 0.3843 loss_db: 0.0952 loss: 1.0149 2022/08/30 11:23:05 - mmengine - INFO - Epoch(train) [453][15/63] lr: 4.5725e-03 eta: 19:12:47 time: 0.7803 data_time: 0.0293 memory: 16201 loss_prob: 0.5739 loss_thr: 0.3913 loss_db: 0.0989 loss: 1.0641 2022/08/30 11:23:09 - mmengine - INFO - Epoch(train) [453][20/63] lr: 4.5725e-03 eta: 19:12:21 time: 0.8216 data_time: 0.0319 memory: 16201 loss_prob: 0.5881 loss_thr: 0.3862 loss_db: 0.0973 loss: 1.0716 2022/08/30 11:23:13 - mmengine - INFO - Epoch(train) [453][25/63] lr: 4.5725e-03 eta: 19:12:21 time: 0.8213 data_time: 0.0350 memory: 16201 loss_prob: 0.5505 loss_thr: 0.3612 loss_db: 0.0956 loss: 1.0073 2022/08/30 11:23:17 - mmengine - INFO - Epoch(train) [453][30/63] lr: 4.5725e-03 eta: 19:11:55 time: 0.7799 data_time: 0.0264 memory: 16201 loss_prob: 0.5609 loss_thr: 0.3680 loss_db: 0.1006 loss: 1.0294 2022/08/30 11:23:21 - mmengine - INFO - Epoch(train) [453][35/63] lr: 4.5725e-03 eta: 19:11:55 time: 0.7731 data_time: 0.0199 memory: 16201 loss_prob: 0.6363 loss_thr: 0.4056 loss_db: 0.1084 loss: 1.1503 2022/08/30 11:23:25 - mmengine - INFO - Epoch(train) [453][40/63] lr: 4.5725e-03 eta: 19:11:29 time: 0.7869 data_time: 0.0276 memory: 16201 loss_prob: 0.6302 loss_thr: 0.4043 loss_db: 0.1045 loss: 1.1391 2022/08/30 11:23:29 - mmengine - INFO - Epoch(train) [453][45/63] lr: 4.5725e-03 eta: 19:11:29 time: 0.8347 data_time: 0.0370 memory: 16201 loss_prob: 0.5770 loss_thr: 0.3872 loss_db: 0.0996 loss: 1.0638 2022/08/30 11:23:33 - mmengine - INFO - Epoch(train) [453][50/63] lr: 4.5725e-03 eta: 19:11:04 time: 0.8314 data_time: 0.0281 memory: 16201 loss_prob: 0.5899 loss_thr: 0.4012 loss_db: 0.1038 loss: 1.0949 2022/08/30 11:23:37 - mmengine - INFO - Epoch(train) [453][55/63] lr: 4.5725e-03 eta: 19:11:04 time: 0.7925 data_time: 0.0355 memory: 16201 loss_prob: 0.6734 loss_thr: 0.4339 loss_db: 0.1153 loss: 1.2227 2022/08/30 11:23:41 - mmengine - INFO - Epoch(train) [453][60/63] lr: 4.5725e-03 eta: 19:10:38 time: 0.7876 data_time: 0.0400 memory: 16201 loss_prob: 0.6744 loss_thr: 0.4251 loss_db: 0.1142 loss: 1.2137 2022/08/30 11:23:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:23:49 - mmengine - INFO - Epoch(train) [454][5/63] lr: 4.5670e-03 eta: 19:10:38 time: 0.9394 data_time: 0.1747 memory: 16201 loss_prob: 0.5667 loss_thr: 0.3897 loss_db: 0.0968 loss: 1.0531 2022/08/30 11:23:53 - mmengine - INFO - Epoch(train) [454][10/63] lr: 4.5670e-03 eta: 19:10:04 time: 0.9938 data_time: 0.1944 memory: 16201 loss_prob: 0.5643 loss_thr: 0.3934 loss_db: 0.0961 loss: 1.0537 2022/08/30 11:23:57 - mmengine - INFO - Epoch(train) [454][15/63] lr: 4.5670e-03 eta: 19:10:04 time: 0.8591 data_time: 0.0446 memory: 16201 loss_prob: 0.6213 loss_thr: 0.4157 loss_db: 0.1056 loss: 1.1427 2022/08/30 11:24:01 - mmengine - INFO - Epoch(train) [454][20/63] lr: 4.5670e-03 eta: 19:09:39 time: 0.8356 data_time: 0.0265 memory: 16201 loss_prob: 0.6185 loss_thr: 0.4106 loss_db: 0.1041 loss: 1.1332 2022/08/30 11:24:05 - mmengine - INFO - Epoch(train) [454][25/63] lr: 4.5670e-03 eta: 19:09:39 time: 0.7842 data_time: 0.0389 memory: 16201 loss_prob: 0.5498 loss_thr: 0.3882 loss_db: 0.0960 loss: 1.0340 2022/08/30 11:24:09 - mmengine - INFO - Epoch(train) [454][30/63] lr: 4.5670e-03 eta: 19:09:14 time: 0.8162 data_time: 0.0403 memory: 16201 loss_prob: 0.5152 loss_thr: 0.3726 loss_db: 0.0909 loss: 0.9786 2022/08/30 11:24:13 - mmengine - INFO - Epoch(train) [454][35/63] lr: 4.5670e-03 eta: 19:09:14 time: 0.8126 data_time: 0.0288 memory: 16201 loss_prob: 0.5256 loss_thr: 0.3727 loss_db: 0.0912 loss: 0.9895 2022/08/30 11:24:17 - mmengine - INFO - Epoch(train) [454][40/63] lr: 4.5670e-03 eta: 19:08:48 time: 0.7913 data_time: 0.0254 memory: 16201 loss_prob: 0.5668 loss_thr: 0.3911 loss_db: 0.0986 loss: 1.0565 2022/08/30 11:24:21 - mmengine - INFO - Epoch(train) [454][45/63] lr: 4.5670e-03 eta: 19:08:48 time: 0.7882 data_time: 0.0270 memory: 16201 loss_prob: 0.5813 loss_thr: 0.3923 loss_db: 0.1007 loss: 1.0743 2022/08/30 11:24:25 - mmengine - INFO - Epoch(train) [454][50/63] lr: 4.5670e-03 eta: 19:08:22 time: 0.7849 data_time: 0.0258 memory: 16201 loss_prob: 0.5648 loss_thr: 0.3750 loss_db: 0.0973 loss: 1.0371 2022/08/30 11:24:30 - mmengine - INFO - Epoch(train) [454][55/63] lr: 4.5670e-03 eta: 19:08:22 time: 0.8947 data_time: 0.0353 memory: 16201 loss_prob: 0.5633 loss_thr: 0.3716 loss_db: 0.0978 loss: 1.0327 2022/08/30 11:24:34 - mmengine - INFO - Epoch(train) [454][60/63] lr: 4.5670e-03 eta: 19:07:58 time: 0.9127 data_time: 0.0496 memory: 16201 loss_prob: 0.5544 loss_thr: 0.3692 loss_db: 0.0990 loss: 1.0226 2022/08/30 11:24:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:24:42 - mmengine - INFO - Epoch(train) [455][5/63] lr: 4.5615e-03 eta: 19:07:58 time: 0.9132 data_time: 0.1777 memory: 16201 loss_prob: 0.4973 loss_thr: 0.3440 loss_db: 0.0843 loss: 0.9256 2022/08/30 11:24:46 - mmengine - INFO - Epoch(train) [455][10/63] lr: 4.5615e-03 eta: 19:07:24 time: 0.9445 data_time: 0.1828 memory: 16201 loss_prob: 0.5085 loss_thr: 0.3518 loss_db: 0.0867 loss: 0.9471 2022/08/30 11:24:50 - mmengine - INFO - Epoch(train) [455][15/63] lr: 4.5615e-03 eta: 19:07:24 time: 0.7982 data_time: 0.0269 memory: 16201 loss_prob: 0.5392 loss_thr: 0.3662 loss_db: 0.0937 loss: 0.9992 2022/08/30 11:24:54 - mmengine - INFO - Epoch(train) [455][20/63] lr: 4.5615e-03 eta: 19:06:58 time: 0.7913 data_time: 0.0234 memory: 16201 loss_prob: 0.5066 loss_thr: 0.3404 loss_db: 0.0890 loss: 0.9359 2022/08/30 11:24:58 - mmengine - INFO - Epoch(train) [455][25/63] lr: 4.5615e-03 eta: 19:06:58 time: 0.8295 data_time: 0.0309 memory: 16201 loss_prob: 0.5311 loss_thr: 0.3504 loss_db: 0.0913 loss: 0.9728 2022/08/30 11:25:02 - mmengine - INFO - Epoch(train) [455][30/63] lr: 4.5615e-03 eta: 19:06:33 time: 0.8639 data_time: 0.0288 memory: 16201 loss_prob: 0.5678 loss_thr: 0.3873 loss_db: 0.0966 loss: 1.0518 2022/08/30 11:25:06 - mmengine - INFO - Epoch(train) [455][35/63] lr: 4.5615e-03 eta: 19:06:33 time: 0.8258 data_time: 0.0320 memory: 16201 loss_prob: 0.5586 loss_thr: 0.3919 loss_db: 0.0963 loss: 1.0469 2022/08/30 11:25:10 - mmengine - INFO - Epoch(train) [455][40/63] lr: 4.5615e-03 eta: 19:06:08 time: 0.8050 data_time: 0.0442 memory: 16201 loss_prob: 0.5709 loss_thr: 0.3928 loss_db: 0.0991 loss: 1.0628 2022/08/30 11:25:14 - mmengine - INFO - Epoch(train) [455][45/63] lr: 4.5615e-03 eta: 19:06:08 time: 0.7930 data_time: 0.0381 memory: 16201 loss_prob: 0.5286 loss_thr: 0.3860 loss_db: 0.0934 loss: 1.0079 2022/08/30 11:25:18 - mmengine - INFO - Epoch(train) [455][50/63] lr: 4.5615e-03 eta: 19:05:42 time: 0.8035 data_time: 0.0280 memory: 16201 loss_prob: 0.5577 loss_thr: 0.3842 loss_db: 0.0973 loss: 1.0392 2022/08/30 11:25:22 - mmengine - INFO - Epoch(train) [455][55/63] lr: 4.5615e-03 eta: 19:05:42 time: 0.8116 data_time: 0.0271 memory: 16201 loss_prob: 0.5871 loss_thr: 0.3922 loss_db: 0.1003 loss: 1.0796 2022/08/30 11:25:26 - mmengine - INFO - Epoch(train) [455][60/63] lr: 4.5615e-03 eta: 19:05:17 time: 0.7922 data_time: 0.0297 memory: 16201 loss_prob: 0.5934 loss_thr: 0.4024 loss_db: 0.1025 loss: 1.0983 2022/08/30 11:25:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:25:34 - mmengine - INFO - Epoch(train) [456][5/63] lr: 4.5560e-03 eta: 19:05:17 time: 0.8823 data_time: 0.1640 memory: 16201 loss_prob: 0.5675 loss_thr: 0.3887 loss_db: 0.0970 loss: 1.0531 2022/08/30 11:25:38 - mmengine - INFO - Epoch(train) [456][10/63] lr: 4.5560e-03 eta: 19:04:42 time: 0.9412 data_time: 0.1819 memory: 16201 loss_prob: 0.5790 loss_thr: 0.3904 loss_db: 0.1010 loss: 1.0704 2022/08/30 11:25:42 - mmengine - INFO - Epoch(train) [456][15/63] lr: 4.5560e-03 eta: 19:04:42 time: 0.7964 data_time: 0.0305 memory: 16201 loss_prob: 0.5874 loss_thr: 0.3974 loss_db: 0.1006 loss: 1.0853 2022/08/30 11:25:46 - mmengine - INFO - Epoch(train) [456][20/63] lr: 4.5560e-03 eta: 19:04:17 time: 0.8072 data_time: 0.0219 memory: 16201 loss_prob: 0.6073 loss_thr: 0.4024 loss_db: 0.1021 loss: 1.1118 2022/08/30 11:25:50 - mmengine - INFO - Epoch(train) [456][25/63] lr: 4.5560e-03 eta: 19:04:17 time: 0.8141 data_time: 0.0404 memory: 16201 loss_prob: 0.5846 loss_thr: 0.3854 loss_db: 0.0999 loss: 1.0699 2022/08/30 11:25:54 - mmengine - INFO - Epoch(train) [456][30/63] lr: 4.5560e-03 eta: 19:03:51 time: 0.7908 data_time: 0.0302 memory: 16201 loss_prob: 0.5235 loss_thr: 0.3605 loss_db: 0.0903 loss: 0.9744 2022/08/30 11:25:58 - mmengine - INFO - Epoch(train) [456][35/63] lr: 4.5560e-03 eta: 19:03:51 time: 0.7883 data_time: 0.0191 memory: 16201 loss_prob: 0.5651 loss_thr: 0.3675 loss_db: 0.0968 loss: 1.0294 2022/08/30 11:26:02 - mmengine - INFO - Epoch(train) [456][40/63] lr: 4.5560e-03 eta: 19:03:25 time: 0.7931 data_time: 0.0301 memory: 16201 loss_prob: 0.6185 loss_thr: 0.4042 loss_db: 0.1045 loss: 1.1271 2022/08/30 11:26:06 - mmengine - INFO - Epoch(train) [456][45/63] lr: 4.5560e-03 eta: 19:03:25 time: 0.7924 data_time: 0.0269 memory: 16201 loss_prob: 0.5661 loss_thr: 0.3876 loss_db: 0.0969 loss: 1.0505 2022/08/30 11:26:10 - mmengine - INFO - Epoch(train) [456][50/63] lr: 4.5560e-03 eta: 19:03:00 time: 0.7893 data_time: 0.0240 memory: 16201 loss_prob: 0.5555 loss_thr: 0.3957 loss_db: 0.0962 loss: 1.0474 2022/08/30 11:26:13 - mmengine - INFO - Epoch(train) [456][55/63] lr: 4.5560e-03 eta: 19:03:00 time: 0.7758 data_time: 0.0260 memory: 16201 loss_prob: 0.6189 loss_thr: 0.4352 loss_db: 0.1049 loss: 1.1590 2022/08/30 11:26:18 - mmengine - INFO - Epoch(train) [456][60/63] lr: 4.5560e-03 eta: 19:02:34 time: 0.7952 data_time: 0.0282 memory: 16201 loss_prob: 0.6305 loss_thr: 0.4168 loss_db: 0.1068 loss: 1.1541 2022/08/30 11:26:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:26:25 - mmengine - INFO - Epoch(train) [457][5/63] lr: 4.5504e-03 eta: 19:02:34 time: 0.9165 data_time: 0.1707 memory: 16201 loss_prob: 0.6468 loss_thr: 0.4127 loss_db: 0.1093 loss: 1.1687 2022/08/30 11:26:29 - mmengine - INFO - Epoch(train) [457][10/63] lr: 4.5504e-03 eta: 19:02:00 time: 0.9533 data_time: 0.1836 memory: 16201 loss_prob: 0.6081 loss_thr: 0.3988 loss_db: 0.1044 loss: 1.1113 2022/08/30 11:26:33 - mmengine - INFO - Epoch(train) [457][15/63] lr: 4.5504e-03 eta: 19:02:00 time: 0.7822 data_time: 0.0347 memory: 16201 loss_prob: 0.5662 loss_thr: 0.3795 loss_db: 0.0992 loss: 1.0449 2022/08/30 11:26:37 - mmengine - INFO - Epoch(train) [457][20/63] lr: 4.5504e-03 eta: 19:01:35 time: 0.8176 data_time: 0.0227 memory: 16201 loss_prob: 0.5474 loss_thr: 0.3873 loss_db: 0.0955 loss: 1.0301 2022/08/30 11:26:41 - mmengine - INFO - Epoch(train) [457][25/63] lr: 4.5504e-03 eta: 19:01:35 time: 0.8421 data_time: 0.0366 memory: 16201 loss_prob: 0.5283 loss_thr: 0.3691 loss_db: 0.0904 loss: 0.9877 2022/08/30 11:26:45 - mmengine - INFO - Epoch(train) [457][30/63] lr: 4.5504e-03 eta: 19:01:09 time: 0.7822 data_time: 0.0346 memory: 16201 loss_prob: 0.5282 loss_thr: 0.3524 loss_db: 0.0899 loss: 0.9705 2022/08/30 11:26:49 - mmengine - INFO - Epoch(train) [457][35/63] lr: 4.5504e-03 eta: 19:01:09 time: 0.7756 data_time: 0.0244 memory: 16201 loss_prob: 0.5149 loss_thr: 0.3508 loss_db: 0.0874 loss: 0.9531 2022/08/30 11:26:53 - mmengine - INFO - Epoch(train) [457][40/63] lr: 4.5504e-03 eta: 19:00:43 time: 0.7922 data_time: 0.0294 memory: 16201 loss_prob: 0.5260 loss_thr: 0.3620 loss_db: 0.0910 loss: 0.9790 2022/08/30 11:26:57 - mmengine - INFO - Epoch(train) [457][45/63] lr: 4.5504e-03 eta: 19:00:43 time: 0.8331 data_time: 0.0337 memory: 16201 loss_prob: 0.5567 loss_thr: 0.3809 loss_db: 0.0974 loss: 1.0350 2022/08/30 11:27:01 - mmengine - INFO - Epoch(train) [457][50/63] lr: 4.5504e-03 eta: 19:00:19 time: 0.8257 data_time: 0.0319 memory: 16201 loss_prob: 0.5868 loss_thr: 0.4090 loss_db: 0.1009 loss: 1.0967 2022/08/30 11:27:05 - mmengine - INFO - Epoch(train) [457][55/63] lr: 4.5504e-03 eta: 19:00:19 time: 0.7855 data_time: 0.0317 memory: 16201 loss_prob: 0.5676 loss_thr: 0.3973 loss_db: 0.0992 loss: 1.0641 2022/08/30 11:27:09 - mmengine - INFO - Epoch(train) [457][60/63] lr: 4.5504e-03 eta: 18:59:53 time: 0.7973 data_time: 0.0350 memory: 16201 loss_prob: 0.5222 loss_thr: 0.3608 loss_db: 0.0928 loss: 0.9759 2022/08/30 11:27:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:27:17 - mmengine - INFO - Epoch(train) [458][5/63] lr: 4.5449e-03 eta: 18:59:53 time: 0.8867 data_time: 0.1598 memory: 16201 loss_prob: 0.5263 loss_thr: 0.3569 loss_db: 0.0915 loss: 0.9747 2022/08/30 11:27:21 - mmengine - INFO - Epoch(train) [458][10/63] lr: 4.5449e-03 eta: 18:59:19 time: 0.9516 data_time: 0.1837 memory: 16201 loss_prob: 0.5883 loss_thr: 0.3778 loss_db: 0.0994 loss: 1.0656 2022/08/30 11:27:25 - mmengine - INFO - Epoch(train) [458][15/63] lr: 4.5449e-03 eta: 18:59:19 time: 0.8105 data_time: 0.0458 memory: 16201 loss_prob: 0.5323 loss_thr: 0.3532 loss_db: 0.0902 loss: 0.9756 2022/08/30 11:27:29 - mmengine - INFO - Epoch(train) [458][20/63] lr: 4.5449e-03 eta: 18:58:54 time: 0.8491 data_time: 0.0286 memory: 16201 loss_prob: 0.5082 loss_thr: 0.3549 loss_db: 0.0904 loss: 0.9534 2022/08/30 11:27:33 - mmengine - INFO - Epoch(train) [458][25/63] lr: 4.5449e-03 eta: 18:58:54 time: 0.8519 data_time: 0.0375 memory: 16201 loss_prob: 0.5971 loss_thr: 0.4043 loss_db: 0.1035 loss: 1.1048 2022/08/30 11:27:37 - mmengine - INFO - Epoch(train) [458][30/63] lr: 4.5449e-03 eta: 18:58:29 time: 0.8018 data_time: 0.0314 memory: 16201 loss_prob: 0.5717 loss_thr: 0.3885 loss_db: 0.0962 loss: 1.0563 2022/08/30 11:27:41 - mmengine - INFO - Epoch(train) [458][35/63] lr: 4.5449e-03 eta: 18:58:29 time: 0.8024 data_time: 0.0245 memory: 16201 loss_prob: 0.5334 loss_thr: 0.3711 loss_db: 0.0913 loss: 0.9959 2022/08/30 11:27:45 - mmengine - INFO - Epoch(train) [458][40/63] lr: 4.5449e-03 eta: 18:58:04 time: 0.8043 data_time: 0.0349 memory: 16201 loss_prob: 0.5994 loss_thr: 0.3899 loss_db: 0.1042 loss: 1.0935 2022/08/30 11:27:49 - mmengine - INFO - Epoch(train) [458][45/63] lr: 4.5449e-03 eta: 18:58:04 time: 0.8131 data_time: 0.0418 memory: 16201 loss_prob: 0.6367 loss_thr: 0.4070 loss_db: 0.1121 loss: 1.1558 2022/08/30 11:27:53 - mmengine - INFO - Epoch(train) [458][50/63] lr: 4.5449e-03 eta: 18:57:38 time: 0.7989 data_time: 0.0317 memory: 16201 loss_prob: 0.5759 loss_thr: 0.3995 loss_db: 0.1015 loss: 1.0768 2022/08/30 11:27:58 - mmengine - INFO - Epoch(train) [458][55/63] lr: 4.5449e-03 eta: 18:57:38 time: 0.8184 data_time: 0.0300 memory: 16201 loss_prob: 0.5287 loss_thr: 0.3782 loss_db: 0.0931 loss: 1.0000 2022/08/30 11:28:02 - mmengine - INFO - Epoch(train) [458][60/63] lr: 4.5449e-03 eta: 18:57:14 time: 0.8335 data_time: 0.0359 memory: 16201 loss_prob: 0.5416 loss_thr: 0.3821 loss_db: 0.0931 loss: 1.0169 2022/08/30 11:28:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:28:09 - mmengine - INFO - Epoch(train) [459][5/63] lr: 4.5394e-03 eta: 18:57:14 time: 0.9181 data_time: 0.1834 memory: 16201 loss_prob: 0.5482 loss_thr: 0.3865 loss_db: 0.0944 loss: 1.0292 2022/08/30 11:28:13 - mmengine - INFO - Epoch(train) [459][10/63] lr: 4.5394e-03 eta: 18:56:39 time: 0.9607 data_time: 0.1977 memory: 16201 loss_prob: 0.5490 loss_thr: 0.3790 loss_db: 0.0965 loss: 1.0245 2022/08/30 11:28:17 - mmengine - INFO - Epoch(train) [459][15/63] lr: 4.5394e-03 eta: 18:56:39 time: 0.7995 data_time: 0.0354 memory: 16201 loss_prob: 0.5788 loss_thr: 0.3829 loss_db: 0.0978 loss: 1.0595 2022/08/30 11:28:21 - mmengine - INFO - Epoch(train) [459][20/63] lr: 4.5394e-03 eta: 18:56:14 time: 0.8006 data_time: 0.0206 memory: 16201 loss_prob: 0.6102 loss_thr: 0.3884 loss_db: 0.1016 loss: 1.1002 2022/08/30 11:28:25 - mmengine - INFO - Epoch(train) [459][25/63] lr: 4.5394e-03 eta: 18:56:14 time: 0.8320 data_time: 0.0529 memory: 16201 loss_prob: 0.6055 loss_thr: 0.3851 loss_db: 0.1032 loss: 1.0938 2022/08/30 11:28:29 - mmengine - INFO - Epoch(train) [459][30/63] lr: 4.5394e-03 eta: 18:55:49 time: 0.8167 data_time: 0.0452 memory: 16201 loss_prob: 0.5995 loss_thr: 0.3782 loss_db: 0.1035 loss: 1.0812 2022/08/30 11:28:34 - mmengine - INFO - Epoch(train) [459][35/63] lr: 4.5394e-03 eta: 18:55:49 time: 0.8510 data_time: 0.0865 memory: 16201 loss_prob: 0.5985 loss_thr: 0.3666 loss_db: 0.1048 loss: 1.0698 2022/08/30 11:28:38 - mmengine - INFO - Epoch(train) [459][40/63] lr: 4.5394e-03 eta: 18:55:25 time: 0.8554 data_time: 0.0908 memory: 16201 loss_prob: 0.5937 loss_thr: 0.3786 loss_db: 0.1017 loss: 1.0739 2022/08/30 11:28:42 - mmengine - INFO - Epoch(train) [459][45/63] lr: 4.5394e-03 eta: 18:55:25 time: 0.7834 data_time: 0.0210 memory: 16201 loss_prob: 0.6019 loss_thr: 0.4014 loss_db: 0.1028 loss: 1.1061 2022/08/30 11:28:46 - mmengine - INFO - Epoch(train) [459][50/63] lr: 4.5394e-03 eta: 18:54:59 time: 0.7915 data_time: 0.0301 memory: 16201 loss_prob: 0.5933 loss_thr: 0.3934 loss_db: 0.1043 loss: 1.0909 2022/08/30 11:28:50 - mmengine - INFO - Epoch(train) [459][55/63] lr: 4.5394e-03 eta: 18:54:59 time: 0.8530 data_time: 0.0527 memory: 16201 loss_prob: 0.5680 loss_thr: 0.3839 loss_db: 0.0976 loss: 1.0495 2022/08/30 11:28:54 - mmengine - INFO - Epoch(train) [459][60/63] lr: 4.5394e-03 eta: 18:54:35 time: 0.8480 data_time: 0.0519 memory: 16201 loss_prob: 0.6136 loss_thr: 0.4013 loss_db: 0.1046 loss: 1.1196 2022/08/30 11:28:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:29:02 - mmengine - INFO - Epoch(train) [460][5/63] lr: 4.5339e-03 eta: 18:54:35 time: 0.9260 data_time: 0.1907 memory: 16201 loss_prob: 0.6257 loss_thr: 0.4176 loss_db: 0.1080 loss: 1.1514 2022/08/30 11:29:06 - mmengine - INFO - Epoch(train) [460][10/63] lr: 4.5339e-03 eta: 18:54:01 time: 0.9687 data_time: 0.2030 memory: 16201 loss_prob: 0.5826 loss_thr: 0.3963 loss_db: 0.1013 loss: 1.0802 2022/08/30 11:29:10 - mmengine - INFO - Epoch(train) [460][15/63] lr: 4.5339e-03 eta: 18:54:01 time: 0.8053 data_time: 0.0280 memory: 16201 loss_prob: 0.5739 loss_thr: 0.3876 loss_db: 0.1000 loss: 1.0615 2022/08/30 11:29:14 - mmengine - INFO - Epoch(train) [460][20/63] lr: 4.5339e-03 eta: 18:53:36 time: 0.7993 data_time: 0.0253 memory: 16201 loss_prob: 0.5588 loss_thr: 0.3747 loss_db: 0.0973 loss: 1.0308 2022/08/30 11:29:18 - mmengine - INFO - Epoch(train) [460][25/63] lr: 4.5339e-03 eta: 18:53:36 time: 0.8149 data_time: 0.0374 memory: 16201 loss_prob: 0.5194 loss_thr: 0.3652 loss_db: 0.0881 loss: 0.9727 2022/08/30 11:29:22 - mmengine - INFO - Epoch(train) [460][30/63] lr: 4.5339e-03 eta: 18:53:11 time: 0.8044 data_time: 0.0353 memory: 16201 loss_prob: 0.5600 loss_thr: 0.4043 loss_db: 0.0965 loss: 1.0608 2022/08/30 11:29:26 - mmengine - INFO - Epoch(train) [460][35/63] lr: 4.5339e-03 eta: 18:53:11 time: 0.7747 data_time: 0.0239 memory: 16201 loss_prob: 0.6287 loss_thr: 0.4324 loss_db: 0.1093 loss: 1.1704 2022/08/30 11:29:30 - mmengine - INFO - Epoch(train) [460][40/63] lr: 4.5339e-03 eta: 18:52:46 time: 0.8329 data_time: 0.0261 memory: 16201 loss_prob: 0.6497 loss_thr: 0.4119 loss_db: 0.1143 loss: 1.1759 2022/08/30 11:29:34 - mmengine - INFO - Epoch(train) [460][45/63] lr: 4.5339e-03 eta: 18:52:46 time: 0.8454 data_time: 0.0295 memory: 16201 loss_prob: 0.6540 loss_thr: 0.4019 loss_db: 0.1107 loss: 1.1666 2022/08/30 11:29:38 - mmengine - INFO - Epoch(train) [460][50/63] lr: 4.5339e-03 eta: 18:52:21 time: 0.7851 data_time: 0.0259 memory: 16201 loss_prob: 0.5962 loss_thr: 0.3880 loss_db: 0.0981 loss: 1.0823 2022/08/30 11:29:42 - mmengine - INFO - Epoch(train) [460][55/63] lr: 4.5339e-03 eta: 18:52:21 time: 0.7732 data_time: 0.0315 memory: 16201 loss_prob: 0.5453 loss_thr: 0.3716 loss_db: 0.0953 loss: 1.0122 2022/08/30 11:29:46 - mmengine - INFO - Epoch(train) [460][60/63] lr: 4.5339e-03 eta: 18:51:56 time: 0.8045 data_time: 0.0399 memory: 16201 loss_prob: 0.5294 loss_thr: 0.3587 loss_db: 0.0924 loss: 0.9805 2022/08/30 11:29:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:29:49 - mmengine - INFO - Saving checkpoint at 460 epochs 2022/08/30 11:29:59 - mmengine - INFO - Epoch(val) [460][5/32] eta: 18:51:56 time: 0.7474 data_time: 0.2327 memory: 16201 2022/08/30 11:30:02 - mmengine - INFO - Epoch(val) [460][10/32] eta: 0:00:17 time: 0.8073 data_time: 0.2487 memory: 15734 2022/08/30 11:30:05 - mmengine - INFO - Epoch(val) [460][15/32] eta: 0:00:17 time: 0.5909 data_time: 0.0484 memory: 15734 2022/08/30 11:30:08 - mmengine - INFO - Epoch(val) [460][20/32] eta: 0:00:07 time: 0.6505 data_time: 0.0896 memory: 15734 2022/08/30 11:30:11 - mmengine - INFO - Epoch(val) [460][25/32] eta: 0:00:07 time: 0.6511 data_time: 0.0775 memory: 15734 2022/08/30 11:30:14 - mmengine - INFO - Epoch(val) [460][30/32] eta: 0:00:01 time: 0.5673 data_time: 0.0212 memory: 15734 2022/08/30 11:30:15 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 11:30:15 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8296, precision: 0.7472, hmean: 0.7862 2022/08/30 11:30:15 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8296, precision: 0.8059, hmean: 0.8176 2022/08/30 11:30:15 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8276, precision: 0.8460, hmean: 0.8367 2022/08/30 11:30:15 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8252, precision: 0.8790, hmean: 0.8513 2022/08/30 11:30:15 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8093, precision: 0.8985, hmean: 0.8516 2022/08/30 11:30:15 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7256, precision: 0.9354, hmean: 0.8172 2022/08/30 11:30:15 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1276, precision: 0.9601, hmean: 0.2252 2022/08/30 11:30:15 - mmengine - INFO - Epoch(val) [460][32/32] icdar/precision: 0.8985 icdar/recall: 0.8093 icdar/hmean: 0.8516 2022/08/30 11:30:22 - mmengine - INFO - Epoch(train) [461][5/63] lr: 4.5284e-03 eta: 0:00:01 time: 1.1757 data_time: 0.3056 memory: 16201 loss_prob: 0.5374 loss_thr: 0.3446 loss_db: 0.0931 loss: 0.9751 2022/08/30 11:30:26 - mmengine - INFO - Epoch(train) [461][10/63] lr: 4.5284e-03 eta: 18:51:24 time: 1.0777 data_time: 0.2985 memory: 16201 loss_prob: 0.5446 loss_thr: 0.3581 loss_db: 0.0938 loss: 0.9965 2022/08/30 11:30:30 - mmengine - INFO - Epoch(train) [461][15/63] lr: 4.5284e-03 eta: 18:51:24 time: 0.8243 data_time: 0.0323 memory: 16201 loss_prob: 0.5412 loss_thr: 0.3729 loss_db: 0.0936 loss: 1.0078 2022/08/30 11:30:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:30:34 - mmengine - INFO - Epoch(train) [461][20/63] lr: 4.5284e-03 eta: 18:50:59 time: 0.8341 data_time: 0.0336 memory: 16201 loss_prob: 0.5894 loss_thr: 0.4037 loss_db: 0.1011 loss: 1.0942 2022/08/30 11:30:38 - mmengine - INFO - Epoch(train) [461][25/63] lr: 4.5284e-03 eta: 18:50:59 time: 0.7863 data_time: 0.0263 memory: 16201 loss_prob: 0.6391 loss_thr: 0.4280 loss_db: 0.1087 loss: 1.1758 2022/08/30 11:30:42 - mmengine - INFO - Epoch(train) [461][30/63] lr: 4.5284e-03 eta: 18:50:34 time: 0.7953 data_time: 0.0326 memory: 16201 loss_prob: 0.5900 loss_thr: 0.3944 loss_db: 0.1024 loss: 1.0869 2022/08/30 11:30:46 - mmengine - INFO - Epoch(train) [461][35/63] lr: 4.5284e-03 eta: 18:50:34 time: 0.8268 data_time: 0.0436 memory: 16201 loss_prob: 0.5647 loss_thr: 0.3775 loss_db: 0.0960 loss: 1.0382 2022/08/30 11:30:50 - mmengine - INFO - Epoch(train) [461][40/63] lr: 4.5284e-03 eta: 18:50:09 time: 0.8005 data_time: 0.0296 memory: 16201 loss_prob: 0.5418 loss_thr: 0.3691 loss_db: 0.0925 loss: 1.0034 2022/08/30 11:30:54 - mmengine - INFO - Epoch(train) [461][45/63] lr: 4.5284e-03 eta: 18:50:09 time: 0.8030 data_time: 0.0306 memory: 16201 loss_prob: 0.5137 loss_thr: 0.3566 loss_db: 0.0903 loss: 0.9606 2022/08/30 11:30:59 - mmengine - INFO - Epoch(train) [461][50/63] lr: 4.5284e-03 eta: 18:49:45 time: 0.8635 data_time: 0.0420 memory: 16201 loss_prob: 0.5613 loss_thr: 0.3692 loss_db: 0.0964 loss: 1.0269 2022/08/30 11:31:03 - mmengine - INFO - Epoch(train) [461][55/63] lr: 4.5284e-03 eta: 18:49:45 time: 0.8464 data_time: 0.0355 memory: 16201 loss_prob: 0.5503 loss_thr: 0.3606 loss_db: 0.0946 loss: 1.0055 2022/08/30 11:31:07 - mmengine - INFO - Epoch(train) [461][60/63] lr: 4.5284e-03 eta: 18:49:20 time: 0.8408 data_time: 0.0450 memory: 16201 loss_prob: 0.5858 loss_thr: 0.3844 loss_db: 0.0992 loss: 1.0695 2022/08/30 11:31:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:31:15 - mmengine - INFO - Epoch(train) [462][5/63] lr: 4.5229e-03 eta: 18:49:20 time: 0.9780 data_time: 0.1911 memory: 16201 loss_prob: 0.5742 loss_thr: 0.3736 loss_db: 0.0917 loss: 1.0395 2022/08/30 11:31:19 - mmengine - INFO - Epoch(train) [462][10/63] lr: 4.5229e-03 eta: 18:48:47 time: 0.9869 data_time: 0.2054 memory: 16201 loss_prob: 0.5557 loss_thr: 0.3754 loss_db: 0.0897 loss: 1.0207 2022/08/30 11:31:23 - mmengine - INFO - Epoch(train) [462][15/63] lr: 4.5229e-03 eta: 18:48:47 time: 0.8133 data_time: 0.0352 memory: 16201 loss_prob: 0.5627 loss_thr: 0.4028 loss_db: 0.0983 loss: 1.0638 2022/08/30 11:31:27 - mmengine - INFO - Epoch(train) [462][20/63] lr: 4.5229e-03 eta: 18:48:22 time: 0.8110 data_time: 0.0332 memory: 16201 loss_prob: 0.5466 loss_thr: 0.3885 loss_db: 0.0948 loss: 1.0299 2022/08/30 11:31:31 - mmengine - INFO - Epoch(train) [462][25/63] lr: 4.5229e-03 eta: 18:48:22 time: 0.7927 data_time: 0.0330 memory: 16201 loss_prob: 0.5206 loss_thr: 0.3671 loss_db: 0.0891 loss: 0.9768 2022/08/30 11:31:35 - mmengine - INFO - Epoch(train) [462][30/63] lr: 4.5229e-03 eta: 18:47:57 time: 0.7834 data_time: 0.0379 memory: 16201 loss_prob: 0.5399 loss_thr: 0.3667 loss_db: 0.0911 loss: 0.9977 2022/08/30 11:31:39 - mmengine - INFO - Epoch(train) [462][35/63] lr: 4.5229e-03 eta: 18:47:57 time: 0.8127 data_time: 0.0441 memory: 16201 loss_prob: 0.6014 loss_thr: 0.3884 loss_db: 0.1009 loss: 1.0907 2022/08/30 11:31:43 - mmengine - INFO - Epoch(train) [462][40/63] lr: 4.5229e-03 eta: 18:47:32 time: 0.8294 data_time: 0.0512 memory: 16201 loss_prob: 0.6441 loss_thr: 0.4091 loss_db: 0.1102 loss: 1.1635 2022/08/30 11:31:47 - mmengine - INFO - Epoch(train) [462][45/63] lr: 4.5229e-03 eta: 18:47:32 time: 0.8048 data_time: 0.0484 memory: 16201 loss_prob: 0.6066 loss_thr: 0.3997 loss_db: 0.1030 loss: 1.1094 2022/08/30 11:31:51 - mmengine - INFO - Epoch(train) [462][50/63] lr: 4.5229e-03 eta: 18:47:07 time: 0.7919 data_time: 0.0261 memory: 16201 loss_prob: 0.6034 loss_thr: 0.4004 loss_db: 0.1036 loss: 1.1074 2022/08/30 11:31:56 - mmengine - INFO - Epoch(train) [462][55/63] lr: 4.5229e-03 eta: 18:47:07 time: 0.8039 data_time: 0.0233 memory: 16201 loss_prob: 0.6047 loss_thr: 0.4046 loss_db: 0.1068 loss: 1.1161 2022/08/30 11:32:00 - mmengine - INFO - Epoch(train) [462][60/63] lr: 4.5229e-03 eta: 18:46:44 time: 0.8914 data_time: 0.0403 memory: 16201 loss_prob: 0.5534 loss_thr: 0.3752 loss_db: 0.0980 loss: 1.0266 2022/08/30 11:32:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:32:08 - mmengine - INFO - Epoch(train) [463][5/63] lr: 4.5174e-03 eta: 18:46:44 time: 0.9237 data_time: 0.1974 memory: 16201 loss_prob: 0.5345 loss_thr: 0.3634 loss_db: 0.0921 loss: 0.9900 2022/08/30 11:32:12 - mmengine - INFO - Epoch(train) [463][10/63] lr: 4.5174e-03 eta: 18:46:10 time: 0.9685 data_time: 0.2025 memory: 16201 loss_prob: 0.6627 loss_thr: 0.3430 loss_db: 0.1175 loss: 1.1232 2022/08/30 11:32:16 - mmengine - INFO - Epoch(train) [463][15/63] lr: 4.5174e-03 eta: 18:46:10 time: 0.7873 data_time: 0.0267 memory: 16201 loss_prob: 0.8715 loss_thr: 0.3765 loss_db: 0.1404 loss: 1.3885 2022/08/30 11:32:21 - mmengine - INFO - Epoch(train) [463][20/63] lr: 4.5174e-03 eta: 18:45:46 time: 0.8722 data_time: 0.0295 memory: 16201 loss_prob: 1.0463 loss_thr: 0.4560 loss_db: 0.1592 loss: 1.6615 2022/08/30 11:32:25 - mmengine - INFO - Epoch(train) [463][25/63] lr: 4.5174e-03 eta: 18:45:46 time: 0.8825 data_time: 0.0452 memory: 16201 loss_prob: 1.1402 loss_thr: 0.4749 loss_db: 0.1847 loss: 1.7998 2022/08/30 11:32:29 - mmengine - INFO - Epoch(train) [463][30/63] lr: 4.5174e-03 eta: 18:45:21 time: 0.8098 data_time: 0.0353 memory: 16201 loss_prob: 1.0598 loss_thr: 0.4620 loss_db: 0.1653 loss: 1.6871 2022/08/30 11:32:33 - mmengine - INFO - Epoch(train) [463][35/63] lr: 4.5174e-03 eta: 18:45:21 time: 0.8041 data_time: 0.0236 memory: 16201 loss_prob: 1.0283 loss_thr: 0.4726 loss_db: 0.1534 loss: 1.6543 2022/08/30 11:32:37 - mmengine - INFO - Epoch(train) [463][40/63] lr: 4.5174e-03 eta: 18:44:56 time: 0.7846 data_time: 0.0295 memory: 16201 loss_prob: 1.0189 loss_thr: 0.4678 loss_db: 0.1639 loss: 1.6506 2022/08/30 11:32:41 - mmengine - INFO - Epoch(train) [463][45/63] lr: 4.5174e-03 eta: 18:44:56 time: 0.7905 data_time: 0.0341 memory: 16201 loss_prob: 0.8304 loss_thr: 0.4425 loss_db: 0.1410 loss: 1.4138 2022/08/30 11:32:45 - mmengine - INFO - Epoch(train) [463][50/63] lr: 4.5174e-03 eta: 18:44:31 time: 0.8020 data_time: 0.0302 memory: 16201 loss_prob: 0.7234 loss_thr: 0.4240 loss_db: 0.1187 loss: 1.2662 2022/08/30 11:32:49 - mmengine - INFO - Epoch(train) [463][55/63] lr: 4.5174e-03 eta: 18:44:31 time: 0.8082 data_time: 0.0326 memory: 16201 loss_prob: 0.9262 loss_thr: 0.4713 loss_db: 0.1553 loss: 1.5528 2022/08/30 11:32:53 - mmengine - INFO - Epoch(train) [463][60/63] lr: 4.5174e-03 eta: 18:44:07 time: 0.8220 data_time: 0.0370 memory: 16201 loss_prob: 0.8884 loss_thr: 0.4599 loss_db: 0.1511 loss: 1.4994 2022/08/30 11:32:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:33:01 - mmengine - INFO - Epoch(train) [464][5/63] lr: 4.5118e-03 eta: 18:44:07 time: 0.9637 data_time: 0.2051 memory: 16201 loss_prob: 0.6871 loss_thr: 0.4139 loss_db: 0.1157 loss: 1.2166 2022/08/30 11:33:05 - mmengine - INFO - Epoch(train) [464][10/63] lr: 4.5118e-03 eta: 18:43:34 time: 1.0104 data_time: 0.2258 memory: 16201 loss_prob: 0.6839 loss_thr: 0.4336 loss_db: 0.1110 loss: 1.2285 2022/08/30 11:33:09 - mmengine - INFO - Epoch(train) [464][15/63] lr: 4.5118e-03 eta: 18:43:34 time: 0.8271 data_time: 0.0532 memory: 16201 loss_prob: 0.7404 loss_thr: 0.4468 loss_db: 0.1245 loss: 1.3118 2022/08/30 11:33:13 - mmengine - INFO - Epoch(train) [464][20/63] lr: 4.5118e-03 eta: 18:43:09 time: 0.8096 data_time: 0.0284 memory: 16201 loss_prob: 0.7645 loss_thr: 0.4409 loss_db: 0.1319 loss: 1.3373 2022/08/30 11:33:17 - mmengine - INFO - Epoch(train) [464][25/63] lr: 4.5118e-03 eta: 18:43:09 time: 0.8188 data_time: 0.0367 memory: 16201 loss_prob: 0.7270 loss_thr: 0.4315 loss_db: 0.1237 loss: 1.2823 2022/08/30 11:33:21 - mmengine - INFO - Epoch(train) [464][30/63] lr: 4.5118e-03 eta: 18:42:44 time: 0.8030 data_time: 0.0384 memory: 16201 loss_prob: 0.6890 loss_thr: 0.4225 loss_db: 0.1177 loss: 1.2293 2022/08/30 11:33:25 - mmengine - INFO - Epoch(train) [464][35/63] lr: 4.5118e-03 eta: 18:42:44 time: 0.7776 data_time: 0.0269 memory: 16201 loss_prob: 0.7771 loss_thr: 0.4365 loss_db: 0.1311 loss: 1.3446 2022/08/30 11:33:29 - mmengine - INFO - Epoch(train) [464][40/63] lr: 4.5118e-03 eta: 18:42:20 time: 0.8107 data_time: 0.0458 memory: 16201 loss_prob: 0.8258 loss_thr: 0.4498 loss_db: 0.1336 loss: 1.4092 2022/08/30 11:33:33 - mmengine - INFO - Epoch(train) [464][45/63] lr: 4.5118e-03 eta: 18:42:20 time: 0.8292 data_time: 0.0524 memory: 16201 loss_prob: 0.7213 loss_thr: 0.4323 loss_db: 0.1193 loss: 1.2728 2022/08/30 11:33:37 - mmengine - INFO - Epoch(train) [464][50/63] lr: 4.5118e-03 eta: 18:41:55 time: 0.8058 data_time: 0.0264 memory: 16201 loss_prob: 0.7367 loss_thr: 0.4448 loss_db: 0.1220 loss: 1.3035 2022/08/30 11:33:41 - mmengine - INFO - Epoch(train) [464][55/63] lr: 4.5118e-03 eta: 18:41:55 time: 0.7837 data_time: 0.0250 memory: 16201 loss_prob: 0.7623 loss_thr: 0.4434 loss_db: 0.1244 loss: 1.3301 2022/08/30 11:33:46 - mmengine - INFO - Epoch(train) [464][60/63] lr: 4.5118e-03 eta: 18:41:30 time: 0.8295 data_time: 0.0251 memory: 16201 loss_prob: 0.7153 loss_thr: 0.4305 loss_db: 0.1223 loss: 1.2681 2022/08/30 11:33:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:33:53 - mmengine - INFO - Epoch(train) [465][5/63] lr: 4.5063e-03 eta: 18:41:30 time: 0.9443 data_time: 0.1774 memory: 16201 loss_prob: 0.7049 loss_thr: 0.4404 loss_db: 0.1158 loss: 1.2611 2022/08/30 11:33:57 - mmengine - INFO - Epoch(train) [465][10/63] lr: 4.5063e-03 eta: 18:40:57 time: 0.9538 data_time: 0.1843 memory: 16201 loss_prob: 0.6897 loss_thr: 0.4221 loss_db: 0.1152 loss: 1.2269 2022/08/30 11:34:01 - mmengine - INFO - Epoch(train) [465][15/63] lr: 4.5063e-03 eta: 18:40:57 time: 0.8098 data_time: 0.0289 memory: 16201 loss_prob: 0.7195 loss_thr: 0.4421 loss_db: 0.1244 loss: 1.2860 2022/08/30 11:34:05 - mmengine - INFO - Epoch(train) [465][20/63] lr: 4.5063e-03 eta: 18:40:32 time: 0.7900 data_time: 0.0210 memory: 16201 loss_prob: 0.6183 loss_thr: 0.4008 loss_db: 0.1087 loss: 1.1277 2022/08/30 11:34:10 - mmengine - INFO - Epoch(train) [465][25/63] lr: 4.5063e-03 eta: 18:40:32 time: 0.8464 data_time: 0.0330 memory: 16201 loss_prob: 0.6569 loss_thr: 0.3821 loss_db: 0.1035 loss: 1.1424 2022/08/30 11:34:14 - mmengine - INFO - Epoch(train) [465][30/63] lr: 4.5063e-03 eta: 18:40:08 time: 0.8618 data_time: 0.0397 memory: 16201 loss_prob: 0.7320 loss_thr: 0.4212 loss_db: 0.1162 loss: 1.2694 2022/08/30 11:34:18 - mmengine - INFO - Epoch(train) [465][35/63] lr: 4.5063e-03 eta: 18:40:08 time: 0.8065 data_time: 0.0325 memory: 16201 loss_prob: 0.6431 loss_thr: 0.4205 loss_db: 0.1112 loss: 1.1748 2022/08/30 11:34:22 - mmengine - INFO - Epoch(train) [465][40/63] lr: 4.5063e-03 eta: 18:39:43 time: 0.8065 data_time: 0.0350 memory: 16201 loss_prob: 0.6312 loss_thr: 0.4079 loss_db: 0.1067 loss: 1.1458 2022/08/30 11:34:26 - mmengine - INFO - Epoch(train) [465][45/63] lr: 4.5063e-03 eta: 18:39:43 time: 0.8101 data_time: 0.0325 memory: 16201 loss_prob: 0.6283 loss_thr: 0.4001 loss_db: 0.1067 loss: 1.1351 2022/08/30 11:34:30 - mmengine - INFO - Epoch(train) [465][50/63] lr: 4.5063e-03 eta: 18:39:19 time: 0.8453 data_time: 0.0257 memory: 16201 loss_prob: 0.5777 loss_thr: 0.3847 loss_db: 0.1006 loss: 1.0629 2022/08/30 11:34:34 - mmengine - INFO - Epoch(train) [465][55/63] lr: 4.5063e-03 eta: 18:39:19 time: 0.8412 data_time: 0.0398 memory: 16201 loss_prob: 0.5830 loss_thr: 0.3943 loss_db: 0.1008 loss: 1.0781 2022/08/30 11:34:38 - mmengine - INFO - Epoch(train) [465][60/63] lr: 4.5063e-03 eta: 18:38:54 time: 0.7867 data_time: 0.0362 memory: 16201 loss_prob: 0.6074 loss_thr: 0.4019 loss_db: 0.1030 loss: 1.1123 2022/08/30 11:34:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:34:46 - mmengine - INFO - Epoch(train) [466][5/63] lr: 4.5008e-03 eta: 18:38:54 time: 0.9303 data_time: 0.1954 memory: 16201 loss_prob: 0.5836 loss_thr: 0.3806 loss_db: 0.1017 loss: 1.0659 2022/08/30 11:34:50 - mmengine - INFO - Epoch(train) [466][10/63] lr: 4.5008e-03 eta: 18:38:21 time: 0.9608 data_time: 0.1891 memory: 16201 loss_prob: 0.6517 loss_thr: 0.4021 loss_db: 0.1106 loss: 1.1644 2022/08/30 11:34:54 - mmengine - INFO - Epoch(train) [466][15/63] lr: 4.5008e-03 eta: 18:38:21 time: 0.7801 data_time: 0.0228 memory: 16201 loss_prob: 0.6888 loss_thr: 0.4245 loss_db: 0.1166 loss: 1.2299 2022/08/30 11:34:58 - mmengine - INFO - Epoch(train) [466][20/63] lr: 4.5008e-03 eta: 18:37:56 time: 0.8202 data_time: 0.0292 memory: 16201 loss_prob: 0.6828 loss_thr: 0.4446 loss_db: 0.1163 loss: 1.2437 2022/08/30 11:35:02 - mmengine - INFO - Epoch(train) [466][25/63] lr: 4.5008e-03 eta: 18:37:56 time: 0.8294 data_time: 0.0337 memory: 16201 loss_prob: 0.6466 loss_thr: 0.4376 loss_db: 0.1088 loss: 1.1931 2022/08/30 11:35:06 - mmengine - INFO - Epoch(train) [466][30/63] lr: 4.5008e-03 eta: 18:37:32 time: 0.7951 data_time: 0.0294 memory: 16201 loss_prob: 0.6365 loss_thr: 0.4181 loss_db: 0.1093 loss: 1.1639 2022/08/30 11:35:10 - mmengine - INFO - Epoch(train) [466][35/63] lr: 4.5008e-03 eta: 18:37:32 time: 0.7923 data_time: 0.0267 memory: 16201 loss_prob: 0.6312 loss_thr: 0.4157 loss_db: 0.1082 loss: 1.1551 2022/08/30 11:35:14 - mmengine - INFO - Epoch(train) [466][40/63] lr: 4.5008e-03 eta: 18:37:07 time: 0.7985 data_time: 0.0305 memory: 16201 loss_prob: 0.6106 loss_thr: 0.4027 loss_db: 0.1053 loss: 1.1186 2022/08/30 11:35:18 - mmengine - INFO - Epoch(train) [466][45/63] lr: 4.5008e-03 eta: 18:37:07 time: 0.7982 data_time: 0.0338 memory: 16201 loss_prob: 0.6069 loss_thr: 0.4075 loss_db: 0.1046 loss: 1.1190 2022/08/30 11:35:22 - mmengine - INFO - Epoch(train) [466][50/63] lr: 4.5008e-03 eta: 18:36:42 time: 0.7989 data_time: 0.0260 memory: 16201 loss_prob: 0.5636 loss_thr: 0.3905 loss_db: 0.0980 loss: 1.0521 2022/08/30 11:35:26 - mmengine - INFO - Epoch(train) [466][55/63] lr: 4.5008e-03 eta: 18:36:42 time: 0.8022 data_time: 0.0268 memory: 16201 loss_prob: 0.5395 loss_thr: 0.3657 loss_db: 0.0948 loss: 0.9999 2022/08/30 11:35:31 - mmengine - INFO - Epoch(train) [466][60/63] lr: 4.5008e-03 eta: 18:36:18 time: 0.8707 data_time: 0.0642 memory: 16201 loss_prob: 0.5250 loss_thr: 0.3567 loss_db: 0.0907 loss: 0.9724 2022/08/30 11:35:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:35:38 - mmengine - INFO - Epoch(train) [467][5/63] lr: 4.4953e-03 eta: 18:36:18 time: 0.9329 data_time: 0.1746 memory: 16201 loss_prob: 0.6527 loss_thr: 0.3953 loss_db: 0.1083 loss: 1.1563 2022/08/30 11:35:42 - mmengine - INFO - Epoch(train) [467][10/63] lr: 4.4953e-03 eta: 18:35:45 time: 0.9688 data_time: 0.1877 memory: 16201 loss_prob: 0.5747 loss_thr: 0.3946 loss_db: 0.0975 loss: 1.0669 2022/08/30 11:35:46 - mmengine - INFO - Epoch(train) [467][15/63] lr: 4.4953e-03 eta: 18:35:45 time: 0.8261 data_time: 0.0374 memory: 16201 loss_prob: 0.6017 loss_thr: 0.4107 loss_db: 0.1019 loss: 1.1143 2022/08/30 11:35:50 - mmengine - INFO - Epoch(train) [467][20/63] lr: 4.4953e-03 eta: 18:35:21 time: 0.8087 data_time: 0.0237 memory: 16201 loss_prob: 0.6148 loss_thr: 0.3981 loss_db: 0.1085 loss: 1.1213 2022/08/30 11:35:54 - mmengine - INFO - Epoch(train) [467][25/63] lr: 4.4953e-03 eta: 18:35:21 time: 0.8001 data_time: 0.0344 memory: 16201 loss_prob: 0.6099 loss_thr: 0.3999 loss_db: 0.1068 loss: 1.1166 2022/08/30 11:35:59 - mmengine - INFO - Epoch(train) [467][30/63] lr: 4.4953e-03 eta: 18:34:56 time: 0.8183 data_time: 0.0388 memory: 16201 loss_prob: 0.5709 loss_thr: 0.3848 loss_db: 0.0957 loss: 1.0514 2022/08/30 11:36:03 - mmengine - INFO - Epoch(train) [467][35/63] lr: 4.4953e-03 eta: 18:34:56 time: 0.8167 data_time: 0.0394 memory: 16201 loss_prob: 0.6318 loss_thr: 0.3991 loss_db: 0.1065 loss: 1.1374 2022/08/30 11:36:07 - mmengine - INFO - Epoch(train) [467][40/63] lr: 4.4953e-03 eta: 18:34:32 time: 0.7943 data_time: 0.0382 memory: 16201 loss_prob: 0.5910 loss_thr: 0.3901 loss_db: 0.1005 loss: 1.0817 2022/08/30 11:36:11 - mmengine - INFO - Epoch(train) [467][45/63] lr: 4.4953e-03 eta: 18:34:32 time: 0.8618 data_time: 0.0340 memory: 16201 loss_prob: 0.5195 loss_thr: 0.3603 loss_db: 0.0896 loss: 0.9694 2022/08/30 11:36:16 - mmengine - INFO - Epoch(train) [467][50/63] lr: 4.4953e-03 eta: 18:34:09 time: 0.8994 data_time: 0.0432 memory: 16201 loss_prob: 0.5580 loss_thr: 0.3778 loss_db: 0.0964 loss: 1.0322 2022/08/30 11:36:20 - mmengine - INFO - Epoch(train) [467][55/63] lr: 4.4953e-03 eta: 18:34:09 time: 0.8608 data_time: 0.0446 memory: 16201 loss_prob: 0.6154 loss_thr: 0.4054 loss_db: 0.1068 loss: 1.1276 2022/08/30 11:36:24 - mmengine - INFO - Epoch(train) [467][60/63] lr: 4.4953e-03 eta: 18:33:44 time: 0.8319 data_time: 0.0338 memory: 16201 loss_prob: 0.6390 loss_thr: 0.4081 loss_db: 0.1084 loss: 1.1555 2022/08/30 11:36:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:36:32 - mmengine - INFO - Epoch(train) [468][5/63] lr: 4.4898e-03 eta: 18:33:44 time: 0.9189 data_time: 0.1635 memory: 16201 loss_prob: 0.6383 loss_thr: 0.3953 loss_db: 0.1059 loss: 1.1395 2022/08/30 11:36:36 - mmengine - INFO - Epoch(train) [468][10/63] lr: 4.4898e-03 eta: 18:33:12 time: 1.0039 data_time: 0.1980 memory: 16201 loss_prob: 0.5923 loss_thr: 0.3827 loss_db: 0.1002 loss: 1.0752 2022/08/30 11:36:40 - mmengine - INFO - Epoch(train) [468][15/63] lr: 4.4898e-03 eta: 18:33:12 time: 0.8894 data_time: 0.0567 memory: 16201 loss_prob: 0.5342 loss_thr: 0.3682 loss_db: 0.0920 loss: 0.9944 2022/08/30 11:36:45 - mmengine - INFO - Epoch(train) [468][20/63] lr: 4.4898e-03 eta: 18:32:48 time: 0.8673 data_time: 0.0308 memory: 16201 loss_prob: 0.5825 loss_thr: 0.3726 loss_db: 0.0969 loss: 1.0520 2022/08/30 11:36:49 - mmengine - INFO - Epoch(train) [468][25/63] lr: 4.4898e-03 eta: 18:32:48 time: 0.8440 data_time: 0.0402 memory: 16201 loss_prob: 0.6441 loss_thr: 0.3957 loss_db: 0.1056 loss: 1.1453 2022/08/30 11:36:53 - mmengine - INFO - Epoch(train) [468][30/63] lr: 4.4898e-03 eta: 18:32:24 time: 0.8169 data_time: 0.0365 memory: 16201 loss_prob: 0.6412 loss_thr: 0.3964 loss_db: 0.1102 loss: 1.1478 2022/08/30 11:36:57 - mmengine - INFO - Epoch(train) [468][35/63] lr: 4.4898e-03 eta: 18:32:24 time: 0.8514 data_time: 0.0244 memory: 16201 loss_prob: 0.6067 loss_thr: 0.3925 loss_db: 0.1048 loss: 1.1039 2022/08/30 11:37:02 - mmengine - INFO - Epoch(train) [468][40/63] lr: 4.4898e-03 eta: 18:32:01 time: 0.8808 data_time: 0.0489 memory: 16201 loss_prob: 0.5945 loss_thr: 0.3993 loss_db: 0.1019 loss: 1.0958 2022/08/30 11:37:06 - mmengine - INFO - Epoch(train) [468][45/63] lr: 4.4898e-03 eta: 18:32:01 time: 0.8439 data_time: 0.0596 memory: 16201 loss_prob: 0.6031 loss_thr: 0.4049 loss_db: 0.1035 loss: 1.1115 2022/08/30 11:37:10 - mmengine - INFO - Epoch(train) [468][50/63] lr: 4.4898e-03 eta: 18:31:37 time: 0.8288 data_time: 0.0415 memory: 16201 loss_prob: 0.5414 loss_thr: 0.3837 loss_db: 0.0945 loss: 1.0196 2022/08/30 11:37:14 - mmengine - INFO - Epoch(train) [468][55/63] lr: 4.4898e-03 eta: 18:31:37 time: 0.8398 data_time: 0.0515 memory: 16201 loss_prob: 0.5284 loss_thr: 0.3686 loss_db: 0.0914 loss: 0.9884 2022/08/30 11:37:19 - mmengine - INFO - Epoch(train) [468][60/63] lr: 4.4898e-03 eta: 18:31:13 time: 0.8830 data_time: 0.0513 memory: 16201 loss_prob: 0.5104 loss_thr: 0.3581 loss_db: 0.0875 loss: 0.9560 2022/08/30 11:37:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:37:27 - mmengine - INFO - Epoch(train) [469][5/63] lr: 4.4843e-03 eta: 18:31:13 time: 0.9654 data_time: 0.1909 memory: 16201 loss_prob: 0.4955 loss_thr: 0.3615 loss_db: 0.0867 loss: 0.9437 2022/08/30 11:37:31 - mmengine - INFO - Epoch(train) [469][10/63] lr: 4.4843e-03 eta: 18:30:41 time: 1.0432 data_time: 0.2191 memory: 16201 loss_prob: 0.5110 loss_thr: 0.3695 loss_db: 0.0881 loss: 0.9686 2022/08/30 11:37:36 - mmengine - INFO - Epoch(train) [469][15/63] lr: 4.4843e-03 eta: 18:30:41 time: 0.9085 data_time: 0.0553 memory: 16201 loss_prob: 0.4971 loss_thr: 0.3501 loss_db: 0.0871 loss: 0.9343 2022/08/30 11:37:40 - mmengine - INFO - Epoch(train) [469][20/63] lr: 4.4843e-03 eta: 18:30:18 time: 0.8665 data_time: 0.0322 memory: 16201 loss_prob: 0.5327 loss_thr: 0.3604 loss_db: 0.0925 loss: 0.9855 2022/08/30 11:37:44 - mmengine - INFO - Epoch(train) [469][25/63] lr: 4.4843e-03 eta: 18:30:18 time: 0.8232 data_time: 0.0500 memory: 16201 loss_prob: 0.5721 loss_thr: 0.3790 loss_db: 0.0987 loss: 1.0497 2022/08/30 11:37:48 - mmengine - INFO - Epoch(train) [469][30/63] lr: 4.4843e-03 eta: 18:29:53 time: 0.8087 data_time: 0.0416 memory: 16201 loss_prob: 0.5691 loss_thr: 0.3835 loss_db: 0.0982 loss: 1.0508 2022/08/30 11:37:52 - mmengine - INFO - Epoch(train) [469][35/63] lr: 4.4843e-03 eta: 18:29:53 time: 0.7987 data_time: 0.0264 memory: 16201 loss_prob: 0.5497 loss_thr: 0.3761 loss_db: 0.0939 loss: 1.0198 2022/08/30 11:37:56 - mmengine - INFO - Epoch(train) [469][40/63] lr: 4.4843e-03 eta: 18:29:29 time: 0.8073 data_time: 0.0422 memory: 16201 loss_prob: 0.5894 loss_thr: 0.3986 loss_db: 0.1011 loss: 1.0890 2022/08/30 11:38:00 - mmengine - INFO - Epoch(train) [469][45/63] lr: 4.4843e-03 eta: 18:29:29 time: 0.8474 data_time: 0.0506 memory: 16201 loss_prob: 0.5593 loss_thr: 0.3833 loss_db: 0.0972 loss: 1.0397 2022/08/30 11:38:05 - mmengine - INFO - Epoch(train) [469][50/63] lr: 4.4843e-03 eta: 18:29:06 time: 0.8600 data_time: 0.0479 memory: 16201 loss_prob: 0.5188 loss_thr: 0.3627 loss_db: 0.0883 loss: 0.9699 2022/08/30 11:38:09 - mmengine - INFO - Epoch(train) [469][55/63] lr: 4.4843e-03 eta: 18:29:06 time: 0.8282 data_time: 0.0438 memory: 16201 loss_prob: 0.5544 loss_thr: 0.3755 loss_db: 0.0945 loss: 1.0244 2022/08/30 11:38:13 - mmengine - INFO - Epoch(train) [469][60/63] lr: 4.4843e-03 eta: 18:28:41 time: 0.8184 data_time: 0.0407 memory: 16201 loss_prob: 0.6709 loss_thr: 0.4149 loss_db: 0.1149 loss: 1.2007 2022/08/30 11:38:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:38:21 - mmengine - INFO - Epoch(train) [470][5/63] lr: 4.4787e-03 eta: 18:28:41 time: 1.0179 data_time: 0.2510 memory: 16201 loss_prob: 0.6299 loss_thr: 0.3995 loss_db: 0.1071 loss: 1.1365 2022/08/30 11:38:26 - mmengine - INFO - Epoch(train) [470][10/63] lr: 4.4787e-03 eta: 18:28:10 time: 1.0444 data_time: 0.2644 memory: 16201 loss_prob: 0.6288 loss_thr: 0.3949 loss_db: 0.1074 loss: 1.1311 2022/08/30 11:38:30 - mmengine - INFO - Epoch(train) [470][15/63] lr: 4.4787e-03 eta: 18:28:10 time: 0.8579 data_time: 0.0410 memory: 16201 loss_prob: 0.6352 loss_thr: 0.3929 loss_db: 0.1076 loss: 1.1358 2022/08/30 11:38:34 - mmengine - INFO - Epoch(train) [470][20/63] lr: 4.4787e-03 eta: 18:27:46 time: 0.8410 data_time: 0.0192 memory: 16201 loss_prob: 0.6457 loss_thr: 0.3966 loss_db: 0.1067 loss: 1.1490 2022/08/30 11:38:38 - mmengine - INFO - Epoch(train) [470][25/63] lr: 4.4787e-03 eta: 18:27:46 time: 0.8234 data_time: 0.0554 memory: 16201 loss_prob: 0.5814 loss_thr: 0.3867 loss_db: 0.0985 loss: 1.0666 2022/08/30 11:38:42 - mmengine - INFO - Epoch(train) [470][30/63] lr: 4.4787e-03 eta: 18:27:22 time: 0.8261 data_time: 0.0519 memory: 16201 loss_prob: 0.5677 loss_thr: 0.3877 loss_db: 0.1000 loss: 1.0553 2022/08/30 11:38:47 - mmengine - INFO - Epoch(train) [470][35/63] lr: 4.4787e-03 eta: 18:27:22 time: 0.8384 data_time: 0.0306 memory: 16201 loss_prob: 0.5566 loss_thr: 0.3759 loss_db: 0.0971 loss: 1.0295 2022/08/30 11:38:51 - mmengine - INFO - Epoch(train) [470][40/63] lr: 4.4787e-03 eta: 18:26:58 time: 0.8571 data_time: 0.0548 memory: 16201 loss_prob: 0.4992 loss_thr: 0.3332 loss_db: 0.0869 loss: 0.9193 2022/08/30 11:38:55 - mmengine - INFO - Epoch(train) [470][45/63] lr: 4.4787e-03 eta: 18:26:58 time: 0.8371 data_time: 0.0541 memory: 16201 loss_prob: 0.5148 loss_thr: 0.3327 loss_db: 0.0891 loss: 0.9365 2022/08/30 11:38:59 - mmengine - INFO - Epoch(train) [470][50/63] lr: 4.4787e-03 eta: 18:26:34 time: 0.8285 data_time: 0.0399 memory: 16201 loss_prob: 0.5827 loss_thr: 0.3823 loss_db: 0.0983 loss: 1.0633 2022/08/30 11:39:03 - mmengine - INFO - Epoch(train) [470][55/63] lr: 4.4787e-03 eta: 18:26:34 time: 0.8309 data_time: 0.0462 memory: 16201 loss_prob: 0.5991 loss_thr: 0.4003 loss_db: 0.1024 loss: 1.1018 2022/08/30 11:39:08 - mmengine - INFO - Epoch(train) [470][60/63] lr: 4.4787e-03 eta: 18:26:10 time: 0.8342 data_time: 0.0447 memory: 16201 loss_prob: 0.6081 loss_thr: 0.4010 loss_db: 0.1045 loss: 1.1136 2022/08/30 11:39:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:39:16 - mmengine - INFO - Epoch(train) [471][5/63] lr: 4.4732e-03 eta: 18:26:10 time: 0.9531 data_time: 0.2230 memory: 16201 loss_prob: 0.5453 loss_thr: 0.3826 loss_db: 0.0930 loss: 1.0209 2022/08/30 11:39:20 - mmengine - INFO - Epoch(train) [471][10/63] lr: 4.4732e-03 eta: 18:25:38 time: 1.0320 data_time: 0.2476 memory: 16201 loss_prob: 0.5412 loss_thr: 0.3874 loss_db: 0.0919 loss: 1.0205 2022/08/30 11:39:24 - mmengine - INFO - Epoch(train) [471][15/63] lr: 4.4732e-03 eta: 18:25:38 time: 0.8576 data_time: 0.0570 memory: 16201 loss_prob: 0.5841 loss_thr: 0.4012 loss_db: 0.1011 loss: 1.0863 2022/08/30 11:39:28 - mmengine - INFO - Epoch(train) [471][20/63] lr: 4.4732e-03 eta: 18:25:14 time: 0.8204 data_time: 0.0361 memory: 16201 loss_prob: 0.5863 loss_thr: 0.4018 loss_db: 0.1025 loss: 1.0907 2022/08/30 11:39:32 - mmengine - INFO - Epoch(train) [471][25/63] lr: 4.4732e-03 eta: 18:25:14 time: 0.7980 data_time: 0.0357 memory: 16201 loss_prob: 0.5785 loss_thr: 0.3888 loss_db: 0.0992 loss: 1.0666 2022/08/30 11:39:36 - mmengine - INFO - Epoch(train) [471][30/63] lr: 4.4732e-03 eta: 18:24:50 time: 0.8356 data_time: 0.0299 memory: 16201 loss_prob: 0.5985 loss_thr: 0.3940 loss_db: 0.1020 loss: 1.0944 2022/08/30 11:39:40 - mmengine - INFO - Epoch(train) [471][35/63] lr: 4.4732e-03 eta: 18:24:50 time: 0.8354 data_time: 0.0273 memory: 16201 loss_prob: 0.6082 loss_thr: 0.3990 loss_db: 0.1046 loss: 1.1118 2022/08/30 11:39:45 - mmengine - INFO - Epoch(train) [471][40/63] lr: 4.4732e-03 eta: 18:24:26 time: 0.8147 data_time: 0.0557 memory: 16201 loss_prob: 0.6067 loss_thr: 0.3831 loss_db: 0.1022 loss: 1.0920 2022/08/30 11:39:49 - mmengine - INFO - Epoch(train) [471][45/63] lr: 4.4732e-03 eta: 18:24:26 time: 0.8456 data_time: 0.0589 memory: 16201 loss_prob: 0.6094 loss_thr: 0.3862 loss_db: 0.1043 loss: 1.0999 2022/08/30 11:39:53 - mmengine - INFO - Epoch(train) [471][50/63] lr: 4.4732e-03 eta: 18:24:02 time: 0.8245 data_time: 0.0377 memory: 16201 loss_prob: 0.6186 loss_thr: 0.4153 loss_db: 0.1096 loss: 1.1434 2022/08/30 11:39:57 - mmengine - INFO - Epoch(train) [471][55/63] lr: 4.4732e-03 eta: 18:24:02 time: 0.8322 data_time: 0.0585 memory: 16201 loss_prob: 0.6265 loss_thr: 0.4128 loss_db: 0.1068 loss: 1.1461 2022/08/30 11:40:02 - mmengine - INFO - Epoch(train) [471][60/63] lr: 4.4732e-03 eta: 18:23:39 time: 0.8797 data_time: 0.0591 memory: 16201 loss_prob: 0.5924 loss_thr: 0.3947 loss_db: 0.1017 loss: 1.0889 2022/08/30 11:40:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:40:09 - mmengine - INFO - Epoch(train) [472][5/63] lr: 4.4677e-03 eta: 18:23:39 time: 0.9561 data_time: 0.1972 memory: 16201 loss_prob: 0.5557 loss_thr: 0.3820 loss_db: 0.0960 loss: 1.0337 2022/08/30 11:40:14 - mmengine - INFO - Epoch(train) [472][10/63] lr: 4.4677e-03 eta: 18:23:07 time: 0.9823 data_time: 0.2086 memory: 16201 loss_prob: 0.5710 loss_thr: 0.3844 loss_db: 0.0996 loss: 1.0550 2022/08/30 11:40:19 - mmengine - INFO - Epoch(train) [472][15/63] lr: 4.4677e-03 eta: 18:23:07 time: 0.9175 data_time: 0.0483 memory: 16201 loss_prob: 0.6896 loss_thr: 0.4119 loss_db: 0.1124 loss: 1.2139 2022/08/30 11:40:23 - mmengine - INFO - Epoch(train) [472][20/63] lr: 4.4677e-03 eta: 18:22:45 time: 0.9457 data_time: 0.0475 memory: 16201 loss_prob: 0.6689 loss_thr: 0.3940 loss_db: 0.1101 loss: 1.1730 2022/08/30 11:40:27 - mmengine - INFO - Epoch(train) [472][25/63] lr: 4.4677e-03 eta: 18:22:45 time: 0.8633 data_time: 0.0677 memory: 16201 loss_prob: 0.6169 loss_thr: 0.3917 loss_db: 0.1083 loss: 1.1169 2022/08/30 11:40:32 - mmengine - INFO - Epoch(train) [472][30/63] lr: 4.4677e-03 eta: 18:22:21 time: 0.8778 data_time: 0.0570 memory: 16201 loss_prob: 0.6314 loss_thr: 0.4038 loss_db: 0.1104 loss: 1.1455 2022/08/30 11:40:36 - mmengine - INFO - Epoch(train) [472][35/63] lr: 4.4677e-03 eta: 18:22:21 time: 0.8784 data_time: 0.0415 memory: 16201 loss_prob: 0.5981 loss_thr: 0.3883 loss_db: 0.1063 loss: 1.0927 2022/08/30 11:40:40 - mmengine - INFO - Epoch(train) [472][40/63] lr: 4.4677e-03 eta: 18:21:58 time: 0.8611 data_time: 0.0733 memory: 16201 loss_prob: 0.5949 loss_thr: 0.3834 loss_db: 0.1046 loss: 1.0829 2022/08/30 11:40:44 - mmengine - INFO - Epoch(train) [472][45/63] lr: 4.4677e-03 eta: 18:21:58 time: 0.8315 data_time: 0.0669 memory: 16201 loss_prob: 0.6435 loss_thr: 0.4113 loss_db: 0.1101 loss: 1.1649 2022/08/30 11:40:49 - mmengine - INFO - Epoch(train) [472][50/63] lr: 4.4677e-03 eta: 18:21:34 time: 0.8172 data_time: 0.0353 memory: 16201 loss_prob: 0.7118 loss_thr: 0.4068 loss_db: 0.1166 loss: 1.2353 2022/08/30 11:40:53 - mmengine - INFO - Epoch(train) [472][55/63] lr: 4.4677e-03 eta: 18:21:34 time: 0.8626 data_time: 0.0718 memory: 16201 loss_prob: 0.7290 loss_thr: 0.4039 loss_db: 0.1160 loss: 1.2489 2022/08/30 11:40:57 - mmengine - INFO - Epoch(train) [472][60/63] lr: 4.4677e-03 eta: 18:21:11 time: 0.8510 data_time: 0.0710 memory: 16201 loss_prob: 0.6444 loss_thr: 0.4090 loss_db: 0.1066 loss: 1.1599 2022/08/30 11:41:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:41:06 - mmengine - INFO - Epoch(train) [473][5/63] lr: 4.4622e-03 eta: 18:21:11 time: 1.0108 data_time: 0.2109 memory: 16201 loss_prob: 0.6738 loss_thr: 0.4150 loss_db: 0.1168 loss: 1.2057 2022/08/30 11:41:10 - mmengine - INFO - Epoch(train) [473][10/63] lr: 4.4622e-03 eta: 18:20:39 time: 1.0359 data_time: 0.2375 memory: 16201 loss_prob: 0.6473 loss_thr: 0.4110 loss_db: 0.1101 loss: 1.1684 2022/08/30 11:41:14 - mmengine - INFO - Epoch(train) [473][15/63] lr: 4.4622e-03 eta: 18:20:39 time: 0.8494 data_time: 0.0681 memory: 16201 loss_prob: 0.5988 loss_thr: 0.4023 loss_db: 0.0980 loss: 1.0991 2022/08/30 11:41:19 - mmengine - INFO - Epoch(train) [473][20/63] lr: 4.4622e-03 eta: 18:20:16 time: 0.8779 data_time: 0.0467 memory: 16201 loss_prob: 0.5885 loss_thr: 0.3896 loss_db: 0.0999 loss: 1.0780 2022/08/30 11:41:23 - mmengine - INFO - Epoch(train) [473][25/63] lr: 4.4622e-03 eta: 18:20:16 time: 0.8800 data_time: 0.0539 memory: 16201 loss_prob: 0.5570 loss_thr: 0.3764 loss_db: 0.0983 loss: 1.0317 2022/08/30 11:41:27 - mmengine - INFO - Epoch(train) [473][30/63] lr: 4.4622e-03 eta: 18:19:52 time: 0.8156 data_time: 0.0518 memory: 16201 loss_prob: 0.5642 loss_thr: 0.3829 loss_db: 0.0979 loss: 1.0450 2022/08/30 11:41:31 - mmengine - INFO - Epoch(train) [473][35/63] lr: 4.4622e-03 eta: 18:19:52 time: 0.8264 data_time: 0.0467 memory: 16201 loss_prob: 0.5861 loss_thr: 0.3947 loss_db: 0.0995 loss: 1.0803 2022/08/30 11:41:35 - mmengine - INFO - Epoch(train) [473][40/63] lr: 4.4622e-03 eta: 18:19:28 time: 0.8406 data_time: 0.0626 memory: 16201 loss_prob: 0.5712 loss_thr: 0.3822 loss_db: 0.1011 loss: 1.0545 2022/08/30 11:41:40 - mmengine - INFO - Epoch(train) [473][45/63] lr: 4.4622e-03 eta: 18:19:28 time: 0.8376 data_time: 0.0596 memory: 16201 loss_prob: 0.5795 loss_thr: 0.3814 loss_db: 0.1042 loss: 1.0651 2022/08/30 11:41:44 - mmengine - INFO - Epoch(train) [473][50/63] lr: 4.4622e-03 eta: 18:19:04 time: 0.8259 data_time: 0.0438 memory: 16201 loss_prob: 0.5901 loss_thr: 0.3888 loss_db: 0.1021 loss: 1.0810 2022/08/30 11:41:49 - mmengine - INFO - Epoch(train) [473][55/63] lr: 4.4622e-03 eta: 18:19:04 time: 0.9255 data_time: 0.0548 memory: 16201 loss_prob: 0.5667 loss_thr: 0.3943 loss_db: 0.0982 loss: 1.0592 2022/08/30 11:41:53 - mmengine - INFO - Epoch(train) [473][60/63] lr: 4.4622e-03 eta: 18:18:43 time: 0.9611 data_time: 0.0678 memory: 16201 loss_prob: 0.5493 loss_thr: 0.3976 loss_db: 0.0966 loss: 1.0434 2022/08/30 11:41:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:42:01 - mmengine - INFO - Epoch(train) [474][5/63] lr: 4.4566e-03 eta: 18:18:43 time: 0.9214 data_time: 0.1837 memory: 16201 loss_prob: 0.5462 loss_thr: 0.3836 loss_db: 0.0955 loss: 1.0253 2022/08/30 11:42:05 - mmengine - INFO - Epoch(train) [474][10/63] lr: 4.4566e-03 eta: 18:18:10 time: 0.9947 data_time: 0.2108 memory: 16201 loss_prob: 0.5517 loss_thr: 0.3846 loss_db: 0.0956 loss: 1.0319 2022/08/30 11:42:10 - mmengine - INFO - Epoch(train) [474][15/63] lr: 4.4566e-03 eta: 18:18:10 time: 0.9168 data_time: 0.0575 memory: 16201 loss_prob: 0.5442 loss_thr: 0.3690 loss_db: 0.0910 loss: 1.0042 2022/08/30 11:42:14 - mmengine - INFO - Epoch(train) [474][20/63] lr: 4.4566e-03 eta: 18:17:48 time: 0.8872 data_time: 0.0370 memory: 16201 loss_prob: 0.5324 loss_thr: 0.3658 loss_db: 0.0924 loss: 0.9906 2022/08/30 11:42:18 - mmengine - INFO - Epoch(train) [474][25/63] lr: 4.4566e-03 eta: 18:17:48 time: 0.8268 data_time: 0.0671 memory: 16201 loss_prob: 0.5540 loss_thr: 0.3743 loss_db: 0.0994 loss: 1.0277 2022/08/30 11:42:22 - mmengine - INFO - Epoch(train) [474][30/63] lr: 4.4566e-03 eta: 18:17:24 time: 0.8402 data_time: 0.0616 memory: 16201 loss_prob: 0.6193 loss_thr: 0.3972 loss_db: 0.1076 loss: 1.1241 2022/08/30 11:42:27 - mmengine - INFO - Epoch(train) [474][35/63] lr: 4.4566e-03 eta: 18:17:24 time: 0.8320 data_time: 0.0331 memory: 16201 loss_prob: 0.6087 loss_thr: 0.3948 loss_db: 0.1036 loss: 1.1070 2022/08/30 11:42:31 - mmengine - INFO - Epoch(train) [474][40/63] lr: 4.4566e-03 eta: 18:17:00 time: 0.8359 data_time: 0.0497 memory: 16201 loss_prob: 0.5838 loss_thr: 0.3873 loss_db: 0.1009 loss: 1.0719 2022/08/30 11:42:35 - mmengine - INFO - Epoch(train) [474][45/63] lr: 4.4566e-03 eta: 18:17:00 time: 0.8468 data_time: 0.0581 memory: 16201 loss_prob: 0.5723 loss_thr: 0.3892 loss_db: 0.0999 loss: 1.0613 2022/08/30 11:42:39 - mmengine - INFO - Epoch(train) [474][50/63] lr: 4.4566e-03 eta: 18:16:37 time: 0.8213 data_time: 0.0431 memory: 16201 loss_prob: 0.5982 loss_thr: 0.4094 loss_db: 0.1015 loss: 1.1091 2022/08/30 11:42:43 - mmengine - INFO - Epoch(train) [474][55/63] lr: 4.4566e-03 eta: 18:16:37 time: 0.8235 data_time: 0.0670 memory: 16201 loss_prob: 0.6313 loss_thr: 0.4274 loss_db: 0.1094 loss: 1.1681 2022/08/30 11:42:47 - mmengine - INFO - Epoch(train) [474][60/63] lr: 4.4566e-03 eta: 18:16:13 time: 0.8371 data_time: 0.0693 memory: 16201 loss_prob: 0.6256 loss_thr: 0.4071 loss_db: 0.1067 loss: 1.1393 2022/08/30 11:42:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:42:55 - mmengine - INFO - Epoch(train) [475][5/63] lr: 4.4511e-03 eta: 18:16:13 time: 0.9522 data_time: 0.1961 memory: 16201 loss_prob: 0.6604 loss_thr: 0.4254 loss_db: 0.1085 loss: 1.1943 2022/08/30 11:43:00 - mmengine - INFO - Epoch(train) [475][10/63] lr: 4.4511e-03 eta: 18:15:41 time: 0.9885 data_time: 0.2119 memory: 16201 loss_prob: 0.5745 loss_thr: 0.3959 loss_db: 0.1008 loss: 1.0712 2022/08/30 11:43:04 - mmengine - INFO - Epoch(train) [475][15/63] lr: 4.4511e-03 eta: 18:15:41 time: 0.8809 data_time: 0.0546 memory: 16201 loss_prob: 0.5173 loss_thr: 0.3715 loss_db: 0.0930 loss: 0.9818 2022/08/30 11:43:08 - mmengine - INFO - Epoch(train) [475][20/63] lr: 4.4511e-03 eta: 18:15:18 time: 0.8634 data_time: 0.0358 memory: 16201 loss_prob: 0.5134 loss_thr: 0.3655 loss_db: 0.0907 loss: 0.9696 2022/08/30 11:43:13 - mmengine - INFO - Epoch(train) [475][25/63] lr: 4.4511e-03 eta: 18:15:18 time: 0.8464 data_time: 0.0668 memory: 16201 loss_prob: 0.4908 loss_thr: 0.3550 loss_db: 0.0845 loss: 0.9303 2022/08/30 11:43:17 - mmengine - INFO - Epoch(train) [475][30/63] lr: 4.4511e-03 eta: 18:14:54 time: 0.8393 data_time: 0.0651 memory: 16201 loss_prob: 0.5471 loss_thr: 0.3856 loss_db: 0.0941 loss: 1.0269 2022/08/30 11:43:21 - mmengine - INFO - Epoch(train) [475][35/63] lr: 4.4511e-03 eta: 18:14:54 time: 0.8210 data_time: 0.0430 memory: 16201 loss_prob: 0.5891 loss_thr: 0.3929 loss_db: 0.1029 loss: 1.0849 2022/08/30 11:43:25 - mmengine - INFO - Epoch(train) [475][40/63] lr: 4.4511e-03 eta: 18:14:31 time: 0.8352 data_time: 0.0707 memory: 16201 loss_prob: 0.5744 loss_thr: 0.3810 loss_db: 0.0997 loss: 1.0551 2022/08/30 11:43:29 - mmengine - INFO - Epoch(train) [475][45/63] lr: 4.4511e-03 eta: 18:14:31 time: 0.8381 data_time: 0.0731 memory: 16201 loss_prob: 0.5980 loss_thr: 0.3985 loss_db: 0.1035 loss: 1.1000 2022/08/30 11:43:33 - mmengine - INFO - Epoch(train) [475][50/63] lr: 4.4511e-03 eta: 18:14:07 time: 0.8126 data_time: 0.0468 memory: 16201 loss_prob: 0.5884 loss_thr: 0.3979 loss_db: 0.1049 loss: 1.0911 2022/08/30 11:43:38 - mmengine - INFO - Epoch(train) [475][55/63] lr: 4.4511e-03 eta: 18:14:07 time: 0.8294 data_time: 0.0683 memory: 16201 loss_prob: 0.5488 loss_thr: 0.3932 loss_db: 0.0971 loss: 1.0391 2022/08/30 11:43:42 - mmengine - INFO - Epoch(train) [475][60/63] lr: 4.4511e-03 eta: 18:13:44 time: 0.8901 data_time: 0.0702 memory: 16201 loss_prob: 0.5406 loss_thr: 0.3783 loss_db: 0.0934 loss: 1.0123 2022/08/30 11:43:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:43:51 - mmengine - INFO - Epoch(train) [476][5/63] lr: 4.4456e-03 eta: 18:13:44 time: 1.0376 data_time: 0.2897 memory: 16201 loss_prob: 0.4862 loss_thr: 0.3524 loss_db: 0.0851 loss: 0.9237 2022/08/30 11:43:55 - mmengine - INFO - Epoch(train) [476][10/63] lr: 4.4456e-03 eta: 18:13:13 time: 1.0908 data_time: 0.3118 memory: 16201 loss_prob: 0.4881 loss_thr: 0.3484 loss_db: 0.0853 loss: 0.9218 2022/08/30 11:44:00 - mmengine - INFO - Epoch(train) [476][15/63] lr: 4.4456e-03 eta: 18:13:13 time: 0.9086 data_time: 0.0494 memory: 16201 loss_prob: 0.5301 loss_thr: 0.3636 loss_db: 0.0922 loss: 0.9859 2022/08/30 11:44:04 - mmengine - INFO - Epoch(train) [476][20/63] lr: 4.4456e-03 eta: 18:12:51 time: 0.8989 data_time: 0.0399 memory: 16201 loss_prob: 0.4984 loss_thr: 0.3619 loss_db: 0.0885 loss: 0.9488 2022/08/30 11:44:08 - mmengine - INFO - Epoch(train) [476][25/63] lr: 4.4456e-03 eta: 18:12:51 time: 0.8469 data_time: 0.0753 memory: 16201 loss_prob: 0.5063 loss_thr: 0.3747 loss_db: 0.0892 loss: 0.9702 2022/08/30 11:44:13 - mmengine - INFO - Epoch(train) [476][30/63] lr: 4.4456e-03 eta: 18:12:28 time: 0.8770 data_time: 0.0707 memory: 16201 loss_prob: 0.5446 loss_thr: 0.3775 loss_db: 0.0952 loss: 1.0174 2022/08/30 11:44:17 - mmengine - INFO - Epoch(train) [476][35/63] lr: 4.4456e-03 eta: 18:12:28 time: 0.8538 data_time: 0.0495 memory: 16201 loss_prob: 0.5586 loss_thr: 0.3790 loss_db: 0.0972 loss: 1.0348 2022/08/30 11:44:21 - mmengine - INFO - Epoch(train) [476][40/63] lr: 4.4456e-03 eta: 18:12:05 time: 0.8410 data_time: 0.0697 memory: 16201 loss_prob: 0.6011 loss_thr: 0.3941 loss_db: 0.1034 loss: 1.0985 2022/08/30 11:44:25 - mmengine - INFO - Epoch(train) [476][45/63] lr: 4.4456e-03 eta: 18:12:05 time: 0.8553 data_time: 0.0647 memory: 16201 loss_prob: 0.6510 loss_thr: 0.4228 loss_db: 0.1113 loss: 1.1851 2022/08/30 11:44:30 - mmengine - INFO - Epoch(train) [476][50/63] lr: 4.4456e-03 eta: 18:11:41 time: 0.8432 data_time: 0.0566 memory: 16201 loss_prob: 0.6114 loss_thr: 0.4102 loss_db: 0.1043 loss: 1.1258 2022/08/30 11:44:34 - mmengine - INFO - Epoch(train) [476][55/63] lr: 4.4456e-03 eta: 18:11:41 time: 0.8364 data_time: 0.0598 memory: 16201 loss_prob: 0.5657 loss_thr: 0.3780 loss_db: 0.0990 loss: 1.0426 2022/08/30 11:44:38 - mmengine - INFO - Epoch(train) [476][60/63] lr: 4.4456e-03 eta: 18:11:18 time: 0.8543 data_time: 0.0497 memory: 16201 loss_prob: 0.5367 loss_thr: 0.3690 loss_db: 0.0949 loss: 1.0006 2022/08/30 11:44:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:44:46 - mmengine - INFO - Epoch(train) [477][5/63] lr: 4.4401e-03 eta: 18:11:18 time: 1.0005 data_time: 0.1973 memory: 16201 loss_prob: 0.5433 loss_thr: 0.3752 loss_db: 0.0940 loss: 1.0125 2022/08/30 11:44:51 - mmengine - INFO - Epoch(train) [477][10/63] lr: 4.4401e-03 eta: 18:10:46 time: 0.9949 data_time: 0.2169 memory: 16201 loss_prob: 0.5778 loss_thr: 0.3823 loss_db: 0.1004 loss: 1.0604 2022/08/30 11:44:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:44:55 - mmengine - INFO - Epoch(train) [477][15/63] lr: 4.4401e-03 eta: 18:10:46 time: 0.8337 data_time: 0.0481 memory: 16201 loss_prob: 0.5759 loss_thr: 0.3864 loss_db: 0.1008 loss: 1.0631 2022/08/30 11:45:00 - mmengine - INFO - Epoch(train) [477][20/63] lr: 4.4401e-03 eta: 18:10:23 time: 0.8917 data_time: 0.0406 memory: 16201 loss_prob: 0.5017 loss_thr: 0.3581 loss_db: 0.0875 loss: 0.9473 2022/08/30 11:45:04 - mmengine - INFO - Epoch(train) [477][25/63] lr: 4.4401e-03 eta: 18:10:23 time: 0.8997 data_time: 0.0704 memory: 16201 loss_prob: 0.5372 loss_thr: 0.3769 loss_db: 0.0940 loss: 1.0082 2022/08/30 11:45:08 - mmengine - INFO - Epoch(train) [477][30/63] lr: 4.4401e-03 eta: 18:10:00 time: 0.8297 data_time: 0.0537 memory: 16201 loss_prob: 0.5763 loss_thr: 0.3897 loss_db: 0.0986 loss: 1.0646 2022/08/30 11:45:12 - mmengine - INFO - Epoch(train) [477][35/63] lr: 4.4401e-03 eta: 18:10:00 time: 0.8462 data_time: 0.0411 memory: 16201 loss_prob: 0.5435 loss_thr: 0.3724 loss_db: 0.0922 loss: 1.0081 2022/08/30 11:45:17 - mmengine - INFO - Epoch(train) [477][40/63] lr: 4.4401e-03 eta: 18:09:37 time: 0.9038 data_time: 0.0841 memory: 16201 loss_prob: 0.5332 loss_thr: 0.3652 loss_db: 0.0942 loss: 0.9926 2022/08/30 11:45:21 - mmengine - INFO - Epoch(train) [477][45/63] lr: 4.4401e-03 eta: 18:09:37 time: 0.8902 data_time: 0.0797 memory: 16201 loss_prob: 0.5139 loss_thr: 0.3495 loss_db: 0.0912 loss: 0.9545 2022/08/30 11:45:25 - mmengine - INFO - Epoch(train) [477][50/63] lr: 4.4401e-03 eta: 18:09:14 time: 0.8488 data_time: 0.0636 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3422 loss_db: 0.0840 loss: 0.9157 2022/08/30 11:45:30 - mmengine - INFO - Epoch(train) [477][55/63] lr: 4.4401e-03 eta: 18:09:14 time: 0.9075 data_time: 0.0974 memory: 16201 loss_prob: 0.5516 loss_thr: 0.3762 loss_db: 0.0921 loss: 1.0199 2022/08/30 11:45:34 - mmengine - INFO - Epoch(train) [477][60/63] lr: 4.4401e-03 eta: 18:08:52 time: 0.8931 data_time: 0.0914 memory: 16201 loss_prob: 0.5730 loss_thr: 0.3814 loss_db: 0.0981 loss: 1.0525 2022/08/30 11:45:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:45:42 - mmengine - INFO - Epoch(train) [478][5/63] lr: 4.4345e-03 eta: 18:08:52 time: 0.9200 data_time: 0.1870 memory: 16201 loss_prob: 0.5206 loss_thr: 0.3626 loss_db: 0.0898 loss: 0.9731 2022/08/30 11:45:46 - mmengine - INFO - Epoch(train) [478][10/63] lr: 4.4345e-03 eta: 18:08:20 time: 0.9777 data_time: 0.2206 memory: 16201 loss_prob: 0.4977 loss_thr: 0.3561 loss_db: 0.0859 loss: 0.9397 2022/08/30 11:45:50 - mmengine - INFO - Epoch(train) [478][15/63] lr: 4.4345e-03 eta: 18:08:20 time: 0.8470 data_time: 0.0703 memory: 16201 loss_prob: 0.5683 loss_thr: 0.3853 loss_db: 0.0951 loss: 1.0487 2022/08/30 11:45:55 - mmengine - INFO - Epoch(train) [478][20/63] lr: 4.4345e-03 eta: 18:07:56 time: 0.8260 data_time: 0.0466 memory: 16201 loss_prob: 0.5797 loss_thr: 0.3898 loss_db: 0.0992 loss: 1.0687 2022/08/30 11:45:59 - mmengine - INFO - Epoch(train) [478][25/63] lr: 4.4345e-03 eta: 18:07:56 time: 0.8534 data_time: 0.0795 memory: 16201 loss_prob: 0.5124 loss_thr: 0.3658 loss_db: 0.0890 loss: 0.9673 2022/08/30 11:46:03 - mmengine - INFO - Epoch(train) [478][30/63] lr: 4.4345e-03 eta: 18:07:33 time: 0.8738 data_time: 0.0853 memory: 16201 loss_prob: 0.5667 loss_thr: 0.3936 loss_db: 0.0959 loss: 1.0562 2022/08/30 11:46:08 - mmengine - INFO - Epoch(train) [478][35/63] lr: 4.4345e-03 eta: 18:07:33 time: 0.8533 data_time: 0.0542 memory: 16201 loss_prob: 0.6256 loss_thr: 0.4157 loss_db: 0.1062 loss: 1.1475 2022/08/30 11:46:12 - mmengine - INFO - Epoch(train) [478][40/63] lr: 4.4345e-03 eta: 18:07:10 time: 0.8535 data_time: 0.0698 memory: 16201 loss_prob: 0.6144 loss_thr: 0.4050 loss_db: 0.1049 loss: 1.1242 2022/08/30 11:46:16 - mmengine - INFO - Epoch(train) [478][45/63] lr: 4.4345e-03 eta: 18:07:10 time: 0.8266 data_time: 0.0736 memory: 16201 loss_prob: 0.5902 loss_thr: 0.3845 loss_db: 0.1011 loss: 1.0758 2022/08/30 11:46:21 - mmengine - INFO - Epoch(train) [478][50/63] lr: 4.4345e-03 eta: 18:06:48 time: 0.9133 data_time: 0.0484 memory: 16201 loss_prob: 0.5819 loss_thr: 0.3725 loss_db: 0.0998 loss: 1.0542 2022/08/30 11:46:25 - mmengine - INFO - Epoch(train) [478][55/63] lr: 4.4345e-03 eta: 18:06:48 time: 0.9366 data_time: 0.0604 memory: 16201 loss_prob: 0.5577 loss_thr: 0.3777 loss_db: 0.0965 loss: 1.0319 2022/08/30 11:46:29 - mmengine - INFO - Epoch(train) [478][60/63] lr: 4.4345e-03 eta: 18:06:25 time: 0.8482 data_time: 0.0688 memory: 16201 loss_prob: 0.5218 loss_thr: 0.3631 loss_db: 0.0899 loss: 0.9749 2022/08/30 11:46:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:46:38 - mmengine - INFO - Epoch(train) [479][5/63] lr: 4.4290e-03 eta: 18:06:25 time: 1.0332 data_time: 0.2214 memory: 16201 loss_prob: 0.5424 loss_thr: 0.3720 loss_db: 0.0943 loss: 1.0087 2022/08/30 11:46:43 - mmengine - INFO - Epoch(train) [479][10/63] lr: 4.4290e-03 eta: 18:05:54 time: 1.0389 data_time: 0.2597 memory: 16201 loss_prob: 0.5524 loss_thr: 0.3761 loss_db: 0.0945 loss: 1.0230 2022/08/30 11:46:47 - mmengine - INFO - Epoch(train) [479][15/63] lr: 4.4290e-03 eta: 18:05:54 time: 0.8537 data_time: 0.0843 memory: 16201 loss_prob: 0.5577 loss_thr: 0.3873 loss_db: 0.0975 loss: 1.0425 2022/08/30 11:46:51 - mmengine - INFO - Epoch(train) [479][20/63] lr: 4.4290e-03 eta: 18:05:30 time: 0.8080 data_time: 0.0393 memory: 16201 loss_prob: 0.5532 loss_thr: 0.3900 loss_db: 0.0991 loss: 1.0423 2022/08/30 11:46:55 - mmengine - INFO - Epoch(train) [479][25/63] lr: 4.4290e-03 eta: 18:05:30 time: 0.8617 data_time: 0.0936 memory: 16201 loss_prob: 0.5665 loss_thr: 0.3897 loss_db: 0.0967 loss: 1.0529 2022/08/30 11:47:00 - mmengine - INFO - Epoch(train) [479][30/63] lr: 4.4290e-03 eta: 18:05:08 time: 0.8985 data_time: 0.1255 memory: 16201 loss_prob: 0.5591 loss_thr: 0.3870 loss_db: 0.0960 loss: 1.0421 2022/08/30 11:47:04 - mmengine - INFO - Epoch(train) [479][35/63] lr: 4.4290e-03 eta: 18:05:08 time: 0.8497 data_time: 0.0845 memory: 16201 loss_prob: 0.5337 loss_thr: 0.3716 loss_db: 0.0954 loss: 1.0007 2022/08/30 11:47:08 - mmengine - INFO - Epoch(train) [479][40/63] lr: 4.4290e-03 eta: 18:04:44 time: 0.8506 data_time: 0.0840 memory: 16201 loss_prob: 0.5830 loss_thr: 0.3737 loss_db: 0.1004 loss: 1.0571 2022/08/30 11:47:13 - mmengine - INFO - Epoch(train) [479][45/63] lr: 4.4290e-03 eta: 18:04:44 time: 0.9113 data_time: 0.1153 memory: 16201 loss_prob: 0.6144 loss_thr: 0.3913 loss_db: 0.1024 loss: 1.1081 2022/08/30 11:47:17 - mmengine - INFO - Epoch(train) [479][50/63] lr: 4.4290e-03 eta: 18:04:22 time: 0.8672 data_time: 0.0799 memory: 16201 loss_prob: 0.6151 loss_thr: 0.4149 loss_db: 0.1058 loss: 1.1358 2022/08/30 11:47:21 - mmengine - INFO - Epoch(train) [479][55/63] lr: 4.4290e-03 eta: 18:04:22 time: 0.8247 data_time: 0.0580 memory: 16201 loss_prob: 0.5790 loss_thr: 0.4021 loss_db: 0.1006 loss: 1.0817 2022/08/30 11:47:26 - mmengine - INFO - Epoch(train) [479][60/63] lr: 4.4290e-03 eta: 18:03:59 time: 0.9033 data_time: 0.1083 memory: 16201 loss_prob: 0.5559 loss_thr: 0.3942 loss_db: 0.0961 loss: 1.0462 2022/08/30 11:47:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:47:33 - mmengine - INFO - Epoch(train) [480][5/63] lr: 4.4235e-03 eta: 18:03:59 time: 0.9149 data_time: 0.1863 memory: 16201 loss_prob: 0.5136 loss_thr: 0.3637 loss_db: 0.0890 loss: 0.9663 2022/08/30 11:47:38 - mmengine - INFO - Epoch(train) [480][10/63] lr: 4.4235e-03 eta: 18:03:28 time: 0.9992 data_time: 0.2170 memory: 16201 loss_prob: 0.4829 loss_thr: 0.3503 loss_db: 0.0826 loss: 0.9158 2022/08/30 11:47:42 - mmengine - INFO - Epoch(train) [480][15/63] lr: 4.4235e-03 eta: 18:03:28 time: 0.8578 data_time: 0.0658 memory: 16201 loss_prob: 0.5171 loss_thr: 0.3718 loss_db: 0.0915 loss: 0.9804 2022/08/30 11:47:46 - mmengine - INFO - Epoch(train) [480][20/63] lr: 4.4235e-03 eta: 18:03:04 time: 0.8303 data_time: 0.0432 memory: 16201 loss_prob: 0.5852 loss_thr: 0.3860 loss_db: 0.1012 loss: 1.0724 2022/08/30 11:47:51 - mmengine - INFO - Epoch(train) [480][25/63] lr: 4.4235e-03 eta: 18:03:04 time: 0.8654 data_time: 0.0840 memory: 16201 loss_prob: 0.6201 loss_thr: 0.3945 loss_db: 0.1034 loss: 1.1181 2022/08/30 11:47:55 - mmengine - INFO - Epoch(train) [480][30/63] lr: 4.4235e-03 eta: 18:02:42 time: 0.8729 data_time: 0.0934 memory: 16201 loss_prob: 0.6089 loss_thr: 0.3727 loss_db: 0.1009 loss: 1.0824 2022/08/30 11:47:59 - mmengine - INFO - Epoch(train) [480][35/63] lr: 4.4235e-03 eta: 18:02:42 time: 0.8292 data_time: 0.0583 memory: 16201 loss_prob: 0.5478 loss_thr: 0.3461 loss_db: 0.0923 loss: 0.9862 2022/08/30 11:48:03 - mmengine - INFO - Epoch(train) [480][40/63] lr: 4.4235e-03 eta: 18:02:19 time: 0.8472 data_time: 0.0682 memory: 16201 loss_prob: 0.5561 loss_thr: 0.3687 loss_db: 0.0944 loss: 1.0192 2022/08/30 11:48:07 - mmengine - INFO - Epoch(train) [480][45/63] lr: 4.4235e-03 eta: 18:02:19 time: 0.8436 data_time: 0.0699 memory: 16201 loss_prob: 0.5777 loss_thr: 0.3707 loss_db: 0.0994 loss: 1.0478 2022/08/30 11:48:12 - mmengine - INFO - Epoch(train) [480][50/63] lr: 4.4235e-03 eta: 18:01:56 time: 0.8808 data_time: 0.0500 memory: 16201 loss_prob: 0.5484 loss_thr: 0.3575 loss_db: 0.0953 loss: 1.0012 2022/08/30 11:48:17 - mmengine - INFO - Epoch(train) [480][55/63] lr: 4.4235e-03 eta: 18:01:56 time: 0.9077 data_time: 0.0667 memory: 16201 loss_prob: 0.5673 loss_thr: 0.3693 loss_db: 0.0965 loss: 1.0330 2022/08/30 11:48:21 - mmengine - INFO - Epoch(train) [480][60/63] lr: 4.4235e-03 eta: 18:01:34 time: 0.9208 data_time: 0.0723 memory: 16201 loss_prob: 0.5661 loss_thr: 0.3762 loss_db: 0.0977 loss: 1.0400 2022/08/30 11:48:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:48:24 - mmengine - INFO - Saving checkpoint at 480 epochs 2022/08/30 11:48:33 - mmengine - INFO - Epoch(val) [480][5/32] eta: 18:01:34 time: 0.6709 data_time: 0.1661 memory: 16201 2022/08/30 11:48:36 - mmengine - INFO - Epoch(val) [480][10/32] eta: 0:00:16 time: 0.7573 data_time: 0.1974 memory: 15734 2022/08/30 11:48:39 - mmengine - INFO - Epoch(val) [480][15/32] eta: 0:00:16 time: 0.6312 data_time: 0.0647 memory: 15734 2022/08/30 11:48:43 - mmengine - INFO - Epoch(val) [480][20/32] eta: 0:00:08 time: 0.7242 data_time: 0.0649 memory: 15734 2022/08/30 11:48:47 - mmengine - INFO - Epoch(val) [480][25/32] eta: 0:00:08 time: 0.7272 data_time: 0.0612 memory: 15734 2022/08/30 11:48:49 - mmengine - INFO - Epoch(val) [480][30/32] eta: 0:00:01 time: 0.5978 data_time: 0.0367 memory: 15734 2022/08/30 11:48:50 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 11:48:50 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8512, precision: 0.7559, hmean: 0.8007 2022/08/30 11:48:50 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8507, precision: 0.7995, hmean: 0.8244 2022/08/30 11:48:50 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8498, precision: 0.8349, hmean: 0.8423 2022/08/30 11:48:50 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8435, precision: 0.8631, hmean: 0.8532 2022/08/30 11:48:50 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8296, precision: 0.8895, hmean: 0.8585 2022/08/30 11:48:50 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7309, precision: 0.9336, hmean: 0.8199 2022/08/30 11:48:50 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0977, precision: 0.9854, hmean: 0.1778 2022/08/30 11:48:50 - mmengine - INFO - Epoch(val) [480][32/32] icdar/precision: 0.8895 icdar/recall: 0.8296 icdar/hmean: 0.8585 2022/08/30 11:48:57 - mmengine - INFO - Epoch(train) [481][5/63] lr: 4.4179e-03 eta: 0:00:01 time: 1.1403 data_time: 0.2040 memory: 16201 loss_prob: 0.5857 loss_thr: 0.3984 loss_db: 0.1031 loss: 1.0871 2022/08/30 11:49:01 - mmengine - INFO - Epoch(train) [481][10/63] lr: 4.4179e-03 eta: 18:01:04 time: 1.0832 data_time: 0.2148 memory: 16201 loss_prob: 0.5560 loss_thr: 0.3755 loss_db: 0.0953 loss: 1.0267 2022/08/30 11:49:05 - mmengine - INFO - Epoch(train) [481][15/63] lr: 4.4179e-03 eta: 18:01:04 time: 0.8773 data_time: 0.0526 memory: 16201 loss_prob: 0.5460 loss_thr: 0.3603 loss_db: 0.0941 loss: 1.0004 2022/08/30 11:49:11 - mmengine - INFO - Epoch(train) [481][20/63] lr: 4.4179e-03 eta: 18:00:43 time: 0.9708 data_time: 0.0431 memory: 16201 loss_prob: 0.6148 loss_thr: 0.3911 loss_db: 0.1043 loss: 1.1102 2022/08/30 11:49:15 - mmengine - INFO - Epoch(train) [481][25/63] lr: 4.4179e-03 eta: 18:00:43 time: 0.9517 data_time: 0.0294 memory: 16201 loss_prob: 0.6285 loss_thr: 0.4106 loss_db: 0.1071 loss: 1.1461 2022/08/30 11:49:19 - mmengine - INFO - Epoch(train) [481][30/63] lr: 4.4179e-03 eta: 18:00:20 time: 0.8704 data_time: 0.0473 memory: 16201 loss_prob: 0.5314 loss_thr: 0.3697 loss_db: 0.0922 loss: 0.9934 2022/08/30 11:49:24 - mmengine - INFO - Epoch(train) [481][35/63] lr: 4.4179e-03 eta: 18:00:20 time: 0.9019 data_time: 0.0576 memory: 16201 loss_prob: 0.4979 loss_thr: 0.3404 loss_db: 0.0857 loss: 0.9239 2022/08/30 11:49:29 - mmengine - INFO - Epoch(train) [481][40/63] lr: 4.4179e-03 eta: 17:59:58 time: 0.9348 data_time: 0.0349 memory: 16201 loss_prob: 0.5222 loss_thr: 0.3512 loss_db: 0.0901 loss: 0.9635 2022/08/30 11:49:34 - mmengine - INFO - Epoch(train) [481][45/63] lr: 4.4179e-03 eta: 17:59:58 time: 0.9679 data_time: 0.0493 memory: 16201 loss_prob: 0.5394 loss_thr: 0.3726 loss_db: 0.0942 loss: 1.0061 2022/08/30 11:49:38 - mmengine - INFO - Epoch(train) [481][50/63] lr: 4.4179e-03 eta: 17:59:36 time: 0.9254 data_time: 0.0548 memory: 16201 loss_prob: 0.5781 loss_thr: 0.3870 loss_db: 0.0981 loss: 1.0632 2022/08/30 11:49:43 - mmengine - INFO - Epoch(train) [481][55/63] lr: 4.4179e-03 eta: 17:59:36 time: 0.9204 data_time: 0.0254 memory: 16201 loss_prob: 0.5579 loss_thr: 0.3777 loss_db: 0.0939 loss: 1.0295 2022/08/30 11:49:47 - mmengine - INFO - Epoch(train) [481][60/63] lr: 4.4179e-03 eta: 17:59:15 time: 0.9378 data_time: 0.0327 memory: 16201 loss_prob: 0.5021 loss_thr: 0.3532 loss_db: 0.0889 loss: 0.9442 2022/08/30 11:49:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:49:55 - mmengine - INFO - Epoch(train) [482][5/63] lr: 4.4124e-03 eta: 17:59:15 time: 0.9688 data_time: 0.1854 memory: 16201 loss_prob: 0.5455 loss_thr: 0.3647 loss_db: 0.0945 loss: 1.0047 2022/08/30 11:50:00 - mmengine - INFO - Epoch(train) [482][10/63] lr: 4.4124e-03 eta: 17:58:44 time: 1.0444 data_time: 0.2015 memory: 16201 loss_prob: 0.5224 loss_thr: 0.3626 loss_db: 0.0918 loss: 0.9768 2022/08/30 11:50:05 - mmengine - INFO - Epoch(train) [482][15/63] lr: 4.4124e-03 eta: 17:58:44 time: 0.9281 data_time: 0.0464 memory: 16201 loss_prob: 0.5534 loss_thr: 0.3769 loss_db: 0.0946 loss: 1.0248 2022/08/30 11:50:09 - mmengine - INFO - Epoch(train) [482][20/63] lr: 4.4124e-03 eta: 17:58:22 time: 0.8868 data_time: 0.0428 memory: 16201 loss_prob: 0.5657 loss_thr: 0.3810 loss_db: 0.0961 loss: 1.0429 2022/08/30 11:50:13 - mmengine - INFO - Epoch(train) [482][25/63] lr: 4.4124e-03 eta: 17:58:22 time: 0.8566 data_time: 0.0518 memory: 16201 loss_prob: 0.5784 loss_thr: 0.3869 loss_db: 0.1009 loss: 1.0661 2022/08/30 11:50:18 - mmengine - INFO - Epoch(train) [482][30/63] lr: 4.4124e-03 eta: 17:57:59 time: 0.8810 data_time: 0.0504 memory: 16201 loss_prob: 0.5738 loss_thr: 0.3820 loss_db: 0.0991 loss: 1.0549 2022/08/30 11:50:22 - mmengine - INFO - Epoch(train) [482][35/63] lr: 4.4124e-03 eta: 17:57:59 time: 0.9120 data_time: 0.0356 memory: 16201 loss_prob: 0.5666 loss_thr: 0.3956 loss_db: 0.0984 loss: 1.0606 2022/08/30 11:50:27 - mmengine - INFO - Epoch(train) [482][40/63] lr: 4.4124e-03 eta: 17:57:38 time: 0.9390 data_time: 0.0588 memory: 16201 loss_prob: 0.5746 loss_thr: 0.4042 loss_db: 0.0990 loss: 1.0778 2022/08/30 11:50:31 - mmengine - INFO - Epoch(train) [482][45/63] lr: 4.4124e-03 eta: 17:57:38 time: 0.9070 data_time: 0.0567 memory: 16201 loss_prob: 0.5606 loss_thr: 0.3782 loss_db: 0.0966 loss: 1.0353 2022/08/30 11:50:36 - mmengine - INFO - Epoch(train) [482][50/63] lr: 4.4124e-03 eta: 17:57:15 time: 0.8652 data_time: 0.0318 memory: 16201 loss_prob: 0.5337 loss_thr: 0.3621 loss_db: 0.0940 loss: 0.9897 2022/08/30 11:50:41 - mmengine - INFO - Epoch(train) [482][55/63] lr: 4.4124e-03 eta: 17:57:15 time: 0.9184 data_time: 0.0525 memory: 16201 loss_prob: 0.5644 loss_thr: 0.3816 loss_db: 0.0972 loss: 1.0433 2022/08/30 11:50:45 - mmengine - INFO - Epoch(train) [482][60/63] lr: 4.4124e-03 eta: 17:56:53 time: 0.9368 data_time: 0.0543 memory: 16201 loss_prob: 0.5133 loss_thr: 0.3568 loss_db: 0.0882 loss: 0.9584 2022/08/30 11:50:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:50:53 - mmengine - INFO - Epoch(train) [483][5/63] lr: 4.4069e-03 eta: 17:56:53 time: 1.0006 data_time: 0.2023 memory: 16201 loss_prob: 0.5052 loss_thr: 0.3737 loss_db: 0.0897 loss: 0.9686 2022/08/30 11:50:58 - mmengine - INFO - Epoch(train) [483][10/63] lr: 4.4069e-03 eta: 17:56:23 time: 1.0842 data_time: 0.2378 memory: 16201 loss_prob: 0.5038 loss_thr: 0.3642 loss_db: 0.0871 loss: 0.9551 2022/08/30 11:51:03 - mmengine - INFO - Epoch(train) [483][15/63] lr: 4.4069e-03 eta: 17:56:23 time: 0.9763 data_time: 0.0727 memory: 16201 loss_prob: 0.5353 loss_thr: 0.3663 loss_db: 0.0930 loss: 0.9947 2022/08/30 11:51:07 - mmengine - INFO - Epoch(train) [483][20/63] lr: 4.4069e-03 eta: 17:56:02 time: 0.9286 data_time: 0.0426 memory: 16201 loss_prob: 0.5225 loss_thr: 0.3589 loss_db: 0.0922 loss: 0.9736 2022/08/30 11:51:12 - mmengine - INFO - Epoch(train) [483][25/63] lr: 4.4069e-03 eta: 17:56:02 time: 0.8628 data_time: 0.0467 memory: 16201 loss_prob: 0.5132 loss_thr: 0.3477 loss_db: 0.0903 loss: 0.9513 2022/08/30 11:51:16 - mmengine - INFO - Epoch(train) [483][30/63] lr: 4.4069e-03 eta: 17:55:39 time: 0.8779 data_time: 0.0439 memory: 16201 loss_prob: 0.5296 loss_thr: 0.3559 loss_db: 0.0903 loss: 0.9758 2022/08/30 11:51:20 - mmengine - INFO - Epoch(train) [483][35/63] lr: 4.4069e-03 eta: 17:55:39 time: 0.8866 data_time: 0.0265 memory: 16201 loss_prob: 0.5093 loss_thr: 0.3571 loss_db: 0.0883 loss: 0.9548 2022/08/30 11:51:25 - mmengine - INFO - Epoch(train) [483][40/63] lr: 4.4069e-03 eta: 17:55:17 time: 0.8733 data_time: 0.0292 memory: 16201 loss_prob: 0.4980 loss_thr: 0.3531 loss_db: 0.0874 loss: 0.9386 2022/08/30 11:51:29 - mmengine - INFO - Epoch(train) [483][45/63] lr: 4.4069e-03 eta: 17:55:17 time: 0.8829 data_time: 0.0334 memory: 16201 loss_prob: 0.5015 loss_thr: 0.3533 loss_db: 0.0872 loss: 0.9420 2022/08/30 11:51:34 - mmengine - INFO - Epoch(train) [483][50/63] lr: 4.4069e-03 eta: 17:54:54 time: 0.9025 data_time: 0.0432 memory: 16201 loss_prob: 0.5357 loss_thr: 0.3628 loss_db: 0.0882 loss: 0.9867 2022/08/30 11:51:38 - mmengine - INFO - Epoch(train) [483][55/63] lr: 4.4069e-03 eta: 17:54:54 time: 0.8830 data_time: 0.0525 memory: 16201 loss_prob: 0.5167 loss_thr: 0.3569 loss_db: 0.0861 loss: 0.9598 2022/08/30 11:51:43 - mmengine - INFO - Epoch(train) [483][60/63] lr: 4.4069e-03 eta: 17:54:32 time: 0.8850 data_time: 0.0452 memory: 16201 loss_prob: 0.5245 loss_thr: 0.3656 loss_db: 0.0939 loss: 0.9840 2022/08/30 11:51:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:51:51 - mmengine - INFO - Epoch(train) [484][5/63] lr: 4.4014e-03 eta: 17:54:32 time: 1.0086 data_time: 0.2268 memory: 16201 loss_prob: 0.5337 loss_thr: 0.3686 loss_db: 0.0904 loss: 0.9927 2022/08/30 11:51:56 - mmengine - INFO - Epoch(train) [484][10/63] lr: 4.4014e-03 eta: 17:54:02 time: 1.1016 data_time: 0.2683 memory: 16201 loss_prob: 0.5355 loss_thr: 0.3712 loss_db: 0.0931 loss: 0.9998 2022/08/30 11:52:00 - mmengine - INFO - Epoch(train) [484][15/63] lr: 4.4014e-03 eta: 17:54:02 time: 0.9121 data_time: 0.0657 memory: 16201 loss_prob: 0.5318 loss_thr: 0.3661 loss_db: 0.0947 loss: 0.9925 2022/08/30 11:52:05 - mmengine - INFO - Epoch(train) [484][20/63] lr: 4.4014e-03 eta: 17:53:40 time: 0.8861 data_time: 0.0277 memory: 16201 loss_prob: 0.5528 loss_thr: 0.3647 loss_db: 0.0954 loss: 1.0129 2022/08/30 11:52:09 - mmengine - INFO - Epoch(train) [484][25/63] lr: 4.4014e-03 eta: 17:53:40 time: 0.8945 data_time: 0.0550 memory: 16201 loss_prob: 0.5663 loss_thr: 0.3650 loss_db: 0.0970 loss: 1.0283 2022/08/30 11:52:13 - mmengine - INFO - Epoch(train) [484][30/63] lr: 4.4014e-03 eta: 17:53:18 time: 0.8766 data_time: 0.0517 memory: 16201 loss_prob: 0.5512 loss_thr: 0.3722 loss_db: 0.0940 loss: 1.0174 2022/08/30 11:52:18 - mmengine - INFO - Epoch(train) [484][35/63] lr: 4.4014e-03 eta: 17:53:18 time: 0.8512 data_time: 0.0238 memory: 16201 loss_prob: 0.5550 loss_thr: 0.3830 loss_db: 0.0943 loss: 1.0324 2022/08/30 11:52:23 - mmengine - INFO - Epoch(train) [484][40/63] lr: 4.4014e-03 eta: 17:52:56 time: 0.9556 data_time: 0.0466 memory: 16201 loss_prob: 0.5319 loss_thr: 0.3633 loss_db: 0.0928 loss: 0.9880 2022/08/30 11:52:27 - mmengine - INFO - Epoch(train) [484][45/63] lr: 4.4014e-03 eta: 17:52:56 time: 0.9512 data_time: 0.0533 memory: 16201 loss_prob: 0.5170 loss_thr: 0.3463 loss_db: 0.0913 loss: 0.9546 2022/08/30 11:52:31 - mmengine - INFO - Epoch(train) [484][50/63] lr: 4.4014e-03 eta: 17:52:34 time: 0.8483 data_time: 0.0327 memory: 16201 loss_prob: 0.5472 loss_thr: 0.3642 loss_db: 0.0951 loss: 1.0065 2022/08/30 11:52:36 - mmengine - INFO - Epoch(train) [484][55/63] lr: 4.4014e-03 eta: 17:52:34 time: 0.8842 data_time: 0.0469 memory: 16201 loss_prob: 0.5528 loss_thr: 0.3759 loss_db: 0.0956 loss: 1.0242 2022/08/30 11:52:41 - mmengine - INFO - Epoch(train) [484][60/63] lr: 4.4014e-03 eta: 17:52:12 time: 0.9269 data_time: 0.0618 memory: 16201 loss_prob: 0.5539 loss_thr: 0.3806 loss_db: 0.0967 loss: 1.0312 2022/08/30 11:52:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:52:49 - mmengine - INFO - Epoch(train) [485][5/63] lr: 4.3958e-03 eta: 17:52:12 time: 1.0314 data_time: 0.2302 memory: 16201 loss_prob: 0.5745 loss_thr: 0.3782 loss_db: 0.0993 loss: 1.0520 2022/08/30 11:52:53 - mmengine - INFO - Epoch(train) [485][10/63] lr: 4.3958e-03 eta: 17:51:41 time: 1.0143 data_time: 0.2256 memory: 16201 loss_prob: 0.5659 loss_thr: 0.3785 loss_db: 0.0981 loss: 1.0425 2022/08/30 11:52:57 - mmengine - INFO - Epoch(train) [485][15/63] lr: 4.3958e-03 eta: 17:51:41 time: 0.8235 data_time: 0.0322 memory: 16201 loss_prob: 0.5610 loss_thr: 0.3801 loss_db: 0.0958 loss: 1.0369 2022/08/30 11:53:01 - mmengine - INFO - Epoch(train) [485][20/63] lr: 4.3958e-03 eta: 17:51:18 time: 0.8166 data_time: 0.0243 memory: 16201 loss_prob: 0.5630 loss_thr: 0.3774 loss_db: 0.0962 loss: 1.0367 2022/08/30 11:53:05 - mmengine - INFO - Epoch(train) [485][25/63] lr: 4.3958e-03 eta: 17:51:18 time: 0.8014 data_time: 0.0295 memory: 16201 loss_prob: 0.5470 loss_thr: 0.3806 loss_db: 0.0978 loss: 1.0254 2022/08/30 11:53:10 - mmengine - INFO - Epoch(train) [485][30/63] lr: 4.3958e-03 eta: 17:50:55 time: 0.8813 data_time: 0.0324 memory: 16201 loss_prob: 0.5843 loss_thr: 0.3934 loss_db: 0.1032 loss: 1.0809 2022/08/30 11:53:15 - mmengine - INFO - Epoch(train) [485][35/63] lr: 4.3958e-03 eta: 17:50:55 time: 0.9221 data_time: 0.0320 memory: 16201 loss_prob: 0.6232 loss_thr: 0.4016 loss_db: 0.1053 loss: 1.1300 2022/08/30 11:53:19 - mmengine - INFO - Epoch(train) [485][40/63] lr: 4.3958e-03 eta: 17:50:33 time: 0.8778 data_time: 0.0323 memory: 16201 loss_prob: 0.5732 loss_thr: 0.3849 loss_db: 0.0986 loss: 1.0566 2022/08/30 11:53:23 - mmengine - INFO - Epoch(train) [485][45/63] lr: 4.3958e-03 eta: 17:50:33 time: 0.8472 data_time: 0.0296 memory: 16201 loss_prob: 0.5363 loss_thr: 0.3710 loss_db: 0.0953 loss: 1.0025 2022/08/30 11:53:28 - mmengine - INFO - Epoch(train) [485][50/63] lr: 4.3958e-03 eta: 17:50:11 time: 0.9019 data_time: 0.0239 memory: 16201 loss_prob: 0.5530 loss_thr: 0.3717 loss_db: 0.0952 loss: 1.0199 2022/08/30 11:53:32 - mmengine - INFO - Epoch(train) [485][55/63] lr: 4.3958e-03 eta: 17:50:11 time: 0.9337 data_time: 0.0437 memory: 16201 loss_prob: 0.5440 loss_thr: 0.3730 loss_db: 0.0925 loss: 1.0095 2022/08/30 11:53:37 - mmengine - INFO - Epoch(train) [485][60/63] lr: 4.3958e-03 eta: 17:49:49 time: 0.8938 data_time: 0.0509 memory: 16201 loss_prob: 0.5104 loss_thr: 0.3610 loss_db: 0.0906 loss: 0.9620 2022/08/30 11:53:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:53:45 - mmengine - INFO - Epoch(train) [486][5/63] lr: 4.3903e-03 eta: 17:49:49 time: 1.0160 data_time: 0.2325 memory: 16201 loss_prob: 0.5285 loss_thr: 0.3495 loss_db: 0.0918 loss: 0.9698 2022/08/30 11:53:50 - mmengine - INFO - Epoch(train) [486][10/63] lr: 4.3903e-03 eta: 17:49:19 time: 1.0368 data_time: 0.2337 memory: 16201 loss_prob: 0.5141 loss_thr: 0.3503 loss_db: 0.0885 loss: 0.9529 2022/08/30 11:53:54 - mmengine - INFO - Epoch(train) [486][15/63] lr: 4.3903e-03 eta: 17:49:19 time: 0.8661 data_time: 0.0490 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3491 loss_db: 0.0838 loss: 0.9081 2022/08/30 11:53:58 - mmengine - INFO - Epoch(train) [486][20/63] lr: 4.3903e-03 eta: 17:48:56 time: 0.8399 data_time: 0.0394 memory: 16201 loss_prob: 0.4803 loss_thr: 0.3633 loss_db: 0.0854 loss: 0.9291 2022/08/30 11:54:02 - mmengine - INFO - Epoch(train) [486][25/63] lr: 4.3903e-03 eta: 17:48:56 time: 0.8421 data_time: 0.0505 memory: 16201 loss_prob: 0.4822 loss_thr: 0.3542 loss_db: 0.0831 loss: 0.9194 2022/08/30 11:54:07 - mmengine - INFO - Epoch(train) [486][30/63] lr: 4.3903e-03 eta: 17:48:33 time: 0.8805 data_time: 0.0526 memory: 16201 loss_prob: 0.5066 loss_thr: 0.3484 loss_db: 0.0863 loss: 0.9413 2022/08/30 11:54:11 - mmengine - INFO - Epoch(train) [486][35/63] lr: 4.3903e-03 eta: 17:48:33 time: 0.8926 data_time: 0.0290 memory: 16201 loss_prob: 0.5548 loss_thr: 0.3819 loss_db: 0.0968 loss: 1.0335 2022/08/30 11:54:16 - mmengine - INFO - Epoch(train) [486][40/63] lr: 4.3903e-03 eta: 17:48:12 time: 0.9069 data_time: 0.0478 memory: 16201 loss_prob: 0.5262 loss_thr: 0.3734 loss_db: 0.0930 loss: 0.9927 2022/08/30 11:54:20 - mmengine - INFO - Epoch(train) [486][45/63] lr: 4.3903e-03 eta: 17:48:12 time: 0.9157 data_time: 0.0501 memory: 16201 loss_prob: 0.5096 loss_thr: 0.3613 loss_db: 0.0865 loss: 0.9574 2022/08/30 11:54:25 - mmengine - INFO - Epoch(train) [486][50/63] lr: 4.3903e-03 eta: 17:47:50 time: 0.8913 data_time: 0.0410 memory: 16201 loss_prob: 0.4990 loss_thr: 0.3607 loss_db: 0.0861 loss: 0.9457 2022/08/30 11:54:29 - mmengine - INFO - Epoch(train) [486][55/63] lr: 4.3903e-03 eta: 17:47:50 time: 0.8728 data_time: 0.0401 memory: 16201 loss_prob: 0.5258 loss_thr: 0.3630 loss_db: 0.0957 loss: 0.9845 2022/08/30 11:54:33 - mmengine - INFO - Epoch(train) [486][60/63] lr: 4.3903e-03 eta: 17:47:27 time: 0.8657 data_time: 0.0310 memory: 16201 loss_prob: 0.5655 loss_thr: 0.3791 loss_db: 0.0993 loss: 1.0439 2022/08/30 11:54:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:54:42 - mmengine - INFO - Epoch(train) [487][5/63] lr: 4.3848e-03 eta: 17:47:27 time: 0.9914 data_time: 0.1874 memory: 16201 loss_prob: 0.6041 loss_thr: 0.3935 loss_db: 0.1027 loss: 1.1003 2022/08/30 11:54:46 - mmengine - INFO - Epoch(train) [487][10/63] lr: 4.3848e-03 eta: 17:46:56 time: 1.0281 data_time: 0.2008 memory: 16201 loss_prob: 0.5918 loss_thr: 0.3667 loss_db: 0.0998 loss: 1.0583 2022/08/30 11:54:51 - mmengine - INFO - Epoch(train) [487][15/63] lr: 4.3848e-03 eta: 17:46:56 time: 0.9287 data_time: 0.0395 memory: 16201 loss_prob: 0.5645 loss_thr: 0.3627 loss_db: 0.0963 loss: 1.0235 2022/08/30 11:54:55 - mmengine - INFO - Epoch(train) [487][20/63] lr: 4.3848e-03 eta: 17:46:35 time: 0.9278 data_time: 0.0258 memory: 16201 loss_prob: 0.5488 loss_thr: 0.3715 loss_db: 0.0942 loss: 1.0144 2022/08/30 11:55:00 - mmengine - INFO - Epoch(train) [487][25/63] lr: 4.3848e-03 eta: 17:46:35 time: 0.8796 data_time: 0.0414 memory: 16201 loss_prob: 0.5227 loss_thr: 0.3517 loss_db: 0.0902 loss: 0.9646 2022/08/30 11:55:04 - mmengine - INFO - Epoch(train) [487][30/63] lr: 4.3848e-03 eta: 17:46:12 time: 0.8572 data_time: 0.0371 memory: 16201 loss_prob: 0.4855 loss_thr: 0.3307 loss_db: 0.0842 loss: 0.9004 2022/08/30 11:55:08 - mmengine - INFO - Epoch(train) [487][35/63] lr: 4.3848e-03 eta: 17:46:12 time: 0.8351 data_time: 0.0249 memory: 16201 loss_prob: 0.4648 loss_thr: 0.3272 loss_db: 0.0806 loss: 0.8727 2022/08/30 11:55:12 - mmengine - INFO - Epoch(train) [487][40/63] lr: 4.3848e-03 eta: 17:45:50 time: 0.8395 data_time: 0.0328 memory: 16201 loss_prob: 0.5222 loss_thr: 0.3580 loss_db: 0.0921 loss: 0.9724 2022/08/30 11:55:16 - mmengine - INFO - Epoch(train) [487][45/63] lr: 4.3848e-03 eta: 17:45:50 time: 0.8325 data_time: 0.0342 memory: 16201 loss_prob: 0.5527 loss_thr: 0.3828 loss_db: 0.0951 loss: 1.0307 2022/08/30 11:55:22 - mmengine - INFO - Epoch(train) [487][50/63] lr: 4.3848e-03 eta: 17:45:28 time: 0.9402 data_time: 0.0278 memory: 16201 loss_prob: 0.5034 loss_thr: 0.3619 loss_db: 0.0863 loss: 0.9517 2022/08/30 11:55:26 - mmengine - INFO - Epoch(train) [487][55/63] lr: 4.3848e-03 eta: 17:45:28 time: 0.9545 data_time: 0.0397 memory: 16201 loss_prob: 0.4905 loss_thr: 0.3511 loss_db: 0.0869 loss: 0.9284 2022/08/30 11:55:30 - mmengine - INFO - Epoch(train) [487][60/63] lr: 4.3848e-03 eta: 17:45:06 time: 0.8399 data_time: 0.0357 memory: 16201 loss_prob: 0.5462 loss_thr: 0.3671 loss_db: 0.0955 loss: 1.0088 2022/08/30 11:55:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:55:38 - mmengine - INFO - Epoch(train) [488][5/63] lr: 4.3792e-03 eta: 17:45:06 time: 0.9946 data_time: 0.1920 memory: 16201 loss_prob: 0.5717 loss_thr: 0.3835 loss_db: 0.0991 loss: 1.0543 2022/08/30 11:55:43 - mmengine - INFO - Epoch(train) [488][10/63] lr: 4.3792e-03 eta: 17:44:35 time: 1.0481 data_time: 0.2054 memory: 16201 loss_prob: 0.5517 loss_thr: 0.3684 loss_db: 0.0961 loss: 1.0161 2022/08/30 11:55:47 - mmengine - INFO - Epoch(train) [488][15/63] lr: 4.3792e-03 eta: 17:44:35 time: 0.8717 data_time: 0.0450 memory: 16201 loss_prob: 0.5220 loss_thr: 0.3527 loss_db: 0.0919 loss: 0.9665 2022/08/30 11:55:52 - mmengine - INFO - Epoch(train) [488][20/63] lr: 4.3792e-03 eta: 17:44:14 time: 0.9498 data_time: 0.0377 memory: 16201 loss_prob: 0.5385 loss_thr: 0.3614 loss_db: 0.0940 loss: 0.9939 2022/08/30 11:55:57 - mmengine - INFO - Epoch(train) [488][25/63] lr: 4.3792e-03 eta: 17:44:14 time: 0.9516 data_time: 0.0521 memory: 16201 loss_prob: 0.5831 loss_thr: 0.3792 loss_db: 0.0994 loss: 1.0617 2022/08/30 11:56:01 - mmengine - INFO - Epoch(train) [488][30/63] lr: 4.3792e-03 eta: 17:43:52 time: 0.8707 data_time: 0.0433 memory: 16201 loss_prob: 0.5814 loss_thr: 0.3801 loss_db: 0.1013 loss: 1.0628 2022/08/30 11:56:05 - mmengine - INFO - Epoch(train) [488][35/63] lr: 4.3792e-03 eta: 17:43:52 time: 0.8427 data_time: 0.0279 memory: 16201 loss_prob: 0.5193 loss_thr: 0.3566 loss_db: 0.0937 loss: 0.9695 2022/08/30 11:56:10 - mmengine - INFO - Epoch(train) [488][40/63] lr: 4.3792e-03 eta: 17:43:30 time: 0.9116 data_time: 0.0456 memory: 16201 loss_prob: 0.4986 loss_thr: 0.3410 loss_db: 0.0874 loss: 0.9269 2022/08/30 11:56:14 - mmengine - INFO - Epoch(train) [488][45/63] lr: 4.3792e-03 eta: 17:43:30 time: 0.9125 data_time: 0.0492 memory: 16201 loss_prob: 0.5273 loss_thr: 0.3661 loss_db: 0.0911 loss: 0.9844 2022/08/30 11:56:19 - mmengine - INFO - Epoch(train) [488][50/63] lr: 4.3792e-03 eta: 17:43:08 time: 0.8588 data_time: 0.0351 memory: 16201 loss_prob: 0.5208 loss_thr: 0.3666 loss_db: 0.0924 loss: 0.9798 2022/08/30 11:56:23 - mmengine - INFO - Epoch(train) [488][55/63] lr: 4.3792e-03 eta: 17:43:08 time: 0.8877 data_time: 0.0604 memory: 16201 loss_prob: 0.5272 loss_thr: 0.3519 loss_db: 0.0919 loss: 0.9711 2022/08/30 11:56:27 - mmengine - INFO - Epoch(train) [488][60/63] lr: 4.3792e-03 eta: 17:42:45 time: 0.8584 data_time: 0.0699 memory: 16201 loss_prob: 0.5088 loss_thr: 0.3422 loss_db: 0.0868 loss: 0.9377 2022/08/30 11:56:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:56:36 - mmengine - INFO - Epoch(train) [489][5/63] lr: 4.3737e-03 eta: 17:42:45 time: 1.0099 data_time: 0.1911 memory: 16201 loss_prob: 0.5471 loss_thr: 0.3635 loss_db: 0.0927 loss: 1.0033 2022/08/30 11:56:40 - mmengine - INFO - Epoch(train) [489][10/63] lr: 4.3737e-03 eta: 17:42:16 time: 1.0654 data_time: 0.2239 memory: 16201 loss_prob: 0.5539 loss_thr: 0.3757 loss_db: 0.0974 loss: 1.0270 2022/08/30 11:56:44 - mmengine - INFO - Epoch(train) [489][15/63] lr: 4.3737e-03 eta: 17:42:16 time: 0.8748 data_time: 0.0558 memory: 16201 loss_prob: 0.5579 loss_thr: 0.3755 loss_db: 0.0987 loss: 1.0321 2022/08/30 11:56:49 - mmengine - INFO - Epoch(train) [489][20/63] lr: 4.3737e-03 eta: 17:41:53 time: 0.8386 data_time: 0.0299 memory: 16201 loss_prob: 0.5256 loss_thr: 0.3672 loss_db: 0.0912 loss: 0.9840 2022/08/30 11:56:54 - mmengine - INFO - Epoch(train) [489][25/63] lr: 4.3737e-03 eta: 17:41:53 time: 0.9343 data_time: 0.0627 memory: 16201 loss_prob: 0.5128 loss_thr: 0.3701 loss_db: 0.0887 loss: 0.9716 2022/08/30 11:56:58 - mmengine - INFO - Epoch(train) [489][30/63] lr: 4.3737e-03 eta: 17:41:32 time: 0.9525 data_time: 0.0589 memory: 16201 loss_prob: 0.5056 loss_thr: 0.3504 loss_db: 0.0873 loss: 0.9433 2022/08/30 11:57:02 - mmengine - INFO - Epoch(train) [489][35/63] lr: 4.3737e-03 eta: 17:41:32 time: 0.8635 data_time: 0.0276 memory: 16201 loss_prob: 0.5106 loss_thr: 0.3507 loss_db: 0.0886 loss: 0.9499 2022/08/30 11:57:07 - mmengine - INFO - Epoch(train) [489][40/63] lr: 4.3737e-03 eta: 17:41:10 time: 0.9022 data_time: 0.0328 memory: 16201 loss_prob: 0.5236 loss_thr: 0.3702 loss_db: 0.0911 loss: 0.9848 2022/08/30 11:57:11 - mmengine - INFO - Epoch(train) [489][45/63] lr: 4.3737e-03 eta: 17:41:10 time: 0.8811 data_time: 0.0382 memory: 16201 loss_prob: 0.5078 loss_thr: 0.3666 loss_db: 0.0896 loss: 0.9640 2022/08/30 11:57:15 - mmengine - INFO - Epoch(train) [489][50/63] lr: 4.3737e-03 eta: 17:40:47 time: 0.8030 data_time: 0.0307 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3472 loss_db: 0.0843 loss: 0.9066 2022/08/30 11:57:20 - mmengine - INFO - Epoch(train) [489][55/63] lr: 4.3737e-03 eta: 17:40:47 time: 0.8444 data_time: 0.0309 memory: 16201 loss_prob: 0.4901 loss_thr: 0.3465 loss_db: 0.0851 loss: 0.9218 2022/08/30 11:57:24 - mmengine - INFO - Epoch(train) [489][60/63] lr: 4.3737e-03 eta: 17:40:24 time: 0.8541 data_time: 0.0379 memory: 16201 loss_prob: 0.5508 loss_thr: 0.3595 loss_db: 0.0948 loss: 1.0051 2022/08/30 11:57:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:57:32 - mmengine - INFO - Epoch(train) [490][5/63] lr: 4.3681e-03 eta: 17:40:24 time: 0.9439 data_time: 0.1933 memory: 16201 loss_prob: 0.5427 loss_thr: 0.3698 loss_db: 0.0937 loss: 1.0062 2022/08/30 11:57:36 - mmengine - INFO - Epoch(train) [490][10/63] lr: 4.3681e-03 eta: 17:39:54 time: 1.0112 data_time: 0.2016 memory: 16201 loss_prob: 0.5053 loss_thr: 0.3609 loss_db: 0.0873 loss: 0.9535 2022/08/30 11:57:40 - mmengine - INFO - Epoch(train) [490][15/63] lr: 4.3681e-03 eta: 17:39:54 time: 0.8670 data_time: 0.0329 memory: 16201 loss_prob: 0.5383 loss_thr: 0.3656 loss_db: 0.0942 loss: 0.9981 2022/08/30 11:57:45 - mmengine - INFO - Epoch(train) [490][20/63] lr: 4.3681e-03 eta: 17:39:32 time: 0.9079 data_time: 0.0254 memory: 16201 loss_prob: 0.5348 loss_thr: 0.3607 loss_db: 0.0929 loss: 0.9884 2022/08/30 11:57:49 - mmengine - INFO - Epoch(train) [490][25/63] lr: 4.3681e-03 eta: 17:39:32 time: 0.9080 data_time: 0.0486 memory: 16201 loss_prob: 0.5128 loss_thr: 0.3552 loss_db: 0.0879 loss: 0.9559 2022/08/30 11:57:54 - mmengine - INFO - Epoch(train) [490][30/63] lr: 4.3681e-03 eta: 17:39:10 time: 0.8633 data_time: 0.0457 memory: 16201 loss_prob: 0.5967 loss_thr: 0.3639 loss_db: 0.1020 loss: 1.0626 2022/08/30 11:57:58 - mmengine - INFO - Epoch(train) [490][35/63] lr: 4.3681e-03 eta: 17:39:10 time: 0.8546 data_time: 0.0270 memory: 16201 loss_prob: 0.6123 loss_thr: 0.3740 loss_db: 0.1064 loss: 1.0927 2022/08/30 11:58:02 - mmengine - INFO - Epoch(train) [490][40/63] lr: 4.3681e-03 eta: 17:38:48 time: 0.8791 data_time: 0.0380 memory: 16201 loss_prob: 0.5576 loss_thr: 0.3735 loss_db: 0.0997 loss: 1.0308 2022/08/30 11:58:07 - mmengine - INFO - Epoch(train) [490][45/63] lr: 4.3681e-03 eta: 17:38:48 time: 0.8893 data_time: 0.0387 memory: 16201 loss_prob: 0.5723 loss_thr: 0.3839 loss_db: 0.1007 loss: 1.0570 2022/08/30 11:58:11 - mmengine - INFO - Epoch(train) [490][50/63] lr: 4.3681e-03 eta: 17:38:26 time: 0.8889 data_time: 0.0349 memory: 16201 loss_prob: 0.5918 loss_thr: 0.3959 loss_db: 0.1022 loss: 1.0899 2022/08/30 11:58:15 - mmengine - INFO - Epoch(train) [490][55/63] lr: 4.3681e-03 eta: 17:38:26 time: 0.8594 data_time: 0.0357 memory: 16201 loss_prob: 0.5867 loss_thr: 0.3838 loss_db: 0.0986 loss: 1.0691 2022/08/30 11:58:20 - mmengine - INFO - Epoch(train) [490][60/63] lr: 4.3681e-03 eta: 17:38:04 time: 0.8928 data_time: 0.0306 memory: 16201 loss_prob: 0.5596 loss_thr: 0.3666 loss_db: 0.0932 loss: 1.0194 2022/08/30 11:58:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:58:29 - mmengine - INFO - Epoch(train) [491][5/63] lr: 4.3626e-03 eta: 17:38:04 time: 1.0678 data_time: 0.2159 memory: 16201 loss_prob: 0.6163 loss_thr: 0.3962 loss_db: 0.1073 loss: 1.1198 2022/08/30 11:58:33 - mmengine - INFO - Epoch(train) [491][10/63] lr: 4.3626e-03 eta: 17:37:34 time: 1.0602 data_time: 0.2178 memory: 16201 loss_prob: 0.6840 loss_thr: 0.3839 loss_db: 0.1063 loss: 1.1742 2022/08/30 11:58:37 - mmengine - INFO - Epoch(train) [491][15/63] lr: 4.3626e-03 eta: 17:37:34 time: 0.8446 data_time: 0.0281 memory: 16201 loss_prob: 0.6540 loss_thr: 0.3868 loss_db: 0.1011 loss: 1.1419 2022/08/30 11:58:43 - mmengine - INFO - Epoch(train) [491][20/63] lr: 4.3626e-03 eta: 17:37:13 time: 0.9495 data_time: 0.0401 memory: 16201 loss_prob: 0.5328 loss_thr: 0.3677 loss_db: 0.0924 loss: 0.9929 2022/08/30 11:58:47 - mmengine - INFO - Epoch(train) [491][25/63] lr: 4.3626e-03 eta: 17:37:13 time: 0.9782 data_time: 0.0610 memory: 16201 loss_prob: 0.5058 loss_thr: 0.3439 loss_db: 0.0885 loss: 0.9381 2022/08/30 11:58:51 - mmengine - INFO - Epoch(train) [491][30/63] lr: 4.3626e-03 eta: 17:36:51 time: 0.8733 data_time: 0.0381 memory: 16201 loss_prob: 0.5502 loss_thr: 0.3638 loss_db: 0.0955 loss: 1.0095 2022/08/30 11:58:56 - mmengine - INFO - Epoch(train) [491][35/63] lr: 4.3626e-03 eta: 17:36:51 time: 0.8765 data_time: 0.0327 memory: 16201 loss_prob: 0.5377 loss_thr: 0.3555 loss_db: 0.0925 loss: 0.9857 2022/08/30 11:59:00 - mmengine - INFO - Epoch(train) [491][40/63] lr: 4.3626e-03 eta: 17:36:29 time: 0.8944 data_time: 0.0621 memory: 16201 loss_prob: 0.5294 loss_thr: 0.3436 loss_db: 0.0921 loss: 0.9651 2022/08/30 11:59:04 - mmengine - INFO - Epoch(train) [491][45/63] lr: 4.3626e-03 eta: 17:36:29 time: 0.8810 data_time: 0.0625 memory: 16201 loss_prob: 0.5492 loss_thr: 0.3565 loss_db: 0.0941 loss: 0.9998 2022/08/30 11:59:09 - mmengine - INFO - Epoch(train) [491][50/63] lr: 4.3626e-03 eta: 17:36:07 time: 0.8435 data_time: 0.0403 memory: 16201 loss_prob: 0.5474 loss_thr: 0.3801 loss_db: 0.0942 loss: 1.0217 2022/08/30 11:59:14 - mmengine - INFO - Epoch(train) [491][55/63] lr: 4.3626e-03 eta: 17:36:07 time: 0.9275 data_time: 0.0347 memory: 16201 loss_prob: 0.5864 loss_thr: 0.3916 loss_db: 0.0998 loss: 1.0778 2022/08/30 11:59:18 - mmengine - INFO - Epoch(train) [491][60/63] lr: 4.3626e-03 eta: 17:35:46 time: 0.9225 data_time: 0.0346 memory: 16201 loss_prob: 0.5878 loss_thr: 0.3855 loss_db: 0.0977 loss: 1.0709 2022/08/30 11:59:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 11:59:26 - mmengine - INFO - Epoch(train) [492][5/63] lr: 4.3571e-03 eta: 17:35:46 time: 0.9818 data_time: 0.1784 memory: 16201 loss_prob: 0.5517 loss_thr: 0.3878 loss_db: 0.0949 loss: 1.0344 2022/08/30 11:59:31 - mmengine - INFO - Epoch(train) [492][10/63] lr: 4.3571e-03 eta: 17:35:16 time: 1.0678 data_time: 0.1830 memory: 16201 loss_prob: 0.5032 loss_thr: 0.3553 loss_db: 0.0865 loss: 0.9450 2022/08/30 11:59:35 - mmengine - INFO - Epoch(train) [492][15/63] lr: 4.3571e-03 eta: 17:35:16 time: 0.9187 data_time: 0.0361 memory: 16201 loss_prob: 0.4813 loss_thr: 0.3368 loss_db: 0.0852 loss: 0.9033 2022/08/30 11:59:40 - mmengine - INFO - Epoch(train) [492][20/63] lr: 4.3571e-03 eta: 17:34:55 time: 0.9144 data_time: 0.0407 memory: 16201 loss_prob: 0.5183 loss_thr: 0.3564 loss_db: 0.0920 loss: 0.9666 2022/08/30 11:59:44 - mmengine - INFO - Epoch(train) [492][25/63] lr: 4.3571e-03 eta: 17:34:55 time: 0.8944 data_time: 0.0521 memory: 16201 loss_prob: 0.5825 loss_thr: 0.3863 loss_db: 0.1008 loss: 1.0696 2022/08/30 11:59:48 - mmengine - INFO - Epoch(train) [492][30/63] lr: 4.3571e-03 eta: 17:34:32 time: 0.8595 data_time: 0.0460 memory: 16201 loss_prob: 0.5525 loss_thr: 0.3695 loss_db: 0.0962 loss: 1.0182 2022/08/30 11:59:53 - mmengine - INFO - Epoch(train) [492][35/63] lr: 4.3571e-03 eta: 17:34:32 time: 0.8411 data_time: 0.0281 memory: 16201 loss_prob: 0.5282 loss_thr: 0.3591 loss_db: 0.0923 loss: 0.9797 2022/08/30 11:59:57 - mmengine - INFO - Epoch(train) [492][40/63] lr: 4.3571e-03 eta: 17:34:10 time: 0.8786 data_time: 0.0349 memory: 16201 loss_prob: 0.5582 loss_thr: 0.3800 loss_db: 0.0961 loss: 1.0344 2022/08/30 12:00:07 - mmengine - INFO - Epoch(train) [492][45/63] lr: 4.3571e-03 eta: 17:34:10 time: 1.4631 data_time: 0.0357 memory: 16201 loss_prob: 0.5622 loss_thr: 0.3534 loss_db: 0.0938 loss: 1.0094 2022/08/30 12:00:12 - mmengine - INFO - Epoch(train) [492][50/63] lr: 4.3571e-03 eta: 17:33:58 time: 1.5079 data_time: 0.0462 memory: 16201 loss_prob: 0.5940 loss_thr: 0.3735 loss_db: 0.0974 loss: 1.0650 2022/08/30 12:00:16 - mmengine - INFO - Epoch(train) [492][55/63] lr: 4.3571e-03 eta: 17:33:58 time: 0.9082 data_time: 0.0457 memory: 16201 loss_prob: 0.5755 loss_thr: 0.3870 loss_db: 0.0982 loss: 1.0607 2022/08/30 12:00:22 - mmengine - INFO - Epoch(train) [492][60/63] lr: 4.3571e-03 eta: 17:33:36 time: 0.9187 data_time: 0.0512 memory: 16201 loss_prob: 0.5439 loss_thr: 0.3684 loss_db: 0.0948 loss: 1.0071 2022/08/30 12:00:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:00:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:00:30 - mmengine - INFO - Epoch(train) [493][5/63] lr: 4.3515e-03 eta: 17:33:36 time: 1.0794 data_time: 0.2265 memory: 16201 loss_prob: 0.4988 loss_thr: 0.3410 loss_db: 0.0856 loss: 0.9254 2022/08/30 12:00:34 - mmengine - INFO - Epoch(train) [493][10/63] lr: 4.3515e-03 eta: 17:33:06 time: 1.0096 data_time: 0.1940 memory: 16201 loss_prob: 0.5437 loss_thr: 0.3668 loss_db: 0.0957 loss: 1.0062 2022/08/30 12:00:38 - mmengine - INFO - Epoch(train) [493][15/63] lr: 4.3515e-03 eta: 17:33:06 time: 0.8447 data_time: 0.0457 memory: 16201 loss_prob: 0.5527 loss_thr: 0.3782 loss_db: 0.0949 loss: 1.0259 2022/08/30 12:00:43 - mmengine - INFO - Epoch(train) [493][20/63] lr: 4.3515e-03 eta: 17:32:44 time: 0.8837 data_time: 0.0384 memory: 16201 loss_prob: 0.5465 loss_thr: 0.3791 loss_db: 0.0948 loss: 1.0205 2022/08/30 12:00:47 - mmengine - INFO - Epoch(train) [493][25/63] lr: 4.3515e-03 eta: 17:32:44 time: 0.9036 data_time: 0.0294 memory: 16201 loss_prob: 0.4984 loss_thr: 0.3589 loss_db: 0.0899 loss: 0.9471 2022/08/30 12:00:52 - mmengine - INFO - Epoch(train) [493][30/63] lr: 4.3515e-03 eta: 17:32:23 time: 0.9580 data_time: 0.0438 memory: 16201 loss_prob: 0.4892 loss_thr: 0.3405 loss_db: 0.0880 loss: 0.9177 2022/08/30 12:00:57 - mmengine - INFO - Epoch(train) [493][35/63] lr: 4.3515e-03 eta: 17:32:23 time: 0.9331 data_time: 0.0447 memory: 16201 loss_prob: 0.5428 loss_thr: 0.3587 loss_db: 0.0950 loss: 0.9965 2022/08/30 12:01:01 - mmengine - INFO - Epoch(train) [493][40/63] lr: 4.3515e-03 eta: 17:32:01 time: 0.8786 data_time: 0.0323 memory: 16201 loss_prob: 0.5652 loss_thr: 0.3871 loss_db: 0.0974 loss: 1.0497 2022/08/30 12:01:06 - mmengine - INFO - Epoch(train) [493][45/63] lr: 4.3515e-03 eta: 17:32:01 time: 0.9185 data_time: 0.0662 memory: 16201 loss_prob: 0.5775 loss_thr: 0.3942 loss_db: 0.1006 loss: 1.0722 2022/08/30 12:01:10 - mmengine - INFO - Epoch(train) [493][50/63] lr: 4.3515e-03 eta: 17:31:39 time: 0.8743 data_time: 0.0721 memory: 16201 loss_prob: 0.5424 loss_thr: 0.3712 loss_db: 0.0934 loss: 1.0070 2022/08/30 12:01:14 - mmengine - INFO - Epoch(train) [493][55/63] lr: 4.3515e-03 eta: 17:31:39 time: 0.8390 data_time: 0.0313 memory: 16201 loss_prob: 0.5211 loss_thr: 0.3662 loss_db: 0.0886 loss: 0.9759 2022/08/30 12:01:19 - mmengine - INFO - Epoch(train) [493][60/63] lr: 4.3515e-03 eta: 17:31:17 time: 0.8616 data_time: 0.0517 memory: 16201 loss_prob: 0.5400 loss_thr: 0.3790 loss_db: 0.0940 loss: 1.0131 2022/08/30 12:01:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:01:27 - mmengine - INFO - Epoch(train) [494][5/63] lr: 4.3460e-03 eta: 17:31:17 time: 1.0402 data_time: 0.1893 memory: 16201 loss_prob: 0.5774 loss_thr: 0.3913 loss_db: 0.1002 loss: 1.0688 2022/08/30 12:01:32 - mmengine - INFO - Epoch(train) [494][10/63] lr: 4.3460e-03 eta: 17:30:47 time: 1.0150 data_time: 0.2156 memory: 16201 loss_prob: 0.5672 loss_thr: 0.3887 loss_db: 0.1001 loss: 1.0560 2022/08/30 12:01:36 - mmengine - INFO - Epoch(train) [494][15/63] lr: 4.3460e-03 eta: 17:30:47 time: 0.8304 data_time: 0.0525 memory: 16201 loss_prob: 0.5379 loss_thr: 0.3742 loss_db: 0.0956 loss: 1.0077 2022/08/30 12:01:40 - mmengine - INFO - Epoch(train) [494][20/63] lr: 4.3460e-03 eta: 17:30:24 time: 0.8308 data_time: 0.0337 memory: 16201 loss_prob: 0.5542 loss_thr: 0.3808 loss_db: 0.0968 loss: 1.0318 2022/08/30 12:01:44 - mmengine - INFO - Epoch(train) [494][25/63] lr: 4.3460e-03 eta: 17:30:24 time: 0.8701 data_time: 0.0511 memory: 16201 loss_prob: 0.5463 loss_thr: 0.3859 loss_db: 0.0949 loss: 1.0271 2022/08/30 12:01:48 - mmengine - INFO - Epoch(train) [494][30/63] lr: 4.3460e-03 eta: 17:30:02 time: 0.8429 data_time: 0.0445 memory: 16201 loss_prob: 0.4966 loss_thr: 0.3674 loss_db: 0.0870 loss: 0.9510 2022/08/30 12:01:53 - mmengine - INFO - Epoch(train) [494][35/63] lr: 4.3460e-03 eta: 17:30:02 time: 0.8267 data_time: 0.0225 memory: 16201 loss_prob: 0.4780 loss_thr: 0.3442 loss_db: 0.0861 loss: 0.9083 2022/08/30 12:01:58 - mmengine - INFO - Epoch(train) [494][40/63] lr: 4.3460e-03 eta: 17:29:41 time: 0.9341 data_time: 0.1083 memory: 16201 loss_prob: 0.6684 loss_thr: 0.3799 loss_db: 0.1079 loss: 1.1562 2022/08/30 12:02:02 - mmengine - INFO - Epoch(train) [494][45/63] lr: 4.3460e-03 eta: 17:29:41 time: 0.9322 data_time: 0.1185 memory: 16201 loss_prob: 0.7217 loss_thr: 0.4059 loss_db: 0.1155 loss: 1.2432 2022/08/30 12:02:07 - mmengine - INFO - Epoch(train) [494][50/63] lr: 4.3460e-03 eta: 17:29:19 time: 0.8733 data_time: 0.0372 memory: 16201 loss_prob: 0.6458 loss_thr: 0.3826 loss_db: 0.1073 loss: 1.1357 2022/08/30 12:02:11 - mmengine - INFO - Epoch(train) [494][55/63] lr: 4.3460e-03 eta: 17:29:19 time: 0.8805 data_time: 0.0447 memory: 16201 loss_prob: 0.7970 loss_thr: 0.4005 loss_db: 0.1308 loss: 1.3283 2022/08/30 12:02:15 - mmengine - INFO - Epoch(train) [494][60/63] lr: 4.3460e-03 eta: 17:28:57 time: 0.8690 data_time: 0.0444 memory: 16201 loss_prob: 1.0530 loss_thr: 0.4416 loss_db: 0.1882 loss: 1.6828 2022/08/30 12:02:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:02:24 - mmengine - INFO - Epoch(train) [495][5/63] lr: 4.3405e-03 eta: 17:28:57 time: 1.0030 data_time: 0.2099 memory: 16201 loss_prob: 1.1407 loss_thr: 0.4713 loss_db: 0.1834 loss: 1.7953 2022/08/30 12:02:28 - mmengine - INFO - Epoch(train) [495][10/63] lr: 4.3405e-03 eta: 17:28:27 time: 1.0475 data_time: 0.2265 memory: 16201 loss_prob: 0.9540 loss_thr: 0.4756 loss_db: 0.1499 loss: 1.5795 2022/08/30 12:02:32 - mmengine - INFO - Epoch(train) [495][15/63] lr: 4.3405e-03 eta: 17:28:27 time: 0.8437 data_time: 0.0280 memory: 16201 loss_prob: 1.0246 loss_thr: 0.4928 loss_db: 0.1521 loss: 1.6695 2022/08/30 12:02:36 - mmengine - INFO - Epoch(train) [495][20/63] lr: 4.3405e-03 eta: 17:28:05 time: 0.8349 data_time: 0.0193 memory: 16201 loss_prob: 1.0463 loss_thr: 0.4916 loss_db: 0.1520 loss: 1.6899 2022/08/30 12:02:41 - mmengine - INFO - Epoch(train) [495][25/63] lr: 4.3405e-03 eta: 17:28:05 time: 0.8514 data_time: 0.0476 memory: 16201 loss_prob: 0.9213 loss_thr: 0.5052 loss_db: 0.1475 loss: 1.5740 2022/08/30 12:02:45 - mmengine - INFO - Epoch(train) [495][30/63] lr: 4.3405e-03 eta: 17:27:43 time: 0.8811 data_time: 0.0487 memory: 16201 loss_prob: 0.8820 loss_thr: 0.5135 loss_db: 0.1482 loss: 1.5438 2022/08/30 12:02:49 - mmengine - INFO - Epoch(train) [495][35/63] lr: 4.3405e-03 eta: 17:27:43 time: 0.8880 data_time: 0.0371 memory: 16201 loss_prob: 0.8842 loss_thr: 0.5044 loss_db: 0.1430 loss: 1.5316 2022/08/30 12:02:54 - mmengine - INFO - Epoch(train) [495][40/63] lr: 4.3405e-03 eta: 17:27:22 time: 0.9037 data_time: 0.0650 memory: 16201 loss_prob: 0.7712 loss_thr: 0.4636 loss_db: 0.1245 loss: 1.3593 2022/08/30 12:02:58 - mmengine - INFO - Epoch(train) [495][45/63] lr: 4.3405e-03 eta: 17:27:22 time: 0.8845 data_time: 0.0657 memory: 16201 loss_prob: 0.7904 loss_thr: 0.4493 loss_db: 0.1278 loss: 1.3676 2022/08/30 12:03:03 - mmengine - INFO - Epoch(train) [495][50/63] lr: 4.3405e-03 eta: 17:27:00 time: 0.8815 data_time: 0.0459 memory: 16201 loss_prob: 0.7654 loss_thr: 0.4302 loss_db: 0.1218 loss: 1.3174 2022/08/30 12:03:07 - mmengine - INFO - Epoch(train) [495][55/63] lr: 4.3405e-03 eta: 17:27:00 time: 0.9020 data_time: 0.0427 memory: 16201 loss_prob: 0.6826 loss_thr: 0.4118 loss_db: 0.1153 loss: 1.2097 2022/08/30 12:03:12 - mmengine - INFO - Epoch(train) [495][60/63] lr: 4.3405e-03 eta: 17:26:38 time: 0.8760 data_time: 0.0325 memory: 16201 loss_prob: 0.7721 loss_thr: 0.4481 loss_db: 0.1308 loss: 1.3511 2022/08/30 12:03:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:03:21 - mmengine - INFO - Epoch(train) [496][5/63] lr: 4.3349e-03 eta: 17:26:38 time: 1.0644 data_time: 0.2053 memory: 16201 loss_prob: 0.7451 loss_thr: 0.4532 loss_db: 0.1211 loss: 1.3194 2022/08/30 12:03:25 - mmengine - INFO - Epoch(train) [496][10/63] lr: 4.3349e-03 eta: 17:26:10 time: 1.1441 data_time: 0.2533 memory: 16201 loss_prob: 0.6729 loss_thr: 0.4075 loss_db: 0.1138 loss: 1.1942 2022/08/30 12:03:29 - mmengine - INFO - Epoch(train) [496][15/63] lr: 4.3349e-03 eta: 17:26:10 time: 0.8539 data_time: 0.0637 memory: 16201 loss_prob: 0.6884 loss_thr: 0.4035 loss_db: 0.1149 loss: 1.2069 2022/08/30 12:03:34 - mmengine - INFO - Epoch(train) [496][20/63] lr: 4.3349e-03 eta: 17:25:48 time: 0.8546 data_time: 0.0271 memory: 16201 loss_prob: 0.7039 loss_thr: 0.4202 loss_db: 0.1170 loss: 1.2411 2022/08/30 12:03:38 - mmengine - INFO - Epoch(train) [496][25/63] lr: 4.3349e-03 eta: 17:25:48 time: 0.9022 data_time: 0.0489 memory: 16201 loss_prob: 0.7187 loss_thr: 0.4280 loss_db: 0.1210 loss: 1.2677 2022/08/30 12:03:43 - mmengine - INFO - Epoch(train) [496][30/63] lr: 4.3349e-03 eta: 17:25:26 time: 0.8825 data_time: 0.0355 memory: 16201 loss_prob: 0.7564 loss_thr: 0.4302 loss_db: 0.1308 loss: 1.3174 2022/08/30 12:03:47 - mmengine - INFO - Epoch(train) [496][35/63] lr: 4.3349e-03 eta: 17:25:26 time: 0.8529 data_time: 0.0190 memory: 16201 loss_prob: 0.7273 loss_thr: 0.4271 loss_db: 0.1253 loss: 1.2797 2022/08/30 12:03:52 - mmengine - INFO - Epoch(train) [496][40/63] lr: 4.3349e-03 eta: 17:25:05 time: 0.8984 data_time: 0.0300 memory: 16201 loss_prob: 0.7501 loss_thr: 0.4483 loss_db: 0.1262 loss: 1.3246 2022/08/30 12:03:56 - mmengine - INFO - Epoch(train) [496][45/63] lr: 4.3349e-03 eta: 17:25:05 time: 0.9101 data_time: 0.0359 memory: 16201 loss_prob: 0.7908 loss_thr: 0.4453 loss_db: 0.1320 loss: 1.3681 2022/08/30 12:04:00 - mmengine - INFO - Epoch(train) [496][50/63] lr: 4.3349e-03 eta: 17:24:43 time: 0.8549 data_time: 0.0344 memory: 16201 loss_prob: 0.7520 loss_thr: 0.4264 loss_db: 0.1266 loss: 1.3051 2022/08/30 12:04:04 - mmengine - INFO - Epoch(train) [496][55/63] lr: 4.3349e-03 eta: 17:24:43 time: 0.8532 data_time: 0.0292 memory: 16201 loss_prob: 0.7469 loss_thr: 0.4382 loss_db: 0.1266 loss: 1.3117 2022/08/30 12:04:09 - mmengine - INFO - Epoch(train) [496][60/63] lr: 4.3349e-03 eta: 17:24:21 time: 0.8528 data_time: 0.0357 memory: 16201 loss_prob: 0.7222 loss_thr: 0.4343 loss_db: 0.1208 loss: 1.2774 2022/08/30 12:04:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:04:17 - mmengine - INFO - Epoch(train) [497][5/63] lr: 4.3294e-03 eta: 17:24:21 time: 0.9741 data_time: 0.1810 memory: 16201 loss_prob: 0.7150 loss_thr: 0.4433 loss_db: 0.1218 loss: 1.2801 2022/08/30 12:04:21 - mmengine - INFO - Epoch(train) [497][10/63] lr: 4.3294e-03 eta: 17:23:51 time: 1.0254 data_time: 0.2014 memory: 16201 loss_prob: 0.6742 loss_thr: 0.4255 loss_db: 0.1153 loss: 1.2150 2022/08/30 12:04:25 - mmengine - INFO - Epoch(train) [497][15/63] lr: 4.3294e-03 eta: 17:23:51 time: 0.8584 data_time: 0.0365 memory: 16201 loss_prob: 0.6406 loss_thr: 0.4186 loss_db: 0.1124 loss: 1.1715 2022/08/30 12:04:30 - mmengine - INFO - Epoch(train) [497][20/63] lr: 4.3294e-03 eta: 17:23:28 time: 0.8250 data_time: 0.0229 memory: 16201 loss_prob: 0.6702 loss_thr: 0.4369 loss_db: 0.1166 loss: 1.2237 2022/08/30 12:04:34 - mmengine - INFO - Epoch(train) [497][25/63] lr: 4.3294e-03 eta: 17:23:28 time: 0.8496 data_time: 0.0385 memory: 16201 loss_prob: 0.6688 loss_thr: 0.4288 loss_db: 0.1155 loss: 1.2131 2022/08/30 12:04:38 - mmengine - INFO - Epoch(train) [497][30/63] lr: 4.3294e-03 eta: 17:23:06 time: 0.8602 data_time: 0.0371 memory: 16201 loss_prob: 0.6180 loss_thr: 0.3965 loss_db: 0.1055 loss: 1.1200 2022/08/30 12:04:42 - mmengine - INFO - Epoch(train) [497][35/63] lr: 4.3294e-03 eta: 17:23:06 time: 0.8337 data_time: 0.0373 memory: 16201 loss_prob: 0.6074 loss_thr: 0.3908 loss_db: 0.1001 loss: 1.0983 2022/08/30 12:04:47 - mmengine - INFO - Epoch(train) [497][40/63] lr: 4.3294e-03 eta: 17:22:44 time: 0.8572 data_time: 0.0483 memory: 16201 loss_prob: 0.6911 loss_thr: 0.4123 loss_db: 0.1114 loss: 1.2148 2022/08/30 12:04:52 - mmengine - INFO - Epoch(train) [497][45/63] lr: 4.3294e-03 eta: 17:22:44 time: 0.9381 data_time: 0.0464 memory: 16201 loss_prob: 0.6866 loss_thr: 0.4311 loss_db: 0.1126 loss: 1.2303 2022/08/30 12:04:56 - mmengine - INFO - Epoch(train) [497][50/63] lr: 4.3294e-03 eta: 17:22:23 time: 0.8993 data_time: 0.0491 memory: 16201 loss_prob: 0.6392 loss_thr: 0.4198 loss_db: 0.1097 loss: 1.1687 2022/08/30 12:05:00 - mmengine - INFO - Epoch(train) [497][55/63] lr: 4.3294e-03 eta: 17:22:23 time: 0.8204 data_time: 0.0459 memory: 16201 loss_prob: 0.6582 loss_thr: 0.4096 loss_db: 0.1108 loss: 1.1787 2022/08/30 12:05:04 - mmengine - INFO - Epoch(train) [497][60/63] lr: 4.3294e-03 eta: 17:22:01 time: 0.8789 data_time: 0.0394 memory: 16201 loss_prob: 0.6981 loss_thr: 0.4092 loss_db: 0.1161 loss: 1.2235 2022/08/30 12:05:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:05:13 - mmengine - INFO - Epoch(train) [498][5/63] lr: 4.3238e-03 eta: 17:22:01 time: 1.0630 data_time: 0.1971 memory: 16201 loss_prob: 0.6519 loss_thr: 0.3800 loss_db: 0.1124 loss: 1.1443 2022/08/30 12:05:17 - mmengine - INFO - Epoch(train) [498][10/63] lr: 4.3238e-03 eta: 17:21:32 time: 1.0427 data_time: 0.2039 memory: 16201 loss_prob: 0.7655 loss_thr: 0.4198 loss_db: 0.1323 loss: 1.3176 2022/08/30 12:05:22 - mmengine - INFO - Epoch(train) [498][15/63] lr: 4.3238e-03 eta: 17:21:32 time: 0.8948 data_time: 0.0312 memory: 16201 loss_prob: 0.8832 loss_thr: 0.4317 loss_db: 0.1395 loss: 1.4544 2022/08/30 12:05:27 - mmengine - INFO - Epoch(train) [498][20/63] lr: 4.3238e-03 eta: 17:21:11 time: 0.9281 data_time: 0.0315 memory: 16201 loss_prob: 0.7897 loss_thr: 0.4079 loss_db: 0.1209 loss: 1.3185 2022/08/30 12:05:31 - mmengine - INFO - Epoch(train) [498][25/63] lr: 4.3238e-03 eta: 17:21:11 time: 0.9131 data_time: 0.0381 memory: 16201 loss_prob: 0.7012 loss_thr: 0.4228 loss_db: 0.1180 loss: 1.2419 2022/08/30 12:05:35 - mmengine - INFO - Epoch(train) [498][30/63] lr: 4.3238e-03 eta: 17:20:49 time: 0.8396 data_time: 0.0374 memory: 16201 loss_prob: 0.7253 loss_thr: 0.4555 loss_db: 0.1260 loss: 1.3068 2022/08/30 12:05:39 - mmengine - INFO - Epoch(train) [498][35/63] lr: 4.3238e-03 eta: 17:20:49 time: 0.8144 data_time: 0.0314 memory: 16201 loss_prob: 0.7368 loss_thr: 0.4626 loss_db: 0.1267 loss: 1.3260 2022/08/30 12:05:44 - mmengine - INFO - Epoch(train) [498][40/63] lr: 4.3238e-03 eta: 17:20:27 time: 0.8757 data_time: 0.0369 memory: 16201 loss_prob: 0.6531 loss_thr: 0.4218 loss_db: 0.1106 loss: 1.1855 2022/08/30 12:05:48 - mmengine - INFO - Epoch(train) [498][45/63] lr: 4.3238e-03 eta: 17:20:27 time: 0.8557 data_time: 0.0387 memory: 16201 loss_prob: 0.6289 loss_thr: 0.4252 loss_db: 0.1084 loss: 1.1626 2022/08/30 12:05:52 - mmengine - INFO - Epoch(train) [498][50/63] lr: 4.3238e-03 eta: 17:20:04 time: 0.7812 data_time: 0.0265 memory: 16201 loss_prob: 0.6488 loss_thr: 0.4335 loss_db: 0.1123 loss: 1.1945 2022/08/30 12:05:56 - mmengine - INFO - Epoch(train) [498][55/63] lr: 4.3238e-03 eta: 17:20:04 time: 0.7795 data_time: 0.0265 memory: 16201 loss_prob: 0.6051 loss_thr: 0.4015 loss_db: 0.1051 loss: 1.1117 2022/08/30 12:06:01 - mmengine - INFO - Epoch(train) [498][60/63] lr: 4.3238e-03 eta: 17:19:43 time: 0.8815 data_time: 0.0349 memory: 16201 loss_prob: 0.5884 loss_thr: 0.3830 loss_db: 0.1004 loss: 1.0719 2022/08/30 12:06:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:06:09 - mmengine - INFO - Epoch(train) [499][5/63] lr: 4.3183e-03 eta: 17:19:43 time: 1.0189 data_time: 0.2417 memory: 16201 loss_prob: 0.6491 loss_thr: 0.4111 loss_db: 0.1064 loss: 1.1666 2022/08/30 12:06:14 - mmengine - INFO - Epoch(train) [499][10/63] lr: 4.3183e-03 eta: 17:19:14 time: 1.1017 data_time: 0.2594 memory: 16201 loss_prob: 0.6457 loss_thr: 0.4207 loss_db: 0.1090 loss: 1.1755 2022/08/30 12:06:18 - mmengine - INFO - Epoch(train) [499][15/63] lr: 4.3183e-03 eta: 17:19:14 time: 0.9009 data_time: 0.0737 memory: 16201 loss_prob: 0.6592 loss_thr: 0.4154 loss_db: 0.1097 loss: 1.1843 2022/08/30 12:06:25 - mmengine - INFO - Epoch(train) [499][20/63] lr: 4.3183e-03 eta: 17:18:56 time: 1.1127 data_time: 0.0687 memory: 16201 loss_prob: 0.6620 loss_thr: 0.4209 loss_db: 0.1146 loss: 1.1975 2022/08/30 12:06:29 - mmengine - INFO - Epoch(train) [499][25/63] lr: 4.3183e-03 eta: 17:18:56 time: 1.0830 data_time: 0.0454 memory: 16201 loss_prob: 0.6251 loss_thr: 0.4195 loss_db: 0.1100 loss: 1.1546 2022/08/30 12:06:33 - mmengine - INFO - Epoch(train) [499][30/63] lr: 4.3183e-03 eta: 17:18:34 time: 0.8557 data_time: 0.0329 memory: 16201 loss_prob: 0.6245 loss_thr: 0.4175 loss_db: 0.1075 loss: 1.1495 2022/08/30 12:06:37 - mmengine - INFO - Epoch(train) [499][35/63] lr: 4.3183e-03 eta: 17:18:34 time: 0.8228 data_time: 0.0238 memory: 16201 loss_prob: 0.6109 loss_thr: 0.3975 loss_db: 0.1052 loss: 1.1136 2022/08/30 12:06:43 - mmengine - INFO - Epoch(train) [499][40/63] lr: 4.3183e-03 eta: 17:18:13 time: 0.9588 data_time: 0.0480 memory: 16201 loss_prob: 0.5783 loss_thr: 0.3861 loss_db: 0.0993 loss: 1.0637 2022/08/30 12:06:47 - mmengine - INFO - Epoch(train) [499][45/63] lr: 4.3183e-03 eta: 17:18:13 time: 0.9645 data_time: 0.0549 memory: 16201 loss_prob: 0.5527 loss_thr: 0.3830 loss_db: 0.0954 loss: 1.0312 2022/08/30 12:06:51 - mmengine - INFO - Epoch(train) [499][50/63] lr: 4.3183e-03 eta: 17:17:51 time: 0.8274 data_time: 0.0403 memory: 16201 loss_prob: 0.5378 loss_thr: 0.3865 loss_db: 0.0928 loss: 1.0171 2022/08/30 12:06:55 - mmengine - INFO - Epoch(train) [499][55/63] lr: 4.3183e-03 eta: 17:17:51 time: 0.8598 data_time: 0.0361 memory: 16201 loss_prob: 0.5149 loss_thr: 0.3733 loss_db: 0.0888 loss: 0.9771 2022/08/30 12:07:00 - mmengine - INFO - Epoch(train) [499][60/63] lr: 4.3183e-03 eta: 17:17:30 time: 0.8864 data_time: 0.0345 memory: 16201 loss_prob: 0.5472 loss_thr: 0.3779 loss_db: 0.0927 loss: 1.0179 2022/08/30 12:07:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:07:09 - mmengine - INFO - Epoch(train) [500][5/63] lr: 4.3127e-03 eta: 17:17:30 time: 1.1233 data_time: 0.2199 memory: 16201 loss_prob: 0.6066 loss_thr: 0.3962 loss_db: 0.1019 loss: 1.1047 2022/08/30 12:07:14 - mmengine - INFO - Epoch(train) [500][10/63] lr: 4.3127e-03 eta: 17:17:00 time: 1.0319 data_time: 0.2235 memory: 16201 loss_prob: 0.6204 loss_thr: 0.3958 loss_db: 0.1052 loss: 1.1214 2022/08/30 12:07:18 - mmengine - INFO - Epoch(train) [500][15/63] lr: 4.3127e-03 eta: 17:17:00 time: 0.8617 data_time: 0.0396 memory: 16201 loss_prob: 0.6568 loss_thr: 0.3934 loss_db: 0.1112 loss: 1.1613 2022/08/30 12:07:24 - mmengine - INFO - Epoch(train) [500][20/63] lr: 4.3127e-03 eta: 17:16:40 time: 0.9909 data_time: 0.0331 memory: 16201 loss_prob: 0.6424 loss_thr: 0.3839 loss_db: 0.1099 loss: 1.1362 2022/08/30 12:07:28 - mmengine - INFO - Epoch(train) [500][25/63] lr: 4.3127e-03 eta: 17:16:40 time: 0.9700 data_time: 0.0450 memory: 16201 loss_prob: 0.6607 loss_thr: 0.4063 loss_db: 0.1100 loss: 1.1770 2022/08/30 12:07:32 - mmengine - INFO - Epoch(train) [500][30/63] lr: 4.3127e-03 eta: 17:16:18 time: 0.8333 data_time: 0.0291 memory: 16201 loss_prob: 0.6761 loss_thr: 0.4316 loss_db: 0.1128 loss: 1.2205 2022/08/30 12:07:37 - mmengine - INFO - Epoch(train) [500][35/63] lr: 4.3127e-03 eta: 17:16:18 time: 0.8772 data_time: 0.0199 memory: 16201 loss_prob: 0.6658 loss_thr: 0.4291 loss_db: 0.1148 loss: 1.2097 2022/08/30 12:07:41 - mmengine - INFO - Epoch(train) [500][40/63] lr: 4.3127e-03 eta: 17:15:57 time: 0.9088 data_time: 0.0440 memory: 16201 loss_prob: 0.6252 loss_thr: 0.4064 loss_db: 0.1068 loss: 1.1384 2022/08/30 12:07:45 - mmengine - INFO - Epoch(train) [500][45/63] lr: 4.3127e-03 eta: 17:15:57 time: 0.8580 data_time: 0.0452 memory: 16201 loss_prob: 0.5870 loss_thr: 0.3905 loss_db: 0.1001 loss: 1.0776 2022/08/30 12:07:49 - mmengine - INFO - Epoch(train) [500][50/63] lr: 4.3127e-03 eta: 17:15:35 time: 0.8548 data_time: 0.0388 memory: 16201 loss_prob: 0.5231 loss_thr: 0.3665 loss_db: 0.0927 loss: 0.9823 2022/08/30 12:07:54 - mmengine - INFO - Epoch(train) [500][55/63] lr: 4.3127e-03 eta: 17:15:35 time: 0.8917 data_time: 0.0655 memory: 16201 loss_prob: 0.5803 loss_thr: 0.3925 loss_db: 0.1016 loss: 1.0743 2022/08/30 12:07:58 - mmengine - INFO - Epoch(train) [500][60/63] lr: 4.3127e-03 eta: 17:15:13 time: 0.8878 data_time: 0.0613 memory: 16201 loss_prob: 0.6141 loss_thr: 0.4063 loss_db: 0.1048 loss: 1.1252 2022/08/30 12:08:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:08:01 - mmengine - INFO - Saving checkpoint at 500 epochs 2022/08/30 12:08:09 - mmengine - INFO - Epoch(val) [500][5/32] eta: 17:15:13 time: 0.6027 data_time: 0.0893 memory: 16201 2022/08/30 12:08:12 - mmengine - INFO - Epoch(val) [500][10/32] eta: 0:00:15 time: 0.7004 data_time: 0.1356 memory: 15734 2022/08/30 12:08:15 - mmengine - INFO - Epoch(val) [500][15/32] eta: 0:00:15 time: 0.6171 data_time: 0.0596 memory: 15734 2022/08/30 12:08:19 - mmengine - INFO - Epoch(val) [500][20/32] eta: 0:00:07 time: 0.6056 data_time: 0.0546 memory: 15734 2022/08/30 12:08:22 - mmengine - INFO - Epoch(val) [500][25/32] eta: 0:00:07 time: 0.7074 data_time: 0.0683 memory: 15734 2022/08/30 12:08:25 - mmengine - INFO - Epoch(val) [500][30/32] eta: 0:00:01 time: 0.6706 data_time: 0.0322 memory: 15734 2022/08/30 12:08:26 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 12:08:26 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8450, precision: 0.7571, hmean: 0.7986 2022/08/30 12:08:26 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8450, precision: 0.8073, hmean: 0.8257 2022/08/30 12:08:26 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8435, precision: 0.8403, hmean: 0.8419 2022/08/30 12:08:26 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8392, precision: 0.8663, hmean: 0.8525 2022/08/30 12:08:26 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8219, precision: 0.8895, hmean: 0.8544 2022/08/30 12:08:26 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7078, precision: 0.9351, hmean: 0.8057 2022/08/30 12:08:26 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0881, precision: 0.9839, hmean: 0.1617 2022/08/30 12:08:26 - mmengine - INFO - Epoch(val) [500][32/32] icdar/precision: 0.8895 icdar/recall: 0.8219 icdar/hmean: 0.8544 2022/08/30 12:08:33 - mmengine - INFO - Epoch(train) [501][5/63] lr: 4.3072e-03 eta: 0:00:01 time: 1.0358 data_time: 0.2041 memory: 16201 loss_prob: 0.5608 loss_thr: 0.3933 loss_db: 0.0976 loss: 1.0518 2022/08/30 12:08:37 - mmengine - INFO - Epoch(train) [501][10/63] lr: 4.3072e-03 eta: 17:14:45 time: 1.0734 data_time: 0.2144 memory: 16201 loss_prob: 0.5456 loss_thr: 0.3760 loss_db: 0.0962 loss: 1.0178 2022/08/30 12:08:43 - mmengine - INFO - Epoch(train) [501][15/63] lr: 4.3072e-03 eta: 17:14:45 time: 0.9861 data_time: 0.0536 memory: 16201 loss_prob: 0.4953 loss_thr: 0.3469 loss_db: 0.0879 loss: 0.9301 2022/08/30 12:08:47 - mmengine - INFO - Epoch(train) [501][20/63] lr: 4.3072e-03 eta: 17:14:25 time: 0.9917 data_time: 0.0598 memory: 16201 loss_prob: 0.4797 loss_thr: 0.3559 loss_db: 0.0842 loss: 0.9197 2022/08/30 12:08:51 - mmengine - INFO - Epoch(train) [501][25/63] lr: 4.3072e-03 eta: 17:14:25 time: 0.8739 data_time: 0.0384 memory: 16201 loss_prob: 0.5388 loss_thr: 0.3804 loss_db: 0.0917 loss: 1.0109 2022/08/30 12:08:56 - mmengine - INFO - Epoch(train) [501][30/63] lr: 4.3072e-03 eta: 17:14:03 time: 0.8960 data_time: 0.0377 memory: 16201 loss_prob: 0.5684 loss_thr: 0.3731 loss_db: 0.0969 loss: 1.0385 2022/08/30 12:09:00 - mmengine - INFO - Epoch(train) [501][35/63] lr: 4.3072e-03 eta: 17:14:03 time: 0.8785 data_time: 0.0381 memory: 16201 loss_prob: 0.5933 loss_thr: 0.3784 loss_db: 0.1012 loss: 1.0729 2022/08/30 12:09:04 - mmengine - INFO - Epoch(train) [501][40/63] lr: 4.3072e-03 eta: 17:13:41 time: 0.8207 data_time: 0.0248 memory: 16201 loss_prob: 0.5760 loss_thr: 0.3797 loss_db: 0.0990 loss: 1.0547 2022/08/30 12:09:09 - mmengine - INFO - Epoch(train) [501][45/63] lr: 4.3072e-03 eta: 17:13:41 time: 0.8623 data_time: 0.0410 memory: 16201 loss_prob: 0.5936 loss_thr: 0.3913 loss_db: 0.1057 loss: 1.0906 2022/08/30 12:09:13 - mmengine - INFO - Epoch(train) [501][50/63] lr: 4.3072e-03 eta: 17:13:20 time: 0.9311 data_time: 0.0538 memory: 16201 loss_prob: 0.6049 loss_thr: 0.3967 loss_db: 0.1062 loss: 1.1078 2022/08/30 12:09:18 - mmengine - INFO - Epoch(train) [501][55/63] lr: 4.3072e-03 eta: 17:13:20 time: 0.8905 data_time: 0.0331 memory: 16201 loss_prob: 0.5539 loss_thr: 0.3773 loss_db: 0.0960 loss: 1.0272 2022/08/30 12:09:23 - mmengine - INFO - Epoch(train) [501][60/63] lr: 4.3072e-03 eta: 17:13:01 time: 0.9878 data_time: 0.0443 memory: 16201 loss_prob: 0.5423 loss_thr: 0.3749 loss_db: 0.0953 loss: 1.0126 2022/08/30 12:09:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:09:31 - mmengine - INFO - Epoch(train) [502][5/63] lr: 4.3016e-03 eta: 17:13:01 time: 1.0304 data_time: 0.2030 memory: 16201 loss_prob: 0.5277 loss_thr: 0.3644 loss_db: 0.0930 loss: 0.9851 2022/08/30 12:09:36 - mmengine - INFO - Epoch(train) [502][10/63] lr: 4.3016e-03 eta: 17:12:31 time: 1.0069 data_time: 0.1930 memory: 16201 loss_prob: 0.5447 loss_thr: 0.3640 loss_db: 0.0937 loss: 1.0024 2022/08/30 12:09:40 - mmengine - INFO - Epoch(train) [502][15/63] lr: 4.3016e-03 eta: 17:12:31 time: 0.8303 data_time: 0.0321 memory: 16201 loss_prob: 0.5796 loss_thr: 0.4040 loss_db: 0.0953 loss: 1.0789 2022/08/30 12:09:45 - mmengine - INFO - Epoch(train) [502][20/63] lr: 4.3016e-03 eta: 17:12:10 time: 0.9338 data_time: 0.0398 memory: 16201 loss_prob: 0.6372 loss_thr: 0.4060 loss_db: 0.1058 loss: 1.1489 2022/08/30 12:09:49 - mmengine - INFO - Epoch(train) [502][25/63] lr: 4.3016e-03 eta: 17:12:10 time: 0.9434 data_time: 0.0362 memory: 16201 loss_prob: 0.6732 loss_thr: 0.4031 loss_db: 0.1153 loss: 1.1916 2022/08/30 12:09:54 - mmengine - INFO - Epoch(train) [502][30/63] lr: 4.3016e-03 eta: 17:11:49 time: 0.9049 data_time: 0.0314 memory: 16201 loss_prob: 0.5973 loss_thr: 0.3955 loss_db: 0.1018 loss: 1.0946 2022/08/30 12:09:58 - mmengine - INFO - Epoch(train) [502][35/63] lr: 4.3016e-03 eta: 17:11:49 time: 0.9010 data_time: 0.0406 memory: 16201 loss_prob: 0.5747 loss_thr: 0.3970 loss_db: 0.1003 loss: 1.0720 2022/08/30 12:10:02 - mmengine - INFO - Epoch(train) [502][40/63] lr: 4.3016e-03 eta: 17:11:27 time: 0.8487 data_time: 0.0506 memory: 16201 loss_prob: 0.5458 loss_thr: 0.3870 loss_db: 0.0974 loss: 1.0302 2022/08/30 12:10:06 - mmengine - INFO - Epoch(train) [502][45/63] lr: 4.3016e-03 eta: 17:11:27 time: 0.8379 data_time: 0.0357 memory: 16201 loss_prob: 0.5069 loss_thr: 0.3673 loss_db: 0.0878 loss: 0.9619 2022/08/30 12:10:11 - mmengine - INFO - Epoch(train) [502][50/63] lr: 4.3016e-03 eta: 17:11:05 time: 0.8303 data_time: 0.0231 memory: 16201 loss_prob: 0.5822 loss_thr: 0.3869 loss_db: 0.1011 loss: 1.0702 2022/08/30 12:10:15 - mmengine - INFO - Epoch(train) [502][55/63] lr: 4.3016e-03 eta: 17:11:05 time: 0.8601 data_time: 0.0493 memory: 16201 loss_prob: 0.5489 loss_thr: 0.3725 loss_db: 0.0967 loss: 1.0181 2022/08/30 12:10:19 - mmengine - INFO - Epoch(train) [502][60/63] lr: 4.3016e-03 eta: 17:10:44 time: 0.8738 data_time: 0.0559 memory: 16201 loss_prob: 0.5117 loss_thr: 0.3687 loss_db: 0.0889 loss: 0.9692 2022/08/30 12:10:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:10:28 - mmengine - INFO - Epoch(train) [503][5/63] lr: 4.2961e-03 eta: 17:10:44 time: 1.0731 data_time: 0.2653 memory: 16201 loss_prob: 0.5509 loss_thr: 0.3806 loss_db: 0.0931 loss: 1.0246 2022/08/30 12:10:33 - mmengine - INFO - Epoch(train) [503][10/63] lr: 4.2961e-03 eta: 17:10:16 time: 1.1231 data_time: 0.2968 memory: 16201 loss_prob: 0.5591 loss_thr: 0.3942 loss_db: 0.0984 loss: 1.0517 2022/08/30 12:10:37 - mmengine - INFO - Epoch(train) [503][15/63] lr: 4.2961e-03 eta: 17:10:16 time: 0.9177 data_time: 0.0692 memory: 16201 loss_prob: 0.5760 loss_thr: 0.3884 loss_db: 0.1022 loss: 1.0666 2022/08/30 12:10:42 - mmengine - INFO - Epoch(train) [503][20/63] lr: 4.2961e-03 eta: 17:09:54 time: 0.8747 data_time: 0.0429 memory: 16201 loss_prob: 0.6129 loss_thr: 0.3877 loss_db: 0.1050 loss: 1.1056 2022/08/30 12:10:46 - mmengine - INFO - Epoch(train) [503][25/63] lr: 4.2961e-03 eta: 17:09:54 time: 0.8672 data_time: 0.0515 memory: 16201 loss_prob: 0.6085 loss_thr: 0.3936 loss_db: 0.1029 loss: 1.1050 2022/08/30 12:10:50 - mmengine - INFO - Epoch(train) [503][30/63] lr: 4.2961e-03 eta: 17:09:33 time: 0.8648 data_time: 0.0418 memory: 16201 loss_prob: 0.5393 loss_thr: 0.3725 loss_db: 0.0941 loss: 1.0059 2022/08/30 12:10:55 - mmengine - INFO - Epoch(train) [503][35/63] lr: 4.2961e-03 eta: 17:09:33 time: 0.8586 data_time: 0.0375 memory: 16201 loss_prob: 0.5387 loss_thr: 0.3687 loss_db: 0.0955 loss: 1.0028 2022/08/30 12:10:59 - mmengine - INFO - Epoch(train) [503][40/63] lr: 4.2961e-03 eta: 17:09:11 time: 0.8857 data_time: 0.0567 memory: 16201 loss_prob: 0.6982 loss_thr: 0.3914 loss_db: 0.1095 loss: 1.1990 2022/08/30 12:11:04 - mmengine - INFO - Epoch(train) [503][45/63] lr: 4.2961e-03 eta: 17:09:11 time: 0.9667 data_time: 0.0686 memory: 16201 loss_prob: 0.6609 loss_thr: 0.3604 loss_db: 0.0990 loss: 1.1203 2022/08/30 12:11:09 - mmengine - INFO - Epoch(train) [503][50/63] lr: 4.2961e-03 eta: 17:08:51 time: 0.9453 data_time: 0.0559 memory: 16201 loss_prob: 0.5692 loss_thr: 0.3623 loss_db: 0.0943 loss: 1.0258 2022/08/30 12:11:13 - mmengine - INFO - Epoch(train) [503][55/63] lr: 4.2961e-03 eta: 17:08:51 time: 0.8937 data_time: 0.0610 memory: 16201 loss_prob: 0.6114 loss_thr: 0.3872 loss_db: 0.1055 loss: 1.1041 2022/08/30 12:11:17 - mmengine - INFO - Epoch(train) [503][60/63] lr: 4.2961e-03 eta: 17:08:30 time: 0.8832 data_time: 0.0565 memory: 16201 loss_prob: 0.5510 loss_thr: 0.3658 loss_db: 0.0956 loss: 1.0124 2022/08/30 12:11:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:11:25 - mmengine - INFO - Epoch(train) [504][5/63] lr: 4.2906e-03 eta: 17:08:30 time: 0.9672 data_time: 0.1725 memory: 16201 loss_prob: 0.5379 loss_thr: 0.3644 loss_db: 0.0940 loss: 0.9962 2022/08/30 12:11:30 - mmengine - INFO - Epoch(train) [504][10/63] lr: 4.2906e-03 eta: 17:08:00 time: 1.0248 data_time: 0.1910 memory: 16201 loss_prob: 0.5287 loss_thr: 0.3624 loss_db: 0.0916 loss: 0.9826 2022/08/30 12:11:35 - mmengine - INFO - Epoch(train) [504][15/63] lr: 4.2906e-03 eta: 17:08:00 time: 0.9118 data_time: 0.0320 memory: 16201 loss_prob: 0.5629 loss_thr: 0.3840 loss_db: 0.0974 loss: 1.0443 2022/08/30 12:11:39 - mmengine - INFO - Epoch(train) [504][20/63] lr: 4.2906e-03 eta: 17:07:39 time: 0.9215 data_time: 0.0219 memory: 16201 loss_prob: 0.5991 loss_thr: 0.3983 loss_db: 0.1037 loss: 1.1010 2022/08/30 12:11:44 - mmengine - INFO - Epoch(train) [504][25/63] lr: 4.2906e-03 eta: 17:07:39 time: 0.9353 data_time: 0.0606 memory: 16201 loss_prob: 0.5973 loss_thr: 0.3890 loss_db: 0.1021 loss: 1.0884 2022/08/30 12:11:48 - mmengine - INFO - Epoch(train) [504][30/63] lr: 4.2906e-03 eta: 17:07:18 time: 0.8952 data_time: 0.0611 memory: 16201 loss_prob: 0.5973 loss_thr: 0.3719 loss_db: 0.1015 loss: 1.0706 2022/08/30 12:11:52 - mmengine - INFO - Epoch(train) [504][35/63] lr: 4.2906e-03 eta: 17:07:18 time: 0.8160 data_time: 0.0301 memory: 16201 loss_prob: 0.6123 loss_thr: 0.3989 loss_db: 0.1035 loss: 1.1147 2022/08/30 12:11:56 - mmengine - INFO - Epoch(train) [504][40/63] lr: 4.2906e-03 eta: 17:06:56 time: 0.8397 data_time: 0.0501 memory: 16201 loss_prob: 0.5794 loss_thr: 0.3982 loss_db: 0.1007 loss: 1.0782 2022/08/30 12:12:01 - mmengine - INFO - Epoch(train) [504][45/63] lr: 4.2906e-03 eta: 17:06:56 time: 0.9225 data_time: 0.0562 memory: 16201 loss_prob: 0.5262 loss_thr: 0.3604 loss_db: 0.0922 loss: 0.9788 2022/08/30 12:12:06 - mmengine - INFO - Epoch(train) [504][50/63] lr: 4.2906e-03 eta: 17:06:36 time: 0.9490 data_time: 0.0473 memory: 16201 loss_prob: 0.5122 loss_thr: 0.3558 loss_db: 0.0885 loss: 0.9565 2022/08/30 12:12:10 - mmengine - INFO - Epoch(train) [504][55/63] lr: 4.2906e-03 eta: 17:06:36 time: 0.8774 data_time: 0.0436 memory: 16201 loss_prob: 0.5167 loss_thr: 0.3587 loss_db: 0.0904 loss: 0.9658 2022/08/30 12:12:15 - mmengine - INFO - Epoch(train) [504][60/63] lr: 4.2906e-03 eta: 17:06:15 time: 0.8935 data_time: 0.0434 memory: 16201 loss_prob: 0.5276 loss_thr: 0.3776 loss_db: 0.0916 loss: 0.9968 2022/08/30 12:12:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:12:23 - mmengine - INFO - Epoch(train) [505][5/63] lr: 4.2850e-03 eta: 17:06:15 time: 1.0201 data_time: 0.1769 memory: 16201 loss_prob: 0.5885 loss_thr: 0.4003 loss_db: 0.1015 loss: 1.0903 2022/08/30 12:12:27 - mmengine - INFO - Epoch(train) [505][10/63] lr: 4.2850e-03 eta: 17:05:46 time: 1.0326 data_time: 0.2018 memory: 16201 loss_prob: 0.5845 loss_thr: 0.3953 loss_db: 0.1005 loss: 1.0804 2022/08/30 12:12:32 - mmengine - INFO - Epoch(train) [505][15/63] lr: 4.2850e-03 eta: 17:05:46 time: 0.9104 data_time: 0.0623 memory: 16201 loss_prob: 0.5981 loss_thr: 0.4042 loss_db: 0.1038 loss: 1.1060 2022/08/30 12:12:36 - mmengine - INFO - Epoch(train) [505][20/63] lr: 4.2850e-03 eta: 17:05:25 time: 0.8901 data_time: 0.0408 memory: 16201 loss_prob: 0.5801 loss_thr: 0.3791 loss_db: 0.1011 loss: 1.0602 2022/08/30 12:12:41 - mmengine - INFO - Epoch(train) [505][25/63] lr: 4.2850e-03 eta: 17:05:25 time: 0.8797 data_time: 0.0582 memory: 16201 loss_prob: 0.5753 loss_thr: 0.3811 loss_db: 0.0984 loss: 1.0548 2022/08/30 12:12:45 - mmengine - INFO - Epoch(train) [505][30/63] lr: 4.2850e-03 eta: 17:05:04 time: 0.8867 data_time: 0.0620 memory: 16201 loss_prob: 0.5153 loss_thr: 0.3593 loss_db: 0.0882 loss: 0.9628 2022/08/30 12:12:49 - mmengine - INFO - Epoch(train) [505][35/63] lr: 4.2850e-03 eta: 17:05:04 time: 0.8654 data_time: 0.0376 memory: 16201 loss_prob: 0.5187 loss_thr: 0.3695 loss_db: 0.0896 loss: 0.9778 2022/08/30 12:12:54 - mmengine - INFO - Epoch(train) [505][40/63] lr: 4.2850e-03 eta: 17:04:42 time: 0.8644 data_time: 0.0444 memory: 16201 loss_prob: 0.5722 loss_thr: 0.4017 loss_db: 0.1001 loss: 1.0740 2022/08/30 12:12:58 - mmengine - INFO - Epoch(train) [505][45/63] lr: 4.2850e-03 eta: 17:04:42 time: 0.8590 data_time: 0.0515 memory: 16201 loss_prob: 0.5460 loss_thr: 0.3925 loss_db: 0.0932 loss: 1.0317 2022/08/30 12:13:02 - mmengine - INFO - Epoch(train) [505][50/63] lr: 4.2850e-03 eta: 17:04:21 time: 0.8624 data_time: 0.0381 memory: 16201 loss_prob: 0.5027 loss_thr: 0.3663 loss_db: 0.0848 loss: 0.9538 2022/08/30 12:13:06 - mmengine - INFO - Epoch(train) [505][55/63] lr: 4.2850e-03 eta: 17:04:21 time: 0.8494 data_time: 0.0374 memory: 16201 loss_prob: 0.5460 loss_thr: 0.3702 loss_db: 0.0946 loss: 1.0108 2022/08/30 12:13:11 - mmengine - INFO - Epoch(train) [505][60/63] lr: 4.2850e-03 eta: 17:03:59 time: 0.8837 data_time: 0.0335 memory: 16201 loss_prob: 0.6018 loss_thr: 0.4017 loss_db: 0.1043 loss: 1.1078 2022/08/30 12:13:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:13:20 - mmengine - INFO - Epoch(train) [506][5/63] lr: 4.2795e-03 eta: 17:03:59 time: 1.0631 data_time: 0.1812 memory: 16201 loss_prob: 0.5757 loss_thr: 0.3998 loss_db: 0.0992 loss: 1.0747 2022/08/30 12:13:24 - mmengine - INFO - Epoch(train) [506][10/63] lr: 4.2795e-03 eta: 17:03:31 time: 1.0581 data_time: 0.2044 memory: 16201 loss_prob: 0.5707 loss_thr: 0.3915 loss_db: 0.0996 loss: 1.0618 2022/08/30 12:13:29 - mmengine - INFO - Epoch(train) [506][15/63] lr: 4.2795e-03 eta: 17:03:31 time: 0.9238 data_time: 0.0563 memory: 16201 loss_prob: 0.5757 loss_thr: 0.3908 loss_db: 0.0991 loss: 1.0656 2022/08/30 12:13:33 - mmengine - INFO - Epoch(train) [506][20/63] lr: 4.2795e-03 eta: 17:03:10 time: 0.9164 data_time: 0.0328 memory: 16201 loss_prob: 0.6128 loss_thr: 0.3883 loss_db: 0.0983 loss: 1.0994 2022/08/30 12:13:37 - mmengine - INFO - Epoch(train) [506][25/63] lr: 4.2795e-03 eta: 17:03:10 time: 0.8597 data_time: 0.0519 memory: 16201 loss_prob: 0.6241 loss_thr: 0.3853 loss_db: 0.1021 loss: 1.1115 2022/08/30 12:13:42 - mmengine - INFO - Epoch(train) [506][30/63] lr: 4.2795e-03 eta: 17:02:49 time: 0.9057 data_time: 0.0518 memory: 16201 loss_prob: 0.5561 loss_thr: 0.3748 loss_db: 0.0973 loss: 1.0283 2022/08/30 12:13:47 - mmengine - INFO - Epoch(train) [506][35/63] lr: 4.2795e-03 eta: 17:02:49 time: 0.9114 data_time: 0.0348 memory: 16201 loss_prob: 0.5260 loss_thr: 0.3546 loss_db: 0.0914 loss: 0.9720 2022/08/30 12:13:51 - mmengine - INFO - Epoch(train) [506][40/63] lr: 4.2795e-03 eta: 17:02:27 time: 0.8502 data_time: 0.0396 memory: 16201 loss_prob: 0.5268 loss_thr: 0.3419 loss_db: 0.0934 loss: 0.9621 2022/08/30 12:13:55 - mmengine - INFO - Epoch(train) [506][45/63] lr: 4.2795e-03 eta: 17:02:27 time: 0.8796 data_time: 0.0384 memory: 16201 loss_prob: 0.5325 loss_thr: 0.3474 loss_db: 0.0917 loss: 0.9716 2022/08/30 12:14:00 - mmengine - INFO - Epoch(train) [506][50/63] lr: 4.2795e-03 eta: 17:02:06 time: 0.8687 data_time: 0.0362 memory: 16201 loss_prob: 0.5337 loss_thr: 0.3667 loss_db: 0.0924 loss: 0.9929 2022/08/30 12:14:05 - mmengine - INFO - Epoch(train) [506][55/63] lr: 4.2795e-03 eta: 17:02:06 time: 1.0000 data_time: 0.0506 memory: 16201 loss_prob: 0.5637 loss_thr: 0.3936 loss_db: 0.0999 loss: 1.0572 2022/08/30 12:14:10 - mmengine - INFO - Epoch(train) [506][60/63] lr: 4.2795e-03 eta: 17:01:47 time: 0.9989 data_time: 0.0546 memory: 16201 loss_prob: 0.5478 loss_thr: 0.3788 loss_db: 0.0943 loss: 1.0209 2022/08/30 12:14:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:14:17 - mmengine - INFO - Epoch(train) [507][5/63] lr: 4.2739e-03 eta: 17:01:47 time: 0.9340 data_time: 0.1856 memory: 16201 loss_prob: 0.5150 loss_thr: 0.3684 loss_db: 0.0907 loss: 0.9741 2022/08/30 12:14:21 - mmengine - INFO - Epoch(train) [507][10/63] lr: 4.2739e-03 eta: 17:01:17 time: 0.9801 data_time: 0.1976 memory: 16201 loss_prob: 0.5766 loss_thr: 0.3861 loss_db: 0.0974 loss: 1.0601 2022/08/30 12:14:26 - mmengine - INFO - Epoch(train) [507][15/63] lr: 4.2739e-03 eta: 17:01:17 time: 0.8314 data_time: 0.0306 memory: 16201 loss_prob: 0.6034 loss_thr: 0.3919 loss_db: 0.1008 loss: 1.0961 2022/08/30 12:14:30 - mmengine - INFO - Epoch(train) [507][20/63] lr: 4.2739e-03 eta: 17:00:55 time: 0.8527 data_time: 0.0359 memory: 16201 loss_prob: 0.5315 loss_thr: 0.3682 loss_db: 0.0923 loss: 0.9919 2022/08/30 12:14:34 - mmengine - INFO - Epoch(train) [507][25/63] lr: 4.2739e-03 eta: 17:00:55 time: 0.8465 data_time: 0.0387 memory: 16201 loss_prob: 0.5326 loss_thr: 0.3631 loss_db: 0.0939 loss: 0.9896 2022/08/30 12:14:39 - mmengine - INFO - Epoch(train) [507][30/63] lr: 4.2739e-03 eta: 17:00:34 time: 0.8670 data_time: 0.0313 memory: 16201 loss_prob: 0.5040 loss_thr: 0.3620 loss_db: 0.0887 loss: 0.9547 2022/08/30 12:14:43 - mmengine - INFO - Epoch(train) [507][35/63] lr: 4.2739e-03 eta: 17:00:34 time: 0.8581 data_time: 0.0374 memory: 16201 loss_prob: 0.4712 loss_thr: 0.3577 loss_db: 0.0832 loss: 0.9121 2022/08/30 12:14:47 - mmengine - INFO - Epoch(train) [507][40/63] lr: 4.2739e-03 eta: 17:00:12 time: 0.8455 data_time: 0.0315 memory: 16201 loss_prob: 0.5428 loss_thr: 0.3773 loss_db: 0.0962 loss: 1.0163 2022/08/30 12:14:52 - mmengine - INFO - Epoch(train) [507][45/63] lr: 4.2739e-03 eta: 17:00:12 time: 0.9574 data_time: 0.0335 memory: 16201 loss_prob: 0.5683 loss_thr: 0.3844 loss_db: 0.0992 loss: 1.0519 2022/08/30 12:14:57 - mmengine - INFO - Epoch(train) [507][50/63] lr: 4.2739e-03 eta: 16:59:52 time: 0.9644 data_time: 0.0476 memory: 16201 loss_prob: 0.5143 loss_thr: 0.3529 loss_db: 0.0890 loss: 0.9562 2022/08/30 12:15:01 - mmengine - INFO - Epoch(train) [507][55/63] lr: 4.2739e-03 eta: 16:59:52 time: 0.8770 data_time: 0.0400 memory: 16201 loss_prob: 0.5207 loss_thr: 0.3467 loss_db: 0.0897 loss: 0.9570 2022/08/30 12:15:05 - mmengine - INFO - Epoch(train) [507][60/63] lr: 4.2739e-03 eta: 16:59:31 time: 0.8419 data_time: 0.0271 memory: 16201 loss_prob: 0.5617 loss_thr: 0.3776 loss_db: 0.0980 loss: 1.0373 2022/08/30 12:15:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:15:13 - mmengine - INFO - Epoch(train) [508][5/63] lr: 4.2684e-03 eta: 16:59:31 time: 0.9240 data_time: 0.1523 memory: 16201 loss_prob: 0.5314 loss_thr: 0.3694 loss_db: 0.0920 loss: 0.9928 2022/08/30 12:15:17 - mmengine - INFO - Epoch(train) [508][10/63] lr: 4.2684e-03 eta: 16:59:01 time: 1.0031 data_time: 0.1733 memory: 16201 loss_prob: 0.5213 loss_thr: 0.3692 loss_db: 0.0916 loss: 0.9821 2022/08/30 12:15:22 - mmengine - INFO - Epoch(train) [508][15/63] lr: 4.2684e-03 eta: 16:59:01 time: 0.8695 data_time: 0.0441 memory: 16201 loss_prob: 0.5544 loss_thr: 0.3901 loss_db: 0.0965 loss: 1.0411 2022/08/30 12:15:26 - mmengine - INFO - Epoch(train) [508][20/63] lr: 4.2684e-03 eta: 16:58:40 time: 0.8828 data_time: 0.0338 memory: 16201 loss_prob: 0.5236 loss_thr: 0.3795 loss_db: 0.0913 loss: 0.9944 2022/08/30 12:15:31 - mmengine - INFO - Epoch(train) [508][25/63] lr: 4.2684e-03 eta: 16:58:40 time: 0.9214 data_time: 0.0608 memory: 16201 loss_prob: 0.7178 loss_thr: 0.3961 loss_db: 0.1118 loss: 1.2257 2022/08/30 12:15:35 - mmengine - INFO - Epoch(train) [508][30/63] lr: 4.2684e-03 eta: 16:58:19 time: 0.8821 data_time: 0.0595 memory: 16201 loss_prob: 0.7383 loss_thr: 0.4017 loss_db: 0.1119 loss: 1.2520 2022/08/30 12:15:39 - mmengine - INFO - Epoch(train) [508][35/63] lr: 4.2684e-03 eta: 16:58:19 time: 0.8303 data_time: 0.0299 memory: 16201 loss_prob: 0.5567 loss_thr: 0.3883 loss_db: 0.0961 loss: 1.0411 2022/08/30 12:15:44 - mmengine - INFO - Epoch(train) [508][40/63] lr: 4.2684e-03 eta: 16:57:58 time: 0.8951 data_time: 0.0768 memory: 16201 loss_prob: 0.5774 loss_thr: 0.3942 loss_db: 0.1012 loss: 1.0728 2022/08/30 12:15:49 - mmengine - INFO - Epoch(train) [508][45/63] lr: 4.2684e-03 eta: 16:57:58 time: 0.9576 data_time: 0.0851 memory: 16201 loss_prob: 0.5332 loss_thr: 0.3749 loss_db: 0.0930 loss: 1.0010 2022/08/30 12:15:53 - mmengine - INFO - Epoch(train) [508][50/63] lr: 4.2684e-03 eta: 16:57:37 time: 0.9068 data_time: 0.0343 memory: 16201 loss_prob: 0.5385 loss_thr: 0.3765 loss_db: 0.0947 loss: 1.0097 2022/08/30 12:15:57 - mmengine - INFO - Epoch(train) [508][55/63] lr: 4.2684e-03 eta: 16:57:37 time: 0.8607 data_time: 0.0456 memory: 16201 loss_prob: 0.5554 loss_thr: 0.3709 loss_db: 0.0964 loss: 1.0227 2022/08/30 12:16:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:16:02 - mmengine - INFO - Epoch(train) [508][60/63] lr: 4.2684e-03 eta: 16:57:17 time: 0.8999 data_time: 0.0524 memory: 16201 loss_prob: 0.5208 loss_thr: 0.3460 loss_db: 0.0905 loss: 0.9573 2022/08/30 12:16:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:16:10 - mmengine - INFO - Epoch(train) [509][5/63] lr: 4.2628e-03 eta: 16:57:17 time: 1.0248 data_time: 0.1958 memory: 16201 loss_prob: 0.5340 loss_thr: 0.3650 loss_db: 0.0926 loss: 0.9916 2022/08/30 12:16:14 - mmengine - INFO - Epoch(train) [509][10/63] lr: 4.2628e-03 eta: 16:56:47 time: 1.0143 data_time: 0.2045 memory: 16201 loss_prob: 0.5723 loss_thr: 0.3872 loss_db: 0.0994 loss: 1.0590 2022/08/30 12:16:18 - mmengine - INFO - Epoch(train) [509][15/63] lr: 4.2628e-03 eta: 16:56:47 time: 0.8509 data_time: 0.0317 memory: 16201 loss_prob: 0.5563 loss_thr: 0.3863 loss_db: 0.0971 loss: 1.0397 2022/08/30 12:16:23 - mmengine - INFO - Epoch(train) [509][20/63] lr: 4.2628e-03 eta: 16:56:26 time: 0.8891 data_time: 0.0240 memory: 16201 loss_prob: 0.6170 loss_thr: 0.4183 loss_db: 0.1072 loss: 1.1425 2022/08/30 12:16:28 - mmengine - INFO - Epoch(train) [509][25/63] lr: 4.2628e-03 eta: 16:56:26 time: 0.9264 data_time: 0.0519 memory: 16201 loss_prob: 0.5646 loss_thr: 0.3879 loss_db: 0.0981 loss: 1.0506 2022/08/30 12:16:32 - mmengine - INFO - Epoch(train) [509][30/63] lr: 4.2628e-03 eta: 16:56:05 time: 0.8739 data_time: 0.0500 memory: 16201 loss_prob: 0.4572 loss_thr: 0.3352 loss_db: 0.0785 loss: 0.8710 2022/08/30 12:16:36 - mmengine - INFO - Epoch(train) [509][35/63] lr: 4.2628e-03 eta: 16:56:05 time: 0.8391 data_time: 0.0325 memory: 16201 loss_prob: 0.4590 loss_thr: 0.3387 loss_db: 0.0795 loss: 0.8772 2022/08/30 12:16:40 - mmengine - INFO - Epoch(train) [509][40/63] lr: 4.2628e-03 eta: 16:55:44 time: 0.8609 data_time: 0.0414 memory: 16201 loss_prob: 0.4752 loss_thr: 0.3431 loss_db: 0.0822 loss: 0.9006 2022/08/30 12:16:45 - mmengine - INFO - Epoch(train) [509][45/63] lr: 4.2628e-03 eta: 16:55:44 time: 0.9125 data_time: 0.0574 memory: 16201 loss_prob: 0.5091 loss_thr: 0.3528 loss_db: 0.0883 loss: 0.9502 2022/08/30 12:16:49 - mmengine - INFO - Epoch(train) [509][50/63] lr: 4.2628e-03 eta: 16:55:23 time: 0.8872 data_time: 0.0526 memory: 16201 loss_prob: 0.5528 loss_thr: 0.3706 loss_db: 0.0962 loss: 1.0196 2022/08/30 12:16:54 - mmengine - INFO - Epoch(train) [509][55/63] lr: 4.2628e-03 eta: 16:55:23 time: 0.8896 data_time: 0.0555 memory: 16201 loss_prob: 0.5460 loss_thr: 0.3635 loss_db: 0.0953 loss: 1.0049 2022/08/30 12:16:58 - mmengine - INFO - Epoch(train) [509][60/63] lr: 4.2628e-03 eta: 16:55:02 time: 0.9114 data_time: 0.0587 memory: 16201 loss_prob: 0.5594 loss_thr: 0.3694 loss_db: 0.0962 loss: 1.0250 2022/08/30 12:17:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:17:07 - mmengine - INFO - Epoch(train) [510][5/63] lr: 4.2572e-03 eta: 16:55:02 time: 1.0495 data_time: 0.2509 memory: 16201 loss_prob: 0.5227 loss_thr: 0.3628 loss_db: 0.0873 loss: 0.9727 2022/08/30 12:17:12 - mmengine - INFO - Epoch(train) [510][10/63] lr: 4.2572e-03 eta: 16:54:35 time: 1.1413 data_time: 0.2868 memory: 16201 loss_prob: 0.5082 loss_thr: 0.3599 loss_db: 0.0886 loss: 0.9567 2022/08/30 12:17:16 - mmengine - INFO - Epoch(train) [510][15/63] lr: 4.2572e-03 eta: 16:54:35 time: 0.8848 data_time: 0.0605 memory: 16201 loss_prob: 0.5909 loss_thr: 0.3996 loss_db: 0.1037 loss: 1.0941 2022/08/30 12:17:20 - mmengine - INFO - Epoch(train) [510][20/63] lr: 4.2572e-03 eta: 16:54:13 time: 0.8275 data_time: 0.0293 memory: 16201 loss_prob: 0.5987 loss_thr: 0.4090 loss_db: 0.1049 loss: 1.1126 2022/08/30 12:17:25 - mmengine - INFO - Epoch(train) [510][25/63] lr: 4.2572e-03 eta: 16:54:13 time: 0.9237 data_time: 0.0454 memory: 16201 loss_prob: 0.5525 loss_thr: 0.3822 loss_db: 0.0959 loss: 1.0306 2022/08/30 12:17:29 - mmengine - INFO - Epoch(train) [510][30/63] lr: 4.2572e-03 eta: 16:53:53 time: 0.9248 data_time: 0.0443 memory: 16201 loss_prob: 0.5385 loss_thr: 0.3659 loss_db: 0.0927 loss: 0.9972 2022/08/30 12:17:34 - mmengine - INFO - Epoch(train) [510][35/63] lr: 4.2572e-03 eta: 16:53:53 time: 0.8414 data_time: 0.0332 memory: 16201 loss_prob: 0.5650 loss_thr: 0.3695 loss_db: 0.0961 loss: 1.0306 2022/08/30 12:17:38 - mmengine - INFO - Epoch(train) [510][40/63] lr: 4.2572e-03 eta: 16:53:32 time: 0.8492 data_time: 0.0366 memory: 16201 loss_prob: 0.5339 loss_thr: 0.3515 loss_db: 0.0926 loss: 0.9780 2022/08/30 12:17:43 - mmengine - INFO - Epoch(train) [510][45/63] lr: 4.2572e-03 eta: 16:53:32 time: 0.9122 data_time: 0.0293 memory: 16201 loss_prob: 0.4834 loss_thr: 0.3328 loss_db: 0.0864 loss: 0.9026 2022/08/30 12:17:47 - mmengine - INFO - Epoch(train) [510][50/63] lr: 4.2572e-03 eta: 16:53:11 time: 0.9131 data_time: 0.0330 memory: 16201 loss_prob: 0.5279 loss_thr: 0.3594 loss_db: 0.0907 loss: 0.9780 2022/08/30 12:17:52 - mmengine - INFO - Epoch(train) [510][55/63] lr: 4.2572e-03 eta: 16:53:11 time: 0.8862 data_time: 0.0401 memory: 16201 loss_prob: 0.5473 loss_thr: 0.3700 loss_db: 0.0935 loss: 1.0108 2022/08/30 12:17:56 - mmengine - INFO - Epoch(train) [510][60/63] lr: 4.2572e-03 eta: 16:52:50 time: 0.8875 data_time: 0.0402 memory: 16201 loss_prob: 0.5594 loss_thr: 0.3642 loss_db: 0.0987 loss: 1.0224 2022/08/30 12:17:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:18:04 - mmengine - INFO - Epoch(train) [511][5/63] lr: 4.2517e-03 eta: 16:52:50 time: 0.9762 data_time: 0.1957 memory: 16201 loss_prob: 0.6065 loss_thr: 0.3855 loss_db: 0.1050 loss: 1.0971 2022/08/30 12:18:08 - mmengine - INFO - Epoch(train) [511][10/63] lr: 4.2517e-03 eta: 16:52:21 time: 1.0269 data_time: 0.2179 memory: 16201 loss_prob: 0.5484 loss_thr: 0.3674 loss_db: 0.0943 loss: 1.0101 2022/08/30 12:18:13 - mmengine - INFO - Epoch(train) [511][15/63] lr: 4.2517e-03 eta: 16:52:21 time: 0.8991 data_time: 0.0439 memory: 16201 loss_prob: 0.5308 loss_thr: 0.3683 loss_db: 0.0921 loss: 0.9913 2022/08/30 12:18:18 - mmengine - INFO - Epoch(train) [511][20/63] lr: 4.2517e-03 eta: 16:52:01 time: 0.9240 data_time: 0.0541 memory: 16201 loss_prob: 0.5271 loss_thr: 0.3573 loss_db: 0.0929 loss: 0.9773 2022/08/30 12:18:22 - mmengine - INFO - Epoch(train) [511][25/63] lr: 4.2517e-03 eta: 16:52:01 time: 0.8743 data_time: 0.0709 memory: 16201 loss_prob: 0.5024 loss_thr: 0.3499 loss_db: 0.0885 loss: 0.9408 2022/08/30 12:18:26 - mmengine - INFO - Epoch(train) [511][30/63] lr: 4.2517e-03 eta: 16:51:39 time: 0.8349 data_time: 0.0364 memory: 16201 loss_prob: 0.5115 loss_thr: 0.3664 loss_db: 0.0885 loss: 0.9664 2022/08/30 12:18:30 - mmengine - INFO - Epoch(train) [511][35/63] lr: 4.2517e-03 eta: 16:51:39 time: 0.8492 data_time: 0.0314 memory: 16201 loss_prob: 0.5406 loss_thr: 0.3864 loss_db: 0.0925 loss: 1.0195 2022/08/30 12:18:35 - mmengine - INFO - Epoch(train) [511][40/63] lr: 4.2517e-03 eta: 16:51:18 time: 0.8667 data_time: 0.0422 memory: 16201 loss_prob: 0.5317 loss_thr: 0.3685 loss_db: 0.0921 loss: 0.9923 2022/08/30 12:18:39 - mmengine - INFO - Epoch(train) [511][45/63] lr: 4.2517e-03 eta: 16:51:18 time: 0.8314 data_time: 0.0376 memory: 16201 loss_prob: 0.5169 loss_thr: 0.3483 loss_db: 0.0896 loss: 0.9548 2022/08/30 12:18:45 - mmengine - INFO - Epoch(train) [511][50/63] lr: 4.2517e-03 eta: 16:50:59 time: 0.9895 data_time: 0.1055 memory: 16201 loss_prob: 0.5149 loss_thr: 0.3633 loss_db: 0.0866 loss: 0.9648 2022/08/30 12:18:49 - mmengine - INFO - Epoch(train) [511][55/63] lr: 4.2517e-03 eta: 16:50:59 time: 0.9926 data_time: 0.1229 memory: 16201 loss_prob: 0.5279 loss_thr: 0.3718 loss_db: 0.0902 loss: 0.9899 2022/08/30 12:18:53 - mmengine - INFO - Epoch(train) [511][60/63] lr: 4.2517e-03 eta: 16:50:37 time: 0.8167 data_time: 0.0566 memory: 16201 loss_prob: 0.5379 loss_thr: 0.3674 loss_db: 0.0939 loss: 0.9992 2022/08/30 12:18:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:19:02 - mmengine - INFO - Epoch(train) [512][5/63] lr: 4.2461e-03 eta: 16:50:37 time: 1.0294 data_time: 0.1993 memory: 16201 loss_prob: 0.5624 loss_thr: 0.3767 loss_db: 0.0979 loss: 1.0370 2022/08/30 12:19:06 - mmengine - INFO - Epoch(train) [512][10/63] lr: 4.2461e-03 eta: 16:50:08 time: 1.0507 data_time: 0.2114 memory: 16201 loss_prob: 0.6423 loss_thr: 0.4004 loss_db: 0.1057 loss: 1.1483 2022/08/30 12:19:10 - mmengine - INFO - Epoch(train) [512][15/63] lr: 4.2461e-03 eta: 16:50:08 time: 0.8770 data_time: 0.0310 memory: 16201 loss_prob: 0.6495 loss_thr: 0.4056 loss_db: 0.1059 loss: 1.1610 2022/08/30 12:19:15 - mmengine - INFO - Epoch(train) [512][20/63] lr: 4.2461e-03 eta: 16:49:47 time: 0.8769 data_time: 0.0340 memory: 16201 loss_prob: 0.5484 loss_thr: 0.3670 loss_db: 0.0933 loss: 1.0088 2022/08/30 12:19:19 - mmengine - INFO - Epoch(train) [512][25/63] lr: 4.2461e-03 eta: 16:49:47 time: 0.8815 data_time: 0.0529 memory: 16201 loss_prob: 0.5139 loss_thr: 0.3396 loss_db: 0.0854 loss: 0.9389 2022/08/30 12:19:23 - mmengine - INFO - Epoch(train) [512][30/63] lr: 4.2461e-03 eta: 16:49:26 time: 0.8619 data_time: 0.0450 memory: 16201 loss_prob: 0.5203 loss_thr: 0.3533 loss_db: 0.0885 loss: 0.9620 2022/08/30 12:19:28 - mmengine - INFO - Epoch(train) [512][35/63] lr: 4.2461e-03 eta: 16:49:26 time: 0.8570 data_time: 0.0417 memory: 16201 loss_prob: 0.5409 loss_thr: 0.3787 loss_db: 0.0943 loss: 1.0139 2022/08/30 12:19:32 - mmengine - INFO - Epoch(train) [512][40/63] lr: 4.2461e-03 eta: 16:49:05 time: 0.8612 data_time: 0.0475 memory: 16201 loss_prob: 0.5337 loss_thr: 0.3720 loss_db: 0.0927 loss: 0.9984 2022/08/30 12:19:36 - mmengine - INFO - Epoch(train) [512][45/63] lr: 4.2461e-03 eta: 16:49:05 time: 0.8443 data_time: 0.0375 memory: 16201 loss_prob: 0.5189 loss_thr: 0.3630 loss_db: 0.0909 loss: 0.9728 2022/08/30 12:19:40 - mmengine - INFO - Epoch(train) [512][50/63] lr: 4.2461e-03 eta: 16:48:44 time: 0.8452 data_time: 0.0302 memory: 16201 loss_prob: 0.5359 loss_thr: 0.3717 loss_db: 0.0938 loss: 1.0014 2022/08/30 12:19:46 - mmengine - INFO - Epoch(train) [512][55/63] lr: 4.2461e-03 eta: 16:48:44 time: 0.9425 data_time: 0.0374 memory: 16201 loss_prob: 0.5743 loss_thr: 0.3707 loss_db: 0.1000 loss: 1.0450 2022/08/30 12:19:50 - mmengine - INFO - Epoch(train) [512][60/63] lr: 4.2461e-03 eta: 16:48:24 time: 0.9586 data_time: 0.0575 memory: 16201 loss_prob: 0.5624 loss_thr: 0.3614 loss_db: 0.0953 loss: 1.0191 2022/08/30 12:19:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:19:58 - mmengine - INFO - Epoch(train) [513][5/63] lr: 4.2406e-03 eta: 16:48:24 time: 0.9690 data_time: 0.1887 memory: 16201 loss_prob: 0.5274 loss_thr: 0.3520 loss_db: 0.0910 loss: 0.9705 2022/08/30 12:20:03 - mmengine - INFO - Epoch(train) [513][10/63] lr: 4.2406e-03 eta: 16:47:56 time: 1.0913 data_time: 0.2138 memory: 16201 loss_prob: 0.5035 loss_thr: 0.3527 loss_db: 0.0885 loss: 0.9448 2022/08/30 12:20:07 - mmengine - INFO - Epoch(train) [513][15/63] lr: 4.2406e-03 eta: 16:47:56 time: 0.9209 data_time: 0.0392 memory: 16201 loss_prob: 0.5316 loss_thr: 0.3711 loss_db: 0.0914 loss: 0.9942 2022/08/30 12:20:11 - mmengine - INFO - Epoch(train) [513][20/63] lr: 4.2406e-03 eta: 16:47:35 time: 0.8324 data_time: 0.0248 memory: 16201 loss_prob: 0.5582 loss_thr: 0.3759 loss_db: 0.0961 loss: 1.0302 2022/08/30 12:20:16 - mmengine - INFO - Epoch(train) [513][25/63] lr: 4.2406e-03 eta: 16:47:35 time: 0.8358 data_time: 0.0546 memory: 16201 loss_prob: 0.5263 loss_thr: 0.3643 loss_db: 0.0914 loss: 0.9820 2022/08/30 12:20:20 - mmengine - INFO - Epoch(train) [513][30/63] lr: 4.2406e-03 eta: 16:47:13 time: 0.8649 data_time: 0.0502 memory: 16201 loss_prob: 0.5197 loss_thr: 0.3508 loss_db: 0.0889 loss: 0.9595 2022/08/30 12:20:25 - mmengine - INFO - Epoch(train) [513][35/63] lr: 4.2406e-03 eta: 16:47:13 time: 0.8987 data_time: 0.0304 memory: 16201 loss_prob: 0.5335 loss_thr: 0.3502 loss_db: 0.0908 loss: 0.9744 2022/08/30 12:20:29 - mmengine - INFO - Epoch(train) [513][40/63] lr: 4.2406e-03 eta: 16:46:53 time: 0.9039 data_time: 0.0399 memory: 16201 loss_prob: 0.5341 loss_thr: 0.3607 loss_db: 0.0913 loss: 0.9861 2022/08/30 12:20:33 - mmengine - INFO - Epoch(train) [513][45/63] lr: 4.2406e-03 eta: 16:46:53 time: 0.8731 data_time: 0.0409 memory: 16201 loss_prob: 0.5874 loss_thr: 0.3862 loss_db: 0.1023 loss: 1.0759 2022/08/30 12:20:37 - mmengine - INFO - Epoch(train) [513][50/63] lr: 4.2406e-03 eta: 16:46:32 time: 0.8435 data_time: 0.0322 memory: 16201 loss_prob: 0.5702 loss_thr: 0.3785 loss_db: 0.0981 loss: 1.0468 2022/08/30 12:20:43 - mmengine - INFO - Epoch(train) [513][55/63] lr: 4.2406e-03 eta: 16:46:32 time: 0.9596 data_time: 0.0375 memory: 16201 loss_prob: 0.4945 loss_thr: 0.3539 loss_db: 0.0835 loss: 0.9318 2022/08/30 12:20:47 - mmengine - INFO - Epoch(train) [513][60/63] lr: 4.2406e-03 eta: 16:46:12 time: 0.9828 data_time: 0.0451 memory: 16201 loss_prob: 0.5378 loss_thr: 0.3704 loss_db: 0.0892 loss: 0.9975 2022/08/30 12:20:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:20:56 - mmengine - INFO - Epoch(train) [514][5/63] lr: 4.2350e-03 eta: 16:46:12 time: 1.0024 data_time: 0.2150 memory: 16201 loss_prob: 0.6048 loss_thr: 0.3960 loss_db: 0.1021 loss: 1.1029 2022/08/30 12:21:00 - mmengine - INFO - Epoch(train) [514][10/63] lr: 4.2350e-03 eta: 16:45:44 time: 1.0542 data_time: 0.2214 memory: 16201 loss_prob: 0.6105 loss_thr: 0.3960 loss_db: 0.1046 loss: 1.1112 2022/08/30 12:21:06 - mmengine - INFO - Epoch(train) [514][15/63] lr: 4.2350e-03 eta: 16:45:44 time: 1.0478 data_time: 0.0714 memory: 16201 loss_prob: 0.5744 loss_thr: 0.3936 loss_db: 0.1008 loss: 1.0688 2022/08/30 12:21:11 - mmengine - INFO - Epoch(train) [514][20/63] lr: 4.2350e-03 eta: 16:45:26 time: 1.0718 data_time: 0.0939 memory: 16201 loss_prob: 0.5680 loss_thr: 0.3790 loss_db: 0.0962 loss: 1.0433 2022/08/30 12:21:15 - mmengine - INFO - Epoch(train) [514][25/63] lr: 4.2350e-03 eta: 16:45:26 time: 0.8514 data_time: 0.0504 memory: 16201 loss_prob: 0.5855 loss_thr: 0.3850 loss_db: 0.0998 loss: 1.0704 2022/08/30 12:21:19 - mmengine - INFO - Epoch(train) [514][30/63] lr: 4.2350e-03 eta: 16:45:04 time: 0.8129 data_time: 0.0249 memory: 16201 loss_prob: 0.5731 loss_thr: 0.3928 loss_db: 0.0999 loss: 1.0658 2022/08/30 12:21:24 - mmengine - INFO - Epoch(train) [514][35/63] lr: 4.2350e-03 eta: 16:45:04 time: 0.8788 data_time: 0.0408 memory: 16201 loss_prob: 0.5845 loss_thr: 0.3915 loss_db: 0.1008 loss: 1.0768 2022/08/30 12:21:28 - mmengine - INFO - Epoch(train) [514][40/63] lr: 4.2350e-03 eta: 16:44:43 time: 0.8922 data_time: 0.0408 memory: 16201 loss_prob: 0.5648 loss_thr: 0.3719 loss_db: 0.0981 loss: 1.0348 2022/08/30 12:21:32 - mmengine - INFO - Epoch(train) [514][45/63] lr: 4.2350e-03 eta: 16:44:43 time: 0.8366 data_time: 0.0302 memory: 16201 loss_prob: 0.5038 loss_thr: 0.3406 loss_db: 0.0879 loss: 0.9323 2022/08/30 12:21:37 - mmengine - INFO - Epoch(train) [514][50/63] lr: 4.2350e-03 eta: 16:44:22 time: 0.8763 data_time: 0.0646 memory: 16201 loss_prob: 0.4910 loss_thr: 0.3482 loss_db: 0.0850 loss: 0.9242 2022/08/30 12:21:41 - mmengine - INFO - Epoch(train) [514][55/63] lr: 4.2350e-03 eta: 16:44:22 time: 0.8972 data_time: 0.0603 memory: 16201 loss_prob: 0.5597 loss_thr: 0.3744 loss_db: 0.0939 loss: 1.0280 2022/08/30 12:21:45 - mmengine - INFO - Epoch(train) [514][60/63] lr: 4.2350e-03 eta: 16:44:01 time: 0.8533 data_time: 0.0246 memory: 16201 loss_prob: 0.5463 loss_thr: 0.3786 loss_db: 0.0929 loss: 1.0178 2022/08/30 12:21:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:21:53 - mmengine - INFO - Epoch(train) [515][5/63] lr: 4.2295e-03 eta: 16:44:01 time: 0.9758 data_time: 0.1848 memory: 16201 loss_prob: 0.5549 loss_thr: 0.3758 loss_db: 0.0985 loss: 1.0292 2022/08/30 12:21:58 - mmengine - INFO - Epoch(train) [515][10/63] lr: 4.2295e-03 eta: 16:43:33 time: 1.0496 data_time: 0.2025 memory: 16201 loss_prob: 0.5674 loss_thr: 0.3771 loss_db: 0.1013 loss: 1.0458 2022/08/30 12:22:03 - mmengine - INFO - Epoch(train) [515][15/63] lr: 4.2295e-03 eta: 16:43:33 time: 1.0087 data_time: 0.0774 memory: 16201 loss_prob: 0.5315 loss_thr: 0.3515 loss_db: 0.0929 loss: 0.9758 2022/08/30 12:22:08 - mmengine - INFO - Epoch(train) [515][20/63] lr: 4.2295e-03 eta: 16:43:14 time: 0.9877 data_time: 0.0611 memory: 16201 loss_prob: 0.5835 loss_thr: 0.3724 loss_db: 0.0997 loss: 1.0556 2022/08/30 12:22:12 - mmengine - INFO - Epoch(train) [515][25/63] lr: 4.2295e-03 eta: 16:43:14 time: 0.8711 data_time: 0.0297 memory: 16201 loss_prob: 0.5611 loss_thr: 0.3663 loss_db: 0.0971 loss: 1.0245 2022/08/30 12:22:16 - mmengine - INFO - Epoch(train) [515][30/63] lr: 4.2295e-03 eta: 16:42:52 time: 0.8413 data_time: 0.0297 memory: 16201 loss_prob: 0.4982 loss_thr: 0.3467 loss_db: 0.0859 loss: 0.9308 2022/08/30 12:22:20 - mmengine - INFO - Epoch(train) [515][35/63] lr: 4.2295e-03 eta: 16:42:52 time: 0.8534 data_time: 0.0391 memory: 16201 loss_prob: 0.5105 loss_thr: 0.3586 loss_db: 0.0865 loss: 0.9556 2022/08/30 12:22:25 - mmengine - INFO - Epoch(train) [515][40/63] lr: 4.2295e-03 eta: 16:42:31 time: 0.8613 data_time: 0.0358 memory: 16201 loss_prob: 0.5190 loss_thr: 0.3593 loss_db: 0.0880 loss: 0.9663 2022/08/30 12:22:29 - mmengine - INFO - Epoch(train) [515][45/63] lr: 4.2295e-03 eta: 16:42:31 time: 0.8585 data_time: 0.0518 memory: 16201 loss_prob: 0.5138 loss_thr: 0.3550 loss_db: 0.0889 loss: 0.9578 2022/08/30 12:22:34 - mmengine - INFO - Epoch(train) [515][50/63] lr: 4.2295e-03 eta: 16:42:12 time: 0.9675 data_time: 0.0577 memory: 16201 loss_prob: 0.5354 loss_thr: 0.3677 loss_db: 0.0930 loss: 0.9961 2022/08/30 12:22:38 - mmengine - INFO - Epoch(train) [515][55/63] lr: 4.2295e-03 eta: 16:42:12 time: 0.9368 data_time: 0.0281 memory: 16201 loss_prob: 0.5631 loss_thr: 0.3834 loss_db: 0.0973 loss: 1.0439 2022/08/30 12:22:43 - mmengine - INFO - Epoch(train) [515][60/63] lr: 4.2295e-03 eta: 16:41:51 time: 0.8546 data_time: 0.0432 memory: 16201 loss_prob: 0.5168 loss_thr: 0.3621 loss_db: 0.0906 loss: 0.9696 2022/08/30 12:22:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:22:51 - mmengine - INFO - Epoch(train) [516][5/63] lr: 4.2239e-03 eta: 16:41:51 time: 0.9504 data_time: 0.1979 memory: 16201 loss_prob: 0.5396 loss_thr: 0.3651 loss_db: 0.0930 loss: 0.9977 2022/08/30 12:22:55 - mmengine - INFO - Epoch(train) [516][10/63] lr: 4.2239e-03 eta: 16:41:22 time: 1.0054 data_time: 0.2139 memory: 16201 loss_prob: 0.5598 loss_thr: 0.3630 loss_db: 0.0960 loss: 1.0188 2022/08/30 12:22:59 - mmengine - INFO - Epoch(train) [516][15/63] lr: 4.2239e-03 eta: 16:41:22 time: 0.8155 data_time: 0.0406 memory: 16201 loss_prob: 0.5243 loss_thr: 0.3472 loss_db: 0.0917 loss: 0.9632 2022/08/30 12:23:03 - mmengine - INFO - Epoch(train) [516][20/63] lr: 4.2239e-03 eta: 16:41:01 time: 0.8470 data_time: 0.0273 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3328 loss_db: 0.0831 loss: 0.8910 2022/08/30 12:23:08 - mmengine - INFO - Epoch(train) [516][25/63] lr: 4.2239e-03 eta: 16:41:01 time: 0.9192 data_time: 0.0654 memory: 16201 loss_prob: 0.5176 loss_thr: 0.3597 loss_db: 0.0881 loss: 0.9654 2022/08/30 12:23:12 - mmengine - INFO - Epoch(train) [516][30/63] lr: 4.2239e-03 eta: 16:40:40 time: 0.9009 data_time: 0.0630 memory: 16201 loss_prob: 0.5683 loss_thr: 0.3825 loss_db: 0.0978 loss: 1.0486 2022/08/30 12:23:17 - mmengine - INFO - Epoch(train) [516][35/63] lr: 4.2239e-03 eta: 16:40:40 time: 0.8546 data_time: 0.0363 memory: 16201 loss_prob: 0.5698 loss_thr: 0.3783 loss_db: 0.1009 loss: 1.0490 2022/08/30 12:23:21 - mmengine - INFO - Epoch(train) [516][40/63] lr: 4.2239e-03 eta: 16:40:19 time: 0.8665 data_time: 0.0471 memory: 16201 loss_prob: 0.5350 loss_thr: 0.3644 loss_db: 0.0932 loss: 0.9926 2022/08/30 12:23:26 - mmengine - INFO - Epoch(train) [516][45/63] lr: 4.2239e-03 eta: 16:40:19 time: 0.9651 data_time: 0.0525 memory: 16201 loss_prob: 0.5150 loss_thr: 0.3448 loss_db: 0.0891 loss: 0.9489 2022/08/30 12:23:31 - mmengine - INFO - Epoch(train) [516][50/63] lr: 4.2239e-03 eta: 16:39:59 time: 0.9568 data_time: 0.0487 memory: 16201 loss_prob: 0.5239 loss_thr: 0.3521 loss_db: 0.0923 loss: 0.9683 2022/08/30 12:23:35 - mmengine - INFO - Epoch(train) [516][55/63] lr: 4.2239e-03 eta: 16:39:59 time: 0.8630 data_time: 0.0376 memory: 16201 loss_prob: 0.5258 loss_thr: 0.3623 loss_db: 0.0920 loss: 0.9801 2022/08/30 12:23:39 - mmengine - INFO - Epoch(train) [516][60/63] lr: 4.2239e-03 eta: 16:39:39 time: 0.8722 data_time: 0.0337 memory: 16201 loss_prob: 0.5611 loss_thr: 0.3685 loss_db: 0.0979 loss: 1.0274 2022/08/30 12:23:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:23:47 - mmengine - INFO - Epoch(train) [517][5/63] lr: 4.2184e-03 eta: 16:39:39 time: 0.9631 data_time: 0.1776 memory: 16201 loss_prob: 0.6727 loss_thr: 0.4066 loss_db: 0.1172 loss: 1.1965 2022/08/30 12:23:52 - mmengine - INFO - Epoch(train) [517][10/63] lr: 4.2184e-03 eta: 16:39:10 time: 1.0123 data_time: 0.1946 memory: 16201 loss_prob: 0.6152 loss_thr: 0.3809 loss_db: 0.1055 loss: 1.1016 2022/08/30 12:23:56 - mmengine - INFO - Epoch(train) [517][15/63] lr: 4.2184e-03 eta: 16:39:10 time: 0.8648 data_time: 0.0395 memory: 16201 loss_prob: 0.5787 loss_thr: 0.3616 loss_db: 0.0994 loss: 1.0396 2022/08/30 12:24:00 - mmengine - INFO - Epoch(train) [517][20/63] lr: 4.2184e-03 eta: 16:38:49 time: 0.8422 data_time: 0.0319 memory: 16201 loss_prob: 0.5675 loss_thr: 0.3652 loss_db: 0.1005 loss: 1.0332 2022/08/30 12:24:05 - mmengine - INFO - Epoch(train) [517][25/63] lr: 4.2184e-03 eta: 16:38:49 time: 0.9049 data_time: 0.0392 memory: 16201 loss_prob: 0.6070 loss_thr: 0.3810 loss_db: 0.1041 loss: 1.0921 2022/08/30 12:24:09 - mmengine - INFO - Epoch(train) [517][30/63] lr: 4.2184e-03 eta: 16:38:29 time: 0.9144 data_time: 0.0366 memory: 16201 loss_prob: 0.6449 loss_thr: 0.4203 loss_db: 0.1089 loss: 1.1740 2022/08/30 12:24:13 - mmengine - INFO - Epoch(train) [517][35/63] lr: 4.2184e-03 eta: 16:38:29 time: 0.8418 data_time: 0.0229 memory: 16201 loss_prob: 0.5976 loss_thr: 0.4061 loss_db: 0.1036 loss: 1.1073 2022/08/30 12:24:18 - mmengine - INFO - Epoch(train) [517][40/63] lr: 4.2184e-03 eta: 16:38:08 time: 0.8617 data_time: 0.0376 memory: 16201 loss_prob: 0.5611 loss_thr: 0.3604 loss_db: 0.0957 loss: 1.0171 2022/08/30 12:24:23 - mmengine - INFO - Epoch(train) [517][45/63] lr: 4.2184e-03 eta: 16:38:08 time: 0.9980 data_time: 0.0627 memory: 16201 loss_prob: 0.5822 loss_thr: 0.3652 loss_db: 0.0975 loss: 1.0449 2022/08/30 12:24:28 - mmengine - INFO - Epoch(train) [517][50/63] lr: 4.2184e-03 eta: 16:37:49 time: 0.9947 data_time: 0.0500 memory: 16201 loss_prob: 0.5502 loss_thr: 0.3548 loss_db: 0.0950 loss: 1.0000 2022/08/30 12:24:32 - mmengine - INFO - Epoch(train) [517][55/63] lr: 4.2184e-03 eta: 16:37:49 time: 0.8757 data_time: 0.0450 memory: 16201 loss_prob: 0.5154 loss_thr: 0.3375 loss_db: 0.0894 loss: 0.9422 2022/08/30 12:24:37 - mmengine - INFO - Epoch(train) [517][60/63] lr: 4.2184e-03 eta: 16:37:28 time: 0.9022 data_time: 0.0517 memory: 16201 loss_prob: 0.5728 loss_thr: 0.3653 loss_db: 0.1027 loss: 1.0408 2022/08/30 12:24:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:24:46 - mmengine - INFO - Epoch(train) [518][5/63] lr: 4.2128e-03 eta: 16:37:28 time: 1.0550 data_time: 0.2173 memory: 16201 loss_prob: 0.5042 loss_thr: 0.3433 loss_db: 0.0854 loss: 0.9330 2022/08/30 12:24:50 - mmengine - INFO - Epoch(train) [518][10/63] lr: 4.2128e-03 eta: 16:37:01 time: 1.1195 data_time: 0.2358 memory: 16201 loss_prob: 0.5673 loss_thr: 0.3777 loss_db: 0.0962 loss: 1.0412 2022/08/30 12:24:55 - mmengine - INFO - Epoch(train) [518][15/63] lr: 4.2128e-03 eta: 16:37:01 time: 0.9258 data_time: 0.0398 memory: 16201 loss_prob: 0.5620 loss_thr: 0.3847 loss_db: 0.0979 loss: 1.0445 2022/08/30 12:24:59 - mmengine - INFO - Epoch(train) [518][20/63] lr: 4.2128e-03 eta: 16:36:41 time: 0.9073 data_time: 0.0310 memory: 16201 loss_prob: 0.5434 loss_thr: 0.3745 loss_db: 0.0944 loss: 1.0124 2022/08/30 12:25:04 - mmengine - INFO - Epoch(train) [518][25/63] lr: 4.2128e-03 eta: 16:36:41 time: 0.9228 data_time: 0.0603 memory: 16201 loss_prob: 0.5578 loss_thr: 0.3696 loss_db: 0.0949 loss: 1.0223 2022/08/30 12:25:09 - mmengine - INFO - Epoch(train) [518][30/63] lr: 4.2128e-03 eta: 16:36:21 time: 0.9462 data_time: 0.0489 memory: 16201 loss_prob: 0.5761 loss_thr: 0.3807 loss_db: 0.0990 loss: 1.0558 2022/08/30 12:25:13 - mmengine - INFO - Epoch(train) [518][35/63] lr: 4.2128e-03 eta: 16:36:21 time: 0.9222 data_time: 0.0313 memory: 16201 loss_prob: 0.6058 loss_thr: 0.3915 loss_db: 0.1061 loss: 1.1033 2022/08/30 12:25:18 - mmengine - INFO - Epoch(train) [518][40/63] lr: 4.2128e-03 eta: 16:36:00 time: 0.8885 data_time: 0.0384 memory: 16201 loss_prob: 0.5894 loss_thr: 0.3958 loss_db: 0.0985 loss: 1.0836 2022/08/30 12:25:22 - mmengine - INFO - Epoch(train) [518][45/63] lr: 4.2128e-03 eta: 16:36:00 time: 0.8583 data_time: 0.0309 memory: 16201 loss_prob: 0.6716 loss_thr: 0.4113 loss_db: 0.1111 loss: 1.1940 2022/08/30 12:25:27 - mmengine - INFO - Epoch(train) [518][50/63] lr: 4.2128e-03 eta: 16:35:40 time: 0.9016 data_time: 0.0269 memory: 16201 loss_prob: 0.7850 loss_thr: 0.4229 loss_db: 0.1308 loss: 1.3387 2022/08/30 12:25:31 - mmengine - INFO - Epoch(train) [518][55/63] lr: 4.2128e-03 eta: 16:35:40 time: 0.8986 data_time: 0.0341 memory: 16201 loss_prob: 0.8101 loss_thr: 0.4346 loss_db: 0.1277 loss: 1.3724 2022/08/30 12:25:36 - mmengine - INFO - Epoch(train) [518][60/63] lr: 4.2128e-03 eta: 16:35:20 time: 0.8876 data_time: 0.0382 memory: 16201 loss_prob: 0.7787 loss_thr: 0.4392 loss_db: 0.1232 loss: 1.3410 2022/08/30 12:25:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:25:44 - mmengine - INFO - Epoch(train) [519][5/63] lr: 4.2072e-03 eta: 16:35:20 time: 0.9945 data_time: 0.1951 memory: 16201 loss_prob: 0.7531 loss_thr: 0.4522 loss_db: 0.1253 loss: 1.3306 2022/08/30 12:25:48 - mmengine - INFO - Epoch(train) [519][10/63] lr: 4.2072e-03 eta: 16:34:51 time: 1.0169 data_time: 0.2000 memory: 16201 loss_prob: 0.7346 loss_thr: 0.4501 loss_db: 0.1253 loss: 1.3100 2022/08/30 12:25:53 - mmengine - INFO - Epoch(train) [519][15/63] lr: 4.2072e-03 eta: 16:34:51 time: 0.9092 data_time: 0.0360 memory: 16201 loss_prob: 0.6959 loss_thr: 0.4401 loss_db: 0.1196 loss: 1.2557 2022/08/30 12:25:57 - mmengine - INFO - Epoch(train) [519][20/63] lr: 4.2072e-03 eta: 16:34:31 time: 0.9125 data_time: 0.0410 memory: 16201 loss_prob: 0.6964 loss_thr: 0.4357 loss_db: 0.1199 loss: 1.2519 2022/08/30 12:26:01 - mmengine - INFO - Epoch(train) [519][25/63] lr: 4.2072e-03 eta: 16:34:31 time: 0.8482 data_time: 0.0451 memory: 16201 loss_prob: 0.6552 loss_thr: 0.4163 loss_db: 0.1113 loss: 1.1828 2022/08/30 12:26:06 - mmengine - INFO - Epoch(train) [519][30/63] lr: 4.2072e-03 eta: 16:34:10 time: 0.8684 data_time: 0.0334 memory: 16201 loss_prob: 0.5803 loss_thr: 0.3835 loss_db: 0.0988 loss: 1.0625 2022/08/30 12:26:10 - mmengine - INFO - Epoch(train) [519][35/63] lr: 4.2072e-03 eta: 16:34:10 time: 0.8770 data_time: 0.0292 memory: 16201 loss_prob: 0.6009 loss_thr: 0.3919 loss_db: 0.1029 loss: 1.0956 2022/08/30 12:26:15 - mmengine - INFO - Epoch(train) [519][40/63] lr: 4.2072e-03 eta: 16:33:50 time: 0.9271 data_time: 0.0434 memory: 16201 loss_prob: 0.6262 loss_thr: 0.4014 loss_db: 0.1064 loss: 1.1341 2022/08/30 12:26:19 - mmengine - INFO - Epoch(train) [519][45/63] lr: 4.2072e-03 eta: 16:33:50 time: 0.9140 data_time: 0.0472 memory: 16201 loss_prob: 0.6003 loss_thr: 0.4008 loss_db: 0.1032 loss: 1.1044 2022/08/30 12:26:24 - mmengine - INFO - Epoch(train) [519][50/63] lr: 4.2072e-03 eta: 16:33:30 time: 0.8750 data_time: 0.0360 memory: 16201 loss_prob: 0.6609 loss_thr: 0.4087 loss_db: 0.1097 loss: 1.1792 2022/08/30 12:26:28 - mmengine - INFO - Epoch(train) [519][55/63] lr: 4.2072e-03 eta: 16:33:30 time: 0.8881 data_time: 0.0389 memory: 16201 loss_prob: 0.7111 loss_thr: 0.4354 loss_db: 0.1173 loss: 1.2638 2022/08/30 12:26:33 - mmengine - INFO - Epoch(train) [519][60/63] lr: 4.2072e-03 eta: 16:33:09 time: 0.8858 data_time: 0.0435 memory: 16201 loss_prob: 0.6375 loss_thr: 0.4189 loss_db: 0.1106 loss: 1.1670 2022/08/30 12:26:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:26:41 - mmengine - INFO - Epoch(train) [520][5/63] lr: 4.2017e-03 eta: 16:33:09 time: 0.9932 data_time: 0.1947 memory: 16201 loss_prob: 0.6175 loss_thr: 0.4091 loss_db: 0.1042 loss: 1.1308 2022/08/30 12:26:45 - mmengine - INFO - Epoch(train) [520][10/63] lr: 4.2017e-03 eta: 16:32:41 time: 1.0157 data_time: 0.2234 memory: 16201 loss_prob: 0.5976 loss_thr: 0.3996 loss_db: 0.1023 loss: 1.0995 2022/08/30 12:26:49 - mmengine - INFO - Epoch(train) [520][15/63] lr: 4.2017e-03 eta: 16:32:41 time: 0.8706 data_time: 0.0522 memory: 16201 loss_prob: 0.6220 loss_thr: 0.4001 loss_db: 0.1050 loss: 1.1271 2022/08/30 12:26:54 - mmengine - INFO - Epoch(train) [520][20/63] lr: 4.2017e-03 eta: 16:32:20 time: 0.8574 data_time: 0.0277 memory: 16201 loss_prob: 0.6365 loss_thr: 0.3983 loss_db: 0.1065 loss: 1.1413 2022/08/30 12:26:58 - mmengine - INFO - Epoch(train) [520][25/63] lr: 4.2017e-03 eta: 16:32:20 time: 0.8485 data_time: 0.0500 memory: 16201 loss_prob: 0.6140 loss_thr: 0.4002 loss_db: 0.1064 loss: 1.1206 2022/08/30 12:27:02 - mmengine - INFO - Epoch(train) [520][30/63] lr: 4.2017e-03 eta: 16:31:59 time: 0.8490 data_time: 0.0408 memory: 16201 loss_prob: 0.5942 loss_thr: 0.4040 loss_db: 0.1033 loss: 1.1014 2022/08/30 12:27:06 - mmengine - INFO - Epoch(train) [520][35/63] lr: 4.2017e-03 eta: 16:31:59 time: 0.8331 data_time: 0.0227 memory: 16201 loss_prob: 0.5945 loss_thr: 0.3984 loss_db: 0.0997 loss: 1.0926 2022/08/30 12:27:10 - mmengine - INFO - Epoch(train) [520][40/63] lr: 4.2017e-03 eta: 16:31:38 time: 0.8352 data_time: 0.0483 memory: 16201 loss_prob: 0.6233 loss_thr: 0.3993 loss_db: 0.1061 loss: 1.1287 2022/08/30 12:27:15 - mmengine - INFO - Epoch(train) [520][45/63] lr: 4.2017e-03 eta: 16:31:38 time: 0.8623 data_time: 0.0555 memory: 16201 loss_prob: 0.5914 loss_thr: 0.3833 loss_db: 0.1024 loss: 1.0771 2022/08/30 12:27:20 - mmengine - INFO - Epoch(train) [520][50/63] lr: 4.2017e-03 eta: 16:31:18 time: 0.9158 data_time: 0.0455 memory: 16201 loss_prob: 0.5707 loss_thr: 0.3880 loss_db: 0.0981 loss: 1.0567 2022/08/30 12:27:24 - mmengine - INFO - Epoch(train) [520][55/63] lr: 4.2017e-03 eta: 16:31:18 time: 0.9273 data_time: 0.0464 memory: 16201 loss_prob: 0.5814 loss_thr: 0.4004 loss_db: 0.1010 loss: 1.0828 2022/08/30 12:27:28 - mmengine - INFO - Epoch(train) [520][60/63] lr: 4.2017e-03 eta: 16:30:57 time: 0.8757 data_time: 0.0366 memory: 16201 loss_prob: 0.6038 loss_thr: 0.3856 loss_db: 0.1022 loss: 1.0916 2022/08/30 12:27:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:27:31 - mmengine - INFO - Saving checkpoint at 520 epochs 2022/08/30 12:27:40 - mmengine - INFO - Epoch(val) [520][5/32] eta: 16:30:57 time: 0.6672 data_time: 0.1018 memory: 16201 2022/08/30 12:27:43 - mmengine - INFO - Epoch(val) [520][10/32] eta: 0:00:16 time: 0.7333 data_time: 0.1138 memory: 15734 2022/08/30 12:27:46 - mmengine - INFO - Epoch(val) [520][15/32] eta: 0:00:16 time: 0.6148 data_time: 0.0450 memory: 15734 2022/08/30 12:27:49 - mmengine - INFO - Epoch(val) [520][20/32] eta: 0:00:08 time: 0.6891 data_time: 0.0768 memory: 15734 2022/08/30 12:27:53 - mmengine - INFO - Epoch(val) [520][25/32] eta: 0:00:08 time: 0.7207 data_time: 0.0625 memory: 15734 2022/08/30 12:27:56 - mmengine - INFO - Epoch(val) [520][30/32] eta: 0:00:01 time: 0.6264 data_time: 0.0233 memory: 15734 2022/08/30 12:27:56 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 12:27:57 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8421, precision: 0.7634, hmean: 0.8008 2022/08/30 12:27:57 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8421, precision: 0.8082, hmean: 0.8248 2022/08/30 12:27:57 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8397, precision: 0.8429, hmean: 0.8413 2022/08/30 12:27:57 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8353, precision: 0.8658, hmean: 0.8503 2022/08/30 12:27:57 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8156, precision: 0.8874, hmean: 0.8500 2022/08/30 12:27:57 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7174, precision: 0.9324, hmean: 0.8109 2022/08/30 12:27:57 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1146, precision: 0.9835, hmean: 0.2053 2022/08/30 12:27:57 - mmengine - INFO - Epoch(val) [520][32/32] icdar/precision: 0.8658 icdar/recall: 0.8353 icdar/hmean: 0.8503 2022/08/30 12:28:03 - mmengine - INFO - Epoch(train) [521][5/63] lr: 4.1961e-03 eta: 0:00:01 time: 1.0043 data_time: 0.1943 memory: 16201 loss_prob: 0.6385 loss_thr: 0.3961 loss_db: 0.1059 loss: 1.1405 2022/08/30 12:28:07 - mmengine - INFO - Epoch(train) [521][10/63] lr: 4.1961e-03 eta: 16:30:29 time: 1.0509 data_time: 0.1950 memory: 16201 loss_prob: 0.5523 loss_thr: 0.3725 loss_db: 0.0965 loss: 1.0212 2022/08/30 12:28:12 - mmengine - INFO - Epoch(train) [521][15/63] lr: 4.1961e-03 eta: 16:30:29 time: 0.8927 data_time: 0.0365 memory: 16201 loss_prob: 0.5721 loss_thr: 0.3853 loss_db: 0.0988 loss: 1.0562 2022/08/30 12:28:17 - mmengine - INFO - Epoch(train) [521][20/63] lr: 4.1961e-03 eta: 16:30:10 time: 0.9521 data_time: 0.0450 memory: 16201 loss_prob: 0.6044 loss_thr: 0.4040 loss_db: 0.1034 loss: 1.1118 2022/08/30 12:28:21 - mmengine - INFO - Epoch(train) [521][25/63] lr: 4.1961e-03 eta: 16:30:10 time: 0.9188 data_time: 0.0455 memory: 16201 loss_prob: 0.5526 loss_thr: 0.3867 loss_db: 0.0939 loss: 1.0332 2022/08/30 12:28:26 - mmengine - INFO - Epoch(train) [521][30/63] lr: 4.1961e-03 eta: 16:29:49 time: 0.8715 data_time: 0.0490 memory: 16201 loss_prob: 0.5166 loss_thr: 0.3737 loss_db: 0.0894 loss: 0.9797 2022/08/30 12:28:30 - mmengine - INFO - Epoch(train) [521][35/63] lr: 4.1961e-03 eta: 16:29:49 time: 0.8909 data_time: 0.0469 memory: 16201 loss_prob: 0.5446 loss_thr: 0.3764 loss_db: 0.0954 loss: 1.0164 2022/08/30 12:28:34 - mmengine - INFO - Epoch(train) [521][40/63] lr: 4.1961e-03 eta: 16:29:29 time: 0.8795 data_time: 0.0321 memory: 16201 loss_prob: 0.5605 loss_thr: 0.3721 loss_db: 0.0970 loss: 1.0296 2022/08/30 12:28:39 - mmengine - INFO - Epoch(train) [521][45/63] lr: 4.1961e-03 eta: 16:29:29 time: 0.8701 data_time: 0.0319 memory: 16201 loss_prob: 0.6192 loss_thr: 0.3796 loss_db: 0.1002 loss: 1.0990 2022/08/30 12:28:44 - mmengine - INFO - Epoch(train) [521][50/63] lr: 4.1961e-03 eta: 16:29:09 time: 0.9124 data_time: 0.0383 memory: 16201 loss_prob: 0.6306 loss_thr: 0.3789 loss_db: 0.1035 loss: 1.1131 2022/08/30 12:28:48 - mmengine - INFO - Epoch(train) [521][55/63] lr: 4.1961e-03 eta: 16:29:09 time: 0.9106 data_time: 0.0341 memory: 16201 loss_prob: 0.5474 loss_thr: 0.3529 loss_db: 0.0947 loss: 0.9950 2022/08/30 12:28:52 - mmengine - INFO - Epoch(train) [521][60/63] lr: 4.1961e-03 eta: 16:28:48 time: 0.8522 data_time: 0.0365 memory: 16201 loss_prob: 0.5722 loss_thr: 0.3703 loss_db: 0.0974 loss: 1.0399 2022/08/30 12:28:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:29:01 - mmengine - INFO - Epoch(train) [522][5/63] lr: 4.1906e-03 eta: 16:28:48 time: 0.9966 data_time: 0.1859 memory: 16201 loss_prob: 0.5612 loss_thr: 0.3795 loss_db: 0.0988 loss: 1.0396 2022/08/30 12:29:05 - mmengine - INFO - Epoch(train) [522][10/63] lr: 4.1906e-03 eta: 16:28:20 time: 1.0385 data_time: 0.2068 memory: 16201 loss_prob: 0.5240 loss_thr: 0.3631 loss_db: 0.0909 loss: 0.9781 2022/08/30 12:29:09 - mmengine - INFO - Epoch(train) [522][15/63] lr: 4.1906e-03 eta: 16:28:20 time: 0.8622 data_time: 0.0396 memory: 16201 loss_prob: 0.5003 loss_thr: 0.3582 loss_db: 0.0859 loss: 0.9444 2022/08/30 12:29:13 - mmengine - INFO - Epoch(train) [522][20/63] lr: 4.1906e-03 eta: 16:27:59 time: 0.8718 data_time: 0.0274 memory: 16201 loss_prob: 0.5898 loss_thr: 0.3845 loss_db: 0.1013 loss: 1.0757 2022/08/30 12:29:18 - mmengine - INFO - Epoch(train) [522][25/63] lr: 4.1906e-03 eta: 16:27:59 time: 0.8849 data_time: 0.0596 memory: 16201 loss_prob: 0.5869 loss_thr: 0.3751 loss_db: 0.1005 loss: 1.0625 2022/08/30 12:29:22 - mmengine - INFO - Epoch(train) [522][30/63] lr: 4.1906e-03 eta: 16:27:39 time: 0.8870 data_time: 0.0528 memory: 16201 loss_prob: 0.5292 loss_thr: 0.3636 loss_db: 0.0919 loss: 0.9848 2022/08/30 12:29:27 - mmengine - INFO - Epoch(train) [522][35/63] lr: 4.1906e-03 eta: 16:27:39 time: 0.8734 data_time: 0.0312 memory: 16201 loss_prob: 0.5846 loss_thr: 0.4007 loss_db: 0.1017 loss: 1.0870 2022/08/30 12:29:31 - mmengine - INFO - Epoch(train) [522][40/63] lr: 4.1906e-03 eta: 16:27:19 time: 0.9143 data_time: 0.0584 memory: 16201 loss_prob: 0.5867 loss_thr: 0.3940 loss_db: 0.0978 loss: 1.0785 2022/08/30 12:29:36 - mmengine - INFO - Epoch(train) [522][45/63] lr: 4.1906e-03 eta: 16:27:19 time: 0.9047 data_time: 0.0518 memory: 16201 loss_prob: 0.5258 loss_thr: 0.3594 loss_db: 0.0895 loss: 0.9747 2022/08/30 12:29:40 - mmengine - INFO - Epoch(train) [522][50/63] lr: 4.1906e-03 eta: 16:26:58 time: 0.8623 data_time: 0.0358 memory: 16201 loss_prob: 0.4911 loss_thr: 0.3440 loss_db: 0.0878 loss: 0.9229 2022/08/30 12:29:45 - mmengine - INFO - Epoch(train) [522][55/63] lr: 4.1906e-03 eta: 16:26:58 time: 0.9088 data_time: 0.0487 memory: 16201 loss_prob: 0.5084 loss_thr: 0.3424 loss_db: 0.0882 loss: 0.9390 2022/08/30 12:29:50 - mmengine - INFO - Epoch(train) [522][60/63] lr: 4.1906e-03 eta: 16:26:38 time: 0.9423 data_time: 0.0416 memory: 16201 loss_prob: 0.5114 loss_thr: 0.3420 loss_db: 0.0888 loss: 0.9423 2022/08/30 12:29:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:29:58 - mmengine - INFO - Epoch(train) [523][5/63] lr: 4.1850e-03 eta: 16:26:38 time: 1.0044 data_time: 0.2100 memory: 16201 loss_prob: 0.6155 loss_thr: 0.3864 loss_db: 0.1024 loss: 1.1043 2022/08/30 12:30:03 - mmengine - INFO - Epoch(train) [523][10/63] lr: 4.1850e-03 eta: 16:26:12 time: 1.1359 data_time: 0.2358 memory: 16201 loss_prob: 0.5427 loss_thr: 0.3705 loss_db: 0.0929 loss: 1.0061 2022/08/30 12:30:07 - mmengine - INFO - Epoch(train) [523][15/63] lr: 4.1850e-03 eta: 16:26:12 time: 0.9439 data_time: 0.0510 memory: 16201 loss_prob: 0.5658 loss_thr: 0.3926 loss_db: 0.0987 loss: 1.0571 2022/08/30 12:30:12 - mmengine - INFO - Epoch(train) [523][20/63] lr: 4.1850e-03 eta: 16:25:51 time: 0.8460 data_time: 0.0237 memory: 16201 loss_prob: 0.6639 loss_thr: 0.3973 loss_db: 0.1153 loss: 1.1765 2022/08/30 12:30:16 - mmengine - INFO - Epoch(train) [523][25/63] lr: 4.1850e-03 eta: 16:25:51 time: 0.9026 data_time: 0.0654 memory: 16201 loss_prob: 0.6390 loss_thr: 0.3873 loss_db: 0.1088 loss: 1.1351 2022/08/30 12:30:20 - mmengine - INFO - Epoch(train) [523][30/63] lr: 4.1850e-03 eta: 16:25:30 time: 0.8715 data_time: 0.0553 memory: 16201 loss_prob: 0.5456 loss_thr: 0.3823 loss_db: 0.0940 loss: 1.0218 2022/08/30 12:30:25 - mmengine - INFO - Epoch(train) [523][35/63] lr: 4.1850e-03 eta: 16:25:30 time: 0.8492 data_time: 0.0375 memory: 16201 loss_prob: 0.5535 loss_thr: 0.3753 loss_db: 0.0963 loss: 1.0251 2022/08/30 12:30:29 - mmengine - INFO - Epoch(train) [523][40/63] lr: 4.1850e-03 eta: 16:25:10 time: 0.8658 data_time: 0.0466 memory: 16201 loss_prob: 0.5785 loss_thr: 0.3859 loss_db: 0.0992 loss: 1.0636 2022/08/30 12:30:33 - mmengine - INFO - Epoch(train) [523][45/63] lr: 4.1850e-03 eta: 16:25:10 time: 0.8456 data_time: 0.0310 memory: 16201 loss_prob: 0.6182 loss_thr: 0.4058 loss_db: 0.1054 loss: 1.1295 2022/08/30 12:30:37 - mmengine - INFO - Epoch(train) [523][50/63] lr: 4.1850e-03 eta: 16:24:49 time: 0.8382 data_time: 0.0353 memory: 16201 loss_prob: 0.5871 loss_thr: 0.3971 loss_db: 0.1029 loss: 1.0871 2022/08/30 12:30:42 - mmengine - INFO - Epoch(train) [523][55/63] lr: 4.1850e-03 eta: 16:24:49 time: 0.8433 data_time: 0.0305 memory: 16201 loss_prob: 0.5523 loss_thr: 0.3815 loss_db: 0.0962 loss: 1.0300 2022/08/30 12:30:47 - mmengine - INFO - Epoch(train) [523][60/63] lr: 4.1850e-03 eta: 16:24:30 time: 0.9755 data_time: 0.0291 memory: 16201 loss_prob: 0.5970 loss_thr: 0.3914 loss_db: 0.0998 loss: 1.0883 2022/08/30 12:30:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:30:56 - mmengine - INFO - Epoch(train) [524][5/63] lr: 4.1794e-03 eta: 16:24:30 time: 1.0875 data_time: 0.3203 memory: 16201 loss_prob: 0.6284 loss_thr: 0.4083 loss_db: 0.1091 loss: 1.1458 2022/08/30 12:31:01 - mmengine - INFO - Epoch(train) [524][10/63] lr: 4.1794e-03 eta: 16:24:03 time: 1.1510 data_time: 0.3438 memory: 16201 loss_prob: 0.5889 loss_thr: 0.3772 loss_db: 0.0989 loss: 1.0650 2022/08/30 12:31:05 - mmengine - INFO - Epoch(train) [524][15/63] lr: 4.1794e-03 eta: 16:24:03 time: 0.8724 data_time: 0.0408 memory: 16201 loss_prob: 0.6971 loss_thr: 0.4038 loss_db: 0.1126 loss: 1.2135 2022/08/30 12:31:09 - mmengine - INFO - Epoch(train) [524][20/63] lr: 4.1794e-03 eta: 16:23:43 time: 0.8589 data_time: 0.0281 memory: 16201 loss_prob: 0.6970 loss_thr: 0.4164 loss_db: 0.1168 loss: 1.2302 2022/08/30 12:31:14 - mmengine - INFO - Epoch(train) [524][25/63] lr: 4.1794e-03 eta: 16:23:43 time: 0.8416 data_time: 0.0544 memory: 16201 loss_prob: 0.6056 loss_thr: 0.3931 loss_db: 0.1050 loss: 1.1037 2022/08/30 12:31:18 - mmengine - INFO - Epoch(train) [524][30/63] lr: 4.1794e-03 eta: 16:23:22 time: 0.8559 data_time: 0.0387 memory: 16201 loss_prob: 0.5956 loss_thr: 0.3734 loss_db: 0.1029 loss: 1.0719 2022/08/30 12:31:22 - mmengine - INFO - Epoch(train) [524][35/63] lr: 4.1794e-03 eta: 16:23:22 time: 0.8544 data_time: 0.0257 memory: 16201 loss_prob: 0.5898 loss_thr: 0.3848 loss_db: 0.1028 loss: 1.0774 2022/08/30 12:31:27 - mmengine - INFO - Epoch(train) [524][40/63] lr: 4.1794e-03 eta: 16:23:02 time: 0.8916 data_time: 0.0633 memory: 16201 loss_prob: 0.6082 loss_thr: 0.4038 loss_db: 0.1062 loss: 1.1182 2022/08/30 12:31:31 - mmengine - INFO - Epoch(train) [524][45/63] lr: 4.1794e-03 eta: 16:23:02 time: 0.9168 data_time: 0.0600 memory: 16201 loss_prob: 0.5586 loss_thr: 0.3939 loss_db: 0.0975 loss: 1.0500 2022/08/30 12:31:36 - mmengine - INFO - Epoch(train) [524][50/63] lr: 4.1794e-03 eta: 16:22:42 time: 0.9012 data_time: 0.0373 memory: 16201 loss_prob: 0.5947 loss_thr: 0.3906 loss_db: 0.1019 loss: 1.0872 2022/08/30 12:31:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:31:40 - mmengine - INFO - Epoch(train) [524][55/63] lr: 4.1794e-03 eta: 16:22:42 time: 0.9116 data_time: 0.0703 memory: 16201 loss_prob: 0.5747 loss_thr: 0.3715 loss_db: 0.1002 loss: 1.0463 2022/08/30 12:31:45 - mmengine - INFO - Epoch(train) [524][60/63] lr: 4.1794e-03 eta: 16:22:22 time: 0.8933 data_time: 0.0678 memory: 16201 loss_prob: 0.5037 loss_thr: 0.3518 loss_db: 0.0868 loss: 0.9423 2022/08/30 12:31:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:31:54 - mmengine - INFO - Epoch(train) [525][5/63] lr: 4.1739e-03 eta: 16:22:22 time: 1.0659 data_time: 0.2637 memory: 16201 loss_prob: 0.5596 loss_thr: 0.3674 loss_db: 0.0953 loss: 1.0223 2022/08/30 12:31:58 - mmengine - INFO - Epoch(train) [525][10/63] lr: 4.1739e-03 eta: 16:21:55 time: 1.1278 data_time: 0.3025 memory: 16201 loss_prob: 0.5887 loss_thr: 0.3818 loss_db: 0.1008 loss: 1.0713 2022/08/30 12:32:03 - mmengine - INFO - Epoch(train) [525][15/63] lr: 4.1739e-03 eta: 16:21:55 time: 0.9669 data_time: 0.0550 memory: 16201 loss_prob: 0.5860 loss_thr: 0.3883 loss_db: 0.0995 loss: 1.0737 2022/08/30 12:32:08 - mmengine - INFO - Epoch(train) [525][20/63] lr: 4.1739e-03 eta: 16:21:36 time: 0.9528 data_time: 0.0264 memory: 16201 loss_prob: 0.5603 loss_thr: 0.3784 loss_db: 0.0965 loss: 1.0351 2022/08/30 12:32:12 - mmengine - INFO - Epoch(train) [525][25/63] lr: 4.1739e-03 eta: 16:21:36 time: 0.8700 data_time: 0.0419 memory: 16201 loss_prob: 0.5656 loss_thr: 0.3891 loss_db: 0.0999 loss: 1.0546 2022/08/30 12:32:17 - mmengine - INFO - Epoch(train) [525][30/63] lr: 4.1739e-03 eta: 16:21:15 time: 0.8915 data_time: 0.0316 memory: 16201 loss_prob: 0.5532 loss_thr: 0.3891 loss_db: 0.0971 loss: 1.0395 2022/08/30 12:32:21 - mmengine - INFO - Epoch(train) [525][35/63] lr: 4.1739e-03 eta: 16:21:15 time: 0.9307 data_time: 0.0239 memory: 16201 loss_prob: 0.4990 loss_thr: 0.3616 loss_db: 0.0873 loss: 0.9479 2022/08/30 12:32:26 - mmengine - INFO - Epoch(train) [525][40/63] lr: 4.1739e-03 eta: 16:20:56 time: 0.9425 data_time: 0.0381 memory: 16201 loss_prob: 0.5161 loss_thr: 0.3631 loss_db: 0.0920 loss: 0.9712 2022/08/30 12:32:31 - mmengine - INFO - Epoch(train) [525][45/63] lr: 4.1739e-03 eta: 16:20:56 time: 0.9266 data_time: 0.0437 memory: 16201 loss_prob: 0.5564 loss_thr: 0.3833 loss_db: 0.0971 loss: 1.0367 2022/08/30 12:32:35 - mmengine - INFO - Epoch(train) [525][50/63] lr: 4.1739e-03 eta: 16:20:36 time: 0.8803 data_time: 0.0421 memory: 16201 loss_prob: 0.5772 loss_thr: 0.3820 loss_db: 0.0982 loss: 1.0574 2022/08/30 12:32:40 - mmengine - INFO - Epoch(train) [525][55/63] lr: 4.1739e-03 eta: 16:20:36 time: 0.8948 data_time: 0.0530 memory: 16201 loss_prob: 0.5653 loss_thr: 0.3825 loss_db: 0.0976 loss: 1.0454 2022/08/30 12:32:45 - mmengine - INFO - Epoch(train) [525][60/63] lr: 4.1739e-03 eta: 16:20:17 time: 0.9815 data_time: 0.0670 memory: 16201 loss_prob: 0.5063 loss_thr: 0.3599 loss_db: 0.0894 loss: 0.9555 2022/08/30 12:32:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:32:53 - mmengine - INFO - Epoch(train) [526][5/63] lr: 4.1683e-03 eta: 16:20:17 time: 1.0344 data_time: 0.2118 memory: 16201 loss_prob: 0.5416 loss_thr: 0.3658 loss_db: 0.0941 loss: 1.0015 2022/08/30 12:32:57 - mmengine - INFO - Epoch(train) [526][10/63] lr: 4.1683e-03 eta: 16:19:49 time: 1.0232 data_time: 0.2139 memory: 16201 loss_prob: 0.5254 loss_thr: 0.3549 loss_db: 0.0921 loss: 0.9725 2022/08/30 12:33:01 - mmengine - INFO - Epoch(train) [526][15/63] lr: 4.1683e-03 eta: 16:19:49 time: 0.8597 data_time: 0.0390 memory: 16201 loss_prob: 0.5344 loss_thr: 0.3674 loss_db: 0.0938 loss: 0.9955 2022/08/30 12:33:06 - mmengine - INFO - Epoch(train) [526][20/63] lr: 4.1683e-03 eta: 16:19:29 time: 0.9290 data_time: 0.0314 memory: 16201 loss_prob: 0.5701 loss_thr: 0.3903 loss_db: 0.0982 loss: 1.0586 2022/08/30 12:33:11 - mmengine - INFO - Epoch(train) [526][25/63] lr: 4.1683e-03 eta: 16:19:29 time: 0.9557 data_time: 0.0638 memory: 16201 loss_prob: 0.5369 loss_thr: 0.3717 loss_db: 0.0937 loss: 1.0022 2022/08/30 12:33:15 - mmengine - INFO - Epoch(train) [526][30/63] lr: 4.1683e-03 eta: 16:19:09 time: 0.8824 data_time: 0.0612 memory: 16201 loss_prob: 0.5308 loss_thr: 0.3821 loss_db: 0.0933 loss: 1.0062 2022/08/30 12:33:20 - mmengine - INFO - Epoch(train) [526][35/63] lr: 4.1683e-03 eta: 16:19:09 time: 0.8590 data_time: 0.0329 memory: 16201 loss_prob: 0.5453 loss_thr: 0.3788 loss_db: 0.0952 loss: 1.0193 2022/08/30 12:33:25 - mmengine - INFO - Epoch(train) [526][40/63] lr: 4.1683e-03 eta: 16:18:49 time: 0.9335 data_time: 0.0365 memory: 16201 loss_prob: 0.5358 loss_thr: 0.3542 loss_db: 0.0921 loss: 0.9821 2022/08/30 12:33:29 - mmengine - INFO - Epoch(train) [526][45/63] lr: 4.1683e-03 eta: 16:18:49 time: 0.9440 data_time: 0.0427 memory: 16201 loss_prob: 0.5113 loss_thr: 0.3419 loss_db: 0.0880 loss: 0.9411 2022/08/30 12:33:33 - mmengine - INFO - Epoch(train) [526][50/63] lr: 4.1683e-03 eta: 16:18:29 time: 0.8719 data_time: 0.0420 memory: 16201 loss_prob: 0.5154 loss_thr: 0.3487 loss_db: 0.0905 loss: 0.9546 2022/08/30 12:33:38 - mmengine - INFO - Epoch(train) [526][55/63] lr: 4.1683e-03 eta: 16:18:29 time: 0.8573 data_time: 0.0527 memory: 16201 loss_prob: 0.5692 loss_thr: 0.3748 loss_db: 0.0981 loss: 1.0420 2022/08/30 12:33:42 - mmengine - INFO - Epoch(train) [526][60/63] lr: 4.1683e-03 eta: 16:18:08 time: 0.8589 data_time: 0.0465 memory: 16201 loss_prob: 0.6047 loss_thr: 0.3891 loss_db: 0.1024 loss: 1.0963 2022/08/30 12:33:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:33:51 - mmengine - INFO - Epoch(train) [527][5/63] lr: 4.1627e-03 eta: 16:18:08 time: 1.0619 data_time: 0.2113 memory: 16201 loss_prob: 0.5530 loss_thr: 0.3774 loss_db: 0.0964 loss: 1.0268 2022/08/30 12:33:55 - mmengine - INFO - Epoch(train) [527][10/63] lr: 4.1627e-03 eta: 16:17:41 time: 1.0732 data_time: 0.2703 memory: 16201 loss_prob: 0.5549 loss_thr: 0.3668 loss_db: 0.0968 loss: 1.0185 2022/08/30 12:34:00 - mmengine - INFO - Epoch(train) [527][15/63] lr: 4.1627e-03 eta: 16:17:41 time: 0.8806 data_time: 0.0722 memory: 16201 loss_prob: 0.5308 loss_thr: 0.3615 loss_db: 0.0924 loss: 0.9847 2022/08/30 12:34:04 - mmengine - INFO - Epoch(train) [527][20/63] lr: 4.1627e-03 eta: 16:17:21 time: 0.8813 data_time: 0.0276 memory: 16201 loss_prob: 0.5110 loss_thr: 0.3484 loss_db: 0.0870 loss: 0.9464 2022/08/30 12:34:09 - mmengine - INFO - Epoch(train) [527][25/63] lr: 4.1627e-03 eta: 16:17:21 time: 0.8984 data_time: 0.0573 memory: 16201 loss_prob: 0.5152 loss_thr: 0.3465 loss_db: 0.0863 loss: 0.9480 2022/08/30 12:34:13 - mmengine - INFO - Epoch(train) [527][30/63] lr: 4.1627e-03 eta: 16:17:01 time: 0.9328 data_time: 0.0617 memory: 16201 loss_prob: 0.4680 loss_thr: 0.3346 loss_db: 0.0796 loss: 0.8821 2022/08/30 12:34:18 - mmengine - INFO - Epoch(train) [527][35/63] lr: 4.1627e-03 eta: 16:17:01 time: 0.9121 data_time: 0.0371 memory: 16201 loss_prob: 0.4903 loss_thr: 0.3425 loss_db: 0.0838 loss: 0.9166 2022/08/30 12:34:22 - mmengine - INFO - Epoch(train) [527][40/63] lr: 4.1627e-03 eta: 16:16:41 time: 0.8615 data_time: 0.0318 memory: 16201 loss_prob: 0.5107 loss_thr: 0.3437 loss_db: 0.0892 loss: 0.9435 2022/08/30 12:34:27 - mmengine - INFO - Epoch(train) [527][45/63] lr: 4.1627e-03 eta: 16:16:41 time: 0.9520 data_time: 0.0414 memory: 16201 loss_prob: 0.5127 loss_thr: 0.3506 loss_db: 0.0902 loss: 0.9535 2022/08/30 12:34:32 - mmengine - INFO - Epoch(train) [527][50/63] lr: 4.1627e-03 eta: 16:16:22 time: 0.9807 data_time: 0.0637 memory: 16201 loss_prob: 0.5359 loss_thr: 0.3611 loss_db: 0.0923 loss: 0.9893 2022/08/30 12:34:36 - mmengine - INFO - Epoch(train) [527][55/63] lr: 4.1627e-03 eta: 16:16:22 time: 0.8831 data_time: 0.0530 memory: 16201 loss_prob: 0.5234 loss_thr: 0.3626 loss_db: 0.0895 loss: 0.9755 2022/08/30 12:34:40 - mmengine - INFO - Epoch(train) [527][60/63] lr: 4.1627e-03 eta: 16:16:01 time: 0.8509 data_time: 0.0266 memory: 16201 loss_prob: 0.4805 loss_thr: 0.3596 loss_db: 0.0848 loss: 0.9249 2022/08/30 12:34:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:34:50 - mmengine - INFO - Epoch(train) [528][5/63] lr: 4.1572e-03 eta: 16:16:01 time: 1.1047 data_time: 0.2668 memory: 16201 loss_prob: 0.5870 loss_thr: 0.3885 loss_db: 0.1001 loss: 1.0756 2022/08/30 12:34:54 - mmengine - INFO - Epoch(train) [528][10/63] lr: 4.1572e-03 eta: 16:15:35 time: 1.1532 data_time: 0.2871 memory: 16201 loss_prob: 0.5603 loss_thr: 0.3841 loss_db: 0.0955 loss: 1.0399 2022/08/30 12:34:58 - mmengine - INFO - Epoch(train) [528][15/63] lr: 4.1572e-03 eta: 16:15:35 time: 0.8391 data_time: 0.0442 memory: 16201 loss_prob: 0.5250 loss_thr: 0.3740 loss_db: 0.0934 loss: 0.9924 2022/08/30 12:35:02 - mmengine - INFO - Epoch(train) [528][20/63] lr: 4.1572e-03 eta: 16:15:14 time: 0.8206 data_time: 0.0292 memory: 16201 loss_prob: 0.4765 loss_thr: 0.3506 loss_db: 0.0835 loss: 0.9106 2022/08/30 12:35:07 - mmengine - INFO - Epoch(train) [528][25/63] lr: 4.1572e-03 eta: 16:15:14 time: 0.8317 data_time: 0.0457 memory: 16201 loss_prob: 0.5173 loss_thr: 0.3632 loss_db: 0.0874 loss: 0.9679 2022/08/30 12:35:11 - mmengine - INFO - Epoch(train) [528][30/63] lr: 4.1572e-03 eta: 16:14:53 time: 0.8315 data_time: 0.0521 memory: 16201 loss_prob: 0.5336 loss_thr: 0.3685 loss_db: 0.0923 loss: 0.9943 2022/08/30 12:35:15 - mmengine - INFO - Epoch(train) [528][35/63] lr: 4.1572e-03 eta: 16:14:53 time: 0.8467 data_time: 0.0453 memory: 16201 loss_prob: 0.5028 loss_thr: 0.3502 loss_db: 0.0877 loss: 0.9408 2022/08/30 12:35:19 - mmengine - INFO - Epoch(train) [528][40/63] lr: 4.1572e-03 eta: 16:14:32 time: 0.8303 data_time: 0.0394 memory: 16201 loss_prob: 0.5137 loss_thr: 0.3539 loss_db: 0.0863 loss: 0.9539 2022/08/30 12:35:23 - mmengine - INFO - Epoch(train) [528][45/63] lr: 4.1572e-03 eta: 16:14:32 time: 0.8120 data_time: 0.0369 memory: 16201 loss_prob: 0.4738 loss_thr: 0.3278 loss_db: 0.0794 loss: 0.8810 2022/08/30 12:35:28 - mmengine - INFO - Epoch(train) [528][50/63] lr: 4.1572e-03 eta: 16:14:12 time: 0.8779 data_time: 0.0425 memory: 16201 loss_prob: 0.4656 loss_thr: 0.3295 loss_db: 0.0817 loss: 0.8768 2022/08/30 12:35:32 - mmengine - INFO - Epoch(train) [528][55/63] lr: 4.1572e-03 eta: 16:14:12 time: 0.9119 data_time: 0.0474 memory: 16201 loss_prob: 0.5000 loss_thr: 0.3547 loss_db: 0.0869 loss: 0.9417 2022/08/30 12:35:36 - mmengine - INFO - Epoch(train) [528][60/63] lr: 4.1572e-03 eta: 16:13:52 time: 0.8648 data_time: 0.0423 memory: 16201 loss_prob: 0.5241 loss_thr: 0.3648 loss_db: 0.0893 loss: 0.9782 2022/08/30 12:35:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:35:45 - mmengine - INFO - Epoch(train) [529][5/63] lr: 4.1516e-03 eta: 16:13:52 time: 0.9991 data_time: 0.2065 memory: 16201 loss_prob: 0.5199 loss_thr: 0.3843 loss_db: 0.0931 loss: 0.9973 2022/08/30 12:35:49 - mmengine - INFO - Epoch(train) [529][10/63] lr: 4.1516e-03 eta: 16:13:25 time: 1.0717 data_time: 0.2359 memory: 16201 loss_prob: 0.5192 loss_thr: 0.3746 loss_db: 0.0897 loss: 0.9836 2022/08/30 12:35:54 - mmengine - INFO - Epoch(train) [529][15/63] lr: 4.1516e-03 eta: 16:13:25 time: 0.9550 data_time: 0.0554 memory: 16201 loss_prob: 0.5765 loss_thr: 0.3603 loss_db: 0.0919 loss: 1.0287 2022/08/30 12:35:59 - mmengine - INFO - Epoch(train) [529][20/63] lr: 4.1516e-03 eta: 16:13:05 time: 0.9357 data_time: 0.0369 memory: 16201 loss_prob: 0.5643 loss_thr: 0.3540 loss_db: 0.0920 loss: 1.0103 2022/08/30 12:36:03 - mmengine - INFO - Epoch(train) [529][25/63] lr: 4.1516e-03 eta: 16:13:05 time: 0.9153 data_time: 0.0381 memory: 16201 loss_prob: 0.4880 loss_thr: 0.3458 loss_db: 0.0879 loss: 0.9216 2022/08/30 12:36:08 - mmengine - INFO - Epoch(train) [529][30/63] lr: 4.1516e-03 eta: 16:12:45 time: 0.9002 data_time: 0.0325 memory: 16201 loss_prob: 0.4600 loss_thr: 0.3333 loss_db: 0.0837 loss: 0.8770 2022/08/30 12:36:12 - mmengine - INFO - Epoch(train) [529][35/63] lr: 4.1516e-03 eta: 16:12:45 time: 0.8281 data_time: 0.0265 memory: 16201 loss_prob: 0.4492 loss_thr: 0.3328 loss_db: 0.0786 loss: 0.8605 2022/08/30 12:36:16 - mmengine - INFO - Epoch(train) [529][40/63] lr: 4.1516e-03 eta: 16:12:25 time: 0.8415 data_time: 0.0323 memory: 16201 loss_prob: 0.4877 loss_thr: 0.3574 loss_db: 0.0842 loss: 0.9294 2022/08/30 12:36:20 - mmengine - INFO - Epoch(train) [529][45/63] lr: 4.1516e-03 eta: 16:12:25 time: 0.8391 data_time: 0.0393 memory: 16201 loss_prob: 0.5091 loss_thr: 0.3689 loss_db: 0.0882 loss: 0.9662 2022/08/30 12:36:24 - mmengine - INFO - Epoch(train) [529][50/63] lr: 4.1516e-03 eta: 16:12:04 time: 0.8312 data_time: 0.0401 memory: 16201 loss_prob: 0.5387 loss_thr: 0.3905 loss_db: 0.0917 loss: 1.0209 2022/08/30 12:36:29 - mmengine - INFO - Epoch(train) [529][55/63] lr: 4.1516e-03 eta: 16:12:04 time: 0.8639 data_time: 0.0464 memory: 16201 loss_prob: 0.6674 loss_thr: 0.4043 loss_db: 0.1159 loss: 1.1876 2022/08/30 12:36:33 - mmengine - INFO - Epoch(train) [529][60/63] lr: 4.1516e-03 eta: 16:11:44 time: 0.8737 data_time: 0.0424 memory: 16201 loss_prob: 0.6467 loss_thr: 0.3801 loss_db: 0.1144 loss: 1.1412 2022/08/30 12:36:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:36:42 - mmengine - INFO - Epoch(train) [530][5/63] lr: 4.1460e-03 eta: 16:11:44 time: 1.0510 data_time: 0.2051 memory: 16201 loss_prob: 0.6854 loss_thr: 0.3855 loss_db: 0.1176 loss: 1.1886 2022/08/30 12:36:47 - mmengine - INFO - Epoch(train) [530][10/63] lr: 4.1460e-03 eta: 16:11:17 time: 1.0793 data_time: 0.2147 memory: 16201 loss_prob: 0.6428 loss_thr: 0.3798 loss_db: 0.1086 loss: 1.1312 2022/08/30 12:36:51 - mmengine - INFO - Epoch(train) [530][15/63] lr: 4.1460e-03 eta: 16:11:17 time: 0.8907 data_time: 0.0376 memory: 16201 loss_prob: 0.5584 loss_thr: 0.3913 loss_db: 0.0965 loss: 1.0463 2022/08/30 12:36:55 - mmengine - INFO - Epoch(train) [530][20/63] lr: 4.1460e-03 eta: 16:10:57 time: 0.8600 data_time: 0.0256 memory: 16201 loss_prob: 0.6117 loss_thr: 0.4013 loss_db: 0.1073 loss: 1.1203 2022/08/30 12:37:00 - mmengine - INFO - Epoch(train) [530][25/63] lr: 4.1460e-03 eta: 16:10:57 time: 0.8874 data_time: 0.0557 memory: 16201 loss_prob: 0.5435 loss_thr: 0.3611 loss_db: 0.0945 loss: 0.9990 2022/08/30 12:37:04 - mmengine - INFO - Epoch(train) [530][30/63] lr: 4.1460e-03 eta: 16:10:37 time: 0.9271 data_time: 0.0581 memory: 16201 loss_prob: 0.5318 loss_thr: 0.3514 loss_db: 0.0903 loss: 0.9734 2022/08/30 12:37:09 - mmengine - INFO - Epoch(train) [530][35/63] lr: 4.1460e-03 eta: 16:10:37 time: 0.9052 data_time: 0.0335 memory: 16201 loss_prob: 0.6013 loss_thr: 0.3832 loss_db: 0.0996 loss: 1.0841 2022/08/30 12:37:13 - mmengine - INFO - Epoch(train) [530][40/63] lr: 4.1460e-03 eta: 16:10:16 time: 0.8420 data_time: 0.0293 memory: 16201 loss_prob: 0.5741 loss_thr: 0.3707 loss_db: 0.0971 loss: 1.0419 2022/08/30 12:37:17 - mmengine - INFO - Epoch(train) [530][45/63] lr: 4.1460e-03 eta: 16:10:16 time: 0.8250 data_time: 0.0281 memory: 16201 loss_prob: 0.5865 loss_thr: 0.3807 loss_db: 0.1010 loss: 1.0682 2022/08/30 12:37:21 - mmengine - INFO - Epoch(train) [530][50/63] lr: 4.1460e-03 eta: 16:09:56 time: 0.8350 data_time: 0.0323 memory: 16201 loss_prob: 0.5920 loss_thr: 0.3993 loss_db: 0.1027 loss: 1.0939 2022/08/30 12:37:26 - mmengine - INFO - Epoch(train) [530][55/63] lr: 4.1460e-03 eta: 16:09:56 time: 0.8872 data_time: 0.0336 memory: 16201 loss_prob: 0.5749 loss_thr: 0.3791 loss_db: 0.0995 loss: 1.0535 2022/08/30 12:37:30 - mmengine - INFO - Epoch(train) [530][60/63] lr: 4.1460e-03 eta: 16:09:36 time: 0.8823 data_time: 0.0318 memory: 16201 loss_prob: 0.5722 loss_thr: 0.3708 loss_db: 0.0961 loss: 1.0391 2022/08/30 12:37:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:37:38 - mmengine - INFO - Epoch(train) [531][5/63] lr: 4.1405e-03 eta: 16:09:36 time: 0.9831 data_time: 0.1871 memory: 16201 loss_prob: 0.5432 loss_thr: 0.3765 loss_db: 0.0926 loss: 1.0123 2022/08/30 12:37:43 - mmengine - INFO - Epoch(train) [531][10/63] lr: 4.1405e-03 eta: 16:09:08 time: 1.0361 data_time: 0.1990 memory: 16201 loss_prob: 0.5195 loss_thr: 0.3682 loss_db: 0.0892 loss: 0.9770 2022/08/30 12:37:48 - mmengine - INFO - Epoch(train) [531][15/63] lr: 4.1405e-03 eta: 16:09:08 time: 0.9814 data_time: 0.0524 memory: 16201 loss_prob: 0.6763 loss_thr: 0.3833 loss_db: 0.1037 loss: 1.1633 2022/08/30 12:37:52 - mmengine - INFO - Epoch(train) [531][20/63] lr: 4.1405e-03 eta: 16:08:49 time: 0.9611 data_time: 0.0433 memory: 16201 loss_prob: 0.6509 loss_thr: 0.3712 loss_db: 0.0999 loss: 1.1221 2022/08/30 12:37:56 - mmengine - INFO - Epoch(train) [531][25/63] lr: 4.1405e-03 eta: 16:08:49 time: 0.8352 data_time: 0.0424 memory: 16201 loss_prob: 0.4817 loss_thr: 0.3428 loss_db: 0.0853 loss: 0.9097 2022/08/30 12:38:01 - mmengine - INFO - Epoch(train) [531][30/63] lr: 4.1405e-03 eta: 16:08:29 time: 0.8603 data_time: 0.0434 memory: 16201 loss_prob: 0.5304 loss_thr: 0.3648 loss_db: 0.0937 loss: 0.9888 2022/08/30 12:38:06 - mmengine - INFO - Epoch(train) [531][35/63] lr: 4.1405e-03 eta: 16:08:29 time: 0.9693 data_time: 0.0339 memory: 16201 loss_prob: 0.5293 loss_thr: 0.3655 loss_db: 0.0919 loss: 0.9867 2022/08/30 12:38:11 - mmengine - INFO - Epoch(train) [531][40/63] lr: 4.1405e-03 eta: 16:08:10 time: 0.9792 data_time: 0.0445 memory: 16201 loss_prob: 0.5333 loss_thr: 0.3658 loss_db: 0.0927 loss: 0.9918 2022/08/30 12:38:15 - mmengine - INFO - Epoch(train) [531][45/63] lr: 4.1405e-03 eta: 16:08:10 time: 0.8866 data_time: 0.0423 memory: 16201 loss_prob: 0.5226 loss_thr: 0.3584 loss_db: 0.0901 loss: 0.9712 2022/08/30 12:38:19 - mmengine - INFO - Epoch(train) [531][50/63] lr: 4.1405e-03 eta: 16:07:50 time: 0.8488 data_time: 0.0261 memory: 16201 loss_prob: 0.4965 loss_thr: 0.3429 loss_db: 0.0850 loss: 0.9243 2022/08/30 12:38:24 - mmengine - INFO - Epoch(train) [531][55/63] lr: 4.1405e-03 eta: 16:07:50 time: 0.9360 data_time: 0.0285 memory: 16201 loss_prob: 0.5243 loss_thr: 0.3396 loss_db: 0.0909 loss: 0.9547 2022/08/30 12:38:29 - mmengine - INFO - Epoch(train) [531][60/63] lr: 4.1405e-03 eta: 16:07:31 time: 0.9941 data_time: 0.0386 memory: 16201 loss_prob: 0.5345 loss_thr: 0.3539 loss_db: 0.0933 loss: 0.9817 2022/08/30 12:38:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:38:37 - mmengine - INFO - Epoch(train) [532][5/63] lr: 4.1349e-03 eta: 16:07:31 time: 1.0197 data_time: 0.2237 memory: 16201 loss_prob: 0.5968 loss_thr: 0.3924 loss_db: 0.1038 loss: 1.0930 2022/08/30 12:38:42 - mmengine - INFO - Epoch(train) [532][10/63] lr: 4.1349e-03 eta: 16:07:04 time: 1.0416 data_time: 0.1983 memory: 16201 loss_prob: 0.4791 loss_thr: 0.3409 loss_db: 0.0842 loss: 0.9041 2022/08/30 12:38:46 - mmengine - INFO - Epoch(train) [532][15/63] lr: 4.1349e-03 eta: 16:07:04 time: 0.8502 data_time: 0.0345 memory: 16201 loss_prob: 0.4768 loss_thr: 0.3385 loss_db: 0.0807 loss: 0.8960 2022/08/30 12:38:50 - mmengine - INFO - Epoch(train) [532][20/63] lr: 4.1349e-03 eta: 16:06:43 time: 0.8493 data_time: 0.0313 memory: 16201 loss_prob: 0.5081 loss_thr: 0.3710 loss_db: 0.0890 loss: 0.9681 2022/08/30 12:38:55 - mmengine - INFO - Epoch(train) [532][25/63] lr: 4.1349e-03 eta: 16:06:43 time: 0.8809 data_time: 0.0283 memory: 16201 loss_prob: 0.5213 loss_thr: 0.3596 loss_db: 0.0957 loss: 0.9765 2022/08/30 12:38:59 - mmengine - INFO - Epoch(train) [532][30/63] lr: 4.1349e-03 eta: 16:06:24 time: 0.9008 data_time: 0.0599 memory: 16201 loss_prob: 0.5771 loss_thr: 0.3618 loss_db: 0.0990 loss: 1.0379 2022/08/30 12:39:04 - mmengine - INFO - Epoch(train) [532][35/63] lr: 4.1349e-03 eta: 16:06:24 time: 0.9066 data_time: 0.0646 memory: 16201 loss_prob: 0.5975 loss_thr: 0.3756 loss_db: 0.0977 loss: 1.0708 2022/08/30 12:39:08 - mmengine - INFO - Epoch(train) [532][40/63] lr: 4.1349e-03 eta: 16:06:03 time: 0.8647 data_time: 0.0281 memory: 16201 loss_prob: 0.6676 loss_thr: 0.3734 loss_db: 0.1078 loss: 1.1489 2022/08/30 12:39:12 - mmengine - INFO - Epoch(train) [532][45/63] lr: 4.1349e-03 eta: 16:06:03 time: 0.8150 data_time: 0.0287 memory: 16201 loss_prob: 0.6824 loss_thr: 0.3915 loss_db: 0.1115 loss: 1.1855 2022/08/30 12:39:16 - mmengine - INFO - Epoch(train) [532][50/63] lr: 4.1349e-03 eta: 16:05:42 time: 0.8124 data_time: 0.0321 memory: 16201 loss_prob: 0.6537 loss_thr: 0.4031 loss_db: 0.1129 loss: 1.1697 2022/08/30 12:39:20 - mmengine - INFO - Epoch(train) [532][55/63] lr: 4.1349e-03 eta: 16:05:42 time: 0.8386 data_time: 0.0303 memory: 16201 loss_prob: 0.6275 loss_thr: 0.3874 loss_db: 0.1099 loss: 1.1247 2022/08/30 12:39:25 - mmengine - INFO - Epoch(train) [532][60/63] lr: 4.1349e-03 eta: 16:05:22 time: 0.8733 data_time: 0.0820 memory: 16201 loss_prob: 0.5898 loss_thr: 0.3864 loss_db: 0.1001 loss: 1.0763 2022/08/30 12:39:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:39:33 - mmengine - INFO - Epoch(train) [533][5/63] lr: 4.1293e-03 eta: 16:05:22 time: 1.0210 data_time: 0.2447 memory: 16201 loss_prob: 0.6042 loss_thr: 0.4161 loss_db: 0.1050 loss: 1.1253 2022/08/30 12:39:38 - mmengine - INFO - Epoch(train) [533][10/63] lr: 4.1293e-03 eta: 16:04:56 time: 1.0977 data_time: 0.2608 memory: 16201 loss_prob: 0.5932 loss_thr: 0.3894 loss_db: 0.0983 loss: 1.0808 2022/08/30 12:39:42 - mmengine - INFO - Epoch(train) [533][15/63] lr: 4.1293e-03 eta: 16:04:56 time: 0.8871 data_time: 0.0361 memory: 16201 loss_prob: 0.6724 loss_thr: 0.3974 loss_db: 0.1099 loss: 1.1797 2022/08/30 12:39:47 - mmengine - INFO - Epoch(train) [533][20/63] lr: 4.1293e-03 eta: 16:04:36 time: 0.9038 data_time: 0.0228 memory: 16201 loss_prob: 0.6684 loss_thr: 0.4018 loss_db: 0.1153 loss: 1.1854 2022/08/30 12:39:51 - mmengine - INFO - Epoch(train) [533][25/63] lr: 4.1293e-03 eta: 16:04:36 time: 0.9083 data_time: 0.0506 memory: 16201 loss_prob: 0.5615 loss_thr: 0.3758 loss_db: 0.0977 loss: 1.0351 2022/08/30 12:39:55 - mmengine - INFO - Epoch(train) [533][30/63] lr: 4.1293e-03 eta: 16:04:16 time: 0.8530 data_time: 0.0406 memory: 16201 loss_prob: 0.5158 loss_thr: 0.3616 loss_db: 0.0905 loss: 0.9679 2022/08/30 12:39:59 - mmengine - INFO - Epoch(train) [533][35/63] lr: 4.1293e-03 eta: 16:04:16 time: 0.8076 data_time: 0.0210 memory: 16201 loss_prob: 0.5490 loss_thr: 0.3714 loss_db: 0.0944 loss: 1.0148 2022/08/30 12:40:04 - mmengine - INFO - Epoch(train) [533][40/63] lr: 4.1293e-03 eta: 16:03:56 time: 0.9054 data_time: 0.0453 memory: 16201 loss_prob: 0.5801 loss_thr: 0.3793 loss_db: 0.0996 loss: 1.0590 2022/08/30 12:40:09 - mmengine - INFO - Epoch(train) [533][45/63] lr: 4.1293e-03 eta: 16:03:56 time: 0.9494 data_time: 0.0526 memory: 16201 loss_prob: 0.6060 loss_thr: 0.3996 loss_db: 0.1056 loss: 1.1111 2022/08/30 12:40:13 - mmengine - INFO - Epoch(train) [533][50/63] lr: 4.1293e-03 eta: 16:03:36 time: 0.8784 data_time: 0.0476 memory: 16201 loss_prob: 0.5843 loss_thr: 0.3954 loss_db: 0.0998 loss: 1.0796 2022/08/30 12:40:18 - mmengine - INFO - Epoch(train) [533][55/63] lr: 4.1293e-03 eta: 16:03:36 time: 0.8570 data_time: 0.0404 memory: 16201 loss_prob: 0.6221 loss_thr: 0.3971 loss_db: 0.1004 loss: 1.1196 2022/08/30 12:40:22 - mmengine - INFO - Epoch(train) [533][60/63] lr: 4.1293e-03 eta: 16:03:16 time: 0.8816 data_time: 0.0415 memory: 16201 loss_prob: 0.6164 loss_thr: 0.4059 loss_db: 0.1016 loss: 1.1239 2022/08/30 12:40:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:40:31 - mmengine - INFO - Epoch(train) [534][5/63] lr: 4.1237e-03 eta: 16:03:16 time: 1.0371 data_time: 0.2069 memory: 16201 loss_prob: 0.5198 loss_thr: 0.3678 loss_db: 0.0909 loss: 0.9785 2022/08/30 12:40:35 - mmengine - INFO - Epoch(train) [534][10/63] lr: 4.1237e-03 eta: 16:02:49 time: 1.0501 data_time: 0.2152 memory: 16201 loss_prob: 0.5069 loss_thr: 0.3492 loss_db: 0.0884 loss: 0.9446 2022/08/30 12:40:39 - mmengine - INFO - Epoch(train) [534][15/63] lr: 4.1237e-03 eta: 16:02:49 time: 0.8420 data_time: 0.0312 memory: 16201 loss_prob: 0.5066 loss_thr: 0.3537 loss_db: 0.0879 loss: 0.9481 2022/08/30 12:40:45 - mmengine - INFO - Epoch(train) [534][20/63] lr: 4.1237e-03 eta: 16:02:30 time: 0.9611 data_time: 0.0295 memory: 16201 loss_prob: 0.4869 loss_thr: 0.3568 loss_db: 0.0856 loss: 0.9293 2022/08/30 12:40:49 - mmengine - INFO - Epoch(train) [534][25/63] lr: 4.1237e-03 eta: 16:02:30 time: 0.9863 data_time: 0.0517 memory: 16201 loss_prob: 0.4846 loss_thr: 0.3535 loss_db: 0.0855 loss: 0.9236 2022/08/30 12:40:53 - mmengine - INFO - Epoch(train) [534][30/63] lr: 4.1237e-03 eta: 16:02:10 time: 0.8795 data_time: 0.0455 memory: 16201 loss_prob: 0.5259 loss_thr: 0.3545 loss_db: 0.0924 loss: 0.9727 2022/08/30 12:40:58 - mmengine - INFO - Epoch(train) [534][35/63] lr: 4.1237e-03 eta: 16:02:10 time: 0.8587 data_time: 0.0326 memory: 16201 loss_prob: 0.4871 loss_thr: 0.3399 loss_db: 0.0848 loss: 0.9118 2022/08/30 12:41:02 - mmengine - INFO - Epoch(train) [534][40/63] lr: 4.1237e-03 eta: 16:01:50 time: 0.8341 data_time: 0.0360 memory: 16201 loss_prob: 0.5145 loss_thr: 0.3623 loss_db: 0.0886 loss: 0.9654 2022/08/30 12:41:06 - mmengine - INFO - Epoch(train) [534][45/63] lr: 4.1237e-03 eta: 16:01:50 time: 0.8772 data_time: 0.0296 memory: 16201 loss_prob: 0.5721 loss_thr: 0.3877 loss_db: 0.0985 loss: 1.0583 2022/08/30 12:41:10 - mmengine - INFO - Epoch(train) [534][50/63] lr: 4.1237e-03 eta: 16:01:30 time: 0.8781 data_time: 0.0201 memory: 16201 loss_prob: 0.5643 loss_thr: 0.3815 loss_db: 0.0975 loss: 1.0434 2022/08/30 12:41:15 - mmengine - INFO - Epoch(train) [534][55/63] lr: 4.1237e-03 eta: 16:01:30 time: 0.8760 data_time: 0.0481 memory: 16201 loss_prob: 0.6018 loss_thr: 0.4031 loss_db: 0.1034 loss: 1.1084 2022/08/30 12:41:20 - mmengine - INFO - Epoch(train) [534][60/63] lr: 4.1237e-03 eta: 16:01:10 time: 0.9110 data_time: 0.0567 memory: 16201 loss_prob: 0.5815 loss_thr: 0.3958 loss_db: 0.0985 loss: 1.0759 2022/08/30 12:41:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:41:28 - mmengine - INFO - Epoch(train) [535][5/63] lr: 4.1182e-03 eta: 16:01:10 time: 0.9813 data_time: 0.1919 memory: 16201 loss_prob: 0.5266 loss_thr: 0.3829 loss_db: 0.0913 loss: 1.0008 2022/08/30 12:41:32 - mmengine - INFO - Epoch(train) [535][10/63] lr: 4.1182e-03 eta: 16:00:43 time: 1.0252 data_time: 0.2016 memory: 16201 loss_prob: 0.5644 loss_thr: 0.3854 loss_db: 0.0951 loss: 1.0449 2022/08/30 12:41:37 - mmengine - INFO - Epoch(train) [535][15/63] lr: 4.1182e-03 eta: 16:00:43 time: 0.9434 data_time: 0.0276 memory: 16201 loss_prob: 0.5458 loss_thr: 0.3601 loss_db: 0.0923 loss: 0.9982 2022/08/30 12:41:41 - mmengine - INFO - Epoch(train) [535][20/63] lr: 4.1182e-03 eta: 16:00:24 time: 0.9397 data_time: 0.0255 memory: 16201 loss_prob: 0.5245 loss_thr: 0.3551 loss_db: 0.0908 loss: 0.9703 2022/08/30 12:41:46 - mmengine - INFO - Epoch(train) [535][25/63] lr: 4.1182e-03 eta: 16:00:24 time: 0.8530 data_time: 0.0457 memory: 16201 loss_prob: 0.5415 loss_thr: 0.3706 loss_db: 0.0924 loss: 1.0046 2022/08/30 12:41:50 - mmengine - INFO - Epoch(train) [535][30/63] lr: 4.1182e-03 eta: 16:00:03 time: 0.8365 data_time: 0.0409 memory: 16201 loss_prob: 0.5476 loss_thr: 0.3753 loss_db: 0.0955 loss: 1.0185 2022/08/30 12:41:54 - mmengine - INFO - Epoch(train) [535][35/63] lr: 4.1182e-03 eta: 16:00:03 time: 0.8225 data_time: 0.0316 memory: 16201 loss_prob: 0.5589 loss_thr: 0.3822 loss_db: 0.0986 loss: 1.0397 2022/08/30 12:41:58 - mmengine - INFO - Epoch(train) [535][40/63] lr: 4.1182e-03 eta: 15:59:43 time: 0.8419 data_time: 0.0346 memory: 16201 loss_prob: 0.5175 loss_thr: 0.3624 loss_db: 0.0882 loss: 0.9682 2022/08/30 12:42:02 - mmengine - INFO - Epoch(train) [535][45/63] lr: 4.1182e-03 eta: 15:59:43 time: 0.8733 data_time: 0.0408 memory: 16201 loss_prob: 0.4928 loss_thr: 0.3523 loss_db: 0.0840 loss: 0.9291 2022/08/30 12:42:07 - mmengine - INFO - Epoch(train) [535][50/63] lr: 4.1182e-03 eta: 15:59:23 time: 0.8797 data_time: 0.0433 memory: 16201 loss_prob: 0.5212 loss_thr: 0.3744 loss_db: 0.0913 loss: 0.9869 2022/08/30 12:42:11 - mmengine - INFO - Epoch(train) [535][55/63] lr: 4.1182e-03 eta: 15:59:23 time: 0.8761 data_time: 0.0577 memory: 16201 loss_prob: 0.5499 loss_thr: 0.3775 loss_db: 0.0970 loss: 1.0245 2022/08/30 12:42:16 - mmengine - INFO - Epoch(train) [535][60/63] lr: 4.1182e-03 eta: 15:59:04 time: 0.9036 data_time: 0.0540 memory: 16201 loss_prob: 0.5381 loss_thr: 0.3773 loss_db: 0.0924 loss: 1.0077 2022/08/30 12:42:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:42:24 - mmengine - INFO - Epoch(train) [536][5/63] lr: 4.1126e-03 eta: 15:59:04 time: 0.9589 data_time: 0.1805 memory: 16201 loss_prob: 0.5600 loss_thr: 0.3644 loss_db: 0.0925 loss: 1.0169 2022/08/30 12:42:28 - mmengine - INFO - Epoch(train) [536][10/63] lr: 4.1126e-03 eta: 15:58:36 time: 0.9689 data_time: 0.1803 memory: 16201 loss_prob: 0.5075 loss_thr: 0.3397 loss_db: 0.0889 loss: 0.9361 2022/08/30 12:42:32 - mmengine - INFO - Epoch(train) [536][15/63] lr: 4.1126e-03 eta: 15:58:36 time: 0.8257 data_time: 0.0293 memory: 16201 loss_prob: 0.5198 loss_thr: 0.3459 loss_db: 0.0900 loss: 0.9557 2022/08/30 12:42:37 - mmengine - INFO - Epoch(train) [536][20/63] lr: 4.1126e-03 eta: 15:58:16 time: 0.8891 data_time: 0.0317 memory: 16201 loss_prob: 0.5180 loss_thr: 0.3491 loss_db: 0.0876 loss: 0.9546 2022/08/30 12:42:41 - mmengine - INFO - Epoch(train) [536][25/63] lr: 4.1126e-03 eta: 15:58:16 time: 0.8743 data_time: 0.0299 memory: 16201 loss_prob: 0.5335 loss_thr: 0.3671 loss_db: 0.0933 loss: 0.9939 2022/08/30 12:42:46 - mmengine - INFO - Epoch(train) [536][30/63] lr: 4.1126e-03 eta: 15:57:56 time: 0.8765 data_time: 0.0253 memory: 16201 loss_prob: 0.5389 loss_thr: 0.3652 loss_db: 0.0942 loss: 0.9983 2022/08/30 12:42:50 - mmengine - INFO - Epoch(train) [536][35/63] lr: 4.1126e-03 eta: 15:57:56 time: 0.8977 data_time: 0.0256 memory: 16201 loss_prob: 0.5036 loss_thr: 0.3484 loss_db: 0.0869 loss: 0.9389 2022/08/30 12:42:54 - mmengine - INFO - Epoch(train) [536][40/63] lr: 4.1126e-03 eta: 15:57:36 time: 0.8945 data_time: 0.0382 memory: 16201 loss_prob: 0.4726 loss_thr: 0.3356 loss_db: 0.0815 loss: 0.8897 2022/08/30 12:42:59 - mmengine - INFO - Epoch(train) [536][45/63] lr: 4.1126e-03 eta: 15:57:36 time: 0.8937 data_time: 0.0479 memory: 16201 loss_prob: 0.4923 loss_thr: 0.3583 loss_db: 0.0858 loss: 0.9364 2022/08/30 12:43:03 - mmengine - INFO - Epoch(train) [536][50/63] lr: 4.1126e-03 eta: 15:57:16 time: 0.8596 data_time: 0.0349 memory: 16201 loss_prob: 0.5115 loss_thr: 0.3669 loss_db: 0.0912 loss: 0.9695 2022/08/30 12:43:08 - mmengine - INFO - Epoch(train) [536][55/63] lr: 4.1126e-03 eta: 15:57:16 time: 0.9075 data_time: 0.0742 memory: 16201 loss_prob: 0.5322 loss_thr: 0.3544 loss_db: 0.0906 loss: 0.9772 2022/08/30 12:43:12 - mmengine - INFO - Epoch(train) [536][60/63] lr: 4.1126e-03 eta: 15:56:57 time: 0.8974 data_time: 0.0830 memory: 16201 loss_prob: 0.5310 loss_thr: 0.3540 loss_db: 0.0889 loss: 0.9740 2022/08/30 12:43:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:43:20 - mmengine - INFO - Epoch(train) [537][5/63] lr: 4.1070e-03 eta: 15:56:57 time: 0.9518 data_time: 0.1937 memory: 16201 loss_prob: 0.5013 loss_thr: 0.3413 loss_db: 0.0850 loss: 0.9276 2022/08/30 12:43:24 - mmengine - INFO - Epoch(train) [537][10/63] lr: 4.1070e-03 eta: 15:56:29 time: 0.9994 data_time: 0.2095 memory: 16201 loss_prob: 0.5302 loss_thr: 0.3595 loss_db: 0.0902 loss: 0.9799 2022/08/30 12:43:28 - mmengine - INFO - Epoch(train) [537][15/63] lr: 4.1070e-03 eta: 15:56:29 time: 0.8172 data_time: 0.0303 memory: 16201 loss_prob: 0.5407 loss_thr: 0.3798 loss_db: 0.0930 loss: 1.0135 2022/08/30 12:43:33 - mmengine - INFO - Epoch(train) [537][20/63] lr: 4.1070e-03 eta: 15:56:09 time: 0.8471 data_time: 0.0173 memory: 16201 loss_prob: 0.5292 loss_thr: 0.3813 loss_db: 0.0909 loss: 1.0014 2022/08/30 12:43:37 - mmengine - INFO - Epoch(train) [537][25/63] lr: 4.1070e-03 eta: 15:56:09 time: 0.9041 data_time: 0.0511 memory: 16201 loss_prob: 0.5477 loss_thr: 0.3742 loss_db: 0.0944 loss: 1.0163 2022/08/30 12:43:41 - mmengine - INFO - Epoch(train) [537][30/63] lr: 4.1070e-03 eta: 15:55:49 time: 0.8742 data_time: 0.0429 memory: 16201 loss_prob: 0.5400 loss_thr: 0.3588 loss_db: 0.0924 loss: 0.9913 2022/08/30 12:43:46 - mmengine - INFO - Epoch(train) [537][35/63] lr: 4.1070e-03 eta: 15:55:49 time: 0.8686 data_time: 0.0305 memory: 16201 loss_prob: 0.4843 loss_thr: 0.3342 loss_db: 0.0839 loss: 0.9025 2022/08/30 12:43:50 - mmengine - INFO - Epoch(train) [537][40/63] lr: 4.1070e-03 eta: 15:55:29 time: 0.8813 data_time: 0.0604 memory: 16201 loss_prob: 0.5208 loss_thr: 0.3595 loss_db: 0.0920 loss: 0.9723 2022/08/30 12:43:54 - mmengine - INFO - Epoch(train) [537][45/63] lr: 4.1070e-03 eta: 15:55:29 time: 0.8473 data_time: 0.0502 memory: 16201 loss_prob: 0.5320 loss_thr: 0.3683 loss_db: 0.0921 loss: 0.9924 2022/08/30 12:43:59 - mmengine - INFO - Epoch(train) [537][50/63] lr: 4.1070e-03 eta: 15:55:09 time: 0.8642 data_time: 0.0324 memory: 16201 loss_prob: 0.5143 loss_thr: 0.3386 loss_db: 0.0842 loss: 0.9371 2022/08/30 12:44:03 - mmengine - INFO - Epoch(train) [537][55/63] lr: 4.1070e-03 eta: 15:55:09 time: 0.9102 data_time: 0.0566 memory: 16201 loss_prob: 0.5217 loss_thr: 0.3422 loss_db: 0.0882 loss: 0.9520 2022/08/30 12:44:08 - mmengine - INFO - Epoch(train) [537][60/63] lr: 4.1070e-03 eta: 15:54:50 time: 0.9239 data_time: 0.0573 memory: 16201 loss_prob: 0.4722 loss_thr: 0.3375 loss_db: 0.0827 loss: 0.8924 2022/08/30 12:44:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:44:16 - mmengine - INFO - Epoch(train) [538][5/63] lr: 4.1014e-03 eta: 15:54:50 time: 1.0073 data_time: 0.1724 memory: 16201 loss_prob: 0.4854 loss_thr: 0.3516 loss_db: 0.0860 loss: 0.9230 2022/08/30 12:44:20 - mmengine - INFO - Epoch(train) [538][10/63] lr: 4.1014e-03 eta: 15:54:23 time: 1.0374 data_time: 0.1984 memory: 16201 loss_prob: 0.5705 loss_thr: 0.3778 loss_db: 0.0996 loss: 1.0479 2022/08/30 12:44:25 - mmengine - INFO - Epoch(train) [538][15/63] lr: 4.1014e-03 eta: 15:54:23 time: 0.9292 data_time: 0.0462 memory: 16201 loss_prob: 0.5664 loss_thr: 0.3706 loss_db: 0.0963 loss: 1.0333 2022/08/30 12:44:30 - mmengine - INFO - Epoch(train) [538][20/63] lr: 4.1014e-03 eta: 15:54:03 time: 0.9130 data_time: 0.0293 memory: 16201 loss_prob: 0.5489 loss_thr: 0.3681 loss_db: 0.0936 loss: 1.0106 2022/08/30 12:44:34 - mmengine - INFO - Epoch(train) [538][25/63] lr: 4.1014e-03 eta: 15:54:03 time: 0.8450 data_time: 0.0508 memory: 16201 loss_prob: 0.5686 loss_thr: 0.3773 loss_db: 0.0970 loss: 1.0429 2022/08/30 12:44:38 - mmengine - INFO - Epoch(train) [538][30/63] lr: 4.1014e-03 eta: 15:53:43 time: 0.8513 data_time: 0.0496 memory: 16201 loss_prob: 0.5883 loss_thr: 0.3863 loss_db: 0.1016 loss: 1.0762 2022/08/30 12:44:42 - mmengine - INFO - Epoch(train) [538][35/63] lr: 4.1014e-03 eta: 15:53:43 time: 0.8535 data_time: 0.0319 memory: 16201 loss_prob: 0.5662 loss_thr: 0.3847 loss_db: 0.0989 loss: 1.0498 2022/08/30 12:44:47 - mmengine - INFO - Epoch(train) [538][40/63] lr: 4.1014e-03 eta: 15:53:24 time: 0.9169 data_time: 0.0274 memory: 16201 loss_prob: 0.5007 loss_thr: 0.3528 loss_db: 0.0846 loss: 0.9381 2022/08/30 12:44:52 - mmengine - INFO - Epoch(train) [538][45/63] lr: 4.1014e-03 eta: 15:53:24 time: 0.9240 data_time: 0.0333 memory: 16201 loss_prob: 0.5121 loss_thr: 0.3415 loss_db: 0.0882 loss: 0.9418 2022/08/30 12:44:56 - mmengine - INFO - Epoch(train) [538][50/63] lr: 4.1014e-03 eta: 15:53:04 time: 0.8463 data_time: 0.0350 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3206 loss_db: 0.0840 loss: 0.8797 2022/08/30 12:45:00 - mmengine - INFO - Epoch(train) [538][55/63] lr: 4.1014e-03 eta: 15:53:04 time: 0.8197 data_time: 0.0380 memory: 16201 loss_prob: 0.4681 loss_thr: 0.3336 loss_db: 0.0816 loss: 0.8833 2022/08/30 12:45:05 - mmengine - INFO - Epoch(train) [538][60/63] lr: 4.1014e-03 eta: 15:52:45 time: 0.9635 data_time: 0.0435 memory: 16201 loss_prob: 0.5225 loss_thr: 0.3600 loss_db: 0.0901 loss: 0.9726 2022/08/30 12:45:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:45:13 - mmengine - INFO - Epoch(train) [539][5/63] lr: 4.0959e-03 eta: 15:52:45 time: 1.0148 data_time: 0.1965 memory: 16201 loss_prob: 0.5191 loss_thr: 0.3515 loss_db: 0.0888 loss: 0.9594 2022/08/30 12:45:18 - mmengine - INFO - Epoch(train) [539][10/63] lr: 4.0959e-03 eta: 15:52:18 time: 1.0407 data_time: 0.2151 memory: 16201 loss_prob: 0.5649 loss_thr: 0.3683 loss_db: 0.0964 loss: 1.0296 2022/08/30 12:45:22 - mmengine - INFO - Epoch(train) [539][15/63] lr: 4.0959e-03 eta: 15:52:18 time: 0.8784 data_time: 0.0505 memory: 16201 loss_prob: 0.5357 loss_thr: 0.3568 loss_db: 0.0905 loss: 0.9829 2022/08/30 12:45:27 - mmengine - INFO - Epoch(train) [539][20/63] lr: 4.0959e-03 eta: 15:51:59 time: 0.9543 data_time: 0.0287 memory: 16201 loss_prob: 0.4661 loss_thr: 0.3245 loss_db: 0.0815 loss: 0.8721 2022/08/30 12:45:32 - mmengine - INFO - Epoch(train) [539][25/63] lr: 4.0959e-03 eta: 15:51:59 time: 1.0006 data_time: 0.0521 memory: 16201 loss_prob: 0.4755 loss_thr: 0.3379 loss_db: 0.0852 loss: 0.8987 2022/08/30 12:45:36 - mmengine - INFO - Epoch(train) [539][30/63] lr: 4.0959e-03 eta: 15:51:40 time: 0.8931 data_time: 0.0525 memory: 16201 loss_prob: 0.5373 loss_thr: 0.3652 loss_db: 0.0931 loss: 0.9955 2022/08/30 12:45:41 - mmengine - INFO - Epoch(train) [539][35/63] lr: 4.0959e-03 eta: 15:51:40 time: 0.8472 data_time: 0.0266 memory: 16201 loss_prob: 0.5832 loss_thr: 0.3788 loss_db: 0.0990 loss: 1.0610 2022/08/30 12:45:46 - mmengine - INFO - Epoch(train) [539][40/63] lr: 4.0959e-03 eta: 15:51:21 time: 0.9564 data_time: 0.0511 memory: 16201 loss_prob: 0.5462 loss_thr: 0.3778 loss_db: 0.0947 loss: 1.0186 2022/08/30 12:45:50 - mmengine - INFO - Epoch(train) [539][45/63] lr: 4.0959e-03 eta: 15:51:21 time: 0.9638 data_time: 0.0623 memory: 16201 loss_prob: 0.5418 loss_thr: 0.3579 loss_db: 0.0930 loss: 0.9927 2022/08/30 12:45:54 - mmengine - INFO - Epoch(train) [539][50/63] lr: 4.0959e-03 eta: 15:51:01 time: 0.8587 data_time: 0.0368 memory: 16201 loss_prob: 0.5449 loss_thr: 0.3466 loss_db: 0.0898 loss: 0.9812 2022/08/30 12:45:59 - mmengine - INFO - Epoch(train) [539][55/63] lr: 4.0959e-03 eta: 15:51:01 time: 0.8501 data_time: 0.0343 memory: 16201 loss_prob: 0.5582 loss_thr: 0.3743 loss_db: 0.0954 loss: 1.0279 2022/08/30 12:46:03 - mmengine - INFO - Epoch(train) [539][60/63] lr: 4.0959e-03 eta: 15:50:41 time: 0.8566 data_time: 0.0398 memory: 16201 loss_prob: 0.5802 loss_thr: 0.3873 loss_db: 0.1028 loss: 1.0704 2022/08/30 12:46:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:46:12 - mmengine - INFO - Epoch(train) [540][5/63] lr: 4.0903e-03 eta: 15:50:41 time: 1.0323 data_time: 0.2449 memory: 16201 loss_prob: 0.5387 loss_thr: 0.3728 loss_db: 0.0926 loss: 1.0041 2022/08/30 12:46:17 - mmengine - INFO - Epoch(train) [540][10/63] lr: 4.0903e-03 eta: 15:50:15 time: 1.1191 data_time: 0.2742 memory: 16201 loss_prob: 0.5054 loss_thr: 0.3727 loss_db: 0.0875 loss: 0.9656 2022/08/30 12:46:21 - mmengine - INFO - Epoch(train) [540][15/63] lr: 4.0903e-03 eta: 15:50:15 time: 0.9131 data_time: 0.0621 memory: 16201 loss_prob: 0.4749 loss_thr: 0.3541 loss_db: 0.0851 loss: 0.9141 2022/08/30 12:46:25 - mmengine - INFO - Epoch(train) [540][20/63] lr: 4.0903e-03 eta: 15:49:55 time: 0.8634 data_time: 0.0230 memory: 16201 loss_prob: 0.5229 loss_thr: 0.3572 loss_db: 0.0923 loss: 0.9724 2022/08/30 12:46:29 - mmengine - INFO - Epoch(train) [540][25/63] lr: 4.0903e-03 eta: 15:49:55 time: 0.8625 data_time: 0.0428 memory: 16201 loss_prob: 0.5486 loss_thr: 0.3540 loss_db: 0.0941 loss: 0.9967 2022/08/30 12:46:34 - mmengine - INFO - Epoch(train) [540][30/63] lr: 4.0903e-03 eta: 15:49:35 time: 0.8643 data_time: 0.0420 memory: 16201 loss_prob: 0.5199 loss_thr: 0.3481 loss_db: 0.0906 loss: 0.9586 2022/08/30 12:46:38 - mmengine - INFO - Epoch(train) [540][35/63] lr: 4.0903e-03 eta: 15:49:35 time: 0.8743 data_time: 0.0305 memory: 16201 loss_prob: 0.5211 loss_thr: 0.3587 loss_db: 0.0919 loss: 0.9717 2022/08/30 12:46:43 - mmengine - INFO - Epoch(train) [540][40/63] lr: 4.0903e-03 eta: 15:49:16 time: 0.8828 data_time: 0.0600 memory: 16201 loss_prob: 0.5260 loss_thr: 0.3701 loss_db: 0.0919 loss: 0.9879 2022/08/30 12:46:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:46:48 - mmengine - INFO - Epoch(train) [540][45/63] lr: 4.0903e-03 eta: 15:49:16 time: 1.0085 data_time: 0.1240 memory: 16201 loss_prob: 0.5029 loss_thr: 0.3471 loss_db: 0.0874 loss: 0.9374 2022/08/30 12:46:53 - mmengine - INFO - Epoch(train) [540][50/63] lr: 4.0903e-03 eta: 15:48:58 time: 1.0489 data_time: 0.1156 memory: 16201 loss_prob: 0.4496 loss_thr: 0.3171 loss_db: 0.0781 loss: 0.8449 2022/08/30 12:46:57 - mmengine - INFO - Epoch(train) [540][55/63] lr: 4.0903e-03 eta: 15:48:58 time: 0.9088 data_time: 0.0457 memory: 16201 loss_prob: 0.4801 loss_thr: 0.3513 loss_db: 0.0812 loss: 0.9126 2022/08/30 12:47:02 - mmengine - INFO - Epoch(train) [540][60/63] lr: 4.0903e-03 eta: 15:48:38 time: 0.8694 data_time: 0.0493 memory: 16201 loss_prob: 0.5546 loss_thr: 0.3848 loss_db: 0.0947 loss: 1.0341 2022/08/30 12:47:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:47:05 - mmengine - INFO - Saving checkpoint at 540 epochs 2022/08/30 12:47:13 - mmengine - INFO - Epoch(val) [540][5/32] eta: 15:48:38 time: 0.6563 data_time: 0.1206 memory: 16201 2022/08/30 12:47:16 - mmengine - INFO - Epoch(val) [540][10/32] eta: 0:00:15 time: 0.7134 data_time: 0.1383 memory: 15734 2022/08/30 12:47:19 - mmengine - INFO - Epoch(val) [540][15/32] eta: 0:00:15 time: 0.6125 data_time: 0.0563 memory: 15734 2022/08/30 12:47:23 - mmengine - INFO - Epoch(val) [540][20/32] eta: 0:00:08 time: 0.6684 data_time: 0.0919 memory: 15734 2022/08/30 12:47:27 - mmengine - INFO - Epoch(val) [540][25/32] eta: 0:00:08 time: 0.7089 data_time: 0.0744 memory: 15734 2022/08/30 12:47:29 - mmengine - INFO - Epoch(val) [540][30/32] eta: 0:00:01 time: 0.6275 data_time: 0.0276 memory: 15734 2022/08/30 12:47:30 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 12:47:30 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8382, precision: 0.7914, hmean: 0.8141 2022/08/30 12:47:30 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8377, precision: 0.8333, hmean: 0.8355 2022/08/30 12:47:30 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8368, precision: 0.8595, hmean: 0.8480 2022/08/30 12:47:30 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8329, precision: 0.8768, hmean: 0.8543 2022/08/30 12:47:30 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8151, precision: 0.8958, hmean: 0.8535 2022/08/30 12:47:30 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7285, precision: 0.9254, hmean: 0.8152 2022/08/30 12:47:30 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1363, precision: 0.9826, hmean: 0.2393 2022/08/30 12:47:30 - mmengine - INFO - Epoch(val) [540][32/32] icdar/precision: 0.8768 icdar/recall: 0.8329 icdar/hmean: 0.8543 2022/08/30 12:47:37 - mmengine - INFO - Epoch(train) [541][5/63] lr: 4.0847e-03 eta: 0:00:01 time: 1.1116 data_time: 0.2403 memory: 16201 loss_prob: 0.5069 loss_thr: 0.3446 loss_db: 0.0890 loss: 0.9405 2022/08/30 12:47:41 - mmengine - INFO - Epoch(train) [541][10/63] lr: 4.0847e-03 eta: 15:48:12 time: 1.0490 data_time: 0.2351 memory: 16201 loss_prob: 0.4944 loss_thr: 0.3400 loss_db: 0.0849 loss: 0.9192 2022/08/30 12:47:46 - mmengine - INFO - Epoch(train) [541][15/63] lr: 4.0847e-03 eta: 15:48:12 time: 0.9189 data_time: 0.0354 memory: 16201 loss_prob: 0.5558 loss_thr: 0.3771 loss_db: 0.0951 loss: 1.0280 2022/08/30 12:47:50 - mmengine - INFO - Epoch(train) [541][20/63] lr: 4.0847e-03 eta: 15:47:53 time: 0.9482 data_time: 0.0348 memory: 16201 loss_prob: 0.5536 loss_thr: 0.3758 loss_db: 0.0967 loss: 1.0262 2022/08/30 12:47:55 - mmengine - INFO - Epoch(train) [541][25/63] lr: 4.0847e-03 eta: 15:47:53 time: 0.8787 data_time: 0.0468 memory: 16201 loss_prob: 0.5106 loss_thr: 0.3684 loss_db: 0.0882 loss: 0.9672 2022/08/30 12:47:59 - mmengine - INFO - Epoch(train) [541][30/63] lr: 4.0847e-03 eta: 15:47:33 time: 0.8918 data_time: 0.0658 memory: 16201 loss_prob: 0.5091 loss_thr: 0.3697 loss_db: 0.0874 loss: 0.9662 2022/08/30 12:48:04 - mmengine - INFO - Epoch(train) [541][35/63] lr: 4.0847e-03 eta: 15:47:33 time: 0.9068 data_time: 0.0640 memory: 16201 loss_prob: 0.5621 loss_thr: 0.3800 loss_db: 0.0983 loss: 1.0404 2022/08/30 12:48:08 - mmengine - INFO - Epoch(train) [541][40/63] lr: 4.0847e-03 eta: 15:47:14 time: 0.8754 data_time: 0.0431 memory: 16201 loss_prob: 0.6338 loss_thr: 0.3953 loss_db: 0.1110 loss: 1.1400 2022/08/30 12:48:13 - mmengine - INFO - Epoch(train) [541][45/63] lr: 4.0847e-03 eta: 15:47:14 time: 0.8681 data_time: 0.0454 memory: 16201 loss_prob: 0.5886 loss_thr: 0.3887 loss_db: 0.1035 loss: 1.0808 2022/08/30 12:48:17 - mmengine - INFO - Epoch(train) [541][50/63] lr: 4.0847e-03 eta: 15:46:54 time: 0.9026 data_time: 0.0586 memory: 16201 loss_prob: 0.5142 loss_thr: 0.3641 loss_db: 0.0892 loss: 0.9675 2022/08/30 12:48:21 - mmengine - INFO - Epoch(train) [541][55/63] lr: 4.0847e-03 eta: 15:46:54 time: 0.8539 data_time: 0.0437 memory: 16201 loss_prob: 0.5397 loss_thr: 0.3621 loss_db: 0.0935 loss: 0.9953 2022/08/30 12:48:26 - mmengine - INFO - Epoch(train) [541][60/63] lr: 4.0847e-03 eta: 15:46:34 time: 0.8577 data_time: 0.0436 memory: 16201 loss_prob: 0.5097 loss_thr: 0.3567 loss_db: 0.0887 loss: 0.9551 2022/08/30 12:48:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:48:34 - mmengine - INFO - Epoch(train) [542][5/63] lr: 4.0791e-03 eta: 15:46:34 time: 0.9848 data_time: 0.2068 memory: 16201 loss_prob: 0.5221 loss_thr: 0.3679 loss_db: 0.0892 loss: 0.9792 2022/08/30 12:48:38 - mmengine - INFO - Epoch(train) [542][10/63] lr: 4.0791e-03 eta: 15:46:08 time: 1.0578 data_time: 0.2235 memory: 16201 loss_prob: 0.5452 loss_thr: 0.3729 loss_db: 0.0945 loss: 1.0125 2022/08/30 12:48:43 - mmengine - INFO - Epoch(train) [542][15/63] lr: 4.0791e-03 eta: 15:46:08 time: 0.9488 data_time: 0.0458 memory: 16201 loss_prob: 0.5013 loss_thr: 0.3519 loss_db: 0.0883 loss: 0.9415 2022/08/30 12:48:48 - mmengine - INFO - Epoch(train) [542][20/63] lr: 4.0791e-03 eta: 15:45:49 time: 0.9759 data_time: 0.0777 memory: 16201 loss_prob: 0.5354 loss_thr: 0.3567 loss_db: 0.0925 loss: 0.9845 2022/08/30 12:48:52 - mmengine - INFO - Epoch(train) [542][25/63] lr: 4.0791e-03 eta: 15:45:49 time: 0.9225 data_time: 0.0856 memory: 16201 loss_prob: 0.5201 loss_thr: 0.3429 loss_db: 0.0896 loss: 0.9526 2022/08/30 12:48:57 - mmengine - INFO - Epoch(train) [542][30/63] lr: 4.0791e-03 eta: 15:45:29 time: 0.8548 data_time: 0.0396 memory: 16201 loss_prob: 0.4918 loss_thr: 0.3324 loss_db: 0.0855 loss: 0.9097 2022/08/30 12:49:01 - mmengine - INFO - Epoch(train) [542][35/63] lr: 4.0791e-03 eta: 15:45:29 time: 0.8535 data_time: 0.0295 memory: 16201 loss_prob: 0.4956 loss_thr: 0.3355 loss_db: 0.0850 loss: 0.9162 2022/08/30 12:49:06 - mmengine - INFO - Epoch(train) [542][40/63] lr: 4.0791e-03 eta: 15:45:10 time: 0.9081 data_time: 0.0380 memory: 16201 loss_prob: 0.5272 loss_thr: 0.3692 loss_db: 0.0914 loss: 0.9877 2022/08/30 12:49:10 - mmengine - INFO - Epoch(train) [542][45/63] lr: 4.0791e-03 eta: 15:45:10 time: 0.8985 data_time: 0.0454 memory: 16201 loss_prob: 0.5577 loss_thr: 0.3821 loss_db: 0.0978 loss: 1.0376 2022/08/30 12:49:14 - mmengine - INFO - Epoch(train) [542][50/63] lr: 4.0791e-03 eta: 15:44:50 time: 0.8658 data_time: 0.0357 memory: 16201 loss_prob: 0.4953 loss_thr: 0.3346 loss_db: 0.0862 loss: 0.9162 2022/08/30 12:49:19 - mmengine - INFO - Epoch(train) [542][55/63] lr: 4.0791e-03 eta: 15:44:50 time: 0.8931 data_time: 0.0402 memory: 16201 loss_prob: 0.4645 loss_thr: 0.3173 loss_db: 0.0810 loss: 0.8627 2022/08/30 12:49:23 - mmengine - INFO - Epoch(train) [542][60/63] lr: 4.0791e-03 eta: 15:44:31 time: 0.8712 data_time: 0.0463 memory: 16201 loss_prob: 0.4827 loss_thr: 0.3302 loss_db: 0.0846 loss: 0.8975 2022/08/30 12:49:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:49:32 - mmengine - INFO - Epoch(train) [543][5/63] lr: 4.0736e-03 eta: 15:44:31 time: 1.0472 data_time: 0.2058 memory: 16201 loss_prob: 0.4753 loss_thr: 0.3411 loss_db: 0.0857 loss: 0.9021 2022/08/30 12:49:36 - mmengine - INFO - Epoch(train) [543][10/63] lr: 4.0736e-03 eta: 15:44:05 time: 1.0950 data_time: 0.2116 memory: 16201 loss_prob: 0.4832 loss_thr: 0.3444 loss_db: 0.0845 loss: 0.9121 2022/08/30 12:49:41 - mmengine - INFO - Epoch(train) [543][15/63] lr: 4.0736e-03 eta: 15:44:05 time: 0.9065 data_time: 0.0316 memory: 16201 loss_prob: 0.4723 loss_thr: 0.3456 loss_db: 0.0826 loss: 0.9005 2022/08/30 12:49:46 - mmengine - INFO - Epoch(train) [543][20/63] lr: 4.0736e-03 eta: 15:43:45 time: 0.9068 data_time: 0.0259 memory: 16201 loss_prob: 0.4993 loss_thr: 0.3554 loss_db: 0.0868 loss: 0.9415 2022/08/30 12:49:50 - mmengine - INFO - Epoch(train) [543][25/63] lr: 4.0736e-03 eta: 15:43:45 time: 0.9210 data_time: 0.0581 memory: 16201 loss_prob: 0.4750 loss_thr: 0.3350 loss_db: 0.0830 loss: 0.8931 2022/08/30 12:49:55 - mmengine - INFO - Epoch(train) [543][30/63] lr: 4.0736e-03 eta: 15:43:26 time: 0.9052 data_time: 0.0530 memory: 16201 loss_prob: 0.4875 loss_thr: 0.3442 loss_db: 0.0839 loss: 0.9156 2022/08/30 12:49:59 - mmengine - INFO - Epoch(train) [543][35/63] lr: 4.0736e-03 eta: 15:43:26 time: 0.8553 data_time: 0.0218 memory: 16201 loss_prob: 0.5166 loss_thr: 0.3581 loss_db: 0.0931 loss: 0.9679 2022/08/30 12:50:03 - mmengine - INFO - Epoch(train) [543][40/63] lr: 4.0736e-03 eta: 15:43:06 time: 0.8450 data_time: 0.0405 memory: 16201 loss_prob: 0.4977 loss_thr: 0.3447 loss_db: 0.0901 loss: 0.9325 2022/08/30 12:50:07 - mmengine - INFO - Epoch(train) [543][45/63] lr: 4.0736e-03 eta: 15:43:06 time: 0.8614 data_time: 0.0452 memory: 16201 loss_prob: 0.5255 loss_thr: 0.3702 loss_db: 0.0905 loss: 0.9863 2022/08/30 12:50:12 - mmengine - INFO - Epoch(train) [543][50/63] lr: 4.0736e-03 eta: 15:42:46 time: 0.8472 data_time: 0.0326 memory: 16201 loss_prob: 0.5223 loss_thr: 0.3662 loss_db: 0.0921 loss: 0.9805 2022/08/30 12:50:17 - mmengine - INFO - Epoch(train) [543][55/63] lr: 4.0736e-03 eta: 15:42:46 time: 0.9334 data_time: 0.0522 memory: 16201 loss_prob: 0.5163 loss_thr: 0.3485 loss_db: 0.0913 loss: 0.9560 2022/08/30 12:50:21 - mmengine - INFO - Epoch(train) [543][60/63] lr: 4.0736e-03 eta: 15:42:28 time: 0.9528 data_time: 0.0511 memory: 16201 loss_prob: 0.5038 loss_thr: 0.3537 loss_db: 0.0871 loss: 0.9446 2022/08/30 12:50:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:50:29 - mmengine - INFO - Epoch(train) [544][5/63] lr: 4.0680e-03 eta: 15:42:28 time: 1.0060 data_time: 0.2150 memory: 16201 loss_prob: 0.5017 loss_thr: 0.3342 loss_db: 0.0917 loss: 0.9277 2022/08/30 12:50:34 - mmengine - INFO - Epoch(train) [544][10/63] lr: 4.0680e-03 eta: 15:42:01 time: 1.0834 data_time: 0.2556 memory: 16201 loss_prob: 0.5202 loss_thr: 0.3666 loss_db: 0.0886 loss: 0.9754 2022/08/30 12:50:39 - mmengine - INFO - Epoch(train) [544][15/63] lr: 4.0680e-03 eta: 15:42:01 time: 0.9642 data_time: 0.0785 memory: 16201 loss_prob: 0.5463 loss_thr: 0.3975 loss_db: 0.0942 loss: 1.0380 2022/08/30 12:50:43 - mmengine - INFO - Epoch(train) [544][20/63] lr: 4.0680e-03 eta: 15:41:43 time: 0.9307 data_time: 0.0401 memory: 16201 loss_prob: 0.5162 loss_thr: 0.3690 loss_db: 0.0917 loss: 0.9769 2022/08/30 12:50:48 - mmengine - INFO - Epoch(train) [544][25/63] lr: 4.0680e-03 eta: 15:41:43 time: 0.9253 data_time: 0.0579 memory: 16201 loss_prob: 0.5107 loss_thr: 0.3513 loss_db: 0.0888 loss: 0.9508 2022/08/30 12:50:53 - mmengine - INFO - Epoch(train) [544][30/63] lr: 4.0680e-03 eta: 15:41:24 time: 0.9227 data_time: 0.0669 memory: 16201 loss_prob: 0.5256 loss_thr: 0.3520 loss_db: 0.0894 loss: 0.9669 2022/08/30 12:50:57 - mmengine - INFO - Epoch(train) [544][35/63] lr: 4.0680e-03 eta: 15:41:24 time: 0.8528 data_time: 0.0377 memory: 16201 loss_prob: 0.5471 loss_thr: 0.3692 loss_db: 0.0940 loss: 1.0103 2022/08/30 12:51:01 - mmengine - INFO - Epoch(train) [544][40/63] lr: 4.0680e-03 eta: 15:41:04 time: 0.8396 data_time: 0.0345 memory: 16201 loss_prob: 0.5596 loss_thr: 0.3717 loss_db: 0.0970 loss: 1.0283 2022/08/30 12:51:06 - mmengine - INFO - Epoch(train) [544][45/63] lr: 4.0680e-03 eta: 15:41:04 time: 0.8833 data_time: 0.0406 memory: 16201 loss_prob: 0.5317 loss_thr: 0.3499 loss_db: 0.0908 loss: 0.9724 2022/08/30 12:51:10 - mmengine - INFO - Epoch(train) [544][50/63] lr: 4.0680e-03 eta: 15:40:44 time: 0.8954 data_time: 0.0333 memory: 16201 loss_prob: 0.4858 loss_thr: 0.3303 loss_db: 0.0834 loss: 0.8995 2022/08/30 12:51:15 - mmengine - INFO - Epoch(train) [544][55/63] lr: 4.0680e-03 eta: 15:40:44 time: 0.9293 data_time: 0.0704 memory: 16201 loss_prob: 0.4679 loss_thr: 0.3282 loss_db: 0.0810 loss: 0.8771 2022/08/30 12:51:19 - mmengine - INFO - Epoch(train) [544][60/63] lr: 4.0680e-03 eta: 15:40:26 time: 0.9582 data_time: 0.0804 memory: 16201 loss_prob: 0.7044 loss_thr: 0.3610 loss_db: 0.1095 loss: 1.1750 2022/08/30 12:51:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:51:28 - mmengine - INFO - Epoch(train) [545][5/63] lr: 4.0624e-03 eta: 15:40:26 time: 1.0043 data_time: 0.2323 memory: 16201 loss_prob: 0.5246 loss_thr: 0.3524 loss_db: 0.0913 loss: 0.9684 2022/08/30 12:51:32 - mmengine - INFO - Epoch(train) [545][10/63] lr: 4.0624e-03 eta: 15:39:59 time: 1.0708 data_time: 0.2707 memory: 16201 loss_prob: 0.5258 loss_thr: 0.3591 loss_db: 0.0878 loss: 0.9726 2022/08/30 12:51:36 - mmengine - INFO - Epoch(train) [545][15/63] lr: 4.0624e-03 eta: 15:39:59 time: 0.8673 data_time: 0.0738 memory: 16201 loss_prob: 0.5181 loss_thr: 0.3473 loss_db: 0.0859 loss: 0.9513 2022/08/30 12:51:40 - mmengine - INFO - Epoch(train) [545][20/63] lr: 4.0624e-03 eta: 15:39:39 time: 0.8097 data_time: 0.0374 memory: 16201 loss_prob: 0.5776 loss_thr: 0.3839 loss_db: 0.0982 loss: 1.0597 2022/08/30 12:51:45 - mmengine - INFO - Epoch(train) [545][25/63] lr: 4.0624e-03 eta: 15:39:39 time: 0.8644 data_time: 0.0741 memory: 16201 loss_prob: 0.6213 loss_thr: 0.4110 loss_db: 0.1064 loss: 1.1387 2022/08/30 12:51:49 - mmengine - INFO - Epoch(train) [545][30/63] lr: 4.0624e-03 eta: 15:39:20 time: 0.8891 data_time: 0.0683 memory: 16201 loss_prob: 0.5794 loss_thr: 0.3809 loss_db: 0.0975 loss: 1.0578 2022/08/30 12:51:54 - mmengine - INFO - Epoch(train) [545][35/63] lr: 4.0624e-03 eta: 15:39:20 time: 0.8781 data_time: 0.0453 memory: 16201 loss_prob: 0.5335 loss_thr: 0.3577 loss_db: 0.0920 loss: 0.9831 2022/08/30 12:51:58 - mmengine - INFO - Epoch(train) [545][40/63] lr: 4.0624e-03 eta: 15:39:01 time: 0.9181 data_time: 0.0724 memory: 16201 loss_prob: 0.5504 loss_thr: 0.3630 loss_db: 0.0983 loss: 1.0117 2022/08/30 12:52:03 - mmengine - INFO - Epoch(train) [545][45/63] lr: 4.0624e-03 eta: 15:39:01 time: 0.9139 data_time: 0.0549 memory: 16201 loss_prob: 0.5393 loss_thr: 0.3651 loss_db: 0.0949 loss: 0.9993 2022/08/30 12:52:08 - mmengine - INFO - Epoch(train) [545][50/63] lr: 4.0624e-03 eta: 15:38:42 time: 0.9721 data_time: 0.0529 memory: 16201 loss_prob: 0.5163 loss_thr: 0.3605 loss_db: 0.0888 loss: 0.9657 2022/08/30 12:52:12 - mmengine - INFO - Epoch(train) [545][55/63] lr: 4.0624e-03 eta: 15:38:42 time: 0.9504 data_time: 0.0527 memory: 16201 loss_prob: 0.5906 loss_thr: 0.3867 loss_db: 0.0977 loss: 1.0750 2022/08/30 12:52:17 - mmengine - INFO - Epoch(train) [545][60/63] lr: 4.0624e-03 eta: 15:38:23 time: 0.8549 data_time: 0.0327 memory: 16201 loss_prob: 0.6153 loss_thr: 0.4005 loss_db: 0.1034 loss: 1.1191 2022/08/30 12:52:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:52:26 - mmengine - INFO - Epoch(train) [546][5/63] lr: 4.0568e-03 eta: 15:38:23 time: 1.0536 data_time: 0.2536 memory: 16201 loss_prob: 0.5730 loss_thr: 0.3923 loss_db: 0.0998 loss: 1.0652 2022/08/30 12:52:30 - mmengine - INFO - Epoch(train) [546][10/63] lr: 4.0568e-03 eta: 15:37:57 time: 1.1018 data_time: 0.2418 memory: 16201 loss_prob: 0.5777 loss_thr: 0.3611 loss_db: 0.1010 loss: 1.0398 2022/08/30 12:52:35 - mmengine - INFO - Epoch(train) [546][15/63] lr: 4.0568e-03 eta: 15:37:57 time: 0.9324 data_time: 0.0629 memory: 16201 loss_prob: 0.5418 loss_thr: 0.3525 loss_db: 0.0933 loss: 0.9876 2022/08/30 12:52:40 - mmengine - INFO - Epoch(train) [546][20/63] lr: 4.0568e-03 eta: 15:37:38 time: 0.9198 data_time: 0.0476 memory: 16201 loss_prob: 0.4640 loss_thr: 0.3402 loss_db: 0.0802 loss: 0.8844 2022/08/30 12:52:44 - mmengine - INFO - Epoch(train) [546][25/63] lr: 4.0568e-03 eta: 15:37:38 time: 0.9199 data_time: 0.0719 memory: 16201 loss_prob: 0.5097 loss_thr: 0.3513 loss_db: 0.0892 loss: 0.9502 2022/08/30 12:52:49 - mmengine - INFO - Epoch(train) [546][30/63] lr: 4.0568e-03 eta: 15:37:19 time: 0.9136 data_time: 0.0615 memory: 16201 loss_prob: 0.5122 loss_thr: 0.3454 loss_db: 0.0884 loss: 0.9460 2022/08/30 12:52:53 - mmengine - INFO - Epoch(train) [546][35/63] lr: 4.0568e-03 eta: 15:37:19 time: 0.9033 data_time: 0.0438 memory: 16201 loss_prob: 0.4863 loss_thr: 0.3328 loss_db: 0.0816 loss: 0.9007 2022/08/30 12:52:59 - mmengine - INFO - Epoch(train) [546][40/63] lr: 4.0568e-03 eta: 15:37:01 time: 0.9883 data_time: 0.0985 memory: 16201 loss_prob: 0.5645 loss_thr: 0.3754 loss_db: 0.0952 loss: 1.0350 2022/08/30 12:53:04 - mmengine - INFO - Epoch(train) [546][45/63] lr: 4.0568e-03 eta: 15:37:01 time: 1.0430 data_time: 0.1021 memory: 16201 loss_prob: 0.5534 loss_thr: 0.3712 loss_db: 0.0965 loss: 1.0211 2022/08/30 12:53:08 - mmengine - INFO - Epoch(train) [546][50/63] lr: 4.0568e-03 eta: 15:36:42 time: 0.9902 data_time: 0.0793 memory: 16201 loss_prob: 0.4715 loss_thr: 0.3178 loss_db: 0.0814 loss: 0.8707 2022/08/30 12:53:13 - mmengine - INFO - Epoch(train) [546][55/63] lr: 4.0568e-03 eta: 15:36:42 time: 0.8850 data_time: 0.0602 memory: 16201 loss_prob: 0.5061 loss_thr: 0.3473 loss_db: 0.0847 loss: 0.9380 2022/08/30 12:53:17 - mmengine - INFO - Epoch(train) [546][60/63] lr: 4.0568e-03 eta: 15:36:23 time: 0.8476 data_time: 0.0313 memory: 16201 loss_prob: 0.5429 loss_thr: 0.3749 loss_db: 0.0941 loss: 1.0119 2022/08/30 12:53:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:53:25 - mmengine - INFO - Epoch(train) [547][5/63] lr: 4.0512e-03 eta: 15:36:23 time: 1.0031 data_time: 0.2119 memory: 16201 loss_prob: 0.5468 loss_thr: 0.3645 loss_db: 0.0951 loss: 1.0065 2022/08/30 12:53:30 - mmengine - INFO - Epoch(train) [547][10/63] lr: 4.0512e-03 eta: 15:35:56 time: 1.0658 data_time: 0.2219 memory: 16201 loss_prob: 0.5464 loss_thr: 0.3698 loss_db: 0.0917 loss: 1.0080 2022/08/30 12:53:34 - mmengine - INFO - Epoch(train) [547][15/63] lr: 4.0512e-03 eta: 15:35:56 time: 0.8961 data_time: 0.0697 memory: 16201 loss_prob: 0.5508 loss_thr: 0.3672 loss_db: 0.0938 loss: 1.0118 2022/08/30 12:53:39 - mmengine - INFO - Epoch(train) [547][20/63] lr: 4.0512e-03 eta: 15:35:38 time: 0.9418 data_time: 0.0709 memory: 16201 loss_prob: 0.5182 loss_thr: 0.3541 loss_db: 0.0908 loss: 0.9630 2022/08/30 12:53:43 - mmengine - INFO - Epoch(train) [547][25/63] lr: 4.0512e-03 eta: 15:35:38 time: 0.9038 data_time: 0.0481 memory: 16201 loss_prob: 0.5209 loss_thr: 0.3630 loss_db: 0.0893 loss: 0.9732 2022/08/30 12:53:48 - mmengine - INFO - Epoch(train) [547][30/63] lr: 4.0512e-03 eta: 15:35:19 time: 0.8934 data_time: 0.0747 memory: 16201 loss_prob: 0.5203 loss_thr: 0.3767 loss_db: 0.0871 loss: 0.9841 2022/08/30 12:53:52 - mmengine - INFO - Epoch(train) [547][35/63] lr: 4.0512e-03 eta: 15:35:19 time: 0.9052 data_time: 0.0692 memory: 16201 loss_prob: 0.5041 loss_thr: 0.3659 loss_db: 0.0888 loss: 0.9588 2022/08/30 12:53:57 - mmengine - INFO - Epoch(train) [547][40/63] lr: 4.0512e-03 eta: 15:34:59 time: 0.8734 data_time: 0.0338 memory: 16201 loss_prob: 0.5388 loss_thr: 0.3669 loss_db: 0.0949 loss: 1.0006 2022/08/30 12:54:01 - mmengine - INFO - Epoch(train) [547][45/63] lr: 4.0512e-03 eta: 15:34:59 time: 0.9036 data_time: 0.0755 memory: 16201 loss_prob: 0.5547 loss_thr: 0.3702 loss_db: 0.0950 loss: 1.0199 2022/08/30 12:54:06 - mmengine - INFO - Epoch(train) [547][50/63] lr: 4.0512e-03 eta: 15:34:41 time: 0.9590 data_time: 0.0823 memory: 16201 loss_prob: 0.5106 loss_thr: 0.3501 loss_db: 0.0877 loss: 0.9484 2022/08/30 12:54:11 - mmengine - INFO - Epoch(train) [547][55/63] lr: 4.0512e-03 eta: 15:34:41 time: 0.9271 data_time: 0.0488 memory: 16201 loss_prob: 0.4940 loss_thr: 0.3540 loss_db: 0.0850 loss: 0.9331 2022/08/30 12:54:15 - mmengine - INFO - Epoch(train) [547][60/63] lr: 4.0512e-03 eta: 15:34:21 time: 0.8952 data_time: 0.0802 memory: 16201 loss_prob: 0.5308 loss_thr: 0.3703 loss_db: 0.0934 loss: 0.9944 2022/08/30 12:54:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:54:24 - mmengine - INFO - Epoch(train) [548][5/63] lr: 4.0456e-03 eta: 15:34:21 time: 1.0459 data_time: 0.2776 memory: 16201 loss_prob: 0.5115 loss_thr: 0.3680 loss_db: 0.0917 loss: 0.9712 2022/08/30 12:54:29 - mmengine - INFO - Epoch(train) [548][10/63] lr: 4.0456e-03 eta: 15:33:56 time: 1.0963 data_time: 0.3263 memory: 16201 loss_prob: 0.4953 loss_thr: 0.3596 loss_db: 0.0873 loss: 0.9422 2022/08/30 12:54:33 - mmengine - INFO - Epoch(train) [548][15/63] lr: 4.0456e-03 eta: 15:33:56 time: 0.8744 data_time: 0.0797 memory: 16201 loss_prob: 0.4976 loss_thr: 0.3456 loss_db: 0.0843 loss: 0.9275 2022/08/30 12:54:38 - mmengine - INFO - Epoch(train) [548][20/63] lr: 4.0456e-03 eta: 15:33:37 time: 0.9613 data_time: 0.0405 memory: 16201 loss_prob: 0.5188 loss_thr: 0.3453 loss_db: 0.0877 loss: 0.9519 2022/08/30 12:54:43 - mmengine - INFO - Epoch(train) [548][25/63] lr: 4.0456e-03 eta: 15:33:37 time: 0.9854 data_time: 0.0633 memory: 16201 loss_prob: 0.5343 loss_thr: 0.3630 loss_db: 0.0931 loss: 0.9904 2022/08/30 12:54:47 - mmengine - INFO - Epoch(train) [548][30/63] lr: 4.0456e-03 eta: 15:33:18 time: 0.8664 data_time: 0.0484 memory: 16201 loss_prob: 0.5232 loss_thr: 0.3619 loss_db: 0.0898 loss: 0.9749 2022/08/30 12:54:51 - mmengine - INFO - Epoch(train) [548][35/63] lr: 4.0456e-03 eta: 15:33:18 time: 0.8586 data_time: 0.0294 memory: 16201 loss_prob: 0.4944 loss_thr: 0.3523 loss_db: 0.0849 loss: 0.9315 2022/08/30 12:54:56 - mmengine - INFO - Epoch(train) [548][40/63] lr: 4.0456e-03 eta: 15:32:59 time: 0.9113 data_time: 0.0347 memory: 16201 loss_prob: 0.5322 loss_thr: 0.3650 loss_db: 0.0945 loss: 0.9917 2022/08/30 12:55:00 - mmengine - INFO - Epoch(train) [548][45/63] lr: 4.0456e-03 eta: 15:32:59 time: 0.8809 data_time: 0.0283 memory: 16201 loss_prob: 0.5422 loss_thr: 0.3667 loss_db: 0.0941 loss: 1.0031 2022/08/30 12:55:04 - mmengine - INFO - Epoch(train) [548][50/63] lr: 4.0456e-03 eta: 15:32:39 time: 0.8238 data_time: 0.0322 memory: 16201 loss_prob: 0.4956 loss_thr: 0.3644 loss_db: 0.0857 loss: 0.9457 2022/08/30 12:55:09 - mmengine - INFO - Epoch(train) [548][55/63] lr: 4.0456e-03 eta: 15:32:39 time: 0.8723 data_time: 0.0574 memory: 16201 loss_prob: 0.5134 loss_thr: 0.3679 loss_db: 0.0923 loss: 0.9736 2022/08/30 12:55:13 - mmengine - INFO - Epoch(train) [548][60/63] lr: 4.0456e-03 eta: 15:32:20 time: 0.9088 data_time: 0.0609 memory: 16201 loss_prob: 0.5207 loss_thr: 0.3585 loss_db: 0.0891 loss: 0.9683 2022/08/30 12:55:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:55:22 - mmengine - INFO - Epoch(train) [549][5/63] lr: 4.0401e-03 eta: 15:32:20 time: 1.0545 data_time: 0.1891 memory: 16201 loss_prob: 0.4753 loss_thr: 0.3391 loss_db: 0.0812 loss: 0.8956 2022/08/30 12:55:27 - mmengine - INFO - Epoch(train) [549][10/63] lr: 4.0401e-03 eta: 15:31:53 time: 1.0290 data_time: 0.2026 memory: 16201 loss_prob: 0.4800 loss_thr: 0.3491 loss_db: 0.0857 loss: 0.9148 2022/08/30 12:55:31 - mmengine - INFO - Epoch(train) [549][15/63] lr: 4.0401e-03 eta: 15:31:53 time: 0.8781 data_time: 0.0444 memory: 16201 loss_prob: 0.5170 loss_thr: 0.3663 loss_db: 0.0921 loss: 0.9755 2022/08/30 12:55:35 - mmengine - INFO - Epoch(train) [549][20/63] lr: 4.0401e-03 eta: 15:31:34 time: 0.8619 data_time: 0.0339 memory: 16201 loss_prob: 0.5001 loss_thr: 0.3436 loss_db: 0.0860 loss: 0.9296 2022/08/30 12:55:40 - mmengine - INFO - Epoch(train) [549][25/63] lr: 4.0401e-03 eta: 15:31:34 time: 0.8532 data_time: 0.0521 memory: 16201 loss_prob: 0.4889 loss_thr: 0.3409 loss_db: 0.0830 loss: 0.9128 2022/08/30 12:55:44 - mmengine - INFO - Epoch(train) [549][30/63] lr: 4.0401e-03 eta: 15:31:14 time: 0.8476 data_time: 0.0622 memory: 16201 loss_prob: 0.5163 loss_thr: 0.3631 loss_db: 0.0901 loss: 0.9695 2022/08/30 12:55:48 - mmengine - INFO - Epoch(train) [549][35/63] lr: 4.0401e-03 eta: 15:31:14 time: 0.8663 data_time: 0.0503 memory: 16201 loss_prob: 0.5226 loss_thr: 0.3543 loss_db: 0.0922 loss: 0.9691 2022/08/30 12:55:53 - mmengine - INFO - Epoch(train) [549][40/63] lr: 4.0401e-03 eta: 15:30:55 time: 0.8782 data_time: 0.0604 memory: 16201 loss_prob: 0.5517 loss_thr: 0.3670 loss_db: 0.0968 loss: 1.0155 2022/08/30 12:55:57 - mmengine - INFO - Epoch(train) [549][45/63] lr: 4.0401e-03 eta: 15:30:55 time: 0.8950 data_time: 0.0534 memory: 16201 loss_prob: 0.5352 loss_thr: 0.3572 loss_db: 0.0944 loss: 0.9868 2022/08/30 12:56:02 - mmengine - INFO - Epoch(train) [549][50/63] lr: 4.0401e-03 eta: 15:30:35 time: 0.8957 data_time: 0.0430 memory: 16201 loss_prob: 0.4651 loss_thr: 0.3216 loss_db: 0.0839 loss: 0.8706 2022/08/30 12:56:07 - mmengine - INFO - Epoch(train) [549][55/63] lr: 4.0401e-03 eta: 15:30:35 time: 0.9182 data_time: 0.0497 memory: 16201 loss_prob: 0.4771 loss_thr: 0.3357 loss_db: 0.0852 loss: 0.8980 2022/08/30 12:56:12 - mmengine - INFO - Epoch(train) [549][60/63] lr: 4.0401e-03 eta: 15:30:17 time: 0.9971 data_time: 0.0611 memory: 16201 loss_prob: 0.5092 loss_thr: 0.3536 loss_db: 0.0871 loss: 0.9499 2022/08/30 12:56:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:56:20 - mmengine - INFO - Epoch(train) [550][5/63] lr: 4.0345e-03 eta: 15:30:17 time: 1.1339 data_time: 0.2814 memory: 16201 loss_prob: 0.4325 loss_thr: 0.3101 loss_db: 0.0770 loss: 0.8196 2022/08/30 12:56:25 - mmengine - INFO - Epoch(train) [550][10/63] lr: 4.0345e-03 eta: 15:29:52 time: 1.1303 data_time: 0.2814 memory: 16201 loss_prob: 0.4808 loss_thr: 0.3385 loss_db: 0.0853 loss: 0.9046 2022/08/30 12:56:29 - mmengine - INFO - Epoch(train) [550][15/63] lr: 4.0345e-03 eta: 15:29:52 time: 0.8859 data_time: 0.0263 memory: 16201 loss_prob: 0.4962 loss_thr: 0.3540 loss_db: 0.0865 loss: 0.9367 2022/08/30 12:56:33 - mmengine - INFO - Epoch(train) [550][20/63] lr: 4.0345e-03 eta: 15:29:32 time: 0.8307 data_time: 0.0221 memory: 16201 loss_prob: 0.4822 loss_thr: 0.3479 loss_db: 0.0850 loss: 0.9150 2022/08/30 12:56:38 - mmengine - INFO - Epoch(train) [550][25/63] lr: 4.0345e-03 eta: 15:29:32 time: 0.8647 data_time: 0.0440 memory: 16201 loss_prob: 0.4900 loss_thr: 0.3414 loss_db: 0.0858 loss: 0.9172 2022/08/30 12:56:42 - mmengine - INFO - Epoch(train) [550][30/63] lr: 4.0345e-03 eta: 15:29:13 time: 0.8840 data_time: 0.0425 memory: 16201 loss_prob: 0.4858 loss_thr: 0.3462 loss_db: 0.0841 loss: 0.9160 2022/08/30 12:56:47 - mmengine - INFO - Epoch(train) [550][35/63] lr: 4.0345e-03 eta: 15:29:13 time: 0.8724 data_time: 0.0363 memory: 16201 loss_prob: 0.5156 loss_thr: 0.3741 loss_db: 0.0905 loss: 0.9801 2022/08/30 12:56:51 - mmengine - INFO - Epoch(train) [550][40/63] lr: 4.0345e-03 eta: 15:28:54 time: 0.8931 data_time: 0.0476 memory: 16201 loss_prob: 0.5763 loss_thr: 0.3877 loss_db: 0.0994 loss: 1.0635 2022/08/30 12:56:56 - mmengine - INFO - Epoch(train) [550][45/63] lr: 4.0345e-03 eta: 15:28:54 time: 0.9490 data_time: 0.0500 memory: 16201 loss_prob: 0.5713 loss_thr: 0.3748 loss_db: 0.0984 loss: 1.0445 2022/08/30 12:57:00 - mmengine - INFO - Epoch(train) [550][50/63] lr: 4.0345e-03 eta: 15:28:35 time: 0.9341 data_time: 0.0372 memory: 16201 loss_prob: 0.5040 loss_thr: 0.3484 loss_db: 0.0885 loss: 0.9408 2022/08/30 12:57:05 - mmengine - INFO - Epoch(train) [550][55/63] lr: 4.0345e-03 eta: 15:28:35 time: 0.8428 data_time: 0.0254 memory: 16201 loss_prob: 0.5095 loss_thr: 0.3498 loss_db: 0.0876 loss: 0.9469 2022/08/30 12:57:09 - mmengine - INFO - Epoch(train) [550][60/63] lr: 4.0345e-03 eta: 15:28:16 time: 0.8709 data_time: 0.0297 memory: 16201 loss_prob: 0.4916 loss_thr: 0.3437 loss_db: 0.0860 loss: 0.9213 2022/08/30 12:57:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:57:18 - mmengine - INFO - Epoch(train) [551][5/63] lr: 4.0289e-03 eta: 15:28:16 time: 0.9909 data_time: 0.2042 memory: 16201 loss_prob: 0.5284 loss_thr: 0.3664 loss_db: 0.0928 loss: 0.9876 2022/08/30 12:57:22 - mmengine - INFO - Epoch(train) [551][10/63] lr: 4.0289e-03 eta: 15:27:50 time: 1.0534 data_time: 0.2128 memory: 16201 loss_prob: 0.5650 loss_thr: 0.3762 loss_db: 0.0935 loss: 1.0347 2022/08/30 12:57:27 - mmengine - INFO - Epoch(train) [551][15/63] lr: 4.0289e-03 eta: 15:27:50 time: 0.9153 data_time: 0.0288 memory: 16201 loss_prob: 0.5322 loss_thr: 0.3549 loss_db: 0.0891 loss: 0.9763 2022/08/30 12:57:31 - mmengine - INFO - Epoch(train) [551][20/63] lr: 4.0289e-03 eta: 15:27:31 time: 0.9131 data_time: 0.0317 memory: 16201 loss_prob: 0.5201 loss_thr: 0.3525 loss_db: 0.0904 loss: 0.9630 2022/08/30 12:57:36 - mmengine - INFO - Epoch(train) [551][25/63] lr: 4.0289e-03 eta: 15:27:31 time: 0.9094 data_time: 0.0638 memory: 16201 loss_prob: 0.5357 loss_thr: 0.3684 loss_db: 0.0942 loss: 0.9983 2022/08/30 12:57:40 - mmengine - INFO - Epoch(train) [551][30/63] lr: 4.0289e-03 eta: 15:27:12 time: 0.9040 data_time: 0.0643 memory: 16201 loss_prob: 0.5408 loss_thr: 0.3698 loss_db: 0.0937 loss: 1.0044 2022/08/30 12:57:44 - mmengine - INFO - Epoch(train) [551][35/63] lr: 4.0289e-03 eta: 15:27:12 time: 0.8543 data_time: 0.0332 memory: 16201 loss_prob: 0.4775 loss_thr: 0.3246 loss_db: 0.0824 loss: 0.8845 2022/08/30 12:57:49 - mmengine - INFO - Epoch(train) [551][40/63] lr: 4.0289e-03 eta: 15:26:53 time: 0.9138 data_time: 0.0576 memory: 16201 loss_prob: 0.4499 loss_thr: 0.3174 loss_db: 0.0810 loss: 0.8482 2022/08/30 12:57:54 - mmengine - INFO - Epoch(train) [551][45/63] lr: 4.0289e-03 eta: 15:26:53 time: 0.9320 data_time: 0.0631 memory: 16201 loss_prob: 0.4914 loss_thr: 0.3525 loss_db: 0.0876 loss: 0.9315 2022/08/30 12:57:58 - mmengine - INFO - Epoch(train) [551][50/63] lr: 4.0289e-03 eta: 15:26:34 time: 0.9241 data_time: 0.0772 memory: 16201 loss_prob: 0.5093 loss_thr: 0.3634 loss_db: 0.0892 loss: 0.9618 2022/08/30 12:58:03 - mmengine - INFO - Epoch(train) [551][55/63] lr: 4.0289e-03 eta: 15:26:34 time: 0.9269 data_time: 0.0991 memory: 16201 loss_prob: 0.5038 loss_thr: 0.3554 loss_db: 0.0873 loss: 0.9465 2022/08/30 12:58:07 - mmengine - INFO - Epoch(train) [551][60/63] lr: 4.0289e-03 eta: 15:26:15 time: 0.8785 data_time: 0.0593 memory: 16201 loss_prob: 0.4679 loss_thr: 0.3328 loss_db: 0.0820 loss: 0.8828 2022/08/30 12:58:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:58:16 - mmengine - INFO - Epoch(train) [552][5/63] lr: 4.0233e-03 eta: 15:26:15 time: 1.0114 data_time: 0.2119 memory: 16201 loss_prob: 0.5187 loss_thr: 0.3475 loss_db: 0.0885 loss: 0.9548 2022/08/30 12:58:20 - mmengine - INFO - Epoch(train) [552][10/63] lr: 4.0233e-03 eta: 15:25:49 time: 1.0789 data_time: 0.2228 memory: 16201 loss_prob: 0.4850 loss_thr: 0.3437 loss_db: 0.0861 loss: 0.9148 2022/08/30 12:58:24 - mmengine - INFO - Epoch(train) [552][15/63] lr: 4.0233e-03 eta: 15:25:49 time: 0.8714 data_time: 0.0453 memory: 16201 loss_prob: 0.5241 loss_thr: 0.3642 loss_db: 0.0930 loss: 0.9813 2022/08/30 12:58:29 - mmengine - INFO - Epoch(train) [552][20/63] lr: 4.0233e-03 eta: 15:25:30 time: 0.8345 data_time: 0.0319 memory: 16201 loss_prob: 0.5313 loss_thr: 0.3662 loss_db: 0.0923 loss: 0.9898 2022/08/30 12:58:33 - mmengine - INFO - Epoch(train) [552][25/63] lr: 4.0233e-03 eta: 15:25:30 time: 0.8403 data_time: 0.0445 memory: 16201 loss_prob: 0.4982 loss_thr: 0.3540 loss_db: 0.0868 loss: 0.9389 2022/08/30 12:58:38 - mmengine - INFO - Epoch(train) [552][30/63] lr: 4.0233e-03 eta: 15:25:11 time: 0.9775 data_time: 0.0355 memory: 16201 loss_prob: 0.5202 loss_thr: 0.3618 loss_db: 0.0918 loss: 0.9738 2022/08/30 12:58:43 - mmengine - INFO - Epoch(train) [552][35/63] lr: 4.0233e-03 eta: 15:25:11 time: 0.9777 data_time: 0.0244 memory: 16201 loss_prob: 0.5138 loss_thr: 0.3559 loss_db: 0.0906 loss: 0.9603 2022/08/30 12:58:47 - mmengine - INFO - Epoch(train) [552][40/63] lr: 4.0233e-03 eta: 15:24:52 time: 0.8471 data_time: 0.0272 memory: 16201 loss_prob: 0.4888 loss_thr: 0.3444 loss_db: 0.0850 loss: 0.9182 2022/08/30 12:58:51 - mmengine - INFO - Epoch(train) [552][45/63] lr: 4.0233e-03 eta: 15:24:52 time: 0.8534 data_time: 0.0292 memory: 16201 loss_prob: 0.4980 loss_thr: 0.3489 loss_db: 0.0864 loss: 0.9333 2022/08/30 12:58:57 - mmengine - INFO - Epoch(train) [552][50/63] lr: 4.0233e-03 eta: 15:24:34 time: 0.9952 data_time: 0.0379 memory: 16201 loss_prob: 0.5079 loss_thr: 0.3484 loss_db: 0.0880 loss: 0.9442 2022/08/30 12:59:01 - mmengine - INFO - Epoch(train) [552][55/63] lr: 4.0233e-03 eta: 15:24:34 time: 1.0000 data_time: 0.0352 memory: 16201 loss_prob: 0.5256 loss_thr: 0.3513 loss_db: 0.0910 loss: 0.9680 2022/08/30 12:59:05 - mmengine - INFO - Epoch(train) [552][60/63] lr: 4.0233e-03 eta: 15:24:15 time: 0.8546 data_time: 0.0356 memory: 16201 loss_prob: 0.5540 loss_thr: 0.3705 loss_db: 0.0968 loss: 1.0213 2022/08/30 12:59:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 12:59:14 - mmengine - INFO - Epoch(train) [553][5/63] lr: 4.0177e-03 eta: 15:24:15 time: 1.0413 data_time: 0.2360 memory: 16201 loss_prob: 0.5717 loss_thr: 0.3713 loss_db: 0.0958 loss: 1.0388 2022/08/30 12:59:19 - mmengine - INFO - Epoch(train) [553][10/63] lr: 4.0177e-03 eta: 15:23:49 time: 1.1220 data_time: 0.2870 memory: 16201 loss_prob: 0.5426 loss_thr: 0.3660 loss_db: 0.0965 loss: 1.0051 2022/08/30 12:59:23 - mmengine - INFO - Epoch(train) [553][15/63] lr: 4.0177e-03 eta: 15:23:49 time: 0.8630 data_time: 0.0809 memory: 16201 loss_prob: 0.5228 loss_thr: 0.3560 loss_db: 0.0911 loss: 0.9698 2022/08/30 12:59:28 - mmengine - INFO - Epoch(train) [553][20/63] lr: 4.0177e-03 eta: 15:23:31 time: 0.9818 data_time: 0.0422 memory: 16201 loss_prob: 0.5326 loss_thr: 0.3706 loss_db: 0.0905 loss: 0.9937 2022/08/30 12:59:33 - mmengine - INFO - Epoch(train) [553][25/63] lr: 4.0177e-03 eta: 15:23:31 time: 0.9976 data_time: 0.0509 memory: 16201 loss_prob: 0.4823 loss_thr: 0.3532 loss_db: 0.0813 loss: 0.9169 2022/08/30 12:59:37 - mmengine - INFO - Epoch(train) [553][30/63] lr: 4.0177e-03 eta: 15:23:11 time: 0.8198 data_time: 0.0414 memory: 16201 loss_prob: 0.4404 loss_thr: 0.3206 loss_db: 0.0764 loss: 0.8374 2022/08/30 12:59:41 - mmengine - INFO - Epoch(train) [553][35/63] lr: 4.0177e-03 eta: 15:23:11 time: 0.7961 data_time: 0.0311 memory: 16201 loss_prob: 0.4536 loss_thr: 0.3213 loss_db: 0.0821 loss: 0.8569 2022/08/30 12:59:45 - mmengine - INFO - Epoch(train) [553][40/63] lr: 4.0177e-03 eta: 15:22:52 time: 0.8257 data_time: 0.0353 memory: 16201 loss_prob: 0.5033 loss_thr: 0.3643 loss_db: 0.0879 loss: 0.9555 2022/08/30 12:59:49 - mmengine - INFO - Epoch(train) [553][45/63] lr: 4.0177e-03 eta: 15:22:52 time: 0.8298 data_time: 0.0324 memory: 16201 loss_prob: 0.5743 loss_thr: 0.3944 loss_db: 0.0996 loss: 1.0683 2022/08/30 12:59:53 - mmengine - INFO - Epoch(train) [553][50/63] lr: 4.0177e-03 eta: 15:22:32 time: 0.8103 data_time: 0.0305 memory: 16201 loss_prob: 0.5835 loss_thr: 0.3803 loss_db: 0.1006 loss: 1.0645 2022/08/30 12:59:58 - mmengine - INFO - Epoch(train) [553][55/63] lr: 4.0177e-03 eta: 15:22:32 time: 0.8881 data_time: 0.0499 memory: 16201 loss_prob: 0.5155 loss_thr: 0.3580 loss_db: 0.0897 loss: 0.9632 2022/08/30 13:00:02 - mmengine - INFO - Epoch(train) [553][60/63] lr: 4.0177e-03 eta: 15:22:13 time: 0.9054 data_time: 0.0583 memory: 16201 loss_prob: 0.5034 loss_thr: 0.3524 loss_db: 0.0903 loss: 0.9461 2022/08/30 13:00:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:00:10 - mmengine - INFO - Epoch(train) [554][5/63] lr: 4.0121e-03 eta: 15:22:13 time: 0.9888 data_time: 0.2058 memory: 16201 loss_prob: 0.5276 loss_thr: 0.3668 loss_db: 0.0921 loss: 0.9865 2022/08/30 13:00:15 - mmengine - INFO - Epoch(train) [554][10/63] lr: 4.0121e-03 eta: 15:21:47 time: 1.0334 data_time: 0.2027 memory: 16201 loss_prob: 0.4643 loss_thr: 0.3450 loss_db: 0.0829 loss: 0.8922 2022/08/30 13:00:20 - mmengine - INFO - Epoch(train) [554][15/63] lr: 4.0121e-03 eta: 15:21:47 time: 0.9216 data_time: 0.0436 memory: 16201 loss_prob: 0.4794 loss_thr: 0.3394 loss_db: 0.0823 loss: 0.9011 2022/08/30 13:00:24 - mmengine - INFO - Epoch(train) [554][20/63] lr: 4.0121e-03 eta: 15:21:28 time: 0.9333 data_time: 0.0475 memory: 16201 loss_prob: 0.4804 loss_thr: 0.3319 loss_db: 0.0812 loss: 0.8935 2022/08/30 13:00:28 - mmengine - INFO - Epoch(train) [554][25/63] lr: 4.0121e-03 eta: 15:21:28 time: 0.8582 data_time: 0.0467 memory: 16201 loss_prob: 0.4295 loss_thr: 0.3195 loss_db: 0.0760 loss: 0.8250 2022/08/30 13:00:32 - mmengine - INFO - Epoch(train) [554][30/63] lr: 4.0121e-03 eta: 15:21:09 time: 0.8453 data_time: 0.0323 memory: 16201 loss_prob: 0.4704 loss_thr: 0.3375 loss_db: 0.0847 loss: 0.8926 2022/08/30 13:00:38 - mmengine - INFO - Epoch(train) [554][35/63] lr: 4.0121e-03 eta: 15:21:09 time: 0.9479 data_time: 0.0274 memory: 16201 loss_prob: 0.5212 loss_thr: 0.3523 loss_db: 0.0902 loss: 0.9638 2022/08/30 13:00:42 - mmengine - INFO - Epoch(train) [554][40/63] lr: 4.0121e-03 eta: 15:20:50 time: 0.9449 data_time: 0.0313 memory: 16201 loss_prob: 0.5325 loss_thr: 0.3619 loss_db: 0.0907 loss: 0.9851 2022/08/30 13:00:46 - mmengine - INFO - Epoch(train) [554][45/63] lr: 4.0121e-03 eta: 15:20:50 time: 0.8602 data_time: 0.0350 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3451 loss_db: 0.0869 loss: 0.9216 2022/08/30 13:00:50 - mmengine - INFO - Epoch(train) [554][50/63] lr: 4.0121e-03 eta: 15:20:31 time: 0.8430 data_time: 0.0266 memory: 16201 loss_prob: 0.4870 loss_thr: 0.3490 loss_db: 0.0852 loss: 0.9213 2022/08/30 13:00:55 - mmengine - INFO - Epoch(train) [554][55/63] lr: 4.0121e-03 eta: 15:20:31 time: 0.8319 data_time: 0.0254 memory: 16201 loss_prob: 0.4878 loss_thr: 0.3526 loss_db: 0.0847 loss: 0.9251 2022/08/30 13:00:59 - mmengine - INFO - Epoch(train) [554][60/63] lr: 4.0121e-03 eta: 15:20:12 time: 0.9206 data_time: 0.0366 memory: 16201 loss_prob: 0.6195 loss_thr: 0.3786 loss_db: 0.0997 loss: 1.0979 2022/08/30 13:01:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:01:08 - mmengine - INFO - Epoch(train) [555][5/63] lr: 4.0065e-03 eta: 15:20:12 time: 1.0216 data_time: 0.2195 memory: 16201 loss_prob: 0.5364 loss_thr: 0.3407 loss_db: 0.0878 loss: 0.9649 2022/08/30 13:01:12 - mmengine - INFO - Epoch(train) [555][10/63] lr: 4.0065e-03 eta: 15:19:46 time: 1.0481 data_time: 0.2305 memory: 16201 loss_prob: 0.4394 loss_thr: 0.2996 loss_db: 0.0768 loss: 0.8158 2022/08/30 13:01:17 - mmengine - INFO - Epoch(train) [555][15/63] lr: 4.0065e-03 eta: 15:19:46 time: 0.9242 data_time: 0.0451 memory: 16201 loss_prob: 0.4753 loss_thr: 0.3273 loss_db: 0.0832 loss: 0.8858 2022/08/30 13:01:22 - mmengine - INFO - Epoch(train) [555][20/63] lr: 4.0065e-03 eta: 15:19:28 time: 0.9560 data_time: 0.0218 memory: 16201 loss_prob: 0.5481 loss_thr: 0.3803 loss_db: 0.0943 loss: 1.0227 2022/08/30 13:01:26 - mmengine - INFO - Epoch(train) [555][25/63] lr: 4.0065e-03 eta: 15:19:28 time: 0.9003 data_time: 0.0544 memory: 16201 loss_prob: 0.5073 loss_thr: 0.3486 loss_db: 0.0860 loss: 0.9420 2022/08/30 13:01:30 - mmengine - INFO - Epoch(train) [555][30/63] lr: 4.0065e-03 eta: 15:19:08 time: 0.8470 data_time: 0.0516 memory: 16201 loss_prob: 0.4840 loss_thr: 0.3384 loss_db: 0.0838 loss: 0.9061 2022/08/30 13:01:35 - mmengine - INFO - Epoch(train) [555][35/63] lr: 4.0065e-03 eta: 15:19:08 time: 0.8431 data_time: 0.0311 memory: 16201 loss_prob: 0.5200 loss_thr: 0.3775 loss_db: 0.0912 loss: 0.9888 2022/08/30 13:01:40 - mmengine - INFO - Epoch(train) [555][40/63] lr: 4.0065e-03 eta: 15:18:49 time: 0.9124 data_time: 0.0421 memory: 16201 loss_prob: 0.5933 loss_thr: 0.3905 loss_db: 0.1008 loss: 1.0846 2022/08/30 13:01:44 - mmengine - INFO - Epoch(train) [555][45/63] lr: 4.0065e-03 eta: 15:18:49 time: 0.8963 data_time: 0.0476 memory: 16201 loss_prob: 0.5921 loss_thr: 0.3766 loss_db: 0.1012 loss: 1.0699 2022/08/30 13:01:48 - mmengine - INFO - Epoch(train) [555][50/63] lr: 4.0065e-03 eta: 15:18:30 time: 0.8647 data_time: 0.0530 memory: 16201 loss_prob: 0.5330 loss_thr: 0.3594 loss_db: 0.0921 loss: 0.9845 2022/08/30 13:01:52 - mmengine - INFO - Epoch(train) [555][55/63] lr: 4.0065e-03 eta: 15:18:30 time: 0.8681 data_time: 0.0565 memory: 16201 loss_prob: 0.5328 loss_thr: 0.3651 loss_db: 0.0917 loss: 0.9895 2022/08/30 13:01:57 - mmengine - INFO - Epoch(train) [555][60/63] lr: 4.0065e-03 eta: 15:18:11 time: 0.8621 data_time: 0.0452 memory: 16201 loss_prob: 0.5367 loss_thr: 0.3711 loss_db: 0.0947 loss: 1.0024 2022/08/30 13:01:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:02:05 - mmengine - INFO - Epoch(train) [556][5/63] lr: 4.0009e-03 eta: 15:18:11 time: 1.0018 data_time: 0.2041 memory: 16201 loss_prob: 0.5608 loss_thr: 0.3867 loss_db: 0.0950 loss: 1.0425 2022/08/30 13:02:09 - mmengine - INFO - Epoch(train) [556][10/63] lr: 4.0009e-03 eta: 15:17:45 time: 1.0318 data_time: 0.2182 memory: 16201 loss_prob: 0.5761 loss_thr: 0.3758 loss_db: 0.0981 loss: 1.0501 2022/08/30 13:02:14 - mmengine - INFO - Epoch(train) [556][15/63] lr: 4.0009e-03 eta: 15:17:45 time: 0.8634 data_time: 0.0286 memory: 16201 loss_prob: 0.4968 loss_thr: 0.3349 loss_db: 0.0861 loss: 0.9178 2022/08/30 13:02:19 - mmengine - INFO - Epoch(train) [556][20/63] lr: 4.0009e-03 eta: 15:17:26 time: 0.9263 data_time: 0.0223 memory: 16201 loss_prob: 0.4616 loss_thr: 0.3147 loss_db: 0.0815 loss: 0.8578 2022/08/30 13:02:23 - mmengine - INFO - Epoch(train) [556][25/63] lr: 4.0009e-03 eta: 15:17:26 time: 0.9644 data_time: 0.0709 memory: 16201 loss_prob: 0.4698 loss_thr: 0.3347 loss_db: 0.0836 loss: 0.8881 2022/08/30 13:02:27 - mmengine - INFO - Epoch(train) [556][30/63] lr: 4.0009e-03 eta: 15:17:07 time: 0.8907 data_time: 0.0745 memory: 16201 loss_prob: 0.4604 loss_thr: 0.3345 loss_db: 0.0797 loss: 0.8746 2022/08/30 13:02:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:02:32 - mmengine - INFO - Epoch(train) [556][35/63] lr: 4.0009e-03 eta: 15:17:07 time: 0.8896 data_time: 0.0371 memory: 16201 loss_prob: 0.4901 loss_thr: 0.3401 loss_db: 0.0830 loss: 0.9132 2022/08/30 13:02:37 - mmengine - INFO - Epoch(train) [556][40/63] lr: 4.0009e-03 eta: 15:16:49 time: 0.9579 data_time: 0.0464 memory: 16201 loss_prob: 0.5013 loss_thr: 0.3374 loss_db: 0.0864 loss: 0.9251 2022/08/30 13:02:41 - mmengine - INFO - Epoch(train) [556][45/63] lr: 4.0009e-03 eta: 15:16:49 time: 0.9137 data_time: 0.0576 memory: 16201 loss_prob: 0.4881 loss_thr: 0.3318 loss_db: 0.0854 loss: 0.9053 2022/08/30 13:02:46 - mmengine - INFO - Epoch(train) [556][50/63] lr: 4.0009e-03 eta: 15:16:30 time: 0.8890 data_time: 0.0403 memory: 16201 loss_prob: 0.4957 loss_thr: 0.3452 loss_db: 0.0858 loss: 0.9268 2022/08/30 13:02:51 - mmengine - INFO - Epoch(train) [556][55/63] lr: 4.0009e-03 eta: 15:16:30 time: 0.9335 data_time: 0.0609 memory: 16201 loss_prob: 0.4818 loss_thr: 0.3352 loss_db: 0.0865 loss: 0.9035 2022/08/30 13:02:55 - mmengine - INFO - Epoch(train) [556][60/63] lr: 4.0009e-03 eta: 15:16:11 time: 0.8646 data_time: 0.0562 memory: 16201 loss_prob: 0.5444 loss_thr: 0.3693 loss_db: 0.0951 loss: 1.0088 2022/08/30 13:02:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:03:03 - mmengine - INFO - Epoch(train) [557][5/63] lr: 3.9954e-03 eta: 15:16:11 time: 1.0007 data_time: 0.2275 memory: 16201 loss_prob: 0.5841 loss_thr: 0.3788 loss_db: 0.0975 loss: 1.0604 2022/08/30 13:03:08 - mmengine - INFO - Epoch(train) [557][10/63] lr: 3.9954e-03 eta: 15:15:46 time: 1.1188 data_time: 0.2669 memory: 16201 loss_prob: 0.5444 loss_thr: 0.3600 loss_db: 0.0939 loss: 0.9983 2022/08/30 13:03:12 - mmengine - INFO - Epoch(train) [557][15/63] lr: 3.9954e-03 eta: 15:15:46 time: 0.9161 data_time: 0.0671 memory: 16201 loss_prob: 0.4849 loss_thr: 0.3416 loss_db: 0.0844 loss: 0.9109 2022/08/30 13:03:17 - mmengine - INFO - Epoch(train) [557][20/63] lr: 3.9954e-03 eta: 15:15:27 time: 0.8776 data_time: 0.0328 memory: 16201 loss_prob: 0.4889 loss_thr: 0.3350 loss_db: 0.0840 loss: 0.9079 2022/08/30 13:03:21 - mmengine - INFO - Epoch(train) [557][25/63] lr: 3.9954e-03 eta: 15:15:27 time: 0.8687 data_time: 0.0410 memory: 16201 loss_prob: 0.4669 loss_thr: 0.3190 loss_db: 0.0787 loss: 0.8646 2022/08/30 13:03:25 - mmengine - INFO - Epoch(train) [557][30/63] lr: 3.9954e-03 eta: 15:15:07 time: 0.8401 data_time: 0.0325 memory: 16201 loss_prob: 0.4549 loss_thr: 0.3223 loss_db: 0.0779 loss: 0.8551 2022/08/30 13:03:29 - mmengine - INFO - Epoch(train) [557][35/63] lr: 3.9954e-03 eta: 15:15:07 time: 0.8427 data_time: 0.0428 memory: 16201 loss_prob: 0.4754 loss_thr: 0.3304 loss_db: 0.0830 loss: 0.8888 2022/08/30 13:03:34 - mmengine - INFO - Epoch(train) [557][40/63] lr: 3.9954e-03 eta: 15:14:48 time: 0.8722 data_time: 0.0716 memory: 16201 loss_prob: 0.5127 loss_thr: 0.3463 loss_db: 0.0881 loss: 0.9471 2022/08/30 13:03:38 - mmengine - INFO - Epoch(train) [557][45/63] lr: 3.9954e-03 eta: 15:14:48 time: 0.8530 data_time: 0.0504 memory: 16201 loss_prob: 0.5407 loss_thr: 0.3540 loss_db: 0.0907 loss: 0.9854 2022/08/30 13:03:43 - mmengine - INFO - Epoch(train) [557][50/63] lr: 3.9954e-03 eta: 15:14:29 time: 0.8754 data_time: 0.0245 memory: 16201 loss_prob: 0.5545 loss_thr: 0.3712 loss_db: 0.0932 loss: 1.0189 2022/08/30 13:03:47 - mmengine - INFO - Epoch(train) [557][55/63] lr: 3.9954e-03 eta: 15:14:29 time: 0.9037 data_time: 0.0523 memory: 16201 loss_prob: 0.5582 loss_thr: 0.3779 loss_db: 0.0981 loss: 1.0341 2022/08/30 13:03:51 - mmengine - INFO - Epoch(train) [557][60/63] lr: 3.9954e-03 eta: 15:14:10 time: 0.8463 data_time: 0.0626 memory: 16201 loss_prob: 0.5606 loss_thr: 0.3724 loss_db: 0.0978 loss: 1.0308 2022/08/30 13:03:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:04:00 - mmengine - INFO - Epoch(train) [558][5/63] lr: 3.9898e-03 eta: 15:14:10 time: 1.0331 data_time: 0.2270 memory: 16201 loss_prob: 0.5334 loss_thr: 0.3695 loss_db: 0.0937 loss: 0.9966 2022/08/30 13:04:04 - mmengine - INFO - Epoch(train) [558][10/63] lr: 3.9898e-03 eta: 15:13:44 time: 1.0619 data_time: 0.2503 memory: 16201 loss_prob: 0.5326 loss_thr: 0.3707 loss_db: 0.0935 loss: 0.9968 2022/08/30 13:04:10 - mmengine - INFO - Epoch(train) [558][15/63] lr: 3.9898e-03 eta: 15:13:44 time: 0.9783 data_time: 0.1120 memory: 16201 loss_prob: 0.5096 loss_thr: 0.3679 loss_db: 0.0870 loss: 0.9645 2022/08/30 13:04:14 - mmengine - INFO - Epoch(train) [558][20/63] lr: 3.9898e-03 eta: 15:13:26 time: 0.9843 data_time: 0.0973 memory: 16201 loss_prob: 0.4867 loss_thr: 0.3505 loss_db: 0.0856 loss: 0.9228 2022/08/30 13:04:19 - mmengine - INFO - Epoch(train) [558][25/63] lr: 3.9898e-03 eta: 15:13:26 time: 0.9380 data_time: 0.0403 memory: 16201 loss_prob: 0.5009 loss_thr: 0.3491 loss_db: 0.0888 loss: 0.9388 2022/08/30 13:04:23 - mmengine - INFO - Epoch(train) [558][30/63] lr: 3.9898e-03 eta: 15:13:08 time: 0.8961 data_time: 0.0403 memory: 16201 loss_prob: 0.5747 loss_thr: 0.3795 loss_db: 0.0968 loss: 1.0510 2022/08/30 13:04:28 - mmengine - INFO - Epoch(train) [558][35/63] lr: 3.9898e-03 eta: 15:13:08 time: 0.8974 data_time: 0.0370 memory: 16201 loss_prob: 0.5386 loss_thr: 0.3461 loss_db: 0.0939 loss: 0.9785 2022/08/30 13:04:32 - mmengine - INFO - Epoch(train) [558][40/63] lr: 3.9898e-03 eta: 15:12:49 time: 0.9310 data_time: 0.0387 memory: 16201 loss_prob: 0.5035 loss_thr: 0.3318 loss_db: 0.0898 loss: 0.9251 2022/08/30 13:04:37 - mmengine - INFO - Epoch(train) [558][45/63] lr: 3.9898e-03 eta: 15:12:49 time: 0.8696 data_time: 0.0319 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3501 loss_db: 0.0852 loss: 0.9248 2022/08/30 13:04:41 - mmengine - INFO - Epoch(train) [558][50/63] lr: 3.9898e-03 eta: 15:12:30 time: 0.8578 data_time: 0.0334 memory: 16201 loss_prob: 0.4841 loss_thr: 0.3519 loss_db: 0.0863 loss: 0.9223 2022/08/30 13:04:45 - mmengine - INFO - Epoch(train) [558][55/63] lr: 3.9898e-03 eta: 15:12:30 time: 0.8754 data_time: 0.0321 memory: 16201 loss_prob: 0.5264 loss_thr: 0.3642 loss_db: 0.0936 loss: 0.9842 2022/08/30 13:04:50 - mmengine - INFO - Epoch(train) [558][60/63] lr: 3.9898e-03 eta: 15:12:11 time: 0.8927 data_time: 0.0368 memory: 16201 loss_prob: 0.5263 loss_thr: 0.3588 loss_db: 0.0907 loss: 0.9758 2022/08/30 13:04:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:04:59 - mmengine - INFO - Epoch(train) [559][5/63] lr: 3.9842e-03 eta: 15:12:11 time: 1.0270 data_time: 0.2089 memory: 16201 loss_prob: 0.4894 loss_thr: 0.3386 loss_db: 0.0839 loss: 0.9118 2022/08/30 13:05:03 - mmengine - INFO - Epoch(train) [559][10/63] lr: 3.9842e-03 eta: 15:11:46 time: 1.0689 data_time: 0.2269 memory: 16201 loss_prob: 0.5133 loss_thr: 0.3537 loss_db: 0.0911 loss: 0.9581 2022/08/30 13:05:08 - mmengine - INFO - Epoch(train) [559][15/63] lr: 3.9842e-03 eta: 15:11:46 time: 0.9395 data_time: 0.0411 memory: 16201 loss_prob: 0.5061 loss_thr: 0.3448 loss_db: 0.0872 loss: 0.9380 2022/08/30 13:05:12 - mmengine - INFO - Epoch(train) [559][20/63] lr: 3.9842e-03 eta: 15:11:27 time: 0.9011 data_time: 0.0276 memory: 16201 loss_prob: 0.4709 loss_thr: 0.3309 loss_db: 0.0812 loss: 0.8830 2022/08/30 13:05:17 - mmengine - INFO - Epoch(train) [559][25/63] lr: 3.9842e-03 eta: 15:11:27 time: 0.8791 data_time: 0.0648 memory: 16201 loss_prob: 0.4995 loss_thr: 0.3522 loss_db: 0.0873 loss: 0.9390 2022/08/30 13:05:21 - mmengine - INFO - Epoch(train) [559][30/63] lr: 3.9842e-03 eta: 15:11:08 time: 0.8979 data_time: 0.0540 memory: 16201 loss_prob: 0.4545 loss_thr: 0.3389 loss_db: 0.0791 loss: 0.8725 2022/08/30 13:05:25 - mmengine - INFO - Epoch(train) [559][35/63] lr: 3.9842e-03 eta: 15:11:08 time: 0.8544 data_time: 0.0258 memory: 16201 loss_prob: 0.4344 loss_thr: 0.3215 loss_db: 0.0761 loss: 0.8319 2022/08/30 13:05:30 - mmengine - INFO - Epoch(train) [559][40/63] lr: 3.9842e-03 eta: 15:10:50 time: 0.9426 data_time: 0.0485 memory: 16201 loss_prob: 0.4533 loss_thr: 0.3245 loss_db: 0.0793 loss: 0.8571 2022/08/30 13:05:35 - mmengine - INFO - Epoch(train) [559][45/63] lr: 3.9842e-03 eta: 15:10:50 time: 0.9313 data_time: 0.0416 memory: 16201 loss_prob: 0.4545 loss_thr: 0.3307 loss_db: 0.0803 loss: 0.8655 2022/08/30 13:05:39 - mmengine - INFO - Epoch(train) [559][50/63] lr: 3.9842e-03 eta: 15:10:31 time: 0.8557 data_time: 0.0385 memory: 16201 loss_prob: 0.5064 loss_thr: 0.3440 loss_db: 0.0868 loss: 0.9372 2022/08/30 13:05:43 - mmengine - INFO - Epoch(train) [559][55/63] lr: 3.9842e-03 eta: 15:10:31 time: 0.8542 data_time: 0.0603 memory: 16201 loss_prob: 0.5227 loss_thr: 0.3531 loss_db: 0.0894 loss: 0.9653 2022/08/30 13:05:47 - mmengine - INFO - Epoch(train) [559][60/63] lr: 3.9842e-03 eta: 15:10:11 time: 0.8353 data_time: 0.0514 memory: 16201 loss_prob: 0.5340 loss_thr: 0.3662 loss_db: 0.0928 loss: 0.9930 2022/08/30 13:05:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:05:56 - mmengine - INFO - Epoch(train) [560][5/63] lr: 3.9786e-03 eta: 15:10:11 time: 1.0421 data_time: 0.2055 memory: 16201 loss_prob: 0.5901 loss_thr: 0.3779 loss_db: 0.0991 loss: 1.0670 2022/08/30 13:06:01 - mmengine - INFO - Epoch(train) [560][10/63] lr: 3.9786e-03 eta: 15:09:46 time: 1.0599 data_time: 0.2202 memory: 16201 loss_prob: 0.5235 loss_thr: 0.3568 loss_db: 0.0924 loss: 0.9726 2022/08/30 13:06:05 - mmengine - INFO - Epoch(train) [560][15/63] lr: 3.9786e-03 eta: 15:09:46 time: 0.9351 data_time: 0.1029 memory: 16201 loss_prob: 0.5493 loss_thr: 0.3723 loss_db: 0.0956 loss: 1.0171 2022/08/30 13:06:10 - mmengine - INFO - Epoch(train) [560][20/63] lr: 3.9786e-03 eta: 15:09:27 time: 0.9332 data_time: 0.0888 memory: 16201 loss_prob: 0.5089 loss_thr: 0.3595 loss_db: 0.0878 loss: 0.9562 2022/08/30 13:06:14 - mmengine - INFO - Epoch(train) [560][25/63] lr: 3.9786e-03 eta: 15:09:27 time: 0.9016 data_time: 0.0514 memory: 16201 loss_prob: 0.4998 loss_thr: 0.3454 loss_db: 0.0871 loss: 0.9323 2022/08/30 13:06:19 - mmengine - INFO - Epoch(train) [560][30/63] lr: 3.9786e-03 eta: 15:09:08 time: 0.8922 data_time: 0.0537 memory: 16201 loss_prob: 0.5223 loss_thr: 0.3527 loss_db: 0.0919 loss: 0.9669 2022/08/30 13:06:23 - mmengine - INFO - Epoch(train) [560][35/63] lr: 3.9786e-03 eta: 15:09:08 time: 0.8625 data_time: 0.0356 memory: 16201 loss_prob: 0.5305 loss_thr: 0.3557 loss_db: 0.0922 loss: 0.9783 2022/08/30 13:06:28 - mmengine - INFO - Epoch(train) [560][40/63] lr: 3.9786e-03 eta: 15:08:50 time: 0.9207 data_time: 0.0321 memory: 16201 loss_prob: 0.5202 loss_thr: 0.3520 loss_db: 0.0883 loss: 0.9604 2022/08/30 13:06:33 - mmengine - INFO - Epoch(train) [560][45/63] lr: 3.9786e-03 eta: 15:08:50 time: 0.9386 data_time: 0.0355 memory: 16201 loss_prob: 0.5160 loss_thr: 0.3582 loss_db: 0.0897 loss: 0.9638 2022/08/30 13:06:37 - mmengine - INFO - Epoch(train) [560][50/63] lr: 3.9786e-03 eta: 15:08:31 time: 0.8797 data_time: 0.0467 memory: 16201 loss_prob: 0.5384 loss_thr: 0.3687 loss_db: 0.0954 loss: 1.0025 2022/08/30 13:06:41 - mmengine - INFO - Epoch(train) [560][55/63] lr: 3.9786e-03 eta: 15:08:31 time: 0.8764 data_time: 0.0374 memory: 16201 loss_prob: 0.5113 loss_thr: 0.3485 loss_db: 0.0901 loss: 0.9499 2022/08/30 13:06:46 - mmengine - INFO - Epoch(train) [560][60/63] lr: 3.9786e-03 eta: 15:08:13 time: 0.9409 data_time: 0.0448 memory: 16201 loss_prob: 0.4499 loss_thr: 0.3311 loss_db: 0.0793 loss: 0.8603 2022/08/30 13:06:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:06:49 - mmengine - INFO - Saving checkpoint at 560 epochs 2022/08/30 13:06:57 - mmengine - INFO - Epoch(val) [560][5/32] eta: 15:08:13 time: 0.6342 data_time: 0.1185 memory: 16201 2022/08/30 13:07:01 - mmengine - INFO - Epoch(val) [560][10/32] eta: 0:00:15 time: 0.7155 data_time: 0.1382 memory: 15734 2022/08/30 13:07:04 - mmengine - INFO - Epoch(val) [560][15/32] eta: 0:00:15 time: 0.6108 data_time: 0.0507 memory: 15734 2022/08/30 13:07:07 - mmengine - INFO - Epoch(val) [560][20/32] eta: 0:00:07 time: 0.6429 data_time: 0.0634 memory: 15734 2022/08/30 13:07:10 - mmengine - INFO - Epoch(val) [560][25/32] eta: 0:00:07 time: 0.6522 data_time: 0.0576 memory: 15734 2022/08/30 13:07:13 - mmengine - INFO - Epoch(val) [560][30/32] eta: 0:00:01 time: 0.5799 data_time: 0.0255 memory: 15734 2022/08/30 13:07:14 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 13:07:14 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8257, precision: 0.7732, hmean: 0.7986 2022/08/30 13:07:14 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8257, precision: 0.8003, hmean: 0.8128 2022/08/30 13:07:14 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8247, precision: 0.8324, hmean: 0.8285 2022/08/30 13:07:14 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8180, precision: 0.8598, hmean: 0.8384 2022/08/30 13:07:14 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8007, precision: 0.8813, hmean: 0.8391 2022/08/30 13:07:14 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7352, precision: 0.9193, hmean: 0.8170 2022/08/30 13:07:14 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2013, precision: 0.9609, hmean: 0.3328 2022/08/30 13:07:14 - mmengine - INFO - Epoch(val) [560][32/32] icdar/precision: 0.8813 icdar/recall: 0.8007 icdar/hmean: 0.8391 2022/08/30 13:07:20 - mmengine - INFO - Epoch(train) [561][5/63] lr: 3.9730e-03 eta: 0:00:01 time: 1.0885 data_time: 0.2090 memory: 16201 loss_prob: 0.5116 loss_thr: 0.3636 loss_db: 0.0907 loss: 0.9659 2022/08/30 13:07:24 - mmengine - INFO - Epoch(train) [561][10/63] lr: 3.9730e-03 eta: 15:07:47 time: 1.0540 data_time: 0.2161 memory: 16201 loss_prob: 0.4923 loss_thr: 0.3488 loss_db: 0.0842 loss: 0.9253 2022/08/30 13:07:29 - mmengine - INFO - Epoch(train) [561][15/63] lr: 3.9730e-03 eta: 15:07:47 time: 0.8350 data_time: 0.0398 memory: 16201 loss_prob: 0.4934 loss_thr: 0.3412 loss_db: 0.0851 loss: 0.9197 2022/08/30 13:07:33 - mmengine - INFO - Epoch(train) [561][20/63] lr: 3.9730e-03 eta: 15:07:28 time: 0.8301 data_time: 0.0396 memory: 16201 loss_prob: 0.5687 loss_thr: 0.3677 loss_db: 0.0987 loss: 1.0351 2022/08/30 13:07:37 - mmengine - INFO - Epoch(train) [561][25/63] lr: 3.9730e-03 eta: 15:07:28 time: 0.8548 data_time: 0.0430 memory: 16201 loss_prob: 0.5225 loss_thr: 0.3517 loss_db: 0.0906 loss: 0.9649 2022/08/30 13:07:41 - mmengine - INFO - Epoch(train) [561][30/63] lr: 3.9730e-03 eta: 15:07:09 time: 0.8444 data_time: 0.0507 memory: 16201 loss_prob: 0.4493 loss_thr: 0.3259 loss_db: 0.0788 loss: 0.8540 2022/08/30 13:07:45 - mmengine - INFO - Epoch(train) [561][35/63] lr: 3.9730e-03 eta: 15:07:09 time: 0.7916 data_time: 0.0334 memory: 16201 loss_prob: 0.4818 loss_thr: 0.3388 loss_db: 0.0854 loss: 0.9060 2022/08/30 13:07:50 - mmengine - INFO - Epoch(train) [561][40/63] lr: 3.9730e-03 eta: 15:06:49 time: 0.8395 data_time: 0.0308 memory: 16201 loss_prob: 0.4786 loss_thr: 0.3357 loss_db: 0.0843 loss: 0.8986 2022/08/30 13:07:54 - mmengine - INFO - Epoch(train) [561][45/63] lr: 3.9730e-03 eta: 15:06:49 time: 0.8692 data_time: 0.0388 memory: 16201 loss_prob: 0.4811 loss_thr: 0.3385 loss_db: 0.0833 loss: 0.9029 2022/08/30 13:07:58 - mmengine - INFO - Epoch(train) [561][50/63] lr: 3.9730e-03 eta: 15:06:30 time: 0.8316 data_time: 0.0435 memory: 16201 loss_prob: 0.4975 loss_thr: 0.3422 loss_db: 0.0874 loss: 0.9270 2022/08/30 13:08:02 - mmengine - INFO - Epoch(train) [561][55/63] lr: 3.9730e-03 eta: 15:06:30 time: 0.8180 data_time: 0.0370 memory: 16201 loss_prob: 0.4863 loss_thr: 0.3385 loss_db: 0.0862 loss: 0.9110 2022/08/30 13:08:07 - mmengine - INFO - Epoch(train) [561][60/63] lr: 3.9730e-03 eta: 15:06:12 time: 0.9399 data_time: 0.0371 memory: 16201 loss_prob: 0.4614 loss_thr: 0.3233 loss_db: 0.0819 loss: 0.8666 2022/08/30 13:08:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:08:16 - mmengine - INFO - Epoch(train) [562][5/63] lr: 3.9674e-03 eta: 15:06:12 time: 1.0854 data_time: 0.2094 memory: 16201 loss_prob: 0.4595 loss_thr: 0.3267 loss_db: 0.0802 loss: 0.8663 2022/08/30 13:08:20 - mmengine - INFO - Epoch(train) [562][10/63] lr: 3.9674e-03 eta: 15:05:46 time: 1.0651 data_time: 0.2208 memory: 16201 loss_prob: 0.4254 loss_thr: 0.3123 loss_db: 0.0735 loss: 0.8112 2022/08/30 13:08:24 - mmengine - INFO - Epoch(train) [562][15/63] lr: 3.9674e-03 eta: 15:05:46 time: 0.8784 data_time: 0.0474 memory: 16201 loss_prob: 0.4179 loss_thr: 0.3103 loss_db: 0.0732 loss: 0.8014 2022/08/30 13:08:29 - mmengine - INFO - Epoch(train) [562][20/63] lr: 3.9674e-03 eta: 15:05:28 time: 0.9314 data_time: 0.0392 memory: 16201 loss_prob: 0.4696 loss_thr: 0.3432 loss_db: 0.0838 loss: 0.8966 2022/08/30 13:08:34 - mmengine - INFO - Epoch(train) [562][25/63] lr: 3.9674e-03 eta: 15:05:28 time: 0.9585 data_time: 0.0750 memory: 16201 loss_prob: 0.5026 loss_thr: 0.3515 loss_db: 0.0855 loss: 0.9395 2022/08/30 13:08:38 - mmengine - INFO - Epoch(train) [562][30/63] lr: 3.9674e-03 eta: 15:05:09 time: 0.8815 data_time: 0.0610 memory: 16201 loss_prob: 0.5574 loss_thr: 0.3737 loss_db: 0.0909 loss: 1.0219 2022/08/30 13:08:43 - mmengine - INFO - Epoch(train) [562][35/63] lr: 3.9674e-03 eta: 15:05:09 time: 0.8502 data_time: 0.0280 memory: 16201 loss_prob: 0.5740 loss_thr: 0.3914 loss_db: 0.0977 loss: 1.0631 2022/08/30 13:08:48 - mmengine - INFO - Epoch(train) [562][40/63] lr: 3.9674e-03 eta: 15:04:51 time: 0.9283 data_time: 0.0614 memory: 16201 loss_prob: 0.4946 loss_thr: 0.3478 loss_db: 0.0853 loss: 0.9278 2022/08/30 13:08:52 - mmengine - INFO - Epoch(train) [562][45/63] lr: 3.9674e-03 eta: 15:04:51 time: 0.9454 data_time: 0.0631 memory: 16201 loss_prob: 0.4766 loss_thr: 0.3361 loss_db: 0.0808 loss: 0.8935 2022/08/30 13:08:57 - mmengine - INFO - Epoch(train) [562][50/63] lr: 3.9674e-03 eta: 15:04:32 time: 0.8977 data_time: 0.0422 memory: 16201 loss_prob: 0.4899 loss_thr: 0.3398 loss_db: 0.0858 loss: 0.9155 2022/08/30 13:09:01 - mmengine - INFO - Epoch(train) [562][55/63] lr: 3.9674e-03 eta: 15:04:32 time: 0.8846 data_time: 0.0480 memory: 16201 loss_prob: 0.4963 loss_thr: 0.3367 loss_db: 0.0889 loss: 0.9220 2022/08/30 13:09:05 - mmengine - INFO - Epoch(train) [562][60/63] lr: 3.9674e-03 eta: 15:04:13 time: 0.8495 data_time: 0.0487 memory: 16201 loss_prob: 0.5059 loss_thr: 0.3429 loss_db: 0.0890 loss: 0.9378 2022/08/30 13:09:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:09:13 - mmengine - INFO - Epoch(train) [563][5/63] lr: 3.9618e-03 eta: 15:04:13 time: 1.0096 data_time: 0.1942 memory: 16201 loss_prob: 0.5139 loss_thr: 0.3547 loss_db: 0.0916 loss: 0.9602 2022/08/30 13:09:18 - mmengine - INFO - Epoch(train) [563][10/63] lr: 3.9618e-03 eta: 15:03:47 time: 1.0514 data_time: 0.2105 memory: 16201 loss_prob: 0.5311 loss_thr: 0.3574 loss_db: 0.0934 loss: 0.9818 2022/08/30 13:09:22 - mmengine - INFO - Epoch(train) [563][15/63] lr: 3.9618e-03 eta: 15:03:47 time: 0.8415 data_time: 0.0307 memory: 16201 loss_prob: 0.5442 loss_thr: 0.3514 loss_db: 0.0961 loss: 0.9918 2022/08/30 13:09:27 - mmengine - INFO - Epoch(train) [563][20/63] lr: 3.9618e-03 eta: 15:03:29 time: 0.9004 data_time: 0.0220 memory: 16201 loss_prob: 0.5236 loss_thr: 0.3401 loss_db: 0.0920 loss: 0.9558 2022/08/30 13:09:31 - mmengine - INFO - Epoch(train) [563][25/63] lr: 3.9618e-03 eta: 15:03:29 time: 0.9344 data_time: 0.0405 memory: 16201 loss_prob: 0.4770 loss_thr: 0.3318 loss_db: 0.0836 loss: 0.8924 2022/08/30 13:09:35 - mmengine - INFO - Epoch(train) [563][30/63] lr: 3.9618e-03 eta: 15:03:10 time: 0.8620 data_time: 0.0364 memory: 16201 loss_prob: 0.4687 loss_thr: 0.3334 loss_db: 0.0848 loss: 0.8869 2022/08/30 13:09:40 - mmengine - INFO - Epoch(train) [563][35/63] lr: 3.9618e-03 eta: 15:03:10 time: 0.8330 data_time: 0.0303 memory: 16201 loss_prob: 0.4893 loss_thr: 0.3409 loss_db: 0.0883 loss: 0.9185 2022/08/30 13:09:44 - mmengine - INFO - Epoch(train) [563][40/63] lr: 3.9618e-03 eta: 15:02:51 time: 0.8377 data_time: 0.0402 memory: 16201 loss_prob: 0.4963 loss_thr: 0.3448 loss_db: 0.0877 loss: 0.9288 2022/08/30 13:09:48 - mmengine - INFO - Epoch(train) [563][45/63] lr: 3.9618e-03 eta: 15:02:51 time: 0.8413 data_time: 0.0381 memory: 16201 loss_prob: 0.5520 loss_thr: 0.3581 loss_db: 0.0937 loss: 1.0038 2022/08/30 13:09:52 - mmengine - INFO - Epoch(train) [563][50/63] lr: 3.9618e-03 eta: 15:02:31 time: 0.8522 data_time: 0.0451 memory: 16201 loss_prob: 0.5246 loss_thr: 0.3431 loss_db: 0.0888 loss: 0.9565 2022/08/30 13:09:57 - mmengine - INFO - Epoch(train) [563][55/63] lr: 3.9618e-03 eta: 15:02:31 time: 0.8529 data_time: 0.0515 memory: 16201 loss_prob: 0.5182 loss_thr: 0.3461 loss_db: 0.0875 loss: 0.9519 2022/08/30 13:10:01 - mmengine - INFO - Epoch(train) [563][60/63] lr: 3.9618e-03 eta: 15:02:12 time: 0.8508 data_time: 0.0446 memory: 16201 loss_prob: 0.5348 loss_thr: 0.3486 loss_db: 0.0898 loss: 0.9733 2022/08/30 13:10:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:10:09 - mmengine - INFO - Epoch(train) [564][5/63] lr: 3.9562e-03 eta: 15:02:12 time: 1.0352 data_time: 0.2363 memory: 16201 loss_prob: 0.4943 loss_thr: 0.3290 loss_db: 0.0864 loss: 0.9098 2022/08/30 13:10:14 - mmengine - INFO - Epoch(train) [564][10/63] lr: 3.9562e-03 eta: 15:01:47 time: 1.1010 data_time: 0.2583 memory: 16201 loss_prob: 0.5299 loss_thr: 0.3438 loss_db: 0.0899 loss: 0.9636 2022/08/30 13:10:19 - mmengine - INFO - Epoch(train) [564][15/63] lr: 3.9562e-03 eta: 15:01:47 time: 0.9424 data_time: 0.0496 memory: 16201 loss_prob: 0.4998 loss_thr: 0.3435 loss_db: 0.0863 loss: 0.9295 2022/08/30 13:10:23 - mmengine - INFO - Epoch(train) [564][20/63] lr: 3.9562e-03 eta: 15:01:29 time: 0.9236 data_time: 0.0424 memory: 16201 loss_prob: 0.4798 loss_thr: 0.3448 loss_db: 0.0852 loss: 0.9098 2022/08/30 13:10:28 - mmengine - INFO - Epoch(train) [564][25/63] lr: 3.9562e-03 eta: 15:01:29 time: 0.8777 data_time: 0.0497 memory: 16201 loss_prob: 0.4799 loss_thr: 0.3381 loss_db: 0.0833 loss: 0.9012 2022/08/30 13:10:32 - mmengine - INFO - Epoch(train) [564][30/63] lr: 3.9562e-03 eta: 15:01:10 time: 0.8609 data_time: 0.0368 memory: 16201 loss_prob: 0.5052 loss_thr: 0.3419 loss_db: 0.0885 loss: 0.9356 2022/08/30 13:10:36 - mmengine - INFO - Epoch(train) [564][35/63] lr: 3.9562e-03 eta: 15:01:10 time: 0.8516 data_time: 0.0313 memory: 16201 loss_prob: 0.5249 loss_thr: 0.3570 loss_db: 0.0925 loss: 0.9743 2022/08/30 13:10:41 - mmengine - INFO - Epoch(train) [564][40/63] lr: 3.9562e-03 eta: 15:00:51 time: 0.8777 data_time: 0.0639 memory: 16201 loss_prob: 0.4792 loss_thr: 0.3286 loss_db: 0.0846 loss: 0.8924 2022/08/30 13:10:45 - mmengine - INFO - Epoch(train) [564][45/63] lr: 3.9562e-03 eta: 15:00:51 time: 0.8893 data_time: 0.0654 memory: 16201 loss_prob: 0.5043 loss_thr: 0.3443 loss_db: 0.0910 loss: 0.9396 2022/08/30 13:10:49 - mmengine - INFO - Epoch(train) [564][50/63] lr: 3.9562e-03 eta: 15:00:32 time: 0.8731 data_time: 0.0356 memory: 16201 loss_prob: 0.5340 loss_thr: 0.3522 loss_db: 0.0946 loss: 0.9808 2022/08/30 13:10:54 - mmengine - INFO - Epoch(train) [564][55/63] lr: 3.9562e-03 eta: 15:00:32 time: 0.8687 data_time: 0.0280 memory: 16201 loss_prob: 0.5066 loss_thr: 0.3363 loss_db: 0.0851 loss: 0.9279 2022/08/30 13:10:58 - mmengine - INFO - Epoch(train) [564][60/63] lr: 3.9562e-03 eta: 15:00:14 time: 0.8980 data_time: 0.0299 memory: 16201 loss_prob: 0.5032 loss_thr: 0.3449 loss_db: 0.0866 loss: 0.9347 2022/08/30 13:11:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:11:07 - mmengine - INFO - Epoch(train) [565][5/63] lr: 3.9506e-03 eta: 15:00:14 time: 1.0578 data_time: 0.2567 memory: 16201 loss_prob: 0.4962 loss_thr: 0.3389 loss_db: 0.0865 loss: 0.9216 2022/08/30 13:11:12 - mmengine - INFO - Epoch(train) [565][10/63] lr: 3.9506e-03 eta: 14:59:50 time: 1.1466 data_time: 0.2876 memory: 16201 loss_prob: 0.5092 loss_thr: 0.3484 loss_db: 0.0859 loss: 0.9436 2022/08/30 13:11:16 - mmengine - INFO - Epoch(train) [565][15/63] lr: 3.9506e-03 eta: 14:59:50 time: 0.9051 data_time: 0.0471 memory: 16201 loss_prob: 0.4945 loss_thr: 0.3414 loss_db: 0.0857 loss: 0.9216 2022/08/30 13:11:20 - mmengine - INFO - Epoch(train) [565][20/63] lr: 3.9506e-03 eta: 14:59:30 time: 0.8505 data_time: 0.0248 memory: 16201 loss_prob: 0.4914 loss_thr: 0.3309 loss_db: 0.0866 loss: 0.9088 2022/08/30 13:11:25 - mmengine - INFO - Epoch(train) [565][25/63] lr: 3.9506e-03 eta: 14:59:30 time: 0.8760 data_time: 0.0433 memory: 16201 loss_prob: 0.4959 loss_thr: 0.3415 loss_db: 0.0855 loss: 0.9229 2022/08/30 13:11:29 - mmengine - INFO - Epoch(train) [565][30/63] lr: 3.9506e-03 eta: 14:59:11 time: 0.8278 data_time: 0.0306 memory: 16201 loss_prob: 0.4737 loss_thr: 0.3421 loss_db: 0.0827 loss: 0.8984 2022/08/30 13:11:33 - mmengine - INFO - Epoch(train) [565][35/63] lr: 3.9506e-03 eta: 14:59:11 time: 0.7914 data_time: 0.0283 memory: 16201 loss_prob: 0.5146 loss_thr: 0.3482 loss_db: 0.0889 loss: 0.9516 2022/08/30 13:11:37 - mmengine - INFO - Epoch(train) [565][40/63] lr: 3.9506e-03 eta: 14:58:52 time: 0.8620 data_time: 0.0451 memory: 16201 loss_prob: 0.5147 loss_thr: 0.3428 loss_db: 0.0866 loss: 0.9441 2022/08/30 13:11:41 - mmengine - INFO - Epoch(train) [565][45/63] lr: 3.9506e-03 eta: 14:58:52 time: 0.8447 data_time: 0.0415 memory: 16201 loss_prob: 0.4879 loss_thr: 0.3348 loss_db: 0.0827 loss: 0.9054 2022/08/30 13:11:45 - mmengine - INFO - Epoch(train) [565][50/63] lr: 3.9506e-03 eta: 14:58:33 time: 0.7979 data_time: 0.0397 memory: 16201 loss_prob: 0.5105 loss_thr: 0.3431 loss_db: 0.0899 loss: 0.9435 2022/08/30 13:11:50 - mmengine - INFO - Epoch(train) [565][55/63] lr: 3.9506e-03 eta: 14:58:33 time: 0.8599 data_time: 0.0548 memory: 16201 loss_prob: 0.5247 loss_thr: 0.3494 loss_db: 0.0931 loss: 0.9672 2022/08/30 13:11:54 - mmengine - INFO - Epoch(train) [565][60/63] lr: 3.9506e-03 eta: 14:58:14 time: 0.8683 data_time: 0.0559 memory: 16201 loss_prob: 0.5096 loss_thr: 0.3394 loss_db: 0.0868 loss: 0.9357 2022/08/30 13:11:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:12:02 - mmengine - INFO - Epoch(train) [566][5/63] lr: 3.9450e-03 eta: 14:58:14 time: 0.9549 data_time: 0.1914 memory: 16201 loss_prob: 0.4573 loss_thr: 0.3189 loss_db: 0.0819 loss: 0.8581 2022/08/30 13:12:06 - mmengine - INFO - Epoch(train) [566][10/63] lr: 3.9450e-03 eta: 14:57:48 time: 1.0368 data_time: 0.2145 memory: 16201 loss_prob: 0.4965 loss_thr: 0.3511 loss_db: 0.0861 loss: 0.9337 2022/08/30 13:12:11 - mmengine - INFO - Epoch(train) [566][15/63] lr: 3.9450e-03 eta: 14:57:48 time: 0.8727 data_time: 0.0406 memory: 16201 loss_prob: 0.4866 loss_thr: 0.3456 loss_db: 0.0821 loss: 0.9143 2022/08/30 13:12:15 - mmengine - INFO - Epoch(train) [566][20/63] lr: 3.9450e-03 eta: 14:57:29 time: 0.8589 data_time: 0.0277 memory: 16201 loss_prob: 0.4506 loss_thr: 0.3260 loss_db: 0.0781 loss: 0.8548 2022/08/30 13:12:20 - mmengine - INFO - Epoch(train) [566][25/63] lr: 3.9450e-03 eta: 14:57:29 time: 0.9389 data_time: 0.0907 memory: 16201 loss_prob: 0.4897 loss_thr: 0.3617 loss_db: 0.0873 loss: 0.9387 2022/08/30 13:12:25 - mmengine - INFO - Epoch(train) [566][30/63] lr: 3.9450e-03 eta: 14:57:12 time: 0.9898 data_time: 0.1465 memory: 16201 loss_prob: 0.4945 loss_thr: 0.3614 loss_db: 0.0873 loss: 0.9432 2022/08/30 13:12:30 - mmengine - INFO - Epoch(train) [566][35/63] lr: 3.9450e-03 eta: 14:57:12 time: 0.9867 data_time: 0.1123 memory: 16201 loss_prob: 0.4595 loss_thr: 0.3263 loss_db: 0.0787 loss: 0.8645 2022/08/30 13:12:34 - mmengine - INFO - Epoch(train) [566][40/63] lr: 3.9450e-03 eta: 14:56:54 time: 0.9423 data_time: 0.0660 memory: 16201 loss_prob: 0.5048 loss_thr: 0.3474 loss_db: 0.0879 loss: 0.9401 2022/08/30 13:12:39 - mmengine - INFO - Epoch(train) [566][45/63] lr: 3.9450e-03 eta: 14:56:54 time: 0.9206 data_time: 0.0436 memory: 16201 loss_prob: 0.5100 loss_thr: 0.3507 loss_db: 0.0907 loss: 0.9515 2022/08/30 13:12:44 - mmengine - INFO - Epoch(train) [566][50/63] lr: 3.9450e-03 eta: 14:56:35 time: 0.9201 data_time: 0.0276 memory: 16201 loss_prob: 0.4983 loss_thr: 0.3372 loss_db: 0.0858 loss: 0.9214 2022/08/30 13:12:48 - mmengine - INFO - Epoch(train) [566][55/63] lr: 3.9450e-03 eta: 14:56:35 time: 0.8943 data_time: 0.0338 memory: 16201 loss_prob: 0.5422 loss_thr: 0.3618 loss_db: 0.0936 loss: 0.9977 2022/08/30 13:12:52 - mmengine - INFO - Epoch(train) [566][60/63] lr: 3.9450e-03 eta: 14:56:17 time: 0.8951 data_time: 0.0349 memory: 16201 loss_prob: 0.5305 loss_thr: 0.3632 loss_db: 0.0928 loss: 0.9866 2022/08/30 13:12:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:13:01 - mmengine - INFO - Epoch(train) [567][5/63] lr: 3.9394e-03 eta: 14:56:17 time: 0.9978 data_time: 0.1916 memory: 16201 loss_prob: 0.4600 loss_thr: 0.3126 loss_db: 0.0808 loss: 0.8534 2022/08/30 13:13:05 - mmengine - INFO - Epoch(train) [567][10/63] lr: 3.9394e-03 eta: 14:55:51 time: 1.0317 data_time: 0.2036 memory: 16201 loss_prob: 0.4702 loss_thr: 0.3307 loss_db: 0.0812 loss: 0.8820 2022/08/30 13:13:10 - mmengine - INFO - Epoch(train) [567][15/63] lr: 3.9394e-03 eta: 14:55:51 time: 0.9043 data_time: 0.0389 memory: 16201 loss_prob: 0.5024 loss_thr: 0.3571 loss_db: 0.0860 loss: 0.9454 2022/08/30 13:13:14 - mmengine - INFO - Epoch(train) [567][20/63] lr: 3.9394e-03 eta: 14:55:33 time: 0.9050 data_time: 0.0366 memory: 16201 loss_prob: 0.4888 loss_thr: 0.3424 loss_db: 0.0838 loss: 0.9149 2022/08/30 13:13:19 - mmengine - INFO - Epoch(train) [567][25/63] lr: 3.9394e-03 eta: 14:55:33 time: 0.9093 data_time: 0.0542 memory: 16201 loss_prob: 0.4724 loss_thr: 0.3268 loss_db: 0.0833 loss: 0.8825 2022/08/30 13:13:23 - mmengine - INFO - Epoch(train) [567][30/63] lr: 3.9394e-03 eta: 14:55:15 time: 0.8958 data_time: 0.0474 memory: 16201 loss_prob: 0.4382 loss_thr: 0.3167 loss_db: 0.0786 loss: 0.8335 2022/08/30 13:13:27 - mmengine - INFO - Epoch(train) [567][35/63] lr: 3.9394e-03 eta: 14:55:15 time: 0.8211 data_time: 0.0218 memory: 16201 loss_prob: 0.4685 loss_thr: 0.3294 loss_db: 0.0807 loss: 0.8786 2022/08/30 13:13:31 - mmengine - INFO - Epoch(train) [567][40/63] lr: 3.9394e-03 eta: 14:54:55 time: 0.8366 data_time: 0.0529 memory: 16201 loss_prob: 0.5113 loss_thr: 0.3481 loss_db: 0.0887 loss: 0.9481 2022/08/30 13:13:36 - mmengine - INFO - Epoch(train) [567][45/63] lr: 3.9394e-03 eta: 14:54:55 time: 0.8790 data_time: 0.0599 memory: 16201 loss_prob: 0.4756 loss_thr: 0.3268 loss_db: 0.0839 loss: 0.8862 2022/08/30 13:13:40 - mmengine - INFO - Epoch(train) [567][50/63] lr: 3.9394e-03 eta: 14:54:37 time: 0.9059 data_time: 0.0383 memory: 16201 loss_prob: 0.4718 loss_thr: 0.3268 loss_db: 0.0824 loss: 0.8811 2022/08/30 13:13:45 - mmengine - INFO - Epoch(train) [567][55/63] lr: 3.9394e-03 eta: 14:54:37 time: 0.8926 data_time: 0.0508 memory: 16201 loss_prob: 0.4570 loss_thr: 0.3291 loss_db: 0.0812 loss: 0.8674 2022/08/30 13:13:49 - mmengine - INFO - Epoch(train) [567][60/63] lr: 3.9394e-03 eta: 14:54:18 time: 0.8723 data_time: 0.0458 memory: 16201 loss_prob: 0.4255 loss_thr: 0.3122 loss_db: 0.0753 loss: 0.8131 2022/08/30 13:13:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:13:58 - mmengine - INFO - Epoch(train) [568][5/63] lr: 3.9338e-03 eta: 14:54:18 time: 1.0414 data_time: 0.2621 memory: 16201 loss_prob: 0.4638 loss_thr: 0.3380 loss_db: 0.0803 loss: 0.8821 2022/08/30 13:14:02 - mmengine - INFO - Epoch(train) [568][10/63] lr: 3.9338e-03 eta: 14:53:53 time: 1.0711 data_time: 0.2731 memory: 16201 loss_prob: 0.4944 loss_thr: 0.3509 loss_db: 0.0856 loss: 0.9309 2022/08/30 13:14:06 - mmengine - INFO - Epoch(train) [568][15/63] lr: 3.9338e-03 eta: 14:53:53 time: 0.8426 data_time: 0.0370 memory: 16201 loss_prob: 0.5368 loss_thr: 0.3694 loss_db: 0.0937 loss: 0.9999 2022/08/30 13:14:11 - mmengine - INFO - Epoch(train) [568][20/63] lr: 3.9338e-03 eta: 14:53:34 time: 0.8627 data_time: 0.0309 memory: 16201 loss_prob: 0.5258 loss_thr: 0.3612 loss_db: 0.0909 loss: 0.9780 2022/08/30 13:14:15 - mmengine - INFO - Epoch(train) [568][25/63] lr: 3.9338e-03 eta: 14:53:34 time: 0.8789 data_time: 0.0353 memory: 16201 loss_prob: 0.4709 loss_thr: 0.3378 loss_db: 0.0813 loss: 0.8901 2022/08/30 13:14:19 - mmengine - INFO - Epoch(train) [568][30/63] lr: 3.9338e-03 eta: 14:53:16 time: 0.8677 data_time: 0.0318 memory: 16201 loss_prob: 0.5008 loss_thr: 0.3569 loss_db: 0.0855 loss: 0.9431 2022/08/30 13:14:24 - mmengine - INFO - Epoch(train) [568][35/63] lr: 3.9338e-03 eta: 14:53:16 time: 0.8552 data_time: 0.0383 memory: 16201 loss_prob: 0.5527 loss_thr: 0.3844 loss_db: 0.0961 loss: 1.0331 2022/08/30 13:14:28 - mmengine - INFO - Epoch(train) [568][40/63] lr: 3.9338e-03 eta: 14:52:57 time: 0.8584 data_time: 0.0374 memory: 16201 loss_prob: 0.4866 loss_thr: 0.3504 loss_db: 0.0850 loss: 0.9220 2022/08/30 13:14:32 - mmengine - INFO - Epoch(train) [568][45/63] lr: 3.9338e-03 eta: 14:52:57 time: 0.8566 data_time: 0.0326 memory: 16201 loss_prob: 0.4827 loss_thr: 0.3380 loss_db: 0.0828 loss: 0.9035 2022/08/30 13:14:37 - mmengine - INFO - Epoch(train) [568][50/63] lr: 3.9338e-03 eta: 14:52:38 time: 0.8628 data_time: 0.0419 memory: 16201 loss_prob: 0.5184 loss_thr: 0.3611 loss_db: 0.0913 loss: 0.9708 2022/08/30 13:14:41 - mmengine - INFO - Epoch(train) [568][55/63] lr: 3.9338e-03 eta: 14:52:38 time: 0.8732 data_time: 0.0696 memory: 16201 loss_prob: 0.5280 loss_thr: 0.3705 loss_db: 0.0925 loss: 0.9910 2022/08/30 13:14:45 - mmengine - INFO - Epoch(train) [568][60/63] lr: 3.9338e-03 eta: 14:52:19 time: 0.8836 data_time: 0.0624 memory: 16201 loss_prob: 0.5130 loss_thr: 0.3484 loss_db: 0.0887 loss: 0.9501 2022/08/30 13:14:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:14:53 - mmengine - INFO - Epoch(train) [569][5/63] lr: 3.9282e-03 eta: 14:52:19 time: 0.9910 data_time: 0.1968 memory: 16201 loss_prob: 0.4802 loss_thr: 0.3207 loss_db: 0.0818 loss: 0.8827 2022/08/30 13:14:58 - mmengine - INFO - Epoch(train) [569][10/63] lr: 3.9282e-03 eta: 14:51:54 time: 1.0269 data_time: 0.2090 memory: 16201 loss_prob: 0.5045 loss_thr: 0.3395 loss_db: 0.0852 loss: 0.9292 2022/08/30 13:15:02 - mmengine - INFO - Epoch(train) [569][15/63] lr: 3.9282e-03 eta: 14:51:54 time: 0.8430 data_time: 0.0313 memory: 16201 loss_prob: 0.4834 loss_thr: 0.3467 loss_db: 0.0838 loss: 0.9139 2022/08/30 13:15:06 - mmengine - INFO - Epoch(train) [569][20/63] lr: 3.9282e-03 eta: 14:51:35 time: 0.8565 data_time: 0.0359 memory: 16201 loss_prob: 0.5559 loss_thr: 0.3499 loss_db: 0.0936 loss: 0.9994 2022/08/30 13:15:11 - mmengine - INFO - Epoch(train) [569][25/63] lr: 3.9282e-03 eta: 14:51:35 time: 0.9535 data_time: 0.1036 memory: 16201 loss_prob: 0.6167 loss_thr: 0.3684 loss_db: 0.1023 loss: 1.0873 2022/08/30 13:15:16 - mmengine - INFO - Epoch(train) [569][30/63] lr: 3.9282e-03 eta: 14:51:17 time: 0.9225 data_time: 0.0850 memory: 16201 loss_prob: 0.5987 loss_thr: 0.3723 loss_db: 0.1014 loss: 1.0723 2022/08/30 13:15:20 - mmengine - INFO - Epoch(train) [569][35/63] lr: 3.9282e-03 eta: 14:51:17 time: 0.8496 data_time: 0.0241 memory: 16201 loss_prob: 0.5941 loss_thr: 0.3834 loss_db: 0.0997 loss: 1.0771 2022/08/30 13:15:25 - mmengine - INFO - Epoch(train) [569][40/63] lr: 3.9282e-03 eta: 14:50:58 time: 0.8958 data_time: 0.0466 memory: 16201 loss_prob: 0.5637 loss_thr: 0.3767 loss_db: 0.0956 loss: 1.0359 2022/08/30 13:15:29 - mmengine - INFO - Epoch(train) [569][45/63] lr: 3.9282e-03 eta: 14:50:58 time: 0.8586 data_time: 0.0469 memory: 16201 loss_prob: 0.5773 loss_thr: 0.3906 loss_db: 0.1011 loss: 1.0690 2022/08/30 13:15:33 - mmengine - INFO - Epoch(train) [569][50/63] lr: 3.9282e-03 eta: 14:50:39 time: 0.8142 data_time: 0.0368 memory: 16201 loss_prob: 0.6076 loss_thr: 0.4081 loss_db: 0.1038 loss: 1.1194 2022/08/30 13:15:38 - mmengine - INFO - Epoch(train) [569][55/63] lr: 3.9282e-03 eta: 14:50:39 time: 0.9153 data_time: 0.0630 memory: 16201 loss_prob: 0.5729 loss_thr: 0.3835 loss_db: 0.0961 loss: 1.0525 2022/08/30 13:15:42 - mmengine - INFO - Epoch(train) [569][60/63] lr: 3.9282e-03 eta: 14:50:21 time: 0.9002 data_time: 0.0630 memory: 16201 loss_prob: 0.5611 loss_thr: 0.3712 loss_db: 0.0963 loss: 1.0287 2022/08/30 13:15:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:15:50 - mmengine - INFO - Epoch(train) [570][5/63] lr: 3.9226e-03 eta: 14:50:21 time: 0.9464 data_time: 0.1893 memory: 16201 loss_prob: 0.5294 loss_thr: 0.3580 loss_db: 0.0907 loss: 0.9782 2022/08/30 13:15:54 - mmengine - INFO - Epoch(train) [570][10/63] lr: 3.9226e-03 eta: 14:49:55 time: 1.0434 data_time: 0.2091 memory: 16201 loss_prob: 0.5119 loss_thr: 0.3582 loss_db: 0.0880 loss: 0.9581 2022/08/30 13:15:58 - mmengine - INFO - Epoch(train) [570][15/63] lr: 3.9226e-03 eta: 14:49:55 time: 0.8779 data_time: 0.0418 memory: 16201 loss_prob: 0.4946 loss_thr: 0.3528 loss_db: 0.0870 loss: 0.9344 2022/08/30 13:16:03 - mmengine - INFO - Epoch(train) [570][20/63] lr: 3.9226e-03 eta: 14:49:37 time: 0.8819 data_time: 0.0356 memory: 16201 loss_prob: 0.4982 loss_thr: 0.3473 loss_db: 0.0885 loss: 0.9340 2022/08/30 13:16:07 - mmengine - INFO - Epoch(train) [570][25/63] lr: 3.9226e-03 eta: 14:49:37 time: 0.8999 data_time: 0.0486 memory: 16201 loss_prob: 0.5124 loss_thr: 0.3593 loss_db: 0.0907 loss: 0.9624 2022/08/30 13:16:12 - mmengine - INFO - Epoch(train) [570][30/63] lr: 3.9226e-03 eta: 14:49:18 time: 0.8863 data_time: 0.0471 memory: 16201 loss_prob: 0.5092 loss_thr: 0.3601 loss_db: 0.0895 loss: 0.9588 2022/08/30 13:16:17 - mmengine - INFO - Epoch(train) [570][35/63] lr: 3.9226e-03 eta: 14:49:18 time: 0.9141 data_time: 0.0792 memory: 16201 loss_prob: 0.5177 loss_thr: 0.3422 loss_db: 0.0931 loss: 0.9530 2022/08/30 13:16:21 - mmengine - INFO - Epoch(train) [570][40/63] lr: 3.9226e-03 eta: 14:49:00 time: 0.9148 data_time: 0.0968 memory: 16201 loss_prob: 0.5087 loss_thr: 0.3359 loss_db: 0.0910 loss: 0.9357 2022/08/30 13:16:25 - mmengine - INFO - Epoch(train) [570][45/63] lr: 3.9226e-03 eta: 14:49:00 time: 0.8529 data_time: 0.0585 memory: 16201 loss_prob: 0.4999 loss_thr: 0.3386 loss_db: 0.0861 loss: 0.9245 2022/08/30 13:16:31 - mmengine - INFO - Epoch(train) [570][50/63] lr: 3.9226e-03 eta: 14:48:43 time: 0.9534 data_time: 0.0448 memory: 16201 loss_prob: 0.4985 loss_thr: 0.3334 loss_db: 0.0878 loss: 0.9197 2022/08/30 13:16:35 - mmengine - INFO - Epoch(train) [570][55/63] lr: 3.9226e-03 eta: 14:48:43 time: 0.9785 data_time: 0.0645 memory: 16201 loss_prob: 0.4502 loss_thr: 0.3199 loss_db: 0.0811 loss: 0.8511 2022/08/30 13:16:39 - mmengine - INFO - Epoch(train) [570][60/63] lr: 3.9226e-03 eta: 14:48:24 time: 0.8787 data_time: 0.0544 memory: 16201 loss_prob: 0.5244 loss_thr: 0.3587 loss_db: 0.0939 loss: 0.9771 2022/08/30 13:16:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:16:48 - mmengine - INFO - Epoch(train) [571][5/63] lr: 3.9170e-03 eta: 14:48:24 time: 1.0556 data_time: 0.2663 memory: 16201 loss_prob: 0.5602 loss_thr: 0.3657 loss_db: 0.0971 loss: 1.0231 2022/08/30 13:16:52 - mmengine - INFO - Epoch(train) [571][10/63] lr: 3.9170e-03 eta: 14:47:59 time: 1.1022 data_time: 0.2875 memory: 16201 loss_prob: 0.4933 loss_thr: 0.3501 loss_db: 0.0857 loss: 0.9290 2022/08/30 13:16:57 - mmengine - INFO - Epoch(train) [571][15/63] lr: 3.9170e-03 eta: 14:47:59 time: 0.8811 data_time: 0.0399 memory: 16201 loss_prob: 0.4797 loss_thr: 0.3465 loss_db: 0.0843 loss: 0.9105 2022/08/30 13:17:01 - mmengine - INFO - Epoch(train) [571][20/63] lr: 3.9170e-03 eta: 14:47:41 time: 0.9049 data_time: 0.0355 memory: 16201 loss_prob: 0.5040 loss_thr: 0.3534 loss_db: 0.0881 loss: 0.9455 2022/08/30 13:17:06 - mmengine - INFO - Epoch(train) [571][25/63] lr: 3.9170e-03 eta: 14:47:41 time: 0.8610 data_time: 0.0391 memory: 16201 loss_prob: 0.5260 loss_thr: 0.3532 loss_db: 0.0914 loss: 0.9706 2022/08/30 13:17:10 - mmengine - INFO - Epoch(train) [571][30/63] lr: 3.9170e-03 eta: 14:47:22 time: 0.8180 data_time: 0.0306 memory: 16201 loss_prob: 0.5303 loss_thr: 0.3615 loss_db: 0.0932 loss: 0.9851 2022/08/30 13:17:14 - mmengine - INFO - Epoch(train) [571][35/63] lr: 3.9170e-03 eta: 14:47:22 time: 0.8344 data_time: 0.0286 memory: 16201 loss_prob: 0.5493 loss_thr: 0.3646 loss_db: 0.0949 loss: 1.0088 2022/08/30 13:17:18 - mmengine - INFO - Epoch(train) [571][40/63] lr: 3.9170e-03 eta: 14:47:03 time: 0.8732 data_time: 0.0413 memory: 16201 loss_prob: 0.4961 loss_thr: 0.3373 loss_db: 0.0848 loss: 0.9182 2022/08/30 13:17:23 - mmengine - INFO - Epoch(train) [571][45/63] lr: 3.9170e-03 eta: 14:47:03 time: 0.8697 data_time: 0.0442 memory: 16201 loss_prob: 0.4756 loss_thr: 0.3475 loss_db: 0.0829 loss: 0.9060 2022/08/30 13:17:27 - mmengine - INFO - Epoch(train) [571][50/63] lr: 3.9170e-03 eta: 14:46:45 time: 0.8732 data_time: 0.0364 memory: 16201 loss_prob: 0.4744 loss_thr: 0.3392 loss_db: 0.0834 loss: 0.8970 2022/08/30 13:17:32 - mmengine - INFO - Epoch(train) [571][55/63] lr: 3.9170e-03 eta: 14:46:45 time: 0.9062 data_time: 0.0482 memory: 16201 loss_prob: 0.4763 loss_thr: 0.3247 loss_db: 0.0835 loss: 0.8845 2022/08/30 13:17:36 - mmengine - INFO - Epoch(train) [571][60/63] lr: 3.9170e-03 eta: 14:46:26 time: 0.8885 data_time: 0.0490 memory: 16201 loss_prob: 0.5113 loss_thr: 0.3482 loss_db: 0.0887 loss: 0.9482 2022/08/30 13:17:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:17:45 - mmengine - INFO - Epoch(train) [572][5/63] lr: 3.9114e-03 eta: 14:46:26 time: 1.0085 data_time: 0.2068 memory: 16201 loss_prob: 0.4802 loss_thr: 0.3321 loss_db: 0.0828 loss: 0.8951 2022/08/30 13:17:49 - mmengine - INFO - Epoch(train) [572][10/63] lr: 3.9114e-03 eta: 14:46:01 time: 1.0758 data_time: 0.2236 memory: 16201 loss_prob: 0.4629 loss_thr: 0.3044 loss_db: 0.0803 loss: 0.8476 2022/08/30 13:17:53 - mmengine - INFO - Epoch(train) [572][15/63] lr: 3.9114e-03 eta: 14:46:01 time: 0.8648 data_time: 0.0381 memory: 16201 loss_prob: 0.4776 loss_thr: 0.3270 loss_db: 0.0834 loss: 0.8880 2022/08/30 13:17:58 - mmengine - INFO - Epoch(train) [572][20/63] lr: 3.9114e-03 eta: 14:45:43 time: 0.8978 data_time: 0.0367 memory: 16201 loss_prob: 0.5031 loss_thr: 0.3411 loss_db: 0.0880 loss: 0.9322 2022/08/30 13:18:02 - mmengine - INFO - Epoch(train) [572][25/63] lr: 3.9114e-03 eta: 14:45:43 time: 0.9217 data_time: 0.0671 memory: 16201 loss_prob: 0.5358 loss_thr: 0.3556 loss_db: 0.0939 loss: 0.9854 2022/08/30 13:18:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:18:07 - mmengine - INFO - Epoch(train) [572][30/63] lr: 3.9114e-03 eta: 14:45:25 time: 0.8881 data_time: 0.0628 memory: 16201 loss_prob: 0.4994 loss_thr: 0.3441 loss_db: 0.0870 loss: 0.9305 2022/08/30 13:18:11 - mmengine - INFO - Epoch(train) [572][35/63] lr: 3.9114e-03 eta: 14:45:25 time: 0.8749 data_time: 0.0373 memory: 16201 loss_prob: 0.4269 loss_thr: 0.3231 loss_db: 0.0744 loss: 0.8245 2022/08/30 13:18:16 - mmengine - INFO - Epoch(train) [572][40/63] lr: 3.9114e-03 eta: 14:45:06 time: 0.8755 data_time: 0.0362 memory: 16201 loss_prob: 0.4898 loss_thr: 0.3453 loss_db: 0.0848 loss: 0.9198 2022/08/30 13:18:21 - mmengine - INFO - Epoch(train) [572][45/63] lr: 3.9114e-03 eta: 14:45:06 time: 0.9725 data_time: 0.0410 memory: 16201 loss_prob: 0.5465 loss_thr: 0.3656 loss_db: 0.0930 loss: 1.0051 2022/08/30 13:18:25 - mmengine - INFO - Epoch(train) [572][50/63] lr: 3.9114e-03 eta: 14:44:49 time: 0.9822 data_time: 0.0457 memory: 16201 loss_prob: 0.5033 loss_thr: 0.3612 loss_db: 0.0875 loss: 0.9520 2022/08/30 13:18:30 - mmengine - INFO - Epoch(train) [572][55/63] lr: 3.9114e-03 eta: 14:44:49 time: 0.9131 data_time: 0.0574 memory: 16201 loss_prob: 0.5183 loss_thr: 0.3624 loss_db: 0.0893 loss: 0.9700 2022/08/30 13:18:34 - mmengine - INFO - Epoch(train) [572][60/63] lr: 3.9114e-03 eta: 14:44:30 time: 0.8774 data_time: 0.0479 memory: 16201 loss_prob: 0.5509 loss_thr: 0.3848 loss_db: 0.0948 loss: 1.0305 2022/08/30 13:18:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:18:43 - mmengine - INFO - Epoch(train) [573][5/63] lr: 3.9058e-03 eta: 14:44:30 time: 1.0632 data_time: 0.2486 memory: 16201 loss_prob: 0.4784 loss_thr: 0.3589 loss_db: 0.0840 loss: 0.9213 2022/08/30 13:18:48 - mmengine - INFO - Epoch(train) [573][10/63] lr: 3.9058e-03 eta: 14:44:07 time: 1.2089 data_time: 0.2676 memory: 16201 loss_prob: 0.4610 loss_thr: 0.3428 loss_db: 0.0804 loss: 0.8842 2022/08/30 13:18:53 - mmengine - INFO - Epoch(train) [573][15/63] lr: 3.9058e-03 eta: 14:44:07 time: 0.9239 data_time: 0.0385 memory: 16201 loss_prob: 0.5115 loss_thr: 0.3545 loss_db: 0.0892 loss: 0.9552 2022/08/30 13:18:57 - mmengine - INFO - Epoch(train) [573][20/63] lr: 3.9058e-03 eta: 14:43:48 time: 0.8240 data_time: 0.0235 memory: 16201 loss_prob: 0.5477 loss_thr: 0.3797 loss_db: 0.0955 loss: 1.0228 2022/08/30 13:19:01 - mmengine - INFO - Epoch(train) [573][25/63] lr: 3.9058e-03 eta: 14:43:48 time: 0.8644 data_time: 0.0405 memory: 16201 loss_prob: 0.5220 loss_thr: 0.3738 loss_db: 0.0912 loss: 0.9870 2022/08/30 13:19:05 - mmengine - INFO - Epoch(train) [573][30/63] lr: 3.9058e-03 eta: 14:43:29 time: 0.8725 data_time: 0.0428 memory: 16201 loss_prob: 0.5127 loss_thr: 0.3535 loss_db: 0.0890 loss: 0.9552 2022/08/30 13:19:10 - mmengine - INFO - Epoch(train) [573][35/63] lr: 3.9058e-03 eta: 14:43:29 time: 0.8439 data_time: 0.0315 memory: 16201 loss_prob: 0.5153 loss_thr: 0.3543 loss_db: 0.0905 loss: 0.9601 2022/08/30 13:19:14 - mmengine - INFO - Epoch(train) [573][40/63] lr: 3.9058e-03 eta: 14:43:11 time: 0.8384 data_time: 0.0289 memory: 16201 loss_prob: 0.4504 loss_thr: 0.3251 loss_db: 0.0788 loss: 0.8543 2022/08/30 13:19:18 - mmengine - INFO - Epoch(train) [573][45/63] lr: 3.9058e-03 eta: 14:43:11 time: 0.8208 data_time: 0.0248 memory: 16201 loss_prob: 0.4418 loss_thr: 0.3051 loss_db: 0.0771 loss: 0.8239 2022/08/30 13:19:22 - mmengine - INFO - Epoch(train) [573][50/63] lr: 3.9058e-03 eta: 14:42:52 time: 0.8393 data_time: 0.0287 memory: 16201 loss_prob: 0.4406 loss_thr: 0.3081 loss_db: 0.0776 loss: 0.8263 2022/08/30 13:19:26 - mmengine - INFO - Epoch(train) [573][55/63] lr: 3.9058e-03 eta: 14:42:52 time: 0.8588 data_time: 0.0414 memory: 16201 loss_prob: 0.4855 loss_thr: 0.3398 loss_db: 0.0832 loss: 0.9086 2022/08/30 13:19:31 - mmengine - INFO - Epoch(train) [573][60/63] lr: 3.9058e-03 eta: 14:42:33 time: 0.8715 data_time: 0.0378 memory: 16201 loss_prob: 0.5598 loss_thr: 0.3682 loss_db: 0.0975 loss: 1.0255 2022/08/30 13:19:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:19:39 - mmengine - INFO - Epoch(train) [574][5/63] lr: 3.9002e-03 eta: 14:42:33 time: 0.9489 data_time: 0.1987 memory: 16201 loss_prob: 0.5018 loss_thr: 0.3551 loss_db: 0.0886 loss: 0.9456 2022/08/30 13:19:43 - mmengine - INFO - Epoch(train) [574][10/63] lr: 3.9002e-03 eta: 14:42:07 time: 0.9768 data_time: 0.2043 memory: 16201 loss_prob: 0.4878 loss_thr: 0.3612 loss_db: 0.0835 loss: 0.9325 2022/08/30 13:19:47 - mmengine - INFO - Epoch(train) [574][15/63] lr: 3.9002e-03 eta: 14:42:07 time: 0.7844 data_time: 0.0255 memory: 16201 loss_prob: 0.5111 loss_thr: 0.3539 loss_db: 0.0865 loss: 0.9514 2022/08/30 13:19:51 - mmengine - INFO - Epoch(train) [574][20/63] lr: 3.9002e-03 eta: 14:41:48 time: 0.8135 data_time: 0.0186 memory: 16201 loss_prob: 0.4930 loss_thr: 0.3301 loss_db: 0.0838 loss: 0.9069 2022/08/30 13:19:55 - mmengine - INFO - Epoch(train) [574][25/63] lr: 3.9002e-03 eta: 14:41:48 time: 0.8500 data_time: 0.0333 memory: 16201 loss_prob: 0.4975 loss_thr: 0.3409 loss_db: 0.0887 loss: 0.9270 2022/08/30 13:20:00 - mmengine - INFO - Epoch(train) [574][30/63] lr: 3.9002e-03 eta: 14:41:30 time: 0.8935 data_time: 0.0326 memory: 16201 loss_prob: 0.5332 loss_thr: 0.3724 loss_db: 0.0939 loss: 0.9995 2022/08/30 13:20:04 - mmengine - INFO - Epoch(train) [574][35/63] lr: 3.9002e-03 eta: 14:41:30 time: 0.9056 data_time: 0.0341 memory: 16201 loss_prob: 0.5107 loss_thr: 0.3757 loss_db: 0.0871 loss: 0.9735 2022/08/30 13:20:08 - mmengine - INFO - Epoch(train) [574][40/63] lr: 3.9002e-03 eta: 14:41:11 time: 0.8732 data_time: 0.0575 memory: 16201 loss_prob: 0.4585 loss_thr: 0.3402 loss_db: 0.0795 loss: 0.8782 2022/08/30 13:20:13 - mmengine - INFO - Epoch(train) [574][45/63] lr: 3.9002e-03 eta: 14:41:11 time: 0.8940 data_time: 0.0499 memory: 16201 loss_prob: 0.4463 loss_thr: 0.3318 loss_db: 0.0789 loss: 0.8570 2022/08/30 13:20:18 - mmengine - INFO - Epoch(train) [574][50/63] lr: 3.9002e-03 eta: 14:40:53 time: 0.9153 data_time: 0.0342 memory: 16201 loss_prob: 0.5072 loss_thr: 0.3697 loss_db: 0.0904 loss: 0.9673 2022/08/30 13:20:22 - mmengine - INFO - Epoch(train) [574][55/63] lr: 3.9002e-03 eta: 14:40:53 time: 0.9157 data_time: 0.0587 memory: 16201 loss_prob: 0.5449 loss_thr: 0.3854 loss_db: 0.0962 loss: 1.0266 2022/08/30 13:20:27 - mmengine - INFO - Epoch(train) [574][60/63] lr: 3.9002e-03 eta: 14:40:35 time: 0.9122 data_time: 0.0620 memory: 16201 loss_prob: 0.5114 loss_thr: 0.3593 loss_db: 0.0912 loss: 0.9618 2022/08/30 13:20:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:20:36 - mmengine - INFO - Epoch(train) [575][5/63] lr: 3.8946e-03 eta: 14:40:35 time: 1.0947 data_time: 0.2641 memory: 16201 loss_prob: 0.5215 loss_thr: 0.3524 loss_db: 0.0879 loss: 0.9618 2022/08/30 13:20:40 - mmengine - INFO - Epoch(train) [575][10/63] lr: 3.8946e-03 eta: 14:40:11 time: 1.1425 data_time: 0.2680 memory: 16201 loss_prob: 0.5166 loss_thr: 0.3533 loss_db: 0.0885 loss: 0.9583 2022/08/30 13:20:45 - mmengine - INFO - Epoch(train) [575][15/63] lr: 3.8946e-03 eta: 14:40:11 time: 0.8824 data_time: 0.0349 memory: 16201 loss_prob: 0.4896 loss_thr: 0.3387 loss_db: 0.0870 loss: 0.9153 2022/08/30 13:20:49 - mmengine - INFO - Epoch(train) [575][20/63] lr: 3.8946e-03 eta: 14:39:53 time: 0.8739 data_time: 0.0341 memory: 16201 loss_prob: 0.5019 loss_thr: 0.3428 loss_db: 0.0880 loss: 0.9328 2022/08/30 13:20:54 - mmengine - INFO - Epoch(train) [575][25/63] lr: 3.8946e-03 eta: 14:39:53 time: 0.8992 data_time: 0.0376 memory: 16201 loss_prob: 0.5270 loss_thr: 0.3594 loss_db: 0.0911 loss: 0.9775 2022/08/30 13:20:58 - mmengine - INFO - Epoch(train) [575][30/63] lr: 3.8946e-03 eta: 14:39:35 time: 0.8854 data_time: 0.0357 memory: 16201 loss_prob: 0.4995 loss_thr: 0.3431 loss_db: 0.0866 loss: 0.9292 2022/08/30 13:21:02 - mmengine - INFO - Epoch(train) [575][35/63] lr: 3.8946e-03 eta: 14:39:35 time: 0.8781 data_time: 0.0532 memory: 16201 loss_prob: 0.4462 loss_thr: 0.3184 loss_db: 0.0790 loss: 0.8435 2022/08/30 13:21:07 - mmengine - INFO - Epoch(train) [575][40/63] lr: 3.8946e-03 eta: 14:39:16 time: 0.8985 data_time: 0.0605 memory: 16201 loss_prob: 0.4608 loss_thr: 0.3265 loss_db: 0.0801 loss: 0.8675 2022/08/30 13:21:11 - mmengine - INFO - Epoch(train) [575][45/63] lr: 3.8946e-03 eta: 14:39:16 time: 0.8925 data_time: 0.0445 memory: 16201 loss_prob: 0.4884 loss_thr: 0.3398 loss_db: 0.0846 loss: 0.9128 2022/08/30 13:21:16 - mmengine - INFO - Epoch(train) [575][50/63] lr: 3.8946e-03 eta: 14:38:58 time: 0.8590 data_time: 0.0331 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3455 loss_db: 0.0865 loss: 0.9215 2022/08/30 13:21:21 - mmengine - INFO - Epoch(train) [575][55/63] lr: 3.8946e-03 eta: 14:38:58 time: 0.9561 data_time: 0.0411 memory: 16201 loss_prob: 0.4969 loss_thr: 0.3540 loss_db: 0.0893 loss: 0.9403 2022/08/30 13:21:25 - mmengine - INFO - Epoch(train) [575][60/63] lr: 3.8946e-03 eta: 14:38:40 time: 0.9493 data_time: 0.0385 memory: 16201 loss_prob: 0.4937 loss_thr: 0.3411 loss_db: 0.0879 loss: 0.9227 2022/08/30 13:21:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:21:33 - mmengine - INFO - Epoch(train) [576][5/63] lr: 3.8889e-03 eta: 14:38:40 time: 0.9844 data_time: 0.1877 memory: 16201 loss_prob: 0.4740 loss_thr: 0.3409 loss_db: 0.0812 loss: 0.8961 2022/08/30 13:21:38 - mmengine - INFO - Epoch(train) [576][10/63] lr: 3.8889e-03 eta: 14:38:15 time: 1.0597 data_time: 0.2093 memory: 16201 loss_prob: 0.5177 loss_thr: 0.3523 loss_db: 0.0890 loss: 0.9591 2022/08/30 13:21:42 - mmengine - INFO - Epoch(train) [576][15/63] lr: 3.8889e-03 eta: 14:38:15 time: 0.8975 data_time: 0.0340 memory: 16201 loss_prob: 0.5562 loss_thr: 0.3737 loss_db: 0.0950 loss: 1.0249 2022/08/30 13:21:47 - mmengine - INFO - Epoch(train) [576][20/63] lr: 3.8889e-03 eta: 14:37:57 time: 0.8940 data_time: 0.0260 memory: 16201 loss_prob: 0.5297 loss_thr: 0.3565 loss_db: 0.0910 loss: 0.9773 2022/08/30 13:21:52 - mmengine - INFO - Epoch(train) [576][25/63] lr: 3.8889e-03 eta: 14:37:57 time: 0.9214 data_time: 0.0613 memory: 16201 loss_prob: 0.4650 loss_thr: 0.3341 loss_db: 0.0806 loss: 0.8797 2022/08/30 13:21:56 - mmengine - INFO - Epoch(train) [576][30/63] lr: 3.8889e-03 eta: 14:37:39 time: 0.9047 data_time: 0.0573 memory: 16201 loss_prob: 0.4738 loss_thr: 0.3394 loss_db: 0.0828 loss: 0.8960 2022/08/30 13:22:01 - mmengine - INFO - Epoch(train) [576][35/63] lr: 3.8889e-03 eta: 14:37:39 time: 0.8953 data_time: 0.0287 memory: 16201 loss_prob: 0.5330 loss_thr: 0.3584 loss_db: 0.0903 loss: 0.9816 2022/08/30 13:22:05 - mmengine - INFO - Epoch(train) [576][40/63] lr: 3.8889e-03 eta: 14:37:21 time: 0.8902 data_time: 0.0290 memory: 16201 loss_prob: 0.5643 loss_thr: 0.3728 loss_db: 0.0957 loss: 1.0328 2022/08/30 13:22:09 - mmengine - INFO - Epoch(train) [576][45/63] lr: 3.8889e-03 eta: 14:37:21 time: 0.8837 data_time: 0.0407 memory: 16201 loss_prob: 0.5332 loss_thr: 0.3464 loss_db: 0.0928 loss: 0.9723 2022/08/30 13:22:14 - mmengine - INFO - Epoch(train) [576][50/63] lr: 3.8889e-03 eta: 14:37:03 time: 0.9436 data_time: 0.0427 memory: 16201 loss_prob: 0.5226 loss_thr: 0.3404 loss_db: 0.0901 loss: 0.9530 2022/08/30 13:22:19 - mmengine - INFO - Epoch(train) [576][55/63] lr: 3.8889e-03 eta: 14:37:03 time: 0.9327 data_time: 0.0459 memory: 16201 loss_prob: 0.5148 loss_thr: 0.3477 loss_db: 0.0910 loss: 0.9535 2022/08/30 13:22:23 - mmengine - INFO - Epoch(train) [576][60/63] lr: 3.8889e-03 eta: 14:36:45 time: 0.8784 data_time: 0.0552 memory: 16201 loss_prob: 0.4812 loss_thr: 0.3403 loss_db: 0.0848 loss: 0.9064 2022/08/30 13:22:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:22:31 - mmengine - INFO - Epoch(train) [577][5/63] lr: 3.8833e-03 eta: 14:36:45 time: 1.0035 data_time: 0.1824 memory: 16201 loss_prob: 0.4557 loss_thr: 0.3180 loss_db: 0.0802 loss: 0.8539 2022/08/30 13:22:36 - mmengine - INFO - Epoch(train) [577][10/63] lr: 3.8833e-03 eta: 14:36:20 time: 1.0626 data_time: 0.1992 memory: 16201 loss_prob: 0.4859 loss_thr: 0.3318 loss_db: 0.0845 loss: 0.9022 2022/08/30 13:22:41 - mmengine - INFO - Epoch(train) [577][15/63] lr: 3.8833e-03 eta: 14:36:20 time: 0.9318 data_time: 0.0365 memory: 16201 loss_prob: 0.5102 loss_thr: 0.3431 loss_db: 0.0893 loss: 0.9426 2022/08/30 13:22:45 - mmengine - INFO - Epoch(train) [577][20/63] lr: 3.8833e-03 eta: 14:36:02 time: 0.8916 data_time: 0.0216 memory: 16201 loss_prob: 0.4688 loss_thr: 0.3334 loss_db: 0.0839 loss: 0.8861 2022/08/30 13:22:49 - mmengine - INFO - Epoch(train) [577][25/63] lr: 3.8833e-03 eta: 14:36:02 time: 0.8217 data_time: 0.0450 memory: 16201 loss_prob: 0.4711 loss_thr: 0.3279 loss_db: 0.0817 loss: 0.8806 2022/08/30 13:22:54 - mmengine - INFO - Epoch(train) [577][30/63] lr: 3.8833e-03 eta: 14:35:43 time: 0.8783 data_time: 0.0415 memory: 16201 loss_prob: 0.4849 loss_thr: 0.3428 loss_db: 0.0817 loss: 0.9094 2022/08/30 13:22:58 - mmengine - INFO - Epoch(train) [577][35/63] lr: 3.8833e-03 eta: 14:35:43 time: 0.8734 data_time: 0.0263 memory: 16201 loss_prob: 0.4790 loss_thr: 0.3558 loss_db: 0.0837 loss: 0.9185 2022/08/30 13:23:02 - mmengine - INFO - Epoch(train) [577][40/63] lr: 3.8833e-03 eta: 14:35:25 time: 0.8337 data_time: 0.0360 memory: 16201 loss_prob: 0.4778 loss_thr: 0.3641 loss_db: 0.0861 loss: 0.9280 2022/08/30 13:23:06 - mmengine - INFO - Epoch(train) [577][45/63] lr: 3.8833e-03 eta: 14:35:25 time: 0.8268 data_time: 0.0328 memory: 16201 loss_prob: 0.4778 loss_thr: 0.3469 loss_db: 0.0803 loss: 0.9050 2022/08/30 13:23:11 - mmengine - INFO - Epoch(train) [577][50/63] lr: 3.8833e-03 eta: 14:35:07 time: 0.9241 data_time: 0.0331 memory: 16201 loss_prob: 0.5217 loss_thr: 0.3422 loss_db: 0.0903 loss: 0.9541 2022/08/30 13:23:16 - mmengine - INFO - Epoch(train) [577][55/63] lr: 3.8833e-03 eta: 14:35:07 time: 0.9736 data_time: 0.0432 memory: 16201 loss_prob: 0.5289 loss_thr: 0.3461 loss_db: 0.0950 loss: 0.9701 2022/08/30 13:23:20 - mmengine - INFO - Epoch(train) [577][60/63] lr: 3.8833e-03 eta: 14:34:49 time: 0.9051 data_time: 0.0393 memory: 16201 loss_prob: 0.5167 loss_thr: 0.3510 loss_db: 0.0885 loss: 0.9562 2022/08/30 13:23:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:23:28 - mmengine - INFO - Epoch(train) [578][5/63] lr: 3.8777e-03 eta: 14:34:49 time: 0.9885 data_time: 0.2070 memory: 16201 loss_prob: 0.4881 loss_thr: 0.3364 loss_db: 0.0860 loss: 0.9104 2022/08/30 13:23:32 - mmengine - INFO - Epoch(train) [578][10/63] lr: 3.8777e-03 eta: 14:34:24 time: 1.0269 data_time: 0.2267 memory: 16201 loss_prob: 0.5908 loss_thr: 0.3907 loss_db: 0.0992 loss: 1.0808 2022/08/30 13:23:36 - mmengine - INFO - Epoch(train) [578][15/63] lr: 3.8777e-03 eta: 14:34:24 time: 0.8150 data_time: 0.0428 memory: 16201 loss_prob: 0.6131 loss_thr: 0.4018 loss_db: 0.1034 loss: 1.1184 2022/08/30 13:23:42 - mmengine - INFO - Epoch(train) [578][20/63] lr: 3.8777e-03 eta: 14:34:06 time: 0.9262 data_time: 0.0787 memory: 16201 loss_prob: 0.5170 loss_thr: 0.3627 loss_db: 0.0893 loss: 0.9690 2022/08/30 13:23:46 - mmengine - INFO - Epoch(train) [578][25/63] lr: 3.8777e-03 eta: 14:34:06 time: 0.9356 data_time: 0.0933 memory: 16201 loss_prob: 0.5279 loss_thr: 0.3555 loss_db: 0.0881 loss: 0.9715 2022/08/30 13:23:50 - mmengine - INFO - Epoch(train) [578][30/63] lr: 3.8777e-03 eta: 14:33:47 time: 0.8539 data_time: 0.0526 memory: 16201 loss_prob: 0.5063 loss_thr: 0.3426 loss_db: 0.0866 loss: 0.9355 2022/08/30 13:23:55 - mmengine - INFO - Epoch(train) [578][35/63] lr: 3.8777e-03 eta: 14:33:47 time: 0.8781 data_time: 0.0434 memory: 16201 loss_prob: 0.4664 loss_thr: 0.3314 loss_db: 0.0833 loss: 0.8810 2022/08/30 13:23:59 - mmengine - INFO - Epoch(train) [578][40/63] lr: 3.8777e-03 eta: 14:33:29 time: 0.9048 data_time: 0.0411 memory: 16201 loss_prob: 0.5084 loss_thr: 0.3371 loss_db: 0.0862 loss: 0.9317 2022/08/30 13:24:04 - mmengine - INFO - Epoch(train) [578][45/63] lr: 3.8777e-03 eta: 14:33:29 time: 0.9018 data_time: 0.0393 memory: 16201 loss_prob: 0.5307 loss_thr: 0.3403 loss_db: 0.0882 loss: 0.9592 2022/08/30 13:24:08 - mmengine - INFO - Epoch(train) [578][50/63] lr: 3.8777e-03 eta: 14:33:11 time: 0.8772 data_time: 0.0276 memory: 16201 loss_prob: 0.5075 loss_thr: 0.3446 loss_db: 0.0865 loss: 0.9387 2022/08/30 13:24:13 - mmengine - INFO - Epoch(train) [578][55/63] lr: 3.8777e-03 eta: 14:33:11 time: 0.9137 data_time: 0.0599 memory: 16201 loss_prob: 0.4734 loss_thr: 0.3411 loss_db: 0.0817 loss: 0.8962 2022/08/30 13:24:17 - mmengine - INFO - Epoch(train) [578][60/63] lr: 3.8777e-03 eta: 14:32:53 time: 0.8941 data_time: 0.0668 memory: 16201 loss_prob: 0.4434 loss_thr: 0.3213 loss_db: 0.0771 loss: 0.8418 2022/08/30 13:24:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:24:26 - mmengine - INFO - Epoch(train) [579][5/63] lr: 3.8721e-03 eta: 14:32:53 time: 1.1189 data_time: 0.2488 memory: 16201 loss_prob: 0.5041 loss_thr: 0.3455 loss_db: 0.0885 loss: 0.9382 2022/08/30 13:24:31 - mmengine - INFO - Epoch(train) [579][10/63] lr: 3.8721e-03 eta: 14:32:28 time: 1.0716 data_time: 0.2477 memory: 16201 loss_prob: 0.4527 loss_thr: 0.3100 loss_db: 0.0802 loss: 0.8429 2022/08/30 13:24:35 - mmengine - INFO - Epoch(train) [579][15/63] lr: 3.8721e-03 eta: 14:32:28 time: 0.8434 data_time: 0.0448 memory: 16201 loss_prob: 0.5500 loss_thr: 0.3418 loss_db: 0.0900 loss: 0.9818 2022/08/30 13:24:40 - mmengine - INFO - Epoch(train) [579][20/63] lr: 3.8721e-03 eta: 14:32:11 time: 0.9402 data_time: 0.0362 memory: 16201 loss_prob: 0.5746 loss_thr: 0.3554 loss_db: 0.0930 loss: 1.0230 2022/08/30 13:24:45 - mmengine - INFO - Epoch(train) [579][25/63] lr: 3.8721e-03 eta: 14:32:11 time: 0.9760 data_time: 0.0481 memory: 16201 loss_prob: 0.5093 loss_thr: 0.3365 loss_db: 0.0886 loss: 0.9344 2022/08/30 13:24:49 - mmengine - INFO - Epoch(train) [579][30/63] lr: 3.8721e-03 eta: 14:31:53 time: 0.9128 data_time: 0.0549 memory: 16201 loss_prob: 0.4907 loss_thr: 0.3210 loss_db: 0.0870 loss: 0.8987 2022/08/30 13:24:53 - mmengine - INFO - Epoch(train) [579][35/63] lr: 3.8721e-03 eta: 14:31:53 time: 0.8806 data_time: 0.0405 memory: 16201 loss_prob: 0.4883 loss_thr: 0.3335 loss_db: 0.0852 loss: 0.9069 2022/08/30 13:24:58 - mmengine - INFO - Epoch(train) [579][40/63] lr: 3.8721e-03 eta: 14:31:35 time: 0.8918 data_time: 0.0369 memory: 16201 loss_prob: 0.5122 loss_thr: 0.3536 loss_db: 0.0878 loss: 0.9536 2022/08/30 13:25:03 - mmengine - INFO - Epoch(train) [579][45/63] lr: 3.8721e-03 eta: 14:31:35 time: 0.9032 data_time: 0.0507 memory: 16201 loss_prob: 0.4850 loss_thr: 0.3396 loss_db: 0.0863 loss: 0.9109 2022/08/30 13:25:07 - mmengine - INFO - Epoch(train) [579][50/63] lr: 3.8721e-03 eta: 14:31:16 time: 0.8764 data_time: 0.0486 memory: 16201 loss_prob: 0.4996 loss_thr: 0.3420 loss_db: 0.0890 loss: 0.9306 2022/08/30 13:25:12 - mmengine - INFO - Epoch(train) [579][55/63] lr: 3.8721e-03 eta: 14:31:16 time: 0.9459 data_time: 0.0512 memory: 16201 loss_prob: 0.5266 loss_thr: 0.3503 loss_db: 0.0908 loss: 0.9676 2022/08/30 13:25:16 - mmengine - INFO - Epoch(train) [579][60/63] lr: 3.8721e-03 eta: 14:30:59 time: 0.9451 data_time: 0.0560 memory: 16201 loss_prob: 0.5380 loss_thr: 0.3611 loss_db: 0.0944 loss: 0.9935 2022/08/30 13:25:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:25:25 - mmengine - INFO - Epoch(train) [580][5/63] lr: 3.8665e-03 eta: 14:30:59 time: 1.0105 data_time: 0.1918 memory: 16201 loss_prob: 0.5296 loss_thr: 0.3579 loss_db: 0.0934 loss: 0.9808 2022/08/30 13:25:29 - mmengine - INFO - Epoch(train) [580][10/63] lr: 3.8665e-03 eta: 14:30:34 time: 1.0504 data_time: 0.2092 memory: 16201 loss_prob: 0.5039 loss_thr: 0.3468 loss_db: 0.0885 loss: 0.9392 2022/08/30 13:25:34 - mmengine - INFO - Epoch(train) [580][15/63] lr: 3.8665e-03 eta: 14:30:34 time: 0.8763 data_time: 0.0382 memory: 16201 loss_prob: 0.5027 loss_thr: 0.3413 loss_db: 0.0864 loss: 0.9303 2022/08/30 13:25:39 - mmengine - INFO - Epoch(train) [580][20/63] lr: 3.8665e-03 eta: 14:30:17 time: 0.9499 data_time: 0.0233 memory: 16201 loss_prob: 0.4957 loss_thr: 0.3408 loss_db: 0.0843 loss: 0.9208 2022/08/30 13:25:44 - mmengine - INFO - Epoch(train) [580][25/63] lr: 3.8665e-03 eta: 14:30:17 time: 1.0098 data_time: 0.0610 memory: 16201 loss_prob: 0.5148 loss_thr: 0.3540 loss_db: 0.0888 loss: 0.9576 2022/08/30 13:25:48 - mmengine - INFO - Epoch(train) [580][30/63] lr: 3.8665e-03 eta: 14:29:59 time: 0.9162 data_time: 0.0649 memory: 16201 loss_prob: 0.5523 loss_thr: 0.3778 loss_db: 0.0977 loss: 1.0278 2022/08/30 13:25:52 - mmengine - INFO - Epoch(train) [580][35/63] lr: 3.8665e-03 eta: 14:29:59 time: 0.8401 data_time: 0.0306 memory: 16201 loss_prob: 0.5023 loss_thr: 0.3611 loss_db: 0.0893 loss: 0.9526 2022/08/30 13:25:56 - mmengine - INFO - Epoch(train) [580][40/63] lr: 3.8665e-03 eta: 14:29:40 time: 0.8458 data_time: 0.0443 memory: 16201 loss_prob: 0.4614 loss_thr: 0.3383 loss_db: 0.0810 loss: 0.8807 2022/08/30 13:26:02 - mmengine - INFO - Epoch(train) [580][45/63] lr: 3.8665e-03 eta: 14:29:40 time: 0.9720 data_time: 0.1004 memory: 16201 loss_prob: 0.4736 loss_thr: 0.3309 loss_db: 0.0828 loss: 0.8873 2022/08/30 13:26:06 - mmengine - INFO - Epoch(train) [580][50/63] lr: 3.8665e-03 eta: 14:29:23 time: 0.9704 data_time: 0.0850 memory: 16201 loss_prob: 0.4456 loss_thr: 0.3217 loss_db: 0.0781 loss: 0.8454 2022/08/30 13:26:11 - mmengine - INFO - Epoch(train) [580][55/63] lr: 3.8665e-03 eta: 14:29:23 time: 0.8917 data_time: 0.0513 memory: 16201 loss_prob: 0.4634 loss_thr: 0.3367 loss_db: 0.0818 loss: 0.8818 2022/08/30 13:26:15 - mmengine - INFO - Epoch(train) [580][60/63] lr: 3.8665e-03 eta: 14:29:05 time: 0.8847 data_time: 0.0497 memory: 16201 loss_prob: 0.4902 loss_thr: 0.3349 loss_db: 0.0851 loss: 0.9102 2022/08/30 13:26:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:26:17 - mmengine - INFO - Saving checkpoint at 580 epochs 2022/08/30 13:26:26 - mmengine - INFO - Epoch(val) [580][5/32] eta: 14:29:05 time: 0.6685 data_time: 0.1168 memory: 16201 2022/08/30 13:26:30 - mmengine - INFO - Epoch(val) [580][10/32] eta: 0:00:16 time: 0.7595 data_time: 0.1508 memory: 15734 2022/08/30 13:26:33 - mmengine - INFO - Epoch(val) [580][15/32] eta: 0:00:16 time: 0.6316 data_time: 0.0571 memory: 15734 2022/08/30 13:26:36 - mmengine - INFO - Epoch(val) [580][20/32] eta: 0:00:07 time: 0.6262 data_time: 0.0684 memory: 15734 2022/08/30 13:26:40 - mmengine - INFO - Epoch(val) [580][25/32] eta: 0:00:07 time: 0.7185 data_time: 0.0702 memory: 15734 2022/08/30 13:26:43 - mmengine - INFO - Epoch(val) [580][30/32] eta: 0:00:01 time: 0.6864 data_time: 0.0386 memory: 15734 2022/08/30 13:26:44 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 13:26:44 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8560, precision: 0.7598, hmean: 0.8051 2022/08/30 13:26:44 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8560, precision: 0.8016, hmean: 0.8279 2022/08/30 13:26:44 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8541, precision: 0.8259, hmean: 0.8398 2022/08/30 13:26:44 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8507, precision: 0.8512, hmean: 0.8510 2022/08/30 13:26:44 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8402, precision: 0.8791, hmean: 0.8592 2022/08/30 13:26:44 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7843, precision: 0.9193, hmean: 0.8465 2022/08/30 13:26:44 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1883, precision: 0.9775, hmean: 0.3157 2022/08/30 13:26:44 - mmengine - INFO - Epoch(val) [580][32/32] icdar/precision: 0.8791 icdar/recall: 0.8402 icdar/hmean: 0.8592 2022/08/30 13:26:50 - mmengine - INFO - Epoch(train) [581][5/63] lr: 3.8609e-03 eta: 0:00:01 time: 1.0258 data_time: 0.2365 memory: 16201 loss_prob: 0.5219 loss_thr: 0.3440 loss_db: 0.0854 loss: 0.9513 2022/08/30 13:26:55 - mmengine - INFO - Epoch(train) [581][10/63] lr: 3.8609e-03 eta: 14:28:40 time: 1.0813 data_time: 0.2399 memory: 16201 loss_prob: 0.4902 loss_thr: 0.3510 loss_db: 0.0842 loss: 0.9255 2022/08/30 13:27:01 - mmengine - INFO - Epoch(train) [581][15/63] lr: 3.8609e-03 eta: 14:28:40 time: 1.0050 data_time: 0.0515 memory: 16201 loss_prob: 0.4900 loss_thr: 0.3513 loss_db: 0.0861 loss: 0.9273 2022/08/30 13:27:05 - mmengine - INFO - Epoch(train) [581][20/63] lr: 3.8609e-03 eta: 14:28:24 time: 1.0080 data_time: 0.0507 memory: 16201 loss_prob: 0.5277 loss_thr: 0.3630 loss_db: 0.0914 loss: 0.9821 2022/08/30 13:27:09 - mmengine - INFO - Epoch(train) [581][25/63] lr: 3.8609e-03 eta: 14:28:24 time: 0.8754 data_time: 0.0481 memory: 16201 loss_prob: 0.5411 loss_thr: 0.3672 loss_db: 0.0926 loss: 1.0009 2022/08/30 13:27:13 - mmengine - INFO - Epoch(train) [581][30/63] lr: 3.8609e-03 eta: 14:28:05 time: 0.8594 data_time: 0.0412 memory: 16201 loss_prob: 0.5212 loss_thr: 0.3563 loss_db: 0.0920 loss: 0.9695 2022/08/30 13:27:18 - mmengine - INFO - Epoch(train) [581][35/63] lr: 3.8609e-03 eta: 14:28:05 time: 0.8774 data_time: 0.0252 memory: 16201 loss_prob: 0.5005 loss_thr: 0.3571 loss_db: 0.0869 loss: 0.9445 2022/08/30 13:27:22 - mmengine - INFO - Epoch(train) [581][40/63] lr: 3.8609e-03 eta: 14:27:47 time: 0.8969 data_time: 0.0470 memory: 16201 loss_prob: 0.4764 loss_thr: 0.3345 loss_db: 0.0838 loss: 0.8946 2022/08/30 13:27:26 - mmengine - INFO - Epoch(train) [581][45/63] lr: 3.8609e-03 eta: 14:27:47 time: 0.8320 data_time: 0.0464 memory: 16201 loss_prob: 0.5514 loss_thr: 0.3511 loss_db: 0.0958 loss: 0.9983 2022/08/30 13:27:30 - mmengine - INFO - Epoch(train) [581][50/63] lr: 3.8609e-03 eta: 14:27:28 time: 0.8084 data_time: 0.0301 memory: 16201 loss_prob: 0.5723 loss_thr: 0.3784 loss_db: 0.0987 loss: 1.0494 2022/08/30 13:27:34 - mmengine - INFO - Epoch(train) [581][55/63] lr: 3.8609e-03 eta: 14:27:28 time: 0.7963 data_time: 0.0274 memory: 16201 loss_prob: 0.5060 loss_thr: 0.3555 loss_db: 0.0886 loss: 0.9501 2022/08/30 13:27:39 - mmengine - INFO - Epoch(train) [581][60/63] lr: 3.8609e-03 eta: 14:27:09 time: 0.8322 data_time: 0.0239 memory: 16201 loss_prob: 0.4973 loss_thr: 0.3441 loss_db: 0.0851 loss: 0.9266 2022/08/30 13:27:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:27:46 - mmengine - INFO - Epoch(train) [582][5/63] lr: 3.8553e-03 eta: 14:27:09 time: 0.9275 data_time: 0.1642 memory: 16201 loss_prob: 0.4567 loss_thr: 0.3297 loss_db: 0.0802 loss: 0.8666 2022/08/30 13:27:51 - mmengine - INFO - Epoch(train) [582][10/63] lr: 3.8553e-03 eta: 14:26:44 time: 0.9913 data_time: 0.1905 memory: 16201 loss_prob: 0.5261 loss_thr: 0.3636 loss_db: 0.0919 loss: 0.9817 2022/08/30 13:27:55 - mmengine - INFO - Epoch(train) [582][15/63] lr: 3.8553e-03 eta: 14:26:44 time: 0.8984 data_time: 0.0616 memory: 16201 loss_prob: 0.5203 loss_thr: 0.3623 loss_db: 0.0901 loss: 0.9727 2022/08/30 13:28:00 - mmengine - INFO - Epoch(train) [582][20/63] lr: 3.8553e-03 eta: 14:26:26 time: 0.8805 data_time: 0.0419 memory: 16201 loss_prob: 0.4830 loss_thr: 0.3405 loss_db: 0.0854 loss: 0.9089 2022/08/30 13:28:04 - mmengine - INFO - Epoch(train) [582][25/63] lr: 3.8553e-03 eta: 14:26:26 time: 0.8765 data_time: 0.0582 memory: 16201 loss_prob: 0.4630 loss_thr: 0.3338 loss_db: 0.0831 loss: 0.8799 2022/08/30 13:28:08 - mmengine - INFO - Epoch(train) [582][30/63] lr: 3.8553e-03 eta: 14:26:08 time: 0.8764 data_time: 0.0548 memory: 16201 loss_prob: 0.4456 loss_thr: 0.3295 loss_db: 0.0794 loss: 0.8544 2022/08/30 13:28:13 - mmengine - INFO - Epoch(train) [582][35/63] lr: 3.8553e-03 eta: 14:26:08 time: 0.8667 data_time: 0.0329 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3410 loss_db: 0.0829 loss: 0.8990 2022/08/30 13:28:17 - mmengine - INFO - Epoch(train) [582][40/63] lr: 3.8553e-03 eta: 14:25:50 time: 0.8768 data_time: 0.0343 memory: 16201 loss_prob: 0.4732 loss_thr: 0.3406 loss_db: 0.0823 loss: 0.8961 2022/08/30 13:28:22 - mmengine - INFO - Epoch(train) [582][45/63] lr: 3.8553e-03 eta: 14:25:50 time: 0.9063 data_time: 0.0349 memory: 16201 loss_prob: 0.4425 loss_thr: 0.3188 loss_db: 0.0782 loss: 0.8395 2022/08/30 13:28:26 - mmengine - INFO - Epoch(train) [582][50/63] lr: 3.8553e-03 eta: 14:25:32 time: 0.9016 data_time: 0.0328 memory: 16201 loss_prob: 0.4224 loss_thr: 0.3101 loss_db: 0.0739 loss: 0.8064 2022/08/30 13:28:31 - mmengine - INFO - Epoch(train) [582][55/63] lr: 3.8553e-03 eta: 14:25:32 time: 0.9135 data_time: 0.0475 memory: 16201 loss_prob: 0.4825 loss_thr: 0.3441 loss_db: 0.0850 loss: 0.9117 2022/08/30 13:28:35 - mmengine - INFO - Epoch(train) [582][60/63] lr: 3.8553e-03 eta: 14:25:14 time: 0.9062 data_time: 0.0567 memory: 16201 loss_prob: 0.5415 loss_thr: 0.3587 loss_db: 0.0945 loss: 0.9947 2022/08/30 13:28:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:28:43 - mmengine - INFO - Epoch(train) [583][5/63] lr: 3.8497e-03 eta: 14:25:14 time: 0.9747 data_time: 0.1837 memory: 16201 loss_prob: 0.4954 loss_thr: 0.3326 loss_db: 0.0846 loss: 0.9126 2022/08/30 13:28:48 - mmengine - INFO - Epoch(train) [583][10/63] lr: 3.8497e-03 eta: 14:24:49 time: 1.0071 data_time: 0.1881 memory: 16201 loss_prob: 0.5123 loss_thr: 0.3434 loss_db: 0.0904 loss: 0.9461 2022/08/30 13:28:52 - mmengine - INFO - Epoch(train) [583][15/63] lr: 3.8497e-03 eta: 14:24:49 time: 0.8498 data_time: 0.0354 memory: 16201 loss_prob: 0.5180 loss_thr: 0.3599 loss_db: 0.0871 loss: 0.9650 2022/08/30 13:28:56 - mmengine - INFO - Epoch(train) [583][20/63] lr: 3.8497e-03 eta: 14:24:30 time: 0.8605 data_time: 0.0283 memory: 16201 loss_prob: 0.5162 loss_thr: 0.3578 loss_db: 0.0876 loss: 0.9616 2022/08/30 13:29:01 - mmengine - INFO - Epoch(train) [583][25/63] lr: 3.8497e-03 eta: 14:24:30 time: 0.8982 data_time: 0.0537 memory: 16201 loss_prob: 0.4778 loss_thr: 0.3310 loss_db: 0.0867 loss: 0.8955 2022/08/30 13:29:05 - mmengine - INFO - Epoch(train) [583][30/63] lr: 3.8497e-03 eta: 14:24:13 time: 0.9019 data_time: 0.0544 memory: 16201 loss_prob: 0.5070 loss_thr: 0.3504 loss_db: 0.0880 loss: 0.9453 2022/08/30 13:29:10 - mmengine - INFO - Epoch(train) [583][35/63] lr: 3.8497e-03 eta: 14:24:13 time: 0.8645 data_time: 0.0365 memory: 16201 loss_prob: 0.5765 loss_thr: 0.3756 loss_db: 0.0997 loss: 1.0518 2022/08/30 13:29:14 - mmengine - INFO - Epoch(train) [583][40/63] lr: 3.8497e-03 eta: 14:23:54 time: 0.8490 data_time: 0.0501 memory: 16201 loss_prob: 0.5637 loss_thr: 0.3650 loss_db: 0.1006 loss: 1.0293 2022/08/30 13:29:18 - mmengine - INFO - Epoch(train) [583][45/63] lr: 3.8497e-03 eta: 14:23:54 time: 0.8734 data_time: 0.0473 memory: 16201 loss_prob: 0.5504 loss_thr: 0.3690 loss_db: 0.0954 loss: 1.0149 2022/08/30 13:29:22 - mmengine - INFO - Epoch(train) [583][50/63] lr: 3.8497e-03 eta: 14:23:36 time: 0.8615 data_time: 0.0351 memory: 16201 loss_prob: 0.5002 loss_thr: 0.3524 loss_db: 0.0867 loss: 0.9393 2022/08/30 13:29:27 - mmengine - INFO - Epoch(train) [583][55/63] lr: 3.8497e-03 eta: 14:23:36 time: 0.8511 data_time: 0.0329 memory: 16201 loss_prob: 0.4700 loss_thr: 0.3450 loss_db: 0.0826 loss: 0.8976 2022/08/30 13:29:32 - mmengine - INFO - Epoch(train) [583][60/63] lr: 3.8497e-03 eta: 14:23:18 time: 0.8653 data_time: 0.0385 memory: 16201 loss_prob: 0.4794 loss_thr: 0.3485 loss_db: 0.0830 loss: 0.9109 2022/08/30 13:29:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:29:46 - mmengine - INFO - Epoch(train) [584][5/63] lr: 3.8440e-03 eta: 14:23:18 time: 1.6646 data_time: 0.5935 memory: 16201 loss_prob: 0.4672 loss_thr: 0.3313 loss_db: 0.0810 loss: 0.8795 2022/08/30 13:29:51 - mmengine - INFO - Epoch(train) [584][10/63] lr: 3.8440e-03 eta: 14:22:57 time: 1.4747 data_time: 0.5204 memory: 16201 loss_prob: 0.4649 loss_thr: 0.3227 loss_db: 0.0818 loss: 0.8694 2022/08/30 13:29:55 - mmengine - INFO - Epoch(train) [584][15/63] lr: 3.8440e-03 eta: 14:22:57 time: 0.8594 data_time: 0.0373 memory: 16201 loss_prob: 0.4896 loss_thr: 0.3327 loss_db: 0.0864 loss: 0.9088 2022/08/30 13:29:59 - mmengine - INFO - Epoch(train) [584][20/63] lr: 3.8440e-03 eta: 14:22:39 time: 0.8792 data_time: 0.0306 memory: 16201 loss_prob: 0.4922 loss_thr: 0.3423 loss_db: 0.0844 loss: 0.9189 2022/08/30 13:30:04 - mmengine - INFO - Epoch(train) [584][25/63] lr: 3.8440e-03 eta: 14:22:39 time: 0.8784 data_time: 0.0436 memory: 16201 loss_prob: 0.5096 loss_thr: 0.3499 loss_db: 0.0876 loss: 0.9472 2022/08/30 13:30:08 - mmengine - INFO - Epoch(train) [584][30/63] lr: 3.8440e-03 eta: 14:22:21 time: 0.8392 data_time: 0.0275 memory: 16201 loss_prob: 0.4815 loss_thr: 0.3403 loss_db: 0.0846 loss: 0.9063 2022/08/30 13:30:12 - mmengine - INFO - Epoch(train) [584][35/63] lr: 3.8440e-03 eta: 14:22:21 time: 0.8789 data_time: 0.0370 memory: 16201 loss_prob: 0.4589 loss_thr: 0.3315 loss_db: 0.0814 loss: 0.8718 2022/08/30 13:30:17 - mmengine - INFO - Epoch(train) [584][40/63] lr: 3.8440e-03 eta: 14:22:03 time: 0.8867 data_time: 0.0646 memory: 16201 loss_prob: 0.5054 loss_thr: 0.3498 loss_db: 0.0885 loss: 0.9437 2022/08/30 13:30:21 - mmengine - INFO - Epoch(train) [584][45/63] lr: 3.8440e-03 eta: 14:22:03 time: 0.9020 data_time: 0.0653 memory: 16201 loss_prob: 0.6288 loss_thr: 0.3938 loss_db: 0.1091 loss: 1.1317 2022/08/30 13:30:26 - mmengine - INFO - Epoch(train) [584][50/63] lr: 3.8440e-03 eta: 14:21:45 time: 0.8995 data_time: 0.0497 memory: 16201 loss_prob: 0.6038 loss_thr: 0.3687 loss_db: 0.1068 loss: 1.0794 2022/08/30 13:30:30 - mmengine - INFO - Epoch(train) [584][55/63] lr: 3.8440e-03 eta: 14:21:45 time: 0.8649 data_time: 0.0476 memory: 16201 loss_prob: 0.5356 loss_thr: 0.3581 loss_db: 0.0929 loss: 0.9866 2022/08/30 13:30:35 - mmengine - INFO - Epoch(train) [584][60/63] lr: 3.8440e-03 eta: 14:21:27 time: 0.8903 data_time: 0.0548 memory: 16201 loss_prob: 0.5287 loss_thr: 0.3641 loss_db: 0.0925 loss: 0.9853 2022/08/30 13:30:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:30:43 - mmengine - INFO - Epoch(train) [585][5/63] lr: 3.8384e-03 eta: 14:21:27 time: 0.9891 data_time: 0.2006 memory: 16201 loss_prob: 0.5887 loss_thr: 0.3749 loss_db: 0.0976 loss: 1.0612 2022/08/30 13:30:47 - mmengine - INFO - Epoch(train) [585][10/63] lr: 3.8384e-03 eta: 14:21:02 time: 1.0300 data_time: 0.2109 memory: 16201 loss_prob: 0.5870 loss_thr: 0.3774 loss_db: 0.0996 loss: 1.0639 2022/08/30 13:30:52 - mmengine - INFO - Epoch(train) [585][15/63] lr: 3.8384e-03 eta: 14:21:02 time: 0.8900 data_time: 0.0372 memory: 16201 loss_prob: 0.5617 loss_thr: 0.3429 loss_db: 0.0996 loss: 1.0042 2022/08/30 13:30:56 - mmengine - INFO - Epoch(train) [585][20/63] lr: 3.8384e-03 eta: 14:20:44 time: 0.8782 data_time: 0.0342 memory: 16201 loss_prob: 0.5658 loss_thr: 0.3558 loss_db: 0.0983 loss: 1.0199 2022/08/30 13:31:01 - mmengine - INFO - Epoch(train) [585][25/63] lr: 3.8384e-03 eta: 14:20:44 time: 0.8874 data_time: 0.0456 memory: 16201 loss_prob: 0.5364 loss_thr: 0.3567 loss_db: 0.0907 loss: 0.9838 2022/08/30 13:31:05 - mmengine - INFO - Epoch(train) [585][30/63] lr: 3.8384e-03 eta: 14:20:26 time: 0.8969 data_time: 0.0545 memory: 16201 loss_prob: 0.6199 loss_thr: 0.3486 loss_db: 0.0957 loss: 1.0641 2022/08/30 13:31:09 - mmengine - INFO - Epoch(train) [585][35/63] lr: 3.8384e-03 eta: 14:20:26 time: 0.8570 data_time: 0.0440 memory: 16201 loss_prob: 0.6392 loss_thr: 0.3517 loss_db: 0.1003 loss: 1.0911 2022/08/30 13:31:14 - mmengine - INFO - Epoch(train) [585][40/63] lr: 3.8384e-03 eta: 14:20:08 time: 0.8668 data_time: 0.0376 memory: 16201 loss_prob: 0.5358 loss_thr: 0.3518 loss_db: 0.0910 loss: 0.9786 2022/08/30 13:31:18 - mmengine - INFO - Epoch(train) [585][45/63] lr: 3.8384e-03 eta: 14:20:08 time: 0.8647 data_time: 0.0358 memory: 16201 loss_prob: 0.5646 loss_thr: 0.3543 loss_db: 0.1000 loss: 1.0189 2022/08/30 13:31:23 - mmengine - INFO - Epoch(train) [585][50/63] lr: 3.8384e-03 eta: 14:19:50 time: 0.9133 data_time: 0.0362 memory: 16201 loss_prob: 0.6032 loss_thr: 0.3592 loss_db: 0.1055 loss: 1.0679 2022/08/30 13:31:27 - mmengine - INFO - Epoch(train) [585][55/63] lr: 3.8384e-03 eta: 14:19:50 time: 0.9291 data_time: 0.0540 memory: 16201 loss_prob: 0.5647 loss_thr: 0.3663 loss_db: 0.0950 loss: 1.0260 2022/08/30 13:31:31 - mmengine - INFO - Epoch(train) [585][60/63] lr: 3.8384e-03 eta: 14:19:32 time: 0.8568 data_time: 0.0599 memory: 16201 loss_prob: 0.5410 loss_thr: 0.3688 loss_db: 0.0941 loss: 1.0039 2022/08/30 13:31:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:31:39 - mmengine - INFO - Epoch(train) [586][5/63] lr: 3.8328e-03 eta: 14:19:32 time: 0.9050 data_time: 0.1606 memory: 16201 loss_prob: 0.5264 loss_thr: 0.3515 loss_db: 0.0903 loss: 0.9682 2022/08/30 13:31:43 - mmengine - INFO - Epoch(train) [586][10/63] lr: 3.8328e-03 eta: 14:19:07 time: 0.9459 data_time: 0.1791 memory: 16201 loss_prob: 0.5138 loss_thr: 0.3612 loss_db: 0.0854 loss: 0.9604 2022/08/30 13:31:47 - mmengine - INFO - Epoch(train) [586][15/63] lr: 3.8328e-03 eta: 14:19:07 time: 0.8031 data_time: 0.0377 memory: 16201 loss_prob: 0.4928 loss_thr: 0.3583 loss_db: 0.0870 loss: 0.9380 2022/08/30 13:31:51 - mmengine - INFO - Epoch(train) [586][20/63] lr: 3.8328e-03 eta: 14:18:47 time: 0.7874 data_time: 0.0166 memory: 16201 loss_prob: 0.5183 loss_thr: 0.3612 loss_db: 0.0928 loss: 0.9723 2022/08/30 13:31:55 - mmengine - INFO - Epoch(train) [586][25/63] lr: 3.8328e-03 eta: 14:18:47 time: 0.8158 data_time: 0.0389 memory: 16201 loss_prob: 0.4997 loss_thr: 0.3345 loss_db: 0.0873 loss: 0.9215 2022/08/30 13:31:59 - mmengine - INFO - Epoch(train) [586][30/63] lr: 3.8328e-03 eta: 14:18:29 time: 0.8405 data_time: 0.0328 memory: 16201 loss_prob: 0.5176 loss_thr: 0.3428 loss_db: 0.0871 loss: 0.9474 2022/08/30 13:32:03 - mmengine - INFO - Epoch(train) [586][35/63] lr: 3.8328e-03 eta: 14:18:29 time: 0.8603 data_time: 0.0281 memory: 16201 loss_prob: 0.5854 loss_thr: 0.3868 loss_db: 0.1001 loss: 1.0723 2022/08/30 13:32:08 - mmengine - INFO - Epoch(train) [586][40/63] lr: 3.8328e-03 eta: 14:18:11 time: 0.9018 data_time: 0.0812 memory: 16201 loss_prob: 0.5410 loss_thr: 0.3657 loss_db: 0.0956 loss: 1.0023 2022/08/30 13:32:12 - mmengine - INFO - Epoch(train) [586][45/63] lr: 3.8328e-03 eta: 14:18:11 time: 0.8830 data_time: 0.0696 memory: 16201 loss_prob: 0.4833 loss_thr: 0.3472 loss_db: 0.0846 loss: 0.9152 2022/08/30 13:32:16 - mmengine - INFO - Epoch(train) [586][50/63] lr: 3.8328e-03 eta: 14:17:53 time: 0.8290 data_time: 0.0291 memory: 16201 loss_prob: 0.4783 loss_thr: 0.3323 loss_db: 0.0823 loss: 0.8929 2022/08/30 13:32:21 - mmengine - INFO - Epoch(train) [586][55/63] lr: 3.8328e-03 eta: 14:17:53 time: 0.8466 data_time: 0.0338 memory: 16201 loss_prob: 0.4823 loss_thr: 0.3264 loss_db: 0.0842 loss: 0.8929 2022/08/30 13:32:25 - mmengine - INFO - Epoch(train) [586][60/63] lr: 3.8328e-03 eta: 14:17:34 time: 0.8618 data_time: 0.0368 memory: 16201 loss_prob: 0.4544 loss_thr: 0.3250 loss_db: 0.0793 loss: 0.8587 2022/08/30 13:32:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:32:33 - mmengine - INFO - Epoch(train) [587][5/63] lr: 3.8272e-03 eta: 14:17:34 time: 0.9602 data_time: 0.1751 memory: 16201 loss_prob: 0.4968 loss_thr: 0.3510 loss_db: 0.0879 loss: 0.9357 2022/08/30 13:32:37 - mmengine - INFO - Epoch(train) [587][10/63] lr: 3.8272e-03 eta: 14:17:10 time: 1.0264 data_time: 0.1934 memory: 16201 loss_prob: 0.4595 loss_thr: 0.3341 loss_db: 0.0847 loss: 0.8783 2022/08/30 13:32:42 - mmengine - INFO - Epoch(train) [587][15/63] lr: 3.8272e-03 eta: 14:17:10 time: 0.9051 data_time: 0.0358 memory: 16201 loss_prob: 0.4882 loss_thr: 0.3392 loss_db: 0.0834 loss: 0.9108 2022/08/30 13:32:46 - mmengine - INFO - Epoch(train) [587][20/63] lr: 3.8272e-03 eta: 14:16:52 time: 0.9039 data_time: 0.0306 memory: 16201 loss_prob: 0.5130 loss_thr: 0.3653 loss_db: 0.0858 loss: 0.9641 2022/08/30 13:32:51 - mmengine - INFO - Epoch(train) [587][25/63] lr: 3.8272e-03 eta: 14:16:52 time: 0.8703 data_time: 0.0520 memory: 16201 loss_prob: 0.5014 loss_thr: 0.3571 loss_db: 0.0873 loss: 0.9457 2022/08/30 13:32:55 - mmengine - INFO - Epoch(train) [587][30/63] lr: 3.8272e-03 eta: 14:16:34 time: 0.8442 data_time: 0.0406 memory: 16201 loss_prob: 0.4821 loss_thr: 0.3368 loss_db: 0.0829 loss: 0.9018 2022/08/30 13:33:00 - mmengine - INFO - Epoch(train) [587][35/63] lr: 3.8272e-03 eta: 14:16:34 time: 0.8848 data_time: 0.0278 memory: 16201 loss_prob: 0.5196 loss_thr: 0.3504 loss_db: 0.0890 loss: 0.9591 2022/08/30 13:33:04 - mmengine - INFO - Epoch(train) [587][40/63] lr: 3.8272e-03 eta: 14:16:16 time: 0.9078 data_time: 0.0345 memory: 16201 loss_prob: 0.5173 loss_thr: 0.3430 loss_db: 0.0894 loss: 0.9497 2022/08/30 13:33:08 - mmengine - INFO - Epoch(train) [587][45/63] lr: 3.8272e-03 eta: 14:16:16 time: 0.8430 data_time: 0.0238 memory: 16201 loss_prob: 0.5064 loss_thr: 0.3493 loss_db: 0.0883 loss: 0.9440 2022/08/30 13:33:12 - mmengine - INFO - Epoch(train) [587][50/63] lr: 3.8272e-03 eta: 14:15:58 time: 0.8566 data_time: 0.0315 memory: 16201 loss_prob: 0.5406 loss_thr: 0.3580 loss_db: 0.0933 loss: 0.9920 2022/08/30 13:33:17 - mmengine - INFO - Epoch(train) [587][55/63] lr: 3.8272e-03 eta: 14:15:58 time: 0.8634 data_time: 0.0568 memory: 16201 loss_prob: 0.5201 loss_thr: 0.3325 loss_db: 0.0885 loss: 0.9411 2022/08/30 13:33:21 - mmengine - INFO - Epoch(train) [587][60/63] lr: 3.8272e-03 eta: 14:15:40 time: 0.8765 data_time: 0.0541 memory: 16201 loss_prob: 0.5112 loss_thr: 0.3507 loss_db: 0.0884 loss: 0.9504 2022/08/30 13:33:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:33:30 - mmengine - INFO - Epoch(train) [588][5/63] lr: 3.8216e-03 eta: 14:15:40 time: 1.0360 data_time: 0.2404 memory: 16201 loss_prob: 0.4979 loss_thr: 0.3681 loss_db: 0.0884 loss: 0.9544 2022/08/30 13:33:34 - mmengine - INFO - Epoch(train) [588][10/63] lr: 3.8216e-03 eta: 14:15:16 time: 1.0906 data_time: 0.2563 memory: 16201 loss_prob: 0.4992 loss_thr: 0.3589 loss_db: 0.0857 loss: 0.9439 2022/08/30 13:33:38 - mmengine - INFO - Epoch(train) [588][15/63] lr: 3.8216e-03 eta: 14:15:16 time: 0.8549 data_time: 0.0376 memory: 16201 loss_prob: 0.4802 loss_thr: 0.3446 loss_db: 0.0837 loss: 0.9085 2022/08/30 13:33:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:33:43 - mmengine - INFO - Epoch(train) [588][20/63] lr: 3.8216e-03 eta: 14:14:57 time: 0.8315 data_time: 0.0303 memory: 16201 loss_prob: 0.4748 loss_thr: 0.3552 loss_db: 0.0844 loss: 0.9143 2022/08/30 13:33:47 - mmengine - INFO - Epoch(train) [588][25/63] lr: 3.8216e-03 eta: 14:14:57 time: 0.8616 data_time: 0.0462 memory: 16201 loss_prob: 0.5108 loss_thr: 0.3612 loss_db: 0.0864 loss: 0.9585 2022/08/30 13:33:52 - mmengine - INFO - Epoch(train) [588][30/63] lr: 3.8216e-03 eta: 14:14:40 time: 0.9410 data_time: 0.0609 memory: 16201 loss_prob: 0.5232 loss_thr: 0.3530 loss_db: 0.0883 loss: 0.9645 2022/08/30 13:33:56 - mmengine - INFO - Epoch(train) [588][35/63] lr: 3.8216e-03 eta: 14:14:40 time: 0.9061 data_time: 0.0459 memory: 16201 loss_prob: 0.5226 loss_thr: 0.3605 loss_db: 0.0905 loss: 0.9736 2022/08/30 13:34:00 - mmengine - INFO - Epoch(train) [588][40/63] lr: 3.8216e-03 eta: 14:14:21 time: 0.8128 data_time: 0.0247 memory: 16201 loss_prob: 0.5362 loss_thr: 0.3615 loss_db: 0.0934 loss: 0.9912 2022/08/30 13:34:04 - mmengine - INFO - Epoch(train) [588][45/63] lr: 3.8216e-03 eta: 14:14:21 time: 0.8160 data_time: 0.0310 memory: 16201 loss_prob: 0.5499 loss_thr: 0.3629 loss_db: 0.0965 loss: 1.0094 2022/08/30 13:34:09 - mmengine - INFO - Epoch(train) [588][50/63] lr: 3.8216e-03 eta: 14:14:04 time: 0.9255 data_time: 0.0374 memory: 16201 loss_prob: 0.5676 loss_thr: 0.3728 loss_db: 0.0981 loss: 1.0386 2022/08/30 13:34:14 - mmengine - INFO - Epoch(train) [588][55/63] lr: 3.8216e-03 eta: 14:14:04 time: 0.9581 data_time: 0.0524 memory: 16201 loss_prob: 0.5202 loss_thr: 0.3503 loss_db: 0.0911 loss: 0.9615 2022/08/30 13:34:18 - mmengine - INFO - Epoch(train) [588][60/63] lr: 3.8216e-03 eta: 14:13:46 time: 0.8799 data_time: 0.0472 memory: 16201 loss_prob: 0.4759 loss_thr: 0.3355 loss_db: 0.0854 loss: 0.8969 2022/08/30 13:34:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:34:27 - mmengine - INFO - Epoch(train) [589][5/63] lr: 3.8160e-03 eta: 14:13:46 time: 1.0175 data_time: 0.2059 memory: 16201 loss_prob: 0.4801 loss_thr: 0.3378 loss_db: 0.0821 loss: 0.9000 2022/08/30 13:34:31 - mmengine - INFO - Epoch(train) [589][10/63] lr: 3.8160e-03 eta: 14:13:21 time: 1.0334 data_time: 0.2088 memory: 16201 loss_prob: 0.4551 loss_thr: 0.3187 loss_db: 0.0805 loss: 0.8543 2022/08/30 13:34:35 - mmengine - INFO - Epoch(train) [589][15/63] lr: 3.8160e-03 eta: 14:13:21 time: 0.8461 data_time: 0.0450 memory: 16201 loss_prob: 0.4728 loss_thr: 0.3402 loss_db: 0.0845 loss: 0.8975 2022/08/30 13:34:39 - mmengine - INFO - Epoch(train) [589][20/63] lr: 3.8160e-03 eta: 14:13:03 time: 0.8243 data_time: 0.0379 memory: 16201 loss_prob: 0.5093 loss_thr: 0.3580 loss_db: 0.0886 loss: 0.9559 2022/08/30 13:34:43 - mmengine - INFO - Epoch(train) [589][25/63] lr: 3.8160e-03 eta: 14:13:03 time: 0.8220 data_time: 0.0303 memory: 16201 loss_prob: 0.5646 loss_thr: 0.3623 loss_db: 0.0967 loss: 1.0236 2022/08/30 13:34:48 - mmengine - INFO - Epoch(train) [589][30/63] lr: 3.8160e-03 eta: 14:12:45 time: 0.8582 data_time: 0.0293 memory: 16201 loss_prob: 0.5240 loss_thr: 0.3464 loss_db: 0.0910 loss: 0.9614 2022/08/30 13:34:52 - mmengine - INFO - Epoch(train) [589][35/63] lr: 3.8160e-03 eta: 14:12:45 time: 0.8560 data_time: 0.0357 memory: 16201 loss_prob: 0.4903 loss_thr: 0.3567 loss_db: 0.0881 loss: 0.9351 2022/08/30 13:34:56 - mmengine - INFO - Epoch(train) [589][40/63] lr: 3.8160e-03 eta: 14:12:26 time: 0.8253 data_time: 0.0345 memory: 16201 loss_prob: 0.6025 loss_thr: 0.3697 loss_db: 0.1046 loss: 1.0768 2022/08/30 13:35:01 - mmengine - INFO - Epoch(train) [589][45/63] lr: 3.8160e-03 eta: 14:12:26 time: 0.8958 data_time: 0.0328 memory: 16201 loss_prob: 0.6178 loss_thr: 0.3693 loss_db: 0.1032 loss: 1.0903 2022/08/30 13:35:05 - mmengine - INFO - Epoch(train) [589][50/63] lr: 3.8160e-03 eta: 14:12:08 time: 0.9033 data_time: 0.0294 memory: 16201 loss_prob: 0.5225 loss_thr: 0.3541 loss_db: 0.0916 loss: 0.9683 2022/08/30 13:35:09 - mmengine - INFO - Epoch(train) [589][55/63] lr: 3.8160e-03 eta: 14:12:08 time: 0.8364 data_time: 0.0387 memory: 16201 loss_prob: 0.5048 loss_thr: 0.3388 loss_db: 0.0908 loss: 0.9344 2022/08/30 13:35:13 - mmengine - INFO - Epoch(train) [589][60/63] lr: 3.8160e-03 eta: 14:11:50 time: 0.8542 data_time: 0.0425 memory: 16201 loss_prob: 0.7253 loss_thr: 0.3705 loss_db: 0.1030 loss: 1.1988 2022/08/30 13:35:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:35:22 - mmengine - INFO - Epoch(train) [590][5/63] lr: 3.8103e-03 eta: 14:11:50 time: 0.9829 data_time: 0.2053 memory: 16201 loss_prob: 0.7866 loss_thr: 0.3688 loss_db: 0.1072 loss: 1.2626 2022/08/30 13:35:26 - mmengine - INFO - Epoch(train) [590][10/63] lr: 3.8103e-03 eta: 14:11:26 time: 1.0453 data_time: 0.2147 memory: 16201 loss_prob: 0.6015 loss_thr: 0.3723 loss_db: 0.0988 loss: 1.0727 2022/08/30 13:35:30 - mmengine - INFO - Epoch(train) [590][15/63] lr: 3.8103e-03 eta: 14:11:26 time: 0.8330 data_time: 0.0287 memory: 16201 loss_prob: 0.5474 loss_thr: 0.3793 loss_db: 0.0953 loss: 1.0221 2022/08/30 13:35:34 - mmengine - INFO - Epoch(train) [590][20/63] lr: 3.8103e-03 eta: 14:11:07 time: 0.7961 data_time: 0.0244 memory: 16201 loss_prob: 0.5294 loss_thr: 0.3743 loss_db: 0.0913 loss: 0.9950 2022/08/30 13:35:38 - mmengine - INFO - Epoch(train) [590][25/63] lr: 3.8103e-03 eta: 14:11:07 time: 0.7996 data_time: 0.0318 memory: 16201 loss_prob: 0.4711 loss_thr: 0.3418 loss_db: 0.0836 loss: 0.8965 2022/08/30 13:35:43 - mmengine - INFO - Epoch(train) [590][30/63] lr: 3.8103e-03 eta: 14:10:49 time: 0.8661 data_time: 0.0319 memory: 16201 loss_prob: 0.4783 loss_thr: 0.3477 loss_db: 0.0846 loss: 0.9106 2022/08/30 13:35:47 - mmengine - INFO - Epoch(train) [590][35/63] lr: 3.8103e-03 eta: 14:10:49 time: 0.8582 data_time: 0.0299 memory: 16201 loss_prob: 0.5110 loss_thr: 0.3633 loss_db: 0.0880 loss: 0.9623 2022/08/30 13:35:51 - mmengine - INFO - Epoch(train) [590][40/63] lr: 3.8103e-03 eta: 14:10:30 time: 0.8011 data_time: 0.0331 memory: 16201 loss_prob: 0.4942 loss_thr: 0.3492 loss_db: 0.0858 loss: 0.9293 2022/08/30 13:35:55 - mmengine - INFO - Epoch(train) [590][45/63] lr: 3.8103e-03 eta: 14:10:30 time: 0.8419 data_time: 0.0358 memory: 16201 loss_prob: 0.5152 loss_thr: 0.3501 loss_db: 0.0894 loss: 0.9547 2022/08/30 13:35:59 - mmengine - INFO - Epoch(train) [590][50/63] lr: 3.8103e-03 eta: 14:10:12 time: 0.8658 data_time: 0.0342 memory: 16201 loss_prob: 0.5169 loss_thr: 0.3478 loss_db: 0.0889 loss: 0.9535 2022/08/30 13:36:04 - mmengine - INFO - Epoch(train) [590][55/63] lr: 3.8103e-03 eta: 14:10:12 time: 0.8718 data_time: 0.0525 memory: 16201 loss_prob: 0.4977 loss_thr: 0.3500 loss_db: 0.0889 loss: 0.9366 2022/08/30 13:36:08 - mmengine - INFO - Epoch(train) [590][60/63] lr: 3.8103e-03 eta: 14:09:54 time: 0.8680 data_time: 0.0530 memory: 16201 loss_prob: 0.4762 loss_thr: 0.3312 loss_db: 0.0859 loss: 0.8933 2022/08/30 13:36:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:36:16 - mmengine - INFO - Epoch(train) [591][5/63] lr: 3.8047e-03 eta: 14:09:54 time: 1.0061 data_time: 0.1979 memory: 16201 loss_prob: 0.5312 loss_thr: 0.3590 loss_db: 0.0899 loss: 0.9801 2022/08/30 13:36:21 - mmengine - INFO - Epoch(train) [591][10/63] lr: 3.8047e-03 eta: 14:09:30 time: 1.0626 data_time: 0.2111 memory: 16201 loss_prob: 0.5451 loss_thr: 0.3675 loss_db: 0.0944 loss: 1.0070 2022/08/30 13:36:25 - mmengine - INFO - Epoch(train) [591][15/63] lr: 3.8047e-03 eta: 14:09:30 time: 0.8786 data_time: 0.0378 memory: 16201 loss_prob: 0.5568 loss_thr: 0.3808 loss_db: 0.0951 loss: 1.0327 2022/08/30 13:36:30 - mmengine - INFO - Epoch(train) [591][20/63] lr: 3.8047e-03 eta: 14:09:13 time: 0.9173 data_time: 0.0304 memory: 16201 loss_prob: 0.5340 loss_thr: 0.3600 loss_db: 0.0919 loss: 0.9859 2022/08/30 13:36:34 - mmengine - INFO - Epoch(train) [591][25/63] lr: 3.8047e-03 eta: 14:09:13 time: 0.9239 data_time: 0.0513 memory: 16201 loss_prob: 0.4992 loss_thr: 0.3407 loss_db: 0.0872 loss: 0.9271 2022/08/30 13:36:39 - mmengine - INFO - Epoch(train) [591][30/63] lr: 3.8047e-03 eta: 14:08:55 time: 0.8658 data_time: 0.0470 memory: 16201 loss_prob: 0.4712 loss_thr: 0.3251 loss_db: 0.0821 loss: 0.8784 2022/08/30 13:36:43 - mmengine - INFO - Epoch(train) [591][35/63] lr: 3.8047e-03 eta: 14:08:55 time: 0.8356 data_time: 0.0288 memory: 16201 loss_prob: 0.4920 loss_thr: 0.3297 loss_db: 0.0846 loss: 0.9063 2022/08/30 13:36:48 - mmengine - INFO - Epoch(train) [591][40/63] lr: 3.8047e-03 eta: 14:08:37 time: 0.9201 data_time: 0.0448 memory: 16201 loss_prob: 0.4725 loss_thr: 0.3261 loss_db: 0.0822 loss: 0.8807 2022/08/30 13:36:52 - mmengine - INFO - Epoch(train) [591][45/63] lr: 3.8047e-03 eta: 14:08:37 time: 0.9256 data_time: 0.0468 memory: 16201 loss_prob: 0.4426 loss_thr: 0.3128 loss_db: 0.0773 loss: 0.8327 2022/08/30 13:36:56 - mmengine - INFO - Epoch(train) [591][50/63] lr: 3.8047e-03 eta: 14:08:19 time: 0.8700 data_time: 0.0346 memory: 16201 loss_prob: 0.4761 loss_thr: 0.3271 loss_db: 0.0829 loss: 0.8861 2022/08/30 13:37:01 - mmengine - INFO - Epoch(train) [591][55/63] lr: 3.8047e-03 eta: 14:08:19 time: 0.8657 data_time: 0.0488 memory: 16201 loss_prob: 0.4953 loss_thr: 0.3304 loss_db: 0.0862 loss: 0.9119 2022/08/30 13:37:05 - mmengine - INFO - Epoch(train) [591][60/63] lr: 3.8047e-03 eta: 14:08:01 time: 0.8364 data_time: 0.0455 memory: 16201 loss_prob: 0.4481 loss_thr: 0.3145 loss_db: 0.0766 loss: 0.8392 2022/08/30 13:37:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:37:13 - mmengine - INFO - Epoch(train) [592][5/63] lr: 3.7991e-03 eta: 14:08:01 time: 0.9691 data_time: 0.1979 memory: 16201 loss_prob: 0.6016 loss_thr: 0.3625 loss_db: 0.0938 loss: 1.0579 2022/08/30 13:37:17 - mmengine - INFO - Epoch(train) [592][10/63] lr: 3.7991e-03 eta: 14:07:36 time: 1.0086 data_time: 0.2128 memory: 16201 loss_prob: 0.5653 loss_thr: 0.3790 loss_db: 0.0991 loss: 1.0434 2022/08/30 13:37:21 - mmengine - INFO - Epoch(train) [592][15/63] lr: 3.7991e-03 eta: 14:07:36 time: 0.8549 data_time: 0.0313 memory: 16201 loss_prob: 0.5271 loss_thr: 0.3590 loss_db: 0.0907 loss: 0.9768 2022/08/30 13:37:26 - mmengine - INFO - Epoch(train) [592][20/63] lr: 3.7991e-03 eta: 14:07:18 time: 0.8673 data_time: 0.0311 memory: 16201 loss_prob: 0.5206 loss_thr: 0.3452 loss_db: 0.0916 loss: 0.9574 2022/08/30 13:37:30 - mmengine - INFO - Epoch(train) [592][25/63] lr: 3.7991e-03 eta: 14:07:18 time: 0.8861 data_time: 0.0482 memory: 16201 loss_prob: 0.4923 loss_thr: 0.3447 loss_db: 0.0870 loss: 0.9240 2022/08/30 13:37:35 - mmengine - INFO - Epoch(train) [592][30/63] lr: 3.7991e-03 eta: 14:07:01 time: 0.8848 data_time: 0.0425 memory: 16201 loss_prob: 0.4782 loss_thr: 0.3422 loss_db: 0.0834 loss: 0.9037 2022/08/30 13:37:39 - mmengine - INFO - Epoch(train) [592][35/63] lr: 3.7991e-03 eta: 14:07:01 time: 0.8545 data_time: 0.0293 memory: 16201 loss_prob: 0.5061 loss_thr: 0.3477 loss_db: 0.0882 loss: 0.9421 2022/08/30 13:37:43 - mmengine - INFO - Epoch(train) [592][40/63] lr: 3.7991e-03 eta: 14:06:42 time: 0.8454 data_time: 0.0260 memory: 16201 loss_prob: 0.5291 loss_thr: 0.3552 loss_db: 0.0895 loss: 0.9737 2022/08/30 13:37:47 - mmengine - INFO - Epoch(train) [592][45/63] lr: 3.7991e-03 eta: 14:06:42 time: 0.8499 data_time: 0.0282 memory: 16201 loss_prob: 0.5221 loss_thr: 0.3494 loss_db: 0.0903 loss: 0.9618 2022/08/30 13:37:52 - mmengine - INFO - Epoch(train) [592][50/63] lr: 3.7991e-03 eta: 14:06:25 time: 0.9004 data_time: 0.0315 memory: 16201 loss_prob: 0.4897 loss_thr: 0.3378 loss_db: 0.0854 loss: 0.9130 2022/08/30 13:37:56 - mmengine - INFO - Epoch(train) [592][55/63] lr: 3.7991e-03 eta: 14:06:25 time: 0.8773 data_time: 0.0279 memory: 16201 loss_prob: 0.4692 loss_thr: 0.3328 loss_db: 0.0808 loss: 0.8828 2022/08/30 13:38:01 - mmengine - INFO - Epoch(train) [592][60/63] lr: 3.7991e-03 eta: 14:06:07 time: 0.8527 data_time: 0.0243 memory: 16201 loss_prob: 0.4756 loss_thr: 0.3420 loss_db: 0.0827 loss: 0.9002 2022/08/30 13:38:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:38:09 - mmengine - INFO - Epoch(train) [593][5/63] lr: 3.7935e-03 eta: 14:06:07 time: 0.9909 data_time: 0.1851 memory: 16201 loss_prob: 0.4490 loss_thr: 0.3092 loss_db: 0.0793 loss: 0.8375 2022/08/30 13:38:13 - mmengine - INFO - Epoch(train) [593][10/63] lr: 3.7935e-03 eta: 14:05:42 time: 1.0088 data_time: 0.2011 memory: 16201 loss_prob: 0.5020 loss_thr: 0.3270 loss_db: 0.0861 loss: 0.9151 2022/08/30 13:38:17 - mmengine - INFO - Epoch(train) [593][15/63] lr: 3.7935e-03 eta: 14:05:42 time: 0.8630 data_time: 0.0340 memory: 16201 loss_prob: 0.5199 loss_thr: 0.3508 loss_db: 0.0870 loss: 0.9578 2022/08/30 13:38:22 - mmengine - INFO - Epoch(train) [593][20/63] lr: 3.7935e-03 eta: 14:05:24 time: 0.8833 data_time: 0.0316 memory: 16201 loss_prob: 0.5088 loss_thr: 0.3446 loss_db: 0.0898 loss: 0.9431 2022/08/30 13:38:26 - mmengine - INFO - Epoch(train) [593][25/63] lr: 3.7935e-03 eta: 14:05:24 time: 0.8836 data_time: 0.0468 memory: 16201 loss_prob: 0.5169 loss_thr: 0.3404 loss_db: 0.0909 loss: 0.9482 2022/08/30 13:38:30 - mmengine - INFO - Epoch(train) [593][30/63] lr: 3.7935e-03 eta: 14:05:06 time: 0.8600 data_time: 0.0374 memory: 16201 loss_prob: 0.4999 loss_thr: 0.3367 loss_db: 0.0830 loss: 0.9196 2022/08/30 13:38:34 - mmengine - INFO - Epoch(train) [593][35/63] lr: 3.7935e-03 eta: 14:05:06 time: 0.8208 data_time: 0.0267 memory: 16201 loss_prob: 0.5241 loss_thr: 0.3499 loss_db: 0.0892 loss: 0.9631 2022/08/30 13:38:39 - mmengine - INFO - Epoch(train) [593][40/63] lr: 3.7935e-03 eta: 14:04:48 time: 0.8242 data_time: 0.0395 memory: 16201 loss_prob: 0.5019 loss_thr: 0.3478 loss_db: 0.0893 loss: 0.9390 2022/08/30 13:38:46 - mmengine - INFO - Epoch(train) [593][45/63] lr: 3.7935e-03 eta: 14:04:48 time: 1.1192 data_time: 0.0793 memory: 16201 loss_prob: 0.4532 loss_thr: 0.3342 loss_db: 0.0801 loss: 0.8675 2022/08/30 13:38:50 - mmengine - INFO - Epoch(train) [593][50/63] lr: 3.7935e-03 eta: 14:04:33 time: 1.1350 data_time: 0.0913 memory: 16201 loss_prob: 0.4663 loss_thr: 0.3368 loss_db: 0.0817 loss: 0.8848 2022/08/30 13:38:54 - mmengine - INFO - Epoch(train) [593][55/63] lr: 3.7935e-03 eta: 14:04:33 time: 0.8625 data_time: 0.0462 memory: 16201 loss_prob: 0.5187 loss_thr: 0.3480 loss_db: 0.0917 loss: 0.9584 2022/08/30 13:38:58 - mmengine - INFO - Epoch(train) [593][60/63] lr: 3.7935e-03 eta: 14:04:15 time: 0.8379 data_time: 0.0223 memory: 16201 loss_prob: 0.5151 loss_thr: 0.3469 loss_db: 0.0911 loss: 0.9531 2022/08/30 13:39:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:39:07 - mmengine - INFO - Epoch(train) [594][5/63] lr: 3.7878e-03 eta: 14:04:15 time: 1.0664 data_time: 0.2159 memory: 16201 loss_prob: 0.4582 loss_thr: 0.3219 loss_db: 0.0804 loss: 0.8604 2022/08/30 13:39:11 - mmengine - INFO - Epoch(train) [594][10/63] lr: 3.7878e-03 eta: 14:03:50 time: 0.9996 data_time: 0.2021 memory: 16201 loss_prob: 0.4231 loss_thr: 0.3137 loss_db: 0.0742 loss: 0.8109 2022/08/30 13:39:16 - mmengine - INFO - Epoch(train) [594][15/63] lr: 3.7878e-03 eta: 14:03:50 time: 0.8127 data_time: 0.0279 memory: 16201 loss_prob: 0.4290 loss_thr: 0.3131 loss_db: 0.0756 loss: 0.8177 2022/08/30 13:39:20 - mmengine - INFO - Epoch(train) [594][20/63] lr: 3.7878e-03 eta: 14:03:32 time: 0.8691 data_time: 0.0430 memory: 16201 loss_prob: 0.4983 loss_thr: 0.3430 loss_db: 0.0880 loss: 0.9292 2022/08/30 13:39:24 - mmengine - INFO - Epoch(train) [594][25/63] lr: 3.7878e-03 eta: 14:03:32 time: 0.8453 data_time: 0.0352 memory: 16201 loss_prob: 0.5251 loss_thr: 0.3501 loss_db: 0.0902 loss: 0.9654 2022/08/30 13:39:29 - mmengine - INFO - Epoch(train) [594][30/63] lr: 3.7878e-03 eta: 14:03:14 time: 0.8556 data_time: 0.0304 memory: 16201 loss_prob: 0.5326 loss_thr: 0.3653 loss_db: 0.0910 loss: 0.9889 2022/08/30 13:39:33 - mmengine - INFO - Epoch(train) [594][35/63] lr: 3.7878e-03 eta: 14:03:14 time: 0.8896 data_time: 0.0357 memory: 16201 loss_prob: 0.5191 loss_thr: 0.3675 loss_db: 0.0908 loss: 0.9775 2022/08/30 13:39:37 - mmengine - INFO - Epoch(train) [594][40/63] lr: 3.7878e-03 eta: 14:02:56 time: 0.8157 data_time: 0.0241 memory: 16201 loss_prob: 0.5161 loss_thr: 0.3601 loss_db: 0.0905 loss: 0.9667 2022/08/30 13:39:41 - mmengine - INFO - Epoch(train) [594][45/63] lr: 3.7878e-03 eta: 14:02:56 time: 0.8306 data_time: 0.0276 memory: 16201 loss_prob: 0.5111 loss_thr: 0.3531 loss_db: 0.0907 loss: 0.9549 2022/08/30 13:39:45 - mmengine - INFO - Epoch(train) [594][50/63] lr: 3.7878e-03 eta: 14:02:37 time: 0.8349 data_time: 0.0315 memory: 16201 loss_prob: 0.4830 loss_thr: 0.3320 loss_db: 0.0871 loss: 0.9021 2022/08/30 13:39:49 - mmengine - INFO - Epoch(train) [594][55/63] lr: 3.7878e-03 eta: 14:02:37 time: 0.7752 data_time: 0.0231 memory: 16201 loss_prob: 0.4872 loss_thr: 0.3317 loss_db: 0.0841 loss: 0.9030 2022/08/30 13:39:53 - mmengine - INFO - Epoch(train) [594][60/63] lr: 3.7878e-03 eta: 14:02:19 time: 0.7915 data_time: 0.0307 memory: 16201 loss_prob: 0.4683 loss_thr: 0.3272 loss_db: 0.0810 loss: 0.8764 2022/08/30 13:39:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:40:02 - mmengine - INFO - Epoch(train) [595][5/63] lr: 3.7822e-03 eta: 14:02:19 time: 1.0286 data_time: 0.2249 memory: 16201 loss_prob: 0.5036 loss_thr: 0.3260 loss_db: 0.0874 loss: 0.9169 2022/08/30 13:40:06 - mmengine - INFO - Epoch(train) [595][10/63] lr: 3.7822e-03 eta: 14:01:55 time: 1.0475 data_time: 0.2501 memory: 16201 loss_prob: 0.5301 loss_thr: 0.3519 loss_db: 0.0909 loss: 0.9728 2022/08/30 13:40:15 - mmengine - INFO - Epoch(train) [595][15/63] lr: 3.7822e-03 eta: 14:01:55 time: 1.2960 data_time: 0.0615 memory: 16201 loss_prob: 0.5774 loss_thr: 0.3645 loss_db: 0.0952 loss: 1.0372 2022/08/30 13:40:21 - mmengine - INFO - Epoch(train) [595][20/63] lr: 3.7822e-03 eta: 14:01:43 time: 1.4495 data_time: 0.1691 memory: 16201 loss_prob: 0.5211 loss_thr: 0.3325 loss_db: 0.0877 loss: 0.9413 2022/08/30 13:40:35 - mmengine - INFO - Epoch(train) [595][25/63] lr: 3.7822e-03 eta: 14:01:43 time: 1.9771 data_time: 0.1613 memory: 16201 loss_prob: 0.4509 loss_thr: 0.3222 loss_db: 0.0795 loss: 0.8526 2022/08/30 13:40:39 - mmengine - INFO - Epoch(train) [595][30/63] lr: 3.7822e-03 eta: 14:01:35 time: 1.8365 data_time: 0.0429 memory: 16201 loss_prob: 0.4768 loss_thr: 0.3333 loss_db: 0.0794 loss: 0.8895 2022/08/30 13:40:44 - mmengine - INFO - Epoch(train) [595][35/63] lr: 3.7822e-03 eta: 14:01:35 time: 0.9056 data_time: 0.0708 memory: 16201 loss_prob: 0.4913 loss_thr: 0.3389 loss_db: 0.0826 loss: 0.9128 2022/08/30 13:40:50 - mmengine - INFO - Epoch(train) [595][40/63] lr: 3.7822e-03 eta: 14:01:19 time: 1.0891 data_time: 0.0836 memory: 16201 loss_prob: 0.4738 loss_thr: 0.3379 loss_db: 0.0841 loss: 0.8958 2022/08/30 13:40:55 - mmengine - INFO - Epoch(train) [595][45/63] lr: 3.7822e-03 eta: 14:01:19 time: 1.0955 data_time: 0.0649 memory: 16201 loss_prob: 0.4796 loss_thr: 0.3332 loss_db: 0.0843 loss: 0.8972 2022/08/30 13:40:59 - mmengine - INFO - Epoch(train) [595][50/63] lr: 3.7822e-03 eta: 14:01:02 time: 0.9417 data_time: 0.0315 memory: 16201 loss_prob: 0.4913 loss_thr: 0.3331 loss_db: 0.0853 loss: 0.9098 2022/08/30 13:41:08 - mmengine - INFO - Epoch(train) [595][55/63] lr: 3.7822e-03 eta: 14:01:02 time: 1.2805 data_time: 0.0497 memory: 16201 loss_prob: 0.5121 loss_thr: 0.3499 loss_db: 0.0891 loss: 0.9511 2022/08/30 13:41:12 - mmengine - INFO - Epoch(train) [595][60/63] lr: 3.7822e-03 eta: 14:00:48 time: 1.2654 data_time: 0.0831 memory: 16201 loss_prob: 0.4799 loss_thr: 0.3277 loss_db: 0.0824 loss: 0.8900 2022/08/30 13:41:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:41:22 - mmengine - INFO - Epoch(train) [596][5/63] lr: 3.7766e-03 eta: 14:00:48 time: 1.1504 data_time: 0.2396 memory: 16201 loss_prob: 0.4963 loss_thr: 0.3292 loss_db: 0.0860 loss: 0.9115 2022/08/30 13:41:26 - mmengine - INFO - Epoch(train) [596][10/63] lr: 3.7766e-03 eta: 14:00:24 time: 1.0415 data_time: 0.2446 memory: 16201 loss_prob: 0.5381 loss_thr: 0.3554 loss_db: 0.0911 loss: 0.9846 2022/08/30 13:41:38 - mmengine - INFO - Epoch(train) [596][15/63] lr: 3.7766e-03 eta: 14:00:24 time: 1.5922 data_time: 0.1603 memory: 16201 loss_prob: 0.5299 loss_thr: 0.3518 loss_db: 0.0880 loss: 0.9697 2022/08/30 13:41:42 - mmengine - INFO - Epoch(train) [596][20/63] lr: 3.7766e-03 eta: 14:00:13 time: 1.5785 data_time: 0.1357 memory: 16201 loss_prob: 0.5256 loss_thr: 0.3613 loss_db: 0.0905 loss: 0.9774 2022/08/30 13:41:46 - mmengine - INFO - Epoch(train) [596][25/63] lr: 3.7766e-03 eta: 14:00:13 time: 0.8636 data_time: 0.0425 memory: 16201 loss_prob: 0.5259 loss_thr: 0.3730 loss_db: 0.0931 loss: 0.9920 2022/08/30 13:41:56 - mmengine - INFO - Epoch(train) [596][30/63] lr: 3.7766e-03 eta: 14:00:00 time: 1.3452 data_time: 0.0417 memory: 16201 loss_prob: 0.4856 loss_thr: 0.3454 loss_db: 0.0847 loss: 0.9158 2022/08/30 13:42:00 - mmengine - INFO - Epoch(train) [596][35/63] lr: 3.7766e-03 eta: 14:00:00 time: 1.3504 data_time: 0.0409 memory: 16201 loss_prob: 0.4459 loss_thr: 0.3199 loss_db: 0.0777 loss: 0.8434 2022/08/30 13:42:04 - mmengine - INFO - Epoch(train) [596][40/63] lr: 3.7766e-03 eta: 13:59:42 time: 0.8203 data_time: 0.0266 memory: 16201 loss_prob: 0.4051 loss_thr: 0.3131 loss_db: 0.0719 loss: 0.7901 2022/08/30 13:42:10 - mmengine - INFO - Epoch(train) [596][45/63] lr: 3.7766e-03 eta: 13:59:42 time: 1.0427 data_time: 0.1176 memory: 16201 loss_prob: 0.4429 loss_thr: 0.3309 loss_db: 0.0787 loss: 0.8525 2022/08/30 13:42:15 - mmengine - INFO - Epoch(train) [596][50/63] lr: 3.7766e-03 eta: 13:59:27 time: 1.1202 data_time: 0.1302 memory: 16201 loss_prob: 0.5111 loss_thr: 0.3632 loss_db: 0.0910 loss: 0.9653 2022/08/30 13:42:20 - mmengine - INFO - Epoch(train) [596][55/63] lr: 3.7766e-03 eta: 13:59:27 time: 0.9132 data_time: 0.0280 memory: 16201 loss_prob: 0.5298 loss_thr: 0.3680 loss_db: 0.0925 loss: 0.9902 2022/08/30 13:42:25 - mmengine - INFO - Epoch(train) [596][60/63] lr: 3.7766e-03 eta: 13:59:10 time: 0.9497 data_time: 0.0309 memory: 16201 loss_prob: 0.5277 loss_thr: 0.3565 loss_db: 0.0916 loss: 0.9758 2022/08/30 13:42:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:42:34 - mmengine - INFO - Epoch(train) [597][5/63] lr: 3.7710e-03 eta: 13:59:10 time: 1.1160 data_time: 0.3091 memory: 16201 loss_prob: 0.5071 loss_thr: 0.3522 loss_db: 0.0900 loss: 0.9493 2022/08/30 13:42:43 - mmengine - INFO - Epoch(train) [597][10/63] lr: 3.7710e-03 eta: 13:58:50 time: 1.5043 data_time: 0.2600 memory: 16201 loss_prob: 0.4358 loss_thr: 0.3293 loss_db: 0.0773 loss: 0.8425 2022/08/30 13:42:49 - mmengine - INFO - Epoch(train) [597][15/63] lr: 3.7710e-03 eta: 13:58:50 time: 1.5025 data_time: 0.0699 memory: 16201 loss_prob: 0.4249 loss_thr: 0.3200 loss_db: 0.0746 loss: 0.8195 2022/08/30 13:42:53 - mmengine - INFO - Epoch(train) [597][20/63] lr: 3.7710e-03 eta: 13:58:34 time: 1.0415 data_time: 0.0701 memory: 16201 loss_prob: 0.4530 loss_thr: 0.3324 loss_db: 0.0792 loss: 0.8646 2022/08/30 13:42:58 - mmengine - INFO - Epoch(train) [597][25/63] lr: 3.7710e-03 eta: 13:58:34 time: 0.8922 data_time: 0.0291 memory: 16201 loss_prob: 0.4664 loss_thr: 0.3339 loss_db: 0.0813 loss: 0.8816 2022/08/30 13:43:03 - mmengine - INFO - Epoch(train) [597][30/63] lr: 3.7710e-03 eta: 13:58:17 time: 0.9453 data_time: 0.0312 memory: 16201 loss_prob: 0.4716 loss_thr: 0.3219 loss_db: 0.0798 loss: 0.8733 2022/08/30 13:43:07 - mmengine - INFO - Epoch(train) [597][35/63] lr: 3.7710e-03 eta: 13:58:17 time: 0.9077 data_time: 0.0210 memory: 16201 loss_prob: 0.4953 loss_thr: 0.3366 loss_db: 0.0830 loss: 0.9148 2022/08/30 13:43:15 - mmengine - INFO - Epoch(train) [597][40/63] lr: 3.7710e-03 eta: 13:58:03 time: 1.1943 data_time: 0.0358 memory: 16201 loss_prob: 0.4867 loss_thr: 0.3488 loss_db: 0.0837 loss: 0.9193 2022/08/30 13:43:19 - mmengine - INFO - Epoch(train) [597][45/63] lr: 3.7710e-03 eta: 13:58:03 time: 1.1393 data_time: 0.0385 memory: 16201 loss_prob: 0.4677 loss_thr: 0.3390 loss_db: 0.0830 loss: 0.8897 2022/08/30 13:43:23 - mmengine - INFO - Epoch(train) [597][50/63] lr: 3.7710e-03 eta: 13:57:45 time: 0.8593 data_time: 0.0267 memory: 16201 loss_prob: 0.4886 loss_thr: 0.3328 loss_db: 0.0855 loss: 0.9070 2022/08/30 13:43:27 - mmengine - INFO - Epoch(train) [597][55/63] lr: 3.7710e-03 eta: 13:57:45 time: 0.8614 data_time: 0.0273 memory: 16201 loss_prob: 0.4719 loss_thr: 0.3294 loss_db: 0.0801 loss: 0.8814 2022/08/30 13:43:31 - mmengine - INFO - Epoch(train) [597][60/63] lr: 3.7710e-03 eta: 13:57:27 time: 0.8308 data_time: 0.0246 memory: 16201 loss_prob: 0.4550 loss_thr: 0.3276 loss_db: 0.0800 loss: 0.8626 2022/08/30 13:43:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:43:39 - mmengine - INFO - Epoch(train) [598][5/63] lr: 3.7653e-03 eta: 13:57:27 time: 0.9386 data_time: 0.1709 memory: 16201 loss_prob: 0.4920 loss_thr: 0.3478 loss_db: 0.0837 loss: 0.9235 2022/08/30 13:43:44 - mmengine - INFO - Epoch(train) [598][10/63] lr: 3.7653e-03 eta: 13:57:02 time: 1.0019 data_time: 0.1766 memory: 16201 loss_prob: 0.5218 loss_thr: 0.3721 loss_db: 0.0887 loss: 0.9826 2022/08/30 13:43:48 - mmengine - INFO - Epoch(train) [598][15/63] lr: 3.7653e-03 eta: 13:57:02 time: 0.8904 data_time: 0.0329 memory: 16201 loss_prob: 0.4890 loss_thr: 0.3674 loss_db: 0.0870 loss: 0.9434 2022/08/30 13:43:52 - mmengine - INFO - Epoch(train) [598][20/63] lr: 3.7653e-03 eta: 13:56:44 time: 0.8746 data_time: 0.0228 memory: 16201 loss_prob: 0.4681 loss_thr: 0.3456 loss_db: 0.0824 loss: 0.8961 2022/08/30 13:43:56 - mmengine - INFO - Epoch(train) [598][25/63] lr: 3.7653e-03 eta: 13:56:44 time: 0.8285 data_time: 0.0271 memory: 16201 loss_prob: 0.4796 loss_thr: 0.3272 loss_db: 0.0824 loss: 0.8892 2022/08/30 13:44:01 - mmengine - INFO - Epoch(train) [598][30/63] lr: 3.7653e-03 eta: 13:56:27 time: 0.8762 data_time: 0.0243 memory: 16201 loss_prob: 0.4172 loss_thr: 0.2912 loss_db: 0.0719 loss: 0.7803 2022/08/30 13:44:05 - mmengine - INFO - Epoch(train) [598][35/63] lr: 3.7653e-03 eta: 13:56:27 time: 0.8909 data_time: 0.0239 memory: 16201 loss_prob: 0.4525 loss_thr: 0.3191 loss_db: 0.0798 loss: 0.8514 2022/08/30 13:44:09 - mmengine - INFO - Epoch(train) [598][40/63] lr: 3.7653e-03 eta: 13:56:08 time: 0.8230 data_time: 0.0206 memory: 16201 loss_prob: 0.4867 loss_thr: 0.3462 loss_db: 0.0863 loss: 0.9192 2022/08/30 13:44:14 - mmengine - INFO - Epoch(train) [598][45/63] lr: 3.7653e-03 eta: 13:56:08 time: 0.8230 data_time: 0.0301 memory: 16201 loss_prob: 0.4893 loss_thr: 0.3433 loss_db: 0.0865 loss: 0.9191 2022/08/30 13:44:18 - mmengine - INFO - Epoch(train) [598][50/63] lr: 3.7653e-03 eta: 13:55:50 time: 0.8539 data_time: 0.0371 memory: 16201 loss_prob: 0.5553 loss_thr: 0.3586 loss_db: 0.0954 loss: 1.0093 2022/08/30 13:44:22 - mmengine - INFO - Epoch(train) [598][55/63] lr: 3.7653e-03 eta: 13:55:50 time: 0.8152 data_time: 0.0181 memory: 16201 loss_prob: 0.5328 loss_thr: 0.3572 loss_db: 0.0920 loss: 0.9820 2022/08/30 13:44:26 - mmengine - INFO - Epoch(train) [598][60/63] lr: 3.7653e-03 eta: 13:55:32 time: 0.7865 data_time: 0.0292 memory: 16201 loss_prob: 0.4636 loss_thr: 0.3313 loss_db: 0.0840 loss: 0.8789 2022/08/30 13:44:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:44:33 - mmengine - INFO - Epoch(train) [599][5/63] lr: 3.7597e-03 eta: 13:55:32 time: 0.8995 data_time: 0.1652 memory: 16201 loss_prob: 0.4378 loss_thr: 0.3182 loss_db: 0.0757 loss: 0.8316 2022/08/30 13:44:37 - mmengine - INFO - Epoch(train) [599][10/63] lr: 3.7597e-03 eta: 13:55:07 time: 0.9512 data_time: 0.1786 memory: 16201 loss_prob: 0.4495 loss_thr: 0.3180 loss_db: 0.0777 loss: 0.8452 2022/08/30 13:44:42 - mmengine - INFO - Epoch(train) [599][15/63] lr: 3.7597e-03 eta: 13:55:07 time: 0.8364 data_time: 0.0237 memory: 16201 loss_prob: 0.4807 loss_thr: 0.3452 loss_db: 0.0853 loss: 0.9111 2022/08/30 13:44:46 - mmengine - INFO - Epoch(train) [599][20/63] lr: 3.7597e-03 eta: 13:54:49 time: 0.8530 data_time: 0.0316 memory: 16201 loss_prob: 0.4814 loss_thr: 0.3485 loss_db: 0.0848 loss: 0.9147 2022/08/30 13:44:50 - mmengine - INFO - Epoch(train) [599][25/63] lr: 3.7597e-03 eta: 13:54:49 time: 0.8492 data_time: 0.0408 memory: 16201 loss_prob: 0.4960 loss_thr: 0.3502 loss_db: 0.0876 loss: 0.9337 2022/08/30 13:44:54 - mmengine - INFO - Epoch(train) [599][30/63] lr: 3.7597e-03 eta: 13:54:31 time: 0.8401 data_time: 0.0222 memory: 16201 loss_prob: 0.4830 loss_thr: 0.3438 loss_db: 0.0857 loss: 0.9125 2022/08/30 13:44:58 - mmengine - INFO - Epoch(train) [599][35/63] lr: 3.7597e-03 eta: 13:54:31 time: 0.8051 data_time: 0.0216 memory: 16201 loss_prob: 0.4548 loss_thr: 0.3256 loss_db: 0.0810 loss: 0.8614 2022/08/30 13:45:03 - mmengine - INFO - Epoch(train) [599][40/63] lr: 3.7597e-03 eta: 13:54:13 time: 0.8747 data_time: 0.0338 memory: 16201 loss_prob: 0.4546 loss_thr: 0.3123 loss_db: 0.0808 loss: 0.8477 2022/08/30 13:45:07 - mmengine - INFO - Epoch(train) [599][45/63] lr: 3.7597e-03 eta: 13:54:13 time: 0.9053 data_time: 0.0344 memory: 16201 loss_prob: 0.4729 loss_thr: 0.3251 loss_db: 0.0810 loss: 0.8790 2022/08/30 13:45:12 - mmengine - INFO - Epoch(train) [599][50/63] lr: 3.7597e-03 eta: 13:53:55 time: 0.8607 data_time: 0.0310 memory: 16201 loss_prob: 0.5046 loss_thr: 0.3432 loss_db: 0.0848 loss: 0.9327 2022/08/30 13:45:16 - mmengine - INFO - Epoch(train) [599][55/63] lr: 3.7597e-03 eta: 13:53:55 time: 0.8659 data_time: 0.0262 memory: 16201 loss_prob: 0.4842 loss_thr: 0.3324 loss_db: 0.0836 loss: 0.9001 2022/08/30 13:45:20 - mmengine - INFO - Epoch(train) [599][60/63] lr: 3.7597e-03 eta: 13:53:37 time: 0.8405 data_time: 0.0261 memory: 16201 loss_prob: 0.4239 loss_thr: 0.3112 loss_db: 0.0755 loss: 0.8107 2022/08/30 13:45:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:45:28 - mmengine - INFO - Epoch(train) [600][5/63] lr: 3.7541e-03 eta: 13:53:37 time: 0.9402 data_time: 0.1750 memory: 16201 loss_prob: 0.5087 loss_thr: 0.3538 loss_db: 0.0895 loss: 0.9519 2022/08/30 13:45:32 - mmengine - INFO - Epoch(train) [600][10/63] lr: 3.7541e-03 eta: 13:53:13 time: 0.9970 data_time: 0.1844 memory: 16201 loss_prob: 0.4863 loss_thr: 0.3463 loss_db: 0.0854 loss: 0.9181 2022/08/30 13:45:36 - mmengine - INFO - Epoch(train) [600][15/63] lr: 3.7541e-03 eta: 13:53:13 time: 0.8454 data_time: 0.0244 memory: 16201 loss_prob: 0.5010 loss_thr: 0.3459 loss_db: 0.0864 loss: 0.9332 2022/08/30 13:45:41 - mmengine - INFO - Epoch(train) [600][20/63] lr: 3.7541e-03 eta: 13:52:56 time: 0.9027 data_time: 0.0274 memory: 16201 loss_prob: 0.4748 loss_thr: 0.3193 loss_db: 0.0833 loss: 0.8773 2022/08/30 13:45:45 - mmengine - INFO - Epoch(train) [600][25/63] lr: 3.7541e-03 eta: 13:52:56 time: 0.9084 data_time: 0.0392 memory: 16201 loss_prob: 0.4615 loss_thr: 0.3196 loss_db: 0.0814 loss: 0.8626 2022/08/30 13:45:50 - mmengine - INFO - Epoch(train) [600][30/63] lr: 3.7541e-03 eta: 13:52:38 time: 0.8556 data_time: 0.0327 memory: 16201 loss_prob: 0.4261 loss_thr: 0.3133 loss_db: 0.0753 loss: 0.8147 2022/08/30 13:45:54 - mmengine - INFO - Epoch(train) [600][35/63] lr: 3.7541e-03 eta: 13:52:38 time: 0.8357 data_time: 0.0259 memory: 16201 loss_prob: 0.4513 loss_thr: 0.3191 loss_db: 0.0804 loss: 0.8507 2022/08/30 13:45:58 - mmengine - INFO - Epoch(train) [600][40/63] lr: 3.7541e-03 eta: 13:52:19 time: 0.8154 data_time: 0.0237 memory: 16201 loss_prob: 0.4810 loss_thr: 0.3285 loss_db: 0.0848 loss: 0.8944 2022/08/30 13:46:02 - mmengine - INFO - Epoch(train) [600][45/63] lr: 3.7541e-03 eta: 13:52:19 time: 0.8648 data_time: 0.0282 memory: 16201 loss_prob: 0.4533 loss_thr: 0.3165 loss_db: 0.0792 loss: 0.8490 2022/08/30 13:46:07 - mmengine - INFO - Epoch(train) [600][50/63] lr: 3.7541e-03 eta: 13:52:02 time: 0.8794 data_time: 0.0259 memory: 16201 loss_prob: 0.5053 loss_thr: 0.3462 loss_db: 0.0877 loss: 0.9392 2022/08/30 13:46:11 - mmengine - INFO - Epoch(train) [600][55/63] lr: 3.7541e-03 eta: 13:52:02 time: 0.8354 data_time: 0.0247 memory: 16201 loss_prob: 0.4689 loss_thr: 0.3381 loss_db: 0.0822 loss: 0.8892 2022/08/30 13:46:15 - mmengine - INFO - Epoch(train) [600][60/63] lr: 3.7541e-03 eta: 13:51:44 time: 0.8113 data_time: 0.0286 memory: 16201 loss_prob: 0.4749 loss_thr: 0.3341 loss_db: 0.0856 loss: 0.8946 2022/08/30 13:46:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:46:17 - mmengine - INFO - Saving checkpoint at 600 epochs 2022/08/30 13:46:25 - mmengine - INFO - Epoch(val) [600][5/32] eta: 13:51:44 time: 0.6267 data_time: 0.1139 memory: 16201 2022/08/30 13:46:28 - mmengine - INFO - Epoch(val) [600][10/32] eta: 0:00:15 time: 0.6857 data_time: 0.1346 memory: 15734 2022/08/30 13:46:31 - mmengine - INFO - Epoch(val) [600][15/32] eta: 0:00:15 time: 0.5999 data_time: 0.0511 memory: 15734 2022/08/30 13:46:34 - mmengine - INFO - Epoch(val) [600][20/32] eta: 0:00:07 time: 0.6286 data_time: 0.0554 memory: 15734 2022/08/30 13:46:37 - mmengine - INFO - Epoch(val) [600][25/32] eta: 0:00:07 time: 0.6509 data_time: 0.0650 memory: 15734 2022/08/30 13:46:40 - mmengine - INFO - Epoch(val) [600][30/32] eta: 0:00:01 time: 0.5842 data_time: 0.0382 memory: 15734 2022/08/30 13:46:41 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 13:46:41 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8291, precision: 0.8062, hmean: 0.8175 2022/08/30 13:46:41 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8291, precision: 0.8474, hmean: 0.8382 2022/08/30 13:46:41 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8267, precision: 0.8698, hmean: 0.8477 2022/08/30 13:46:41 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8219, precision: 0.8923, hmean: 0.8556 2022/08/30 13:46:41 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8036, precision: 0.9071, hmean: 0.8522 2022/08/30 13:46:41 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7347, precision: 0.9368, hmean: 0.8235 2022/08/30 13:46:41 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1820, precision: 0.9668, hmean: 0.3063 2022/08/30 13:46:41 - mmengine - INFO - Epoch(val) [600][32/32] icdar/precision: 0.8923 icdar/recall: 0.8219 icdar/hmean: 0.8556 2022/08/30 13:46:47 - mmengine - INFO - Epoch(train) [601][5/63] lr: 3.7484e-03 eta: 0:00:01 time: 0.9610 data_time: 0.1838 memory: 16201 loss_prob: 0.5397 loss_thr: 0.3593 loss_db: 0.0886 loss: 0.9876 2022/08/30 13:46:51 - mmengine - INFO - Epoch(train) [601][10/63] lr: 3.7484e-03 eta: 13:51:19 time: 1.0039 data_time: 0.1933 memory: 16201 loss_prob: 0.4796 loss_thr: 0.3173 loss_db: 0.0807 loss: 0.8776 2022/08/30 13:46:55 - mmengine - INFO - Epoch(train) [601][15/63] lr: 3.7484e-03 eta: 13:51:19 time: 0.8396 data_time: 0.0333 memory: 16201 loss_prob: 0.4505 loss_thr: 0.3274 loss_db: 0.0806 loss: 0.8584 2022/08/30 13:46:59 - mmengine - INFO - Epoch(train) [601][20/63] lr: 3.7484e-03 eta: 13:51:01 time: 0.8320 data_time: 0.0288 memory: 16201 loss_prob: 0.5106 loss_thr: 0.3657 loss_db: 0.0888 loss: 0.9651 2022/08/30 13:47:04 - mmengine - INFO - Epoch(train) [601][25/63] lr: 3.7484e-03 eta: 13:51:01 time: 0.8367 data_time: 0.0268 memory: 16201 loss_prob: 0.5274 loss_thr: 0.3589 loss_db: 0.0911 loss: 0.9774 2022/08/30 13:47:08 - mmengine - INFO - Epoch(train) [601][30/63] lr: 3.7484e-03 eta: 13:50:43 time: 0.8676 data_time: 0.0267 memory: 16201 loss_prob: 0.4700 loss_thr: 0.3254 loss_db: 0.0824 loss: 0.8779 2022/08/30 13:47:12 - mmengine - INFO - Epoch(train) [601][35/63] lr: 3.7484e-03 eta: 13:50:43 time: 0.8554 data_time: 0.0295 memory: 16201 loss_prob: 0.4432 loss_thr: 0.3203 loss_db: 0.0798 loss: 0.8433 2022/08/30 13:47:16 - mmengine - INFO - Epoch(train) [601][40/63] lr: 3.7484e-03 eta: 13:50:25 time: 0.8161 data_time: 0.0243 memory: 16201 loss_prob: 0.4840 loss_thr: 0.3311 loss_db: 0.0835 loss: 0.8986 2022/08/30 13:47:20 - mmengine - INFO - Epoch(train) [601][45/63] lr: 3.7484e-03 eta: 13:50:25 time: 0.8315 data_time: 0.0264 memory: 16201 loss_prob: 0.5094 loss_thr: 0.3475 loss_db: 0.0880 loss: 0.9448 2022/08/30 13:47:25 - mmengine - INFO - Epoch(train) [601][50/63] lr: 3.7484e-03 eta: 13:50:07 time: 0.8560 data_time: 0.0358 memory: 16201 loss_prob: 0.4909 loss_thr: 0.3517 loss_db: 0.0885 loss: 0.9311 2022/08/30 13:47:29 - mmengine - INFO - Epoch(train) [601][55/63] lr: 3.7484e-03 eta: 13:50:07 time: 0.8502 data_time: 0.0213 memory: 16201 loss_prob: 0.4784 loss_thr: 0.3355 loss_db: 0.0847 loss: 0.8985 2022/08/30 13:47:33 - mmengine - INFO - Epoch(train) [601][60/63] lr: 3.7484e-03 eta: 13:49:50 time: 0.8582 data_time: 0.0266 memory: 16201 loss_prob: 0.4645 loss_thr: 0.3321 loss_db: 0.0816 loss: 0.8783 2022/08/30 13:47:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:47:41 - mmengine - INFO - Epoch(train) [602][5/63] lr: 3.7428e-03 eta: 13:49:50 time: 0.9682 data_time: 0.1690 memory: 16201 loss_prob: 0.5065 loss_thr: 0.3565 loss_db: 0.0868 loss: 0.9498 2022/08/30 13:47:46 - mmengine - INFO - Epoch(train) [602][10/63] lr: 3.7428e-03 eta: 13:49:25 time: 1.0079 data_time: 0.1691 memory: 16201 loss_prob: 0.4549 loss_thr: 0.3328 loss_db: 0.0803 loss: 0.8679 2022/08/30 13:47:50 - mmengine - INFO - Epoch(train) [602][15/63] lr: 3.7428e-03 eta: 13:49:25 time: 0.8657 data_time: 0.0258 memory: 16201 loss_prob: 0.4660 loss_thr: 0.3286 loss_db: 0.0818 loss: 0.8764 2022/08/30 13:47:54 - mmengine - INFO - Epoch(train) [602][20/63] lr: 3.7428e-03 eta: 13:49:08 time: 0.8561 data_time: 0.0227 memory: 16201 loss_prob: 0.4717 loss_thr: 0.3284 loss_db: 0.0819 loss: 0.8820 2022/08/30 13:47:58 - mmengine - INFO - Epoch(train) [602][25/63] lr: 3.7428e-03 eta: 13:49:08 time: 0.8434 data_time: 0.0287 memory: 16201 loss_prob: 0.4714 loss_thr: 0.3314 loss_db: 0.0823 loss: 0.8851 2022/08/30 13:48:03 - mmengine - INFO - Epoch(train) [602][30/63] lr: 3.7428e-03 eta: 13:48:50 time: 0.8538 data_time: 0.0304 memory: 16201 loss_prob: 0.4534 loss_thr: 0.3177 loss_db: 0.0804 loss: 0.8515 2022/08/30 13:48:07 - mmengine - INFO - Epoch(train) [602][35/63] lr: 3.7428e-03 eta: 13:48:50 time: 0.8377 data_time: 0.0230 memory: 16201 loss_prob: 0.4597 loss_thr: 0.3203 loss_db: 0.0797 loss: 0.8597 2022/08/30 13:48:11 - mmengine - INFO - Epoch(train) [602][40/63] lr: 3.7428e-03 eta: 13:48:32 time: 0.8649 data_time: 0.0293 memory: 16201 loss_prob: 0.4519 loss_thr: 0.3307 loss_db: 0.0777 loss: 0.8603 2022/08/30 13:48:15 - mmengine - INFO - Epoch(train) [602][45/63] lr: 3.7428e-03 eta: 13:48:32 time: 0.8599 data_time: 0.0339 memory: 16201 loss_prob: 0.4377 loss_thr: 0.3262 loss_db: 0.0784 loss: 0.8423 2022/08/30 13:48:19 - mmengine - INFO - Epoch(train) [602][50/63] lr: 3.7428e-03 eta: 13:48:14 time: 0.7934 data_time: 0.0216 memory: 16201 loss_prob: 0.4124 loss_thr: 0.2996 loss_db: 0.0743 loss: 0.7862 2022/08/30 13:48:23 - mmengine - INFO - Epoch(train) [602][55/63] lr: 3.7428e-03 eta: 13:48:14 time: 0.8071 data_time: 0.0263 memory: 16201 loss_prob: 0.4264 loss_thr: 0.3100 loss_db: 0.0724 loss: 0.8089 2022/08/30 13:48:27 - mmengine - INFO - Epoch(train) [602][60/63] lr: 3.7428e-03 eta: 13:47:56 time: 0.8225 data_time: 0.0318 memory: 16201 loss_prob: 0.4813 loss_thr: 0.3468 loss_db: 0.0814 loss: 0.9094 2022/08/30 13:48:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:48:35 - mmengine - INFO - Epoch(train) [603][5/63] lr: 3.7372e-03 eta: 13:47:56 time: 0.9003 data_time: 0.1656 memory: 16201 loss_prob: 0.5348 loss_thr: 0.3496 loss_db: 0.0884 loss: 0.9728 2022/08/30 13:48:39 - mmengine - INFO - Epoch(train) [603][10/63] lr: 3.7372e-03 eta: 13:47:31 time: 0.9739 data_time: 0.1785 memory: 16201 loss_prob: 0.4627 loss_thr: 0.3274 loss_db: 0.0811 loss: 0.8712 2022/08/30 13:48:44 - mmengine - INFO - Epoch(train) [603][15/63] lr: 3.7372e-03 eta: 13:47:31 time: 0.8729 data_time: 0.0269 memory: 16201 loss_prob: 0.4745 loss_thr: 0.3360 loss_db: 0.0824 loss: 0.8929 2022/08/30 13:48:48 - mmengine - INFO - Epoch(train) [603][20/63] lr: 3.7372e-03 eta: 13:47:13 time: 0.8518 data_time: 0.0211 memory: 16201 loss_prob: 0.4836 loss_thr: 0.3316 loss_db: 0.0830 loss: 0.8982 2022/08/30 13:48:52 - mmengine - INFO - Epoch(train) [603][25/63] lr: 3.7372e-03 eta: 13:47:13 time: 0.8462 data_time: 0.0373 memory: 16201 loss_prob: 0.5029 loss_thr: 0.3383 loss_db: 0.0879 loss: 0.9291 2022/08/30 13:48:56 - mmengine - INFO - Epoch(train) [603][30/63] lr: 3.7372e-03 eta: 13:46:55 time: 0.8363 data_time: 0.0272 memory: 16201 loss_prob: 0.4718 loss_thr: 0.3333 loss_db: 0.0845 loss: 0.8896 2022/08/30 13:49:00 - mmengine - INFO - Epoch(train) [603][35/63] lr: 3.7372e-03 eta: 13:46:55 time: 0.8159 data_time: 0.0207 memory: 16201 loss_prob: 0.5003 loss_thr: 0.3528 loss_db: 0.0875 loss: 0.9406 2022/08/30 13:49:05 - mmengine - INFO - Epoch(train) [603][40/63] lr: 3.7372e-03 eta: 13:46:37 time: 0.8431 data_time: 0.0271 memory: 16201 loss_prob: 0.5076 loss_thr: 0.3472 loss_db: 0.0882 loss: 0.9431 2022/08/30 13:49:09 - mmengine - INFO - Epoch(train) [603][45/63] lr: 3.7372e-03 eta: 13:46:37 time: 0.8383 data_time: 0.0229 memory: 16201 loss_prob: 0.4896 loss_thr: 0.3395 loss_db: 0.0866 loss: 0.9157 2022/08/30 13:49:13 - mmengine - INFO - Epoch(train) [603][50/63] lr: 3.7372e-03 eta: 13:46:20 time: 0.8670 data_time: 0.0251 memory: 16201 loss_prob: 0.5002 loss_thr: 0.3546 loss_db: 0.0880 loss: 0.9428 2022/08/30 13:49:17 - mmengine - INFO - Epoch(train) [603][55/63] lr: 3.7372e-03 eta: 13:46:20 time: 0.8669 data_time: 0.0279 memory: 16201 loss_prob: 0.4745 loss_thr: 0.3531 loss_db: 0.0837 loss: 0.9113 2022/08/30 13:49:22 - mmengine - INFO - Epoch(train) [603][60/63] lr: 3.7372e-03 eta: 13:46:03 time: 0.9182 data_time: 0.0813 memory: 16201 loss_prob: 0.4719 loss_thr: 0.3544 loss_db: 0.0834 loss: 0.9096 2022/08/30 13:49:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:49:30 - mmengine - INFO - Epoch(train) [604][5/63] lr: 3.7315e-03 eta: 13:46:03 time: 0.9415 data_time: 0.1956 memory: 16201 loss_prob: 0.5394 loss_thr: 0.3477 loss_db: 0.0908 loss: 0.9779 2022/08/30 13:49:34 - mmengine - INFO - Epoch(train) [604][10/63] lr: 3.7315e-03 eta: 13:45:38 time: 0.9913 data_time: 0.2034 memory: 16201 loss_prob: 0.5440 loss_thr: 0.3526 loss_db: 0.0896 loss: 0.9862 2022/08/30 13:49:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:49:38 - mmengine - INFO - Epoch(train) [604][15/63] lr: 3.7315e-03 eta: 13:45:38 time: 0.8141 data_time: 0.0290 memory: 16201 loss_prob: 0.4353 loss_thr: 0.3154 loss_db: 0.0741 loss: 0.8249 2022/08/30 13:49:43 - mmengine - INFO - Epoch(train) [604][20/63] lr: 3.7315e-03 eta: 13:45:20 time: 0.8313 data_time: 0.0188 memory: 16201 loss_prob: 0.4405 loss_thr: 0.3209 loss_db: 0.0769 loss: 0.8383 2022/08/30 13:49:47 - mmengine - INFO - Epoch(train) [604][25/63] lr: 3.7315e-03 eta: 13:45:20 time: 0.8562 data_time: 0.0327 memory: 16201 loss_prob: 0.4985 loss_thr: 0.3454 loss_db: 0.0875 loss: 0.9314 2022/08/30 13:49:51 - mmengine - INFO - Epoch(train) [604][30/63] lr: 3.7315e-03 eta: 13:45:02 time: 0.8256 data_time: 0.0266 memory: 16201 loss_prob: 0.5530 loss_thr: 0.3694 loss_db: 0.0956 loss: 1.0181 2022/08/30 13:49:55 - mmengine - INFO - Epoch(train) [604][35/63] lr: 3.7315e-03 eta: 13:45:02 time: 0.8369 data_time: 0.0199 memory: 16201 loss_prob: 0.5195 loss_thr: 0.3503 loss_db: 0.0908 loss: 0.9606 2022/08/30 13:50:00 - mmengine - INFO - Epoch(train) [604][40/63] lr: 3.7315e-03 eta: 13:44:45 time: 0.8603 data_time: 0.0293 memory: 16201 loss_prob: 0.4796 loss_thr: 0.3289 loss_db: 0.0851 loss: 0.8936 2022/08/30 13:50:04 - mmengine - INFO - Epoch(train) [604][45/63] lr: 3.7315e-03 eta: 13:44:45 time: 0.8597 data_time: 0.0322 memory: 16201 loss_prob: 0.5048 loss_thr: 0.3406 loss_db: 0.0871 loss: 0.9326 2022/08/30 13:50:08 - mmengine - INFO - Epoch(train) [604][50/63] lr: 3.7315e-03 eta: 13:44:27 time: 0.8290 data_time: 0.0277 memory: 16201 loss_prob: 0.5324 loss_thr: 0.3540 loss_db: 0.0903 loss: 0.9767 2022/08/30 13:50:13 - mmengine - INFO - Epoch(train) [604][55/63] lr: 3.7315e-03 eta: 13:44:27 time: 0.8717 data_time: 0.0324 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3360 loss_db: 0.0855 loss: 0.9109 2022/08/30 13:50:17 - mmengine - INFO - Epoch(train) [604][60/63] lr: 3.7315e-03 eta: 13:44:09 time: 0.8780 data_time: 0.0347 memory: 16201 loss_prob: 0.4359 loss_thr: 0.3132 loss_db: 0.0776 loss: 0.8266 2022/08/30 13:50:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:50:25 - mmengine - INFO - Epoch(train) [605][5/63] lr: 3.7259e-03 eta: 13:44:09 time: 0.9898 data_time: 0.2137 memory: 16201 loss_prob: 0.4767 loss_thr: 0.3425 loss_db: 0.0847 loss: 0.9039 2022/08/30 13:50:29 - mmengine - INFO - Epoch(train) [605][10/63] lr: 3.7259e-03 eta: 13:43:46 time: 1.0497 data_time: 0.2315 memory: 16201 loss_prob: 0.5103 loss_thr: 0.3532 loss_db: 0.0902 loss: 0.9537 2022/08/30 13:50:34 - mmengine - INFO - Epoch(train) [605][15/63] lr: 3.7259e-03 eta: 13:43:46 time: 0.8989 data_time: 0.0325 memory: 16201 loss_prob: 0.4511 loss_thr: 0.3134 loss_db: 0.0796 loss: 0.8441 2022/08/30 13:50:38 - mmengine - INFO - Epoch(train) [605][20/63] lr: 3.7259e-03 eta: 13:43:28 time: 0.8954 data_time: 0.0209 memory: 16201 loss_prob: 0.4403 loss_thr: 0.3106 loss_db: 0.0775 loss: 0.8285 2022/08/30 13:50:42 - mmengine - INFO - Epoch(train) [605][25/63] lr: 3.7259e-03 eta: 13:43:28 time: 0.8446 data_time: 0.0272 memory: 16201 loss_prob: 0.4318 loss_thr: 0.3192 loss_db: 0.0760 loss: 0.8270 2022/08/30 13:50:47 - mmengine - INFO - Epoch(train) [605][30/63] lr: 3.7259e-03 eta: 13:43:10 time: 0.8180 data_time: 0.0254 memory: 16201 loss_prob: 0.4439 loss_thr: 0.3365 loss_db: 0.0785 loss: 0.8589 2022/08/30 13:50:51 - mmengine - INFO - Epoch(train) [605][35/63] lr: 3.7259e-03 eta: 13:43:10 time: 0.8783 data_time: 0.0217 memory: 16201 loss_prob: 0.4449 loss_thr: 0.3302 loss_db: 0.0781 loss: 0.8532 2022/08/30 13:50:55 - mmengine - INFO - Epoch(train) [605][40/63] lr: 3.7259e-03 eta: 13:42:53 time: 0.8947 data_time: 0.0247 memory: 16201 loss_prob: 0.4407 loss_thr: 0.3079 loss_db: 0.0766 loss: 0.8252 2022/08/30 13:51:00 - mmengine - INFO - Epoch(train) [605][45/63] lr: 3.7259e-03 eta: 13:42:53 time: 0.8354 data_time: 0.0307 memory: 16201 loss_prob: 0.4861 loss_thr: 0.3257 loss_db: 0.0843 loss: 0.8961 2022/08/30 13:51:04 - mmengine - INFO - Epoch(train) [605][50/63] lr: 3.7259e-03 eta: 13:42:35 time: 0.8277 data_time: 0.0297 memory: 16201 loss_prob: 0.4859 loss_thr: 0.3405 loss_db: 0.0845 loss: 0.9109 2022/08/30 13:51:08 - mmengine - INFO - Epoch(train) [605][55/63] lr: 3.7259e-03 eta: 13:42:35 time: 0.7928 data_time: 0.0286 memory: 16201 loss_prob: 0.5051 loss_thr: 0.3530 loss_db: 0.0877 loss: 0.9458 2022/08/30 13:51:12 - mmengine - INFO - Epoch(train) [605][60/63] lr: 3.7259e-03 eta: 13:42:17 time: 0.7902 data_time: 0.0262 memory: 16201 loss_prob: 0.5390 loss_thr: 0.3664 loss_db: 0.0935 loss: 0.9990 2022/08/30 13:51:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:51:20 - mmengine - INFO - Epoch(train) [606][5/63] lr: 3.7203e-03 eta: 13:42:17 time: 0.9963 data_time: 0.2139 memory: 16201 loss_prob: 0.5258 loss_thr: 0.3650 loss_db: 0.0914 loss: 0.9822 2022/08/30 13:51:25 - mmengine - INFO - Epoch(train) [606][10/63] lr: 3.7203e-03 eta: 13:41:53 time: 1.0745 data_time: 0.2251 memory: 16201 loss_prob: 0.4422 loss_thr: 0.3208 loss_db: 0.0773 loss: 0.8404 2022/08/30 13:51:29 - mmengine - INFO - Epoch(train) [606][15/63] lr: 3.7203e-03 eta: 13:41:53 time: 0.8520 data_time: 0.0247 memory: 16201 loss_prob: 0.4477 loss_thr: 0.3209 loss_db: 0.0796 loss: 0.8481 2022/08/30 13:51:33 - mmengine - INFO - Epoch(train) [606][20/63] lr: 3.7203e-03 eta: 13:41:36 time: 0.8748 data_time: 0.0150 memory: 16201 loss_prob: 0.5349 loss_thr: 0.3655 loss_db: 0.0930 loss: 0.9933 2022/08/30 13:51:38 - mmengine - INFO - Epoch(train) [606][25/63] lr: 3.7203e-03 eta: 13:41:36 time: 0.9061 data_time: 0.0343 memory: 16201 loss_prob: 0.5014 loss_thr: 0.3493 loss_db: 0.0877 loss: 0.9384 2022/08/30 13:51:42 - mmengine - INFO - Epoch(train) [606][30/63] lr: 3.7203e-03 eta: 13:41:18 time: 0.8480 data_time: 0.0264 memory: 16201 loss_prob: 0.4740 loss_thr: 0.3313 loss_db: 0.0837 loss: 0.8891 2022/08/30 13:51:46 - mmengine - INFO - Epoch(train) [606][35/63] lr: 3.7203e-03 eta: 13:41:18 time: 0.8444 data_time: 0.0184 memory: 16201 loss_prob: 0.4879 loss_thr: 0.3388 loss_db: 0.0863 loss: 0.9130 2022/08/30 13:51:50 - mmengine - INFO - Epoch(train) [606][40/63] lr: 3.7203e-03 eta: 13:41:00 time: 0.8157 data_time: 0.0267 memory: 16201 loss_prob: 0.4448 loss_thr: 0.3235 loss_db: 0.0783 loss: 0.8465 2022/08/30 13:51:54 - mmengine - INFO - Epoch(train) [606][45/63] lr: 3.7203e-03 eta: 13:41:00 time: 0.8206 data_time: 0.0274 memory: 16201 loss_prob: 0.4540 loss_thr: 0.3345 loss_db: 0.0798 loss: 0.8684 2022/08/30 13:51:58 - mmengine - INFO - Epoch(train) [606][50/63] lr: 3.7203e-03 eta: 13:40:42 time: 0.8330 data_time: 0.0273 memory: 16201 loss_prob: 0.4791 loss_thr: 0.3366 loss_db: 0.0844 loss: 0.9001 2022/08/30 13:52:02 - mmengine - INFO - Epoch(train) [606][55/63] lr: 3.7203e-03 eta: 13:40:42 time: 0.8119 data_time: 0.0223 memory: 16201 loss_prob: 0.4440 loss_thr: 0.3222 loss_db: 0.0769 loss: 0.8431 2022/08/30 13:52:07 - mmengine - INFO - Epoch(train) [606][60/63] lr: 3.7203e-03 eta: 13:40:24 time: 0.8245 data_time: 0.0290 memory: 16201 loss_prob: 0.4762 loss_thr: 0.3490 loss_db: 0.0853 loss: 0.9105 2022/08/30 13:52:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:52:14 - mmengine - INFO - Epoch(train) [607][5/63] lr: 3.7146e-03 eta: 13:40:24 time: 0.9457 data_time: 0.2093 memory: 16201 loss_prob: 0.4671 loss_thr: 0.3238 loss_db: 0.0815 loss: 0.8724 2022/08/30 13:52:18 - mmengine - INFO - Epoch(train) [607][10/63] lr: 3.7146e-03 eta: 13:40:00 time: 0.9978 data_time: 0.2246 memory: 16201 loss_prob: 0.4580 loss_thr: 0.3286 loss_db: 0.0794 loss: 0.8660 2022/08/30 13:52:22 - mmengine - INFO - Epoch(train) [607][15/63] lr: 3.7146e-03 eta: 13:40:00 time: 0.7961 data_time: 0.0280 memory: 16201 loss_prob: 0.4772 loss_thr: 0.3465 loss_db: 0.0854 loss: 0.9091 2022/08/30 13:52:26 - mmengine - INFO - Epoch(train) [607][20/63] lr: 3.7146e-03 eta: 13:39:42 time: 0.7990 data_time: 0.0172 memory: 16201 loss_prob: 0.4729 loss_thr: 0.3306 loss_db: 0.0853 loss: 0.8887 2022/08/30 13:52:31 - mmengine - INFO - Epoch(train) [607][25/63] lr: 3.7146e-03 eta: 13:39:42 time: 0.8363 data_time: 0.0351 memory: 16201 loss_prob: 0.4731 loss_thr: 0.3082 loss_db: 0.0807 loss: 0.8620 2022/08/30 13:52:35 - mmengine - INFO - Epoch(train) [607][30/63] lr: 3.7146e-03 eta: 13:39:24 time: 0.8390 data_time: 0.0286 memory: 16201 loss_prob: 0.4939 loss_thr: 0.3277 loss_db: 0.0832 loss: 0.9049 2022/08/30 13:52:39 - mmengine - INFO - Epoch(train) [607][35/63] lr: 3.7146e-03 eta: 13:39:24 time: 0.8122 data_time: 0.0190 memory: 16201 loss_prob: 0.4941 loss_thr: 0.3479 loss_db: 0.0852 loss: 0.9271 2022/08/30 13:52:43 - mmengine - INFO - Epoch(train) [607][40/63] lr: 3.7146e-03 eta: 13:39:06 time: 0.8329 data_time: 0.0276 memory: 16201 loss_prob: 0.4539 loss_thr: 0.3162 loss_db: 0.0799 loss: 0.8501 2022/08/30 13:52:47 - mmengine - INFO - Epoch(train) [607][45/63] lr: 3.7146e-03 eta: 13:39:06 time: 0.8500 data_time: 0.0258 memory: 16201 loss_prob: 0.4337 loss_thr: 0.3121 loss_db: 0.0775 loss: 0.8233 2022/08/30 13:52:52 - mmengine - INFO - Epoch(train) [607][50/63] lr: 3.7146e-03 eta: 13:38:49 time: 0.8715 data_time: 0.0281 memory: 16201 loss_prob: 0.4562 loss_thr: 0.3357 loss_db: 0.0786 loss: 0.8705 2022/08/30 13:52:56 - mmengine - INFO - Epoch(train) [607][55/63] lr: 3.7146e-03 eta: 13:38:49 time: 0.8417 data_time: 0.0261 memory: 16201 loss_prob: 0.5208 loss_thr: 0.3640 loss_db: 0.0904 loss: 0.9752 2022/08/30 13:53:00 - mmengine - INFO - Epoch(train) [607][60/63] lr: 3.7146e-03 eta: 13:38:31 time: 0.8435 data_time: 0.0258 memory: 16201 loss_prob: 0.4963 loss_thr: 0.3377 loss_db: 0.0872 loss: 0.9212 2022/08/30 13:53:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:53:09 - mmengine - INFO - Epoch(train) [608][5/63] lr: 3.7090e-03 eta: 13:38:31 time: 0.9734 data_time: 0.2137 memory: 16201 loss_prob: 0.4232 loss_thr: 0.2988 loss_db: 0.0748 loss: 0.7968 2022/08/30 13:53:13 - mmengine - INFO - Epoch(train) [608][10/63] lr: 3.7090e-03 eta: 13:38:07 time: 1.0222 data_time: 0.2308 memory: 16201 loss_prob: 0.4508 loss_thr: 0.3170 loss_db: 0.0788 loss: 0.8466 2022/08/30 13:53:17 - mmengine - INFO - Epoch(train) [608][15/63] lr: 3.7090e-03 eta: 13:38:07 time: 0.8847 data_time: 0.0455 memory: 16201 loss_prob: 0.5393 loss_thr: 0.3577 loss_db: 0.0915 loss: 0.9885 2022/08/30 13:53:22 - mmengine - INFO - Epoch(train) [608][20/63] lr: 3.7090e-03 eta: 13:37:50 time: 0.8946 data_time: 0.0378 memory: 16201 loss_prob: 0.5258 loss_thr: 0.3493 loss_db: 0.0905 loss: 0.9656 2022/08/30 13:53:26 - mmengine - INFO - Epoch(train) [608][25/63] lr: 3.7090e-03 eta: 13:37:50 time: 0.8509 data_time: 0.0365 memory: 16201 loss_prob: 0.4536 loss_thr: 0.3306 loss_db: 0.0790 loss: 0.8631 2022/08/30 13:53:30 - mmengine - INFO - Epoch(train) [608][30/63] lr: 3.7090e-03 eta: 13:37:32 time: 0.8519 data_time: 0.0285 memory: 16201 loss_prob: 0.4157 loss_thr: 0.3097 loss_db: 0.0722 loss: 0.7977 2022/08/30 13:53:35 - mmengine - INFO - Epoch(train) [608][35/63] lr: 3.7090e-03 eta: 13:37:32 time: 0.8642 data_time: 0.0247 memory: 16201 loss_prob: 0.4484 loss_thr: 0.3110 loss_db: 0.0777 loss: 0.8371 2022/08/30 13:53:39 - mmengine - INFO - Epoch(train) [608][40/63] lr: 3.7090e-03 eta: 13:37:14 time: 0.8479 data_time: 0.0329 memory: 16201 loss_prob: 0.4808 loss_thr: 0.3266 loss_db: 0.0848 loss: 0.8922 2022/08/30 13:53:43 - mmengine - INFO - Epoch(train) [608][45/63] lr: 3.7090e-03 eta: 13:37:14 time: 0.8490 data_time: 0.0350 memory: 16201 loss_prob: 0.4755 loss_thr: 0.3330 loss_db: 0.0823 loss: 0.8909 2022/08/30 13:53:47 - mmengine - INFO - Epoch(train) [608][50/63] lr: 3.7090e-03 eta: 13:36:57 time: 0.8417 data_time: 0.0313 memory: 16201 loss_prob: 0.4836 loss_thr: 0.3419 loss_db: 0.0829 loss: 0.9085 2022/08/30 13:53:52 - mmengine - INFO - Epoch(train) [608][55/63] lr: 3.7090e-03 eta: 13:36:57 time: 0.8515 data_time: 0.0248 memory: 16201 loss_prob: 0.4698 loss_thr: 0.3269 loss_db: 0.0833 loss: 0.8801 2022/08/30 13:53:56 - mmengine - INFO - Epoch(train) [608][60/63] lr: 3.7090e-03 eta: 13:36:39 time: 0.8764 data_time: 0.0297 memory: 16201 loss_prob: 0.4309 loss_thr: 0.3105 loss_db: 0.0765 loss: 0.8180 2022/08/30 13:53:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:54:04 - mmengine - INFO - Epoch(train) [609][5/63] lr: 3.7034e-03 eta: 13:36:39 time: 0.9992 data_time: 0.2148 memory: 16201 loss_prob: 0.4342 loss_thr: 0.3102 loss_db: 0.0739 loss: 0.8183 2022/08/30 13:54:09 - mmengine - INFO - Epoch(train) [609][10/63] lr: 3.7034e-03 eta: 13:36:16 time: 1.0653 data_time: 0.2292 memory: 16201 loss_prob: 0.4606 loss_thr: 0.3271 loss_db: 0.0783 loss: 0.8660 2022/08/30 13:54:13 - mmengine - INFO - Epoch(train) [609][15/63] lr: 3.7034e-03 eta: 13:36:16 time: 0.8776 data_time: 0.0326 memory: 16201 loss_prob: 0.4746 loss_thr: 0.3344 loss_db: 0.0832 loss: 0.8922 2022/08/30 13:54:17 - mmengine - INFO - Epoch(train) [609][20/63] lr: 3.7034e-03 eta: 13:35:58 time: 0.8629 data_time: 0.0251 memory: 16201 loss_prob: 0.4807 loss_thr: 0.3453 loss_db: 0.0850 loss: 0.9110 2022/08/30 13:54:22 - mmengine - INFO - Epoch(train) [609][25/63] lr: 3.7034e-03 eta: 13:35:58 time: 0.8557 data_time: 0.0278 memory: 16201 loss_prob: 0.4913 loss_thr: 0.3522 loss_db: 0.0880 loss: 0.9314 2022/08/30 13:54:26 - mmengine - INFO - Epoch(train) [609][30/63] lr: 3.7034e-03 eta: 13:35:41 time: 0.8540 data_time: 0.0253 memory: 16201 loss_prob: 0.5108 loss_thr: 0.3528 loss_db: 0.0910 loss: 0.9546 2022/08/30 13:54:30 - mmengine - INFO - Epoch(train) [609][35/63] lr: 3.7034e-03 eta: 13:35:41 time: 0.8665 data_time: 0.0257 memory: 16201 loss_prob: 0.4794 loss_thr: 0.3369 loss_db: 0.0834 loss: 0.8997 2022/08/30 13:54:35 - mmengine - INFO - Epoch(train) [609][40/63] lr: 3.7034e-03 eta: 13:35:23 time: 0.8680 data_time: 0.0264 memory: 16201 loss_prob: 0.4214 loss_thr: 0.3131 loss_db: 0.0739 loss: 0.8085 2022/08/30 13:54:39 - mmengine - INFO - Epoch(train) [609][45/63] lr: 3.7034e-03 eta: 13:35:23 time: 0.8570 data_time: 0.0259 memory: 16201 loss_prob: 0.4113 loss_thr: 0.3009 loss_db: 0.0718 loss: 0.7839 2022/08/30 13:54:43 - mmengine - INFO - Epoch(train) [609][50/63] lr: 3.7034e-03 eta: 13:35:06 time: 0.8499 data_time: 0.0256 memory: 16201 loss_prob: 0.4626 loss_thr: 0.3299 loss_db: 0.0787 loss: 0.8713 2022/08/30 13:54:47 - mmengine - INFO - Epoch(train) [609][55/63] lr: 3.7034e-03 eta: 13:35:06 time: 0.8349 data_time: 0.0242 memory: 16201 loss_prob: 0.4680 loss_thr: 0.3382 loss_db: 0.0800 loss: 0.8862 2022/08/30 13:54:53 - mmengine - INFO - Epoch(train) [609][60/63] lr: 3.7034e-03 eta: 13:34:49 time: 0.9558 data_time: 0.0230 memory: 16201 loss_prob: 0.4455 loss_thr: 0.3182 loss_db: 0.0781 loss: 0.8418 2022/08/30 13:54:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:55:01 - mmengine - INFO - Epoch(train) [610][5/63] lr: 3.6977e-03 eta: 13:34:49 time: 1.1280 data_time: 0.2069 memory: 16201 loss_prob: 0.5214 loss_thr: 0.3680 loss_db: 0.0903 loss: 0.9797 2022/08/30 13:55:05 - mmengine - INFO - Epoch(train) [610][10/63] lr: 3.6977e-03 eta: 13:34:26 time: 1.0499 data_time: 0.2126 memory: 16201 loss_prob: 0.4390 loss_thr: 0.3355 loss_db: 0.0761 loss: 0.8506 2022/08/30 13:55:09 - mmengine - INFO - Epoch(train) [610][15/63] lr: 3.6977e-03 eta: 13:34:26 time: 0.8436 data_time: 0.0261 memory: 16201 loss_prob: 0.4184 loss_thr: 0.3145 loss_db: 0.0749 loss: 0.8077 2022/08/30 13:55:15 - mmengine - INFO - Epoch(train) [610][20/63] lr: 3.6977e-03 eta: 13:34:09 time: 0.9127 data_time: 0.0247 memory: 16201 loss_prob: 0.4233 loss_thr: 0.3141 loss_db: 0.0754 loss: 0.8127 2022/08/30 13:55:19 - mmengine - INFO - Epoch(train) [610][25/63] lr: 3.6977e-03 eta: 13:34:09 time: 0.9325 data_time: 0.0272 memory: 16201 loss_prob: 0.4451 loss_thr: 0.3184 loss_db: 0.0759 loss: 0.8395 2022/08/30 13:55:23 - mmengine - INFO - Epoch(train) [610][30/63] lr: 3.6977e-03 eta: 13:33:51 time: 0.8865 data_time: 0.0275 memory: 16201 loss_prob: 0.4460 loss_thr: 0.3231 loss_db: 0.0762 loss: 0.8452 2022/08/30 13:55:28 - mmengine - INFO - Epoch(train) [610][35/63] lr: 3.6977e-03 eta: 13:33:51 time: 0.8712 data_time: 0.0263 memory: 16201 loss_prob: 0.5044 loss_thr: 0.3213 loss_db: 0.0886 loss: 0.9143 2022/08/30 13:55:32 - mmengine - INFO - Epoch(train) [610][40/63] lr: 3.6977e-03 eta: 13:33:34 time: 0.9058 data_time: 0.0350 memory: 16201 loss_prob: 0.5166 loss_thr: 0.3116 loss_db: 0.0887 loss: 0.9169 2022/08/30 13:55:37 - mmengine - INFO - Epoch(train) [610][45/63] lr: 3.6977e-03 eta: 13:33:34 time: 0.9256 data_time: 0.0464 memory: 16201 loss_prob: 0.4557 loss_thr: 0.3218 loss_db: 0.0795 loss: 0.8570 2022/08/30 13:55:41 - mmengine - INFO - Epoch(train) [610][50/63] lr: 3.6977e-03 eta: 13:33:17 time: 0.8428 data_time: 0.0364 memory: 16201 loss_prob: 0.4747 loss_thr: 0.3429 loss_db: 0.0863 loss: 0.9038 2022/08/30 13:55:45 - mmengine - INFO - Epoch(train) [610][55/63] lr: 3.6977e-03 eta: 13:33:17 time: 0.8667 data_time: 0.0297 memory: 16201 loss_prob: 0.4956 loss_thr: 0.3506 loss_db: 0.0891 loss: 0.9354 2022/08/30 13:55:50 - mmengine - INFO - Epoch(train) [610][60/63] lr: 3.6977e-03 eta: 13:32:59 time: 0.8733 data_time: 0.0317 memory: 16201 loss_prob: 0.4951 loss_thr: 0.3461 loss_db: 0.0869 loss: 0.9282 2022/08/30 13:55:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:55:58 - mmengine - INFO - Epoch(train) [611][5/63] lr: 3.6921e-03 eta: 13:32:59 time: 0.9943 data_time: 0.2206 memory: 16201 loss_prob: 0.4612 loss_thr: 0.3327 loss_db: 0.0805 loss: 0.8744 2022/08/30 13:56:02 - mmengine - INFO - Epoch(train) [611][10/63] lr: 3.6921e-03 eta: 13:32:36 time: 1.0528 data_time: 0.2294 memory: 16201 loss_prob: 0.4786 loss_thr: 0.3441 loss_db: 0.0848 loss: 0.9074 2022/08/30 13:56:06 - mmengine - INFO - Epoch(train) [611][15/63] lr: 3.6921e-03 eta: 13:32:36 time: 0.8505 data_time: 0.0328 memory: 16201 loss_prob: 0.4948 loss_thr: 0.3486 loss_db: 0.0881 loss: 0.9315 2022/08/30 13:56:10 - mmengine - INFO - Epoch(train) [611][20/63] lr: 3.6921e-03 eta: 13:32:18 time: 0.8240 data_time: 0.0304 memory: 16201 loss_prob: 0.4958 loss_thr: 0.3393 loss_db: 0.0882 loss: 0.9234 2022/08/30 13:56:15 - mmengine - INFO - Epoch(train) [611][25/63] lr: 3.6921e-03 eta: 13:32:18 time: 0.8129 data_time: 0.0299 memory: 16201 loss_prob: 0.4742 loss_thr: 0.3324 loss_db: 0.0827 loss: 0.8893 2022/08/30 13:56:19 - mmengine - INFO - Epoch(train) [611][30/63] lr: 3.6921e-03 eta: 13:32:00 time: 0.8071 data_time: 0.0271 memory: 16201 loss_prob: 0.4497 loss_thr: 0.3180 loss_db: 0.0777 loss: 0.8454 2022/08/30 13:56:23 - mmengine - INFO - Epoch(train) [611][35/63] lr: 3.6921e-03 eta: 13:32:00 time: 0.8007 data_time: 0.0262 memory: 16201 loss_prob: 0.4471 loss_thr: 0.3060 loss_db: 0.0773 loss: 0.8304 2022/08/30 13:56:27 - mmengine - INFO - Epoch(train) [611][40/63] lr: 3.6921e-03 eta: 13:31:42 time: 0.8134 data_time: 0.0339 memory: 16201 loss_prob: 0.4561 loss_thr: 0.3136 loss_db: 0.0771 loss: 0.8468 2022/08/30 13:56:31 - mmengine - INFO - Epoch(train) [611][45/63] lr: 3.6921e-03 eta: 13:31:42 time: 0.8504 data_time: 0.0347 memory: 16201 loss_prob: 0.4409 loss_thr: 0.3178 loss_db: 0.0760 loss: 0.8347 2022/08/30 13:56:35 - mmengine - INFO - Epoch(train) [611][50/63] lr: 3.6921e-03 eta: 13:31:25 time: 0.8562 data_time: 0.0263 memory: 16201 loss_prob: 0.4223 loss_thr: 0.3075 loss_db: 0.0748 loss: 0.8046 2022/08/30 13:56:39 - mmengine - INFO - Epoch(train) [611][55/63] lr: 3.6921e-03 eta: 13:31:25 time: 0.8367 data_time: 0.0302 memory: 16201 loss_prob: 0.4407 loss_thr: 0.3033 loss_db: 0.0769 loss: 0.8210 2022/08/30 13:56:44 - mmengine - INFO - Epoch(train) [611][60/63] lr: 3.6921e-03 eta: 13:31:07 time: 0.8529 data_time: 0.0372 memory: 16201 loss_prob: 0.4619 loss_thr: 0.3124 loss_db: 0.0786 loss: 0.8529 2022/08/30 13:56:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:56:53 - mmengine - INFO - Epoch(train) [612][5/63] lr: 3.6864e-03 eta: 13:31:07 time: 1.0949 data_time: 0.2826 memory: 16201 loss_prob: 0.4647 loss_thr: 0.3341 loss_db: 0.0821 loss: 0.8809 2022/08/30 13:56:57 - mmengine - INFO - Epoch(train) [612][10/63] lr: 3.6864e-03 eta: 13:30:45 time: 1.1417 data_time: 0.2909 memory: 16201 loss_prob: 0.4431 loss_thr: 0.3219 loss_db: 0.0767 loss: 0.8417 2022/08/30 13:57:02 - mmengine - INFO - Epoch(train) [612][15/63] lr: 3.6864e-03 eta: 13:30:45 time: 0.8341 data_time: 0.0315 memory: 16201 loss_prob: 0.5265 loss_thr: 0.3463 loss_db: 0.0888 loss: 0.9616 2022/08/30 13:57:06 - mmengine - INFO - Epoch(train) [612][20/63] lr: 3.6864e-03 eta: 13:30:27 time: 0.8463 data_time: 0.0241 memory: 16201 loss_prob: 0.5167 loss_thr: 0.3468 loss_db: 0.0893 loss: 0.9529 2022/08/30 13:57:10 - mmengine - INFO - Epoch(train) [612][25/63] lr: 3.6864e-03 eta: 13:30:27 time: 0.8706 data_time: 0.0357 memory: 16201 loss_prob: 0.4588 loss_thr: 0.3245 loss_db: 0.0802 loss: 0.8635 2022/08/30 13:57:14 - mmengine - INFO - Epoch(train) [612][30/63] lr: 3.6864e-03 eta: 13:30:10 time: 0.8589 data_time: 0.0344 memory: 16201 loss_prob: 0.5184 loss_thr: 0.3478 loss_db: 0.0866 loss: 0.9529 2022/08/30 13:57:19 - mmengine - INFO - Epoch(train) [612][35/63] lr: 3.6864e-03 eta: 13:30:10 time: 0.8378 data_time: 0.0235 memory: 16201 loss_prob: 0.5125 loss_thr: 0.3485 loss_db: 0.0880 loss: 0.9491 2022/08/30 13:57:23 - mmengine - INFO - Epoch(train) [612][40/63] lr: 3.6864e-03 eta: 13:29:52 time: 0.8509 data_time: 0.0257 memory: 16201 loss_prob: 0.5192 loss_thr: 0.3693 loss_db: 0.0911 loss: 0.9796 2022/08/30 13:57:27 - mmengine - INFO - Epoch(train) [612][45/63] lr: 3.6864e-03 eta: 13:29:52 time: 0.8680 data_time: 0.0275 memory: 16201 loss_prob: 0.5027 loss_thr: 0.3625 loss_db: 0.0855 loss: 0.9507 2022/08/30 13:57:33 - mmengine - INFO - Epoch(train) [612][50/63] lr: 3.6864e-03 eta: 13:29:36 time: 0.9844 data_time: 0.0286 memory: 16201 loss_prob: 0.4817 loss_thr: 0.3330 loss_db: 0.0826 loss: 0.8973 2022/08/30 13:57:37 - mmengine - INFO - Epoch(train) [612][55/63] lr: 3.6864e-03 eta: 13:29:36 time: 0.9740 data_time: 0.0294 memory: 16201 loss_prob: 0.5158 loss_thr: 0.3488 loss_db: 0.0899 loss: 0.9544 2022/08/30 13:57:41 - mmengine - INFO - Epoch(train) [612][60/63] lr: 3.6864e-03 eta: 13:29:18 time: 0.8463 data_time: 0.0320 memory: 16201 loss_prob: 0.4609 loss_thr: 0.3258 loss_db: 0.0818 loss: 0.8686 2022/08/30 13:57:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:57:50 - mmengine - INFO - Epoch(train) [613][5/63] lr: 3.6808e-03 eta: 13:29:18 time: 1.0527 data_time: 0.2536 memory: 16201 loss_prob: 0.4581 loss_thr: 0.3219 loss_db: 0.0802 loss: 0.8602 2022/08/30 13:57:54 - mmengine - INFO - Epoch(train) [613][10/63] lr: 3.6808e-03 eta: 13:28:55 time: 1.0904 data_time: 0.2635 memory: 16201 loss_prob: 0.4836 loss_thr: 0.3336 loss_db: 0.0841 loss: 0.9013 2022/08/30 13:57:59 - mmengine - INFO - Epoch(train) [613][15/63] lr: 3.6808e-03 eta: 13:28:55 time: 0.8395 data_time: 0.0297 memory: 16201 loss_prob: 0.4900 loss_thr: 0.3271 loss_db: 0.0844 loss: 0.9015 2022/08/30 13:58:04 - mmengine - INFO - Epoch(train) [613][20/63] lr: 3.6808e-03 eta: 13:28:39 time: 0.9267 data_time: 0.0375 memory: 16201 loss_prob: 0.5024 loss_thr: 0.3358 loss_db: 0.0873 loss: 0.9256 2022/08/30 13:58:08 - mmengine - INFO - Epoch(train) [613][25/63] lr: 3.6808e-03 eta: 13:28:39 time: 0.9378 data_time: 0.0413 memory: 16201 loss_prob: 0.4739 loss_thr: 0.3235 loss_db: 0.0841 loss: 0.8815 2022/08/30 13:58:12 - mmengine - INFO - Epoch(train) [613][30/63] lr: 3.6808e-03 eta: 13:28:21 time: 0.8266 data_time: 0.0270 memory: 16201 loss_prob: 0.4362 loss_thr: 0.3149 loss_db: 0.0749 loss: 0.8260 2022/08/30 13:58:16 - mmengine - INFO - Epoch(train) [613][35/63] lr: 3.6808e-03 eta: 13:28:21 time: 0.8366 data_time: 0.0293 memory: 16201 loss_prob: 0.4296 loss_thr: 0.3179 loss_db: 0.0736 loss: 0.8211 2022/08/30 13:58:20 - mmengine - INFO - Epoch(train) [613][40/63] lr: 3.6808e-03 eta: 13:28:03 time: 0.8365 data_time: 0.0286 memory: 16201 loss_prob: 0.4529 loss_thr: 0.3252 loss_db: 0.0792 loss: 0.8573 2022/08/30 13:58:25 - mmengine - INFO - Epoch(train) [613][45/63] lr: 3.6808e-03 eta: 13:28:03 time: 0.8649 data_time: 0.0322 memory: 16201 loss_prob: 0.4344 loss_thr: 0.3149 loss_db: 0.0766 loss: 0.8260 2022/08/30 13:58:29 - mmengine - INFO - Epoch(train) [613][50/63] lr: 3.6808e-03 eta: 13:27:46 time: 0.8950 data_time: 0.0345 memory: 16201 loss_prob: 0.4317 loss_thr: 0.3062 loss_db: 0.0751 loss: 0.8130 2022/08/30 13:58:34 - mmengine - INFO - Epoch(train) [613][55/63] lr: 3.6808e-03 eta: 13:27:46 time: 0.8599 data_time: 0.0403 memory: 16201 loss_prob: 0.4269 loss_thr: 0.3006 loss_db: 0.0740 loss: 0.8015 2022/08/30 13:58:38 - mmengine - INFO - Epoch(train) [613][60/63] lr: 3.6808e-03 eta: 13:27:29 time: 0.8506 data_time: 0.0429 memory: 16201 loss_prob: 0.4269 loss_thr: 0.3031 loss_db: 0.0758 loss: 0.8058 2022/08/30 13:58:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:58:47 - mmengine - INFO - Epoch(train) [614][5/63] lr: 3.6751e-03 eta: 13:27:29 time: 1.0482 data_time: 0.2449 memory: 16201 loss_prob: 0.4627 loss_thr: 0.3355 loss_db: 0.0806 loss: 0.8788 2022/08/30 13:58:51 - mmengine - INFO - Epoch(train) [614][10/63] lr: 3.6751e-03 eta: 13:27:06 time: 1.1221 data_time: 0.2597 memory: 16201 loss_prob: 0.4658 loss_thr: 0.3416 loss_db: 0.0808 loss: 0.8882 2022/08/30 13:58:55 - mmengine - INFO - Epoch(train) [614][15/63] lr: 3.6751e-03 eta: 13:27:06 time: 0.8756 data_time: 0.0312 memory: 16201 loss_prob: 0.4805 loss_thr: 0.3471 loss_db: 0.0844 loss: 0.9120 2022/08/30 13:59:00 - mmengine - INFO - Epoch(train) [614][20/63] lr: 3.6751e-03 eta: 13:26:48 time: 0.8292 data_time: 0.0204 memory: 16201 loss_prob: 0.4340 loss_thr: 0.3165 loss_db: 0.0774 loss: 0.8278 2022/08/30 13:59:04 - mmengine - INFO - Epoch(train) [614][25/63] lr: 3.6751e-03 eta: 13:26:48 time: 0.8445 data_time: 0.0313 memory: 16201 loss_prob: 0.4409 loss_thr: 0.3153 loss_db: 0.0777 loss: 0.8339 2022/08/30 13:59:08 - mmengine - INFO - Epoch(train) [614][30/63] lr: 3.6751e-03 eta: 13:26:31 time: 0.8393 data_time: 0.0312 memory: 16201 loss_prob: 0.4569 loss_thr: 0.3298 loss_db: 0.0808 loss: 0.8676 2022/08/30 13:59:12 - mmengine - INFO - Epoch(train) [614][35/63] lr: 3.6751e-03 eta: 13:26:31 time: 0.8396 data_time: 0.0207 memory: 16201 loss_prob: 0.4371 loss_thr: 0.3133 loss_db: 0.0771 loss: 0.8275 2022/08/30 13:59:17 - mmengine - INFO - Epoch(train) [614][40/63] lr: 3.6751e-03 eta: 13:26:13 time: 0.8650 data_time: 0.0269 memory: 16201 loss_prob: 0.4084 loss_thr: 0.3012 loss_db: 0.0718 loss: 0.7815 2022/08/30 13:59:21 - mmengine - INFO - Epoch(train) [614][45/63] lr: 3.6751e-03 eta: 13:26:13 time: 0.8661 data_time: 0.0289 memory: 16201 loss_prob: 0.4185 loss_thr: 0.3085 loss_db: 0.0754 loss: 0.8024 2022/08/30 13:59:25 - mmengine - INFO - Epoch(train) [614][50/63] lr: 3.6751e-03 eta: 13:25:56 time: 0.8678 data_time: 0.0278 memory: 16201 loss_prob: 0.4727 loss_thr: 0.3265 loss_db: 0.0828 loss: 0.8821 2022/08/30 13:59:30 - mmengine - INFO - Epoch(train) [614][55/63] lr: 3.6751e-03 eta: 13:25:56 time: 0.8701 data_time: 0.0319 memory: 16201 loss_prob: 0.4655 loss_thr: 0.3336 loss_db: 0.0808 loss: 0.8799 2022/08/30 13:59:34 - mmengine - INFO - Epoch(train) [614][60/63] lr: 3.6751e-03 eta: 13:25:39 time: 0.8755 data_time: 0.0303 memory: 16201 loss_prob: 0.4205 loss_thr: 0.3095 loss_db: 0.0750 loss: 0.8051 2022/08/30 13:59:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 13:59:42 - mmengine - INFO - Epoch(train) [615][5/63] lr: 3.6695e-03 eta: 13:25:39 time: 0.9879 data_time: 0.2174 memory: 16201 loss_prob: 0.4262 loss_thr: 0.3141 loss_db: 0.0756 loss: 0.8159 2022/08/30 13:59:46 - mmengine - INFO - Epoch(train) [615][10/63] lr: 3.6695e-03 eta: 13:25:16 time: 1.0424 data_time: 0.2313 memory: 16201 loss_prob: 0.4188 loss_thr: 0.3082 loss_db: 0.0745 loss: 0.8015 2022/08/30 13:59:51 - mmengine - INFO - Epoch(train) [615][15/63] lr: 3.6695e-03 eta: 13:25:16 time: 0.8453 data_time: 0.0280 memory: 16201 loss_prob: 0.4235 loss_thr: 0.3004 loss_db: 0.0765 loss: 0.8004 2022/08/30 13:59:55 - mmengine - INFO - Epoch(train) [615][20/63] lr: 3.6695e-03 eta: 13:24:59 time: 0.9033 data_time: 0.0274 memory: 16201 loss_prob: 0.4596 loss_thr: 0.3167 loss_db: 0.0800 loss: 0.8563 2022/08/30 14:00:00 - mmengine - INFO - Epoch(train) [615][25/63] lr: 3.6695e-03 eta: 13:24:59 time: 0.8992 data_time: 0.0350 memory: 16201 loss_prob: 0.4636 loss_thr: 0.3208 loss_db: 0.0797 loss: 0.8640 2022/08/30 14:00:04 - mmengine - INFO - Epoch(train) [615][30/63] lr: 3.6695e-03 eta: 13:24:41 time: 0.8577 data_time: 0.0329 memory: 16201 loss_prob: 0.5425 loss_thr: 0.3369 loss_db: 0.0893 loss: 0.9687 2022/08/30 14:00:08 - mmengine - INFO - Epoch(train) [615][35/63] lr: 3.6695e-03 eta: 13:24:41 time: 0.8625 data_time: 0.0325 memory: 16201 loss_prob: 0.5987 loss_thr: 0.3609 loss_db: 0.0971 loss: 1.0566 2022/08/30 14:00:12 - mmengine - INFO - Epoch(train) [615][40/63] lr: 3.6695e-03 eta: 13:24:24 time: 0.8285 data_time: 0.0261 memory: 16201 loss_prob: 0.5185 loss_thr: 0.3494 loss_db: 0.0911 loss: 0.9589 2022/08/30 14:00:16 - mmengine - INFO - Epoch(train) [615][45/63] lr: 3.6695e-03 eta: 13:24:24 time: 0.8041 data_time: 0.0250 memory: 16201 loss_prob: 0.4558 loss_thr: 0.3282 loss_db: 0.0820 loss: 0.8659 2022/08/30 14:00:20 - mmengine - INFO - Epoch(train) [615][50/63] lr: 3.6695e-03 eta: 13:24:06 time: 0.8122 data_time: 0.0250 memory: 16201 loss_prob: 0.4424 loss_thr: 0.3134 loss_db: 0.0769 loss: 0.8328 2022/08/30 14:00:24 - mmengine - INFO - Epoch(train) [615][55/63] lr: 3.6695e-03 eta: 13:24:06 time: 0.7968 data_time: 0.0233 memory: 16201 loss_prob: 0.5481 loss_thr: 0.3522 loss_db: 0.0899 loss: 0.9902 2022/08/30 14:00:29 - mmengine - INFO - Epoch(train) [615][60/63] lr: 3.6695e-03 eta: 13:23:48 time: 0.8615 data_time: 0.0269 memory: 16201 loss_prob: 0.5725 loss_thr: 0.3745 loss_db: 0.0950 loss: 1.0420 2022/08/30 14:00:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:00:38 - mmengine - INFO - Epoch(train) [616][5/63] lr: 3.6639e-03 eta: 13:23:48 time: 1.0911 data_time: 0.2285 memory: 16201 loss_prob: 0.5458 loss_thr: 0.3717 loss_db: 0.0935 loss: 1.0109 2022/08/30 14:00:42 - mmengine - INFO - Epoch(train) [616][10/63] lr: 3.6639e-03 eta: 13:23:25 time: 1.0533 data_time: 0.2365 memory: 16201 loss_prob: 0.5436 loss_thr: 0.3698 loss_db: 0.0966 loss: 1.0100 2022/08/30 14:00:46 - mmengine - INFO - Epoch(train) [616][15/63] lr: 3.6639e-03 eta: 13:23:25 time: 0.8778 data_time: 0.0265 memory: 16201 loss_prob: 0.5100 loss_thr: 0.3493 loss_db: 0.0902 loss: 0.9495 2022/08/30 14:00:50 - mmengine - INFO - Epoch(train) [616][20/63] lr: 3.6639e-03 eta: 13:23:08 time: 0.8675 data_time: 0.0257 memory: 16201 loss_prob: 0.4656 loss_thr: 0.3336 loss_db: 0.0810 loss: 0.8802 2022/08/30 14:00:55 - mmengine - INFO - Epoch(train) [616][25/63] lr: 3.6639e-03 eta: 13:23:08 time: 0.8220 data_time: 0.0336 memory: 16201 loss_prob: 0.4596 loss_thr: 0.3303 loss_db: 0.0820 loss: 0.8718 2022/08/30 14:00:59 - mmengine - INFO - Epoch(train) [616][30/63] lr: 3.6639e-03 eta: 13:22:50 time: 0.8233 data_time: 0.0321 memory: 16201 loss_prob: 0.4497 loss_thr: 0.3313 loss_db: 0.0798 loss: 0.8609 2022/08/30 14:01:03 - mmengine - INFO - Epoch(train) [616][35/63] lr: 3.6639e-03 eta: 13:22:50 time: 0.8520 data_time: 0.0232 memory: 16201 loss_prob: 0.4547 loss_thr: 0.3396 loss_db: 0.0788 loss: 0.8730 2022/08/30 14:01:07 - mmengine - INFO - Epoch(train) [616][40/63] lr: 3.6639e-03 eta: 13:22:33 time: 0.8738 data_time: 0.0289 memory: 16201 loss_prob: 0.4381 loss_thr: 0.3316 loss_db: 0.0771 loss: 0.8469 2022/08/30 14:01:12 - mmengine - INFO - Epoch(train) [616][45/63] lr: 3.6639e-03 eta: 13:22:33 time: 0.8429 data_time: 0.0356 memory: 16201 loss_prob: 0.4402 loss_thr: 0.3374 loss_db: 0.0806 loss: 0.8582 2022/08/30 14:01:16 - mmengine - INFO - Epoch(train) [616][50/63] lr: 3.6639e-03 eta: 13:22:16 time: 0.8870 data_time: 0.0292 memory: 16201 loss_prob: 0.4739 loss_thr: 0.3530 loss_db: 0.0839 loss: 0.9107 2022/08/30 14:01:21 - mmengine - INFO - Epoch(train) [616][55/63] lr: 3.6639e-03 eta: 13:22:16 time: 0.9104 data_time: 0.0376 memory: 16201 loss_prob: 0.4753 loss_thr: 0.3341 loss_db: 0.0809 loss: 0.8903 2022/08/30 14:01:25 - mmengine - INFO - Epoch(train) [616][60/63] lr: 3.6639e-03 eta: 13:21:59 time: 0.8751 data_time: 0.0440 memory: 16201 loss_prob: 0.4958 loss_thr: 0.3391 loss_db: 0.0864 loss: 0.9214 2022/08/30 14:01:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:01:34 - mmengine - INFO - Epoch(train) [617][5/63] lr: 3.6582e-03 eta: 13:21:59 time: 1.0197 data_time: 0.2247 memory: 16201 loss_prob: 0.4953 loss_thr: 0.3452 loss_db: 0.0869 loss: 0.9274 2022/08/30 14:01:38 - mmengine - INFO - Epoch(train) [617][10/63] lr: 3.6582e-03 eta: 13:21:36 time: 1.0704 data_time: 0.2420 memory: 16201 loss_prob: 0.5058 loss_thr: 0.3472 loss_db: 0.0882 loss: 0.9412 2022/08/30 14:01:42 - mmengine - INFO - Epoch(train) [617][15/63] lr: 3.6582e-03 eta: 13:21:36 time: 0.8680 data_time: 0.0372 memory: 16201 loss_prob: 0.4888 loss_thr: 0.3204 loss_db: 0.0844 loss: 0.8935 2022/08/30 14:01:47 - mmengine - INFO - Epoch(train) [617][20/63] lr: 3.6582e-03 eta: 13:21:18 time: 0.8596 data_time: 0.0238 memory: 16201 loss_prob: 0.5202 loss_thr: 0.3370 loss_db: 0.0890 loss: 0.9461 2022/08/30 14:01:51 - mmengine - INFO - Epoch(train) [617][25/63] lr: 3.6582e-03 eta: 13:21:18 time: 0.8401 data_time: 0.0341 memory: 16201 loss_prob: 0.4942 loss_thr: 0.3321 loss_db: 0.0857 loss: 0.9119 2022/08/30 14:01:55 - mmengine - INFO - Epoch(train) [617][30/63] lr: 3.6582e-03 eta: 13:21:01 time: 0.8519 data_time: 0.0348 memory: 16201 loss_prob: 0.4351 loss_thr: 0.3068 loss_db: 0.0769 loss: 0.8187 2022/08/30 14:01:59 - mmengine - INFO - Epoch(train) [617][35/63] lr: 3.6582e-03 eta: 13:21:01 time: 0.8362 data_time: 0.0326 memory: 16201 loss_prob: 0.4666 loss_thr: 0.3285 loss_db: 0.0826 loss: 0.8778 2022/08/30 14:02:04 - mmengine - INFO - Epoch(train) [617][40/63] lr: 3.6582e-03 eta: 13:20:44 time: 0.8592 data_time: 0.0273 memory: 16201 loss_prob: 0.5562 loss_thr: 0.3702 loss_db: 0.0952 loss: 1.0216 2022/08/30 14:02:08 - mmengine - INFO - Epoch(train) [617][45/63] lr: 3.6582e-03 eta: 13:20:44 time: 0.8889 data_time: 0.0291 memory: 16201 loss_prob: 0.5417 loss_thr: 0.3663 loss_db: 0.0920 loss: 1.0000 2022/08/30 14:02:12 - mmengine - INFO - Epoch(train) [617][50/63] lr: 3.6582e-03 eta: 13:20:26 time: 0.8433 data_time: 0.0331 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3337 loss_db: 0.0834 loss: 0.8922 2022/08/30 14:02:16 - mmengine - INFO - Epoch(train) [617][55/63] lr: 3.6582e-03 eta: 13:20:26 time: 0.8559 data_time: 0.0309 memory: 16201 loss_prob: 0.4720 loss_thr: 0.3329 loss_db: 0.0829 loss: 0.8878 2022/08/30 14:02:21 - mmengine - INFO - Epoch(train) [617][60/63] lr: 3.6582e-03 eta: 13:20:09 time: 0.8734 data_time: 0.0324 memory: 16201 loss_prob: 0.4789 loss_thr: 0.3393 loss_db: 0.0837 loss: 0.9019 2022/08/30 14:02:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:02:29 - mmengine - INFO - Epoch(train) [618][5/63] lr: 3.6526e-03 eta: 13:20:09 time: 1.0066 data_time: 0.1975 memory: 16201 loss_prob: 0.4719 loss_thr: 0.3300 loss_db: 0.0814 loss: 0.8833 2022/08/30 14:02:34 - mmengine - INFO - Epoch(train) [618][10/63] lr: 3.6526e-03 eta: 13:19:46 time: 1.0759 data_time: 0.2097 memory: 16201 loss_prob: 0.5196 loss_thr: 0.3567 loss_db: 0.0920 loss: 0.9683 2022/08/30 14:02:38 - mmengine - INFO - Epoch(train) [618][15/63] lr: 3.6526e-03 eta: 13:19:46 time: 0.9087 data_time: 0.0275 memory: 16201 loss_prob: 0.5083 loss_thr: 0.3660 loss_db: 0.0897 loss: 0.9639 2022/08/30 14:02:43 - mmengine - INFO - Epoch(train) [618][20/63] lr: 3.6526e-03 eta: 13:19:30 time: 0.9541 data_time: 0.0674 memory: 16201 loss_prob: 0.4901 loss_thr: 0.3591 loss_db: 0.0830 loss: 0.9323 2022/08/30 14:02:48 - mmengine - INFO - Epoch(train) [618][25/63] lr: 3.6526e-03 eta: 13:19:30 time: 0.9310 data_time: 0.0779 memory: 16201 loss_prob: 0.4868 loss_thr: 0.3648 loss_db: 0.0867 loss: 0.9384 2022/08/30 14:02:52 - mmengine - INFO - Epoch(train) [618][30/63] lr: 3.6526e-03 eta: 13:19:13 time: 0.8952 data_time: 0.0266 memory: 16201 loss_prob: 0.4888 loss_thr: 0.3496 loss_db: 0.0897 loss: 0.9280 2022/08/30 14:02:56 - mmengine - INFO - Epoch(train) [618][35/63] lr: 3.6526e-03 eta: 13:19:13 time: 0.8883 data_time: 0.0241 memory: 16201 loss_prob: 0.4617 loss_thr: 0.3164 loss_db: 0.0813 loss: 0.8593 2022/08/30 14:03:01 - mmengine - INFO - Epoch(train) [618][40/63] lr: 3.6526e-03 eta: 13:18:56 time: 0.8483 data_time: 0.0272 memory: 16201 loss_prob: 0.4610 loss_thr: 0.3190 loss_db: 0.0771 loss: 0.8570 2022/08/30 14:03:05 - mmengine - INFO - Epoch(train) [618][45/63] lr: 3.6526e-03 eta: 13:18:56 time: 0.8371 data_time: 0.0298 memory: 16201 loss_prob: 0.5045 loss_thr: 0.3370 loss_db: 0.0904 loss: 0.9318 2022/08/30 14:03:09 - mmengine - INFO - Epoch(train) [618][50/63] lr: 3.6526e-03 eta: 13:18:38 time: 0.8593 data_time: 0.0371 memory: 16201 loss_prob: 0.4764 loss_thr: 0.3153 loss_db: 0.0868 loss: 0.8785 2022/08/30 14:03:14 - mmengine - INFO - Epoch(train) [618][55/63] lr: 3.6526e-03 eta: 13:18:38 time: 0.8685 data_time: 0.0319 memory: 16201 loss_prob: 0.4195 loss_thr: 0.2948 loss_db: 0.0717 loss: 0.7861 2022/08/30 14:03:18 - mmengine - INFO - Epoch(train) [618][60/63] lr: 3.6526e-03 eta: 13:18:21 time: 0.8474 data_time: 0.0249 memory: 16201 loss_prob: 0.4089 loss_thr: 0.3088 loss_db: 0.0714 loss: 0.7891 2022/08/30 14:03:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:03:26 - mmengine - INFO - Epoch(train) [619][5/63] lr: 3.6469e-03 eta: 13:18:21 time: 1.0189 data_time: 0.2015 memory: 16201 loss_prob: 0.4597 loss_thr: 0.3206 loss_db: 0.0811 loss: 0.8614 2022/08/30 14:03:31 - mmengine - INFO - Epoch(train) [619][10/63] lr: 3.6469e-03 eta: 13:17:58 time: 1.0685 data_time: 0.2157 memory: 16201 loss_prob: 0.4576 loss_thr: 0.3192 loss_db: 0.0813 loss: 0.8581 2022/08/30 14:03:35 - mmengine - INFO - Epoch(train) [619][15/63] lr: 3.6469e-03 eta: 13:17:58 time: 0.9180 data_time: 0.0302 memory: 16201 loss_prob: 0.4792 loss_thr: 0.3187 loss_db: 0.0821 loss: 0.8800 2022/08/30 14:03:40 - mmengine - INFO - Epoch(train) [619][20/63] lr: 3.6469e-03 eta: 13:17:41 time: 0.9116 data_time: 0.0236 memory: 16201 loss_prob: 0.5468 loss_thr: 0.3323 loss_db: 0.0918 loss: 0.9708 2022/08/30 14:03:44 - mmengine - INFO - Epoch(train) [619][25/63] lr: 3.6469e-03 eta: 13:17:41 time: 0.8561 data_time: 0.0367 memory: 16201 loss_prob: 0.5141 loss_thr: 0.3349 loss_db: 0.0905 loss: 0.9395 2022/08/30 14:03:48 - mmengine - INFO - Epoch(train) [619][30/63] lr: 3.6469e-03 eta: 13:17:24 time: 0.8550 data_time: 0.0290 memory: 16201 loss_prob: 0.4469 loss_thr: 0.3283 loss_db: 0.0779 loss: 0.8531 2022/08/30 14:03:53 - mmengine - INFO - Epoch(train) [619][35/63] lr: 3.6469e-03 eta: 13:17:24 time: 0.8982 data_time: 0.0199 memory: 16201 loss_prob: 0.4291 loss_thr: 0.3147 loss_db: 0.0749 loss: 0.8188 2022/08/30 14:03:57 - mmengine - INFO - Epoch(train) [619][40/63] lr: 3.6469e-03 eta: 13:17:07 time: 0.8849 data_time: 0.0290 memory: 16201 loss_prob: 0.4762 loss_thr: 0.3209 loss_db: 0.0811 loss: 0.8782 2022/08/30 14:04:01 - mmengine - INFO - Epoch(train) [619][45/63] lr: 3.6469e-03 eta: 13:17:07 time: 0.8138 data_time: 0.0265 memory: 16201 loss_prob: 0.5129 loss_thr: 0.3415 loss_db: 0.0842 loss: 0.9386 2022/08/30 14:04:06 - mmengine - INFO - Epoch(train) [619][50/63] lr: 3.6469e-03 eta: 13:16:50 time: 0.8530 data_time: 0.0312 memory: 16201 loss_prob: 0.5179 loss_thr: 0.3492 loss_db: 0.0877 loss: 0.9548 2022/08/30 14:04:10 - mmengine - INFO - Epoch(train) [619][55/63] lr: 3.6469e-03 eta: 13:16:50 time: 0.8688 data_time: 0.0379 memory: 16201 loss_prob: 0.4648 loss_thr: 0.3219 loss_db: 0.0799 loss: 0.8666 2022/08/30 14:04:14 - mmengine - INFO - Epoch(train) [619][60/63] lr: 3.6469e-03 eta: 13:16:32 time: 0.8205 data_time: 0.0328 memory: 16201 loss_prob: 0.4150 loss_thr: 0.3022 loss_db: 0.0723 loss: 0.7895 2022/08/30 14:04:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:04:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:04:21 - mmengine - INFO - Epoch(train) [620][5/63] lr: 3.6413e-03 eta: 13:16:32 time: 0.9072 data_time: 0.1499 memory: 16201 loss_prob: 0.4622 loss_thr: 0.3398 loss_db: 0.0811 loss: 0.8831 2022/08/30 14:04:25 - mmengine - INFO - Epoch(train) [620][10/63] lr: 3.6413e-03 eta: 13:16:08 time: 0.9484 data_time: 0.1603 memory: 16201 loss_prob: 0.4794 loss_thr: 0.3381 loss_db: 0.0853 loss: 0.9027 2022/08/30 14:04:29 - mmengine - INFO - Epoch(train) [620][15/63] lr: 3.6413e-03 eta: 13:16:08 time: 0.8133 data_time: 0.0282 memory: 16201 loss_prob: 0.4475 loss_thr: 0.3117 loss_db: 0.0794 loss: 0.8387 2022/08/30 14:04:34 - mmengine - INFO - Epoch(train) [620][20/63] lr: 3.6413e-03 eta: 13:15:50 time: 0.8360 data_time: 0.0263 memory: 16201 loss_prob: 0.4365 loss_thr: 0.2964 loss_db: 0.0786 loss: 0.8115 2022/08/30 14:04:38 - mmengine - INFO - Epoch(train) [620][25/63] lr: 3.6413e-03 eta: 13:15:50 time: 0.8461 data_time: 0.0363 memory: 16201 loss_prob: 0.4707 loss_thr: 0.3144 loss_db: 0.0846 loss: 0.8697 2022/08/30 14:04:42 - mmengine - INFO - Epoch(train) [620][30/63] lr: 3.6413e-03 eta: 13:15:33 time: 0.8576 data_time: 0.0288 memory: 16201 loss_prob: 0.4731 loss_thr: 0.3301 loss_db: 0.0829 loss: 0.8861 2022/08/30 14:04:47 - mmengine - INFO - Epoch(train) [620][35/63] lr: 3.6413e-03 eta: 13:15:33 time: 0.8715 data_time: 0.0210 memory: 16201 loss_prob: 0.4327 loss_thr: 0.3042 loss_db: 0.0744 loss: 0.8113 2022/08/30 14:04:51 - mmengine - INFO - Epoch(train) [620][40/63] lr: 3.6413e-03 eta: 13:15:16 time: 0.8613 data_time: 0.0240 memory: 16201 loss_prob: 0.4221 loss_thr: 0.2982 loss_db: 0.0738 loss: 0.7941 2022/08/30 14:04:55 - mmengine - INFO - Epoch(train) [620][45/63] lr: 3.6413e-03 eta: 13:15:16 time: 0.8513 data_time: 0.0268 memory: 16201 loss_prob: 0.4654 loss_thr: 0.3256 loss_db: 0.0827 loss: 0.8737 2022/08/30 14:04:59 - mmengine - INFO - Epoch(train) [620][50/63] lr: 3.6413e-03 eta: 13:14:59 time: 0.8335 data_time: 0.0253 memory: 16201 loss_prob: 0.5000 loss_thr: 0.3498 loss_db: 0.0869 loss: 0.9367 2022/08/30 14:05:04 - mmengine - INFO - Epoch(train) [620][55/63] lr: 3.6413e-03 eta: 13:14:59 time: 0.8540 data_time: 0.0308 memory: 16201 loss_prob: 0.4725 loss_thr: 0.3312 loss_db: 0.0819 loss: 0.8856 2022/08/30 14:05:08 - mmengine - INFO - Epoch(train) [620][60/63] lr: 3.6413e-03 eta: 13:14:41 time: 0.8670 data_time: 0.0309 memory: 16201 loss_prob: 0.4501 loss_thr: 0.3251 loss_db: 0.0791 loss: 0.8542 2022/08/30 14:05:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:05:10 - mmengine - INFO - Saving checkpoint at 620 epochs 2022/08/30 14:05:19 - mmengine - INFO - Epoch(val) [620][5/32] eta: 13:14:41 time: 0.6184 data_time: 0.1102 memory: 16201 2022/08/30 14:05:22 - mmengine - INFO - Epoch(val) [620][10/32] eta: 0:00:15 time: 0.6926 data_time: 0.1245 memory: 15734 2022/08/30 14:05:25 - mmengine - INFO - Epoch(val) [620][15/32] eta: 0:00:15 time: 0.6127 data_time: 0.0506 memory: 15734 2022/08/30 14:05:28 - mmengine - INFO - Epoch(val) [620][20/32] eta: 0:00:07 time: 0.6298 data_time: 0.0769 memory: 15734 2022/08/30 14:05:31 - mmengine - INFO - Epoch(val) [620][25/32] eta: 0:00:07 time: 0.6699 data_time: 0.0711 memory: 15734 2022/08/30 14:05:35 - mmengine - INFO - Epoch(val) [620][30/32] eta: 0:00:01 time: 0.6712 data_time: 0.0442 memory: 15734 2022/08/30 14:05:35 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 14:05:35 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8392, precision: 0.7966, hmean: 0.8174 2022/08/30 14:05:35 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8392, precision: 0.8272, hmean: 0.8332 2022/08/30 14:05:35 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8377, precision: 0.8529, hmean: 0.8453 2022/08/30 14:05:35 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8334, precision: 0.8729, hmean: 0.8527 2022/08/30 14:05:35 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8161, precision: 0.8884, hmean: 0.8507 2022/08/30 14:05:35 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7453, precision: 0.9209, hmean: 0.8238 2022/08/30 14:05:35 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1647, precision: 0.9607, hmean: 0.2811 2022/08/30 14:05:35 - mmengine - INFO - Epoch(val) [620][32/32] icdar/precision: 0.8729 icdar/recall: 0.8334 icdar/hmean: 0.8527 2022/08/30 14:05:42 - mmengine - INFO - Epoch(train) [621][5/63] lr: 3.6356e-03 eta: 0:00:01 time: 1.0868 data_time: 0.2346 memory: 16201 loss_prob: 0.4931 loss_thr: 0.3353 loss_db: 0.0861 loss: 0.9145 2022/08/30 14:05:46 - mmengine - INFO - Epoch(train) [621][10/63] lr: 3.6356e-03 eta: 13:14:19 time: 1.0912 data_time: 0.2354 memory: 16201 loss_prob: 0.4945 loss_thr: 0.3407 loss_db: 0.0861 loss: 0.9214 2022/08/30 14:05:51 - mmengine - INFO - Epoch(train) [621][15/63] lr: 3.6356e-03 eta: 13:14:19 time: 0.8756 data_time: 0.0239 memory: 16201 loss_prob: 0.4654 loss_thr: 0.3144 loss_db: 0.0797 loss: 0.8595 2022/08/30 14:05:56 - mmengine - INFO - Epoch(train) [621][20/63] lr: 3.6356e-03 eta: 13:14:03 time: 0.9652 data_time: 0.0534 memory: 16201 loss_prob: 0.4610 loss_thr: 0.3182 loss_db: 0.0787 loss: 0.8579 2022/08/30 14:06:00 - mmengine - INFO - Epoch(train) [621][25/63] lr: 3.6356e-03 eta: 13:14:03 time: 0.9330 data_time: 0.0502 memory: 16201 loss_prob: 0.4516 loss_thr: 0.3201 loss_db: 0.0791 loss: 0.8508 2022/08/30 14:06:04 - mmengine - INFO - Epoch(train) [621][30/63] lr: 3.6356e-03 eta: 13:13:45 time: 0.8338 data_time: 0.0247 memory: 16201 loss_prob: 0.4483 loss_thr: 0.3200 loss_db: 0.0782 loss: 0.8464 2022/08/30 14:06:09 - mmengine - INFO - Epoch(train) [621][35/63] lr: 3.6356e-03 eta: 13:13:45 time: 0.8519 data_time: 0.0357 memory: 16201 loss_prob: 0.4540 loss_thr: 0.3215 loss_db: 0.0788 loss: 0.8542 2022/08/30 14:06:13 - mmengine - INFO - Epoch(train) [621][40/63] lr: 3.6356e-03 eta: 13:13:28 time: 0.8988 data_time: 0.0230 memory: 16201 loss_prob: 0.4520 loss_thr: 0.3209 loss_db: 0.0808 loss: 0.8537 2022/08/30 14:06:18 - mmengine - INFO - Epoch(train) [621][45/63] lr: 3.6356e-03 eta: 13:13:28 time: 0.8900 data_time: 0.0321 memory: 16201 loss_prob: 0.4227 loss_thr: 0.3250 loss_db: 0.0741 loss: 0.8217 2022/08/30 14:06:22 - mmengine - INFO - Epoch(train) [621][50/63] lr: 3.6356e-03 eta: 13:13:11 time: 0.8561 data_time: 0.0447 memory: 16201 loss_prob: 0.4362 loss_thr: 0.3212 loss_db: 0.0735 loss: 0.8309 2022/08/30 14:06:26 - mmengine - INFO - Epoch(train) [621][55/63] lr: 3.6356e-03 eta: 13:13:11 time: 0.8574 data_time: 0.0234 memory: 16201 loss_prob: 0.4423 loss_thr: 0.3181 loss_db: 0.0771 loss: 0.8375 2022/08/30 14:06:31 - mmengine - INFO - Epoch(train) [621][60/63] lr: 3.6356e-03 eta: 13:12:54 time: 0.8670 data_time: 0.0227 memory: 16201 loss_prob: 0.4558 loss_thr: 0.3290 loss_db: 0.0799 loss: 0.8646 2022/08/30 14:06:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:06:40 - mmengine - INFO - Epoch(train) [622][5/63] lr: 3.6300e-03 eta: 13:12:54 time: 1.0747 data_time: 0.1886 memory: 16201 loss_prob: 0.4675 loss_thr: 0.3296 loss_db: 0.0821 loss: 0.8791 2022/08/30 14:06:44 - mmengine - INFO - Epoch(train) [622][10/63] lr: 3.6300e-03 eta: 13:12:31 time: 1.0294 data_time: 0.2019 memory: 16201 loss_prob: 0.4860 loss_thr: 0.3309 loss_db: 0.0844 loss: 0.9013 2022/08/30 14:06:48 - mmengine - INFO - Epoch(train) [622][15/63] lr: 3.6300e-03 eta: 13:12:31 time: 0.8411 data_time: 0.0255 memory: 16201 loss_prob: 0.5399 loss_thr: 0.3409 loss_db: 0.0855 loss: 0.9663 2022/08/30 14:06:52 - mmengine - INFO - Epoch(train) [622][20/63] lr: 3.6300e-03 eta: 13:12:14 time: 0.8471 data_time: 0.0202 memory: 16201 loss_prob: 0.5247 loss_thr: 0.3393 loss_db: 0.0868 loss: 0.9508 2022/08/30 14:06:57 - mmengine - INFO - Epoch(train) [622][25/63] lr: 3.6300e-03 eta: 13:12:14 time: 0.8448 data_time: 0.0384 memory: 16201 loss_prob: 0.4451 loss_thr: 0.3233 loss_db: 0.0801 loss: 0.8485 2022/08/30 14:07:01 - mmengine - INFO - Epoch(train) [622][30/63] lr: 3.6300e-03 eta: 13:11:56 time: 0.8338 data_time: 0.0302 memory: 16201 loss_prob: 0.4327 loss_thr: 0.3228 loss_db: 0.0747 loss: 0.8302 2022/08/30 14:07:05 - mmengine - INFO - Epoch(train) [622][35/63] lr: 3.6300e-03 eta: 13:11:56 time: 0.8378 data_time: 0.0210 memory: 16201 loss_prob: 0.4609 loss_thr: 0.3215 loss_db: 0.0798 loss: 0.8622 2022/08/30 14:07:09 - mmengine - INFO - Epoch(train) [622][40/63] lr: 3.6300e-03 eta: 13:11:39 time: 0.8464 data_time: 0.0275 memory: 16201 loss_prob: 0.4473 loss_thr: 0.3027 loss_db: 0.0785 loss: 0.8284 2022/08/30 14:07:14 - mmengine - INFO - Epoch(train) [622][45/63] lr: 3.6300e-03 eta: 13:11:39 time: 0.9047 data_time: 0.0254 memory: 16201 loss_prob: 0.4640 loss_thr: 0.3136 loss_db: 0.0800 loss: 0.8576 2022/08/30 14:07:18 - mmengine - INFO - Epoch(train) [622][50/63] lr: 3.6300e-03 eta: 13:11:22 time: 0.8994 data_time: 0.0300 memory: 16201 loss_prob: 0.5198 loss_thr: 0.3458 loss_db: 0.0892 loss: 0.9548 2022/08/30 14:07:22 - mmengine - INFO - Epoch(train) [622][55/63] lr: 3.6300e-03 eta: 13:11:22 time: 0.7969 data_time: 0.0264 memory: 16201 loss_prob: 0.5111 loss_thr: 0.3522 loss_db: 0.0892 loss: 0.9525 2022/08/30 14:07:26 - mmengine - INFO - Epoch(train) [622][60/63] lr: 3.6300e-03 eta: 13:11:04 time: 0.7935 data_time: 0.0210 memory: 16201 loss_prob: 0.4835 loss_thr: 0.3389 loss_db: 0.0848 loss: 0.9071 2022/08/30 14:07:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:07:33 - mmengine - INFO - Epoch(train) [623][5/63] lr: 3.6243e-03 eta: 13:11:04 time: 0.9047 data_time: 0.1392 memory: 16201 loss_prob: 0.4428 loss_thr: 0.3321 loss_db: 0.0778 loss: 0.8527 2022/08/30 14:07:38 - mmengine - INFO - Epoch(train) [623][10/63] lr: 3.6243e-03 eta: 13:10:40 time: 0.9535 data_time: 0.1548 memory: 16201 loss_prob: 0.4255 loss_thr: 0.3163 loss_db: 0.0754 loss: 0.8172 2022/08/30 14:07:42 - mmengine - INFO - Epoch(train) [623][15/63] lr: 3.6243e-03 eta: 13:10:40 time: 0.8545 data_time: 0.0245 memory: 16201 loss_prob: 0.4548 loss_thr: 0.3106 loss_db: 0.0784 loss: 0.8438 2022/08/30 14:07:46 - mmengine - INFO - Epoch(train) [623][20/63] lr: 3.6243e-03 eta: 13:10:23 time: 0.8386 data_time: 0.0180 memory: 16201 loss_prob: 0.4872 loss_thr: 0.3280 loss_db: 0.0834 loss: 0.8986 2022/08/30 14:07:50 - mmengine - INFO - Epoch(train) [623][25/63] lr: 3.6243e-03 eta: 13:10:23 time: 0.8002 data_time: 0.0305 memory: 16201 loss_prob: 0.4932 loss_thr: 0.3499 loss_db: 0.0866 loss: 0.9298 2022/08/30 14:07:54 - mmengine - INFO - Epoch(train) [623][30/63] lr: 3.6243e-03 eta: 13:10:05 time: 0.8083 data_time: 0.0237 memory: 16201 loss_prob: 0.4714 loss_thr: 0.3428 loss_db: 0.0838 loss: 0.8980 2022/08/30 14:07:58 - mmengine - INFO - Epoch(train) [623][35/63] lr: 3.6243e-03 eta: 13:10:05 time: 0.8152 data_time: 0.0221 memory: 16201 loss_prob: 0.4406 loss_thr: 0.3275 loss_db: 0.0784 loss: 0.8465 2022/08/30 14:08:02 - mmengine - INFO - Epoch(train) [623][40/63] lr: 3.6243e-03 eta: 13:09:48 time: 0.8147 data_time: 0.0251 memory: 16201 loss_prob: 0.3996 loss_thr: 0.3049 loss_db: 0.0708 loss: 0.7753 2022/08/30 14:08:06 - mmengine - INFO - Epoch(train) [623][45/63] lr: 3.6243e-03 eta: 13:09:48 time: 0.7977 data_time: 0.0232 memory: 16201 loss_prob: 0.4231 loss_thr: 0.3006 loss_db: 0.0754 loss: 0.7990 2022/08/30 14:08:10 - mmengine - INFO - Epoch(train) [623][50/63] lr: 3.6243e-03 eta: 13:09:30 time: 0.7858 data_time: 0.0242 memory: 16201 loss_prob: 0.4258 loss_thr: 0.3006 loss_db: 0.0758 loss: 0.8023 2022/08/30 14:08:14 - mmengine - INFO - Epoch(train) [623][55/63] lr: 3.6243e-03 eta: 13:09:30 time: 0.7835 data_time: 0.0208 memory: 16201 loss_prob: 0.4859 loss_thr: 0.3348 loss_db: 0.0854 loss: 0.9061 2022/08/30 14:08:18 - mmengine - INFO - Epoch(train) [623][60/63] lr: 3.6243e-03 eta: 13:09:13 time: 0.8183 data_time: 0.0264 memory: 16201 loss_prob: 0.5202 loss_thr: 0.3444 loss_db: 0.0904 loss: 0.9550 2022/08/30 14:08:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:08:26 - mmengine - INFO - Epoch(train) [624][5/63] lr: 3.6187e-03 eta: 13:09:13 time: 0.9347 data_time: 0.1899 memory: 16201 loss_prob: 0.4888 loss_thr: 0.3354 loss_db: 0.0850 loss: 0.9092 2022/08/30 14:08:30 - mmengine - INFO - Epoch(train) [624][10/63] lr: 3.6187e-03 eta: 13:08:49 time: 0.9842 data_time: 0.2014 memory: 16201 loss_prob: 0.5211 loss_thr: 0.3457 loss_db: 0.0899 loss: 0.9567 2022/08/30 14:08:34 - mmengine - INFO - Epoch(train) [624][15/63] lr: 3.6187e-03 eta: 13:08:49 time: 0.8168 data_time: 0.0229 memory: 16201 loss_prob: 0.5243 loss_thr: 0.3487 loss_db: 0.0903 loss: 0.9632 2022/08/30 14:08:38 - mmengine - INFO - Epoch(train) [624][20/63] lr: 3.6187e-03 eta: 13:08:32 time: 0.8389 data_time: 0.0238 memory: 16201 loss_prob: 0.4684 loss_thr: 0.3259 loss_db: 0.0824 loss: 0.8767 2022/08/30 14:08:42 - mmengine - INFO - Epoch(train) [624][25/63] lr: 3.6187e-03 eta: 13:08:32 time: 0.8302 data_time: 0.0269 memory: 16201 loss_prob: 0.4658 loss_thr: 0.3244 loss_db: 0.0855 loss: 0.8757 2022/08/30 14:08:46 - mmengine - INFO - Epoch(train) [624][30/63] lr: 3.6187e-03 eta: 13:08:14 time: 0.8095 data_time: 0.0232 memory: 16201 loss_prob: 0.4724 loss_thr: 0.3393 loss_db: 0.0835 loss: 0.8952 2022/08/30 14:08:51 - mmengine - INFO - Epoch(train) [624][35/63] lr: 3.6187e-03 eta: 13:08:14 time: 0.8247 data_time: 0.0235 memory: 16201 loss_prob: 0.4663 loss_thr: 0.3371 loss_db: 0.0789 loss: 0.8823 2022/08/30 14:08:56 - mmengine - INFO - Epoch(train) [624][40/63] lr: 3.6187e-03 eta: 13:07:58 time: 0.9131 data_time: 0.0326 memory: 16201 loss_prob: 0.4547 loss_thr: 0.3236 loss_db: 0.0808 loss: 0.8591 2022/08/30 14:09:00 - mmengine - INFO - Epoch(train) [624][45/63] lr: 3.6187e-03 eta: 13:07:58 time: 0.8954 data_time: 0.0301 memory: 16201 loss_prob: 0.4548 loss_thr: 0.3282 loss_db: 0.0816 loss: 0.8647 2022/08/30 14:09:04 - mmengine - INFO - Epoch(train) [624][50/63] lr: 3.6187e-03 eta: 13:07:40 time: 0.7914 data_time: 0.0186 memory: 16201 loss_prob: 0.4733 loss_thr: 0.3450 loss_db: 0.0825 loss: 0.9008 2022/08/30 14:09:08 - mmengine - INFO - Epoch(train) [624][55/63] lr: 3.6187e-03 eta: 13:07:40 time: 0.8015 data_time: 0.0267 memory: 16201 loss_prob: 0.4952 loss_thr: 0.3438 loss_db: 0.0864 loss: 0.9255 2022/08/30 14:09:12 - mmengine - INFO - Epoch(train) [624][60/63] lr: 3.6187e-03 eta: 13:07:22 time: 0.8348 data_time: 0.0218 memory: 16201 loss_prob: 0.4957 loss_thr: 0.3403 loss_db: 0.0872 loss: 0.9232 2022/08/30 14:09:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:09:20 - mmengine - INFO - Epoch(train) [625][5/63] lr: 3.6130e-03 eta: 13:07:22 time: 0.9920 data_time: 0.2215 memory: 16201 loss_prob: 0.4553 loss_thr: 0.3325 loss_db: 0.0785 loss: 0.8663 2022/08/30 14:09:24 - mmengine - INFO - Epoch(train) [625][10/63] lr: 3.6130e-03 eta: 13:06:59 time: 0.9985 data_time: 0.2193 memory: 16201 loss_prob: 0.4649 loss_thr: 0.3319 loss_db: 0.0830 loss: 0.8798 2022/08/30 14:09:28 - mmengine - INFO - Epoch(train) [625][15/63] lr: 3.6130e-03 eta: 13:06:59 time: 0.8329 data_time: 0.0268 memory: 16201 loss_prob: 0.4477 loss_thr: 0.3230 loss_db: 0.0795 loss: 0.8502 2022/08/30 14:09:33 - mmengine - INFO - Epoch(train) [625][20/63] lr: 3.6130e-03 eta: 13:06:42 time: 0.8357 data_time: 0.0221 memory: 16201 loss_prob: 0.4838 loss_thr: 0.3341 loss_db: 0.0847 loss: 0.9026 2022/08/30 14:09:37 - mmengine - INFO - Epoch(train) [625][25/63] lr: 3.6130e-03 eta: 13:06:42 time: 0.8256 data_time: 0.0354 memory: 16201 loss_prob: 0.5113 loss_thr: 0.3434 loss_db: 0.0893 loss: 0.9440 2022/08/30 14:09:41 - mmengine - INFO - Epoch(train) [625][30/63] lr: 3.6130e-03 eta: 13:06:24 time: 0.8222 data_time: 0.0261 memory: 16201 loss_prob: 0.4894 loss_thr: 0.3334 loss_db: 0.0822 loss: 0.9051 2022/08/30 14:09:45 - mmengine - INFO - Epoch(train) [625][35/63] lr: 3.6130e-03 eta: 13:06:24 time: 0.8294 data_time: 0.0182 memory: 16201 loss_prob: 0.4854 loss_thr: 0.3326 loss_db: 0.0830 loss: 0.9010 2022/08/30 14:09:49 - mmengine - INFO - Epoch(train) [625][40/63] lr: 3.6130e-03 eta: 13:06:07 time: 0.8426 data_time: 0.0246 memory: 16201 loss_prob: 0.4935 loss_thr: 0.3520 loss_db: 0.0886 loss: 0.9340 2022/08/30 14:09:53 - mmengine - INFO - Epoch(train) [625][45/63] lr: 3.6130e-03 eta: 13:06:07 time: 0.8452 data_time: 0.0235 memory: 16201 loss_prob: 0.4946 loss_thr: 0.3479 loss_db: 0.0875 loss: 0.9300 2022/08/30 14:09:58 - mmengine - INFO - Epoch(train) [625][50/63] lr: 3.6130e-03 eta: 13:05:50 time: 0.8550 data_time: 0.0260 memory: 16201 loss_prob: 0.4534 loss_thr: 0.3079 loss_db: 0.0783 loss: 0.8396 2022/08/30 14:10:02 - mmengine - INFO - Epoch(train) [625][55/63] lr: 3.6130e-03 eta: 13:05:50 time: 0.8549 data_time: 0.0257 memory: 16201 loss_prob: 0.4460 loss_thr: 0.3147 loss_db: 0.0760 loss: 0.8366 2022/08/30 14:10:06 - mmengine - INFO - Epoch(train) [625][60/63] lr: 3.6130e-03 eta: 13:05:33 time: 0.8651 data_time: 0.0260 memory: 16201 loss_prob: 0.4274 loss_thr: 0.3123 loss_db: 0.0751 loss: 0.8148 2022/08/30 14:10:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:10:15 - mmengine - INFO - Epoch(train) [626][5/63] lr: 3.6073e-03 eta: 13:05:33 time: 1.0008 data_time: 0.2080 memory: 16201 loss_prob: 0.4656 loss_thr: 0.3188 loss_db: 0.0814 loss: 0.8658 2022/08/30 14:10:19 - mmengine - INFO - Epoch(train) [626][10/63] lr: 3.6073e-03 eta: 13:05:10 time: 1.0264 data_time: 0.2157 memory: 16201 loss_prob: 0.5116 loss_thr: 0.3479 loss_db: 0.0894 loss: 0.9488 2022/08/30 14:10:23 - mmengine - INFO - Epoch(train) [626][15/63] lr: 3.6073e-03 eta: 13:05:10 time: 0.8238 data_time: 0.0280 memory: 16201 loss_prob: 0.4643 loss_thr: 0.3402 loss_db: 0.0822 loss: 0.8867 2022/08/30 14:10:27 - mmengine - INFO - Epoch(train) [626][20/63] lr: 3.6073e-03 eta: 13:04:52 time: 0.7978 data_time: 0.0210 memory: 16201 loss_prob: 0.3802 loss_thr: 0.3008 loss_db: 0.0679 loss: 0.7489 2022/08/30 14:10:31 - mmengine - INFO - Epoch(train) [626][25/63] lr: 3.6073e-03 eta: 13:04:52 time: 0.8163 data_time: 0.0318 memory: 16201 loss_prob: 0.4085 loss_thr: 0.2993 loss_db: 0.0725 loss: 0.7803 2022/08/30 14:10:35 - mmengine - INFO - Epoch(train) [626][30/63] lr: 3.6073e-03 eta: 13:04:35 time: 0.8317 data_time: 0.0271 memory: 16201 loss_prob: 0.4442 loss_thr: 0.3191 loss_db: 0.0771 loss: 0.8403 2022/08/30 14:10:39 - mmengine - INFO - Epoch(train) [626][35/63] lr: 3.6073e-03 eta: 13:04:35 time: 0.8482 data_time: 0.0258 memory: 16201 loss_prob: 0.4509 loss_thr: 0.3276 loss_db: 0.0781 loss: 0.8565 2022/08/30 14:10:44 - mmengine - INFO - Epoch(train) [626][40/63] lr: 3.6073e-03 eta: 13:04:18 time: 0.8470 data_time: 0.0274 memory: 16201 loss_prob: 0.4591 loss_thr: 0.3243 loss_db: 0.0798 loss: 0.8632 2022/08/30 14:10:48 - mmengine - INFO - Epoch(train) [626][45/63] lr: 3.6073e-03 eta: 13:04:18 time: 0.8163 data_time: 0.0236 memory: 16201 loss_prob: 0.4951 loss_thr: 0.3371 loss_db: 0.0827 loss: 0.9149 2022/08/30 14:10:52 - mmengine - INFO - Epoch(train) [626][50/63] lr: 3.6073e-03 eta: 13:04:01 time: 0.8330 data_time: 0.0268 memory: 16201 loss_prob: 0.4892 loss_thr: 0.3415 loss_db: 0.0826 loss: 0.9133 2022/08/30 14:10:56 - mmengine - INFO - Epoch(train) [626][55/63] lr: 3.6073e-03 eta: 13:04:01 time: 0.8381 data_time: 0.0310 memory: 16201 loss_prob: 0.4783 loss_thr: 0.3514 loss_db: 0.0853 loss: 0.9150 2022/08/30 14:11:00 - mmengine - INFO - Epoch(train) [626][60/63] lr: 3.6073e-03 eta: 13:03:43 time: 0.8210 data_time: 0.0349 memory: 16201 loss_prob: 0.4715 loss_thr: 0.3546 loss_db: 0.0826 loss: 0.9087 2022/08/30 14:11:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:11:08 - mmengine - INFO - Epoch(train) [627][5/63] lr: 3.6017e-03 eta: 13:03:43 time: 0.9976 data_time: 0.1966 memory: 16201 loss_prob: 0.4407 loss_thr: 0.3067 loss_db: 0.0762 loss: 0.8236 2022/08/30 14:11:13 - mmengine - INFO - Epoch(train) [627][10/63] lr: 3.6017e-03 eta: 13:03:21 time: 1.0610 data_time: 0.2137 memory: 16201 loss_prob: 0.4764 loss_thr: 0.3313 loss_db: 0.0840 loss: 0.8917 2022/08/30 14:11:17 - mmengine - INFO - Epoch(train) [627][15/63] lr: 3.6017e-03 eta: 13:03:21 time: 0.8626 data_time: 0.0252 memory: 16201 loss_prob: 0.4719 loss_thr: 0.3335 loss_db: 0.0836 loss: 0.8891 2022/08/30 14:11:22 - mmengine - INFO - Epoch(train) [627][20/63] lr: 3.6017e-03 eta: 13:03:04 time: 0.8673 data_time: 0.0165 memory: 16201 loss_prob: 0.4263 loss_thr: 0.3039 loss_db: 0.0756 loss: 0.8058 2022/08/30 14:11:26 - mmengine - INFO - Epoch(train) [627][25/63] lr: 3.6017e-03 eta: 13:03:04 time: 0.8616 data_time: 0.0292 memory: 16201 loss_prob: 0.4226 loss_thr: 0.3005 loss_db: 0.0740 loss: 0.7971 2022/08/30 14:11:30 - mmengine - INFO - Epoch(train) [627][30/63] lr: 3.6017e-03 eta: 13:02:46 time: 0.8073 data_time: 0.0297 memory: 16201 loss_prob: 0.4325 loss_thr: 0.3028 loss_db: 0.0751 loss: 0.8105 2022/08/30 14:11:34 - mmengine - INFO - Epoch(train) [627][35/63] lr: 3.6017e-03 eta: 13:02:46 time: 0.8459 data_time: 0.0311 memory: 16201 loss_prob: 0.4856 loss_thr: 0.3122 loss_db: 0.0820 loss: 0.8798 2022/08/30 14:11:38 - mmengine - INFO - Epoch(train) [627][40/63] lr: 3.6017e-03 eta: 13:02:29 time: 0.8427 data_time: 0.0271 memory: 16201 loss_prob: 0.5347 loss_thr: 0.3395 loss_db: 0.0903 loss: 0.9645 2022/08/30 14:11:42 - mmengine - INFO - Epoch(train) [627][45/63] lr: 3.6017e-03 eta: 13:02:29 time: 0.8167 data_time: 0.0267 memory: 16201 loss_prob: 0.5036 loss_thr: 0.3432 loss_db: 0.0890 loss: 0.9359 2022/08/30 14:11:47 - mmengine - INFO - Epoch(train) [627][50/63] lr: 3.6017e-03 eta: 13:02:12 time: 0.8594 data_time: 0.0323 memory: 16201 loss_prob: 0.4952 loss_thr: 0.3457 loss_db: 0.0863 loss: 0.9272 2022/08/30 14:11:51 - mmengine - INFO - Epoch(train) [627][55/63] lr: 3.6017e-03 eta: 13:02:12 time: 0.8471 data_time: 0.0236 memory: 16201 loss_prob: 0.5062 loss_thr: 0.3574 loss_db: 0.0887 loss: 0.9523 2022/08/30 14:11:55 - mmengine - INFO - Epoch(train) [627][60/63] lr: 3.6017e-03 eta: 13:01:55 time: 0.8430 data_time: 0.0267 memory: 16201 loss_prob: 0.5010 loss_thr: 0.3409 loss_db: 0.0890 loss: 0.9310 2022/08/30 14:11:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:12:03 - mmengine - INFO - Epoch(train) [628][5/63] lr: 3.5960e-03 eta: 13:01:55 time: 0.9630 data_time: 0.2082 memory: 16201 loss_prob: 0.5233 loss_thr: 0.3484 loss_db: 0.0872 loss: 0.9589 2022/08/30 14:12:07 - mmengine - INFO - Epoch(train) [628][10/63] lr: 3.5960e-03 eta: 13:01:31 time: 0.9959 data_time: 0.2077 memory: 16201 loss_prob: 0.5209 loss_thr: 0.3319 loss_db: 0.0914 loss: 0.9442 2022/08/30 14:12:11 - mmengine - INFO - Epoch(train) [628][15/63] lr: 3.5960e-03 eta: 13:01:31 time: 0.8243 data_time: 0.0233 memory: 16201 loss_prob: 0.5357 loss_thr: 0.3529 loss_db: 0.0949 loss: 0.9835 2022/08/30 14:12:15 - mmengine - INFO - Epoch(train) [628][20/63] lr: 3.5960e-03 eta: 13:01:14 time: 0.8139 data_time: 0.0165 memory: 16201 loss_prob: 0.5428 loss_thr: 0.3533 loss_db: 0.0916 loss: 0.9877 2022/08/30 14:12:20 - mmengine - INFO - Epoch(train) [628][25/63] lr: 3.5960e-03 eta: 13:01:14 time: 0.8090 data_time: 0.0336 memory: 16201 loss_prob: 0.4698 loss_thr: 0.3256 loss_db: 0.0801 loss: 0.8754 2022/08/30 14:12:24 - mmengine - INFO - Epoch(train) [628][30/63] lr: 3.5960e-03 eta: 13:00:57 time: 0.8088 data_time: 0.0253 memory: 16201 loss_prob: 0.4889 loss_thr: 0.3416 loss_db: 0.0838 loss: 0.9143 2022/08/30 14:12:28 - mmengine - INFO - Epoch(train) [628][35/63] lr: 3.5960e-03 eta: 13:00:57 time: 0.8302 data_time: 0.0194 memory: 16201 loss_prob: 0.4869 loss_thr: 0.3387 loss_db: 0.0851 loss: 0.9107 2022/08/30 14:12:32 - mmengine - INFO - Epoch(train) [628][40/63] lr: 3.5960e-03 eta: 13:00:39 time: 0.8458 data_time: 0.0274 memory: 16201 loss_prob: 0.4482 loss_thr: 0.3280 loss_db: 0.0795 loss: 0.8557 2022/08/30 14:12:36 - mmengine - INFO - Epoch(train) [628][45/63] lr: 3.5960e-03 eta: 13:00:39 time: 0.8618 data_time: 0.0238 memory: 16201 loss_prob: 0.4296 loss_thr: 0.3158 loss_db: 0.0756 loss: 0.8210 2022/08/30 14:12:41 - mmengine - INFO - Epoch(train) [628][50/63] lr: 3.5960e-03 eta: 13:00:22 time: 0.8500 data_time: 0.0267 memory: 16201 loss_prob: 0.4450 loss_thr: 0.3212 loss_db: 0.0776 loss: 0.8438 2022/08/30 14:12:45 - mmengine - INFO - Epoch(train) [628][55/63] lr: 3.5960e-03 eta: 13:00:22 time: 0.8295 data_time: 0.0265 memory: 16201 loss_prob: 0.4526 loss_thr: 0.3202 loss_db: 0.0795 loss: 0.8524 2022/08/30 14:12:49 - mmengine - INFO - Epoch(train) [628][60/63] lr: 3.5960e-03 eta: 13:00:05 time: 0.8492 data_time: 0.0323 memory: 16201 loss_prob: 0.4353 loss_thr: 0.2977 loss_db: 0.0752 loss: 0.8082 2022/08/30 14:12:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:12:58 - mmengine - INFO - Epoch(train) [629][5/63] lr: 3.5904e-03 eta: 13:00:05 time: 1.0155 data_time: 0.2210 memory: 16201 loss_prob: 0.4222 loss_thr: 0.2975 loss_db: 0.0742 loss: 0.7940 2022/08/30 14:13:02 - mmengine - INFO - Epoch(train) [629][10/63] lr: 3.5904e-03 eta: 12:59:43 time: 1.0829 data_time: 0.2378 memory: 16201 loss_prob: 0.3924 loss_thr: 0.2874 loss_db: 0.0705 loss: 0.7502 2022/08/30 14:13:06 - mmengine - INFO - Epoch(train) [629][15/63] lr: 3.5904e-03 eta: 12:59:43 time: 0.8476 data_time: 0.0310 memory: 16201 loss_prob: 0.4212 loss_thr: 0.3026 loss_db: 0.0734 loss: 0.7972 2022/08/30 14:13:10 - mmengine - INFO - Epoch(train) [629][20/63] lr: 3.5904e-03 eta: 12:59:25 time: 0.8144 data_time: 0.0203 memory: 16201 loss_prob: 0.4943 loss_thr: 0.3471 loss_db: 0.0845 loss: 0.9259 2022/08/30 14:13:15 - mmengine - INFO - Epoch(train) [629][25/63] lr: 3.5904e-03 eta: 12:59:25 time: 0.9036 data_time: 0.0331 memory: 16201 loss_prob: 0.4926 loss_thr: 0.3450 loss_db: 0.0838 loss: 0.9213 2022/08/30 14:13:19 - mmengine - INFO - Epoch(train) [629][30/63] lr: 3.5904e-03 eta: 12:59:09 time: 0.9014 data_time: 0.0280 memory: 16201 loss_prob: 0.4971 loss_thr: 0.3415 loss_db: 0.0857 loss: 0.9243 2022/08/30 14:13:23 - mmengine - INFO - Epoch(train) [629][35/63] lr: 3.5904e-03 eta: 12:59:09 time: 0.8422 data_time: 0.0215 memory: 16201 loss_prob: 0.5446 loss_thr: 0.3593 loss_db: 0.0918 loss: 0.9957 2022/08/30 14:13:27 - mmengine - INFO - Epoch(train) [629][40/63] lr: 3.5904e-03 eta: 12:58:52 time: 0.8358 data_time: 0.0266 memory: 16201 loss_prob: 0.5181 loss_thr: 0.3422 loss_db: 0.0876 loss: 0.9479 2022/08/30 14:13:32 - mmengine - INFO - Epoch(train) [629][45/63] lr: 3.5904e-03 eta: 12:58:52 time: 0.8233 data_time: 0.0270 memory: 16201 loss_prob: 0.4900 loss_thr: 0.3509 loss_db: 0.0865 loss: 0.9274 2022/08/30 14:13:37 - mmengine - INFO - Epoch(train) [629][50/63] lr: 3.5904e-03 eta: 12:58:35 time: 0.9204 data_time: 0.0273 memory: 16201 loss_prob: 0.4974 loss_thr: 0.3685 loss_db: 0.0871 loss: 0.9530 2022/08/30 14:13:41 - mmengine - INFO - Epoch(train) [629][55/63] lr: 3.5904e-03 eta: 12:58:35 time: 0.9252 data_time: 0.0230 memory: 16201 loss_prob: 0.4760 loss_thr: 0.3489 loss_db: 0.0825 loss: 0.9073 2022/08/30 14:13:45 - mmengine - INFO - Epoch(train) [629][60/63] lr: 3.5904e-03 eta: 12:58:18 time: 0.8411 data_time: 0.0280 memory: 16201 loss_prob: 0.5024 loss_thr: 0.3471 loss_db: 0.0862 loss: 0.9358 2022/08/30 14:13:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:13:53 - mmengine - INFO - Epoch(train) [630][5/63] lr: 3.5847e-03 eta: 12:58:18 time: 0.9322 data_time: 0.1531 memory: 16201 loss_prob: 0.5277 loss_thr: 0.3499 loss_db: 0.0930 loss: 0.9707 2022/08/30 14:13:57 - mmengine - INFO - Epoch(train) [630][10/63] lr: 3.5847e-03 eta: 12:57:55 time: 1.0221 data_time: 0.1726 memory: 16201 loss_prob: 0.5191 loss_thr: 0.3486 loss_db: 0.0923 loss: 0.9600 2022/08/30 14:14:01 - mmengine - INFO - Epoch(train) [630][15/63] lr: 3.5847e-03 eta: 12:57:55 time: 0.8367 data_time: 0.0292 memory: 16201 loss_prob: 0.5192 loss_thr: 0.3469 loss_db: 0.0916 loss: 0.9577 2022/08/30 14:14:05 - mmengine - INFO - Epoch(train) [630][20/63] lr: 3.5847e-03 eta: 12:57:38 time: 0.8150 data_time: 0.0172 memory: 16201 loss_prob: 0.4719 loss_thr: 0.3209 loss_db: 0.0836 loss: 0.8764 2022/08/30 14:14:10 - mmengine - INFO - Epoch(train) [630][25/63] lr: 3.5847e-03 eta: 12:57:38 time: 0.8402 data_time: 0.0274 memory: 16201 loss_prob: 0.4344 loss_thr: 0.3155 loss_db: 0.0768 loss: 0.8267 2022/08/30 14:14:14 - mmengine - INFO - Epoch(train) [630][30/63] lr: 3.5847e-03 eta: 12:57:21 time: 0.8597 data_time: 0.0268 memory: 16201 loss_prob: 0.4357 loss_thr: 0.3177 loss_db: 0.0766 loss: 0.8301 2022/08/30 14:14:18 - mmengine - INFO - Epoch(train) [630][35/63] lr: 3.5847e-03 eta: 12:57:21 time: 0.8589 data_time: 0.0213 memory: 16201 loss_prob: 0.4623 loss_thr: 0.3283 loss_db: 0.0812 loss: 0.8718 2022/08/30 14:14:22 - mmengine - INFO - Epoch(train) [630][40/63] lr: 3.5847e-03 eta: 12:57:04 time: 0.8336 data_time: 0.0243 memory: 16201 loss_prob: 0.4866 loss_thr: 0.3528 loss_db: 0.0862 loss: 0.9256 2022/08/30 14:14:27 - mmengine - INFO - Epoch(train) [630][45/63] lr: 3.5847e-03 eta: 12:57:04 time: 0.8831 data_time: 0.0335 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3528 loss_db: 0.0864 loss: 0.9288 2022/08/30 14:14:31 - mmengine - INFO - Epoch(train) [630][50/63] lr: 3.5847e-03 eta: 12:56:47 time: 0.9014 data_time: 0.0304 memory: 16201 loss_prob: 0.5121 loss_thr: 0.3445 loss_db: 0.0883 loss: 0.9449 2022/08/30 14:14:36 - mmengine - INFO - Epoch(train) [630][55/63] lr: 3.5847e-03 eta: 12:56:47 time: 0.8534 data_time: 0.0268 memory: 16201 loss_prob: 0.5135 loss_thr: 0.3428 loss_db: 0.0881 loss: 0.9445 2022/08/30 14:14:40 - mmengine - INFO - Epoch(train) [630][60/63] lr: 3.5847e-03 eta: 12:56:30 time: 0.8322 data_time: 0.0257 memory: 16201 loss_prob: 0.4732 loss_thr: 0.3360 loss_db: 0.0856 loss: 0.8948 2022/08/30 14:14:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:14:48 - mmengine - INFO - Epoch(train) [631][5/63] lr: 3.5790e-03 eta: 12:56:30 time: 1.0367 data_time: 0.2419 memory: 16201 loss_prob: 0.5178 loss_thr: 0.3493 loss_db: 0.0885 loss: 0.9556 2022/08/30 14:14:53 - mmengine - INFO - Epoch(train) [631][10/63] lr: 3.5790e-03 eta: 12:56:08 time: 1.1439 data_time: 0.2536 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3330 loss_db: 0.0826 loss: 0.8906 2022/08/30 14:14:57 - mmengine - INFO - Epoch(train) [631][15/63] lr: 3.5790e-03 eta: 12:56:08 time: 0.8874 data_time: 0.0251 memory: 16201 loss_prob: 0.4094 loss_thr: 0.3139 loss_db: 0.0718 loss: 0.7951 2022/08/30 14:15:01 - mmengine - INFO - Epoch(train) [631][20/63] lr: 3.5790e-03 eta: 12:55:51 time: 0.8148 data_time: 0.0204 memory: 16201 loss_prob: 0.4521 loss_thr: 0.3223 loss_db: 0.0787 loss: 0.8531 2022/08/30 14:15:06 - mmengine - INFO - Epoch(train) [631][25/63] lr: 3.5790e-03 eta: 12:55:51 time: 0.8323 data_time: 0.0384 memory: 16201 loss_prob: 0.4959 loss_thr: 0.3400 loss_db: 0.0877 loss: 0.9236 2022/08/30 14:15:10 - mmengine - INFO - Epoch(train) [631][30/63] lr: 3.5790e-03 eta: 12:55:34 time: 0.8381 data_time: 0.0378 memory: 16201 loss_prob: 0.5103 loss_thr: 0.3512 loss_db: 0.0893 loss: 0.9509 2022/08/30 14:15:14 - mmengine - INFO - Epoch(train) [631][35/63] lr: 3.5790e-03 eta: 12:55:34 time: 0.8446 data_time: 0.0249 memory: 16201 loss_prob: 0.5017 loss_thr: 0.3324 loss_db: 0.0851 loss: 0.9192 2022/08/30 14:15:18 - mmengine - INFO - Epoch(train) [631][40/63] lr: 3.5790e-03 eta: 12:55:17 time: 0.8359 data_time: 0.0266 memory: 16201 loss_prob: 0.4872 loss_thr: 0.3247 loss_db: 0.0838 loss: 0.8956 2022/08/30 14:15:22 - mmengine - INFO - Epoch(train) [631][45/63] lr: 3.5790e-03 eta: 12:55:17 time: 0.8134 data_time: 0.0265 memory: 16201 loss_prob: 0.4649 loss_thr: 0.3157 loss_db: 0.0828 loss: 0.8634 2022/08/30 14:15:26 - mmengine - INFO - Epoch(train) [631][50/63] lr: 3.5790e-03 eta: 12:54:59 time: 0.8266 data_time: 0.0264 memory: 16201 loss_prob: 0.4270 loss_thr: 0.3040 loss_db: 0.0748 loss: 0.8058 2022/08/30 14:15:30 - mmengine - INFO - Epoch(train) [631][55/63] lr: 3.5790e-03 eta: 12:54:59 time: 0.8239 data_time: 0.0245 memory: 16201 loss_prob: 0.4385 loss_thr: 0.3159 loss_db: 0.0768 loss: 0.8312 2022/08/30 14:15:35 - mmengine - INFO - Epoch(train) [631][60/63] lr: 3.5790e-03 eta: 12:54:43 time: 0.8652 data_time: 0.0255 memory: 16201 loss_prob: 0.4455 loss_thr: 0.3230 loss_db: 0.0788 loss: 0.8473 2022/08/30 14:15:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:15:43 - mmengine - INFO - Epoch(train) [632][5/63] lr: 3.5734e-03 eta: 12:54:43 time: 0.9052 data_time: 0.1633 memory: 16201 loss_prob: 0.4362 loss_thr: 0.3151 loss_db: 0.0774 loss: 0.8287 2022/08/30 14:15:47 - mmengine - INFO - Epoch(train) [632][10/63] lr: 3.5734e-03 eta: 12:54:19 time: 0.9602 data_time: 0.1742 memory: 16201 loss_prob: 0.5281 loss_thr: 0.3383 loss_db: 0.0884 loss: 0.9548 2022/08/30 14:15:51 - mmengine - INFO - Epoch(train) [632][15/63] lr: 3.5734e-03 eta: 12:54:19 time: 0.8399 data_time: 0.0274 memory: 16201 loss_prob: 0.5261 loss_thr: 0.3410 loss_db: 0.0890 loss: 0.9561 2022/08/30 14:15:55 - mmengine - INFO - Epoch(train) [632][20/63] lr: 3.5734e-03 eta: 12:54:02 time: 0.8484 data_time: 0.0220 memory: 16201 loss_prob: 0.4811 loss_thr: 0.3388 loss_db: 0.0827 loss: 0.9026 2022/08/30 14:15:59 - mmengine - INFO - Epoch(train) [632][25/63] lr: 3.5734e-03 eta: 12:54:02 time: 0.8055 data_time: 0.0285 memory: 16201 loss_prob: 0.4789 loss_thr: 0.3320 loss_db: 0.0821 loss: 0.8931 2022/08/30 14:16:03 - mmengine - INFO - Epoch(train) [632][30/63] lr: 3.5734e-03 eta: 12:53:45 time: 0.8114 data_time: 0.0281 memory: 16201 loss_prob: 0.4637 loss_thr: 0.3205 loss_db: 0.0814 loss: 0.8656 2022/08/30 14:16:07 - mmengine - INFO - Epoch(train) [632][35/63] lr: 3.5734e-03 eta: 12:53:45 time: 0.8328 data_time: 0.0235 memory: 16201 loss_prob: 0.4590 loss_thr: 0.3243 loss_db: 0.0785 loss: 0.8618 2022/08/30 14:16:11 - mmengine - INFO - Epoch(train) [632][40/63] lr: 3.5734e-03 eta: 12:53:27 time: 0.8078 data_time: 0.0265 memory: 16201 loss_prob: 0.4321 loss_thr: 0.3131 loss_db: 0.0749 loss: 0.8201 2022/08/30 14:16:16 - mmengine - INFO - Epoch(train) [632][45/63] lr: 3.5734e-03 eta: 12:53:27 time: 0.8303 data_time: 0.0284 memory: 16201 loss_prob: 0.4273 loss_thr: 0.3065 loss_db: 0.0752 loss: 0.8091 2022/08/30 14:16:20 - mmengine - INFO - Epoch(train) [632][50/63] lr: 3.5734e-03 eta: 12:53:11 time: 0.8902 data_time: 0.0229 memory: 16201 loss_prob: 0.4490 loss_thr: 0.3078 loss_db: 0.0785 loss: 0.8352 2022/08/30 14:16:24 - mmengine - INFO - Epoch(train) [632][55/63] lr: 3.5734e-03 eta: 12:53:11 time: 0.8811 data_time: 0.0252 memory: 16201 loss_prob: 0.4818 loss_thr: 0.3166 loss_db: 0.0808 loss: 0.8792 2022/08/30 14:16:28 - mmengine - INFO - Epoch(train) [632][60/63] lr: 3.5734e-03 eta: 12:52:54 time: 0.8246 data_time: 0.0277 memory: 16201 loss_prob: 0.4588 loss_thr: 0.3125 loss_db: 0.0770 loss: 0.8483 2022/08/30 14:16:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:16:37 - mmengine - INFO - Epoch(train) [633][5/63] lr: 3.5677e-03 eta: 12:52:54 time: 0.9642 data_time: 0.1805 memory: 16201 loss_prob: 0.4205 loss_thr: 0.3047 loss_db: 0.0719 loss: 0.7971 2022/08/30 14:16:41 - mmengine - INFO - Epoch(train) [633][10/63] lr: 3.5677e-03 eta: 12:52:31 time: 1.0123 data_time: 0.1860 memory: 16201 loss_prob: 0.4444 loss_thr: 0.3178 loss_db: 0.0766 loss: 0.8389 2022/08/30 14:16:45 - mmengine - INFO - Epoch(train) [633][15/63] lr: 3.5677e-03 eta: 12:52:31 time: 0.8616 data_time: 0.0245 memory: 16201 loss_prob: 0.4592 loss_thr: 0.3163 loss_db: 0.0811 loss: 0.8566 2022/08/30 14:16:49 - mmengine - INFO - Epoch(train) [633][20/63] lr: 3.5677e-03 eta: 12:52:14 time: 0.8490 data_time: 0.0244 memory: 16201 loss_prob: 0.4557 loss_thr: 0.3097 loss_db: 0.0804 loss: 0.8457 2022/08/30 14:16:53 - mmengine - INFO - Epoch(train) [633][25/63] lr: 3.5677e-03 eta: 12:52:14 time: 0.8134 data_time: 0.0303 memory: 16201 loss_prob: 0.4681 loss_thr: 0.3283 loss_db: 0.0813 loss: 0.8776 2022/08/30 14:16:57 - mmengine - INFO - Epoch(train) [633][30/63] lr: 3.5677e-03 eta: 12:51:57 time: 0.8158 data_time: 0.0251 memory: 16201 loss_prob: 0.4590 loss_thr: 0.3301 loss_db: 0.0795 loss: 0.8687 2022/08/30 14:17:02 - mmengine - INFO - Epoch(train) [633][35/63] lr: 3.5677e-03 eta: 12:51:57 time: 0.8354 data_time: 0.0232 memory: 16201 loss_prob: 0.5866 loss_thr: 0.3364 loss_db: 0.1028 loss: 1.0259 2022/08/30 14:17:06 - mmengine - INFO - Epoch(train) [633][40/63] lr: 3.5677e-03 eta: 12:51:40 time: 0.8857 data_time: 0.0277 memory: 16201 loss_prob: 0.6961 loss_thr: 0.3720 loss_db: 0.1175 loss: 1.1856 2022/08/30 14:17:10 - mmengine - INFO - Epoch(train) [633][45/63] lr: 3.5677e-03 eta: 12:51:40 time: 0.8709 data_time: 0.0274 memory: 16201 loss_prob: 0.6002 loss_thr: 0.3683 loss_db: 0.0993 loss: 1.0678 2022/08/30 14:17:15 - mmengine - INFO - Epoch(train) [633][50/63] lr: 3.5677e-03 eta: 12:51:23 time: 0.8435 data_time: 0.0250 memory: 16201 loss_prob: 0.6170 loss_thr: 0.3853 loss_db: 0.1053 loss: 1.1076 2022/08/30 14:17:19 - mmengine - INFO - Epoch(train) [633][55/63] lr: 3.5677e-03 eta: 12:51:23 time: 0.8403 data_time: 0.0299 memory: 16201 loss_prob: 0.6267 loss_thr: 0.3934 loss_db: 0.1090 loss: 1.1292 2022/08/30 14:17:23 - mmengine - INFO - Epoch(train) [633][60/63] lr: 3.5677e-03 eta: 12:51:06 time: 0.8603 data_time: 0.0299 memory: 16201 loss_prob: 0.6143 loss_thr: 0.3731 loss_db: 0.1055 loss: 1.0929 2022/08/30 14:17:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:17:32 - mmengine - INFO - Epoch(train) [634][5/63] lr: 3.5621e-03 eta: 12:51:06 time: 1.0612 data_time: 0.2332 memory: 16201 loss_prob: 0.6537 loss_thr: 0.4008 loss_db: 0.1088 loss: 1.1633 2022/08/30 14:17:36 - mmengine - INFO - Epoch(train) [634][10/63] lr: 3.5621e-03 eta: 12:50:44 time: 1.0733 data_time: 0.2484 memory: 16201 loss_prob: 0.6137 loss_thr: 0.4078 loss_db: 0.1033 loss: 1.1248 2022/08/30 14:17:40 - mmengine - INFO - Epoch(train) [634][15/63] lr: 3.5621e-03 eta: 12:50:44 time: 0.8493 data_time: 0.0270 memory: 16201 loss_prob: 0.5776 loss_thr: 0.3944 loss_db: 0.0992 loss: 1.0712 2022/08/30 14:17:45 - mmengine - INFO - Epoch(train) [634][20/63] lr: 3.5621e-03 eta: 12:50:27 time: 0.9007 data_time: 0.0201 memory: 16201 loss_prob: 0.5439 loss_thr: 0.3661 loss_db: 0.0947 loss: 1.0047 2022/08/30 14:17:50 - mmengine - INFO - Epoch(train) [634][25/63] lr: 3.5621e-03 eta: 12:50:27 time: 0.9233 data_time: 0.0372 memory: 16201 loss_prob: 0.5512 loss_thr: 0.3724 loss_db: 0.0951 loss: 1.0187 2022/08/30 14:17:54 - mmengine - INFO - Epoch(train) [634][30/63] lr: 3.5621e-03 eta: 12:50:10 time: 0.8547 data_time: 0.0266 memory: 16201 loss_prob: 0.7029 loss_thr: 0.4181 loss_db: 0.1133 loss: 1.2343 2022/08/30 14:17:58 - mmengine - INFO - Epoch(train) [634][35/63] lr: 3.5621e-03 eta: 12:50:10 time: 0.8340 data_time: 0.0180 memory: 16201 loss_prob: 0.6440 loss_thr: 0.3834 loss_db: 0.1052 loss: 1.1325 2022/08/30 14:18:02 - mmengine - INFO - Epoch(train) [634][40/63] lr: 3.5621e-03 eta: 12:49:54 time: 0.8495 data_time: 0.0233 memory: 16201 loss_prob: 0.4908 loss_thr: 0.3316 loss_db: 0.0872 loss: 0.9096 2022/08/30 14:18:07 - mmengine - INFO - Epoch(train) [634][45/63] lr: 3.5621e-03 eta: 12:49:54 time: 0.9162 data_time: 0.0270 memory: 16201 loss_prob: 0.5169 loss_thr: 0.3352 loss_db: 0.0906 loss: 0.9427 2022/08/30 14:18:11 - mmengine - INFO - Epoch(train) [634][50/63] lr: 3.5621e-03 eta: 12:49:37 time: 0.8822 data_time: 0.0319 memory: 16201 loss_prob: 0.4965 loss_thr: 0.3351 loss_db: 0.0858 loss: 0.9174 2022/08/30 14:18:15 - mmengine - INFO - Epoch(train) [634][55/63] lr: 3.5621e-03 eta: 12:49:37 time: 0.8055 data_time: 0.0238 memory: 16201 loss_prob: 0.4818 loss_thr: 0.3410 loss_db: 0.0844 loss: 0.9072 2022/08/30 14:18:20 - mmengine - INFO - Epoch(train) [634][60/63] lr: 3.5621e-03 eta: 12:49:20 time: 0.8603 data_time: 0.0247 memory: 16201 loss_prob: 0.5426 loss_thr: 0.3777 loss_db: 0.0961 loss: 1.0164 2022/08/30 14:18:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:18:28 - mmengine - INFO - Epoch(train) [635][5/63] lr: 3.5564e-03 eta: 12:49:20 time: 1.0266 data_time: 0.2443 memory: 16201 loss_prob: 0.5250 loss_thr: 0.3651 loss_db: 0.0914 loss: 0.9814 2022/08/30 14:18:32 - mmengine - INFO - Epoch(train) [635][10/63] lr: 3.5564e-03 eta: 12:48:58 time: 1.0779 data_time: 0.2581 memory: 16201 loss_prob: 0.4889 loss_thr: 0.3347 loss_db: 0.0876 loss: 0.9112 2022/08/30 14:18:37 - mmengine - INFO - Epoch(train) [635][15/63] lr: 3.5564e-03 eta: 12:48:58 time: 0.8557 data_time: 0.0278 memory: 16201 loss_prob: 0.5042 loss_thr: 0.3410 loss_db: 0.0904 loss: 0.9355 2022/08/30 14:18:41 - mmengine - INFO - Epoch(train) [635][20/63] lr: 3.5564e-03 eta: 12:48:41 time: 0.8664 data_time: 0.0393 memory: 16201 loss_prob: 0.5215 loss_thr: 0.3594 loss_db: 0.0898 loss: 0.9707 2022/08/30 14:18:45 - mmengine - INFO - Epoch(train) [635][25/63] lr: 3.5564e-03 eta: 12:48:41 time: 0.8563 data_time: 0.0529 memory: 16201 loss_prob: 0.5192 loss_thr: 0.3544 loss_db: 0.0909 loss: 0.9645 2022/08/30 14:18:50 - mmengine - INFO - Epoch(train) [635][30/63] lr: 3.5564e-03 eta: 12:48:24 time: 0.8541 data_time: 0.0387 memory: 16201 loss_prob: 0.5174 loss_thr: 0.3537 loss_db: 0.0922 loss: 0.9633 2022/08/30 14:18:54 - mmengine - INFO - Epoch(train) [635][35/63] lr: 3.5564e-03 eta: 12:48:24 time: 0.8243 data_time: 0.0314 memory: 16201 loss_prob: 0.5252 loss_thr: 0.3625 loss_db: 0.0906 loss: 0.9784 2022/08/30 14:18:58 - mmengine - INFO - Epoch(train) [635][40/63] lr: 3.5564e-03 eta: 12:48:07 time: 0.8100 data_time: 0.0391 memory: 16201 loss_prob: 0.4712 loss_thr: 0.3408 loss_db: 0.0814 loss: 0.8934 2022/08/30 14:19:02 - mmengine - INFO - Epoch(train) [635][45/63] lr: 3.5564e-03 eta: 12:48:07 time: 0.8187 data_time: 0.0332 memory: 16201 loss_prob: 0.4633 loss_thr: 0.3457 loss_db: 0.0840 loss: 0.8930 2022/08/30 14:19:06 - mmengine - INFO - Epoch(train) [635][50/63] lr: 3.5564e-03 eta: 12:47:50 time: 0.8289 data_time: 0.0256 memory: 16201 loss_prob: 0.4795 loss_thr: 0.3483 loss_db: 0.0872 loss: 0.9149 2022/08/30 14:19:10 - mmengine - INFO - Epoch(train) [635][55/63] lr: 3.5564e-03 eta: 12:47:50 time: 0.8372 data_time: 0.0363 memory: 16201 loss_prob: 0.4692 loss_thr: 0.3443 loss_db: 0.0811 loss: 0.8946 2022/08/30 14:19:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:19:14 - mmengine - INFO - Epoch(train) [635][60/63] lr: 3.5564e-03 eta: 12:47:33 time: 0.8369 data_time: 0.0317 memory: 16201 loss_prob: 0.4779 loss_thr: 0.3502 loss_db: 0.0813 loss: 0.9095 2022/08/30 14:19:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:19:23 - mmengine - INFO - Epoch(train) [636][5/63] lr: 3.5507e-03 eta: 12:47:33 time: 1.0228 data_time: 0.2302 memory: 16201 loss_prob: 0.5083 loss_thr: 0.3566 loss_db: 0.0893 loss: 0.9542 2022/08/30 14:19:27 - mmengine - INFO - Epoch(train) [636][10/63] lr: 3.5507e-03 eta: 12:47:11 time: 1.1066 data_time: 0.2417 memory: 16201 loss_prob: 0.4914 loss_thr: 0.3603 loss_db: 0.0855 loss: 0.9373 2022/08/30 14:19:32 - mmengine - INFO - Epoch(train) [636][15/63] lr: 3.5507e-03 eta: 12:47:11 time: 0.8702 data_time: 0.0394 memory: 16201 loss_prob: 0.5090 loss_thr: 0.3559 loss_db: 0.0896 loss: 0.9545 2022/08/30 14:19:36 - mmengine - INFO - Epoch(train) [636][20/63] lr: 3.5507e-03 eta: 12:46:54 time: 0.8626 data_time: 0.0338 memory: 16201 loss_prob: 0.5065 loss_thr: 0.3447 loss_db: 0.0889 loss: 0.9401 2022/08/30 14:19:40 - mmengine - INFO - Epoch(train) [636][25/63] lr: 3.5507e-03 eta: 12:46:54 time: 0.8608 data_time: 0.0366 memory: 16201 loss_prob: 0.5136 loss_thr: 0.3612 loss_db: 0.0884 loss: 0.9632 2022/08/30 14:19:44 - mmengine - INFO - Epoch(train) [636][30/63] lr: 3.5507e-03 eta: 12:46:37 time: 0.8305 data_time: 0.0239 memory: 16201 loss_prob: 0.4786 loss_thr: 0.3454 loss_db: 0.0827 loss: 0.9067 2022/08/30 14:19:49 - mmengine - INFO - Epoch(train) [636][35/63] lr: 3.5507e-03 eta: 12:46:37 time: 0.8231 data_time: 0.0217 memory: 16201 loss_prob: 0.4389 loss_thr: 0.3313 loss_db: 0.0782 loss: 0.8484 2022/08/30 14:19:53 - mmengine - INFO - Epoch(train) [636][40/63] lr: 3.5507e-03 eta: 12:46:20 time: 0.8086 data_time: 0.0269 memory: 16201 loss_prob: 0.4533 loss_thr: 0.3349 loss_db: 0.0823 loss: 0.8705 2022/08/30 14:19:56 - mmengine - INFO - Epoch(train) [636][45/63] lr: 3.5507e-03 eta: 12:46:20 time: 0.7856 data_time: 0.0262 memory: 16201 loss_prob: 0.4626 loss_thr: 0.3279 loss_db: 0.0827 loss: 0.8732 2022/08/30 14:20:01 - mmengine - INFO - Epoch(train) [636][50/63] lr: 3.5507e-03 eta: 12:46:03 time: 0.8085 data_time: 0.0226 memory: 16201 loss_prob: 0.5114 loss_thr: 0.3431 loss_db: 0.0889 loss: 0.9434 2022/08/30 14:20:05 - mmengine - INFO - Epoch(train) [636][55/63] lr: 3.5507e-03 eta: 12:46:03 time: 0.8581 data_time: 0.0286 memory: 16201 loss_prob: 0.5197 loss_thr: 0.3507 loss_db: 0.0887 loss: 0.9592 2022/08/30 14:20:09 - mmengine - INFO - Epoch(train) [636][60/63] lr: 3.5507e-03 eta: 12:45:46 time: 0.8447 data_time: 0.0321 memory: 16201 loss_prob: 0.4992 loss_thr: 0.3567 loss_db: 0.0843 loss: 0.9402 2022/08/30 14:20:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:20:17 - mmengine - INFO - Epoch(train) [637][5/63] lr: 3.5451e-03 eta: 12:45:46 time: 0.9820 data_time: 0.2178 memory: 16201 loss_prob: 0.4840 loss_thr: 0.3392 loss_db: 0.0833 loss: 0.9066 2022/08/30 14:20:21 - mmengine - INFO - Epoch(train) [637][10/63] lr: 3.5451e-03 eta: 12:45:23 time: 1.0519 data_time: 0.2209 memory: 16201 loss_prob: 0.4469 loss_thr: 0.3254 loss_db: 0.0775 loss: 0.8498 2022/08/30 14:20:26 - mmengine - INFO - Epoch(train) [637][15/63] lr: 3.5451e-03 eta: 12:45:23 time: 0.8424 data_time: 0.0286 memory: 16201 loss_prob: 0.4632 loss_thr: 0.3209 loss_db: 0.0800 loss: 0.8640 2022/08/30 14:20:30 - mmengine - INFO - Epoch(train) [637][20/63] lr: 3.5451e-03 eta: 12:45:06 time: 0.8172 data_time: 0.0225 memory: 16201 loss_prob: 0.6202 loss_thr: 0.3308 loss_db: 0.0923 loss: 1.0434 2022/08/30 14:20:34 - mmengine - INFO - Epoch(train) [637][25/63] lr: 3.5451e-03 eta: 12:45:06 time: 0.8595 data_time: 0.0295 memory: 16201 loss_prob: 0.7635 loss_thr: 0.3523 loss_db: 0.1091 loss: 1.2248 2022/08/30 14:20:39 - mmengine - INFO - Epoch(train) [637][30/63] lr: 3.5451e-03 eta: 12:44:50 time: 0.8883 data_time: 0.0351 memory: 16201 loss_prob: 0.7224 loss_thr: 0.3741 loss_db: 0.1109 loss: 1.2075 2022/08/30 14:20:43 - mmengine - INFO - Epoch(train) [637][35/63] lr: 3.5451e-03 eta: 12:44:50 time: 0.8355 data_time: 0.0241 memory: 16201 loss_prob: 0.7329 loss_thr: 0.3881 loss_db: 0.1142 loss: 1.2352 2022/08/30 14:20:48 - mmengine - INFO - Epoch(train) [637][40/63] lr: 3.5451e-03 eta: 12:44:33 time: 0.8998 data_time: 0.0304 memory: 16201 loss_prob: 0.6829 loss_thr: 0.3778 loss_db: 0.1103 loss: 1.1710 2022/08/30 14:20:52 - mmengine - INFO - Epoch(train) [637][45/63] lr: 3.5451e-03 eta: 12:44:33 time: 0.8935 data_time: 0.0343 memory: 16201 loss_prob: 0.5768 loss_thr: 0.3683 loss_db: 0.0970 loss: 1.0422 2022/08/30 14:20:56 - mmengine - INFO - Epoch(train) [637][50/63] lr: 3.5451e-03 eta: 12:44:16 time: 0.8295 data_time: 0.0257 memory: 16201 loss_prob: 0.5554 loss_thr: 0.3752 loss_db: 0.0952 loss: 1.0258 2022/08/30 14:21:00 - mmengine - INFO - Epoch(train) [637][55/63] lr: 3.5451e-03 eta: 12:44:16 time: 0.8554 data_time: 0.0301 memory: 16201 loss_prob: 0.5934 loss_thr: 0.3939 loss_db: 0.1023 loss: 1.0896 2022/08/30 14:21:04 - mmengine - INFO - Epoch(train) [637][60/63] lr: 3.5451e-03 eta: 12:43:59 time: 0.8515 data_time: 0.0317 memory: 16201 loss_prob: 0.5804 loss_thr: 0.4046 loss_db: 0.0988 loss: 1.0839 2022/08/30 14:21:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:21:12 - mmengine - INFO - Epoch(train) [638][5/63] lr: 3.5394e-03 eta: 12:43:59 time: 0.9675 data_time: 0.1856 memory: 16201 loss_prob: 0.5242 loss_thr: 0.3756 loss_db: 0.0892 loss: 0.9890 2022/08/30 14:21:17 - mmengine - INFO - Epoch(train) [638][10/63] lr: 3.5394e-03 eta: 12:43:37 time: 0.9983 data_time: 0.1834 memory: 16201 loss_prob: 0.5430 loss_thr: 0.3704 loss_db: 0.0930 loss: 1.0064 2022/08/30 14:21:21 - mmengine - INFO - Epoch(train) [638][15/63] lr: 3.5394e-03 eta: 12:43:37 time: 0.8587 data_time: 0.0252 memory: 16201 loss_prob: 0.5295 loss_thr: 0.3770 loss_db: 0.0933 loss: 0.9998 2022/08/30 14:21:25 - mmengine - INFO - Epoch(train) [638][20/63] lr: 3.5394e-03 eta: 12:43:20 time: 0.8538 data_time: 0.0240 memory: 16201 loss_prob: 0.4790 loss_thr: 0.3528 loss_db: 0.0857 loss: 0.9175 2022/08/30 14:21:30 - mmengine - INFO - Epoch(train) [638][25/63] lr: 3.5394e-03 eta: 12:43:20 time: 0.8707 data_time: 0.0281 memory: 16201 loss_prob: 0.4815 loss_thr: 0.3445 loss_db: 0.0829 loss: 0.9090 2022/08/30 14:21:34 - mmengine - INFO - Epoch(train) [638][30/63] lr: 3.5394e-03 eta: 12:43:03 time: 0.8709 data_time: 0.0261 memory: 16201 loss_prob: 0.5431 loss_thr: 0.3790 loss_db: 0.0929 loss: 1.0151 2022/08/30 14:21:38 - mmengine - INFO - Epoch(train) [638][35/63] lr: 3.5394e-03 eta: 12:43:03 time: 0.8702 data_time: 0.0275 memory: 16201 loss_prob: 0.5793 loss_thr: 0.3510 loss_db: 0.1007 loss: 1.0310 2022/08/30 14:21:42 - mmengine - INFO - Epoch(train) [638][40/63] lr: 3.5394e-03 eta: 12:42:46 time: 0.8469 data_time: 0.0311 memory: 16201 loss_prob: 0.5583 loss_thr: 0.3319 loss_db: 0.0964 loss: 0.9866 2022/08/30 14:21:47 - mmengine - INFO - Epoch(train) [638][45/63] lr: 3.5394e-03 eta: 12:42:46 time: 0.8325 data_time: 0.0329 memory: 16201 loss_prob: 0.5267 loss_thr: 0.3542 loss_db: 0.0900 loss: 0.9709 2022/08/30 14:21:51 - mmengine - INFO - Epoch(train) [638][50/63] lr: 3.5394e-03 eta: 12:42:30 time: 0.8873 data_time: 0.0269 memory: 16201 loss_prob: 0.5538 loss_thr: 0.3584 loss_db: 0.0937 loss: 1.0059 2022/08/30 14:21:56 - mmengine - INFO - Epoch(train) [638][55/63] lr: 3.5394e-03 eta: 12:42:30 time: 0.8968 data_time: 0.0253 memory: 16201 loss_prob: 0.5523 loss_thr: 0.3641 loss_db: 0.0938 loss: 1.0102 2022/08/30 14:22:00 - mmengine - INFO - Epoch(train) [638][60/63] lr: 3.5394e-03 eta: 12:42:13 time: 0.8344 data_time: 0.0297 memory: 16201 loss_prob: 0.5123 loss_thr: 0.3497 loss_db: 0.0888 loss: 0.9508 2022/08/30 14:22:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:22:08 - mmengine - INFO - Epoch(train) [639][5/63] lr: 3.5337e-03 eta: 12:42:13 time: 0.9591 data_time: 0.1679 memory: 16201 loss_prob: 0.5066 loss_thr: 0.3326 loss_db: 0.0884 loss: 0.9277 2022/08/30 14:22:12 - mmengine - INFO - Epoch(train) [639][10/63] lr: 3.5337e-03 eta: 12:41:50 time: 1.0180 data_time: 0.1803 memory: 16201 loss_prob: 0.5543 loss_thr: 0.3608 loss_db: 0.0982 loss: 1.0134 2022/08/30 14:22:16 - mmengine - INFO - Epoch(train) [639][15/63] lr: 3.5337e-03 eta: 12:41:50 time: 0.8408 data_time: 0.0296 memory: 16201 loss_prob: 0.5662 loss_thr: 0.3472 loss_db: 0.0974 loss: 1.0108 2022/08/30 14:22:20 - mmengine - INFO - Epoch(train) [639][20/63] lr: 3.5337e-03 eta: 12:41:33 time: 0.8234 data_time: 0.0204 memory: 16201 loss_prob: 0.5421 loss_thr: 0.3432 loss_db: 0.0921 loss: 0.9773 2022/08/30 14:22:24 - mmengine - INFO - Epoch(train) [639][25/63] lr: 3.5337e-03 eta: 12:41:33 time: 0.8350 data_time: 0.0333 memory: 16201 loss_prob: 0.5382 loss_thr: 0.3591 loss_db: 0.0942 loss: 0.9916 2022/08/30 14:22:29 - mmengine - INFO - Epoch(train) [639][30/63] lr: 3.5337e-03 eta: 12:41:17 time: 0.8527 data_time: 0.0319 memory: 16201 loss_prob: 0.5277 loss_thr: 0.3546 loss_db: 0.0921 loss: 0.9744 2022/08/30 14:22:33 - mmengine - INFO - Epoch(train) [639][35/63] lr: 3.5337e-03 eta: 12:41:17 time: 0.8351 data_time: 0.0205 memory: 16201 loss_prob: 0.5147 loss_thr: 0.3524 loss_db: 0.0897 loss: 0.9568 2022/08/30 14:22:37 - mmengine - INFO - Epoch(train) [639][40/63] lr: 3.5337e-03 eta: 12:41:00 time: 0.8398 data_time: 0.0262 memory: 16201 loss_prob: 0.4998 loss_thr: 0.3575 loss_db: 0.0891 loss: 0.9464 2022/08/30 14:22:41 - mmengine - INFO - Epoch(train) [639][45/63] lr: 3.5337e-03 eta: 12:41:00 time: 0.8531 data_time: 0.0274 memory: 16201 loss_prob: 0.5182 loss_thr: 0.3480 loss_db: 0.0897 loss: 0.9558 2022/08/30 14:22:45 - mmengine - INFO - Epoch(train) [639][50/63] lr: 3.5337e-03 eta: 12:40:43 time: 0.8347 data_time: 0.0269 memory: 16201 loss_prob: 0.5178 loss_thr: 0.3393 loss_db: 0.0878 loss: 0.9449 2022/08/30 14:22:50 - mmengine - INFO - Epoch(train) [639][55/63] lr: 3.5337e-03 eta: 12:40:43 time: 0.8515 data_time: 0.0365 memory: 16201 loss_prob: 0.5321 loss_thr: 0.3487 loss_db: 0.0939 loss: 0.9747 2022/08/30 14:22:54 - mmengine - INFO - Epoch(train) [639][60/63] lr: 3.5337e-03 eta: 12:40:26 time: 0.8512 data_time: 0.0337 memory: 16201 loss_prob: 0.5278 loss_thr: 0.3459 loss_db: 0.0934 loss: 0.9670 2022/08/30 14:22:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:23:02 - mmengine - INFO - Epoch(train) [640][5/63] lr: 3.5281e-03 eta: 12:40:26 time: 0.9809 data_time: 0.1872 memory: 16201 loss_prob: 0.4975 loss_thr: 0.3525 loss_db: 0.0852 loss: 0.9352 2022/08/30 14:23:07 - mmengine - INFO - Epoch(train) [640][10/63] lr: 3.5281e-03 eta: 12:40:04 time: 1.0369 data_time: 0.2017 memory: 16201 loss_prob: 0.4513 loss_thr: 0.3201 loss_db: 0.0790 loss: 0.8504 2022/08/30 14:23:11 - mmengine - INFO - Epoch(train) [640][15/63] lr: 3.5281e-03 eta: 12:40:04 time: 0.8661 data_time: 0.0288 memory: 16201 loss_prob: 0.4522 loss_thr: 0.3147 loss_db: 0.0808 loss: 0.8477 2022/08/30 14:23:15 - mmengine - INFO - Epoch(train) [640][20/63] lr: 3.5281e-03 eta: 12:39:47 time: 0.8550 data_time: 0.0207 memory: 16201 loss_prob: 0.5076 loss_thr: 0.3443 loss_db: 0.0896 loss: 0.9415 2022/08/30 14:23:20 - mmengine - INFO - Epoch(train) [640][25/63] lr: 3.5281e-03 eta: 12:39:47 time: 0.8692 data_time: 0.0279 memory: 16201 loss_prob: 0.5259 loss_thr: 0.3519 loss_db: 0.0912 loss: 0.9690 2022/08/30 14:23:24 - mmengine - INFO - Epoch(train) [640][30/63] lr: 3.5281e-03 eta: 12:39:31 time: 0.9047 data_time: 0.0281 memory: 16201 loss_prob: 0.5508 loss_thr: 0.3579 loss_db: 0.0954 loss: 1.0040 2022/08/30 14:23:28 - mmengine - INFO - Epoch(train) [640][35/63] lr: 3.5281e-03 eta: 12:39:31 time: 0.8870 data_time: 0.0327 memory: 16201 loss_prob: 0.5245 loss_thr: 0.3445 loss_db: 0.0916 loss: 0.9606 2022/08/30 14:23:32 - mmengine - INFO - Epoch(train) [640][40/63] lr: 3.5281e-03 eta: 12:39:14 time: 0.8272 data_time: 0.0257 memory: 16201 loss_prob: 0.4478 loss_thr: 0.3069 loss_db: 0.0789 loss: 0.8336 2022/08/30 14:23:37 - mmengine - INFO - Epoch(train) [640][45/63] lr: 3.5281e-03 eta: 12:39:14 time: 0.8364 data_time: 0.0228 memory: 16201 loss_prob: 0.4571 loss_thr: 0.3178 loss_db: 0.0798 loss: 0.8548 2022/08/30 14:23:41 - mmengine - INFO - Epoch(train) [640][50/63] lr: 3.5281e-03 eta: 12:38:57 time: 0.8459 data_time: 0.0269 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3413 loss_db: 0.0826 loss: 0.8990 2022/08/30 14:23:45 - mmengine - INFO - Epoch(train) [640][55/63] lr: 3.5281e-03 eta: 12:38:57 time: 0.8331 data_time: 0.0213 memory: 16201 loss_prob: 0.5371 loss_thr: 0.3741 loss_db: 0.0959 loss: 1.0071 2022/08/30 14:23:50 - mmengine - INFO - Epoch(train) [640][60/63] lr: 3.5281e-03 eta: 12:38:40 time: 0.8604 data_time: 0.0255 memory: 16201 loss_prob: 0.5504 loss_thr: 0.3732 loss_db: 0.0996 loss: 1.0232 2022/08/30 14:23:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:23:52 - mmengine - INFO - Saving checkpoint at 640 epochs 2022/08/30 14:24:01 - mmengine - INFO - Epoch(val) [640][5/32] eta: 12:38:40 time: 0.6104 data_time: 0.0858 memory: 16201 2022/08/30 14:24:04 - mmengine - INFO - Epoch(val) [640][10/32] eta: 0:00:14 time: 0.6582 data_time: 0.0886 memory: 15734 2022/08/30 14:24:07 - mmengine - INFO - Epoch(val) [640][15/32] eta: 0:00:14 time: 0.6051 data_time: 0.0429 memory: 15734 2022/08/30 14:24:11 - mmengine - INFO - Epoch(val) [640][20/32] eta: 0:00:07 time: 0.6411 data_time: 0.0623 memory: 15734 2022/08/30 14:24:14 - mmengine - INFO - Epoch(val) [640][25/32] eta: 0:00:07 time: 0.6752 data_time: 0.0565 memory: 15734 2022/08/30 14:24:17 - mmengine - INFO - Epoch(val) [640][30/32] eta: 0:00:01 time: 0.6419 data_time: 0.0415 memory: 15734 2022/08/30 14:24:18 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 14:24:18 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8512, precision: 0.7530, hmean: 0.7991 2022/08/30 14:24:18 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8507, precision: 0.7959, hmean: 0.8224 2022/08/30 14:24:18 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8498, precision: 0.8236, hmean: 0.8365 2022/08/30 14:24:18 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8455, precision: 0.8475, hmean: 0.8465 2022/08/30 14:24:18 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8339, precision: 0.8686, hmean: 0.8509 2022/08/30 14:24:18 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7790, precision: 0.9100, hmean: 0.8394 2022/08/30 14:24:18 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2017, precision: 0.9523, hmean: 0.3329 2022/08/30 14:24:18 - mmengine - INFO - Epoch(val) [640][32/32] icdar/precision: 0.8686 icdar/recall: 0.8339 icdar/hmean: 0.8509 2022/08/30 14:24:24 - mmengine - INFO - Epoch(train) [641][5/63] lr: 3.5224e-03 eta: 0:00:01 time: 0.9594 data_time: 0.1628 memory: 16201 loss_prob: 0.4876 loss_thr: 0.3341 loss_db: 0.0840 loss: 0.9057 2022/08/30 14:24:28 - mmengine - INFO - Epoch(train) [641][10/63] lr: 3.5224e-03 eta: 12:38:17 time: 0.9884 data_time: 0.1714 memory: 16201 loss_prob: 0.4875 loss_thr: 0.3154 loss_db: 0.0839 loss: 0.8868 2022/08/30 14:24:32 - mmengine - INFO - Epoch(train) [641][15/63] lr: 3.5224e-03 eta: 12:38:17 time: 0.8379 data_time: 0.0213 memory: 16201 loss_prob: 0.5009 loss_thr: 0.3303 loss_db: 0.0868 loss: 0.9180 2022/08/30 14:24:36 - mmengine - INFO - Epoch(train) [641][20/63] lr: 3.5224e-03 eta: 12:38:01 time: 0.8473 data_time: 0.0267 memory: 16201 loss_prob: 0.4672 loss_thr: 0.3405 loss_db: 0.0824 loss: 0.8901 2022/08/30 14:24:41 - mmengine - INFO - Epoch(train) [641][25/63] lr: 3.5224e-03 eta: 12:38:01 time: 0.8609 data_time: 0.0249 memory: 16201 loss_prob: 0.4873 loss_thr: 0.3520 loss_db: 0.0860 loss: 0.9254 2022/08/30 14:24:45 - mmengine - INFO - Epoch(train) [641][30/63] lr: 3.5224e-03 eta: 12:37:44 time: 0.9130 data_time: 0.0225 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3465 loss_db: 0.0849 loss: 0.9209 2022/08/30 14:24:50 - mmengine - INFO - Epoch(train) [641][35/63] lr: 3.5224e-03 eta: 12:37:44 time: 0.9003 data_time: 0.0365 memory: 16201 loss_prob: 0.4503 loss_thr: 0.3206 loss_db: 0.0774 loss: 0.8483 2022/08/30 14:24:54 - mmengine - INFO - Epoch(train) [641][40/63] lr: 3.5224e-03 eta: 12:37:28 time: 0.8380 data_time: 0.0242 memory: 16201 loss_prob: 0.4636 loss_thr: 0.3272 loss_db: 0.0795 loss: 0.8703 2022/08/30 14:24:58 - mmengine - INFO - Epoch(train) [641][45/63] lr: 3.5224e-03 eta: 12:37:28 time: 0.8125 data_time: 0.0174 memory: 16201 loss_prob: 0.4805 loss_thr: 0.3402 loss_db: 0.0822 loss: 0.9029 2022/08/30 14:25:03 - mmengine - INFO - Epoch(train) [641][50/63] lr: 3.5224e-03 eta: 12:37:11 time: 0.8849 data_time: 0.0302 memory: 16201 loss_prob: 0.4619 loss_thr: 0.3265 loss_db: 0.0807 loss: 0.8692 2022/08/30 14:25:07 - mmengine - INFO - Epoch(train) [641][55/63] lr: 3.5224e-03 eta: 12:37:11 time: 0.8850 data_time: 0.0243 memory: 16201 loss_prob: 0.4661 loss_thr: 0.3309 loss_db: 0.0814 loss: 0.8784 2022/08/30 14:25:11 - mmengine - INFO - Epoch(train) [641][60/63] lr: 3.5224e-03 eta: 12:36:54 time: 0.8204 data_time: 0.0188 memory: 16201 loss_prob: 0.4835 loss_thr: 0.3451 loss_db: 0.0851 loss: 0.9137 2022/08/30 14:25:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:25:19 - mmengine - INFO - Epoch(train) [642][5/63] lr: 3.5167e-03 eta: 12:36:54 time: 1.0144 data_time: 0.2304 memory: 16201 loss_prob: 0.4616 loss_thr: 0.3316 loss_db: 0.0797 loss: 0.8729 2022/08/30 14:25:23 - mmengine - INFO - Epoch(train) [642][10/63] lr: 3.5167e-03 eta: 12:36:32 time: 1.0603 data_time: 0.2362 memory: 16201 loss_prob: 0.4477 loss_thr: 0.3084 loss_db: 0.0781 loss: 0.8341 2022/08/30 14:25:28 - mmengine - INFO - Epoch(train) [642][15/63] lr: 3.5167e-03 eta: 12:36:32 time: 0.8379 data_time: 0.0269 memory: 16201 loss_prob: 0.4456 loss_thr: 0.3067 loss_db: 0.0795 loss: 0.8318 2022/08/30 14:25:32 - mmengine - INFO - Epoch(train) [642][20/63] lr: 3.5167e-03 eta: 12:36:15 time: 0.8470 data_time: 0.0239 memory: 16201 loss_prob: 0.4556 loss_thr: 0.3164 loss_db: 0.0817 loss: 0.8537 2022/08/30 14:25:36 - mmengine - INFO - Epoch(train) [642][25/63] lr: 3.5167e-03 eta: 12:36:15 time: 0.8780 data_time: 0.0243 memory: 16201 loss_prob: 0.4582 loss_thr: 0.3230 loss_db: 0.0811 loss: 0.8622 2022/08/30 14:25:41 - mmengine - INFO - Epoch(train) [642][30/63] lr: 3.5167e-03 eta: 12:35:59 time: 0.8781 data_time: 0.0241 memory: 16201 loss_prob: 0.4567 loss_thr: 0.3232 loss_db: 0.0798 loss: 0.8597 2022/08/30 14:25:45 - mmengine - INFO - Epoch(train) [642][35/63] lr: 3.5167e-03 eta: 12:35:59 time: 0.8625 data_time: 0.0295 memory: 16201 loss_prob: 0.4660 loss_thr: 0.3174 loss_db: 0.0813 loss: 0.8647 2022/08/30 14:25:49 - mmengine - INFO - Epoch(train) [642][40/63] lr: 3.5167e-03 eta: 12:35:42 time: 0.8370 data_time: 0.0224 memory: 16201 loss_prob: 0.4704 loss_thr: 0.3257 loss_db: 0.0827 loss: 0.8789 2022/08/30 14:25:53 - mmengine - INFO - Epoch(train) [642][45/63] lr: 3.5167e-03 eta: 12:35:42 time: 0.8141 data_time: 0.0244 memory: 16201 loss_prob: 0.4938 loss_thr: 0.3308 loss_db: 0.0838 loss: 0.9084 2022/08/30 14:25:58 - mmengine - INFO - Epoch(train) [642][50/63] lr: 3.5167e-03 eta: 12:35:25 time: 0.8680 data_time: 0.0370 memory: 16201 loss_prob: 0.4593 loss_thr: 0.3112 loss_db: 0.0768 loss: 0.8473 2022/08/30 14:26:02 - mmengine - INFO - Epoch(train) [642][55/63] lr: 3.5167e-03 eta: 12:35:25 time: 0.8387 data_time: 0.0235 memory: 16201 loss_prob: 0.4263 loss_thr: 0.3090 loss_db: 0.0754 loss: 0.8107 2022/08/30 14:26:06 - mmengine - INFO - Epoch(train) [642][60/63] lr: 3.5167e-03 eta: 12:35:08 time: 0.8049 data_time: 0.0212 memory: 16201 loss_prob: 0.5709 loss_thr: 0.3667 loss_db: 0.0946 loss: 1.0321 2022/08/30 14:26:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:26:13 - mmengine - INFO - Epoch(train) [643][5/63] lr: 3.5110e-03 eta: 12:35:08 time: 0.9023 data_time: 0.1469 memory: 16201 loss_prob: 0.5529 loss_thr: 0.3837 loss_db: 0.0970 loss: 1.0336 2022/08/30 14:26:17 - mmengine - INFO - Epoch(train) [643][10/63] lr: 3.5110e-03 eta: 12:34:45 time: 0.9527 data_time: 0.1647 memory: 16201 loss_prob: 0.5516 loss_thr: 0.3672 loss_db: 0.0973 loss: 1.0161 2022/08/30 14:26:22 - mmengine - INFO - Epoch(train) [643][15/63] lr: 3.5110e-03 eta: 12:34:45 time: 0.8498 data_time: 0.0287 memory: 16201 loss_prob: 0.5065 loss_thr: 0.3392 loss_db: 0.0889 loss: 0.9345 2022/08/30 14:26:26 - mmengine - INFO - Epoch(train) [643][20/63] lr: 3.5110e-03 eta: 12:34:29 time: 0.8555 data_time: 0.0199 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3369 loss_db: 0.0829 loss: 0.8948 2022/08/30 14:26:30 - mmengine - INFO - Epoch(train) [643][25/63] lr: 3.5110e-03 eta: 12:34:29 time: 0.8303 data_time: 0.0286 memory: 16201 loss_prob: 0.4638 loss_thr: 0.3376 loss_db: 0.0815 loss: 0.8828 2022/08/30 14:26:34 - mmengine - INFO - Epoch(train) [643][30/63] lr: 3.5110e-03 eta: 12:34:12 time: 0.8227 data_time: 0.0255 memory: 16201 loss_prob: 0.5082 loss_thr: 0.3463 loss_db: 0.0885 loss: 0.9430 2022/08/30 14:26:38 - mmengine - INFO - Epoch(train) [643][35/63] lr: 3.5110e-03 eta: 12:34:12 time: 0.8285 data_time: 0.0277 memory: 16201 loss_prob: 0.5177 loss_thr: 0.3475 loss_db: 0.0894 loss: 0.9546 2022/08/30 14:26:42 - mmengine - INFO - Epoch(train) [643][40/63] lr: 3.5110e-03 eta: 12:33:55 time: 0.8198 data_time: 0.0293 memory: 16201 loss_prob: 0.4704 loss_thr: 0.3190 loss_db: 0.0828 loss: 0.8723 2022/08/30 14:26:47 - mmengine - INFO - Epoch(train) [643][45/63] lr: 3.5110e-03 eta: 12:33:55 time: 0.8332 data_time: 0.0224 memory: 16201 loss_prob: 0.5351 loss_thr: 0.3437 loss_db: 0.0915 loss: 0.9704 2022/08/30 14:26:51 - mmengine - INFO - Epoch(train) [643][50/63] lr: 3.5110e-03 eta: 12:33:38 time: 0.8582 data_time: 0.0285 memory: 16201 loss_prob: 0.5308 loss_thr: 0.3434 loss_db: 0.0898 loss: 0.9640 2022/08/30 14:26:55 - mmengine - INFO - Epoch(train) [643][55/63] lr: 3.5110e-03 eta: 12:33:38 time: 0.8423 data_time: 0.0314 memory: 16201 loss_prob: 0.4962 loss_thr: 0.3364 loss_db: 0.0862 loss: 0.9188 2022/08/30 14:26:59 - mmengine - INFO - Epoch(train) [643][60/63] lr: 3.5110e-03 eta: 12:33:21 time: 0.8315 data_time: 0.0277 memory: 16201 loss_prob: 0.5118 loss_thr: 0.3594 loss_db: 0.0891 loss: 0.9603 2022/08/30 14:27:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:27:07 - mmengine - INFO - Epoch(train) [644][5/63] lr: 3.5054e-03 eta: 12:33:21 time: 0.9589 data_time: 0.1825 memory: 16201 loss_prob: 0.4779 loss_thr: 0.3261 loss_db: 0.0842 loss: 0.8882 2022/08/30 14:27:11 - mmengine - INFO - Epoch(train) [644][10/63] lr: 3.5054e-03 eta: 12:32:59 time: 1.0226 data_time: 0.1998 memory: 16201 loss_prob: 0.5125 loss_thr: 0.3447 loss_db: 0.0879 loss: 0.9451 2022/08/30 14:27:16 - mmengine - INFO - Epoch(train) [644][15/63] lr: 3.5054e-03 eta: 12:32:59 time: 0.8804 data_time: 0.0291 memory: 16201 loss_prob: 0.4903 loss_thr: 0.3399 loss_db: 0.0843 loss: 0.9144 2022/08/30 14:27:20 - mmengine - INFO - Epoch(train) [644][20/63] lr: 3.5054e-03 eta: 12:32:42 time: 0.8828 data_time: 0.0232 memory: 16201 loss_prob: 0.4599 loss_thr: 0.3300 loss_db: 0.0807 loss: 0.8706 2022/08/30 14:27:25 - mmengine - INFO - Epoch(train) [644][25/63] lr: 3.5054e-03 eta: 12:32:42 time: 0.8519 data_time: 0.0278 memory: 16201 loss_prob: 0.4269 loss_thr: 0.3008 loss_db: 0.0759 loss: 0.8035 2022/08/30 14:27:28 - mmengine - INFO - Epoch(train) [644][30/63] lr: 3.5054e-03 eta: 12:32:26 time: 0.8189 data_time: 0.0231 memory: 16201 loss_prob: 0.4261 loss_thr: 0.2999 loss_db: 0.0766 loss: 0.8026 2022/08/30 14:27:33 - mmengine - INFO - Epoch(train) [644][35/63] lr: 3.5054e-03 eta: 12:32:26 time: 0.8151 data_time: 0.0252 memory: 16201 loss_prob: 0.4561 loss_thr: 0.3183 loss_db: 0.0796 loss: 0.8539 2022/08/30 14:27:37 - mmengine - INFO - Epoch(train) [644][40/63] lr: 3.5054e-03 eta: 12:32:09 time: 0.8530 data_time: 0.0237 memory: 16201 loss_prob: 0.4860 loss_thr: 0.3301 loss_db: 0.0814 loss: 0.8976 2022/08/30 14:27:41 - mmengine - INFO - Epoch(train) [644][45/63] lr: 3.5054e-03 eta: 12:32:09 time: 0.8561 data_time: 0.0255 memory: 16201 loss_prob: 0.5167 loss_thr: 0.3443 loss_db: 0.0872 loss: 0.9483 2022/08/30 14:27:45 - mmengine - INFO - Epoch(train) [644][50/63] lr: 3.5054e-03 eta: 12:31:52 time: 0.8075 data_time: 0.0295 memory: 16201 loss_prob: 0.4934 loss_thr: 0.3335 loss_db: 0.0866 loss: 0.9135 2022/08/30 14:27:49 - mmengine - INFO - Epoch(train) [644][55/63] lr: 3.5054e-03 eta: 12:31:52 time: 0.7799 data_time: 0.0223 memory: 16201 loss_prob: 0.4898 loss_thr: 0.3317 loss_db: 0.0848 loss: 0.9063 2022/08/30 14:27:53 - mmengine - INFO - Epoch(train) [644][60/63] lr: 3.5054e-03 eta: 12:31:35 time: 0.7827 data_time: 0.0203 memory: 16201 loss_prob: 0.4832 loss_thr: 0.3295 loss_db: 0.0823 loss: 0.8949 2022/08/30 14:27:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:28:01 - mmengine - INFO - Epoch(train) [645][5/63] lr: 3.4997e-03 eta: 12:31:35 time: 0.9511 data_time: 0.2030 memory: 16201 loss_prob: 0.4862 loss_thr: 0.3347 loss_db: 0.0868 loss: 0.9077 2022/08/30 14:28:05 - mmengine - INFO - Epoch(train) [645][10/63] lr: 3.4997e-03 eta: 12:31:12 time: 0.9945 data_time: 0.2115 memory: 16201 loss_prob: 0.4846 loss_thr: 0.3386 loss_db: 0.0839 loss: 0.9071 2022/08/30 14:28:09 - mmengine - INFO - Epoch(train) [645][15/63] lr: 3.4997e-03 eta: 12:31:12 time: 0.8469 data_time: 0.0277 memory: 16201 loss_prob: 0.4619 loss_thr: 0.3410 loss_db: 0.0812 loss: 0.8842 2022/08/30 14:28:13 - mmengine - INFO - Epoch(train) [645][20/63] lr: 3.4997e-03 eta: 12:30:55 time: 0.8378 data_time: 0.0276 memory: 16201 loss_prob: 0.4889 loss_thr: 0.3549 loss_db: 0.0866 loss: 0.9303 2022/08/30 14:28:18 - mmengine - INFO - Epoch(train) [645][25/63] lr: 3.4997e-03 eta: 12:30:55 time: 0.9105 data_time: 0.0322 memory: 16201 loss_prob: 0.4726 loss_thr: 0.3475 loss_db: 0.0825 loss: 0.9027 2022/08/30 14:28:23 - mmengine - INFO - Epoch(train) [645][30/63] lr: 3.4997e-03 eta: 12:30:39 time: 0.9119 data_time: 0.0311 memory: 16201 loss_prob: 0.4438 loss_thr: 0.3266 loss_db: 0.0775 loss: 0.8478 2022/08/30 14:28:27 - mmengine - INFO - Epoch(train) [645][35/63] lr: 3.4997e-03 eta: 12:30:39 time: 0.8407 data_time: 0.0314 memory: 16201 loss_prob: 0.4272 loss_thr: 0.3104 loss_db: 0.0751 loss: 0.8127 2022/08/30 14:28:31 - mmengine - INFO - Epoch(train) [645][40/63] lr: 3.4997e-03 eta: 12:30:22 time: 0.8265 data_time: 0.0291 memory: 16201 loss_prob: 0.4223 loss_thr: 0.3113 loss_db: 0.0735 loss: 0.8071 2022/08/30 14:28:36 - mmengine - INFO - Epoch(train) [645][45/63] lr: 3.4997e-03 eta: 12:30:22 time: 0.8778 data_time: 0.0257 memory: 16201 loss_prob: 0.4364 loss_thr: 0.3063 loss_db: 0.0743 loss: 0.8170 2022/08/30 14:28:40 - mmengine - INFO - Epoch(train) [645][50/63] lr: 3.4997e-03 eta: 12:30:06 time: 0.8946 data_time: 0.0240 memory: 16201 loss_prob: 0.4364 loss_thr: 0.3038 loss_db: 0.0751 loss: 0.8153 2022/08/30 14:28:44 - mmengine - INFO - Epoch(train) [645][55/63] lr: 3.4997e-03 eta: 12:30:06 time: 0.8282 data_time: 0.0231 memory: 16201 loss_prob: 0.4606 loss_thr: 0.3248 loss_db: 0.0809 loss: 0.8663 2022/08/30 14:28:48 - mmengine - INFO - Epoch(train) [645][60/63] lr: 3.4997e-03 eta: 12:29:49 time: 0.8155 data_time: 0.0269 memory: 16201 loss_prob: 0.4668 loss_thr: 0.3237 loss_db: 0.0831 loss: 0.8735 2022/08/30 14:28:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:28:55 - mmengine - INFO - Epoch(train) [646][5/63] lr: 3.4940e-03 eta: 12:29:49 time: 0.9091 data_time: 0.1474 memory: 16201 loss_prob: 0.4666 loss_thr: 0.3318 loss_db: 0.0808 loss: 0.8792 2022/08/30 14:28:59 - mmengine - INFO - Epoch(train) [646][10/63] lr: 3.4940e-03 eta: 12:29:26 time: 0.9655 data_time: 0.1521 memory: 16201 loss_prob: 0.4946 loss_thr: 0.3381 loss_db: 0.0847 loss: 0.9174 2022/08/30 14:29:04 - mmengine - INFO - Epoch(train) [646][15/63] lr: 3.4940e-03 eta: 12:29:26 time: 0.8071 data_time: 0.0247 memory: 16201 loss_prob: 0.4809 loss_thr: 0.3277 loss_db: 0.0845 loss: 0.8932 2022/08/30 14:29:08 - mmengine - INFO - Epoch(train) [646][20/63] lr: 3.4940e-03 eta: 12:29:10 time: 0.8318 data_time: 0.0291 memory: 16201 loss_prob: 0.4665 loss_thr: 0.3233 loss_db: 0.0820 loss: 0.8719 2022/08/30 14:29:12 - mmengine - INFO - Epoch(train) [646][25/63] lr: 3.4940e-03 eta: 12:29:10 time: 0.8298 data_time: 0.0304 memory: 16201 loss_prob: 0.4368 loss_thr: 0.2995 loss_db: 0.0753 loss: 0.8115 2022/08/30 14:29:16 - mmengine - INFO - Epoch(train) [646][30/63] lr: 3.4940e-03 eta: 12:28:53 time: 0.8292 data_time: 0.0250 memory: 16201 loss_prob: 0.4182 loss_thr: 0.3056 loss_db: 0.0721 loss: 0.7959 2022/08/30 14:29:20 - mmengine - INFO - Epoch(train) [646][35/63] lr: 3.4940e-03 eta: 12:28:53 time: 0.8367 data_time: 0.0230 memory: 16201 loss_prob: 0.4892 loss_thr: 0.3500 loss_db: 0.0838 loss: 0.9231 2022/08/30 14:29:25 - mmengine - INFO - Epoch(train) [646][40/63] lr: 3.4940e-03 eta: 12:28:36 time: 0.8594 data_time: 0.0277 memory: 16201 loss_prob: 0.4494 loss_thr: 0.3123 loss_db: 0.0784 loss: 0.8400 2022/08/30 14:29:29 - mmengine - INFO - Epoch(train) [646][45/63] lr: 3.4940e-03 eta: 12:28:36 time: 0.9135 data_time: 0.0311 memory: 16201 loss_prob: 0.4000 loss_thr: 0.2821 loss_db: 0.0710 loss: 0.7531 2022/08/30 14:29:33 - mmengine - INFO - Epoch(train) [646][50/63] lr: 3.4940e-03 eta: 12:28:20 time: 0.8692 data_time: 0.0239 memory: 16201 loss_prob: 0.4539 loss_thr: 0.3238 loss_db: 0.0795 loss: 0.8572 2022/08/30 14:29:38 - mmengine - INFO - Epoch(train) [646][55/63] lr: 3.4940e-03 eta: 12:28:20 time: 0.8217 data_time: 0.0274 memory: 16201 loss_prob: 0.4509 loss_thr: 0.3358 loss_db: 0.0791 loss: 0.8658 2022/08/30 14:29:42 - mmengine - INFO - Epoch(train) [646][60/63] lr: 3.4940e-03 eta: 12:28:03 time: 0.8419 data_time: 0.0306 memory: 16201 loss_prob: 0.4315 loss_thr: 0.3205 loss_db: 0.0758 loss: 0.8278 2022/08/30 14:29:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:29:50 - mmengine - INFO - Epoch(train) [647][5/63] lr: 3.4883e-03 eta: 12:28:03 time: 1.0197 data_time: 0.2438 memory: 16201 loss_prob: 0.4504 loss_thr: 0.3224 loss_db: 0.0806 loss: 0.8533 2022/08/30 14:29:54 - mmengine - INFO - Epoch(train) [647][10/63] lr: 3.4883e-03 eta: 12:27:41 time: 1.0462 data_time: 0.2600 memory: 16201 loss_prob: 0.4940 loss_thr: 0.3416 loss_db: 0.0863 loss: 0.9220 2022/08/30 14:29:59 - mmengine - INFO - Epoch(train) [647][15/63] lr: 3.4883e-03 eta: 12:27:41 time: 0.8168 data_time: 0.0352 memory: 16201 loss_prob: 0.4637 loss_thr: 0.3267 loss_db: 0.0823 loss: 0.8727 2022/08/30 14:30:02 - mmengine - INFO - Epoch(train) [647][20/63] lr: 3.4883e-03 eta: 12:27:24 time: 0.8019 data_time: 0.0212 memory: 16201 loss_prob: 0.4755 loss_thr: 0.3420 loss_db: 0.0849 loss: 0.9024 2022/08/30 14:30:07 - mmengine - INFO - Epoch(train) [647][25/63] lr: 3.4883e-03 eta: 12:27:24 time: 0.8648 data_time: 0.0476 memory: 16201 loss_prob: 0.4800 loss_thr: 0.3524 loss_db: 0.0834 loss: 0.9158 2022/08/30 14:30:11 - mmengine - INFO - Epoch(train) [647][30/63] lr: 3.4883e-03 eta: 12:27:08 time: 0.8735 data_time: 0.0437 memory: 16201 loss_prob: 0.4438 loss_thr: 0.3205 loss_db: 0.0766 loss: 0.8409 2022/08/30 14:30:15 - mmengine - INFO - Epoch(train) [647][35/63] lr: 3.4883e-03 eta: 12:27:08 time: 0.8153 data_time: 0.0241 memory: 16201 loss_prob: 0.4728 loss_thr: 0.3147 loss_db: 0.0814 loss: 0.8690 2022/08/30 14:30:20 - mmengine - INFO - Epoch(train) [647][40/63] lr: 3.4883e-03 eta: 12:26:51 time: 0.8367 data_time: 0.0308 memory: 16201 loss_prob: 0.4913 loss_thr: 0.3344 loss_db: 0.0841 loss: 0.9099 2022/08/30 14:30:24 - mmengine - INFO - Epoch(train) [647][45/63] lr: 3.4883e-03 eta: 12:26:51 time: 0.8271 data_time: 0.0295 memory: 16201 loss_prob: 0.4968 loss_thr: 0.3477 loss_db: 0.0863 loss: 0.9308 2022/08/30 14:30:28 - mmengine - INFO - Epoch(train) [647][50/63] lr: 3.4883e-03 eta: 12:26:35 time: 0.8639 data_time: 0.0302 memory: 16201 loss_prob: 0.4906 loss_thr: 0.3366 loss_db: 0.0859 loss: 0.9131 2022/08/30 14:30:32 - mmengine - INFO - Epoch(train) [647][55/63] lr: 3.4883e-03 eta: 12:26:35 time: 0.8591 data_time: 0.0263 memory: 16201 loss_prob: 0.4487 loss_thr: 0.3131 loss_db: 0.0786 loss: 0.8404 2022/08/30 14:30:37 - mmengine - INFO - Epoch(train) [647][60/63] lr: 3.4883e-03 eta: 12:26:18 time: 0.8400 data_time: 0.0281 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2936 loss_db: 0.0712 loss: 0.7685 2022/08/30 14:30:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:30:45 - mmengine - INFO - Epoch(train) [648][5/63] lr: 3.4827e-03 eta: 12:26:18 time: 1.0216 data_time: 0.2248 memory: 16201 loss_prob: 0.4324 loss_thr: 0.3128 loss_db: 0.0760 loss: 0.8212 2022/08/30 14:30:50 - mmengine - INFO - Epoch(train) [648][10/63] lr: 3.4827e-03 eta: 12:25:56 time: 1.0599 data_time: 0.2408 memory: 16201 loss_prob: 0.4581 loss_thr: 0.3194 loss_db: 0.0804 loss: 0.8580 2022/08/30 14:30:54 - mmengine - INFO - Epoch(train) [648][15/63] lr: 3.4827e-03 eta: 12:25:56 time: 0.8534 data_time: 0.0300 memory: 16201 loss_prob: 0.4889 loss_thr: 0.3223 loss_db: 0.0844 loss: 0.8955 2022/08/30 14:30:58 - mmengine - INFO - Epoch(train) [648][20/63] lr: 3.4827e-03 eta: 12:25:39 time: 0.8236 data_time: 0.0187 memory: 16201 loss_prob: 0.4875 loss_thr: 0.3301 loss_db: 0.0838 loss: 0.9014 2022/08/30 14:31:02 - mmengine - INFO - Epoch(train) [648][25/63] lr: 3.4827e-03 eta: 12:25:39 time: 0.8360 data_time: 0.0333 memory: 16201 loss_prob: 0.4701 loss_thr: 0.3265 loss_db: 0.0808 loss: 0.8774 2022/08/30 14:31:06 - mmengine - INFO - Epoch(train) [648][30/63] lr: 3.4827e-03 eta: 12:25:22 time: 0.8190 data_time: 0.0248 memory: 16201 loss_prob: 0.4650 loss_thr: 0.3270 loss_db: 0.0802 loss: 0.8721 2022/08/30 14:31:10 - mmengine - INFO - Epoch(train) [648][35/63] lr: 3.4827e-03 eta: 12:25:22 time: 0.8069 data_time: 0.0188 memory: 16201 loss_prob: 0.4837 loss_thr: 0.3319 loss_db: 0.0837 loss: 0.8994 2022/08/30 14:31:14 - mmengine - INFO - Epoch(train) [648][40/63] lr: 3.4827e-03 eta: 12:25:06 time: 0.8361 data_time: 0.0251 memory: 16201 loss_prob: 0.4757 loss_thr: 0.3174 loss_db: 0.0820 loss: 0.8751 2022/08/30 14:31:18 - mmengine - INFO - Epoch(train) [648][45/63] lr: 3.4827e-03 eta: 12:25:06 time: 0.8260 data_time: 0.0246 memory: 16201 loss_prob: 0.4730 loss_thr: 0.3281 loss_db: 0.0819 loss: 0.8829 2022/08/30 14:31:22 - mmengine - INFO - Epoch(train) [648][50/63] lr: 3.4827e-03 eta: 12:24:49 time: 0.8085 data_time: 0.0268 memory: 16201 loss_prob: 0.4811 loss_thr: 0.3393 loss_db: 0.0844 loss: 0.9047 2022/08/30 14:31:26 - mmengine - INFO - Epoch(train) [648][55/63] lr: 3.4827e-03 eta: 12:24:49 time: 0.8116 data_time: 0.0226 memory: 16201 loss_prob: 0.4244 loss_thr: 0.3110 loss_db: 0.0749 loss: 0.8102 2022/08/30 14:31:31 - mmengine - INFO - Epoch(train) [648][60/63] lr: 3.4827e-03 eta: 12:24:32 time: 0.8242 data_time: 0.0310 memory: 16201 loss_prob: 0.4101 loss_thr: 0.3056 loss_db: 0.0728 loss: 0.7885 2022/08/30 14:31:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:31:38 - mmengine - INFO - Epoch(train) [649][5/63] lr: 3.4770e-03 eta: 12:24:32 time: 0.9288 data_time: 0.1935 memory: 16201 loss_prob: 0.4575 loss_thr: 0.3144 loss_db: 0.0807 loss: 0.8526 2022/08/30 14:31:43 - mmengine - INFO - Epoch(train) [649][10/63] lr: 3.4770e-03 eta: 12:24:10 time: 0.9865 data_time: 0.2053 memory: 16201 loss_prob: 0.4698 loss_thr: 0.3194 loss_db: 0.0806 loss: 0.8699 2022/08/30 14:31:47 - mmengine - INFO - Epoch(train) [649][15/63] lr: 3.4770e-03 eta: 12:24:10 time: 0.8873 data_time: 0.0246 memory: 16201 loss_prob: 0.4317 loss_thr: 0.3100 loss_db: 0.0749 loss: 0.8166 2022/08/30 14:31:51 - mmengine - INFO - Epoch(train) [649][20/63] lr: 3.4770e-03 eta: 12:23:53 time: 0.8733 data_time: 0.0195 memory: 16201 loss_prob: 0.4610 loss_thr: 0.3233 loss_db: 0.0794 loss: 0.8638 2022/08/30 14:31:55 - mmengine - INFO - Epoch(train) [649][25/63] lr: 3.4770e-03 eta: 12:23:53 time: 0.8021 data_time: 0.0313 memory: 16201 loss_prob: 0.5104 loss_thr: 0.3280 loss_db: 0.0894 loss: 0.9278 2022/08/30 14:31:59 - mmengine - INFO - Epoch(train) [649][30/63] lr: 3.4770e-03 eta: 12:23:36 time: 0.7934 data_time: 0.0294 memory: 16201 loss_prob: 0.4979 loss_thr: 0.3121 loss_db: 0.0887 loss: 0.8987 2022/08/30 14:32:04 - mmengine - INFO - Epoch(train) [649][35/63] lr: 3.4770e-03 eta: 12:23:36 time: 0.8199 data_time: 0.0190 memory: 16201 loss_prob: 0.4494 loss_thr: 0.3078 loss_db: 0.0797 loss: 0.8370 2022/08/30 14:32:07 - mmengine - INFO - Epoch(train) [649][40/63] lr: 3.4770e-03 eta: 12:23:19 time: 0.8246 data_time: 0.0281 memory: 16201 loss_prob: 0.4546 loss_thr: 0.3243 loss_db: 0.0809 loss: 0.8598 2022/08/30 14:32:12 - mmengine - INFO - Epoch(train) [649][45/63] lr: 3.4770e-03 eta: 12:23:19 time: 0.8181 data_time: 0.0299 memory: 16201 loss_prob: 0.4756 loss_thr: 0.3306 loss_db: 0.0836 loss: 0.8898 2022/08/30 14:32:16 - mmengine - INFO - Epoch(train) [649][50/63] lr: 3.4770e-03 eta: 12:23:03 time: 0.8654 data_time: 0.0245 memory: 16201 loss_prob: 0.4780 loss_thr: 0.3236 loss_db: 0.0831 loss: 0.8848 2022/08/30 14:32:20 - mmengine - INFO - Epoch(train) [649][55/63] lr: 3.4770e-03 eta: 12:23:03 time: 0.8501 data_time: 0.0258 memory: 16201 loss_prob: 0.5032 loss_thr: 0.3522 loss_db: 0.0853 loss: 0.9407 2022/08/30 14:32:24 - mmengine - INFO - Epoch(train) [649][60/63] lr: 3.4770e-03 eta: 12:22:46 time: 0.8114 data_time: 0.0229 memory: 16201 loss_prob: 0.5037 loss_thr: 0.3656 loss_db: 0.0858 loss: 0.9551 2022/08/30 14:32:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:32:32 - mmengine - INFO - Epoch(train) [650][5/63] lr: 3.4713e-03 eta: 12:22:46 time: 0.9693 data_time: 0.1999 memory: 16201 loss_prob: 0.4815 loss_thr: 0.3382 loss_db: 0.0835 loss: 0.9032 2022/08/30 14:32:36 - mmengine - INFO - Epoch(train) [650][10/63] lr: 3.4713e-03 eta: 12:22:24 time: 1.0031 data_time: 0.2104 memory: 16201 loss_prob: 0.5150 loss_thr: 0.3568 loss_db: 0.0909 loss: 0.9628 2022/08/30 14:32:41 - mmengine - INFO - Epoch(train) [650][15/63] lr: 3.4713e-03 eta: 12:22:24 time: 0.8714 data_time: 0.0254 memory: 16201 loss_prob: 0.5140 loss_thr: 0.3529 loss_db: 0.0908 loss: 0.9576 2022/08/30 14:32:45 - mmengine - INFO - Epoch(train) [650][20/63] lr: 3.4713e-03 eta: 12:22:08 time: 0.8804 data_time: 0.0180 memory: 16201 loss_prob: 0.4666 loss_thr: 0.3229 loss_db: 0.0802 loss: 0.8698 2022/08/30 14:32:50 - mmengine - INFO - Epoch(train) [650][25/63] lr: 3.4713e-03 eta: 12:22:08 time: 0.8547 data_time: 0.0322 memory: 16201 loss_prob: 0.4631 loss_thr: 0.3316 loss_db: 0.0794 loss: 0.8742 2022/08/30 14:32:53 - mmengine - INFO - Epoch(train) [650][30/63] lr: 3.4713e-03 eta: 12:21:51 time: 0.8113 data_time: 0.0237 memory: 16201 loss_prob: 0.4605 loss_thr: 0.3321 loss_db: 0.0784 loss: 0.8711 2022/08/30 14:32:58 - mmengine - INFO - Epoch(train) [650][35/63] lr: 3.4713e-03 eta: 12:21:51 time: 0.8483 data_time: 0.0207 memory: 16201 loss_prob: 0.4499 loss_thr: 0.3169 loss_db: 0.0784 loss: 0.8452 2022/08/30 14:33:02 - mmengine - INFO - Epoch(train) [650][40/63] lr: 3.4713e-03 eta: 12:21:34 time: 0.8693 data_time: 0.0280 memory: 16201 loss_prob: 0.4864 loss_thr: 0.3358 loss_db: 0.0873 loss: 0.9095 2022/08/30 14:33:06 - mmengine - INFO - Epoch(train) [650][45/63] lr: 3.4713e-03 eta: 12:21:34 time: 0.8301 data_time: 0.0252 memory: 16201 loss_prob: 0.5238 loss_thr: 0.3483 loss_db: 0.0904 loss: 0.9625 2022/08/30 14:33:11 - mmengine - INFO - Epoch(train) [650][50/63] lr: 3.4713e-03 eta: 12:21:18 time: 0.8566 data_time: 0.0280 memory: 16201 loss_prob: 0.5078 loss_thr: 0.3386 loss_db: 0.0850 loss: 0.9314 2022/08/30 14:33:15 - mmengine - INFO - Epoch(train) [650][55/63] lr: 3.4713e-03 eta: 12:21:18 time: 0.8706 data_time: 0.0240 memory: 16201 loss_prob: 0.5490 loss_thr: 0.3477 loss_db: 0.0920 loss: 0.9887 2022/08/30 14:33:19 - mmengine - INFO - Epoch(train) [650][60/63] lr: 3.4713e-03 eta: 12:21:02 time: 0.8528 data_time: 0.0240 memory: 16201 loss_prob: 0.5458 loss_thr: 0.3552 loss_db: 0.0930 loss: 0.9939 2022/08/30 14:33:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:33:27 - mmengine - INFO - Epoch(train) [651][5/63] lr: 3.4656e-03 eta: 12:21:02 time: 0.9506 data_time: 0.1691 memory: 16201 loss_prob: 0.4576 loss_thr: 0.3273 loss_db: 0.0781 loss: 0.8630 2022/08/30 14:33:31 - mmengine - INFO - Epoch(train) [651][10/63] lr: 3.4656e-03 eta: 12:20:39 time: 0.9753 data_time: 0.1838 memory: 16201 loss_prob: 0.4882 loss_thr: 0.3319 loss_db: 0.0817 loss: 0.9018 2022/08/30 14:33:36 - mmengine - INFO - Epoch(train) [651][15/63] lr: 3.4656e-03 eta: 12:20:39 time: 0.8824 data_time: 0.0276 memory: 16201 loss_prob: 0.4843 loss_thr: 0.3299 loss_db: 0.0845 loss: 0.8988 2022/08/30 14:33:40 - mmengine - INFO - Epoch(train) [651][20/63] lr: 3.4656e-03 eta: 12:20:23 time: 0.8803 data_time: 0.0205 memory: 16201 loss_prob: 0.4375 loss_thr: 0.3164 loss_db: 0.0790 loss: 0.8329 2022/08/30 14:33:44 - mmengine - INFO - Epoch(train) [651][25/63] lr: 3.4656e-03 eta: 12:20:23 time: 0.8134 data_time: 0.0236 memory: 16201 loss_prob: 0.4262 loss_thr: 0.3179 loss_db: 0.0754 loss: 0.8195 2022/08/30 14:33:48 - mmengine - INFO - Epoch(train) [651][30/63] lr: 3.4656e-03 eta: 12:20:06 time: 0.8100 data_time: 0.0236 memory: 16201 loss_prob: 0.4697 loss_thr: 0.3335 loss_db: 0.0834 loss: 0.8866 2022/08/30 14:33:52 - mmengine - INFO - Epoch(train) [651][35/63] lr: 3.4656e-03 eta: 12:20:06 time: 0.8140 data_time: 0.0238 memory: 16201 loss_prob: 0.4906 loss_thr: 0.3391 loss_db: 0.0863 loss: 0.9159 2022/08/30 14:33:57 - mmengine - INFO - Epoch(train) [651][40/63] lr: 3.4656e-03 eta: 12:19:50 time: 0.8970 data_time: 0.0281 memory: 16201 loss_prob: 0.4653 loss_thr: 0.3302 loss_db: 0.0804 loss: 0.8759 2022/08/30 14:34:01 - mmengine - INFO - Epoch(train) [651][45/63] lr: 3.4656e-03 eta: 12:19:50 time: 0.8849 data_time: 0.0286 memory: 16201 loss_prob: 0.4899 loss_thr: 0.3336 loss_db: 0.0838 loss: 0.9074 2022/08/30 14:34:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:34:05 - mmengine - INFO - Epoch(train) [651][50/63] lr: 3.4656e-03 eta: 12:19:33 time: 0.8117 data_time: 0.0271 memory: 16201 loss_prob: 0.5078 loss_thr: 0.3596 loss_db: 0.0874 loss: 0.9547 2022/08/30 14:34:09 - mmengine - INFO - Epoch(train) [651][55/63] lr: 3.4656e-03 eta: 12:19:33 time: 0.8346 data_time: 0.0296 memory: 16201 loss_prob: 0.5096 loss_thr: 0.3644 loss_db: 0.0877 loss: 0.9616 2022/08/30 14:34:13 - mmengine - INFO - Epoch(train) [651][60/63] lr: 3.4656e-03 eta: 12:19:16 time: 0.8361 data_time: 0.0255 memory: 16201 loss_prob: 0.4812 loss_thr: 0.3401 loss_db: 0.0821 loss: 0.9034 2022/08/30 14:34:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:34:22 - mmengine - INFO - Epoch(train) [652][5/63] lr: 3.4599e-03 eta: 12:19:16 time: 1.0124 data_time: 0.1982 memory: 16201 loss_prob: 0.4562 loss_thr: 0.3173 loss_db: 0.0809 loss: 0.8543 2022/08/30 14:34:26 - mmengine - INFO - Epoch(train) [652][10/63] lr: 3.4599e-03 eta: 12:18:54 time: 1.0285 data_time: 0.2119 memory: 16201 loss_prob: 0.4471 loss_thr: 0.3199 loss_db: 0.0763 loss: 0.8433 2022/08/30 14:34:30 - mmengine - INFO - Epoch(train) [652][15/63] lr: 3.4599e-03 eta: 12:18:54 time: 0.8367 data_time: 0.0302 memory: 16201 loss_prob: 0.4377 loss_thr: 0.3173 loss_db: 0.0737 loss: 0.8288 2022/08/30 14:34:35 - mmengine - INFO - Epoch(train) [652][20/63] lr: 3.4599e-03 eta: 12:18:38 time: 0.8467 data_time: 0.0213 memory: 16201 loss_prob: 0.4609 loss_thr: 0.3314 loss_db: 0.0802 loss: 0.8725 2022/08/30 14:34:39 - mmengine - INFO - Epoch(train) [652][25/63] lr: 3.4599e-03 eta: 12:18:38 time: 0.8592 data_time: 0.0293 memory: 16201 loss_prob: 0.4876 loss_thr: 0.3409 loss_db: 0.0848 loss: 0.9133 2022/08/30 14:34:43 - mmengine - INFO - Epoch(train) [652][30/63] lr: 3.4599e-03 eta: 12:18:21 time: 0.8110 data_time: 0.0231 memory: 16201 loss_prob: 0.4597 loss_thr: 0.3036 loss_db: 0.0805 loss: 0.8438 2022/08/30 14:34:47 - mmengine - INFO - Epoch(train) [652][35/63] lr: 3.4599e-03 eta: 12:18:21 time: 0.8309 data_time: 0.0247 memory: 16201 loss_prob: 0.4224 loss_thr: 0.2912 loss_db: 0.0751 loss: 0.7887 2022/08/30 14:34:51 - mmengine - INFO - Epoch(train) [652][40/63] lr: 3.4599e-03 eta: 12:18:05 time: 0.8352 data_time: 0.0244 memory: 16201 loss_prob: 0.4428 loss_thr: 0.3233 loss_db: 0.0772 loss: 0.8433 2022/08/30 14:34:56 - mmengine - INFO - Epoch(train) [652][45/63] lr: 3.4599e-03 eta: 12:18:05 time: 0.8832 data_time: 0.0687 memory: 16201 loss_prob: 0.4480 loss_thr: 0.3276 loss_db: 0.0788 loss: 0.8544 2022/08/30 14:35:00 - mmengine - INFO - Epoch(train) [652][50/63] lr: 3.4599e-03 eta: 12:17:49 time: 0.9030 data_time: 0.0705 memory: 16201 loss_prob: 0.4252 loss_thr: 0.3125 loss_db: 0.0764 loss: 0.8141 2022/08/30 14:35:04 - mmengine - INFO - Epoch(train) [652][55/63] lr: 3.4599e-03 eta: 12:17:49 time: 0.8185 data_time: 0.0228 memory: 16201 loss_prob: 0.4379 loss_thr: 0.3285 loss_db: 0.0773 loss: 0.8437 2022/08/30 14:35:09 - mmengine - INFO - Epoch(train) [652][60/63] lr: 3.4599e-03 eta: 12:17:32 time: 0.8473 data_time: 0.0312 memory: 16201 loss_prob: 0.4431 loss_thr: 0.3297 loss_db: 0.0781 loss: 0.8509 2022/08/30 14:35:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:35:17 - mmengine - INFO - Epoch(train) [653][5/63] lr: 3.4543e-03 eta: 12:17:32 time: 0.9318 data_time: 0.1713 memory: 16201 loss_prob: 0.4777 loss_thr: 0.3363 loss_db: 0.0823 loss: 0.8963 2022/08/30 14:35:21 - mmengine - INFO - Epoch(train) [653][10/63] lr: 3.4543e-03 eta: 12:17:09 time: 0.9627 data_time: 0.1821 memory: 16201 loss_prob: 0.4754 loss_thr: 0.3357 loss_db: 0.0827 loss: 0.8937 2022/08/30 14:35:25 - mmengine - INFO - Epoch(train) [653][15/63] lr: 3.4543e-03 eta: 12:17:09 time: 0.8817 data_time: 0.0289 memory: 16201 loss_prob: 0.4501 loss_thr: 0.3269 loss_db: 0.0786 loss: 0.8556 2022/08/30 14:35:29 - mmengine - INFO - Epoch(train) [653][20/63] lr: 3.4543e-03 eta: 12:16:53 time: 0.8877 data_time: 0.0220 memory: 16201 loss_prob: 0.4291 loss_thr: 0.3170 loss_db: 0.0759 loss: 0.8220 2022/08/30 14:35:34 - mmengine - INFO - Epoch(train) [653][25/63] lr: 3.4543e-03 eta: 12:16:53 time: 0.8237 data_time: 0.0231 memory: 16201 loss_prob: 0.4717 loss_thr: 0.3270 loss_db: 0.0831 loss: 0.8818 2022/08/30 14:35:38 - mmengine - INFO - Epoch(train) [653][30/63] lr: 3.4543e-03 eta: 12:16:37 time: 0.8622 data_time: 0.0275 memory: 16201 loss_prob: 0.4682 loss_thr: 0.3178 loss_db: 0.0803 loss: 0.8663 2022/08/30 14:35:42 - mmengine - INFO - Epoch(train) [653][35/63] lr: 3.4543e-03 eta: 12:16:37 time: 0.8544 data_time: 0.0235 memory: 16201 loss_prob: 0.4388 loss_thr: 0.3034 loss_db: 0.0748 loss: 0.8170 2022/08/30 14:35:47 - mmengine - INFO - Epoch(train) [653][40/63] lr: 3.4543e-03 eta: 12:16:21 time: 0.8527 data_time: 0.0278 memory: 16201 loss_prob: 0.4763 loss_thr: 0.3254 loss_db: 0.0829 loss: 0.8845 2022/08/30 14:35:51 - mmengine - INFO - Epoch(train) [653][45/63] lr: 3.4543e-03 eta: 12:16:21 time: 0.8262 data_time: 0.0319 memory: 16201 loss_prob: 0.5024 loss_thr: 0.3393 loss_db: 0.0861 loss: 0.9278 2022/08/30 14:35:54 - mmengine - INFO - Epoch(train) [653][50/63] lr: 3.4543e-03 eta: 12:16:04 time: 0.7753 data_time: 0.0213 memory: 16201 loss_prob: 0.4633 loss_thr: 0.3306 loss_db: 0.0808 loss: 0.8747 2022/08/30 14:35:58 - mmengine - INFO - Epoch(train) [653][55/63] lr: 3.4543e-03 eta: 12:16:04 time: 0.7909 data_time: 0.0281 memory: 16201 loss_prob: 0.4761 loss_thr: 0.3375 loss_db: 0.0836 loss: 0.8972 2022/08/30 14:36:02 - mmengine - INFO - Epoch(train) [653][60/63] lr: 3.4543e-03 eta: 12:15:47 time: 0.7884 data_time: 0.0318 memory: 16201 loss_prob: 0.4693 loss_thr: 0.3314 loss_db: 0.0816 loss: 0.8823 2022/08/30 14:36:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:36:10 - mmengine - INFO - Epoch(train) [654][5/63] lr: 3.4486e-03 eta: 12:15:47 time: 0.9352 data_time: 0.1973 memory: 16201 loss_prob: 0.4905 loss_thr: 0.3608 loss_db: 0.0883 loss: 0.9396 2022/08/30 14:36:14 - mmengine - INFO - Epoch(train) [654][10/63] lr: 3.4486e-03 eta: 12:15:25 time: 1.0222 data_time: 0.2036 memory: 16201 loss_prob: 0.4837 loss_thr: 0.3434 loss_db: 0.0847 loss: 0.9119 2022/08/30 14:36:19 - mmengine - INFO - Epoch(train) [654][15/63] lr: 3.4486e-03 eta: 12:15:25 time: 0.8486 data_time: 0.0234 memory: 16201 loss_prob: 0.4692 loss_thr: 0.3376 loss_db: 0.0820 loss: 0.8888 2022/08/30 14:36:23 - mmengine - INFO - Epoch(train) [654][20/63] lr: 3.4486e-03 eta: 12:15:08 time: 0.8541 data_time: 0.0195 memory: 16201 loss_prob: 0.4823 loss_thr: 0.3458 loss_db: 0.0861 loss: 0.9143 2022/08/30 14:36:27 - mmengine - INFO - Epoch(train) [654][25/63] lr: 3.4486e-03 eta: 12:15:08 time: 0.8375 data_time: 0.0241 memory: 16201 loss_prob: 0.4663 loss_thr: 0.3242 loss_db: 0.0812 loss: 0.8716 2022/08/30 14:36:31 - mmengine - INFO - Epoch(train) [654][30/63] lr: 3.4486e-03 eta: 12:14:51 time: 0.8107 data_time: 0.0277 memory: 16201 loss_prob: 0.4607 loss_thr: 0.3248 loss_db: 0.0791 loss: 0.8646 2022/08/30 14:36:35 - mmengine - INFO - Epoch(train) [654][35/63] lr: 3.4486e-03 eta: 12:14:51 time: 0.8253 data_time: 0.0257 memory: 16201 loss_prob: 0.4211 loss_thr: 0.3048 loss_db: 0.0748 loss: 0.8007 2022/08/30 14:36:39 - mmengine - INFO - Epoch(train) [654][40/63] lr: 3.4486e-03 eta: 12:14:35 time: 0.8202 data_time: 0.0226 memory: 16201 loss_prob: 0.4256 loss_thr: 0.3104 loss_db: 0.0753 loss: 0.8113 2022/08/30 14:36:43 - mmengine - INFO - Epoch(train) [654][45/63] lr: 3.4486e-03 eta: 12:14:35 time: 0.8162 data_time: 0.0240 memory: 16201 loss_prob: 0.4649 loss_thr: 0.3251 loss_db: 0.0805 loss: 0.8704 2022/08/30 14:36:48 - mmengine - INFO - Epoch(train) [654][50/63] lr: 3.4486e-03 eta: 12:14:18 time: 0.8336 data_time: 0.0208 memory: 16201 loss_prob: 0.4763 loss_thr: 0.3197 loss_db: 0.0837 loss: 0.8798 2022/08/30 14:36:52 - mmengine - INFO - Epoch(train) [654][55/63] lr: 3.4486e-03 eta: 12:14:18 time: 0.8263 data_time: 0.0233 memory: 16201 loss_prob: 0.5002 loss_thr: 0.3398 loss_db: 0.0867 loss: 0.9268 2022/08/30 14:36:57 - mmengine - INFO - Epoch(train) [654][60/63] lr: 3.4486e-03 eta: 12:14:02 time: 0.9011 data_time: 0.0344 memory: 16201 loss_prob: 0.4889 loss_thr: 0.3412 loss_db: 0.0853 loss: 0.9154 2022/08/30 14:36:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:37:04 - mmengine - INFO - Epoch(train) [655][5/63] lr: 3.4429e-03 eta: 12:14:02 time: 0.9965 data_time: 0.1638 memory: 16201 loss_prob: 0.4429 loss_thr: 0.3027 loss_db: 0.0772 loss: 0.8227 2022/08/30 14:37:08 - mmengine - INFO - Epoch(train) [655][10/63] lr: 3.4429e-03 eta: 12:13:40 time: 0.9509 data_time: 0.1620 memory: 16201 loss_prob: 0.5071 loss_thr: 0.3353 loss_db: 0.0895 loss: 0.9319 2022/08/30 14:37:12 - mmengine - INFO - Epoch(train) [655][15/63] lr: 3.4429e-03 eta: 12:13:40 time: 0.8001 data_time: 0.0207 memory: 16201 loss_prob: 0.4895 loss_thr: 0.3388 loss_db: 0.0850 loss: 0.9134 2022/08/30 14:37:17 - mmengine - INFO - Epoch(train) [655][20/63] lr: 3.4429e-03 eta: 12:13:24 time: 0.9162 data_time: 0.0248 memory: 16201 loss_prob: 0.4622 loss_thr: 0.3316 loss_db: 0.0809 loss: 0.8747 2022/08/30 14:37:22 - mmengine - INFO - Epoch(train) [655][25/63] lr: 3.4429e-03 eta: 12:13:24 time: 0.9402 data_time: 0.0392 memory: 16201 loss_prob: 0.4426 loss_thr: 0.3302 loss_db: 0.0797 loss: 0.8525 2022/08/30 14:37:26 - mmengine - INFO - Epoch(train) [655][30/63] lr: 3.4429e-03 eta: 12:13:07 time: 0.8296 data_time: 0.0271 memory: 16201 loss_prob: 0.4342 loss_thr: 0.3206 loss_db: 0.0787 loss: 0.8334 2022/08/30 14:37:30 - mmengine - INFO - Epoch(train) [655][35/63] lr: 3.4429e-03 eta: 12:13:07 time: 0.8558 data_time: 0.0209 memory: 16201 loss_prob: 0.4358 loss_thr: 0.3081 loss_db: 0.0782 loss: 0.8220 2022/08/30 14:37:34 - mmengine - INFO - Epoch(train) [655][40/63] lr: 3.4429e-03 eta: 12:12:51 time: 0.8511 data_time: 0.0244 memory: 16201 loss_prob: 0.3792 loss_thr: 0.2778 loss_db: 0.0665 loss: 0.7236 2022/08/30 14:37:39 - mmengine - INFO - Epoch(train) [655][45/63] lr: 3.4429e-03 eta: 12:12:51 time: 0.8318 data_time: 0.0258 memory: 16201 loss_prob: 0.4216 loss_thr: 0.2994 loss_db: 0.0736 loss: 0.7946 2022/08/30 14:37:43 - mmengine - INFO - Epoch(train) [655][50/63] lr: 3.4429e-03 eta: 12:12:35 time: 0.8592 data_time: 0.0272 memory: 16201 loss_prob: 0.4731 loss_thr: 0.3278 loss_db: 0.0819 loss: 0.8828 2022/08/30 14:37:47 - mmengine - INFO - Epoch(train) [655][55/63] lr: 3.4429e-03 eta: 12:12:35 time: 0.8336 data_time: 0.0235 memory: 16201 loss_prob: 0.4265 loss_thr: 0.3066 loss_db: 0.0741 loss: 0.8073 2022/08/30 14:37:51 - mmengine - INFO - Epoch(train) [655][60/63] lr: 3.4429e-03 eta: 12:12:18 time: 0.8059 data_time: 0.0239 memory: 16201 loss_prob: 0.4407 loss_thr: 0.3191 loss_db: 0.0767 loss: 0.8365 2022/08/30 14:37:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:37:59 - mmengine - INFO - Epoch(train) [656][5/63] lr: 3.4372e-03 eta: 12:12:18 time: 0.9566 data_time: 0.1895 memory: 16201 loss_prob: 0.4734 loss_thr: 0.3387 loss_db: 0.0832 loss: 0.8953 2022/08/30 14:38:03 - mmengine - INFO - Epoch(train) [656][10/63] lr: 3.4372e-03 eta: 12:11:56 time: 0.9876 data_time: 0.2037 memory: 16201 loss_prob: 0.4831 loss_thr: 0.3321 loss_db: 0.0852 loss: 0.9004 2022/08/30 14:38:07 - mmengine - INFO - Epoch(train) [656][15/63] lr: 3.4372e-03 eta: 12:11:56 time: 0.8075 data_time: 0.0280 memory: 16201 loss_prob: 0.5021 loss_thr: 0.3420 loss_db: 0.0858 loss: 0.9299 2022/08/30 14:38:11 - mmengine - INFO - Epoch(train) [656][20/63] lr: 3.4372e-03 eta: 12:11:39 time: 0.8242 data_time: 0.0226 memory: 16201 loss_prob: 0.5204 loss_thr: 0.3589 loss_db: 0.0887 loss: 0.9680 2022/08/30 14:38:15 - mmengine - INFO - Epoch(train) [656][25/63] lr: 3.4372e-03 eta: 12:11:39 time: 0.8320 data_time: 0.0313 memory: 16201 loss_prob: 0.4756 loss_thr: 0.3302 loss_db: 0.0816 loss: 0.8873 2022/08/30 14:38:20 - mmengine - INFO - Epoch(train) [656][30/63] lr: 3.4372e-03 eta: 12:11:23 time: 0.8257 data_time: 0.0247 memory: 16201 loss_prob: 0.4153 loss_thr: 0.3051 loss_db: 0.0730 loss: 0.7935 2022/08/30 14:38:24 - mmengine - INFO - Epoch(train) [656][35/63] lr: 3.4372e-03 eta: 12:11:23 time: 0.8252 data_time: 0.0194 memory: 16201 loss_prob: 0.4438 loss_thr: 0.3199 loss_db: 0.0785 loss: 0.8423 2022/08/30 14:38:28 - mmengine - INFO - Epoch(train) [656][40/63] lr: 3.4372e-03 eta: 12:11:06 time: 0.8297 data_time: 0.0259 memory: 16201 loss_prob: 0.4748 loss_thr: 0.3409 loss_db: 0.0835 loss: 0.8992 2022/08/30 14:38:32 - mmengine - INFO - Epoch(train) [656][45/63] lr: 3.4372e-03 eta: 12:11:06 time: 0.8423 data_time: 0.0287 memory: 16201 loss_prob: 0.4668 loss_thr: 0.3424 loss_db: 0.0807 loss: 0.8899 2022/08/30 14:38:36 - mmengine - INFO - Epoch(train) [656][50/63] lr: 3.4372e-03 eta: 12:10:50 time: 0.8668 data_time: 0.0296 memory: 16201 loss_prob: 0.4683 loss_thr: 0.3269 loss_db: 0.0811 loss: 0.8764 2022/08/30 14:38:41 - mmengine - INFO - Epoch(train) [656][55/63] lr: 3.4372e-03 eta: 12:10:50 time: 0.8539 data_time: 0.0313 memory: 16201 loss_prob: 0.4580 loss_thr: 0.3187 loss_db: 0.0802 loss: 0.8570 2022/08/30 14:38:45 - mmengine - INFO - Epoch(train) [656][60/63] lr: 3.4372e-03 eta: 12:10:33 time: 0.8285 data_time: 0.0280 memory: 16201 loss_prob: 0.4527 loss_thr: 0.3215 loss_db: 0.0794 loss: 0.8537 2022/08/30 14:38:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:38:53 - mmengine - INFO - Epoch(train) [657][5/63] lr: 3.4315e-03 eta: 12:10:33 time: 0.9391 data_time: 0.1971 memory: 16201 loss_prob: 0.5174 loss_thr: 0.3459 loss_db: 0.0879 loss: 0.9513 2022/08/30 14:38:57 - mmengine - INFO - Epoch(train) [657][10/63] lr: 3.4315e-03 eta: 12:10:11 time: 1.0020 data_time: 0.2094 memory: 16201 loss_prob: 0.4441 loss_thr: 0.3081 loss_db: 0.0758 loss: 0.8280 2022/08/30 14:39:01 - mmengine - INFO - Epoch(train) [657][15/63] lr: 3.4315e-03 eta: 12:10:11 time: 0.8229 data_time: 0.0294 memory: 16201 loss_prob: 0.4340 loss_thr: 0.3155 loss_db: 0.0770 loss: 0.8265 2022/08/30 14:39:05 - mmengine - INFO - Epoch(train) [657][20/63] lr: 3.4315e-03 eta: 12:09:54 time: 0.8045 data_time: 0.0235 memory: 16201 loss_prob: 0.4246 loss_thr: 0.3142 loss_db: 0.0764 loss: 0.8152 2022/08/30 14:39:09 - mmengine - INFO - Epoch(train) [657][25/63] lr: 3.4315e-03 eta: 12:09:54 time: 0.8027 data_time: 0.0293 memory: 16201 loss_prob: 0.4779 loss_thr: 0.3321 loss_db: 0.0856 loss: 0.8956 2022/08/30 14:39:13 - mmengine - INFO - Epoch(train) [657][30/63] lr: 3.4315e-03 eta: 12:09:38 time: 0.8022 data_time: 0.0242 memory: 16201 loss_prob: 0.5012 loss_thr: 0.3312 loss_db: 0.0881 loss: 0.9206 2022/08/30 14:39:17 - mmengine - INFO - Epoch(train) [657][35/63] lr: 3.4315e-03 eta: 12:09:38 time: 0.8389 data_time: 0.0252 memory: 16201 loss_prob: 0.4548 loss_thr: 0.3189 loss_db: 0.0793 loss: 0.8529 2022/08/30 14:39:21 - mmengine - INFO - Epoch(train) [657][40/63] lr: 3.4315e-03 eta: 12:09:21 time: 0.8544 data_time: 0.0284 memory: 16201 loss_prob: 0.4418 loss_thr: 0.3230 loss_db: 0.0771 loss: 0.8419 2022/08/30 14:39:26 - mmengine - INFO - Epoch(train) [657][45/63] lr: 3.4315e-03 eta: 12:09:21 time: 0.8118 data_time: 0.0249 memory: 16201 loss_prob: 0.4414 loss_thr: 0.3236 loss_db: 0.0769 loss: 0.8419 2022/08/30 14:39:30 - mmengine - INFO - Epoch(train) [657][50/63] lr: 3.4315e-03 eta: 12:09:05 time: 0.8245 data_time: 0.0263 memory: 16201 loss_prob: 0.4418 loss_thr: 0.3296 loss_db: 0.0766 loss: 0.8480 2022/08/30 14:39:34 - mmengine - INFO - Epoch(train) [657][55/63] lr: 3.4315e-03 eta: 12:09:05 time: 0.8266 data_time: 0.0272 memory: 16201 loss_prob: 0.4346 loss_thr: 0.3296 loss_db: 0.0765 loss: 0.8406 2022/08/30 14:39:38 - mmengine - INFO - Epoch(train) [657][60/63] lr: 3.4315e-03 eta: 12:08:48 time: 0.8200 data_time: 0.0264 memory: 16201 loss_prob: 0.4390 loss_thr: 0.3402 loss_db: 0.0781 loss: 0.8573 2022/08/30 14:39:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:39:46 - mmengine - INFO - Epoch(train) [658][5/63] lr: 3.4258e-03 eta: 12:08:48 time: 0.9374 data_time: 0.1624 memory: 16201 loss_prob: 0.4267 loss_thr: 0.3142 loss_db: 0.0736 loss: 0.8145 2022/08/30 14:39:50 - mmengine - INFO - Epoch(train) [658][10/63] lr: 3.4258e-03 eta: 12:08:26 time: 0.9723 data_time: 0.1753 memory: 16201 loss_prob: 0.4215 loss_thr: 0.3038 loss_db: 0.0732 loss: 0.7985 2022/08/30 14:39:54 - mmengine - INFO - Epoch(train) [658][15/63] lr: 3.4258e-03 eta: 12:08:26 time: 0.8105 data_time: 0.0250 memory: 16201 loss_prob: 0.5034 loss_thr: 0.3343 loss_db: 0.0893 loss: 0.9270 2022/08/30 14:39:58 - mmengine - INFO - Epoch(train) [658][20/63] lr: 3.4258e-03 eta: 12:08:09 time: 0.8138 data_time: 0.0202 memory: 16201 loss_prob: 0.4998 loss_thr: 0.3371 loss_db: 0.0891 loss: 0.9260 2022/08/30 14:40:02 - mmengine - INFO - Epoch(train) [658][25/63] lr: 3.4258e-03 eta: 12:08:09 time: 0.8177 data_time: 0.0338 memory: 16201 loss_prob: 0.4590 loss_thr: 0.3188 loss_db: 0.0799 loss: 0.8576 2022/08/30 14:40:06 - mmengine - INFO - Epoch(train) [658][30/63] lr: 3.4258e-03 eta: 12:07:53 time: 0.8389 data_time: 0.0256 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3336 loss_db: 0.0836 loss: 0.8923 2022/08/30 14:40:10 - mmengine - INFO - Epoch(train) [658][35/63] lr: 3.4258e-03 eta: 12:07:53 time: 0.8344 data_time: 0.0220 memory: 16201 loss_prob: 0.4615 loss_thr: 0.3311 loss_db: 0.0818 loss: 0.8744 2022/08/30 14:40:14 - mmengine - INFO - Epoch(train) [658][40/63] lr: 3.4258e-03 eta: 12:07:36 time: 0.8055 data_time: 0.0283 memory: 16201 loss_prob: 0.4548 loss_thr: 0.3288 loss_db: 0.0798 loss: 0.8634 2022/08/30 14:40:19 - mmengine - INFO - Epoch(train) [658][45/63] lr: 3.4258e-03 eta: 12:07:36 time: 0.8269 data_time: 0.0319 memory: 16201 loss_prob: 0.4553 loss_thr: 0.3230 loss_db: 0.0789 loss: 0.8572 2022/08/30 14:40:23 - mmengine - INFO - Epoch(train) [658][50/63] lr: 3.4258e-03 eta: 12:07:20 time: 0.8540 data_time: 0.0360 memory: 16201 loss_prob: 0.4364 loss_thr: 0.3102 loss_db: 0.0776 loss: 0.8243 2022/08/30 14:40:27 - mmengine - INFO - Epoch(train) [658][55/63] lr: 3.4258e-03 eta: 12:07:20 time: 0.8202 data_time: 0.0273 memory: 16201 loss_prob: 0.4396 loss_thr: 0.3106 loss_db: 0.0785 loss: 0.8287 2022/08/30 14:40:31 - mmengine - INFO - Epoch(train) [658][60/63] lr: 3.4258e-03 eta: 12:07:03 time: 0.8120 data_time: 0.0222 memory: 16201 loss_prob: 0.4166 loss_thr: 0.2908 loss_db: 0.0723 loss: 0.7797 2022/08/30 14:40:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:40:39 - mmengine - INFO - Epoch(train) [659][5/63] lr: 3.4201e-03 eta: 12:07:03 time: 0.9616 data_time: 0.1761 memory: 16201 loss_prob: 0.4122 loss_thr: 0.2985 loss_db: 0.0739 loss: 0.7845 2022/08/30 14:40:43 - mmengine - INFO - Epoch(train) [659][10/63] lr: 3.4201e-03 eta: 12:06:41 time: 0.9958 data_time: 0.1893 memory: 16201 loss_prob: 0.4577 loss_thr: 0.3219 loss_db: 0.0810 loss: 0.8606 2022/08/30 14:40:47 - mmengine - INFO - Epoch(train) [659][15/63] lr: 3.4201e-03 eta: 12:06:41 time: 0.8395 data_time: 0.0375 memory: 16201 loss_prob: 0.5002 loss_thr: 0.3340 loss_db: 0.0845 loss: 0.9186 2022/08/30 14:40:52 - mmengine - INFO - Epoch(train) [659][20/63] lr: 3.4201e-03 eta: 12:06:25 time: 0.8633 data_time: 0.0322 memory: 16201 loss_prob: 0.4978 loss_thr: 0.3349 loss_db: 0.0855 loss: 0.9181 2022/08/30 14:40:56 - mmengine - INFO - Epoch(train) [659][25/63] lr: 3.4201e-03 eta: 12:06:25 time: 0.8484 data_time: 0.0334 memory: 16201 loss_prob: 0.4845 loss_thr: 0.3342 loss_db: 0.0840 loss: 0.9026 2022/08/30 14:41:00 - mmengine - INFO - Epoch(train) [659][30/63] lr: 3.4201e-03 eta: 12:06:09 time: 0.8162 data_time: 0.0245 memory: 16201 loss_prob: 0.4625 loss_thr: 0.3220 loss_db: 0.0799 loss: 0.8645 2022/08/30 14:41:04 - mmengine - INFO - Epoch(train) [659][35/63] lr: 3.4201e-03 eta: 12:06:09 time: 0.7944 data_time: 0.0179 memory: 16201 loss_prob: 0.4419 loss_thr: 0.3107 loss_db: 0.0785 loss: 0.8311 2022/08/30 14:41:08 - mmengine - INFO - Epoch(train) [659][40/63] lr: 3.4201e-03 eta: 12:05:52 time: 0.8200 data_time: 0.0265 memory: 16201 loss_prob: 0.4337 loss_thr: 0.3035 loss_db: 0.0743 loss: 0.8116 2022/08/30 14:41:12 - mmengine - INFO - Epoch(train) [659][45/63] lr: 3.4201e-03 eta: 12:05:52 time: 0.8342 data_time: 0.0244 memory: 16201 loss_prob: 0.4403 loss_thr: 0.2929 loss_db: 0.0763 loss: 0.8095 2022/08/30 14:41:17 - mmengine - INFO - Epoch(train) [659][50/63] lr: 3.4201e-03 eta: 12:05:36 time: 0.8553 data_time: 0.0295 memory: 16201 loss_prob: 0.4738 loss_thr: 0.3147 loss_db: 0.0840 loss: 0.8725 2022/08/30 14:41:21 - mmengine - INFO - Epoch(train) [659][55/63] lr: 3.4201e-03 eta: 12:05:36 time: 0.8444 data_time: 0.0297 memory: 16201 loss_prob: 0.4802 loss_thr: 0.3323 loss_db: 0.0828 loss: 0.8953 2022/08/30 14:41:25 - mmengine - INFO - Epoch(train) [659][60/63] lr: 3.4201e-03 eta: 12:05:19 time: 0.8289 data_time: 0.0268 memory: 16201 loss_prob: 0.4775 loss_thr: 0.3307 loss_db: 0.0825 loss: 0.8908 2022/08/30 14:41:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:41:33 - mmengine - INFO - Epoch(train) [660][5/63] lr: 3.4145e-03 eta: 12:05:19 time: 1.0144 data_time: 0.2092 memory: 16201 loss_prob: 0.4446 loss_thr: 0.3180 loss_db: 0.0805 loss: 0.8430 2022/08/30 14:41:38 - mmengine - INFO - Epoch(train) [660][10/63] lr: 3.4145e-03 eta: 12:04:58 time: 1.0354 data_time: 0.2221 memory: 16201 loss_prob: 0.4318 loss_thr: 0.3034 loss_db: 0.0735 loss: 0.8087 2022/08/30 14:41:42 - mmengine - INFO - Epoch(train) [660][15/63] lr: 3.4145e-03 eta: 12:04:58 time: 0.8455 data_time: 0.0344 memory: 16201 loss_prob: 0.4644 loss_thr: 0.3236 loss_db: 0.0788 loss: 0.8668 2022/08/30 14:41:46 - mmengine - INFO - Epoch(train) [660][20/63] lr: 3.4145e-03 eta: 12:04:41 time: 0.8397 data_time: 0.0222 memory: 16201 loss_prob: 0.4599 loss_thr: 0.3250 loss_db: 0.0818 loss: 0.8667 2022/08/30 14:41:50 - mmengine - INFO - Epoch(train) [660][25/63] lr: 3.4145e-03 eta: 12:04:41 time: 0.8400 data_time: 0.0343 memory: 16201 loss_prob: 0.4715 loss_thr: 0.3239 loss_db: 0.0824 loss: 0.8778 2022/08/30 14:41:54 - mmengine - INFO - Epoch(train) [660][30/63] lr: 3.4145e-03 eta: 12:04:25 time: 0.8383 data_time: 0.0294 memory: 16201 loss_prob: 0.4666 loss_thr: 0.3274 loss_db: 0.0808 loss: 0.8749 2022/08/30 14:41:59 - mmengine - INFO - Epoch(train) [660][35/63] lr: 3.4145e-03 eta: 12:04:25 time: 0.9115 data_time: 0.0181 memory: 16201 loss_prob: 0.4477 loss_thr: 0.3275 loss_db: 0.0803 loss: 0.8555 2022/08/30 14:42:03 - mmengine - INFO - Epoch(train) [660][40/63] lr: 3.4145e-03 eta: 12:04:09 time: 0.9137 data_time: 0.0352 memory: 16201 loss_prob: 0.4630 loss_thr: 0.3405 loss_db: 0.0818 loss: 0.8852 2022/08/30 14:42:08 - mmengine - INFO - Epoch(train) [660][45/63] lr: 3.4145e-03 eta: 12:04:09 time: 0.8376 data_time: 0.0352 memory: 16201 loss_prob: 0.4488 loss_thr: 0.3378 loss_db: 0.0770 loss: 0.8635 2022/08/30 14:42:12 - mmengine - INFO - Epoch(train) [660][50/63] lr: 3.4145e-03 eta: 12:03:53 time: 0.8329 data_time: 0.0230 memory: 16201 loss_prob: 0.4299 loss_thr: 0.3264 loss_db: 0.0762 loss: 0.8326 2022/08/30 14:42:16 - mmengine - INFO - Epoch(train) [660][55/63] lr: 3.4145e-03 eta: 12:03:53 time: 0.8591 data_time: 0.0270 memory: 16201 loss_prob: 0.4067 loss_thr: 0.3083 loss_db: 0.0727 loss: 0.7877 2022/08/30 14:42:20 - mmengine - INFO - Epoch(train) [660][60/63] lr: 3.4145e-03 eta: 12:03:37 time: 0.8525 data_time: 0.0236 memory: 16201 loss_prob: 0.4301 loss_thr: 0.3116 loss_db: 0.0766 loss: 0.8183 2022/08/30 14:42:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:42:23 - mmengine - INFO - Saving checkpoint at 660 epochs 2022/08/30 14:42:31 - mmengine - INFO - Epoch(val) [660][5/32] eta: 12:03:37 time: 0.6276 data_time: 0.1027 memory: 16201 2022/08/30 14:42:34 - mmengine - INFO - Epoch(val) [660][10/32] eta: 0:00:15 time: 0.6962 data_time: 0.1316 memory: 15734 2022/08/30 14:42:37 - mmengine - INFO - Epoch(val) [660][15/32] eta: 0:00:15 time: 0.5962 data_time: 0.0468 memory: 15734 2022/08/30 14:42:40 - mmengine - INFO - Epoch(val) [660][20/32] eta: 0:00:07 time: 0.6571 data_time: 0.0439 memory: 15734 2022/08/30 14:42:44 - mmengine - INFO - Epoch(val) [660][25/32] eta: 0:00:07 time: 0.6884 data_time: 0.0623 memory: 15734 2022/08/30 14:42:46 - mmengine - INFO - Epoch(val) [660][30/32] eta: 0:00:01 time: 0.5966 data_time: 0.0319 memory: 15734 2022/08/30 14:42:47 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 14:42:47 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8445, precision: 0.7869, hmean: 0.8147 2022/08/30 14:42:47 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8445, precision: 0.8239, hmean: 0.8340 2022/08/30 14:42:47 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8445, precision: 0.8445, hmean: 0.8445 2022/08/30 14:42:47 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8387, precision: 0.8632, hmean: 0.8508 2022/08/30 14:42:47 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8310, precision: 0.8888, hmean: 0.8589 2022/08/30 14:42:47 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7800, precision: 0.9199, hmean: 0.8442 2022/08/30 14:42:47 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2350, precision: 0.9606, hmean: 0.3776 2022/08/30 14:42:47 - mmengine - INFO - Epoch(val) [660][32/32] icdar/precision: 0.8888 icdar/recall: 0.8310 icdar/hmean: 0.8589 2022/08/30 14:42:54 - mmengine - INFO - Epoch(train) [661][5/63] lr: 3.4088e-03 eta: 0:00:01 time: 1.0360 data_time: 0.2145 memory: 16201 loss_prob: 0.4361 loss_thr: 0.3133 loss_db: 0.0769 loss: 0.8263 2022/08/30 14:42:58 - mmengine - INFO - Epoch(train) [661][10/63] lr: 3.4088e-03 eta: 12:03:15 time: 1.0647 data_time: 0.2165 memory: 16201 loss_prob: 0.4488 loss_thr: 0.3244 loss_db: 0.0795 loss: 0.8527 2022/08/30 14:43:02 - mmengine - INFO - Epoch(train) [661][15/63] lr: 3.4088e-03 eta: 12:03:15 time: 0.8531 data_time: 0.0273 memory: 16201 loss_prob: 0.4357 loss_thr: 0.3198 loss_db: 0.0753 loss: 0.8307 2022/08/30 14:43:07 - mmengine - INFO - Epoch(train) [661][20/63] lr: 3.4088e-03 eta: 12:03:00 time: 0.9285 data_time: 0.0318 memory: 16201 loss_prob: 0.3706 loss_thr: 0.2811 loss_db: 0.0646 loss: 0.7163 2022/08/30 14:43:11 - mmengine - INFO - Epoch(train) [661][25/63] lr: 3.4088e-03 eta: 12:03:00 time: 0.9085 data_time: 0.0250 memory: 16201 loss_prob: 0.3805 loss_thr: 0.2829 loss_db: 0.0681 loss: 0.7315 2022/08/30 14:43:16 - mmengine - INFO - Epoch(train) [661][30/63] lr: 3.4088e-03 eta: 12:02:43 time: 0.8460 data_time: 0.0245 memory: 16201 loss_prob: 0.5643 loss_thr: 0.3116 loss_db: 0.0848 loss: 0.9607 2022/08/30 14:43:20 - mmengine - INFO - Epoch(train) [661][35/63] lr: 3.4088e-03 eta: 12:02:43 time: 0.8364 data_time: 0.0251 memory: 16201 loss_prob: 0.5638 loss_thr: 0.3129 loss_db: 0.0836 loss: 0.9603 2022/08/30 14:43:24 - mmengine - INFO - Epoch(train) [661][40/63] lr: 3.4088e-03 eta: 12:02:27 time: 0.8207 data_time: 0.0206 memory: 16201 loss_prob: 0.4274 loss_thr: 0.3039 loss_db: 0.0729 loss: 0.8042 2022/08/30 14:43:28 - mmengine - INFO - Epoch(train) [661][45/63] lr: 3.4088e-03 eta: 12:02:27 time: 0.8288 data_time: 0.0305 memory: 16201 loss_prob: 0.4560 loss_thr: 0.3014 loss_db: 0.0798 loss: 0.8373 2022/08/30 14:43:32 - mmengine - INFO - Epoch(train) [661][50/63] lr: 3.4088e-03 eta: 12:02:10 time: 0.8187 data_time: 0.0258 memory: 16201 loss_prob: 0.5029 loss_thr: 0.3193 loss_db: 0.0896 loss: 0.9118 2022/08/30 14:43:36 - mmengine - INFO - Epoch(train) [661][55/63] lr: 3.4088e-03 eta: 12:02:10 time: 0.8336 data_time: 0.0164 memory: 16201 loss_prob: 0.5334 loss_thr: 0.3434 loss_db: 0.0912 loss: 0.9679 2022/08/30 14:43:40 - mmengine - INFO - Epoch(train) [661][60/63] lr: 3.4088e-03 eta: 12:01:54 time: 0.8293 data_time: 0.0267 memory: 16201 loss_prob: 0.5010 loss_thr: 0.3399 loss_db: 0.0859 loss: 0.9268 2022/08/30 14:43:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:43:48 - mmengine - INFO - Epoch(train) [662][5/63] lr: 3.4031e-03 eta: 12:01:54 time: 0.9111 data_time: 0.1588 memory: 16201 loss_prob: 0.4425 loss_thr: 0.3245 loss_db: 0.0779 loss: 0.8449 2022/08/30 14:43:52 - mmengine - INFO - Epoch(train) [662][10/63] lr: 3.4031e-03 eta: 12:01:32 time: 0.9494 data_time: 0.1685 memory: 16201 loss_prob: 0.4225 loss_thr: 0.3067 loss_db: 0.0730 loss: 0.8022 2022/08/30 14:43:56 - mmengine - INFO - Epoch(train) [662][15/63] lr: 3.4031e-03 eta: 12:01:32 time: 0.7975 data_time: 0.0233 memory: 16201 loss_prob: 0.4751 loss_thr: 0.3359 loss_db: 0.0836 loss: 0.8947 2022/08/30 14:44:00 - mmengine - INFO - Epoch(train) [662][20/63] lr: 3.4031e-03 eta: 12:01:15 time: 0.7879 data_time: 0.0191 memory: 16201 loss_prob: 0.4917 loss_thr: 0.3459 loss_db: 0.0862 loss: 0.9238 2022/08/30 14:44:04 - mmengine - INFO - Epoch(train) [662][25/63] lr: 3.4031e-03 eta: 12:01:15 time: 0.7976 data_time: 0.0322 memory: 16201 loss_prob: 0.4432 loss_thr: 0.3117 loss_db: 0.0768 loss: 0.8317 2022/08/30 14:44:08 - mmengine - INFO - Epoch(train) [662][30/63] lr: 3.4031e-03 eta: 12:00:58 time: 0.7877 data_time: 0.0243 memory: 16201 loss_prob: 0.4438 loss_thr: 0.3197 loss_db: 0.0791 loss: 0.8425 2022/08/30 14:44:12 - mmengine - INFO - Epoch(train) [662][35/63] lr: 3.4031e-03 eta: 12:00:58 time: 0.7681 data_time: 0.0166 memory: 16201 loss_prob: 0.4709 loss_thr: 0.3324 loss_db: 0.0838 loss: 0.8871 2022/08/30 14:44:16 - mmengine - INFO - Epoch(train) [662][40/63] lr: 3.4031e-03 eta: 12:00:42 time: 0.8201 data_time: 0.0265 memory: 16201 loss_prob: 0.4773 loss_thr: 0.3341 loss_db: 0.0811 loss: 0.8925 2022/08/30 14:44:20 - mmengine - INFO - Epoch(train) [662][45/63] lr: 3.4031e-03 eta: 12:00:42 time: 0.8360 data_time: 0.0263 memory: 16201 loss_prob: 0.4638 loss_thr: 0.3344 loss_db: 0.0791 loss: 0.8773 2022/08/30 14:44:24 - mmengine - INFO - Epoch(train) [662][50/63] lr: 3.4031e-03 eta: 12:00:25 time: 0.8245 data_time: 0.0236 memory: 16201 loss_prob: 0.4414 loss_thr: 0.3170 loss_db: 0.0786 loss: 0.8370 2022/08/30 14:44:29 - mmengine - INFO - Epoch(train) [662][55/63] lr: 3.4031e-03 eta: 12:00:25 time: 0.8636 data_time: 0.0247 memory: 16201 loss_prob: 0.4500 loss_thr: 0.3139 loss_db: 0.0810 loss: 0.8449 2022/08/30 14:44:33 - mmengine - INFO - Epoch(train) [662][60/63] lr: 3.4031e-03 eta: 12:00:09 time: 0.8610 data_time: 0.0295 memory: 16201 loss_prob: 0.4632 loss_thr: 0.3275 loss_db: 0.0821 loss: 0.8728 2022/08/30 14:44:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:44:41 - mmengine - INFO - Epoch(train) [663][5/63] lr: 3.3974e-03 eta: 12:00:09 time: 0.9870 data_time: 0.1813 memory: 16201 loss_prob: 0.4682 loss_thr: 0.3450 loss_db: 0.0819 loss: 0.8951 2022/08/30 14:44:45 - mmengine - INFO - Epoch(train) [663][10/63] lr: 3.3974e-03 eta: 11:59:47 time: 1.0288 data_time: 0.1888 memory: 16201 loss_prob: 0.4593 loss_thr: 0.3326 loss_db: 0.0818 loss: 0.8737 2022/08/30 14:44:49 - mmengine - INFO - Epoch(train) [663][15/63] lr: 3.3974e-03 eta: 11:59:47 time: 0.8075 data_time: 0.0270 memory: 16201 loss_prob: 0.4840 loss_thr: 0.3447 loss_db: 0.0858 loss: 0.9145 2022/08/30 14:44:54 - mmengine - INFO - Epoch(train) [663][20/63] lr: 3.3974e-03 eta: 11:59:31 time: 0.8519 data_time: 0.0252 memory: 16201 loss_prob: 0.4994 loss_thr: 0.3523 loss_db: 0.0881 loss: 0.9398 2022/08/30 14:44:58 - mmengine - INFO - Epoch(train) [663][25/63] lr: 3.3974e-03 eta: 11:59:31 time: 0.8637 data_time: 0.0301 memory: 16201 loss_prob: 0.4535 loss_thr: 0.3239 loss_db: 0.0807 loss: 0.8581 2022/08/30 14:45:02 - mmengine - INFO - Epoch(train) [663][30/63] lr: 3.3974e-03 eta: 11:59:15 time: 0.8537 data_time: 0.0281 memory: 16201 loss_prob: 0.3922 loss_thr: 0.2868 loss_db: 0.0681 loss: 0.7471 2022/08/30 14:45:07 - mmengine - INFO - Epoch(train) [663][35/63] lr: 3.3974e-03 eta: 11:59:15 time: 0.8751 data_time: 0.0254 memory: 16201 loss_prob: 0.4100 loss_thr: 0.2917 loss_db: 0.0712 loss: 0.7730 2022/08/30 14:45:11 - mmengine - INFO - Epoch(train) [663][40/63] lr: 3.3974e-03 eta: 11:58:59 time: 0.8468 data_time: 0.0264 memory: 16201 loss_prob: 0.4332 loss_thr: 0.2947 loss_db: 0.0775 loss: 0.8054 2022/08/30 14:45:15 - mmengine - INFO - Epoch(train) [663][45/63] lr: 3.3974e-03 eta: 11:58:59 time: 0.8116 data_time: 0.0232 memory: 16201 loss_prob: 0.4362 loss_thr: 0.2985 loss_db: 0.0765 loss: 0.8112 2022/08/30 14:45:19 - mmengine - INFO - Epoch(train) [663][50/63] lr: 3.3974e-03 eta: 11:58:43 time: 0.8729 data_time: 0.0242 memory: 16201 loss_prob: 0.4555 loss_thr: 0.3117 loss_db: 0.0796 loss: 0.8468 2022/08/30 14:45:24 - mmengine - INFO - Epoch(train) [663][55/63] lr: 3.3974e-03 eta: 11:58:43 time: 0.8800 data_time: 0.0314 memory: 16201 loss_prob: 0.4511 loss_thr: 0.3092 loss_db: 0.0805 loss: 0.8408 2022/08/30 14:45:28 - mmengine - INFO - Epoch(train) [663][60/63] lr: 3.3974e-03 eta: 11:58:27 time: 0.8208 data_time: 0.0309 memory: 16201 loss_prob: 0.4492 loss_thr: 0.3244 loss_db: 0.0801 loss: 0.8537 2022/08/30 14:45:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:45:35 - mmengine - INFO - Epoch(train) [664][5/63] lr: 3.3917e-03 eta: 11:58:27 time: 0.9161 data_time: 0.1826 memory: 16201 loss_prob: 0.4429 loss_thr: 0.3211 loss_db: 0.0765 loss: 0.8405 2022/08/30 14:45:40 - mmengine - INFO - Epoch(train) [664][10/63] lr: 3.3917e-03 eta: 11:58:05 time: 0.9834 data_time: 0.1888 memory: 16201 loss_prob: 0.5021 loss_thr: 0.3266 loss_db: 0.0835 loss: 0.9121 2022/08/30 14:45:44 - mmengine - INFO - Epoch(train) [664][15/63] lr: 3.3917e-03 eta: 11:58:05 time: 0.8404 data_time: 0.0243 memory: 16201 loss_prob: 0.4977 loss_thr: 0.3236 loss_db: 0.0840 loss: 0.9052 2022/08/30 14:45:48 - mmengine - INFO - Epoch(train) [664][20/63] lr: 3.3917e-03 eta: 11:57:48 time: 0.8270 data_time: 0.0224 memory: 16201 loss_prob: 0.4620 loss_thr: 0.3236 loss_db: 0.0813 loss: 0.8669 2022/08/30 14:45:52 - mmengine - INFO - Epoch(train) [664][25/63] lr: 3.3917e-03 eta: 11:57:48 time: 0.8336 data_time: 0.0288 memory: 16201 loss_prob: 0.4863 loss_thr: 0.3292 loss_db: 0.0835 loss: 0.8990 2022/08/30 14:45:57 - mmengine - INFO - Epoch(train) [664][30/63] lr: 3.3917e-03 eta: 11:57:32 time: 0.9048 data_time: 0.0272 memory: 16201 loss_prob: 0.4655 loss_thr: 0.3226 loss_db: 0.0810 loss: 0.8691 2022/08/30 14:46:01 - mmengine - INFO - Epoch(train) [664][35/63] lr: 3.3917e-03 eta: 11:57:32 time: 0.8763 data_time: 0.0240 memory: 16201 loss_prob: 0.4596 loss_thr: 0.3234 loss_db: 0.0816 loss: 0.8646 2022/08/30 14:46:05 - mmengine - INFO - Epoch(train) [664][40/63] lr: 3.3917e-03 eta: 11:57:16 time: 0.8082 data_time: 0.0242 memory: 16201 loss_prob: 0.5057 loss_thr: 0.3511 loss_db: 0.0881 loss: 0.9449 2022/08/30 14:46:09 - mmengine - INFO - Epoch(train) [664][45/63] lr: 3.3917e-03 eta: 11:57:16 time: 0.8383 data_time: 0.0253 memory: 16201 loss_prob: 0.5151 loss_thr: 0.3723 loss_db: 0.0905 loss: 0.9779 2022/08/30 14:46:13 - mmengine - INFO - Epoch(train) [664][50/63] lr: 3.3917e-03 eta: 11:57:00 time: 0.8313 data_time: 0.0239 memory: 16201 loss_prob: 0.5013 loss_thr: 0.3604 loss_db: 0.0892 loss: 0.9509 2022/08/30 14:46:18 - mmengine - INFO - Epoch(train) [664][55/63] lr: 3.3917e-03 eta: 11:57:00 time: 0.8861 data_time: 0.0239 memory: 16201 loss_prob: 0.4596 loss_thr: 0.3182 loss_db: 0.0791 loss: 0.8568 2022/08/30 14:46:22 - mmengine - INFO - Epoch(train) [664][60/63] lr: 3.3917e-03 eta: 11:56:44 time: 0.8896 data_time: 0.0277 memory: 16201 loss_prob: 0.4449 loss_thr: 0.3016 loss_db: 0.0745 loss: 0.8210 2022/08/30 14:46:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:46:30 - mmengine - INFO - Epoch(train) [665][5/63] lr: 3.3860e-03 eta: 11:56:44 time: 0.9663 data_time: 0.2005 memory: 16201 loss_prob: 0.4335 loss_thr: 0.3098 loss_db: 0.0781 loss: 0.8214 2022/08/30 14:46:34 - mmengine - INFO - Epoch(train) [665][10/63] lr: 3.3860e-03 eta: 11:56:22 time: 1.0196 data_time: 0.2128 memory: 16201 loss_prob: 0.4168 loss_thr: 0.3029 loss_db: 0.0724 loss: 0.7921 2022/08/30 14:46:39 - mmengine - INFO - Epoch(train) [665][15/63] lr: 3.3860e-03 eta: 11:56:22 time: 0.8664 data_time: 0.0287 memory: 16201 loss_prob: 0.4512 loss_thr: 0.3112 loss_db: 0.0790 loss: 0.8414 2022/08/30 14:46:43 - mmengine - INFO - Epoch(train) [665][20/63] lr: 3.3860e-03 eta: 11:56:06 time: 0.8627 data_time: 0.0173 memory: 16201 loss_prob: 0.5021 loss_thr: 0.3177 loss_db: 0.0869 loss: 0.9067 2022/08/30 14:46:48 - mmengine - INFO - Epoch(train) [665][25/63] lr: 3.3860e-03 eta: 11:56:06 time: 0.8680 data_time: 0.0350 memory: 16201 loss_prob: 0.4675 loss_thr: 0.3017 loss_db: 0.0781 loss: 0.8473 2022/08/30 14:46:52 - mmengine - INFO - Epoch(train) [665][30/63] lr: 3.3860e-03 eta: 11:55:50 time: 0.8575 data_time: 0.0274 memory: 16201 loss_prob: 0.4253 loss_thr: 0.2934 loss_db: 0.0725 loss: 0.7911 2022/08/30 14:46:56 - mmengine - INFO - Epoch(train) [665][35/63] lr: 3.3860e-03 eta: 11:55:50 time: 0.8616 data_time: 0.0206 memory: 16201 loss_prob: 0.4325 loss_thr: 0.3060 loss_db: 0.0763 loss: 0.8149 2022/08/30 14:47:00 - mmengine - INFO - Epoch(train) [665][40/63] lr: 3.3860e-03 eta: 11:55:34 time: 0.8777 data_time: 0.0284 memory: 16201 loss_prob: 0.4567 loss_thr: 0.3278 loss_db: 0.0809 loss: 0.8654 2022/08/30 14:47:05 - mmengine - INFO - Epoch(train) [665][45/63] lr: 3.3860e-03 eta: 11:55:34 time: 0.8357 data_time: 0.0243 memory: 16201 loss_prob: 0.4608 loss_thr: 0.3381 loss_db: 0.0795 loss: 0.8783 2022/08/30 14:47:09 - mmengine - INFO - Epoch(train) [665][50/63] lr: 3.3860e-03 eta: 11:55:18 time: 0.8147 data_time: 0.0281 memory: 16201 loss_prob: 0.4669 loss_thr: 0.3356 loss_db: 0.0818 loss: 0.8843 2022/08/30 14:47:13 - mmengine - INFO - Epoch(train) [665][55/63] lr: 3.3860e-03 eta: 11:55:18 time: 0.8212 data_time: 0.0255 memory: 16201 loss_prob: 0.4988 loss_thr: 0.3472 loss_db: 0.0891 loss: 0.9351 2022/08/30 14:47:17 - mmengine - INFO - Epoch(train) [665][60/63] lr: 3.3860e-03 eta: 11:55:02 time: 0.8580 data_time: 0.0239 memory: 16201 loss_prob: 0.4851 loss_thr: 0.3437 loss_db: 0.0849 loss: 0.9137 2022/08/30 14:47:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:47:25 - mmengine - INFO - Epoch(train) [666][5/63] lr: 3.3803e-03 eta: 11:55:02 time: 0.9511 data_time: 0.1649 memory: 16201 loss_prob: 0.4635 loss_thr: 0.3294 loss_db: 0.0824 loss: 0.8752 2022/08/30 14:47:29 - mmengine - INFO - Epoch(train) [666][10/63] lr: 3.3803e-03 eta: 11:54:40 time: 1.0328 data_time: 0.1767 memory: 16201 loss_prob: 0.4438 loss_thr: 0.3186 loss_db: 0.0801 loss: 0.8425 2022/08/30 14:47:33 - mmengine - INFO - Epoch(train) [666][15/63] lr: 3.3803e-03 eta: 11:54:40 time: 0.8478 data_time: 0.0244 memory: 16201 loss_prob: 0.4467 loss_thr: 0.3137 loss_db: 0.0774 loss: 0.8378 2022/08/30 14:47:38 - mmengine - INFO - Epoch(train) [666][20/63] lr: 3.3803e-03 eta: 11:54:24 time: 0.8247 data_time: 0.0208 memory: 16201 loss_prob: 0.4677 loss_thr: 0.3174 loss_db: 0.0809 loss: 0.8660 2022/08/30 14:47:42 - mmengine - INFO - Epoch(train) [666][25/63] lr: 3.3803e-03 eta: 11:54:24 time: 0.8275 data_time: 0.0249 memory: 16201 loss_prob: 0.5086 loss_thr: 0.3428 loss_db: 0.0891 loss: 0.9405 2022/08/30 14:47:46 - mmengine - INFO - Epoch(train) [666][30/63] lr: 3.3803e-03 eta: 11:54:08 time: 0.8440 data_time: 0.0235 memory: 16201 loss_prob: 0.4540 loss_thr: 0.3131 loss_db: 0.0802 loss: 0.8473 2022/08/30 14:47:50 - mmengine - INFO - Epoch(train) [666][35/63] lr: 3.3803e-03 eta: 11:54:08 time: 0.8287 data_time: 0.0242 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2955 loss_db: 0.0723 loss: 0.7782 2022/08/30 14:47:54 - mmengine - INFO - Epoch(train) [666][40/63] lr: 3.3803e-03 eta: 11:53:51 time: 0.7743 data_time: 0.0225 memory: 16201 loss_prob: 0.4227 loss_thr: 0.3112 loss_db: 0.0736 loss: 0.8075 2022/08/30 14:47:58 - mmengine - INFO - Epoch(train) [666][45/63] lr: 3.3803e-03 eta: 11:53:51 time: 0.8147 data_time: 0.0280 memory: 16201 loss_prob: 0.4282 loss_thr: 0.3111 loss_db: 0.0752 loss: 0.8144 2022/08/30 14:48:02 - mmengine - INFO - Epoch(train) [666][50/63] lr: 3.3803e-03 eta: 11:53:34 time: 0.8204 data_time: 0.0284 memory: 16201 loss_prob: 0.4749 loss_thr: 0.3308 loss_db: 0.0836 loss: 0.8893 2022/08/30 14:48:06 - mmengine - INFO - Epoch(train) [666][55/63] lr: 3.3803e-03 eta: 11:53:34 time: 0.7844 data_time: 0.0233 memory: 16201 loss_prob: 0.5027 loss_thr: 0.3413 loss_db: 0.0879 loss: 0.9320 2022/08/30 14:48:10 - mmengine - INFO - Epoch(train) [666][60/63] lr: 3.3803e-03 eta: 11:53:18 time: 0.8446 data_time: 0.0248 memory: 16201 loss_prob: 0.4557 loss_thr: 0.3207 loss_db: 0.0808 loss: 0.8572 2022/08/30 14:48:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:48:18 - mmengine - INFO - Epoch(train) [667][5/63] lr: 3.3746e-03 eta: 11:53:18 time: 0.9354 data_time: 0.1753 memory: 16201 loss_prob: 0.4241 loss_thr: 0.3066 loss_db: 0.0737 loss: 0.8044 2022/08/30 14:48:23 - mmengine - INFO - Epoch(train) [667][10/63] lr: 3.3746e-03 eta: 11:52:57 time: 1.0015 data_time: 0.1859 memory: 16201 loss_prob: 0.4096 loss_thr: 0.2985 loss_db: 0.0717 loss: 0.7797 2022/08/30 14:48:27 - mmengine - INFO - Epoch(train) [667][15/63] lr: 3.3746e-03 eta: 11:52:57 time: 0.8775 data_time: 0.0231 memory: 16201 loss_prob: 0.4327 loss_thr: 0.3197 loss_db: 0.0756 loss: 0.8280 2022/08/30 14:48:31 - mmengine - INFO - Epoch(train) [667][20/63] lr: 3.3746e-03 eta: 11:52:41 time: 0.8814 data_time: 0.0223 memory: 16201 loss_prob: 0.4455 loss_thr: 0.3328 loss_db: 0.0783 loss: 0.8566 2022/08/30 14:48:35 - mmengine - INFO - Epoch(train) [667][25/63] lr: 3.3746e-03 eta: 11:52:41 time: 0.8339 data_time: 0.0248 memory: 16201 loss_prob: 0.4358 loss_thr: 0.3146 loss_db: 0.0776 loss: 0.8279 2022/08/30 14:48:40 - mmengine - INFO - Epoch(train) [667][30/63] lr: 3.3746e-03 eta: 11:52:25 time: 0.8369 data_time: 0.0277 memory: 16201 loss_prob: 0.4515 loss_thr: 0.3147 loss_db: 0.0785 loss: 0.8447 2022/08/30 14:48:44 - mmengine - INFO - Epoch(train) [667][35/63] lr: 3.3746e-03 eta: 11:52:25 time: 0.8582 data_time: 0.0310 memory: 16201 loss_prob: 0.4666 loss_thr: 0.3290 loss_db: 0.0809 loss: 0.8765 2022/08/30 14:48:49 - mmengine - INFO - Epoch(train) [667][40/63] lr: 3.3746e-03 eta: 11:52:09 time: 0.8809 data_time: 0.0217 memory: 16201 loss_prob: 0.4422 loss_thr: 0.3260 loss_db: 0.0775 loss: 0.8457 2022/08/30 14:48:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:48:53 - mmengine - INFO - Epoch(train) [667][45/63] lr: 3.3746e-03 eta: 11:52:09 time: 0.8742 data_time: 0.0239 memory: 16201 loss_prob: 0.4029 loss_thr: 0.3044 loss_db: 0.0716 loss: 0.7789 2022/08/30 14:48:57 - mmengine - INFO - Epoch(train) [667][50/63] lr: 3.3746e-03 eta: 11:51:53 time: 0.8575 data_time: 0.0273 memory: 16201 loss_prob: 0.4510 loss_thr: 0.3269 loss_db: 0.0790 loss: 0.8569 2022/08/30 14:49:01 - mmengine - INFO - Epoch(train) [667][55/63] lr: 3.3746e-03 eta: 11:51:53 time: 0.8471 data_time: 0.0258 memory: 16201 loss_prob: 0.5015 loss_thr: 0.3536 loss_db: 0.0866 loss: 0.9416 2022/08/30 14:49:06 - mmengine - INFO - Epoch(train) [667][60/63] lr: 3.3746e-03 eta: 11:51:37 time: 0.8727 data_time: 0.0267 memory: 16201 loss_prob: 0.4396 loss_thr: 0.3154 loss_db: 0.0775 loss: 0.8325 2022/08/30 14:49:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:49:14 - mmengine - INFO - Epoch(train) [668][5/63] lr: 3.3689e-03 eta: 11:51:37 time: 0.9966 data_time: 0.2060 memory: 16201 loss_prob: 0.4499 loss_thr: 0.3236 loss_db: 0.0776 loss: 0.8511 2022/08/30 14:49:18 - mmengine - INFO - Epoch(train) [668][10/63] lr: 3.3689e-03 eta: 11:51:15 time: 1.0301 data_time: 0.2201 memory: 16201 loss_prob: 0.4939 loss_thr: 0.3437 loss_db: 0.0847 loss: 0.9223 2022/08/30 14:49:22 - mmengine - INFO - Epoch(train) [668][15/63] lr: 3.3689e-03 eta: 11:51:15 time: 0.8394 data_time: 0.0317 memory: 16201 loss_prob: 0.4845 loss_thr: 0.3271 loss_db: 0.0824 loss: 0.8941 2022/08/30 14:49:27 - mmengine - INFO - Epoch(train) [668][20/63] lr: 3.3689e-03 eta: 11:50:59 time: 0.8868 data_time: 0.0218 memory: 16201 loss_prob: 0.4572 loss_thr: 0.3203 loss_db: 0.0795 loss: 0.8569 2022/08/30 14:49:31 - mmengine - INFO - Epoch(train) [668][25/63] lr: 3.3689e-03 eta: 11:50:59 time: 0.9085 data_time: 0.0322 memory: 16201 loss_prob: 0.4647 loss_thr: 0.3227 loss_db: 0.0821 loss: 0.8695 2022/08/30 14:49:36 - mmengine - INFO - Epoch(train) [668][30/63] lr: 3.3689e-03 eta: 11:50:44 time: 0.8673 data_time: 0.0297 memory: 16201 loss_prob: 0.4905 loss_thr: 0.3461 loss_db: 0.0852 loss: 0.9217 2022/08/30 14:49:40 - mmengine - INFO - Epoch(train) [668][35/63] lr: 3.3689e-03 eta: 11:50:44 time: 0.8456 data_time: 0.0205 memory: 16201 loss_prob: 0.4723 loss_thr: 0.3436 loss_db: 0.0817 loss: 0.8976 2022/08/30 14:49:44 - mmengine - INFO - Epoch(train) [668][40/63] lr: 3.3689e-03 eta: 11:50:27 time: 0.8520 data_time: 0.0223 memory: 16201 loss_prob: 0.4580 loss_thr: 0.3299 loss_db: 0.0783 loss: 0.8662 2022/08/30 14:49:49 - mmengine - INFO - Epoch(train) [668][45/63] lr: 3.3689e-03 eta: 11:50:27 time: 0.9304 data_time: 0.0255 memory: 16201 loss_prob: 0.4378 loss_thr: 0.3231 loss_db: 0.0745 loss: 0.8353 2022/08/30 14:49:53 - mmengine - INFO - Epoch(train) [668][50/63] lr: 3.3689e-03 eta: 11:50:12 time: 0.9126 data_time: 0.0300 memory: 16201 loss_prob: 0.3958 loss_thr: 0.3129 loss_db: 0.0700 loss: 0.7787 2022/08/30 14:49:57 - mmengine - INFO - Epoch(train) [668][55/63] lr: 3.3689e-03 eta: 11:50:12 time: 0.8151 data_time: 0.0289 memory: 16201 loss_prob: 0.4041 loss_thr: 0.3160 loss_db: 0.0734 loss: 0.7935 2022/08/30 14:50:01 - mmengine - INFO - Epoch(train) [668][60/63] lr: 3.3689e-03 eta: 11:49:56 time: 0.8107 data_time: 0.0236 memory: 16201 loss_prob: 0.4199 loss_thr: 0.3120 loss_db: 0.0760 loss: 0.8078 2022/08/30 14:50:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:50:10 - mmengine - INFO - Epoch(train) [669][5/63] lr: 3.3632e-03 eta: 11:49:56 time: 0.9721 data_time: 0.1705 memory: 16201 loss_prob: 0.3942 loss_thr: 0.2946 loss_db: 0.0682 loss: 0.7570 2022/08/30 14:50:14 - mmengine - INFO - Epoch(train) [669][10/63] lr: 3.3632e-03 eta: 11:49:34 time: 1.0216 data_time: 0.1794 memory: 16201 loss_prob: 0.4148 loss_thr: 0.2966 loss_db: 0.0699 loss: 0.7813 2022/08/30 14:50:18 - mmengine - INFO - Epoch(train) [669][15/63] lr: 3.3632e-03 eta: 11:49:34 time: 0.8434 data_time: 0.0287 memory: 16201 loss_prob: 0.5251 loss_thr: 0.3327 loss_db: 0.0833 loss: 0.9411 2022/08/30 14:50:22 - mmengine - INFO - Epoch(train) [669][20/63] lr: 3.3632e-03 eta: 11:49:18 time: 0.8428 data_time: 0.0209 memory: 16201 loss_prob: 0.5134 loss_thr: 0.3365 loss_db: 0.0819 loss: 0.9318 2022/08/30 14:50:27 - mmengine - INFO - Epoch(train) [669][25/63] lr: 3.3632e-03 eta: 11:49:18 time: 0.8842 data_time: 0.0278 memory: 16201 loss_prob: 0.4735 loss_thr: 0.3413 loss_db: 0.0815 loss: 0.8962 2022/08/30 14:50:31 - mmengine - INFO - Epoch(train) [669][30/63] lr: 3.3632e-03 eta: 11:49:02 time: 0.8740 data_time: 0.0286 memory: 16201 loss_prob: 0.4467 loss_thr: 0.3275 loss_db: 0.0792 loss: 0.8534 2022/08/30 14:50:35 - mmengine - INFO - Epoch(train) [669][35/63] lr: 3.3632e-03 eta: 11:49:02 time: 0.8302 data_time: 0.0222 memory: 16201 loss_prob: 0.4117 loss_thr: 0.3103 loss_db: 0.0751 loss: 0.7971 2022/08/30 14:50:39 - mmengine - INFO - Epoch(train) [669][40/63] lr: 3.3632e-03 eta: 11:48:46 time: 0.8386 data_time: 0.0274 memory: 16201 loss_prob: 0.4645 loss_thr: 0.3350 loss_db: 0.0813 loss: 0.8808 2022/08/30 14:50:43 - mmengine - INFO - Epoch(train) [669][45/63] lr: 3.3632e-03 eta: 11:48:46 time: 0.8318 data_time: 0.0303 memory: 16201 loss_prob: 0.4290 loss_thr: 0.3107 loss_db: 0.0752 loss: 0.8150 2022/08/30 14:50:48 - mmengine - INFO - Epoch(train) [669][50/63] lr: 3.3632e-03 eta: 11:48:30 time: 0.8172 data_time: 0.0241 memory: 16201 loss_prob: 0.4796 loss_thr: 0.3196 loss_db: 0.0823 loss: 0.8815 2022/08/30 14:50:52 - mmengine - INFO - Epoch(train) [669][55/63] lr: 3.3632e-03 eta: 11:48:30 time: 0.8730 data_time: 0.0751 memory: 16201 loss_prob: 0.4772 loss_thr: 0.3222 loss_db: 0.0802 loss: 0.8797 2022/08/30 14:50:56 - mmengine - INFO - Epoch(train) [669][60/63] lr: 3.3632e-03 eta: 11:48:14 time: 0.8874 data_time: 0.0743 memory: 16201 loss_prob: 0.4417 loss_thr: 0.3155 loss_db: 0.0779 loss: 0.8351 2022/08/30 14:50:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:51:05 - mmengine - INFO - Epoch(train) [670][5/63] lr: 3.3575e-03 eta: 11:48:14 time: 1.0070 data_time: 0.1764 memory: 16201 loss_prob: 0.4654 loss_thr: 0.3078 loss_db: 0.0807 loss: 0.8540 2022/08/30 14:51:09 - mmengine - INFO - Epoch(train) [670][10/63] lr: 3.3575e-03 eta: 11:47:52 time: 0.9901 data_time: 0.1778 memory: 16201 loss_prob: 0.4538 loss_thr: 0.3091 loss_db: 0.0800 loss: 0.8428 2022/08/30 14:51:13 - mmengine - INFO - Epoch(train) [670][15/63] lr: 3.3575e-03 eta: 11:47:52 time: 0.8262 data_time: 0.0240 memory: 16201 loss_prob: 0.4180 loss_thr: 0.3008 loss_db: 0.0741 loss: 0.7929 2022/08/30 14:51:17 - mmengine - INFO - Epoch(train) [670][20/63] lr: 3.3575e-03 eta: 11:47:36 time: 0.8729 data_time: 0.0247 memory: 16201 loss_prob: 0.4616 loss_thr: 0.3334 loss_db: 0.0799 loss: 0.8750 2022/08/30 14:51:22 - mmengine - INFO - Epoch(train) [670][25/63] lr: 3.3575e-03 eta: 11:47:36 time: 0.8919 data_time: 0.0290 memory: 16201 loss_prob: 0.4860 loss_thr: 0.3410 loss_db: 0.0855 loss: 0.9124 2022/08/30 14:51:26 - mmengine - INFO - Epoch(train) [670][30/63] lr: 3.3575e-03 eta: 11:47:21 time: 0.8977 data_time: 0.0279 memory: 16201 loss_prob: 0.4395 loss_thr: 0.3062 loss_db: 0.0772 loss: 0.8229 2022/08/30 14:51:31 - mmengine - INFO - Epoch(train) [670][35/63] lr: 3.3575e-03 eta: 11:47:21 time: 0.8803 data_time: 0.0299 memory: 16201 loss_prob: 0.4196 loss_thr: 0.3027 loss_db: 0.0713 loss: 0.7936 2022/08/30 14:51:35 - mmengine - INFO - Epoch(train) [670][40/63] lr: 3.3575e-03 eta: 11:47:05 time: 0.8686 data_time: 0.0253 memory: 16201 loss_prob: 0.4306 loss_thr: 0.3105 loss_db: 0.0752 loss: 0.8163 2022/08/30 14:51:39 - mmengine - INFO - Epoch(train) [670][45/63] lr: 3.3575e-03 eta: 11:47:05 time: 0.8592 data_time: 0.0237 memory: 16201 loss_prob: 0.4112 loss_thr: 0.2999 loss_db: 0.0740 loss: 0.7851 2022/08/30 14:51:43 - mmengine - INFO - Epoch(train) [670][50/63] lr: 3.3575e-03 eta: 11:46:49 time: 0.8483 data_time: 0.0229 memory: 16201 loss_prob: 0.4191 loss_thr: 0.3091 loss_db: 0.0739 loss: 0.8021 2022/08/30 14:51:48 - mmengine - INFO - Epoch(train) [670][55/63] lr: 3.3575e-03 eta: 11:46:49 time: 0.8476 data_time: 0.0240 memory: 16201 loss_prob: 0.4693 loss_thr: 0.3330 loss_db: 0.0815 loss: 0.8838 2022/08/30 14:51:52 - mmengine - INFO - Epoch(train) [670][60/63] lr: 3.3575e-03 eta: 11:46:32 time: 0.8189 data_time: 0.0294 memory: 16201 loss_prob: 0.4718 loss_thr: 0.3254 loss_db: 0.0816 loss: 0.8787 2022/08/30 14:51:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:51:59 - mmengine - INFO - Epoch(train) [671][5/63] lr: 3.3518e-03 eta: 11:46:32 time: 0.9382 data_time: 0.1946 memory: 16201 loss_prob: 0.4506 loss_thr: 0.3354 loss_db: 0.0798 loss: 0.8658 2022/08/30 14:52:03 - mmengine - INFO - Epoch(train) [671][10/63] lr: 3.3518e-03 eta: 11:46:11 time: 0.9768 data_time: 0.2049 memory: 16201 loss_prob: 0.4563 loss_thr: 0.3284 loss_db: 0.0793 loss: 0.8640 2022/08/30 14:52:08 - mmengine - INFO - Epoch(train) [671][15/63] lr: 3.3518e-03 eta: 11:46:11 time: 0.8295 data_time: 0.0259 memory: 16201 loss_prob: 0.4323 loss_thr: 0.3054 loss_db: 0.0756 loss: 0.8132 2022/08/30 14:52:12 - mmengine - INFO - Epoch(train) [671][20/63] lr: 3.3518e-03 eta: 11:45:55 time: 0.8543 data_time: 0.0210 memory: 16201 loss_prob: 0.4468 loss_thr: 0.3102 loss_db: 0.0773 loss: 0.8343 2022/08/30 14:52:16 - mmengine - INFO - Epoch(train) [671][25/63] lr: 3.3518e-03 eta: 11:45:55 time: 0.8306 data_time: 0.0333 memory: 16201 loss_prob: 0.4541 loss_thr: 0.3165 loss_db: 0.0792 loss: 0.8498 2022/08/30 14:52:20 - mmengine - INFO - Epoch(train) [671][30/63] lr: 3.3518e-03 eta: 11:45:38 time: 0.8060 data_time: 0.0280 memory: 16201 loss_prob: 0.4452 loss_thr: 0.3193 loss_db: 0.0799 loss: 0.8444 2022/08/30 14:52:25 - mmengine - INFO - Epoch(train) [671][35/63] lr: 3.3518e-03 eta: 11:45:38 time: 0.8851 data_time: 0.0229 memory: 16201 loss_prob: 0.4260 loss_thr: 0.3097 loss_db: 0.0748 loss: 0.8105 2022/08/30 14:52:29 - mmengine - INFO - Epoch(train) [671][40/63] lr: 3.3518e-03 eta: 11:45:23 time: 0.8937 data_time: 0.0255 memory: 16201 loss_prob: 0.4395 loss_thr: 0.3176 loss_db: 0.0781 loss: 0.8352 2022/08/30 14:52:33 - mmengine - INFO - Epoch(train) [671][45/63] lr: 3.3518e-03 eta: 11:45:23 time: 0.8349 data_time: 0.0250 memory: 16201 loss_prob: 0.4863 loss_thr: 0.3439 loss_db: 0.0861 loss: 0.9163 2022/08/30 14:52:38 - mmengine - INFO - Epoch(train) [671][50/63] lr: 3.3518e-03 eta: 11:45:07 time: 0.8587 data_time: 0.0287 memory: 16201 loss_prob: 0.4493 loss_thr: 0.3219 loss_db: 0.0793 loss: 0.8506 2022/08/30 14:52:42 - mmengine - INFO - Epoch(train) [671][55/63] lr: 3.3518e-03 eta: 11:45:07 time: 0.8511 data_time: 0.0273 memory: 16201 loss_prob: 0.4156 loss_thr: 0.3012 loss_db: 0.0746 loss: 0.7914 2022/08/30 14:52:46 - mmengine - INFO - Epoch(train) [671][60/63] lr: 3.3518e-03 eta: 11:44:51 time: 0.8518 data_time: 0.0311 memory: 16201 loss_prob: 0.4736 loss_thr: 0.3225 loss_db: 0.0830 loss: 0.8790 2022/08/30 14:52:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:52:54 - mmengine - INFO - Epoch(train) [672][5/63] lr: 3.3461e-03 eta: 11:44:51 time: 0.9587 data_time: 0.1853 memory: 16201 loss_prob: 0.4331 loss_thr: 0.3026 loss_db: 0.0749 loss: 0.8105 2022/08/30 14:52:58 - mmengine - INFO - Epoch(train) [672][10/63] lr: 3.3461e-03 eta: 11:44:29 time: 1.0035 data_time: 0.1919 memory: 16201 loss_prob: 0.4319 loss_thr: 0.3173 loss_db: 0.0760 loss: 0.8253 2022/08/30 14:53:03 - mmengine - INFO - Epoch(train) [672][15/63] lr: 3.3461e-03 eta: 11:44:29 time: 0.8617 data_time: 0.0287 memory: 16201 loss_prob: 0.4615 loss_thr: 0.3355 loss_db: 0.0834 loss: 0.8803 2022/08/30 14:53:07 - mmengine - INFO - Epoch(train) [672][20/63] lr: 3.3461e-03 eta: 11:44:13 time: 0.8717 data_time: 0.0259 memory: 16201 loss_prob: 0.4599 loss_thr: 0.3036 loss_db: 0.0834 loss: 0.8469 2022/08/30 14:53:11 - mmengine - INFO - Epoch(train) [672][25/63] lr: 3.3461e-03 eta: 11:44:13 time: 0.8286 data_time: 0.0283 memory: 16201 loss_prob: 0.5064 loss_thr: 0.3181 loss_db: 0.0878 loss: 0.9124 2022/08/30 14:53:15 - mmengine - INFO - Epoch(train) [672][30/63] lr: 3.3461e-03 eta: 11:43:57 time: 0.8160 data_time: 0.0279 memory: 16201 loss_prob: 0.5129 loss_thr: 0.3305 loss_db: 0.0893 loss: 0.9328 2022/08/30 14:53:19 - mmengine - INFO - Epoch(train) [672][35/63] lr: 3.3461e-03 eta: 11:43:57 time: 0.8399 data_time: 0.0264 memory: 16201 loss_prob: 0.4374 loss_thr: 0.3090 loss_db: 0.0795 loss: 0.8258 2022/08/30 14:53:24 - mmengine - INFO - Epoch(train) [672][40/63] lr: 3.3461e-03 eta: 11:43:41 time: 0.8424 data_time: 0.0260 memory: 16201 loss_prob: 0.4527 loss_thr: 0.3246 loss_db: 0.0786 loss: 0.8560 2022/08/30 14:53:28 - mmengine - INFO - Epoch(train) [672][45/63] lr: 3.3461e-03 eta: 11:43:41 time: 0.8548 data_time: 0.0308 memory: 16201 loss_prob: 0.5054 loss_thr: 0.3452 loss_db: 0.0850 loss: 0.9356 2022/08/30 14:53:32 - mmengine - INFO - Epoch(train) [672][50/63] lr: 3.3461e-03 eta: 11:43:25 time: 0.8414 data_time: 0.0266 memory: 16201 loss_prob: 0.4637 loss_thr: 0.3304 loss_db: 0.0815 loss: 0.8755 2022/08/30 14:53:36 - mmengine - INFO - Epoch(train) [672][55/63] lr: 3.3461e-03 eta: 11:43:25 time: 0.8467 data_time: 0.0294 memory: 16201 loss_prob: 0.4714 loss_thr: 0.3226 loss_db: 0.0840 loss: 0.8780 2022/08/30 14:53:40 - mmengine - INFO - Epoch(train) [672][60/63] lr: 3.3461e-03 eta: 11:43:09 time: 0.8429 data_time: 0.0353 memory: 16201 loss_prob: 0.4836 loss_thr: 0.3172 loss_db: 0.0846 loss: 0.8854 2022/08/30 14:53:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:53:49 - mmengine - INFO - Epoch(train) [673][5/63] lr: 3.3404e-03 eta: 11:43:09 time: 1.0231 data_time: 0.2674 memory: 16201 loss_prob: 0.6477 loss_thr: 0.3400 loss_db: 0.0974 loss: 1.0851 2022/08/30 14:53:53 - mmengine - INFO - Epoch(train) [673][10/63] lr: 3.3404e-03 eta: 11:42:48 time: 1.1029 data_time: 0.2833 memory: 16201 loss_prob: 0.4797 loss_thr: 0.3259 loss_db: 0.0846 loss: 0.8902 2022/08/30 14:53:58 - mmengine - INFO - Epoch(train) [673][15/63] lr: 3.3404e-03 eta: 11:42:48 time: 0.8948 data_time: 0.0384 memory: 16201 loss_prob: 0.4560 loss_thr: 0.3204 loss_db: 0.0815 loss: 0.8580 2022/08/30 14:54:02 - mmengine - INFO - Epoch(train) [673][20/63] lr: 3.3404e-03 eta: 11:42:32 time: 0.8429 data_time: 0.0225 memory: 16201 loss_prob: 0.4580 loss_thr: 0.3164 loss_db: 0.0804 loss: 0.8548 2022/08/30 14:54:07 - mmengine - INFO - Epoch(train) [673][25/63] lr: 3.3404e-03 eta: 11:42:32 time: 0.8773 data_time: 0.0377 memory: 16201 loss_prob: 0.4656 loss_thr: 0.3170 loss_db: 0.0818 loss: 0.8644 2022/08/30 14:54:11 - mmengine - INFO - Epoch(train) [673][30/63] lr: 3.3404e-03 eta: 11:42:16 time: 0.8841 data_time: 0.0344 memory: 16201 loss_prob: 0.4766 loss_thr: 0.3423 loss_db: 0.0850 loss: 0.9039 2022/08/30 14:54:15 - mmengine - INFO - Epoch(train) [673][35/63] lr: 3.3404e-03 eta: 11:42:16 time: 0.8331 data_time: 0.0272 memory: 16201 loss_prob: 0.4888 loss_thr: 0.3398 loss_db: 0.0845 loss: 0.9131 2022/08/30 14:54:19 - mmengine - INFO - Epoch(train) [673][40/63] lr: 3.3404e-03 eta: 11:42:00 time: 0.8433 data_time: 0.0359 memory: 16201 loss_prob: 0.4927 loss_thr: 0.3273 loss_db: 0.0830 loss: 0.9030 2022/08/30 14:54:23 - mmengine - INFO - Epoch(train) [673][45/63] lr: 3.3404e-03 eta: 11:42:00 time: 0.8192 data_time: 0.0329 memory: 16201 loss_prob: 0.4666 loss_thr: 0.3224 loss_db: 0.0807 loss: 0.8698 2022/08/30 14:54:28 - mmengine - INFO - Epoch(train) [673][50/63] lr: 3.3404e-03 eta: 11:41:45 time: 0.9054 data_time: 0.0305 memory: 16201 loss_prob: 0.4532 loss_thr: 0.3254 loss_db: 0.0792 loss: 0.8578 2022/08/30 14:54:33 - mmengine - INFO - Epoch(train) [673][55/63] lr: 3.3404e-03 eta: 11:41:45 time: 0.9268 data_time: 0.0315 memory: 16201 loss_prob: 0.4677 loss_thr: 0.3333 loss_db: 0.0806 loss: 0.8816 2022/08/30 14:54:37 - mmengine - INFO - Epoch(train) [673][60/63] lr: 3.3404e-03 eta: 11:41:29 time: 0.8451 data_time: 0.0259 memory: 16201 loss_prob: 0.4558 loss_thr: 0.3199 loss_db: 0.0793 loss: 0.8550 2022/08/30 14:54:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:54:45 - mmengine - INFO - Epoch(train) [674][5/63] lr: 3.3347e-03 eta: 11:41:29 time: 0.9858 data_time: 0.1981 memory: 16201 loss_prob: 0.4497 loss_thr: 0.3186 loss_db: 0.0786 loss: 0.8469 2022/08/30 14:54:49 - mmengine - INFO - Epoch(train) [674][10/63] lr: 3.3347e-03 eta: 11:41:08 time: 1.0295 data_time: 0.2094 memory: 16201 loss_prob: 0.5114 loss_thr: 0.3502 loss_db: 0.0905 loss: 0.9520 2022/08/30 14:54:53 - mmengine - INFO - Epoch(train) [674][15/63] lr: 3.3347e-03 eta: 11:41:08 time: 0.8364 data_time: 0.0268 memory: 16201 loss_prob: 0.5472 loss_thr: 0.3713 loss_db: 0.0952 loss: 1.0137 2022/08/30 14:54:58 - mmengine - INFO - Epoch(train) [674][20/63] lr: 3.3347e-03 eta: 11:40:52 time: 0.8890 data_time: 0.0272 memory: 16201 loss_prob: 0.4873 loss_thr: 0.3414 loss_db: 0.0859 loss: 0.9147 2022/08/30 14:55:02 - mmengine - INFO - Epoch(train) [674][25/63] lr: 3.3347e-03 eta: 11:40:52 time: 0.8833 data_time: 0.0336 memory: 16201 loss_prob: 0.4568 loss_thr: 0.3138 loss_db: 0.0828 loss: 0.8534 2022/08/30 14:55:06 - mmengine - INFO - Epoch(train) [674][30/63] lr: 3.3347e-03 eta: 11:40:36 time: 0.8156 data_time: 0.0287 memory: 16201 loss_prob: 0.4402 loss_thr: 0.3143 loss_db: 0.0777 loss: 0.8322 2022/08/30 14:55:10 - mmengine - INFO - Epoch(train) [674][35/63] lr: 3.3347e-03 eta: 11:40:36 time: 0.8087 data_time: 0.0245 memory: 16201 loss_prob: 0.4322 loss_thr: 0.3163 loss_db: 0.0740 loss: 0.8225 2022/08/30 14:55:14 - mmengine - INFO - Epoch(train) [674][40/63] lr: 3.3347e-03 eta: 11:40:20 time: 0.8135 data_time: 0.0277 memory: 16201 loss_prob: 0.4760 loss_thr: 0.3273 loss_db: 0.0822 loss: 0.8855 2022/08/30 14:55:19 - mmengine - INFO - Epoch(train) [674][45/63] lr: 3.3347e-03 eta: 11:40:20 time: 0.8288 data_time: 0.0324 memory: 16201 loss_prob: 0.4616 loss_thr: 0.3204 loss_db: 0.0808 loss: 0.8628 2022/08/30 14:55:23 - mmengine - INFO - Epoch(train) [674][50/63] lr: 3.3347e-03 eta: 11:40:03 time: 0.8163 data_time: 0.0262 memory: 16201 loss_prob: 0.3817 loss_thr: 0.2814 loss_db: 0.0664 loss: 0.7295 2022/08/30 14:55:27 - mmengine - INFO - Epoch(train) [674][55/63] lr: 3.3347e-03 eta: 11:40:03 time: 0.8111 data_time: 0.0231 memory: 16201 loss_prob: 0.4296 loss_thr: 0.3033 loss_db: 0.0746 loss: 0.8075 2022/08/30 14:55:31 - mmengine - INFO - Epoch(train) [674][60/63] lr: 3.3347e-03 eta: 11:39:47 time: 0.8014 data_time: 0.0278 memory: 16201 loss_prob: 0.4428 loss_thr: 0.3092 loss_db: 0.0779 loss: 0.8299 2022/08/30 14:55:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:55:38 - mmengine - INFO - Epoch(train) [675][5/63] lr: 3.3290e-03 eta: 11:39:47 time: 0.9405 data_time: 0.1600 memory: 16201 loss_prob: 0.4099 loss_thr: 0.2988 loss_db: 0.0723 loss: 0.7810 2022/08/30 14:55:42 - mmengine - INFO - Epoch(train) [675][10/63] lr: 3.3290e-03 eta: 11:39:25 time: 0.9708 data_time: 0.1708 memory: 16201 loss_prob: 0.4570 loss_thr: 0.3247 loss_db: 0.0809 loss: 0.8626 2022/08/30 14:55:47 - mmengine - INFO - Epoch(train) [675][15/63] lr: 3.3290e-03 eta: 11:39:25 time: 0.8085 data_time: 0.0241 memory: 16201 loss_prob: 0.4602 loss_thr: 0.3226 loss_db: 0.0819 loss: 0.8647 2022/08/30 14:55:51 - mmengine - INFO - Epoch(train) [675][20/63] lr: 3.3290e-03 eta: 11:39:09 time: 0.8067 data_time: 0.0159 memory: 16201 loss_prob: 0.4408 loss_thr: 0.3138 loss_db: 0.0777 loss: 0.8324 2022/08/30 14:55:54 - mmengine - INFO - Epoch(train) [675][25/63] lr: 3.3290e-03 eta: 11:39:09 time: 0.7908 data_time: 0.0279 memory: 16201 loss_prob: 0.4225 loss_thr: 0.2966 loss_db: 0.0755 loss: 0.7947 2022/08/30 14:55:58 - mmengine - INFO - Epoch(train) [675][30/63] lr: 3.3290e-03 eta: 11:38:53 time: 0.7795 data_time: 0.0225 memory: 16201 loss_prob: 0.4273 loss_thr: 0.2902 loss_db: 0.0745 loss: 0.7920 2022/08/30 14:56:03 - mmengine - INFO - Epoch(train) [675][35/63] lr: 3.3290e-03 eta: 11:38:53 time: 0.8271 data_time: 0.0207 memory: 16201 loss_prob: 0.4075 loss_thr: 0.2871 loss_db: 0.0717 loss: 0.7663 2022/08/30 14:56:07 - mmengine - INFO - Epoch(train) [675][40/63] lr: 3.3290e-03 eta: 11:38:37 time: 0.8250 data_time: 0.0238 memory: 16201 loss_prob: 0.3688 loss_thr: 0.2781 loss_db: 0.0681 loss: 0.7151 2022/08/30 14:56:10 - mmengine - INFO - Epoch(train) [675][45/63] lr: 3.3290e-03 eta: 11:38:37 time: 0.7772 data_time: 0.0213 memory: 16201 loss_prob: 0.3849 loss_thr: 0.2812 loss_db: 0.0684 loss: 0.7346 2022/08/30 14:56:14 - mmengine - INFO - Epoch(train) [675][50/63] lr: 3.3290e-03 eta: 11:38:20 time: 0.7929 data_time: 0.0258 memory: 16201 loss_prob: 0.4564 loss_thr: 0.3148 loss_db: 0.0781 loss: 0.8493 2022/08/30 14:56:19 - mmengine - INFO - Epoch(train) [675][55/63] lr: 3.3290e-03 eta: 11:38:20 time: 0.8581 data_time: 0.0227 memory: 16201 loss_prob: 0.5015 loss_thr: 0.3353 loss_db: 0.0859 loss: 0.9226 2022/08/30 14:56:23 - mmengine - INFO - Epoch(train) [675][60/63] lr: 3.3290e-03 eta: 11:38:04 time: 0.8720 data_time: 0.0224 memory: 16201 loss_prob: 0.4995 loss_thr: 0.3246 loss_db: 0.0836 loss: 0.9077 2022/08/30 14:56:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:56:31 - mmengine - INFO - Epoch(train) [676][5/63] lr: 3.3233e-03 eta: 11:38:04 time: 0.9716 data_time: 0.1967 memory: 16201 loss_prob: 0.4460 loss_thr: 0.3178 loss_db: 0.0791 loss: 0.8429 2022/08/30 14:56:35 - mmengine - INFO - Epoch(train) [676][10/63] lr: 3.3233e-03 eta: 11:37:43 time: 0.9876 data_time: 0.2041 memory: 16201 loss_prob: 0.4827 loss_thr: 0.3320 loss_db: 0.0848 loss: 0.8995 2022/08/30 14:56:40 - mmengine - INFO - Epoch(train) [676][15/63] lr: 3.3233e-03 eta: 11:37:43 time: 0.8504 data_time: 0.0220 memory: 16201 loss_prob: 0.4942 loss_thr: 0.3342 loss_db: 0.0858 loss: 0.9142 2022/08/30 14:56:44 - mmengine - INFO - Epoch(train) [676][20/63] lr: 3.3233e-03 eta: 11:37:27 time: 0.8395 data_time: 0.0188 memory: 16201 loss_prob: 0.4805 loss_thr: 0.3323 loss_db: 0.0829 loss: 0.8956 2022/08/30 14:56:48 - mmengine - INFO - Epoch(train) [676][25/63] lr: 3.3233e-03 eta: 11:37:27 time: 0.8220 data_time: 0.0302 memory: 16201 loss_prob: 0.4405 loss_thr: 0.3069 loss_db: 0.0756 loss: 0.8230 2022/08/30 14:56:52 - mmengine - INFO - Epoch(train) [676][30/63] lr: 3.3233e-03 eta: 11:37:11 time: 0.8326 data_time: 0.0225 memory: 16201 loss_prob: 0.3974 loss_thr: 0.2780 loss_db: 0.0692 loss: 0.7445 2022/08/30 14:56:56 - mmengine - INFO - Epoch(train) [676][35/63] lr: 3.3233e-03 eta: 11:37:11 time: 0.8432 data_time: 0.0177 memory: 16201 loss_prob: 0.4022 loss_thr: 0.2853 loss_db: 0.0731 loss: 0.7606 2022/08/30 14:57:00 - mmengine - INFO - Epoch(train) [676][40/63] lr: 3.3233e-03 eta: 11:36:55 time: 0.8403 data_time: 0.0277 memory: 16201 loss_prob: 0.5107 loss_thr: 0.3207 loss_db: 0.0865 loss: 0.9178 2022/08/30 14:57:05 - mmengine - INFO - Epoch(train) [676][45/63] lr: 3.3233e-03 eta: 11:36:55 time: 0.8219 data_time: 0.0252 memory: 16201 loss_prob: 0.5465 loss_thr: 0.3429 loss_db: 0.0905 loss: 0.9799 2022/08/30 14:57:09 - mmengine - INFO - Epoch(train) [676][50/63] lr: 3.3233e-03 eta: 11:36:39 time: 0.8144 data_time: 0.0231 memory: 16201 loss_prob: 0.5076 loss_thr: 0.3514 loss_db: 0.0853 loss: 0.9444 2022/08/30 14:57:13 - mmengine - INFO - Epoch(train) [676][55/63] lr: 3.3233e-03 eta: 11:36:39 time: 0.8088 data_time: 0.0226 memory: 16201 loss_prob: 0.4716 loss_thr: 0.3339 loss_db: 0.0799 loss: 0.8854 2022/08/30 14:57:18 - mmengine - INFO - Epoch(train) [676][60/63] lr: 3.3233e-03 eta: 11:36:23 time: 0.9215 data_time: 0.0223 memory: 16201 loss_prob: 0.5241 loss_thr: 0.3401 loss_db: 0.0866 loss: 0.9507 2022/08/30 14:57:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:57:26 - mmengine - INFO - Epoch(train) [677][5/63] lr: 3.3176e-03 eta: 11:36:23 time: 1.0753 data_time: 0.2053 memory: 16201 loss_prob: 0.5300 loss_thr: 0.3388 loss_db: 0.0891 loss: 0.9579 2022/08/30 14:57:30 - mmengine - INFO - Epoch(train) [677][10/63] lr: 3.3176e-03 eta: 11:36:02 time: 1.0111 data_time: 0.2097 memory: 16201 loss_prob: 0.4583 loss_thr: 0.3177 loss_db: 0.0821 loss: 0.8581 2022/08/30 14:57:34 - mmengine - INFO - Epoch(train) [677][15/63] lr: 3.3176e-03 eta: 11:36:02 time: 0.8490 data_time: 0.0241 memory: 16201 loss_prob: 0.4881 loss_thr: 0.3334 loss_db: 0.0857 loss: 0.9072 2022/08/30 14:57:39 - mmengine - INFO - Epoch(train) [677][20/63] lr: 3.3176e-03 eta: 11:35:47 time: 0.9410 data_time: 0.0315 memory: 16201 loss_prob: 0.4667 loss_thr: 0.3299 loss_db: 0.0816 loss: 0.8782 2022/08/30 14:57:44 - mmengine - INFO - Epoch(train) [677][25/63] lr: 3.3176e-03 eta: 11:35:47 time: 0.9173 data_time: 0.0292 memory: 16201 loss_prob: 0.3637 loss_thr: 0.2812 loss_db: 0.0649 loss: 0.7098 2022/08/30 14:57:48 - mmengine - INFO - Epoch(train) [677][30/63] lr: 3.3176e-03 eta: 11:35:31 time: 0.8285 data_time: 0.0241 memory: 16201 loss_prob: 0.3925 loss_thr: 0.2902 loss_db: 0.0692 loss: 0.7520 2022/08/30 14:57:52 - mmengine - INFO - Epoch(train) [677][35/63] lr: 3.3176e-03 eta: 11:35:31 time: 0.8353 data_time: 0.0283 memory: 16201 loss_prob: 0.4670 loss_thr: 0.3226 loss_db: 0.0806 loss: 0.8703 2022/08/30 14:57:56 - mmengine - INFO - Epoch(train) [677][40/63] lr: 3.3176e-03 eta: 11:35:15 time: 0.8262 data_time: 0.0265 memory: 16201 loss_prob: 0.4517 loss_thr: 0.3168 loss_db: 0.0793 loss: 0.8479 2022/08/30 14:58:01 - mmengine - INFO - Epoch(train) [677][45/63] lr: 3.3176e-03 eta: 11:35:15 time: 0.9008 data_time: 0.0287 memory: 16201 loss_prob: 0.4131 loss_thr: 0.2964 loss_db: 0.0731 loss: 0.7825 2022/08/30 14:58:05 - mmengine - INFO - Epoch(train) [677][50/63] lr: 3.3176e-03 eta: 11:34:59 time: 0.8875 data_time: 0.0227 memory: 16201 loss_prob: 0.4348 loss_thr: 0.3080 loss_db: 0.0758 loss: 0.8186 2022/08/30 14:58:09 - mmengine - INFO - Epoch(train) [677][55/63] lr: 3.3176e-03 eta: 11:34:59 time: 0.8038 data_time: 0.0212 memory: 16201 loss_prob: 0.4918 loss_thr: 0.3344 loss_db: 0.0862 loss: 0.9124 2022/08/30 14:58:13 - mmengine - INFO - Epoch(train) [677][60/63] lr: 3.3176e-03 eta: 11:34:43 time: 0.8139 data_time: 0.0247 memory: 16201 loss_prob: 0.5020 loss_thr: 0.3355 loss_db: 0.0869 loss: 0.9245 2022/08/30 14:58:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 14:58:21 - mmengine - INFO - Epoch(train) [678][5/63] lr: 3.3119e-03 eta: 11:34:43 time: 0.9704 data_time: 0.1914 memory: 16201 loss_prob: 0.4444 loss_thr: 0.3103 loss_db: 0.0779 loss: 0.8326 2022/08/30 14:58:25 - mmengine - INFO - Epoch(train) [678][10/63] lr: 3.3119e-03 eta: 11:34:22 time: 1.0052 data_time: 0.2057 memory: 16201 loss_prob: 0.4671 loss_thr: 0.3271 loss_db: 0.0825 loss: 0.8767 2022/08/30 14:58:29 - mmengine - INFO - Epoch(train) [678][15/63] lr: 3.3119e-03 eta: 11:34:22 time: 0.8125 data_time: 0.0319 memory: 16201 loss_prob: 0.4986 loss_thr: 0.3382 loss_db: 0.0876 loss: 0.9244 2022/08/30 14:58:34 - mmengine - INFO - Epoch(train) [678][20/63] lr: 3.3119e-03 eta: 11:34:06 time: 0.8391 data_time: 0.0248 memory: 16201 loss_prob: 0.4699 loss_thr: 0.3198 loss_db: 0.0818 loss: 0.8715 2022/08/30 14:58:52 - mmengine - INFO - Epoch(train) [678][25/63] lr: 3.3119e-03 eta: 11:34:06 time: 2.3110 data_time: 0.0435 memory: 16201 loss_prob: 0.4493 loss_thr: 0.3127 loss_db: 0.0788 loss: 0.8408 2022/08/30 14:59:15 - mmengine - INFO - Epoch(train) [678][30/63] lr: 3.3119e-03 eta: 11:34:15 time: 4.1610 data_time: 0.0789 memory: 16201 loss_prob: 0.4646 loss_thr: 0.3218 loss_db: 0.0829 loss: 0.8693 2022/08/30 14:59:40 - mmengine - INFO - Epoch(train) [678][35/63] lr: 3.3119e-03 eta: 11:34:15 time: 4.7857 data_time: 0.1034 memory: 16201 loss_prob: 0.4600 loss_thr: 0.3229 loss_db: 0.0799 loss: 0.8629 2022/08/30 15:00:05 - mmengine - INFO - Epoch(train) [678][40/63] lr: 3.3119e-03 eta: 11:34:31 time: 4.9472 data_time: 0.1030 memory: 16201 loss_prob: 0.4385 loss_thr: 0.3168 loss_db: 0.0771 loss: 0.8325 2022/08/30 15:00:28 - mmengine - INFO - Epoch(train) [678][45/63] lr: 3.3119e-03 eta: 11:34:31 time: 4.7833 data_time: 0.1232 memory: 16201 loss_prob: 0.4843 loss_thr: 0.3378 loss_db: 0.0850 loss: 0.9071 2022/08/30 15:00:50 - mmengine - INFO - Epoch(train) [678][50/63] lr: 3.3119e-03 eta: 11:34:44 time: 4.5526 data_time: 0.1154 memory: 16201 loss_prob: 0.4545 loss_thr: 0.3276 loss_db: 0.0792 loss: 0.8613 2022/08/30 15:01:13 - mmengine - INFO - Epoch(train) [678][55/63] lr: 3.3119e-03 eta: 11:34:44 time: 4.5239 data_time: 0.1120 memory: 16201 loss_prob: 0.3909 loss_thr: 0.2974 loss_db: 0.0700 loss: 0.7583 2022/08/30 15:01:38 - mmengine - INFO - Epoch(train) [678][60/63] lr: 3.3119e-03 eta: 11:34:58 time: 4.8147 data_time: 0.1208 memory: 16201 loss_prob: 0.3898 loss_thr: 0.2937 loss_db: 0.0688 loss: 0.7523 2022/08/30 15:01:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:02:18 - mmengine - INFO - Epoch(train) [679][5/63] lr: 3.3061e-03 eta: 11:34:58 time: 4.9492 data_time: 0.5220 memory: 16201 loss_prob: 0.4387 loss_thr: 0.3098 loss_db: 0.0756 loss: 0.8240 2022/08/30 15:02:41 - mmengine - INFO - Epoch(train) [679][10/63] lr: 3.3061e-03 eta: 11:35:08 time: 4.9706 data_time: 0.5231 memory: 16201 loss_prob: 0.4654 loss_thr: 0.3213 loss_db: 0.0815 loss: 0.8682 2022/08/30 15:03:03 - mmengine - INFO - Epoch(train) [679][15/63] lr: 3.3061e-03 eta: 11:35:08 time: 4.5059 data_time: 0.0957 memory: 16201 loss_prob: 0.4223 loss_thr: 0.2982 loss_db: 0.0759 loss: 0.7964 2022/08/30 15:03:27 - mmengine - INFO - Epoch(train) [679][20/63] lr: 3.3061e-03 eta: 11:35:21 time: 4.6367 data_time: 0.0881 memory: 16201 loss_prob: 0.4005 loss_thr: 0.2855 loss_db: 0.0712 loss: 0.7572 2022/08/30 15:03:49 - mmengine - INFO - Epoch(train) [679][25/63] lr: 3.3061e-03 eta: 11:35:21 time: 4.6128 data_time: 0.1020 memory: 16201 loss_prob: 0.3812 loss_thr: 0.2832 loss_db: 0.0671 loss: 0.7315 2022/08/30 15:04:13 - mmengine - INFO - Epoch(train) [679][30/63] lr: 3.3061e-03 eta: 11:35:34 time: 4.6544 data_time: 0.1658 memory: 16201 loss_prob: 0.3757 loss_thr: 0.2901 loss_db: 0.0673 loss: 0.7332 2022/08/30 15:04:38 - mmengine - INFO - Epoch(train) [679][35/63] lr: 3.3061e-03 eta: 11:35:34 time: 4.9093 data_time: 0.2054 memory: 16201 loss_prob: 0.4338 loss_thr: 0.3199 loss_db: 0.0776 loss: 0.8313 2022/08/30 15:05:04 - mmengine - INFO - Epoch(train) [679][40/63] lr: 3.3061e-03 eta: 11:35:50 time: 5.0089 data_time: 0.1417 memory: 16201 loss_prob: 0.4319 loss_thr: 0.3128 loss_db: 0.0762 loss: 0.8210 2022/08/30 15:05:28 - mmengine - INFO - Epoch(train) [679][45/63] lr: 3.3061e-03 eta: 11:35:50 time: 4.9262 data_time: 0.1427 memory: 16201 loss_prob: 0.4405 loss_thr: 0.3007 loss_db: 0.0752 loss: 0.8164 2022/08/30 15:05:53 - mmengine - INFO - Epoch(train) [679][50/63] lr: 3.3061e-03 eta: 11:36:06 time: 4.9417 data_time: 0.1734 memory: 16201 loss_prob: 0.4684 loss_thr: 0.3221 loss_db: 0.0794 loss: 0.8699 2022/08/30 15:06:18 - mmengine - INFO - Epoch(train) [679][55/63] lr: 3.3061e-03 eta: 11:36:06 time: 5.0306 data_time: 0.1213 memory: 16201 loss_prob: 0.4357 loss_thr: 0.3134 loss_db: 0.0760 loss: 0.8252 2022/08/30 15:06:41 - mmengine - INFO - Epoch(train) [679][60/63] lr: 3.3061e-03 eta: 11:36:20 time: 4.7887 data_time: 0.1202 memory: 16201 loss_prob: 0.4462 loss_thr: 0.3006 loss_db: 0.0776 loss: 0.8244 2022/08/30 15:06:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:06:58 - mmengine - INFO - Epoch(train) [680][5/63] lr: 3.3004e-03 eta: 11:36:20 time: 2.6074 data_time: 0.3334 memory: 16201 loss_prob: 0.4418 loss_thr: 0.3110 loss_db: 0.0771 loss: 0.8299 2022/08/30 15:07:02 - mmengine - INFO - Epoch(train) [680][10/63] lr: 3.3004e-03 eta: 11:36:02 time: 1.4313 data_time: 0.3031 memory: 16201 loss_prob: 0.3973 loss_thr: 0.2880 loss_db: 0.0715 loss: 0.7569 2022/08/30 15:07:06 - mmengine - INFO - Epoch(train) [680][15/63] lr: 3.3004e-03 eta: 11:36:02 time: 0.7996 data_time: 0.0267 memory: 16201 loss_prob: 0.4095 loss_thr: 0.3059 loss_db: 0.0724 loss: 0.7878 2022/08/30 15:07:10 - mmengine - INFO - Epoch(train) [680][20/63] lr: 3.3004e-03 eta: 11:35:45 time: 0.7848 data_time: 0.0268 memory: 16201 loss_prob: 0.4397 loss_thr: 0.3225 loss_db: 0.0763 loss: 0.8385 2022/08/30 15:07:14 - mmengine - INFO - Epoch(train) [680][25/63] lr: 3.3004e-03 eta: 11:35:45 time: 0.7807 data_time: 0.0293 memory: 16201 loss_prob: 0.4029 loss_thr: 0.2905 loss_db: 0.0720 loss: 0.7655 2022/08/30 15:07:18 - mmengine - INFO - Epoch(train) [680][30/63] lr: 3.3004e-03 eta: 11:35:29 time: 0.8072 data_time: 0.0220 memory: 16201 loss_prob: 0.4418 loss_thr: 0.3042 loss_db: 0.0787 loss: 0.8247 2022/08/30 15:07:22 - mmengine - INFO - Epoch(train) [680][35/63] lr: 3.3004e-03 eta: 11:35:29 time: 0.8224 data_time: 0.0214 memory: 16201 loss_prob: 0.4263 loss_thr: 0.3020 loss_db: 0.0749 loss: 0.8032 2022/08/30 15:07:26 - mmengine - INFO - Epoch(train) [680][40/63] lr: 3.3004e-03 eta: 11:35:13 time: 0.8020 data_time: 0.0247 memory: 16201 loss_prob: 0.3922 loss_thr: 0.2857 loss_db: 0.0679 loss: 0.7458 2022/08/30 15:07:31 - mmengine - INFO - Epoch(train) [680][45/63] lr: 3.3004e-03 eta: 11:35:13 time: 0.8383 data_time: 0.0309 memory: 16201 loss_prob: 0.4803 loss_thr: 0.3173 loss_db: 0.0831 loss: 0.8807 2022/08/30 15:07:35 - mmengine - INFO - Epoch(train) [680][50/63] lr: 3.3004e-03 eta: 11:34:57 time: 0.8583 data_time: 0.0319 memory: 16201 loss_prob: 0.4869 loss_thr: 0.3201 loss_db: 0.0851 loss: 0.8922 2022/08/30 15:07:39 - mmengine - INFO - Epoch(train) [680][55/63] lr: 3.3004e-03 eta: 11:34:57 time: 0.8481 data_time: 0.0287 memory: 16201 loss_prob: 0.4574 loss_thr: 0.3189 loss_db: 0.0795 loss: 0.8557 2022/08/30 15:07:43 - mmengine - INFO - Epoch(train) [680][60/63] lr: 3.3004e-03 eta: 11:34:41 time: 0.8473 data_time: 0.0269 memory: 16201 loss_prob: 0.4692 loss_thr: 0.3229 loss_db: 0.0816 loss: 0.8737 2022/08/30 15:08:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:08:10 - mmengine - INFO - Saving checkpoint at 680 epochs 2022/08/30 15:08:32 - mmengine - INFO - Epoch(val) [680][5/32] eta: 11:34:41 time: 1.4007 data_time: 0.4649 memory: 16201 2022/08/30 15:08:35 - mmengine - INFO - Epoch(val) [680][10/32] eta: 0:00:32 time: 1.4761 data_time: 0.5022 memory: 15734 2022/08/30 15:08:38 - mmengine - INFO - Epoch(val) [680][15/32] eta: 0:00:32 time: 0.6377 data_time: 0.0527 memory: 15734 2022/08/30 15:08:42 - mmengine - INFO - Epoch(val) [680][20/32] eta: 0:00:07 time: 0.6494 data_time: 0.0583 memory: 15734 2022/08/30 15:08:45 - mmengine - INFO - Epoch(val) [680][25/32] eta: 0:00:07 time: 0.6594 data_time: 0.0662 memory: 15734 2022/08/30 15:08:48 - mmengine - INFO - Epoch(val) [680][30/32] eta: 0:00:01 time: 0.6193 data_time: 0.0291 memory: 15734 2022/08/30 15:08:49 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 15:08:49 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8455, precision: 0.7864, hmean: 0.8148 2022/08/30 15:08:49 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8455, precision: 0.8378, hmean: 0.8416 2022/08/30 15:08:49 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8450, precision: 0.8603, hmean: 0.8526 2022/08/30 15:08:49 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8397, precision: 0.8817, hmean: 0.8602 2022/08/30 15:08:49 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8286, precision: 0.8959, hmean: 0.8609 2022/08/30 15:08:49 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7718, precision: 0.9277, hmean: 0.8426 2022/08/30 15:08:49 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1887, precision: 0.9727, hmean: 0.3161 2022/08/30 15:08:49 - mmengine - INFO - Epoch(val) [680][32/32] icdar/precision: 0.8959 icdar/recall: 0.8286 icdar/hmean: 0.8609 2022/08/30 15:08:56 - mmengine - INFO - Epoch(train) [681][5/63] lr: 3.2947e-03 eta: 0:00:01 time: 3.4824 data_time: 0.2563 memory: 16201 loss_prob: 0.4382 loss_thr: 0.2969 loss_db: 0.0787 loss: 0.8138 2022/08/30 15:09:01 - mmengine - INFO - Epoch(train) [681][10/63] lr: 3.2947e-03 eta: 11:34:21 time: 1.1870 data_time: 0.2318 memory: 16201 loss_prob: 0.4659 loss_thr: 0.3132 loss_db: 0.0812 loss: 0.8603 2022/08/30 15:09:06 - mmengine - INFO - Epoch(train) [681][15/63] lr: 3.2947e-03 eta: 11:34:21 time: 0.9797 data_time: 0.0317 memory: 16201 loss_prob: 0.4299 loss_thr: 0.3041 loss_db: 0.0748 loss: 0.8089 2022/08/30 15:09:10 - mmengine - INFO - Epoch(train) [681][20/63] lr: 3.2947e-03 eta: 11:34:05 time: 0.9091 data_time: 0.0298 memory: 16201 loss_prob: 0.4346 loss_thr: 0.3126 loss_db: 0.0770 loss: 0.8241 2022/08/30 15:09:14 - mmengine - INFO - Epoch(train) [681][25/63] lr: 3.2947e-03 eta: 11:34:05 time: 0.8106 data_time: 0.0261 memory: 16201 loss_prob: 0.4403 loss_thr: 0.3176 loss_db: 0.0771 loss: 0.8351 2022/08/30 15:09:18 - mmengine - INFO - Epoch(train) [681][30/63] lr: 3.2947e-03 eta: 11:33:49 time: 0.8616 data_time: 0.0273 memory: 16201 loss_prob: 0.4257 loss_thr: 0.3003 loss_db: 0.0754 loss: 0.8013 2022/08/30 15:09:23 - mmengine - INFO - Epoch(train) [681][35/63] lr: 3.2947e-03 eta: 11:33:49 time: 0.8759 data_time: 0.0259 memory: 16201 loss_prob: 0.4270 loss_thr: 0.3029 loss_db: 0.0749 loss: 0.8049 2022/08/30 15:09:27 - mmengine - INFO - Epoch(train) [681][40/63] lr: 3.2947e-03 eta: 11:33:33 time: 0.8140 data_time: 0.0234 memory: 16201 loss_prob: 0.4491 loss_thr: 0.2960 loss_db: 0.0775 loss: 0.8226 2022/08/30 15:09:30 - mmengine - INFO - Epoch(train) [681][45/63] lr: 3.2947e-03 eta: 11:33:33 time: 0.7868 data_time: 0.0251 memory: 16201 loss_prob: 0.4652 loss_thr: 0.3047 loss_db: 0.0813 loss: 0.8512 2022/08/30 15:09:34 - mmengine - INFO - Epoch(train) [681][50/63] lr: 3.2947e-03 eta: 11:33:17 time: 0.7910 data_time: 0.0280 memory: 16201 loss_prob: 0.4722 loss_thr: 0.3321 loss_db: 0.0828 loss: 0.8871 2022/08/30 15:09:39 - mmengine - INFO - Epoch(train) [681][55/63] lr: 3.2947e-03 eta: 11:33:17 time: 0.8454 data_time: 0.0284 memory: 16201 loss_prob: 0.4563 loss_thr: 0.3114 loss_db: 0.0796 loss: 0.8473 2022/08/30 15:09:43 - mmengine - INFO - Epoch(train) [681][60/63] lr: 3.2947e-03 eta: 11:33:01 time: 0.8627 data_time: 0.0322 memory: 16201 loss_prob: 0.3831 loss_thr: 0.2836 loss_db: 0.0666 loss: 0.7332 2022/08/30 15:09:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:09:51 - mmengine - INFO - Epoch(train) [682][5/63] lr: 3.2890e-03 eta: 11:33:01 time: 0.9189 data_time: 0.1618 memory: 16201 loss_prob: 0.4727 loss_thr: 0.3211 loss_db: 0.0846 loss: 0.8783 2022/08/30 15:09:55 - mmengine - INFO - Epoch(train) [682][10/63] lr: 3.2890e-03 eta: 11:32:39 time: 0.9570 data_time: 0.1685 memory: 16201 loss_prob: 0.4932 loss_thr: 0.3501 loss_db: 0.0865 loss: 0.9298 2022/08/30 15:10:00 - mmengine - INFO - Epoch(train) [682][15/63] lr: 3.2890e-03 eta: 11:32:39 time: 0.8894 data_time: 0.0259 memory: 16201 loss_prob: 0.4974 loss_thr: 0.3466 loss_db: 0.0872 loss: 0.9312 2022/08/30 15:10:04 - mmengine - INFO - Epoch(train) [682][20/63] lr: 3.2890e-03 eta: 11:32:24 time: 0.9171 data_time: 0.0290 memory: 16201 loss_prob: 0.4732 loss_thr: 0.3224 loss_db: 0.0830 loss: 0.8785 2022/08/30 15:10:08 - mmengine - INFO - Epoch(train) [682][25/63] lr: 3.2890e-03 eta: 11:32:24 time: 0.8446 data_time: 0.0276 memory: 16201 loss_prob: 0.4775 loss_thr: 0.3257 loss_db: 0.0823 loss: 0.8854 2022/08/30 15:10:12 - mmengine - INFO - Epoch(train) [682][30/63] lr: 3.2890e-03 eta: 11:32:07 time: 0.8091 data_time: 0.0224 memory: 16201 loss_prob: 0.4672 loss_thr: 0.3293 loss_db: 0.0807 loss: 0.8773 2022/08/30 15:10:16 - mmengine - INFO - Epoch(train) [682][35/63] lr: 3.2890e-03 eta: 11:32:07 time: 0.7958 data_time: 0.0272 memory: 16201 loss_prob: 0.4822 loss_thr: 0.3400 loss_db: 0.0844 loss: 0.9066 2022/08/30 15:10:21 - mmengine - INFO - Epoch(train) [682][40/63] lr: 3.2890e-03 eta: 11:31:51 time: 0.8610 data_time: 0.0257 memory: 16201 loss_prob: 0.5135 loss_thr: 0.3611 loss_db: 0.0902 loss: 0.9648 2022/08/30 15:10:25 - mmengine - INFO - Epoch(train) [682][45/63] lr: 3.2890e-03 eta: 11:31:51 time: 0.8630 data_time: 0.0265 memory: 16201 loss_prob: 0.5349 loss_thr: 0.3815 loss_db: 0.0944 loss: 1.0107 2022/08/30 15:10:29 - mmengine - INFO - Epoch(train) [682][50/63] lr: 3.2890e-03 eta: 11:31:35 time: 0.8042 data_time: 0.0250 memory: 16201 loss_prob: 0.4788 loss_thr: 0.3452 loss_db: 0.0849 loss: 0.9088 2022/08/30 15:10:33 - mmengine - INFO - Epoch(train) [682][55/63] lr: 3.2890e-03 eta: 11:31:35 time: 0.8198 data_time: 0.0247 memory: 16201 loss_prob: 0.4142 loss_thr: 0.2991 loss_db: 0.0742 loss: 0.7876 2022/08/30 15:10:37 - mmengine - INFO - Epoch(train) [682][60/63] lr: 3.2890e-03 eta: 11:31:19 time: 0.8260 data_time: 0.0264 memory: 16201 loss_prob: 0.4250 loss_thr: 0.2970 loss_db: 0.0746 loss: 0.7967 2022/08/30 15:10:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:10:46 - mmengine - INFO - Epoch(train) [683][5/63] lr: 3.2833e-03 eta: 11:31:19 time: 1.0550 data_time: 0.2133 memory: 16201 loss_prob: 0.4329 loss_thr: 0.3093 loss_db: 0.0752 loss: 0.8174 2022/08/30 15:10:50 - mmengine - INFO - Epoch(train) [683][10/63] lr: 3.2833e-03 eta: 11:30:58 time: 1.0609 data_time: 0.2220 memory: 16201 loss_prob: 0.4782 loss_thr: 0.3370 loss_db: 0.0837 loss: 0.8989 2022/08/30 15:10:54 - mmengine - INFO - Epoch(train) [683][15/63] lr: 3.2833e-03 eta: 11:30:58 time: 0.8306 data_time: 0.0233 memory: 16201 loss_prob: 0.4453 loss_thr: 0.3229 loss_db: 0.0791 loss: 0.8472 2022/08/30 15:10:59 - mmengine - INFO - Epoch(train) [683][20/63] lr: 3.2833e-03 eta: 11:30:42 time: 0.8671 data_time: 0.0180 memory: 16201 loss_prob: 0.4362 loss_thr: 0.3008 loss_db: 0.0824 loss: 0.8195 2022/08/30 15:11:03 - mmengine - INFO - Epoch(train) [683][25/63] lr: 3.2833e-03 eta: 11:30:42 time: 0.8881 data_time: 0.0297 memory: 16201 loss_prob: 0.4605 loss_thr: 0.3035 loss_db: 0.0853 loss: 0.8493 2022/08/30 15:11:07 - mmengine - INFO - Epoch(train) [683][30/63] lr: 3.2833e-03 eta: 11:30:26 time: 0.8204 data_time: 0.0256 memory: 16201 loss_prob: 0.4511 loss_thr: 0.3169 loss_db: 0.0781 loss: 0.8461 2022/08/30 15:11:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:11:11 - mmengine - INFO - Epoch(train) [683][35/63] lr: 3.2833e-03 eta: 11:30:26 time: 0.8026 data_time: 0.0208 memory: 16201 loss_prob: 0.5138 loss_thr: 0.3580 loss_db: 0.0879 loss: 0.9598 2022/08/30 15:11:15 - mmengine - INFO - Epoch(train) [683][40/63] lr: 3.2833e-03 eta: 11:30:10 time: 0.8254 data_time: 0.0227 memory: 16201 loss_prob: 0.5574 loss_thr: 0.3632 loss_db: 0.0943 loss: 1.0149 2022/08/30 15:11:19 - mmengine - INFO - Epoch(train) [683][45/63] lr: 3.2833e-03 eta: 11:30:10 time: 0.8322 data_time: 0.0248 memory: 16201 loss_prob: 0.5149 loss_thr: 0.3195 loss_db: 0.0856 loss: 0.9200 2022/08/30 15:11:23 - mmengine - INFO - Epoch(train) [683][50/63] lr: 3.2833e-03 eta: 11:29:54 time: 0.8100 data_time: 0.0273 memory: 16201 loss_prob: 0.4813 loss_thr: 0.3215 loss_db: 0.0815 loss: 0.8844 2022/08/30 15:11:27 - mmengine - INFO - Epoch(train) [683][55/63] lr: 3.2833e-03 eta: 11:29:54 time: 0.7849 data_time: 0.0224 memory: 16201 loss_prob: 0.4367 loss_thr: 0.3189 loss_db: 0.0756 loss: 0.8313 2022/08/30 15:11:31 - mmengine - INFO - Epoch(train) [683][60/63] lr: 3.2833e-03 eta: 11:29:38 time: 0.8054 data_time: 0.0217 memory: 16201 loss_prob: 0.4096 loss_thr: 0.2869 loss_db: 0.0717 loss: 0.7681 2022/08/30 15:11:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:11:39 - mmengine - INFO - Epoch(train) [684][5/63] lr: 3.2776e-03 eta: 11:29:38 time: 0.8852 data_time: 0.1510 memory: 16201 loss_prob: 0.4063 loss_thr: 0.3021 loss_db: 0.0735 loss: 0.7819 2022/08/30 15:11:43 - mmengine - INFO - Epoch(train) [684][10/63] lr: 3.2776e-03 eta: 11:29:16 time: 0.9355 data_time: 0.1590 memory: 16201 loss_prob: 0.4785 loss_thr: 0.3235 loss_db: 0.0816 loss: 0.8836 2022/08/30 15:11:47 - mmengine - INFO - Epoch(train) [684][15/63] lr: 3.2776e-03 eta: 11:29:16 time: 0.8031 data_time: 0.0234 memory: 16201 loss_prob: 0.4796 loss_thr: 0.3220 loss_db: 0.0809 loss: 0.8825 2022/08/30 15:11:51 - mmengine - INFO - Epoch(train) [684][20/63] lr: 3.2776e-03 eta: 11:29:00 time: 0.8699 data_time: 0.0356 memory: 16201 loss_prob: 0.4905 loss_thr: 0.3404 loss_db: 0.0866 loss: 0.9175 2022/08/30 15:11:55 - mmengine - INFO - Epoch(train) [684][25/63] lr: 3.2776e-03 eta: 11:29:00 time: 0.8816 data_time: 0.0414 memory: 16201 loss_prob: 0.4844 loss_thr: 0.3455 loss_db: 0.0844 loss: 0.9143 2022/08/30 15:11:59 - mmengine - INFO - Epoch(train) [684][30/63] lr: 3.2776e-03 eta: 11:28:44 time: 0.8155 data_time: 0.0233 memory: 16201 loss_prob: 0.4478 loss_thr: 0.3228 loss_db: 0.0771 loss: 0.8477 2022/08/30 15:12:04 - mmengine - INFO - Epoch(train) [684][35/63] lr: 3.2776e-03 eta: 11:28:44 time: 0.8335 data_time: 0.0220 memory: 16201 loss_prob: 0.4070 loss_thr: 0.2973 loss_db: 0.0720 loss: 0.7763 2022/08/30 15:12:08 - mmengine - INFO - Epoch(train) [684][40/63] lr: 3.2776e-03 eta: 11:28:28 time: 0.8390 data_time: 0.0252 memory: 16201 loss_prob: 0.4169 loss_thr: 0.2930 loss_db: 0.0740 loss: 0.7840 2022/08/30 15:12:12 - mmengine - INFO - Epoch(train) [684][45/63] lr: 3.2776e-03 eta: 11:28:28 time: 0.8279 data_time: 0.0275 memory: 16201 loss_prob: 0.4462 loss_thr: 0.3102 loss_db: 0.0793 loss: 0.8357 2022/08/30 15:12:16 - mmengine - INFO - Epoch(train) [684][50/63] lr: 3.2776e-03 eta: 11:28:12 time: 0.8185 data_time: 0.0249 memory: 16201 loss_prob: 0.4474 loss_thr: 0.3188 loss_db: 0.0792 loss: 0.8454 2022/08/30 15:12:20 - mmengine - INFO - Epoch(train) [684][55/63] lr: 3.2776e-03 eta: 11:28:12 time: 0.8329 data_time: 0.0218 memory: 16201 loss_prob: 0.4702 loss_thr: 0.3200 loss_db: 0.0821 loss: 0.8723 2022/08/30 15:12:24 - mmengine - INFO - Epoch(train) [684][60/63] lr: 3.2776e-03 eta: 11:27:56 time: 0.8422 data_time: 0.0309 memory: 16201 loss_prob: 0.4255 loss_thr: 0.2947 loss_db: 0.0750 loss: 0.7952 2022/08/30 15:12:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:12:33 - mmengine - INFO - Epoch(train) [685][5/63] lr: 3.2719e-03 eta: 11:27:56 time: 0.9878 data_time: 0.2056 memory: 16201 loss_prob: 0.4168 loss_thr: 0.2873 loss_db: 0.0751 loss: 0.7791 2022/08/30 15:12:37 - mmengine - INFO - Epoch(train) [685][10/63] lr: 3.2719e-03 eta: 11:27:35 time: 1.0398 data_time: 0.2188 memory: 16201 loss_prob: 0.4452 loss_thr: 0.3174 loss_db: 0.0785 loss: 0.8411 2022/08/30 15:12:41 - mmengine - INFO - Epoch(train) [685][15/63] lr: 3.2719e-03 eta: 11:27:35 time: 0.8524 data_time: 0.0261 memory: 16201 loss_prob: 0.4489 loss_thr: 0.3214 loss_db: 0.0794 loss: 0.8497 2022/08/30 15:12:45 - mmengine - INFO - Epoch(train) [685][20/63] lr: 3.2719e-03 eta: 11:27:19 time: 0.8348 data_time: 0.0179 memory: 16201 loss_prob: 0.4235 loss_thr: 0.3100 loss_db: 0.0740 loss: 0.8075 2022/08/30 15:12:50 - mmengine - INFO - Epoch(train) [685][25/63] lr: 3.2719e-03 eta: 11:27:19 time: 0.8244 data_time: 0.0322 memory: 16201 loss_prob: 0.4214 loss_thr: 0.3138 loss_db: 0.0745 loss: 0.8098 2022/08/30 15:12:53 - mmengine - INFO - Epoch(train) [685][30/63] lr: 3.2719e-03 eta: 11:27:03 time: 0.8174 data_time: 0.0241 memory: 16201 loss_prob: 0.4473 loss_thr: 0.3245 loss_db: 0.0792 loss: 0.8509 2022/08/30 15:12:58 - mmengine - INFO - Epoch(train) [685][35/63] lr: 3.2719e-03 eta: 11:27:03 time: 0.7996 data_time: 0.0192 memory: 16201 loss_prob: 0.4728 loss_thr: 0.3334 loss_db: 0.0837 loss: 0.8899 2022/08/30 15:13:02 - mmengine - INFO - Epoch(train) [685][40/63] lr: 3.2719e-03 eta: 11:26:47 time: 0.8030 data_time: 0.0295 memory: 16201 loss_prob: 0.4356 loss_thr: 0.3087 loss_db: 0.0781 loss: 0.8224 2022/08/30 15:13:06 - mmengine - INFO - Epoch(train) [685][45/63] lr: 3.2719e-03 eta: 11:26:47 time: 0.7994 data_time: 0.0274 memory: 16201 loss_prob: 0.4254 loss_thr: 0.2966 loss_db: 0.0727 loss: 0.7947 2022/08/30 15:13:10 - mmengine - INFO - Epoch(train) [685][50/63] lr: 3.2719e-03 eta: 11:26:31 time: 0.8214 data_time: 0.0249 memory: 16201 loss_prob: 0.4301 loss_thr: 0.2992 loss_db: 0.0732 loss: 0.8024 2022/08/30 15:13:14 - mmengine - INFO - Epoch(train) [685][55/63] lr: 3.2719e-03 eta: 11:26:31 time: 0.8303 data_time: 0.0251 memory: 16201 loss_prob: 0.4452 loss_thr: 0.3166 loss_db: 0.0792 loss: 0.8410 2022/08/30 15:13:18 - mmengine - INFO - Epoch(train) [685][60/63] lr: 3.2719e-03 eta: 11:26:15 time: 0.8361 data_time: 0.0266 memory: 16201 loss_prob: 0.4773 loss_thr: 0.3216 loss_db: 0.0833 loss: 0.8822 2022/08/30 15:13:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:13:26 - mmengine - INFO - Epoch(train) [686][5/63] lr: 3.2661e-03 eta: 11:26:15 time: 0.9480 data_time: 0.2025 memory: 16201 loss_prob: 0.4588 loss_thr: 0.3208 loss_db: 0.0796 loss: 0.8593 2022/08/30 15:13:30 - mmengine - INFO - Epoch(train) [686][10/63] lr: 3.2661e-03 eta: 11:25:53 time: 1.0300 data_time: 0.2175 memory: 16201 loss_prob: 0.4248 loss_thr: 0.3013 loss_db: 0.0751 loss: 0.8011 2022/08/30 15:13:34 - mmengine - INFO - Epoch(train) [686][15/63] lr: 3.2661e-03 eta: 11:25:53 time: 0.8259 data_time: 0.0234 memory: 16201 loss_prob: 0.4193 loss_thr: 0.3048 loss_db: 0.0741 loss: 0.7981 2022/08/30 15:13:39 - mmengine - INFO - Epoch(train) [686][20/63] lr: 3.2661e-03 eta: 11:25:38 time: 0.8519 data_time: 0.0158 memory: 16201 loss_prob: 0.4681 loss_thr: 0.3326 loss_db: 0.0821 loss: 0.8829 2022/08/30 15:13:43 - mmengine - INFO - Epoch(train) [686][25/63] lr: 3.2661e-03 eta: 11:25:38 time: 0.8918 data_time: 0.0291 memory: 16201 loss_prob: 0.4600 loss_thr: 0.3268 loss_db: 0.0812 loss: 0.8679 2022/08/30 15:13:47 - mmengine - INFO - Epoch(train) [686][30/63] lr: 3.2661e-03 eta: 11:25:22 time: 0.8454 data_time: 0.0274 memory: 16201 loss_prob: 0.4353 loss_thr: 0.3179 loss_db: 0.0782 loss: 0.8315 2022/08/30 15:13:52 - mmengine - INFO - Epoch(train) [686][35/63] lr: 3.2661e-03 eta: 11:25:22 time: 0.8431 data_time: 0.0241 memory: 16201 loss_prob: 0.4582 loss_thr: 0.3218 loss_db: 0.0820 loss: 0.8620 2022/08/30 15:13:56 - mmengine - INFO - Epoch(train) [686][40/63] lr: 3.2661e-03 eta: 11:25:06 time: 0.8354 data_time: 0.0232 memory: 16201 loss_prob: 0.4605 loss_thr: 0.3149 loss_db: 0.0805 loss: 0.8559 2022/08/30 15:14:00 - mmengine - INFO - Epoch(train) [686][45/63] lr: 3.2661e-03 eta: 11:25:06 time: 0.8975 data_time: 0.0240 memory: 16201 loss_prob: 0.4003 loss_thr: 0.2875 loss_db: 0.0718 loss: 0.7597 2022/08/30 15:14:05 - mmengine - INFO - Epoch(train) [686][50/63] lr: 3.2661e-03 eta: 11:24:50 time: 0.9183 data_time: 0.0542 memory: 16201 loss_prob: 0.3668 loss_thr: 0.2765 loss_db: 0.0661 loss: 0.7093 2022/08/30 15:14:09 - mmengine - INFO - Epoch(train) [686][55/63] lr: 3.2661e-03 eta: 11:24:50 time: 0.8506 data_time: 0.0495 memory: 16201 loss_prob: 0.3901 loss_thr: 0.2854 loss_db: 0.0672 loss: 0.7427 2022/08/30 15:14:13 - mmengine - INFO - Epoch(train) [686][60/63] lr: 3.2661e-03 eta: 11:24:34 time: 0.8182 data_time: 0.0209 memory: 16201 loss_prob: 0.4118 loss_thr: 0.2918 loss_db: 0.0705 loss: 0.7742 2022/08/30 15:14:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:14:21 - mmengine - INFO - Epoch(train) [687][5/63] lr: 3.2604e-03 eta: 11:24:34 time: 0.9355 data_time: 0.1591 memory: 16201 loss_prob: 0.4813 loss_thr: 0.3372 loss_db: 0.0840 loss: 0.9025 2022/08/30 15:14:25 - mmengine - INFO - Epoch(train) [687][10/63] lr: 3.2604e-03 eta: 11:24:13 time: 0.9781 data_time: 0.1684 memory: 16201 loss_prob: 0.5300 loss_thr: 0.3443 loss_db: 0.0892 loss: 0.9634 2022/08/30 15:14:29 - mmengine - INFO - Epoch(train) [687][15/63] lr: 3.2604e-03 eta: 11:24:13 time: 0.8457 data_time: 0.0233 memory: 16201 loss_prob: 0.5147 loss_thr: 0.3307 loss_db: 0.0881 loss: 0.9335 2022/08/30 15:14:34 - mmengine - INFO - Epoch(train) [687][20/63] lr: 3.2604e-03 eta: 11:23:57 time: 0.8670 data_time: 0.0260 memory: 16201 loss_prob: 0.4524 loss_thr: 0.3137 loss_db: 0.0810 loss: 0.8472 2022/08/30 15:14:38 - mmengine - INFO - Epoch(train) [687][25/63] lr: 3.2604e-03 eta: 11:23:57 time: 0.8316 data_time: 0.0255 memory: 16201 loss_prob: 0.4100 loss_thr: 0.3025 loss_db: 0.0744 loss: 0.7869 2022/08/30 15:14:42 - mmengine - INFO - Epoch(train) [687][30/63] lr: 3.2604e-03 eta: 11:23:41 time: 0.8424 data_time: 0.0235 memory: 16201 loss_prob: 0.4153 loss_thr: 0.3048 loss_db: 0.0727 loss: 0.7927 2022/08/30 15:14:46 - mmengine - INFO - Epoch(train) [687][35/63] lr: 3.2604e-03 eta: 11:23:41 time: 0.8434 data_time: 0.0239 memory: 16201 loss_prob: 0.4273 loss_thr: 0.3049 loss_db: 0.0748 loss: 0.8070 2022/08/30 15:14:51 - mmengine - INFO - Epoch(train) [687][40/63] lr: 3.2604e-03 eta: 11:23:26 time: 0.8858 data_time: 0.0236 memory: 16201 loss_prob: 0.4340 loss_thr: 0.3113 loss_db: 0.0777 loss: 0.8230 2022/08/30 15:14:55 - mmengine - INFO - Epoch(train) [687][45/63] lr: 3.2604e-03 eta: 11:23:26 time: 0.8704 data_time: 0.0314 memory: 16201 loss_prob: 0.4553 loss_thr: 0.3203 loss_db: 0.0812 loss: 0.8568 2022/08/30 15:14:59 - mmengine - INFO - Epoch(train) [687][50/63] lr: 3.2604e-03 eta: 11:23:10 time: 0.7877 data_time: 0.0245 memory: 16201 loss_prob: 0.4806 loss_thr: 0.3127 loss_db: 0.0815 loss: 0.8748 2022/08/30 15:15:03 - mmengine - INFO - Epoch(train) [687][55/63] lr: 3.2604e-03 eta: 11:23:10 time: 0.7772 data_time: 0.0236 memory: 16201 loss_prob: 0.5287 loss_thr: 0.3406 loss_db: 0.0891 loss: 0.9584 2022/08/30 15:15:07 - mmengine - INFO - Epoch(train) [687][60/63] lr: 3.2604e-03 eta: 11:22:53 time: 0.7892 data_time: 0.0270 memory: 16201 loss_prob: 0.5004 loss_thr: 0.3422 loss_db: 0.0871 loss: 0.9298 2022/08/30 15:15:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:15:14 - mmengine - INFO - Epoch(train) [688][5/63] lr: 3.2547e-03 eta: 11:22:53 time: 0.9463 data_time: 0.2022 memory: 16201 loss_prob: 0.4398 loss_thr: 0.3115 loss_db: 0.0777 loss: 0.8290 2022/08/30 15:15:19 - mmengine - INFO - Epoch(train) [688][10/63] lr: 3.2547e-03 eta: 11:22:32 time: 0.9904 data_time: 0.2160 memory: 16201 loss_prob: 0.4387 loss_thr: 0.3078 loss_db: 0.0799 loss: 0.8263 2022/08/30 15:15:23 - mmengine - INFO - Epoch(train) [688][15/63] lr: 3.2547e-03 eta: 11:22:32 time: 0.8503 data_time: 0.0284 memory: 16201 loss_prob: 0.4626 loss_thr: 0.3140 loss_db: 0.0807 loss: 0.8573 2022/08/30 15:15:27 - mmengine - INFO - Epoch(train) [688][20/63] lr: 3.2547e-03 eta: 11:22:16 time: 0.8386 data_time: 0.0182 memory: 16201 loss_prob: 0.4306 loss_thr: 0.2984 loss_db: 0.0734 loss: 0.8024 2022/08/30 15:15:31 - mmengine - INFO - Epoch(train) [688][25/63] lr: 3.2547e-03 eta: 11:22:16 time: 0.7975 data_time: 0.0335 memory: 16201 loss_prob: 0.4575 loss_thr: 0.3218 loss_db: 0.0808 loss: 0.8601 2022/08/30 15:15:35 - mmengine - INFO - Epoch(train) [688][30/63] lr: 3.2547e-03 eta: 11:22:00 time: 0.7983 data_time: 0.0264 memory: 16201 loss_prob: 0.4660 loss_thr: 0.3347 loss_db: 0.0827 loss: 0.8834 2022/08/30 15:15:39 - mmengine - INFO - Epoch(train) [688][35/63] lr: 3.2547e-03 eta: 11:22:00 time: 0.8317 data_time: 0.0201 memory: 16201 loss_prob: 0.4146 loss_thr: 0.3082 loss_db: 0.0726 loss: 0.7954 2022/08/30 15:15:43 - mmengine - INFO - Epoch(train) [688][40/63] lr: 3.2547e-03 eta: 11:21:44 time: 0.8380 data_time: 0.0256 memory: 16201 loss_prob: 0.4189 loss_thr: 0.3047 loss_db: 0.0735 loss: 0.7972 2022/08/30 15:15:47 - mmengine - INFO - Epoch(train) [688][45/63] lr: 3.2547e-03 eta: 11:21:44 time: 0.8110 data_time: 0.0239 memory: 16201 loss_prob: 0.4427 loss_thr: 0.3142 loss_db: 0.0782 loss: 0.8351 2022/08/30 15:15:51 - mmengine - INFO - Epoch(train) [688][50/63] lr: 3.2547e-03 eta: 11:21:28 time: 0.8010 data_time: 0.0260 memory: 16201 loss_prob: 0.4611 loss_thr: 0.3197 loss_db: 0.0812 loss: 0.8620 2022/08/30 15:15:55 - mmengine - INFO - Epoch(train) [688][55/63] lr: 3.2547e-03 eta: 11:21:28 time: 0.7917 data_time: 0.0237 memory: 16201 loss_prob: 0.5446 loss_thr: 0.3557 loss_db: 0.0950 loss: 0.9954 2022/08/30 15:16:00 - mmengine - INFO - Epoch(train) [688][60/63] lr: 3.2547e-03 eta: 11:21:12 time: 0.8841 data_time: 0.0240 memory: 16201 loss_prob: 0.5309 loss_thr: 0.3504 loss_db: 0.0912 loss: 0.9725 2022/08/30 15:16:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:16:08 - mmengine - INFO - Epoch(train) [689][5/63] lr: 3.2490e-03 eta: 11:21:12 time: 1.0056 data_time: 0.1769 memory: 16201 loss_prob: 0.4191 loss_thr: 0.2957 loss_db: 0.0760 loss: 0.7908 2022/08/30 15:16:12 - mmengine - INFO - Epoch(train) [689][10/63] lr: 3.2490e-03 eta: 11:20:51 time: 1.0103 data_time: 0.1880 memory: 16201 loss_prob: 0.4263 loss_thr: 0.3049 loss_db: 0.0776 loss: 0.8088 2022/08/30 15:16:17 - mmengine - INFO - Epoch(train) [689][15/63] lr: 3.2490e-03 eta: 11:20:51 time: 0.8425 data_time: 0.0294 memory: 16201 loss_prob: 0.3993 loss_thr: 0.2976 loss_db: 0.0695 loss: 0.7664 2022/08/30 15:16:21 - mmengine - INFO - Epoch(train) [689][20/63] lr: 3.2490e-03 eta: 11:20:35 time: 0.8509 data_time: 0.0216 memory: 16201 loss_prob: 0.4105 loss_thr: 0.2996 loss_db: 0.0723 loss: 0.7824 2022/08/30 15:16:25 - mmengine - INFO - Epoch(train) [689][25/63] lr: 3.2490e-03 eta: 11:20:35 time: 0.8494 data_time: 0.0286 memory: 16201 loss_prob: 0.4852 loss_thr: 0.3412 loss_db: 0.0865 loss: 0.9129 2022/08/30 15:16:29 - mmengine - INFO - Epoch(train) [689][30/63] lr: 3.2490e-03 eta: 11:20:19 time: 0.8184 data_time: 0.0256 memory: 16201 loss_prob: 0.4459 loss_thr: 0.3277 loss_db: 0.0796 loss: 0.8532 2022/08/30 15:16:33 - mmengine - INFO - Epoch(train) [689][35/63] lr: 3.2490e-03 eta: 11:20:19 time: 0.8172 data_time: 0.0231 memory: 16201 loss_prob: 0.4360 loss_thr: 0.3229 loss_db: 0.0771 loss: 0.8361 2022/08/30 15:16:37 - mmengine - INFO - Epoch(train) [689][40/63] lr: 3.2490e-03 eta: 11:20:03 time: 0.8123 data_time: 0.0258 memory: 16201 loss_prob: 0.4656 loss_thr: 0.3264 loss_db: 0.0807 loss: 0.8727 2022/08/30 15:16:41 - mmengine - INFO - Epoch(train) [689][45/63] lr: 3.2490e-03 eta: 11:20:03 time: 0.8287 data_time: 0.0271 memory: 16201 loss_prob: 0.4159 loss_thr: 0.2953 loss_db: 0.0724 loss: 0.7836 2022/08/30 15:16:46 - mmengine - INFO - Epoch(train) [689][50/63] lr: 3.2490e-03 eta: 11:19:48 time: 0.8643 data_time: 0.0253 memory: 16201 loss_prob: 0.3713 loss_thr: 0.2697 loss_db: 0.0672 loss: 0.7083 2022/08/30 15:16:50 - mmengine - INFO - Epoch(train) [689][55/63] lr: 3.2490e-03 eta: 11:19:48 time: 0.8551 data_time: 0.0223 memory: 16201 loss_prob: 0.3730 loss_thr: 0.2629 loss_db: 0.0681 loss: 0.7041 2022/08/30 15:16:54 - mmengine - INFO - Epoch(train) [689][60/63] lr: 3.2490e-03 eta: 11:19:32 time: 0.8251 data_time: 0.0225 memory: 16201 loss_prob: 0.4168 loss_thr: 0.2884 loss_db: 0.0733 loss: 0.7784 2022/08/30 15:16:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:17:02 - mmengine - INFO - Epoch(train) [690][5/63] lr: 3.2433e-03 eta: 11:19:32 time: 0.9323 data_time: 0.1738 memory: 16201 loss_prob: 0.4563 loss_thr: 0.3092 loss_db: 0.0796 loss: 0.8452 2022/08/30 15:17:06 - mmengine - INFO - Epoch(train) [690][10/63] lr: 3.2433e-03 eta: 11:19:10 time: 0.9912 data_time: 0.1828 memory: 16201 loss_prob: 0.4555 loss_thr: 0.3141 loss_db: 0.0776 loss: 0.8472 2022/08/30 15:17:10 - mmengine - INFO - Epoch(train) [690][15/63] lr: 3.2433e-03 eta: 11:19:10 time: 0.8034 data_time: 0.0218 memory: 16201 loss_prob: 0.4037 loss_thr: 0.2873 loss_db: 0.0714 loss: 0.7623 2022/08/30 15:17:14 - mmengine - INFO - Epoch(train) [690][20/63] lr: 3.2433e-03 eta: 11:18:55 time: 0.8291 data_time: 0.0208 memory: 16201 loss_prob: 0.4112 loss_thr: 0.2961 loss_db: 0.0747 loss: 0.7821 2022/08/30 15:17:19 - mmengine - INFO - Epoch(train) [690][25/63] lr: 3.2433e-03 eta: 11:18:55 time: 0.8934 data_time: 0.0414 memory: 16201 loss_prob: 0.4295 loss_thr: 0.3145 loss_db: 0.0763 loss: 0.8203 2022/08/30 15:17:23 - mmengine - INFO - Epoch(train) [690][30/63] lr: 3.2433e-03 eta: 11:18:39 time: 0.8635 data_time: 0.0300 memory: 16201 loss_prob: 0.4505 loss_thr: 0.3225 loss_db: 0.0778 loss: 0.8507 2022/08/30 15:17:27 - mmengine - INFO - Epoch(train) [690][35/63] lr: 3.2433e-03 eta: 11:18:39 time: 0.8148 data_time: 0.0182 memory: 16201 loss_prob: 0.4462 loss_thr: 0.3175 loss_db: 0.0787 loss: 0.8424 2022/08/30 15:17:31 - mmengine - INFO - Epoch(train) [690][40/63] lr: 3.2433e-03 eta: 11:18:23 time: 0.8455 data_time: 0.0277 memory: 16201 loss_prob: 0.4363 loss_thr: 0.3137 loss_db: 0.0782 loss: 0.8282 2022/08/30 15:17:35 - mmengine - INFO - Epoch(train) [690][45/63] lr: 3.2433e-03 eta: 11:18:23 time: 0.8427 data_time: 0.0258 memory: 16201 loss_prob: 0.4804 loss_thr: 0.3051 loss_db: 0.0805 loss: 0.8660 2022/08/30 15:17:40 - mmengine - INFO - Epoch(train) [690][50/63] lr: 3.2433e-03 eta: 11:18:07 time: 0.8544 data_time: 0.0239 memory: 16201 loss_prob: 0.4828 loss_thr: 0.2992 loss_db: 0.0799 loss: 0.8620 2022/08/30 15:17:44 - mmengine - INFO - Epoch(train) [690][55/63] lr: 3.2433e-03 eta: 11:18:07 time: 0.8641 data_time: 0.0224 memory: 16201 loss_prob: 0.4433 loss_thr: 0.3032 loss_db: 0.0734 loss: 0.8199 2022/08/30 15:17:48 - mmengine - INFO - Epoch(train) [690][60/63] lr: 3.2433e-03 eta: 11:17:51 time: 0.8265 data_time: 0.0246 memory: 16201 loss_prob: 0.4574 loss_thr: 0.3167 loss_db: 0.0769 loss: 0.8510 2022/08/30 15:17:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:17:57 - mmengine - INFO - Epoch(train) [691][5/63] lr: 3.2375e-03 eta: 11:17:51 time: 0.9954 data_time: 0.2285 memory: 16201 loss_prob: 0.4765 loss_thr: 0.3212 loss_db: 0.0819 loss: 0.8797 2022/08/30 15:18:01 - mmengine - INFO - Epoch(train) [691][10/63] lr: 3.2375e-03 eta: 11:17:31 time: 1.0403 data_time: 0.2435 memory: 16201 loss_prob: 0.4848 loss_thr: 0.3422 loss_db: 0.0842 loss: 0.9111 2022/08/30 15:18:05 - mmengine - INFO - Epoch(train) [691][15/63] lr: 3.2375e-03 eta: 11:17:31 time: 0.8303 data_time: 0.0285 memory: 16201 loss_prob: 0.4670 loss_thr: 0.3384 loss_db: 0.0834 loss: 0.8888 2022/08/30 15:18:09 - mmengine - INFO - Epoch(train) [691][20/63] lr: 3.2375e-03 eta: 11:17:15 time: 0.8376 data_time: 0.0244 memory: 16201 loss_prob: 0.4123 loss_thr: 0.3052 loss_db: 0.0737 loss: 0.7913 2022/08/30 15:18:13 - mmengine - INFO - Epoch(train) [691][25/63] lr: 3.2375e-03 eta: 11:17:15 time: 0.8419 data_time: 0.0371 memory: 16201 loss_prob: 0.4162 loss_thr: 0.3031 loss_db: 0.0720 loss: 0.7913 2022/08/30 15:18:17 - mmengine - INFO - Epoch(train) [691][30/63] lr: 3.2375e-03 eta: 11:16:59 time: 0.8277 data_time: 0.0264 memory: 16201 loss_prob: 0.3831 loss_thr: 0.2788 loss_db: 0.0686 loss: 0.7306 2022/08/30 15:18:21 - mmengine - INFO - Epoch(train) [691][35/63] lr: 3.2375e-03 eta: 11:16:59 time: 0.8089 data_time: 0.0194 memory: 16201 loss_prob: 0.4209 loss_thr: 0.3046 loss_db: 0.0744 loss: 0.7999 2022/08/30 15:18:25 - mmengine - INFO - Epoch(train) [691][40/63] lr: 3.2375e-03 eta: 11:16:43 time: 0.8030 data_time: 0.0270 memory: 16201 loss_prob: 0.4530 loss_thr: 0.3314 loss_db: 0.0797 loss: 0.8640 2022/08/30 15:18:30 - mmengine - INFO - Epoch(train) [691][45/63] lr: 3.2375e-03 eta: 11:16:43 time: 0.8253 data_time: 0.0226 memory: 16201 loss_prob: 0.4130 loss_thr: 0.3033 loss_db: 0.0741 loss: 0.7905 2022/08/30 15:18:34 - mmengine - INFO - Epoch(train) [691][50/63] lr: 3.2375e-03 eta: 11:16:27 time: 0.8446 data_time: 0.0250 memory: 16201 loss_prob: 0.4125 loss_thr: 0.2961 loss_db: 0.0722 loss: 0.7809 2022/08/30 15:18:38 - mmengine - INFO - Epoch(train) [691][55/63] lr: 3.2375e-03 eta: 11:16:27 time: 0.8294 data_time: 0.0241 memory: 16201 loss_prob: 0.4143 loss_thr: 0.2975 loss_db: 0.0717 loss: 0.7835 2022/08/30 15:18:42 - mmengine - INFO - Epoch(train) [691][60/63] lr: 3.2375e-03 eta: 11:16:11 time: 0.8257 data_time: 0.0228 memory: 16201 loss_prob: 0.4199 loss_thr: 0.2992 loss_db: 0.0736 loss: 0.7928 2022/08/30 15:18:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:18:50 - mmengine - INFO - Epoch(train) [692][5/63] lr: 3.2318e-03 eta: 11:16:11 time: 0.9526 data_time: 0.1581 memory: 16201 loss_prob: 0.4612 loss_thr: 0.3270 loss_db: 0.0819 loss: 0.8701 2022/08/30 15:18:54 - mmengine - INFO - Epoch(train) [692][10/63] lr: 3.2318e-03 eta: 11:15:50 time: 1.0164 data_time: 0.1750 memory: 16201 loss_prob: 0.4202 loss_thr: 0.2996 loss_db: 0.0743 loss: 0.7941 2022/08/30 15:18:58 - mmengine - INFO - Epoch(train) [692][15/63] lr: 3.2318e-03 eta: 11:15:50 time: 0.8351 data_time: 0.0257 memory: 16201 loss_prob: 0.4263 loss_thr: 0.2978 loss_db: 0.0749 loss: 0.7990 2022/08/30 15:19:02 - mmengine - INFO - Epoch(train) [692][20/63] lr: 3.2318e-03 eta: 11:15:34 time: 0.8143 data_time: 0.0219 memory: 16201 loss_prob: 0.4640 loss_thr: 0.3264 loss_db: 0.0829 loss: 0.8732 2022/08/30 15:19:06 - mmengine - INFO - Epoch(train) [692][25/63] lr: 3.2318e-03 eta: 11:15:34 time: 0.7978 data_time: 0.0287 memory: 16201 loss_prob: 0.4514 loss_thr: 0.3202 loss_db: 0.0806 loss: 0.8522 2022/08/30 15:19:11 - mmengine - INFO - Epoch(train) [692][30/63] lr: 3.2318e-03 eta: 11:15:18 time: 0.8133 data_time: 0.0244 memory: 16201 loss_prob: 0.4534 loss_thr: 0.3169 loss_db: 0.0794 loss: 0.8497 2022/08/30 15:19:14 - mmengine - INFO - Epoch(train) [692][35/63] lr: 3.2318e-03 eta: 11:15:18 time: 0.8179 data_time: 0.0276 memory: 16201 loss_prob: 0.5126 loss_thr: 0.3206 loss_db: 0.0832 loss: 0.9165 2022/08/30 15:19:18 - mmengine - INFO - Epoch(train) [692][40/63] lr: 3.2318e-03 eta: 11:15:02 time: 0.7817 data_time: 0.0231 memory: 16201 loss_prob: 0.4783 loss_thr: 0.3150 loss_db: 0.0787 loss: 0.8720 2022/08/30 15:19:22 - mmengine - INFO - Epoch(train) [692][45/63] lr: 3.2318e-03 eta: 11:15:02 time: 0.7980 data_time: 0.0235 memory: 16201 loss_prob: 0.3959 loss_thr: 0.3023 loss_db: 0.0704 loss: 0.7686 2022/08/30 15:19:26 - mmengine - INFO - Epoch(train) [692][50/63] lr: 3.2318e-03 eta: 11:14:46 time: 0.8103 data_time: 0.0300 memory: 16201 loss_prob: 0.4140 loss_thr: 0.3014 loss_db: 0.0712 loss: 0.7866 2022/08/30 15:19:31 - mmengine - INFO - Epoch(train) [692][55/63] lr: 3.2318e-03 eta: 11:14:46 time: 0.8174 data_time: 0.0257 memory: 16201 loss_prob: 0.4657 loss_thr: 0.3179 loss_db: 0.0824 loss: 0.8659 2022/08/30 15:19:35 - mmengine - INFO - Epoch(train) [692][60/63] lr: 3.2318e-03 eta: 11:14:30 time: 0.8279 data_time: 0.0229 memory: 16201 loss_prob: 0.4661 loss_thr: 0.3160 loss_db: 0.0850 loss: 0.8671 2022/08/30 15:19:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:19:43 - mmengine - INFO - Epoch(train) [693][5/63] lr: 3.2261e-03 eta: 11:14:30 time: 0.9633 data_time: 0.1836 memory: 16201 loss_prob: 0.4700 loss_thr: 0.3181 loss_db: 0.0816 loss: 0.8697 2022/08/30 15:19:47 - mmengine - INFO - Epoch(train) [693][10/63] lr: 3.2261e-03 eta: 11:14:09 time: 1.0080 data_time: 0.1976 memory: 16201 loss_prob: 0.4541 loss_thr: 0.3213 loss_db: 0.0808 loss: 0.8562 2022/08/30 15:19:51 - mmengine - INFO - Epoch(train) [693][15/63] lr: 3.2261e-03 eta: 11:14:09 time: 0.8433 data_time: 0.0242 memory: 16201 loss_prob: 0.4154 loss_thr: 0.3019 loss_db: 0.0734 loss: 0.7908 2022/08/30 15:19:55 - mmengine - INFO - Epoch(train) [693][20/63] lr: 3.2261e-03 eta: 11:13:53 time: 0.8525 data_time: 0.0236 memory: 16201 loss_prob: 0.4071 loss_thr: 0.3010 loss_db: 0.0706 loss: 0.7787 2022/08/30 15:19:59 - mmengine - INFO - Epoch(train) [693][25/63] lr: 3.2261e-03 eta: 11:13:53 time: 0.8249 data_time: 0.0322 memory: 16201 loss_prob: 0.4152 loss_thr: 0.3018 loss_db: 0.0719 loss: 0.7890 2022/08/30 15:20:04 - mmengine - INFO - Epoch(train) [693][30/63] lr: 3.2261e-03 eta: 11:13:37 time: 0.8223 data_time: 0.0236 memory: 16201 loss_prob: 0.4372 loss_thr: 0.2886 loss_db: 0.0715 loss: 0.7973 2022/08/30 15:20:07 - mmengine - INFO - Epoch(train) [693][35/63] lr: 3.2261e-03 eta: 11:13:37 time: 0.8034 data_time: 0.0222 memory: 16201 loss_prob: 0.4447 loss_thr: 0.2996 loss_db: 0.0734 loss: 0.8178 2022/08/30 15:20:12 - mmengine - INFO - Epoch(train) [693][40/63] lr: 3.2261e-03 eta: 11:13:22 time: 0.8193 data_time: 0.0277 memory: 16201 loss_prob: 0.4348 loss_thr: 0.3191 loss_db: 0.0774 loss: 0.8313 2022/08/30 15:20:16 - mmengine - INFO - Epoch(train) [693][45/63] lr: 3.2261e-03 eta: 11:13:22 time: 0.8400 data_time: 0.0277 memory: 16201 loss_prob: 0.4735 loss_thr: 0.3398 loss_db: 0.0844 loss: 0.8977 2022/08/30 15:20:20 - mmengine - INFO - Epoch(train) [693][50/63] lr: 3.2261e-03 eta: 11:13:06 time: 0.8423 data_time: 0.0258 memory: 16201 loss_prob: 0.4963 loss_thr: 0.3363 loss_db: 0.0871 loss: 0.9198 2022/08/30 15:20:24 - mmengine - INFO - Epoch(train) [693][55/63] lr: 3.2261e-03 eta: 11:13:06 time: 0.8265 data_time: 0.0228 memory: 16201 loss_prob: 0.4974 loss_thr: 0.3349 loss_db: 0.0872 loss: 0.9195 2022/08/30 15:20:29 - mmengine - INFO - Epoch(train) [693][60/63] lr: 3.2261e-03 eta: 11:12:50 time: 0.8305 data_time: 0.0247 memory: 16201 loss_prob: 0.4781 loss_thr: 0.3272 loss_db: 0.0823 loss: 0.8876 2022/08/30 15:20:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:20:37 - mmengine - INFO - Epoch(train) [694][5/63] lr: 3.2204e-03 eta: 11:12:50 time: 1.0225 data_time: 0.2202 memory: 16201 loss_prob: 0.3904 loss_thr: 0.3047 loss_db: 0.0695 loss: 0.7646 2022/08/30 15:20:41 - mmengine - INFO - Epoch(train) [694][10/63] lr: 3.2204e-03 eta: 11:12:29 time: 1.0197 data_time: 0.2187 memory: 16201 loss_prob: 0.4166 loss_thr: 0.3194 loss_db: 0.0747 loss: 0.8107 2022/08/30 15:20:45 - mmengine - INFO - Epoch(train) [694][15/63] lr: 3.2204e-03 eta: 11:12:29 time: 0.8406 data_time: 0.0258 memory: 16201 loss_prob: 0.4470 loss_thr: 0.3269 loss_db: 0.0793 loss: 0.8532 2022/08/30 15:20:49 - mmengine - INFO - Epoch(train) [694][20/63] lr: 3.2204e-03 eta: 11:12:13 time: 0.8460 data_time: 0.0259 memory: 16201 loss_prob: 0.4507 loss_thr: 0.3246 loss_db: 0.0796 loss: 0.8549 2022/08/30 15:20:54 - mmengine - INFO - Epoch(train) [694][25/63] lr: 3.2204e-03 eta: 11:12:13 time: 0.8278 data_time: 0.0279 memory: 16201 loss_prob: 0.4292 loss_thr: 0.3052 loss_db: 0.0764 loss: 0.8108 2022/08/30 15:20:58 - mmengine - INFO - Epoch(train) [694][30/63] lr: 3.2204e-03 eta: 11:11:58 time: 0.8438 data_time: 0.0237 memory: 16201 loss_prob: 0.4066 loss_thr: 0.2990 loss_db: 0.0727 loss: 0.7783 2022/08/30 15:21:02 - mmengine - INFO - Epoch(train) [694][35/63] lr: 3.2204e-03 eta: 11:11:58 time: 0.8393 data_time: 0.0266 memory: 16201 loss_prob: 0.4158 loss_thr: 0.3052 loss_db: 0.0725 loss: 0.7935 2022/08/30 15:21:06 - mmengine - INFO - Epoch(train) [694][40/63] lr: 3.2204e-03 eta: 11:11:42 time: 0.8076 data_time: 0.0239 memory: 16201 loss_prob: 0.4042 loss_thr: 0.2944 loss_db: 0.0701 loss: 0.7687 2022/08/30 15:21:11 - mmengine - INFO - Epoch(train) [694][45/63] lr: 3.2204e-03 eta: 11:11:42 time: 0.8562 data_time: 0.0233 memory: 16201 loss_prob: 0.4044 loss_thr: 0.2987 loss_db: 0.0712 loss: 0.7742 2022/08/30 15:21:15 - mmengine - INFO - Epoch(train) [694][50/63] lr: 3.2204e-03 eta: 11:11:26 time: 0.8592 data_time: 0.0226 memory: 16201 loss_prob: 0.4252 loss_thr: 0.3123 loss_db: 0.0746 loss: 0.8121 2022/08/30 15:21:20 - mmengine - INFO - Epoch(train) [694][55/63] lr: 3.2204e-03 eta: 11:11:26 time: 0.9829 data_time: 0.0225 memory: 16201 loss_prob: 0.4387 loss_thr: 0.2986 loss_db: 0.0759 loss: 0.8132 2022/08/30 15:21:25 - mmengine - INFO - Epoch(train) [694][60/63] lr: 3.2204e-03 eta: 11:11:12 time: 1.0703 data_time: 0.0324 memory: 16201 loss_prob: 0.4567 loss_thr: 0.3058 loss_db: 0.0794 loss: 0.8419 2022/08/30 15:21:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:21:35 - mmengine - INFO - Epoch(train) [695][5/63] lr: 3.2146e-03 eta: 11:11:12 time: 1.2429 data_time: 0.3287 memory: 16201 loss_prob: 0.4485 loss_thr: 0.3205 loss_db: 0.0788 loss: 0.8478 2022/08/30 15:21:40 - mmengine - INFO - Epoch(train) [695][10/63] lr: 3.2146e-03 eta: 11:10:53 time: 1.2512 data_time: 0.3234 memory: 16201 loss_prob: 0.4949 loss_thr: 0.3073 loss_db: 0.0803 loss: 0.8825 2022/08/30 15:21:44 - mmengine - INFO - Epoch(train) [695][15/63] lr: 3.2146e-03 eta: 11:10:53 time: 0.8934 data_time: 0.0289 memory: 16201 loss_prob: 0.4561 loss_thr: 0.2858 loss_db: 0.0742 loss: 0.8162 2022/08/30 15:21:50 - mmengine - INFO - Epoch(train) [695][20/63] lr: 3.2146e-03 eta: 11:10:38 time: 1.0223 data_time: 0.0310 memory: 16201 loss_prob: 0.3803 loss_thr: 0.2845 loss_db: 0.0681 loss: 0.7329 2022/08/30 15:21:56 - mmengine - INFO - Epoch(train) [695][25/63] lr: 3.2146e-03 eta: 11:10:38 time: 1.2064 data_time: 0.0391 memory: 16201 loss_prob: 0.3980 loss_thr: 0.2911 loss_db: 0.0709 loss: 0.7599 2022/08/30 15:22:00 - mmengine - INFO - Epoch(train) [695][30/63] lr: 3.2146e-03 eta: 11:10:24 time: 1.0104 data_time: 0.0282 memory: 16201 loss_prob: 0.4418 loss_thr: 0.3198 loss_db: 0.0781 loss: 0.8397 2022/08/30 15:22:06 - mmengine - INFO - Epoch(train) [695][35/63] lr: 3.2146e-03 eta: 11:10:24 time: 0.9860 data_time: 0.0294 memory: 16201 loss_prob: 0.4740 loss_thr: 0.3309 loss_db: 0.0839 loss: 0.8888 2022/08/30 15:22:10 - mmengine - INFO - Epoch(train) [695][40/63] lr: 3.2146e-03 eta: 11:10:09 time: 0.9961 data_time: 0.0295 memory: 16201 loss_prob: 0.4309 loss_thr: 0.2997 loss_db: 0.0762 loss: 0.8068 2022/08/30 15:22:17 - mmengine - INFO - Epoch(train) [695][45/63] lr: 3.2146e-03 eta: 11:10:09 time: 1.1029 data_time: 0.0207 memory: 16201 loss_prob: 0.4033 loss_thr: 0.2944 loss_db: 0.0725 loss: 0.7702 2022/08/30 15:22:22 - mmengine - INFO - Epoch(train) [695][50/63] lr: 3.2146e-03 eta: 11:09:56 time: 1.1254 data_time: 0.0366 memory: 16201 loss_prob: 0.4702 loss_thr: 0.3328 loss_db: 0.0804 loss: 0.8834 2022/08/30 15:22:27 - mmengine - INFO - Epoch(train) [695][55/63] lr: 3.2146e-03 eta: 11:09:56 time: 0.9973 data_time: 0.0334 memory: 16201 loss_prob: 0.5256 loss_thr: 0.3577 loss_db: 0.0877 loss: 0.9710 2022/08/30 15:22:31 - mmengine - INFO - Epoch(train) [695][60/63] lr: 3.2146e-03 eta: 11:09:41 time: 0.9670 data_time: 0.0228 memory: 16201 loss_prob: 0.4588 loss_thr: 0.3229 loss_db: 0.0797 loss: 0.8615 2022/08/30 15:22:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:22:40 - mmengine - INFO - Epoch(train) [696][5/63] lr: 3.2089e-03 eta: 11:09:41 time: 1.0012 data_time: 0.1982 memory: 16201 loss_prob: 0.4638 loss_thr: 0.3176 loss_db: 0.0819 loss: 0.8633 2022/08/30 15:22:44 - mmengine - INFO - Epoch(train) [696][10/63] lr: 3.2089e-03 eta: 11:09:20 time: 1.0143 data_time: 0.1933 memory: 16201 loss_prob: 0.4509 loss_thr: 0.3086 loss_db: 0.0792 loss: 0.8387 2022/08/30 15:22:48 - mmengine - INFO - Epoch(train) [696][15/63] lr: 3.2089e-03 eta: 11:09:20 time: 0.8824 data_time: 0.0373 memory: 16201 loss_prob: 0.4154 loss_thr: 0.3016 loss_db: 0.0729 loss: 0.7899 2022/08/30 15:22:53 - mmengine - INFO - Epoch(train) [696][20/63] lr: 3.2089e-03 eta: 11:09:05 time: 0.8967 data_time: 0.0437 memory: 16201 loss_prob: 0.4287 loss_thr: 0.3114 loss_db: 0.0764 loss: 0.8165 2022/08/30 15:22:57 - mmengine - INFO - Epoch(train) [696][25/63] lr: 3.2089e-03 eta: 11:09:05 time: 0.8439 data_time: 0.0288 memory: 16201 loss_prob: 0.4189 loss_thr: 0.3076 loss_db: 0.0755 loss: 0.8020 2022/08/30 15:23:01 - mmengine - INFO - Epoch(train) [696][30/63] lr: 3.2089e-03 eta: 11:08:49 time: 0.8362 data_time: 0.0286 memory: 16201 loss_prob: 0.4189 loss_thr: 0.3078 loss_db: 0.0749 loss: 0.8016 2022/08/30 15:23:05 - mmengine - INFO - Epoch(train) [696][35/63] lr: 3.2089e-03 eta: 11:08:49 time: 0.8133 data_time: 0.0274 memory: 16201 loss_prob: 0.4564 loss_thr: 0.3173 loss_db: 0.0801 loss: 0.8539 2022/08/30 15:23:09 - mmengine - INFO - Epoch(train) [696][40/63] lr: 3.2089e-03 eta: 11:08:33 time: 0.7745 data_time: 0.0173 memory: 16201 loss_prob: 0.4950 loss_thr: 0.3197 loss_db: 0.0844 loss: 0.8990 2022/08/30 15:23:13 - mmengine - INFO - Epoch(train) [696][45/63] lr: 3.2089e-03 eta: 11:08:33 time: 0.7907 data_time: 0.0293 memory: 16201 loss_prob: 0.5017 loss_thr: 0.3295 loss_db: 0.0861 loss: 0.9174 2022/08/30 15:23:17 - mmengine - INFO - Epoch(train) [696][50/63] lr: 3.2089e-03 eta: 11:08:17 time: 0.7970 data_time: 0.0277 memory: 16201 loss_prob: 0.4412 loss_thr: 0.3208 loss_db: 0.0775 loss: 0.8395 2022/08/30 15:23:21 - mmengine - INFO - Epoch(train) [696][55/63] lr: 3.2089e-03 eta: 11:08:17 time: 0.7767 data_time: 0.0188 memory: 16201 loss_prob: 0.4508 loss_thr: 0.3215 loss_db: 0.0789 loss: 0.8513 2022/08/30 15:23:26 - mmengine - INFO - Epoch(train) [696][60/63] lr: 3.2089e-03 eta: 11:08:02 time: 0.8988 data_time: 0.0328 memory: 16201 loss_prob: 0.4770 loss_thr: 0.3212 loss_db: 0.0817 loss: 0.8800 2022/08/30 15:23:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:23:34 - mmengine - INFO - Epoch(train) [697][5/63] lr: 3.2032e-03 eta: 11:08:02 time: 1.0036 data_time: 0.2098 memory: 16201 loss_prob: 0.4713 loss_thr: 0.3110 loss_db: 0.0840 loss: 0.8663 2022/08/30 15:23:38 - mmengine - INFO - Epoch(train) [697][10/63] lr: 3.2032e-03 eta: 11:07:41 time: 1.0191 data_time: 0.2068 memory: 16201 loss_prob: 0.4430 loss_thr: 0.2971 loss_db: 0.0784 loss: 0.8185 2022/08/30 15:23:42 - mmengine - INFO - Epoch(train) [697][15/63] lr: 3.2032e-03 eta: 11:07:41 time: 0.8432 data_time: 0.0239 memory: 16201 loss_prob: 0.4281 loss_thr: 0.2982 loss_db: 0.0741 loss: 0.8003 2022/08/30 15:23:47 - mmengine - INFO - Epoch(train) [697][20/63] lr: 3.2032e-03 eta: 11:07:25 time: 0.8430 data_time: 0.0222 memory: 16201 loss_prob: 0.4257 loss_thr: 0.3108 loss_db: 0.0748 loss: 0.8114 2022/08/30 15:23:51 - mmengine - INFO - Epoch(train) [697][25/63] lr: 3.2032e-03 eta: 11:07:25 time: 0.8285 data_time: 0.0331 memory: 16201 loss_prob: 0.4348 loss_thr: 0.3104 loss_db: 0.0781 loss: 0.8232 2022/08/30 15:23:55 - mmengine - INFO - Epoch(train) [697][30/63] lr: 3.2032e-03 eta: 11:07:09 time: 0.8055 data_time: 0.0251 memory: 16201 loss_prob: 0.4967 loss_thr: 0.3258 loss_db: 0.0861 loss: 0.9085 2022/08/30 15:23:59 - mmengine - INFO - Epoch(train) [697][35/63] lr: 3.2032e-03 eta: 11:07:09 time: 0.8115 data_time: 0.0260 memory: 16201 loss_prob: 0.4510 loss_thr: 0.3054 loss_db: 0.0768 loss: 0.8333 2022/08/30 15:24:03 - mmengine - INFO - Epoch(train) [697][40/63] lr: 3.2032e-03 eta: 11:06:53 time: 0.8292 data_time: 0.0255 memory: 16201 loss_prob: 0.3856 loss_thr: 0.2912 loss_db: 0.0677 loss: 0.7445 2022/08/30 15:24:08 - mmengine - INFO - Epoch(train) [697][45/63] lr: 3.2032e-03 eta: 11:06:53 time: 0.8676 data_time: 0.0210 memory: 16201 loss_prob: 0.4273 loss_thr: 0.3125 loss_db: 0.0773 loss: 0.8171 2022/08/30 15:24:12 - mmengine - INFO - Epoch(train) [697][50/63] lr: 3.2032e-03 eta: 11:06:38 time: 0.9295 data_time: 0.0295 memory: 16201 loss_prob: 0.4464 loss_thr: 0.3177 loss_db: 0.0797 loss: 0.8439 2022/08/30 15:24:18 - mmengine - INFO - Epoch(train) [697][55/63] lr: 3.2032e-03 eta: 11:06:38 time: 0.9986 data_time: 0.0294 memory: 16201 loss_prob: 0.4478 loss_thr: 0.3206 loss_db: 0.0779 loss: 0.8462 2022/08/30 15:24:22 - mmengine - INFO - Epoch(train) [697][60/63] lr: 3.2032e-03 eta: 11:06:24 time: 1.0162 data_time: 0.0251 memory: 16201 loss_prob: 0.4313 loss_thr: 0.3138 loss_db: 0.0744 loss: 0.8194 2022/08/30 15:24:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:24:32 - mmengine - INFO - Epoch(train) [698][5/63] lr: 3.1974e-03 eta: 11:06:24 time: 1.1683 data_time: 0.2048 memory: 16201 loss_prob: 0.4125 loss_thr: 0.2909 loss_db: 0.0738 loss: 0.7772 2022/08/30 15:24:36 - mmengine - INFO - Epoch(train) [698][10/63] lr: 3.1974e-03 eta: 11:06:04 time: 1.0927 data_time: 0.2023 memory: 16201 loss_prob: 0.4329 loss_thr: 0.3131 loss_db: 0.0773 loss: 0.8233 2022/08/30 15:24:41 - mmengine - INFO - Epoch(train) [698][15/63] lr: 3.1974e-03 eta: 11:06:04 time: 0.9421 data_time: 0.0259 memory: 16201 loss_prob: 0.4347 loss_thr: 0.3181 loss_db: 0.0770 loss: 0.8298 2022/08/30 15:24:46 - mmengine - INFO - Epoch(train) [698][20/63] lr: 3.1974e-03 eta: 11:05:49 time: 1.0482 data_time: 0.0389 memory: 16201 loss_prob: 0.4362 loss_thr: 0.3052 loss_db: 0.0774 loss: 0.8189 2022/08/30 15:24:50 - mmengine - INFO - Epoch(train) [698][25/63] lr: 3.1974e-03 eta: 11:05:49 time: 0.9339 data_time: 0.0319 memory: 16201 loss_prob: 0.4212 loss_thr: 0.2937 loss_db: 0.0741 loss: 0.7890 2022/08/30 15:24:56 - mmengine - INFO - Epoch(train) [698][30/63] lr: 3.1974e-03 eta: 11:05:34 time: 0.9351 data_time: 0.0304 memory: 16201 loss_prob: 0.4283 loss_thr: 0.2922 loss_db: 0.0762 loss: 0.7968 2022/08/30 15:25:00 - mmengine - INFO - Epoch(train) [698][35/63] lr: 3.1974e-03 eta: 11:05:34 time: 0.9874 data_time: 0.0390 memory: 16201 loss_prob: 0.4450 loss_thr: 0.3059 loss_db: 0.0792 loss: 0.8301 2022/08/30 15:25:05 - mmengine - INFO - Epoch(train) [698][40/63] lr: 3.1974e-03 eta: 11:05:19 time: 0.9312 data_time: 0.0310 memory: 16201 loss_prob: 0.4034 loss_thr: 0.2895 loss_db: 0.0703 loss: 0.7632 2022/08/30 15:25:10 - mmengine - INFO - Epoch(train) [698][45/63] lr: 3.1974e-03 eta: 11:05:19 time: 0.9917 data_time: 0.0339 memory: 16201 loss_prob: 0.3898 loss_thr: 0.2924 loss_db: 0.0673 loss: 0.7494 2022/08/30 15:25:15 - mmengine - INFO - Epoch(train) [698][50/63] lr: 3.1974e-03 eta: 11:05:05 time: 1.0158 data_time: 0.0328 memory: 16201 loss_prob: 0.4118 loss_thr: 0.3040 loss_db: 0.0737 loss: 0.7895 2022/08/30 15:25:19 - mmengine - INFO - Epoch(train) [698][55/63] lr: 3.1974e-03 eta: 11:05:05 time: 0.9043 data_time: 0.0256 memory: 16201 loss_prob: 0.4272 loss_thr: 0.3044 loss_db: 0.0767 loss: 0.8083 2022/08/30 15:25:24 - mmengine - INFO - Epoch(train) [698][60/63] lr: 3.1974e-03 eta: 11:04:50 time: 0.9289 data_time: 0.0353 memory: 16201 loss_prob: 0.3834 loss_thr: 0.2863 loss_db: 0.0672 loss: 0.7369 2022/08/30 15:25:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:25:33 - mmengine - INFO - Epoch(train) [699][5/63] lr: 3.1917e-03 eta: 11:04:50 time: 0.9911 data_time: 0.2400 memory: 16201 loss_prob: 0.4366 loss_thr: 0.3042 loss_db: 0.0767 loss: 0.8176 2022/08/30 15:25:37 - mmengine - INFO - Epoch(train) [699][10/63] lr: 3.1917e-03 eta: 11:04:30 time: 1.1118 data_time: 0.2532 memory: 16201 loss_prob: 0.4991 loss_thr: 0.3228 loss_db: 0.0834 loss: 0.9053 2022/08/30 15:25:42 - mmengine - INFO - Epoch(train) [699][15/63] lr: 3.1917e-03 eta: 11:04:30 time: 0.9255 data_time: 0.0307 memory: 16201 loss_prob: 0.4703 loss_thr: 0.3045 loss_db: 0.0789 loss: 0.8537 2022/08/30 15:25:47 - mmengine - INFO - Epoch(train) [699][20/63] lr: 3.1917e-03 eta: 11:04:15 time: 0.9101 data_time: 0.0301 memory: 16201 loss_prob: 0.4352 loss_thr: 0.3055 loss_db: 0.0751 loss: 0.8158 2022/08/30 15:25:52 - mmengine - INFO - Epoch(train) [699][25/63] lr: 3.1917e-03 eta: 11:04:15 time: 1.0015 data_time: 0.0401 memory: 16201 loss_prob: 0.4155 loss_thr: 0.3046 loss_db: 0.0730 loss: 0.7932 2022/08/30 15:25:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:25:56 - mmengine - INFO - Epoch(train) [699][30/63] lr: 3.1917e-03 eta: 11:04:00 time: 0.9912 data_time: 0.0232 memory: 16201 loss_prob: 0.3838 loss_thr: 0.2888 loss_db: 0.0674 loss: 0.7400 2022/08/30 15:26:02 - mmengine - INFO - Epoch(train) [699][35/63] lr: 3.1917e-03 eta: 11:04:00 time: 1.0008 data_time: 0.0661 memory: 16201 loss_prob: 0.4012 loss_thr: 0.2985 loss_db: 0.0704 loss: 0.7700 2022/08/30 15:26:07 - mmengine - INFO - Epoch(train) [699][40/63] lr: 3.1917e-03 eta: 11:03:46 time: 1.0811 data_time: 0.0728 memory: 16201 loss_prob: 0.4192 loss_thr: 0.3015 loss_db: 0.0734 loss: 0.7941 2022/08/30 15:26:12 - mmengine - INFO - Epoch(train) [699][45/63] lr: 3.1917e-03 eta: 11:03:46 time: 0.9904 data_time: 0.0272 memory: 16201 loss_prob: 0.4480 loss_thr: 0.3005 loss_db: 0.0782 loss: 0.8267 2022/08/30 15:26:17 - mmengine - INFO - Epoch(train) [699][50/63] lr: 3.1917e-03 eta: 11:03:32 time: 0.9596 data_time: 0.0269 memory: 16201 loss_prob: 0.4675 loss_thr: 0.3074 loss_db: 0.0834 loss: 0.8584 2022/08/30 15:26:22 - mmengine - INFO - Epoch(train) [699][55/63] lr: 3.1917e-03 eta: 11:03:32 time: 1.0526 data_time: 0.0303 memory: 16201 loss_prob: 0.4344 loss_thr: 0.2940 loss_db: 0.0776 loss: 0.8060 2022/08/30 15:26:27 - mmengine - INFO - Epoch(train) [699][60/63] lr: 3.1917e-03 eta: 11:03:17 time: 1.0100 data_time: 0.0333 memory: 16201 loss_prob: 0.4315 loss_thr: 0.3054 loss_db: 0.0751 loss: 0.8121 2022/08/30 15:26:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:26:36 - mmengine - INFO - Epoch(train) [700][5/63] lr: 3.1860e-03 eta: 11:03:17 time: 1.1485 data_time: 0.2218 memory: 16201 loss_prob: 0.4489 loss_thr: 0.3157 loss_db: 0.0805 loss: 0.8451 2022/08/30 15:26:41 - mmengine - INFO - Epoch(train) [700][10/63] lr: 3.1860e-03 eta: 11:02:57 time: 1.1675 data_time: 0.2224 memory: 16201 loss_prob: 0.4492 loss_thr: 0.3054 loss_db: 0.0803 loss: 0.8349 2022/08/30 15:26:46 - mmengine - INFO - Epoch(train) [700][15/63] lr: 3.1860e-03 eta: 11:02:57 time: 0.9067 data_time: 0.0230 memory: 16201 loss_prob: 0.4545 loss_thr: 0.3007 loss_db: 0.0780 loss: 0.8332 2022/08/30 15:26:51 - mmengine - INFO - Epoch(train) [700][20/63] lr: 3.1860e-03 eta: 11:02:43 time: 0.9696 data_time: 0.0243 memory: 16201 loss_prob: 0.4880 loss_thr: 0.3234 loss_db: 0.0832 loss: 0.8945 2022/08/30 15:26:55 - mmengine - INFO - Epoch(train) [700][25/63] lr: 3.1860e-03 eta: 11:02:43 time: 0.9787 data_time: 0.0294 memory: 16201 loss_prob: 0.4763 loss_thr: 0.3241 loss_db: 0.0815 loss: 0.8820 2022/08/30 15:27:00 - mmengine - INFO - Epoch(train) [700][30/63] lr: 3.1860e-03 eta: 11:02:28 time: 0.9372 data_time: 0.0268 memory: 16201 loss_prob: 0.4401 loss_thr: 0.3056 loss_db: 0.0770 loss: 0.8227 2022/08/30 15:27:05 - mmengine - INFO - Epoch(train) [700][35/63] lr: 3.1860e-03 eta: 11:02:28 time: 0.9280 data_time: 0.0252 memory: 16201 loss_prob: 0.4033 loss_thr: 0.2978 loss_db: 0.0720 loss: 0.7731 2022/08/30 15:27:09 - mmengine - INFO - Epoch(train) [700][40/63] lr: 3.1860e-03 eta: 11:02:13 time: 0.9320 data_time: 0.0225 memory: 16201 loss_prob: 0.3985 loss_thr: 0.3021 loss_db: 0.0706 loss: 0.7713 2022/08/30 15:27:13 - mmengine - INFO - Epoch(train) [700][45/63] lr: 3.1860e-03 eta: 11:02:13 time: 0.8742 data_time: 0.0268 memory: 16201 loss_prob: 0.4055 loss_thr: 0.2986 loss_db: 0.0739 loss: 0.7780 2022/08/30 15:27:18 - mmengine - INFO - Epoch(train) [700][50/63] lr: 3.1860e-03 eta: 11:01:57 time: 0.8397 data_time: 0.0314 memory: 16201 loss_prob: 0.4210 loss_thr: 0.3018 loss_db: 0.0759 loss: 0.7987 2022/08/30 15:27:23 - mmengine - INFO - Epoch(train) [700][55/63] lr: 3.1860e-03 eta: 11:01:57 time: 0.9532 data_time: 0.0328 memory: 16201 loss_prob: 0.4201 loss_thr: 0.3045 loss_db: 0.0733 loss: 0.7979 2022/08/30 15:27:27 - mmengine - INFO - Epoch(train) [700][60/63] lr: 3.1860e-03 eta: 11:01:42 time: 0.9179 data_time: 0.0380 memory: 16201 loss_prob: 0.4127 loss_thr: 0.3042 loss_db: 0.0733 loss: 0.7902 2022/08/30 15:27:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:27:29 - mmengine - INFO - Saving checkpoint at 700 epochs 2022/08/30 15:27:37 - mmengine - INFO - Epoch(val) [700][5/32] eta: 11:01:42 time: 0.6673 data_time: 0.1231 memory: 16201 2022/08/30 15:27:40 - mmengine - INFO - Epoch(val) [700][10/32] eta: 0:00:15 time: 0.7217 data_time: 0.1541 memory: 15734 2022/08/30 15:27:43 - mmengine - INFO - Epoch(val) [700][15/32] eta: 0:00:15 time: 0.6016 data_time: 0.0485 memory: 15734 2022/08/30 15:27:48 - mmengine - INFO - Epoch(val) [700][20/32] eta: 0:00:08 time: 0.7301 data_time: 0.0521 memory: 15734 2022/08/30 15:27:51 - mmengine - INFO - Epoch(val) [700][25/32] eta: 0:00:08 time: 0.7479 data_time: 0.0627 memory: 15734 2022/08/30 15:27:54 - mmengine - INFO - Epoch(val) [700][30/32] eta: 0:00:01 time: 0.5840 data_time: 0.0294 memory: 15734 2022/08/30 15:27:54 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 15:27:54 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8440, precision: 0.7826, hmean: 0.8121 2022/08/30 15:27:54 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8435, precision: 0.8218, hmean: 0.8325 2022/08/30 15:27:54 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8421, precision: 0.8528, hmean: 0.8474 2022/08/30 15:27:54 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8363, precision: 0.8698, hmean: 0.8527 2022/08/30 15:27:54 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8272, precision: 0.8892, hmean: 0.8571 2022/08/30 15:27:54 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7785, precision: 0.9198, hmean: 0.8433 2022/08/30 15:27:54 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.3043, precision: 0.9619, hmean: 0.4623 2022/08/30 15:27:54 - mmengine - INFO - Epoch(val) [700][32/32] icdar/precision: 0.8892 icdar/recall: 0.8272 icdar/hmean: 0.8571 2022/08/30 15:28:01 - mmengine - INFO - Epoch(train) [701][5/63] lr: 3.1802e-03 eta: 0:00:01 time: 1.0820 data_time: 0.2253 memory: 16201 loss_prob: 0.4369 loss_thr: 0.3011 loss_db: 0.0772 loss: 0.8152 2022/08/30 15:28:06 - mmengine - INFO - Epoch(train) [701][10/63] lr: 3.1802e-03 eta: 11:01:23 time: 1.1968 data_time: 0.2390 memory: 16201 loss_prob: 0.4326 loss_thr: 0.2946 loss_db: 0.0745 loss: 0.8018 2022/08/30 15:28:11 - mmengine - INFO - Epoch(train) [701][15/63] lr: 3.1802e-03 eta: 11:01:23 time: 0.9737 data_time: 0.0304 memory: 16201 loss_prob: 0.4718 loss_thr: 0.3205 loss_db: 0.0812 loss: 0.8735 2022/08/30 15:28:16 - mmengine - INFO - Epoch(train) [701][20/63] lr: 3.1802e-03 eta: 11:01:08 time: 0.9334 data_time: 0.0261 memory: 16201 loss_prob: 0.4926 loss_thr: 0.3400 loss_db: 0.0853 loss: 0.9179 2022/08/30 15:28:21 - mmengine - INFO - Epoch(train) [701][25/63] lr: 3.1802e-03 eta: 11:01:08 time: 1.0204 data_time: 0.0311 memory: 16201 loss_prob: 0.4500 loss_thr: 0.3152 loss_db: 0.0784 loss: 0.8436 2022/08/30 15:28:25 - mmengine - INFO - Epoch(train) [701][30/63] lr: 3.1802e-03 eta: 11:00:53 time: 0.9311 data_time: 0.0274 memory: 16201 loss_prob: 0.4801 loss_thr: 0.3225 loss_db: 0.0825 loss: 0.8851 2022/08/30 15:28:30 - mmengine - INFO - Epoch(train) [701][35/63] lr: 3.1802e-03 eta: 11:00:53 time: 0.9007 data_time: 0.0222 memory: 16201 loss_prob: 0.5077 loss_thr: 0.3412 loss_db: 0.0881 loss: 0.9371 2022/08/30 15:28:36 - mmengine - INFO - Epoch(train) [701][40/63] lr: 3.1802e-03 eta: 11:00:39 time: 1.0687 data_time: 0.0219 memory: 16201 loss_prob: 0.4633 loss_thr: 0.3245 loss_db: 0.0808 loss: 0.8686 2022/08/30 15:28:40 - mmengine - INFO - Epoch(train) [701][45/63] lr: 3.1802e-03 eta: 11:00:39 time: 0.9768 data_time: 0.0295 memory: 16201 loss_prob: 0.4133 loss_thr: 0.2961 loss_db: 0.0718 loss: 0.7811 2022/08/30 15:28:45 - mmengine - INFO - Epoch(train) [701][50/63] lr: 3.1802e-03 eta: 11:00:24 time: 0.9311 data_time: 0.0307 memory: 16201 loss_prob: 0.4159 loss_thr: 0.3065 loss_db: 0.0738 loss: 0.7962 2022/08/30 15:28:50 - mmengine - INFO - Epoch(train) [701][55/63] lr: 3.1802e-03 eta: 11:00:24 time: 1.0308 data_time: 0.0199 memory: 16201 loss_prob: 0.4183 loss_thr: 0.3035 loss_db: 0.0736 loss: 0.7954 2022/08/30 15:28:54 - mmengine - INFO - Epoch(train) [701][60/63] lr: 3.1802e-03 eta: 11:00:09 time: 0.9298 data_time: 0.0325 memory: 16201 loss_prob: 0.4222 loss_thr: 0.2971 loss_db: 0.0729 loss: 0.7921 2022/08/30 15:28:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:29:04 - mmengine - INFO - Epoch(train) [702][5/63] lr: 3.1745e-03 eta: 11:00:09 time: 1.1514 data_time: 0.1902 memory: 16201 loss_prob: 0.4596 loss_thr: 0.3297 loss_db: 0.0823 loss: 0.8716 2022/08/30 15:29:09 - mmengine - INFO - Epoch(train) [702][10/63] lr: 3.1745e-03 eta: 10:59:49 time: 1.1107 data_time: 0.2070 memory: 16201 loss_prob: 0.3961 loss_thr: 0.3045 loss_db: 0.0707 loss: 0.7712 2022/08/30 15:29:14 - mmengine - INFO - Epoch(train) [702][15/63] lr: 3.1745e-03 eta: 10:59:49 time: 0.9118 data_time: 0.0265 memory: 16201 loss_prob: 0.3748 loss_thr: 0.2782 loss_db: 0.0649 loss: 0.7178 2022/08/30 15:29:19 - mmengine - INFO - Epoch(train) [702][20/63] lr: 3.1745e-03 eta: 10:59:35 time: 1.0334 data_time: 0.0164 memory: 16201 loss_prob: 0.4183 loss_thr: 0.3019 loss_db: 0.0732 loss: 0.7933 2022/08/30 15:29:23 - mmengine - INFO - Epoch(train) [702][25/63] lr: 3.1745e-03 eta: 10:59:35 time: 0.9598 data_time: 0.0327 memory: 16201 loss_prob: 0.4172 loss_thr: 0.3118 loss_db: 0.0740 loss: 0.8030 2022/08/30 15:29:28 - mmengine - INFO - Epoch(train) [702][30/63] lr: 3.1745e-03 eta: 10:59:20 time: 0.9566 data_time: 0.0296 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2854 loss_db: 0.0675 loss: 0.7387 2022/08/30 15:29:34 - mmengine - INFO - Epoch(train) [702][35/63] lr: 3.1745e-03 eta: 10:59:20 time: 1.0527 data_time: 0.0290 memory: 16201 loss_prob: 0.4417 loss_thr: 0.3061 loss_db: 0.0773 loss: 0.8251 2022/08/30 15:29:38 - mmengine - INFO - Epoch(train) [702][40/63] lr: 3.1745e-03 eta: 10:59:05 time: 0.9640 data_time: 0.0322 memory: 16201 loss_prob: 0.4711 loss_thr: 0.3235 loss_db: 0.0825 loss: 0.8772 2022/08/30 15:29:44 - mmengine - INFO - Epoch(train) [702][45/63] lr: 3.1745e-03 eta: 10:59:05 time: 1.0477 data_time: 0.0263 memory: 16201 loss_prob: 0.4234 loss_thr: 0.3133 loss_db: 0.0749 loss: 0.8116 2022/08/30 15:29:50 - mmengine - INFO - Epoch(train) [702][50/63] lr: 3.1745e-03 eta: 10:58:52 time: 1.1626 data_time: 0.0679 memory: 16201 loss_prob: 0.4105 loss_thr: 0.3115 loss_db: 0.0734 loss: 0.7953 2022/08/30 15:29:54 - mmengine - INFO - Epoch(train) [702][55/63] lr: 3.1745e-03 eta: 10:58:52 time: 1.0181 data_time: 0.0751 memory: 16201 loss_prob: 0.4165 loss_thr: 0.3022 loss_db: 0.0732 loss: 0.7919 2022/08/30 15:30:00 - mmengine - INFO - Epoch(train) [702][60/63] lr: 3.1745e-03 eta: 10:58:37 time: 0.9942 data_time: 0.0732 memory: 16201 loss_prob: 0.4550 loss_thr: 0.3137 loss_db: 0.0788 loss: 0.8476 2022/08/30 15:30:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:30:10 - mmengine - INFO - Epoch(train) [703][5/63] lr: 3.1688e-03 eta: 10:58:37 time: 1.1994 data_time: 0.2638 memory: 16201 loss_prob: 0.4110 loss_thr: 0.2931 loss_db: 0.0732 loss: 0.7773 2022/08/30 15:30:16 - mmengine - INFO - Epoch(train) [703][10/63] lr: 3.1688e-03 eta: 10:58:19 time: 1.4224 data_time: 0.3078 memory: 16201 loss_prob: 0.4063 loss_thr: 0.2908 loss_db: 0.0718 loss: 0.7689 2022/08/30 15:30:21 - mmengine - INFO - Epoch(train) [703][15/63] lr: 3.1688e-03 eta: 10:58:19 time: 1.0839 data_time: 0.0831 memory: 16201 loss_prob: 0.4202 loss_thr: 0.2969 loss_db: 0.0743 loss: 0.7915 2022/08/30 15:30:26 - mmengine - INFO - Epoch(train) [703][20/63] lr: 3.1688e-03 eta: 10:58:05 time: 1.0346 data_time: 0.0762 memory: 16201 loss_prob: 0.4342 loss_thr: 0.3044 loss_db: 0.0777 loss: 0.8164 2022/08/30 15:30:32 - mmengine - INFO - Epoch(train) [703][25/63] lr: 3.1688e-03 eta: 10:58:05 time: 1.1341 data_time: 0.0911 memory: 16201 loss_prob: 0.4334 loss_thr: 0.3063 loss_db: 0.0770 loss: 0.8167 2022/08/30 15:30:36 - mmengine - INFO - Epoch(train) [703][30/63] lr: 3.1688e-03 eta: 10:57:51 time: 1.0043 data_time: 0.0800 memory: 16201 loss_prob: 0.4019 loss_thr: 0.2995 loss_db: 0.0703 loss: 0.7717 2022/08/30 15:30:42 - mmengine - INFO - Epoch(train) [703][35/63] lr: 3.1688e-03 eta: 10:57:51 time: 0.9860 data_time: 0.0684 memory: 16201 loss_prob: 0.4412 loss_thr: 0.3142 loss_db: 0.0751 loss: 0.8305 2022/08/30 15:30:47 - mmengine - INFO - Epoch(train) [703][40/63] lr: 3.1688e-03 eta: 10:57:37 time: 1.0334 data_time: 0.0454 memory: 16201 loss_prob: 0.4692 loss_thr: 0.3202 loss_db: 0.0807 loss: 0.8702 2022/08/30 15:30:52 - mmengine - INFO - Epoch(train) [703][45/63] lr: 3.1688e-03 eta: 10:57:37 time: 1.0159 data_time: 0.0788 memory: 16201 loss_prob: 0.3988 loss_thr: 0.2886 loss_db: 0.0709 loss: 0.7583 2022/08/30 15:30:57 - mmengine - INFO - Epoch(train) [703][50/63] lr: 3.1688e-03 eta: 10:57:22 time: 1.0228 data_time: 0.0806 memory: 16201 loss_prob: 0.4065 loss_thr: 0.2950 loss_db: 0.0717 loss: 0.7731 2022/08/30 15:31:03 - mmengine - INFO - Epoch(train) [703][55/63] lr: 3.1688e-03 eta: 10:57:22 time: 1.0618 data_time: 0.0732 memory: 16201 loss_prob: 0.4133 loss_thr: 0.2975 loss_db: 0.0732 loss: 0.7840 2022/08/30 15:31:07 - mmengine - INFO - Epoch(train) [703][60/63] lr: 3.1688e-03 eta: 10:57:08 time: 1.0324 data_time: 0.0852 memory: 16201 loss_prob: 0.3683 loss_thr: 0.2689 loss_db: 0.0647 loss: 0.7019 2022/08/30 15:31:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:31:18 - mmengine - INFO - Epoch(train) [704][5/63] lr: 3.1630e-03 eta: 10:57:08 time: 1.2190 data_time: 0.2759 memory: 16201 loss_prob: 0.3908 loss_thr: 0.2860 loss_db: 0.0695 loss: 0.7463 2022/08/30 15:31:22 - mmengine - INFO - Epoch(train) [704][10/63] lr: 3.1630e-03 eta: 10:56:48 time: 1.1217 data_time: 0.2892 memory: 16201 loss_prob: 0.4110 loss_thr: 0.2980 loss_db: 0.0720 loss: 0.7810 2022/08/30 15:31:28 - mmengine - INFO - Epoch(train) [704][15/63] lr: 3.1630e-03 eta: 10:56:48 time: 0.9870 data_time: 0.0825 memory: 16201 loss_prob: 0.4327 loss_thr: 0.3115 loss_db: 0.0761 loss: 0.8203 2022/08/30 15:31:33 - mmengine - INFO - Epoch(train) [704][20/63] lr: 3.1630e-03 eta: 10:56:34 time: 1.0620 data_time: 0.0460 memory: 16201 loss_prob: 0.4108 loss_thr: 0.3087 loss_db: 0.0745 loss: 0.7940 2022/08/30 15:31:37 - mmengine - INFO - Epoch(train) [704][25/63] lr: 3.1630e-03 eta: 10:56:34 time: 0.9520 data_time: 0.0865 memory: 16201 loss_prob: 0.4308 loss_thr: 0.3223 loss_db: 0.0751 loss: 0.8283 2022/08/30 15:31:44 - mmengine - INFO - Epoch(train) [704][30/63] lr: 3.1630e-03 eta: 10:56:20 time: 1.0548 data_time: 0.0790 memory: 16201 loss_prob: 0.3976 loss_thr: 0.2962 loss_db: 0.0676 loss: 0.7613 2022/08/30 15:31:49 - mmengine - INFO - Epoch(train) [704][35/63] lr: 3.1630e-03 eta: 10:56:20 time: 1.1320 data_time: 0.0767 memory: 16201 loss_prob: 0.3731 loss_thr: 0.2820 loss_db: 0.0677 loss: 0.7228 2022/08/30 15:31:53 - mmengine - INFO - Epoch(train) [704][40/63] lr: 3.1630e-03 eta: 10:56:05 time: 0.9402 data_time: 0.0773 memory: 16201 loss_prob: 0.4211 loss_thr: 0.2967 loss_db: 0.0758 loss: 0.7936 2022/08/30 15:31:59 - mmengine - INFO - Epoch(train) [704][45/63] lr: 3.1630e-03 eta: 10:56:05 time: 1.0067 data_time: 0.0516 memory: 16201 loss_prob: 0.4264 loss_thr: 0.3013 loss_db: 0.0743 loss: 0.8020 2022/08/30 15:32:04 - mmengine - INFO - Epoch(train) [704][50/63] lr: 3.1630e-03 eta: 10:55:51 time: 1.0734 data_time: 0.0826 memory: 16201 loss_prob: 0.4163 loss_thr: 0.3022 loss_db: 0.0729 loss: 0.7914 2022/08/30 15:32:08 - mmengine - INFO - Epoch(train) [704][55/63] lr: 3.1630e-03 eta: 10:55:51 time: 0.8990 data_time: 0.0755 memory: 16201 loss_prob: 0.4256 loss_thr: 0.3033 loss_db: 0.0758 loss: 0.8048 2022/08/30 15:32:13 - mmengine - INFO - Epoch(train) [704][60/63] lr: 3.1630e-03 eta: 10:55:36 time: 0.8991 data_time: 0.0534 memory: 16201 loss_prob: 0.4270 loss_thr: 0.2946 loss_db: 0.0741 loss: 0.7957 2022/08/30 15:32:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:32:22 - mmengine - INFO - Epoch(train) [705][5/63] lr: 3.1573e-03 eta: 10:55:36 time: 1.0547 data_time: 0.2624 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2761 loss_db: 0.0705 loss: 0.7387 2022/08/30 15:32:26 - mmengine - INFO - Epoch(train) [705][10/63] lr: 3.1573e-03 eta: 10:55:16 time: 1.0510 data_time: 0.2299 memory: 16201 loss_prob: 0.3981 loss_thr: 0.2951 loss_db: 0.0703 loss: 0.7635 2022/08/30 15:32:30 - mmengine - INFO - Epoch(train) [705][15/63] lr: 3.1573e-03 eta: 10:55:16 time: 0.8455 data_time: 0.0293 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2998 loss_db: 0.0699 loss: 0.7725 2022/08/30 15:32:34 - mmengine - INFO - Epoch(train) [705][20/63] lr: 3.1573e-03 eta: 10:55:00 time: 0.8399 data_time: 0.0282 memory: 16201 loss_prob: 0.4397 loss_thr: 0.3045 loss_db: 0.0767 loss: 0.8209 2022/08/30 15:32:38 - mmengine - INFO - Epoch(train) [705][25/63] lr: 3.1573e-03 eta: 10:55:00 time: 0.8149 data_time: 0.0249 memory: 16201 loss_prob: 0.4427 loss_thr: 0.3036 loss_db: 0.0767 loss: 0.8230 2022/08/30 15:32:43 - mmengine - INFO - Epoch(train) [705][30/63] lr: 3.1573e-03 eta: 10:54:45 time: 0.8526 data_time: 0.0266 memory: 16201 loss_prob: 0.4139 loss_thr: 0.2929 loss_db: 0.0724 loss: 0.7792 2022/08/30 15:32:47 - mmengine - INFO - Epoch(train) [705][35/63] lr: 3.1573e-03 eta: 10:54:45 time: 0.8797 data_time: 0.0355 memory: 16201 loss_prob: 0.3751 loss_thr: 0.2686 loss_db: 0.0681 loss: 0.7118 2022/08/30 15:32:51 - mmengine - INFO - Epoch(train) [705][40/63] lr: 3.1573e-03 eta: 10:54:29 time: 0.8417 data_time: 0.0224 memory: 16201 loss_prob: 0.4117 loss_thr: 0.2902 loss_db: 0.0719 loss: 0.7738 2022/08/30 15:32:56 - mmengine - INFO - Epoch(train) [705][45/63] lr: 3.1573e-03 eta: 10:54:29 time: 0.8514 data_time: 0.0256 memory: 16201 loss_prob: 0.5058 loss_thr: 0.3475 loss_db: 0.0848 loss: 0.9380 2022/08/30 15:33:00 - mmengine - INFO - Epoch(train) [705][50/63] lr: 3.1573e-03 eta: 10:54:14 time: 0.8479 data_time: 0.0334 memory: 16201 loss_prob: 0.4721 loss_thr: 0.3332 loss_db: 0.0811 loss: 0.8864 2022/08/30 15:33:04 - mmengine - INFO - Epoch(train) [705][55/63] lr: 3.1573e-03 eta: 10:54:14 time: 0.8435 data_time: 0.0241 memory: 16201 loss_prob: 0.4475 loss_thr: 0.3256 loss_db: 0.0791 loss: 0.8521 2022/08/30 15:33:08 - mmengine - INFO - Epoch(train) [705][60/63] lr: 3.1573e-03 eta: 10:53:58 time: 0.8453 data_time: 0.0303 memory: 16201 loss_prob: 0.4468 loss_thr: 0.3252 loss_db: 0.0779 loss: 0.8498 2022/08/30 15:33:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:33:16 - mmengine - INFO - Epoch(train) [706][5/63] lr: 3.1515e-03 eta: 10:53:58 time: 0.9549 data_time: 0.1961 memory: 16201 loss_prob: 0.4400 loss_thr: 0.3214 loss_db: 0.0786 loss: 0.8400 2022/08/30 15:33:21 - mmengine - INFO - Epoch(train) [706][10/63] lr: 3.1515e-03 eta: 10:53:38 time: 1.0453 data_time: 0.2133 memory: 16201 loss_prob: 0.4087 loss_thr: 0.3084 loss_db: 0.0717 loss: 0.7889 2022/08/30 15:33:25 - mmengine - INFO - Epoch(train) [706][15/63] lr: 3.1515e-03 eta: 10:53:38 time: 0.8436 data_time: 0.0256 memory: 16201 loss_prob: 0.4222 loss_thr: 0.3042 loss_db: 0.0740 loss: 0.8004 2022/08/30 15:33:29 - mmengine - INFO - Epoch(train) [706][20/63] lr: 3.1515e-03 eta: 10:53:22 time: 0.8211 data_time: 0.0175 memory: 16201 loss_prob: 0.4057 loss_thr: 0.2864 loss_db: 0.0702 loss: 0.7623 2022/08/30 15:33:33 - mmengine - INFO - Epoch(train) [706][25/63] lr: 3.1515e-03 eta: 10:53:22 time: 0.8625 data_time: 0.0269 memory: 16201 loss_prob: 0.3795 loss_thr: 0.2772 loss_db: 0.0654 loss: 0.7221 2022/08/30 15:33:37 - mmengine - INFO - Epoch(train) [706][30/63] lr: 3.1515e-03 eta: 10:53:07 time: 0.8423 data_time: 0.0262 memory: 16201 loss_prob: 0.4170 loss_thr: 0.2987 loss_db: 0.0731 loss: 0.7889 2022/08/30 15:33:42 - mmengine - INFO - Epoch(train) [706][35/63] lr: 3.1515e-03 eta: 10:53:07 time: 0.8248 data_time: 0.0278 memory: 16201 loss_prob: 0.4136 loss_thr: 0.2954 loss_db: 0.0736 loss: 0.7826 2022/08/30 15:33:46 - mmengine - INFO - Epoch(train) [706][40/63] lr: 3.1515e-03 eta: 10:52:52 time: 0.8928 data_time: 0.0250 memory: 16201 loss_prob: 0.3945 loss_thr: 0.2884 loss_db: 0.0687 loss: 0.7516 2022/08/30 15:33:51 - mmengine - INFO - Epoch(train) [706][45/63] lr: 3.1515e-03 eta: 10:52:52 time: 0.9178 data_time: 0.0296 memory: 16201 loss_prob: 0.4072 loss_thr: 0.2933 loss_db: 0.0707 loss: 0.7711 2022/08/30 15:33:55 - mmengine - INFO - Epoch(train) [706][50/63] lr: 3.1515e-03 eta: 10:52:36 time: 0.8556 data_time: 0.0318 memory: 16201 loss_prob: 0.3968 loss_thr: 0.2864 loss_db: 0.0700 loss: 0.7532 2022/08/30 15:33:59 - mmengine - INFO - Epoch(train) [706][55/63] lr: 3.1515e-03 eta: 10:52:36 time: 0.8222 data_time: 0.0220 memory: 16201 loss_prob: 0.4323 loss_thr: 0.3083 loss_db: 0.0762 loss: 0.8169 2022/08/30 15:34:04 - mmengine - INFO - Epoch(train) [706][60/63] lr: 3.1515e-03 eta: 10:52:21 time: 0.8913 data_time: 0.0241 memory: 16201 loss_prob: 0.4677 loss_thr: 0.3281 loss_db: 0.0834 loss: 0.8793 2022/08/30 15:34:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:34:12 - mmengine - INFO - Epoch(train) [707][5/63] lr: 3.1458e-03 eta: 10:52:21 time: 1.0779 data_time: 0.2115 memory: 16201 loss_prob: 0.4423 loss_thr: 0.3008 loss_db: 0.0733 loss: 0.8165 2022/08/30 15:34:16 - mmengine - INFO - Epoch(train) [707][10/63] lr: 3.1458e-03 eta: 10:52:00 time: 1.0153 data_time: 0.2210 memory: 16201 loss_prob: 0.4307 loss_thr: 0.3035 loss_db: 0.0742 loss: 0.8084 2022/08/30 15:34:22 - mmengine - INFO - Epoch(train) [707][15/63] lr: 3.1458e-03 eta: 10:52:00 time: 0.9134 data_time: 0.0313 memory: 16201 loss_prob: 0.4163 loss_thr: 0.2994 loss_db: 0.0741 loss: 0.7898 2022/08/30 15:34:26 - mmengine - INFO - Epoch(train) [707][20/63] lr: 3.1458e-03 eta: 10:51:45 time: 0.9045 data_time: 0.0332 memory: 16201 loss_prob: 0.4233 loss_thr: 0.3020 loss_db: 0.0741 loss: 0.7994 2022/08/30 15:34:30 - mmengine - INFO - Epoch(train) [707][25/63] lr: 3.1458e-03 eta: 10:51:45 time: 0.8141 data_time: 0.0280 memory: 16201 loss_prob: 0.4728 loss_thr: 0.3280 loss_db: 0.0819 loss: 0.8826 2022/08/30 15:34:34 - mmengine - INFO - Epoch(train) [707][30/63] lr: 3.1458e-03 eta: 10:51:30 time: 0.8399 data_time: 0.0241 memory: 16201 loss_prob: 0.4743 loss_thr: 0.3309 loss_db: 0.0820 loss: 0.8872 2022/08/30 15:34:38 - mmengine - INFO - Epoch(train) [707][35/63] lr: 3.1458e-03 eta: 10:51:30 time: 0.8387 data_time: 0.0258 memory: 16201 loss_prob: 0.4545 loss_thr: 0.3200 loss_db: 0.0793 loss: 0.8538 2022/08/30 15:34:42 - mmengine - INFO - Epoch(train) [707][40/63] lr: 3.1458e-03 eta: 10:51:14 time: 0.8331 data_time: 0.0252 memory: 16201 loss_prob: 0.4412 loss_thr: 0.3159 loss_db: 0.0785 loss: 0.8356 2022/08/30 15:34:46 - mmengine - INFO - Epoch(train) [707][45/63] lr: 3.1458e-03 eta: 10:51:14 time: 0.8428 data_time: 0.0303 memory: 16201 loss_prob: 0.3784 loss_thr: 0.2815 loss_db: 0.0685 loss: 0.7283 2022/08/30 15:34:51 - mmengine - INFO - Epoch(train) [707][50/63] lr: 3.1458e-03 eta: 10:50:59 time: 0.8458 data_time: 0.0292 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2748 loss_db: 0.0666 loss: 0.7218 2022/08/30 15:34:55 - mmengine - INFO - Epoch(train) [707][55/63] lr: 3.1458e-03 eta: 10:50:59 time: 0.8337 data_time: 0.0260 memory: 16201 loss_prob: 0.4088 loss_thr: 0.2933 loss_db: 0.0714 loss: 0.7734 2022/08/30 15:34:59 - mmengine - INFO - Epoch(train) [707][60/63] lr: 3.1458e-03 eta: 10:50:43 time: 0.8402 data_time: 0.0340 memory: 16201 loss_prob: 0.4135 loss_thr: 0.2988 loss_db: 0.0738 loss: 0.7861 2022/08/30 15:35:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:35:08 - mmengine - INFO - Epoch(train) [708][5/63] lr: 3.1401e-03 eta: 10:50:43 time: 1.0315 data_time: 0.2333 memory: 16201 loss_prob: 0.4089 loss_thr: 0.3001 loss_db: 0.0708 loss: 0.7798 2022/08/30 15:35:12 - mmengine - INFO - Epoch(train) [708][10/63] lr: 3.1401e-03 eta: 10:50:23 time: 1.0493 data_time: 0.2420 memory: 16201 loss_prob: 0.3956 loss_thr: 0.2903 loss_db: 0.0700 loss: 0.7559 2022/08/30 15:35:16 - mmengine - INFO - Epoch(train) [708][15/63] lr: 3.1401e-03 eta: 10:50:23 time: 0.8066 data_time: 0.0258 memory: 16201 loss_prob: 0.3824 loss_thr: 0.2832 loss_db: 0.0683 loss: 0.7340 2022/08/30 15:35:20 - mmengine - INFO - Epoch(train) [708][20/63] lr: 3.1401e-03 eta: 10:50:07 time: 0.7897 data_time: 0.0202 memory: 16201 loss_prob: 0.4330 loss_thr: 0.2958 loss_db: 0.0718 loss: 0.8006 2022/08/30 15:35:24 - mmengine - INFO - Epoch(train) [708][25/63] lr: 3.1401e-03 eta: 10:50:07 time: 0.7892 data_time: 0.0273 memory: 16201 loss_prob: 0.4370 loss_thr: 0.2947 loss_db: 0.0725 loss: 0.8043 2022/08/30 15:35:28 - mmengine - INFO - Epoch(train) [708][30/63] lr: 3.1401e-03 eta: 10:49:52 time: 0.8241 data_time: 0.0264 memory: 16201 loss_prob: 0.3988 loss_thr: 0.2863 loss_db: 0.0690 loss: 0.7541 2022/08/30 15:35:32 - mmengine - INFO - Epoch(train) [708][35/63] lr: 3.1401e-03 eta: 10:49:52 time: 0.8261 data_time: 0.0263 memory: 16201 loss_prob: 0.4138 loss_thr: 0.3049 loss_db: 0.0728 loss: 0.7916 2022/08/30 15:35:36 - mmengine - INFO - Epoch(train) [708][40/63] lr: 3.1401e-03 eta: 10:49:36 time: 0.7935 data_time: 0.0230 memory: 16201 loss_prob: 0.4358 loss_thr: 0.3036 loss_db: 0.0775 loss: 0.8170 2022/08/30 15:35:40 - mmengine - INFO - Epoch(train) [708][45/63] lr: 3.1401e-03 eta: 10:49:36 time: 0.8143 data_time: 0.0315 memory: 16201 loss_prob: 0.4334 loss_thr: 0.2964 loss_db: 0.0765 loss: 0.8063 2022/08/30 15:35:44 - mmengine - INFO - Epoch(train) [708][50/63] lr: 3.1401e-03 eta: 10:49:20 time: 0.8462 data_time: 0.0331 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2984 loss_db: 0.0737 loss: 0.7824 2022/08/30 15:35:48 - mmengine - INFO - Epoch(train) [708][55/63] lr: 3.1401e-03 eta: 10:49:20 time: 0.8359 data_time: 0.0224 memory: 16201 loss_prob: 0.4468 loss_thr: 0.3126 loss_db: 0.0813 loss: 0.8408 2022/08/30 15:35:54 - mmengine - INFO - Epoch(train) [708][60/63] lr: 3.1401e-03 eta: 10:49:06 time: 0.9308 data_time: 0.0340 memory: 16201 loss_prob: 0.4521 loss_thr: 0.3105 loss_db: 0.0808 loss: 0.8434 2022/08/30 15:35:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:36:01 - mmengine - INFO - Epoch(train) [709][5/63] lr: 3.1343e-03 eta: 10:49:06 time: 0.9323 data_time: 0.1573 memory: 16201 loss_prob: 0.3907 loss_thr: 0.2842 loss_db: 0.0692 loss: 0.7441 2022/08/30 15:36:06 - mmengine - INFO - Epoch(train) [709][10/63] lr: 3.1343e-03 eta: 10:48:45 time: 0.9710 data_time: 0.1680 memory: 16201 loss_prob: 0.4353 loss_thr: 0.3082 loss_db: 0.0778 loss: 0.8213 2022/08/30 15:36:09 - mmengine - INFO - Epoch(train) [709][15/63] lr: 3.1343e-03 eta: 10:48:45 time: 0.8110 data_time: 0.0236 memory: 16201 loss_prob: 0.4348 loss_thr: 0.3069 loss_db: 0.0776 loss: 0.8193 2022/08/30 15:36:14 - mmengine - INFO - Epoch(train) [709][20/63] lr: 3.1343e-03 eta: 10:48:29 time: 0.8687 data_time: 0.0227 memory: 16201 loss_prob: 0.4135 loss_thr: 0.2905 loss_db: 0.0729 loss: 0.7768 2022/08/30 15:36:18 - mmengine - INFO - Epoch(train) [709][25/63] lr: 3.1343e-03 eta: 10:48:29 time: 0.8854 data_time: 0.0348 memory: 16201 loss_prob: 0.4104 loss_thr: 0.2939 loss_db: 0.0716 loss: 0.7759 2022/08/30 15:36:22 - mmengine - INFO - Epoch(train) [709][30/63] lr: 3.1343e-03 eta: 10:48:14 time: 0.8020 data_time: 0.0242 memory: 16201 loss_prob: 0.3700 loss_thr: 0.2806 loss_db: 0.0658 loss: 0.7164 2022/08/30 15:36:27 - mmengine - INFO - Epoch(train) [709][35/63] lr: 3.1343e-03 eta: 10:48:14 time: 0.8251 data_time: 0.0230 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2923 loss_db: 0.0700 loss: 0.7468 2022/08/30 15:36:31 - mmengine - INFO - Epoch(train) [709][40/63] lr: 3.1343e-03 eta: 10:47:58 time: 0.8356 data_time: 0.0256 memory: 16201 loss_prob: 0.4357 loss_thr: 0.3060 loss_db: 0.0762 loss: 0.8179 2022/08/30 15:36:35 - mmengine - INFO - Epoch(train) [709][45/63] lr: 3.1343e-03 eta: 10:47:58 time: 0.8218 data_time: 0.0251 memory: 16201 loss_prob: 0.4588 loss_thr: 0.3123 loss_db: 0.0806 loss: 0.8517 2022/08/30 15:36:39 - mmengine - INFO - Epoch(train) [709][50/63] lr: 3.1343e-03 eta: 10:47:43 time: 0.8175 data_time: 0.0348 memory: 16201 loss_prob: 0.4627 loss_thr: 0.3270 loss_db: 0.0827 loss: 0.8724 2022/08/30 15:36:43 - mmengine - INFO - Epoch(train) [709][55/63] lr: 3.1343e-03 eta: 10:47:43 time: 0.8122 data_time: 0.0316 memory: 16201 loss_prob: 0.4581 loss_thr: 0.3216 loss_db: 0.0808 loss: 0.8605 2022/08/30 15:36:48 - mmengine - INFO - Epoch(train) [709][60/63] lr: 3.1343e-03 eta: 10:47:28 time: 0.8956 data_time: 0.0257 memory: 16201 loss_prob: 0.4466 loss_thr: 0.3132 loss_db: 0.0770 loss: 0.8367 2022/08/30 15:36:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:36:56 - mmengine - INFO - Epoch(train) [710][5/63] lr: 3.1286e-03 eta: 10:47:28 time: 1.0442 data_time: 0.2123 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2993 loss_db: 0.0716 loss: 0.7736 2022/08/30 15:37:00 - mmengine - INFO - Epoch(train) [710][10/63] lr: 3.1286e-03 eta: 10:47:07 time: 1.0112 data_time: 0.2168 memory: 16201 loss_prob: 0.4265 loss_thr: 0.3068 loss_db: 0.0750 loss: 0.8082 2022/08/30 15:37:04 - mmengine - INFO - Epoch(train) [710][15/63] lr: 3.1286e-03 eta: 10:47:07 time: 0.8294 data_time: 0.0278 memory: 16201 loss_prob: 0.4555 loss_thr: 0.3239 loss_db: 0.0787 loss: 0.8581 2022/08/30 15:37:08 - mmengine - INFO - Epoch(train) [710][20/63] lr: 3.1286e-03 eta: 10:46:51 time: 0.8250 data_time: 0.0284 memory: 16201 loss_prob: 0.4149 loss_thr: 0.2987 loss_db: 0.0715 loss: 0.7851 2022/08/30 15:37:12 - mmengine - INFO - Epoch(train) [710][25/63] lr: 3.1286e-03 eta: 10:46:51 time: 0.8389 data_time: 0.0293 memory: 16201 loss_prob: 0.4347 loss_thr: 0.2984 loss_db: 0.0741 loss: 0.8071 2022/08/30 15:37:17 - mmengine - INFO - Epoch(train) [710][30/63] lr: 3.1286e-03 eta: 10:46:36 time: 0.8536 data_time: 0.0285 memory: 16201 loss_prob: 0.4522 loss_thr: 0.3111 loss_db: 0.0783 loss: 0.8415 2022/08/30 15:37:21 - mmengine - INFO - Epoch(train) [710][35/63] lr: 3.1286e-03 eta: 10:46:36 time: 0.8503 data_time: 0.0332 memory: 16201 loss_prob: 0.4045 loss_thr: 0.2944 loss_db: 0.0727 loss: 0.7717 2022/08/30 15:37:25 - mmengine - INFO - Epoch(train) [710][40/63] lr: 3.1286e-03 eta: 10:46:21 time: 0.8570 data_time: 0.0298 memory: 16201 loss_prob: 0.4002 loss_thr: 0.2954 loss_db: 0.0721 loss: 0.7677 2022/08/30 15:37:29 - mmengine - INFO - Epoch(train) [710][45/63] lr: 3.1286e-03 eta: 10:46:21 time: 0.8318 data_time: 0.0276 memory: 16201 loss_prob: 0.4130 loss_thr: 0.2947 loss_db: 0.0732 loss: 0.7810 2022/08/30 15:37:34 - mmengine - INFO - Epoch(train) [710][50/63] lr: 3.1286e-03 eta: 10:46:05 time: 0.8229 data_time: 0.0276 memory: 16201 loss_prob: 0.4309 loss_thr: 0.2947 loss_db: 0.0757 loss: 0.8013 2022/08/30 15:37:38 - mmengine - INFO - Epoch(train) [710][55/63] lr: 3.1286e-03 eta: 10:46:05 time: 0.8202 data_time: 0.0242 memory: 16201 loss_prob: 0.4243 loss_thr: 0.2943 loss_db: 0.0758 loss: 0.7944 2022/08/30 15:37:42 - mmengine - INFO - Epoch(train) [710][60/63] lr: 3.1286e-03 eta: 10:45:50 time: 0.8616 data_time: 0.0219 memory: 16201 loss_prob: 0.4138 loss_thr: 0.2925 loss_db: 0.0750 loss: 0.7813 2022/08/30 15:37:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:37:50 - mmengine - INFO - Epoch(train) [711][5/63] lr: 3.1228e-03 eta: 10:45:50 time: 1.0341 data_time: 0.2214 memory: 16201 loss_prob: 0.4522 loss_thr: 0.3020 loss_db: 0.0787 loss: 0.8329 2022/08/30 15:37:55 - mmengine - INFO - Epoch(train) [711][10/63] lr: 3.1228e-03 eta: 10:45:30 time: 1.0547 data_time: 0.2306 memory: 16201 loss_prob: 0.4643 loss_thr: 0.3164 loss_db: 0.0793 loss: 0.8600 2022/08/30 15:37:59 - mmengine - INFO - Epoch(train) [711][15/63] lr: 3.1228e-03 eta: 10:45:30 time: 0.8565 data_time: 0.0276 memory: 16201 loss_prob: 0.4384 loss_thr: 0.3017 loss_db: 0.0793 loss: 0.8194 2022/08/30 15:38:03 - mmengine - INFO - Epoch(train) [711][20/63] lr: 3.1228e-03 eta: 10:45:14 time: 0.8363 data_time: 0.0274 memory: 16201 loss_prob: 0.4320 loss_thr: 0.3037 loss_db: 0.0767 loss: 0.8124 2022/08/30 15:38:07 - mmengine - INFO - Epoch(train) [711][25/63] lr: 3.1228e-03 eta: 10:45:14 time: 0.8477 data_time: 0.0355 memory: 16201 loss_prob: 0.4069 loss_thr: 0.2903 loss_db: 0.0692 loss: 0.7665 2022/08/30 15:38:12 - mmengine - INFO - Epoch(train) [711][30/63] lr: 3.1228e-03 eta: 10:44:59 time: 0.8561 data_time: 0.0247 memory: 16201 loss_prob: 0.4252 loss_thr: 0.3032 loss_db: 0.0744 loss: 0.8027 2022/08/30 15:38:16 - mmengine - INFO - Epoch(train) [711][35/63] lr: 3.1228e-03 eta: 10:44:59 time: 0.8460 data_time: 0.0244 memory: 16201 loss_prob: 0.4471 loss_thr: 0.3311 loss_db: 0.0806 loss: 0.8588 2022/08/30 15:38:20 - mmengine - INFO - Epoch(train) [711][40/63] lr: 3.1228e-03 eta: 10:44:43 time: 0.8219 data_time: 0.0235 memory: 16201 loss_prob: 0.4285 loss_thr: 0.3162 loss_db: 0.0761 loss: 0.8208 2022/08/30 15:38:24 - mmengine - INFO - Epoch(train) [711][45/63] lr: 3.1228e-03 eta: 10:44:43 time: 0.8302 data_time: 0.0210 memory: 16201 loss_prob: 0.4356 loss_thr: 0.3080 loss_db: 0.0761 loss: 0.8196 2022/08/30 15:38:28 - mmengine - INFO - Epoch(train) [711][50/63] lr: 3.1228e-03 eta: 10:44:28 time: 0.8310 data_time: 0.0221 memory: 16201 loss_prob: 0.4251 loss_thr: 0.3027 loss_db: 0.0757 loss: 0.8034 2022/08/30 15:38:33 - mmengine - INFO - Epoch(train) [711][55/63] lr: 3.1228e-03 eta: 10:44:28 time: 0.8650 data_time: 0.0269 memory: 16201 loss_prob: 0.4354 loss_thr: 0.3088 loss_db: 0.0773 loss: 0.8215 2022/08/30 15:38:37 - mmengine - INFO - Epoch(train) [711][60/63] lr: 3.1228e-03 eta: 10:44:13 time: 0.8780 data_time: 0.0394 memory: 16201 loss_prob: 0.4408 loss_thr: 0.3112 loss_db: 0.0764 loss: 0.8284 2022/08/30 15:38:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:38:45 - mmengine - INFO - Epoch(train) [712][5/63] lr: 3.1171e-03 eta: 10:44:13 time: 0.9529 data_time: 0.2024 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2902 loss_db: 0.0720 loss: 0.7726 2022/08/30 15:38:49 - mmengine - INFO - Epoch(train) [712][10/63] lr: 3.1171e-03 eta: 10:43:52 time: 1.0013 data_time: 0.2125 memory: 16201 loss_prob: 0.4396 loss_thr: 0.3111 loss_db: 0.0782 loss: 0.8289 2022/08/30 15:38:54 - mmengine - INFO - Epoch(train) [712][15/63] lr: 3.1171e-03 eta: 10:43:52 time: 0.9114 data_time: 0.0257 memory: 16201 loss_prob: 0.4499 loss_thr: 0.3126 loss_db: 0.0808 loss: 0.8433 2022/08/30 15:38:58 - mmengine - INFO - Epoch(train) [712][20/63] lr: 3.1171e-03 eta: 10:43:37 time: 0.9015 data_time: 0.0201 memory: 16201 loss_prob: 0.4618 loss_thr: 0.3135 loss_db: 0.0814 loss: 0.8567 2022/08/30 15:39:02 - mmengine - INFO - Epoch(train) [712][25/63] lr: 3.1171e-03 eta: 10:43:37 time: 0.8214 data_time: 0.0340 memory: 16201 loss_prob: 0.4894 loss_thr: 0.3235 loss_db: 0.0857 loss: 0.8986 2022/08/30 15:39:06 - mmengine - INFO - Epoch(train) [712][30/63] lr: 3.1171e-03 eta: 10:43:22 time: 0.8436 data_time: 0.0358 memory: 16201 loss_prob: 0.5093 loss_thr: 0.3295 loss_db: 0.0891 loss: 0.9279 2022/08/30 15:39:10 - mmengine - INFO - Epoch(train) [712][35/63] lr: 3.1171e-03 eta: 10:43:22 time: 0.8108 data_time: 0.0233 memory: 16201 loss_prob: 0.5227 loss_thr: 0.3395 loss_db: 0.0913 loss: 0.9534 2022/08/30 15:39:14 - mmengine - INFO - Epoch(train) [712][40/63] lr: 3.1171e-03 eta: 10:43:06 time: 0.7746 data_time: 0.0227 memory: 16201 loss_prob: 0.4457 loss_thr: 0.3061 loss_db: 0.0779 loss: 0.8297 2022/08/30 15:39:18 - mmengine - INFO - Epoch(train) [712][45/63] lr: 3.1171e-03 eta: 10:43:06 time: 0.7951 data_time: 0.0257 memory: 16201 loss_prob: 0.3767 loss_thr: 0.2714 loss_db: 0.0659 loss: 0.7140 2022/08/30 15:39:22 - mmengine - INFO - Epoch(train) [712][50/63] lr: 3.1171e-03 eta: 10:42:50 time: 0.8047 data_time: 0.0263 memory: 16201 loss_prob: 0.4057 loss_thr: 0.2818 loss_db: 0.0715 loss: 0.7590 2022/08/30 15:39:26 - mmengine - INFO - Epoch(train) [712][55/63] lr: 3.1171e-03 eta: 10:42:50 time: 0.7912 data_time: 0.0276 memory: 16201 loss_prob: 0.4079 loss_thr: 0.2805 loss_db: 0.0724 loss: 0.7609 2022/08/30 15:39:30 - mmengine - INFO - Epoch(train) [712][60/63] lr: 3.1171e-03 eta: 10:42:35 time: 0.8071 data_time: 0.0246 memory: 16201 loss_prob: 0.4643 loss_thr: 0.3081 loss_db: 0.0816 loss: 0.8540 2022/08/30 15:39:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:39:38 - mmengine - INFO - Epoch(train) [713][5/63] lr: 3.1113e-03 eta: 10:42:35 time: 0.9850 data_time: 0.2135 memory: 16201 loss_prob: 0.4464 loss_thr: 0.3000 loss_db: 0.0774 loss: 0.8237 2022/08/30 15:39:43 - mmengine - INFO - Epoch(train) [713][10/63] lr: 3.1113e-03 eta: 10:42:14 time: 1.0348 data_time: 0.2196 memory: 16201 loss_prob: 0.3764 loss_thr: 0.2732 loss_db: 0.0646 loss: 0.7142 2022/08/30 15:39:47 - mmengine - INFO - Epoch(train) [713][15/63] lr: 3.1113e-03 eta: 10:42:14 time: 0.8235 data_time: 0.0276 memory: 16201 loss_prob: 0.3635 loss_thr: 0.2656 loss_db: 0.0650 loss: 0.6941 2022/08/30 15:39:52 - mmengine - INFO - Epoch(train) [713][20/63] lr: 3.1113e-03 eta: 10:41:59 time: 0.9053 data_time: 0.0271 memory: 16201 loss_prob: 0.3994 loss_thr: 0.3023 loss_db: 0.0723 loss: 0.7741 2022/08/30 15:39:56 - mmengine - INFO - Epoch(train) [713][25/63] lr: 3.1113e-03 eta: 10:41:59 time: 0.9508 data_time: 0.0343 memory: 16201 loss_prob: 0.4522 loss_thr: 0.3317 loss_db: 0.0786 loss: 0.8626 2022/08/30 15:40:00 - mmengine - INFO - Epoch(train) [713][30/63] lr: 3.1113e-03 eta: 10:41:44 time: 0.8449 data_time: 0.0326 memory: 16201 loss_prob: 0.4572 loss_thr: 0.3197 loss_db: 0.0794 loss: 0.8563 2022/08/30 15:40:05 - mmengine - INFO - Epoch(train) [713][35/63] lr: 3.1113e-03 eta: 10:41:44 time: 0.8704 data_time: 0.0307 memory: 16201 loss_prob: 0.4285 loss_thr: 0.3006 loss_db: 0.0755 loss: 0.8046 2022/08/30 15:40:09 - mmengine - INFO - Epoch(train) [713][40/63] lr: 3.1113e-03 eta: 10:41:29 time: 0.8617 data_time: 0.0265 memory: 16201 loss_prob: 0.4424 loss_thr: 0.3127 loss_db: 0.0778 loss: 0.8329 2022/08/30 15:40:14 - mmengine - INFO - Epoch(train) [713][45/63] lr: 3.1113e-03 eta: 10:41:29 time: 0.9124 data_time: 0.0276 memory: 16201 loss_prob: 0.4469 loss_thr: 0.3166 loss_db: 0.0795 loss: 0.8431 2022/08/30 15:40:18 - mmengine - INFO - Epoch(train) [713][50/63] lr: 3.1113e-03 eta: 10:41:14 time: 0.9370 data_time: 0.0281 memory: 16201 loss_prob: 0.4111 loss_thr: 0.2912 loss_db: 0.0741 loss: 0.7764 2022/08/30 15:40:22 - mmengine - INFO - Epoch(train) [713][55/63] lr: 3.1113e-03 eta: 10:41:14 time: 0.8250 data_time: 0.0235 memory: 16201 loss_prob: 0.4227 loss_thr: 0.2997 loss_db: 0.0741 loss: 0.7966 2022/08/30 15:40:27 - mmengine - INFO - Epoch(train) [713][60/63] lr: 3.1113e-03 eta: 10:40:59 time: 0.8473 data_time: 0.0295 memory: 16201 loss_prob: 0.4431 loss_thr: 0.3118 loss_db: 0.0756 loss: 0.8305 2022/08/30 15:40:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:40:35 - mmengine - INFO - Epoch(train) [714][5/63] lr: 3.1056e-03 eta: 10:40:59 time: 0.9885 data_time: 0.2078 memory: 16201 loss_prob: 0.4383 loss_thr: 0.3044 loss_db: 0.0754 loss: 0.8181 2022/08/30 15:40:39 - mmengine - INFO - Epoch(train) [714][10/63] lr: 3.1056e-03 eta: 10:40:38 time: 1.0291 data_time: 0.2199 memory: 16201 loss_prob: 0.4453 loss_thr: 0.3260 loss_db: 0.0789 loss: 0.8502 2022/08/30 15:40:45 - mmengine - INFO - Epoch(train) [714][15/63] lr: 3.1056e-03 eta: 10:40:38 time: 0.9761 data_time: 0.1294 memory: 16201 loss_prob: 0.4397 loss_thr: 0.3255 loss_db: 0.0804 loss: 0.8456 2022/08/30 15:40:49 - mmengine - INFO - Epoch(train) [714][20/63] lr: 3.1056e-03 eta: 10:40:24 time: 0.9881 data_time: 0.1180 memory: 16201 loss_prob: 0.3855 loss_thr: 0.2729 loss_db: 0.0697 loss: 0.7281 2022/08/30 15:40:53 - mmengine - INFO - Epoch(train) [714][25/63] lr: 3.1056e-03 eta: 10:40:24 time: 0.8451 data_time: 0.0304 memory: 16201 loss_prob: 0.3880 loss_thr: 0.2721 loss_db: 0.0664 loss: 0.7265 2022/08/30 15:40:57 - mmengine - INFO - Epoch(train) [714][30/63] lr: 3.1056e-03 eta: 10:40:09 time: 0.8102 data_time: 0.0267 memory: 16201 loss_prob: 0.4412 loss_thr: 0.3177 loss_db: 0.0769 loss: 0.8358 2022/08/30 15:41:01 - mmengine - INFO - Epoch(train) [714][35/63] lr: 3.1056e-03 eta: 10:40:09 time: 0.7986 data_time: 0.0209 memory: 16201 loss_prob: 0.4431 loss_thr: 0.3174 loss_db: 0.0787 loss: 0.8392 2022/08/30 15:41:06 - mmengine - INFO - Epoch(train) [714][40/63] lr: 3.1056e-03 eta: 10:39:53 time: 0.8582 data_time: 0.0302 memory: 16201 loss_prob: 0.4433 loss_thr: 0.3060 loss_db: 0.0783 loss: 0.8275 2022/08/30 15:41:10 - mmengine - INFO - Epoch(train) [714][45/63] lr: 3.1056e-03 eta: 10:39:53 time: 0.9118 data_time: 0.0589 memory: 16201 loss_prob: 0.4282 loss_thr: 0.2967 loss_db: 0.0750 loss: 0.7999 2022/08/30 15:41:15 - mmengine - INFO - Epoch(train) [714][50/63] lr: 3.1056e-03 eta: 10:39:38 time: 0.8885 data_time: 0.0583 memory: 16201 loss_prob: 0.4188 loss_thr: 0.3016 loss_db: 0.0724 loss: 0.7928 2022/08/30 15:41:19 - mmengine - INFO - Epoch(train) [714][55/63] lr: 3.1056e-03 eta: 10:39:38 time: 0.8392 data_time: 0.0288 memory: 16201 loss_prob: 0.4349 loss_thr: 0.3240 loss_db: 0.0769 loss: 0.8359 2022/08/30 15:41:23 - mmengine - INFO - Epoch(train) [714][60/63] lr: 3.1056e-03 eta: 10:39:23 time: 0.8092 data_time: 0.0243 memory: 16201 loss_prob: 0.4183 loss_thr: 0.3102 loss_db: 0.0757 loss: 0.8041 2022/08/30 15:41:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:41:31 - mmengine - INFO - Epoch(train) [715][5/63] lr: 3.0998e-03 eta: 10:39:23 time: 0.9768 data_time: 0.1970 memory: 16201 loss_prob: 0.4349 loss_thr: 0.3279 loss_db: 0.0766 loss: 0.8395 2022/08/30 15:41:35 - mmengine - INFO - Epoch(train) [715][10/63] lr: 3.0998e-03 eta: 10:39:02 time: 1.0283 data_time: 0.2050 memory: 16201 loss_prob: 0.4240 loss_thr: 0.3147 loss_db: 0.0749 loss: 0.8137 2022/08/30 15:41:39 - mmengine - INFO - Epoch(train) [715][15/63] lr: 3.0998e-03 eta: 10:39:02 time: 0.8374 data_time: 0.0236 memory: 16201 loss_prob: 0.4064 loss_thr: 0.2904 loss_db: 0.0735 loss: 0.7703 2022/08/30 15:41:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:41:43 - mmengine - INFO - Epoch(train) [715][20/63] lr: 3.0998e-03 eta: 10:38:47 time: 0.8468 data_time: 0.0243 memory: 16201 loss_prob: 0.3996 loss_thr: 0.3016 loss_db: 0.0713 loss: 0.7725 2022/08/30 15:41:47 - mmengine - INFO - Epoch(train) [715][25/63] lr: 3.0998e-03 eta: 10:38:47 time: 0.8221 data_time: 0.0274 memory: 16201 loss_prob: 0.4428 loss_thr: 0.3247 loss_db: 0.0735 loss: 0.8411 2022/08/30 15:41:52 - mmengine - INFO - Epoch(train) [715][30/63] lr: 3.0998e-03 eta: 10:38:32 time: 0.8610 data_time: 0.0246 memory: 16201 loss_prob: 0.4528 loss_thr: 0.3130 loss_db: 0.0756 loss: 0.8415 2022/08/30 15:41:56 - mmengine - INFO - Epoch(train) [715][35/63] lr: 3.0998e-03 eta: 10:38:32 time: 0.8525 data_time: 0.0255 memory: 16201 loss_prob: 0.4095 loss_thr: 0.2831 loss_db: 0.0726 loss: 0.7653 2022/08/30 15:42:00 - mmengine - INFO - Epoch(train) [715][40/63] lr: 3.0998e-03 eta: 10:38:16 time: 0.7958 data_time: 0.0271 memory: 16201 loss_prob: 0.4466 loss_thr: 0.3164 loss_db: 0.0790 loss: 0.8420 2022/08/30 15:42:04 - mmengine - INFO - Epoch(train) [715][45/63] lr: 3.0998e-03 eta: 10:38:16 time: 0.8033 data_time: 0.0285 memory: 16201 loss_prob: 0.4846 loss_thr: 0.3346 loss_db: 0.0850 loss: 0.9042 2022/08/30 15:42:08 - mmengine - INFO - Epoch(train) [715][50/63] lr: 3.0998e-03 eta: 10:38:01 time: 0.7960 data_time: 0.0258 memory: 16201 loss_prob: 0.4480 loss_thr: 0.3039 loss_db: 0.0795 loss: 0.8314 2022/08/30 15:42:12 - mmengine - INFO - Epoch(train) [715][55/63] lr: 3.0998e-03 eta: 10:38:01 time: 0.8121 data_time: 0.0247 memory: 16201 loss_prob: 0.4473 loss_thr: 0.3139 loss_db: 0.0792 loss: 0.8404 2022/08/30 15:42:16 - mmengine - INFO - Epoch(train) [715][60/63] lr: 3.0998e-03 eta: 10:37:45 time: 0.8064 data_time: 0.0279 memory: 16201 loss_prob: 0.4526 loss_thr: 0.3375 loss_db: 0.0798 loss: 0.8699 2022/08/30 15:42:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:42:24 - mmengine - INFO - Epoch(train) [716][5/63] lr: 3.0941e-03 eta: 10:37:45 time: 0.9452 data_time: 0.1686 memory: 16201 loss_prob: 0.4537 loss_thr: 0.3263 loss_db: 0.0819 loss: 0.8618 2022/08/30 15:42:28 - mmengine - INFO - Epoch(train) [716][10/63] lr: 3.0941e-03 eta: 10:37:25 time: 1.0402 data_time: 0.1850 memory: 16201 loss_prob: 0.4658 loss_thr: 0.3285 loss_db: 0.0829 loss: 0.8772 2022/08/30 15:42:33 - mmengine - INFO - Epoch(train) [716][15/63] lr: 3.0941e-03 eta: 10:37:25 time: 0.9213 data_time: 0.0295 memory: 16201 loss_prob: 0.4054 loss_thr: 0.3055 loss_db: 0.0707 loss: 0.7816 2022/08/30 15:42:37 - mmengine - INFO - Epoch(train) [716][20/63] lr: 3.0941e-03 eta: 10:37:10 time: 0.9014 data_time: 0.0244 memory: 16201 loss_prob: 0.3785 loss_thr: 0.2789 loss_db: 0.0681 loss: 0.7255 2022/08/30 15:42:42 - mmengine - INFO - Epoch(train) [716][25/63] lr: 3.0941e-03 eta: 10:37:10 time: 0.8646 data_time: 0.0335 memory: 16201 loss_prob: 0.4094 loss_thr: 0.2892 loss_db: 0.0734 loss: 0.7719 2022/08/30 15:42:46 - mmengine - INFO - Epoch(train) [716][30/63] lr: 3.0941e-03 eta: 10:36:55 time: 0.8620 data_time: 0.0250 memory: 16201 loss_prob: 0.4910 loss_thr: 0.3201 loss_db: 0.0846 loss: 0.8957 2022/08/30 15:42:50 - mmengine - INFO - Epoch(train) [716][35/63] lr: 3.0941e-03 eta: 10:36:55 time: 0.8389 data_time: 0.0224 memory: 16201 loss_prob: 0.4585 loss_thr: 0.3045 loss_db: 0.0788 loss: 0.8417 2022/08/30 15:42:54 - mmengine - INFO - Epoch(train) [716][40/63] lr: 3.0941e-03 eta: 10:36:39 time: 0.8102 data_time: 0.0241 memory: 16201 loss_prob: 0.4143 loss_thr: 0.2959 loss_db: 0.0736 loss: 0.7838 2022/08/30 15:42:58 - mmengine - INFO - Epoch(train) [716][45/63] lr: 3.0941e-03 eta: 10:36:39 time: 0.7882 data_time: 0.0216 memory: 16201 loss_prob: 0.4599 loss_thr: 0.3205 loss_db: 0.0829 loss: 0.8633 2022/08/30 15:43:03 - mmengine - INFO - Epoch(train) [716][50/63] lr: 3.0941e-03 eta: 10:36:24 time: 0.8563 data_time: 0.0306 memory: 16201 loss_prob: 0.4541 loss_thr: 0.3069 loss_db: 0.0795 loss: 0.8405 2022/08/30 15:43:07 - mmengine - INFO - Epoch(train) [716][55/63] lr: 3.0941e-03 eta: 10:36:24 time: 0.8558 data_time: 0.0315 memory: 16201 loss_prob: 0.4071 loss_thr: 0.2826 loss_db: 0.0717 loss: 0.7613 2022/08/30 15:43:11 - mmengine - INFO - Epoch(train) [716][60/63] lr: 3.0941e-03 eta: 10:36:08 time: 0.7845 data_time: 0.0250 memory: 16201 loss_prob: 0.4303 loss_thr: 0.3049 loss_db: 0.0777 loss: 0.8129 2022/08/30 15:43:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:43:18 - mmengine - INFO - Epoch(train) [717][5/63] lr: 3.0883e-03 eta: 10:36:08 time: 0.9357 data_time: 0.2020 memory: 16201 loss_prob: 0.4351 loss_thr: 0.3049 loss_db: 0.0760 loss: 0.8160 2022/08/30 15:43:22 - mmengine - INFO - Epoch(train) [717][10/63] lr: 3.0883e-03 eta: 10:35:48 time: 0.9870 data_time: 0.2150 memory: 16201 loss_prob: 0.3982 loss_thr: 0.2881 loss_db: 0.0697 loss: 0.7559 2022/08/30 15:43:26 - mmengine - INFO - Epoch(train) [717][15/63] lr: 3.0883e-03 eta: 10:35:48 time: 0.7854 data_time: 0.0224 memory: 16201 loss_prob: 0.3987 loss_thr: 0.2934 loss_db: 0.0700 loss: 0.7620 2022/08/30 15:43:31 - mmengine - INFO - Epoch(train) [717][20/63] lr: 3.0883e-03 eta: 10:35:33 time: 0.8400 data_time: 0.0203 memory: 16201 loss_prob: 0.4270 loss_thr: 0.3132 loss_db: 0.0745 loss: 0.8146 2022/08/30 15:43:35 - mmengine - INFO - Epoch(train) [717][25/63] lr: 3.0883e-03 eta: 10:35:33 time: 0.8634 data_time: 0.0260 memory: 16201 loss_prob: 0.4178 loss_thr: 0.2986 loss_db: 0.0732 loss: 0.7896 2022/08/30 15:43:40 - mmengine - INFO - Epoch(train) [717][30/63] lr: 3.0883e-03 eta: 10:35:18 time: 0.8876 data_time: 0.0277 memory: 16201 loss_prob: 0.4439 loss_thr: 0.3009 loss_db: 0.0781 loss: 0.8229 2022/08/30 15:43:44 - mmengine - INFO - Epoch(train) [717][35/63] lr: 3.0883e-03 eta: 10:35:18 time: 0.9302 data_time: 0.0350 memory: 16201 loss_prob: 0.4799 loss_thr: 0.3218 loss_db: 0.0839 loss: 0.8856 2022/08/30 15:43:50 - mmengine - INFO - Epoch(train) [717][40/63] lr: 3.0883e-03 eta: 10:35:03 time: 0.9938 data_time: 0.0296 memory: 16201 loss_prob: 0.4650 loss_thr: 0.3160 loss_db: 0.0818 loss: 0.8628 2022/08/30 15:43:55 - mmengine - INFO - Epoch(train) [717][45/63] lr: 3.0883e-03 eta: 10:35:03 time: 1.0272 data_time: 0.0310 memory: 16201 loss_prob: 0.4128 loss_thr: 0.3035 loss_db: 0.0733 loss: 0.7896 2022/08/30 15:43:59 - mmengine - INFO - Epoch(train) [717][50/63] lr: 3.0883e-03 eta: 10:34:49 time: 0.9126 data_time: 0.0400 memory: 16201 loss_prob: 0.3754 loss_thr: 0.2906 loss_db: 0.0654 loss: 0.7314 2022/08/30 15:44:03 - mmengine - INFO - Epoch(train) [717][55/63] lr: 3.0883e-03 eta: 10:34:49 time: 0.8106 data_time: 0.0255 memory: 16201 loss_prob: 0.4238 loss_thr: 0.3158 loss_db: 0.0752 loss: 0.8149 2022/08/30 15:44:09 - mmengine - INFO - Epoch(train) [717][60/63] lr: 3.0883e-03 eta: 10:34:35 time: 1.0302 data_time: 0.0260 memory: 16201 loss_prob: 0.4447 loss_thr: 0.3150 loss_db: 0.0778 loss: 0.8375 2022/08/30 15:44:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:44:20 - mmengine - INFO - Epoch(train) [718][5/63] lr: 3.0826e-03 eta: 10:34:35 time: 1.3927 data_time: 0.2562 memory: 16201 loss_prob: 0.4340 loss_thr: 0.2959 loss_db: 0.0772 loss: 0.8070 2022/08/30 15:44:24 - mmengine - INFO - Epoch(train) [718][10/63] lr: 3.0826e-03 eta: 10:34:16 time: 1.2298 data_time: 0.2591 memory: 16201 loss_prob: 0.4944 loss_thr: 0.3205 loss_db: 0.0858 loss: 0.9007 2022/08/30 15:44:28 - mmengine - INFO - Epoch(train) [718][15/63] lr: 3.0826e-03 eta: 10:34:16 time: 0.8792 data_time: 0.0242 memory: 16201 loss_prob: 0.6860 loss_thr: 0.3523 loss_db: 0.1006 loss: 1.1389 2022/08/30 15:44:32 - mmengine - INFO - Epoch(train) [718][20/63] lr: 3.0826e-03 eta: 10:34:00 time: 0.8226 data_time: 0.0227 memory: 16201 loss_prob: 0.6229 loss_thr: 0.3315 loss_db: 0.0916 loss: 1.0460 2022/08/30 15:44:37 - mmengine - INFO - Epoch(train) [718][25/63] lr: 3.0826e-03 eta: 10:34:00 time: 0.8335 data_time: 0.0391 memory: 16201 loss_prob: 0.4295 loss_thr: 0.3148 loss_db: 0.0766 loss: 0.8210 2022/08/30 15:44:42 - mmengine - INFO - Epoch(train) [718][30/63] lr: 3.0826e-03 eta: 10:33:46 time: 0.9788 data_time: 0.0244 memory: 16201 loss_prob: 0.4667 loss_thr: 0.3255 loss_db: 0.0809 loss: 0.8731 2022/08/30 15:44:48 - mmengine - INFO - Epoch(train) [718][35/63] lr: 3.0826e-03 eta: 10:33:46 time: 1.0907 data_time: 0.0274 memory: 16201 loss_prob: 0.5299 loss_thr: 0.3302 loss_db: 0.0935 loss: 0.9536 2022/08/30 15:44:52 - mmengine - INFO - Epoch(train) [718][40/63] lr: 3.0826e-03 eta: 10:33:32 time: 1.0189 data_time: 0.0355 memory: 16201 loss_prob: 0.5253 loss_thr: 0.3320 loss_db: 0.0926 loss: 0.9500 2022/08/30 15:44:57 - mmengine - INFO - Epoch(train) [718][45/63] lr: 3.0826e-03 eta: 10:33:32 time: 0.8980 data_time: 0.0237 memory: 16201 loss_prob: 0.4643 loss_thr: 0.3231 loss_db: 0.0788 loss: 0.8663 2022/08/30 15:45:01 - mmengine - INFO - Epoch(train) [718][50/63] lr: 3.0826e-03 eta: 10:33:17 time: 0.8583 data_time: 0.0248 memory: 16201 loss_prob: 0.4238 loss_thr: 0.3045 loss_db: 0.0753 loss: 0.8036 2022/08/30 15:45:07 - mmengine - INFO - Epoch(train) [718][55/63] lr: 3.0826e-03 eta: 10:33:17 time: 1.0847 data_time: 0.0324 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2918 loss_db: 0.0717 loss: 0.7556 2022/08/30 15:45:13 - mmengine - INFO - Epoch(train) [718][60/63] lr: 3.0826e-03 eta: 10:33:04 time: 1.1980 data_time: 0.0383 memory: 16201 loss_prob: 0.3915 loss_thr: 0.2931 loss_db: 0.0693 loss: 0.7539 2022/08/30 15:45:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:45:23 - mmengine - INFO - Epoch(train) [719][5/63] lr: 3.0768e-03 eta: 10:33:04 time: 1.1862 data_time: 0.2256 memory: 16201 loss_prob: 0.4266 loss_thr: 0.3063 loss_db: 0.0746 loss: 0.8076 2022/08/30 15:45:28 - mmengine - INFO - Epoch(train) [719][10/63] lr: 3.0768e-03 eta: 10:32:44 time: 1.1643 data_time: 0.2285 memory: 16201 loss_prob: 0.4830 loss_thr: 0.3375 loss_db: 0.0832 loss: 0.9037 2022/08/30 15:45:36 - mmengine - INFO - Epoch(train) [719][15/63] lr: 3.0768e-03 eta: 10:32:44 time: 1.3786 data_time: 0.0298 memory: 16201 loss_prob: 0.4652 loss_thr: 0.3274 loss_db: 0.0807 loss: 0.8734 2022/08/30 15:45:44 - mmengine - INFO - Epoch(train) [719][20/63] lr: 3.0768e-03 eta: 10:32:34 time: 1.5962 data_time: 0.0376 memory: 16201 loss_prob: 0.4389 loss_thr: 0.3089 loss_db: 0.0784 loss: 0.8262 2022/08/30 15:45:50 - mmengine - INFO - Epoch(train) [719][25/63] lr: 3.0768e-03 eta: 10:32:34 time: 1.3249 data_time: 0.0377 memory: 16201 loss_prob: 0.4226 loss_thr: 0.3072 loss_db: 0.0768 loss: 0.8066 2022/08/30 15:45:56 - mmengine - INFO - Epoch(train) [719][30/63] lr: 3.0768e-03 eta: 10:32:21 time: 1.1802 data_time: 0.0332 memory: 16201 loss_prob: 0.4330 loss_thr: 0.3217 loss_db: 0.0773 loss: 0.8320 2022/08/30 15:46:03 - mmengine - INFO - Epoch(train) [719][35/63] lr: 3.0768e-03 eta: 10:32:21 time: 1.3478 data_time: 0.0353 memory: 16201 loss_prob: 0.4424 loss_thr: 0.3264 loss_db: 0.0774 loss: 0.8462 2022/08/30 15:46:09 - mmengine - INFO - Epoch(train) [719][40/63] lr: 3.0768e-03 eta: 10:32:10 time: 1.3688 data_time: 0.0356 memory: 16201 loss_prob: 0.4141 loss_thr: 0.3055 loss_db: 0.0737 loss: 0.7933 2022/08/30 15:46:16 - mmengine - INFO - Epoch(train) [719][45/63] lr: 3.0768e-03 eta: 10:32:10 time: 1.2446 data_time: 0.0383 memory: 16201 loss_prob: 0.4163 loss_thr: 0.2984 loss_db: 0.0733 loss: 0.7880 2022/08/30 15:46:20 - mmengine - INFO - Epoch(train) [719][50/63] lr: 3.0768e-03 eta: 10:31:56 time: 1.1131 data_time: 0.0331 memory: 16201 loss_prob: 0.3948 loss_thr: 0.2820 loss_db: 0.0695 loss: 0.7463 2022/08/30 15:46:27 - mmengine - INFO - Epoch(train) [719][55/63] lr: 3.0768e-03 eta: 10:31:56 time: 1.1505 data_time: 0.0311 memory: 16201 loss_prob: 0.3982 loss_thr: 0.2835 loss_db: 0.0714 loss: 0.7531 2022/08/30 15:46:36 - mmengine - INFO - Epoch(train) [719][60/63] lr: 3.0768e-03 eta: 10:31:45 time: 1.5152 data_time: 0.0676 memory: 16201 loss_prob: 0.4184 loss_thr: 0.3041 loss_db: 0.0742 loss: 0.7967 2022/08/30 15:46:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:46:46 - mmengine - INFO - Epoch(train) [720][5/63] lr: 3.0710e-03 eta: 10:31:45 time: 1.4052 data_time: 0.2459 memory: 16201 loss_prob: 0.4475 loss_thr: 0.3043 loss_db: 0.0781 loss: 0.8299 2022/08/30 15:46:50 - mmengine - INFO - Epoch(train) [720][10/63] lr: 3.0710e-03 eta: 10:31:25 time: 1.0511 data_time: 0.2347 memory: 16201 loss_prob: 0.4236 loss_thr: 0.2951 loss_db: 0.0736 loss: 0.7924 2022/08/30 15:46:58 - mmengine - INFO - Epoch(train) [720][15/63] lr: 3.0710e-03 eta: 10:31:25 time: 1.2191 data_time: 0.0337 memory: 16201 loss_prob: 0.4106 loss_thr: 0.2945 loss_db: 0.0718 loss: 0.7768 2022/08/30 15:47:07 - mmengine - INFO - Epoch(train) [720][20/63] lr: 3.0710e-03 eta: 10:31:15 time: 1.6351 data_time: 0.0396 memory: 16201 loss_prob: 0.4278 loss_thr: 0.2992 loss_db: 0.0752 loss: 0.8021 2022/08/30 15:47:12 - mmengine - INFO - Epoch(train) [720][25/63] lr: 3.0710e-03 eta: 10:31:15 time: 1.4031 data_time: 0.0542 memory: 16201 loss_prob: 0.4143 loss_thr: 0.2986 loss_db: 0.0733 loss: 0.7863 2022/08/30 15:47:16 - mmengine - INFO - Epoch(train) [720][30/63] lr: 3.0710e-03 eta: 10:31:01 time: 0.9459 data_time: 0.0312 memory: 16201 loss_prob: 0.3909 loss_thr: 0.2946 loss_db: 0.0694 loss: 0.7549 2022/08/30 15:47:21 - mmengine - INFO - Epoch(train) [720][35/63] lr: 3.0710e-03 eta: 10:31:01 time: 0.8716 data_time: 0.0227 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2783 loss_db: 0.0672 loss: 0.7234 2022/08/30 15:47:27 - mmengine - INFO - Epoch(train) [720][40/63] lr: 3.0710e-03 eta: 10:30:48 time: 1.1406 data_time: 0.0235 memory: 16201 loss_prob: 0.4134 loss_thr: 0.2930 loss_db: 0.0736 loss: 0.7799 2022/08/30 15:47:34 - mmengine - INFO - Epoch(train) [720][45/63] lr: 3.0710e-03 eta: 10:30:48 time: 1.3608 data_time: 0.0326 memory: 16201 loss_prob: 0.4654 loss_thr: 0.3211 loss_db: 0.0808 loss: 0.8674 2022/08/30 15:47:40 - mmengine - INFO - Epoch(train) [720][50/63] lr: 3.0710e-03 eta: 10:30:35 time: 1.2790 data_time: 0.0437 memory: 16201 loss_prob: 0.4622 loss_thr: 0.3207 loss_db: 0.0798 loss: 0.8627 2022/08/30 15:47:46 - mmengine - INFO - Epoch(train) [720][55/63] lr: 3.0710e-03 eta: 10:30:35 time: 1.1518 data_time: 0.0306 memory: 16201 loss_prob: 0.3909 loss_thr: 0.2827 loss_db: 0.0683 loss: 0.7419 2022/08/30 15:47:56 - mmengine - INFO - Epoch(train) [720][60/63] lr: 3.0710e-03 eta: 10:30:25 time: 1.5381 data_time: 0.0460 memory: 16201 loss_prob: 0.3998 loss_thr: 0.2811 loss_db: 0.0714 loss: 0.7522 2022/08/30 15:47:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:47:59 - mmengine - INFO - Saving checkpoint at 720 epochs 2022/08/30 15:48:08 - mmengine - INFO - Epoch(val) [720][5/32] eta: 10:30:25 time: 0.7177 data_time: 0.1491 memory: 16201 2022/08/30 15:48:11 - mmengine - INFO - Epoch(val) [720][10/32] eta: 0:00:17 time: 0.7790 data_time: 0.1564 memory: 15734 2022/08/30 15:48:14 - mmengine - INFO - Epoch(val) [720][15/32] eta: 0:00:17 time: 0.6158 data_time: 0.0390 memory: 15734 2022/08/30 15:48:18 - mmengine - INFO - Epoch(val) [720][20/32] eta: 0:00:07 time: 0.6382 data_time: 0.0571 memory: 15734 2022/08/30 15:48:22 - mmengine - INFO - Epoch(val) [720][25/32] eta: 0:00:07 time: 0.7601 data_time: 0.0773 memory: 15734 2022/08/30 15:48:25 - mmengine - INFO - Epoch(val) [720][30/32] eta: 0:00:01 time: 0.7853 data_time: 0.0813 memory: 15734 2022/08/30 15:48:26 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 15:48:26 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8498, precision: 0.7933, hmean: 0.8205 2022/08/30 15:48:26 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8498, precision: 0.8314, hmean: 0.8405 2022/08/30 15:48:26 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8493, precision: 0.8555, hmean: 0.8524 2022/08/30 15:48:26 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8469, precision: 0.8730, hmean: 0.8597 2022/08/30 15:48:26 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8349, precision: 0.8920, hmean: 0.8625 2022/08/30 15:48:26 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7896, precision: 0.9229, hmean: 0.8511 2022/08/30 15:48:26 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2961, precision: 0.9594, hmean: 0.4525 2022/08/30 15:48:26 - mmengine - INFO - Epoch(val) [720][32/32] icdar/precision: 0.8920 icdar/recall: 0.8349 icdar/hmean: 0.8625 2022/08/30 15:48:38 - mmengine - INFO - Epoch(train) [721][5/63] lr: 3.0653e-03 eta: 0:00:01 time: 1.7761 data_time: 0.3031 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2747 loss_db: 0.0676 loss: 0.7276 2022/08/30 15:48:44 - mmengine - INFO - Epoch(train) [721][10/63] lr: 3.0653e-03 eta: 10:30:09 time: 1.7374 data_time: 0.3163 memory: 16201 loss_prob: 0.3919 loss_thr: 0.2822 loss_db: 0.0674 loss: 0.7415 2022/08/30 15:48:49 - mmengine - INFO - Epoch(train) [721][15/63] lr: 3.0653e-03 eta: 10:30:09 time: 1.0765 data_time: 0.0397 memory: 16201 loss_prob: 0.4128 loss_thr: 0.2949 loss_db: 0.0728 loss: 0.7805 2022/08/30 15:48:54 - mmengine - INFO - Epoch(train) [721][20/63] lr: 3.0653e-03 eta: 10:29:55 time: 1.0313 data_time: 0.0342 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2657 loss_db: 0.0660 loss: 0.6983 2022/08/30 15:49:04 - mmengine - INFO - Epoch(train) [721][25/63] lr: 3.0653e-03 eta: 10:29:55 time: 1.4767 data_time: 0.0406 memory: 16201 loss_prob: 0.4147 loss_thr: 0.2858 loss_db: 0.0737 loss: 0.7742 2022/08/30 15:49:11 - mmengine - INFO - Epoch(train) [721][30/63] lr: 3.0653e-03 eta: 10:29:46 time: 1.7016 data_time: 0.0454 memory: 16201 loss_prob: 0.4423 loss_thr: 0.3081 loss_db: 0.0778 loss: 0.8282 2022/08/30 15:49:16 - mmengine - INFO - Epoch(train) [721][35/63] lr: 3.0653e-03 eta: 10:29:46 time: 1.2211 data_time: 0.0449 memory: 16201 loss_prob: 0.4050 loss_thr: 0.2931 loss_db: 0.0708 loss: 0.7689 2022/08/30 15:49:20 - mmengine - INFO - Epoch(train) [721][40/63] lr: 3.0653e-03 eta: 10:29:31 time: 0.9105 data_time: 0.0299 memory: 16201 loss_prob: 0.3816 loss_thr: 0.2711 loss_db: 0.0674 loss: 0.7201 2022/08/30 15:49:25 - mmengine - INFO - Epoch(train) [721][45/63] lr: 3.0653e-03 eta: 10:29:31 time: 0.9275 data_time: 0.0345 memory: 16201 loss_prob: 0.3973 loss_thr: 0.2846 loss_db: 0.0709 loss: 0.7528 2022/08/30 15:49:31 - mmengine - INFO - Epoch(train) [721][50/63] lr: 3.0653e-03 eta: 10:29:17 time: 1.0761 data_time: 0.0325 memory: 16201 loss_prob: 0.4128 loss_thr: 0.2959 loss_db: 0.0735 loss: 0.7822 2022/08/30 15:49:40 - mmengine - INFO - Epoch(train) [721][55/63] lr: 3.0653e-03 eta: 10:29:17 time: 1.4544 data_time: 0.0435 memory: 16201 loss_prob: 0.4402 loss_thr: 0.2971 loss_db: 0.0766 loss: 0.8139 2022/08/30 15:49:44 - mmengine - INFO - Epoch(train) [721][60/63] lr: 3.0653e-03 eta: 10:29:05 time: 1.3410 data_time: 0.0589 memory: 16201 loss_prob: 0.4542 loss_thr: 0.3042 loss_db: 0.0781 loss: 0.8364 2022/08/30 15:49:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:49:53 - mmengine - INFO - Epoch(train) [722][5/63] lr: 3.0595e-03 eta: 10:29:05 time: 1.0030 data_time: 0.2203 memory: 16201 loss_prob: 0.4388 loss_thr: 0.3029 loss_db: 0.0759 loss: 0.8177 2022/08/30 15:49:57 - mmengine - INFO - Epoch(train) [722][10/63] lr: 3.0595e-03 eta: 10:28:45 time: 1.0569 data_time: 0.2132 memory: 16201 loss_prob: 0.3990 loss_thr: 0.2771 loss_db: 0.0681 loss: 0.7441 2022/08/30 15:50:02 - mmengine - INFO - Epoch(train) [722][15/63] lr: 3.0595e-03 eta: 10:28:45 time: 0.9596 data_time: 0.0261 memory: 16201 loss_prob: 0.4101 loss_thr: 0.2952 loss_db: 0.0729 loss: 0.7782 2022/08/30 15:50:07 - mmengine - INFO - Epoch(train) [722][20/63] lr: 3.0595e-03 eta: 10:28:31 time: 0.9444 data_time: 0.0319 memory: 16201 loss_prob: 0.4161 loss_thr: 0.3019 loss_db: 0.0760 loss: 0.7940 2022/08/30 15:50:11 - mmengine - INFO - Epoch(train) [722][25/63] lr: 3.0595e-03 eta: 10:28:31 time: 0.8231 data_time: 0.0236 memory: 16201 loss_prob: 0.4165 loss_thr: 0.2942 loss_db: 0.0718 loss: 0.7826 2022/08/30 15:50:15 - mmengine - INFO - Epoch(train) [722][30/63] lr: 3.0595e-03 eta: 10:28:15 time: 0.8279 data_time: 0.0225 memory: 16201 loss_prob: 0.4493 loss_thr: 0.3125 loss_db: 0.0754 loss: 0.8372 2022/08/30 15:50:19 - mmengine - INFO - Epoch(train) [722][35/63] lr: 3.0595e-03 eta: 10:28:15 time: 0.8247 data_time: 0.0262 memory: 16201 loss_prob: 0.4472 loss_thr: 0.3173 loss_db: 0.0798 loss: 0.8442 2022/08/30 15:50:23 - mmengine - INFO - Epoch(train) [722][40/63] lr: 3.0595e-03 eta: 10:28:00 time: 0.8065 data_time: 0.0175 memory: 16201 loss_prob: 0.4183 loss_thr: 0.3004 loss_db: 0.0756 loss: 0.7943 2022/08/30 15:50:27 - mmengine - INFO - Epoch(train) [722][45/63] lr: 3.0595e-03 eta: 10:28:00 time: 0.8515 data_time: 0.0328 memory: 16201 loss_prob: 0.4158 loss_thr: 0.3023 loss_db: 0.0727 loss: 0.7908 2022/08/30 15:50:32 - mmengine - INFO - Epoch(train) [722][50/63] lr: 3.0595e-03 eta: 10:27:45 time: 0.8531 data_time: 0.0346 memory: 16201 loss_prob: 0.4670 loss_thr: 0.3055 loss_db: 0.0792 loss: 0.8517 2022/08/30 15:50:36 - mmengine - INFO - Epoch(train) [722][55/63] lr: 3.0595e-03 eta: 10:27:45 time: 0.8253 data_time: 0.0170 memory: 16201 loss_prob: 0.4606 loss_thr: 0.3048 loss_db: 0.0778 loss: 0.8432 2022/08/30 15:50:40 - mmengine - INFO - Epoch(train) [722][60/63] lr: 3.0595e-03 eta: 10:27:30 time: 0.8354 data_time: 0.0237 memory: 16201 loss_prob: 0.4419 loss_thr: 0.3206 loss_db: 0.0784 loss: 0.8409 2022/08/30 15:50:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:50:50 - mmengine - INFO - Epoch(train) [723][5/63] lr: 3.0538e-03 eta: 10:27:30 time: 1.1564 data_time: 0.2138 memory: 16201 loss_prob: 0.4105 loss_thr: 0.2944 loss_db: 0.0716 loss: 0.7766 2022/08/30 15:50:54 - mmengine - INFO - Epoch(train) [723][10/63] lr: 3.0538e-03 eta: 10:27:09 time: 1.0190 data_time: 0.2270 memory: 16201 loss_prob: 0.4146 loss_thr: 0.3018 loss_db: 0.0712 loss: 0.7876 2022/08/30 15:50:58 - mmengine - INFO - Epoch(train) [723][15/63] lr: 3.0538e-03 eta: 10:27:09 time: 0.8704 data_time: 0.0272 memory: 16201 loss_prob: 0.4175 loss_thr: 0.2979 loss_db: 0.0749 loss: 0.7902 2022/08/30 15:51:03 - mmengine - INFO - Epoch(train) [723][20/63] lr: 3.0538e-03 eta: 10:26:54 time: 0.8716 data_time: 0.0209 memory: 16201 loss_prob: 0.4112 loss_thr: 0.2899 loss_db: 0.0731 loss: 0.7742 2022/08/30 15:51:08 - mmengine - INFO - Epoch(train) [723][25/63] lr: 3.0538e-03 eta: 10:26:54 time: 0.9058 data_time: 0.0437 memory: 16201 loss_prob: 0.4698 loss_thr: 0.3235 loss_db: 0.0805 loss: 0.8738 2022/08/30 15:51:12 - mmengine - INFO - Epoch(train) [723][30/63] lr: 3.0538e-03 eta: 10:26:40 time: 0.9289 data_time: 0.0412 memory: 16201 loss_prob: 0.4692 loss_thr: 0.3183 loss_db: 0.0820 loss: 0.8696 2022/08/30 15:51:18 - mmengine - INFO - Epoch(train) [723][35/63] lr: 3.0538e-03 eta: 10:26:40 time: 1.0878 data_time: 0.0403 memory: 16201 loss_prob: 0.4496 loss_thr: 0.3079 loss_db: 0.0793 loss: 0.8368 2022/08/30 15:51:23 - mmengine - INFO - Epoch(train) [723][40/63] lr: 3.0538e-03 eta: 10:26:26 time: 1.1348 data_time: 0.0475 memory: 16201 loss_prob: 0.4514 loss_thr: 0.3134 loss_db: 0.0787 loss: 0.8435 2022/08/30 15:51:28 - mmengine - INFO - Epoch(train) [723][45/63] lr: 3.0538e-03 eta: 10:26:26 time: 0.9386 data_time: 0.0356 memory: 16201 loss_prob: 0.4132 loss_thr: 0.2898 loss_db: 0.0731 loss: 0.7761 2022/08/30 15:51:33 - mmengine - INFO - Epoch(train) [723][50/63] lr: 3.0538e-03 eta: 10:26:12 time: 0.9431 data_time: 0.0275 memory: 16201 loss_prob: 0.3934 loss_thr: 0.2713 loss_db: 0.0702 loss: 0.7349 2022/08/30 15:51:37 - mmengine - INFO - Epoch(train) [723][55/63] lr: 3.0538e-03 eta: 10:26:12 time: 0.8888 data_time: 0.0282 memory: 16201 loss_prob: 0.3931 loss_thr: 0.2804 loss_db: 0.0690 loss: 0.7425 2022/08/30 15:51:41 - mmengine - INFO - Epoch(train) [723][60/63] lr: 3.0538e-03 eta: 10:25:57 time: 0.8094 data_time: 0.0310 memory: 16201 loss_prob: 0.4185 loss_thr: 0.3066 loss_db: 0.0726 loss: 0.7977 2022/08/30 15:51:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:51:49 - mmengine - INFO - Epoch(train) [724][5/63] lr: 3.0480e-03 eta: 10:25:57 time: 1.0226 data_time: 0.2179 memory: 16201 loss_prob: 0.4279 loss_thr: 0.3012 loss_db: 0.0768 loss: 0.8060 2022/08/30 15:51:54 - mmengine - INFO - Epoch(train) [724][10/63] lr: 3.0480e-03 eta: 10:25:37 time: 1.0780 data_time: 0.2281 memory: 16201 loss_prob: 0.4135 loss_thr: 0.2923 loss_db: 0.0718 loss: 0.7776 2022/08/30 15:51:58 - mmengine - INFO - Epoch(train) [724][15/63] lr: 3.0480e-03 eta: 10:25:37 time: 0.8872 data_time: 0.0311 memory: 16201 loss_prob: 0.4238 loss_thr: 0.2988 loss_db: 0.0739 loss: 0.7964 2022/08/30 15:52:03 - mmengine - INFO - Epoch(train) [724][20/63] lr: 3.0480e-03 eta: 10:25:22 time: 0.8684 data_time: 0.0244 memory: 16201 loss_prob: 0.4252 loss_thr: 0.3086 loss_db: 0.0755 loss: 0.8092 2022/08/30 15:52:07 - mmengine - INFO - Epoch(train) [724][25/63] lr: 3.0480e-03 eta: 10:25:22 time: 0.8909 data_time: 0.0353 memory: 16201 loss_prob: 0.4181 loss_thr: 0.3034 loss_db: 0.0747 loss: 0.7962 2022/08/30 15:52:12 - mmengine - INFO - Epoch(train) [724][30/63] lr: 3.0480e-03 eta: 10:25:07 time: 0.8968 data_time: 0.0352 memory: 16201 loss_prob: 0.4061 loss_thr: 0.2883 loss_db: 0.0728 loss: 0.7672 2022/08/30 15:52:16 - mmengine - INFO - Epoch(train) [724][35/63] lr: 3.0480e-03 eta: 10:25:07 time: 0.8873 data_time: 0.0250 memory: 16201 loss_prob: 0.4068 loss_thr: 0.2835 loss_db: 0.0719 loss: 0.7623 2022/08/30 15:52:20 - mmengine - INFO - Epoch(train) [724][40/63] lr: 3.0480e-03 eta: 10:24:52 time: 0.8618 data_time: 0.0258 memory: 16201 loss_prob: 0.4098 loss_thr: 0.2855 loss_db: 0.0720 loss: 0.7673 2022/08/30 15:52:25 - mmengine - INFO - Epoch(train) [724][45/63] lr: 3.0480e-03 eta: 10:24:52 time: 0.9090 data_time: 0.0296 memory: 16201 loss_prob: 0.4228 loss_thr: 0.3001 loss_db: 0.0738 loss: 0.7967 2022/08/30 15:52:29 - mmengine - INFO - Epoch(train) [724][50/63] lr: 3.0480e-03 eta: 10:24:37 time: 0.9101 data_time: 0.0302 memory: 16201 loss_prob: 0.4210 loss_thr: 0.2971 loss_db: 0.0738 loss: 0.7919 2022/08/30 15:52:34 - mmengine - INFO - Epoch(train) [724][55/63] lr: 3.0480e-03 eta: 10:24:37 time: 0.8646 data_time: 0.0260 memory: 16201 loss_prob: 0.4236 loss_thr: 0.2924 loss_db: 0.0742 loss: 0.7902 2022/08/30 15:52:38 - mmengine - INFO - Epoch(train) [724][60/63] lr: 3.0480e-03 eta: 10:24:22 time: 0.8668 data_time: 0.0248 memory: 16201 loss_prob: 0.4425 loss_thr: 0.3042 loss_db: 0.0770 loss: 0.8236 2022/08/30 15:52:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:52:46 - mmengine - INFO - Epoch(train) [725][5/63] lr: 3.0422e-03 eta: 10:24:22 time: 0.9841 data_time: 0.1936 memory: 16201 loss_prob: 0.3930 loss_thr: 0.2785 loss_db: 0.0702 loss: 0.7417 2022/08/30 15:52:51 - mmengine - INFO - Epoch(train) [725][10/63] lr: 3.0422e-03 eta: 10:24:02 time: 1.0425 data_time: 0.2119 memory: 16201 loss_prob: 0.4229 loss_thr: 0.2992 loss_db: 0.0747 loss: 0.7967 2022/08/30 15:52:55 - mmengine - INFO - Epoch(train) [725][15/63] lr: 3.0422e-03 eta: 10:24:02 time: 0.9199 data_time: 0.0323 memory: 16201 loss_prob: 0.4158 loss_thr: 0.2952 loss_db: 0.0739 loss: 0.7848 2022/08/30 15:53:00 - mmengine - INFO - Epoch(train) [725][20/63] lr: 3.0422e-03 eta: 10:23:47 time: 0.9356 data_time: 0.0251 memory: 16201 loss_prob: 0.3940 loss_thr: 0.2988 loss_db: 0.0712 loss: 0.7641 2022/08/30 15:53:05 - mmengine - INFO - Epoch(train) [725][25/63] lr: 3.0422e-03 eta: 10:23:47 time: 0.9385 data_time: 0.0397 memory: 16201 loss_prob: 0.3754 loss_thr: 0.2862 loss_db: 0.0669 loss: 0.7285 2022/08/30 15:53:09 - mmengine - INFO - Epoch(train) [725][30/63] lr: 3.0422e-03 eta: 10:23:33 time: 0.8822 data_time: 0.0311 memory: 16201 loss_prob: 0.3864 loss_thr: 0.2716 loss_db: 0.0689 loss: 0.7268 2022/08/30 15:53:13 - mmengine - INFO - Epoch(train) [725][35/63] lr: 3.0422e-03 eta: 10:23:33 time: 0.8458 data_time: 0.0284 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2806 loss_db: 0.0723 loss: 0.7566 2022/08/30 15:53:17 - mmengine - INFO - Epoch(train) [725][40/63] lr: 3.0422e-03 eta: 10:23:18 time: 0.8566 data_time: 0.0342 memory: 16201 loss_prob: 0.4313 loss_thr: 0.3014 loss_db: 0.0752 loss: 0.8079 2022/08/30 15:53:22 - mmengine - INFO - Epoch(train) [725][45/63] lr: 3.0422e-03 eta: 10:23:18 time: 0.8452 data_time: 0.0304 memory: 16201 loss_prob: 0.4203 loss_thr: 0.2939 loss_db: 0.0736 loss: 0.7878 2022/08/30 15:53:26 - mmengine - INFO - Epoch(train) [725][50/63] lr: 3.0422e-03 eta: 10:23:02 time: 0.8538 data_time: 0.0305 memory: 16201 loss_prob: 0.3686 loss_thr: 0.2757 loss_db: 0.0667 loss: 0.7111 2022/08/30 15:53:30 - mmengine - INFO - Epoch(train) [725][55/63] lr: 3.0422e-03 eta: 10:23:02 time: 0.8653 data_time: 0.0236 memory: 16201 loss_prob: 0.3435 loss_thr: 0.2638 loss_db: 0.0608 loss: 0.6680 2022/08/30 15:53:35 - mmengine - INFO - Epoch(train) [725][60/63] lr: 3.0422e-03 eta: 10:22:48 time: 0.8830 data_time: 0.0256 memory: 16201 loss_prob: 0.3983 loss_thr: 0.2865 loss_db: 0.0703 loss: 0.7552 2022/08/30 15:53:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:53:43 - mmengine - INFO - Epoch(train) [726][5/63] lr: 3.0365e-03 eta: 10:22:48 time: 0.9904 data_time: 0.1772 memory: 16201 loss_prob: 0.4410 loss_thr: 0.3127 loss_db: 0.0801 loss: 0.8338 2022/08/30 15:53:47 - mmengine - INFO - Epoch(train) [726][10/63] lr: 3.0365e-03 eta: 10:22:28 time: 1.0557 data_time: 0.1948 memory: 16201 loss_prob: 0.4271 loss_thr: 0.3034 loss_db: 0.0753 loss: 0.8058 2022/08/30 15:53:51 - mmengine - INFO - Epoch(train) [726][15/63] lr: 3.0365e-03 eta: 10:22:28 time: 0.8281 data_time: 0.0326 memory: 16201 loss_prob: 0.3909 loss_thr: 0.2859 loss_db: 0.0689 loss: 0.7457 2022/08/30 15:53:56 - mmengine - INFO - Epoch(train) [726][20/63] lr: 3.0365e-03 eta: 10:22:13 time: 0.9139 data_time: 0.0299 memory: 16201 loss_prob: 0.3980 loss_thr: 0.2919 loss_db: 0.0711 loss: 0.7610 2022/08/30 15:54:01 - mmengine - INFO - Epoch(train) [726][25/63] lr: 3.0365e-03 eta: 10:22:13 time: 0.9532 data_time: 0.0374 memory: 16201 loss_prob: 0.4454 loss_thr: 0.3019 loss_db: 0.0773 loss: 0.8245 2022/08/30 15:54:05 - mmengine - INFO - Epoch(train) [726][30/63] lr: 3.0365e-03 eta: 10:21:58 time: 0.8673 data_time: 0.0287 memory: 16201 loss_prob: 0.4363 loss_thr: 0.2932 loss_db: 0.0746 loss: 0.8041 2022/08/30 15:54:09 - mmengine - INFO - Epoch(train) [726][35/63] lr: 3.0365e-03 eta: 10:21:58 time: 0.8437 data_time: 0.0218 memory: 16201 loss_prob: 0.4142 loss_thr: 0.2983 loss_db: 0.0720 loss: 0.7845 2022/08/30 15:54:14 - mmengine - INFO - Epoch(train) [726][40/63] lr: 3.0365e-03 eta: 10:21:43 time: 0.8633 data_time: 0.0252 memory: 16201 loss_prob: 0.4051 loss_thr: 0.2863 loss_db: 0.0725 loss: 0.7639 2022/08/30 15:54:18 - mmengine - INFO - Epoch(train) [726][45/63] lr: 3.0365e-03 eta: 10:21:43 time: 0.8710 data_time: 0.0307 memory: 16201 loss_prob: 0.4260 loss_thr: 0.3068 loss_db: 0.0757 loss: 0.8084 2022/08/30 15:54:23 - mmengine - INFO - Epoch(train) [726][50/63] lr: 3.0365e-03 eta: 10:21:28 time: 0.9318 data_time: 0.0324 memory: 16201 loss_prob: 0.4340 loss_thr: 0.3110 loss_db: 0.0771 loss: 0.8221 2022/08/30 15:54:28 - mmengine - INFO - Epoch(train) [726][55/63] lr: 3.0365e-03 eta: 10:21:28 time: 0.9511 data_time: 0.0302 memory: 16201 loss_prob: 0.3959 loss_thr: 0.2840 loss_db: 0.0694 loss: 0.7493 2022/08/30 15:54:32 - mmengine - INFO - Epoch(train) [726][60/63] lr: 3.0365e-03 eta: 10:21:13 time: 0.8662 data_time: 0.0339 memory: 16201 loss_prob: 0.4110 loss_thr: 0.2969 loss_db: 0.0723 loss: 0.7802 2022/08/30 15:54:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:54:41 - mmengine - INFO - Epoch(train) [727][5/63] lr: 3.0307e-03 eta: 10:21:13 time: 1.0678 data_time: 0.2315 memory: 16201 loss_prob: 0.4721 loss_thr: 0.3274 loss_db: 0.0829 loss: 0.8825 2022/08/30 15:54:45 - mmengine - INFO - Epoch(train) [727][10/63] lr: 3.0307e-03 eta: 10:20:54 time: 1.1113 data_time: 0.2419 memory: 16201 loss_prob: 0.4239 loss_thr: 0.3051 loss_db: 0.0751 loss: 0.8041 2022/08/30 15:54:50 - mmengine - INFO - Epoch(train) [727][15/63] lr: 3.0307e-03 eta: 10:20:54 time: 0.9122 data_time: 0.0345 memory: 16201 loss_prob: 0.4228 loss_thr: 0.2995 loss_db: 0.0751 loss: 0.7974 2022/08/30 15:54:55 - mmengine - INFO - Epoch(train) [727][20/63] lr: 3.0307e-03 eta: 10:20:40 time: 0.9674 data_time: 0.0341 memory: 16201 loss_prob: 0.4258 loss_thr: 0.3077 loss_db: 0.0759 loss: 0.8094 2022/08/30 15:54:59 - mmengine - INFO - Epoch(train) [727][25/63] lr: 3.0307e-03 eta: 10:20:40 time: 0.9560 data_time: 0.0439 memory: 16201 loss_prob: 0.4032 loss_thr: 0.2999 loss_db: 0.0707 loss: 0.7738 2022/08/30 15:55:04 - mmengine - INFO - Epoch(train) [727][30/63] lr: 3.0307e-03 eta: 10:20:25 time: 0.8794 data_time: 0.0310 memory: 16201 loss_prob: 0.3752 loss_thr: 0.2850 loss_db: 0.0648 loss: 0.7249 2022/08/30 15:55:08 - mmengine - INFO - Epoch(train) [727][35/63] lr: 3.0307e-03 eta: 10:20:25 time: 0.8719 data_time: 0.0369 memory: 16201 loss_prob: 0.3664 loss_thr: 0.2759 loss_db: 0.0650 loss: 0.7073 2022/08/30 15:55:13 - mmengine - INFO - Epoch(train) [727][40/63] lr: 3.0307e-03 eta: 10:20:10 time: 0.9786 data_time: 0.0807 memory: 16201 loss_prob: 0.3860 loss_thr: 0.2765 loss_db: 0.0683 loss: 0.7309 2022/08/30 15:55:18 - mmengine - INFO - Epoch(train) [727][45/63] lr: 3.0307e-03 eta: 10:20:10 time: 0.9622 data_time: 0.0694 memory: 16201 loss_prob: 0.3723 loss_thr: 0.2724 loss_db: 0.0654 loss: 0.7101 2022/08/30 15:55:22 - mmengine - INFO - Epoch(train) [727][50/63] lr: 3.0307e-03 eta: 10:19:56 time: 0.8827 data_time: 0.0461 memory: 16201 loss_prob: 0.3766 loss_thr: 0.2741 loss_db: 0.0670 loss: 0.7177 2022/08/30 15:55:27 - mmengine - INFO - Epoch(train) [727][55/63] lr: 3.0307e-03 eta: 10:19:56 time: 0.9431 data_time: 0.0857 memory: 16201 loss_prob: 0.4556 loss_thr: 0.3051 loss_db: 0.0774 loss: 0.8380 2022/08/30 15:55:31 - mmengine - INFO - Epoch(train) [727][60/63] lr: 3.0307e-03 eta: 10:19:41 time: 0.9213 data_time: 0.0842 memory: 16201 loss_prob: 0.4689 loss_thr: 0.3217 loss_db: 0.0791 loss: 0.8697 2022/08/30 15:55:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:55:40 - mmengine - INFO - Epoch(train) [728][5/63] lr: 3.0249e-03 eta: 10:19:41 time: 1.0057 data_time: 0.2396 memory: 16201 loss_prob: 0.4109 loss_thr: 0.2953 loss_db: 0.0736 loss: 0.7799 2022/08/30 15:55:44 - mmengine - INFO - Epoch(train) [728][10/63] lr: 3.0249e-03 eta: 10:19:21 time: 1.0672 data_time: 0.2822 memory: 16201 loss_prob: 0.3823 loss_thr: 0.2835 loss_db: 0.0677 loss: 0.7335 2022/08/30 15:55:49 - mmengine - INFO - Epoch(train) [728][15/63] lr: 3.0249e-03 eta: 10:19:21 time: 0.9007 data_time: 0.0802 memory: 16201 loss_prob: 0.3739 loss_thr: 0.2742 loss_db: 0.0661 loss: 0.7142 2022/08/30 15:55:53 - mmengine - INFO - Epoch(train) [728][20/63] lr: 3.0249e-03 eta: 10:19:06 time: 0.8867 data_time: 0.0452 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2663 loss_db: 0.0652 loss: 0.6936 2022/08/30 15:55:58 - mmengine - INFO - Epoch(train) [728][25/63] lr: 3.0249e-03 eta: 10:19:06 time: 0.8902 data_time: 0.0805 memory: 16201 loss_prob: 0.3985 loss_thr: 0.2885 loss_db: 0.0711 loss: 0.7581 2022/08/30 15:56:02 - mmengine - INFO - Epoch(train) [728][30/63] lr: 3.0249e-03 eta: 10:18:51 time: 0.8767 data_time: 0.0753 memory: 16201 loss_prob: 0.4284 loss_thr: 0.3056 loss_db: 0.0752 loss: 0.8091 2022/08/30 15:56:07 - mmengine - INFO - Epoch(train) [728][35/63] lr: 3.0249e-03 eta: 10:18:51 time: 0.9006 data_time: 0.0437 memory: 16201 loss_prob: 0.4462 loss_thr: 0.3094 loss_db: 0.0764 loss: 0.8320 2022/08/30 15:56:12 - mmengine - INFO - Epoch(train) [728][40/63] lr: 3.0249e-03 eta: 10:18:37 time: 0.9624 data_time: 0.0789 memory: 16201 loss_prob: 0.4317 loss_thr: 0.3017 loss_db: 0.0745 loss: 0.8078 2022/08/30 15:56:16 - mmengine - INFO - Epoch(train) [728][45/63] lr: 3.0249e-03 eta: 10:18:37 time: 0.9587 data_time: 0.0772 memory: 16201 loss_prob: 0.3951 loss_thr: 0.2894 loss_db: 0.0700 loss: 0.7544 2022/08/30 15:56:21 - mmengine - INFO - Epoch(train) [728][50/63] lr: 3.0249e-03 eta: 10:18:22 time: 0.9032 data_time: 0.0413 memory: 16201 loss_prob: 0.4079 loss_thr: 0.2887 loss_db: 0.0710 loss: 0.7677 2022/08/30 15:56:25 - mmengine - INFO - Epoch(train) [728][55/63] lr: 3.0249e-03 eta: 10:18:22 time: 0.8666 data_time: 0.0640 memory: 16201 loss_prob: 0.4233 loss_thr: 0.2807 loss_db: 0.0731 loss: 0.7771 2022/08/30 15:56:29 - mmengine - INFO - Epoch(train) [728][60/63] lr: 3.0249e-03 eta: 10:18:08 time: 0.8787 data_time: 0.0806 memory: 16201 loss_prob: 0.4596 loss_thr: 0.3080 loss_db: 0.0807 loss: 0.8483 2022/08/30 15:56:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:56:39 - mmengine - INFO - Epoch(train) [729][5/63] lr: 3.0192e-03 eta: 10:18:08 time: 1.0707 data_time: 0.2628 memory: 16201 loss_prob: 0.4395 loss_thr: 0.3107 loss_db: 0.0773 loss: 0.8275 2022/08/30 15:56:44 - mmengine - INFO - Epoch(train) [729][10/63] lr: 3.0192e-03 eta: 10:17:49 time: 1.2204 data_time: 0.2920 memory: 16201 loss_prob: 0.4443 loss_thr: 0.3079 loss_db: 0.0767 loss: 0.8289 2022/08/30 15:56:48 - mmengine - INFO - Epoch(train) [729][15/63] lr: 3.0192e-03 eta: 10:17:49 time: 0.9932 data_time: 0.0728 memory: 16201 loss_prob: 0.4226 loss_thr: 0.3020 loss_db: 0.0756 loss: 0.8001 2022/08/30 15:56:53 - mmengine - INFO - Epoch(train) [729][20/63] lr: 3.0192e-03 eta: 10:17:34 time: 0.8912 data_time: 0.0510 memory: 16201 loss_prob: 0.3920 loss_thr: 0.2795 loss_db: 0.0716 loss: 0.7432 2022/08/30 15:56:58 - mmengine - INFO - Epoch(train) [729][25/63] lr: 3.0192e-03 eta: 10:17:34 time: 0.9913 data_time: 0.0896 memory: 16201 loss_prob: 0.4271 loss_thr: 0.2924 loss_db: 0.0760 loss: 0.7954 2022/08/30 15:57:03 - mmengine - INFO - Epoch(train) [729][30/63] lr: 3.0192e-03 eta: 10:17:20 time: 0.9987 data_time: 0.0829 memory: 16201 loss_prob: 0.4031 loss_thr: 0.2915 loss_db: 0.0699 loss: 0.7645 2022/08/30 15:57:07 - mmengine - INFO - Epoch(train) [729][35/63] lr: 3.0192e-03 eta: 10:17:20 time: 0.8861 data_time: 0.0695 memory: 16201 loss_prob: 0.3998 loss_thr: 0.2984 loss_db: 0.0713 loss: 0.7695 2022/08/30 15:57:12 - mmengine - INFO - Epoch(train) [729][40/63] lr: 3.0192e-03 eta: 10:17:05 time: 0.8899 data_time: 0.0751 memory: 16201 loss_prob: 0.4421 loss_thr: 0.3131 loss_db: 0.0787 loss: 0.8339 2022/08/30 15:57:17 - mmengine - INFO - Epoch(train) [729][45/63] lr: 3.0192e-03 eta: 10:17:05 time: 0.9340 data_time: 0.0720 memory: 16201 loss_prob: 0.4195 loss_thr: 0.2892 loss_db: 0.0744 loss: 0.7831 2022/08/30 15:57:21 - mmengine - INFO - Epoch(train) [729][50/63] lr: 3.0192e-03 eta: 10:16:50 time: 0.8991 data_time: 0.0603 memory: 16201 loss_prob: 0.4008 loss_thr: 0.2813 loss_db: 0.0732 loss: 0.7553 2022/08/30 15:57:25 - mmengine - INFO - Epoch(train) [729][55/63] lr: 3.0192e-03 eta: 10:16:50 time: 0.8541 data_time: 0.0550 memory: 16201 loss_prob: 0.4128 loss_thr: 0.2903 loss_db: 0.0749 loss: 0.7780 2022/08/30 15:57:29 - mmengine - INFO - Epoch(train) [729][60/63] lr: 3.0192e-03 eta: 10:16:35 time: 0.8539 data_time: 0.0549 memory: 16201 loss_prob: 0.4279 loss_thr: 0.2968 loss_db: 0.0746 loss: 0.7993 2022/08/30 15:57:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:57:38 - mmengine - INFO - Epoch(train) [730][5/63] lr: 3.0134e-03 eta: 10:16:35 time: 1.0815 data_time: 0.2933 memory: 16201 loss_prob: 0.4293 loss_thr: 0.3006 loss_db: 0.0757 loss: 0.8056 2022/08/30 15:57:43 - mmengine - INFO - Epoch(train) [730][10/63] lr: 3.0134e-03 eta: 10:16:16 time: 1.1559 data_time: 0.2738 memory: 16201 loss_prob: 0.4580 loss_thr: 0.3184 loss_db: 0.0800 loss: 0.8564 2022/08/30 15:57:47 - mmengine - INFO - Epoch(train) [730][15/63] lr: 3.0134e-03 eta: 10:16:16 time: 0.8779 data_time: 0.0291 memory: 16201 loss_prob: 0.4599 loss_thr: 0.3122 loss_db: 0.0807 loss: 0.8528 2022/08/30 15:57:51 - mmengine - INFO - Epoch(train) [730][20/63] lr: 3.0134e-03 eta: 10:16:01 time: 0.8097 data_time: 0.0284 memory: 16201 loss_prob: 0.4571 loss_thr: 0.2681 loss_db: 0.0766 loss: 0.8017 2022/08/30 15:57:56 - mmengine - INFO - Epoch(train) [730][25/63] lr: 3.0134e-03 eta: 10:16:01 time: 0.8389 data_time: 0.0277 memory: 16201 loss_prob: 0.4677 loss_thr: 0.2787 loss_db: 0.0775 loss: 0.8239 2022/08/30 15:58:00 - mmengine - INFO - Epoch(train) [730][30/63] lr: 3.0134e-03 eta: 10:15:46 time: 0.8680 data_time: 0.0273 memory: 16201 loss_prob: 0.4332 loss_thr: 0.3089 loss_db: 0.0749 loss: 0.8171 2022/08/30 15:58:04 - mmengine - INFO - Epoch(train) [730][35/63] lr: 3.0134e-03 eta: 10:15:46 time: 0.8557 data_time: 0.0304 memory: 16201 loss_prob: 0.3938 loss_thr: 0.2931 loss_db: 0.0687 loss: 0.7556 2022/08/30 15:58:08 - mmengine - INFO - Epoch(train) [730][40/63] lr: 3.0134e-03 eta: 10:15:31 time: 0.8321 data_time: 0.0219 memory: 16201 loss_prob: 0.3852 loss_thr: 0.2764 loss_db: 0.0701 loss: 0.7316 2022/08/30 15:58:13 - mmengine - INFO - Epoch(train) [730][45/63] lr: 3.0134e-03 eta: 10:15:31 time: 0.8889 data_time: 0.0318 memory: 16201 loss_prob: 0.4007 loss_thr: 0.2819 loss_db: 0.0713 loss: 0.7538 2022/08/30 15:58:17 - mmengine - INFO - Epoch(train) [730][50/63] lr: 3.0134e-03 eta: 10:15:16 time: 0.9140 data_time: 0.0381 memory: 16201 loss_prob: 0.4186 loss_thr: 0.2885 loss_db: 0.0712 loss: 0.7783 2022/08/30 15:58:22 - mmengine - INFO - Epoch(train) [730][55/63] lr: 3.0134e-03 eta: 10:15:16 time: 0.8644 data_time: 0.0235 memory: 16201 loss_prob: 0.4363 loss_thr: 0.2935 loss_db: 0.0759 loss: 0.8057 2022/08/30 15:58:26 - mmengine - INFO - Epoch(train) [730][60/63] lr: 3.0134e-03 eta: 10:15:01 time: 0.8578 data_time: 0.0272 memory: 16201 loss_prob: 0.4548 loss_thr: 0.3158 loss_db: 0.0805 loss: 0.8510 2022/08/30 15:58:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:58:34 - mmengine - INFO - Epoch(train) [731][5/63] lr: 3.0076e-03 eta: 10:15:01 time: 0.9920 data_time: 0.1948 memory: 16201 loss_prob: 0.4275 loss_thr: 0.3070 loss_db: 0.0754 loss: 0.8098 2022/08/30 15:58:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:58:38 - mmengine - INFO - Epoch(train) [731][10/63] lr: 3.0076e-03 eta: 10:14:41 time: 1.0394 data_time: 0.2057 memory: 16201 loss_prob: 0.4348 loss_thr: 0.3109 loss_db: 0.0784 loss: 0.8241 2022/08/30 15:58:43 - mmengine - INFO - Epoch(train) [731][15/63] lr: 3.0076e-03 eta: 10:14:41 time: 0.8824 data_time: 0.0304 memory: 16201 loss_prob: 0.3803 loss_thr: 0.2780 loss_db: 0.0679 loss: 0.7263 2022/08/30 15:58:47 - mmengine - INFO - Epoch(train) [731][20/63] lr: 3.0076e-03 eta: 10:14:26 time: 0.8609 data_time: 0.0234 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2745 loss_db: 0.0663 loss: 0.7179 2022/08/30 15:58:51 - mmengine - INFO - Epoch(train) [731][25/63] lr: 3.0076e-03 eta: 10:14:26 time: 0.8534 data_time: 0.0327 memory: 16201 loss_prob: 0.4252 loss_thr: 0.3051 loss_db: 0.0749 loss: 0.8051 2022/08/30 15:58:56 - mmengine - INFO - Epoch(train) [731][30/63] lr: 3.0076e-03 eta: 10:14:12 time: 0.9325 data_time: 0.0349 memory: 16201 loss_prob: 0.4200 loss_thr: 0.3074 loss_db: 0.0746 loss: 0.8020 2022/08/30 15:59:01 - mmengine - INFO - Epoch(train) [731][35/63] lr: 3.0076e-03 eta: 10:14:12 time: 0.9152 data_time: 0.0321 memory: 16201 loss_prob: 0.3987 loss_thr: 0.2985 loss_db: 0.0703 loss: 0.7675 2022/08/30 15:59:05 - mmengine - INFO - Epoch(train) [731][40/63] lr: 3.0076e-03 eta: 10:13:57 time: 0.8242 data_time: 0.0284 memory: 16201 loss_prob: 0.4266 loss_thr: 0.3075 loss_db: 0.0757 loss: 0.8099 2022/08/30 15:59:09 - mmengine - INFO - Epoch(train) [731][45/63] lr: 3.0076e-03 eta: 10:13:57 time: 0.8108 data_time: 0.0279 memory: 16201 loss_prob: 0.4215 loss_thr: 0.2954 loss_db: 0.0751 loss: 0.7921 2022/08/30 15:59:13 - mmengine - INFO - Epoch(train) [731][50/63] lr: 3.0076e-03 eta: 10:13:42 time: 0.8460 data_time: 0.0260 memory: 16201 loss_prob: 0.4491 loss_thr: 0.3160 loss_db: 0.0792 loss: 0.8444 2022/08/30 15:59:17 - mmengine - INFO - Epoch(train) [731][55/63] lr: 3.0076e-03 eta: 10:13:42 time: 0.8732 data_time: 0.0288 memory: 16201 loss_prob: 0.4426 loss_thr: 0.3096 loss_db: 0.0793 loss: 0.8316 2022/08/30 15:59:22 - mmengine - INFO - Epoch(train) [731][60/63] lr: 3.0076e-03 eta: 10:13:27 time: 0.8808 data_time: 0.0330 memory: 16201 loss_prob: 0.4183 loss_thr: 0.2873 loss_db: 0.0733 loss: 0.7789 2022/08/30 15:59:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 15:59:30 - mmengine - INFO - Epoch(train) [732][5/63] lr: 3.0019e-03 eta: 10:13:27 time: 1.0273 data_time: 0.2335 memory: 16201 loss_prob: 0.4378 loss_thr: 0.3127 loss_db: 0.0750 loss: 0.8254 2022/08/30 15:59:35 - mmengine - INFO - Epoch(train) [732][10/63] lr: 3.0019e-03 eta: 10:13:07 time: 1.0421 data_time: 0.2423 memory: 16201 loss_prob: 0.4709 loss_thr: 0.3257 loss_db: 0.0827 loss: 0.8794 2022/08/30 15:59:39 - mmengine - INFO - Epoch(train) [732][15/63] lr: 3.0019e-03 eta: 10:13:07 time: 0.8252 data_time: 0.0275 memory: 16201 loss_prob: 0.4462 loss_thr: 0.3081 loss_db: 0.0807 loss: 0.8351 2022/08/30 15:59:43 - mmengine - INFO - Epoch(train) [732][20/63] lr: 3.0019e-03 eta: 10:12:52 time: 0.8236 data_time: 0.0266 memory: 16201 loss_prob: 0.4244 loss_thr: 0.2946 loss_db: 0.0758 loss: 0.7947 2022/08/30 15:59:47 - mmengine - INFO - Epoch(train) [732][25/63] lr: 3.0019e-03 eta: 10:12:52 time: 0.8299 data_time: 0.0311 memory: 16201 loss_prob: 0.4297 loss_thr: 0.3024 loss_db: 0.0743 loss: 0.8063 2022/08/30 15:59:51 - mmengine - INFO - Epoch(train) [732][30/63] lr: 3.0019e-03 eta: 10:12:37 time: 0.7956 data_time: 0.0240 memory: 16201 loss_prob: 0.4525 loss_thr: 0.3258 loss_db: 0.0785 loss: 0.8569 2022/08/30 15:59:55 - mmengine - INFO - Epoch(train) [732][35/63] lr: 3.0019e-03 eta: 10:12:37 time: 0.8577 data_time: 0.0205 memory: 16201 loss_prob: 0.4154 loss_thr: 0.3107 loss_db: 0.0735 loss: 0.7996 2022/08/30 16:00:00 - mmengine - INFO - Epoch(train) [732][40/63] lr: 3.0019e-03 eta: 10:12:22 time: 0.9121 data_time: 0.0269 memory: 16201 loss_prob: 0.4080 loss_thr: 0.2850 loss_db: 0.0707 loss: 0.7637 2022/08/30 16:00:04 - mmengine - INFO - Epoch(train) [732][45/63] lr: 3.0019e-03 eta: 10:12:22 time: 0.8726 data_time: 0.0353 memory: 16201 loss_prob: 0.4763 loss_thr: 0.3109 loss_db: 0.0802 loss: 0.8674 2022/08/30 16:00:09 - mmengine - INFO - Epoch(train) [732][50/63] lr: 3.0019e-03 eta: 10:12:07 time: 0.8606 data_time: 0.0286 memory: 16201 loss_prob: 0.5049 loss_thr: 0.3351 loss_db: 0.0857 loss: 0.9258 2022/08/30 16:00:13 - mmengine - INFO - Epoch(train) [732][55/63] lr: 3.0019e-03 eta: 10:12:07 time: 0.9117 data_time: 0.0657 memory: 16201 loss_prob: 0.4792 loss_thr: 0.3296 loss_db: 0.0809 loss: 0.8897 2022/08/30 16:00:18 - mmengine - INFO - Epoch(train) [732][60/63] lr: 3.0019e-03 eta: 10:11:53 time: 0.9649 data_time: 0.0924 memory: 16201 loss_prob: 0.4605 loss_thr: 0.3126 loss_db: 0.0785 loss: 0.8516 2022/08/30 16:00:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:00:27 - mmengine - INFO - Epoch(train) [733][5/63] lr: 2.9961e-03 eta: 10:11:53 time: 1.0449 data_time: 0.2273 memory: 16201 loss_prob: 0.4698 loss_thr: 0.3120 loss_db: 0.0807 loss: 0.8625 2022/08/30 16:00:31 - mmengine - INFO - Epoch(train) [733][10/63] lr: 2.9961e-03 eta: 10:11:33 time: 1.1100 data_time: 0.2458 memory: 16201 loss_prob: 0.4606 loss_thr: 0.3118 loss_db: 0.0786 loss: 0.8511 2022/08/30 16:00:36 - mmengine - INFO - Epoch(train) [733][15/63] lr: 2.9961e-03 eta: 10:11:33 time: 0.9104 data_time: 0.0384 memory: 16201 loss_prob: 0.4547 loss_thr: 0.3075 loss_db: 0.0775 loss: 0.8397 2022/08/30 16:00:40 - mmengine - INFO - Epoch(train) [733][20/63] lr: 2.9961e-03 eta: 10:11:19 time: 0.8914 data_time: 0.0233 memory: 16201 loss_prob: 0.4457 loss_thr: 0.2997 loss_db: 0.0786 loss: 0.8239 2022/08/30 16:00:45 - mmengine - INFO - Epoch(train) [733][25/63] lr: 2.9961e-03 eta: 10:11:19 time: 0.9249 data_time: 0.0328 memory: 16201 loss_prob: 0.4199 loss_thr: 0.2946 loss_db: 0.0751 loss: 0.7897 2022/08/30 16:00:51 - mmengine - INFO - Epoch(train) [733][30/63] lr: 2.9961e-03 eta: 10:11:05 time: 1.0353 data_time: 0.0301 memory: 16201 loss_prob: 0.4110 loss_thr: 0.3007 loss_db: 0.0721 loss: 0.7838 2022/08/30 16:00:55 - mmengine - INFO - Epoch(train) [733][35/63] lr: 2.9961e-03 eta: 10:11:05 time: 0.9999 data_time: 0.0383 memory: 16201 loss_prob: 0.4299 loss_thr: 0.3114 loss_db: 0.0759 loss: 0.8172 2022/08/30 16:00:59 - mmengine - INFO - Epoch(train) [733][40/63] lr: 2.9961e-03 eta: 10:10:50 time: 0.8811 data_time: 0.0279 memory: 16201 loss_prob: 0.4341 loss_thr: 0.3156 loss_db: 0.0773 loss: 0.8269 2022/08/30 16:01:04 - mmengine - INFO - Epoch(train) [733][45/63] lr: 2.9961e-03 eta: 10:10:50 time: 0.8827 data_time: 0.0195 memory: 16201 loss_prob: 0.4015 loss_thr: 0.2887 loss_db: 0.0736 loss: 0.7638 2022/08/30 16:01:10 - mmengine - INFO - Epoch(train) [733][50/63] lr: 2.9961e-03 eta: 10:10:36 time: 1.0444 data_time: 0.0465 memory: 16201 loss_prob: 0.3979 loss_thr: 0.2785 loss_db: 0.0716 loss: 0.7479 2022/08/30 16:01:15 - mmengine - INFO - Epoch(train) [733][55/63] lr: 2.9961e-03 eta: 10:10:36 time: 1.1341 data_time: 0.0395 memory: 16201 loss_prob: 0.4198 loss_thr: 0.2939 loss_db: 0.0731 loss: 0.7868 2022/08/30 16:01:21 - mmengine - INFO - Epoch(train) [733][60/63] lr: 2.9961e-03 eta: 10:10:23 time: 1.1158 data_time: 0.0294 memory: 16201 loss_prob: 0.4733 loss_thr: 0.3217 loss_db: 0.0837 loss: 0.8787 2022/08/30 16:01:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:01:30 - mmengine - INFO - Epoch(train) [734][5/63] lr: 2.9903e-03 eta: 10:10:23 time: 1.0659 data_time: 0.1980 memory: 16201 loss_prob: 0.4466 loss_thr: 0.3175 loss_db: 0.0796 loss: 0.8437 2022/08/30 16:01:34 - mmengine - INFO - Epoch(train) [734][10/63] lr: 2.9903e-03 eta: 10:10:03 time: 1.0380 data_time: 0.2103 memory: 16201 loss_prob: 0.4349 loss_thr: 0.3185 loss_db: 0.0772 loss: 0.8306 2022/08/30 16:01:39 - mmengine - INFO - Epoch(train) [734][15/63] lr: 2.9903e-03 eta: 10:10:03 time: 0.9726 data_time: 0.0268 memory: 16201 loss_prob: 0.4260 loss_thr: 0.3007 loss_db: 0.0756 loss: 0.8022 2022/08/30 16:01:46 - mmengine - INFO - Epoch(train) [734][20/63] lr: 2.9903e-03 eta: 10:09:50 time: 1.1722 data_time: 0.0340 memory: 16201 loss_prob: 0.3959 loss_thr: 0.2764 loss_db: 0.0696 loss: 0.7419 2022/08/30 16:01:50 - mmengine - INFO - Epoch(train) [734][25/63] lr: 2.9903e-03 eta: 10:09:50 time: 1.0703 data_time: 0.0408 memory: 16201 loss_prob: 0.4150 loss_thr: 0.3025 loss_db: 0.0738 loss: 0.7913 2022/08/30 16:01:54 - mmengine - INFO - Epoch(train) [734][30/63] lr: 2.9903e-03 eta: 10:09:36 time: 0.8645 data_time: 0.0301 memory: 16201 loss_prob: 0.4802 loss_thr: 0.3358 loss_db: 0.0855 loss: 0.9015 2022/08/30 16:02:00 - mmengine - INFO - Epoch(train) [734][35/63] lr: 2.9903e-03 eta: 10:09:36 time: 1.0029 data_time: 0.0335 memory: 16201 loss_prob: 0.4359 loss_thr: 0.3108 loss_db: 0.0769 loss: 0.8236 2022/08/30 16:02:07 - mmengine - INFO - Epoch(train) [734][40/63] lr: 2.9903e-03 eta: 10:09:23 time: 1.2664 data_time: 0.0315 memory: 16201 loss_prob: 0.4246 loss_thr: 0.2950 loss_db: 0.0773 loss: 0.7969 2022/08/30 16:02:12 - mmengine - INFO - Epoch(train) [734][45/63] lr: 2.9903e-03 eta: 10:09:23 time: 1.2275 data_time: 0.0426 memory: 16201 loss_prob: 0.4560 loss_thr: 0.3078 loss_db: 0.0816 loss: 0.8454 2022/08/30 16:02:17 - mmengine - INFO - Epoch(train) [734][50/63] lr: 2.9903e-03 eta: 10:09:10 time: 1.0447 data_time: 0.0466 memory: 16201 loss_prob: 0.4638 loss_thr: 0.3078 loss_db: 0.0785 loss: 0.8501 2022/08/30 16:02:22 - mmengine - INFO - Epoch(train) [734][55/63] lr: 2.9903e-03 eta: 10:09:10 time: 0.9380 data_time: 0.0250 memory: 16201 loss_prob: 0.4275 loss_thr: 0.2928 loss_db: 0.0736 loss: 0.7939 2022/08/30 16:02:26 - mmengine - INFO - Epoch(train) [734][60/63] lr: 2.9903e-03 eta: 10:08:55 time: 0.8703 data_time: 0.0246 memory: 16201 loss_prob: 0.3862 loss_thr: 0.2858 loss_db: 0.0682 loss: 0.7402 2022/08/30 16:02:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:02:35 - mmengine - INFO - Epoch(train) [735][5/63] lr: 2.9845e-03 eta: 10:08:55 time: 1.0915 data_time: 0.2327 memory: 16201 loss_prob: 0.4592 loss_thr: 0.3068 loss_db: 0.0797 loss: 0.8458 2022/08/30 16:02:41 - mmengine - INFO - Epoch(train) [735][10/63] lr: 2.9845e-03 eta: 10:08:36 time: 1.2952 data_time: 0.2333 memory: 16201 loss_prob: 0.4658 loss_thr: 0.3089 loss_db: 0.0798 loss: 0.8546 2022/08/30 16:02:47 - mmengine - INFO - Epoch(train) [735][15/63] lr: 2.9845e-03 eta: 10:08:36 time: 1.1608 data_time: 0.0421 memory: 16201 loss_prob: 0.4647 loss_thr: 0.3170 loss_db: 0.0787 loss: 0.8604 2022/08/30 16:02:53 - mmengine - INFO - Epoch(train) [735][20/63] lr: 2.9845e-03 eta: 10:08:23 time: 1.1437 data_time: 0.0527 memory: 16201 loss_prob: 0.4171 loss_thr: 0.3061 loss_db: 0.0736 loss: 0.7968 2022/08/30 16:02:57 - mmengine - INFO - Epoch(train) [735][25/63] lr: 2.9845e-03 eta: 10:08:23 time: 1.0186 data_time: 0.0396 memory: 16201 loss_prob: 0.4111 loss_thr: 0.3037 loss_db: 0.0750 loss: 0.7899 2022/08/30 16:03:02 - mmengine - INFO - Epoch(train) [735][30/63] lr: 2.9845e-03 eta: 10:08:09 time: 0.9081 data_time: 0.0295 memory: 16201 loss_prob: 0.3992 loss_thr: 0.2822 loss_db: 0.0705 loss: 0.7518 2022/08/30 16:03:07 - mmengine - INFO - Epoch(train) [735][35/63] lr: 2.9845e-03 eta: 10:08:09 time: 1.0030 data_time: 0.0345 memory: 16201 loss_prob: 0.3766 loss_thr: 0.2703 loss_db: 0.0657 loss: 0.7126 2022/08/30 16:03:12 - mmengine - INFO - Epoch(train) [735][40/63] lr: 2.9845e-03 eta: 10:07:55 time: 0.9977 data_time: 0.0356 memory: 16201 loss_prob: 0.4423 loss_thr: 0.3082 loss_db: 0.0780 loss: 0.8286 2022/08/30 16:03:19 - mmengine - INFO - Epoch(train) [735][45/63] lr: 2.9845e-03 eta: 10:07:55 time: 1.1813 data_time: 0.0372 memory: 16201 loss_prob: 0.4382 loss_thr: 0.3106 loss_db: 0.0784 loss: 0.8272 2022/08/30 16:03:24 - mmengine - INFO - Epoch(train) [735][50/63] lr: 2.9845e-03 eta: 10:07:42 time: 1.2621 data_time: 0.0404 memory: 16201 loss_prob: 0.3982 loss_thr: 0.2809 loss_db: 0.0707 loss: 0.7499 2022/08/30 16:03:29 - mmengine - INFO - Epoch(train) [735][55/63] lr: 2.9845e-03 eta: 10:07:42 time: 1.0184 data_time: 0.0318 memory: 16201 loss_prob: 0.4159 loss_thr: 0.2836 loss_db: 0.0719 loss: 0.7714 2022/08/30 16:03:34 - mmengine - INFO - Epoch(train) [735][60/63] lr: 2.9845e-03 eta: 10:07:28 time: 0.9641 data_time: 0.0373 memory: 16201 loss_prob: 0.4109 loss_thr: 0.3005 loss_db: 0.0710 loss: 0.7824 2022/08/30 16:03:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:03:43 - mmengine - INFO - Epoch(train) [736][5/63] lr: 2.9788e-03 eta: 10:07:28 time: 1.1522 data_time: 0.2495 memory: 16201 loss_prob: 0.4198 loss_thr: 0.2943 loss_db: 0.0743 loss: 0.7883 2022/08/30 16:03:50 - mmengine - INFO - Epoch(train) [736][10/63] lr: 2.9788e-03 eta: 10:07:11 time: 1.4171 data_time: 0.2560 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2774 loss_db: 0.0699 loss: 0.7425 2022/08/30 16:03:56 - mmengine - INFO - Epoch(train) [736][15/63] lr: 2.9788e-03 eta: 10:07:11 time: 1.2984 data_time: 0.0356 memory: 16201 loss_prob: 0.3911 loss_thr: 0.2839 loss_db: 0.0700 loss: 0.7450 2022/08/30 16:04:01 - mmengine - INFO - Epoch(train) [736][20/63] lr: 2.9788e-03 eta: 10:06:57 time: 1.0608 data_time: 0.0355 memory: 16201 loss_prob: 0.4029 loss_thr: 0.2942 loss_db: 0.0702 loss: 0.7672 2022/08/30 16:04:05 - mmengine - INFO - Epoch(train) [736][25/63] lr: 2.9788e-03 eta: 10:06:57 time: 0.8872 data_time: 0.0319 memory: 16201 loss_prob: 0.4214 loss_thr: 0.2970 loss_db: 0.0731 loss: 0.7915 2022/08/30 16:04:09 - mmengine - INFO - Epoch(train) [736][30/63] lr: 2.9788e-03 eta: 10:06:42 time: 0.8108 data_time: 0.0192 memory: 16201 loss_prob: 0.4393 loss_thr: 0.3005 loss_db: 0.0783 loss: 0.8181 2022/08/30 16:04:15 - mmengine - INFO - Epoch(train) [736][35/63] lr: 2.9788e-03 eta: 10:06:42 time: 0.9330 data_time: 0.0294 memory: 16201 loss_prob: 0.4225 loss_thr: 0.2953 loss_db: 0.0766 loss: 0.7944 2022/08/30 16:04:21 - mmengine - INFO - Epoch(train) [736][40/63] lr: 2.9788e-03 eta: 10:06:29 time: 1.1755 data_time: 0.0270 memory: 16201 loss_prob: 0.4274 loss_thr: 0.3182 loss_db: 0.0750 loss: 0.8206 2022/08/30 16:04:27 - mmengine - INFO - Epoch(train) [736][45/63] lr: 2.9788e-03 eta: 10:06:29 time: 1.2141 data_time: 0.0351 memory: 16201 loss_prob: 0.4397 loss_thr: 0.3324 loss_db: 0.0761 loss: 0.8482 2022/08/30 16:04:31 - mmengine - INFO - Epoch(train) [736][50/63] lr: 2.9788e-03 eta: 10:06:15 time: 1.0076 data_time: 0.0347 memory: 16201 loss_prob: 0.4270 loss_thr: 0.3099 loss_db: 0.0763 loss: 0.8132 2022/08/30 16:04:35 - mmengine - INFO - Epoch(train) [736][55/63] lr: 2.9788e-03 eta: 10:06:15 time: 0.8527 data_time: 0.0209 memory: 16201 loss_prob: 0.4217 loss_thr: 0.2987 loss_db: 0.0735 loss: 0.7939 2022/08/30 16:04:40 - mmengine - INFO - Epoch(train) [736][60/63] lr: 2.9788e-03 eta: 10:06:01 time: 0.9154 data_time: 0.0302 memory: 16201 loss_prob: 0.4038 loss_thr: 0.2885 loss_db: 0.0709 loss: 0.7631 2022/08/30 16:04:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:04:51 - mmengine - INFO - Epoch(train) [737][5/63] lr: 2.9730e-03 eta: 10:06:01 time: 1.3235 data_time: 0.2373 memory: 16201 loss_prob: 0.4753 loss_thr: 0.3263 loss_db: 0.0839 loss: 0.8855 2022/08/30 16:04:57 - mmengine - INFO - Epoch(train) [737][10/63] lr: 2.9730e-03 eta: 10:05:43 time: 1.3467 data_time: 0.2546 memory: 16201 loss_prob: 0.4432 loss_thr: 0.3243 loss_db: 0.0777 loss: 0.8453 2022/08/30 16:05:01 - mmengine - INFO - Epoch(train) [737][15/63] lr: 2.9730e-03 eta: 10:05:43 time: 0.9866 data_time: 0.0309 memory: 16201 loss_prob: 0.4239 loss_thr: 0.3134 loss_db: 0.0740 loss: 0.8112 2022/08/30 16:05:06 - mmengine - INFO - Epoch(train) [737][20/63] lr: 2.9730e-03 eta: 10:05:28 time: 0.8800 data_time: 0.0239 memory: 16201 loss_prob: 0.4293 loss_thr: 0.3007 loss_db: 0.0755 loss: 0.8055 2022/08/30 16:05:11 - mmengine - INFO - Epoch(train) [737][25/63] lr: 2.9730e-03 eta: 10:05:28 time: 1.0265 data_time: 0.0479 memory: 16201 loss_prob: 0.4112 loss_thr: 0.2898 loss_db: 0.0711 loss: 0.7720 2022/08/30 16:05:17 - mmengine - INFO - Epoch(train) [737][30/63] lr: 2.9730e-03 eta: 10:05:15 time: 1.1310 data_time: 0.0373 memory: 16201 loss_prob: 0.3993 loss_thr: 0.2913 loss_db: 0.0699 loss: 0.7605 2022/08/30 16:05:23 - mmengine - INFO - Epoch(train) [737][35/63] lr: 2.9730e-03 eta: 10:05:15 time: 1.1556 data_time: 0.0297 memory: 16201 loss_prob: 0.4044 loss_thr: 0.2878 loss_db: 0.0725 loss: 0.7647 2022/08/30 16:05:29 - mmengine - INFO - Epoch(train) [737][40/63] lr: 2.9730e-03 eta: 10:05:02 time: 1.1510 data_time: 0.0375 memory: 16201 loss_prob: 0.4095 loss_thr: 0.2935 loss_db: 0.0718 loss: 0.7748 2022/08/30 16:05:34 - mmengine - INFO - Epoch(train) [737][45/63] lr: 2.9730e-03 eta: 10:05:02 time: 1.1019 data_time: 0.0412 memory: 16201 loss_prob: 0.4158 loss_thr: 0.3011 loss_db: 0.0731 loss: 0.7900 2022/08/30 16:05:38 - mmengine - INFO - Epoch(train) [737][50/63] lr: 2.9730e-03 eta: 10:04:48 time: 0.9463 data_time: 0.0423 memory: 16201 loss_prob: 0.4323 loss_thr: 0.3017 loss_db: 0.0797 loss: 0.8138 2022/08/30 16:05:42 - mmengine - INFO - Epoch(train) [737][55/63] lr: 2.9730e-03 eta: 10:04:48 time: 0.8447 data_time: 0.0219 memory: 16201 loss_prob: 0.4572 loss_thr: 0.3120 loss_db: 0.0818 loss: 0.8511 2022/08/30 16:05:47 - mmengine - INFO - Epoch(train) [737][60/63] lr: 2.9730e-03 eta: 10:04:33 time: 0.9228 data_time: 0.0300 memory: 16201 loss_prob: 0.4621 loss_thr: 0.3199 loss_db: 0.0792 loss: 0.8612 2022/08/30 16:05:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:05:56 - mmengine - INFO - Epoch(train) [738][5/63] lr: 2.9672e-03 eta: 10:04:33 time: 1.0956 data_time: 0.2326 memory: 16201 loss_prob: 0.3978 loss_thr: 0.2900 loss_db: 0.0697 loss: 0.7575 2022/08/30 16:06:03 - mmengine - INFO - Epoch(train) [738][10/63] lr: 2.9672e-03 eta: 10:04:15 time: 1.3207 data_time: 0.2427 memory: 16201 loss_prob: 0.4286 loss_thr: 0.3030 loss_db: 0.0751 loss: 0.8067 2022/08/30 16:06:10 - mmengine - INFO - Epoch(train) [738][15/63] lr: 2.9672e-03 eta: 10:04:15 time: 1.3488 data_time: 0.0699 memory: 16201 loss_prob: 0.4216 loss_thr: 0.3018 loss_db: 0.0734 loss: 0.7969 2022/08/30 16:06:16 - mmengine - INFO - Epoch(train) [738][20/63] lr: 2.9672e-03 eta: 10:04:03 time: 1.3055 data_time: 0.0744 memory: 16201 loss_prob: 0.4485 loss_thr: 0.3211 loss_db: 0.0779 loss: 0.8474 2022/08/30 16:06:22 - mmengine - INFO - Epoch(train) [738][25/63] lr: 2.9672e-03 eta: 10:04:03 time: 1.2200 data_time: 0.0382 memory: 16201 loss_prob: 0.4111 loss_thr: 0.2956 loss_db: 0.0726 loss: 0.7794 2022/08/30 16:06:28 - mmengine - INFO - Epoch(train) [738][30/63] lr: 2.9672e-03 eta: 10:03:50 time: 1.1866 data_time: 0.0324 memory: 16201 loss_prob: 0.3770 loss_thr: 0.2817 loss_db: 0.0657 loss: 0.7245 2022/08/30 16:06:32 - mmengine - INFO - Epoch(train) [738][35/63] lr: 2.9672e-03 eta: 10:03:50 time: 0.9897 data_time: 0.0371 memory: 16201 loss_prob: 0.3864 loss_thr: 0.2849 loss_db: 0.0675 loss: 0.7387 2022/08/30 16:06:36 - mmengine - INFO - Epoch(train) [738][40/63] lr: 2.9672e-03 eta: 10:03:36 time: 0.8743 data_time: 0.0207 memory: 16201 loss_prob: 0.3875 loss_thr: 0.2821 loss_db: 0.0693 loss: 0.7389 2022/08/30 16:06:41 - mmengine - INFO - Epoch(train) [738][45/63] lr: 2.9672e-03 eta: 10:03:36 time: 0.8702 data_time: 0.0313 memory: 16201 loss_prob: 0.3963 loss_thr: 0.2876 loss_db: 0.0719 loss: 0.7558 2022/08/30 16:06:45 - mmengine - INFO - Epoch(train) [738][50/63] lr: 2.9672e-03 eta: 10:03:21 time: 0.8759 data_time: 0.0389 memory: 16201 loss_prob: 0.4218 loss_thr: 0.3044 loss_db: 0.0732 loss: 0.7994 2022/08/30 16:06:50 - mmengine - INFO - Epoch(train) [738][55/63] lr: 2.9672e-03 eta: 10:03:21 time: 0.9536 data_time: 0.0242 memory: 16201 loss_prob: 0.4217 loss_thr: 0.3025 loss_db: 0.0731 loss: 0.7973 2022/08/30 16:06:58 - mmengine - INFO - Epoch(train) [738][60/63] lr: 2.9672e-03 eta: 10:03:09 time: 1.2884 data_time: 0.0391 memory: 16201 loss_prob: 0.3759 loss_thr: 0.2743 loss_db: 0.0676 loss: 0.7179 2022/08/30 16:07:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:07:09 - mmengine - INFO - Epoch(train) [739][5/63] lr: 2.9614e-03 eta: 10:03:09 time: 1.4139 data_time: 0.2260 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2641 loss_db: 0.0649 loss: 0.6909 2022/08/30 16:07:16 - mmengine - INFO - Epoch(train) [739][10/63] lr: 2.9614e-03 eta: 10:02:52 time: 1.5161 data_time: 0.2450 memory: 16201 loss_prob: 0.3988 loss_thr: 0.2895 loss_db: 0.0700 loss: 0.7584 2022/08/30 16:07:22 - mmengine - INFO - Epoch(train) [739][15/63] lr: 2.9614e-03 eta: 10:02:52 time: 1.2747 data_time: 0.0433 memory: 16201 loss_prob: 0.4334 loss_thr: 0.3040 loss_db: 0.0756 loss: 0.8131 2022/08/30 16:07:27 - mmengine - INFO - Epoch(train) [739][20/63] lr: 2.9614e-03 eta: 10:02:38 time: 1.0710 data_time: 0.0370 memory: 16201 loss_prob: 0.4577 loss_thr: 0.3086 loss_db: 0.0790 loss: 0.8453 2022/08/30 16:07:32 - mmengine - INFO - Epoch(train) [739][25/63] lr: 2.9614e-03 eta: 10:02:38 time: 0.9537 data_time: 0.0318 memory: 16201 loss_prob: 0.4250 loss_thr: 0.2953 loss_db: 0.0752 loss: 0.7955 2022/08/30 16:07:37 - mmengine - INFO - Epoch(train) [739][30/63] lr: 2.9614e-03 eta: 10:02:25 time: 1.0545 data_time: 0.0267 memory: 16201 loss_prob: 0.3981 loss_thr: 0.2803 loss_db: 0.0729 loss: 0.7513 2022/08/30 16:07:43 - mmengine - INFO - Epoch(train) [739][35/63] lr: 2.9614e-03 eta: 10:02:25 time: 1.1266 data_time: 0.0401 memory: 16201 loss_prob: 0.4219 loss_thr: 0.3064 loss_db: 0.0744 loss: 0.8027 2022/08/30 16:07:49 - mmengine - INFO - Epoch(train) [739][40/63] lr: 2.9614e-03 eta: 10:02:12 time: 1.1661 data_time: 0.0364 memory: 16201 loss_prob: 0.4572 loss_thr: 0.3224 loss_db: 0.0794 loss: 0.8590 2022/08/30 16:07:56 - mmengine - INFO - Epoch(train) [739][45/63] lr: 2.9614e-03 eta: 10:02:12 time: 1.2567 data_time: 0.0464 memory: 16201 loss_prob: 0.5369 loss_thr: 0.3174 loss_db: 0.0874 loss: 0.9417 2022/08/30 16:08:02 - mmengine - INFO - Epoch(train) [739][50/63] lr: 2.9614e-03 eta: 10:02:00 time: 1.2455 data_time: 0.0431 memory: 16201 loss_prob: 0.5242 loss_thr: 0.3181 loss_db: 0.0853 loss: 0.9276 2022/08/30 16:08:08 - mmengine - INFO - Epoch(train) [739][55/63] lr: 2.9614e-03 eta: 10:02:00 time: 1.2741 data_time: 0.0385 memory: 16201 loss_prob: 0.4316 loss_thr: 0.2952 loss_db: 0.0766 loss: 0.8034 2022/08/30 16:08:14 - mmengine - INFO - Epoch(train) [739][60/63] lr: 2.9614e-03 eta: 10:01:47 time: 1.2003 data_time: 0.0451 memory: 16201 loss_prob: 0.4091 loss_thr: 0.2848 loss_db: 0.0725 loss: 0.7664 2022/08/30 16:08:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:08:22 - mmengine - INFO - Epoch(train) [740][5/63] lr: 2.9556e-03 eta: 10:01:47 time: 1.0344 data_time: 0.2065 memory: 16201 loss_prob: 0.4935 loss_thr: 0.3048 loss_db: 0.0874 loss: 0.8856 2022/08/30 16:08:27 - mmengine - INFO - Epoch(train) [740][10/63] lr: 2.9556e-03 eta: 10:01:27 time: 1.1087 data_time: 0.2087 memory: 16201 loss_prob: 0.4936 loss_thr: 0.2965 loss_db: 0.0884 loss: 0.8785 2022/08/30 16:08:31 - mmengine - INFO - Epoch(train) [740][15/63] lr: 2.9556e-03 eta: 10:01:27 time: 0.9198 data_time: 0.0298 memory: 16201 loss_prob: 0.4393 loss_thr: 0.2969 loss_db: 0.0750 loss: 0.8113 2022/08/30 16:08:37 - mmengine - INFO - Epoch(train) [740][20/63] lr: 2.9556e-03 eta: 10:01:13 time: 0.9741 data_time: 0.0317 memory: 16201 loss_prob: 0.4360 loss_thr: 0.3060 loss_db: 0.0747 loss: 0.8168 2022/08/30 16:08:41 - mmengine - INFO - Epoch(train) [740][25/63] lr: 2.9556e-03 eta: 10:01:13 time: 0.9411 data_time: 0.0309 memory: 16201 loss_prob: 0.4361 loss_thr: 0.3045 loss_db: 0.0786 loss: 0.8191 2022/08/30 16:08:46 - mmengine - INFO - Epoch(train) [740][30/63] lr: 2.9556e-03 eta: 10:00:59 time: 0.9180 data_time: 0.0283 memory: 16201 loss_prob: 0.4174 loss_thr: 0.2885 loss_db: 0.0750 loss: 0.7810 2022/08/30 16:08:51 - mmengine - INFO - Epoch(train) [740][35/63] lr: 2.9556e-03 eta: 10:00:59 time: 1.0361 data_time: 0.0338 memory: 16201 loss_prob: 0.4131 loss_thr: 0.2780 loss_db: 0.0724 loss: 0.7635 2022/08/30 16:08:57 - mmengine - INFO - Epoch(train) [740][40/63] lr: 2.9556e-03 eta: 10:00:46 time: 1.1229 data_time: 0.0386 memory: 16201 loss_prob: 0.4150 loss_thr: 0.2873 loss_db: 0.0730 loss: 0.7753 2022/08/30 16:09:03 - mmengine - INFO - Epoch(train) [740][45/63] lr: 2.9556e-03 eta: 10:00:46 time: 1.1563 data_time: 0.0430 memory: 16201 loss_prob: 0.4178 loss_thr: 0.3023 loss_db: 0.0740 loss: 0.7941 2022/08/30 16:09:08 - mmengine - INFO - Epoch(train) [740][50/63] lr: 2.9556e-03 eta: 10:00:32 time: 1.0605 data_time: 0.0404 memory: 16201 loss_prob: 0.4312 loss_thr: 0.3009 loss_db: 0.0773 loss: 0.8093 2022/08/30 16:09:12 - mmengine - INFO - Epoch(train) [740][55/63] lr: 2.9556e-03 eta: 10:00:32 time: 0.9334 data_time: 0.0249 memory: 16201 loss_prob: 0.4332 loss_thr: 0.3051 loss_db: 0.0749 loss: 0.8133 2022/08/30 16:09:18 - mmengine - INFO - Epoch(train) [740][60/63] lr: 2.9556e-03 eta: 10:00:18 time: 0.9898 data_time: 0.0406 memory: 16201 loss_prob: 0.4392 loss_thr: 0.3097 loss_db: 0.0757 loss: 0.8246 2022/08/30 16:09:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:09:21 - mmengine - INFO - Saving checkpoint at 740 epochs 2022/08/30 16:09:30 - mmengine - INFO - Epoch(val) [740][5/32] eta: 10:00:18 time: 0.7307 data_time: 0.1376 memory: 16201 2022/08/30 16:09:34 - mmengine - INFO - Epoch(val) [740][10/32] eta: 0:00:17 time: 0.8155 data_time: 0.1708 memory: 15734 2022/08/30 16:09:37 - mmengine - INFO - Epoch(val) [740][15/32] eta: 0:00:17 time: 0.7127 data_time: 0.0663 memory: 15734 2022/08/30 16:09:41 - mmengine - INFO - Epoch(val) [740][20/32] eta: 0:00:09 time: 0.7709 data_time: 0.0815 memory: 15734 2022/08/30 16:09:45 - mmengine - INFO - Epoch(val) [740][25/32] eta: 0:00:09 time: 0.7569 data_time: 0.1003 memory: 15734 2022/08/30 16:09:48 - mmengine - INFO - Epoch(val) [740][30/32] eta: 0:00:01 time: 0.6146 data_time: 0.0358 memory: 15734 2022/08/30 16:09:48 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 16:09:48 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8503, precision: 0.7969, hmean: 0.8227 2022/08/30 16:09:48 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8503, precision: 0.8382, hmean: 0.8442 2022/08/30 16:09:48 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8498, precision: 0.8618, hmean: 0.8558 2022/08/30 16:09:48 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8402, precision: 0.8822, hmean: 0.8607 2022/08/30 16:09:48 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8272, precision: 0.8981, hmean: 0.8612 2022/08/30 16:09:48 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7742, precision: 0.9279, hmean: 0.8441 2022/08/30 16:09:48 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2662, precision: 0.9584, hmean: 0.4167 2022/08/30 16:09:48 - mmengine - INFO - Epoch(val) [740][32/32] icdar/precision: 0.8981 icdar/recall: 0.8272 icdar/hmean: 0.8612 2022/08/30 16:09:57 - mmengine - INFO - Epoch(train) [741][5/63] lr: 2.9499e-03 eta: 0:00:01 time: 1.3609 data_time: 0.2376 memory: 16201 loss_prob: 0.4203 loss_thr: 0.2941 loss_db: 0.0747 loss: 0.7890 2022/08/30 16:10:03 - mmengine - INFO - Epoch(train) [741][10/63] lr: 2.9499e-03 eta: 10:00:01 time: 1.4693 data_time: 0.2425 memory: 16201 loss_prob: 0.4251 loss_thr: 0.2996 loss_db: 0.0736 loss: 0.7984 2022/08/30 16:10:09 - mmengine - INFO - Epoch(train) [741][15/63] lr: 2.9499e-03 eta: 10:00:01 time: 1.1898 data_time: 0.0395 memory: 16201 loss_prob: 0.4434 loss_thr: 0.3120 loss_db: 0.0768 loss: 0.8321 2022/08/30 16:10:15 - mmengine - INFO - Epoch(train) [741][20/63] lr: 2.9499e-03 eta: 9:59:48 time: 1.1852 data_time: 0.0385 memory: 16201 loss_prob: 0.4345 loss_thr: 0.3040 loss_db: 0.0779 loss: 0.8165 2022/08/30 16:10:21 - mmengine - INFO - Epoch(train) [741][25/63] lr: 2.9499e-03 eta: 9:59:48 time: 1.2690 data_time: 0.0445 memory: 16201 loss_prob: 0.4329 loss_thr: 0.2973 loss_db: 0.0769 loss: 0.8071 2022/08/30 16:10:27 - mmengine - INFO - Epoch(train) [741][30/63] lr: 2.9499e-03 eta: 9:59:35 time: 1.1737 data_time: 0.0364 memory: 16201 loss_prob: 0.3929 loss_thr: 0.2785 loss_db: 0.0677 loss: 0.7391 2022/08/30 16:10:32 - mmengine - INFO - Epoch(train) [741][35/63] lr: 2.9499e-03 eta: 9:59:35 time: 1.0133 data_time: 0.0297 memory: 16201 loss_prob: 0.4097 loss_thr: 0.2861 loss_db: 0.0717 loss: 0.7676 2022/08/30 16:10:36 - mmengine - INFO - Epoch(train) [741][40/63] lr: 2.9499e-03 eta: 9:59:21 time: 0.9132 data_time: 0.0305 memory: 16201 loss_prob: 0.4556 loss_thr: 0.3119 loss_db: 0.0820 loss: 0.8494 2022/08/30 16:10:40 - mmengine - INFO - Epoch(train) [741][45/63] lr: 2.9499e-03 eta: 9:59:21 time: 0.8460 data_time: 0.0249 memory: 16201 loss_prob: 0.4695 loss_thr: 0.3253 loss_db: 0.0845 loss: 0.8792 2022/08/30 16:10:44 - mmengine - INFO - Epoch(train) [741][50/63] lr: 2.9499e-03 eta: 9:59:06 time: 0.8419 data_time: 0.0331 memory: 16201 loss_prob: 0.4313 loss_thr: 0.3134 loss_db: 0.0767 loss: 0.8214 2022/08/30 16:10:49 - mmengine - INFO - Epoch(train) [741][55/63] lr: 2.9499e-03 eta: 9:59:06 time: 0.8960 data_time: 0.0274 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2742 loss_db: 0.0642 loss: 0.7037 2022/08/30 16:10:53 - mmengine - INFO - Epoch(train) [741][60/63] lr: 2.9499e-03 eta: 9:58:52 time: 0.9011 data_time: 0.0259 memory: 16201 loss_prob: 0.4056 loss_thr: 0.2838 loss_db: 0.0714 loss: 0.7608 2022/08/30 16:10:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:11:04 - mmengine - INFO - Epoch(train) [742][5/63] lr: 2.9441e-03 eta: 9:58:52 time: 1.2274 data_time: 0.2528 memory: 16201 loss_prob: 0.3922 loss_thr: 0.2777 loss_db: 0.0713 loss: 0.7412 2022/08/30 16:11:09 - mmengine - INFO - Epoch(train) [742][10/63] lr: 2.9441e-03 eta: 9:58:33 time: 1.2525 data_time: 0.2576 memory: 16201 loss_prob: 0.4257 loss_thr: 0.2965 loss_db: 0.0754 loss: 0.7976 2022/08/30 16:11:13 - mmengine - INFO - Epoch(train) [742][15/63] lr: 2.9441e-03 eta: 9:58:33 time: 0.9155 data_time: 0.0305 memory: 16201 loss_prob: 0.4412 loss_thr: 0.3139 loss_db: 0.0744 loss: 0.8295 2022/08/30 16:11:19 - mmengine - INFO - Epoch(train) [742][20/63] lr: 2.9441e-03 eta: 9:58:19 time: 0.9888 data_time: 0.0379 memory: 16201 loss_prob: 0.4295 loss_thr: 0.3056 loss_db: 0.0756 loss: 0.8107 2022/08/30 16:11:24 - mmengine - INFO - Epoch(train) [742][25/63] lr: 2.9441e-03 eta: 9:58:19 time: 1.0940 data_time: 0.0396 memory: 16201 loss_prob: 0.4267 loss_thr: 0.2981 loss_db: 0.0762 loss: 0.8011 2022/08/30 16:11:30 - mmengine - INFO - Epoch(train) [742][30/63] lr: 2.9441e-03 eta: 9:58:06 time: 1.1744 data_time: 0.0353 memory: 16201 loss_prob: 0.4254 loss_thr: 0.2875 loss_db: 0.0741 loss: 0.7870 2022/08/30 16:11:37 - mmengine - INFO - Epoch(train) [742][35/63] lr: 2.9441e-03 eta: 9:58:06 time: 1.2899 data_time: 0.0487 memory: 16201 loss_prob: 0.4297 loss_thr: 0.3003 loss_db: 0.0755 loss: 0.8055 2022/08/30 16:11:42 - mmengine - INFO - Epoch(train) [742][40/63] lr: 2.9441e-03 eta: 9:57:54 time: 1.1931 data_time: 0.0384 memory: 16201 loss_prob: 0.5030 loss_thr: 0.3612 loss_db: 0.0846 loss: 0.9488 2022/08/30 16:11:48 - mmengine - INFO - Epoch(train) [742][45/63] lr: 2.9441e-03 eta: 9:57:54 time: 1.0599 data_time: 0.0327 memory: 16201 loss_prob: 0.4849 loss_thr: 0.3524 loss_db: 0.0823 loss: 0.9196 2022/08/30 16:11:54 - mmengine - INFO - Epoch(train) [742][50/63] lr: 2.9441e-03 eta: 9:57:41 time: 1.1499 data_time: 0.0361 memory: 16201 loss_prob: 0.4214 loss_thr: 0.2991 loss_db: 0.0771 loss: 0.7976 2022/08/30 16:12:00 - mmengine - INFO - Epoch(train) [742][55/63] lr: 2.9441e-03 eta: 9:57:41 time: 1.2182 data_time: 0.0510 memory: 16201 loss_prob: 0.4384 loss_thr: 0.3101 loss_db: 0.0788 loss: 0.8273 2022/08/30 16:12:04 - mmengine - INFO - Epoch(train) [742][60/63] lr: 2.9441e-03 eta: 9:57:27 time: 1.0320 data_time: 0.0499 memory: 16201 loss_prob: 0.4387 loss_thr: 0.3237 loss_db: 0.0757 loss: 0.8382 2022/08/30 16:12:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:12:13 - mmengine - INFO - Epoch(train) [743][5/63] lr: 2.9383e-03 eta: 9:57:27 time: 1.0789 data_time: 0.2209 memory: 16201 loss_prob: 0.4116 loss_thr: 0.3024 loss_db: 0.0749 loss: 0.7889 2022/08/30 16:12:18 - mmengine - INFO - Epoch(train) [743][10/63] lr: 2.9383e-03 eta: 9:57:08 time: 1.1192 data_time: 0.2224 memory: 16201 loss_prob: 0.3691 loss_thr: 0.2814 loss_db: 0.0665 loss: 0.7171 2022/08/30 16:12:23 - mmengine - INFO - Epoch(train) [743][15/63] lr: 2.9383e-03 eta: 9:57:08 time: 0.9502 data_time: 0.0283 memory: 16201 loss_prob: 0.3958 loss_thr: 0.2925 loss_db: 0.0683 loss: 0.7567 2022/08/30 16:12:29 - mmengine - INFO - Epoch(train) [743][20/63] lr: 2.9383e-03 eta: 9:56:55 time: 1.1466 data_time: 0.0361 memory: 16201 loss_prob: 0.4109 loss_thr: 0.2896 loss_db: 0.0727 loss: 0.7733 2022/08/30 16:12:34 - mmengine - INFO - Epoch(train) [743][25/63] lr: 2.9383e-03 eta: 9:56:55 time: 1.1842 data_time: 0.0402 memory: 16201 loss_prob: 0.4567 loss_thr: 0.3148 loss_db: 0.0812 loss: 0.8528 2022/08/30 16:12:39 - mmengine - INFO - Epoch(train) [743][30/63] lr: 2.9383e-03 eta: 9:56:41 time: 1.0395 data_time: 0.0373 memory: 16201 loss_prob: 0.4517 loss_thr: 0.3189 loss_db: 0.0795 loss: 0.8501 2022/08/30 16:12:45 - mmengine - INFO - Epoch(train) [743][35/63] lr: 2.9383e-03 eta: 9:56:41 time: 1.0512 data_time: 0.0501 memory: 16201 loss_prob: 0.4173 loss_thr: 0.2944 loss_db: 0.0749 loss: 0.7866 2022/08/30 16:12:50 - mmengine - INFO - Epoch(train) [743][40/63] lr: 2.9383e-03 eta: 9:56:27 time: 1.0194 data_time: 0.0365 memory: 16201 loss_prob: 0.4691 loss_thr: 0.3236 loss_db: 0.0842 loss: 0.8768 2022/08/30 16:12:55 - mmengine - INFO - Epoch(train) [743][45/63] lr: 2.9383e-03 eta: 9:56:27 time: 1.0327 data_time: 0.0347 memory: 16201 loss_prob: 0.4389 loss_thr: 0.3061 loss_db: 0.0798 loss: 0.8248 2022/08/30 16:13:02 - mmengine - INFO - Epoch(train) [743][50/63] lr: 2.9383e-03 eta: 9:56:15 time: 1.1996 data_time: 0.0442 memory: 16201 loss_prob: 0.3883 loss_thr: 0.2762 loss_db: 0.0697 loss: 0.7341 2022/08/30 16:13:08 - mmengine - INFO - Epoch(train) [743][55/63] lr: 2.9383e-03 eta: 9:56:15 time: 1.2604 data_time: 0.0288 memory: 16201 loss_prob: 0.4028 loss_thr: 0.2888 loss_db: 0.0708 loss: 0.7625 2022/08/30 16:13:13 - mmengine - INFO - Epoch(train) [743][60/63] lr: 2.9383e-03 eta: 9:56:01 time: 1.1418 data_time: 0.0368 memory: 16201 loss_prob: 0.4377 loss_thr: 0.3066 loss_db: 0.0788 loss: 0.8232 2022/08/30 16:13:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:13:22 - mmengine - INFO - Epoch(train) [744][5/63] lr: 2.9325e-03 eta: 9:56:01 time: 1.0563 data_time: 0.1896 memory: 16201 loss_prob: 0.4060 loss_thr: 0.2841 loss_db: 0.0712 loss: 0.7613 2022/08/30 16:13:26 - mmengine - INFO - Epoch(train) [744][10/63] lr: 2.9325e-03 eta: 9:55:42 time: 1.0155 data_time: 0.1950 memory: 16201 loss_prob: 0.4410 loss_thr: 0.3140 loss_db: 0.0768 loss: 0.8318 2022/08/30 16:13:30 - mmengine - INFO - Epoch(train) [744][15/63] lr: 2.9325e-03 eta: 9:55:42 time: 0.8015 data_time: 0.0257 memory: 16201 loss_prob: 0.4729 loss_thr: 0.3371 loss_db: 0.0827 loss: 0.8928 2022/08/30 16:13:35 - mmengine - INFO - Epoch(train) [744][20/63] lr: 2.9325e-03 eta: 9:55:27 time: 0.9349 data_time: 0.0323 memory: 16201 loss_prob: 0.4588 loss_thr: 0.3223 loss_db: 0.0795 loss: 0.8606 2022/08/30 16:13:41 - mmengine - INFO - Epoch(train) [744][25/63] lr: 2.9325e-03 eta: 9:55:27 time: 1.1234 data_time: 0.0439 memory: 16201 loss_prob: 0.3959 loss_thr: 0.2755 loss_db: 0.0702 loss: 0.7416 2022/08/30 16:13:47 - mmengine - INFO - Epoch(train) [744][30/63] lr: 2.9325e-03 eta: 9:55:14 time: 1.1620 data_time: 0.0345 memory: 16201 loss_prob: 0.3830 loss_thr: 0.2729 loss_db: 0.0695 loss: 0.7255 2022/08/30 16:13:52 - mmengine - INFO - Epoch(train) [744][35/63] lr: 2.9325e-03 eta: 9:55:14 time: 1.0826 data_time: 0.0338 memory: 16201 loss_prob: 0.4153 loss_thr: 0.2960 loss_db: 0.0729 loss: 0.7842 2022/08/30 16:13:59 - mmengine - INFO - Epoch(train) [744][40/63] lr: 2.9325e-03 eta: 9:55:02 time: 1.1795 data_time: 0.0370 memory: 16201 loss_prob: 0.4257 loss_thr: 0.2984 loss_db: 0.0755 loss: 0.7996 2022/08/30 16:14:04 - mmengine - INFO - Epoch(train) [744][45/63] lr: 2.9325e-03 eta: 9:55:02 time: 1.2171 data_time: 0.0310 memory: 16201 loss_prob: 0.4213 loss_thr: 0.2976 loss_db: 0.0766 loss: 0.7956 2022/08/30 16:14:09 - mmengine - INFO - Epoch(train) [744][50/63] lr: 2.9325e-03 eta: 9:54:48 time: 1.0812 data_time: 0.0507 memory: 16201 loss_prob: 0.4151 loss_thr: 0.2920 loss_db: 0.0739 loss: 0.7810 2022/08/30 16:14:16 - mmengine - INFO - Epoch(train) [744][55/63] lr: 2.9325e-03 eta: 9:54:48 time: 1.1615 data_time: 0.0434 memory: 16201 loss_prob: 0.4094 loss_thr: 0.2912 loss_db: 0.0719 loss: 0.7725 2022/08/30 16:14:20 - mmengine - INFO - Epoch(train) [744][60/63] lr: 2.9325e-03 eta: 9:54:35 time: 1.0618 data_time: 0.0349 memory: 16201 loss_prob: 0.4201 loss_thr: 0.3046 loss_db: 0.0744 loss: 0.7991 2022/08/30 16:14:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:14:29 - mmengine - INFO - Epoch(train) [745][5/63] lr: 2.9267e-03 eta: 9:54:35 time: 1.0492 data_time: 0.2363 memory: 16201 loss_prob: 0.4862 loss_thr: 0.3237 loss_db: 0.0801 loss: 0.8899 2022/08/30 16:14:33 - mmengine - INFO - Epoch(train) [745][10/63] lr: 2.9267e-03 eta: 9:54:16 time: 1.1175 data_time: 0.2474 memory: 16201 loss_prob: 0.4767 loss_thr: 0.3187 loss_db: 0.0779 loss: 0.8734 2022/08/30 16:14:38 - mmengine - INFO - Epoch(train) [745][15/63] lr: 2.9267e-03 eta: 9:54:16 time: 0.9341 data_time: 0.0257 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2921 loss_db: 0.0721 loss: 0.7627 2022/08/30 16:14:44 - mmengine - INFO - Epoch(train) [745][20/63] lr: 2.9267e-03 eta: 9:54:02 time: 1.0633 data_time: 0.0257 memory: 16201 loss_prob: 0.3979 loss_thr: 0.2894 loss_db: 0.0715 loss: 0.7588 2022/08/30 16:14:50 - mmengine - INFO - Epoch(train) [745][25/63] lr: 2.9267e-03 eta: 9:54:02 time: 1.1469 data_time: 0.0439 memory: 16201 loss_prob: 0.4019 loss_thr: 0.3000 loss_db: 0.0711 loss: 0.7730 2022/08/30 16:14:55 - mmengine - INFO - Epoch(train) [745][30/63] lr: 2.9267e-03 eta: 9:53:49 time: 1.1474 data_time: 0.0322 memory: 16201 loss_prob: 0.4434 loss_thr: 0.3085 loss_db: 0.0792 loss: 0.8312 2022/08/30 16:15:01 - mmengine - INFO - Epoch(train) [745][35/63] lr: 2.9267e-03 eta: 9:53:49 time: 1.1309 data_time: 0.0339 memory: 16201 loss_prob: 0.4594 loss_thr: 0.3224 loss_db: 0.0830 loss: 0.8648 2022/08/30 16:15:05 - mmengine - INFO - Epoch(train) [745][40/63] lr: 2.9267e-03 eta: 9:53:35 time: 0.9938 data_time: 0.0354 memory: 16201 loss_prob: 0.4168 loss_thr: 0.3045 loss_db: 0.0741 loss: 0.7954 2022/08/30 16:15:10 - mmengine - INFO - Epoch(train) [745][45/63] lr: 2.9267e-03 eta: 9:53:35 time: 0.8813 data_time: 0.0274 memory: 16201 loss_prob: 0.4268 loss_thr: 0.2960 loss_db: 0.0742 loss: 0.7969 2022/08/30 16:15:14 - mmengine - INFO - Epoch(train) [745][50/63] lr: 2.9267e-03 eta: 9:53:21 time: 0.9082 data_time: 0.0430 memory: 16201 loss_prob: 0.4070 loss_thr: 0.2884 loss_db: 0.0722 loss: 0.7676 2022/08/30 16:15:20 - mmengine - INFO - Epoch(train) [745][55/63] lr: 2.9267e-03 eta: 9:53:21 time: 1.0071 data_time: 0.0284 memory: 16201 loss_prob: 0.4314 loss_thr: 0.2957 loss_db: 0.0754 loss: 0.8025 2022/08/30 16:15:26 - mmengine - INFO - Epoch(train) [745][60/63] lr: 2.9267e-03 eta: 9:53:08 time: 1.1681 data_time: 0.0311 memory: 16201 loss_prob: 0.4785 loss_thr: 0.3096 loss_db: 0.0839 loss: 0.8719 2022/08/30 16:15:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:15:36 - mmengine - INFO - Epoch(train) [746][5/63] lr: 2.9209e-03 eta: 9:53:08 time: 1.2899 data_time: 0.2214 memory: 16201 loss_prob: 0.4105 loss_thr: 0.2943 loss_db: 0.0713 loss: 0.7761 2022/08/30 16:15:42 - mmengine - INFO - Epoch(train) [746][10/63] lr: 2.9209e-03 eta: 9:52:50 time: 1.2650 data_time: 0.2349 memory: 16201 loss_prob: 0.4136 loss_thr: 0.3068 loss_db: 0.0733 loss: 0.7937 2022/08/30 16:15:46 - mmengine - INFO - Epoch(train) [746][15/63] lr: 2.9209e-03 eta: 9:52:50 time: 1.0105 data_time: 0.0296 memory: 16201 loss_prob: 0.4638 loss_thr: 0.3304 loss_db: 0.0812 loss: 0.8755 2022/08/30 16:15:51 - mmengine - INFO - Epoch(train) [746][20/63] lr: 2.9209e-03 eta: 9:52:35 time: 0.9105 data_time: 0.0274 memory: 16201 loss_prob: 0.4595 loss_thr: 0.3255 loss_db: 0.0791 loss: 0.8642 2022/08/30 16:15:55 - mmengine - INFO - Epoch(train) [746][25/63] lr: 2.9209e-03 eta: 9:52:35 time: 0.8929 data_time: 0.0359 memory: 16201 loss_prob: 0.4076 loss_thr: 0.2980 loss_db: 0.0722 loss: 0.7778 2022/08/30 16:16:01 - mmengine - INFO - Epoch(train) [746][30/63] lr: 2.9209e-03 eta: 9:52:21 time: 1.0205 data_time: 0.0266 memory: 16201 loss_prob: 0.3918 loss_thr: 0.2867 loss_db: 0.0697 loss: 0.7481 2022/08/30 16:16:07 - mmengine - INFO - Epoch(train) [746][35/63] lr: 2.9209e-03 eta: 9:52:21 time: 1.1773 data_time: 0.0330 memory: 16201 loss_prob: 0.3954 loss_thr: 0.2831 loss_db: 0.0683 loss: 0.7469 2022/08/30 16:16:12 - mmengine - INFO - Epoch(train) [746][40/63] lr: 2.9209e-03 eta: 9:52:08 time: 1.0273 data_time: 0.0295 memory: 16201 loss_prob: 0.4064 loss_thr: 0.2921 loss_db: 0.0716 loss: 0.7702 2022/08/30 16:16:18 - mmengine - INFO - Epoch(train) [746][45/63] lr: 2.9209e-03 eta: 9:52:08 time: 1.1287 data_time: 0.1399 memory: 16201 loss_prob: 0.4439 loss_thr: 0.3166 loss_db: 0.0791 loss: 0.8396 2022/08/30 16:16:23 - mmengine - INFO - Epoch(train) [746][50/63] lr: 2.9209e-03 eta: 9:51:54 time: 1.1174 data_time: 0.1444 memory: 16201 loss_prob: 0.4203 loss_thr: 0.2866 loss_db: 0.0738 loss: 0.7807 2022/08/30 16:16:27 - mmengine - INFO - Epoch(train) [746][55/63] lr: 2.9209e-03 eta: 9:51:54 time: 0.8697 data_time: 0.0653 memory: 16201 loss_prob: 0.3961 loss_thr: 0.2672 loss_db: 0.0702 loss: 0.7335 2022/08/30 16:16:33 - mmengine - INFO - Epoch(train) [746][60/63] lr: 2.9209e-03 eta: 9:51:41 time: 1.0674 data_time: 0.0755 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2870 loss_db: 0.0706 loss: 0.7562 2022/08/30 16:16:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:16:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:16:43 - mmengine - INFO - Epoch(train) [747][5/63] lr: 2.9151e-03 eta: 9:51:41 time: 1.1867 data_time: 0.2201 memory: 16201 loss_prob: 0.3790 loss_thr: 0.2679 loss_db: 0.0688 loss: 0.7157 2022/08/30 16:16:47 - mmengine - INFO - Epoch(train) [747][10/63] lr: 2.9151e-03 eta: 9:51:22 time: 1.1291 data_time: 0.2129 memory: 16201 loss_prob: 0.3935 loss_thr: 0.2825 loss_db: 0.0682 loss: 0.7443 2022/08/30 16:16:51 - mmengine - INFO - Epoch(train) [747][15/63] lr: 2.9151e-03 eta: 9:51:22 time: 0.8626 data_time: 0.0282 memory: 16201 loss_prob: 0.4086 loss_thr: 0.2937 loss_db: 0.0696 loss: 0.7719 2022/08/30 16:16:56 - mmengine - INFO - Epoch(train) [747][20/63] lr: 2.9151e-03 eta: 9:51:08 time: 0.9432 data_time: 0.0355 memory: 16201 loss_prob: 0.4150 loss_thr: 0.2808 loss_db: 0.0722 loss: 0.7679 2022/08/30 16:17:02 - mmengine - INFO - Epoch(train) [747][25/63] lr: 2.9151e-03 eta: 9:51:08 time: 1.0541 data_time: 0.0497 memory: 16201 loss_prob: 0.4829 loss_thr: 0.3026 loss_db: 0.0829 loss: 0.8684 2022/08/30 16:17:08 - mmengine - INFO - Epoch(train) [747][30/63] lr: 2.9151e-03 eta: 9:50:55 time: 1.1416 data_time: 0.0479 memory: 16201 loss_prob: 0.4649 loss_thr: 0.3077 loss_db: 0.0802 loss: 0.8528 2022/08/30 16:17:14 - mmengine - INFO - Epoch(train) [747][35/63] lr: 2.9151e-03 eta: 9:50:55 time: 1.2126 data_time: 0.0374 memory: 16201 loss_prob: 0.4539 loss_thr: 0.3121 loss_db: 0.0762 loss: 0.8422 2022/08/30 16:17:20 - mmengine - INFO - Epoch(train) [747][40/63] lr: 2.9151e-03 eta: 9:50:42 time: 1.2471 data_time: 0.0380 memory: 16201 loss_prob: 0.5030 loss_thr: 0.3536 loss_db: 0.0865 loss: 0.9432 2022/08/30 16:17:26 - mmengine - INFO - Epoch(train) [747][45/63] lr: 2.9151e-03 eta: 9:50:42 time: 1.2497 data_time: 0.0399 memory: 16201 loss_prob: 0.4440 loss_thr: 0.3279 loss_db: 0.0792 loss: 0.8510 2022/08/30 16:17:31 - mmengine - INFO - Epoch(train) [747][50/63] lr: 2.9151e-03 eta: 9:50:29 time: 1.0491 data_time: 0.0423 memory: 16201 loss_prob: 0.4398 loss_thr: 0.3120 loss_db: 0.0776 loss: 0.8294 2022/08/30 16:17:35 - mmengine - INFO - Epoch(train) [747][55/63] lr: 2.9151e-03 eta: 9:50:29 time: 0.8592 data_time: 0.0278 memory: 16201 loss_prob: 0.4497 loss_thr: 0.3130 loss_db: 0.0776 loss: 0.8403 2022/08/30 16:17:40 - mmengine - INFO - Epoch(train) [747][60/63] lr: 2.9151e-03 eta: 9:50:14 time: 0.8754 data_time: 0.0292 memory: 16201 loss_prob: 0.4086 loss_thr: 0.2957 loss_db: 0.0702 loss: 0.7745 2022/08/30 16:17:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:17:49 - mmengine - INFO - Epoch(train) [748][5/63] lr: 2.9093e-03 eta: 9:50:14 time: 1.1309 data_time: 0.2513 memory: 16201 loss_prob: 0.4052 loss_thr: 0.2871 loss_db: 0.0725 loss: 0.7647 2022/08/30 16:17:54 - mmengine - INFO - Epoch(train) [748][10/63] lr: 2.9093e-03 eta: 9:49:55 time: 1.1627 data_time: 0.2562 memory: 16201 loss_prob: 0.4057 loss_thr: 0.2923 loss_db: 0.0700 loss: 0.7679 2022/08/30 16:17:59 - mmengine - INFO - Epoch(train) [748][15/63] lr: 2.9093e-03 eta: 9:49:55 time: 0.9787 data_time: 0.0287 memory: 16201 loss_prob: 0.3947 loss_thr: 0.2901 loss_db: 0.0709 loss: 0.7556 2022/08/30 16:18:04 - mmengine - INFO - Epoch(train) [748][20/63] lr: 2.9093e-03 eta: 9:49:42 time: 1.0825 data_time: 0.0297 memory: 16201 loss_prob: 0.3765 loss_thr: 0.2779 loss_db: 0.0667 loss: 0.7210 2022/08/30 16:18:11 - mmengine - INFO - Epoch(train) [748][25/63] lr: 2.9093e-03 eta: 9:49:42 time: 1.1730 data_time: 0.0408 memory: 16201 loss_prob: 0.3936 loss_thr: 0.2894 loss_db: 0.0677 loss: 0.7507 2022/08/30 16:18:16 - mmengine - INFO - Epoch(train) [748][30/63] lr: 2.9093e-03 eta: 9:49:29 time: 1.1927 data_time: 0.0393 memory: 16201 loss_prob: 0.3966 loss_thr: 0.2987 loss_db: 0.0700 loss: 0.7653 2022/08/30 16:18:22 - mmengine - INFO - Epoch(train) [748][35/63] lr: 2.9093e-03 eta: 9:49:29 time: 1.1486 data_time: 0.0422 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2811 loss_db: 0.0672 loss: 0.7251 2022/08/30 16:18:28 - mmengine - INFO - Epoch(train) [748][40/63] lr: 2.9093e-03 eta: 9:49:16 time: 1.1149 data_time: 0.0321 memory: 16201 loss_prob: 0.4188 loss_thr: 0.3037 loss_db: 0.0721 loss: 0.7945 2022/08/30 16:18:34 - mmengine - INFO - Epoch(train) [748][45/63] lr: 2.9093e-03 eta: 9:49:16 time: 1.1860 data_time: 0.0728 memory: 16201 loss_prob: 0.4205 loss_thr: 0.3113 loss_db: 0.0726 loss: 0.8043 2022/08/30 16:18:40 - mmengine - INFO - Epoch(train) [748][50/63] lr: 2.9093e-03 eta: 9:49:04 time: 1.2488 data_time: 0.0860 memory: 16201 loss_prob: 0.3954 loss_thr: 0.2890 loss_db: 0.0705 loss: 0.7549 2022/08/30 16:18:45 - mmengine - INFO - Epoch(train) [748][55/63] lr: 2.9093e-03 eta: 9:49:04 time: 1.1148 data_time: 0.0323 memory: 16201 loss_prob: 0.4275 loss_thr: 0.2867 loss_db: 0.0729 loss: 0.7872 2022/08/30 16:18:51 - mmengine - INFO - Epoch(train) [748][60/63] lr: 2.9093e-03 eta: 9:48:50 time: 1.1055 data_time: 0.0286 memory: 16201 loss_prob: 0.4291 loss_thr: 0.2893 loss_db: 0.0736 loss: 0.7919 2022/08/30 16:18:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:19:00 - mmengine - INFO - Epoch(train) [749][5/63] lr: 2.9035e-03 eta: 9:48:50 time: 1.1094 data_time: 0.2249 memory: 16201 loss_prob: 0.4230 loss_thr: 0.2925 loss_db: 0.0739 loss: 0.7895 2022/08/30 16:19:04 - mmengine - INFO - Epoch(train) [749][10/63] lr: 2.9035e-03 eta: 9:48:31 time: 1.0945 data_time: 0.2330 memory: 16201 loss_prob: 0.3939 loss_thr: 0.2902 loss_db: 0.0692 loss: 0.7534 2022/08/30 16:19:09 - mmengine - INFO - Epoch(train) [749][15/63] lr: 2.9035e-03 eta: 9:48:31 time: 0.8852 data_time: 0.0368 memory: 16201 loss_prob: 0.4266 loss_thr: 0.3096 loss_db: 0.0765 loss: 0.8127 2022/08/30 16:19:13 - mmengine - INFO - Epoch(train) [749][20/63] lr: 2.9035e-03 eta: 9:48:17 time: 0.9128 data_time: 0.0328 memory: 16201 loss_prob: 0.4222 loss_thr: 0.2969 loss_db: 0.0758 loss: 0.7948 2022/08/30 16:19:17 - mmengine - INFO - Epoch(train) [749][25/63] lr: 2.9035e-03 eta: 9:48:17 time: 0.8687 data_time: 0.0265 memory: 16201 loss_prob: 0.3731 loss_thr: 0.2707 loss_db: 0.0650 loss: 0.7088 2022/08/30 16:19:22 - mmengine - INFO - Epoch(train) [749][30/63] lr: 2.9035e-03 eta: 9:48:02 time: 0.8343 data_time: 0.0257 memory: 16201 loss_prob: 0.4082 loss_thr: 0.2851 loss_db: 0.0726 loss: 0.7659 2022/08/30 16:19:27 - mmengine - INFO - Epoch(train) [749][35/63] lr: 2.9035e-03 eta: 9:48:02 time: 0.9413 data_time: 0.0284 memory: 16201 loss_prob: 0.3904 loss_thr: 0.2773 loss_db: 0.0704 loss: 0.7380 2022/08/30 16:19:33 - mmengine - INFO - Epoch(train) [749][40/63] lr: 2.9035e-03 eta: 9:47:49 time: 1.0877 data_time: 0.0289 memory: 16201 loss_prob: 0.3550 loss_thr: 0.2692 loss_db: 0.0631 loss: 0.6874 2022/08/30 16:19:38 - mmengine - INFO - Epoch(train) [749][45/63] lr: 2.9035e-03 eta: 9:47:49 time: 1.1037 data_time: 0.0376 memory: 16201 loss_prob: 0.3856 loss_thr: 0.2819 loss_db: 0.0684 loss: 0.7359 2022/08/30 16:19:44 - mmengine - INFO - Epoch(train) [749][50/63] lr: 2.9035e-03 eta: 9:47:35 time: 1.1115 data_time: 0.0438 memory: 16201 loss_prob: 0.3799 loss_thr: 0.2852 loss_db: 0.0676 loss: 0.7326 2022/08/30 16:19:50 - mmengine - INFO - Epoch(train) [749][55/63] lr: 2.9035e-03 eta: 9:47:35 time: 1.1580 data_time: 0.0366 memory: 16201 loss_prob: 0.3868 loss_thr: 0.2855 loss_db: 0.0698 loss: 0.7421 2022/08/30 16:19:56 - mmengine - INFO - Epoch(train) [749][60/63] lr: 2.9035e-03 eta: 9:47:23 time: 1.2133 data_time: 0.0355 memory: 16201 loss_prob: 0.4376 loss_thr: 0.3036 loss_db: 0.0772 loss: 0.8184 2022/08/30 16:19:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:20:07 - mmengine - INFO - Epoch(train) [750][5/63] lr: 2.8977e-03 eta: 9:47:23 time: 1.3619 data_time: 0.2436 memory: 16201 loss_prob: 0.4271 loss_thr: 0.3092 loss_db: 0.0749 loss: 0.8112 2022/08/30 16:20:13 - mmengine - INFO - Epoch(train) [750][10/63] lr: 2.8977e-03 eta: 9:47:05 time: 1.3762 data_time: 0.2627 memory: 16201 loss_prob: 0.4456 loss_thr: 0.3085 loss_db: 0.0780 loss: 0.8321 2022/08/30 16:20:18 - mmengine - INFO - Epoch(train) [750][15/63] lr: 2.8977e-03 eta: 9:47:05 time: 1.1614 data_time: 0.0429 memory: 16201 loss_prob: 0.4311 loss_thr: 0.2983 loss_db: 0.0748 loss: 0.8042 2022/08/30 16:20:23 - mmengine - INFO - Epoch(train) [750][20/63] lr: 2.8977e-03 eta: 9:46:52 time: 1.0536 data_time: 0.0338 memory: 16201 loss_prob: 0.3987 loss_thr: 0.2845 loss_db: 0.0707 loss: 0.7540 2022/08/30 16:20:27 - mmengine - INFO - Epoch(train) [750][25/63] lr: 2.8977e-03 eta: 9:46:52 time: 0.9004 data_time: 0.0306 memory: 16201 loss_prob: 0.3878 loss_thr: 0.2793 loss_db: 0.0709 loss: 0.7380 2022/08/30 16:20:32 - mmengine - INFO - Epoch(train) [750][30/63] lr: 2.8977e-03 eta: 9:46:37 time: 0.8321 data_time: 0.0190 memory: 16201 loss_prob: 0.4241 loss_thr: 0.2961 loss_db: 0.0755 loss: 0.7958 2022/08/30 16:20:36 - mmengine - INFO - Epoch(train) [750][35/63] lr: 2.8977e-03 eta: 9:46:37 time: 0.8777 data_time: 0.0353 memory: 16201 loss_prob: 0.4456 loss_thr: 0.3111 loss_db: 0.0779 loss: 0.8346 2022/08/30 16:20:41 - mmengine - INFO - Epoch(train) [750][40/63] lr: 2.8977e-03 eta: 9:46:22 time: 0.8971 data_time: 0.0273 memory: 16201 loss_prob: 0.4377 loss_thr: 0.3068 loss_db: 0.0784 loss: 0.8230 2022/08/30 16:20:46 - mmengine - INFO - Epoch(train) [750][45/63] lr: 2.8977e-03 eta: 9:46:22 time: 0.9428 data_time: 0.0200 memory: 16201 loss_prob: 0.4080 loss_thr: 0.2859 loss_db: 0.0730 loss: 0.7669 2022/08/30 16:20:51 - mmengine - INFO - Epoch(train) [750][50/63] lr: 2.8977e-03 eta: 9:46:09 time: 1.0935 data_time: 0.0385 memory: 16201 loss_prob: 0.4078 loss_thr: 0.2852 loss_db: 0.0717 loss: 0.7647 2022/08/30 16:20:59 - mmengine - INFO - Epoch(train) [750][55/63] lr: 2.8977e-03 eta: 9:46:09 time: 1.3018 data_time: 0.0319 memory: 16201 loss_prob: 0.4482 loss_thr: 0.3172 loss_db: 0.0802 loss: 0.8456 2022/08/30 16:21:05 - mmengine - INFO - Epoch(train) [750][60/63] lr: 2.8977e-03 eta: 9:45:57 time: 1.3408 data_time: 0.0332 memory: 16201 loss_prob: 0.4071 loss_thr: 0.2992 loss_db: 0.0735 loss: 0.7799 2022/08/30 16:21:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:21:15 - mmengine - INFO - Epoch(train) [751][5/63] lr: 2.8920e-03 eta: 9:45:57 time: 1.2688 data_time: 0.2942 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2652 loss_db: 0.0641 loss: 0.6886 2022/08/30 16:21:20 - mmengine - INFO - Epoch(train) [751][10/63] lr: 2.8920e-03 eta: 9:45:39 time: 1.1977 data_time: 0.3309 memory: 16201 loss_prob: 0.4047 loss_thr: 0.2915 loss_db: 0.0721 loss: 0.7683 2022/08/30 16:21:24 - mmengine - INFO - Epoch(train) [751][15/63] lr: 2.8920e-03 eta: 9:45:39 time: 0.9252 data_time: 0.0764 memory: 16201 loss_prob: 0.4159 loss_thr: 0.3045 loss_db: 0.0739 loss: 0.7942 2022/08/30 16:21:30 - mmengine - INFO - Epoch(train) [751][20/63] lr: 2.8920e-03 eta: 9:45:25 time: 1.0426 data_time: 0.0511 memory: 16201 loss_prob: 0.3926 loss_thr: 0.2898 loss_db: 0.0681 loss: 0.7504 2022/08/30 16:21:36 - mmengine - INFO - Epoch(train) [751][25/63] lr: 2.8920e-03 eta: 9:45:25 time: 1.1901 data_time: 0.0891 memory: 16201 loss_prob: 0.4321 loss_thr: 0.3022 loss_db: 0.0756 loss: 0.8099 2022/08/30 16:21:41 - mmengine - INFO - Epoch(train) [751][30/63] lr: 2.8920e-03 eta: 9:45:12 time: 1.0475 data_time: 0.0740 memory: 16201 loss_prob: 0.4784 loss_thr: 0.3302 loss_db: 0.0829 loss: 0.8914 2022/08/30 16:21:46 - mmengine - INFO - Epoch(train) [751][35/63] lr: 2.8920e-03 eta: 9:45:12 time: 1.0258 data_time: 0.0751 memory: 16201 loss_prob: 0.4539 loss_thr: 0.3164 loss_db: 0.0786 loss: 0.8489 2022/08/30 16:21:52 - mmengine - INFO - Epoch(train) [751][40/63] lr: 2.8920e-03 eta: 9:44:59 time: 1.1149 data_time: 0.0734 memory: 16201 loss_prob: 0.4444 loss_thr: 0.3060 loss_db: 0.0789 loss: 0.8293 2022/08/30 16:21:58 - mmengine - INFO - Epoch(train) [751][45/63] lr: 2.8920e-03 eta: 9:44:59 time: 1.1379 data_time: 0.0814 memory: 16201 loss_prob: 0.4391 loss_thr: 0.3093 loss_db: 0.0780 loss: 0.8264 2022/08/30 16:22:04 - mmengine - INFO - Epoch(train) [751][50/63] lr: 2.8920e-03 eta: 9:44:46 time: 1.2521 data_time: 0.0944 memory: 16201 loss_prob: 0.4270 loss_thr: 0.3035 loss_db: 0.0757 loss: 0.8063 2022/08/30 16:22:09 - mmengine - INFO - Epoch(train) [751][55/63] lr: 2.8920e-03 eta: 9:44:46 time: 1.1289 data_time: 0.0883 memory: 16201 loss_prob: 0.4201 loss_thr: 0.2929 loss_db: 0.0746 loss: 0.7876 2022/08/30 16:22:13 - mmengine - INFO - Epoch(train) [751][60/63] lr: 2.8920e-03 eta: 9:44:32 time: 0.8819 data_time: 0.0813 memory: 16201 loss_prob: 0.4205 loss_thr: 0.2880 loss_db: 0.0735 loss: 0.7820 2022/08/30 16:22:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:22:23 - mmengine - INFO - Epoch(train) [752][5/63] lr: 2.8862e-03 eta: 9:44:32 time: 1.1036 data_time: 0.2384 memory: 16201 loss_prob: 0.4086 loss_thr: 0.2966 loss_db: 0.0723 loss: 0.7774 2022/08/30 16:22:28 - mmengine - INFO - Epoch(train) [752][10/63] lr: 2.8862e-03 eta: 9:44:14 time: 1.2731 data_time: 0.2814 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2987 loss_db: 0.0739 loss: 0.7829 2022/08/30 16:22:33 - mmengine - INFO - Epoch(train) [752][15/63] lr: 2.8862e-03 eta: 9:44:14 time: 1.0815 data_time: 0.0881 memory: 16201 loss_prob: 0.4346 loss_thr: 0.3036 loss_db: 0.0755 loss: 0.8137 2022/08/30 16:22:40 - mmengine - INFO - Epoch(train) [752][20/63] lr: 2.8862e-03 eta: 9:44:01 time: 1.1537 data_time: 0.0878 memory: 16201 loss_prob: 0.3978 loss_thr: 0.2795 loss_db: 0.0691 loss: 0.7465 2022/08/30 16:22:46 - mmengine - INFO - Epoch(train) [752][25/63] lr: 2.8862e-03 eta: 9:44:01 time: 1.2216 data_time: 0.0874 memory: 16201 loss_prob: 0.3888 loss_thr: 0.2699 loss_db: 0.0695 loss: 0.7282 2022/08/30 16:22:51 - mmengine - INFO - Epoch(train) [752][30/63] lr: 2.8862e-03 eta: 9:43:48 time: 1.1482 data_time: 0.0803 memory: 16201 loss_prob: 0.4252 loss_thr: 0.2909 loss_db: 0.0759 loss: 0.7920 2022/08/30 16:22:56 - mmengine - INFO - Epoch(train) [752][35/63] lr: 2.8862e-03 eta: 9:43:48 time: 1.0659 data_time: 0.0927 memory: 16201 loss_prob: 0.4288 loss_thr: 0.3021 loss_db: 0.0750 loss: 0.8059 2022/08/30 16:23:01 - mmengine - INFO - Epoch(train) [752][40/63] lr: 2.8862e-03 eta: 9:43:34 time: 0.9995 data_time: 0.0918 memory: 16201 loss_prob: 0.4355 loss_thr: 0.3023 loss_db: 0.0745 loss: 0.8123 2022/08/30 16:23:06 - mmengine - INFO - Epoch(train) [752][45/63] lr: 2.8862e-03 eta: 9:43:34 time: 0.9597 data_time: 0.0771 memory: 16201 loss_prob: 0.4411 loss_thr: 0.3108 loss_db: 0.0765 loss: 0.8284 2022/08/30 16:23:10 - mmengine - INFO - Epoch(train) [752][50/63] lr: 2.8862e-03 eta: 9:43:20 time: 0.9139 data_time: 0.0541 memory: 16201 loss_prob: 0.3983 loss_thr: 0.2906 loss_db: 0.0707 loss: 0.7595 2022/08/30 16:23:16 - mmengine - INFO - Epoch(train) [752][55/63] lr: 2.8862e-03 eta: 9:43:20 time: 0.9671 data_time: 0.0677 memory: 16201 loss_prob: 0.4199 loss_thr: 0.2981 loss_db: 0.0727 loss: 0.7906 2022/08/30 16:23:21 - mmengine - INFO - Epoch(train) [752][60/63] lr: 2.8862e-03 eta: 9:43:06 time: 1.1119 data_time: 0.0726 memory: 16201 loss_prob: 0.4419 loss_thr: 0.3062 loss_db: 0.0771 loss: 0.8251 2022/08/30 16:23:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:23:34 - mmengine - INFO - Epoch(train) [753][5/63] lr: 2.8804e-03 eta: 9:43:06 time: 1.4472 data_time: 0.3319 memory: 16201 loss_prob: 0.4231 loss_thr: 0.3063 loss_db: 0.0760 loss: 0.8054 2022/08/30 16:23:40 - mmengine - INFO - Epoch(train) [753][10/63] lr: 2.8804e-03 eta: 9:42:50 time: 1.4991 data_time: 0.3403 memory: 16201 loss_prob: 0.4231 loss_thr: 0.2908 loss_db: 0.0737 loss: 0.7876 2022/08/30 16:23:45 - mmengine - INFO - Epoch(train) [753][15/63] lr: 2.8804e-03 eta: 9:42:50 time: 1.1073 data_time: 0.0574 memory: 16201 loss_prob: 0.4191 loss_thr: 0.2891 loss_db: 0.0735 loss: 0.7817 2022/08/30 16:23:51 - mmengine - INFO - Epoch(train) [753][20/63] lr: 2.8804e-03 eta: 9:42:36 time: 1.0586 data_time: 0.0348 memory: 16201 loss_prob: 0.4276 loss_thr: 0.3129 loss_db: 0.0755 loss: 0.8159 2022/08/30 16:23:56 - mmengine - INFO - Epoch(train) [753][25/63] lr: 2.8804e-03 eta: 9:42:36 time: 1.1133 data_time: 0.0484 memory: 16201 loss_prob: 0.4240 loss_thr: 0.3018 loss_db: 0.0746 loss: 0.8004 2022/08/30 16:24:01 - mmengine - INFO - Epoch(train) [753][30/63] lr: 2.8804e-03 eta: 9:42:22 time: 1.0349 data_time: 0.0332 memory: 16201 loss_prob: 0.3772 loss_thr: 0.2696 loss_db: 0.0669 loss: 0.7138 2022/08/30 16:24:05 - mmengine - INFO - Epoch(train) [753][35/63] lr: 2.8804e-03 eta: 9:42:22 time: 0.9441 data_time: 0.0265 memory: 16201 loss_prob: 0.3824 loss_thr: 0.2842 loss_db: 0.0686 loss: 0.7351 2022/08/30 16:24:10 - mmengine - INFO - Epoch(train) [753][40/63] lr: 2.8804e-03 eta: 9:42:08 time: 0.8758 data_time: 0.0217 memory: 16201 loss_prob: 0.3828 loss_thr: 0.2855 loss_db: 0.0685 loss: 0.7368 2022/08/30 16:24:14 - mmengine - INFO - Epoch(train) [753][45/63] lr: 2.8804e-03 eta: 9:42:08 time: 0.8436 data_time: 0.0307 memory: 16201 loss_prob: 0.3664 loss_thr: 0.2630 loss_db: 0.0664 loss: 0.6958 2022/08/30 16:24:18 - mmengine - INFO - Epoch(train) [753][50/63] lr: 2.8804e-03 eta: 9:41:53 time: 0.8606 data_time: 0.0380 memory: 16201 loss_prob: 0.3821 loss_thr: 0.2668 loss_db: 0.0684 loss: 0.7173 2022/08/30 16:24:22 - mmengine - INFO - Epoch(train) [753][55/63] lr: 2.8804e-03 eta: 9:41:53 time: 0.8508 data_time: 0.0212 memory: 16201 loss_prob: 0.4151 loss_thr: 0.2997 loss_db: 0.0715 loss: 0.7864 2022/08/30 16:24:28 - mmengine - INFO - Epoch(train) [753][60/63] lr: 2.8804e-03 eta: 9:41:39 time: 0.9947 data_time: 0.0294 memory: 16201 loss_prob: 0.4209 loss_thr: 0.3164 loss_db: 0.0753 loss: 0.8127 2022/08/30 16:24:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:24:38 - mmengine - INFO - Epoch(train) [754][5/63] lr: 2.8746e-03 eta: 9:41:39 time: 1.2032 data_time: 0.2247 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2687 loss_db: 0.0637 loss: 0.6887 2022/08/30 16:24:44 - mmengine - INFO - Epoch(train) [754][10/63] lr: 2.8746e-03 eta: 9:41:22 time: 1.3226 data_time: 0.2514 memory: 16201 loss_prob: 0.3839 loss_thr: 0.2896 loss_db: 0.0678 loss: 0.7414 2022/08/30 16:24:49 - mmengine - INFO - Epoch(train) [754][15/63] lr: 2.8746e-03 eta: 9:41:22 time: 1.0747 data_time: 0.0372 memory: 16201 loss_prob: 0.3955 loss_thr: 0.2949 loss_db: 0.0706 loss: 0.7610 2022/08/30 16:24:55 - mmengine - INFO - Epoch(train) [754][20/63] lr: 2.8746e-03 eta: 9:41:08 time: 1.1025 data_time: 0.0269 memory: 16201 loss_prob: 0.4087 loss_thr: 0.2926 loss_db: 0.0713 loss: 0.7726 2022/08/30 16:25:00 - mmengine - INFO - Epoch(train) [754][25/63] lr: 2.8746e-03 eta: 9:41:08 time: 1.0985 data_time: 0.0542 memory: 16201 loss_prob: 0.4080 loss_thr: 0.2930 loss_db: 0.0716 loss: 0.7726 2022/08/30 16:25:05 - mmengine - INFO - Epoch(train) [754][30/63] lr: 2.8746e-03 eta: 9:40:55 time: 1.0680 data_time: 0.0417 memory: 16201 loss_prob: 0.3663 loss_thr: 0.2661 loss_db: 0.0650 loss: 0.6975 2022/08/30 16:25:11 - mmengine - INFO - Epoch(train) [754][35/63] lr: 2.8746e-03 eta: 9:40:55 time: 1.1049 data_time: 0.0298 memory: 16201 loss_prob: 0.3762 loss_thr: 0.2721 loss_db: 0.0659 loss: 0.7142 2022/08/30 16:25:16 - mmengine - INFO - Epoch(train) [754][40/63] lr: 2.8746e-03 eta: 9:40:42 time: 1.1186 data_time: 0.0393 memory: 16201 loss_prob: 0.3983 loss_thr: 0.2875 loss_db: 0.0703 loss: 0.7561 2022/08/30 16:25:21 - mmengine - INFO - Epoch(train) [754][45/63] lr: 2.8746e-03 eta: 9:40:42 time: 0.9903 data_time: 0.0342 memory: 16201 loss_prob: 0.3976 loss_thr: 0.2781 loss_db: 0.0700 loss: 0.7457 2022/08/30 16:25:25 - mmengine - INFO - Epoch(train) [754][50/63] lr: 2.8746e-03 eta: 9:40:27 time: 0.8497 data_time: 0.0316 memory: 16201 loss_prob: 0.3862 loss_thr: 0.2794 loss_db: 0.0696 loss: 0.7352 2022/08/30 16:25:29 - mmengine - INFO - Epoch(train) [754][55/63] lr: 2.8746e-03 eta: 9:40:27 time: 0.8547 data_time: 0.0300 memory: 16201 loss_prob: 0.3940 loss_thr: 0.2842 loss_db: 0.0704 loss: 0.7486 2022/08/30 16:25:34 - mmengine - INFO - Epoch(train) [754][60/63] lr: 2.8746e-03 eta: 9:40:13 time: 0.8693 data_time: 0.0344 memory: 16201 loss_prob: 0.4325 loss_thr: 0.2975 loss_db: 0.0741 loss: 0.8041 2022/08/30 16:25:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:25:43 - mmengine - INFO - Epoch(train) [755][5/63] lr: 2.8688e-03 eta: 9:40:13 time: 1.1079 data_time: 0.2378 memory: 16201 loss_prob: 0.4112 loss_thr: 0.2810 loss_db: 0.0724 loss: 0.7646 2022/08/30 16:25:49 - mmengine - INFO - Epoch(train) [755][10/63] lr: 2.8688e-03 eta: 9:39:55 time: 1.3272 data_time: 0.2581 memory: 16201 loss_prob: 0.3836 loss_thr: 0.2593 loss_db: 0.0671 loss: 0.7100 2022/08/30 16:25:55 - mmengine - INFO - Epoch(train) [755][15/63] lr: 2.8688e-03 eta: 9:39:55 time: 1.2007 data_time: 0.0349 memory: 16201 loss_prob: 0.3890 loss_thr: 0.2737 loss_db: 0.0677 loss: 0.7304 2022/08/30 16:26:00 - mmengine - INFO - Epoch(train) [755][20/63] lr: 2.8688e-03 eta: 9:39:42 time: 1.1185 data_time: 0.0379 memory: 16201 loss_prob: 0.4166 loss_thr: 0.2995 loss_db: 0.0740 loss: 0.7900 2022/08/30 16:26:06 - mmengine - INFO - Epoch(train) [755][25/63] lr: 2.8688e-03 eta: 9:39:42 time: 1.0979 data_time: 0.0425 memory: 16201 loss_prob: 0.4284 loss_thr: 0.2986 loss_db: 0.0770 loss: 0.8041 2022/08/30 16:26:12 - mmengine - INFO - Epoch(train) [755][30/63] lr: 2.8688e-03 eta: 9:39:29 time: 1.1168 data_time: 0.0366 memory: 16201 loss_prob: 0.4312 loss_thr: 0.2952 loss_db: 0.0750 loss: 0.8015 2022/08/30 16:26:18 - mmengine - INFO - Epoch(train) [755][35/63] lr: 2.8688e-03 eta: 9:39:29 time: 1.2205 data_time: 0.0523 memory: 16201 loss_prob: 0.4157 loss_thr: 0.2962 loss_db: 0.0735 loss: 0.7854 2022/08/30 16:26:23 - mmengine - INFO - Epoch(train) [755][40/63] lr: 2.8688e-03 eta: 9:39:16 time: 1.1707 data_time: 0.0414 memory: 16201 loss_prob: 0.4164 loss_thr: 0.3016 loss_db: 0.0738 loss: 0.7919 2022/08/30 16:26:28 - mmengine - INFO - Epoch(train) [755][45/63] lr: 2.8688e-03 eta: 9:39:16 time: 0.9976 data_time: 0.0307 memory: 16201 loss_prob: 0.3906 loss_thr: 0.2816 loss_db: 0.0679 loss: 0.7400 2022/08/30 16:26:32 - mmengine - INFO - Epoch(train) [755][50/63] lr: 2.8688e-03 eta: 9:39:01 time: 0.8776 data_time: 0.0312 memory: 16201 loss_prob: 0.4302 loss_thr: 0.3044 loss_db: 0.0767 loss: 0.8114 2022/08/30 16:26:36 - mmengine - INFO - Epoch(train) [755][55/63] lr: 2.8688e-03 eta: 9:39:01 time: 0.8119 data_time: 0.0251 memory: 16201 loss_prob: 0.4438 loss_thr: 0.3127 loss_db: 0.0797 loss: 0.8361 2022/08/30 16:26:41 - mmengine - INFO - Epoch(train) [755][60/63] lr: 2.8688e-03 eta: 9:38:47 time: 0.8844 data_time: 0.0311 memory: 16201 loss_prob: 0.3802 loss_thr: 0.2734 loss_db: 0.0669 loss: 0.7205 2022/08/30 16:26:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:26:50 - mmengine - INFO - Epoch(train) [756][5/63] lr: 2.8630e-03 eta: 9:38:47 time: 1.1581 data_time: 0.2145 memory: 16201 loss_prob: 0.3814 loss_thr: 0.2760 loss_db: 0.0684 loss: 0.7258 2022/08/30 16:26:57 - mmengine - INFO - Epoch(train) [756][10/63] lr: 2.8630e-03 eta: 9:38:29 time: 1.3261 data_time: 0.2285 memory: 16201 loss_prob: 0.3764 loss_thr: 0.2850 loss_db: 0.0673 loss: 0.7287 2022/08/30 16:27:03 - mmengine - INFO - Epoch(train) [756][15/63] lr: 2.8630e-03 eta: 9:38:29 time: 1.2063 data_time: 0.0357 memory: 16201 loss_prob: 0.3872 loss_thr: 0.2909 loss_db: 0.0689 loss: 0.7471 2022/08/30 16:27:08 - mmengine - INFO - Epoch(train) [756][20/63] lr: 2.8630e-03 eta: 9:38:16 time: 1.1378 data_time: 0.0312 memory: 16201 loss_prob: 0.3967 loss_thr: 0.2816 loss_db: 0.0698 loss: 0.7481 2022/08/30 16:27:13 - mmengine - INFO - Epoch(train) [756][25/63] lr: 2.8630e-03 eta: 9:38:16 time: 1.0766 data_time: 0.0292 memory: 16201 loss_prob: 0.4148 loss_thr: 0.2910 loss_db: 0.0730 loss: 0.7788 2022/08/30 16:27:20 - mmengine - INFO - Epoch(train) [756][30/63] lr: 2.8630e-03 eta: 9:38:03 time: 1.1607 data_time: 0.0369 memory: 16201 loss_prob: 0.4102 loss_thr: 0.2940 loss_db: 0.0727 loss: 0.7769 2022/08/30 16:27:24 - mmengine - INFO - Epoch(train) [756][35/63] lr: 2.8630e-03 eta: 9:38:03 time: 1.0941 data_time: 0.0482 memory: 16201 loss_prob: 0.3959 loss_thr: 0.2939 loss_db: 0.0690 loss: 0.7588 2022/08/30 16:27:29 - mmengine - INFO - Epoch(train) [756][40/63] lr: 2.8630e-03 eta: 9:37:49 time: 0.8966 data_time: 0.0278 memory: 16201 loss_prob: 0.3887 loss_thr: 0.2900 loss_db: 0.0672 loss: 0.7458 2022/08/30 16:27:33 - mmengine - INFO - Epoch(train) [756][45/63] lr: 2.8630e-03 eta: 9:37:49 time: 0.8468 data_time: 0.0252 memory: 16201 loss_prob: 0.3609 loss_thr: 0.2718 loss_db: 0.0635 loss: 0.6961 2022/08/30 16:27:38 - mmengine - INFO - Epoch(train) [756][50/63] lr: 2.8630e-03 eta: 9:37:35 time: 0.9499 data_time: 0.0385 memory: 16201 loss_prob: 0.4017 loss_thr: 0.2746 loss_db: 0.0671 loss: 0.7434 2022/08/30 16:27:42 - mmengine - INFO - Epoch(train) [756][55/63] lr: 2.8630e-03 eta: 9:37:35 time: 0.9621 data_time: 0.0389 memory: 16201 loss_prob: 0.4389 loss_thr: 0.2909 loss_db: 0.0724 loss: 0.8022 2022/08/30 16:27:47 - mmengine - INFO - Epoch(train) [756][60/63] lr: 2.8630e-03 eta: 9:37:20 time: 0.8492 data_time: 0.0296 memory: 16201 loss_prob: 0.3978 loss_thr: 0.2920 loss_db: 0.0702 loss: 0.7601 2022/08/30 16:27:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:27:57 - mmengine - INFO - Epoch(train) [757][5/63] lr: 2.8572e-03 eta: 9:37:20 time: 1.1862 data_time: 0.2422 memory: 16201 loss_prob: 0.3709 loss_thr: 0.2844 loss_db: 0.0669 loss: 0.7222 2022/08/30 16:28:02 - mmengine - INFO - Epoch(train) [757][10/63] lr: 2.8572e-03 eta: 9:37:03 time: 1.3743 data_time: 0.2577 memory: 16201 loss_prob: 0.3788 loss_thr: 0.2910 loss_db: 0.0679 loss: 0.7377 2022/08/30 16:28:08 - mmengine - INFO - Epoch(train) [757][15/63] lr: 2.8572e-03 eta: 9:37:03 time: 1.1722 data_time: 0.0343 memory: 16201 loss_prob: 0.3611 loss_thr: 0.2774 loss_db: 0.0648 loss: 0.7034 2022/08/30 16:28:13 - mmengine - INFO - Epoch(train) [757][20/63] lr: 2.8572e-03 eta: 9:36:49 time: 1.0986 data_time: 0.0317 memory: 16201 loss_prob: 0.3529 loss_thr: 0.2828 loss_db: 0.0640 loss: 0.6996 2022/08/30 16:28:18 - mmengine - INFO - Epoch(train) [757][25/63] lr: 2.8572e-03 eta: 9:36:49 time: 0.9314 data_time: 0.0355 memory: 16201 loss_prob: 0.4130 loss_thr: 0.3005 loss_db: 0.0723 loss: 0.7858 2022/08/30 16:28:22 - mmengine - INFO - Epoch(train) [757][30/63] lr: 2.8572e-03 eta: 9:36:35 time: 0.8598 data_time: 0.0233 memory: 16201 loss_prob: 0.4548 loss_thr: 0.3020 loss_db: 0.0787 loss: 0.8354 2022/08/30 16:28:27 - mmengine - INFO - Epoch(train) [757][35/63] lr: 2.8572e-03 eta: 9:36:35 time: 0.9078 data_time: 0.0347 memory: 16201 loss_prob: 0.4072 loss_thr: 0.2848 loss_db: 0.0730 loss: 0.7650 2022/08/30 16:28:32 - mmengine - INFO - Epoch(train) [757][40/63] lr: 2.8572e-03 eta: 9:36:21 time: 0.9754 data_time: 0.0361 memory: 16201 loss_prob: 0.3750 loss_thr: 0.2748 loss_db: 0.0680 loss: 0.7178 2022/08/30 16:28:38 - mmengine - INFO - Epoch(train) [757][45/63] lr: 2.8572e-03 eta: 9:36:21 time: 1.1028 data_time: 0.0255 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2879 loss_db: 0.0713 loss: 0.7628 2022/08/30 16:28:44 - mmengine - INFO - Epoch(train) [757][50/63] lr: 2.8572e-03 eta: 9:36:08 time: 1.1938 data_time: 0.0387 memory: 16201 loss_prob: 0.3962 loss_thr: 0.2848 loss_db: 0.0700 loss: 0.7509 2022/08/30 16:28:50 - mmengine - INFO - Epoch(train) [757][55/63] lr: 2.8572e-03 eta: 9:36:08 time: 1.1656 data_time: 0.0385 memory: 16201 loss_prob: 0.4017 loss_thr: 0.2969 loss_db: 0.0713 loss: 0.7699 2022/08/30 16:28:54 - mmengine - INFO - Epoch(train) [757][60/63] lr: 2.8572e-03 eta: 9:35:55 time: 1.0379 data_time: 0.0378 memory: 16201 loss_prob: 0.3931 loss_thr: 0.2935 loss_db: 0.0692 loss: 0.7558 2022/08/30 16:28:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:29:03 - mmengine - INFO - Epoch(train) [758][5/63] lr: 2.8513e-03 eta: 9:35:55 time: 1.0522 data_time: 0.2580 memory: 16201 loss_prob: 0.3495 loss_thr: 0.2706 loss_db: 0.0608 loss: 0.6810 2022/08/30 16:29:07 - mmengine - INFO - Epoch(train) [758][10/63] lr: 2.8513e-03 eta: 9:35:36 time: 1.1211 data_time: 0.2694 memory: 16201 loss_prob: 0.3755 loss_thr: 0.2831 loss_db: 0.0657 loss: 0.7243 2022/08/30 16:29:13 - mmengine - INFO - Epoch(train) [758][15/63] lr: 2.8513e-03 eta: 9:35:36 time: 0.9993 data_time: 0.0260 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2770 loss_db: 0.0681 loss: 0.7296 2022/08/30 16:29:19 - mmengine - INFO - Epoch(train) [758][20/63] lr: 2.8513e-03 eta: 9:35:23 time: 1.1639 data_time: 0.0266 memory: 16201 loss_prob: 0.4148 loss_thr: 0.2987 loss_db: 0.0731 loss: 0.7866 2022/08/30 16:29:24 - mmengine - INFO - Epoch(train) [758][25/63] lr: 2.8513e-03 eta: 9:35:23 time: 1.1163 data_time: 0.0405 memory: 16201 loss_prob: 0.4176 loss_thr: 0.3190 loss_db: 0.0734 loss: 0.8100 2022/08/30 16:29:29 - mmengine - INFO - Epoch(train) [758][30/63] lr: 2.8513e-03 eta: 9:35:09 time: 1.0013 data_time: 0.0334 memory: 16201 loss_prob: 0.3996 loss_thr: 0.3018 loss_db: 0.0725 loss: 0.7740 2022/08/30 16:29:35 - mmengine - INFO - Epoch(train) [758][35/63] lr: 2.8513e-03 eta: 9:35:09 time: 1.1381 data_time: 0.0413 memory: 16201 loss_prob: 0.4017 loss_thr: 0.2836 loss_db: 0.0743 loss: 0.7596 2022/08/30 16:29:41 - mmengine - INFO - Epoch(train) [758][40/63] lr: 2.8513e-03 eta: 9:34:56 time: 1.1668 data_time: 0.0362 memory: 16201 loss_prob: 0.4337 loss_thr: 0.2906 loss_db: 0.0739 loss: 0.7982 2022/08/30 16:29:47 - mmengine - INFO - Epoch(train) [758][45/63] lr: 2.8513e-03 eta: 9:34:56 time: 1.1564 data_time: 0.0353 memory: 16201 loss_prob: 0.4361 loss_thr: 0.2981 loss_db: 0.0741 loss: 0.8083 2022/08/30 16:29:52 - mmengine - INFO - Epoch(train) [758][50/63] lr: 2.8513e-03 eta: 9:34:43 time: 1.1319 data_time: 0.0514 memory: 16201 loss_prob: 0.4215 loss_thr: 0.3026 loss_db: 0.0771 loss: 0.8012 2022/08/30 16:29:56 - mmengine - INFO - Epoch(train) [758][55/63] lr: 2.8513e-03 eta: 9:34:43 time: 0.9296 data_time: 0.0326 memory: 16201 loss_prob: 0.4474 loss_thr: 0.3169 loss_db: 0.0810 loss: 0.8453 2022/08/30 16:30:01 - mmengine - INFO - Epoch(train) [758][60/63] lr: 2.8513e-03 eta: 9:34:29 time: 0.8779 data_time: 0.0265 memory: 16201 loss_prob: 0.4124 loss_thr: 0.2944 loss_db: 0.0723 loss: 0.7790 2022/08/30 16:30:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:30:09 - mmengine - INFO - Epoch(train) [759][5/63] lr: 2.8455e-03 eta: 9:34:29 time: 0.9873 data_time: 0.1918 memory: 16201 loss_prob: 0.4139 loss_thr: 0.2846 loss_db: 0.0735 loss: 0.7720 2022/08/30 16:30:13 - mmengine - INFO - Epoch(train) [759][10/63] lr: 2.8455e-03 eta: 9:34:09 time: 1.0040 data_time: 0.1961 memory: 16201 loss_prob: 0.4240 loss_thr: 0.2979 loss_db: 0.0759 loss: 0.7978 2022/08/30 16:30:18 - mmengine - INFO - Epoch(train) [759][15/63] lr: 2.8455e-03 eta: 9:34:09 time: 0.8814 data_time: 0.0258 memory: 16201 loss_prob: 0.4157 loss_thr: 0.3036 loss_db: 0.0732 loss: 0.7925 2022/08/30 16:30:23 - mmengine - INFO - Epoch(train) [759][20/63] lr: 2.8455e-03 eta: 9:33:56 time: 1.0269 data_time: 0.0294 memory: 16201 loss_prob: 0.3900 loss_thr: 0.2882 loss_db: 0.0697 loss: 0.7479 2022/08/30 16:30:29 - mmengine - INFO - Epoch(train) [759][25/63] lr: 2.8455e-03 eta: 9:33:56 time: 1.1602 data_time: 0.0428 memory: 16201 loss_prob: 0.4068 loss_thr: 0.2932 loss_db: 0.0728 loss: 0.7728 2022/08/30 16:30:35 - mmengine - INFO - Epoch(train) [759][30/63] lr: 2.8455e-03 eta: 9:33:43 time: 1.1317 data_time: 0.0327 memory: 16201 loss_prob: 0.4031 loss_thr: 0.2932 loss_db: 0.0724 loss: 0.7687 2022/08/30 16:30:40 - mmengine - INFO - Epoch(train) [759][35/63] lr: 2.8455e-03 eta: 9:33:43 time: 1.1103 data_time: 0.0360 memory: 16201 loss_prob: 0.3832 loss_thr: 0.2867 loss_db: 0.0673 loss: 0.7371 2022/08/30 16:30:46 - mmengine - INFO - Epoch(train) [759][40/63] lr: 2.8455e-03 eta: 9:33:29 time: 1.0729 data_time: 0.0394 memory: 16201 loss_prob: 0.4115 loss_thr: 0.2962 loss_db: 0.0716 loss: 0.7793 2022/08/30 16:30:50 - mmengine - INFO - Epoch(train) [759][45/63] lr: 2.8455e-03 eta: 9:33:29 time: 0.9063 data_time: 0.0331 memory: 16201 loss_prob: 0.4080 loss_thr: 0.2868 loss_db: 0.0717 loss: 0.7665 2022/08/30 16:30:54 - mmengine - INFO - Epoch(train) [759][50/63] lr: 2.8455e-03 eta: 9:33:15 time: 0.8207 data_time: 0.0332 memory: 16201 loss_prob: 0.4317 loss_thr: 0.2882 loss_db: 0.0749 loss: 0.7949 2022/08/30 16:30:58 - mmengine - INFO - Epoch(train) [759][55/63] lr: 2.8455e-03 eta: 9:33:15 time: 0.8291 data_time: 0.0247 memory: 16201 loss_prob: 0.4380 loss_thr: 0.3034 loss_db: 0.0760 loss: 0.8174 2022/08/30 16:31:02 - mmengine - INFO - Epoch(train) [759][60/63] lr: 2.8455e-03 eta: 9:33:00 time: 0.8256 data_time: 0.0286 memory: 16201 loss_prob: 0.4326 loss_thr: 0.3160 loss_db: 0.0741 loss: 0.8226 2022/08/30 16:31:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:31:13 - mmengine - INFO - Epoch(train) [760][5/63] lr: 2.8397e-03 eta: 9:33:00 time: 1.2289 data_time: 0.2391 memory: 16201 loss_prob: 0.4070 loss_thr: 0.2989 loss_db: 0.0713 loss: 0.7772 2022/08/30 16:31:19 - mmengine - INFO - Epoch(train) [760][10/63] lr: 2.8397e-03 eta: 9:32:43 time: 1.4522 data_time: 0.2612 memory: 16201 loss_prob: 0.3956 loss_thr: 0.2810 loss_db: 0.0682 loss: 0.7448 2022/08/30 16:31:25 - mmengine - INFO - Epoch(train) [760][15/63] lr: 2.8397e-03 eta: 9:32:43 time: 1.1840 data_time: 0.0381 memory: 16201 loss_prob: 0.4132 loss_thr: 0.2842 loss_db: 0.0724 loss: 0.7698 2022/08/30 16:31:30 - mmengine - INFO - Epoch(train) [760][20/63] lr: 2.8397e-03 eta: 9:32:30 time: 1.1150 data_time: 0.0300 memory: 16201 loss_prob: 0.4098 loss_thr: 0.2879 loss_db: 0.0729 loss: 0.7706 2022/08/30 16:31:36 - mmengine - INFO - Epoch(train) [760][25/63] lr: 2.8397e-03 eta: 9:32:30 time: 1.1381 data_time: 0.0330 memory: 16201 loss_prob: 0.4060 loss_thr: 0.2936 loss_db: 0.0713 loss: 0.7709 2022/08/30 16:31:41 - mmengine - INFO - Epoch(train) [760][30/63] lr: 2.8397e-03 eta: 9:32:16 time: 1.0337 data_time: 0.0338 memory: 16201 loss_prob: 0.4134 loss_thr: 0.2955 loss_db: 0.0748 loss: 0.7836 2022/08/30 16:31:45 - mmengine - INFO - Epoch(train) [760][35/63] lr: 2.8397e-03 eta: 9:32:16 time: 0.9134 data_time: 0.0325 memory: 16201 loss_prob: 0.4102 loss_thr: 0.2967 loss_db: 0.0733 loss: 0.7802 2022/08/30 16:31:50 - mmengine - INFO - Epoch(train) [760][40/63] lr: 2.8397e-03 eta: 9:32:02 time: 0.9447 data_time: 0.0246 memory: 16201 loss_prob: 0.4053 loss_thr: 0.3023 loss_db: 0.0714 loss: 0.7791 2022/08/30 16:31:54 - mmengine - INFO - Epoch(train) [760][45/63] lr: 2.8397e-03 eta: 9:32:02 time: 0.9408 data_time: 0.0355 memory: 16201 loss_prob: 0.4465 loss_thr: 0.3200 loss_db: 0.0779 loss: 0.8443 2022/08/30 16:31:59 - mmengine - INFO - Epoch(train) [760][50/63] lr: 2.8397e-03 eta: 9:31:48 time: 0.8791 data_time: 0.0354 memory: 16201 loss_prob: 0.4511 loss_thr: 0.3152 loss_db: 0.0795 loss: 0.8458 2022/08/30 16:32:03 - mmengine - INFO - Epoch(train) [760][55/63] lr: 2.8397e-03 eta: 9:31:48 time: 0.8681 data_time: 0.0218 memory: 16201 loss_prob: 0.4106 loss_thr: 0.2938 loss_db: 0.0732 loss: 0.7776 2022/08/30 16:32:09 - mmengine - INFO - Epoch(train) [760][60/63] lr: 2.8397e-03 eta: 9:31:34 time: 1.0056 data_time: 0.0314 memory: 16201 loss_prob: 0.4127 loss_thr: 0.2924 loss_db: 0.0721 loss: 0.7773 2022/08/30 16:32:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:32:11 - mmengine - INFO - Saving checkpoint at 760 epochs 2022/08/30 16:32:21 - mmengine - INFO - Epoch(val) [760][5/32] eta: 9:31:34 time: 0.7030 data_time: 0.1052 memory: 16201 2022/08/30 16:32:24 - mmengine - INFO - Epoch(val) [760][10/32] eta: 0:00:18 time: 0.8293 data_time: 0.1642 memory: 15734 2022/08/30 16:32:28 - mmengine - INFO - Epoch(val) [760][15/32] eta: 0:00:18 time: 0.7000 data_time: 0.0770 memory: 15734 2022/08/30 16:32:31 - mmengine - INFO - Epoch(val) [760][20/32] eta: 0:00:08 time: 0.6875 data_time: 0.0658 memory: 15734 2022/08/30 16:32:34 - mmengine - INFO - Epoch(val) [760][25/32] eta: 0:00:08 time: 0.6580 data_time: 0.0627 memory: 15734 2022/08/30 16:32:37 - mmengine - INFO - Epoch(val) [760][30/32] eta: 0:00:01 time: 0.5979 data_time: 0.0258 memory: 15734 2022/08/30 16:32:38 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 16:32:38 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8580, precision: 0.7931, hmean: 0.8242 2022/08/30 16:32:38 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8580, precision: 0.8292, hmean: 0.8434 2022/08/30 16:32:38 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8575, precision: 0.8501, hmean: 0.8538 2022/08/30 16:32:38 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8546, precision: 0.8731, hmean: 0.8637 2022/08/30 16:32:38 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8440, precision: 0.8889, hmean: 0.8659 2022/08/30 16:32:38 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7992, precision: 0.9222, hmean: 0.8563 2022/08/30 16:32:38 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2894, precision: 0.9647, hmean: 0.4452 2022/08/30 16:32:38 - mmengine - INFO - Epoch(val) [760][32/32] icdar/precision: 0.8889 icdar/recall: 0.8440 icdar/hmean: 0.8659 2022/08/30 16:32:46 - mmengine - INFO - Epoch(train) [761][5/63] lr: 2.8339e-03 eta: 0:00:01 time: 1.2218 data_time: 0.1928 memory: 16201 loss_prob: 0.4269 loss_thr: 0.3022 loss_db: 0.0753 loss: 0.8044 2022/08/30 16:32:51 - mmengine - INFO - Epoch(train) [761][10/63] lr: 2.8339e-03 eta: 9:31:16 time: 1.3179 data_time: 0.1966 memory: 16201 loss_prob: 0.4312 loss_thr: 0.3067 loss_db: 0.0748 loss: 0.8127 2022/08/30 16:32:56 - mmengine - INFO - Epoch(train) [761][15/63] lr: 2.8339e-03 eta: 9:31:16 time: 1.0620 data_time: 0.0375 memory: 16201 loss_prob: 0.4083 loss_thr: 0.2945 loss_db: 0.0722 loss: 0.7750 2022/08/30 16:33:02 - mmengine - INFO - Epoch(train) [761][20/63] lr: 2.8339e-03 eta: 9:31:03 time: 1.0355 data_time: 0.0360 memory: 16201 loss_prob: 0.4163 loss_thr: 0.2924 loss_db: 0.0729 loss: 0.7815 2022/08/30 16:33:06 - mmengine - INFO - Epoch(train) [761][25/63] lr: 2.8339e-03 eta: 9:31:03 time: 1.0064 data_time: 0.0297 memory: 16201 loss_prob: 0.4143 loss_thr: 0.2908 loss_db: 0.0740 loss: 0.7792 2022/08/30 16:33:11 - mmengine - INFO - Epoch(train) [761][30/63] lr: 2.8339e-03 eta: 9:30:48 time: 0.9153 data_time: 0.0301 memory: 16201 loss_prob: 0.3851 loss_thr: 0.2769 loss_db: 0.0693 loss: 0.7313 2022/08/30 16:33:17 - mmengine - INFO - Epoch(train) [761][35/63] lr: 2.8339e-03 eta: 9:30:48 time: 1.0010 data_time: 0.0286 memory: 16201 loss_prob: 0.3632 loss_thr: 0.2677 loss_db: 0.0643 loss: 0.6952 2022/08/30 16:33:22 - mmengine - INFO - Epoch(train) [761][40/63] lr: 2.8339e-03 eta: 9:30:35 time: 1.1248 data_time: 0.0388 memory: 16201 loss_prob: 0.3770 loss_thr: 0.2690 loss_db: 0.0669 loss: 0.7130 2022/08/30 16:33:28 - mmengine - INFO - Epoch(train) [761][45/63] lr: 2.8339e-03 eta: 9:30:35 time: 1.1295 data_time: 0.0414 memory: 16201 loss_prob: 0.4222 loss_thr: 0.2901 loss_db: 0.0750 loss: 0.7873 2022/08/30 16:33:34 - mmengine - INFO - Epoch(train) [761][50/63] lr: 2.8339e-03 eta: 9:30:23 time: 1.1461 data_time: 0.0352 memory: 16201 loss_prob: 0.3969 loss_thr: 0.2872 loss_db: 0.0696 loss: 0.7537 2022/08/30 16:33:39 - mmengine - INFO - Epoch(train) [761][55/63] lr: 2.8339e-03 eta: 9:30:23 time: 1.1341 data_time: 0.0402 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2858 loss_db: 0.0655 loss: 0.7251 2022/08/30 16:33:43 - mmengine - INFO - Epoch(train) [761][60/63] lr: 2.8339e-03 eta: 9:30:09 time: 0.9896 data_time: 0.0453 memory: 16201 loss_prob: 0.4233 loss_thr: 0.2982 loss_db: 0.0762 loss: 0.7976 2022/08/30 16:33:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:33:52 - mmengine - INFO - Epoch(train) [762][5/63] lr: 2.8281e-03 eta: 9:30:09 time: 1.0083 data_time: 0.2240 memory: 16201 loss_prob: 0.4700 loss_thr: 0.3168 loss_db: 0.0807 loss: 0.8675 2022/08/30 16:33:57 - mmengine - INFO - Epoch(train) [762][10/63] lr: 2.8281e-03 eta: 9:29:50 time: 1.1117 data_time: 0.2321 memory: 16201 loss_prob: 0.4377 loss_thr: 0.3096 loss_db: 0.0767 loss: 0.8240 2022/08/30 16:34:02 - mmengine - INFO - Epoch(train) [762][15/63] lr: 2.8281e-03 eta: 9:29:50 time: 0.9988 data_time: 0.0281 memory: 16201 loss_prob: 0.4136 loss_thr: 0.2946 loss_db: 0.0731 loss: 0.7813 2022/08/30 16:34:07 - mmengine - INFO - Epoch(train) [762][20/63] lr: 2.8281e-03 eta: 9:29:37 time: 1.0831 data_time: 0.0333 memory: 16201 loss_prob: 0.3998 loss_thr: 0.2993 loss_db: 0.0699 loss: 0.7690 2022/08/30 16:34:13 - mmengine - INFO - Epoch(train) [762][25/63] lr: 2.8281e-03 eta: 9:29:37 time: 1.1113 data_time: 0.0467 memory: 16201 loss_prob: 0.3855 loss_thr: 0.2950 loss_db: 0.0690 loss: 0.7494 2022/08/30 16:34:18 - mmengine - INFO - Epoch(train) [762][30/63] lr: 2.8281e-03 eta: 9:29:23 time: 1.0786 data_time: 0.0446 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2906 loss_db: 0.0717 loss: 0.7587 2022/08/30 16:34:24 - mmengine - INFO - Epoch(train) [762][35/63] lr: 2.8281e-03 eta: 9:29:23 time: 1.0786 data_time: 0.0440 memory: 16201 loss_prob: 0.4154 loss_thr: 0.2983 loss_db: 0.0739 loss: 0.7877 2022/08/30 16:34:28 - mmengine - INFO - Epoch(train) [762][40/63] lr: 2.8281e-03 eta: 9:29:10 time: 1.0259 data_time: 0.0327 memory: 16201 loss_prob: 0.4004 loss_thr: 0.2818 loss_db: 0.0695 loss: 0.7517 2022/08/30 16:34:33 - mmengine - INFO - Epoch(train) [762][45/63] lr: 2.8281e-03 eta: 9:29:10 time: 0.9044 data_time: 0.0240 memory: 16201 loss_prob: 0.3899 loss_thr: 0.2748 loss_db: 0.0673 loss: 0.7319 2022/08/30 16:34:37 - mmengine - INFO - Epoch(train) [762][50/63] lr: 2.8281e-03 eta: 9:28:55 time: 0.8930 data_time: 0.0326 memory: 16201 loss_prob: 0.4042 loss_thr: 0.2983 loss_db: 0.0714 loss: 0.7738 2022/08/30 16:34:42 - mmengine - INFO - Epoch(train) [762][55/63] lr: 2.8281e-03 eta: 9:28:55 time: 0.9703 data_time: 0.0311 memory: 16201 loss_prob: 0.3995 loss_thr: 0.2901 loss_db: 0.0717 loss: 0.7613 2022/08/30 16:34:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:34:47 - mmengine - INFO - Epoch(train) [762][60/63] lr: 2.8281e-03 eta: 9:28:41 time: 0.9665 data_time: 0.0284 memory: 16201 loss_prob: 0.3615 loss_thr: 0.2545 loss_db: 0.0643 loss: 0.6804 2022/08/30 16:34:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:34:57 - mmengine - INFO - Epoch(train) [763][5/63] lr: 2.8223e-03 eta: 9:28:41 time: 1.1529 data_time: 0.2497 memory: 16201 loss_prob: 0.3951 loss_thr: 0.2748 loss_db: 0.0716 loss: 0.7414 2022/08/30 16:35:02 - mmengine - INFO - Epoch(train) [763][10/63] lr: 2.8223e-03 eta: 9:28:23 time: 1.2186 data_time: 0.2610 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2888 loss_db: 0.0716 loss: 0.7631 2022/08/30 16:35:07 - mmengine - INFO - Epoch(train) [763][15/63] lr: 2.8223e-03 eta: 9:28:23 time: 1.0268 data_time: 0.0281 memory: 16201 loss_prob: 0.3822 loss_thr: 0.2849 loss_db: 0.0668 loss: 0.7339 2022/08/30 16:35:12 - mmengine - INFO - Epoch(train) [763][20/63] lr: 2.8223e-03 eta: 9:28:10 time: 1.0524 data_time: 0.0337 memory: 16201 loss_prob: 0.3600 loss_thr: 0.2772 loss_db: 0.0653 loss: 0.7025 2022/08/30 16:35:17 - mmengine - INFO - Epoch(train) [763][25/63] lr: 2.8223e-03 eta: 9:28:10 time: 0.9901 data_time: 0.0335 memory: 16201 loss_prob: 0.3790 loss_thr: 0.2816 loss_db: 0.0691 loss: 0.7296 2022/08/30 16:35:22 - mmengine - INFO - Epoch(train) [763][30/63] lr: 2.8223e-03 eta: 9:27:56 time: 1.0073 data_time: 0.0242 memory: 16201 loss_prob: 0.4054 loss_thr: 0.3001 loss_db: 0.0712 loss: 0.7766 2022/08/30 16:35:27 - mmengine - INFO - Epoch(train) [763][35/63] lr: 2.8223e-03 eta: 9:27:56 time: 0.9716 data_time: 0.0394 memory: 16201 loss_prob: 0.4234 loss_thr: 0.3096 loss_db: 0.0735 loss: 0.8066 2022/08/30 16:35:31 - mmengine - INFO - Epoch(train) [763][40/63] lr: 2.8223e-03 eta: 9:27:41 time: 0.8500 data_time: 0.0310 memory: 16201 loss_prob: 0.4004 loss_thr: 0.2950 loss_db: 0.0715 loss: 0.7670 2022/08/30 16:35:35 - mmengine - INFO - Epoch(train) [763][45/63] lr: 2.8223e-03 eta: 9:27:41 time: 0.8385 data_time: 0.0231 memory: 16201 loss_prob: 0.3787 loss_thr: 0.2913 loss_db: 0.0684 loss: 0.7383 2022/08/30 16:35:40 - mmengine - INFO - Epoch(train) [763][50/63] lr: 2.8223e-03 eta: 9:27:27 time: 0.8989 data_time: 0.0358 memory: 16201 loss_prob: 0.3769 loss_thr: 0.2769 loss_db: 0.0669 loss: 0.7207 2022/08/30 16:35:46 - mmengine - INFO - Epoch(train) [763][55/63] lr: 2.8223e-03 eta: 9:27:27 time: 1.0934 data_time: 0.0339 memory: 16201 loss_prob: 0.4071 loss_thr: 0.2860 loss_db: 0.0708 loss: 0.7638 2022/08/30 16:35:52 - mmengine - INFO - Epoch(train) [763][60/63] lr: 2.8223e-03 eta: 9:27:15 time: 1.2639 data_time: 0.0516 memory: 16201 loss_prob: 0.3857 loss_thr: 0.2747 loss_db: 0.0680 loss: 0.7284 2022/08/30 16:35:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:36:04 - mmengine - INFO - Epoch(train) [764][5/63] lr: 2.8165e-03 eta: 9:27:15 time: 1.3387 data_time: 0.2474 memory: 16201 loss_prob: 0.3848 loss_thr: 0.2704 loss_db: 0.0667 loss: 0.7219 2022/08/30 16:36:10 - mmengine - INFO - Epoch(train) [764][10/63] lr: 2.8165e-03 eta: 9:26:58 time: 1.5135 data_time: 0.2599 memory: 16201 loss_prob: 0.4024 loss_thr: 0.2928 loss_db: 0.0707 loss: 0.7659 2022/08/30 16:36:16 - mmengine - INFO - Epoch(train) [764][15/63] lr: 2.8165e-03 eta: 9:26:58 time: 1.2764 data_time: 0.0336 memory: 16201 loss_prob: 0.3848 loss_thr: 0.2801 loss_db: 0.0710 loss: 0.7360 2022/08/30 16:36:22 - mmengine - INFO - Epoch(train) [764][20/63] lr: 2.8165e-03 eta: 9:26:46 time: 1.1498 data_time: 0.0396 memory: 16201 loss_prob: 0.4240 loss_thr: 0.2875 loss_db: 0.0745 loss: 0.7860 2022/08/30 16:36:26 - mmengine - INFO - Epoch(train) [764][25/63] lr: 2.8165e-03 eta: 9:26:46 time: 0.9438 data_time: 0.0421 memory: 16201 loss_prob: 0.4284 loss_thr: 0.2904 loss_db: 0.0735 loss: 0.7923 2022/08/30 16:36:30 - mmengine - INFO - Epoch(train) [764][30/63] lr: 2.8165e-03 eta: 9:26:31 time: 0.8243 data_time: 0.0174 memory: 16201 loss_prob: 0.3427 loss_thr: 0.2511 loss_db: 0.0629 loss: 0.6567 2022/08/30 16:36:34 - mmengine - INFO - Epoch(train) [764][35/63] lr: 2.8165e-03 eta: 9:26:31 time: 0.8318 data_time: 0.0259 memory: 16201 loss_prob: 0.3633 loss_thr: 0.2672 loss_db: 0.0671 loss: 0.6977 2022/08/30 16:36:39 - mmengine - INFO - Epoch(train) [764][40/63] lr: 2.8165e-03 eta: 9:26:17 time: 0.8980 data_time: 0.0398 memory: 16201 loss_prob: 0.4193 loss_thr: 0.3010 loss_db: 0.0741 loss: 0.7944 2022/08/30 16:36:43 - mmengine - INFO - Epoch(train) [764][45/63] lr: 2.8165e-03 eta: 9:26:17 time: 0.9349 data_time: 0.0328 memory: 16201 loss_prob: 0.4671 loss_thr: 0.3124 loss_db: 0.0821 loss: 0.8616 2022/08/30 16:36:48 - mmengine - INFO - Epoch(train) [764][50/63] lr: 2.8165e-03 eta: 9:26:02 time: 0.9371 data_time: 0.0402 memory: 16201 loss_prob: 0.4631 loss_thr: 0.3198 loss_db: 0.0818 loss: 0.8647 2022/08/30 16:36:54 - mmengine - INFO - Epoch(train) [764][55/63] lr: 2.8165e-03 eta: 9:26:02 time: 1.0137 data_time: 0.0368 memory: 16201 loss_prob: 0.4419 loss_thr: 0.3253 loss_db: 0.0774 loss: 0.8446 2022/08/30 16:36:59 - mmengine - INFO - Epoch(train) [764][60/63] lr: 2.8165e-03 eta: 9:25:49 time: 1.0797 data_time: 0.0358 memory: 16201 loss_prob: 0.4489 loss_thr: 0.3039 loss_db: 0.0750 loss: 0.8277 2022/08/30 16:37:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:37:08 - mmengine - INFO - Epoch(train) [765][5/63] lr: 2.8107e-03 eta: 9:25:49 time: 1.0206 data_time: 0.2255 memory: 16201 loss_prob: 0.4187 loss_thr: 0.2901 loss_db: 0.0761 loss: 0.7849 2022/08/30 16:37:13 - mmengine - INFO - Epoch(train) [765][10/63] lr: 2.8107e-03 eta: 9:25:31 time: 1.1774 data_time: 0.2369 memory: 16201 loss_prob: 0.4035 loss_thr: 0.2784 loss_db: 0.0733 loss: 0.7553 2022/08/30 16:37:19 - mmengine - INFO - Epoch(train) [765][15/63] lr: 2.8107e-03 eta: 9:25:31 time: 1.1411 data_time: 0.0341 memory: 16201 loss_prob: 0.3655 loss_thr: 0.2624 loss_db: 0.0638 loss: 0.6917 2022/08/30 16:37:24 - mmengine - INFO - Epoch(train) [765][20/63] lr: 2.8107e-03 eta: 9:25:18 time: 1.1069 data_time: 0.0340 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2887 loss_db: 0.0694 loss: 0.7534 2022/08/30 16:37:28 - mmengine - INFO - Epoch(train) [765][25/63] lr: 2.8107e-03 eta: 9:25:18 time: 0.9133 data_time: 0.0390 memory: 16201 loss_prob: 0.4006 loss_thr: 0.2960 loss_db: 0.0716 loss: 0.7682 2022/08/30 16:37:34 - mmengine - INFO - Epoch(train) [765][30/63] lr: 2.8107e-03 eta: 9:25:04 time: 0.9605 data_time: 0.0266 memory: 16201 loss_prob: 0.3898 loss_thr: 0.2877 loss_db: 0.0668 loss: 0.7443 2022/08/30 16:37:39 - mmengine - INFO - Epoch(train) [765][35/63] lr: 2.8107e-03 eta: 9:25:04 time: 1.0682 data_time: 0.0407 memory: 16201 loss_prob: 0.4220 loss_thr: 0.3119 loss_db: 0.0714 loss: 0.8053 2022/08/30 16:37:43 - mmengine - INFO - Epoch(train) [765][40/63] lr: 2.8107e-03 eta: 9:24:50 time: 0.9778 data_time: 0.0392 memory: 16201 loss_prob: 0.4290 loss_thr: 0.3085 loss_db: 0.0767 loss: 0.8143 2022/08/30 16:37:48 - mmengine - INFO - Epoch(train) [765][45/63] lr: 2.8107e-03 eta: 9:24:50 time: 0.9092 data_time: 0.0207 memory: 16201 loss_prob: 0.4089 loss_thr: 0.2865 loss_db: 0.0738 loss: 0.7693 2022/08/30 16:37:53 - mmengine - INFO - Epoch(train) [765][50/63] lr: 2.8107e-03 eta: 9:24:36 time: 0.9405 data_time: 0.0351 memory: 16201 loss_prob: 0.3996 loss_thr: 0.2869 loss_db: 0.0708 loss: 0.7574 2022/08/30 16:37:59 - mmengine - INFO - Epoch(train) [765][55/63] lr: 2.8107e-03 eta: 9:24:36 time: 1.0735 data_time: 0.0319 memory: 16201 loss_prob: 0.4117 loss_thr: 0.2980 loss_db: 0.0734 loss: 0.7831 2022/08/30 16:38:04 - mmengine - INFO - Epoch(train) [765][60/63] lr: 2.8107e-03 eta: 9:24:23 time: 1.1277 data_time: 0.0291 memory: 16201 loss_prob: 0.4213 loss_thr: 0.2999 loss_db: 0.0739 loss: 0.7952 2022/08/30 16:38:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:38:15 - mmengine - INFO - Epoch(train) [766][5/63] lr: 2.8049e-03 eta: 9:24:23 time: 1.3140 data_time: 0.2545 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2932 loss_db: 0.0710 loss: 0.7606 2022/08/30 16:38:20 - mmengine - INFO - Epoch(train) [766][10/63] lr: 2.8049e-03 eta: 9:24:05 time: 1.2089 data_time: 0.2601 memory: 16201 loss_prob: 0.4064 loss_thr: 0.2976 loss_db: 0.0725 loss: 0.7765 2022/08/30 16:38:24 - mmengine - INFO - Epoch(train) [766][15/63] lr: 2.8049e-03 eta: 9:24:05 time: 0.8821 data_time: 0.0288 memory: 16201 loss_prob: 0.4127 loss_thr: 0.3071 loss_db: 0.0735 loss: 0.7934 2022/08/30 16:38:29 - mmengine - INFO - Epoch(train) [766][20/63] lr: 2.8049e-03 eta: 9:23:50 time: 0.9019 data_time: 0.0697 memory: 16201 loss_prob: 0.4200 loss_thr: 0.3075 loss_db: 0.0754 loss: 0.8028 2022/08/30 16:38:34 - mmengine - INFO - Epoch(train) [766][25/63] lr: 2.8049e-03 eta: 9:23:50 time: 1.0250 data_time: 0.0905 memory: 16201 loss_prob: 0.4102 loss_thr: 0.3011 loss_db: 0.0729 loss: 0.7842 2022/08/30 16:38:40 - mmengine - INFO - Epoch(train) [766][30/63] lr: 2.8049e-03 eta: 9:23:37 time: 1.0884 data_time: 0.0333 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2930 loss_db: 0.0730 loss: 0.7696 2022/08/30 16:38:45 - mmengine - INFO - Epoch(train) [766][35/63] lr: 2.8049e-03 eta: 9:23:37 time: 1.0959 data_time: 0.0350 memory: 16201 loss_prob: 0.4190 loss_thr: 0.2967 loss_db: 0.0741 loss: 0.7898 2022/08/30 16:38:51 - mmengine - INFO - Epoch(train) [766][40/63] lr: 2.8049e-03 eta: 9:23:24 time: 1.0828 data_time: 0.0341 memory: 16201 loss_prob: 0.3959 loss_thr: 0.2901 loss_db: 0.0699 loss: 0.7559 2022/08/30 16:38:57 - mmengine - INFO - Epoch(train) [766][45/63] lr: 2.8049e-03 eta: 9:23:24 time: 1.1506 data_time: 0.0324 memory: 16201 loss_prob: 0.3792 loss_thr: 0.2845 loss_db: 0.0689 loss: 0.7326 2022/08/30 16:39:03 - mmengine - INFO - Epoch(train) [766][50/63] lr: 2.8049e-03 eta: 9:23:11 time: 1.1928 data_time: 0.0555 memory: 16201 loss_prob: 0.3766 loss_thr: 0.2799 loss_db: 0.0664 loss: 0.7229 2022/08/30 16:39:08 - mmengine - INFO - Epoch(train) [766][55/63] lr: 2.8049e-03 eta: 9:23:11 time: 1.1443 data_time: 0.0440 memory: 16201 loss_prob: 0.3809 loss_thr: 0.2713 loss_db: 0.0666 loss: 0.7188 2022/08/30 16:39:13 - mmengine - INFO - Epoch(train) [766][60/63] lr: 2.8049e-03 eta: 9:22:58 time: 1.0492 data_time: 0.0386 memory: 16201 loss_prob: 0.4305 loss_thr: 0.3017 loss_db: 0.0754 loss: 0.8076 2022/08/30 16:39:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:39:23 - mmengine - INFO - Epoch(train) [767][5/63] lr: 2.7990e-03 eta: 9:22:58 time: 1.1425 data_time: 0.2552 memory: 16201 loss_prob: 0.4406 loss_thr: 0.3194 loss_db: 0.0781 loss: 0.8381 2022/08/30 16:39:27 - mmengine - INFO - Epoch(train) [767][10/63] lr: 2.7990e-03 eta: 9:22:39 time: 1.1178 data_time: 0.2593 memory: 16201 loss_prob: 0.4012 loss_thr: 0.2891 loss_db: 0.0714 loss: 0.7617 2022/08/30 16:39:31 - mmengine - INFO - Epoch(train) [767][15/63] lr: 2.7990e-03 eta: 9:22:39 time: 0.8164 data_time: 0.0288 memory: 16201 loss_prob: 0.4017 loss_thr: 0.2820 loss_db: 0.0724 loss: 0.7560 2022/08/30 16:39:35 - mmengine - INFO - Epoch(train) [767][20/63] lr: 2.7990e-03 eta: 9:22:24 time: 0.8340 data_time: 0.0321 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2667 loss_db: 0.0684 loss: 0.7196 2022/08/30 16:39:40 - mmengine - INFO - Epoch(train) [767][25/63] lr: 2.7990e-03 eta: 9:22:24 time: 0.8850 data_time: 0.0375 memory: 16201 loss_prob: 0.3956 loss_thr: 0.2841 loss_db: 0.0682 loss: 0.7480 2022/08/30 16:39:44 - mmengine - INFO - Epoch(train) [767][30/63] lr: 2.7990e-03 eta: 9:22:10 time: 0.8786 data_time: 0.0357 memory: 16201 loss_prob: 0.3900 loss_thr: 0.2847 loss_db: 0.0695 loss: 0.7443 2022/08/30 16:39:49 - mmengine - INFO - Epoch(train) [767][35/63] lr: 2.7990e-03 eta: 9:22:10 time: 0.9246 data_time: 0.0321 memory: 16201 loss_prob: 0.3748 loss_thr: 0.2712 loss_db: 0.0672 loss: 0.7133 2022/08/30 16:39:54 - mmengine - INFO - Epoch(train) [767][40/63] lr: 2.7990e-03 eta: 9:21:56 time: 1.0161 data_time: 0.0321 memory: 16201 loss_prob: 0.3989 loss_thr: 0.2865 loss_db: 0.0711 loss: 0.7564 2022/08/30 16:39:59 - mmengine - INFO - Epoch(train) [767][45/63] lr: 2.7990e-03 eta: 9:21:56 time: 1.0413 data_time: 0.0401 memory: 16201 loss_prob: 0.3949 loss_thr: 0.2869 loss_db: 0.0709 loss: 0.7526 2022/08/30 16:40:04 - mmengine - INFO - Epoch(train) [767][50/63] lr: 2.7990e-03 eta: 9:21:43 time: 0.9530 data_time: 0.0426 memory: 16201 loss_prob: 0.3871 loss_thr: 0.2785 loss_db: 0.0686 loss: 0.7341 2022/08/30 16:40:08 - mmengine - INFO - Epoch(train) [767][55/63] lr: 2.7990e-03 eta: 9:21:43 time: 0.9043 data_time: 0.0292 memory: 16201 loss_prob: 0.3958 loss_thr: 0.2846 loss_db: 0.0696 loss: 0.7500 2022/08/30 16:40:14 - mmengine - INFO - Epoch(train) [767][60/63] lr: 2.7990e-03 eta: 9:21:29 time: 1.0513 data_time: 0.0438 memory: 16201 loss_prob: 0.3867 loss_thr: 0.2800 loss_db: 0.0690 loss: 0.7357 2022/08/30 16:40:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:40:25 - mmengine - INFO - Epoch(train) [768][5/63] lr: 2.7932e-03 eta: 9:21:29 time: 1.2681 data_time: 0.2375 memory: 16201 loss_prob: 0.4107 loss_thr: 0.2786 loss_db: 0.0725 loss: 0.7618 2022/08/30 16:40:31 - mmengine - INFO - Epoch(train) [768][10/63] lr: 2.7932e-03 eta: 9:21:12 time: 1.3408 data_time: 0.2528 memory: 16201 loss_prob: 0.4265 loss_thr: 0.2854 loss_db: 0.0721 loss: 0.7840 2022/08/30 16:40:37 - mmengine - INFO - Epoch(train) [768][15/63] lr: 2.7932e-03 eta: 9:21:12 time: 1.1691 data_time: 0.0467 memory: 16201 loss_prob: 0.4154 loss_thr: 0.2903 loss_db: 0.0720 loss: 0.7778 2022/08/30 16:40:42 - mmengine - INFO - Epoch(train) [768][20/63] lr: 2.7932e-03 eta: 9:20:58 time: 1.0984 data_time: 0.0441 memory: 16201 loss_prob: 0.3976 loss_thr: 0.2818 loss_db: 0.0699 loss: 0.7493 2022/08/30 16:40:47 - mmengine - INFO - Epoch(train) [768][25/63] lr: 2.7932e-03 eta: 9:20:58 time: 0.9919 data_time: 0.0381 memory: 16201 loss_prob: 0.4021 loss_thr: 0.2754 loss_db: 0.0713 loss: 0.7488 2022/08/30 16:40:51 - mmengine - INFO - Epoch(train) [768][30/63] lr: 2.7932e-03 eta: 9:20:44 time: 0.8873 data_time: 0.0354 memory: 16201 loss_prob: 0.3743 loss_thr: 0.2711 loss_db: 0.0666 loss: 0.7121 2022/08/30 16:40:55 - mmengine - INFO - Epoch(train) [768][35/63] lr: 2.7932e-03 eta: 9:20:44 time: 0.8365 data_time: 0.0332 memory: 16201 loss_prob: 0.4197 loss_thr: 0.2920 loss_db: 0.0734 loss: 0.7850 2022/08/30 16:41:00 - mmengine - INFO - Epoch(train) [768][40/63] lr: 2.7932e-03 eta: 9:20:30 time: 0.8801 data_time: 0.0262 memory: 16201 loss_prob: 0.4280 loss_thr: 0.2838 loss_db: 0.0758 loss: 0.7876 2022/08/30 16:41:04 - mmengine - INFO - Epoch(train) [768][45/63] lr: 2.7932e-03 eta: 9:20:30 time: 0.9088 data_time: 0.0233 memory: 16201 loss_prob: 0.4089 loss_thr: 0.2835 loss_db: 0.0719 loss: 0.7644 2022/08/30 16:41:10 - mmengine - INFO - Epoch(train) [768][50/63] lr: 2.7932e-03 eta: 9:20:16 time: 1.0150 data_time: 0.0319 memory: 16201 loss_prob: 0.4100 loss_thr: 0.2886 loss_db: 0.0716 loss: 0.7702 2022/08/30 16:41:15 - mmengine - INFO - Epoch(train) [768][55/63] lr: 2.7932e-03 eta: 9:20:16 time: 1.1441 data_time: 0.0409 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2768 loss_db: 0.0685 loss: 0.7439 2022/08/30 16:41:21 - mmengine - INFO - Epoch(train) [768][60/63] lr: 2.7932e-03 eta: 9:20:03 time: 1.1508 data_time: 0.0343 memory: 16201 loss_prob: 0.4119 loss_thr: 0.2932 loss_db: 0.0706 loss: 0.7757 2022/08/30 16:41:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:41:30 - mmengine - INFO - Epoch(train) [769][5/63] lr: 2.7874e-03 eta: 9:20:03 time: 1.0072 data_time: 0.2498 memory: 16201 loss_prob: 0.4208 loss_thr: 0.3001 loss_db: 0.0753 loss: 0.7961 2022/08/30 16:41:36 - mmengine - INFO - Epoch(train) [769][10/63] lr: 2.7874e-03 eta: 9:19:45 time: 1.2119 data_time: 0.2582 memory: 16201 loss_prob: 0.3801 loss_thr: 0.2833 loss_db: 0.0686 loss: 0.7319 2022/08/30 16:41:42 - mmengine - INFO - Epoch(train) [769][15/63] lr: 2.7874e-03 eta: 9:19:45 time: 1.1965 data_time: 0.0316 memory: 16201 loss_prob: 0.3558 loss_thr: 0.2739 loss_db: 0.0640 loss: 0.6936 2022/08/30 16:41:48 - mmengine - INFO - Epoch(train) [769][20/63] lr: 2.7874e-03 eta: 9:19:33 time: 1.2006 data_time: 0.0777 memory: 16201 loss_prob: 0.3915 loss_thr: 0.2964 loss_db: 0.0691 loss: 0.7571 2022/08/30 16:41:53 - mmengine - INFO - Epoch(train) [769][25/63] lr: 2.7874e-03 eta: 9:19:33 time: 1.1138 data_time: 0.0856 memory: 16201 loss_prob: 0.4034 loss_thr: 0.2976 loss_db: 0.0711 loss: 0.7722 2022/08/30 16:41:59 - mmengine - INFO - Epoch(train) [769][30/63] lr: 2.7874e-03 eta: 9:19:20 time: 1.0984 data_time: 0.0263 memory: 16201 loss_prob: 0.4100 loss_thr: 0.3001 loss_db: 0.0725 loss: 0.7826 2022/08/30 16:42:04 - mmengine - INFO - Epoch(train) [769][35/63] lr: 2.7874e-03 eta: 9:19:20 time: 1.0698 data_time: 0.0370 memory: 16201 loss_prob: 0.4404 loss_thr: 0.3084 loss_db: 0.0792 loss: 0.8279 2022/08/30 16:42:10 - mmengine - INFO - Epoch(train) [769][40/63] lr: 2.7874e-03 eta: 9:19:06 time: 1.1062 data_time: 0.0420 memory: 16201 loss_prob: 0.4532 loss_thr: 0.3056 loss_db: 0.0807 loss: 0.8396 2022/08/30 16:42:15 - mmengine - INFO - Epoch(train) [769][45/63] lr: 2.7874e-03 eta: 9:19:06 time: 1.1611 data_time: 0.0300 memory: 16201 loss_prob: 0.4065 loss_thr: 0.2810 loss_db: 0.0717 loss: 0.7592 2022/08/30 16:42:20 - mmengine - INFO - Epoch(train) [769][50/63] lr: 2.7874e-03 eta: 9:18:53 time: 1.0394 data_time: 0.0380 memory: 16201 loss_prob: 0.3540 loss_thr: 0.2550 loss_db: 0.0646 loss: 0.6737 2022/08/30 16:42:24 - mmengine - INFO - Epoch(train) [769][55/63] lr: 2.7874e-03 eta: 9:18:53 time: 0.8842 data_time: 0.0294 memory: 16201 loss_prob: 0.3702 loss_thr: 0.2662 loss_db: 0.0668 loss: 0.7032 2022/08/30 16:42:29 - mmengine - INFO - Epoch(train) [769][60/63] lr: 2.7874e-03 eta: 9:18:39 time: 0.8536 data_time: 0.0207 memory: 16201 loss_prob: 0.3781 loss_thr: 0.2675 loss_db: 0.0654 loss: 0.7111 2022/08/30 16:42:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:42:36 - mmengine - INFO - Epoch(train) [770][5/63] lr: 2.7816e-03 eta: 9:18:39 time: 0.9627 data_time: 0.1783 memory: 16201 loss_prob: 0.4461 loss_thr: 0.2912 loss_db: 0.0754 loss: 0.8128 2022/08/30 16:42:41 - mmengine - INFO - Epoch(train) [770][10/63] lr: 2.7816e-03 eta: 9:18:20 time: 1.0718 data_time: 0.1890 memory: 16201 loss_prob: 0.4006 loss_thr: 0.2889 loss_db: 0.0702 loss: 0.7597 2022/08/30 16:42:47 - mmengine - INFO - Epoch(train) [770][15/63] lr: 2.7816e-03 eta: 9:18:20 time: 1.0741 data_time: 0.0294 memory: 16201 loss_prob: 0.3929 loss_thr: 0.2859 loss_db: 0.0695 loss: 0.7483 2022/08/30 16:42:52 - mmengine - INFO - Epoch(train) [770][20/63] lr: 2.7816e-03 eta: 9:18:06 time: 1.0631 data_time: 0.0314 memory: 16201 loss_prob: 0.3830 loss_thr: 0.2781 loss_db: 0.0678 loss: 0.7288 2022/08/30 16:42:58 - mmengine - INFO - Epoch(train) [770][25/63] lr: 2.7816e-03 eta: 9:18:06 time: 1.0285 data_time: 0.0487 memory: 16201 loss_prob: 0.3993 loss_thr: 0.2871 loss_db: 0.0710 loss: 0.7573 2022/08/30 16:43:02 - mmengine - INFO - Epoch(train) [770][30/63] lr: 2.7816e-03 eta: 9:17:52 time: 0.9526 data_time: 0.0325 memory: 16201 loss_prob: 0.4063 loss_thr: 0.2779 loss_db: 0.0720 loss: 0.7562 2022/08/30 16:43:06 - mmengine - INFO - Epoch(train) [770][35/63] lr: 2.7816e-03 eta: 9:17:52 time: 0.8064 data_time: 0.0229 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2824 loss_db: 0.0726 loss: 0.7653 2022/08/30 16:43:10 - mmengine - INFO - Epoch(train) [770][40/63] lr: 2.7816e-03 eta: 9:17:38 time: 0.8512 data_time: 0.0288 memory: 16201 loss_prob: 0.4447 loss_thr: 0.3155 loss_db: 0.0795 loss: 0.8398 2022/08/30 16:43:14 - mmengine - INFO - Epoch(train) [770][45/63] lr: 2.7816e-03 eta: 9:17:38 time: 0.8829 data_time: 0.0277 memory: 16201 loss_prob: 0.4398 loss_thr: 0.3076 loss_db: 0.0775 loss: 0.8249 2022/08/30 16:43:21 - mmengine - INFO - Epoch(train) [770][50/63] lr: 2.7816e-03 eta: 9:17:24 time: 1.0501 data_time: 0.0362 memory: 16201 loss_prob: 0.4049 loss_thr: 0.2882 loss_db: 0.0701 loss: 0.7631 2022/08/30 16:43:26 - mmengine - INFO - Epoch(train) [770][55/63] lr: 2.7816e-03 eta: 9:17:24 time: 1.1379 data_time: 0.0308 memory: 16201 loss_prob: 0.4143 loss_thr: 0.3028 loss_db: 0.0734 loss: 0.7905 2022/08/30 16:43:31 - mmengine - INFO - Epoch(train) [770][60/63] lr: 2.7816e-03 eta: 9:17:11 time: 1.0016 data_time: 0.0255 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2972 loss_db: 0.0743 loss: 0.7819 2022/08/30 16:43:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:43:38 - mmengine - INFO - Epoch(train) [771][5/63] lr: 2.7758e-03 eta: 9:17:11 time: 0.9091 data_time: 0.1586 memory: 16201 loss_prob: 0.3671 loss_thr: 0.2651 loss_db: 0.0641 loss: 0.6964 2022/08/30 16:43:43 - mmengine - INFO - Epoch(train) [771][10/63] lr: 2.7758e-03 eta: 9:16:51 time: 1.0038 data_time: 0.1674 memory: 16201 loss_prob: 0.4282 loss_thr: 0.2911 loss_db: 0.0765 loss: 0.7958 2022/08/30 16:43:48 - mmengine - INFO - Epoch(train) [771][15/63] lr: 2.7758e-03 eta: 9:16:51 time: 1.0034 data_time: 0.0267 memory: 16201 loss_prob: 0.4518 loss_thr: 0.3128 loss_db: 0.0802 loss: 0.8449 2022/08/30 16:43:54 - mmengine - INFO - Epoch(train) [771][20/63] lr: 2.7758e-03 eta: 9:16:38 time: 1.1151 data_time: 0.0279 memory: 16201 loss_prob: 0.4070 loss_thr: 0.3044 loss_db: 0.0687 loss: 0.7801 2022/08/30 16:43:59 - mmengine - INFO - Epoch(train) [771][25/63] lr: 2.7758e-03 eta: 9:16:38 time: 1.1231 data_time: 0.0435 memory: 16201 loss_prob: 0.4259 loss_thr: 0.3157 loss_db: 0.0748 loss: 0.8165 2022/08/30 16:44:04 - mmengine - INFO - Epoch(train) [771][30/63] lr: 2.7758e-03 eta: 9:16:25 time: 0.9977 data_time: 0.0385 memory: 16201 loss_prob: 0.4389 loss_thr: 0.3159 loss_db: 0.0769 loss: 0.8317 2022/08/30 16:44:08 - mmengine - INFO - Epoch(train) [771][35/63] lr: 2.7758e-03 eta: 9:16:25 time: 0.8884 data_time: 0.0308 memory: 16201 loss_prob: 0.4201 loss_thr: 0.2991 loss_db: 0.0732 loss: 0.7924 2022/08/30 16:44:12 - mmengine - INFO - Epoch(train) [771][40/63] lr: 2.7758e-03 eta: 9:16:10 time: 0.8571 data_time: 0.0284 memory: 16201 loss_prob: 0.4176 loss_thr: 0.3002 loss_db: 0.0749 loss: 0.7927 2022/08/30 16:44:17 - mmengine - INFO - Epoch(train) [771][45/63] lr: 2.7758e-03 eta: 9:16:10 time: 0.8271 data_time: 0.0270 memory: 16201 loss_prob: 0.4424 loss_thr: 0.3168 loss_db: 0.0770 loss: 0.8362 2022/08/30 16:44:22 - mmengine - INFO - Epoch(train) [771][50/63] lr: 2.7758e-03 eta: 9:15:57 time: 0.9961 data_time: 0.0424 memory: 16201 loss_prob: 0.4233 loss_thr: 0.3044 loss_db: 0.0742 loss: 0.8019 2022/08/30 16:44:28 - mmengine - INFO - Epoch(train) [771][55/63] lr: 2.7758e-03 eta: 9:15:57 time: 1.1647 data_time: 0.0409 memory: 16201 loss_prob: 0.3693 loss_thr: 0.2741 loss_db: 0.0676 loss: 0.7110 2022/08/30 16:44:33 - mmengine - INFO - Epoch(train) [771][60/63] lr: 2.7758e-03 eta: 9:15:44 time: 1.1014 data_time: 0.0337 memory: 16201 loss_prob: 0.4097 loss_thr: 0.2909 loss_db: 0.0721 loss: 0.7727 2022/08/30 16:44:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:44:42 - mmengine - INFO - Epoch(train) [772][5/63] lr: 2.7699e-03 eta: 9:15:44 time: 1.0488 data_time: 0.2332 memory: 16201 loss_prob: 0.4374 loss_thr: 0.3004 loss_db: 0.0758 loss: 0.8136 2022/08/30 16:44:46 - mmengine - INFO - Epoch(train) [772][10/63] lr: 2.7699e-03 eta: 9:15:24 time: 1.0539 data_time: 0.2381 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2793 loss_db: 0.0686 loss: 0.7258 2022/08/30 16:44:52 - mmengine - INFO - Epoch(train) [772][15/63] lr: 2.7699e-03 eta: 9:15:24 time: 1.0006 data_time: 0.0312 memory: 16201 loss_prob: 0.3868 loss_thr: 0.2784 loss_db: 0.0703 loss: 0.7355 2022/08/30 16:44:57 - mmengine - INFO - Epoch(train) [772][20/63] lr: 2.7699e-03 eta: 9:15:11 time: 1.0534 data_time: 0.0302 memory: 16201 loss_prob: 0.4033 loss_thr: 0.2771 loss_db: 0.0696 loss: 0.7500 2022/08/30 16:45:01 - mmengine - INFO - Epoch(train) [772][25/63] lr: 2.7699e-03 eta: 9:15:11 time: 0.9351 data_time: 0.0368 memory: 16201 loss_prob: 0.4181 loss_thr: 0.2860 loss_db: 0.0697 loss: 0.7738 2022/08/30 16:45:06 - mmengine - INFO - Epoch(train) [772][30/63] lr: 2.7699e-03 eta: 9:14:57 time: 0.9283 data_time: 0.0260 memory: 16201 loss_prob: 0.4299 loss_thr: 0.2811 loss_db: 0.0748 loss: 0.7859 2022/08/30 16:45:12 - mmengine - INFO - Epoch(train) [772][35/63] lr: 2.7699e-03 eta: 9:14:57 time: 1.0624 data_time: 0.0321 memory: 16201 loss_prob: 0.4115 loss_thr: 0.2884 loss_db: 0.0736 loss: 0.7735 2022/08/30 16:45:17 - mmengine - INFO - Epoch(train) [772][40/63] lr: 2.7699e-03 eta: 9:14:44 time: 1.0731 data_time: 0.0377 memory: 16201 loss_prob: 0.4021 loss_thr: 0.3079 loss_db: 0.0708 loss: 0.7809 2022/08/30 16:45:21 - mmengine - INFO - Epoch(train) [772][45/63] lr: 2.7699e-03 eta: 9:14:44 time: 0.9258 data_time: 0.0319 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2867 loss_db: 0.0694 loss: 0.7419 2022/08/30 16:45:25 - mmengine - INFO - Epoch(train) [772][50/63] lr: 2.7699e-03 eta: 9:14:30 time: 0.8646 data_time: 0.0373 memory: 16201 loss_prob: 0.4079 loss_thr: 0.2761 loss_db: 0.0735 loss: 0.7574 2022/08/30 16:45:31 - mmengine - INFO - Epoch(train) [772][55/63] lr: 2.7699e-03 eta: 9:14:30 time: 0.9756 data_time: 0.0296 memory: 16201 loss_prob: 0.4038 loss_thr: 0.2702 loss_db: 0.0712 loss: 0.7451 2022/08/30 16:45:37 - mmengine - INFO - Epoch(train) [772][60/63] lr: 2.7699e-03 eta: 9:14:17 time: 1.1321 data_time: 0.0435 memory: 16201 loss_prob: 0.3926 loss_thr: 0.2735 loss_db: 0.0691 loss: 0.7352 2022/08/30 16:45:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:45:46 - mmengine - INFO - Epoch(train) [773][5/63] lr: 2.7641e-03 eta: 9:14:17 time: 1.0882 data_time: 0.2198 memory: 16201 loss_prob: 0.3914 loss_thr: 0.2708 loss_db: 0.0704 loss: 0.7326 2022/08/30 16:45:50 - mmengine - INFO - Epoch(train) [773][10/63] lr: 2.7641e-03 eta: 9:13:58 time: 1.0729 data_time: 0.2299 memory: 16201 loss_prob: 0.3619 loss_thr: 0.2669 loss_db: 0.0637 loss: 0.6925 2022/08/30 16:45:55 - mmengine - INFO - Epoch(train) [773][15/63] lr: 2.7641e-03 eta: 9:13:58 time: 0.9607 data_time: 0.0383 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2734 loss_db: 0.0692 loss: 0.7284 2022/08/30 16:46:01 - mmengine - INFO - Epoch(train) [773][20/63] lr: 2.7641e-03 eta: 9:13:45 time: 1.0899 data_time: 0.0295 memory: 16201 loss_prob: 0.4141 loss_thr: 0.2863 loss_db: 0.0738 loss: 0.7741 2022/08/30 16:46:06 - mmengine - INFO - Epoch(train) [773][25/63] lr: 2.7641e-03 eta: 9:13:45 time: 1.0184 data_time: 0.0403 memory: 16201 loss_prob: 0.3952 loss_thr: 0.2785 loss_db: 0.0690 loss: 0.7427 2022/08/30 16:46:10 - mmengine - INFO - Epoch(train) [773][30/63] lr: 2.7641e-03 eta: 9:13:30 time: 0.9033 data_time: 0.0351 memory: 16201 loss_prob: 0.3969 loss_thr: 0.2787 loss_db: 0.0695 loss: 0.7450 2022/08/30 16:46:15 - mmengine - INFO - Epoch(train) [773][35/63] lr: 2.7641e-03 eta: 9:13:30 time: 0.9597 data_time: 0.0305 memory: 16201 loss_prob: 0.3936 loss_thr: 0.2730 loss_db: 0.0679 loss: 0.7346 2022/08/30 16:46:21 - mmengine - INFO - Epoch(train) [773][40/63] lr: 2.7641e-03 eta: 9:13:17 time: 1.0518 data_time: 0.0397 memory: 16201 loss_prob: 0.3863 loss_thr: 0.2747 loss_db: 0.0673 loss: 0.7283 2022/08/30 16:46:28 - mmengine - INFO - Epoch(train) [773][45/63] lr: 2.7641e-03 eta: 9:13:17 time: 1.3324 data_time: 0.0338 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2812 loss_db: 0.0693 loss: 0.7458 2022/08/30 16:46:34 - mmengine - INFO - Epoch(train) [773][50/63] lr: 2.7641e-03 eta: 9:13:05 time: 1.3653 data_time: 0.0430 memory: 16201 loss_prob: 0.4218 loss_thr: 0.2923 loss_db: 0.0733 loss: 0.7875 2022/08/30 16:46:39 - mmengine - INFO - Epoch(train) [773][55/63] lr: 2.7641e-03 eta: 9:13:05 time: 1.0537 data_time: 0.0382 memory: 16201 loss_prob: 0.4328 loss_thr: 0.3043 loss_db: 0.0765 loss: 0.8137 2022/08/30 16:46:45 - mmengine - INFO - Epoch(train) [773][60/63] lr: 2.7641e-03 eta: 9:12:52 time: 1.0331 data_time: 0.0286 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2809 loss_db: 0.0698 loss: 0.7344 2022/08/30 16:46:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:46:55 - mmengine - INFO - Epoch(train) [774][5/63] lr: 2.7583e-03 eta: 9:12:52 time: 1.2779 data_time: 0.2609 memory: 16201 loss_prob: 0.3911 loss_thr: 0.2721 loss_db: 0.0691 loss: 0.7322 2022/08/30 16:47:00 - mmengine - INFO - Epoch(train) [774][10/63] lr: 2.7583e-03 eta: 9:12:34 time: 1.1910 data_time: 0.2999 memory: 16201 loss_prob: 0.4189 loss_thr: 0.2780 loss_db: 0.0712 loss: 0.7681 2022/08/30 16:47:05 - mmengine - INFO - Epoch(train) [774][15/63] lr: 2.7583e-03 eta: 9:12:34 time: 0.9123 data_time: 0.0749 memory: 16201 loss_prob: 0.3987 loss_thr: 0.2816 loss_db: 0.0694 loss: 0.7497 2022/08/30 16:47:09 - mmengine - INFO - Epoch(train) [774][20/63] lr: 2.7583e-03 eta: 9:12:19 time: 0.8664 data_time: 0.0507 memory: 16201 loss_prob: 0.4063 loss_thr: 0.2900 loss_db: 0.0711 loss: 0.7673 2022/08/30 16:47:13 - mmengine - INFO - Epoch(train) [774][25/63] lr: 2.7583e-03 eta: 9:12:19 time: 0.8745 data_time: 0.0670 memory: 16201 loss_prob: 0.4216 loss_thr: 0.3049 loss_db: 0.0741 loss: 0.8006 2022/08/30 16:47:18 - mmengine - INFO - Epoch(train) [774][30/63] lr: 2.7583e-03 eta: 9:12:06 time: 0.9653 data_time: 0.0636 memory: 16201 loss_prob: 0.4007 loss_thr: 0.2990 loss_db: 0.0710 loss: 0.7706 2022/08/30 16:47:25 - mmengine - INFO - Epoch(train) [774][35/63] lr: 2.7583e-03 eta: 9:12:06 time: 1.1338 data_time: 0.0584 memory: 16201 loss_prob: 0.4145 loss_thr: 0.2959 loss_db: 0.0737 loss: 0.7842 2022/08/30 16:47:29 - mmengine - INFO - Epoch(train) [774][40/63] lr: 2.7583e-03 eta: 9:11:52 time: 1.0995 data_time: 0.0767 memory: 16201 loss_prob: 0.4429 loss_thr: 0.3156 loss_db: 0.0789 loss: 0.8375 2022/08/30 16:47:34 - mmengine - INFO - Epoch(train) [774][45/63] lr: 2.7583e-03 eta: 9:11:52 time: 0.9166 data_time: 0.0672 memory: 16201 loss_prob: 0.4353 loss_thr: 0.3000 loss_db: 0.0769 loss: 0.8122 2022/08/30 16:47:39 - mmengine - INFO - Epoch(train) [774][50/63] lr: 2.7583e-03 eta: 9:11:38 time: 0.9239 data_time: 0.0503 memory: 16201 loss_prob: 0.4086 loss_thr: 0.2854 loss_db: 0.0733 loss: 0.7673 2022/08/30 16:47:44 - mmengine - INFO - Epoch(train) [774][55/63] lr: 2.7583e-03 eta: 9:11:38 time: 1.0158 data_time: 0.0816 memory: 16201 loss_prob: 0.4123 loss_thr: 0.2932 loss_db: 0.0746 loss: 0.7801 2022/08/30 16:47:49 - mmengine - INFO - Epoch(train) [774][60/63] lr: 2.7583e-03 eta: 9:11:25 time: 1.0156 data_time: 0.0850 memory: 16201 loss_prob: 0.4056 loss_thr: 0.2789 loss_db: 0.0717 loss: 0.7561 2022/08/30 16:47:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:47:58 - mmengine - INFO - Epoch(train) [775][5/63] lr: 2.7525e-03 eta: 9:11:25 time: 1.0448 data_time: 0.2783 memory: 16201 loss_prob: 0.4023 loss_thr: 0.2813 loss_db: 0.0718 loss: 0.7554 2022/08/30 16:48:03 - mmengine - INFO - Epoch(train) [775][10/63] lr: 2.7525e-03 eta: 9:11:07 time: 1.1752 data_time: 0.2494 memory: 16201 loss_prob: 0.4108 loss_thr: 0.2985 loss_db: 0.0728 loss: 0.7821 2022/08/30 16:48:08 - mmengine - INFO - Epoch(train) [775][15/63] lr: 2.7525e-03 eta: 9:11:07 time: 1.0618 data_time: 0.0743 memory: 16201 loss_prob: 0.4229 loss_thr: 0.3317 loss_db: 0.0728 loss: 0.8274 2022/08/30 16:48:13 - mmengine - INFO - Epoch(train) [775][20/63] lr: 2.7525e-03 eta: 9:10:53 time: 0.9524 data_time: 0.0761 memory: 16201 loss_prob: 0.4683 loss_thr: 0.3415 loss_db: 0.0802 loss: 0.8899 2022/08/30 16:48:17 - mmengine - INFO - Epoch(train) [775][25/63] lr: 2.7525e-03 eta: 9:10:53 time: 0.8688 data_time: 0.0500 memory: 16201 loss_prob: 0.4010 loss_thr: 0.2830 loss_db: 0.0687 loss: 0.7526 2022/08/30 16:48:23 - mmengine - INFO - Epoch(train) [775][30/63] lr: 2.7525e-03 eta: 9:10:39 time: 1.0296 data_time: 0.0768 memory: 16201 loss_prob: 0.3762 loss_thr: 0.2745 loss_db: 0.0666 loss: 0.7173 2022/08/30 16:48:29 - mmengine - INFO - Epoch(train) [775][35/63] lr: 2.7525e-03 eta: 9:10:39 time: 1.1741 data_time: 0.0806 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2838 loss_db: 0.0726 loss: 0.7591 2022/08/30 16:48:34 - mmengine - INFO - Epoch(train) [775][40/63] lr: 2.7525e-03 eta: 9:10:27 time: 1.1600 data_time: 0.0747 memory: 16201 loss_prob: 0.3769 loss_thr: 0.2728 loss_db: 0.0671 loss: 0.7168 2022/08/30 16:48:40 - mmengine - INFO - Epoch(train) [775][45/63] lr: 2.7525e-03 eta: 9:10:27 time: 1.0868 data_time: 0.0754 memory: 16201 loss_prob: 0.3789 loss_thr: 0.2920 loss_db: 0.0670 loss: 0.7379 2022/08/30 16:48:44 - mmengine - INFO - Epoch(train) [775][50/63] lr: 2.7525e-03 eta: 9:10:13 time: 0.9757 data_time: 0.0817 memory: 16201 loss_prob: 0.3997 loss_thr: 0.3021 loss_db: 0.0700 loss: 0.7717 2022/08/30 16:48:49 - mmengine - INFO - Epoch(train) [775][55/63] lr: 2.7525e-03 eta: 9:10:13 time: 0.9355 data_time: 0.0744 memory: 16201 loss_prob: 0.3867 loss_thr: 0.2825 loss_db: 0.0686 loss: 0.7377 2022/08/30 16:48:53 - mmengine - INFO - Epoch(train) [775][60/63] lr: 2.7525e-03 eta: 9:09:59 time: 0.9052 data_time: 0.0467 memory: 16201 loss_prob: 0.3926 loss_thr: 0.2809 loss_db: 0.0698 loss: 0.7433 2022/08/30 16:48:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:49:05 - mmengine - INFO - Epoch(train) [776][5/63] lr: 2.7466e-03 eta: 9:09:59 time: 1.2918 data_time: 0.3180 memory: 16201 loss_prob: 0.4119 loss_thr: 0.2947 loss_db: 0.0715 loss: 0.7781 2022/08/30 16:49:11 - mmengine - INFO - Epoch(train) [776][10/63] lr: 2.7466e-03 eta: 9:09:42 time: 1.4761 data_time: 0.3302 memory: 16201 loss_prob: 0.4091 loss_thr: 0.2929 loss_db: 0.0733 loss: 0.7753 2022/08/30 16:49:17 - mmengine - INFO - Epoch(train) [776][15/63] lr: 2.7466e-03 eta: 9:09:42 time: 1.2389 data_time: 0.0854 memory: 16201 loss_prob: 0.4295 loss_thr: 0.3029 loss_db: 0.0762 loss: 0.8087 2022/08/30 16:49:22 - mmengine - INFO - Epoch(train) [776][20/63] lr: 2.7466e-03 eta: 9:09:29 time: 1.0791 data_time: 0.0769 memory: 16201 loss_prob: 0.4166 loss_thr: 0.2819 loss_db: 0.0728 loss: 0.7713 2022/08/30 16:49:26 - mmengine - INFO - Epoch(train) [776][25/63] lr: 2.7466e-03 eta: 9:09:29 time: 0.9389 data_time: 0.0608 memory: 16201 loss_prob: 0.4217 loss_thr: 0.2785 loss_db: 0.0732 loss: 0.7734 2022/08/30 16:49:30 - mmengine - INFO - Epoch(train) [776][30/63] lr: 2.7466e-03 eta: 9:09:14 time: 0.8422 data_time: 0.0206 memory: 16201 loss_prob: 0.4050 loss_thr: 0.2870 loss_db: 0.0705 loss: 0.7624 2022/08/30 16:49:35 - mmengine - INFO - Epoch(train) [776][35/63] lr: 2.7466e-03 eta: 9:09:14 time: 0.8295 data_time: 0.0313 memory: 16201 loss_prob: 0.4253 loss_thr: 0.3004 loss_db: 0.0729 loss: 0.7986 2022/08/30 16:49:39 - mmengine - INFO - Epoch(train) [776][40/63] lr: 2.7466e-03 eta: 9:09:00 time: 0.8436 data_time: 0.0298 memory: 16201 loss_prob: 0.4570 loss_thr: 0.3156 loss_db: 0.0781 loss: 0.8507 2022/08/30 16:49:44 - mmengine - INFO - Epoch(train) [776][45/63] lr: 2.7466e-03 eta: 9:09:00 time: 0.9365 data_time: 0.0243 memory: 16201 loss_prob: 0.4276 loss_thr: 0.3089 loss_db: 0.0743 loss: 0.8108 2022/08/30 16:49:50 - mmengine - INFO - Epoch(train) [776][50/63] lr: 2.7466e-03 eta: 9:08:47 time: 1.1565 data_time: 0.0353 memory: 16201 loss_prob: 0.5216 loss_thr: 0.3152 loss_db: 0.0858 loss: 0.9226 2022/08/30 16:49:56 - mmengine - INFO - Epoch(train) [776][55/63] lr: 2.7466e-03 eta: 9:08:47 time: 1.1693 data_time: 0.0343 memory: 16201 loss_prob: 0.5193 loss_thr: 0.2959 loss_db: 0.0872 loss: 0.9024 2022/08/30 16:50:02 - mmengine - INFO - Epoch(train) [776][60/63] lr: 2.7466e-03 eta: 9:08:34 time: 1.1675 data_time: 0.0378 memory: 16201 loss_prob: 0.5336 loss_thr: 0.3146 loss_db: 0.0933 loss: 0.9415 2022/08/30 16:50:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:50:12 - mmengine - INFO - Epoch(train) [777][5/63] lr: 2.7408e-03 eta: 9:08:34 time: 1.2786 data_time: 0.2666 memory: 16201 loss_prob: 0.5478 loss_thr: 0.3379 loss_db: 0.0883 loss: 0.9740 2022/08/30 16:50:19 - mmengine - INFO - Epoch(train) [777][10/63] lr: 2.7408e-03 eta: 9:08:17 time: 1.4037 data_time: 0.2696 memory: 16201 loss_prob: 0.4830 loss_thr: 0.3231 loss_db: 0.0801 loss: 0.8863 2022/08/30 16:50:24 - mmengine - INFO - Epoch(train) [777][15/63] lr: 2.7408e-03 eta: 9:08:17 time: 1.1388 data_time: 0.0412 memory: 16201 loss_prob: 0.4397 loss_thr: 0.3019 loss_db: 0.0786 loss: 0.8201 2022/08/30 16:50:28 - mmengine - INFO - Epoch(train) [777][20/63] lr: 2.7408e-03 eta: 9:08:03 time: 0.9326 data_time: 0.0411 memory: 16201 loss_prob: 0.4663 loss_thr: 0.3207 loss_db: 0.0806 loss: 0.8676 2022/08/30 16:50:32 - mmengine - INFO - Epoch(train) [777][25/63] lr: 2.7408e-03 eta: 9:08:03 time: 0.8632 data_time: 0.0357 memory: 16201 loss_prob: 0.4470 loss_thr: 0.3201 loss_db: 0.0749 loss: 0.8420 2022/08/30 16:50:36 - mmengine - INFO - Epoch(train) [777][30/63] lr: 2.7408e-03 eta: 9:07:49 time: 0.8274 data_time: 0.0248 memory: 16201 loss_prob: 0.4801 loss_thr: 0.3146 loss_db: 0.0808 loss: 0.8755 2022/08/30 16:50:41 - mmengine - INFO - Epoch(train) [777][35/63] lr: 2.7408e-03 eta: 9:07:49 time: 0.8283 data_time: 0.0325 memory: 16201 loss_prob: 0.5289 loss_thr: 0.3361 loss_db: 0.0899 loss: 0.9548 2022/08/30 16:50:45 - mmengine - INFO - Epoch(train) [777][40/63] lr: 2.7408e-03 eta: 9:07:34 time: 0.8370 data_time: 0.0261 memory: 16201 loss_prob: 0.4854 loss_thr: 0.3365 loss_db: 0.0853 loss: 0.9072 2022/08/30 16:50:49 - mmengine - INFO - Epoch(train) [777][45/63] lr: 2.7408e-03 eta: 9:07:34 time: 0.8442 data_time: 0.0223 memory: 16201 loss_prob: 0.4774 loss_thr: 0.3282 loss_db: 0.0835 loss: 0.8891 2022/08/30 16:50:55 - mmengine - INFO - Epoch(train) [777][50/63] lr: 2.7408e-03 eta: 9:07:21 time: 0.9782 data_time: 0.0390 memory: 16201 loss_prob: 0.4757 loss_thr: 0.3209 loss_db: 0.0815 loss: 0.8780 2022/08/30 16:51:01 - mmengine - INFO - Epoch(train) [777][55/63] lr: 2.7408e-03 eta: 9:07:21 time: 1.1719 data_time: 0.0467 memory: 16201 loss_prob: 0.4281 loss_thr: 0.3130 loss_db: 0.0753 loss: 0.8164 2022/08/30 16:51:06 - mmengine - INFO - Epoch(train) [777][60/63] lr: 2.7408e-03 eta: 9:07:08 time: 1.0921 data_time: 0.0513 memory: 16201 loss_prob: 0.4189 loss_thr: 0.3102 loss_db: 0.0751 loss: 0.8042 2022/08/30 16:51:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:51:14 - mmengine - INFO - Epoch(train) [778][5/63] lr: 2.7350e-03 eta: 9:07:08 time: 0.9925 data_time: 0.2030 memory: 16201 loss_prob: 0.4146 loss_thr: 0.2941 loss_db: 0.0724 loss: 0.7811 2022/08/30 16:51:20 - mmengine - INFO - Epoch(train) [778][10/63] lr: 2.7350e-03 eta: 9:06:50 time: 1.2817 data_time: 0.2201 memory: 16201 loss_prob: 0.4210 loss_thr: 0.2899 loss_db: 0.0746 loss: 0.7856 2022/08/30 16:51:26 - mmengine - INFO - Epoch(train) [778][15/63] lr: 2.7350e-03 eta: 9:06:50 time: 1.2205 data_time: 0.0328 memory: 16201 loss_prob: 0.4429 loss_thr: 0.2978 loss_db: 0.0816 loss: 0.8224 2022/08/30 16:51:32 - mmengine - INFO - Epoch(train) [778][20/63] lr: 2.7350e-03 eta: 9:06:37 time: 1.1433 data_time: 0.0338 memory: 16201 loss_prob: 0.3992 loss_thr: 0.2674 loss_db: 0.0724 loss: 0.7391 2022/08/30 16:51:37 - mmengine - INFO - Epoch(train) [778][25/63] lr: 2.7350e-03 eta: 9:06:37 time: 1.1268 data_time: 0.0404 memory: 16201 loss_prob: 0.4015 loss_thr: 0.2813 loss_db: 0.0678 loss: 0.7506 2022/08/30 16:51:43 - mmengine - INFO - Epoch(train) [778][30/63] lr: 2.7350e-03 eta: 9:06:24 time: 1.0646 data_time: 0.0284 memory: 16201 loss_prob: 0.4195 loss_thr: 0.2951 loss_db: 0.0697 loss: 0.7843 2022/08/30 16:51:48 - mmengine - INFO - Epoch(train) [778][35/63] lr: 2.7350e-03 eta: 9:06:24 time: 1.1089 data_time: 0.0348 memory: 16201 loss_prob: 0.4373 loss_thr: 0.3031 loss_db: 0.0761 loss: 0.8165 2022/08/30 16:51:53 - mmengine - INFO - Epoch(train) [778][40/63] lr: 2.7350e-03 eta: 9:06:10 time: 1.0109 data_time: 0.0369 memory: 16201 loss_prob: 0.4566 loss_thr: 0.3153 loss_db: 0.0820 loss: 0.8538 2022/08/30 16:51:57 - mmengine - INFO - Epoch(train) [778][45/63] lr: 2.7350e-03 eta: 9:06:10 time: 0.8269 data_time: 0.0305 memory: 16201 loss_prob: 0.4568 loss_thr: 0.3062 loss_db: 0.0815 loss: 0.8445 2022/08/30 16:52:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:52:01 - mmengine - INFO - Epoch(train) [778][50/63] lr: 2.7350e-03 eta: 9:05:56 time: 0.8025 data_time: 0.0260 memory: 16201 loss_prob: 0.4229 loss_thr: 0.2939 loss_db: 0.0749 loss: 0.7918 2022/08/30 16:52:05 - mmengine - INFO - Epoch(train) [778][55/63] lr: 2.7350e-03 eta: 9:05:56 time: 0.7977 data_time: 0.0221 memory: 16201 loss_prob: 0.4149 loss_thr: 0.2993 loss_db: 0.0737 loss: 0.7880 2022/08/30 16:52:09 - mmengine - INFO - Epoch(train) [778][60/63] lr: 2.7350e-03 eta: 9:05:41 time: 0.8222 data_time: 0.0279 memory: 16201 loss_prob: 0.4127 loss_thr: 0.3063 loss_db: 0.0721 loss: 0.7911 2022/08/30 16:52:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:52:19 - mmengine - INFO - Epoch(train) [779][5/63] lr: 2.7291e-03 eta: 9:05:41 time: 1.1945 data_time: 0.2334 memory: 16201 loss_prob: 0.3773 loss_thr: 0.2775 loss_db: 0.0672 loss: 0.7220 2022/08/30 16:52:24 - mmengine - INFO - Epoch(train) [779][10/63] lr: 2.7291e-03 eta: 9:05:24 time: 1.3285 data_time: 0.2504 memory: 16201 loss_prob: 0.4775 loss_thr: 0.3306 loss_db: 0.0839 loss: 0.8921 2022/08/30 16:52:30 - mmengine - INFO - Epoch(train) [779][15/63] lr: 2.7291e-03 eta: 9:05:24 time: 1.1269 data_time: 0.0314 memory: 16201 loss_prob: 0.4975 loss_thr: 0.3396 loss_db: 0.0862 loss: 0.9233 2022/08/30 16:52:36 - mmengine - INFO - Epoch(train) [779][20/63] lr: 2.7291e-03 eta: 9:05:11 time: 1.1452 data_time: 0.0302 memory: 16201 loss_prob: 0.4218 loss_thr: 0.2970 loss_db: 0.0738 loss: 0.7927 2022/08/30 16:52:41 - mmengine - INFO - Epoch(train) [779][25/63] lr: 2.7291e-03 eta: 9:05:11 time: 1.0660 data_time: 0.0378 memory: 16201 loss_prob: 0.4020 loss_thr: 0.2817 loss_db: 0.0700 loss: 0.7536 2022/08/30 16:52:47 - mmengine - INFO - Epoch(train) [779][30/63] lr: 2.7291e-03 eta: 9:04:58 time: 1.0604 data_time: 0.0306 memory: 16201 loss_prob: 0.4134 loss_thr: 0.2932 loss_db: 0.0720 loss: 0.7785 2022/08/30 16:52:52 - mmengine - INFO - Epoch(train) [779][35/63] lr: 2.7291e-03 eta: 9:04:58 time: 1.1527 data_time: 0.0357 memory: 16201 loss_prob: 0.3948 loss_thr: 0.2862 loss_db: 0.0690 loss: 0.7500 2022/08/30 16:52:58 - mmengine - INFO - Epoch(train) [779][40/63] lr: 2.7291e-03 eta: 9:04:45 time: 1.0968 data_time: 0.0343 memory: 16201 loss_prob: 0.4107 loss_thr: 0.2830 loss_db: 0.0715 loss: 0.7652 2022/08/30 16:53:03 - mmengine - INFO - Epoch(train) [779][45/63] lr: 2.7291e-03 eta: 9:04:45 time: 1.0436 data_time: 0.0324 memory: 16201 loss_prob: 0.4493 loss_thr: 0.3042 loss_db: 0.0772 loss: 0.8307 2022/08/30 16:53:09 - mmengine - INFO - Epoch(train) [779][50/63] lr: 2.7291e-03 eta: 9:04:32 time: 1.1952 data_time: 0.0423 memory: 16201 loss_prob: 0.4139 loss_thr: 0.2930 loss_db: 0.0716 loss: 0.7785 2022/08/30 16:53:14 - mmengine - INFO - Epoch(train) [779][55/63] lr: 2.7291e-03 eta: 9:04:32 time: 1.0681 data_time: 0.0379 memory: 16201 loss_prob: 0.4000 loss_thr: 0.2878 loss_db: 0.0703 loss: 0.7581 2022/08/30 16:53:18 - mmengine - INFO - Epoch(train) [779][60/63] lr: 2.7291e-03 eta: 9:04:18 time: 0.8441 data_time: 0.0358 memory: 16201 loss_prob: 0.4227 loss_thr: 0.3119 loss_db: 0.0757 loss: 0.8103 2022/08/30 16:53:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:53:26 - mmengine - INFO - Epoch(train) [780][5/63] lr: 2.7233e-03 eta: 9:04:18 time: 1.0154 data_time: 0.2233 memory: 16201 loss_prob: 0.4047 loss_thr: 0.2986 loss_db: 0.0712 loss: 0.7745 2022/08/30 16:53:31 - mmengine - INFO - Epoch(train) [780][10/63] lr: 2.7233e-03 eta: 9:03:59 time: 1.0729 data_time: 0.2394 memory: 16201 loss_prob: 0.3966 loss_thr: 0.2724 loss_db: 0.0735 loss: 0.7424 2022/08/30 16:53:35 - mmengine - INFO - Epoch(train) [780][15/63] lr: 2.7233e-03 eta: 9:03:59 time: 0.8774 data_time: 0.0306 memory: 16201 loss_prob: 0.4101 loss_thr: 0.2823 loss_db: 0.0757 loss: 0.7682 2022/08/30 16:53:40 - mmengine - INFO - Epoch(train) [780][20/63] lr: 2.7233e-03 eta: 9:03:45 time: 0.9168 data_time: 0.0260 memory: 16201 loss_prob: 0.3970 loss_thr: 0.2778 loss_db: 0.0694 loss: 0.7442 2022/08/30 16:53:46 - mmengine - INFO - Epoch(train) [780][25/63] lr: 2.7233e-03 eta: 9:03:45 time: 1.0453 data_time: 0.0458 memory: 16201 loss_prob: 0.4122 loss_thr: 0.2945 loss_db: 0.0714 loss: 0.7782 2022/08/30 16:53:51 - mmengine - INFO - Epoch(train) [780][30/63] lr: 2.7233e-03 eta: 9:03:32 time: 1.0684 data_time: 0.0336 memory: 16201 loss_prob: 0.4107 loss_thr: 0.3053 loss_db: 0.0717 loss: 0.7877 2022/08/30 16:53:56 - mmengine - INFO - Epoch(train) [780][35/63] lr: 2.7233e-03 eta: 9:03:32 time: 0.9950 data_time: 0.0324 memory: 16201 loss_prob: 0.4038 loss_thr: 0.2903 loss_db: 0.0729 loss: 0.7671 2022/08/30 16:54:01 - mmengine - INFO - Epoch(train) [780][40/63] lr: 2.7233e-03 eta: 9:03:18 time: 1.0521 data_time: 0.0343 memory: 16201 loss_prob: 0.3996 loss_thr: 0.2806 loss_db: 0.0720 loss: 0.7521 2022/08/30 16:54:05 - mmengine - INFO - Epoch(train) [780][45/63] lr: 2.7233e-03 eta: 9:03:18 time: 0.9659 data_time: 0.0288 memory: 16201 loss_prob: 0.4072 loss_thr: 0.2905 loss_db: 0.0700 loss: 0.7677 2022/08/30 16:54:09 - mmengine - INFO - Epoch(train) [780][50/63] lr: 2.7233e-03 eta: 9:03:04 time: 0.8149 data_time: 0.0345 memory: 16201 loss_prob: 0.4134 loss_thr: 0.2946 loss_db: 0.0714 loss: 0.7793 2022/08/30 16:54:14 - mmengine - INFO - Epoch(train) [780][55/63] lr: 2.7233e-03 eta: 9:03:04 time: 0.8924 data_time: 0.0215 memory: 16201 loss_prob: 0.3726 loss_thr: 0.2611 loss_db: 0.0669 loss: 0.7006 2022/08/30 16:54:20 - mmengine - INFO - Epoch(train) [780][60/63] lr: 2.7233e-03 eta: 9:02:51 time: 1.1085 data_time: 0.0316 memory: 16201 loss_prob: 0.3922 loss_thr: 0.2783 loss_db: 0.0707 loss: 0.7412 2022/08/30 16:54:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:54:23 - mmengine - INFO - Saving checkpoint at 780 epochs 2022/08/30 16:54:32 - mmengine - INFO - Epoch(val) [780][5/32] eta: 9:02:51 time: 0.6864 data_time: 0.1322 memory: 16201 2022/08/30 16:54:35 - mmengine - INFO - Epoch(val) [780][10/32] eta: 0:00:17 time: 0.7763 data_time: 0.1790 memory: 15734 2022/08/30 16:54:38 - mmengine - INFO - Epoch(val) [780][15/32] eta: 0:00:17 time: 0.6357 data_time: 0.0614 memory: 15734 2022/08/30 16:54:42 - mmengine - INFO - Epoch(val) [780][20/32] eta: 0:00:07 time: 0.6412 data_time: 0.0624 memory: 15734 2022/08/30 16:54:45 - mmengine - INFO - Epoch(val) [780][25/32] eta: 0:00:07 time: 0.7087 data_time: 0.0761 memory: 15734 2022/08/30 16:54:48 - mmengine - INFO - Epoch(val) [780][30/32] eta: 0:00:01 time: 0.6556 data_time: 0.0331 memory: 15734 2022/08/30 16:54:49 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 16:54:49 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8435, precision: 0.7804, hmean: 0.8107 2022/08/30 16:54:49 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8435, precision: 0.8260, hmean: 0.8347 2022/08/30 16:54:49 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8421, precision: 0.8565, hmean: 0.8492 2022/08/30 16:54:49 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8387, precision: 0.8710, hmean: 0.8545 2022/08/30 16:54:49 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8281, precision: 0.8898, hmean: 0.8579 2022/08/30 16:54:49 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7891, precision: 0.9172, hmean: 0.8483 2022/08/30 16:54:49 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.3476, precision: 0.9601, hmean: 0.5104 2022/08/30 16:54:49 - mmengine - INFO - Epoch(val) [780][32/32] icdar/precision: 0.8898 icdar/recall: 0.8281 icdar/hmean: 0.8579 2022/08/30 16:54:57 - mmengine - INFO - Epoch(train) [781][5/63] lr: 2.7175e-03 eta: 0:00:01 time: 1.3564 data_time: 0.2680 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2836 loss_db: 0.0664 loss: 0.7268 2022/08/30 16:55:03 - mmengine - INFO - Epoch(train) [781][10/63] lr: 2.7175e-03 eta: 9:02:34 time: 1.3714 data_time: 0.2722 memory: 16201 loss_prob: 0.3655 loss_thr: 0.2726 loss_db: 0.0646 loss: 0.7027 2022/08/30 16:55:09 - mmengine - INFO - Epoch(train) [781][15/63] lr: 2.7175e-03 eta: 9:02:34 time: 1.1321 data_time: 0.0306 memory: 16201 loss_prob: 0.3427 loss_thr: 0.2574 loss_db: 0.0619 loss: 0.6621 2022/08/30 16:55:13 - mmengine - INFO - Epoch(train) [781][20/63] lr: 2.7175e-03 eta: 9:02:20 time: 1.0193 data_time: 0.0295 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2610 loss_db: 0.0632 loss: 0.6809 2022/08/30 16:55:17 - mmengine - INFO - Epoch(train) [781][25/63] lr: 2.7175e-03 eta: 9:02:20 time: 0.8560 data_time: 0.0308 memory: 16201 loss_prob: 0.3763 loss_thr: 0.2686 loss_db: 0.0655 loss: 0.7104 2022/08/30 16:55:22 - mmengine - INFO - Epoch(train) [781][30/63] lr: 2.7175e-03 eta: 9:02:06 time: 0.9019 data_time: 0.0309 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2928 loss_db: 0.0709 loss: 0.7590 2022/08/30 16:55:27 - mmengine - INFO - Epoch(train) [781][35/63] lr: 2.7175e-03 eta: 9:02:06 time: 0.9862 data_time: 0.0367 memory: 16201 loss_prob: 0.3911 loss_thr: 0.2975 loss_db: 0.0702 loss: 0.7587 2022/08/30 16:55:34 - mmengine - INFO - Epoch(train) [781][40/63] lr: 2.7175e-03 eta: 9:01:53 time: 1.1418 data_time: 0.0298 memory: 16201 loss_prob: 0.3982 loss_thr: 0.2805 loss_db: 0.0702 loss: 0.7489 2022/08/30 16:55:39 - mmengine - INFO - Epoch(train) [781][45/63] lr: 2.7175e-03 eta: 9:01:53 time: 1.1929 data_time: 0.0349 memory: 16201 loss_prob: 0.4397 loss_thr: 0.2826 loss_db: 0.0756 loss: 0.7979 2022/08/30 16:55:45 - mmengine - INFO - Epoch(train) [781][50/63] lr: 2.7175e-03 eta: 9:01:41 time: 1.1308 data_time: 0.0534 memory: 16201 loss_prob: 0.4342 loss_thr: 0.2895 loss_db: 0.0754 loss: 0.7992 2022/08/30 16:55:50 - mmengine - INFO - Epoch(train) [781][55/63] lr: 2.7175e-03 eta: 9:01:41 time: 1.0668 data_time: 0.0370 memory: 16201 loss_prob: 0.4241 loss_thr: 0.2932 loss_db: 0.0756 loss: 0.7929 2022/08/30 16:55:54 - mmengine - INFO - Epoch(train) [781][60/63] lr: 2.7175e-03 eta: 9:01:27 time: 0.9444 data_time: 0.0247 memory: 16201 loss_prob: 0.4018 loss_thr: 0.2791 loss_db: 0.0718 loss: 0.7527 2022/08/30 16:55:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:56:02 - mmengine - INFO - Epoch(train) [782][5/63] lr: 2.7116e-03 eta: 9:01:27 time: 0.9921 data_time: 0.2162 memory: 16201 loss_prob: 0.4395 loss_thr: 0.3073 loss_db: 0.0765 loss: 0.8233 2022/08/30 16:56:07 - mmengine - INFO - Epoch(train) [782][10/63] lr: 2.7116e-03 eta: 9:01:08 time: 1.1129 data_time: 0.2271 memory: 16201 loss_prob: 0.4010 loss_thr: 0.2898 loss_db: 0.0704 loss: 0.7611 2022/08/30 16:56:13 - mmengine - INFO - Epoch(train) [782][15/63] lr: 2.7116e-03 eta: 9:01:08 time: 1.1028 data_time: 0.0390 memory: 16201 loss_prob: 0.3892 loss_thr: 0.2784 loss_db: 0.0683 loss: 0.7359 2022/08/30 16:56:19 - mmengine - INFO - Epoch(train) [782][20/63] lr: 2.7116e-03 eta: 9:00:55 time: 1.1771 data_time: 0.0428 memory: 16201 loss_prob: 0.3931 loss_thr: 0.2776 loss_db: 0.0696 loss: 0.7403 2022/08/30 16:56:24 - mmengine - INFO - Epoch(train) [782][25/63] lr: 2.7116e-03 eta: 9:00:55 time: 1.0950 data_time: 0.0406 memory: 16201 loss_prob: 0.3843 loss_thr: 0.2723 loss_db: 0.0693 loss: 0.7260 2022/08/30 16:56:29 - mmengine - INFO - Epoch(train) [782][30/63] lr: 2.7116e-03 eta: 9:00:42 time: 1.0001 data_time: 0.0312 memory: 16201 loss_prob: 0.3982 loss_thr: 0.2850 loss_db: 0.0702 loss: 0.7533 2022/08/30 16:56:34 - mmengine - INFO - Epoch(train) [782][35/63] lr: 2.7116e-03 eta: 9:00:42 time: 0.9649 data_time: 0.0315 memory: 16201 loss_prob: 0.4261 loss_thr: 0.3229 loss_db: 0.0725 loss: 0.8215 2022/08/30 16:56:38 - mmengine - INFO - Epoch(train) [782][40/63] lr: 2.7116e-03 eta: 9:00:28 time: 0.9048 data_time: 0.0232 memory: 16201 loss_prob: 0.4054 loss_thr: 0.3141 loss_db: 0.0718 loss: 0.7913 2022/08/30 16:56:43 - mmengine - INFO - Epoch(train) [782][45/63] lr: 2.7116e-03 eta: 9:00:28 time: 0.8493 data_time: 0.0338 memory: 16201 loss_prob: 0.4160 loss_thr: 0.2987 loss_db: 0.0740 loss: 0.7888 2022/08/30 16:56:47 - mmengine - INFO - Epoch(train) [782][50/63] lr: 2.7116e-03 eta: 9:00:14 time: 0.8524 data_time: 0.0346 memory: 16201 loss_prob: 0.4321 loss_thr: 0.2936 loss_db: 0.0748 loss: 0.8006 2022/08/30 16:56:52 - mmengine - INFO - Epoch(train) [782][55/63] lr: 2.7116e-03 eta: 9:00:14 time: 0.9840 data_time: 0.0727 memory: 16201 loss_prob: 0.4353 loss_thr: 0.3002 loss_db: 0.0760 loss: 0.8115 2022/08/30 16:56:59 - mmengine - INFO - Epoch(train) [782][60/63] lr: 2.7116e-03 eta: 9:00:01 time: 1.1897 data_time: 0.0916 memory: 16201 loss_prob: 0.4193 loss_thr: 0.3001 loss_db: 0.0755 loss: 0.7948 2022/08/30 16:57:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:57:09 - mmengine - INFO - Epoch(train) [783][5/63] lr: 2.7058e-03 eta: 9:00:01 time: 1.3324 data_time: 0.2730 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2622 loss_db: 0.0652 loss: 0.6940 2022/08/30 16:57:13 - mmengine - INFO - Epoch(train) [783][10/63] lr: 2.7058e-03 eta: 8:59:43 time: 1.1985 data_time: 0.2637 memory: 16201 loss_prob: 0.3649 loss_thr: 0.2607 loss_db: 0.0648 loss: 0.6904 2022/08/30 16:57:18 - mmengine - INFO - Epoch(train) [783][15/63] lr: 2.7058e-03 eta: 8:59:43 time: 0.8889 data_time: 0.0280 memory: 16201 loss_prob: 0.4236 loss_thr: 0.2801 loss_db: 0.0725 loss: 0.7762 2022/08/30 16:57:23 - mmengine - INFO - Epoch(train) [783][20/63] lr: 2.7058e-03 eta: 8:59:29 time: 0.9707 data_time: 0.0235 memory: 16201 loss_prob: 0.4346 loss_thr: 0.2904 loss_db: 0.0728 loss: 0.7978 2022/08/30 16:57:28 - mmengine - INFO - Epoch(train) [783][25/63] lr: 2.7058e-03 eta: 8:59:29 time: 1.0008 data_time: 0.0446 memory: 16201 loss_prob: 0.4334 loss_thr: 0.3072 loss_db: 0.0764 loss: 0.8169 2022/08/30 16:57:34 - mmengine - INFO - Epoch(train) [783][30/63] lr: 2.7058e-03 eta: 8:59:16 time: 1.0414 data_time: 0.0313 memory: 16201 loss_prob: 0.3994 loss_thr: 0.2838 loss_db: 0.0714 loss: 0.7545 2022/08/30 16:57:40 - mmengine - INFO - Epoch(train) [783][35/63] lr: 2.7058e-03 eta: 8:59:16 time: 1.1938 data_time: 0.0298 memory: 16201 loss_prob: 0.4001 loss_thr: 0.2850 loss_db: 0.0708 loss: 0.7558 2022/08/30 16:57:45 - mmengine - INFO - Epoch(train) [783][40/63] lr: 2.7058e-03 eta: 8:59:03 time: 1.1112 data_time: 0.0333 memory: 16201 loss_prob: 0.4334 loss_thr: 0.3055 loss_db: 0.0760 loss: 0.8150 2022/08/30 16:57:50 - mmengine - INFO - Epoch(train) [783][45/63] lr: 2.7058e-03 eta: 8:59:03 time: 1.0546 data_time: 0.0309 memory: 16201 loss_prob: 0.3775 loss_thr: 0.2762 loss_db: 0.0671 loss: 0.7207 2022/08/30 16:57:56 - mmengine - INFO - Epoch(train) [783][50/63] lr: 2.7058e-03 eta: 8:58:50 time: 1.0996 data_time: 0.0417 memory: 16201 loss_prob: 0.4088 loss_thr: 0.2966 loss_db: 0.0736 loss: 0.7790 2022/08/30 16:58:02 - mmengine - INFO - Epoch(train) [783][55/63] lr: 2.7058e-03 eta: 8:58:50 time: 1.1151 data_time: 0.0355 memory: 16201 loss_prob: 0.4434 loss_thr: 0.3086 loss_db: 0.0787 loss: 0.8307 2022/08/30 16:58:06 - mmengine - INFO - Epoch(train) [783][60/63] lr: 2.7058e-03 eta: 8:58:36 time: 1.0019 data_time: 0.0321 memory: 16201 loss_prob: 0.4066 loss_thr: 0.2872 loss_db: 0.0707 loss: 0.7644 2022/08/30 16:58:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:58:14 - mmengine - INFO - Epoch(train) [784][5/63] lr: 2.6999e-03 eta: 8:58:36 time: 1.0173 data_time: 0.2299 memory: 16201 loss_prob: 0.4118 loss_thr: 0.2969 loss_db: 0.0732 loss: 0.7819 2022/08/30 16:58:19 - mmengine - INFO - Epoch(train) [784][10/63] lr: 2.6999e-03 eta: 8:58:18 time: 1.0785 data_time: 0.2394 memory: 16201 loss_prob: 0.4260 loss_thr: 0.2995 loss_db: 0.0764 loss: 0.8018 2022/08/30 16:58:23 - mmengine - INFO - Epoch(train) [784][15/63] lr: 2.6999e-03 eta: 8:58:18 time: 0.8681 data_time: 0.0297 memory: 16201 loss_prob: 0.3971 loss_thr: 0.2792 loss_db: 0.0705 loss: 0.7468 2022/08/30 16:58:28 - mmengine - INFO - Epoch(train) [784][20/63] lr: 2.6999e-03 eta: 8:58:04 time: 0.8922 data_time: 0.0316 memory: 16201 loss_prob: 0.3938 loss_thr: 0.2854 loss_db: 0.0700 loss: 0.7491 2022/08/30 16:58:34 - mmengine - INFO - Epoch(train) [784][25/63] lr: 2.6999e-03 eta: 8:58:04 time: 1.0929 data_time: 0.0453 memory: 16201 loss_prob: 0.4221 loss_thr: 0.3047 loss_db: 0.0725 loss: 0.7993 2022/08/30 16:58:41 - mmengine - INFO - Epoch(train) [784][30/63] lr: 2.6999e-03 eta: 8:57:52 time: 1.3239 data_time: 0.0399 memory: 16201 loss_prob: 0.4363 loss_thr: 0.3038 loss_db: 0.0751 loss: 0.8151 2022/08/30 16:58:46 - mmengine - INFO - Epoch(train) [784][35/63] lr: 2.6999e-03 eta: 8:57:52 time: 1.2233 data_time: 0.0362 memory: 16201 loss_prob: 0.4140 loss_thr: 0.2989 loss_db: 0.0742 loss: 0.7871 2022/08/30 16:58:52 - mmengine - INFO - Epoch(train) [784][40/63] lr: 2.6999e-03 eta: 8:57:39 time: 1.1491 data_time: 0.0349 memory: 16201 loss_prob: 0.3808 loss_thr: 0.2830 loss_db: 0.0672 loss: 0.7311 2022/08/30 16:58:57 - mmengine - INFO - Epoch(train) [784][45/63] lr: 2.6999e-03 eta: 8:57:39 time: 1.0635 data_time: 0.0330 memory: 16201 loss_prob: 0.3825 loss_thr: 0.2763 loss_db: 0.0673 loss: 0.7261 2022/08/30 16:59:02 - mmengine - INFO - Epoch(train) [784][50/63] lr: 2.6999e-03 eta: 8:57:26 time: 1.0150 data_time: 0.0502 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2666 loss_db: 0.0660 loss: 0.6992 2022/08/30 16:59:07 - mmengine - INFO - Epoch(train) [784][55/63] lr: 2.6999e-03 eta: 8:57:26 time: 0.9657 data_time: 0.0395 memory: 16201 loss_prob: 0.3719 loss_thr: 0.2758 loss_db: 0.0660 loss: 0.7138 2022/08/30 16:59:12 - mmengine - INFO - Epoch(train) [784][60/63] lr: 2.6999e-03 eta: 8:57:12 time: 0.9070 data_time: 0.0226 memory: 16201 loss_prob: 0.4005 loss_thr: 0.2875 loss_db: 0.0700 loss: 0.7580 2022/08/30 16:59:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 16:59:22 - mmengine - INFO - Epoch(train) [785][5/63] lr: 2.6941e-03 eta: 8:57:12 time: 1.2961 data_time: 0.2536 memory: 16201 loss_prob: 0.3854 loss_thr: 0.2767 loss_db: 0.0695 loss: 0.7316 2022/08/30 16:59:29 - mmengine - INFO - Epoch(train) [785][10/63] lr: 2.6941e-03 eta: 8:56:55 time: 1.4607 data_time: 0.2738 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2734 loss_db: 0.0667 loss: 0.7172 2022/08/30 16:59:34 - mmengine - INFO - Epoch(train) [785][15/63] lr: 2.6941e-03 eta: 8:56:55 time: 1.1284 data_time: 0.0429 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2643 loss_db: 0.0625 loss: 0.6863 2022/08/30 16:59:38 - mmengine - INFO - Epoch(train) [785][20/63] lr: 2.6941e-03 eta: 8:56:41 time: 0.9306 data_time: 0.0311 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2782 loss_db: 0.0678 loss: 0.7297 2022/08/30 16:59:43 - mmengine - INFO - Epoch(train) [785][25/63] lr: 2.6941e-03 eta: 8:56:41 time: 0.8906 data_time: 0.0356 memory: 16201 loss_prob: 0.4205 loss_thr: 0.3025 loss_db: 0.0738 loss: 0.7968 2022/08/30 16:59:47 - mmengine - INFO - Epoch(train) [785][30/63] lr: 2.6941e-03 eta: 8:56:27 time: 0.8608 data_time: 0.0233 memory: 16201 loss_prob: 0.4111 loss_thr: 0.2986 loss_db: 0.0716 loss: 0.7813 2022/08/30 16:59:53 - mmengine - INFO - Epoch(train) [785][35/63] lr: 2.6941e-03 eta: 8:56:27 time: 0.9885 data_time: 0.0327 memory: 16201 loss_prob: 0.3782 loss_thr: 0.2735 loss_db: 0.0666 loss: 0.7183 2022/08/30 16:59:58 - mmengine - INFO - Epoch(train) [785][40/63] lr: 2.6941e-03 eta: 8:56:14 time: 1.1206 data_time: 0.0379 memory: 16201 loss_prob: 0.4117 loss_thr: 0.2881 loss_db: 0.0722 loss: 0.7720 2022/08/30 17:00:03 - mmengine - INFO - Epoch(train) [785][45/63] lr: 2.6941e-03 eta: 8:56:14 time: 1.0845 data_time: 0.0388 memory: 16201 loss_prob: 0.4306 loss_thr: 0.2989 loss_db: 0.0757 loss: 0.8052 2022/08/30 17:00:08 - mmengine - INFO - Epoch(train) [785][50/63] lr: 2.6941e-03 eta: 8:56:00 time: 0.9561 data_time: 0.0445 memory: 16201 loss_prob: 0.3737 loss_thr: 0.2743 loss_db: 0.0666 loss: 0.7146 2022/08/30 17:00:12 - mmengine - INFO - Epoch(train) [785][55/63] lr: 2.6941e-03 eta: 8:56:00 time: 0.8354 data_time: 0.0241 memory: 16201 loss_prob: 0.3775 loss_thr: 0.2697 loss_db: 0.0658 loss: 0.7130 2022/08/30 17:00:16 - mmengine - INFO - Epoch(train) [785][60/63] lr: 2.6941e-03 eta: 8:55:46 time: 0.8529 data_time: 0.0283 memory: 16201 loss_prob: 0.4179 loss_thr: 0.2876 loss_db: 0.0730 loss: 0.7785 2022/08/30 17:00:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:00:27 - mmengine - INFO - Epoch(train) [786][5/63] lr: 2.6883e-03 eta: 8:55:46 time: 1.2775 data_time: 0.2146 memory: 16201 loss_prob: 0.3929 loss_thr: 0.2934 loss_db: 0.0690 loss: 0.7552 2022/08/30 17:00:33 - mmengine - INFO - Epoch(train) [786][10/63] lr: 2.6883e-03 eta: 8:55:28 time: 1.2686 data_time: 0.2387 memory: 16201 loss_prob: 0.3898 loss_thr: 0.2824 loss_db: 0.0683 loss: 0.7405 2022/08/30 17:00:39 - mmengine - INFO - Epoch(train) [786][15/63] lr: 2.6883e-03 eta: 8:55:28 time: 1.1441 data_time: 0.0423 memory: 16201 loss_prob: 0.3991 loss_thr: 0.2740 loss_db: 0.0710 loss: 0.7441 2022/08/30 17:00:44 - mmengine - INFO - Epoch(train) [786][20/63] lr: 2.6883e-03 eta: 8:55:15 time: 1.0744 data_time: 0.0359 memory: 16201 loss_prob: 0.4098 loss_thr: 0.2873 loss_db: 0.0739 loss: 0.7709 2022/08/30 17:00:48 - mmengine - INFO - Epoch(train) [786][25/63] lr: 2.6883e-03 eta: 8:55:15 time: 0.9199 data_time: 0.0360 memory: 16201 loss_prob: 0.4168 loss_thr: 0.3018 loss_db: 0.0735 loss: 0.7921 2022/08/30 17:00:52 - mmengine - INFO - Epoch(train) [786][30/63] lr: 2.6883e-03 eta: 8:55:01 time: 0.8408 data_time: 0.0290 memory: 16201 loss_prob: 0.4252 loss_thr: 0.3034 loss_db: 0.0716 loss: 0.8003 2022/08/30 17:00:56 - mmengine - INFO - Epoch(train) [786][35/63] lr: 2.6883e-03 eta: 8:55:01 time: 0.8695 data_time: 0.0436 memory: 16201 loss_prob: 0.4161 loss_thr: 0.2955 loss_db: 0.0719 loss: 0.7836 2022/08/30 17:01:02 - mmengine - INFO - Epoch(train) [786][40/63] lr: 2.6883e-03 eta: 8:54:47 time: 1.0116 data_time: 0.0433 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2772 loss_db: 0.0674 loss: 0.7284 2022/08/30 17:01:08 - mmengine - INFO - Epoch(train) [786][45/63] lr: 2.6883e-03 eta: 8:54:47 time: 1.1868 data_time: 0.0436 memory: 16201 loss_prob: 0.4246 loss_thr: 0.2875 loss_db: 0.0722 loss: 0.7844 2022/08/30 17:01:13 - mmengine - INFO - Epoch(train) [786][50/63] lr: 2.6883e-03 eta: 8:54:34 time: 1.0891 data_time: 0.0474 memory: 16201 loss_prob: 0.4587 loss_thr: 0.3077 loss_db: 0.0795 loss: 0.8459 2022/08/30 17:01:17 - mmengine - INFO - Epoch(train) [786][55/63] lr: 2.6883e-03 eta: 8:54:34 time: 0.9103 data_time: 0.0356 memory: 16201 loss_prob: 0.4404 loss_thr: 0.3047 loss_db: 0.0761 loss: 0.8212 2022/08/30 17:01:23 - mmengine - INFO - Epoch(train) [786][60/63] lr: 2.6883e-03 eta: 8:54:21 time: 0.9992 data_time: 0.0390 memory: 16201 loss_prob: 0.4140 loss_thr: 0.2916 loss_db: 0.0720 loss: 0.7776 2022/08/30 17:01:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:01:34 - mmengine - INFO - Epoch(train) [787][5/63] lr: 2.6824e-03 eta: 8:54:21 time: 1.3371 data_time: 0.2749 memory: 16201 loss_prob: 0.3492 loss_thr: 0.2609 loss_db: 0.0625 loss: 0.6727 2022/08/30 17:01:41 - mmengine - INFO - Epoch(train) [787][10/63] lr: 2.6824e-03 eta: 8:54:04 time: 1.4627 data_time: 0.2924 memory: 16201 loss_prob: 0.3650 loss_thr: 0.2718 loss_db: 0.0650 loss: 0.7018 2022/08/30 17:01:46 - mmengine - INFO - Epoch(train) [787][15/63] lr: 2.6824e-03 eta: 8:54:04 time: 1.1611 data_time: 0.0456 memory: 16201 loss_prob: 0.3784 loss_thr: 0.2814 loss_db: 0.0668 loss: 0.7266 2022/08/30 17:01:52 - mmengine - INFO - Epoch(train) [787][20/63] lr: 2.6824e-03 eta: 8:53:51 time: 1.1235 data_time: 0.0354 memory: 16201 loss_prob: 0.3816 loss_thr: 0.2722 loss_db: 0.0685 loss: 0.7223 2022/08/30 17:01:57 - mmengine - INFO - Epoch(train) [787][25/63] lr: 2.6824e-03 eta: 8:53:51 time: 1.0676 data_time: 0.0417 memory: 16201 loss_prob: 0.4013 loss_thr: 0.2893 loss_db: 0.0709 loss: 0.7615 2022/08/30 17:02:01 - mmengine - INFO - Epoch(train) [787][30/63] lr: 2.6824e-03 eta: 8:53:37 time: 0.9395 data_time: 0.0380 memory: 16201 loss_prob: 0.4133 loss_thr: 0.3005 loss_db: 0.0721 loss: 0.7858 2022/08/30 17:02:06 - mmengine - INFO - Epoch(train) [787][35/63] lr: 2.6824e-03 eta: 8:53:37 time: 0.9099 data_time: 0.0357 memory: 16201 loss_prob: 0.4436 loss_thr: 0.3119 loss_db: 0.0792 loss: 0.8347 2022/08/30 17:02:10 - mmengine - INFO - Epoch(train) [787][40/63] lr: 2.6824e-03 eta: 8:53:23 time: 0.9206 data_time: 0.0254 memory: 16201 loss_prob: 0.4473 loss_thr: 0.3106 loss_db: 0.0812 loss: 0.8391 2022/08/30 17:02:16 - mmengine - INFO - Epoch(train) [787][45/63] lr: 2.6824e-03 eta: 8:53:23 time: 1.0658 data_time: 0.0363 memory: 16201 loss_prob: 0.4085 loss_thr: 0.2954 loss_db: 0.0721 loss: 0.7759 2022/08/30 17:02:22 - mmengine - INFO - Epoch(train) [787][50/63] lr: 2.6824e-03 eta: 8:53:11 time: 1.1821 data_time: 0.0518 memory: 16201 loss_prob: 0.3701 loss_thr: 0.2745 loss_db: 0.0630 loss: 0.7076 2022/08/30 17:02:27 - mmengine - INFO - Epoch(train) [787][55/63] lr: 2.6824e-03 eta: 8:53:11 time: 1.0490 data_time: 0.0398 memory: 16201 loss_prob: 0.3776 loss_thr: 0.2704 loss_db: 0.0677 loss: 0.7157 2022/08/30 17:02:32 - mmengine - INFO - Epoch(train) [787][60/63] lr: 2.6824e-03 eta: 8:52:58 time: 1.0159 data_time: 0.0290 memory: 16201 loss_prob: 0.3820 loss_thr: 0.2846 loss_db: 0.0696 loss: 0.7361 2022/08/30 17:02:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:02:43 - mmengine - INFO - Epoch(train) [788][5/63] lr: 2.6766e-03 eta: 8:52:58 time: 1.2045 data_time: 0.2328 memory: 16201 loss_prob: 0.3791 loss_thr: 0.2824 loss_db: 0.0653 loss: 0.7267 2022/08/30 17:02:50 - mmengine - INFO - Epoch(train) [788][10/63] lr: 2.6766e-03 eta: 8:52:41 time: 1.4787 data_time: 0.2462 memory: 16201 loss_prob: 0.4124 loss_thr: 0.2923 loss_db: 0.0715 loss: 0.7761 2022/08/30 17:02:55 - mmengine - INFO - Epoch(train) [788][15/63] lr: 2.6766e-03 eta: 8:52:41 time: 1.1874 data_time: 0.0380 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2792 loss_db: 0.0704 loss: 0.7532 2022/08/30 17:02:59 - mmengine - INFO - Epoch(train) [788][20/63] lr: 2.6766e-03 eta: 8:52:27 time: 0.9190 data_time: 0.0322 memory: 16201 loss_prob: 0.3911 loss_thr: 0.2724 loss_db: 0.0684 loss: 0.7319 2022/08/30 17:03:03 - mmengine - INFO - Epoch(train) [788][25/63] lr: 2.6766e-03 eta: 8:52:27 time: 0.8643 data_time: 0.0310 memory: 16201 loss_prob: 0.3896 loss_thr: 0.2772 loss_db: 0.0694 loss: 0.7362 2022/08/30 17:03:08 - mmengine - INFO - Epoch(train) [788][30/63] lr: 2.6766e-03 eta: 8:52:13 time: 0.8958 data_time: 0.0220 memory: 16201 loss_prob: 0.3942 loss_thr: 0.2924 loss_db: 0.0703 loss: 0.7569 2022/08/30 17:03:13 - mmengine - INFO - Epoch(train) [788][35/63] lr: 2.6766e-03 eta: 8:52:13 time: 1.0032 data_time: 0.0446 memory: 16201 loss_prob: 0.4030 loss_thr: 0.3016 loss_db: 0.0715 loss: 0.7761 2022/08/30 17:03:18 - mmengine - INFO - Epoch(train) [788][40/63] lr: 2.6766e-03 eta: 8:52:00 time: 1.0491 data_time: 0.0357 memory: 16201 loss_prob: 0.3779 loss_thr: 0.2821 loss_db: 0.0688 loss: 0.7288 2022/08/30 17:03:24 - mmengine - INFO - Epoch(train) [788][45/63] lr: 2.6766e-03 eta: 8:52:00 time: 1.0790 data_time: 0.0327 memory: 16201 loss_prob: 0.3228 loss_thr: 0.2502 loss_db: 0.0588 loss: 0.6318 2022/08/30 17:03:30 - mmengine - INFO - Epoch(train) [788][50/63] lr: 2.6766e-03 eta: 8:51:47 time: 1.1316 data_time: 0.0508 memory: 16201 loss_prob: 0.3093 loss_thr: 0.2375 loss_db: 0.0533 loss: 0.6001 2022/08/30 17:03:34 - mmengine - INFO - Epoch(train) [788][55/63] lr: 2.6766e-03 eta: 8:51:47 time: 1.0413 data_time: 0.0380 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2623 loss_db: 0.0598 loss: 0.6608 2022/08/30 17:03:39 - mmengine - INFO - Epoch(train) [788][60/63] lr: 2.6766e-03 eta: 8:51:33 time: 0.9489 data_time: 0.0285 memory: 16201 loss_prob: 0.3861 loss_thr: 0.2851 loss_db: 0.0701 loss: 0.7413 2022/08/30 17:03:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:03:49 - mmengine - INFO - Epoch(train) [789][5/63] lr: 2.6707e-03 eta: 8:51:33 time: 1.1422 data_time: 0.2379 memory: 16201 loss_prob: 0.4039 loss_thr: 0.2827 loss_db: 0.0699 loss: 0.7565 2022/08/30 17:03:54 - mmengine - INFO - Epoch(train) [789][10/63] lr: 2.6707e-03 eta: 8:51:15 time: 1.2321 data_time: 0.2529 memory: 16201 loss_prob: 0.3850 loss_thr: 0.2637 loss_db: 0.0666 loss: 0.7153 2022/08/30 17:03:59 - mmengine - INFO - Epoch(train) [789][15/63] lr: 2.6707e-03 eta: 8:51:15 time: 1.0628 data_time: 0.0333 memory: 16201 loss_prob: 0.3752 loss_thr: 0.2781 loss_db: 0.0667 loss: 0.7200 2022/08/30 17:04:05 - mmengine - INFO - Epoch(train) [789][20/63] lr: 2.6707e-03 eta: 8:51:02 time: 1.1088 data_time: 0.0357 memory: 16201 loss_prob: 0.4163 loss_thr: 0.3020 loss_db: 0.0736 loss: 0.7918 2022/08/30 17:04:11 - mmengine - INFO - Epoch(train) [789][25/63] lr: 2.6707e-03 eta: 8:51:02 time: 1.2150 data_time: 0.0490 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2677 loss_db: 0.0653 loss: 0.7089 2022/08/30 17:04:16 - mmengine - INFO - Epoch(train) [789][30/63] lr: 2.6707e-03 eta: 8:50:50 time: 1.1073 data_time: 0.0401 memory: 16201 loss_prob: 0.4132 loss_thr: 0.2940 loss_db: 0.0702 loss: 0.7774 2022/08/30 17:04:21 - mmengine - INFO - Epoch(train) [789][35/63] lr: 2.6707e-03 eta: 8:50:50 time: 0.9257 data_time: 0.0346 memory: 16201 loss_prob: 0.4472 loss_thr: 0.3115 loss_db: 0.0776 loss: 0.8363 2022/08/30 17:04:25 - mmengine - INFO - Epoch(train) [789][40/63] lr: 2.6707e-03 eta: 8:50:36 time: 0.9315 data_time: 0.0371 memory: 16201 loss_prob: 0.4119 loss_thr: 0.3004 loss_db: 0.0737 loss: 0.7861 2022/08/30 17:04:31 - mmengine - INFO - Epoch(train) [789][45/63] lr: 2.6707e-03 eta: 8:50:36 time: 1.0595 data_time: 0.0509 memory: 16201 loss_prob: 0.4320 loss_thr: 0.3123 loss_db: 0.0772 loss: 0.8215 2022/08/30 17:04:37 - mmengine - INFO - Epoch(train) [789][50/63] lr: 2.6707e-03 eta: 8:50:23 time: 1.1867 data_time: 0.0495 memory: 16201 loss_prob: 0.4034 loss_thr: 0.2901 loss_db: 0.0717 loss: 0.7652 2022/08/30 17:04:43 - mmengine - INFO - Epoch(train) [789][55/63] lr: 2.6707e-03 eta: 8:50:23 time: 1.1598 data_time: 0.0353 memory: 16201 loss_prob: 0.4042 loss_thr: 0.2857 loss_db: 0.0710 loss: 0.7610 2022/08/30 17:04:50 - mmengine - INFO - Epoch(train) [789][60/63] lr: 2.6707e-03 eta: 8:50:11 time: 1.2886 data_time: 0.0438 memory: 16201 loss_prob: 0.4234 loss_thr: 0.2927 loss_db: 0.0747 loss: 0.7909 2022/08/30 17:04:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:05:00 - mmengine - INFO - Epoch(train) [790][5/63] lr: 2.6649e-03 eta: 8:50:11 time: 1.2237 data_time: 0.2671 memory: 16201 loss_prob: 0.4052 loss_thr: 0.2850 loss_db: 0.0725 loss: 0.7626 2022/08/30 17:05:04 - mmengine - INFO - Epoch(train) [790][10/63] lr: 2.6649e-03 eta: 8:49:53 time: 1.0869 data_time: 0.2666 memory: 16201 loss_prob: 0.4286 loss_thr: 0.2953 loss_db: 0.0774 loss: 0.8013 2022/08/30 17:05:09 - mmengine - INFO - Epoch(train) [790][15/63] lr: 2.6649e-03 eta: 8:49:53 time: 0.9052 data_time: 0.0345 memory: 16201 loss_prob: 0.4224 loss_thr: 0.3016 loss_db: 0.0738 loss: 0.7979 2022/08/30 17:05:14 - mmengine - INFO - Epoch(train) [790][20/63] lr: 2.6649e-03 eta: 8:49:39 time: 0.9692 data_time: 0.0344 memory: 16201 loss_prob: 0.4276 loss_thr: 0.2984 loss_db: 0.0736 loss: 0.7997 2022/08/30 17:05:19 - mmengine - INFO - Epoch(train) [790][25/63] lr: 2.6649e-03 eta: 8:49:39 time: 1.0612 data_time: 0.0327 memory: 16201 loss_prob: 0.4159 loss_thr: 0.2918 loss_db: 0.0737 loss: 0.7814 2022/08/30 17:05:25 - mmengine - INFO - Epoch(train) [790][30/63] lr: 2.6649e-03 eta: 8:49:26 time: 1.1358 data_time: 0.0450 memory: 16201 loss_prob: 0.3976 loss_thr: 0.2951 loss_db: 0.0706 loss: 0.7633 2022/08/30 17:05:31 - mmengine - INFO - Epoch(train) [790][35/63] lr: 2.6649e-03 eta: 8:49:26 time: 1.1801 data_time: 0.0468 memory: 16201 loss_prob: 0.3828 loss_thr: 0.2910 loss_db: 0.0683 loss: 0.7421 2022/08/30 17:05:36 - mmengine - INFO - Epoch(train) [790][40/63] lr: 2.6649e-03 eta: 8:49:13 time: 1.1477 data_time: 0.0401 memory: 16201 loss_prob: 0.4062 loss_thr: 0.3111 loss_db: 0.0734 loss: 0.7907 2022/08/30 17:05:42 - mmengine - INFO - Epoch(train) [790][45/63] lr: 2.6649e-03 eta: 8:49:13 time: 1.0494 data_time: 0.0494 memory: 16201 loss_prob: 0.4235 loss_thr: 0.3239 loss_db: 0.0748 loss: 0.8222 2022/08/30 17:05:47 - mmengine - INFO - Epoch(train) [790][50/63] lr: 2.6649e-03 eta: 8:49:00 time: 1.0585 data_time: 0.0544 memory: 16201 loss_prob: 0.4023 loss_thr: 0.3063 loss_db: 0.0721 loss: 0.7808 2022/08/30 17:05:53 - mmengine - INFO - Epoch(train) [790][55/63] lr: 2.6649e-03 eta: 8:49:00 time: 1.0954 data_time: 0.0428 memory: 16201 loss_prob: 0.4118 loss_thr: 0.2987 loss_db: 0.0746 loss: 0.7850 2022/08/30 17:05:57 - mmengine - INFO - Epoch(train) [790][60/63] lr: 2.6649e-03 eta: 8:48:47 time: 0.9997 data_time: 0.0342 memory: 16201 loss_prob: 0.4280 loss_thr: 0.3101 loss_db: 0.0745 loss: 0.8126 2022/08/30 17:06:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:06:07 - mmengine - INFO - Epoch(train) [791][5/63] lr: 2.6590e-03 eta: 8:48:47 time: 1.1938 data_time: 0.2769 memory: 16201 loss_prob: 0.4067 loss_thr: 0.3086 loss_db: 0.0736 loss: 0.7890 2022/08/30 17:06:12 - mmengine - INFO - Epoch(train) [791][10/63] lr: 2.6590e-03 eta: 8:48:29 time: 1.1777 data_time: 0.2909 memory: 16201 loss_prob: 0.3718 loss_thr: 0.2760 loss_db: 0.0678 loss: 0.7155 2022/08/30 17:06:16 - mmengine - INFO - Epoch(train) [791][15/63] lr: 2.6590e-03 eta: 8:48:29 time: 0.9177 data_time: 0.0346 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2740 loss_db: 0.0646 loss: 0.6984 2022/08/30 17:06:22 - mmengine - INFO - Epoch(train) [791][20/63] lr: 2.6590e-03 eta: 8:48:16 time: 1.0605 data_time: 0.0342 memory: 16201 loss_prob: 0.3828 loss_thr: 0.2857 loss_db: 0.0697 loss: 0.7382 2022/08/30 17:06:28 - mmengine - INFO - Epoch(train) [791][25/63] lr: 2.6590e-03 eta: 8:48:16 time: 1.1499 data_time: 0.0543 memory: 16201 loss_prob: 0.4262 loss_thr: 0.3062 loss_db: 0.0756 loss: 0.8079 2022/08/30 17:06:34 - mmengine - INFO - Epoch(train) [791][30/63] lr: 2.6590e-03 eta: 8:48:03 time: 1.1522 data_time: 0.0470 memory: 16201 loss_prob: 0.4384 loss_thr: 0.3184 loss_db: 0.0750 loss: 0.8318 2022/08/30 17:06:38 - mmengine - INFO - Epoch(train) [791][35/63] lr: 2.6590e-03 eta: 8:48:03 time: 1.0457 data_time: 0.0340 memory: 16201 loss_prob: 0.4225 loss_thr: 0.3162 loss_db: 0.0736 loss: 0.8124 2022/08/30 17:06:43 - mmengine - INFO - Epoch(train) [791][40/63] lr: 2.6590e-03 eta: 8:47:49 time: 0.8891 data_time: 0.0256 memory: 16201 loss_prob: 0.4013 loss_thr: 0.2940 loss_db: 0.0724 loss: 0.7677 2022/08/30 17:06:47 - mmengine - INFO - Epoch(train) [791][45/63] lr: 2.6590e-03 eta: 8:47:49 time: 0.8672 data_time: 0.0246 memory: 16201 loss_prob: 0.3629 loss_thr: 0.2626 loss_db: 0.0657 loss: 0.6912 2022/08/30 17:06:53 - mmengine - INFO - Epoch(train) [791][50/63] lr: 2.6590e-03 eta: 8:47:36 time: 1.0558 data_time: 0.0461 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2642 loss_db: 0.0644 loss: 0.6951 2022/08/30 17:06:59 - mmengine - INFO - Epoch(train) [791][55/63] lr: 2.6590e-03 eta: 8:47:36 time: 1.2114 data_time: 0.0463 memory: 16201 loss_prob: 0.4138 loss_thr: 0.2906 loss_db: 0.0717 loss: 0.7760 2022/08/30 17:07:04 - mmengine - INFO - Epoch(train) [791][60/63] lr: 2.6590e-03 eta: 8:47:23 time: 1.0822 data_time: 0.0370 memory: 16201 loss_prob: 0.3776 loss_thr: 0.2787 loss_db: 0.0667 loss: 0.7230 2022/08/30 17:07:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:07:14 - mmengine - INFO - Epoch(train) [792][5/63] lr: 2.6532e-03 eta: 8:47:23 time: 1.1334 data_time: 0.2331 memory: 16201 loss_prob: 0.4051 loss_thr: 0.2828 loss_db: 0.0735 loss: 0.7614 2022/08/30 17:07:21 - mmengine - INFO - Epoch(train) [792][10/63] lr: 2.6532e-03 eta: 8:47:06 time: 1.5091 data_time: 0.2524 memory: 16201 loss_prob: 0.3887 loss_thr: 0.2757 loss_db: 0.0690 loss: 0.7335 2022/08/30 17:07:27 - mmengine - INFO - Epoch(train) [792][15/63] lr: 2.6532e-03 eta: 8:47:06 time: 1.3288 data_time: 0.0474 memory: 16201 loss_prob: 0.4040 loss_thr: 0.2802 loss_db: 0.0702 loss: 0.7544 2022/08/30 17:07:33 - mmengine - INFO - Epoch(train) [792][20/63] lr: 2.6532e-03 eta: 8:46:54 time: 1.1743 data_time: 0.0415 memory: 16201 loss_prob: 0.4196 loss_thr: 0.2904 loss_db: 0.0740 loss: 0.7841 2022/08/30 17:07:38 - mmengine - INFO - Epoch(train) [792][25/63] lr: 2.6532e-03 eta: 8:46:54 time: 1.0542 data_time: 0.0530 memory: 16201 loss_prob: 0.4361 loss_thr: 0.3073 loss_db: 0.0776 loss: 0.8210 2022/08/30 17:07:44 - mmengine - INFO - Epoch(train) [792][30/63] lr: 2.6532e-03 eta: 8:46:40 time: 1.0396 data_time: 0.0570 memory: 16201 loss_prob: 0.4469 loss_thr: 0.3186 loss_db: 0.0789 loss: 0.8444 2022/08/30 17:07:48 - mmengine - INFO - Epoch(train) [792][35/63] lr: 2.6532e-03 eta: 8:46:40 time: 1.0122 data_time: 0.0503 memory: 16201 loss_prob: 0.3997 loss_thr: 0.2883 loss_db: 0.0719 loss: 0.7599 2022/08/30 17:07:53 - mmengine - INFO - Epoch(train) [792][40/63] lr: 2.6532e-03 eta: 8:46:27 time: 0.9611 data_time: 0.0370 memory: 16201 loss_prob: 0.3818 loss_thr: 0.2655 loss_db: 0.0692 loss: 0.7165 2022/08/30 17:07:59 - mmengine - INFO - Epoch(train) [792][45/63] lr: 2.6532e-03 eta: 8:46:27 time: 1.0822 data_time: 0.0366 memory: 16201 loss_prob: 0.4119 loss_thr: 0.2826 loss_db: 0.0726 loss: 0.7672 2022/08/30 17:08:05 - mmengine - INFO - Epoch(train) [792][50/63] lr: 2.6532e-03 eta: 8:46:15 time: 1.2306 data_time: 0.0905 memory: 16201 loss_prob: 0.4058 loss_thr: 0.2888 loss_db: 0.0711 loss: 0.7658 2022/08/30 17:08:11 - mmengine - INFO - Epoch(train) [792][55/63] lr: 2.6532e-03 eta: 8:46:15 time: 1.2412 data_time: 0.0804 memory: 16201 loss_prob: 0.3911 loss_thr: 0.2841 loss_db: 0.0704 loss: 0.7456 2022/08/30 17:08:16 - mmengine - INFO - Epoch(train) [792][60/63] lr: 2.6532e-03 eta: 8:46:01 time: 1.0708 data_time: 0.0327 memory: 16201 loss_prob: 0.3932 loss_thr: 0.2928 loss_db: 0.0713 loss: 0.7573 2022/08/30 17:08:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:08:25 - mmengine - INFO - Epoch(train) [793][5/63] lr: 2.6473e-03 eta: 8:46:01 time: 1.0648 data_time: 0.2561 memory: 16201 loss_prob: 0.3839 loss_thr: 0.2817 loss_db: 0.0667 loss: 0.7323 2022/08/30 17:08:30 - mmengine - INFO - Epoch(train) [793][10/63] lr: 2.6473e-03 eta: 8:45:43 time: 1.1504 data_time: 0.2753 memory: 16201 loss_prob: 0.3934 loss_thr: 0.2806 loss_db: 0.0699 loss: 0.7439 2022/08/30 17:08:35 - mmengine - INFO - Epoch(train) [793][15/63] lr: 2.6473e-03 eta: 8:45:43 time: 1.0155 data_time: 0.0371 memory: 16201 loss_prob: 0.3761 loss_thr: 0.2759 loss_db: 0.0666 loss: 0.7186 2022/08/30 17:08:41 - mmengine - INFO - Epoch(train) [793][20/63] lr: 2.6473e-03 eta: 8:45:30 time: 1.1404 data_time: 0.0460 memory: 16201 loss_prob: 0.3812 loss_thr: 0.2733 loss_db: 0.0665 loss: 0.7211 2022/08/30 17:08:46 - mmengine - INFO - Epoch(train) [793][25/63] lr: 2.6473e-03 eta: 8:45:30 time: 1.0422 data_time: 0.0551 memory: 16201 loss_prob: 0.3965 loss_thr: 0.2710 loss_db: 0.0688 loss: 0.7363 2022/08/30 17:08:51 - mmengine - INFO - Epoch(train) [793][30/63] lr: 2.6473e-03 eta: 8:45:17 time: 0.9685 data_time: 0.0301 memory: 16201 loss_prob: 0.3950 loss_thr: 0.2743 loss_db: 0.0697 loss: 0.7390 2022/08/30 17:08:56 - mmengine - INFO - Epoch(train) [793][35/63] lr: 2.6473e-03 eta: 8:45:17 time: 1.0683 data_time: 0.0354 memory: 16201 loss_prob: 0.4000 loss_thr: 0.2876 loss_db: 0.0702 loss: 0.7579 2022/08/30 17:09:04 - mmengine - INFO - Epoch(train) [793][40/63] lr: 2.6473e-03 eta: 8:45:05 time: 1.2718 data_time: 0.0410 memory: 16201 loss_prob: 0.3975 loss_thr: 0.2958 loss_db: 0.0688 loss: 0.7621 2022/08/30 17:09:09 - mmengine - INFO - Epoch(train) [793][45/63] lr: 2.6473e-03 eta: 8:45:05 time: 1.3064 data_time: 0.0393 memory: 16201 loss_prob: 0.4055 loss_thr: 0.2973 loss_db: 0.0718 loss: 0.7746 2022/08/30 17:09:16 - mmengine - INFO - Epoch(train) [793][50/63] lr: 2.6473e-03 eta: 8:44:52 time: 1.1959 data_time: 0.0491 memory: 16201 loss_prob: 0.3935 loss_thr: 0.2827 loss_db: 0.0707 loss: 0.7469 2022/08/30 17:09:21 - mmengine - INFO - Epoch(train) [793][55/63] lr: 2.6473e-03 eta: 8:44:52 time: 1.1533 data_time: 0.0358 memory: 16201 loss_prob: 0.4294 loss_thr: 0.2909 loss_db: 0.0719 loss: 0.7923 2022/08/30 17:09:26 - mmengine - INFO - Epoch(train) [793][60/63] lr: 2.6473e-03 eta: 8:44:39 time: 1.0120 data_time: 0.0360 memory: 16201 loss_prob: 0.4524 loss_thr: 0.2991 loss_db: 0.0763 loss: 0.8277 2022/08/30 17:09:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:09:34 - mmengine - INFO - Epoch(train) [794][5/63] lr: 2.6415e-03 eta: 8:44:39 time: 1.0259 data_time: 0.2049 memory: 16201 loss_prob: 0.4082 loss_thr: 0.2824 loss_db: 0.0728 loss: 0.7634 2022/08/30 17:09:39 - mmengine - INFO - Epoch(train) [794][10/63] lr: 2.6415e-03 eta: 8:44:21 time: 1.1108 data_time: 0.2133 memory: 16201 loss_prob: 0.4838 loss_thr: 0.3321 loss_db: 0.0835 loss: 0.8994 2022/08/30 17:09:45 - mmengine - INFO - Epoch(train) [794][15/63] lr: 2.6415e-03 eta: 8:44:21 time: 1.0442 data_time: 0.0379 memory: 16201 loss_prob: 0.4590 loss_thr: 0.3143 loss_db: 0.0776 loss: 0.8509 2022/08/30 17:09:50 - mmengine - INFO - Epoch(train) [794][20/63] lr: 2.6415e-03 eta: 8:44:08 time: 1.0850 data_time: 0.0431 memory: 16201 loss_prob: 0.4166 loss_thr: 0.2849 loss_db: 0.0730 loss: 0.7745 2022/08/30 17:09:55 - mmengine - INFO - Epoch(train) [794][25/63] lr: 2.6415e-03 eta: 8:44:08 time: 1.0637 data_time: 0.0412 memory: 16201 loss_prob: 0.3920 loss_thr: 0.2786 loss_db: 0.0695 loss: 0.7400 2022/08/30 17:10:00 - mmengine - INFO - Epoch(train) [794][30/63] lr: 2.6415e-03 eta: 8:43:54 time: 0.9723 data_time: 0.0345 memory: 16201 loss_prob: 0.3813 loss_thr: 0.2821 loss_db: 0.0674 loss: 0.7309 2022/08/30 17:10:04 - mmengine - INFO - Epoch(train) [794][35/63] lr: 2.6415e-03 eta: 8:43:54 time: 0.8766 data_time: 0.0282 memory: 16201 loss_prob: 0.4069 loss_thr: 0.2961 loss_db: 0.0717 loss: 0.7747 2022/08/30 17:10:10 - mmengine - INFO - Epoch(train) [794][40/63] lr: 2.6415e-03 eta: 8:43:41 time: 1.0742 data_time: 0.0308 memory: 16201 loss_prob: 0.4216 loss_thr: 0.2998 loss_db: 0.0736 loss: 0.7950 2022/08/30 17:10:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:10:16 - mmengine - INFO - Epoch(train) [794][45/63] lr: 2.6415e-03 eta: 8:43:41 time: 1.1947 data_time: 0.0527 memory: 16201 loss_prob: 0.4158 loss_thr: 0.2955 loss_db: 0.0729 loss: 0.7841 2022/08/30 17:10:20 - mmengine - INFO - Epoch(train) [794][50/63] lr: 2.6415e-03 eta: 8:43:27 time: 1.0097 data_time: 0.0452 memory: 16201 loss_prob: 0.3891 loss_thr: 0.2805 loss_db: 0.0692 loss: 0.7387 2022/08/30 17:10:25 - mmengine - INFO - Epoch(train) [794][55/63] lr: 2.6415e-03 eta: 8:43:27 time: 0.8945 data_time: 0.0298 memory: 16201 loss_prob: 0.3810 loss_thr: 0.2785 loss_db: 0.0669 loss: 0.7263 2022/08/30 17:10:30 - mmengine - INFO - Epoch(train) [794][60/63] lr: 2.6415e-03 eta: 8:43:14 time: 0.9406 data_time: 0.0346 memory: 16201 loss_prob: 0.3856 loss_thr: 0.2793 loss_db: 0.0681 loss: 0.7331 2022/08/30 17:10:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:10:40 - mmengine - INFO - Epoch(train) [795][5/63] lr: 2.6356e-03 eta: 8:43:14 time: 1.2232 data_time: 0.2832 memory: 16201 loss_prob: 0.4265 loss_thr: 0.3048 loss_db: 0.0757 loss: 0.8070 2022/08/30 17:10:45 - mmengine - INFO - Epoch(train) [795][10/63] lr: 2.6356e-03 eta: 8:42:56 time: 1.2895 data_time: 0.2921 memory: 16201 loss_prob: 0.3842 loss_thr: 0.2837 loss_db: 0.0670 loss: 0.7349 2022/08/30 17:10:52 - mmengine - INFO - Epoch(train) [795][15/63] lr: 2.6356e-03 eta: 8:42:56 time: 1.1672 data_time: 0.0341 memory: 16201 loss_prob: 0.3670 loss_thr: 0.2690 loss_db: 0.0655 loss: 0.7014 2022/08/30 17:10:57 - mmengine - INFO - Epoch(train) [795][20/63] lr: 2.6356e-03 eta: 8:42:44 time: 1.2116 data_time: 0.0417 memory: 16201 loss_prob: 0.3862 loss_thr: 0.2761 loss_db: 0.0694 loss: 0.7317 2022/08/30 17:11:03 - mmengine - INFO - Epoch(train) [795][25/63] lr: 2.6356e-03 eta: 8:42:44 time: 1.1075 data_time: 0.0485 memory: 16201 loss_prob: 0.3995 loss_thr: 0.2840 loss_db: 0.0727 loss: 0.7563 2022/08/30 17:11:09 - mmengine - INFO - Epoch(train) [795][30/63] lr: 2.6356e-03 eta: 8:42:31 time: 1.1431 data_time: 0.0326 memory: 16201 loss_prob: 0.3989 loss_thr: 0.2823 loss_db: 0.0700 loss: 0.7512 2022/08/30 17:11:14 - mmengine - INFO - Epoch(train) [795][35/63] lr: 2.6356e-03 eta: 8:42:31 time: 1.1010 data_time: 0.0348 memory: 16201 loss_prob: 0.3955 loss_thr: 0.2799 loss_db: 0.0686 loss: 0.7439 2022/08/30 17:11:18 - mmengine - INFO - Epoch(train) [795][40/63] lr: 2.6356e-03 eta: 8:42:17 time: 0.9406 data_time: 0.0348 memory: 16201 loss_prob: 0.4294 loss_thr: 0.2906 loss_db: 0.0768 loss: 0.7969 2022/08/30 17:11:22 - mmengine - INFO - Epoch(train) [795][45/63] lr: 2.6356e-03 eta: 8:42:17 time: 0.8530 data_time: 0.0303 memory: 16201 loss_prob: 0.4219 loss_thr: 0.2913 loss_db: 0.0735 loss: 0.7867 2022/08/30 17:11:27 - mmengine - INFO - Epoch(train) [795][50/63] lr: 2.6356e-03 eta: 8:42:03 time: 0.8653 data_time: 0.0342 memory: 16201 loss_prob: 0.4035 loss_thr: 0.3000 loss_db: 0.0696 loss: 0.7731 2022/08/30 17:11:31 - mmengine - INFO - Epoch(train) [795][55/63] lr: 2.6356e-03 eta: 8:42:03 time: 0.8963 data_time: 0.0373 memory: 16201 loss_prob: 0.3932 loss_thr: 0.2963 loss_db: 0.0698 loss: 0.7593 2022/08/30 17:11:37 - mmengine - INFO - Epoch(train) [795][60/63] lr: 2.6356e-03 eta: 8:41:50 time: 1.0096 data_time: 0.0370 memory: 16201 loss_prob: 0.3970 loss_thr: 0.2865 loss_db: 0.0706 loss: 0.7541 2022/08/30 17:11:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:11:48 - mmengine - INFO - Epoch(train) [796][5/63] lr: 2.6297e-03 eta: 8:41:50 time: 1.3844 data_time: 0.2985 memory: 16201 loss_prob: 0.3899 loss_thr: 0.2800 loss_db: 0.0693 loss: 0.7392 2022/08/30 17:11:54 - mmengine - INFO - Epoch(train) [796][10/63] lr: 2.6297e-03 eta: 8:41:33 time: 1.4467 data_time: 0.3065 memory: 16201 loss_prob: 0.3824 loss_thr: 0.2732 loss_db: 0.0682 loss: 0.7238 2022/08/30 17:12:00 - mmengine - INFO - Epoch(train) [796][15/63] lr: 2.6297e-03 eta: 8:41:33 time: 1.2074 data_time: 0.0348 memory: 16201 loss_prob: 0.3714 loss_thr: 0.2679 loss_db: 0.0654 loss: 0.7047 2022/08/30 17:12:06 - mmengine - INFO - Epoch(train) [796][20/63] lr: 2.6297e-03 eta: 8:41:21 time: 1.1940 data_time: 0.0424 memory: 16201 loss_prob: 0.3808 loss_thr: 0.2702 loss_db: 0.0670 loss: 0.7180 2022/08/30 17:12:11 - mmengine - INFO - Epoch(train) [796][25/63] lr: 2.6297e-03 eta: 8:41:21 time: 1.0922 data_time: 0.0526 memory: 16201 loss_prob: 0.3794 loss_thr: 0.2740 loss_db: 0.0684 loss: 0.7218 2022/08/30 17:12:16 - mmengine - INFO - Epoch(train) [796][30/63] lr: 2.6297e-03 eta: 8:41:07 time: 0.9851 data_time: 0.0339 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2911 loss_db: 0.0713 loss: 0.7610 2022/08/30 17:12:21 - mmengine - INFO - Epoch(train) [796][35/63] lr: 2.6297e-03 eta: 8:41:07 time: 0.9473 data_time: 0.0317 memory: 16201 loss_prob: 0.4068 loss_thr: 0.2885 loss_db: 0.0705 loss: 0.7658 2022/08/30 17:12:25 - mmengine - INFO - Epoch(train) [796][40/63] lr: 2.6297e-03 eta: 8:40:53 time: 0.9014 data_time: 0.0261 memory: 16201 loss_prob: 0.4162 loss_thr: 0.2788 loss_db: 0.0706 loss: 0.7657 2022/08/30 17:12:30 - mmengine - INFO - Epoch(train) [796][45/63] lr: 2.6297e-03 eta: 8:40:53 time: 0.9161 data_time: 0.0602 memory: 16201 loss_prob: 0.3997 loss_thr: 0.2724 loss_db: 0.0680 loss: 0.7401 2022/08/30 17:12:35 - mmengine - INFO - Epoch(train) [796][50/63] lr: 2.6297e-03 eta: 8:40:40 time: 0.9648 data_time: 0.0683 memory: 16201 loss_prob: 0.3695 loss_thr: 0.2731 loss_db: 0.0645 loss: 0.7071 2022/08/30 17:12:40 - mmengine - INFO - Epoch(train) [796][55/63] lr: 2.6297e-03 eta: 8:40:40 time: 1.0296 data_time: 0.0237 memory: 16201 loss_prob: 0.3948 loss_thr: 0.2956 loss_db: 0.0686 loss: 0.7590 2022/08/30 17:12:46 - mmengine - INFO - Epoch(train) [796][60/63] lr: 2.6297e-03 eta: 8:40:27 time: 1.1034 data_time: 0.0423 memory: 16201 loss_prob: 0.4362 loss_thr: 0.3112 loss_db: 0.0766 loss: 0.8240 2022/08/30 17:12:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:12:58 - mmengine - INFO - Epoch(train) [797][5/63] lr: 2.6239e-03 eta: 8:40:27 time: 1.3862 data_time: 0.3338 memory: 16201 loss_prob: 0.4646 loss_thr: 0.3093 loss_db: 0.0797 loss: 0.8536 2022/08/30 17:13:03 - mmengine - INFO - Epoch(train) [797][10/63] lr: 2.6239e-03 eta: 8:40:11 time: 1.5197 data_time: 0.3807 memory: 16201 loss_prob: 0.4220 loss_thr: 0.2914 loss_db: 0.0719 loss: 0.7853 2022/08/30 17:13:08 - mmengine - INFO - Epoch(train) [797][15/63] lr: 2.6239e-03 eta: 8:40:11 time: 1.0273 data_time: 0.0717 memory: 16201 loss_prob: 0.3585 loss_thr: 0.2735 loss_db: 0.0650 loss: 0.6970 2022/08/30 17:13:13 - mmengine - INFO - Epoch(train) [797][20/63] lr: 2.6239e-03 eta: 8:39:57 time: 0.9508 data_time: 0.0774 memory: 16201 loss_prob: 0.3528 loss_thr: 0.2615 loss_db: 0.0637 loss: 0.6780 2022/08/30 17:13:18 - mmengine - INFO - Epoch(train) [797][25/63] lr: 2.6239e-03 eta: 8:39:57 time: 0.9935 data_time: 0.0855 memory: 16201 loss_prob: 0.3593 loss_thr: 0.2539 loss_db: 0.0636 loss: 0.6767 2022/08/30 17:13:23 - mmengine - INFO - Epoch(train) [797][30/63] lr: 2.6239e-03 eta: 8:39:44 time: 1.0296 data_time: 0.0460 memory: 16201 loss_prob: 0.4068 loss_thr: 0.2738 loss_db: 0.0714 loss: 0.7520 2022/08/30 17:13:29 - mmengine - INFO - Epoch(train) [797][35/63] lr: 2.6239e-03 eta: 8:39:44 time: 1.1570 data_time: 0.0883 memory: 16201 loss_prob: 0.4063 loss_thr: 0.2906 loss_db: 0.0712 loss: 0.7680 2022/08/30 17:13:35 - mmengine - INFO - Epoch(train) [797][40/63] lr: 2.6239e-03 eta: 8:39:31 time: 1.1960 data_time: 0.1052 memory: 16201 loss_prob: 0.3824 loss_thr: 0.2882 loss_db: 0.0675 loss: 0.7381 2022/08/30 17:13:41 - mmengine - INFO - Epoch(train) [797][45/63] lr: 2.6239e-03 eta: 8:39:31 time: 1.1255 data_time: 0.0957 memory: 16201 loss_prob: 0.4251 loss_thr: 0.2887 loss_db: 0.0752 loss: 0.7890 2022/08/30 17:13:46 - mmengine - INFO - Epoch(train) [797][50/63] lr: 2.6239e-03 eta: 8:39:18 time: 1.0596 data_time: 0.0870 memory: 16201 loss_prob: 0.4285 loss_thr: 0.2844 loss_db: 0.0744 loss: 0.7873 2022/08/30 17:13:51 - mmengine - INFO - Epoch(train) [797][55/63] lr: 2.6239e-03 eta: 8:39:18 time: 1.0119 data_time: 0.0746 memory: 16201 loss_prob: 0.3733 loss_thr: 0.2709 loss_db: 0.0663 loss: 0.7106 2022/08/30 17:13:55 - mmengine - INFO - Epoch(train) [797][60/63] lr: 2.6239e-03 eta: 8:39:04 time: 0.9309 data_time: 0.0670 memory: 16201 loss_prob: 0.3332 loss_thr: 0.2522 loss_db: 0.0588 loss: 0.6442 2022/08/30 17:13:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:14:05 - mmengine - INFO - Epoch(train) [798][5/63] lr: 2.6180e-03 eta: 8:39:04 time: 1.1900 data_time: 0.2757 memory: 16201 loss_prob: 0.4278 loss_thr: 0.3022 loss_db: 0.0755 loss: 0.8056 2022/08/30 17:14:11 - mmengine - INFO - Epoch(train) [798][10/63] lr: 2.6180e-03 eta: 8:38:47 time: 1.3336 data_time: 0.3195 memory: 16201 loss_prob: 0.4719 loss_thr: 0.3287 loss_db: 0.0826 loss: 0.8831 2022/08/30 17:14:16 - mmengine - INFO - Epoch(train) [798][15/63] lr: 2.6180e-03 eta: 8:38:47 time: 1.0935 data_time: 0.0874 memory: 16201 loss_prob: 0.4579 loss_thr: 0.3164 loss_db: 0.0793 loss: 0.8536 2022/08/30 17:14:22 - mmengine - INFO - Epoch(train) [798][20/63] lr: 2.6180e-03 eta: 8:38:34 time: 1.1269 data_time: 0.0884 memory: 16201 loss_prob: 0.4068 loss_thr: 0.2930 loss_db: 0.0724 loss: 0.7722 2022/08/30 17:14:27 - mmengine - INFO - Epoch(train) [798][25/63] lr: 2.6180e-03 eta: 8:38:34 time: 1.0873 data_time: 0.0803 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2586 loss_db: 0.0627 loss: 0.6710 2022/08/30 17:14:32 - mmengine - INFO - Epoch(train) [798][30/63] lr: 2.6180e-03 eta: 8:38:21 time: 1.0064 data_time: 0.0794 memory: 16201 loss_prob: 0.3548 loss_thr: 0.2612 loss_db: 0.0627 loss: 0.6787 2022/08/30 17:14:37 - mmengine - INFO - Epoch(train) [798][35/63] lr: 2.6180e-03 eta: 8:38:21 time: 0.9812 data_time: 0.0913 memory: 16201 loss_prob: 0.3612 loss_thr: 0.2614 loss_db: 0.0646 loss: 0.6872 2022/08/30 17:14:42 - mmengine - INFO - Epoch(train) [798][40/63] lr: 2.6180e-03 eta: 8:38:07 time: 0.9519 data_time: 0.0571 memory: 16201 loss_prob: 0.3657 loss_thr: 0.2763 loss_db: 0.0662 loss: 0.7082 2022/08/30 17:14:48 - mmengine - INFO - Epoch(train) [798][45/63] lr: 2.6180e-03 eta: 8:38:07 time: 1.0607 data_time: 0.0817 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2938 loss_db: 0.0667 loss: 0.7387 2022/08/30 17:14:54 - mmengine - INFO - Epoch(train) [798][50/63] lr: 2.6180e-03 eta: 8:37:55 time: 1.2244 data_time: 0.0770 memory: 16201 loss_prob: 0.3868 loss_thr: 0.2859 loss_db: 0.0692 loss: 0.7419 2022/08/30 17:15:01 - mmengine - INFO - Epoch(train) [798][55/63] lr: 2.6180e-03 eta: 8:37:55 time: 1.3297 data_time: 0.0744 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2791 loss_db: 0.0713 loss: 0.7458 2022/08/30 17:15:06 - mmengine - INFO - Epoch(train) [798][60/63] lr: 2.6180e-03 eta: 8:37:43 time: 1.2103 data_time: 0.0860 memory: 16201 loss_prob: 0.3735 loss_thr: 0.2759 loss_db: 0.0654 loss: 0.7148 2022/08/30 17:15:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:15:17 - mmengine - INFO - Epoch(train) [799][5/63] lr: 2.6122e-03 eta: 8:37:43 time: 1.3149 data_time: 0.3295 memory: 16201 loss_prob: 0.3843 loss_thr: 0.2673 loss_db: 0.0675 loss: 0.7191 2022/08/30 17:15:22 - mmengine - INFO - Epoch(train) [799][10/63] lr: 2.6122e-03 eta: 8:37:25 time: 1.3242 data_time: 0.3404 memory: 16201 loss_prob: 0.3947 loss_thr: 0.2695 loss_db: 0.0688 loss: 0.7330 2022/08/30 17:15:27 - mmengine - INFO - Epoch(train) [799][15/63] lr: 2.6122e-03 eta: 8:37:25 time: 0.9513 data_time: 0.0791 memory: 16201 loss_prob: 0.4140 loss_thr: 0.2856 loss_db: 0.0729 loss: 0.7725 2022/08/30 17:15:32 - mmengine - INFO - Epoch(train) [799][20/63] lr: 2.6122e-03 eta: 8:37:12 time: 0.9166 data_time: 0.0466 memory: 16201 loss_prob: 0.4126 loss_thr: 0.2885 loss_db: 0.0743 loss: 0.7753 2022/08/30 17:15:37 - mmengine - INFO - Epoch(train) [799][25/63] lr: 2.6122e-03 eta: 8:37:12 time: 0.9745 data_time: 0.0507 memory: 16201 loss_prob: 0.4389 loss_thr: 0.3135 loss_db: 0.0780 loss: 0.8304 2022/08/30 17:15:41 - mmengine - INFO - Epoch(train) [799][30/63] lr: 2.6122e-03 eta: 8:36:58 time: 0.9823 data_time: 0.0312 memory: 16201 loss_prob: 0.4489 loss_thr: 0.3162 loss_db: 0.0783 loss: 0.8435 2022/08/30 17:15:48 - mmengine - INFO - Epoch(train) [799][35/63] lr: 2.6122e-03 eta: 8:36:58 time: 1.1314 data_time: 0.0374 memory: 16201 loss_prob: 0.3935 loss_thr: 0.2814 loss_db: 0.0695 loss: 0.7444 2022/08/30 17:15:53 - mmengine - INFO - Epoch(train) [799][40/63] lr: 2.6122e-03 eta: 8:36:45 time: 1.1626 data_time: 0.0461 memory: 16201 loss_prob: 0.4189 loss_thr: 0.2939 loss_db: 0.0746 loss: 0.7874 2022/08/30 17:16:00 - mmengine - INFO - Epoch(train) [799][45/63] lr: 2.6122e-03 eta: 8:36:45 time: 1.1814 data_time: 0.0445 memory: 16201 loss_prob: 0.3977 loss_thr: 0.2790 loss_db: 0.0714 loss: 0.7481 2022/08/30 17:16:06 - mmengine - INFO - Epoch(train) [799][50/63] lr: 2.6122e-03 eta: 8:36:34 time: 1.3115 data_time: 0.0623 memory: 16201 loss_prob: 0.3492 loss_thr: 0.2564 loss_db: 0.0622 loss: 0.6678 2022/08/30 17:16:12 - mmengine - INFO - Epoch(train) [799][55/63] lr: 2.6122e-03 eta: 8:36:34 time: 1.1865 data_time: 0.0424 memory: 16201 loss_prob: 0.4067 loss_thr: 0.2942 loss_db: 0.0717 loss: 0.7726 2022/08/30 17:16:17 - mmengine - INFO - Epoch(train) [799][60/63] lr: 2.6122e-03 eta: 8:36:21 time: 1.0931 data_time: 0.0348 memory: 16201 loss_prob: 0.4496 loss_thr: 0.2986 loss_db: 0.0779 loss: 0.8261 2022/08/30 17:16:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:16:26 - mmengine - INFO - Epoch(train) [800][5/63] lr: 2.6063e-03 eta: 8:36:21 time: 1.1341 data_time: 0.2422 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2631 loss_db: 0.0668 loss: 0.7037 2022/08/30 17:16:31 - mmengine - INFO - Epoch(train) [800][10/63] lr: 2.6063e-03 eta: 8:36:02 time: 1.1343 data_time: 0.2586 memory: 16201 loss_prob: 0.4005 loss_thr: 0.2762 loss_db: 0.0694 loss: 0.7461 2022/08/30 17:16:35 - mmengine - INFO - Epoch(train) [800][15/63] lr: 2.6063e-03 eta: 8:36:02 time: 0.8982 data_time: 0.0321 memory: 16201 loss_prob: 0.3877 loss_thr: 0.2754 loss_db: 0.0674 loss: 0.7305 2022/08/30 17:16:42 - mmengine - INFO - Epoch(train) [800][20/63] lr: 2.6063e-03 eta: 8:35:50 time: 1.1583 data_time: 0.0345 memory: 16201 loss_prob: 0.3542 loss_thr: 0.2595 loss_db: 0.0639 loss: 0.6776 2022/08/30 17:16:47 - mmengine - INFO - Epoch(train) [800][25/63] lr: 2.6063e-03 eta: 8:35:50 time: 1.2087 data_time: 0.0430 memory: 16201 loss_prob: 0.3633 loss_thr: 0.2649 loss_db: 0.0652 loss: 0.6935 2022/08/30 17:16:51 - mmengine - INFO - Epoch(train) [800][30/63] lr: 2.6063e-03 eta: 8:35:36 time: 0.9117 data_time: 0.0307 memory: 16201 loss_prob: 0.3892 loss_thr: 0.2723 loss_db: 0.0673 loss: 0.7288 2022/08/30 17:16:56 - mmengine - INFO - Epoch(train) [800][35/63] lr: 2.6063e-03 eta: 8:35:36 time: 0.8909 data_time: 0.0363 memory: 16201 loss_prob: 0.4226 loss_thr: 0.2995 loss_db: 0.0739 loss: 0.7960 2022/08/30 17:17:03 - mmengine - INFO - Epoch(train) [800][40/63] lr: 2.6063e-03 eta: 8:35:23 time: 1.1442 data_time: 0.0331 memory: 16201 loss_prob: 0.4163 loss_thr: 0.3088 loss_db: 0.0754 loss: 0.8005 2022/08/30 17:17:08 - mmengine - INFO - Epoch(train) [800][45/63] lr: 2.6063e-03 eta: 8:35:23 time: 1.1874 data_time: 0.0414 memory: 16201 loss_prob: 0.4203 loss_thr: 0.3044 loss_db: 0.0754 loss: 0.8000 2022/08/30 17:17:13 - mmengine - INFO - Epoch(train) [800][50/63] lr: 2.6063e-03 eta: 8:35:10 time: 0.9960 data_time: 0.0523 memory: 16201 loss_prob: 0.4086 loss_thr: 0.2943 loss_db: 0.0716 loss: 0.7745 2022/08/30 17:17:17 - mmengine - INFO - Epoch(train) [800][55/63] lr: 2.6063e-03 eta: 8:35:10 time: 0.9306 data_time: 0.0298 memory: 16201 loss_prob: 0.4234 loss_thr: 0.2983 loss_db: 0.0730 loss: 0.7947 2022/08/30 17:17:22 - mmengine - INFO - Epoch(train) [800][60/63] lr: 2.6063e-03 eta: 8:34:56 time: 0.9131 data_time: 0.0260 memory: 16201 loss_prob: 0.4254 loss_thr: 0.2991 loss_db: 0.0749 loss: 0.7994 2022/08/30 17:17:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:17:24 - mmengine - INFO - Saving checkpoint at 800 epochs 2022/08/30 17:17:33 - mmengine - INFO - Epoch(val) [800][5/32] eta: 8:34:56 time: 0.7164 data_time: 0.1378 memory: 16201 2022/08/30 17:17:37 - mmengine - INFO - Epoch(val) [800][10/32] eta: 0:00:18 time: 0.8596 data_time: 0.2202 memory: 15734 2022/08/30 17:17:40 - mmengine - INFO - Epoch(val) [800][15/32] eta: 0:00:18 time: 0.7124 data_time: 0.1047 memory: 15734 2022/08/30 17:17:44 - mmengine - INFO - Epoch(val) [800][20/32] eta: 0:00:08 time: 0.7097 data_time: 0.0753 memory: 15734 2022/08/30 17:17:48 - mmengine - INFO - Epoch(val) [800][25/32] eta: 0:00:08 time: 0.7530 data_time: 0.0981 memory: 15734 2022/08/30 17:17:51 - mmengine - INFO - Epoch(val) [800][30/32] eta: 0:00:01 time: 0.6898 data_time: 0.0494 memory: 15734 2022/08/30 17:17:52 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 17:17:52 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8493, precision: 0.7946, hmean: 0.8210 2022/08/30 17:17:52 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8493, precision: 0.8329, hmean: 0.8410 2022/08/30 17:17:52 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8479, precision: 0.8557, hmean: 0.8518 2022/08/30 17:17:52 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8421, precision: 0.8719, hmean: 0.8567 2022/08/30 17:17:52 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8344, precision: 0.8878, hmean: 0.8603 2022/08/30 17:17:52 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8012, precision: 0.9143, hmean: 0.8540 2022/08/30 17:17:52 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.3399, precision: 0.9553, hmean: 0.5014 2022/08/30 17:17:52 - mmengine - INFO - Epoch(val) [800][32/32] icdar/precision: 0.8878 icdar/recall: 0.8344 icdar/hmean: 0.8603 2022/08/30 17:17:59 - mmengine - INFO - Epoch(train) [801][5/63] lr: 2.6004e-03 eta: 0:00:01 time: 1.0588 data_time: 0.2348 memory: 16201 loss_prob: 0.3628 loss_thr: 0.2727 loss_db: 0.0647 loss: 0.7002 2022/08/30 17:18:03 - mmengine - INFO - Epoch(train) [801][10/63] lr: 2.6004e-03 eta: 8:34:38 time: 1.0951 data_time: 0.2383 memory: 16201 loss_prob: 0.3791 loss_thr: 0.2689 loss_db: 0.0671 loss: 0.7151 2022/08/30 17:18:07 - mmengine - INFO - Epoch(train) [801][15/63] lr: 2.6004e-03 eta: 8:34:38 time: 0.8768 data_time: 0.0365 memory: 16201 loss_prob: 0.3932 loss_thr: 0.2644 loss_db: 0.0707 loss: 0.7283 2022/08/30 17:18:13 - mmengine - INFO - Epoch(train) [801][20/63] lr: 2.6004e-03 eta: 8:34:24 time: 0.9932 data_time: 0.0357 memory: 16201 loss_prob: 0.3975 loss_thr: 0.2731 loss_db: 0.0712 loss: 0.7417 2022/08/30 17:18:18 - mmengine - INFO - Epoch(train) [801][25/63] lr: 2.6004e-03 eta: 8:34:24 time: 1.0521 data_time: 0.0310 memory: 16201 loss_prob: 0.4067 loss_thr: 0.2799 loss_db: 0.0718 loss: 0.7585 2022/08/30 17:18:23 - mmengine - INFO - Epoch(train) [801][30/63] lr: 2.6004e-03 eta: 8:34:11 time: 1.0075 data_time: 0.0349 memory: 16201 loss_prob: 0.3829 loss_thr: 0.2725 loss_db: 0.0677 loss: 0.7230 2022/08/30 17:18:28 - mmengine - INFO - Epoch(train) [801][35/63] lr: 2.6004e-03 eta: 8:34:11 time: 1.0412 data_time: 0.0421 memory: 16201 loss_prob: 0.3799 loss_thr: 0.2735 loss_db: 0.0683 loss: 0.7217 2022/08/30 17:18:35 - mmengine - INFO - Epoch(train) [801][40/63] lr: 2.6004e-03 eta: 8:33:58 time: 1.1559 data_time: 0.0307 memory: 16201 loss_prob: 0.3818 loss_thr: 0.2702 loss_db: 0.0690 loss: 0.7209 2022/08/30 17:18:39 - mmengine - INFO - Epoch(train) [801][45/63] lr: 2.6004e-03 eta: 8:33:58 time: 1.1230 data_time: 0.0345 memory: 16201 loss_prob: 0.3883 loss_thr: 0.2684 loss_db: 0.0680 loss: 0.7247 2022/08/30 17:18:44 - mmengine - INFO - Epoch(train) [801][50/63] lr: 2.6004e-03 eta: 8:33:45 time: 0.9758 data_time: 0.0359 memory: 16201 loss_prob: 0.4045 loss_thr: 0.2814 loss_db: 0.0721 loss: 0.7580 2022/08/30 17:18:50 - mmengine - INFO - Epoch(train) [801][55/63] lr: 2.6004e-03 eta: 8:33:45 time: 1.0957 data_time: 0.0376 memory: 16201 loss_prob: 0.4097 loss_thr: 0.2843 loss_db: 0.0727 loss: 0.7667 2022/08/30 17:18:56 - mmengine - INFO - Epoch(train) [801][60/63] lr: 2.6004e-03 eta: 8:33:32 time: 1.2111 data_time: 0.0481 memory: 16201 loss_prob: 0.4220 loss_thr: 0.2914 loss_db: 0.0722 loss: 0.7855 2022/08/30 17:18:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:19:06 - mmengine - INFO - Epoch(train) [802][5/63] lr: 2.5946e-03 eta: 8:33:32 time: 1.1937 data_time: 0.2573 memory: 16201 loss_prob: 0.4283 loss_thr: 0.2970 loss_db: 0.0748 loss: 0.8001 2022/08/30 17:19:11 - mmengine - INFO - Epoch(train) [802][10/63] lr: 2.5946e-03 eta: 8:33:14 time: 1.1828 data_time: 0.2719 memory: 16201 loss_prob: 0.4195 loss_thr: 0.2959 loss_db: 0.0751 loss: 0.7906 2022/08/30 17:19:15 - mmengine - INFO - Epoch(train) [802][15/63] lr: 2.5946e-03 eta: 8:33:14 time: 0.9437 data_time: 0.0318 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2740 loss_db: 0.0678 loss: 0.7176 2022/08/30 17:19:20 - mmengine - INFO - Epoch(train) [802][20/63] lr: 2.5946e-03 eta: 8:33:01 time: 0.9037 data_time: 0.0301 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2602 loss_db: 0.0651 loss: 0.6792 2022/08/30 17:19:24 - mmengine - INFO - Epoch(train) [802][25/63] lr: 2.5946e-03 eta: 8:33:01 time: 0.8731 data_time: 0.0386 memory: 16201 loss_prob: 0.3445 loss_thr: 0.2521 loss_db: 0.0630 loss: 0.6596 2022/08/30 17:19:29 - mmengine - INFO - Epoch(train) [802][30/63] lr: 2.5946e-03 eta: 8:32:47 time: 0.9082 data_time: 0.0287 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2538 loss_db: 0.0619 loss: 0.6594 2022/08/30 17:19:35 - mmengine - INFO - Epoch(train) [802][35/63] lr: 2.5946e-03 eta: 8:32:47 time: 1.1105 data_time: 0.0356 memory: 16201 loss_prob: 0.3754 loss_thr: 0.2747 loss_db: 0.0672 loss: 0.7173 2022/08/30 17:19:40 - mmengine - INFO - Epoch(train) [802][40/63] lr: 2.5946e-03 eta: 8:32:34 time: 1.1479 data_time: 0.0334 memory: 16201 loss_prob: 0.3859 loss_thr: 0.2866 loss_db: 0.0677 loss: 0.7402 2022/08/30 17:19:45 - mmengine - INFO - Epoch(train) [802][45/63] lr: 2.5946e-03 eta: 8:32:34 time: 0.9987 data_time: 0.0296 memory: 16201 loss_prob: 0.3980 loss_thr: 0.2889 loss_db: 0.0703 loss: 0.7572 2022/08/30 17:19:50 - mmengine - INFO - Epoch(train) [802][50/63] lr: 2.5946e-03 eta: 8:32:21 time: 0.9959 data_time: 0.0419 memory: 16201 loss_prob: 0.4251 loss_thr: 0.3028 loss_db: 0.0760 loss: 0.8039 2022/08/30 17:19:56 - mmengine - INFO - Epoch(train) [802][55/63] lr: 2.5946e-03 eta: 8:32:21 time: 1.0693 data_time: 0.0349 memory: 16201 loss_prob: 0.4024 loss_thr: 0.2936 loss_db: 0.0707 loss: 0.7667 2022/08/30 17:20:01 - mmengine - INFO - Epoch(train) [802][60/63] lr: 2.5946e-03 eta: 8:32:08 time: 1.0399 data_time: 0.0345 memory: 16201 loss_prob: 0.3581 loss_thr: 0.2673 loss_db: 0.0639 loss: 0.6893 2022/08/30 17:20:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:20:11 - mmengine - INFO - Epoch(train) [803][5/63] lr: 2.5887e-03 eta: 8:32:08 time: 1.1705 data_time: 0.2797 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2774 loss_db: 0.0678 loss: 0.7256 2022/08/30 17:20:17 - mmengine - INFO - Epoch(train) [803][10/63] lr: 2.5887e-03 eta: 8:31:51 time: 1.4041 data_time: 0.2846 memory: 16201 loss_prob: 0.4052 loss_thr: 0.2825 loss_db: 0.0720 loss: 0.7597 2022/08/30 17:20:23 - mmengine - INFO - Epoch(train) [803][15/63] lr: 2.5887e-03 eta: 8:31:51 time: 1.2598 data_time: 0.0364 memory: 16201 loss_prob: 0.3914 loss_thr: 0.2738 loss_db: 0.0704 loss: 0.7357 2022/08/30 17:20:29 - mmengine - INFO - Epoch(train) [803][20/63] lr: 2.5887e-03 eta: 8:31:38 time: 1.1431 data_time: 0.0357 memory: 16201 loss_prob: 0.3830 loss_thr: 0.2735 loss_db: 0.0687 loss: 0.7252 2022/08/30 17:20:33 - mmengine - INFO - Epoch(train) [803][25/63] lr: 2.5887e-03 eta: 8:31:38 time: 0.9963 data_time: 0.0546 memory: 16201 loss_prob: 0.3725 loss_thr: 0.2708 loss_db: 0.0670 loss: 0.7102 2022/08/30 17:20:38 - mmengine - INFO - Epoch(train) [803][30/63] lr: 2.5887e-03 eta: 8:31:24 time: 0.9039 data_time: 0.0442 memory: 16201 loss_prob: 0.3652 loss_thr: 0.2749 loss_db: 0.0650 loss: 0.7051 2022/08/30 17:20:43 - mmengine - INFO - Epoch(train) [803][35/63] lr: 2.5887e-03 eta: 8:31:24 time: 0.9415 data_time: 0.0227 memory: 16201 loss_prob: 0.3800 loss_thr: 0.2841 loss_db: 0.0671 loss: 0.7312 2022/08/30 17:20:48 - mmengine - INFO - Epoch(train) [803][40/63] lr: 2.5887e-03 eta: 8:31:11 time: 1.0746 data_time: 0.0395 memory: 16201 loss_prob: 0.3786 loss_thr: 0.2844 loss_db: 0.0674 loss: 0.7304 2022/08/30 17:20:54 - mmengine - INFO - Epoch(train) [803][45/63] lr: 2.5887e-03 eta: 8:31:11 time: 1.1146 data_time: 0.0452 memory: 16201 loss_prob: 0.3693 loss_thr: 0.2809 loss_db: 0.0652 loss: 0.7154 2022/08/30 17:20:58 - mmengine - INFO - Epoch(train) [803][50/63] lr: 2.5887e-03 eta: 8:30:58 time: 0.9902 data_time: 0.0385 memory: 16201 loss_prob: 0.3985 loss_thr: 0.2862 loss_db: 0.0697 loss: 0.7544 2022/08/30 17:21:03 - mmengine - INFO - Epoch(train) [803][55/63] lr: 2.5887e-03 eta: 8:30:58 time: 0.9168 data_time: 0.0358 memory: 16201 loss_prob: 0.4008 loss_thr: 0.2713 loss_db: 0.0681 loss: 0.7402 2022/08/30 17:21:08 - mmengine - INFO - Epoch(train) [803][60/63] lr: 2.5887e-03 eta: 8:30:44 time: 0.9798 data_time: 0.0379 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2582 loss_db: 0.0647 loss: 0.7082 2022/08/30 17:21:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:21:18 - mmengine - INFO - Epoch(train) [804][5/63] lr: 2.5828e-03 eta: 8:30:44 time: 1.1705 data_time: 0.2288 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2863 loss_db: 0.0712 loss: 0.7611 2022/08/30 17:21:23 - mmengine - INFO - Epoch(train) [804][10/63] lr: 2.5828e-03 eta: 8:30:26 time: 1.1466 data_time: 0.2235 memory: 16201 loss_prob: 0.3909 loss_thr: 0.2764 loss_db: 0.0698 loss: 0.7371 2022/08/30 17:21:28 - mmengine - INFO - Epoch(train) [804][15/63] lr: 2.5828e-03 eta: 8:30:26 time: 0.9897 data_time: 0.0333 memory: 16201 loss_prob: 0.3688 loss_thr: 0.2608 loss_db: 0.0638 loss: 0.6934 2022/08/30 17:21:34 - mmengine - INFO - Epoch(train) [804][20/63] lr: 2.5828e-03 eta: 8:30:13 time: 1.1293 data_time: 0.0531 memory: 16201 loss_prob: 0.3611 loss_thr: 0.2606 loss_db: 0.0624 loss: 0.6840 2022/08/30 17:21:41 - mmengine - INFO - Epoch(train) [804][25/63] lr: 2.5828e-03 eta: 8:30:13 time: 1.2885 data_time: 0.0504 memory: 16201 loss_prob: 0.3605 loss_thr: 0.2632 loss_db: 0.0641 loss: 0.6879 2022/08/30 17:21:47 - mmengine - INFO - Epoch(train) [804][30/63] lr: 2.5828e-03 eta: 8:30:02 time: 1.2785 data_time: 0.0403 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2664 loss_db: 0.0684 loss: 0.7152 2022/08/30 17:21:53 - mmengine - INFO - Epoch(train) [804][35/63] lr: 2.5828e-03 eta: 8:30:02 time: 1.2631 data_time: 0.0561 memory: 16201 loss_prob: 0.4088 loss_thr: 0.2732 loss_db: 0.0735 loss: 0.7555 2022/08/30 17:21:59 - mmengine - INFO - Epoch(train) [804][40/63] lr: 2.5828e-03 eta: 8:29:49 time: 1.2652 data_time: 0.0469 memory: 16201 loss_prob: 0.4025 loss_thr: 0.2835 loss_db: 0.0706 loss: 0.7565 2022/08/30 17:22:04 - mmengine - INFO - Epoch(train) [804][45/63] lr: 2.5828e-03 eta: 8:29:49 time: 1.0726 data_time: 0.0361 memory: 16201 loss_prob: 0.3940 loss_thr: 0.2912 loss_db: 0.0684 loss: 0.7535 2022/08/30 17:22:09 - mmengine - INFO - Epoch(train) [804][50/63] lr: 2.5828e-03 eta: 8:29:36 time: 0.9277 data_time: 0.0390 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2851 loss_db: 0.0701 loss: 0.7396 2022/08/30 17:22:13 - mmengine - INFO - Epoch(train) [804][55/63] lr: 2.5828e-03 eta: 8:29:36 time: 0.9191 data_time: 0.0340 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2642 loss_db: 0.0666 loss: 0.6950 2022/08/30 17:22:18 - mmengine - INFO - Epoch(train) [804][60/63] lr: 2.5828e-03 eta: 8:29:22 time: 0.8917 data_time: 0.0382 memory: 16201 loss_prob: 0.4124 loss_thr: 0.2901 loss_db: 0.0723 loss: 0.7748 2022/08/30 17:22:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:22:27 - mmengine - INFO - Epoch(train) [805][5/63] lr: 2.5770e-03 eta: 8:29:22 time: 1.1128 data_time: 0.2388 memory: 16201 loss_prob: 0.3987 loss_thr: 0.2954 loss_db: 0.0720 loss: 0.7661 2022/08/30 17:22:34 - mmengine - INFO - Epoch(train) [805][10/63] lr: 2.5770e-03 eta: 8:29:05 time: 1.3864 data_time: 0.2592 memory: 16201 loss_prob: 0.4035 loss_thr: 0.2919 loss_db: 0.0727 loss: 0.7682 2022/08/30 17:22:40 - mmengine - INFO - Epoch(train) [805][15/63] lr: 2.5770e-03 eta: 8:29:05 time: 1.2987 data_time: 0.0376 memory: 16201 loss_prob: 0.3881 loss_thr: 0.2867 loss_db: 0.0684 loss: 0.7433 2022/08/30 17:22:45 - mmengine - INFO - Epoch(train) [805][20/63] lr: 2.5770e-03 eta: 8:28:52 time: 1.1672 data_time: 0.0354 memory: 16201 loss_prob: 0.3589 loss_thr: 0.2665 loss_db: 0.0633 loss: 0.6887 2022/08/30 17:22:51 - mmengine - INFO - Epoch(train) [805][25/63] lr: 2.5770e-03 eta: 8:28:52 time: 1.0932 data_time: 0.0511 memory: 16201 loss_prob: 0.3769 loss_thr: 0.2729 loss_db: 0.0668 loss: 0.7166 2022/08/30 17:22:57 - mmengine - INFO - Epoch(train) [805][30/63] lr: 2.5770e-03 eta: 8:28:40 time: 1.1440 data_time: 0.0347 memory: 16201 loss_prob: 0.4033 loss_thr: 0.2885 loss_db: 0.0704 loss: 0.7621 2022/08/30 17:23:02 - mmengine - INFO - Epoch(train) [805][35/63] lr: 2.5770e-03 eta: 8:28:40 time: 1.1216 data_time: 0.0309 memory: 16201 loss_prob: 0.4114 loss_thr: 0.2961 loss_db: 0.0723 loss: 0.7799 2022/08/30 17:23:07 - mmengine - INFO - Epoch(train) [805][40/63] lr: 2.5770e-03 eta: 8:28:27 time: 1.0674 data_time: 0.0339 memory: 16201 loss_prob: 0.4448 loss_thr: 0.3208 loss_db: 0.0794 loss: 0.8451 2022/08/30 17:23:13 - mmengine - INFO - Epoch(train) [805][45/63] lr: 2.5770e-03 eta: 8:28:27 time: 1.1016 data_time: 0.0368 memory: 16201 loss_prob: 0.4157 loss_thr: 0.2977 loss_db: 0.0741 loss: 0.7875 2022/08/30 17:23:18 - mmengine - INFO - Epoch(train) [805][50/63] lr: 2.5770e-03 eta: 8:28:14 time: 1.0435 data_time: 0.0480 memory: 16201 loss_prob: 0.3875 loss_thr: 0.2665 loss_db: 0.0690 loss: 0.7230 2022/08/30 17:23:22 - mmengine - INFO - Epoch(train) [805][55/63] lr: 2.5770e-03 eta: 8:28:14 time: 0.8846 data_time: 0.0332 memory: 16201 loss_prob: 0.4294 loss_thr: 0.2837 loss_db: 0.0755 loss: 0.7886 2022/08/30 17:23:26 - mmengine - INFO - Epoch(train) [805][60/63] lr: 2.5770e-03 eta: 8:28:00 time: 0.8626 data_time: 0.0248 memory: 16201 loss_prob: 0.4033 loss_thr: 0.2830 loss_db: 0.0699 loss: 0.7562 2022/08/30 17:23:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:23:36 - mmengine - INFO - Epoch(train) [806][5/63] lr: 2.5711e-03 eta: 8:28:00 time: 1.1449 data_time: 0.2462 memory: 16201 loss_prob: 0.3904 loss_thr: 0.2843 loss_db: 0.0705 loss: 0.7452 2022/08/30 17:23:43 - mmengine - INFO - Epoch(train) [806][10/63] lr: 2.5711e-03 eta: 8:27:43 time: 1.3922 data_time: 0.2471 memory: 16201 loss_prob: 0.3751 loss_thr: 0.2757 loss_db: 0.0674 loss: 0.7182 2022/08/30 17:23:47 - mmengine - INFO - Epoch(train) [806][15/63] lr: 2.5711e-03 eta: 8:27:43 time: 1.1350 data_time: 0.0427 memory: 16201 loss_prob: 0.3610 loss_thr: 0.2557 loss_db: 0.0640 loss: 0.6807 2022/08/30 17:23:52 - mmengine - INFO - Epoch(train) [806][20/63] lr: 2.5711e-03 eta: 8:27:29 time: 0.9105 data_time: 0.0453 memory: 16201 loss_prob: 0.4074 loss_thr: 0.2786 loss_db: 0.0707 loss: 0.7566 2022/08/30 17:23:57 - mmengine - INFO - Epoch(train) [806][25/63] lr: 2.5711e-03 eta: 8:27:29 time: 0.9812 data_time: 0.0301 memory: 16201 loss_prob: 0.4230 loss_thr: 0.3013 loss_db: 0.0753 loss: 0.7995 2022/08/30 17:24:04 - mmengine - INFO - Epoch(train) [806][30/63] lr: 2.5711e-03 eta: 8:27:17 time: 1.2636 data_time: 0.0366 memory: 16201 loss_prob: 0.3665 loss_thr: 0.2792 loss_db: 0.0666 loss: 0.7123 2022/08/30 17:24:10 - mmengine - INFO - Epoch(train) [806][35/63] lr: 2.5711e-03 eta: 8:27:17 time: 1.3220 data_time: 0.0549 memory: 16201 loss_prob: 0.3483 loss_thr: 0.2769 loss_db: 0.0620 loss: 0.6872 2022/08/30 17:24:15 - mmengine - INFO - Epoch(train) [806][40/63] lr: 2.5711e-03 eta: 8:27:04 time: 1.0319 data_time: 0.0391 memory: 16201 loss_prob: 0.4001 loss_thr: 0.2929 loss_db: 0.0697 loss: 0.7628 2022/08/30 17:24:19 - mmengine - INFO - Epoch(train) [806][45/63] lr: 2.5711e-03 eta: 8:27:04 time: 0.8948 data_time: 0.0307 memory: 16201 loss_prob: 0.3833 loss_thr: 0.2679 loss_db: 0.0676 loss: 0.7188 2022/08/30 17:24:25 - mmengine - INFO - Epoch(train) [806][50/63] lr: 2.5711e-03 eta: 8:26:50 time: 0.9868 data_time: 0.0347 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2501 loss_db: 0.0621 loss: 0.6581 2022/08/30 17:24:30 - mmengine - INFO - Epoch(train) [806][55/63] lr: 2.5711e-03 eta: 8:26:50 time: 1.0809 data_time: 0.0325 memory: 16201 loss_prob: 0.3616 loss_thr: 0.2611 loss_db: 0.0644 loss: 0.6870 2022/08/30 17:24:36 - mmengine - INFO - Epoch(train) [806][60/63] lr: 2.5711e-03 eta: 8:26:38 time: 1.1835 data_time: 0.0534 memory: 16201 loss_prob: 0.3667 loss_thr: 0.2693 loss_db: 0.0655 loss: 0.7015 2022/08/30 17:24:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:24:47 - mmengine - INFO - Epoch(train) [807][5/63] lr: 2.5652e-03 eta: 8:26:38 time: 1.2696 data_time: 0.2709 memory: 16201 loss_prob: 0.3788 loss_thr: 0.2827 loss_db: 0.0674 loss: 0.7289 2022/08/30 17:24:52 - mmengine - INFO - Epoch(train) [807][10/63] lr: 2.5652e-03 eta: 8:26:20 time: 1.2114 data_time: 0.2864 memory: 16201 loss_prob: 0.3649 loss_thr: 0.2701 loss_db: 0.0642 loss: 0.6992 2022/08/30 17:24:58 - mmengine - INFO - Epoch(train) [807][15/63] lr: 2.5652e-03 eta: 8:26:20 time: 1.1013 data_time: 0.0574 memory: 16201 loss_prob: 0.3392 loss_thr: 0.2569 loss_db: 0.0588 loss: 0.6548 2022/08/30 17:25:04 - mmengine - INFO - Epoch(train) [807][20/63] lr: 2.5652e-03 eta: 8:26:08 time: 1.1753 data_time: 0.0524 memory: 16201 loss_prob: 0.3983 loss_thr: 0.2921 loss_db: 0.0699 loss: 0.7603 2022/08/30 17:25:09 - mmengine - INFO - Epoch(train) [807][25/63] lr: 2.5652e-03 eta: 8:26:08 time: 1.0953 data_time: 0.0511 memory: 16201 loss_prob: 0.4438 loss_thr: 0.3149 loss_db: 0.0783 loss: 0.8369 2022/08/30 17:25:14 - mmengine - INFO - Epoch(train) [807][30/63] lr: 2.5652e-03 eta: 8:25:54 time: 1.0532 data_time: 0.0321 memory: 16201 loss_prob: 0.4071 loss_thr: 0.2877 loss_db: 0.0704 loss: 0.7652 2022/08/30 17:25:20 - mmengine - INFO - Epoch(train) [807][35/63] lr: 2.5652e-03 eta: 8:25:54 time: 1.1105 data_time: 0.0420 memory: 16201 loss_prob: 0.3774 loss_thr: 0.2671 loss_db: 0.0660 loss: 0.7106 2022/08/30 17:25:27 - mmengine - INFO - Epoch(train) [807][40/63] lr: 2.5652e-03 eta: 8:25:43 time: 1.2931 data_time: 0.0453 memory: 16201 loss_prob: 0.3950 loss_thr: 0.2810 loss_db: 0.0697 loss: 0.7457 2022/08/30 17:25:33 - mmengine - INFO - Epoch(train) [807][45/63] lr: 2.5652e-03 eta: 8:25:43 time: 1.3549 data_time: 0.0394 memory: 16201 loss_prob: 0.3871 loss_thr: 0.2769 loss_db: 0.0678 loss: 0.7318 2022/08/30 17:25:38 - mmengine - INFO - Epoch(train) [807][50/63] lr: 2.5652e-03 eta: 8:25:30 time: 1.1271 data_time: 0.0461 memory: 16201 loss_prob: 0.3671 loss_thr: 0.2640 loss_db: 0.0641 loss: 0.6952 2022/08/30 17:25:43 - mmengine - INFO - Epoch(train) [807][55/63] lr: 2.5652e-03 eta: 8:25:30 time: 0.9563 data_time: 0.0325 memory: 16201 loss_prob: 0.3694 loss_thr: 0.2668 loss_db: 0.0654 loss: 0.7016 2022/08/30 17:25:48 - mmengine - INFO - Epoch(train) [807][60/63] lr: 2.5652e-03 eta: 8:25:16 time: 0.9218 data_time: 0.0292 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2651 loss_db: 0.0674 loss: 0.7129 2022/08/30 17:25:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:25:57 - mmengine - INFO - Epoch(train) [808][5/63] lr: 2.5593e-03 eta: 8:25:16 time: 1.0751 data_time: 0.2328 memory: 16201 loss_prob: 0.3919 loss_thr: 0.2799 loss_db: 0.0684 loss: 0.7402 2022/08/30 17:26:01 - mmengine - INFO - Epoch(train) [808][10/63] lr: 2.5593e-03 eta: 8:24:58 time: 1.1183 data_time: 0.2388 memory: 16201 loss_prob: 0.3613 loss_thr: 0.2717 loss_db: 0.0654 loss: 0.6984 2022/08/30 17:26:06 - mmengine - INFO - Epoch(train) [808][15/63] lr: 2.5593e-03 eta: 8:24:58 time: 0.9691 data_time: 0.0312 memory: 16201 loss_prob: 0.3663 loss_thr: 0.2692 loss_db: 0.0659 loss: 0.7013 2022/08/30 17:26:11 - mmengine - INFO - Epoch(train) [808][20/63] lr: 2.5593e-03 eta: 8:24:45 time: 1.0504 data_time: 0.0348 memory: 16201 loss_prob: 0.3731 loss_thr: 0.2711 loss_db: 0.0649 loss: 0.7091 2022/08/30 17:26:17 - mmengine - INFO - Epoch(train) [808][25/63] lr: 2.5593e-03 eta: 8:24:45 time: 1.1148 data_time: 0.0498 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2667 loss_db: 0.0640 loss: 0.6894 2022/08/30 17:26:23 - mmengine - INFO - Epoch(train) [808][30/63] lr: 2.5593e-03 eta: 8:24:32 time: 1.1537 data_time: 0.0395 memory: 16201 loss_prob: 0.3900 loss_thr: 0.2805 loss_db: 0.0699 loss: 0.7405 2022/08/30 17:26:27 - mmengine - INFO - Epoch(train) [808][35/63] lr: 2.5593e-03 eta: 8:24:32 time: 1.0055 data_time: 0.0360 memory: 16201 loss_prob: 0.4439 loss_thr: 0.3140 loss_db: 0.0780 loss: 0.8360 2022/08/30 17:26:32 - mmengine - INFO - Epoch(train) [808][40/63] lr: 2.5593e-03 eta: 8:24:18 time: 0.8986 data_time: 0.0321 memory: 16201 loss_prob: 0.4410 loss_thr: 0.3108 loss_db: 0.0786 loss: 0.8304 2022/08/30 17:26:37 - mmengine - INFO - Epoch(train) [808][45/63] lr: 2.5593e-03 eta: 8:24:18 time: 0.9729 data_time: 0.0302 memory: 16201 loss_prob: 0.4070 loss_thr: 0.2906 loss_db: 0.0730 loss: 0.7707 2022/08/30 17:26:43 - mmengine - INFO - Epoch(train) [808][50/63] lr: 2.5593e-03 eta: 8:24:06 time: 1.0971 data_time: 0.0492 memory: 16201 loss_prob: 0.3747 loss_thr: 0.2702 loss_db: 0.0673 loss: 0.7123 2022/08/30 17:26:49 - mmengine - INFO - Epoch(train) [808][55/63] lr: 2.5593e-03 eta: 8:24:06 time: 1.1366 data_time: 0.0397 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2711 loss_db: 0.0689 loss: 0.7204 2022/08/30 17:26:54 - mmengine - INFO - Epoch(train) [808][60/63] lr: 2.5593e-03 eta: 8:23:53 time: 1.1214 data_time: 0.0406 memory: 16201 loss_prob: 0.4145 loss_thr: 0.2980 loss_db: 0.0742 loss: 0.7867 2022/08/30 17:26:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:27:05 - mmengine - INFO - Epoch(train) [809][5/63] lr: 2.5535e-03 eta: 8:23:53 time: 1.2205 data_time: 0.2556 memory: 16201 loss_prob: 0.4251 loss_thr: 0.2985 loss_db: 0.0771 loss: 0.8007 2022/08/30 17:27:09 - mmengine - INFO - Epoch(train) [809][10/63] lr: 2.5535e-03 eta: 8:23:35 time: 1.1858 data_time: 0.2702 memory: 16201 loss_prob: 0.4155 loss_thr: 0.3008 loss_db: 0.0719 loss: 0.7882 2022/08/30 17:27:13 - mmengine - INFO - Epoch(train) [809][15/63] lr: 2.5535e-03 eta: 8:23:35 time: 0.8681 data_time: 0.0277 memory: 16201 loss_prob: 0.3928 loss_thr: 0.2821 loss_db: 0.0665 loss: 0.7413 2022/08/30 17:27:17 - mmengine - INFO - Epoch(train) [809][20/63] lr: 2.5535e-03 eta: 8:23:21 time: 0.8442 data_time: 0.0299 memory: 16201 loss_prob: 0.4014 loss_thr: 0.2856 loss_db: 0.0698 loss: 0.7568 2022/08/30 17:27:23 - mmengine - INFO - Epoch(train) [809][25/63] lr: 2.5535e-03 eta: 8:23:21 time: 0.9565 data_time: 0.0419 memory: 16201 loss_prob: 0.4175 loss_thr: 0.2906 loss_db: 0.0758 loss: 0.7839 2022/08/30 17:27:28 - mmengine - INFO - Epoch(train) [809][30/63] lr: 2.5535e-03 eta: 8:23:08 time: 1.0819 data_time: 0.0320 memory: 16201 loss_prob: 0.3823 loss_thr: 0.2764 loss_db: 0.0689 loss: 0.7276 2022/08/30 17:27:33 - mmengine - INFO - Epoch(train) [809][35/63] lr: 2.5535e-03 eta: 8:23:08 time: 1.0178 data_time: 0.0298 memory: 16201 loss_prob: 0.3722 loss_thr: 0.2744 loss_db: 0.0650 loss: 0.7117 2022/08/30 17:27:38 - mmengine - INFO - Epoch(train) [809][40/63] lr: 2.5535e-03 eta: 8:22:55 time: 1.0201 data_time: 0.0322 memory: 16201 loss_prob: 0.4342 loss_thr: 0.3075 loss_db: 0.0771 loss: 0.8187 2022/08/30 17:27:44 - mmengine - INFO - Epoch(train) [809][45/63] lr: 2.5535e-03 eta: 8:22:55 time: 1.1253 data_time: 0.0434 memory: 16201 loss_prob: 0.4457 loss_thr: 0.3081 loss_db: 0.0778 loss: 0.8316 2022/08/30 17:27:49 - mmengine - INFO - Epoch(train) [809][50/63] lr: 2.5535e-03 eta: 8:22:42 time: 1.0964 data_time: 0.0493 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2606 loss_db: 0.0624 loss: 0.6853 2022/08/30 17:27:55 - mmengine - INFO - Epoch(train) [809][55/63] lr: 2.5535e-03 eta: 8:22:42 time: 1.0760 data_time: 0.0367 memory: 16201 loss_prob: 0.3660 loss_thr: 0.2565 loss_db: 0.0651 loss: 0.6876 2022/08/30 17:27:59 - mmengine - INFO - Epoch(train) [809][60/63] lr: 2.5535e-03 eta: 8:22:28 time: 0.9700 data_time: 0.0334 memory: 16201 loss_prob: 0.4099 loss_thr: 0.2694 loss_db: 0.0689 loss: 0.7482 2022/08/30 17:28:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:28:09 - mmengine - INFO - Epoch(train) [810][5/63] lr: 2.5476e-03 eta: 8:22:28 time: 1.1393 data_time: 0.2656 memory: 16201 loss_prob: 0.4724 loss_thr: 0.2905 loss_db: 0.0787 loss: 0.8416 2022/08/30 17:28:14 - mmengine - INFO - Epoch(train) [810][10/63] lr: 2.5476e-03 eta: 8:22:11 time: 1.3113 data_time: 0.2873 memory: 16201 loss_prob: 0.3761 loss_thr: 0.2511 loss_db: 0.0665 loss: 0.6937 2022/08/30 17:28:20 - mmengine - INFO - Epoch(train) [810][15/63] lr: 2.5476e-03 eta: 8:22:11 time: 1.1000 data_time: 0.0468 memory: 16201 loss_prob: 0.3887 loss_thr: 0.2636 loss_db: 0.0672 loss: 0.7195 2022/08/30 17:28:24 - mmengine - INFO - Epoch(train) [810][20/63] lr: 2.5476e-03 eta: 8:21:58 time: 0.9820 data_time: 0.0378 memory: 16201 loss_prob: 0.3803 loss_thr: 0.2705 loss_db: 0.0681 loss: 0.7189 2022/08/30 17:28:29 - mmengine - INFO - Epoch(train) [810][25/63] lr: 2.5476e-03 eta: 8:21:58 time: 0.9202 data_time: 0.0443 memory: 16201 loss_prob: 0.3628 loss_thr: 0.2686 loss_db: 0.0659 loss: 0.6973 2022/08/30 17:28:34 - mmengine - INFO - Epoch(train) [810][30/63] lr: 2.5476e-03 eta: 8:21:44 time: 0.9486 data_time: 0.0231 memory: 16201 loss_prob: 0.4019 loss_thr: 0.2880 loss_db: 0.0703 loss: 0.7603 2022/08/30 17:28:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:28:39 - mmengine - INFO - Epoch(train) [810][35/63] lr: 2.5476e-03 eta: 8:21:44 time: 1.0127 data_time: 0.0318 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2702 loss_db: 0.0675 loss: 0.7235 2022/08/30 17:28:44 - mmengine - INFO - Epoch(train) [810][40/63] lr: 2.5476e-03 eta: 8:21:31 time: 1.0777 data_time: 0.0432 memory: 16201 loss_prob: 0.3668 loss_thr: 0.2586 loss_db: 0.0665 loss: 0.6918 2022/08/30 17:28:50 - mmengine - INFO - Epoch(train) [810][45/63] lr: 2.5476e-03 eta: 8:21:31 time: 1.0819 data_time: 0.0476 memory: 16201 loss_prob: 0.4048 loss_thr: 0.2762 loss_db: 0.0725 loss: 0.7536 2022/08/30 17:28:55 - mmengine - INFO - Epoch(train) [810][50/63] lr: 2.5476e-03 eta: 8:21:18 time: 1.1017 data_time: 0.0529 memory: 16201 loss_prob: 0.3841 loss_thr: 0.2679 loss_db: 0.0692 loss: 0.7212 2022/08/30 17:29:01 - mmengine - INFO - Epoch(train) [810][55/63] lr: 2.5476e-03 eta: 8:21:18 time: 1.1527 data_time: 0.0412 memory: 16201 loss_prob: 0.3886 loss_thr: 0.2765 loss_db: 0.0687 loss: 0.7338 2022/08/30 17:29:07 - mmengine - INFO - Epoch(train) [810][60/63] lr: 2.5476e-03 eta: 8:21:06 time: 1.1273 data_time: 0.0363 memory: 16201 loss_prob: 0.4064 loss_thr: 0.2815 loss_db: 0.0711 loss: 0.7591 2022/08/30 17:29:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:29:17 - mmengine - INFO - Epoch(train) [811][5/63] lr: 2.5417e-03 eta: 8:21:06 time: 1.2413 data_time: 0.2310 memory: 16201 loss_prob: 0.4369 loss_thr: 0.3033 loss_db: 0.0744 loss: 0.8147 2022/08/30 17:29:22 - mmengine - INFO - Epoch(train) [811][10/63] lr: 2.5417e-03 eta: 8:20:48 time: 1.2485 data_time: 0.2357 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2521 loss_db: 0.0618 loss: 0.6668 2022/08/30 17:29:27 - mmengine - INFO - Epoch(train) [811][15/63] lr: 2.5417e-03 eta: 8:20:48 time: 0.9436 data_time: 0.0332 memory: 16201 loss_prob: 0.3658 loss_thr: 0.2646 loss_db: 0.0653 loss: 0.6956 2022/08/30 17:29:31 - mmengine - INFO - Epoch(train) [811][20/63] lr: 2.5417e-03 eta: 8:20:34 time: 0.8823 data_time: 0.0235 memory: 16201 loss_prob: 0.3830 loss_thr: 0.2706 loss_db: 0.0687 loss: 0.7223 2022/08/30 17:29:36 - mmengine - INFO - Epoch(train) [811][25/63] lr: 2.5417e-03 eta: 8:20:34 time: 0.9013 data_time: 0.0402 memory: 16201 loss_prob: 0.3926 loss_thr: 0.2786 loss_db: 0.0697 loss: 0.7409 2022/08/30 17:29:40 - mmengine - INFO - Epoch(train) [811][30/63] lr: 2.5417e-03 eta: 8:20:21 time: 0.9235 data_time: 0.0391 memory: 16201 loss_prob: 0.3972 loss_thr: 0.2878 loss_db: 0.0711 loss: 0.7561 2022/08/30 17:29:46 - mmengine - INFO - Epoch(train) [811][35/63] lr: 2.5417e-03 eta: 8:20:21 time: 1.0041 data_time: 0.0249 memory: 16201 loss_prob: 0.4250 loss_thr: 0.2894 loss_db: 0.0760 loss: 0.7904 2022/08/30 17:29:51 - mmengine - INFO - Epoch(train) [811][40/63] lr: 2.5417e-03 eta: 8:20:08 time: 1.0816 data_time: 0.0455 memory: 16201 loss_prob: 0.4543 loss_thr: 0.3016 loss_db: 0.0801 loss: 0.8360 2022/08/30 17:29:55 - mmengine - INFO - Epoch(train) [811][45/63] lr: 2.5417e-03 eta: 8:20:08 time: 0.9445 data_time: 0.0466 memory: 16201 loss_prob: 0.4058 loss_thr: 0.2882 loss_db: 0.0713 loss: 0.7653 2022/08/30 17:29:59 - mmengine - INFO - Epoch(train) [811][50/63] lr: 2.5417e-03 eta: 8:19:54 time: 0.8448 data_time: 0.0284 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2637 loss_db: 0.0612 loss: 0.6696 2022/08/30 17:30:07 - mmengine - INFO - Epoch(train) [811][55/63] lr: 2.5417e-03 eta: 8:19:54 time: 1.1682 data_time: 0.0386 memory: 16201 loss_prob: 0.3318 loss_thr: 0.2586 loss_db: 0.0596 loss: 0.6501 2022/08/30 17:30:11 - mmengine - INFO - Epoch(train) [811][60/63] lr: 2.5417e-03 eta: 8:19:41 time: 1.2071 data_time: 0.0371 memory: 16201 loss_prob: 0.4155 loss_thr: 0.2728 loss_db: 0.0696 loss: 0.7579 2022/08/30 17:30:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:30:20 - mmengine - INFO - Epoch(train) [812][5/63] lr: 2.5358e-03 eta: 8:19:41 time: 1.0230 data_time: 0.2196 memory: 16201 loss_prob: 0.4304 loss_thr: 0.2753 loss_db: 0.0718 loss: 0.7775 2022/08/30 17:30:26 - mmengine - INFO - Epoch(train) [812][10/63] lr: 2.5358e-03 eta: 8:19:24 time: 1.2265 data_time: 0.2321 memory: 16201 loss_prob: 0.3632 loss_thr: 0.2700 loss_db: 0.0653 loss: 0.6986 2022/08/30 17:30:31 - mmengine - INFO - Epoch(train) [812][15/63] lr: 2.5358e-03 eta: 8:19:24 time: 1.1617 data_time: 0.0393 memory: 16201 loss_prob: 0.4065 loss_thr: 0.2934 loss_db: 0.0738 loss: 0.7736 2022/08/30 17:30:37 - mmengine - INFO - Epoch(train) [812][20/63] lr: 2.5358e-03 eta: 8:19:11 time: 1.1539 data_time: 0.0345 memory: 16201 loss_prob: 0.4556 loss_thr: 0.3079 loss_db: 0.0797 loss: 0.8433 2022/08/30 17:30:43 - mmengine - INFO - Epoch(train) [812][25/63] lr: 2.5358e-03 eta: 8:19:11 time: 1.1991 data_time: 0.0977 memory: 16201 loss_prob: 0.4366 loss_thr: 0.3008 loss_db: 0.0732 loss: 0.8107 2022/08/30 17:30:49 - mmengine - INFO - Epoch(train) [812][30/63] lr: 2.5358e-03 eta: 8:18:59 time: 1.1766 data_time: 0.0831 memory: 16201 loss_prob: 0.4170 loss_thr: 0.2945 loss_db: 0.0726 loss: 0.7841 2022/08/30 17:30:54 - mmengine - INFO - Epoch(train) [812][35/63] lr: 2.5358e-03 eta: 8:18:59 time: 1.1024 data_time: 0.0400 memory: 16201 loss_prob: 0.3925 loss_thr: 0.2867 loss_db: 0.0713 loss: 0.7505 2022/08/30 17:30:59 - mmengine - INFO - Epoch(train) [812][40/63] lr: 2.5358e-03 eta: 8:18:45 time: 1.0011 data_time: 0.0385 memory: 16201 loss_prob: 0.4345 loss_thr: 0.2787 loss_db: 0.0692 loss: 0.7824 2022/08/30 17:31:04 - mmengine - INFO - Epoch(train) [812][45/63] lr: 2.5358e-03 eta: 8:18:45 time: 0.9192 data_time: 0.0289 memory: 16201 loss_prob: 0.4716 loss_thr: 0.2909 loss_db: 0.0753 loss: 0.8378 2022/08/30 17:31:08 - mmengine - INFO - Epoch(train) [812][50/63] lr: 2.5358e-03 eta: 8:18:31 time: 0.8857 data_time: 0.0391 memory: 16201 loss_prob: 0.4411 loss_thr: 0.2975 loss_db: 0.0789 loss: 0.8174 2022/08/30 17:31:12 - mmengine - INFO - Epoch(train) [812][55/63] lr: 2.5358e-03 eta: 8:18:31 time: 0.8622 data_time: 0.0246 memory: 16201 loss_prob: 0.4324 loss_thr: 0.2848 loss_db: 0.0764 loss: 0.7936 2022/08/30 17:31:17 - mmengine - INFO - Epoch(train) [812][60/63] lr: 2.5358e-03 eta: 8:18:18 time: 0.8860 data_time: 0.0253 memory: 16201 loss_prob: 0.4129 loss_thr: 0.2665 loss_db: 0.0723 loss: 0.7517 2022/08/30 17:31:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:31:27 - mmengine - INFO - Epoch(train) [813][5/63] lr: 2.5299e-03 eta: 8:18:18 time: 1.2419 data_time: 0.2568 memory: 16201 loss_prob: 0.4020 loss_thr: 0.2693 loss_db: 0.0707 loss: 0.7420 2022/08/30 17:31:32 - mmengine - INFO - Epoch(train) [813][10/63] lr: 2.5299e-03 eta: 8:18:00 time: 1.2695 data_time: 0.2681 memory: 16201 loss_prob: 0.3942 loss_thr: 0.2691 loss_db: 0.0700 loss: 0.7333 2022/08/30 17:31:36 - mmengine - INFO - Epoch(train) [813][15/63] lr: 2.5299e-03 eta: 8:18:00 time: 0.8831 data_time: 0.0324 memory: 16201 loss_prob: 0.4000 loss_thr: 0.2863 loss_db: 0.0708 loss: 0.7571 2022/08/30 17:31:41 - mmengine - INFO - Epoch(train) [813][20/63] lr: 2.5299e-03 eta: 8:17:47 time: 0.9199 data_time: 0.0283 memory: 16201 loss_prob: 0.4034 loss_thr: 0.2906 loss_db: 0.0712 loss: 0.7653 2022/08/30 17:31:47 - mmengine - INFO - Epoch(train) [813][25/63] lr: 2.5299e-03 eta: 8:17:47 time: 1.0792 data_time: 0.0461 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2649 loss_db: 0.0657 loss: 0.6959 2022/08/30 17:31:52 - mmengine - INFO - Epoch(train) [813][30/63] lr: 2.5299e-03 eta: 8:17:34 time: 1.0859 data_time: 0.0388 memory: 16201 loss_prob: 0.3796 loss_thr: 0.2712 loss_db: 0.0686 loss: 0.7194 2022/08/30 17:31:58 - mmengine - INFO - Epoch(train) [813][35/63] lr: 2.5299e-03 eta: 8:17:34 time: 1.0539 data_time: 0.0337 memory: 16201 loss_prob: 0.4099 loss_thr: 0.2872 loss_db: 0.0718 loss: 0.7689 2022/08/30 17:32:04 - mmengine - INFO - Epoch(train) [813][40/63] lr: 2.5299e-03 eta: 8:17:21 time: 1.1569 data_time: 0.0383 memory: 16201 loss_prob: 0.4034 loss_thr: 0.2877 loss_db: 0.0703 loss: 0.7615 2022/08/30 17:32:09 - mmengine - INFO - Epoch(train) [813][45/63] lr: 2.5299e-03 eta: 8:17:21 time: 1.1137 data_time: 0.0370 memory: 16201 loss_prob: 0.4125 loss_thr: 0.2942 loss_db: 0.0730 loss: 0.7797 2022/08/30 17:32:13 - mmengine - INFO - Epoch(train) [813][50/63] lr: 2.5299e-03 eta: 8:17:07 time: 0.9322 data_time: 0.0395 memory: 16201 loss_prob: 0.4030 loss_thr: 0.2927 loss_db: 0.0714 loss: 0.7672 2022/08/30 17:32:18 - mmengine - INFO - Epoch(train) [813][55/63] lr: 2.5299e-03 eta: 8:17:07 time: 0.8817 data_time: 0.0288 memory: 16201 loss_prob: 0.3850 loss_thr: 0.2860 loss_db: 0.0676 loss: 0.7386 2022/08/30 17:32:22 - mmengine - INFO - Epoch(train) [813][60/63] lr: 2.5299e-03 eta: 8:16:54 time: 0.8851 data_time: 0.0382 memory: 16201 loss_prob: 0.3998 loss_thr: 0.2995 loss_db: 0.0705 loss: 0.7697 2022/08/30 17:32:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:32:33 - mmengine - INFO - Epoch(train) [814][5/63] lr: 2.5241e-03 eta: 8:16:54 time: 1.2298 data_time: 0.2567 memory: 16201 loss_prob: 0.3740 loss_thr: 0.2696 loss_db: 0.0669 loss: 0.7104 2022/08/30 17:32:38 - mmengine - INFO - Epoch(train) [814][10/63] lr: 2.5241e-03 eta: 8:16:36 time: 1.3223 data_time: 0.2546 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2601 loss_db: 0.0658 loss: 0.6857 2022/08/30 17:32:42 - mmengine - INFO - Epoch(train) [814][15/63] lr: 2.5241e-03 eta: 8:16:36 time: 0.9640 data_time: 0.0339 memory: 16201 loss_prob: 0.3572 loss_thr: 0.2618 loss_db: 0.0640 loss: 0.6829 2022/08/30 17:32:47 - mmengine - INFO - Epoch(train) [814][20/63] lr: 2.5241e-03 eta: 8:16:23 time: 0.8772 data_time: 0.0370 memory: 16201 loss_prob: 0.3846 loss_thr: 0.2724 loss_db: 0.0686 loss: 0.7256 2022/08/30 17:32:53 - mmengine - INFO - Epoch(train) [814][25/63] lr: 2.5241e-03 eta: 8:16:23 time: 1.1054 data_time: 0.0402 memory: 16201 loss_prob: 0.3786 loss_thr: 0.2697 loss_db: 0.0677 loss: 0.7161 2022/08/30 17:32:59 - mmengine - INFO - Epoch(train) [814][30/63] lr: 2.5241e-03 eta: 8:16:11 time: 1.2556 data_time: 0.0434 memory: 16201 loss_prob: 0.3676 loss_thr: 0.2778 loss_db: 0.0633 loss: 0.7088 2022/08/30 17:33:05 - mmengine - INFO - Epoch(train) [814][35/63] lr: 2.5241e-03 eta: 8:16:11 time: 1.2097 data_time: 0.0492 memory: 16201 loss_prob: 0.3873 loss_thr: 0.2947 loss_db: 0.0666 loss: 0.7487 2022/08/30 17:33:10 - mmengine - INFO - Epoch(train) [814][40/63] lr: 2.5241e-03 eta: 8:15:58 time: 1.0522 data_time: 0.0325 memory: 16201 loss_prob: 0.4127 loss_thr: 0.2948 loss_db: 0.0704 loss: 0.7778 2022/08/30 17:33:14 - mmengine - INFO - Epoch(train) [814][45/63] lr: 2.5241e-03 eta: 8:15:58 time: 0.8949 data_time: 0.0342 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2782 loss_db: 0.0672 loss: 0.7375 2022/08/30 17:33:19 - mmengine - INFO - Epoch(train) [814][50/63] lr: 2.5241e-03 eta: 8:15:44 time: 0.8836 data_time: 0.0364 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2826 loss_db: 0.0669 loss: 0.7299 2022/08/30 17:33:24 - mmengine - INFO - Epoch(train) [814][55/63] lr: 2.5241e-03 eta: 8:15:44 time: 0.9847 data_time: 0.0234 memory: 16201 loss_prob: 0.3927 loss_thr: 0.2843 loss_db: 0.0710 loss: 0.7480 2022/08/30 17:33:29 - mmengine - INFO - Epoch(train) [814][60/63] lr: 2.5241e-03 eta: 8:15:31 time: 1.0885 data_time: 0.0407 memory: 16201 loss_prob: 0.3966 loss_thr: 0.2831 loss_db: 0.0715 loss: 0.7512 2022/08/30 17:33:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:33:41 - mmengine - INFO - Epoch(train) [815][5/63] lr: 2.5182e-03 eta: 8:15:31 time: 1.3277 data_time: 0.2940 memory: 16201 loss_prob: 0.3518 loss_thr: 0.2567 loss_db: 0.0619 loss: 0.6704 2022/08/30 17:33:46 - mmengine - INFO - Epoch(train) [815][10/63] lr: 2.5182e-03 eta: 8:15:14 time: 1.3212 data_time: 0.3021 memory: 16201 loss_prob: 0.3489 loss_thr: 0.2560 loss_db: 0.0634 loss: 0.6683 2022/08/30 17:33:51 - mmengine - INFO - Epoch(train) [815][15/63] lr: 2.5182e-03 eta: 8:15:14 time: 0.9864 data_time: 0.0371 memory: 16201 loss_prob: 0.3857 loss_thr: 0.2803 loss_db: 0.0685 loss: 0.7345 2022/08/30 17:33:55 - mmengine - INFO - Epoch(train) [815][20/63] lr: 2.5182e-03 eta: 8:15:00 time: 0.9572 data_time: 0.0241 memory: 16201 loss_prob: 0.3974 loss_thr: 0.2901 loss_db: 0.0690 loss: 0.7565 2022/08/30 17:34:00 - mmengine - INFO - Epoch(train) [815][25/63] lr: 2.5182e-03 eta: 8:15:00 time: 0.9110 data_time: 0.0360 memory: 16201 loss_prob: 0.4310 loss_thr: 0.3059 loss_db: 0.0758 loss: 0.8127 2022/08/30 17:34:04 - mmengine - INFO - Epoch(train) [815][30/63] lr: 2.5182e-03 eta: 8:14:46 time: 0.8519 data_time: 0.0325 memory: 16201 loss_prob: 0.4436 loss_thr: 0.3094 loss_db: 0.0787 loss: 0.8316 2022/08/30 17:34:10 - mmengine - INFO - Epoch(train) [815][35/63] lr: 2.5182e-03 eta: 8:14:46 time: 1.0452 data_time: 0.0288 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2908 loss_db: 0.0713 loss: 0.7607 2022/08/30 17:34:16 - mmengine - INFO - Epoch(train) [815][40/63] lr: 2.5182e-03 eta: 8:14:34 time: 1.1849 data_time: 0.0360 memory: 16201 loss_prob: 0.3864 loss_thr: 0.2764 loss_db: 0.0674 loss: 0.7302 2022/08/30 17:34:21 - mmengine - INFO - Epoch(train) [815][45/63] lr: 2.5182e-03 eta: 8:14:34 time: 1.1202 data_time: 0.0466 memory: 16201 loss_prob: 0.4303 loss_thr: 0.3186 loss_db: 0.0750 loss: 0.8240 2022/08/30 17:34:26 - mmengine - INFO - Epoch(train) [815][50/63] lr: 2.5182e-03 eta: 8:14:20 time: 0.9777 data_time: 0.0465 memory: 16201 loss_prob: 0.3995 loss_thr: 0.2981 loss_db: 0.0711 loss: 0.7687 2022/08/30 17:34:30 - mmengine - INFO - Epoch(train) [815][55/63] lr: 2.5182e-03 eta: 8:14:20 time: 0.8447 data_time: 0.0268 memory: 16201 loss_prob: 0.3589 loss_thr: 0.2541 loss_db: 0.0629 loss: 0.6760 2022/08/30 17:34:35 - mmengine - INFO - Epoch(train) [815][60/63] lr: 2.5182e-03 eta: 8:14:07 time: 0.8929 data_time: 0.0226 memory: 16201 loss_prob: 0.4069 loss_thr: 0.2778 loss_db: 0.0713 loss: 0.7560 2022/08/30 17:34:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:34:44 - mmengine - INFO - Epoch(train) [816][5/63] lr: 2.5123e-03 eta: 8:14:07 time: 1.1352 data_time: 0.2339 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2611 loss_db: 0.0659 loss: 0.7038 2022/08/30 17:34:49 - mmengine - INFO - Epoch(train) [816][10/63] lr: 2.5123e-03 eta: 8:13:49 time: 1.2488 data_time: 0.2373 memory: 16201 loss_prob: 0.3491 loss_thr: 0.2552 loss_db: 0.0625 loss: 0.6669 2022/08/30 17:34:56 - mmengine - INFO - Epoch(train) [816][15/63] lr: 2.5123e-03 eta: 8:13:49 time: 1.1584 data_time: 0.0298 memory: 16201 loss_prob: 0.3984 loss_thr: 0.2747 loss_db: 0.0722 loss: 0.7453 2022/08/30 17:35:00 - mmengine - INFO - Epoch(train) [816][20/63] lr: 2.5123e-03 eta: 8:13:36 time: 1.0504 data_time: 0.0269 memory: 16201 loss_prob: 0.4203 loss_thr: 0.2795 loss_db: 0.0731 loss: 0.7728 2022/08/30 17:35:04 - mmengine - INFO - Epoch(train) [816][25/63] lr: 2.5123e-03 eta: 8:13:36 time: 0.8719 data_time: 0.0400 memory: 16201 loss_prob: 0.4107 loss_thr: 0.2762 loss_db: 0.0707 loss: 0.7576 2022/08/30 17:35:10 - mmengine - INFO - Epoch(train) [816][30/63] lr: 2.5123e-03 eta: 8:13:23 time: 0.9970 data_time: 0.0351 memory: 16201 loss_prob: 0.3797 loss_thr: 0.2698 loss_db: 0.0674 loss: 0.7169 2022/08/30 17:35:15 - mmengine - INFO - Epoch(train) [816][35/63] lr: 2.5123e-03 eta: 8:13:23 time: 1.0865 data_time: 0.0325 memory: 16201 loss_prob: 0.3518 loss_thr: 0.2667 loss_db: 0.0625 loss: 0.6810 2022/08/30 17:35:20 - mmengine - INFO - Epoch(train) [816][40/63] lr: 2.5123e-03 eta: 8:13:10 time: 1.0386 data_time: 0.0329 memory: 16201 loss_prob: 0.3859 loss_thr: 0.2878 loss_db: 0.0664 loss: 0.7401 2022/08/30 17:35:25 - mmengine - INFO - Epoch(train) [816][45/63] lr: 2.5123e-03 eta: 8:13:10 time: 0.9572 data_time: 0.0294 memory: 16201 loss_prob: 0.4260 loss_thr: 0.3104 loss_db: 0.0741 loss: 0.8104 2022/08/30 17:35:29 - mmengine - INFO - Epoch(train) [816][50/63] lr: 2.5123e-03 eta: 8:12:56 time: 0.8830 data_time: 0.0330 memory: 16201 loss_prob: 0.4497 loss_thr: 0.3173 loss_db: 0.0796 loss: 0.8466 2022/08/30 17:35:33 - mmengine - INFO - Epoch(train) [816][55/63] lr: 2.5123e-03 eta: 8:12:56 time: 0.8432 data_time: 0.0263 memory: 16201 loss_prob: 0.4329 loss_thr: 0.3085 loss_db: 0.0767 loss: 0.8181 2022/08/30 17:35:39 - mmengine - INFO - Epoch(train) [816][60/63] lr: 2.5123e-03 eta: 8:12:42 time: 0.9535 data_time: 0.0327 memory: 16201 loss_prob: 0.4028 loss_thr: 0.2871 loss_db: 0.0737 loss: 0.7635 2022/08/30 17:35:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:35:49 - mmengine - INFO - Epoch(train) [817][5/63] lr: 2.5064e-03 eta: 8:12:42 time: 1.2676 data_time: 0.2735 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2565 loss_db: 0.0637 loss: 0.6854 2022/08/30 17:35:54 - mmengine - INFO - Epoch(train) [817][10/63] lr: 2.5064e-03 eta: 8:12:25 time: 1.2896 data_time: 0.2881 memory: 16201 loss_prob: 0.4003 loss_thr: 0.2745 loss_db: 0.0701 loss: 0.7449 2022/08/30 17:35:59 - mmengine - INFO - Epoch(train) [817][15/63] lr: 2.5064e-03 eta: 8:12:25 time: 1.0083 data_time: 0.0304 memory: 16201 loss_prob: 0.4287 loss_thr: 0.2793 loss_db: 0.0769 loss: 0.7849 2022/08/30 17:36:04 - mmengine - INFO - Epoch(train) [817][20/63] lr: 2.5064e-03 eta: 8:12:12 time: 1.0055 data_time: 0.0295 memory: 16201 loss_prob: 0.3790 loss_thr: 0.2501 loss_db: 0.0686 loss: 0.6977 2022/08/30 17:36:09 - mmengine - INFO - Epoch(train) [817][25/63] lr: 2.5064e-03 eta: 8:12:12 time: 1.0147 data_time: 0.0291 memory: 16201 loss_prob: 0.3471 loss_thr: 0.2487 loss_db: 0.0616 loss: 0.6574 2022/08/30 17:36:15 - mmengine - INFO - Epoch(train) [817][30/63] lr: 2.5064e-03 eta: 8:11:59 time: 1.0543 data_time: 0.0263 memory: 16201 loss_prob: 0.3770 loss_thr: 0.2828 loss_db: 0.0657 loss: 0.7255 2022/08/30 17:36:20 - mmengine - INFO - Epoch(train) [817][35/63] lr: 2.5064e-03 eta: 8:11:59 time: 1.0430 data_time: 0.0415 memory: 16201 loss_prob: 0.3634 loss_thr: 0.2779 loss_db: 0.0637 loss: 0.7050 2022/08/30 17:36:24 - mmengine - INFO - Epoch(train) [817][40/63] lr: 2.5064e-03 eta: 8:11:45 time: 0.9212 data_time: 0.0365 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2787 loss_db: 0.0690 loss: 0.7335 2022/08/30 17:36:28 - mmengine - INFO - Epoch(train) [817][45/63] lr: 2.5064e-03 eta: 8:11:45 time: 0.8727 data_time: 0.0318 memory: 16201 loss_prob: 0.3974 loss_thr: 0.2784 loss_db: 0.0716 loss: 0.7473 2022/08/30 17:36:33 - mmengine - INFO - Epoch(train) [817][50/63] lr: 2.5064e-03 eta: 8:11:31 time: 0.8502 data_time: 0.0369 memory: 16201 loss_prob: 0.3943 loss_thr: 0.2744 loss_db: 0.0696 loss: 0.7383 2022/08/30 17:36:37 - mmengine - INFO - Epoch(train) [817][55/63] lr: 2.5064e-03 eta: 8:11:31 time: 0.8522 data_time: 0.0323 memory: 16201 loss_prob: 0.4449 loss_thr: 0.2956 loss_db: 0.0764 loss: 0.8168 2022/08/30 17:36:42 - mmengine - INFO - Epoch(train) [817][60/63] lr: 2.5064e-03 eta: 8:11:18 time: 0.9512 data_time: 0.0377 memory: 16201 loss_prob: 0.4336 loss_thr: 0.2986 loss_db: 0.0737 loss: 0.8060 2022/08/30 17:36:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:36:52 - mmengine - INFO - Epoch(train) [818][5/63] lr: 2.5005e-03 eta: 8:11:18 time: 1.1519 data_time: 0.2314 memory: 16201 loss_prob: 0.3991 loss_thr: 0.2837 loss_db: 0.0699 loss: 0.7527 2022/08/30 17:36:58 - mmengine - INFO - Epoch(train) [818][10/63] lr: 2.5005e-03 eta: 8:11:01 time: 1.2854 data_time: 0.2406 memory: 16201 loss_prob: 0.4257 loss_thr: 0.2653 loss_db: 0.0701 loss: 0.7611 2022/08/30 17:37:03 - mmengine - INFO - Epoch(train) [818][15/63] lr: 2.5005e-03 eta: 8:11:01 time: 1.0592 data_time: 0.0358 memory: 16201 loss_prob: 0.4481 loss_thr: 0.2742 loss_db: 0.0741 loss: 0.7964 2022/08/30 17:37:08 - mmengine - INFO - Epoch(train) [818][20/63] lr: 2.5005e-03 eta: 8:10:48 time: 1.0648 data_time: 0.0372 memory: 16201 loss_prob: 0.4104 loss_thr: 0.2931 loss_db: 0.0711 loss: 0.7746 2022/08/30 17:37:13 - mmengine - INFO - Epoch(train) [818][25/63] lr: 2.5005e-03 eta: 8:10:48 time: 1.0438 data_time: 0.0449 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2858 loss_db: 0.0711 loss: 0.7605 2022/08/30 17:37:17 - mmengine - INFO - Epoch(train) [818][30/63] lr: 2.5005e-03 eta: 8:10:34 time: 0.9121 data_time: 0.0442 memory: 16201 loss_prob: 0.3916 loss_thr: 0.2771 loss_db: 0.0714 loss: 0.7400 2022/08/30 17:37:22 - mmengine - INFO - Epoch(train) [818][35/63] lr: 2.5005e-03 eta: 8:10:34 time: 0.8643 data_time: 0.0283 memory: 16201 loss_prob: 0.3809 loss_thr: 0.2752 loss_db: 0.0674 loss: 0.7235 2022/08/30 17:37:26 - mmengine - INFO - Epoch(train) [818][40/63] lr: 2.5005e-03 eta: 8:10:20 time: 0.8444 data_time: 0.0218 memory: 16201 loss_prob: 0.4258 loss_thr: 0.2963 loss_db: 0.0741 loss: 0.7961 2022/08/30 17:37:31 - mmengine - INFO - Epoch(train) [818][45/63] lr: 2.5005e-03 eta: 8:10:20 time: 0.9353 data_time: 0.0323 memory: 16201 loss_prob: 0.4321 loss_thr: 0.2928 loss_db: 0.0771 loss: 0.8020 2022/08/30 17:37:37 - mmengine - INFO - Epoch(train) [818][50/63] lr: 2.5005e-03 eta: 8:10:07 time: 1.0808 data_time: 0.0369 memory: 16201 loss_prob: 0.3864 loss_thr: 0.2706 loss_db: 0.0691 loss: 0.7260 2022/08/30 17:37:42 - mmengine - INFO - Epoch(train) [818][55/63] lr: 2.5005e-03 eta: 8:10:07 time: 1.1103 data_time: 0.0374 memory: 16201 loss_prob: 0.3729 loss_thr: 0.2650 loss_db: 0.0668 loss: 0.7048 2022/08/30 17:37:47 - mmengine - INFO - Epoch(train) [818][60/63] lr: 2.5005e-03 eta: 8:09:54 time: 1.0329 data_time: 0.0345 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2526 loss_db: 0.0643 loss: 0.6675 2022/08/30 17:37:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:37:56 - mmengine - INFO - Epoch(train) [819][5/63] lr: 2.4946e-03 eta: 8:09:54 time: 1.0326 data_time: 0.2395 memory: 16201 loss_prob: 0.3357 loss_thr: 0.2542 loss_db: 0.0597 loss: 0.6495 2022/08/30 17:38:00 - mmengine - INFO - Epoch(train) [819][10/63] lr: 2.4946e-03 eta: 8:09:36 time: 1.1208 data_time: 0.2394 memory: 16201 loss_prob: 0.3955 loss_thr: 0.2953 loss_db: 0.0694 loss: 0.7601 2022/08/30 17:38:06 - mmengine - INFO - Epoch(train) [819][15/63] lr: 2.4946e-03 eta: 8:09:36 time: 1.0796 data_time: 0.0451 memory: 16201 loss_prob: 0.4214 loss_thr: 0.2997 loss_db: 0.0744 loss: 0.7955 2022/08/30 17:38:12 - mmengine - INFO - Epoch(train) [819][20/63] lr: 2.4946e-03 eta: 8:09:24 time: 1.2051 data_time: 0.0475 memory: 16201 loss_prob: 0.3850 loss_thr: 0.2776 loss_db: 0.0700 loss: 0.7326 2022/08/30 17:38:18 - mmengine - INFO - Epoch(train) [819][25/63] lr: 2.4946e-03 eta: 8:09:24 time: 1.1367 data_time: 0.0429 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2718 loss_db: 0.0665 loss: 0.7141 2022/08/30 17:38:25 - mmengine - INFO - Epoch(train) [819][30/63] lr: 2.4946e-03 eta: 8:09:12 time: 1.2808 data_time: 0.0412 memory: 16201 loss_prob: 0.3687 loss_thr: 0.2712 loss_db: 0.0643 loss: 0.7042 2022/08/30 17:38:32 - mmengine - INFO - Epoch(train) [819][35/63] lr: 2.4946e-03 eta: 8:09:12 time: 1.4188 data_time: 0.0373 memory: 16201 loss_prob: 0.3655 loss_thr: 0.2720 loss_db: 0.0658 loss: 0.7033 2022/08/30 17:38:37 - mmengine - INFO - Epoch(train) [819][40/63] lr: 2.4946e-03 eta: 8:08:59 time: 1.1897 data_time: 0.0326 memory: 16201 loss_prob: 0.3781 loss_thr: 0.2750 loss_db: 0.0674 loss: 0.7206 2022/08/30 17:38:42 - mmengine - INFO - Epoch(train) [819][45/63] lr: 2.4946e-03 eta: 8:08:59 time: 1.0048 data_time: 0.0321 memory: 16201 loss_prob: 0.3878 loss_thr: 0.2773 loss_db: 0.0675 loss: 0.7326 2022/08/30 17:38:46 - mmengine - INFO - Epoch(train) [819][50/63] lr: 2.4946e-03 eta: 8:08:46 time: 0.9114 data_time: 0.0394 memory: 16201 loss_prob: 0.3948 loss_thr: 0.2797 loss_db: 0.0692 loss: 0.7437 2022/08/30 17:38:50 - mmengine - INFO - Epoch(train) [819][55/63] lr: 2.4946e-03 eta: 8:08:46 time: 0.8421 data_time: 0.0311 memory: 16201 loss_prob: 0.3870 loss_thr: 0.2730 loss_db: 0.0690 loss: 0.7290 2022/08/30 17:38:55 - mmengine - INFO - Epoch(train) [819][60/63] lr: 2.4946e-03 eta: 8:08:32 time: 0.8510 data_time: 0.0344 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2633 loss_db: 0.0650 loss: 0.6863 2022/08/30 17:38:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:39:04 - mmengine - INFO - Epoch(train) [820][5/63] lr: 2.4887e-03 eta: 8:08:32 time: 1.1015 data_time: 0.2072 memory: 16201 loss_prob: 0.3797 loss_thr: 0.2738 loss_db: 0.0671 loss: 0.7207 2022/08/30 17:39:10 - mmengine - INFO - Epoch(train) [820][10/63] lr: 2.4887e-03 eta: 8:08:14 time: 1.2696 data_time: 0.2520 memory: 16201 loss_prob: 0.4175 loss_thr: 0.2899 loss_db: 0.0717 loss: 0.7791 2022/08/30 17:39:15 - mmengine - INFO - Epoch(train) [820][15/63] lr: 2.4887e-03 eta: 8:08:14 time: 1.1174 data_time: 0.0894 memory: 16201 loss_prob: 0.4693 loss_thr: 0.3182 loss_db: 0.0829 loss: 0.8704 2022/08/30 17:39:22 - mmengine - INFO - Epoch(train) [820][20/63] lr: 2.4887e-03 eta: 8:08:02 time: 1.1361 data_time: 0.0777 memory: 16201 loss_prob: 0.4339 loss_thr: 0.3042 loss_db: 0.0775 loss: 0.8156 2022/08/30 17:39:27 - mmengine - INFO - Epoch(train) [820][25/63] lr: 2.4887e-03 eta: 8:08:02 time: 1.1579 data_time: 0.0848 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2740 loss_db: 0.0660 loss: 0.7184 2022/08/30 17:39:32 - mmengine - INFO - Epoch(train) [820][30/63] lr: 2.4887e-03 eta: 8:07:49 time: 1.0486 data_time: 0.0743 memory: 16201 loss_prob: 0.4461 loss_thr: 0.3024 loss_db: 0.0757 loss: 0.8242 2022/08/30 17:39:37 - mmengine - INFO - Epoch(train) [820][35/63] lr: 2.4887e-03 eta: 8:07:49 time: 1.0026 data_time: 0.0751 memory: 16201 loss_prob: 0.4284 loss_thr: 0.2959 loss_db: 0.0731 loss: 0.7974 2022/08/30 17:39:41 - mmengine - INFO - Epoch(train) [820][40/63] lr: 2.4887e-03 eta: 8:07:35 time: 0.9250 data_time: 0.0724 memory: 16201 loss_prob: 0.3922 loss_thr: 0.2962 loss_db: 0.0695 loss: 0.7579 2022/08/30 17:39:46 - mmengine - INFO - Epoch(train) [820][45/63] lr: 2.4887e-03 eta: 8:07:35 time: 0.9177 data_time: 0.0669 memory: 16201 loss_prob: 0.4042 loss_thr: 0.3031 loss_db: 0.0725 loss: 0.7798 2022/08/30 17:39:51 - mmengine - INFO - Epoch(train) [820][50/63] lr: 2.4887e-03 eta: 8:07:22 time: 0.9537 data_time: 0.0594 memory: 16201 loss_prob: 0.3827 loss_thr: 0.2714 loss_db: 0.0664 loss: 0.7205 2022/08/30 17:39:57 - mmengine - INFO - Epoch(train) [820][55/63] lr: 2.4887e-03 eta: 8:07:22 time: 1.0549 data_time: 0.0675 memory: 16201 loss_prob: 0.3865 loss_thr: 0.2764 loss_db: 0.0657 loss: 0.7286 2022/08/30 17:40:01 - mmengine - INFO - Epoch(train) [820][60/63] lr: 2.4887e-03 eta: 8:07:09 time: 1.0461 data_time: 0.0769 memory: 16201 loss_prob: 0.3745 loss_thr: 0.2908 loss_db: 0.0677 loss: 0.7330 2022/08/30 17:40:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:40:04 - mmengine - INFO - Saving checkpoint at 820 epochs 2022/08/30 17:40:14 - mmengine - INFO - Epoch(val) [820][5/32] eta: 8:07:09 time: 0.7494 data_time: 0.1447 memory: 16201 2022/08/30 17:40:18 - mmengine - INFO - Epoch(val) [820][10/32] eta: 0:00:17 time: 0.7844 data_time: 0.1868 memory: 15734 2022/08/30 17:40:21 - mmengine - INFO - Epoch(val) [820][15/32] eta: 0:00:17 time: 0.6264 data_time: 0.0626 memory: 15734 2022/08/30 17:40:25 - mmengine - INFO - Epoch(val) [820][20/32] eta: 0:00:08 time: 0.6768 data_time: 0.0633 memory: 15734 2022/08/30 17:40:28 - mmengine - INFO - Epoch(val) [820][25/32] eta: 0:00:08 time: 0.7290 data_time: 0.0736 memory: 15734 2022/08/30 17:40:31 - mmengine - INFO - Epoch(val) [820][30/32] eta: 0:00:01 time: 0.6568 data_time: 0.0348 memory: 15734 2022/08/30 17:40:32 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 17:40:32 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8344, precision: 0.7842, hmean: 0.8085 2022/08/30 17:40:32 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8344, precision: 0.8312, hmean: 0.8328 2022/08/30 17:40:32 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8334, precision: 0.8552, hmean: 0.8442 2022/08/30 17:40:32 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8276, precision: 0.8704, hmean: 0.8485 2022/08/30 17:40:32 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8161, precision: 0.8860, hmean: 0.8496 2022/08/30 17:40:32 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7829, precision: 0.9104, hmean: 0.8418 2022/08/30 17:40:32 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.3356, precision: 0.9574, hmean: 0.4970 2022/08/30 17:40:32 - mmengine - INFO - Epoch(val) [820][32/32] icdar/precision: 0.8860 icdar/recall: 0.8161 icdar/hmean: 0.8496 2022/08/30 17:40:41 - mmengine - INFO - Epoch(train) [821][5/63] lr: 2.4828e-03 eta: 0:00:01 time: 1.2988 data_time: 0.3287 memory: 16201 loss_prob: 0.4127 loss_thr: 0.2922 loss_db: 0.0712 loss: 0.7760 2022/08/30 17:40:47 - mmengine - INFO - Epoch(train) [821][10/63] lr: 2.4828e-03 eta: 8:06:52 time: 1.3929 data_time: 0.3102 memory: 16201 loss_prob: 0.3974 loss_thr: 0.2880 loss_db: 0.0706 loss: 0.7561 2022/08/30 17:40:53 - mmengine - INFO - Epoch(train) [821][15/63] lr: 2.4828e-03 eta: 8:06:52 time: 1.1441 data_time: 0.0726 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2924 loss_db: 0.0744 loss: 0.7772 2022/08/30 17:40:57 - mmengine - INFO - Epoch(train) [821][20/63] lr: 2.4828e-03 eta: 8:06:39 time: 1.0477 data_time: 0.0698 memory: 16201 loss_prob: 0.3840 loss_thr: 0.2648 loss_db: 0.0682 loss: 0.7170 2022/08/30 17:41:02 - mmengine - INFO - Epoch(train) [821][25/63] lr: 2.4828e-03 eta: 8:06:39 time: 0.9317 data_time: 0.0805 memory: 16201 loss_prob: 0.3682 loss_thr: 0.2613 loss_db: 0.0650 loss: 0.6945 2022/08/30 17:41:07 - mmengine - INFO - Epoch(train) [821][30/63] lr: 2.4828e-03 eta: 8:06:26 time: 0.9584 data_time: 0.0634 memory: 16201 loss_prob: 0.4178 loss_thr: 0.2957 loss_db: 0.0729 loss: 0.7865 2022/08/30 17:41:13 - mmengine - INFO - Epoch(train) [821][35/63] lr: 2.4828e-03 eta: 8:06:26 time: 1.1042 data_time: 0.0437 memory: 16201 loss_prob: 0.4067 loss_thr: 0.2903 loss_db: 0.0721 loss: 0.7690 2022/08/30 17:41:19 - mmengine - INFO - Epoch(train) [821][40/63] lr: 2.4828e-03 eta: 8:06:13 time: 1.2454 data_time: 0.0981 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2903 loss_db: 0.0702 loss: 0.7569 2022/08/30 17:41:24 - mmengine - INFO - Epoch(train) [821][45/63] lr: 2.4828e-03 eta: 8:06:13 time: 1.0945 data_time: 0.0894 memory: 16201 loss_prob: 0.4019 loss_thr: 0.2875 loss_db: 0.0699 loss: 0.7593 2022/08/30 17:41:29 - mmengine - INFO - Epoch(train) [821][50/63] lr: 2.4828e-03 eta: 8:06:00 time: 1.0023 data_time: 0.0948 memory: 16201 loss_prob: 0.3825 loss_thr: 0.2729 loss_db: 0.0676 loss: 0.7231 2022/08/30 17:41:34 - mmengine - INFO - Epoch(train) [821][55/63] lr: 2.4828e-03 eta: 8:06:00 time: 0.9413 data_time: 0.0874 memory: 16201 loss_prob: 0.3954 loss_thr: 0.2799 loss_db: 0.0686 loss: 0.7439 2022/08/30 17:41:38 - mmengine - INFO - Epoch(train) [821][60/63] lr: 2.4828e-03 eta: 8:05:47 time: 0.8837 data_time: 0.0452 memory: 16201 loss_prob: 0.4190 loss_thr: 0.2936 loss_db: 0.0711 loss: 0.7837 2022/08/30 17:41:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:41:48 - mmengine - INFO - Epoch(train) [822][5/63] lr: 2.4769e-03 eta: 8:05:47 time: 1.1815 data_time: 0.2387 memory: 16201 loss_prob: 0.3917 loss_thr: 0.2818 loss_db: 0.0690 loss: 0.7425 2022/08/30 17:41:53 - mmengine - INFO - Epoch(train) [822][10/63] lr: 2.4769e-03 eta: 8:05:29 time: 1.1318 data_time: 0.2377 memory: 16201 loss_prob: 0.4150 loss_thr: 0.2843 loss_db: 0.0710 loss: 0.7703 2022/08/30 17:41:57 - mmengine - INFO - Epoch(train) [822][15/63] lr: 2.4769e-03 eta: 8:05:29 time: 0.9001 data_time: 0.0292 memory: 16201 loss_prob: 0.4164 loss_thr: 0.2874 loss_db: 0.0716 loss: 0.7754 2022/08/30 17:42:02 - mmengine - INFO - Epoch(train) [822][20/63] lr: 2.4769e-03 eta: 8:05:15 time: 0.9342 data_time: 0.0319 memory: 16201 loss_prob: 0.5065 loss_thr: 0.3184 loss_db: 0.0790 loss: 0.9040 2022/08/30 17:42:07 - mmengine - INFO - Epoch(train) [822][25/63] lr: 2.4769e-03 eta: 8:05:15 time: 1.0297 data_time: 0.0357 memory: 16201 loss_prob: 0.5183 loss_thr: 0.3317 loss_db: 0.0813 loss: 0.9312 2022/08/30 17:42:14 - mmengine - INFO - Epoch(train) [822][30/63] lr: 2.4769e-03 eta: 8:05:03 time: 1.1902 data_time: 0.0484 memory: 16201 loss_prob: 0.4000 loss_thr: 0.2917 loss_db: 0.0709 loss: 0.7625 2022/08/30 17:42:18 - mmengine - INFO - Epoch(train) [822][35/63] lr: 2.4769e-03 eta: 8:05:03 time: 1.1177 data_time: 0.0509 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2591 loss_db: 0.0623 loss: 0.6679 2022/08/30 17:42:23 - mmengine - INFO - Epoch(train) [822][40/63] lr: 2.4769e-03 eta: 8:04:49 time: 0.8961 data_time: 0.0343 memory: 16201 loss_prob: 0.3531 loss_thr: 0.2625 loss_db: 0.0635 loss: 0.6791 2022/08/30 17:42:27 - mmengine - INFO - Epoch(train) [822][45/63] lr: 2.4769e-03 eta: 8:04:49 time: 0.8329 data_time: 0.0303 memory: 16201 loss_prob: 0.3885 loss_thr: 0.2710 loss_db: 0.0687 loss: 0.7282 2022/08/30 17:42:33 - mmengine - INFO - Epoch(train) [822][50/63] lr: 2.4769e-03 eta: 8:04:36 time: 1.0008 data_time: 0.0355 memory: 16201 loss_prob: 0.3717 loss_thr: 0.2595 loss_db: 0.0650 loss: 0.6962 2022/08/30 17:42:39 - mmengine - INFO - Epoch(train) [822][55/63] lr: 2.4769e-03 eta: 8:04:36 time: 1.1672 data_time: 0.0446 memory: 16201 loss_prob: 0.3640 loss_thr: 0.2649 loss_db: 0.0638 loss: 0.6927 2022/08/30 17:42:44 - mmengine - INFO - Epoch(train) [822][60/63] lr: 2.4769e-03 eta: 8:04:23 time: 1.0911 data_time: 0.0397 memory: 16201 loss_prob: 0.4147 loss_thr: 0.2960 loss_db: 0.0740 loss: 0.7846 2022/08/30 17:42:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:42:54 - mmengine - INFO - Epoch(train) [823][5/63] lr: 2.4710e-03 eta: 8:04:23 time: 1.2338 data_time: 0.2555 memory: 16201 loss_prob: 0.3671 loss_thr: 0.2785 loss_db: 0.0643 loss: 0.7099 2022/08/30 17:42:59 - mmengine - INFO - Epoch(train) [823][10/63] lr: 2.4710e-03 eta: 8:04:05 time: 1.2097 data_time: 0.2592 memory: 16201 loss_prob: 0.4109 loss_thr: 0.2897 loss_db: 0.0731 loss: 0.7737 2022/08/30 17:43:03 - mmengine - INFO - Epoch(train) [823][15/63] lr: 2.4710e-03 eta: 8:04:05 time: 0.9002 data_time: 0.0267 memory: 16201 loss_prob: 0.3939 loss_thr: 0.2748 loss_db: 0.0708 loss: 0.7396 2022/08/30 17:43:07 - mmengine - INFO - Epoch(train) [823][20/63] lr: 2.4710e-03 eta: 8:03:52 time: 0.8762 data_time: 0.0333 memory: 16201 loss_prob: 0.3582 loss_thr: 0.2615 loss_db: 0.0643 loss: 0.6841 2022/08/30 17:43:12 - mmengine - INFO - Epoch(train) [823][25/63] lr: 2.4710e-03 eta: 8:03:52 time: 0.8859 data_time: 0.0366 memory: 16201 loss_prob: 0.3733 loss_thr: 0.2689 loss_db: 0.0664 loss: 0.7085 2022/08/30 17:43:18 - mmengine - INFO - Epoch(train) [823][30/63] lr: 2.4710e-03 eta: 8:03:39 time: 1.0457 data_time: 0.0269 memory: 16201 loss_prob: 0.3914 loss_thr: 0.2635 loss_db: 0.0670 loss: 0.7219 2022/08/30 17:43:22 - mmengine - INFO - Epoch(train) [823][35/63] lr: 2.4710e-03 eta: 8:03:39 time: 1.0499 data_time: 0.0314 memory: 16201 loss_prob: 0.4064 loss_thr: 0.2736 loss_db: 0.0688 loss: 0.7488 2022/08/30 17:43:28 - mmengine - INFO - Epoch(train) [823][40/63] lr: 2.4710e-03 eta: 8:03:25 time: 1.0127 data_time: 0.0311 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2870 loss_db: 0.0717 loss: 0.7690 2022/08/30 17:43:33 - mmengine - INFO - Epoch(train) [823][45/63] lr: 2.4710e-03 eta: 8:03:25 time: 1.0645 data_time: 0.0374 memory: 16201 loss_prob: 0.4223 loss_thr: 0.2915 loss_db: 0.0735 loss: 0.7873 2022/08/30 17:43:38 - mmengine - INFO - Epoch(train) [823][50/63] lr: 2.4710e-03 eta: 8:03:12 time: 0.9870 data_time: 0.0384 memory: 16201 loss_prob: 0.4586 loss_thr: 0.3028 loss_db: 0.0790 loss: 0.8404 2022/08/30 17:43:44 - mmengine - INFO - Epoch(train) [823][55/63] lr: 2.4710e-03 eta: 8:03:12 time: 1.1026 data_time: 0.0295 memory: 16201 loss_prob: 0.4331 loss_thr: 0.2906 loss_db: 0.0746 loss: 0.7983 2022/08/30 17:43:49 - mmengine - INFO - Epoch(train) [823][60/63] lr: 2.4710e-03 eta: 8:02:59 time: 1.0816 data_time: 0.0370 memory: 16201 loss_prob: 0.4120 loss_thr: 0.2815 loss_db: 0.0726 loss: 0.7661 2022/08/30 17:43:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:43:57 - mmengine - INFO - Epoch(train) [824][5/63] lr: 2.4651e-03 eta: 8:02:59 time: 1.0019 data_time: 0.2390 memory: 16201 loss_prob: 0.4593 loss_thr: 0.2991 loss_db: 0.0803 loss: 0.8387 2022/08/30 17:44:02 - mmengine - INFO - Epoch(train) [824][10/63] lr: 2.4651e-03 eta: 8:02:41 time: 1.0902 data_time: 0.2526 memory: 16201 loss_prob: 0.4156 loss_thr: 0.2964 loss_db: 0.0713 loss: 0.7833 2022/08/30 17:44:07 - mmengine - INFO - Epoch(train) [824][15/63] lr: 2.4651e-03 eta: 8:02:41 time: 1.0197 data_time: 0.0322 memory: 16201 loss_prob: 0.4064 loss_thr: 0.2898 loss_db: 0.0682 loss: 0.7644 2022/08/30 17:44:13 - mmengine - INFO - Epoch(train) [824][20/63] lr: 2.4651e-03 eta: 8:02:28 time: 1.1021 data_time: 0.0306 memory: 16201 loss_prob: 0.4123 loss_thr: 0.2743 loss_db: 0.0714 loss: 0.7580 2022/08/30 17:44:18 - mmengine - INFO - Epoch(train) [824][25/63] lr: 2.4651e-03 eta: 8:02:28 time: 1.0291 data_time: 0.0472 memory: 16201 loss_prob: 0.3745 loss_thr: 0.2644 loss_db: 0.0679 loss: 0.7068 2022/08/30 17:44:23 - mmengine - INFO - Epoch(train) [824][30/63] lr: 2.4651e-03 eta: 8:02:16 time: 1.0764 data_time: 0.0326 memory: 16201 loss_prob: 0.4020 loss_thr: 0.2894 loss_db: 0.0708 loss: 0.7622 2022/08/30 17:44:28 - mmengine - INFO - Epoch(train) [824][35/63] lr: 2.4651e-03 eta: 8:02:16 time: 1.0456 data_time: 0.0321 memory: 16201 loss_prob: 0.4183 loss_thr: 0.2921 loss_db: 0.0722 loss: 0.7826 2022/08/30 17:44:32 - mmengine - INFO - Epoch(train) [824][40/63] lr: 2.4651e-03 eta: 8:02:02 time: 0.8547 data_time: 0.0325 memory: 16201 loss_prob: 0.4035 loss_thr: 0.2801 loss_db: 0.0711 loss: 0.7547 2022/08/30 17:44:36 - mmengine - INFO - Epoch(train) [824][45/63] lr: 2.4651e-03 eta: 8:02:02 time: 0.7877 data_time: 0.0247 memory: 16201 loss_prob: 0.4257 loss_thr: 0.2880 loss_db: 0.0759 loss: 0.7896 2022/08/30 17:44:41 - mmengine - INFO - Epoch(train) [824][50/63] lr: 2.4651e-03 eta: 8:01:48 time: 0.8952 data_time: 0.0308 memory: 16201 loss_prob: 0.4071 loss_thr: 0.2816 loss_db: 0.0720 loss: 0.7607 2022/08/30 17:44:46 - mmengine - INFO - Epoch(train) [824][55/63] lr: 2.4651e-03 eta: 8:01:48 time: 1.0044 data_time: 0.0274 memory: 16201 loss_prob: 0.4329 loss_thr: 0.2812 loss_db: 0.0713 loss: 0.7855 2022/08/30 17:44:52 - mmengine - INFO - Epoch(train) [824][60/63] lr: 2.4651e-03 eta: 8:01:35 time: 1.0750 data_time: 0.0327 memory: 16201 loss_prob: 0.4546 loss_thr: 0.3015 loss_db: 0.0755 loss: 0.8316 2022/08/30 17:44:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:45:03 - mmengine - INFO - Epoch(train) [825][5/63] lr: 2.4592e-03 eta: 8:01:35 time: 1.3288 data_time: 0.2651 memory: 16201 loss_prob: 0.3938 loss_thr: 0.2898 loss_db: 0.0691 loss: 0.7527 2022/08/30 17:45:07 - mmengine - INFO - Epoch(train) [825][10/63] lr: 2.4592e-03 eta: 8:01:17 time: 1.1781 data_time: 0.2753 memory: 16201 loss_prob: 0.4073 loss_thr: 0.2985 loss_db: 0.0721 loss: 0.7779 2022/08/30 17:45:11 - mmengine - INFO - Epoch(train) [825][15/63] lr: 2.4592e-03 eta: 8:01:17 time: 0.8316 data_time: 0.0283 memory: 16201 loss_prob: 0.3948 loss_thr: 0.2830 loss_db: 0.0709 loss: 0.7487 2022/08/30 17:45:17 - mmengine - INFO - Epoch(train) [825][20/63] lr: 2.4592e-03 eta: 8:01:04 time: 0.9990 data_time: 0.0286 memory: 16201 loss_prob: 0.3462 loss_thr: 0.2471 loss_db: 0.0610 loss: 0.6543 2022/08/30 17:45:22 - mmengine - INFO - Epoch(train) [825][25/63] lr: 2.4592e-03 eta: 8:01:04 time: 1.1348 data_time: 0.0421 memory: 16201 loss_prob: 0.3727 loss_thr: 0.2620 loss_db: 0.0652 loss: 0.6999 2022/08/30 17:45:27 - mmengine - INFO - Epoch(train) [825][30/63] lr: 2.4592e-03 eta: 8:00:51 time: 1.0306 data_time: 0.0362 memory: 16201 loss_prob: 0.4111 loss_thr: 0.2934 loss_db: 0.0724 loss: 0.7768 2022/08/30 17:45:32 - mmengine - INFO - Epoch(train) [825][35/63] lr: 2.4592e-03 eta: 8:00:51 time: 0.9358 data_time: 0.0437 memory: 16201 loss_prob: 0.3919 loss_thr: 0.2914 loss_db: 0.0696 loss: 0.7529 2022/08/30 17:45:36 - mmengine - INFO - Epoch(train) [825][40/63] lr: 2.4592e-03 eta: 8:00:37 time: 0.8748 data_time: 0.0348 memory: 16201 loss_prob: 0.3925 loss_thr: 0.2828 loss_db: 0.0698 loss: 0.7451 2022/08/30 17:45:41 - mmengine - INFO - Epoch(train) [825][45/63] lr: 2.4592e-03 eta: 8:00:37 time: 0.9235 data_time: 0.0212 memory: 16201 loss_prob: 0.4139 loss_thr: 0.2874 loss_db: 0.0720 loss: 0.7732 2022/08/30 17:45:47 - mmengine - INFO - Epoch(train) [825][50/63] lr: 2.4592e-03 eta: 8:00:25 time: 1.1128 data_time: 0.0416 memory: 16201 loss_prob: 0.4351 loss_thr: 0.3065 loss_db: 0.0759 loss: 0.8176 2022/08/30 17:45:52 - mmengine - INFO - Epoch(train) [825][55/63] lr: 2.4592e-03 eta: 8:00:25 time: 1.1018 data_time: 0.0365 memory: 16201 loss_prob: 0.4227 loss_thr: 0.3062 loss_db: 0.0739 loss: 0.8029 2022/08/30 17:45:57 - mmengine - INFO - Epoch(train) [825][60/63] lr: 2.4592e-03 eta: 8:00:12 time: 1.0153 data_time: 0.0319 memory: 16201 loss_prob: 0.4310 loss_thr: 0.3045 loss_db: 0.0748 loss: 0.8103 2022/08/30 17:46:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:46:08 - mmengine - INFO - Epoch(train) [826][5/63] lr: 2.4533e-03 eta: 8:00:12 time: 1.3024 data_time: 0.2610 memory: 16201 loss_prob: 0.4158 loss_thr: 0.2923 loss_db: 0.0744 loss: 0.7825 2022/08/30 17:46:15 - mmengine - INFO - Epoch(train) [826][10/63] lr: 2.4533e-03 eta: 7:59:55 time: 1.4496 data_time: 0.2809 memory: 16201 loss_prob: 0.4211 loss_thr: 0.2930 loss_db: 0.0743 loss: 0.7884 2022/08/30 17:46:20 - mmengine - INFO - Epoch(train) [826][15/63] lr: 2.4533e-03 eta: 7:59:55 time: 1.1942 data_time: 0.0398 memory: 16201 loss_prob: 0.4363 loss_thr: 0.2900 loss_db: 0.0757 loss: 0.8020 2022/08/30 17:46:24 - mmengine - INFO - Epoch(train) [826][20/63] lr: 2.4533e-03 eta: 7:59:42 time: 0.9682 data_time: 0.0321 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2724 loss_db: 0.0683 loss: 0.7253 2022/08/30 17:46:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:46:29 - mmengine - INFO - Epoch(train) [826][25/63] lr: 2.4533e-03 eta: 7:59:42 time: 0.8866 data_time: 0.0420 memory: 16201 loss_prob: 0.3469 loss_thr: 0.2637 loss_db: 0.0616 loss: 0.6722 2022/08/30 17:46:33 - mmengine - INFO - Epoch(train) [826][30/63] lr: 2.4533e-03 eta: 7:59:28 time: 0.8866 data_time: 0.0255 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2588 loss_db: 0.0631 loss: 0.6842 2022/08/30 17:46:38 - mmengine - INFO - Epoch(train) [826][35/63] lr: 2.4533e-03 eta: 7:59:28 time: 0.8841 data_time: 0.0285 memory: 16201 loss_prob: 0.4198 loss_thr: 0.2791 loss_db: 0.0732 loss: 0.7721 2022/08/30 17:46:42 - mmengine - INFO - Epoch(train) [826][40/63] lr: 2.4533e-03 eta: 7:59:14 time: 0.8422 data_time: 0.0312 memory: 16201 loss_prob: 0.4318 loss_thr: 0.2994 loss_db: 0.0756 loss: 0.8068 2022/08/30 17:46:48 - mmengine - INFO - Epoch(train) [826][45/63] lr: 2.4533e-03 eta: 7:59:14 time: 1.0067 data_time: 0.0719 memory: 16201 loss_prob: 0.4185 loss_thr: 0.2886 loss_db: 0.0713 loss: 0.7784 2022/08/30 17:46:54 - mmengine - INFO - Epoch(train) [826][50/63] lr: 2.4533e-03 eta: 7:59:02 time: 1.1860 data_time: 0.0881 memory: 16201 loss_prob: 0.4139 loss_thr: 0.2841 loss_db: 0.0712 loss: 0.7691 2022/08/30 17:46:58 - mmengine - INFO - Epoch(train) [826][55/63] lr: 2.4533e-03 eta: 7:59:02 time: 1.0197 data_time: 0.0323 memory: 16201 loss_prob: 0.3907 loss_thr: 0.2800 loss_db: 0.0689 loss: 0.7396 2022/08/30 17:47:03 - mmengine - INFO - Epoch(train) [826][60/63] lr: 2.4533e-03 eta: 7:58:48 time: 0.8877 data_time: 0.0361 memory: 16201 loss_prob: 0.3739 loss_thr: 0.2640 loss_db: 0.0656 loss: 0.7036 2022/08/30 17:47:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:47:12 - mmengine - INFO - Epoch(train) [827][5/63] lr: 2.4474e-03 eta: 7:58:48 time: 1.1614 data_time: 0.2522 memory: 16201 loss_prob: 0.3955 loss_thr: 0.2688 loss_db: 0.0686 loss: 0.7328 2022/08/30 17:47:18 - mmengine - INFO - Epoch(train) [827][10/63] lr: 2.4474e-03 eta: 7:58:31 time: 1.3191 data_time: 0.2731 memory: 16201 loss_prob: 0.3997 loss_thr: 0.2737 loss_db: 0.0701 loss: 0.7435 2022/08/30 17:47:23 - mmengine - INFO - Epoch(train) [827][15/63] lr: 2.4474e-03 eta: 7:58:31 time: 1.0675 data_time: 0.0416 memory: 16201 loss_prob: 0.4009 loss_thr: 0.2825 loss_db: 0.0701 loss: 0.7536 2022/08/30 17:47:28 - mmengine - INFO - Epoch(train) [827][20/63] lr: 2.4474e-03 eta: 7:58:18 time: 0.9524 data_time: 0.0365 memory: 16201 loss_prob: 0.4056 loss_thr: 0.2809 loss_db: 0.0699 loss: 0.7564 2022/08/30 17:47:32 - mmengine - INFO - Epoch(train) [827][25/63] lr: 2.4474e-03 eta: 7:58:18 time: 0.8681 data_time: 0.0326 memory: 16201 loss_prob: 0.3922 loss_thr: 0.2817 loss_db: 0.0686 loss: 0.7425 2022/08/30 17:47:37 - mmengine - INFO - Epoch(train) [827][30/63] lr: 2.4474e-03 eta: 7:58:04 time: 0.9346 data_time: 0.0233 memory: 16201 loss_prob: 0.3788 loss_thr: 0.2804 loss_db: 0.0671 loss: 0.7262 2022/08/30 17:47:41 - mmengine - INFO - Epoch(train) [827][35/63] lr: 2.4474e-03 eta: 7:58:04 time: 0.9486 data_time: 0.0339 memory: 16201 loss_prob: 0.3516 loss_thr: 0.2644 loss_db: 0.0613 loss: 0.6773 2022/08/30 17:47:47 - mmengine - INFO - Epoch(train) [827][40/63] lr: 2.4474e-03 eta: 7:57:51 time: 1.0410 data_time: 0.0278 memory: 16201 loss_prob: 0.3477 loss_thr: 0.2692 loss_db: 0.0624 loss: 0.6793 2022/08/30 17:47:52 - mmengine - INFO - Epoch(train) [827][45/63] lr: 2.4474e-03 eta: 7:57:51 time: 1.1049 data_time: 0.0380 memory: 16201 loss_prob: 0.3670 loss_thr: 0.2732 loss_db: 0.0649 loss: 0.7052 2022/08/30 17:47:57 - mmengine - INFO - Epoch(train) [827][50/63] lr: 2.4474e-03 eta: 7:57:38 time: 0.9785 data_time: 0.0444 memory: 16201 loss_prob: 0.3766 loss_thr: 0.2712 loss_db: 0.0648 loss: 0.7126 2022/08/30 17:48:02 - mmengine - INFO - Epoch(train) [827][55/63] lr: 2.4474e-03 eta: 7:57:38 time: 0.9912 data_time: 0.0286 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2575 loss_db: 0.0622 loss: 0.6644 2022/08/30 17:48:10 - mmengine - INFO - Epoch(train) [827][60/63] lr: 2.4474e-03 eta: 7:57:26 time: 1.2518 data_time: 0.0425 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2644 loss_db: 0.0598 loss: 0.6581 2022/08/30 17:48:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:48:18 - mmengine - INFO - Epoch(train) [828][5/63] lr: 2.4415e-03 eta: 7:57:26 time: 1.0854 data_time: 0.2196 memory: 16201 loss_prob: 0.3173 loss_thr: 0.2441 loss_db: 0.0556 loss: 0.6169 2022/08/30 17:48:22 - mmengine - INFO - Epoch(train) [828][10/63] lr: 2.4415e-03 eta: 7:57:08 time: 1.0568 data_time: 0.2301 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2678 loss_db: 0.0654 loss: 0.6967 2022/08/30 17:48:27 - mmengine - INFO - Epoch(train) [828][15/63] lr: 2.4415e-03 eta: 7:57:08 time: 0.9169 data_time: 0.0333 memory: 16201 loss_prob: 0.4080 loss_thr: 0.2906 loss_db: 0.0718 loss: 0.7703 2022/08/30 17:48:32 - mmengine - INFO - Epoch(train) [828][20/63] lr: 2.4415e-03 eta: 7:56:54 time: 0.9702 data_time: 0.0301 memory: 16201 loss_prob: 0.3696 loss_thr: 0.2695 loss_db: 0.0659 loss: 0.7050 2022/08/30 17:48:37 - mmengine - INFO - Epoch(train) [828][25/63] lr: 2.4415e-03 eta: 7:56:54 time: 1.0111 data_time: 0.0385 memory: 16201 loss_prob: 0.3774 loss_thr: 0.2695 loss_db: 0.0676 loss: 0.7145 2022/08/30 17:48:42 - mmengine - INFO - Epoch(train) [828][30/63] lr: 2.4415e-03 eta: 7:56:41 time: 1.0252 data_time: 0.0312 memory: 16201 loss_prob: 0.4270 loss_thr: 0.3070 loss_db: 0.0754 loss: 0.8094 2022/08/30 17:48:47 - mmengine - INFO - Epoch(train) [828][35/63] lr: 2.4415e-03 eta: 7:56:41 time: 1.0221 data_time: 0.0293 memory: 16201 loss_prob: 0.4575 loss_thr: 0.3258 loss_db: 0.0809 loss: 0.8643 2022/08/30 17:48:52 - mmengine - INFO - Epoch(train) [828][40/63] lr: 2.4415e-03 eta: 7:56:28 time: 0.9598 data_time: 0.0298 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2820 loss_db: 0.0695 loss: 0.7437 2022/08/30 17:48:56 - mmengine - INFO - Epoch(train) [828][45/63] lr: 2.4415e-03 eta: 7:56:28 time: 0.8486 data_time: 0.0304 memory: 16201 loss_prob: 0.3686 loss_thr: 0.2595 loss_db: 0.0639 loss: 0.6920 2022/08/30 17:49:00 - mmengine - INFO - Epoch(train) [828][50/63] lr: 2.4415e-03 eta: 7:56:14 time: 0.8057 data_time: 0.0363 memory: 16201 loss_prob: 0.3994 loss_thr: 0.2680 loss_db: 0.0697 loss: 0.7372 2022/08/30 17:49:05 - mmengine - INFO - Epoch(train) [828][55/63] lr: 2.4415e-03 eta: 7:56:14 time: 0.8611 data_time: 0.0329 memory: 16201 loss_prob: 0.4163 loss_thr: 0.2916 loss_db: 0.0732 loss: 0.7812 2022/08/30 17:49:10 - mmengine - INFO - Epoch(train) [828][60/63] lr: 2.4415e-03 eta: 7:56:01 time: 1.0154 data_time: 0.0362 memory: 16201 loss_prob: 0.4383 loss_thr: 0.3138 loss_db: 0.0779 loss: 0.8300 2022/08/30 17:49:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:49:22 - mmengine - INFO - Epoch(train) [829][5/63] lr: 2.4356e-03 eta: 7:56:01 time: 1.4393 data_time: 0.2911 memory: 16201 loss_prob: 0.4100 loss_thr: 0.2882 loss_db: 0.0719 loss: 0.7701 2022/08/30 17:49:28 - mmengine - INFO - Epoch(train) [829][10/63] lr: 2.4356e-03 eta: 7:55:44 time: 1.4506 data_time: 0.3141 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2744 loss_db: 0.0644 loss: 0.7039 2022/08/30 17:49:34 - mmengine - INFO - Epoch(train) [829][15/63] lr: 2.4356e-03 eta: 7:55:44 time: 1.2120 data_time: 0.0433 memory: 16201 loss_prob: 0.3482 loss_thr: 0.2585 loss_db: 0.0619 loss: 0.6687 2022/08/30 17:49:39 - mmengine - INFO - Epoch(train) [829][20/63] lr: 2.4356e-03 eta: 7:55:32 time: 1.1144 data_time: 0.0289 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2592 loss_db: 0.0630 loss: 0.6727 2022/08/30 17:49:45 - mmengine - INFO - Epoch(train) [829][25/63] lr: 2.4356e-03 eta: 7:55:32 time: 1.0929 data_time: 0.0410 memory: 16201 loss_prob: 0.4062 loss_thr: 0.2906 loss_db: 0.0692 loss: 0.7660 2022/08/30 17:49:52 - mmengine - INFO - Epoch(train) [829][30/63] lr: 2.4356e-03 eta: 7:55:20 time: 1.2135 data_time: 0.0278 memory: 16201 loss_prob: 0.3769 loss_thr: 0.2762 loss_db: 0.0640 loss: 0.7171 2022/08/30 17:49:58 - mmengine - INFO - Epoch(train) [829][35/63] lr: 2.4356e-03 eta: 7:55:20 time: 1.2457 data_time: 0.0328 memory: 16201 loss_prob: 0.3559 loss_thr: 0.2607 loss_db: 0.0646 loss: 0.6811 2022/08/30 17:50:03 - mmengine - INFO - Epoch(train) [829][40/63] lr: 2.4356e-03 eta: 7:55:07 time: 1.1244 data_time: 0.0336 memory: 16201 loss_prob: 0.4279 loss_thr: 0.2842 loss_db: 0.0769 loss: 0.7891 2022/08/30 17:50:08 - mmengine - INFO - Epoch(train) [829][45/63] lr: 2.4356e-03 eta: 7:55:07 time: 1.0067 data_time: 0.0347 memory: 16201 loss_prob: 0.4727 loss_thr: 0.3202 loss_db: 0.0818 loss: 0.8747 2022/08/30 17:50:12 - mmengine - INFO - Epoch(train) [829][50/63] lr: 2.4356e-03 eta: 7:54:53 time: 0.9097 data_time: 0.0448 memory: 16201 loss_prob: 0.4628 loss_thr: 0.3335 loss_db: 0.0810 loss: 0.8773 2022/08/30 17:50:16 - mmengine - INFO - Epoch(train) [829][55/63] lr: 2.4356e-03 eta: 7:54:53 time: 0.8139 data_time: 0.0252 memory: 16201 loss_prob: 0.3935 loss_thr: 0.2814 loss_db: 0.0708 loss: 0.7457 2022/08/30 17:50:20 - mmengine - INFO - Epoch(train) [829][60/63] lr: 2.4356e-03 eta: 7:54:40 time: 0.8391 data_time: 0.0233 memory: 16201 loss_prob: 0.3545 loss_thr: 0.2563 loss_db: 0.0634 loss: 0.6741 2022/08/30 17:50:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:50:29 - mmengine - INFO - Epoch(train) [830][5/63] lr: 2.4297e-03 eta: 7:54:40 time: 1.0223 data_time: 0.2417 memory: 16201 loss_prob: 0.3733 loss_thr: 0.2671 loss_db: 0.0653 loss: 0.7057 2022/08/30 17:50:33 - mmengine - INFO - Epoch(train) [830][10/63] lr: 2.4297e-03 eta: 7:54:22 time: 1.0953 data_time: 0.2783 memory: 16201 loss_prob: 0.3823 loss_thr: 0.2848 loss_db: 0.0659 loss: 0.7330 2022/08/30 17:50:37 - mmengine - INFO - Epoch(train) [830][15/63] lr: 2.4297e-03 eta: 7:54:22 time: 0.8569 data_time: 0.0646 memory: 16201 loss_prob: 0.3821 loss_thr: 0.2803 loss_db: 0.0680 loss: 0.7305 2022/08/30 17:50:42 - mmengine - INFO - Epoch(train) [830][20/63] lr: 2.4297e-03 eta: 7:54:08 time: 0.8147 data_time: 0.0317 memory: 16201 loss_prob: 0.3871 loss_thr: 0.2707 loss_db: 0.0690 loss: 0.7268 2022/08/30 17:50:46 - mmengine - INFO - Epoch(train) [830][25/63] lr: 2.4297e-03 eta: 7:54:08 time: 0.8749 data_time: 0.0316 memory: 16201 loss_prob: 0.4155 loss_thr: 0.2956 loss_db: 0.0739 loss: 0.7851 2022/08/30 17:50:52 - mmengine - INFO - Epoch(train) [830][30/63] lr: 2.4297e-03 eta: 7:53:54 time: 1.0209 data_time: 0.0299 memory: 16201 loss_prob: 0.3932 loss_thr: 0.2902 loss_db: 0.0702 loss: 0.7537 2022/08/30 17:50:58 - mmengine - INFO - Epoch(train) [830][35/63] lr: 2.4297e-03 eta: 7:53:54 time: 1.1315 data_time: 0.0341 memory: 16201 loss_prob: 0.3790 loss_thr: 0.2748 loss_db: 0.0681 loss: 0.7219 2022/08/30 17:51:03 - mmengine - INFO - Epoch(train) [830][40/63] lr: 2.4297e-03 eta: 7:53:42 time: 1.1192 data_time: 0.0348 memory: 16201 loss_prob: 0.3769 loss_thr: 0.2739 loss_db: 0.0676 loss: 0.7184 2022/08/30 17:51:09 - mmengine - INFO - Epoch(train) [830][45/63] lr: 2.4297e-03 eta: 7:53:42 time: 1.1375 data_time: 0.0454 memory: 16201 loss_prob: 0.3659 loss_thr: 0.2674 loss_db: 0.0658 loss: 0.6991 2022/08/30 17:51:15 - mmengine - INFO - Epoch(train) [830][50/63] lr: 2.4297e-03 eta: 7:53:29 time: 1.1816 data_time: 0.0509 memory: 16201 loss_prob: 0.3983 loss_thr: 0.2809 loss_db: 0.0705 loss: 0.7497 2022/08/30 17:51:20 - mmengine - INFO - Epoch(train) [830][55/63] lr: 2.4297e-03 eta: 7:53:29 time: 1.0787 data_time: 0.0335 memory: 16201 loss_prob: 0.4068 loss_thr: 0.2821 loss_db: 0.0709 loss: 0.7597 2022/08/30 17:51:24 - mmengine - INFO - Epoch(train) [830][60/63] lr: 2.4297e-03 eta: 7:53:16 time: 0.9363 data_time: 0.0309 memory: 16201 loss_prob: 0.3856 loss_thr: 0.2762 loss_db: 0.0686 loss: 0.7304 2022/08/30 17:51:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:51:33 - mmengine - INFO - Epoch(train) [831][5/63] lr: 2.4238e-03 eta: 7:53:16 time: 1.0617 data_time: 0.2336 memory: 16201 loss_prob: 0.3409 loss_thr: 0.2517 loss_db: 0.0621 loss: 0.6546 2022/08/30 17:51:37 - mmengine - INFO - Epoch(train) [831][10/63] lr: 2.4238e-03 eta: 7:52:58 time: 1.0986 data_time: 0.2465 memory: 16201 loss_prob: 0.3661 loss_thr: 0.2721 loss_db: 0.0651 loss: 0.7033 2022/08/30 17:51:43 - mmengine - INFO - Epoch(train) [831][15/63] lr: 2.4238e-03 eta: 7:52:58 time: 0.9600 data_time: 0.0298 memory: 16201 loss_prob: 0.4075 loss_thr: 0.2909 loss_db: 0.0718 loss: 0.7702 2022/08/30 17:51:48 - mmengine - INFO - Epoch(train) [831][20/63] lr: 2.4238e-03 eta: 7:52:45 time: 1.0377 data_time: 0.0254 memory: 16201 loss_prob: 0.3874 loss_thr: 0.2775 loss_db: 0.0687 loss: 0.7336 2022/08/30 17:51:53 - mmengine - INFO - Epoch(train) [831][25/63] lr: 2.4238e-03 eta: 7:52:45 time: 1.0852 data_time: 0.0443 memory: 16201 loss_prob: 0.3499 loss_thr: 0.2559 loss_db: 0.0624 loss: 0.6682 2022/08/30 17:51:59 - mmengine - INFO - Epoch(train) [831][30/63] lr: 2.4238e-03 eta: 7:52:32 time: 1.0971 data_time: 0.0387 memory: 16201 loss_prob: 0.3633 loss_thr: 0.2671 loss_db: 0.0650 loss: 0.6953 2022/08/30 17:52:05 - mmengine - INFO - Epoch(train) [831][35/63] lr: 2.4238e-03 eta: 7:52:32 time: 1.1591 data_time: 0.0395 memory: 16201 loss_prob: 0.3871 loss_thr: 0.2874 loss_db: 0.0686 loss: 0.7430 2022/08/30 17:52:11 - mmengine - INFO - Epoch(train) [831][40/63] lr: 2.4238e-03 eta: 7:52:20 time: 1.1722 data_time: 0.0391 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2850 loss_db: 0.0707 loss: 0.7521 2022/08/30 17:52:16 - mmengine - INFO - Epoch(train) [831][45/63] lr: 2.4238e-03 eta: 7:52:20 time: 1.0811 data_time: 0.0336 memory: 16201 loss_prob: 0.4005 loss_thr: 0.2674 loss_db: 0.0707 loss: 0.7386 2022/08/30 17:52:22 - mmengine - INFO - Epoch(train) [831][50/63] lr: 2.4238e-03 eta: 7:52:07 time: 1.0973 data_time: 0.0401 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2724 loss_db: 0.0691 loss: 0.7451 2022/08/30 17:52:27 - mmengine - INFO - Epoch(train) [831][55/63] lr: 2.4238e-03 eta: 7:52:07 time: 1.1285 data_time: 0.0328 memory: 16201 loss_prob: 0.3825 loss_thr: 0.2785 loss_db: 0.0687 loss: 0.7297 2022/08/30 17:52:33 - mmengine - INFO - Epoch(train) [831][60/63] lr: 2.4238e-03 eta: 7:51:55 time: 1.1124 data_time: 0.0437 memory: 16201 loss_prob: 0.3519 loss_thr: 0.2618 loss_db: 0.0639 loss: 0.6777 2022/08/30 17:52:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:52:43 - mmengine - INFO - Epoch(train) [832][5/63] lr: 2.4179e-03 eta: 7:51:55 time: 1.2884 data_time: 0.2410 memory: 16201 loss_prob: 0.3778 loss_thr: 0.2603 loss_db: 0.0657 loss: 0.7038 2022/08/30 17:52:47 - mmengine - INFO - Epoch(train) [832][10/63] lr: 2.4179e-03 eta: 7:51:37 time: 1.1297 data_time: 0.2477 memory: 16201 loss_prob: 0.3867 loss_thr: 0.2804 loss_db: 0.0681 loss: 0.7351 2022/08/30 17:52:51 - mmengine - INFO - Epoch(train) [832][15/63] lr: 2.4179e-03 eta: 7:51:37 time: 0.8121 data_time: 0.0289 memory: 16201 loss_prob: 0.3683 loss_thr: 0.2750 loss_db: 0.0655 loss: 0.7088 2022/08/30 17:52:57 - mmengine - INFO - Epoch(train) [832][20/63] lr: 2.4179e-03 eta: 7:51:23 time: 0.9236 data_time: 0.0275 memory: 16201 loss_prob: 0.3662 loss_thr: 0.2658 loss_db: 0.0658 loss: 0.6978 2022/08/30 17:53:01 - mmengine - INFO - Epoch(train) [832][25/63] lr: 2.4179e-03 eta: 7:51:23 time: 0.9137 data_time: 0.0345 memory: 16201 loss_prob: 0.4054 loss_thr: 0.2854 loss_db: 0.0738 loss: 0.7646 2022/08/30 17:53:04 - mmengine - INFO - Epoch(train) [832][30/63] lr: 2.4179e-03 eta: 7:51:09 time: 0.7869 data_time: 0.0269 memory: 16201 loss_prob: 0.4382 loss_thr: 0.2951 loss_db: 0.0771 loss: 0.8105 2022/08/30 17:53:09 - mmengine - INFO - Epoch(train) [832][35/63] lr: 2.4179e-03 eta: 7:51:09 time: 0.8531 data_time: 0.0237 memory: 16201 loss_prob: 0.4274 loss_thr: 0.3000 loss_db: 0.0728 loss: 0.8002 2022/08/30 17:53:13 - mmengine - INFO - Epoch(train) [832][40/63] lr: 2.4179e-03 eta: 7:50:55 time: 0.8654 data_time: 0.0324 memory: 16201 loss_prob: 0.4052 loss_thr: 0.2853 loss_db: 0.0707 loss: 0.7612 2022/08/30 17:53:17 - mmengine - INFO - Epoch(train) [832][45/63] lr: 2.4179e-03 eta: 7:50:55 time: 0.7918 data_time: 0.0307 memory: 16201 loss_prob: 0.3901 loss_thr: 0.2755 loss_db: 0.0699 loss: 0.7355 2022/08/30 17:53:22 - mmengine - INFO - Epoch(train) [832][50/63] lr: 2.4179e-03 eta: 7:50:42 time: 0.8492 data_time: 0.0241 memory: 16201 loss_prob: 0.3954 loss_thr: 0.2883 loss_db: 0.0691 loss: 0.7529 2022/08/30 17:53:28 - mmengine - INFO - Epoch(train) [832][55/63] lr: 2.4179e-03 eta: 7:50:42 time: 1.0437 data_time: 0.0323 memory: 16201 loss_prob: 0.4018 loss_thr: 0.2852 loss_db: 0.0693 loss: 0.7563 2022/08/30 17:53:33 - mmengine - INFO - Epoch(train) [832][60/63] lr: 2.4179e-03 eta: 7:50:29 time: 1.1424 data_time: 0.0410 memory: 16201 loss_prob: 0.4038 loss_thr: 0.2904 loss_db: 0.0721 loss: 0.7663 2022/08/30 17:53:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:53:44 - mmengine - INFO - Epoch(train) [833][5/63] lr: 2.4120e-03 eta: 7:50:29 time: 1.2960 data_time: 0.2781 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2589 loss_db: 0.0637 loss: 0.6862 2022/08/30 17:53:50 - mmengine - INFO - Epoch(train) [833][10/63] lr: 2.4120e-03 eta: 7:50:12 time: 1.3210 data_time: 0.2851 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2577 loss_db: 0.0610 loss: 0.6692 2022/08/30 17:53:56 - mmengine - INFO - Epoch(train) [833][15/63] lr: 2.4120e-03 eta: 7:50:12 time: 1.1875 data_time: 0.0511 memory: 16201 loss_prob: 0.3397 loss_thr: 0.2559 loss_db: 0.0610 loss: 0.6566 2022/08/30 17:54:00 - mmengine - INFO - Epoch(train) [833][20/63] lr: 2.4120e-03 eta: 7:49:59 time: 1.0275 data_time: 0.0331 memory: 16201 loss_prob: 0.3710 loss_thr: 0.2657 loss_db: 0.0678 loss: 0.7045 2022/08/30 17:54:04 - mmengine - INFO - Epoch(train) [833][25/63] lr: 2.4120e-03 eta: 7:49:59 time: 0.8474 data_time: 0.0402 memory: 16201 loss_prob: 0.3903 loss_thr: 0.2698 loss_db: 0.0669 loss: 0.7270 2022/08/30 17:54:08 - mmengine - INFO - Epoch(train) [833][30/63] lr: 2.4120e-03 eta: 7:49:45 time: 0.8423 data_time: 0.0232 memory: 16201 loss_prob: 0.3686 loss_thr: 0.2708 loss_db: 0.0622 loss: 0.7015 2022/08/30 17:54:13 - mmengine - INFO - Epoch(train) [833][35/63] lr: 2.4120e-03 eta: 7:49:45 time: 0.8344 data_time: 0.0254 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2691 loss_db: 0.0641 loss: 0.6925 2022/08/30 17:54:17 - mmengine - INFO - Epoch(train) [833][40/63] lr: 2.4120e-03 eta: 7:49:32 time: 0.8625 data_time: 0.0282 memory: 16201 loss_prob: 0.3696 loss_thr: 0.2695 loss_db: 0.0669 loss: 0.7060 2022/08/30 17:54:22 - mmengine - INFO - Epoch(train) [833][45/63] lr: 2.4120e-03 eta: 7:49:32 time: 0.9479 data_time: 0.0268 memory: 16201 loss_prob: 0.3668 loss_thr: 0.2689 loss_db: 0.0663 loss: 0.7019 2022/08/30 17:54:28 - mmengine - INFO - Epoch(train) [833][50/63] lr: 2.4120e-03 eta: 7:49:19 time: 1.0467 data_time: 0.0484 memory: 16201 loss_prob: 0.4003 loss_thr: 0.2839 loss_db: 0.0705 loss: 0.7547 2022/08/30 17:54:33 - mmengine - INFO - Epoch(train) [833][55/63] lr: 2.4120e-03 eta: 7:49:19 time: 1.0587 data_time: 0.0366 memory: 16201 loss_prob: 0.4330 loss_thr: 0.2978 loss_db: 0.0763 loss: 0.8071 2022/08/30 17:54:38 - mmengine - INFO - Epoch(train) [833][60/63] lr: 2.4120e-03 eta: 7:49:06 time: 1.0749 data_time: 0.0358 memory: 16201 loss_prob: 0.4483 loss_thr: 0.3021 loss_db: 0.0793 loss: 0.8297 2022/08/30 17:54:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:54:47 - mmengine - INFO - Epoch(train) [834][5/63] lr: 2.4061e-03 eta: 7:49:06 time: 1.0517 data_time: 0.2162 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2635 loss_db: 0.0647 loss: 0.6919 2022/08/30 17:54:51 - mmengine - INFO - Epoch(train) [834][10/63] lr: 2.4061e-03 eta: 7:48:48 time: 1.0508 data_time: 0.2142 memory: 16201 loss_prob: 0.3658 loss_thr: 0.2610 loss_db: 0.0636 loss: 0.6904 2022/08/30 17:54:57 - mmengine - INFO - Epoch(train) [834][15/63] lr: 2.4061e-03 eta: 7:48:48 time: 0.9891 data_time: 0.0356 memory: 16201 loss_prob: 0.3885 loss_thr: 0.2713 loss_db: 0.0683 loss: 0.7280 2022/08/30 17:55:02 - mmengine - INFO - Epoch(train) [834][20/63] lr: 2.4061e-03 eta: 7:48:35 time: 1.0671 data_time: 0.0338 memory: 16201 loss_prob: 0.3922 loss_thr: 0.2737 loss_db: 0.0707 loss: 0.7366 2022/08/30 17:55:08 - mmengine - INFO - Epoch(train) [834][25/63] lr: 2.4061e-03 eta: 7:48:35 time: 1.1170 data_time: 0.0429 memory: 16201 loss_prob: 0.3862 loss_thr: 0.2717 loss_db: 0.0685 loss: 0.7263 2022/08/30 17:55:13 - mmengine - INFO - Epoch(train) [834][30/63] lr: 2.4061e-03 eta: 7:48:22 time: 1.1615 data_time: 0.0460 memory: 16201 loss_prob: 0.3716 loss_thr: 0.2756 loss_db: 0.0657 loss: 0.7128 2022/08/30 17:55:18 - mmengine - INFO - Epoch(train) [834][35/63] lr: 2.4061e-03 eta: 7:48:22 time: 1.0415 data_time: 0.0374 memory: 16201 loss_prob: 0.3727 loss_thr: 0.2764 loss_db: 0.0663 loss: 0.7154 2022/08/30 17:55:22 - mmengine - INFO - Epoch(train) [834][40/63] lr: 2.4061e-03 eta: 7:48:09 time: 0.8884 data_time: 0.0261 memory: 16201 loss_prob: 0.3700 loss_thr: 0.2630 loss_db: 0.0647 loss: 0.6977 2022/08/30 17:55:27 - mmengine - INFO - Epoch(train) [834][45/63] lr: 2.4061e-03 eta: 7:48:09 time: 0.9091 data_time: 0.0198 memory: 16201 loss_prob: 0.3480 loss_thr: 0.2592 loss_db: 0.0602 loss: 0.6674 2022/08/30 17:55:32 - mmengine - INFO - Epoch(train) [834][50/63] lr: 2.4061e-03 eta: 7:47:56 time: 0.9706 data_time: 0.0327 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2738 loss_db: 0.0646 loss: 0.7007 2022/08/30 17:55:38 - mmengine - INFO - Epoch(train) [834][55/63] lr: 2.4061e-03 eta: 7:47:56 time: 1.0480 data_time: 0.0376 memory: 16201 loss_prob: 0.3878 loss_thr: 0.2860 loss_db: 0.0698 loss: 0.7436 2022/08/30 17:55:44 - mmengine - INFO - Epoch(train) [834][60/63] lr: 2.4061e-03 eta: 7:47:43 time: 1.2096 data_time: 0.0347 memory: 16201 loss_prob: 0.4118 loss_thr: 0.3052 loss_db: 0.0739 loss: 0.7909 2022/08/30 17:55:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:55:54 - mmengine - INFO - Epoch(train) [835][5/63] lr: 2.4001e-03 eta: 7:47:43 time: 1.2289 data_time: 0.2564 memory: 16201 loss_prob: 0.4110 loss_thr: 0.2968 loss_db: 0.0723 loss: 0.7801 2022/08/30 17:55:58 - mmengine - INFO - Epoch(train) [835][10/63] lr: 2.4001e-03 eta: 7:47:25 time: 1.1009 data_time: 0.2576 memory: 16201 loss_prob: 0.3844 loss_thr: 0.2694 loss_db: 0.0686 loss: 0.7224 2022/08/30 17:56:02 - mmengine - INFO - Epoch(train) [835][15/63] lr: 2.4001e-03 eta: 7:47:25 time: 0.8174 data_time: 0.0291 memory: 16201 loss_prob: 0.3864 loss_thr: 0.2888 loss_db: 0.0703 loss: 0.7455 2022/08/30 17:56:07 - mmengine - INFO - Epoch(train) [835][20/63] lr: 2.4001e-03 eta: 7:47:12 time: 0.8651 data_time: 0.0378 memory: 16201 loss_prob: 0.4114 loss_thr: 0.3006 loss_db: 0.0728 loss: 0.7849 2022/08/30 17:56:13 - mmengine - INFO - Epoch(train) [835][25/63] lr: 2.4001e-03 eta: 7:47:12 time: 1.0260 data_time: 0.0548 memory: 16201 loss_prob: 0.3889 loss_thr: 0.2785 loss_db: 0.0678 loss: 0.7352 2022/08/30 17:56:18 - mmengine - INFO - Epoch(train) [835][30/63] lr: 2.4001e-03 eta: 7:46:59 time: 1.1314 data_time: 0.0276 memory: 16201 loss_prob: 0.3511 loss_thr: 0.2576 loss_db: 0.0637 loss: 0.6723 2022/08/30 17:56:23 - mmengine - INFO - Epoch(train) [835][35/63] lr: 2.4001e-03 eta: 7:46:59 time: 1.0346 data_time: 0.0339 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2539 loss_db: 0.0623 loss: 0.6628 2022/08/30 17:56:27 - mmengine - INFO - Epoch(train) [835][40/63] lr: 2.4001e-03 eta: 7:46:46 time: 0.8879 data_time: 0.0359 memory: 16201 loss_prob: 0.3390 loss_thr: 0.2505 loss_db: 0.0588 loss: 0.6484 2022/08/30 17:56:31 - mmengine - INFO - Epoch(train) [835][45/63] lr: 2.4001e-03 eta: 7:46:46 time: 0.8407 data_time: 0.0225 memory: 16201 loss_prob: 0.3451 loss_thr: 0.2511 loss_db: 0.0602 loss: 0.6564 2022/08/30 17:56:37 - mmengine - INFO - Epoch(train) [835][50/63] lr: 2.4001e-03 eta: 7:46:32 time: 0.9435 data_time: 0.0390 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2725 loss_db: 0.0676 loss: 0.7172 2022/08/30 17:56:42 - mmengine - INFO - Epoch(train) [835][55/63] lr: 2.4001e-03 eta: 7:46:32 time: 1.0526 data_time: 0.0313 memory: 16201 loss_prob: 0.4061 loss_thr: 0.2945 loss_db: 0.0719 loss: 0.7725 2022/08/30 17:56:48 - mmengine - INFO - Epoch(train) [835][60/63] lr: 2.4001e-03 eta: 7:46:20 time: 1.1391 data_time: 0.0287 memory: 16201 loss_prob: 0.4094 loss_thr: 0.2957 loss_db: 0.0714 loss: 0.7764 2022/08/30 17:56:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:56:59 - mmengine - INFO - Epoch(train) [836][5/63] lr: 2.3942e-03 eta: 7:46:20 time: 1.2816 data_time: 0.2451 memory: 16201 loss_prob: 0.3747 loss_thr: 0.2680 loss_db: 0.0642 loss: 0.7069 2022/08/30 17:57:04 - mmengine - INFO - Epoch(train) [836][10/63] lr: 2.3942e-03 eta: 7:46:03 time: 1.3563 data_time: 0.2675 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2592 loss_db: 0.0633 loss: 0.6996 2022/08/30 17:57:09 - mmengine - INFO - Epoch(train) [836][15/63] lr: 2.3942e-03 eta: 7:46:03 time: 1.0465 data_time: 0.0352 memory: 16201 loss_prob: 0.3674 loss_thr: 0.2544 loss_db: 0.0653 loss: 0.6871 2022/08/30 17:57:14 - mmengine - INFO - Epoch(train) [836][20/63] lr: 2.3942e-03 eta: 7:45:50 time: 1.0101 data_time: 0.0312 memory: 16201 loss_prob: 0.3676 loss_thr: 0.2649 loss_db: 0.0646 loss: 0.6971 2022/08/30 17:57:18 - mmengine - INFO - Epoch(train) [836][25/63] lr: 2.3942e-03 eta: 7:45:50 time: 0.8846 data_time: 0.0339 memory: 16201 loss_prob: 0.4185 loss_thr: 0.2926 loss_db: 0.0718 loss: 0.7829 2022/08/30 17:57:22 - mmengine - INFO - Epoch(train) [836][30/63] lr: 2.3942e-03 eta: 7:45:36 time: 0.7726 data_time: 0.0230 memory: 16201 loss_prob: 0.4528 loss_thr: 0.3070 loss_db: 0.0791 loss: 0.8389 2022/08/30 17:57:26 - mmengine - INFO - Epoch(train) [836][35/63] lr: 2.3942e-03 eta: 7:45:36 time: 0.8010 data_time: 0.0316 memory: 16201 loss_prob: 0.4024 loss_thr: 0.2901 loss_db: 0.0712 loss: 0.7637 2022/08/30 17:57:30 - mmengine - INFO - Epoch(train) [836][40/63] lr: 2.3942e-03 eta: 7:45:22 time: 0.8209 data_time: 0.0298 memory: 16201 loss_prob: 0.3392 loss_thr: 0.2531 loss_db: 0.0591 loss: 0.6514 2022/08/30 17:57:35 - mmengine - INFO - Epoch(train) [836][45/63] lr: 2.3942e-03 eta: 7:45:22 time: 0.8592 data_time: 0.0238 memory: 16201 loss_prob: 0.3452 loss_thr: 0.2620 loss_db: 0.0605 loss: 0.6677 2022/08/30 17:57:41 - mmengine - INFO - Epoch(train) [836][50/63] lr: 2.3942e-03 eta: 7:45:09 time: 1.0295 data_time: 0.0464 memory: 16201 loss_prob: 0.3897 loss_thr: 0.2910 loss_db: 0.0688 loss: 0.7494 2022/08/30 17:57:47 - mmengine - INFO - Epoch(train) [836][55/63] lr: 2.3942e-03 eta: 7:45:09 time: 1.1888 data_time: 0.0466 memory: 16201 loss_prob: 0.4057 loss_thr: 0.2824 loss_db: 0.0703 loss: 0.7584 2022/08/30 17:57:53 - mmengine - INFO - Epoch(train) [836][60/63] lr: 2.3942e-03 eta: 7:44:57 time: 1.2365 data_time: 0.0417 memory: 16201 loss_prob: 0.3884 loss_thr: 0.2774 loss_db: 0.0677 loss: 0.7336 2022/08/30 17:57:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:58:04 - mmengine - INFO - Epoch(train) [837][5/63] lr: 2.3883e-03 eta: 7:44:57 time: 1.2881 data_time: 0.2990 memory: 16201 loss_prob: 0.3774 loss_thr: 0.2738 loss_db: 0.0671 loss: 0.7182 2022/08/30 17:58:08 - mmengine - INFO - Epoch(train) [837][10/63] lr: 2.3883e-03 eta: 7:44:39 time: 1.1888 data_time: 0.3131 memory: 16201 loss_prob: 0.3388 loss_thr: 0.2496 loss_db: 0.0599 loss: 0.6483 2022/08/30 17:58:12 - mmengine - INFO - Epoch(train) [837][15/63] lr: 2.3883e-03 eta: 7:44:39 time: 0.8733 data_time: 0.0315 memory: 16201 loss_prob: 0.3575 loss_thr: 0.2600 loss_db: 0.0616 loss: 0.6791 2022/08/30 17:58:17 - mmengine - INFO - Epoch(train) [837][20/63] lr: 2.3883e-03 eta: 7:44:26 time: 0.8643 data_time: 0.0270 memory: 16201 loss_prob: 0.3875 loss_thr: 0.2747 loss_db: 0.0681 loss: 0.7303 2022/08/30 17:58:21 - mmengine - INFO - Epoch(train) [837][25/63] lr: 2.3883e-03 eta: 7:44:26 time: 0.8643 data_time: 0.0489 memory: 16201 loss_prob: 0.3711 loss_thr: 0.2685 loss_db: 0.0667 loss: 0.7063 2022/08/30 17:58:27 - mmengine - INFO - Epoch(train) [837][30/63] lr: 2.3883e-03 eta: 7:44:13 time: 1.0092 data_time: 0.0380 memory: 16201 loss_prob: 0.3494 loss_thr: 0.2586 loss_db: 0.0632 loss: 0.6712 2022/08/30 17:58:32 - mmengine - INFO - Epoch(train) [837][35/63] lr: 2.3883e-03 eta: 7:44:13 time: 1.1455 data_time: 0.0393 memory: 16201 loss_prob: 0.3675 loss_thr: 0.2705 loss_db: 0.0648 loss: 0.7028 2022/08/30 17:58:38 - mmengine - INFO - Epoch(train) [837][40/63] lr: 2.3883e-03 eta: 7:44:00 time: 1.1512 data_time: 0.0400 memory: 16201 loss_prob: 0.4126 loss_thr: 0.2939 loss_db: 0.0733 loss: 0.7798 2022/08/30 17:58:43 - mmengine - INFO - Epoch(train) [837][45/63] lr: 2.3883e-03 eta: 7:44:00 time: 1.0870 data_time: 0.0272 memory: 16201 loss_prob: 0.4339 loss_thr: 0.3055 loss_db: 0.0730 loss: 0.8124 2022/08/30 17:58:49 - mmengine - INFO - Epoch(train) [837][50/63] lr: 2.3883e-03 eta: 7:43:47 time: 1.0996 data_time: 0.0409 memory: 16201 loss_prob: 0.4270 loss_thr: 0.2872 loss_db: 0.0692 loss: 0.7834 2022/08/30 17:58:55 - mmengine - INFO - Epoch(train) [837][55/63] lr: 2.3883e-03 eta: 7:43:47 time: 1.1282 data_time: 0.0363 memory: 16201 loss_prob: 0.4007 loss_thr: 0.2743 loss_db: 0.0671 loss: 0.7420 2022/08/30 17:58:59 - mmengine - INFO - Epoch(train) [837][60/63] lr: 2.3883e-03 eta: 7:43:34 time: 0.9643 data_time: 0.0314 memory: 16201 loss_prob: 0.3854 loss_thr: 0.2771 loss_db: 0.0650 loss: 0.7275 2022/08/30 17:59:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 17:59:07 - mmengine - INFO - Epoch(train) [838][5/63] lr: 2.3824e-03 eta: 7:43:34 time: 0.9858 data_time: 0.1675 memory: 16201 loss_prob: 0.3914 loss_thr: 0.2705 loss_db: 0.0706 loss: 0.7325 2022/08/30 17:59:11 - mmengine - INFO - Epoch(train) [838][10/63] lr: 2.3824e-03 eta: 7:43:16 time: 1.0319 data_time: 0.1800 memory: 16201 loss_prob: 0.3890 loss_thr: 0.2642 loss_db: 0.0706 loss: 0.7237 2022/08/30 17:59:17 - mmengine - INFO - Epoch(train) [838][15/63] lr: 2.3824e-03 eta: 7:43:16 time: 0.9769 data_time: 0.0294 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2500 loss_db: 0.0654 loss: 0.6796 2022/08/30 17:59:22 - mmengine - INFO - Epoch(train) [838][20/63] lr: 2.3824e-03 eta: 7:43:03 time: 1.1165 data_time: 0.0374 memory: 16201 loss_prob: 0.3781 loss_thr: 0.2501 loss_db: 0.0658 loss: 0.6939 2022/08/30 17:59:28 - mmengine - INFO - Epoch(train) [838][25/63] lr: 2.3824e-03 eta: 7:43:03 time: 1.1279 data_time: 0.0412 memory: 16201 loss_prob: 0.4539 loss_thr: 0.2833 loss_db: 0.0772 loss: 0.8144 2022/08/30 17:59:34 - mmengine - INFO - Epoch(train) [838][30/63] lr: 2.3824e-03 eta: 7:42:51 time: 1.1431 data_time: 0.0434 memory: 16201 loss_prob: 0.4394 loss_thr: 0.2887 loss_db: 0.0767 loss: 0.8048 2022/08/30 17:59:39 - mmengine - INFO - Epoch(train) [838][35/63] lr: 2.3824e-03 eta: 7:42:51 time: 1.0578 data_time: 0.0564 memory: 16201 loss_prob: 0.3806 loss_thr: 0.2732 loss_db: 0.0688 loss: 0.7225 2022/08/30 17:59:43 - mmengine - INFO - Epoch(train) [838][40/63] lr: 2.3824e-03 eta: 7:42:38 time: 0.9397 data_time: 0.0354 memory: 16201 loss_prob: 0.3762 loss_thr: 0.2757 loss_db: 0.0657 loss: 0.7176 2022/08/30 17:59:48 - mmengine - INFO - Epoch(train) [838][45/63] lr: 2.3824e-03 eta: 7:42:38 time: 0.8817 data_time: 0.0293 memory: 16201 loss_prob: 0.3727 loss_thr: 0.2753 loss_db: 0.0641 loss: 0.7122 2022/08/30 17:59:52 - mmengine - INFO - Epoch(train) [838][50/63] lr: 2.3824e-03 eta: 7:42:24 time: 0.8430 data_time: 0.0416 memory: 16201 loss_prob: 0.4023 loss_thr: 0.2778 loss_db: 0.0724 loss: 0.7525 2022/08/30 17:59:56 - mmengine - INFO - Epoch(train) [838][55/63] lr: 2.3824e-03 eta: 7:42:24 time: 0.8597 data_time: 0.0283 memory: 16201 loss_prob: 0.4096 loss_thr: 0.2871 loss_db: 0.0736 loss: 0.7704 2022/08/30 18:00:08 - mmengine - INFO - Epoch(train) [838][60/63] lr: 2.3824e-03 eta: 7:42:13 time: 1.6174 data_time: 0.0310 memory: 16201 loss_prob: 0.3970 loss_thr: 0.2943 loss_db: 0.0690 loss: 0.7603 2022/08/30 18:00:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:00:20 - mmengine - INFO - Epoch(train) [839][5/63] lr: 2.3765e-03 eta: 7:42:13 time: 1.9892 data_time: 0.2772 memory: 16201 loss_prob: 0.4112 loss_thr: 0.3027 loss_db: 0.0731 loss: 0.7870 2022/08/30 18:00:26 - mmengine - INFO - Epoch(train) [839][10/63] lr: 2.3765e-03 eta: 7:41:57 time: 1.4083 data_time: 0.2721 memory: 16201 loss_prob: 0.3878 loss_thr: 0.2868 loss_db: 0.0692 loss: 0.7438 2022/08/30 18:00:30 - mmengine - INFO - Epoch(train) [839][15/63] lr: 2.3765e-03 eta: 7:41:57 time: 1.0907 data_time: 0.0322 memory: 16201 loss_prob: 0.3865 loss_thr: 0.2795 loss_db: 0.0678 loss: 0.7338 2022/08/30 18:00:36 - mmengine - INFO - Epoch(train) [839][20/63] lr: 2.3765e-03 eta: 7:41:44 time: 1.0524 data_time: 0.0296 memory: 16201 loss_prob: 0.4192 loss_thr: 0.2847 loss_db: 0.0723 loss: 0.7762 2022/08/30 18:00:42 - mmengine - INFO - Epoch(train) [839][25/63] lr: 2.3765e-03 eta: 7:41:44 time: 1.1210 data_time: 0.0452 memory: 16201 loss_prob: 0.4285 loss_thr: 0.3003 loss_db: 0.0744 loss: 0.8033 2022/08/30 18:00:46 - mmengine - INFO - Epoch(train) [839][30/63] lr: 2.3765e-03 eta: 7:41:31 time: 1.0190 data_time: 0.0367 memory: 16201 loss_prob: 0.3982 loss_thr: 0.2953 loss_db: 0.0706 loss: 0.7641 2022/08/30 18:00:51 - mmengine - INFO - Epoch(train) [839][35/63] lr: 2.3765e-03 eta: 7:41:31 time: 0.8932 data_time: 0.0281 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2749 loss_db: 0.0673 loss: 0.7180 2022/08/30 18:00:55 - mmengine - INFO - Epoch(train) [839][40/63] lr: 2.3765e-03 eta: 7:41:17 time: 0.8545 data_time: 0.0217 memory: 16201 loss_prob: 0.4005 loss_thr: 0.2729 loss_db: 0.0707 loss: 0.7441 2022/08/30 18:00:59 - mmengine - INFO - Epoch(train) [839][45/63] lr: 2.3765e-03 eta: 7:41:17 time: 0.8580 data_time: 0.0269 memory: 16201 loss_prob: 0.3825 loss_thr: 0.2698 loss_db: 0.0672 loss: 0.7195 2022/08/30 18:01:03 - mmengine - INFO - Epoch(train) [839][50/63] lr: 2.3765e-03 eta: 7:41:03 time: 0.8485 data_time: 0.0313 memory: 16201 loss_prob: 0.3595 loss_thr: 0.2629 loss_db: 0.0636 loss: 0.6859 2022/08/30 18:01:09 - mmengine - INFO - Epoch(train) [839][55/63] lr: 2.3765e-03 eta: 7:41:03 time: 0.9891 data_time: 0.0210 memory: 16201 loss_prob: 0.3899 loss_thr: 0.2668 loss_db: 0.0686 loss: 0.7253 2022/08/30 18:01:14 - mmengine - INFO - Epoch(train) [839][60/63] lr: 2.3765e-03 eta: 7:40:51 time: 1.0933 data_time: 0.0353 memory: 16201 loss_prob: 0.3746 loss_thr: 0.2584 loss_db: 0.0661 loss: 0.6991 2022/08/30 18:01:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:01:25 - mmengine - INFO - Epoch(train) [840][5/63] lr: 2.3705e-03 eta: 7:40:51 time: 1.3330 data_time: 0.2373 memory: 16201 loss_prob: 0.3661 loss_thr: 0.2777 loss_db: 0.0657 loss: 0.7094 2022/08/30 18:01:30 - mmengine - INFO - Epoch(train) [840][10/63] lr: 2.3705e-03 eta: 7:40:33 time: 1.2223 data_time: 0.2487 memory: 16201 loss_prob: 0.4224 loss_thr: 0.2914 loss_db: 0.0762 loss: 0.7899 2022/08/30 18:01:34 - mmengine - INFO - Epoch(train) [840][15/63] lr: 2.3705e-03 eta: 7:40:33 time: 0.8374 data_time: 0.0280 memory: 16201 loss_prob: 0.4180 loss_thr: 0.2849 loss_db: 0.0736 loss: 0.7766 2022/08/30 18:01:38 - mmengine - INFO - Epoch(train) [840][20/63] lr: 2.3705e-03 eta: 7:40:20 time: 0.8266 data_time: 0.0279 memory: 16201 loss_prob: 0.3561 loss_thr: 0.2645 loss_db: 0.0624 loss: 0.6830 2022/08/30 18:01:43 - mmengine - INFO - Epoch(train) [840][25/63] lr: 2.3705e-03 eta: 7:40:20 time: 0.8948 data_time: 0.0339 memory: 16201 loss_prob: 0.3786 loss_thr: 0.2709 loss_db: 0.0676 loss: 0.7171 2022/08/30 18:01:48 - mmengine - INFO - Epoch(train) [840][30/63] lr: 2.3705e-03 eta: 7:40:07 time: 0.9965 data_time: 0.0265 memory: 16201 loss_prob: 0.3648 loss_thr: 0.2564 loss_db: 0.0643 loss: 0.6855 2022/08/30 18:01:53 - mmengine - INFO - Epoch(train) [840][35/63] lr: 2.3705e-03 eta: 7:40:07 time: 1.0463 data_time: 0.0273 memory: 16201 loss_prob: 0.3870 loss_thr: 0.2704 loss_db: 0.0682 loss: 0.7257 2022/08/30 18:01:59 - mmengine - INFO - Epoch(train) [840][40/63] lr: 2.3705e-03 eta: 7:39:54 time: 1.0804 data_time: 0.0266 memory: 16201 loss_prob: 0.3945 loss_thr: 0.2777 loss_db: 0.0703 loss: 0.7425 2022/08/30 18:02:04 - mmengine - INFO - Epoch(train) [840][45/63] lr: 2.3705e-03 eta: 7:39:54 time: 1.0812 data_time: 0.0315 memory: 16201 loss_prob: 0.3609 loss_thr: 0.2634 loss_db: 0.0639 loss: 0.6882 2022/08/30 18:02:09 - mmengine - INFO - Epoch(train) [840][50/63] lr: 2.3705e-03 eta: 7:39:41 time: 1.0254 data_time: 0.0460 memory: 16201 loss_prob: 0.3689 loss_thr: 0.2681 loss_db: 0.0664 loss: 0.7034 2022/08/30 18:02:16 - mmengine - INFO - Epoch(train) [840][55/63] lr: 2.3705e-03 eta: 7:39:41 time: 1.1924 data_time: 0.0322 memory: 16201 loss_prob: 0.3934 loss_thr: 0.2758 loss_db: 0.0716 loss: 0.7408 2022/08/30 18:02:21 - mmengine - INFO - Epoch(train) [840][60/63] lr: 2.3705e-03 eta: 7:39:29 time: 1.2493 data_time: 0.0426 memory: 16201 loss_prob: 0.3607 loss_thr: 0.2579 loss_db: 0.0649 loss: 0.6835 2022/08/30 18:02:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:02:24 - mmengine - INFO - Saving checkpoint at 840 epochs 2022/08/30 18:02:33 - mmengine - INFO - Epoch(val) [840][5/32] eta: 7:39:29 time: 0.7398 data_time: 0.1488 memory: 16201 2022/08/30 18:02:36 - mmengine - INFO - Epoch(val) [840][10/32] eta: 0:00:16 time: 0.7630 data_time: 0.1865 memory: 15734 2022/08/30 18:02:39 - mmengine - INFO - Epoch(val) [840][15/32] eta: 0:00:16 time: 0.6083 data_time: 0.0547 memory: 15734 2022/08/30 18:02:42 - mmengine - INFO - Epoch(val) [840][20/32] eta: 0:00:07 time: 0.6015 data_time: 0.0533 memory: 15734 2022/08/30 18:02:45 - mmengine - INFO - Epoch(val) [840][25/32] eta: 0:00:07 time: 0.6395 data_time: 0.0639 memory: 15734 2022/08/30 18:02:48 - mmengine - INFO - Epoch(val) [840][30/32] eta: 0:00:01 time: 0.5990 data_time: 0.0282 memory: 15734 2022/08/30 18:02:49 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 18:02:49 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8517, precision: 0.8019, hmean: 0.8261 2022/08/30 18:02:49 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8517, precision: 0.8392, hmean: 0.8454 2022/08/30 18:02:49 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8512, precision: 0.8616, hmean: 0.8564 2022/08/30 18:02:49 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8498, precision: 0.8803, hmean: 0.8648 2022/08/30 18:02:49 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8406, precision: 0.8926, hmean: 0.8659 2022/08/30 18:02:49 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8031, precision: 0.9215, hmean: 0.8582 2022/08/30 18:02:49 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.3765, precision: 0.9595, hmean: 0.5408 2022/08/30 18:02:49 - mmengine - INFO - Epoch(val) [840][32/32] icdar/precision: 0.8926 icdar/recall: 0.8406 icdar/hmean: 0.8659 2022/08/30 18:02:56 - mmengine - INFO - Epoch(train) [841][5/63] lr: 2.3646e-03 eta: 0:00:01 time: 1.1693 data_time: 0.2142 memory: 16201 loss_prob: 0.4085 loss_thr: 0.2815 loss_db: 0.0729 loss: 0.7630 2022/08/30 18:03:01 - mmengine - INFO - Epoch(train) [841][10/63] lr: 2.3646e-03 eta: 7:39:12 time: 1.2235 data_time: 0.2196 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2641 loss_db: 0.0620 loss: 0.6767 2022/08/30 18:03:07 - mmengine - INFO - Epoch(train) [841][15/63] lr: 2.3646e-03 eta: 7:39:12 time: 1.1557 data_time: 0.0302 memory: 16201 loss_prob: 0.3469 loss_thr: 0.2611 loss_db: 0.0608 loss: 0.6688 2022/08/30 18:03:13 - mmengine - INFO - Epoch(train) [841][20/63] lr: 2.3646e-03 eta: 7:38:59 time: 1.1641 data_time: 0.0304 memory: 16201 loss_prob: 0.4058 loss_thr: 0.2873 loss_db: 0.0711 loss: 0.7643 2022/08/30 18:03:18 - mmengine - INFO - Epoch(train) [841][25/63] lr: 2.3646e-03 eta: 7:38:59 time: 1.0369 data_time: 0.0418 memory: 16201 loss_prob: 0.4258 loss_thr: 0.3045 loss_db: 0.0742 loss: 0.8046 2022/08/30 18:03:22 - mmengine - INFO - Epoch(train) [841][30/63] lr: 2.3646e-03 eta: 7:38:46 time: 0.9613 data_time: 0.0360 memory: 16201 loss_prob: 0.3823 loss_thr: 0.2845 loss_db: 0.0673 loss: 0.7341 2022/08/30 18:03:27 - mmengine - INFO - Epoch(train) [841][35/63] lr: 2.3646e-03 eta: 7:38:46 time: 0.9132 data_time: 0.0241 memory: 16201 loss_prob: 0.3798 loss_thr: 0.2853 loss_db: 0.0683 loss: 0.7334 2022/08/30 18:03:31 - mmengine - INFO - Epoch(train) [841][40/63] lr: 2.3646e-03 eta: 7:38:32 time: 0.8746 data_time: 0.0321 memory: 16201 loss_prob: 0.3863 loss_thr: 0.2833 loss_db: 0.0686 loss: 0.7382 2022/08/30 18:03:35 - mmengine - INFO - Epoch(train) [841][45/63] lr: 2.3646e-03 eta: 7:38:32 time: 0.8502 data_time: 0.0317 memory: 16201 loss_prob: 0.3489 loss_thr: 0.2549 loss_db: 0.0610 loss: 0.6648 2022/08/30 18:03:40 - mmengine - INFO - Epoch(train) [841][50/63] lr: 2.3646e-03 eta: 7:38:19 time: 0.8889 data_time: 0.0256 memory: 16201 loss_prob: 0.3524 loss_thr: 0.2560 loss_db: 0.0639 loss: 0.6723 2022/08/30 18:03:46 - mmengine - INFO - Epoch(train) [841][55/63] lr: 2.3646e-03 eta: 7:38:19 time: 1.0083 data_time: 0.0301 memory: 16201 loss_prob: 0.3968 loss_thr: 0.2854 loss_db: 0.0709 loss: 0.7531 2022/08/30 18:03:51 - mmengine - INFO - Epoch(train) [841][60/63] lr: 2.3646e-03 eta: 7:38:06 time: 1.0880 data_time: 0.0394 memory: 16201 loss_prob: 0.4092 loss_thr: 0.2906 loss_db: 0.0718 loss: 0.7716 2022/08/30 18:03:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:04:02 - mmengine - INFO - Epoch(train) [842][5/63] lr: 2.3587e-03 eta: 7:38:06 time: 1.3090 data_time: 0.2739 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2540 loss_db: 0.0646 loss: 0.6943 2022/08/30 18:04:08 - mmengine - INFO - Epoch(train) [842][10/63] lr: 2.3587e-03 eta: 7:37:49 time: 1.3725 data_time: 0.2849 memory: 16201 loss_prob: 0.3600 loss_thr: 0.2549 loss_db: 0.0630 loss: 0.6780 2022/08/30 18:04:12 - mmengine - INFO - Epoch(train) [842][15/63] lr: 2.3587e-03 eta: 7:37:49 time: 0.9705 data_time: 0.0317 memory: 16201 loss_prob: 0.3935 loss_thr: 0.2664 loss_db: 0.0688 loss: 0.7287 2022/08/30 18:04:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:04:16 - mmengine - INFO - Epoch(train) [842][20/63] lr: 2.3587e-03 eta: 7:37:35 time: 0.7986 data_time: 0.0226 memory: 16201 loss_prob: 0.3713 loss_thr: 0.2628 loss_db: 0.0652 loss: 0.6994 2022/08/30 18:04:21 - mmengine - INFO - Epoch(train) [842][25/63] lr: 2.3587e-03 eta: 7:37:35 time: 0.8759 data_time: 0.0278 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2718 loss_db: 0.0649 loss: 0.6987 2022/08/30 18:04:25 - mmengine - INFO - Epoch(train) [842][30/63] lr: 2.3587e-03 eta: 7:37:22 time: 0.9296 data_time: 0.0411 memory: 16201 loss_prob: 0.3621 loss_thr: 0.2609 loss_db: 0.0657 loss: 0.6887 2022/08/30 18:04:30 - mmengine - INFO - Epoch(train) [842][35/63] lr: 2.3587e-03 eta: 7:37:22 time: 0.9868 data_time: 0.0459 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2600 loss_db: 0.0640 loss: 0.6860 2022/08/30 18:04:36 - mmengine - INFO - Epoch(train) [842][40/63] lr: 2.3587e-03 eta: 7:37:09 time: 1.0666 data_time: 0.0305 memory: 16201 loss_prob: 0.3932 loss_thr: 0.2804 loss_db: 0.0701 loss: 0.7437 2022/08/30 18:04:40 - mmengine - INFO - Epoch(train) [842][45/63] lr: 2.3587e-03 eta: 7:37:09 time: 0.9381 data_time: 0.0315 memory: 16201 loss_prob: 0.4102 loss_thr: 0.2858 loss_db: 0.0737 loss: 0.7697 2022/08/30 18:04:44 - mmengine - INFO - Epoch(train) [842][50/63] lr: 2.3587e-03 eta: 7:36:56 time: 0.8530 data_time: 0.0358 memory: 16201 loss_prob: 0.3645 loss_thr: 0.2632 loss_db: 0.0651 loss: 0.6928 2022/08/30 18:04:49 - mmengine - INFO - Epoch(train) [842][55/63] lr: 2.3587e-03 eta: 7:36:56 time: 0.9362 data_time: 0.0322 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2521 loss_db: 0.0628 loss: 0.6654 2022/08/30 18:04:55 - mmengine - INFO - Epoch(train) [842][60/63] lr: 2.3587e-03 eta: 7:36:43 time: 1.0741 data_time: 0.0291 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2813 loss_db: 0.0695 loss: 0.7494 2022/08/30 18:04:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:05:06 - mmengine - INFO - Epoch(train) [843][5/63] lr: 2.3527e-03 eta: 7:36:43 time: 1.3540 data_time: 0.2946 memory: 16201 loss_prob: 0.3874 loss_thr: 0.2835 loss_db: 0.0682 loss: 0.7391 2022/08/30 18:05:12 - mmengine - INFO - Epoch(train) [843][10/63] lr: 2.3527e-03 eta: 7:36:26 time: 1.3783 data_time: 0.3354 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2847 loss_db: 0.0710 loss: 0.7511 2022/08/30 18:05:17 - mmengine - INFO - Epoch(train) [843][15/63] lr: 2.3527e-03 eta: 7:36:26 time: 1.1345 data_time: 0.0841 memory: 16201 loss_prob: 0.3890 loss_thr: 0.2676 loss_db: 0.0690 loss: 0.7256 2022/08/30 18:05:23 - mmengine - INFO - Epoch(train) [843][20/63] lr: 2.3527e-03 eta: 7:36:14 time: 1.1200 data_time: 0.0786 memory: 16201 loss_prob: 0.3896 loss_thr: 0.2682 loss_db: 0.0680 loss: 0.7258 2022/08/30 18:05:27 - mmengine - INFO - Epoch(train) [843][25/63] lr: 2.3527e-03 eta: 7:36:14 time: 0.9939 data_time: 0.0846 memory: 16201 loss_prob: 0.3930 loss_thr: 0.2920 loss_db: 0.0697 loss: 0.7547 2022/08/30 18:05:32 - mmengine - INFO - Epoch(train) [843][30/63] lr: 2.3527e-03 eta: 7:36:00 time: 0.8712 data_time: 0.0407 memory: 16201 loss_prob: 0.3883 loss_thr: 0.2848 loss_db: 0.0707 loss: 0.7439 2022/08/30 18:05:36 - mmengine - INFO - Epoch(train) [843][35/63] lr: 2.3527e-03 eta: 7:36:00 time: 0.8690 data_time: 0.0636 memory: 16201 loss_prob: 0.3832 loss_thr: 0.2714 loss_db: 0.0685 loss: 0.7230 2022/08/30 18:05:40 - mmengine - INFO - Epoch(train) [843][40/63] lr: 2.3527e-03 eta: 7:35:46 time: 0.8405 data_time: 0.0711 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2657 loss_db: 0.0644 loss: 0.7068 2022/08/30 18:05:44 - mmengine - INFO - Epoch(train) [843][45/63] lr: 2.3527e-03 eta: 7:35:46 time: 0.8438 data_time: 0.0431 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2659 loss_db: 0.0645 loss: 0.7108 2022/08/30 18:05:49 - mmengine - INFO - Epoch(train) [843][50/63] lr: 2.3527e-03 eta: 7:35:33 time: 0.8858 data_time: 0.0789 memory: 16201 loss_prob: 0.3914 loss_thr: 0.2726 loss_db: 0.0689 loss: 0.7329 2022/08/30 18:05:54 - mmengine - INFO - Epoch(train) [843][55/63] lr: 2.3527e-03 eta: 7:35:33 time: 0.9526 data_time: 0.0823 memory: 16201 loss_prob: 0.4160 loss_thr: 0.2803 loss_db: 0.0739 loss: 0.7702 2022/08/30 18:06:00 - mmengine - INFO - Epoch(train) [843][60/63] lr: 2.3527e-03 eta: 7:35:20 time: 1.0823 data_time: 0.0529 memory: 16201 loss_prob: 0.4059 loss_thr: 0.2757 loss_db: 0.0702 loss: 0.7517 2022/08/30 18:06:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:06:11 - mmengine - INFO - Epoch(train) [844][5/63] lr: 2.3468e-03 eta: 7:35:20 time: 1.2949 data_time: 0.3227 memory: 16201 loss_prob: 0.3630 loss_thr: 0.2745 loss_db: 0.0646 loss: 0.7021 2022/08/30 18:06:18 - mmengine - INFO - Epoch(train) [844][10/63] lr: 2.3468e-03 eta: 7:35:04 time: 1.5108 data_time: 0.3498 memory: 16201 loss_prob: 0.3479 loss_thr: 0.2717 loss_db: 0.0642 loss: 0.6838 2022/08/30 18:06:22 - mmengine - INFO - Epoch(train) [844][15/63] lr: 2.3468e-03 eta: 7:35:04 time: 1.1600 data_time: 0.1005 memory: 16201 loss_prob: 0.3875 loss_thr: 0.2757 loss_db: 0.0706 loss: 0.7338 2022/08/30 18:06:27 - mmengine - INFO - Epoch(train) [844][20/63] lr: 2.3468e-03 eta: 7:34:51 time: 0.9026 data_time: 0.0870 memory: 16201 loss_prob: 0.4296 loss_thr: 0.2986 loss_db: 0.0754 loss: 0.8036 2022/08/30 18:06:31 - mmengine - INFO - Epoch(train) [844][25/63] lr: 2.3468e-03 eta: 7:34:51 time: 0.8939 data_time: 0.0841 memory: 16201 loss_prob: 0.4013 loss_thr: 0.2865 loss_db: 0.0699 loss: 0.7578 2022/08/30 18:06:35 - mmengine - INFO - Epoch(train) [844][30/63] lr: 2.3468e-03 eta: 7:34:37 time: 0.8747 data_time: 0.0465 memory: 16201 loss_prob: 0.3720 loss_thr: 0.2641 loss_db: 0.0673 loss: 0.7034 2022/08/30 18:06:40 - mmengine - INFO - Epoch(train) [844][35/63] lr: 2.3468e-03 eta: 7:34:37 time: 0.8881 data_time: 0.0784 memory: 16201 loss_prob: 0.3918 loss_thr: 0.2704 loss_db: 0.0710 loss: 0.7332 2022/08/30 18:06:46 - mmengine - INFO - Epoch(train) [844][40/63] lr: 2.3468e-03 eta: 7:34:24 time: 1.0639 data_time: 0.0816 memory: 16201 loss_prob: 0.4009 loss_thr: 0.2903 loss_db: 0.0711 loss: 0.7623 2022/08/30 18:06:52 - mmengine - INFO - Epoch(train) [844][45/63] lr: 2.3468e-03 eta: 7:34:24 time: 1.1774 data_time: 0.1147 memory: 16201 loss_prob: 0.4174 loss_thr: 0.2925 loss_db: 0.0733 loss: 0.7831 2022/08/30 18:06:57 - mmengine - INFO - Epoch(train) [844][50/63] lr: 2.3468e-03 eta: 7:34:12 time: 1.1210 data_time: 0.1119 memory: 16201 loss_prob: 0.4106 loss_thr: 0.2837 loss_db: 0.0734 loss: 0.7677 2022/08/30 18:07:03 - mmengine - INFO - Epoch(train) [844][55/63] lr: 2.3468e-03 eta: 7:34:12 time: 1.0945 data_time: 0.0743 memory: 16201 loss_prob: 0.3665 loss_thr: 0.2748 loss_db: 0.0665 loss: 0.7077 2022/08/30 18:07:09 - mmengine - INFO - Epoch(train) [844][60/63] lr: 2.3468e-03 eta: 7:33:59 time: 1.2027 data_time: 0.0853 memory: 16201 loss_prob: 0.3721 loss_thr: 0.2730 loss_db: 0.0663 loss: 0.7115 2022/08/30 18:07:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:07:20 - mmengine - INFO - Epoch(train) [845][5/63] lr: 2.3409e-03 eta: 7:33:59 time: 1.3343 data_time: 0.3419 memory: 16201 loss_prob: 0.4342 loss_thr: 0.2959 loss_db: 0.0764 loss: 0.8065 2022/08/30 18:07:26 - mmengine - INFO - Epoch(train) [845][10/63] lr: 2.3409e-03 eta: 7:33:43 time: 1.3679 data_time: 0.3522 memory: 16201 loss_prob: 0.4195 loss_thr: 0.2830 loss_db: 0.0734 loss: 0.7759 2022/08/30 18:07:32 - mmengine - INFO - Epoch(train) [845][15/63] lr: 2.3409e-03 eta: 7:33:43 time: 1.1700 data_time: 0.0976 memory: 16201 loss_prob: 0.3868 loss_thr: 0.2643 loss_db: 0.0671 loss: 0.7183 2022/08/30 18:07:38 - mmengine - INFO - Epoch(train) [845][20/63] lr: 2.3409e-03 eta: 7:33:30 time: 1.1430 data_time: 0.0656 memory: 16201 loss_prob: 0.4016 loss_thr: 0.2792 loss_db: 0.0695 loss: 0.7503 2022/08/30 18:07:42 - mmengine - INFO - Epoch(train) [845][25/63] lr: 2.3409e-03 eta: 7:33:30 time: 1.0151 data_time: 0.0568 memory: 16201 loss_prob: 0.3883 loss_thr: 0.2775 loss_db: 0.0675 loss: 0.7333 2022/08/30 18:07:47 - mmengine - INFO - Epoch(train) [845][30/63] lr: 2.3409e-03 eta: 7:33:17 time: 0.9165 data_time: 0.0294 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2707 loss_db: 0.0669 loss: 0.7229 2022/08/30 18:07:51 - mmengine - INFO - Epoch(train) [845][35/63] lr: 2.3409e-03 eta: 7:33:17 time: 0.8528 data_time: 0.0255 memory: 16201 loss_prob: 0.4191 loss_thr: 0.2935 loss_db: 0.0731 loss: 0.7857 2022/08/30 18:07:55 - mmengine - INFO - Epoch(train) [845][40/63] lr: 2.3409e-03 eta: 7:33:03 time: 0.8574 data_time: 0.0219 memory: 16201 loss_prob: 0.3985 loss_thr: 0.2728 loss_db: 0.0708 loss: 0.7421 2022/08/30 18:07:59 - mmengine - INFO - Epoch(train) [845][45/63] lr: 2.3409e-03 eta: 7:33:03 time: 0.8629 data_time: 0.0301 memory: 16201 loss_prob: 0.3866 loss_thr: 0.2627 loss_db: 0.0691 loss: 0.7183 2022/08/30 18:08:04 - mmengine - INFO - Epoch(train) [845][50/63] lr: 2.3409e-03 eta: 7:32:50 time: 0.8286 data_time: 0.0356 memory: 16201 loss_prob: 0.3901 loss_thr: 0.2775 loss_db: 0.0681 loss: 0.7357 2022/08/30 18:08:08 - mmengine - INFO - Epoch(train) [845][55/63] lr: 2.3409e-03 eta: 7:32:50 time: 0.8525 data_time: 0.0202 memory: 16201 loss_prob: 0.3507 loss_thr: 0.2549 loss_db: 0.0607 loss: 0.6663 2022/08/30 18:08:13 - mmengine - INFO - Epoch(train) [845][60/63] lr: 2.3409e-03 eta: 7:32:36 time: 0.9757 data_time: 0.0297 memory: 16201 loss_prob: 0.3511 loss_thr: 0.2470 loss_db: 0.0629 loss: 0.6611 2022/08/30 18:08:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:08:24 - mmengine - INFO - Epoch(train) [846][5/63] lr: 2.3349e-03 eta: 7:32:36 time: 1.2955 data_time: 0.2498 memory: 16201 loss_prob: 0.4135 loss_thr: 0.2909 loss_db: 0.0724 loss: 0.7768 2022/08/30 18:08:29 - mmengine - INFO - Epoch(train) [846][10/63] lr: 2.3349e-03 eta: 7:32:20 time: 1.3222 data_time: 0.2616 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2697 loss_db: 0.0631 loss: 0.6865 2022/08/30 18:08:35 - mmengine - INFO - Epoch(train) [846][15/63] lr: 2.3349e-03 eta: 7:32:20 time: 1.1001 data_time: 0.0381 memory: 16201 loss_prob: 0.3226 loss_thr: 0.2456 loss_db: 0.0577 loss: 0.6259 2022/08/30 18:08:41 - mmengine - INFO - Epoch(train) [846][20/63] lr: 2.3349e-03 eta: 7:32:07 time: 1.1169 data_time: 0.0437 memory: 16201 loss_prob: 0.4189 loss_thr: 0.2726 loss_db: 0.0671 loss: 0.7586 2022/08/30 18:08:45 - mmengine - INFO - Epoch(train) [846][25/63] lr: 2.3349e-03 eta: 7:32:07 time: 1.0218 data_time: 0.0378 memory: 16201 loss_prob: 0.4355 loss_thr: 0.2916 loss_db: 0.0709 loss: 0.7980 2022/08/30 18:08:50 - mmengine - INFO - Epoch(train) [846][30/63] lr: 2.3349e-03 eta: 7:31:54 time: 0.9456 data_time: 0.0370 memory: 16201 loss_prob: 0.3876 loss_thr: 0.2896 loss_db: 0.0698 loss: 0.7470 2022/08/30 18:08:54 - mmengine - INFO - Epoch(train) [846][35/63] lr: 2.3349e-03 eta: 7:31:54 time: 0.8637 data_time: 0.0409 memory: 16201 loss_prob: 0.4369 loss_thr: 0.3006 loss_db: 0.0769 loss: 0.8144 2022/08/30 18:08:58 - mmengine - INFO - Epoch(train) [846][40/63] lr: 2.3349e-03 eta: 7:31:40 time: 0.8252 data_time: 0.0229 memory: 16201 loss_prob: 0.4270 loss_thr: 0.2876 loss_db: 0.0743 loss: 0.7889 2022/08/30 18:09:03 - mmengine - INFO - Epoch(train) [846][45/63] lr: 2.3349e-03 eta: 7:31:40 time: 0.8626 data_time: 0.0283 memory: 16201 loss_prob: 0.3937 loss_thr: 0.2742 loss_db: 0.0697 loss: 0.7375 2022/08/30 18:09:07 - mmengine - INFO - Epoch(train) [846][50/63] lr: 2.3349e-03 eta: 7:31:26 time: 0.8915 data_time: 0.0308 memory: 16201 loss_prob: 0.4041 loss_thr: 0.2844 loss_db: 0.0730 loss: 0.7615 2022/08/30 18:09:12 - mmengine - INFO - Epoch(train) [846][55/63] lr: 2.3349e-03 eta: 7:31:26 time: 0.9448 data_time: 0.0264 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2597 loss_db: 0.0665 loss: 0.6928 2022/08/30 18:09:18 - mmengine - INFO - Epoch(train) [846][60/63] lr: 2.3349e-03 eta: 7:31:14 time: 1.0882 data_time: 0.0508 memory: 16201 loss_prob: 0.3872 loss_thr: 0.2692 loss_db: 0.0669 loss: 0.7233 2022/08/30 18:09:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:09:28 - mmengine - INFO - Epoch(train) [847][5/63] lr: 2.3290e-03 eta: 7:31:14 time: 1.1550 data_time: 0.2391 memory: 16201 loss_prob: 0.3558 loss_thr: 0.2749 loss_db: 0.0627 loss: 0.6934 2022/08/30 18:09:32 - mmengine - INFO - Epoch(train) [847][10/63] lr: 2.3290e-03 eta: 7:30:56 time: 1.0804 data_time: 0.2397 memory: 16201 loss_prob: 0.3720 loss_thr: 0.2770 loss_db: 0.0658 loss: 0.7148 2022/08/30 18:09:37 - mmengine - INFO - Epoch(train) [847][15/63] lr: 2.3290e-03 eta: 7:30:56 time: 0.8924 data_time: 0.0248 memory: 16201 loss_prob: 0.4299 loss_thr: 0.2967 loss_db: 0.0775 loss: 0.8041 2022/08/30 18:09:42 - mmengine - INFO - Epoch(train) [847][20/63] lr: 2.3290e-03 eta: 7:30:43 time: 1.0175 data_time: 0.0291 memory: 16201 loss_prob: 0.4406 loss_thr: 0.3118 loss_db: 0.0780 loss: 0.8304 2022/08/30 18:09:47 - mmengine - INFO - Epoch(train) [847][25/63] lr: 2.3290e-03 eta: 7:30:43 time: 1.0435 data_time: 0.0350 memory: 16201 loss_prob: 0.4038 loss_thr: 0.2920 loss_db: 0.0695 loss: 0.7653 2022/08/30 18:09:52 - mmengine - INFO - Epoch(train) [847][30/63] lr: 2.3290e-03 eta: 7:30:30 time: 0.9931 data_time: 0.0287 memory: 16201 loss_prob: 0.3492 loss_thr: 0.2619 loss_db: 0.0628 loss: 0.6739 2022/08/30 18:09:56 - mmengine - INFO - Epoch(train) [847][35/63] lr: 2.3290e-03 eta: 7:30:30 time: 0.9126 data_time: 0.0285 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2688 loss_db: 0.0649 loss: 0.6874 2022/08/30 18:10:00 - mmengine - INFO - Epoch(train) [847][40/63] lr: 2.3290e-03 eta: 7:30:16 time: 0.8025 data_time: 0.0281 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2757 loss_db: 0.0679 loss: 0.7289 2022/08/30 18:10:05 - mmengine - INFO - Epoch(train) [847][45/63] lr: 2.3290e-03 eta: 7:30:16 time: 0.8464 data_time: 0.0263 memory: 16201 loss_prob: 0.3831 loss_thr: 0.2582 loss_db: 0.0669 loss: 0.7082 2022/08/30 18:10:11 - mmengine - INFO - Epoch(train) [847][50/63] lr: 2.3290e-03 eta: 7:30:03 time: 1.0870 data_time: 0.0316 memory: 16201 loss_prob: 0.3726 loss_thr: 0.2656 loss_db: 0.0656 loss: 0.7038 2022/08/30 18:10:16 - mmengine - INFO - Epoch(train) [847][55/63] lr: 2.3290e-03 eta: 7:30:03 time: 1.1721 data_time: 0.0343 memory: 16201 loss_prob: 0.3565 loss_thr: 0.2603 loss_db: 0.0620 loss: 0.6788 2022/08/30 18:10:22 - mmengine - INFO - Epoch(train) [847][60/63] lr: 2.3290e-03 eta: 7:29:51 time: 1.1041 data_time: 0.0319 memory: 16201 loss_prob: 0.3559 loss_thr: 0.2586 loss_db: 0.0631 loss: 0.6777 2022/08/30 18:10:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:10:32 - mmengine - INFO - Epoch(train) [848][5/63] lr: 2.3231e-03 eta: 7:29:51 time: 1.1779 data_time: 0.2370 memory: 16201 loss_prob: 0.3951 loss_thr: 0.2930 loss_db: 0.0700 loss: 0.7581 2022/08/30 18:10:38 - mmengine - INFO - Epoch(train) [848][10/63] lr: 2.3231e-03 eta: 7:29:34 time: 1.2911 data_time: 0.2427 memory: 16201 loss_prob: 0.3882 loss_thr: 0.2818 loss_db: 0.0691 loss: 0.7392 2022/08/30 18:10:43 - mmengine - INFO - Epoch(train) [848][15/63] lr: 2.3231e-03 eta: 7:29:34 time: 1.1181 data_time: 0.0298 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2589 loss_db: 0.0621 loss: 0.6715 2022/08/30 18:10:47 - mmengine - INFO - Epoch(train) [848][20/63] lr: 2.3231e-03 eta: 7:29:20 time: 0.9160 data_time: 0.0291 memory: 16201 loss_prob: 0.3773 loss_thr: 0.2820 loss_db: 0.0679 loss: 0.7273 2022/08/30 18:10:51 - mmengine - INFO - Epoch(train) [848][25/63] lr: 2.3231e-03 eta: 7:29:20 time: 0.8411 data_time: 0.0287 memory: 16201 loss_prob: 0.4186 loss_thr: 0.3028 loss_db: 0.0766 loss: 0.7981 2022/08/30 18:10:56 - mmengine - INFO - Epoch(train) [848][30/63] lr: 2.3231e-03 eta: 7:29:07 time: 0.9042 data_time: 0.0246 memory: 16201 loss_prob: 0.3941 loss_thr: 0.2853 loss_db: 0.0703 loss: 0.7496 2022/08/30 18:11:00 - mmengine - INFO - Epoch(train) [848][35/63] lr: 2.3231e-03 eta: 7:29:07 time: 0.9147 data_time: 0.0334 memory: 16201 loss_prob: 0.3736 loss_thr: 0.2805 loss_db: 0.0653 loss: 0.7195 2022/08/30 18:11:05 - mmengine - INFO - Epoch(train) [848][40/63] lr: 2.3231e-03 eta: 7:28:53 time: 0.8617 data_time: 0.0229 memory: 16201 loss_prob: 0.3910 loss_thr: 0.2915 loss_db: 0.0696 loss: 0.7521 2022/08/30 18:11:10 - mmengine - INFO - Epoch(train) [848][45/63] lr: 2.3231e-03 eta: 7:28:53 time: 0.9776 data_time: 0.0267 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2759 loss_db: 0.0671 loss: 0.7168 2022/08/30 18:11:17 - mmengine - INFO - Epoch(train) [848][50/63] lr: 2.3231e-03 eta: 7:28:41 time: 1.2012 data_time: 0.0527 memory: 16201 loss_prob: 0.3407 loss_thr: 0.2566 loss_db: 0.0601 loss: 0.6574 2022/08/30 18:11:22 - mmengine - INFO - Epoch(train) [848][55/63] lr: 2.3231e-03 eta: 7:28:41 time: 1.1864 data_time: 0.0425 memory: 16201 loss_prob: 0.3886 loss_thr: 0.2832 loss_db: 0.0694 loss: 0.7412 2022/08/30 18:11:28 - mmengine - INFO - Epoch(train) [848][60/63] lr: 2.3231e-03 eta: 7:28:29 time: 1.1086 data_time: 0.0302 memory: 16201 loss_prob: 0.4090 loss_thr: 0.2852 loss_db: 0.0720 loss: 0.7662 2022/08/30 18:11:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:11:37 - mmengine - INFO - Epoch(train) [849][5/63] lr: 2.3171e-03 eta: 7:28:29 time: 1.1281 data_time: 0.2239 memory: 16201 loss_prob: 0.3852 loss_thr: 0.2656 loss_db: 0.0677 loss: 0.7185 2022/08/30 18:11:41 - mmengine - INFO - Epoch(train) [849][10/63] lr: 2.3171e-03 eta: 7:28:11 time: 1.0275 data_time: 0.2248 memory: 16201 loss_prob: 0.3664 loss_thr: 0.2653 loss_db: 0.0659 loss: 0.6976 2022/08/30 18:11:45 - mmengine - INFO - Epoch(train) [849][15/63] lr: 2.3171e-03 eta: 7:28:11 time: 0.8102 data_time: 0.0246 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2704 loss_db: 0.0677 loss: 0.7138 2022/08/30 18:11:50 - mmengine - INFO - Epoch(train) [849][20/63] lr: 2.3171e-03 eta: 7:27:57 time: 0.9482 data_time: 0.0380 memory: 16201 loss_prob: 0.3711 loss_thr: 0.2618 loss_db: 0.0662 loss: 0.6991 2022/08/30 18:11:56 - mmengine - INFO - Epoch(train) [849][25/63] lr: 2.3171e-03 eta: 7:27:57 time: 1.0638 data_time: 0.0349 memory: 16201 loss_prob: 0.3861 loss_thr: 0.2627 loss_db: 0.0695 loss: 0.7183 2022/08/30 18:12:01 - mmengine - INFO - Epoch(train) [849][30/63] lr: 2.3171e-03 eta: 7:27:45 time: 1.1004 data_time: 0.0337 memory: 16201 loss_prob: 0.3863 loss_thr: 0.2679 loss_db: 0.0700 loss: 0.7242 2022/08/30 18:12:07 - mmengine - INFO - Epoch(train) [849][35/63] lr: 2.3171e-03 eta: 7:27:45 time: 1.0979 data_time: 0.0389 memory: 16201 loss_prob: 0.3729 loss_thr: 0.2592 loss_db: 0.0658 loss: 0.6978 2022/08/30 18:12:12 - mmengine - INFO - Epoch(train) [849][40/63] lr: 2.3171e-03 eta: 7:27:32 time: 1.0362 data_time: 0.0322 memory: 16201 loss_prob: 0.3786 loss_thr: 0.2536 loss_db: 0.0673 loss: 0.6995 2022/08/30 18:12:17 - mmengine - INFO - Epoch(train) [849][45/63] lr: 2.3171e-03 eta: 7:27:32 time: 1.0305 data_time: 0.0370 memory: 16201 loss_prob: 0.3618 loss_thr: 0.2537 loss_db: 0.0654 loss: 0.6809 2022/08/30 18:12:22 - mmengine - INFO - Epoch(train) [849][50/63] lr: 2.3171e-03 eta: 7:27:19 time: 1.0771 data_time: 0.0445 memory: 16201 loss_prob: 0.3559 loss_thr: 0.2552 loss_db: 0.0648 loss: 0.6759 2022/08/30 18:12:28 - mmengine - INFO - Epoch(train) [849][55/63] lr: 2.3171e-03 eta: 7:27:19 time: 1.1398 data_time: 0.0324 memory: 16201 loss_prob: 0.3809 loss_thr: 0.2736 loss_db: 0.0678 loss: 0.7222 2022/08/30 18:12:32 - mmengine - INFO - Epoch(train) [849][60/63] lr: 2.3171e-03 eta: 7:27:06 time: 0.9982 data_time: 0.0293 memory: 16201 loss_prob: 0.4323 loss_thr: 0.2963 loss_db: 0.0712 loss: 0.7997 2022/08/30 18:12:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:12:41 - mmengine - INFO - Epoch(train) [850][5/63] lr: 2.3112e-03 eta: 7:27:06 time: 1.0430 data_time: 0.2318 memory: 16201 loss_prob: 0.4429 loss_thr: 0.2863 loss_db: 0.0724 loss: 0.8017 2022/08/30 18:12:45 - mmengine - INFO - Epoch(train) [850][10/63] lr: 2.3112e-03 eta: 7:26:48 time: 1.0710 data_time: 0.2330 memory: 16201 loss_prob: 0.3791 loss_thr: 0.2614 loss_db: 0.0672 loss: 0.7077 2022/08/30 18:12:50 - mmengine - INFO - Epoch(train) [850][15/63] lr: 2.3112e-03 eta: 7:26:48 time: 0.8843 data_time: 0.0289 memory: 16201 loss_prob: 0.3564 loss_thr: 0.2594 loss_db: 0.0647 loss: 0.6805 2022/08/30 18:12:56 - mmengine - INFO - Epoch(train) [850][20/63] lr: 2.3112e-03 eta: 7:26:35 time: 1.0228 data_time: 0.0214 memory: 16201 loss_prob: 0.3956 loss_thr: 0.2802 loss_db: 0.0705 loss: 0.7464 2022/08/30 18:13:02 - mmengine - INFO - Epoch(train) [850][25/63] lr: 2.3112e-03 eta: 7:26:35 time: 1.1997 data_time: 0.0372 memory: 16201 loss_prob: 0.4164 loss_thr: 0.2830 loss_db: 0.0733 loss: 0.7727 2022/08/30 18:13:08 - mmengine - INFO - Epoch(train) [850][30/63] lr: 2.3112e-03 eta: 7:26:23 time: 1.2147 data_time: 0.0287 memory: 16201 loss_prob: 0.4055 loss_thr: 0.2833 loss_db: 0.0727 loss: 0.7615 2022/08/30 18:13:13 - mmengine - INFO - Epoch(train) [850][35/63] lr: 2.3112e-03 eta: 7:26:23 time: 1.1025 data_time: 0.0355 memory: 16201 loss_prob: 0.3826 loss_thr: 0.2734 loss_db: 0.0686 loss: 0.7246 2022/08/30 18:13:17 - mmengine - INFO - Epoch(train) [850][40/63] lr: 2.3112e-03 eta: 7:26:10 time: 0.9515 data_time: 0.0465 memory: 16201 loss_prob: 0.3872 loss_thr: 0.2784 loss_db: 0.0688 loss: 0.7345 2022/08/30 18:13:22 - mmengine - INFO - Epoch(train) [850][45/63] lr: 2.3112e-03 eta: 7:26:10 time: 0.8495 data_time: 0.0340 memory: 16201 loss_prob: 0.4298 loss_thr: 0.2978 loss_db: 0.0744 loss: 0.8020 2022/08/30 18:13:26 - mmengine - INFO - Epoch(train) [850][50/63] lr: 2.3112e-03 eta: 7:25:56 time: 0.8371 data_time: 0.0394 memory: 16201 loss_prob: 0.4043 loss_thr: 0.2780 loss_db: 0.0696 loss: 0.7519 2022/08/30 18:13:30 - mmengine - INFO - Epoch(train) [850][55/63] lr: 2.3112e-03 eta: 7:25:56 time: 0.8950 data_time: 0.0296 memory: 16201 loss_prob: 0.3866 loss_thr: 0.2697 loss_db: 0.0683 loss: 0.7247 2022/08/30 18:13:36 - mmengine - INFO - Epoch(train) [850][60/63] lr: 2.3112e-03 eta: 7:25:44 time: 1.0675 data_time: 0.0230 memory: 16201 loss_prob: 0.3754 loss_thr: 0.2709 loss_db: 0.0676 loss: 0.7138 2022/08/30 18:13:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:13:46 - mmengine - INFO - Epoch(train) [851][5/63] lr: 2.3052e-03 eta: 7:25:44 time: 1.2665 data_time: 0.2369 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2476 loss_db: 0.0598 loss: 0.6419 2022/08/30 18:13:52 - mmengine - INFO - Epoch(train) [851][10/63] lr: 2.3052e-03 eta: 7:25:27 time: 1.2932 data_time: 0.2447 memory: 16201 loss_prob: 0.3717 loss_thr: 0.2750 loss_db: 0.0651 loss: 0.7119 2022/08/30 18:13:57 - mmengine - INFO - Epoch(train) [851][15/63] lr: 2.3052e-03 eta: 7:25:27 time: 1.0192 data_time: 0.0315 memory: 16201 loss_prob: 0.3656 loss_thr: 0.2786 loss_db: 0.0635 loss: 0.7078 2022/08/30 18:14:02 - mmengine - INFO - Epoch(train) [851][20/63] lr: 2.3052e-03 eta: 7:25:14 time: 0.9708 data_time: 0.0320 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2588 loss_db: 0.0624 loss: 0.6679 2022/08/30 18:14:06 - mmengine - INFO - Epoch(train) [851][25/63] lr: 2.3052e-03 eta: 7:25:14 time: 0.9050 data_time: 0.0347 memory: 16201 loss_prob: 0.3312 loss_thr: 0.2530 loss_db: 0.0610 loss: 0.6452 2022/08/30 18:14:10 - mmengine - INFO - Epoch(train) [851][30/63] lr: 2.3052e-03 eta: 7:25:00 time: 0.8070 data_time: 0.0219 memory: 16201 loss_prob: 0.3510 loss_thr: 0.2695 loss_db: 0.0626 loss: 0.6831 2022/08/30 18:14:14 - mmengine - INFO - Epoch(train) [851][35/63] lr: 2.3052e-03 eta: 7:25:00 time: 0.8173 data_time: 0.0264 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2786 loss_db: 0.0652 loss: 0.7220 2022/08/30 18:14:18 - mmengine - INFO - Epoch(train) [851][40/63] lr: 2.3052e-03 eta: 7:24:46 time: 0.8277 data_time: 0.0268 memory: 16201 loss_prob: 0.3883 loss_thr: 0.2731 loss_db: 0.0683 loss: 0.7298 2022/08/30 18:14:22 - mmengine - INFO - Epoch(train) [851][45/63] lr: 2.3052e-03 eta: 7:24:46 time: 0.8468 data_time: 0.0258 memory: 16201 loss_prob: 0.3847 loss_thr: 0.2685 loss_db: 0.0698 loss: 0.7229 2022/08/30 18:14:29 - mmengine - INFO - Epoch(train) [851][50/63] lr: 2.3052e-03 eta: 7:24:33 time: 1.0805 data_time: 0.0522 memory: 16201 loss_prob: 0.3669 loss_thr: 0.2625 loss_db: 0.0656 loss: 0.6950 2022/08/30 18:14:34 - mmengine - INFO - Epoch(train) [851][55/63] lr: 2.3052e-03 eta: 7:24:33 time: 1.1808 data_time: 0.0435 memory: 16201 loss_prob: 0.3979 loss_thr: 0.2826 loss_db: 0.0689 loss: 0.7495 2022/08/30 18:14:39 - mmengine - INFO - Epoch(train) [851][60/63] lr: 2.3052e-03 eta: 7:24:21 time: 1.0547 data_time: 0.0285 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2908 loss_db: 0.0697 loss: 0.7570 2022/08/30 18:14:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:14:49 - mmengine - INFO - Epoch(train) [852][5/63] lr: 2.2993e-03 eta: 7:24:21 time: 1.1355 data_time: 0.2516 memory: 16201 loss_prob: 0.3759 loss_thr: 0.2767 loss_db: 0.0663 loss: 0.7188 2022/08/30 18:14:53 - mmengine - INFO - Epoch(train) [852][10/63] lr: 2.2993e-03 eta: 7:24:03 time: 1.1219 data_time: 0.2638 memory: 16201 loss_prob: 0.3625 loss_thr: 0.2725 loss_db: 0.0625 loss: 0.6975 2022/08/30 18:14:58 - mmengine - INFO - Epoch(train) [852][15/63] lr: 2.2993e-03 eta: 7:24:03 time: 0.8887 data_time: 0.0261 memory: 16201 loss_prob: 0.3687 loss_thr: 0.2631 loss_db: 0.0650 loss: 0.6968 2022/08/30 18:15:02 - mmengine - INFO - Epoch(train) [852][20/63] lr: 2.2993e-03 eta: 7:23:50 time: 0.8754 data_time: 0.0215 memory: 16201 loss_prob: 0.3943 loss_thr: 0.2877 loss_db: 0.0706 loss: 0.7527 2022/08/30 18:15:07 - mmengine - INFO - Epoch(train) [852][25/63] lr: 2.2993e-03 eta: 7:23:50 time: 0.9539 data_time: 0.0359 memory: 16201 loss_prob: 0.3899 loss_thr: 0.2817 loss_db: 0.0692 loss: 0.7407 2022/08/30 18:15:12 - mmengine - INFO - Epoch(train) [852][30/63] lr: 2.2993e-03 eta: 7:23:37 time: 1.0543 data_time: 0.0270 memory: 16201 loss_prob: 0.3647 loss_thr: 0.2727 loss_db: 0.0627 loss: 0.7000 2022/08/30 18:15:17 - mmengine - INFO - Epoch(train) [852][35/63] lr: 2.2993e-03 eta: 7:23:37 time: 1.0164 data_time: 0.0269 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2698 loss_db: 0.0629 loss: 0.6900 2022/08/30 18:15:22 - mmengine - INFO - Epoch(train) [852][40/63] lr: 2.2993e-03 eta: 7:23:23 time: 0.9080 data_time: 0.0309 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2716 loss_db: 0.0698 loss: 0.7267 2022/08/30 18:15:26 - mmengine - INFO - Epoch(train) [852][45/63] lr: 2.2993e-03 eta: 7:23:23 time: 0.9029 data_time: 0.0276 memory: 16201 loss_prob: 0.4074 loss_thr: 0.2812 loss_db: 0.0724 loss: 0.7610 2022/08/30 18:15:32 - mmengine - INFO - Epoch(train) [852][50/63] lr: 2.2993e-03 eta: 7:23:11 time: 1.0565 data_time: 0.0410 memory: 16201 loss_prob: 0.3578 loss_thr: 0.2583 loss_db: 0.0631 loss: 0.6792 2022/08/30 18:15:36 - mmengine - INFO - Epoch(train) [852][55/63] lr: 2.2993e-03 eta: 7:23:11 time: 0.9865 data_time: 0.0315 memory: 16201 loss_prob: 0.3321 loss_thr: 0.2545 loss_db: 0.0605 loss: 0.6471 2022/08/30 18:15:41 - mmengine - INFO - Epoch(train) [852][60/63] lr: 2.2993e-03 eta: 7:22:57 time: 0.8620 data_time: 0.0224 memory: 16201 loss_prob: 0.3248 loss_thr: 0.2521 loss_db: 0.0583 loss: 0.6352 2022/08/30 18:15:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:15:52 - mmengine - INFO - Epoch(train) [853][5/63] lr: 2.2933e-03 eta: 7:22:57 time: 1.2908 data_time: 0.2463 memory: 16201 loss_prob: 0.3729 loss_thr: 0.2747 loss_db: 0.0658 loss: 0.7134 2022/08/30 18:15:57 - mmengine - INFO - Epoch(train) [853][10/63] lr: 2.2933e-03 eta: 7:22:41 time: 1.3979 data_time: 0.2665 memory: 16201 loss_prob: 0.3708 loss_thr: 0.2715 loss_db: 0.0662 loss: 0.7084 2022/08/30 18:16:02 - mmengine - INFO - Epoch(train) [853][15/63] lr: 2.2933e-03 eta: 7:22:41 time: 1.0694 data_time: 0.0457 memory: 16201 loss_prob: 0.3562 loss_thr: 0.2591 loss_db: 0.0637 loss: 0.6790 2022/08/30 18:16:08 - mmengine - INFO - Epoch(train) [853][20/63] lr: 2.2933e-03 eta: 7:22:28 time: 1.0455 data_time: 0.0437 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2567 loss_db: 0.0621 loss: 0.6622 2022/08/30 18:16:13 - mmengine - INFO - Epoch(train) [853][25/63] lr: 2.2933e-03 eta: 7:22:28 time: 1.1015 data_time: 0.0433 memory: 16201 loss_prob: 0.3520 loss_thr: 0.2602 loss_db: 0.0628 loss: 0.6750 2022/08/30 18:16:19 - mmengine - INFO - Epoch(train) [853][30/63] lr: 2.2933e-03 eta: 7:22:16 time: 1.1645 data_time: 0.0378 memory: 16201 loss_prob: 0.3869 loss_thr: 0.2751 loss_db: 0.0673 loss: 0.7294 2022/08/30 18:16:25 - mmengine - INFO - Epoch(train) [853][35/63] lr: 2.2933e-03 eta: 7:22:16 time: 1.1376 data_time: 0.0442 memory: 16201 loss_prob: 0.3649 loss_thr: 0.2652 loss_db: 0.0638 loss: 0.6940 2022/08/30 18:16:29 - mmengine - INFO - Epoch(train) [853][40/63] lr: 2.2933e-03 eta: 7:22:03 time: 0.9908 data_time: 0.0350 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2460 loss_db: 0.0602 loss: 0.6497 2022/08/30 18:16:33 - mmengine - INFO - Epoch(train) [853][45/63] lr: 2.2933e-03 eta: 7:22:03 time: 0.8608 data_time: 0.0280 memory: 16201 loss_prob: 0.3496 loss_thr: 0.2474 loss_db: 0.0624 loss: 0.6594 2022/08/30 18:16:38 - mmengine - INFO - Epoch(train) [853][50/63] lr: 2.2933e-03 eta: 7:21:49 time: 0.8613 data_time: 0.0295 memory: 16201 loss_prob: 0.3456 loss_thr: 0.2551 loss_db: 0.0615 loss: 0.6622 2022/08/30 18:16:42 - mmengine - INFO - Epoch(train) [853][55/63] lr: 2.2933e-03 eta: 7:21:49 time: 0.8628 data_time: 0.0342 memory: 16201 loss_prob: 0.3595 loss_thr: 0.2570 loss_db: 0.0646 loss: 0.6811 2022/08/30 18:16:46 - mmengine - INFO - Epoch(train) [853][60/63] lr: 2.2933e-03 eta: 7:21:35 time: 0.8272 data_time: 0.0328 memory: 16201 loss_prob: 0.3500 loss_thr: 0.2656 loss_db: 0.0630 loss: 0.6786 2022/08/30 18:16:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:16:56 - mmengine - INFO - Epoch(train) [854][5/63] lr: 2.2874e-03 eta: 7:21:35 time: 1.1650 data_time: 0.2408 memory: 16201 loss_prob: 0.4022 loss_thr: 0.2911 loss_db: 0.0695 loss: 0.7628 2022/08/30 18:17:02 - mmengine - INFO - Epoch(train) [854][10/63] lr: 2.2874e-03 eta: 7:21:18 time: 1.3090 data_time: 0.2534 memory: 16201 loss_prob: 0.4261 loss_thr: 0.2962 loss_db: 0.0749 loss: 0.7973 2022/08/30 18:17:07 - mmengine - INFO - Epoch(train) [854][15/63] lr: 2.2874e-03 eta: 7:21:18 time: 1.0954 data_time: 0.0470 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2874 loss_db: 0.0713 loss: 0.7615 2022/08/30 18:17:11 - mmengine - INFO - Epoch(train) [854][20/63] lr: 2.2874e-03 eta: 7:21:05 time: 0.9773 data_time: 0.0468 memory: 16201 loss_prob: 0.3421 loss_thr: 0.2520 loss_db: 0.0600 loss: 0.6541 2022/08/30 18:17:16 - mmengine - INFO - Epoch(train) [854][25/63] lr: 2.2874e-03 eta: 7:21:05 time: 0.8720 data_time: 0.0318 memory: 16201 loss_prob: 0.3673 loss_thr: 0.2588 loss_db: 0.0647 loss: 0.6908 2022/08/30 18:17:20 - mmengine - INFO - Epoch(train) [854][30/63] lr: 2.2874e-03 eta: 7:20:52 time: 0.8881 data_time: 0.0205 memory: 16201 loss_prob: 0.3982 loss_thr: 0.2837 loss_db: 0.0704 loss: 0.7524 2022/08/30 18:17:26 - mmengine - INFO - Epoch(train) [854][35/63] lr: 2.2874e-03 eta: 7:20:52 time: 0.9944 data_time: 0.0351 memory: 16201 loss_prob: 0.4106 loss_thr: 0.2871 loss_db: 0.0707 loss: 0.7684 2022/08/30 18:17:31 - mmengine - INFO - Epoch(train) [854][40/63] lr: 2.2874e-03 eta: 7:20:39 time: 1.0996 data_time: 0.0300 memory: 16201 loss_prob: 0.4114 loss_thr: 0.2947 loss_db: 0.0699 loss: 0.7760 2022/08/30 18:17:37 - mmengine - INFO - Epoch(train) [854][45/63] lr: 2.2874e-03 eta: 7:20:39 time: 1.0696 data_time: 0.0289 memory: 16201 loss_prob: 0.3778 loss_thr: 0.2814 loss_db: 0.0658 loss: 0.7249 2022/08/30 18:17:42 - mmengine - INFO - Epoch(train) [854][50/63] lr: 2.2874e-03 eta: 7:20:27 time: 1.0371 data_time: 0.0362 memory: 16201 loss_prob: 0.3529 loss_thr: 0.2645 loss_db: 0.0632 loss: 0.6806 2022/08/30 18:17:48 - mmengine - INFO - Epoch(train) [854][55/63] lr: 2.2874e-03 eta: 7:20:27 time: 1.1344 data_time: 0.0291 memory: 16201 loss_prob: 0.3336 loss_thr: 0.2540 loss_db: 0.0609 loss: 0.6486 2022/08/30 18:17:53 - mmengine - INFO - Epoch(train) [854][60/63] lr: 2.2874e-03 eta: 7:20:14 time: 1.0913 data_time: 0.0373 memory: 16201 loss_prob: 0.3686 loss_thr: 0.2717 loss_db: 0.0664 loss: 0.7067 2022/08/30 18:17:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:18:01 - mmengine - INFO - Epoch(train) [855][5/63] lr: 2.2814e-03 eta: 7:20:14 time: 1.0054 data_time: 0.2142 memory: 16201 loss_prob: 0.3884 loss_thr: 0.2840 loss_db: 0.0701 loss: 0.7425 2022/08/30 18:18:05 - mmengine - INFO - Epoch(train) [855][10/63] lr: 2.2814e-03 eta: 7:19:56 time: 1.0390 data_time: 0.2141 memory: 16201 loss_prob: 0.4003 loss_thr: 0.2791 loss_db: 0.0710 loss: 0.7503 2022/08/30 18:18:09 - mmengine - INFO - Epoch(train) [855][15/63] lr: 2.2814e-03 eta: 7:19:56 time: 0.8345 data_time: 0.0281 memory: 16201 loss_prob: 0.3997 loss_thr: 0.2810 loss_db: 0.0711 loss: 0.7518 2022/08/30 18:18:13 - mmengine - INFO - Epoch(train) [855][20/63] lr: 2.2814e-03 eta: 7:19:42 time: 0.8097 data_time: 0.0309 memory: 16201 loss_prob: 0.3816 loss_thr: 0.2785 loss_db: 0.0689 loss: 0.7289 2022/08/30 18:18:18 - mmengine - INFO - Epoch(train) [855][25/63] lr: 2.2814e-03 eta: 7:19:42 time: 0.8857 data_time: 0.0274 memory: 16201 loss_prob: 0.3748 loss_thr: 0.2735 loss_db: 0.0668 loss: 0.7152 2022/08/30 18:18:23 - mmengine - INFO - Epoch(train) [855][30/63] lr: 2.2814e-03 eta: 7:19:29 time: 0.9863 data_time: 0.0257 memory: 16201 loss_prob: 0.3627 loss_thr: 0.2646 loss_db: 0.0648 loss: 0.6921 2022/08/30 18:18:28 - mmengine - INFO - Epoch(train) [855][35/63] lr: 2.2814e-03 eta: 7:19:29 time: 0.9725 data_time: 0.0306 memory: 16201 loss_prob: 0.3213 loss_thr: 0.2368 loss_db: 0.0580 loss: 0.6162 2022/08/30 18:18:33 - mmengine - INFO - Epoch(train) [855][40/63] lr: 2.2814e-03 eta: 7:19:16 time: 1.0037 data_time: 0.0283 memory: 16201 loss_prob: 0.3584 loss_thr: 0.2561 loss_db: 0.0640 loss: 0.6785 2022/08/30 18:18:39 - mmengine - INFO - Epoch(train) [855][45/63] lr: 2.2814e-03 eta: 7:19:16 time: 1.0812 data_time: 0.0361 memory: 16201 loss_prob: 0.3940 loss_thr: 0.2758 loss_db: 0.0690 loss: 0.7388 2022/08/30 18:18:44 - mmengine - INFO - Epoch(train) [855][50/63] lr: 2.2814e-03 eta: 7:19:04 time: 1.1053 data_time: 0.0442 memory: 16201 loss_prob: 0.4199 loss_thr: 0.2956 loss_db: 0.0712 loss: 0.7866 2022/08/30 18:18:50 - mmengine - INFO - Epoch(train) [855][55/63] lr: 2.2814e-03 eta: 7:19:04 time: 1.1007 data_time: 0.0340 memory: 16201 loss_prob: 0.4414 loss_thr: 0.3024 loss_db: 0.0766 loss: 0.8205 2022/08/30 18:18:55 - mmengine - INFO - Epoch(train) [855][60/63] lr: 2.2814e-03 eta: 7:18:51 time: 1.0926 data_time: 0.0354 memory: 16201 loss_prob: 0.4001 loss_thr: 0.2770 loss_db: 0.0707 loss: 0.7479 2022/08/30 18:18:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:19:04 - mmengine - INFO - Epoch(train) [856][5/63] lr: 2.2755e-03 eta: 7:18:51 time: 1.0970 data_time: 0.2283 memory: 16201 loss_prob: 0.3682 loss_thr: 0.2637 loss_db: 0.0648 loss: 0.6967 2022/08/30 18:19:08 - mmengine - INFO - Epoch(train) [856][10/63] lr: 2.2755e-03 eta: 7:18:33 time: 1.0407 data_time: 0.2268 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2523 loss_db: 0.0638 loss: 0.6601 2022/08/30 18:19:13 - mmengine - INFO - Epoch(train) [856][15/63] lr: 2.2755e-03 eta: 7:18:33 time: 0.8554 data_time: 0.0290 memory: 16201 loss_prob: 0.3896 loss_thr: 0.2773 loss_db: 0.0696 loss: 0.7365 2022/08/30 18:19:17 - mmengine - INFO - Epoch(train) [856][20/63] lr: 2.2755e-03 eta: 7:18:20 time: 0.8930 data_time: 0.0331 memory: 16201 loss_prob: 0.4029 loss_thr: 0.2781 loss_db: 0.0691 loss: 0.7501 2022/08/30 18:19:21 - mmengine - INFO - Epoch(train) [856][25/63] lr: 2.2755e-03 eta: 7:18:20 time: 0.8628 data_time: 0.0314 memory: 16201 loss_prob: 0.3934 loss_thr: 0.2740 loss_db: 0.0702 loss: 0.7376 2022/08/30 18:19:26 - mmengine - INFO - Epoch(train) [856][30/63] lr: 2.2755e-03 eta: 7:18:06 time: 0.8391 data_time: 0.0295 memory: 16201 loss_prob: 0.3639 loss_thr: 0.2614 loss_db: 0.0655 loss: 0.6908 2022/08/30 18:19:32 - mmengine - INFO - Epoch(train) [856][35/63] lr: 2.2755e-03 eta: 7:18:06 time: 1.0367 data_time: 0.0380 memory: 16201 loss_prob: 0.3581 loss_thr: 0.2545 loss_db: 0.0628 loss: 0.6754 2022/08/30 18:19:37 - mmengine - INFO - Epoch(train) [856][40/63] lr: 2.2755e-03 eta: 7:17:54 time: 1.1897 data_time: 0.0406 memory: 16201 loss_prob: 0.3855 loss_thr: 0.2651 loss_db: 0.0694 loss: 0.7200 2022/08/30 18:19:43 - mmengine - INFO - Epoch(train) [856][45/63] lr: 2.2755e-03 eta: 7:17:54 time: 1.1653 data_time: 0.0397 memory: 16201 loss_prob: 0.3716 loss_thr: 0.2554 loss_db: 0.0672 loss: 0.6941 2022/08/30 18:19:49 - mmengine - INFO - Epoch(train) [856][50/63] lr: 2.2755e-03 eta: 7:17:42 time: 1.1648 data_time: 0.0400 memory: 16201 loss_prob: 0.3584 loss_thr: 0.2530 loss_db: 0.0630 loss: 0.6743 2022/08/30 18:19:53 - mmengine - INFO - Epoch(train) [856][55/63] lr: 2.2755e-03 eta: 7:17:42 time: 0.9908 data_time: 0.0282 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2887 loss_db: 0.0704 loss: 0.7618 2022/08/30 18:19:57 - mmengine - INFO - Epoch(train) [856][60/63] lr: 2.2755e-03 eta: 7:17:28 time: 0.8156 data_time: 0.0184 memory: 16201 loss_prob: 0.4078 loss_thr: 0.2905 loss_db: 0.0704 loss: 0.7687 2022/08/30 18:20:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:20:07 - mmengine - INFO - Epoch(train) [857][5/63] lr: 2.2695e-03 eta: 7:17:28 time: 1.1556 data_time: 0.2635 memory: 16201 loss_prob: 0.4334 loss_thr: 0.2910 loss_db: 0.0758 loss: 0.8002 2022/08/30 18:20:12 - mmengine - INFO - Epoch(train) [857][10/63] lr: 2.2695e-03 eta: 7:17:11 time: 1.2602 data_time: 0.2639 memory: 16201 loss_prob: 0.4364 loss_thr: 0.2872 loss_db: 0.0740 loss: 0.7977 2022/08/30 18:20:18 - mmengine - INFO - Epoch(train) [857][15/63] lr: 2.2695e-03 eta: 7:17:11 time: 1.0309 data_time: 0.0360 memory: 16201 loss_prob: 0.3840 loss_thr: 0.2652 loss_db: 0.0658 loss: 0.7150 2022/08/30 18:20:23 - mmengine - INFO - Epoch(train) [857][20/63] lr: 2.2695e-03 eta: 7:16:58 time: 1.0637 data_time: 0.0438 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2442 loss_db: 0.0611 loss: 0.6449 2022/08/30 18:20:29 - mmengine - INFO - Epoch(train) [857][25/63] lr: 2.2695e-03 eta: 7:16:58 time: 1.1151 data_time: 0.0394 memory: 16201 loss_prob: 0.3459 loss_thr: 0.2516 loss_db: 0.0629 loss: 0.6604 2022/08/30 18:20:33 - mmengine - INFO - Epoch(train) [857][30/63] lr: 2.2695e-03 eta: 7:16:45 time: 0.9851 data_time: 0.0304 memory: 16201 loss_prob: 0.3574 loss_thr: 0.2737 loss_db: 0.0649 loss: 0.6960 2022/08/30 18:20:37 - mmengine - INFO - Epoch(train) [857][35/63] lr: 2.2695e-03 eta: 7:16:45 time: 0.8231 data_time: 0.0315 memory: 16201 loss_prob: 0.3597 loss_thr: 0.2620 loss_db: 0.0633 loss: 0.6849 2022/08/30 18:20:41 - mmengine - INFO - Epoch(train) [857][40/63] lr: 2.2695e-03 eta: 7:16:32 time: 0.8139 data_time: 0.0314 memory: 16201 loss_prob: 0.3562 loss_thr: 0.2451 loss_db: 0.0625 loss: 0.6638 2022/08/30 18:20:46 - mmengine - INFO - Epoch(train) [857][45/63] lr: 2.2695e-03 eta: 7:16:32 time: 0.8661 data_time: 0.0297 memory: 16201 loss_prob: 0.3618 loss_thr: 0.2535 loss_db: 0.0654 loss: 0.6807 2022/08/30 18:20:52 - mmengine - INFO - Epoch(train) [857][50/63] lr: 2.2695e-03 eta: 7:16:19 time: 1.0534 data_time: 0.0406 memory: 16201 loss_prob: 0.3689 loss_thr: 0.2644 loss_db: 0.0664 loss: 0.6997 2022/08/30 18:20:57 - mmengine - INFO - Epoch(train) [857][55/63] lr: 2.2695e-03 eta: 7:16:19 time: 1.1492 data_time: 0.0408 memory: 16201 loss_prob: 0.3685 loss_thr: 0.2610 loss_db: 0.0648 loss: 0.6943 2022/08/30 18:21:02 - mmengine - INFO - Epoch(train) [857][60/63] lr: 2.2695e-03 eta: 7:16:06 time: 1.0459 data_time: 0.0322 memory: 16201 loss_prob: 0.3707 loss_thr: 0.2566 loss_db: 0.0655 loss: 0.6929 2022/08/30 18:21:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:21:12 - mmengine - INFO - Epoch(train) [858][5/63] lr: 2.2636e-03 eta: 7:16:06 time: 1.1695 data_time: 0.2705 memory: 16201 loss_prob: 0.4079 loss_thr: 0.2724 loss_db: 0.0745 loss: 0.7548 2022/08/30 18:21:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:21:17 - mmengine - INFO - Epoch(train) [858][10/63] lr: 2.2636e-03 eta: 7:15:49 time: 1.2752 data_time: 0.2695 memory: 16201 loss_prob: 0.3870 loss_thr: 0.2746 loss_db: 0.0693 loss: 0.7308 2022/08/30 18:21:23 - mmengine - INFO - Epoch(train) [858][15/63] lr: 2.2636e-03 eta: 7:15:49 time: 1.0832 data_time: 0.0295 memory: 16201 loss_prob: 0.3773 loss_thr: 0.2734 loss_db: 0.0645 loss: 0.7152 2022/08/30 18:21:28 - mmengine - INFO - Epoch(train) [858][20/63] lr: 2.2636e-03 eta: 7:15:37 time: 1.0581 data_time: 0.0311 memory: 16201 loss_prob: 0.3999 loss_thr: 0.2814 loss_db: 0.0696 loss: 0.7509 2022/08/30 18:21:33 - mmengine - INFO - Epoch(train) [858][25/63] lr: 2.2636e-03 eta: 7:15:37 time: 1.0265 data_time: 0.0368 memory: 16201 loss_prob: 0.3708 loss_thr: 0.2781 loss_db: 0.0670 loss: 0.7159 2022/08/30 18:21:38 - mmengine - INFO - Epoch(train) [858][30/63] lr: 2.2636e-03 eta: 7:15:24 time: 1.0318 data_time: 0.0328 memory: 16201 loss_prob: 0.3457 loss_thr: 0.2743 loss_db: 0.0623 loss: 0.6823 2022/08/30 18:21:44 - mmengine - INFO - Epoch(train) [858][35/63] lr: 2.2636e-03 eta: 7:15:24 time: 1.0749 data_time: 0.0385 memory: 16201 loss_prob: 0.3549 loss_thr: 0.2700 loss_db: 0.0623 loss: 0.6873 2022/08/30 18:21:49 - mmengine - INFO - Epoch(train) [858][40/63] lr: 2.2636e-03 eta: 7:15:11 time: 1.1155 data_time: 0.0437 memory: 16201 loss_prob: 0.3547 loss_thr: 0.2538 loss_db: 0.0623 loss: 0.6708 2022/08/30 18:21:54 - mmengine - INFO - Epoch(train) [858][45/63] lr: 2.2636e-03 eta: 7:15:11 time: 1.0622 data_time: 0.0285 memory: 16201 loss_prob: 0.3745 loss_thr: 0.2668 loss_db: 0.0665 loss: 0.7077 2022/08/30 18:22:00 - mmengine - INFO - Epoch(train) [858][50/63] lr: 2.2636e-03 eta: 7:14:58 time: 1.0430 data_time: 0.0343 memory: 16201 loss_prob: 0.3819 loss_thr: 0.2817 loss_db: 0.0679 loss: 0.7316 2022/08/30 18:22:05 - mmengine - INFO - Epoch(train) [858][55/63] lr: 2.2636e-03 eta: 7:14:58 time: 1.0549 data_time: 0.0348 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2594 loss_db: 0.0620 loss: 0.6660 2022/08/30 18:22:10 - mmengine - INFO - Epoch(train) [858][60/63] lr: 2.2636e-03 eta: 7:14:46 time: 1.0470 data_time: 0.0297 memory: 16201 loss_prob: 0.3775 loss_thr: 0.2891 loss_db: 0.0681 loss: 0.7347 2022/08/30 18:22:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:22:20 - mmengine - INFO - Epoch(train) [859][5/63] lr: 2.2576e-03 eta: 7:14:46 time: 1.2099 data_time: 0.2027 memory: 16201 loss_prob: 0.3669 loss_thr: 0.2803 loss_db: 0.0639 loss: 0.7110 2022/08/30 18:22:25 - mmengine - INFO - Epoch(train) [859][10/63] lr: 2.2576e-03 eta: 7:14:29 time: 1.2405 data_time: 0.2126 memory: 16201 loss_prob: 0.3253 loss_thr: 0.2386 loss_db: 0.0589 loss: 0.6228 2022/08/30 18:22:31 - mmengine - INFO - Epoch(train) [859][15/63] lr: 2.2576e-03 eta: 7:14:29 time: 1.0834 data_time: 0.0393 memory: 16201 loss_prob: 0.3654 loss_thr: 0.2610 loss_db: 0.0673 loss: 0.6938 2022/08/30 18:22:36 - mmengine - INFO - Epoch(train) [859][20/63] lr: 2.2576e-03 eta: 7:14:16 time: 1.0957 data_time: 0.0323 memory: 16201 loss_prob: 0.3913 loss_thr: 0.2805 loss_db: 0.0678 loss: 0.7396 2022/08/30 18:22:41 - mmengine - INFO - Epoch(train) [859][25/63] lr: 2.2576e-03 eta: 7:14:16 time: 1.0475 data_time: 0.0350 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2714 loss_db: 0.0615 loss: 0.6901 2022/08/30 18:22:46 - mmengine - INFO - Epoch(train) [859][30/63] lr: 2.2576e-03 eta: 7:14:03 time: 0.9603 data_time: 0.0284 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2791 loss_db: 0.0660 loss: 0.7102 2022/08/30 18:22:50 - mmengine - INFO - Epoch(train) [859][35/63] lr: 2.2576e-03 eta: 7:14:03 time: 0.8695 data_time: 0.0284 memory: 16201 loss_prob: 0.3662 loss_thr: 0.2672 loss_db: 0.0659 loss: 0.6994 2022/08/30 18:22:54 - mmengine - INFO - Epoch(train) [859][40/63] lr: 2.2576e-03 eta: 7:13:49 time: 0.8433 data_time: 0.0258 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2610 loss_db: 0.0632 loss: 0.6862 2022/08/30 18:22:58 - mmengine - INFO - Epoch(train) [859][45/63] lr: 2.2576e-03 eta: 7:13:49 time: 0.8237 data_time: 0.0283 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2665 loss_db: 0.0645 loss: 0.6945 2022/08/30 18:23:04 - mmengine - INFO - Epoch(train) [859][50/63] lr: 2.2576e-03 eta: 7:13:36 time: 0.9761 data_time: 0.0807 memory: 16201 loss_prob: 0.3903 loss_thr: 0.2798 loss_db: 0.0711 loss: 0.7412 2022/08/30 18:23:08 - mmengine - INFO - Epoch(train) [859][55/63] lr: 2.2576e-03 eta: 7:13:36 time: 0.9974 data_time: 0.0760 memory: 16201 loss_prob: 0.4269 loss_thr: 0.2948 loss_db: 0.0744 loss: 0.7960 2022/08/30 18:23:13 - mmengine - INFO - Epoch(train) [859][60/63] lr: 2.2576e-03 eta: 7:13:23 time: 0.8739 data_time: 0.0291 memory: 16201 loss_prob: 0.4250 loss_thr: 0.2979 loss_db: 0.0740 loss: 0.7968 2022/08/30 18:23:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:23:21 - mmengine - INFO - Epoch(train) [860][5/63] lr: 2.2517e-03 eta: 7:13:23 time: 1.0016 data_time: 0.2131 memory: 16201 loss_prob: 0.4036 loss_thr: 0.2953 loss_db: 0.0729 loss: 0.7718 2022/08/30 18:23:25 - mmengine - INFO - Epoch(train) [860][10/63] lr: 2.2517e-03 eta: 7:13:05 time: 1.0389 data_time: 0.2235 memory: 16201 loss_prob: 0.4091 loss_thr: 0.2887 loss_db: 0.0733 loss: 0.7711 2022/08/30 18:23:29 - mmengine - INFO - Epoch(train) [860][15/63] lr: 2.2517e-03 eta: 7:13:05 time: 0.8255 data_time: 0.0265 memory: 16201 loss_prob: 0.3826 loss_thr: 0.2741 loss_db: 0.0678 loss: 0.7245 2022/08/30 18:23:33 - mmengine - INFO - Epoch(train) [860][20/63] lr: 2.2517e-03 eta: 7:12:51 time: 0.8096 data_time: 0.0214 memory: 16201 loss_prob: 0.3566 loss_thr: 0.2605 loss_db: 0.0626 loss: 0.6796 2022/08/30 18:23:38 - mmengine - INFO - Epoch(train) [860][25/63] lr: 2.2517e-03 eta: 7:12:51 time: 0.8234 data_time: 0.0277 memory: 16201 loss_prob: 0.3637 loss_thr: 0.2702 loss_db: 0.0636 loss: 0.6974 2022/08/30 18:23:42 - mmengine - INFO - Epoch(train) [860][30/63] lr: 2.2517e-03 eta: 7:12:38 time: 0.8380 data_time: 0.0315 memory: 16201 loss_prob: 0.3554 loss_thr: 0.2602 loss_db: 0.0628 loss: 0.6785 2022/08/30 18:23:46 - mmengine - INFO - Epoch(train) [860][35/63] lr: 2.2517e-03 eta: 7:12:38 time: 0.8171 data_time: 0.0275 memory: 16201 loss_prob: 0.3938 loss_thr: 0.2683 loss_db: 0.0680 loss: 0.7301 2022/08/30 18:23:50 - mmengine - INFO - Epoch(train) [860][40/63] lr: 2.2517e-03 eta: 7:12:24 time: 0.8665 data_time: 0.0258 memory: 16201 loss_prob: 0.4218 loss_thr: 0.2906 loss_db: 0.0746 loss: 0.7869 2022/08/30 18:23:55 - mmengine - INFO - Epoch(train) [860][45/63] lr: 2.2517e-03 eta: 7:12:24 time: 0.9546 data_time: 0.0345 memory: 16201 loss_prob: 0.3908 loss_thr: 0.2794 loss_db: 0.0703 loss: 0.7406 2022/08/30 18:24:01 - mmengine - INFO - Epoch(train) [860][50/63] lr: 2.2517e-03 eta: 7:12:12 time: 1.0651 data_time: 0.0375 memory: 16201 loss_prob: 0.3919 loss_thr: 0.2751 loss_db: 0.0697 loss: 0.7368 2022/08/30 18:24:07 - mmengine - INFO - Epoch(train) [860][55/63] lr: 2.2517e-03 eta: 7:12:12 time: 1.1532 data_time: 0.0373 memory: 16201 loss_prob: 0.3785 loss_thr: 0.2625 loss_db: 0.0677 loss: 0.7087 2022/08/30 18:24:12 - mmengine - INFO - Epoch(train) [860][60/63] lr: 2.2517e-03 eta: 7:11:59 time: 1.1253 data_time: 0.0316 memory: 16201 loss_prob: 0.3685 loss_thr: 0.2613 loss_db: 0.0643 loss: 0.6941 2022/08/30 18:24:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:24:15 - mmengine - INFO - Saving checkpoint at 860 epochs 2022/08/30 18:24:24 - mmengine - INFO - Epoch(val) [860][5/32] eta: 7:11:59 time: 0.6480 data_time: 0.1228 memory: 16201 2022/08/30 18:24:27 - mmengine - INFO - Epoch(val) [860][10/32] eta: 0:00:16 time: 0.7359 data_time: 0.1599 memory: 15734 2022/08/30 18:24:30 - mmengine - INFO - Epoch(val) [860][15/32] eta: 0:00:16 time: 0.6105 data_time: 0.0508 memory: 15734 2022/08/30 18:24:34 - mmengine - INFO - Epoch(val) [860][20/32] eta: 0:00:08 time: 0.7007 data_time: 0.0540 memory: 15734 2022/08/30 18:24:37 - mmengine - INFO - Epoch(val) [860][25/32] eta: 0:00:08 time: 0.7070 data_time: 0.0580 memory: 15734 2022/08/30 18:24:39 - mmengine - INFO - Epoch(val) [860][30/32] eta: 0:00:01 time: 0.5732 data_time: 0.0246 memory: 15734 2022/08/30 18:24:40 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 18:24:40 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8560, precision: 0.7973, hmean: 0.8256 2022/08/30 18:24:40 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8560, precision: 0.8231, hmean: 0.8393 2022/08/30 18:24:40 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8546, precision: 0.8448, hmean: 0.8497 2022/08/30 18:24:40 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8532, precision: 0.8657, hmean: 0.8594 2022/08/30 18:24:40 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8440, precision: 0.8840, hmean: 0.8635 2022/08/30 18:24:40 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8113, precision: 0.9143, hmean: 0.8597 2022/08/30 18:24:40 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.3857, precision: 0.9558, hmean: 0.5496 2022/08/30 18:24:40 - mmengine - INFO - Epoch(val) [860][32/32] icdar/precision: 0.8840 icdar/recall: 0.8440 icdar/hmean: 0.8635 2022/08/30 18:24:48 - mmengine - INFO - Epoch(train) [861][5/63] lr: 2.2457e-03 eta: 0:00:01 time: 1.2778 data_time: 0.2270 memory: 16201 loss_prob: 0.4088 loss_thr: 0.2916 loss_db: 0.0728 loss: 0.7732 2022/08/30 18:24:54 - mmengine - INFO - Epoch(train) [861][10/63] lr: 2.2457e-03 eta: 7:11:43 time: 1.3802 data_time: 0.2329 memory: 16201 loss_prob: 0.3961 loss_thr: 0.2851 loss_db: 0.0695 loss: 0.7508 2022/08/30 18:25:00 - mmengine - INFO - Epoch(train) [861][15/63] lr: 2.2457e-03 eta: 7:11:43 time: 1.1868 data_time: 0.0362 memory: 16201 loss_prob: 0.4033 loss_thr: 0.2768 loss_db: 0.0699 loss: 0.7500 2022/08/30 18:25:05 - mmengine - INFO - Epoch(train) [861][20/63] lr: 2.2457e-03 eta: 7:11:30 time: 1.0339 data_time: 0.0303 memory: 16201 loss_prob: 0.3775 loss_thr: 0.2668 loss_db: 0.0676 loss: 0.7118 2022/08/30 18:25:09 - mmengine - INFO - Epoch(train) [861][25/63] lr: 2.2457e-03 eta: 7:11:30 time: 0.8786 data_time: 0.0320 memory: 16201 loss_prob: 0.3822 loss_thr: 0.2650 loss_db: 0.0665 loss: 0.7138 2022/08/30 18:25:13 - mmengine - INFO - Epoch(train) [861][30/63] lr: 2.2457e-03 eta: 7:11:17 time: 0.8737 data_time: 0.0263 memory: 16201 loss_prob: 0.3610 loss_thr: 0.2602 loss_db: 0.0625 loss: 0.6837 2022/08/30 18:25:18 - mmengine - INFO - Epoch(train) [861][35/63] lr: 2.2457e-03 eta: 7:11:17 time: 0.9402 data_time: 0.0272 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2483 loss_db: 0.0591 loss: 0.6319 2022/08/30 18:25:24 - mmengine - INFO - Epoch(train) [861][40/63] lr: 2.2457e-03 eta: 7:11:04 time: 1.0305 data_time: 0.0372 memory: 16201 loss_prob: 0.3602 loss_thr: 0.2537 loss_db: 0.0646 loss: 0.6786 2022/08/30 18:25:29 - mmengine - INFO - Epoch(train) [861][45/63] lr: 2.2457e-03 eta: 7:11:04 time: 1.0614 data_time: 0.0327 memory: 16201 loss_prob: 0.3859 loss_thr: 0.2790 loss_db: 0.0674 loss: 0.7324 2022/08/30 18:25:35 - mmengine - INFO - Epoch(train) [861][50/63] lr: 2.2457e-03 eta: 7:10:51 time: 1.1074 data_time: 0.0433 memory: 16201 loss_prob: 0.3724 loss_thr: 0.2742 loss_db: 0.0653 loss: 0.7118 2022/08/30 18:25:39 - mmengine - INFO - Epoch(train) [861][55/63] lr: 2.2457e-03 eta: 7:10:51 time: 1.0388 data_time: 0.0507 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2740 loss_db: 0.0672 loss: 0.7183 2022/08/30 18:25:44 - mmengine - INFO - Epoch(train) [861][60/63] lr: 2.2457e-03 eta: 7:10:38 time: 0.8825 data_time: 0.0421 memory: 16201 loss_prob: 0.3905 loss_thr: 0.2799 loss_db: 0.0680 loss: 0.7385 2022/08/30 18:25:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:25:52 - mmengine - INFO - Epoch(train) [862][5/63] lr: 2.2397e-03 eta: 7:10:38 time: 1.0536 data_time: 0.2225 memory: 16201 loss_prob: 0.3814 loss_thr: 0.2581 loss_db: 0.0670 loss: 0.7065 2022/08/30 18:25:59 - mmengine - INFO - Epoch(train) [862][10/63] lr: 2.2397e-03 eta: 7:10:21 time: 1.3889 data_time: 0.2411 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2572 loss_db: 0.0647 loss: 0.6869 2022/08/30 18:26:04 - mmengine - INFO - Epoch(train) [862][15/63] lr: 2.2397e-03 eta: 7:10:21 time: 1.1804 data_time: 0.0327 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2734 loss_db: 0.0657 loss: 0.7129 2022/08/30 18:26:09 - mmengine - INFO - Epoch(train) [862][20/63] lr: 2.2397e-03 eta: 7:10:08 time: 0.9788 data_time: 0.0276 memory: 16201 loss_prob: 0.3840 loss_thr: 0.2664 loss_db: 0.0676 loss: 0.7180 2022/08/30 18:26:13 - mmengine - INFO - Epoch(train) [862][25/63] lr: 2.2397e-03 eta: 7:10:08 time: 0.9215 data_time: 0.0384 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2598 loss_db: 0.0681 loss: 0.7136 2022/08/30 18:26:19 - mmengine - INFO - Epoch(train) [862][30/63] lr: 2.2397e-03 eta: 7:09:55 time: 0.9488 data_time: 0.0239 memory: 16201 loss_prob: 0.3701 loss_thr: 0.2647 loss_db: 0.0663 loss: 0.7011 2022/08/30 18:26:24 - mmengine - INFO - Epoch(train) [862][35/63] lr: 2.2397e-03 eta: 7:09:55 time: 1.0572 data_time: 0.0286 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2552 loss_db: 0.0625 loss: 0.6675 2022/08/30 18:26:29 - mmengine - INFO - Epoch(train) [862][40/63] lr: 2.2397e-03 eta: 7:09:42 time: 1.0141 data_time: 0.0302 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2524 loss_db: 0.0610 loss: 0.6599 2022/08/30 18:26:34 - mmengine - INFO - Epoch(train) [862][45/63] lr: 2.2397e-03 eta: 7:09:42 time: 1.0024 data_time: 0.0297 memory: 16201 loss_prob: 0.3874 loss_thr: 0.2615 loss_db: 0.0648 loss: 0.7137 2022/08/30 18:26:40 - mmengine - INFO - Epoch(train) [862][50/63] lr: 2.2397e-03 eta: 7:09:30 time: 1.0764 data_time: 0.0439 memory: 16201 loss_prob: 0.4243 loss_thr: 0.2778 loss_db: 0.0680 loss: 0.7700 2022/08/30 18:26:43 - mmengine - INFO - Epoch(train) [862][55/63] lr: 2.2397e-03 eta: 7:09:30 time: 0.9307 data_time: 0.0320 memory: 16201 loss_prob: 0.3962 loss_thr: 0.2811 loss_db: 0.0682 loss: 0.7454 2022/08/30 18:26:48 - mmengine - INFO - Epoch(train) [862][60/63] lr: 2.2397e-03 eta: 7:09:16 time: 0.8129 data_time: 0.0222 memory: 16201 loss_prob: 0.3695 loss_thr: 0.2701 loss_db: 0.0660 loss: 0.7056 2022/08/30 18:26:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:26:56 - mmengine - INFO - Epoch(train) [863][5/63] lr: 2.2338e-03 eta: 7:09:16 time: 1.0217 data_time: 0.2233 memory: 16201 loss_prob: 0.3650 loss_thr: 0.2633 loss_db: 0.0648 loss: 0.6931 2022/08/30 18:27:02 - mmengine - INFO - Epoch(train) [863][10/63] lr: 2.2338e-03 eta: 7:08:59 time: 1.1950 data_time: 0.2453 memory: 16201 loss_prob: 0.3566 loss_thr: 0.2720 loss_db: 0.0653 loss: 0.6939 2022/08/30 18:27:08 - mmengine - INFO - Epoch(train) [863][15/63] lr: 2.2338e-03 eta: 7:08:59 time: 1.1383 data_time: 0.0405 memory: 16201 loss_prob: 0.3725 loss_thr: 0.2765 loss_db: 0.0666 loss: 0.7157 2022/08/30 18:27:13 - mmengine - INFO - Epoch(train) [863][20/63] lr: 2.2338e-03 eta: 7:08:47 time: 1.1405 data_time: 0.0356 memory: 16201 loss_prob: 0.3918 loss_thr: 0.2710 loss_db: 0.0682 loss: 0.7311 2022/08/30 18:27:19 - mmengine - INFO - Epoch(train) [863][25/63] lr: 2.2338e-03 eta: 7:08:47 time: 1.1455 data_time: 0.0404 memory: 16201 loss_prob: 0.3546 loss_thr: 0.2598 loss_db: 0.0610 loss: 0.6754 2022/08/30 18:27:24 - mmengine - INFO - Epoch(train) [863][30/63] lr: 2.2338e-03 eta: 7:08:34 time: 1.1134 data_time: 0.0352 memory: 16201 loss_prob: 0.3477 loss_thr: 0.2576 loss_db: 0.0611 loss: 0.6665 2022/08/30 18:27:31 - mmengine - INFO - Epoch(train) [863][35/63] lr: 2.2338e-03 eta: 7:08:34 time: 1.1890 data_time: 0.0415 memory: 16201 loss_prob: 0.3969 loss_thr: 0.2742 loss_db: 0.0708 loss: 0.7418 2022/08/30 18:27:35 - mmengine - INFO - Epoch(train) [863][40/63] lr: 2.2338e-03 eta: 7:08:22 time: 1.0933 data_time: 0.0358 memory: 16201 loss_prob: 0.4369 loss_thr: 0.2856 loss_db: 0.0754 loss: 0.7978 2022/08/30 18:27:39 - mmengine - INFO - Epoch(train) [863][45/63] lr: 2.2338e-03 eta: 7:08:22 time: 0.8579 data_time: 0.0239 memory: 16201 loss_prob: 0.4377 loss_thr: 0.2852 loss_db: 0.0746 loss: 0.7974 2022/08/30 18:27:44 - mmengine - INFO - Epoch(train) [863][50/63] lr: 2.2338e-03 eta: 7:08:08 time: 0.8399 data_time: 0.0307 memory: 16201 loss_prob: 0.4169 loss_thr: 0.2802 loss_db: 0.0753 loss: 0.7724 2022/08/30 18:27:49 - mmengine - INFO - Epoch(train) [863][55/63] lr: 2.2338e-03 eta: 7:08:08 time: 0.9156 data_time: 0.0336 memory: 16201 loss_prob: 0.3802 loss_thr: 0.2637 loss_db: 0.0692 loss: 0.7131 2022/08/30 18:27:53 - mmengine - INFO - Epoch(train) [863][60/63] lr: 2.2338e-03 eta: 7:07:55 time: 0.9545 data_time: 0.0288 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2718 loss_db: 0.0639 loss: 0.6920 2022/08/30 18:27:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:28:04 - mmengine - INFO - Epoch(train) [864][5/63] lr: 2.2278e-03 eta: 7:07:55 time: 1.2859 data_time: 0.2538 memory: 16201 loss_prob: 0.3742 loss_thr: 0.2785 loss_db: 0.0680 loss: 0.7208 2022/08/30 18:28:10 - mmengine - INFO - Epoch(train) [864][10/63] lr: 2.2278e-03 eta: 7:07:38 time: 1.3734 data_time: 0.2697 memory: 16201 loss_prob: 0.3827 loss_thr: 0.2730 loss_db: 0.0683 loss: 0.7239 2022/08/30 18:28:15 - mmengine - INFO - Epoch(train) [864][15/63] lr: 2.2278e-03 eta: 7:07:38 time: 1.0996 data_time: 0.0390 memory: 16201 loss_prob: 0.3784 loss_thr: 0.2700 loss_db: 0.0665 loss: 0.7149 2022/08/30 18:28:19 - mmengine - INFO - Epoch(train) [864][20/63] lr: 2.2278e-03 eta: 7:07:25 time: 0.9538 data_time: 0.0360 memory: 16201 loss_prob: 0.3856 loss_thr: 0.2829 loss_db: 0.0691 loss: 0.7376 2022/08/30 18:28:23 - mmengine - INFO - Epoch(train) [864][25/63] lr: 2.2278e-03 eta: 7:07:25 time: 0.8115 data_time: 0.0297 memory: 16201 loss_prob: 0.3882 loss_thr: 0.2789 loss_db: 0.0704 loss: 0.7375 2022/08/30 18:28:28 - mmengine - INFO - Epoch(train) [864][30/63] lr: 2.2278e-03 eta: 7:07:12 time: 0.8516 data_time: 0.0223 memory: 16201 loss_prob: 0.3940 loss_thr: 0.2837 loss_db: 0.0697 loss: 0.7473 2022/08/30 18:28:33 - mmengine - INFO - Epoch(train) [864][35/63] lr: 2.2278e-03 eta: 7:07:12 time: 0.9572 data_time: 0.0290 memory: 16201 loss_prob: 0.4035 loss_thr: 0.3004 loss_db: 0.0722 loss: 0.7762 2022/08/30 18:28:38 - mmengine - INFO - Epoch(train) [864][40/63] lr: 2.2278e-03 eta: 7:06:59 time: 1.0127 data_time: 0.0293 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2812 loss_db: 0.0712 loss: 0.7510 2022/08/30 18:28:43 - mmengine - INFO - Epoch(train) [864][45/63] lr: 2.2278e-03 eta: 7:06:59 time: 1.0242 data_time: 0.0321 memory: 16201 loss_prob: 0.4010 loss_thr: 0.2685 loss_db: 0.0704 loss: 0.7399 2022/08/30 18:28:49 - mmengine - INFO - Epoch(train) [864][50/63] lr: 2.2278e-03 eta: 7:06:47 time: 1.1278 data_time: 0.0348 memory: 16201 loss_prob: 0.3825 loss_thr: 0.2609 loss_db: 0.0678 loss: 0.7112 2022/08/30 18:28:54 - mmengine - INFO - Epoch(train) [864][55/63] lr: 2.2278e-03 eta: 7:06:47 time: 1.1487 data_time: 0.0373 memory: 16201 loss_prob: 0.3700 loss_thr: 0.2570 loss_db: 0.0643 loss: 0.6913 2022/08/30 18:29:00 - mmengine - INFO - Epoch(train) [864][60/63] lr: 2.2278e-03 eta: 7:06:34 time: 1.0958 data_time: 0.0398 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2644 loss_db: 0.0644 loss: 0.6941 2022/08/30 18:29:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:29:11 - mmengine - INFO - Epoch(train) [865][5/63] lr: 2.2218e-03 eta: 7:06:34 time: 1.3380 data_time: 0.2674 memory: 16201 loss_prob: 0.3928 loss_thr: 0.2776 loss_db: 0.0696 loss: 0.7400 2022/08/30 18:29:16 - mmengine - INFO - Epoch(train) [865][10/63] lr: 2.2218e-03 eta: 7:06:18 time: 1.3593 data_time: 0.2759 memory: 16201 loss_prob: 0.4009 loss_thr: 0.2734 loss_db: 0.0705 loss: 0.7449 2022/08/30 18:29:21 - mmengine - INFO - Epoch(train) [865][15/63] lr: 2.2218e-03 eta: 7:06:18 time: 0.9230 data_time: 0.0314 memory: 16201 loss_prob: 0.3909 loss_thr: 0.2773 loss_db: 0.0692 loss: 0.7374 2022/08/30 18:29:25 - mmengine - INFO - Epoch(train) [865][20/63] lr: 2.2218e-03 eta: 7:06:04 time: 0.8525 data_time: 0.0205 memory: 16201 loss_prob: 0.3722 loss_thr: 0.2765 loss_db: 0.0651 loss: 0.7138 2022/08/30 18:29:29 - mmengine - INFO - Epoch(train) [865][25/63] lr: 2.2218e-03 eta: 7:06:04 time: 0.8532 data_time: 0.0331 memory: 16201 loss_prob: 0.4058 loss_thr: 0.2896 loss_db: 0.0705 loss: 0.7658 2022/08/30 18:29:33 - mmengine - INFO - Epoch(train) [865][30/63] lr: 2.2218e-03 eta: 7:05:50 time: 0.8297 data_time: 0.0255 memory: 16201 loss_prob: 0.3952 loss_thr: 0.2830 loss_db: 0.0703 loss: 0.7485 2022/08/30 18:29:38 - mmengine - INFO - Epoch(train) [865][35/63] lr: 2.2218e-03 eta: 7:05:50 time: 0.9097 data_time: 0.0292 memory: 16201 loss_prob: 0.4041 loss_thr: 0.2849 loss_db: 0.0723 loss: 0.7614 2022/08/30 18:29:43 - mmengine - INFO - Epoch(train) [865][40/63] lr: 2.2218e-03 eta: 7:05:38 time: 1.0191 data_time: 0.0357 memory: 16201 loss_prob: 0.4112 loss_thr: 0.2862 loss_db: 0.0738 loss: 0.7713 2022/08/30 18:29:49 - mmengine - INFO - Epoch(train) [865][45/63] lr: 2.2218e-03 eta: 7:05:38 time: 1.0699 data_time: 0.0376 memory: 16201 loss_prob: 0.3798 loss_thr: 0.2823 loss_db: 0.0685 loss: 0.7307 2022/08/30 18:29:55 - mmengine - INFO - Epoch(train) [865][50/63] lr: 2.2218e-03 eta: 7:05:25 time: 1.1696 data_time: 0.0505 memory: 16201 loss_prob: 0.3588 loss_thr: 0.2768 loss_db: 0.0651 loss: 0.7007 2022/08/30 18:30:01 - mmengine - INFO - Epoch(train) [865][55/63] lr: 2.2218e-03 eta: 7:05:25 time: 1.1666 data_time: 0.0355 memory: 16201 loss_prob: 0.3850 loss_thr: 0.2782 loss_db: 0.0698 loss: 0.7329 2022/08/30 18:30:05 - mmengine - INFO - Epoch(train) [865][60/63] lr: 2.2218e-03 eta: 7:05:13 time: 1.0413 data_time: 0.0305 memory: 16201 loss_prob: 0.3951 loss_thr: 0.2760 loss_db: 0.0702 loss: 0.7412 2022/08/30 18:30:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:30:14 - mmengine - INFO - Epoch(train) [866][5/63] lr: 2.2159e-03 eta: 7:05:13 time: 1.0768 data_time: 0.2205 memory: 16201 loss_prob: 0.3751 loss_thr: 0.2780 loss_db: 0.0665 loss: 0.7195 2022/08/30 18:30:19 - mmengine - INFO - Epoch(train) [866][10/63] lr: 2.2159e-03 eta: 7:04:55 time: 1.0832 data_time: 0.2356 memory: 16201 loss_prob: 0.3829 loss_thr: 0.2769 loss_db: 0.0685 loss: 0.7283 2022/08/30 18:30:24 - mmengine - INFO - Epoch(train) [866][15/63] lr: 2.2159e-03 eta: 7:04:55 time: 0.9959 data_time: 0.0300 memory: 16201 loss_prob: 0.4117 loss_thr: 0.2812 loss_db: 0.0732 loss: 0.7661 2022/08/30 18:30:29 - mmengine - INFO - Epoch(train) [866][20/63] lr: 2.2159e-03 eta: 7:04:42 time: 1.0608 data_time: 0.0265 memory: 16201 loss_prob: 0.4181 loss_thr: 0.2799 loss_db: 0.0724 loss: 0.7704 2022/08/30 18:30:35 - mmengine - INFO - Epoch(train) [866][25/63] lr: 2.2159e-03 eta: 7:04:42 time: 1.1181 data_time: 0.0502 memory: 16201 loss_prob: 0.3678 loss_thr: 0.2563 loss_db: 0.0643 loss: 0.6884 2022/08/30 18:30:40 - mmengine - INFO - Epoch(train) [866][30/63] lr: 2.2159e-03 eta: 7:04:30 time: 1.0829 data_time: 0.0429 memory: 16201 loss_prob: 0.3528 loss_thr: 0.2510 loss_db: 0.0630 loss: 0.6668 2022/08/30 18:30:46 - mmengine - INFO - Epoch(train) [866][35/63] lr: 2.2159e-03 eta: 7:04:30 time: 1.0312 data_time: 0.0673 memory: 16201 loss_prob: 0.3924 loss_thr: 0.2740 loss_db: 0.0691 loss: 0.7354 2022/08/30 18:30:51 - mmengine - INFO - Epoch(train) [866][40/63] lr: 2.2159e-03 eta: 7:04:17 time: 1.1001 data_time: 0.0765 memory: 16201 loss_prob: 0.4071 loss_thr: 0.2920 loss_db: 0.0721 loss: 0.7711 2022/08/30 18:30:56 - mmengine - INFO - Epoch(train) [866][45/63] lr: 2.2159e-03 eta: 7:04:17 time: 0.9915 data_time: 0.0766 memory: 16201 loss_prob: 0.3801 loss_thr: 0.2757 loss_db: 0.0674 loss: 0.7232 2022/08/30 18:31:00 - mmengine - INFO - Epoch(train) [866][50/63] lr: 2.2159e-03 eta: 7:04:04 time: 0.8805 data_time: 0.0807 memory: 16201 loss_prob: 0.3689 loss_thr: 0.2591 loss_db: 0.0655 loss: 0.6934 2022/08/30 18:31:05 - mmengine - INFO - Epoch(train) [866][55/63] lr: 2.2159e-03 eta: 7:04:04 time: 0.9007 data_time: 0.0500 memory: 16201 loss_prob: 0.3706 loss_thr: 0.2599 loss_db: 0.0659 loss: 0.6964 2022/08/30 18:31:09 - mmengine - INFO - Epoch(train) [866][60/63] lr: 2.2159e-03 eta: 7:03:51 time: 0.9398 data_time: 0.0793 memory: 16201 loss_prob: 0.3664 loss_thr: 0.2593 loss_db: 0.0660 loss: 0.6918 2022/08/30 18:31:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:31:20 - mmengine - INFO - Epoch(train) [867][5/63] lr: 2.2099e-03 eta: 7:03:51 time: 1.2280 data_time: 0.2895 memory: 16201 loss_prob: 0.3523 loss_thr: 0.2657 loss_db: 0.0633 loss: 0.6812 2022/08/30 18:31:26 - mmengine - INFO - Epoch(train) [867][10/63] lr: 2.2099e-03 eta: 7:03:35 time: 1.4519 data_time: 0.3289 memory: 16201 loss_prob: 0.3660 loss_thr: 0.2718 loss_db: 0.0654 loss: 0.7032 2022/08/30 18:31:32 - mmengine - INFO - Epoch(train) [867][15/63] lr: 2.2099e-03 eta: 7:03:35 time: 1.1555 data_time: 0.0711 memory: 16201 loss_prob: 0.3675 loss_thr: 0.2590 loss_db: 0.0662 loss: 0.6928 2022/08/30 18:31:38 - mmengine - INFO - Epoch(train) [867][20/63] lr: 2.2099e-03 eta: 7:03:22 time: 1.1269 data_time: 0.0688 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2514 loss_db: 0.0637 loss: 0.6803 2022/08/30 18:31:43 - mmengine - INFO - Epoch(train) [867][25/63] lr: 2.2099e-03 eta: 7:03:22 time: 1.1425 data_time: 0.0779 memory: 16201 loss_prob: 0.3942 loss_thr: 0.2688 loss_db: 0.0680 loss: 0.7310 2022/08/30 18:31:48 - mmengine - INFO - Epoch(train) [867][30/63] lr: 2.2099e-03 eta: 7:03:10 time: 1.0686 data_time: 0.0696 memory: 16201 loss_prob: 0.3901 loss_thr: 0.2620 loss_db: 0.0684 loss: 0.7205 2022/08/30 18:31:54 - mmengine - INFO - Epoch(train) [867][35/63] lr: 2.2099e-03 eta: 7:03:10 time: 1.0942 data_time: 0.0815 memory: 16201 loss_prob: 0.3924 loss_thr: 0.2626 loss_db: 0.0686 loss: 0.7236 2022/08/30 18:31:59 - mmengine - INFO - Epoch(train) [867][40/63] lr: 2.2099e-03 eta: 7:02:57 time: 1.1041 data_time: 0.0770 memory: 16201 loss_prob: 0.4491 loss_thr: 0.2883 loss_db: 0.0738 loss: 0.8112 2022/08/30 18:32:04 - mmengine - INFO - Epoch(train) [867][45/63] lr: 2.2099e-03 eta: 7:02:57 time: 0.9499 data_time: 0.0729 memory: 16201 loss_prob: 0.4595 loss_thr: 0.3009 loss_db: 0.0769 loss: 0.8373 2022/08/30 18:32:08 - mmengine - INFO - Epoch(train) [867][50/63] lr: 2.2099e-03 eta: 7:02:44 time: 0.8483 data_time: 0.0553 memory: 16201 loss_prob: 0.4028 loss_thr: 0.2864 loss_db: 0.0699 loss: 0.7590 2022/08/30 18:32:12 - mmengine - INFO - Epoch(train) [867][55/63] lr: 2.2099e-03 eta: 7:02:44 time: 0.8939 data_time: 0.0725 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2642 loss_db: 0.0614 loss: 0.6828 2022/08/30 18:32:18 - mmengine - INFO - Epoch(train) [867][60/63] lr: 2.2099e-03 eta: 7:02:31 time: 1.0082 data_time: 0.0764 memory: 16201 loss_prob: 0.3931 loss_thr: 0.2759 loss_db: 0.0708 loss: 0.7399 2022/08/30 18:32:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:32:29 - mmengine - INFO - Epoch(train) [868][5/63] lr: 2.2039e-03 eta: 7:02:31 time: 1.3213 data_time: 0.3117 memory: 16201 loss_prob: 0.3999 loss_thr: 0.2742 loss_db: 0.0708 loss: 0.7448 2022/08/30 18:32:35 - mmengine - INFO - Epoch(train) [868][10/63] lr: 2.2039e-03 eta: 7:02:14 time: 1.3715 data_time: 0.3137 memory: 16201 loss_prob: 0.3869 loss_thr: 0.2685 loss_db: 0.0681 loss: 0.7235 2022/08/30 18:32:41 - mmengine - INFO - Epoch(train) [868][15/63] lr: 2.2039e-03 eta: 7:02:14 time: 1.2045 data_time: 0.0842 memory: 16201 loss_prob: 0.4274 loss_thr: 0.2938 loss_db: 0.0754 loss: 0.7966 2022/08/30 18:32:46 - mmengine - INFO - Epoch(train) [868][20/63] lr: 2.2039e-03 eta: 7:02:02 time: 1.1108 data_time: 0.0729 memory: 16201 loss_prob: 0.4240 loss_thr: 0.2954 loss_db: 0.0746 loss: 0.7939 2022/08/30 18:32:52 - mmengine - INFO - Epoch(train) [868][25/63] lr: 2.2039e-03 eta: 7:02:02 time: 1.1166 data_time: 0.0805 memory: 16201 loss_prob: 0.3527 loss_thr: 0.2565 loss_db: 0.0621 loss: 0.6714 2022/08/30 18:32:58 - mmengine - INFO - Epoch(train) [868][30/63] lr: 2.2039e-03 eta: 7:01:50 time: 1.1449 data_time: 0.0744 memory: 16201 loss_prob: 0.3819 loss_thr: 0.2748 loss_db: 0.0687 loss: 0.7254 2022/08/30 18:33:02 - mmengine - INFO - Epoch(train) [868][35/63] lr: 2.2039e-03 eta: 7:01:50 time: 1.0082 data_time: 0.0759 memory: 16201 loss_prob: 0.3827 loss_thr: 0.2665 loss_db: 0.0696 loss: 0.7188 2022/08/30 18:33:06 - mmengine - INFO - Epoch(train) [868][40/63] lr: 2.2039e-03 eta: 7:01:36 time: 0.8681 data_time: 0.0731 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2485 loss_db: 0.0619 loss: 0.6537 2022/08/30 18:33:11 - mmengine - INFO - Epoch(train) [868][45/63] lr: 2.2039e-03 eta: 7:01:36 time: 0.8891 data_time: 0.0652 memory: 16201 loss_prob: 0.3445 loss_thr: 0.2535 loss_db: 0.0627 loss: 0.6607 2022/08/30 18:33:15 - mmengine - INFO - Epoch(train) [868][50/63] lr: 2.2039e-03 eta: 7:01:23 time: 0.8698 data_time: 0.0381 memory: 16201 loss_prob: 0.3908 loss_thr: 0.2723 loss_db: 0.0696 loss: 0.7328 2022/08/30 18:33:19 - mmengine - INFO - Epoch(train) [868][55/63] lr: 2.2039e-03 eta: 7:01:23 time: 0.8543 data_time: 0.0250 memory: 16201 loss_prob: 0.3884 loss_thr: 0.2711 loss_db: 0.0686 loss: 0.7281 2022/08/30 18:33:25 - mmengine - INFO - Epoch(train) [868][60/63] lr: 2.2039e-03 eta: 7:01:10 time: 1.0094 data_time: 0.0313 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2413 loss_db: 0.0599 loss: 0.6358 2022/08/30 18:33:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:33:35 - mmengine - INFO - Epoch(train) [869][5/63] lr: 2.1980e-03 eta: 7:01:10 time: 1.2134 data_time: 0.2301 memory: 16201 loss_prob: 0.3560 loss_thr: 0.2597 loss_db: 0.0636 loss: 0.6792 2022/08/30 18:33:39 - mmengine - INFO - Epoch(train) [869][10/63] lr: 2.1980e-03 eta: 7:00:52 time: 1.0694 data_time: 0.2386 memory: 16201 loss_prob: 0.3846 loss_thr: 0.2771 loss_db: 0.0692 loss: 0.7308 2022/08/30 18:33:43 - mmengine - INFO - Epoch(train) [869][15/63] lr: 2.1980e-03 eta: 7:00:52 time: 0.8209 data_time: 0.0268 memory: 16201 loss_prob: 0.3999 loss_thr: 0.2775 loss_db: 0.0710 loss: 0.7484 2022/08/30 18:33:47 - mmengine - INFO - Epoch(train) [869][20/63] lr: 2.1980e-03 eta: 7:00:39 time: 0.8660 data_time: 0.0270 memory: 16201 loss_prob: 0.3733 loss_thr: 0.2523 loss_db: 0.0657 loss: 0.6914 2022/08/30 18:33:52 - mmengine - INFO - Epoch(train) [869][25/63] lr: 2.1980e-03 eta: 7:00:39 time: 0.9604 data_time: 0.0328 memory: 16201 loss_prob: 0.3529 loss_thr: 0.2451 loss_db: 0.0629 loss: 0.6609 2022/08/30 18:33:58 - mmengine - INFO - Epoch(train) [869][30/63] lr: 2.1980e-03 eta: 7:00:26 time: 1.0334 data_time: 0.0319 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2319 loss_db: 0.0591 loss: 0.6131 2022/08/30 18:34:03 - mmengine - INFO - Epoch(train) [869][35/63] lr: 2.1980e-03 eta: 7:00:26 time: 1.0631 data_time: 0.0453 memory: 16201 loss_prob: 0.3920 loss_thr: 0.2689 loss_db: 0.0707 loss: 0.7316 2022/08/30 18:34:09 - mmengine - INFO - Epoch(train) [869][40/63] lr: 2.1980e-03 eta: 7:00:14 time: 1.0892 data_time: 0.0387 memory: 16201 loss_prob: 0.3977 loss_thr: 0.2726 loss_db: 0.0710 loss: 0.7414 2022/08/30 18:34:13 - mmengine - INFO - Epoch(train) [869][45/63] lr: 2.1980e-03 eta: 7:00:14 time: 1.0300 data_time: 0.0281 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2601 loss_db: 0.0652 loss: 0.6847 2022/08/30 18:34:18 - mmengine - INFO - Epoch(train) [869][50/63] lr: 2.1980e-03 eta: 7:00:01 time: 0.9271 data_time: 0.0360 memory: 16201 loss_prob: 0.3817 loss_thr: 0.2778 loss_db: 0.0669 loss: 0.7264 2022/08/30 18:34:22 - mmengine - INFO - Epoch(train) [869][55/63] lr: 2.1980e-03 eta: 7:00:01 time: 0.8545 data_time: 0.0294 memory: 16201 loss_prob: 0.3393 loss_thr: 0.2452 loss_db: 0.0588 loss: 0.6433 2022/08/30 18:34:26 - mmengine - INFO - Epoch(train) [869][60/63] lr: 2.1980e-03 eta: 6:59:47 time: 0.8221 data_time: 0.0249 memory: 16201 loss_prob: 0.3435 loss_thr: 0.2550 loss_db: 0.0611 loss: 0.6595 2022/08/30 18:34:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:34:36 - mmengine - INFO - Epoch(train) [870][5/63] lr: 2.1920e-03 eta: 6:59:47 time: 1.1353 data_time: 0.2231 memory: 16201 loss_prob: 0.4021 loss_thr: 0.2916 loss_db: 0.0704 loss: 0.7641 2022/08/30 18:34:41 - mmengine - INFO - Epoch(train) [870][10/63] lr: 2.1920e-03 eta: 6:59:30 time: 1.2579 data_time: 0.2344 memory: 16201 loss_prob: 0.3781 loss_thr: 0.2640 loss_db: 0.0673 loss: 0.7094 2022/08/30 18:34:47 - mmengine - INFO - Epoch(train) [870][15/63] lr: 2.1920e-03 eta: 6:59:30 time: 1.1190 data_time: 0.0418 memory: 16201 loss_prob: 0.4000 loss_thr: 0.2862 loss_db: 0.0701 loss: 0.7562 2022/08/30 18:34:53 - mmengine - INFO - Epoch(train) [870][20/63] lr: 2.1920e-03 eta: 6:59:18 time: 1.1758 data_time: 0.0598 memory: 16201 loss_prob: 0.4114 loss_thr: 0.2949 loss_db: 0.0725 loss: 0.7787 2022/08/30 18:34:58 - mmengine - INFO - Epoch(train) [870][25/63] lr: 2.1920e-03 eta: 6:59:18 time: 1.0808 data_time: 0.0563 memory: 16201 loss_prob: 0.3770 loss_thr: 0.2738 loss_db: 0.0681 loss: 0.7190 2022/08/30 18:35:02 - mmengine - INFO - Epoch(train) [870][30/63] lr: 2.1920e-03 eta: 6:59:05 time: 0.8711 data_time: 0.0283 memory: 16201 loss_prob: 0.3684 loss_thr: 0.2805 loss_db: 0.0650 loss: 0.7139 2022/08/30 18:35:06 - mmengine - INFO - Epoch(train) [870][35/63] lr: 2.1920e-03 eta: 6:59:05 time: 0.8371 data_time: 0.0236 memory: 16201 loss_prob: 0.3901 loss_thr: 0.2893 loss_db: 0.0685 loss: 0.7479 2022/08/30 18:35:10 - mmengine - INFO - Epoch(train) [870][40/63] lr: 2.1920e-03 eta: 6:58:51 time: 0.8368 data_time: 0.0285 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2698 loss_db: 0.0671 loss: 0.7149 2022/08/30 18:35:14 - mmengine - INFO - Epoch(train) [870][45/63] lr: 2.1920e-03 eta: 6:58:51 time: 0.8121 data_time: 0.0261 memory: 16201 loss_prob: 0.3508 loss_thr: 0.2553 loss_db: 0.0621 loss: 0.6682 2022/08/30 18:35:20 - mmengine - INFO - Epoch(train) [870][50/63] lr: 2.1920e-03 eta: 6:58:38 time: 1.0091 data_time: 0.0289 memory: 16201 loss_prob: 0.3787 loss_thr: 0.2677 loss_db: 0.0680 loss: 0.7144 2022/08/30 18:35:26 - mmengine - INFO - Epoch(train) [870][55/63] lr: 2.1920e-03 eta: 6:58:38 time: 1.1556 data_time: 0.0414 memory: 16201 loss_prob: 0.3709 loss_thr: 0.2641 loss_db: 0.0669 loss: 0.7019 2022/08/30 18:35:32 - mmengine - INFO - Epoch(train) [870][60/63] lr: 2.1920e-03 eta: 6:58:26 time: 1.1384 data_time: 0.0341 memory: 16201 loss_prob: 0.3772 loss_thr: 0.2639 loss_db: 0.0664 loss: 0.7075 2022/08/30 18:35:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:35:41 - mmengine - INFO - Epoch(train) [871][5/63] lr: 2.1860e-03 eta: 6:58:26 time: 1.1325 data_time: 0.2206 memory: 16201 loss_prob: 0.3402 loss_thr: 0.2453 loss_db: 0.0620 loss: 0.6474 2022/08/30 18:35:45 - mmengine - INFO - Epoch(train) [871][10/63] lr: 2.1860e-03 eta: 6:58:08 time: 1.0410 data_time: 0.2129 memory: 16201 loss_prob: 0.3380 loss_thr: 0.2432 loss_db: 0.0601 loss: 0.6413 2022/08/30 18:35:50 - mmengine - INFO - Epoch(train) [871][15/63] lr: 2.1860e-03 eta: 6:58:08 time: 0.9086 data_time: 0.0276 memory: 16201 loss_prob: 0.3790 loss_thr: 0.2702 loss_db: 0.0665 loss: 0.7157 2022/08/30 18:35:54 - mmengine - INFO - Epoch(train) [871][20/63] lr: 2.1860e-03 eta: 6:57:55 time: 0.9702 data_time: 0.0393 memory: 16201 loss_prob: 0.4066 loss_thr: 0.2872 loss_db: 0.0726 loss: 0.7664 2022/08/30 18:36:00 - mmengine - INFO - Epoch(train) [871][25/63] lr: 2.1860e-03 eta: 6:57:55 time: 1.0041 data_time: 0.0282 memory: 16201 loss_prob: 0.3781 loss_thr: 0.2747 loss_db: 0.0678 loss: 0.7206 2022/08/30 18:36:06 - mmengine - INFO - Epoch(train) [871][30/63] lr: 2.1860e-03 eta: 6:57:43 time: 1.1042 data_time: 0.0311 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2624 loss_db: 0.0633 loss: 0.6893 2022/08/30 18:36:12 - mmengine - INFO - Epoch(train) [871][35/63] lr: 2.1860e-03 eta: 6:57:43 time: 1.2032 data_time: 0.0459 memory: 16201 loss_prob: 0.3682 loss_thr: 0.2587 loss_db: 0.0659 loss: 0.6929 2022/08/30 18:36:18 - mmengine - INFO - Epoch(train) [871][40/63] lr: 2.1860e-03 eta: 6:57:31 time: 1.2253 data_time: 0.0327 memory: 16201 loss_prob: 0.3406 loss_thr: 0.2467 loss_db: 0.0624 loss: 0.6497 2022/08/30 18:36:22 - mmengine - INFO - Epoch(train) [871][45/63] lr: 2.1860e-03 eta: 6:57:31 time: 0.9961 data_time: 0.0318 memory: 16201 loss_prob: 0.3240 loss_thr: 0.2442 loss_db: 0.0581 loss: 0.6263 2022/08/30 18:36:26 - mmengine - INFO - Epoch(train) [871][50/63] lr: 2.1860e-03 eta: 6:57:17 time: 0.8070 data_time: 0.0277 memory: 16201 loss_prob: 0.3826 loss_thr: 0.2692 loss_db: 0.0685 loss: 0.7202 2022/08/30 18:36:31 - mmengine - INFO - Epoch(train) [871][55/63] lr: 2.1860e-03 eta: 6:57:17 time: 0.9113 data_time: 0.0263 memory: 16201 loss_prob: 0.4184 loss_thr: 0.2792 loss_db: 0.0741 loss: 0.7717 2022/08/30 18:36:35 - mmengine - INFO - Epoch(train) [871][60/63] lr: 2.1860e-03 eta: 6:57:04 time: 0.9286 data_time: 0.0364 memory: 16201 loss_prob: 0.4038 loss_thr: 0.2769 loss_db: 0.0706 loss: 0.7513 2022/08/30 18:36:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:36:46 - mmengine - INFO - Epoch(train) [872][5/63] lr: 2.1800e-03 eta: 6:57:04 time: 1.2295 data_time: 0.2686 memory: 16201 loss_prob: 0.4114 loss_thr: 0.2939 loss_db: 0.0716 loss: 0.7769 2022/08/30 18:36:51 - mmengine - INFO - Epoch(train) [872][10/63] lr: 2.1800e-03 eta: 6:56:47 time: 1.3015 data_time: 0.2799 memory: 16201 loss_prob: 0.3833 loss_thr: 0.2759 loss_db: 0.0671 loss: 0.7263 2022/08/30 18:36:56 - mmengine - INFO - Epoch(train) [872][15/63] lr: 2.1800e-03 eta: 6:56:47 time: 1.0051 data_time: 0.0298 memory: 16201 loss_prob: 0.3626 loss_thr: 0.2587 loss_db: 0.0650 loss: 0.6863 2022/08/30 18:37:01 - mmengine - INFO - Epoch(train) [872][20/63] lr: 2.1800e-03 eta: 6:56:35 time: 1.0344 data_time: 0.0369 memory: 16201 loss_prob: 0.3705 loss_thr: 0.2686 loss_db: 0.0656 loss: 0.7047 2022/08/30 18:37:07 - mmengine - INFO - Epoch(train) [872][25/63] lr: 2.1800e-03 eta: 6:56:35 time: 1.1119 data_time: 0.0407 memory: 16201 loss_prob: 0.3883 loss_thr: 0.2888 loss_db: 0.0684 loss: 0.7455 2022/08/30 18:37:12 - mmengine - INFO - Epoch(train) [872][30/63] lr: 2.1800e-03 eta: 6:56:22 time: 1.0973 data_time: 0.0348 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2857 loss_db: 0.0695 loss: 0.7405 2022/08/30 18:37:16 - mmengine - INFO - Epoch(train) [872][35/63] lr: 2.1800e-03 eta: 6:56:22 time: 0.9445 data_time: 0.0377 memory: 16201 loss_prob: 0.3533 loss_thr: 0.2663 loss_db: 0.0645 loss: 0.6840 2022/08/30 18:37:21 - mmengine - INFO - Epoch(train) [872][40/63] lr: 2.1800e-03 eta: 6:56:09 time: 0.8839 data_time: 0.0224 memory: 16201 loss_prob: 0.3555 loss_thr: 0.2632 loss_db: 0.0630 loss: 0.6818 2022/08/30 18:37:26 - mmengine - INFO - Epoch(train) [872][45/63] lr: 2.1800e-03 eta: 6:56:09 time: 0.9231 data_time: 0.0309 memory: 16201 loss_prob: 0.3385 loss_thr: 0.2458 loss_db: 0.0595 loss: 0.6439 2022/08/30 18:37:30 - mmengine - INFO - Epoch(train) [872][50/63] lr: 2.1800e-03 eta: 6:55:56 time: 0.9071 data_time: 0.0396 memory: 16201 loss_prob: 0.3659 loss_thr: 0.2603 loss_db: 0.0657 loss: 0.6919 2022/08/30 18:37:35 - mmengine - INFO - Epoch(train) [872][55/63] lr: 2.1800e-03 eta: 6:55:56 time: 0.9110 data_time: 0.0257 memory: 16201 loss_prob: 0.3894 loss_thr: 0.2766 loss_db: 0.0706 loss: 0.7367 2022/08/30 18:37:40 - mmengine - INFO - Epoch(train) [872][60/63] lr: 2.1800e-03 eta: 6:55:43 time: 0.9963 data_time: 0.0314 memory: 16201 loss_prob: 0.3470 loss_thr: 0.2586 loss_db: 0.0610 loss: 0.6666 2022/08/30 18:37:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:37:50 - mmengine - INFO - Epoch(train) [873][5/63] lr: 2.1740e-03 eta: 6:55:43 time: 1.1734 data_time: 0.2491 memory: 16201 loss_prob: 0.3338 loss_thr: 0.2511 loss_db: 0.0599 loss: 0.6448 2022/08/30 18:37:55 - mmengine - INFO - Epoch(train) [873][10/63] lr: 2.1740e-03 eta: 6:55:26 time: 1.2496 data_time: 0.2687 memory: 16201 loss_prob: 0.3439 loss_thr: 0.2558 loss_db: 0.0612 loss: 0.6608 2022/08/30 18:38:01 - mmengine - INFO - Epoch(train) [873][15/63] lr: 2.1740e-03 eta: 6:55:26 time: 1.0925 data_time: 0.0402 memory: 16201 loss_prob: 0.3603 loss_thr: 0.2582 loss_db: 0.0626 loss: 0.6811 2022/08/30 18:38:07 - mmengine - INFO - Epoch(train) [873][20/63] lr: 2.1740e-03 eta: 6:55:14 time: 1.1407 data_time: 0.0345 memory: 16201 loss_prob: 0.3509 loss_thr: 0.2458 loss_db: 0.0616 loss: 0.6582 2022/08/30 18:38:12 - mmengine - INFO - Epoch(train) [873][25/63] lr: 2.1740e-03 eta: 6:55:14 time: 1.0623 data_time: 0.0285 memory: 16201 loss_prob: 0.3089 loss_thr: 0.2235 loss_db: 0.0564 loss: 0.5888 2022/08/30 18:38:16 - mmengine - INFO - Epoch(train) [873][30/63] lr: 2.1740e-03 eta: 6:55:00 time: 0.9151 data_time: 0.0267 memory: 16201 loss_prob: 0.3193 loss_thr: 0.2349 loss_db: 0.0582 loss: 0.6125 2022/08/30 18:38:20 - mmengine - INFO - Epoch(train) [873][35/63] lr: 2.1740e-03 eta: 6:55:00 time: 0.8636 data_time: 0.0452 memory: 16201 loss_prob: 0.3474 loss_thr: 0.2497 loss_db: 0.0616 loss: 0.6586 2022/08/30 18:38:24 - mmengine - INFO - Epoch(train) [873][40/63] lr: 2.1740e-03 eta: 6:54:47 time: 0.8481 data_time: 0.0279 memory: 16201 loss_prob: 0.3606 loss_thr: 0.2509 loss_db: 0.0632 loss: 0.6746 2022/08/30 18:38:29 - mmengine - INFO - Epoch(train) [873][45/63] lr: 2.1740e-03 eta: 6:54:47 time: 0.8479 data_time: 0.0216 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2654 loss_db: 0.0677 loss: 0.7167 2022/08/30 18:38:34 - mmengine - INFO - Epoch(train) [873][50/63] lr: 2.1740e-03 eta: 6:54:34 time: 0.9834 data_time: 0.0357 memory: 16201 loss_prob: 0.4245 loss_thr: 0.2825 loss_db: 0.0736 loss: 0.7806 2022/08/30 18:38:40 - mmengine - INFO - Epoch(train) [873][55/63] lr: 2.1740e-03 eta: 6:54:34 time: 1.1230 data_time: 0.0253 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2623 loss_db: 0.0683 loss: 0.7259 2022/08/30 18:38:45 - mmengine - INFO - Epoch(train) [873][60/63] lr: 2.1740e-03 eta: 6:54:22 time: 1.0571 data_time: 0.0329 memory: 16201 loss_prob: 0.3765 loss_thr: 0.2647 loss_db: 0.0667 loss: 0.7079 2022/08/30 18:38:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:38:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:38:56 - mmengine - INFO - Epoch(train) [874][5/63] lr: 2.1681e-03 eta: 6:54:22 time: 1.2686 data_time: 0.2397 memory: 16201 loss_prob: 0.3792 loss_thr: 0.2661 loss_db: 0.0683 loss: 0.7137 2022/08/30 18:39:01 - mmengine - INFO - Epoch(train) [874][10/63] lr: 2.1681e-03 eta: 6:54:05 time: 1.2623 data_time: 0.2540 memory: 16201 loss_prob: 0.3792 loss_thr: 0.2630 loss_db: 0.0676 loss: 0.7098 2022/08/30 18:39:05 - mmengine - INFO - Epoch(train) [874][15/63] lr: 2.1681e-03 eta: 6:54:05 time: 0.9518 data_time: 0.0298 memory: 16201 loss_prob: 0.3399 loss_thr: 0.2437 loss_db: 0.0614 loss: 0.6451 2022/08/30 18:39:09 - mmengine - INFO - Epoch(train) [874][20/63] lr: 2.1681e-03 eta: 6:53:51 time: 0.8616 data_time: 0.0261 memory: 16201 loss_prob: 0.3342 loss_thr: 0.2342 loss_db: 0.0586 loss: 0.6270 2022/08/30 18:39:13 - mmengine - INFO - Epoch(train) [874][25/63] lr: 2.1681e-03 eta: 6:53:51 time: 0.7901 data_time: 0.0252 memory: 16201 loss_prob: 0.3477 loss_thr: 0.2366 loss_db: 0.0595 loss: 0.6437 2022/08/30 18:39:17 - mmengine - INFO - Epoch(train) [874][30/63] lr: 2.1681e-03 eta: 6:53:38 time: 0.8140 data_time: 0.0477 memory: 16201 loss_prob: 0.3600 loss_thr: 0.2574 loss_db: 0.0637 loss: 0.6811 2022/08/30 18:39:22 - mmengine - INFO - Epoch(train) [874][35/63] lr: 2.1681e-03 eta: 6:53:38 time: 0.8429 data_time: 0.0610 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2759 loss_db: 0.0678 loss: 0.7195 2022/08/30 18:39:26 - mmengine - INFO - Epoch(train) [874][40/63] lr: 2.1681e-03 eta: 6:53:24 time: 0.8265 data_time: 0.0335 memory: 16201 loss_prob: 0.3947 loss_thr: 0.2888 loss_db: 0.0714 loss: 0.7549 2022/08/30 18:39:32 - mmengine - INFO - Epoch(train) [874][45/63] lr: 2.1681e-03 eta: 6:53:24 time: 1.0395 data_time: 0.0308 memory: 16201 loss_prob: 0.4293 loss_thr: 0.3024 loss_db: 0.0762 loss: 0.8078 2022/08/30 18:39:39 - mmengine - INFO - Epoch(train) [874][50/63] lr: 2.1681e-03 eta: 6:53:13 time: 1.3045 data_time: 0.0428 memory: 16201 loss_prob: 0.4155 loss_thr: 0.2971 loss_db: 0.0726 loss: 0.7852 2022/08/30 18:39:45 - mmengine - INFO - Epoch(train) [874][55/63] lr: 2.1681e-03 eta: 6:53:13 time: 1.2696 data_time: 0.0465 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2752 loss_db: 0.0649 loss: 0.7054 2022/08/30 18:39:50 - mmengine - INFO - Epoch(train) [874][60/63] lr: 2.1681e-03 eta: 6:53:00 time: 1.0856 data_time: 0.0434 memory: 16201 loss_prob: 0.3800 loss_thr: 0.2673 loss_db: 0.0690 loss: 0.7164 2022/08/30 18:39:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:39:58 - mmengine - INFO - Epoch(train) [875][5/63] lr: 2.1621e-03 eta: 6:53:00 time: 0.9812 data_time: 0.2011 memory: 16201 loss_prob: 0.3662 loss_thr: 0.2605 loss_db: 0.0648 loss: 0.6914 2022/08/30 18:40:02 - mmengine - INFO - Epoch(train) [875][10/63] lr: 2.1621e-03 eta: 6:52:42 time: 1.0190 data_time: 0.2160 memory: 16201 loss_prob: 0.3825 loss_thr: 0.2740 loss_db: 0.0678 loss: 0.7244 2022/08/30 18:40:06 - mmengine - INFO - Epoch(train) [875][15/63] lr: 2.1621e-03 eta: 6:52:42 time: 0.8687 data_time: 0.0283 memory: 16201 loss_prob: 0.3741 loss_thr: 0.2623 loss_db: 0.0652 loss: 0.7016 2022/08/30 18:40:12 - mmengine - INFO - Epoch(train) [875][20/63] lr: 2.1621e-03 eta: 6:52:30 time: 1.0199 data_time: 0.0322 memory: 16201 loss_prob: 0.3452 loss_thr: 0.2557 loss_db: 0.0614 loss: 0.6623 2022/08/30 18:40:17 - mmengine - INFO - Epoch(train) [875][25/63] lr: 2.1621e-03 eta: 6:52:30 time: 1.1078 data_time: 0.0461 memory: 16201 loss_prob: 0.3401 loss_thr: 0.2572 loss_db: 0.0619 loss: 0.6591 2022/08/30 18:40:23 - mmengine - INFO - Epoch(train) [875][30/63] lr: 2.1621e-03 eta: 6:52:17 time: 1.0826 data_time: 0.0387 memory: 16201 loss_prob: 0.3273 loss_thr: 0.2426 loss_db: 0.0583 loss: 0.6282 2022/08/30 18:40:28 - mmengine - INFO - Epoch(train) [875][35/63] lr: 2.1621e-03 eta: 6:52:17 time: 1.0616 data_time: 0.0409 memory: 16201 loss_prob: 0.3502 loss_thr: 0.2626 loss_db: 0.0627 loss: 0.6754 2022/08/30 18:40:33 - mmengine - INFO - Epoch(train) [875][40/63] lr: 2.1621e-03 eta: 6:52:04 time: 0.9604 data_time: 0.0316 memory: 16201 loss_prob: 0.3836 loss_thr: 0.2788 loss_db: 0.0691 loss: 0.7315 2022/08/30 18:40:37 - mmengine - INFO - Epoch(train) [875][45/63] lr: 2.1621e-03 eta: 6:52:04 time: 0.8738 data_time: 0.0262 memory: 16201 loss_prob: 0.3532 loss_thr: 0.2525 loss_db: 0.0635 loss: 0.6691 2022/08/30 18:40:41 - mmengine - INFO - Epoch(train) [875][50/63] lr: 2.1621e-03 eta: 6:51:51 time: 0.8764 data_time: 0.0488 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2504 loss_db: 0.0639 loss: 0.6706 2022/08/30 18:40:46 - mmengine - INFO - Epoch(train) [875][55/63] lr: 2.1621e-03 eta: 6:51:51 time: 0.8871 data_time: 0.0497 memory: 16201 loss_prob: 0.4018 loss_thr: 0.2817 loss_db: 0.0704 loss: 0.7538 2022/08/30 18:40:51 - mmengine - INFO - Epoch(train) [875][60/63] lr: 2.1621e-03 eta: 6:51:38 time: 0.9509 data_time: 0.0426 memory: 16201 loss_prob: 0.3827 loss_thr: 0.2717 loss_db: 0.0667 loss: 0.7210 2022/08/30 18:40:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:41:01 - mmengine - INFO - Epoch(train) [876][5/63] lr: 2.1561e-03 eta: 6:51:38 time: 1.1980 data_time: 0.2331 memory: 16201 loss_prob: 0.3649 loss_thr: 0.2567 loss_db: 0.0649 loss: 0.6866 2022/08/30 18:41:06 - mmengine - INFO - Epoch(train) [876][10/63] lr: 2.1561e-03 eta: 6:51:21 time: 1.3019 data_time: 0.2436 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2669 loss_db: 0.0631 loss: 0.6831 2022/08/30 18:41:12 - mmengine - INFO - Epoch(train) [876][15/63] lr: 2.1561e-03 eta: 6:51:21 time: 1.0896 data_time: 0.0384 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2589 loss_db: 0.0612 loss: 0.6611 2022/08/30 18:41:18 - mmengine - INFO - Epoch(train) [876][20/63] lr: 2.1561e-03 eta: 6:51:09 time: 1.1378 data_time: 0.0333 memory: 16201 loss_prob: 0.3324 loss_thr: 0.2440 loss_db: 0.0600 loss: 0.6364 2022/08/30 18:41:23 - mmengine - INFO - Epoch(train) [876][25/63] lr: 2.1561e-03 eta: 6:51:09 time: 1.1552 data_time: 0.0510 memory: 16201 loss_prob: 0.3604 loss_thr: 0.2546 loss_db: 0.0640 loss: 0.6790 2022/08/30 18:41:29 - mmengine - INFO - Epoch(train) [876][30/63] lr: 2.1561e-03 eta: 6:50:56 time: 1.0828 data_time: 0.0413 memory: 16201 loss_prob: 0.3548 loss_thr: 0.2489 loss_db: 0.0624 loss: 0.6662 2022/08/30 18:41:33 - mmengine - INFO - Epoch(train) [876][35/63] lr: 2.1561e-03 eta: 6:50:56 time: 0.9489 data_time: 0.0296 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2609 loss_db: 0.0621 loss: 0.6810 2022/08/30 18:41:37 - mmengine - INFO - Epoch(train) [876][40/63] lr: 2.1561e-03 eta: 6:50:43 time: 0.8412 data_time: 0.0245 memory: 16201 loss_prob: 0.4005 loss_thr: 0.2855 loss_db: 0.0700 loss: 0.7561 2022/08/30 18:41:41 - mmengine - INFO - Epoch(train) [876][45/63] lr: 2.1561e-03 eta: 6:50:43 time: 0.8434 data_time: 0.0280 memory: 16201 loss_prob: 0.4058 loss_thr: 0.2849 loss_db: 0.0719 loss: 0.7626 2022/08/30 18:41:46 - mmengine - INFO - Epoch(train) [876][50/63] lr: 2.1561e-03 eta: 6:50:30 time: 0.8712 data_time: 0.0374 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2694 loss_db: 0.0676 loss: 0.7141 2022/08/30 18:41:51 - mmengine - INFO - Epoch(train) [876][55/63] lr: 2.1561e-03 eta: 6:50:30 time: 0.9359 data_time: 0.0277 memory: 16201 loss_prob: 0.3668 loss_thr: 0.2553 loss_db: 0.0656 loss: 0.6877 2022/08/30 18:41:57 - mmengine - INFO - Epoch(train) [876][60/63] lr: 2.1561e-03 eta: 6:50:17 time: 1.0779 data_time: 0.0321 memory: 16201 loss_prob: 0.3577 loss_thr: 0.2518 loss_db: 0.0631 loss: 0.6725 2022/08/30 18:41:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:42:07 - mmengine - INFO - Epoch(train) [877][5/63] lr: 2.1501e-03 eta: 6:50:17 time: 1.2715 data_time: 0.2440 memory: 16201 loss_prob: 0.3583 loss_thr: 0.2470 loss_db: 0.0625 loss: 0.6679 2022/08/30 18:42:13 - mmengine - INFO - Epoch(train) [877][10/63] lr: 2.1501e-03 eta: 6:50:01 time: 1.3329 data_time: 0.2593 memory: 16201 loss_prob: 0.3501 loss_thr: 0.2542 loss_db: 0.0628 loss: 0.6671 2022/08/30 18:42:18 - mmengine - INFO - Epoch(train) [877][15/63] lr: 2.1501e-03 eta: 6:50:01 time: 1.0913 data_time: 0.0370 memory: 16201 loss_prob: 0.3787 loss_thr: 0.2753 loss_db: 0.0688 loss: 0.7228 2022/08/30 18:42:24 - mmengine - INFO - Epoch(train) [877][20/63] lr: 2.1501e-03 eta: 6:49:48 time: 1.0910 data_time: 0.0393 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2631 loss_db: 0.0635 loss: 0.6845 2022/08/30 18:42:29 - mmengine - INFO - Epoch(train) [877][25/63] lr: 2.1501e-03 eta: 6:49:48 time: 1.1070 data_time: 0.0320 memory: 16201 loss_prob: 0.3379 loss_thr: 0.2444 loss_db: 0.0585 loss: 0.6408 2022/08/30 18:42:34 - mmengine - INFO - Epoch(train) [877][30/63] lr: 2.1501e-03 eta: 6:49:35 time: 1.0563 data_time: 0.0279 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2543 loss_db: 0.0608 loss: 0.6612 2022/08/30 18:42:39 - mmengine - INFO - Epoch(train) [877][35/63] lr: 2.1501e-03 eta: 6:49:35 time: 0.9902 data_time: 0.0365 memory: 16201 loss_prob: 0.3621 loss_thr: 0.2762 loss_db: 0.0646 loss: 0.7029 2022/08/30 18:42:43 - mmengine - INFO - Epoch(train) [877][40/63] lr: 2.1501e-03 eta: 6:49:22 time: 0.8736 data_time: 0.0196 memory: 16201 loss_prob: 0.3983 loss_thr: 0.2883 loss_db: 0.0714 loss: 0.7579 2022/08/30 18:42:47 - mmengine - INFO - Epoch(train) [877][45/63] lr: 2.1501e-03 eta: 6:49:22 time: 0.8611 data_time: 0.0288 memory: 16201 loss_prob: 0.3879 loss_thr: 0.2745 loss_db: 0.0691 loss: 0.7315 2022/08/30 18:42:52 - mmengine - INFO - Epoch(train) [877][50/63] lr: 2.1501e-03 eta: 6:49:09 time: 0.8734 data_time: 0.0352 memory: 16201 loss_prob: 0.4056 loss_thr: 0.2808 loss_db: 0.0713 loss: 0.7578 2022/08/30 18:42:55 - mmengine - INFO - Epoch(train) [877][55/63] lr: 2.1501e-03 eta: 6:49:09 time: 0.8049 data_time: 0.0198 memory: 16201 loss_prob: 0.4574 loss_thr: 0.2824 loss_db: 0.0745 loss: 0.8143 2022/08/30 18:43:00 - mmengine - INFO - Epoch(train) [877][60/63] lr: 2.1501e-03 eta: 6:48:56 time: 0.8563 data_time: 0.0291 memory: 16201 loss_prob: 0.4333 loss_thr: 0.2791 loss_db: 0.0710 loss: 0.7834 2022/08/30 18:43:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:43:10 - mmengine - INFO - Epoch(train) [878][5/63] lr: 2.1441e-03 eta: 6:48:56 time: 1.1284 data_time: 0.2630 memory: 16201 loss_prob: 0.3998 loss_thr: 0.2867 loss_db: 0.0724 loss: 0.7589 2022/08/30 18:43:15 - mmengine - INFO - Epoch(train) [878][10/63] lr: 2.1441e-03 eta: 6:48:39 time: 1.2120 data_time: 0.2810 memory: 16201 loss_prob: 0.3694 loss_thr: 0.2674 loss_db: 0.0664 loss: 0.7031 2022/08/30 18:43:20 - mmengine - INFO - Epoch(train) [878][15/63] lr: 2.1441e-03 eta: 6:48:39 time: 1.0644 data_time: 0.0388 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2468 loss_db: 0.0612 loss: 0.6526 2022/08/30 18:43:24 - mmengine - INFO - Epoch(train) [878][20/63] lr: 2.1441e-03 eta: 6:48:26 time: 0.9371 data_time: 0.0279 memory: 16201 loss_prob: 0.3356 loss_thr: 0.2413 loss_db: 0.0600 loss: 0.6369 2022/08/30 18:43:28 - mmengine - INFO - Epoch(train) [878][25/63] lr: 2.1441e-03 eta: 6:48:26 time: 0.8130 data_time: 0.0335 memory: 16201 loss_prob: 0.3405 loss_thr: 0.2418 loss_db: 0.0605 loss: 0.6428 2022/08/30 18:43:34 - mmengine - INFO - Epoch(train) [878][30/63] lr: 2.1441e-03 eta: 6:48:12 time: 0.9340 data_time: 0.0227 memory: 16201 loss_prob: 0.3608 loss_thr: 0.2641 loss_db: 0.0642 loss: 0.6891 2022/08/30 18:43:40 - mmengine - INFO - Epoch(train) [878][35/63] lr: 2.1441e-03 eta: 6:48:12 time: 1.1100 data_time: 0.0311 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2731 loss_db: 0.0668 loss: 0.7166 2022/08/30 18:43:45 - mmengine - INFO - Epoch(train) [878][40/63] lr: 2.1441e-03 eta: 6:48:00 time: 1.1408 data_time: 0.0371 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2566 loss_db: 0.0642 loss: 0.6861 2022/08/30 18:43:51 - mmengine - INFO - Epoch(train) [878][45/63] lr: 2.1441e-03 eta: 6:48:00 time: 1.1884 data_time: 0.0310 memory: 16201 loss_prob: 0.3508 loss_thr: 0.2470 loss_db: 0.0621 loss: 0.6599 2022/08/30 18:43:56 - mmengine - INFO - Epoch(train) [878][50/63] lr: 2.1441e-03 eta: 6:47:48 time: 1.0548 data_time: 0.0353 memory: 16201 loss_prob: 0.3763 loss_thr: 0.2749 loss_db: 0.0678 loss: 0.7190 2022/08/30 18:44:00 - mmengine - INFO - Epoch(train) [878][55/63] lr: 2.1441e-03 eta: 6:47:48 time: 0.8404 data_time: 0.0323 memory: 16201 loss_prob: 0.3947 loss_thr: 0.2833 loss_db: 0.0695 loss: 0.7475 2022/08/30 18:44:04 - mmengine - INFO - Epoch(train) [878][60/63] lr: 2.1441e-03 eta: 6:47:34 time: 0.8198 data_time: 0.0283 memory: 16201 loss_prob: 0.3669 loss_thr: 0.2618 loss_db: 0.0641 loss: 0.6928 2022/08/30 18:44:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:44:14 - mmengine - INFO - Epoch(train) [879][5/63] lr: 2.1381e-03 eta: 6:47:34 time: 1.1597 data_time: 0.2344 memory: 16201 loss_prob: 0.4098 loss_thr: 0.2869 loss_db: 0.0705 loss: 0.7672 2022/08/30 18:44:20 - mmengine - INFO - Epoch(train) [879][10/63] lr: 2.1381e-03 eta: 6:47:18 time: 1.3957 data_time: 0.2535 memory: 16201 loss_prob: 0.4124 loss_thr: 0.2793 loss_db: 0.0710 loss: 0.7627 2022/08/30 18:44:26 - mmengine - INFO - Epoch(train) [879][15/63] lr: 2.1381e-03 eta: 6:47:18 time: 1.2352 data_time: 0.0390 memory: 16201 loss_prob: 0.3737 loss_thr: 0.2585 loss_db: 0.0668 loss: 0.6990 2022/08/30 18:44:31 - mmengine - INFO - Epoch(train) [879][20/63] lr: 2.1381e-03 eta: 6:47:05 time: 1.0950 data_time: 0.0400 memory: 16201 loss_prob: 0.3719 loss_thr: 0.2659 loss_db: 0.0662 loss: 0.7040 2022/08/30 18:44:36 - mmengine - INFO - Epoch(train) [879][25/63] lr: 2.1381e-03 eta: 6:47:05 time: 0.9251 data_time: 0.0324 memory: 16201 loss_prob: 0.3785 loss_thr: 0.2801 loss_db: 0.0651 loss: 0.7238 2022/08/30 18:44:40 - mmengine - INFO - Epoch(train) [879][30/63] lr: 2.1381e-03 eta: 6:46:52 time: 0.8278 data_time: 0.0243 memory: 16201 loss_prob: 0.3843 loss_thr: 0.2778 loss_db: 0.0658 loss: 0.7279 2022/08/30 18:44:45 - mmengine - INFO - Epoch(train) [879][35/63] lr: 2.1381e-03 eta: 6:46:52 time: 0.9123 data_time: 0.0501 memory: 16201 loss_prob: 0.4008 loss_thr: 0.2793 loss_db: 0.0709 loss: 0.7510 2022/08/30 18:44:50 - mmengine - INFO - Epoch(train) [879][40/63] lr: 2.1381e-03 eta: 6:46:39 time: 1.0521 data_time: 0.0422 memory: 16201 loss_prob: 0.3851 loss_thr: 0.2700 loss_db: 0.0690 loss: 0.7242 2022/08/30 18:44:56 - mmengine - INFO - Epoch(train) [879][45/63] lr: 2.1381e-03 eta: 6:46:39 time: 1.1138 data_time: 0.0390 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2439 loss_db: 0.0605 loss: 0.6440 2022/08/30 18:45:02 - mmengine - INFO - Epoch(train) [879][50/63] lr: 2.1381e-03 eta: 6:46:27 time: 1.1269 data_time: 0.0438 memory: 16201 loss_prob: 0.3849 loss_thr: 0.2691 loss_db: 0.0691 loss: 0.7232 2022/08/30 18:45:07 - mmengine - INFO - Epoch(train) [879][55/63] lr: 2.1381e-03 eta: 6:46:27 time: 1.0990 data_time: 0.0390 memory: 16201 loss_prob: 0.4132 loss_thr: 0.2776 loss_db: 0.0743 loss: 0.7651 2022/08/30 18:45:12 - mmengine - INFO - Epoch(train) [879][60/63] lr: 2.1381e-03 eta: 6:46:14 time: 1.0437 data_time: 0.0442 memory: 16201 loss_prob: 0.3723 loss_thr: 0.2547 loss_db: 0.0649 loss: 0.6920 2022/08/30 18:45:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:45:21 - mmengine - INFO - Epoch(train) [880][5/63] lr: 2.1321e-03 eta: 6:46:14 time: 1.1411 data_time: 0.2435 memory: 16201 loss_prob: 0.3496 loss_thr: 0.2551 loss_db: 0.0620 loss: 0.6667 2022/08/30 18:45:26 - mmengine - INFO - Epoch(train) [880][10/63] lr: 2.1321e-03 eta: 6:45:57 time: 1.0916 data_time: 0.2423 memory: 16201 loss_prob: 0.3544 loss_thr: 0.2563 loss_db: 0.0634 loss: 0.6741 2022/08/30 18:45:30 - mmengine - INFO - Epoch(train) [880][15/63] lr: 2.1321e-03 eta: 6:45:57 time: 0.9209 data_time: 0.0282 memory: 16201 loss_prob: 0.3727 loss_thr: 0.2616 loss_db: 0.0652 loss: 0.6996 2022/08/30 18:45:35 - mmengine - INFO - Epoch(train) [880][20/63] lr: 2.1321e-03 eta: 6:45:44 time: 0.9299 data_time: 0.0288 memory: 16201 loss_prob: 0.3840 loss_thr: 0.2568 loss_db: 0.0668 loss: 0.7076 2022/08/30 18:45:39 - mmengine - INFO - Epoch(train) [880][25/63] lr: 2.1321e-03 eta: 6:45:44 time: 0.8779 data_time: 0.0252 memory: 16201 loss_prob: 0.4154 loss_thr: 0.2769 loss_db: 0.0707 loss: 0.7630 2022/08/30 18:45:45 - mmengine - INFO - Epoch(train) [880][30/63] lr: 2.1321e-03 eta: 6:45:31 time: 1.0094 data_time: 0.0316 memory: 16201 loss_prob: 0.4025 loss_thr: 0.2812 loss_db: 0.0676 loss: 0.7513 2022/08/30 18:45:51 - mmengine - INFO - Epoch(train) [880][35/63] lr: 2.1321e-03 eta: 6:45:31 time: 1.1665 data_time: 0.0517 memory: 16201 loss_prob: 0.3535 loss_thr: 0.2670 loss_db: 0.0621 loss: 0.6826 2022/08/30 18:45:57 - mmengine - INFO - Epoch(train) [880][40/63] lr: 2.1321e-03 eta: 6:45:19 time: 1.1502 data_time: 0.0418 memory: 16201 loss_prob: 0.3622 loss_thr: 0.2730 loss_db: 0.0663 loss: 0.7015 2022/08/30 18:46:03 - mmengine - INFO - Epoch(train) [880][45/63] lr: 2.1321e-03 eta: 6:45:19 time: 1.1582 data_time: 0.0337 memory: 16201 loss_prob: 0.4017 loss_thr: 0.2806 loss_db: 0.0725 loss: 0.7548 2022/08/30 18:46:08 - mmengine - INFO - Epoch(train) [880][50/63] lr: 2.1321e-03 eta: 6:45:07 time: 1.1750 data_time: 0.0472 memory: 16201 loss_prob: 0.3860 loss_thr: 0.2690 loss_db: 0.0683 loss: 0.7233 2022/08/30 18:46:14 - mmengine - INFO - Epoch(train) [880][55/63] lr: 2.1321e-03 eta: 6:45:07 time: 1.1411 data_time: 0.0339 memory: 16201 loss_prob: 0.3552 loss_thr: 0.2609 loss_db: 0.0623 loss: 0.6784 2022/08/30 18:46:21 - mmengine - INFO - Epoch(train) [880][60/63] lr: 2.1321e-03 eta: 6:44:55 time: 1.2374 data_time: 0.0303 memory: 16201 loss_prob: 0.3886 loss_thr: 0.2737 loss_db: 0.0674 loss: 0.7297 2022/08/30 18:46:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:46:23 - mmengine - INFO - Saving checkpoint at 880 epochs 2022/08/30 18:46:31 - mmengine - INFO - Epoch(val) [880][5/32] eta: 6:44:55 time: 0.6417 data_time: 0.1063 memory: 16201 2022/08/30 18:46:35 - mmengine - INFO - Epoch(val) [880][10/32] eta: 0:00:16 time: 0.7273 data_time: 0.1459 memory: 15734 2022/08/30 18:46:38 - mmengine - INFO - Epoch(val) [880][15/32] eta: 0:00:16 time: 0.6222 data_time: 0.0541 memory: 15734 2022/08/30 18:46:41 - mmengine - INFO - Epoch(val) [880][20/32] eta: 0:00:07 time: 0.6337 data_time: 0.0657 memory: 15734 2022/08/30 18:46:45 - mmengine - INFO - Epoch(val) [880][25/32] eta: 0:00:07 time: 0.7380 data_time: 0.0793 memory: 15734 2022/08/30 18:46:48 - mmengine - INFO - Epoch(val) [880][30/32] eta: 0:00:01 time: 0.7067 data_time: 0.0386 memory: 15734 2022/08/30 18:46:49 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 18:46:49 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8426, precision: 0.7879, hmean: 0.8143 2022/08/30 18:46:49 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8426, precision: 0.8243, hmean: 0.8333 2022/08/30 18:46:49 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8421, precision: 0.8433, hmean: 0.8427 2022/08/30 18:46:49 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8392, precision: 0.8624, hmean: 0.8507 2022/08/30 18:46:49 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8320, precision: 0.8821, hmean: 0.8563 2022/08/30 18:46:49 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8031, precision: 0.9070, hmean: 0.8519 2022/08/30 18:46:49 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4088, precision: 0.9615, hmean: 0.5736 2022/08/30 18:46:49 - mmengine - INFO - Epoch(val) [880][32/32] icdar/precision: 0.8821 icdar/recall: 0.8320 icdar/hmean: 0.8563 2022/08/30 18:46:57 - mmengine - INFO - Epoch(train) [881][5/63] lr: 2.1261e-03 eta: 0:00:01 time: 1.2799 data_time: 0.2107 memory: 16201 loss_prob: 0.3720 loss_thr: 0.2532 loss_db: 0.0642 loss: 0.6894 2022/08/30 18:47:02 - mmengine - INFO - Epoch(train) [881][10/63] lr: 2.1261e-03 eta: 6:44:38 time: 1.2506 data_time: 0.2177 memory: 16201 loss_prob: 0.3778 loss_thr: 0.2548 loss_db: 0.0664 loss: 0.6990 2022/08/30 18:47:07 - mmengine - INFO - Epoch(train) [881][15/63] lr: 2.1261e-03 eta: 6:44:38 time: 1.0016 data_time: 0.0419 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2642 loss_db: 0.0683 loss: 0.7107 2022/08/30 18:47:11 - mmengine - INFO - Epoch(train) [881][20/63] lr: 2.1261e-03 eta: 6:44:25 time: 0.9259 data_time: 0.0414 memory: 16201 loss_prob: 0.3699 loss_thr: 0.2672 loss_db: 0.0649 loss: 0.7021 2022/08/30 18:47:15 - mmengine - INFO - Epoch(train) [881][25/63] lr: 2.1261e-03 eta: 6:44:25 time: 0.7966 data_time: 0.0218 memory: 16201 loss_prob: 0.4002 loss_thr: 0.2865 loss_db: 0.0705 loss: 0.7572 2022/08/30 18:47:19 - mmengine - INFO - Epoch(train) [881][30/63] lr: 2.1261e-03 eta: 6:44:11 time: 0.8179 data_time: 0.0234 memory: 16201 loss_prob: 0.4443 loss_thr: 0.3080 loss_db: 0.0781 loss: 0.8303 2022/08/30 18:47:23 - mmengine - INFO - Epoch(train) [881][35/63] lr: 2.1261e-03 eta: 6:44:11 time: 0.8482 data_time: 0.0310 memory: 16201 loss_prob: 0.4088 loss_thr: 0.2798 loss_db: 0.0724 loss: 0.7610 2022/08/30 18:47:27 - mmengine - INFO - Epoch(train) [881][40/63] lr: 2.1261e-03 eta: 6:43:58 time: 0.8114 data_time: 0.0220 memory: 16201 loss_prob: 0.3824 loss_thr: 0.2584 loss_db: 0.0684 loss: 0.7092 2022/08/30 18:47:33 - mmengine - INFO - Epoch(train) [881][45/63] lr: 2.1261e-03 eta: 6:43:58 time: 0.9381 data_time: 0.0279 memory: 16201 loss_prob: 0.3774 loss_thr: 0.2604 loss_db: 0.0668 loss: 0.7045 2022/08/30 18:47:38 - mmengine - INFO - Epoch(train) [881][50/63] lr: 2.1261e-03 eta: 6:43:45 time: 1.0446 data_time: 0.0357 memory: 16201 loss_prob: 0.3609 loss_thr: 0.2567 loss_db: 0.0651 loss: 0.6827 2022/08/30 18:47:43 - mmengine - INFO - Epoch(train) [881][55/63] lr: 2.1261e-03 eta: 6:43:45 time: 1.0751 data_time: 0.0330 memory: 16201 loss_prob: 0.3454 loss_thr: 0.2489 loss_db: 0.0628 loss: 0.6570 2022/08/30 18:47:48 - mmengine - INFO - Epoch(train) [881][60/63] lr: 2.1261e-03 eta: 6:43:33 time: 1.0705 data_time: 0.0379 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2475 loss_db: 0.0635 loss: 0.6677 2022/08/30 18:47:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:47:56 - mmengine - INFO - Epoch(train) [882][5/63] lr: 2.1201e-03 eta: 6:43:33 time: 0.9595 data_time: 0.1864 memory: 16201 loss_prob: 0.3696 loss_thr: 0.2652 loss_db: 0.0640 loss: 0.6988 2022/08/30 18:48:00 - mmengine - INFO - Epoch(train) [882][10/63] lr: 2.1201e-03 eta: 6:43:15 time: 0.9559 data_time: 0.1861 memory: 16201 loss_prob: 0.3319 loss_thr: 0.2609 loss_db: 0.0584 loss: 0.6513 2022/08/30 18:48:04 - mmengine - INFO - Epoch(train) [882][15/63] lr: 2.1201e-03 eta: 6:43:15 time: 0.7927 data_time: 0.0260 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2741 loss_db: 0.0655 loss: 0.6963 2022/08/30 18:48:08 - mmengine - INFO - Epoch(train) [882][20/63] lr: 2.1201e-03 eta: 6:43:02 time: 0.8384 data_time: 0.0331 memory: 16201 loss_prob: 0.3553 loss_thr: 0.2564 loss_db: 0.0651 loss: 0.6768 2022/08/30 18:48:13 - mmengine - INFO - Epoch(train) [882][25/63] lr: 2.1201e-03 eta: 6:43:02 time: 0.9329 data_time: 0.0354 memory: 16201 loss_prob: 0.3520 loss_thr: 0.2434 loss_db: 0.0633 loss: 0.6588 2022/08/30 18:48:19 - mmengine - INFO - Epoch(train) [882][30/63] lr: 2.1201e-03 eta: 6:42:49 time: 1.0357 data_time: 0.0312 memory: 16201 loss_prob: 0.3581 loss_thr: 0.2570 loss_db: 0.0628 loss: 0.6779 2022/08/30 18:48:24 - mmengine - INFO - Epoch(train) [882][35/63] lr: 2.1201e-03 eta: 6:42:49 time: 1.0522 data_time: 0.0385 memory: 16201 loss_prob: 0.3610 loss_thr: 0.2607 loss_db: 0.0630 loss: 0.6848 2022/08/30 18:48:28 - mmengine - INFO - Epoch(train) [882][40/63] lr: 2.1201e-03 eta: 6:42:36 time: 0.9252 data_time: 0.0391 memory: 16201 loss_prob: 0.3566 loss_thr: 0.2592 loss_db: 0.0630 loss: 0.6788 2022/08/30 18:48:32 - mmengine - INFO - Epoch(train) [882][45/63] lr: 2.1201e-03 eta: 6:42:36 time: 0.7999 data_time: 0.0283 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2573 loss_db: 0.0626 loss: 0.6766 2022/08/30 18:48:36 - mmengine - INFO - Epoch(train) [882][50/63] lr: 2.1201e-03 eta: 6:42:23 time: 0.8546 data_time: 0.0300 memory: 16201 loss_prob: 0.3826 loss_thr: 0.2760 loss_db: 0.0683 loss: 0.7268 2022/08/30 18:48:41 - mmengine - INFO - Epoch(train) [882][55/63] lr: 2.1201e-03 eta: 6:42:23 time: 0.9606 data_time: 0.0398 memory: 16201 loss_prob: 0.3674 loss_thr: 0.2737 loss_db: 0.0654 loss: 0.7065 2022/08/30 18:48:46 - mmengine - INFO - Epoch(train) [882][60/63] lr: 2.1201e-03 eta: 6:42:10 time: 1.0077 data_time: 0.0389 memory: 16201 loss_prob: 0.3332 loss_thr: 0.2499 loss_db: 0.0583 loss: 0.6413 2022/08/30 18:48:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:48:57 - mmengine - INFO - Epoch(train) [883][5/63] lr: 2.1141e-03 eta: 6:42:10 time: 1.2604 data_time: 0.2451 memory: 16201 loss_prob: 0.3496 loss_thr: 0.2466 loss_db: 0.0630 loss: 0.6592 2022/08/30 18:49:01 - mmengine - INFO - Epoch(train) [883][10/63] lr: 2.1141e-03 eta: 6:41:53 time: 1.1857 data_time: 0.2564 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2477 loss_db: 0.0629 loss: 0.6595 2022/08/30 18:49:05 - mmengine - INFO - Epoch(train) [883][15/63] lr: 2.1141e-03 eta: 6:41:53 time: 0.8300 data_time: 0.0326 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2560 loss_db: 0.0619 loss: 0.6643 2022/08/30 18:49:10 - mmengine - INFO - Epoch(train) [883][20/63] lr: 2.1141e-03 eta: 6:41:39 time: 0.8221 data_time: 0.0203 memory: 16201 loss_prob: 0.3637 loss_thr: 0.2668 loss_db: 0.0662 loss: 0.6967 2022/08/30 18:49:14 - mmengine - INFO - Epoch(train) [883][25/63] lr: 2.1141e-03 eta: 6:41:39 time: 0.8259 data_time: 0.0357 memory: 16201 loss_prob: 0.3828 loss_thr: 0.2752 loss_db: 0.0686 loss: 0.7265 2022/08/30 18:49:19 - mmengine - INFO - Epoch(train) [883][30/63] lr: 2.1141e-03 eta: 6:41:26 time: 0.9622 data_time: 0.0277 memory: 16201 loss_prob: 0.3619 loss_thr: 0.2707 loss_db: 0.0636 loss: 0.6962 2022/08/30 18:49:24 - mmengine - INFO - Epoch(train) [883][35/63] lr: 2.1141e-03 eta: 6:41:26 time: 1.0678 data_time: 0.0232 memory: 16201 loss_prob: 0.3511 loss_thr: 0.2677 loss_db: 0.0631 loss: 0.6818 2022/08/30 18:49:29 - mmengine - INFO - Epoch(train) [883][40/63] lr: 2.1141e-03 eta: 6:41:14 time: 0.9910 data_time: 0.0327 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2706 loss_db: 0.0695 loss: 0.7322 2022/08/30 18:49:34 - mmengine - INFO - Epoch(train) [883][45/63] lr: 2.1141e-03 eta: 6:41:14 time: 0.9624 data_time: 0.0335 memory: 16201 loss_prob: 0.4068 loss_thr: 0.2784 loss_db: 0.0703 loss: 0.7556 2022/08/30 18:49:39 - mmengine - INFO - Epoch(train) [883][50/63] lr: 2.1141e-03 eta: 6:41:01 time: 0.9709 data_time: 0.0313 memory: 16201 loss_prob: 0.3752 loss_thr: 0.2644 loss_db: 0.0661 loss: 0.7058 2022/08/30 18:49:44 - mmengine - INFO - Epoch(train) [883][55/63] lr: 2.1141e-03 eta: 6:41:01 time: 1.0016 data_time: 0.0307 memory: 16201 loss_prob: 0.3358 loss_thr: 0.2426 loss_db: 0.0605 loss: 0.6389 2022/08/30 18:49:48 - mmengine - INFO - Epoch(train) [883][60/63] lr: 2.1141e-03 eta: 6:40:48 time: 0.9488 data_time: 0.0319 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2633 loss_db: 0.0641 loss: 0.6852 2022/08/30 18:49:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:49:57 - mmengine - INFO - Epoch(train) [884][5/63] lr: 2.1081e-03 eta: 6:40:48 time: 0.9805 data_time: 0.2008 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2676 loss_db: 0.0674 loss: 0.7110 2022/08/30 18:50:01 - mmengine - INFO - Epoch(train) [884][10/63] lr: 2.1081e-03 eta: 6:40:30 time: 0.9911 data_time: 0.2056 memory: 16201 loss_prob: 0.3380 loss_thr: 0.2491 loss_db: 0.0597 loss: 0.6469 2022/08/30 18:50:05 - mmengine - INFO - Epoch(train) [884][15/63] lr: 2.1081e-03 eta: 6:40:30 time: 0.8320 data_time: 0.0244 memory: 16201 loss_prob: 0.3839 loss_thr: 0.2714 loss_db: 0.0666 loss: 0.7218 2022/08/30 18:50:10 - mmengine - INFO - Epoch(train) [884][20/63] lr: 2.1081e-03 eta: 6:40:17 time: 0.9172 data_time: 0.0304 memory: 16201 loss_prob: 0.3779 loss_thr: 0.2633 loss_db: 0.0679 loss: 0.7091 2022/08/30 18:50:15 - mmengine - INFO - Epoch(train) [884][25/63] lr: 2.1081e-03 eta: 6:40:17 time: 1.0045 data_time: 0.0319 memory: 16201 loss_prob: 0.3626 loss_thr: 0.2535 loss_db: 0.0657 loss: 0.6818 2022/08/30 18:50:20 - mmengine - INFO - Epoch(train) [884][30/63] lr: 2.1081e-03 eta: 6:40:04 time: 1.0078 data_time: 0.0297 memory: 16201 loss_prob: 0.4235 loss_thr: 0.2858 loss_db: 0.0742 loss: 0.7834 2022/08/30 18:50:25 - mmengine - INFO - Epoch(train) [884][35/63] lr: 2.1081e-03 eta: 6:40:04 time: 0.9928 data_time: 0.0374 memory: 16201 loss_prob: 0.3813 loss_thr: 0.2717 loss_db: 0.0664 loss: 0.7195 2022/08/30 18:50:29 - mmengine - INFO - Epoch(train) [884][40/63] lr: 2.1081e-03 eta: 6:39:51 time: 0.9232 data_time: 0.0284 memory: 16201 loss_prob: 0.3418 loss_thr: 0.2478 loss_db: 0.0602 loss: 0.6497 2022/08/30 18:50:33 - mmengine - INFO - Epoch(train) [884][45/63] lr: 2.1081e-03 eta: 6:39:51 time: 0.8378 data_time: 0.0232 memory: 16201 loss_prob: 0.3765 loss_thr: 0.2690 loss_db: 0.0668 loss: 0.7123 2022/08/30 18:50:37 - mmengine - INFO - Epoch(train) [884][50/63] lr: 2.1081e-03 eta: 6:39:38 time: 0.8313 data_time: 0.0313 memory: 16201 loss_prob: 0.3444 loss_thr: 0.2598 loss_db: 0.0613 loss: 0.6655 2022/08/30 18:50:43 - mmengine - INFO - Epoch(train) [884][55/63] lr: 2.1081e-03 eta: 6:39:38 time: 0.9291 data_time: 0.0287 memory: 16201 loss_prob: 0.3110 loss_thr: 0.2361 loss_db: 0.0549 loss: 0.6021 2022/08/30 18:50:48 - mmengine - INFO - Epoch(train) [884][60/63] lr: 2.1081e-03 eta: 6:39:25 time: 1.0368 data_time: 0.0499 memory: 16201 loss_prob: 0.3673 loss_thr: 0.2746 loss_db: 0.0642 loss: 0.7061 2022/08/30 18:50:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:50:56 - mmengine - INFO - Epoch(train) [885][5/63] lr: 2.1021e-03 eta: 6:39:25 time: 0.9808 data_time: 0.2104 memory: 16201 loss_prob: 0.3831 loss_thr: 0.2704 loss_db: 0.0689 loss: 0.7224 2022/08/30 18:51:01 - mmengine - INFO - Epoch(train) [885][10/63] lr: 2.1021e-03 eta: 6:39:08 time: 1.0624 data_time: 0.2040 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2547 loss_db: 0.0617 loss: 0.6652 2022/08/30 18:51:06 - mmengine - INFO - Epoch(train) [885][15/63] lr: 2.1021e-03 eta: 6:39:08 time: 1.0086 data_time: 0.0313 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2624 loss_db: 0.0629 loss: 0.6790 2022/08/30 18:51:10 - mmengine - INFO - Epoch(train) [885][20/63] lr: 2.1021e-03 eta: 6:38:55 time: 0.9724 data_time: 0.0330 memory: 16201 loss_prob: 0.4056 loss_thr: 0.2815 loss_db: 0.0702 loss: 0.7573 2022/08/30 18:51:14 - mmengine - INFO - Epoch(train) [885][25/63] lr: 2.1021e-03 eta: 6:38:55 time: 0.8237 data_time: 0.0222 memory: 16201 loss_prob: 0.3779 loss_thr: 0.2608 loss_db: 0.0645 loss: 0.7032 2022/08/30 18:51:18 - mmengine - INFO - Epoch(train) [885][30/63] lr: 2.1021e-03 eta: 6:38:41 time: 0.7943 data_time: 0.0258 memory: 16201 loss_prob: 0.3683 loss_thr: 0.2597 loss_db: 0.0648 loss: 0.6928 2022/08/30 18:51:24 - mmengine - INFO - Epoch(train) [885][35/63] lr: 2.1021e-03 eta: 6:38:41 time: 0.9387 data_time: 0.0263 memory: 16201 loss_prob: 0.4164 loss_thr: 0.2986 loss_db: 0.0748 loss: 0.7898 2022/08/30 18:51:29 - mmengine - INFO - Epoch(train) [885][40/63] lr: 2.1021e-03 eta: 6:38:29 time: 1.0287 data_time: 0.0251 memory: 16201 loss_prob: 0.4032 loss_thr: 0.2910 loss_db: 0.0714 loss: 0.7656 2022/08/30 18:51:33 - mmengine - INFO - Epoch(train) [885][45/63] lr: 2.1021e-03 eta: 6:38:29 time: 0.9794 data_time: 0.0549 memory: 16201 loss_prob: 0.3972 loss_thr: 0.2783 loss_db: 0.0698 loss: 0.7452 2022/08/30 18:51:38 - mmengine - INFO - Epoch(train) [885][50/63] lr: 2.1021e-03 eta: 6:38:16 time: 0.9676 data_time: 0.0488 memory: 16201 loss_prob: 0.4115 loss_thr: 0.2829 loss_db: 0.0727 loss: 0.7670 2022/08/30 18:51:44 - mmengine - INFO - Epoch(train) [885][55/63] lr: 2.1021e-03 eta: 6:38:16 time: 1.0622 data_time: 0.0273 memory: 16201 loss_prob: 0.3500 loss_thr: 0.2488 loss_db: 0.0615 loss: 0.6603 2022/08/30 18:51:48 - mmengine - INFO - Epoch(train) [885][60/63] lr: 2.1021e-03 eta: 6:38:03 time: 0.9708 data_time: 0.0343 memory: 16201 loss_prob: 0.3395 loss_thr: 0.2482 loss_db: 0.0618 loss: 0.6495 2022/08/30 18:51:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:51:56 - mmengine - INFO - Epoch(train) [886][5/63] lr: 2.0961e-03 eta: 6:38:03 time: 0.9455 data_time: 0.2107 memory: 16201 loss_prob: 0.4165 loss_thr: 0.2946 loss_db: 0.0749 loss: 0.7860 2022/08/30 18:52:00 - mmengine - INFO - Epoch(train) [886][10/63] lr: 2.0961e-03 eta: 6:37:45 time: 1.0137 data_time: 0.2195 memory: 16201 loss_prob: 0.3833 loss_thr: 0.2910 loss_db: 0.0674 loss: 0.7417 2022/08/30 18:52:05 - mmengine - INFO - Epoch(train) [886][15/63] lr: 2.0961e-03 eta: 6:37:45 time: 0.9204 data_time: 0.0283 memory: 16201 loss_prob: 0.3722 loss_thr: 0.2724 loss_db: 0.0666 loss: 0.7111 2022/08/30 18:52:10 - mmengine - INFO - Epoch(train) [886][20/63] lr: 2.0961e-03 eta: 6:37:33 time: 1.0131 data_time: 0.0283 memory: 16201 loss_prob: 0.3908 loss_thr: 0.2691 loss_db: 0.0712 loss: 0.7310 2022/08/30 18:52:15 - mmengine - INFO - Epoch(train) [886][25/63] lr: 2.0961e-03 eta: 6:37:33 time: 1.0398 data_time: 0.0340 memory: 16201 loss_prob: 0.3856 loss_thr: 0.2561 loss_db: 0.0665 loss: 0.7082 2022/08/30 18:52:20 - mmengine - INFO - Epoch(train) [886][30/63] lr: 2.0961e-03 eta: 6:37:20 time: 0.9458 data_time: 0.0299 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2399 loss_db: 0.0599 loss: 0.6592 2022/08/30 18:52:24 - mmengine - INFO - Epoch(train) [886][35/63] lr: 2.0961e-03 eta: 6:37:20 time: 0.8141 data_time: 0.0294 memory: 16201 loss_prob: 0.3628 loss_thr: 0.2582 loss_db: 0.0630 loss: 0.6840 2022/08/30 18:52:28 - mmengine - INFO - Epoch(train) [886][40/63] lr: 2.0961e-03 eta: 6:37:06 time: 0.7865 data_time: 0.0262 memory: 16201 loss_prob: 0.3640 loss_thr: 0.2660 loss_db: 0.0655 loss: 0.6955 2022/08/30 18:52:33 - mmengine - INFO - Epoch(train) [886][45/63] lr: 2.0961e-03 eta: 6:37:06 time: 0.9458 data_time: 0.0285 memory: 16201 loss_prob: 0.3566 loss_thr: 0.2574 loss_db: 0.0638 loss: 0.6778 2022/08/30 18:52:38 - mmengine - INFO - Epoch(train) [886][50/63] lr: 2.0961e-03 eta: 6:36:54 time: 1.0334 data_time: 0.0343 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2641 loss_db: 0.0633 loss: 0.6910 2022/08/30 18:52:42 - mmengine - INFO - Epoch(train) [886][55/63] lr: 2.0961e-03 eta: 6:36:54 time: 0.9251 data_time: 0.0293 memory: 16201 loss_prob: 0.3766 loss_thr: 0.2648 loss_db: 0.0676 loss: 0.7090 2022/08/30 18:52:46 - mmengine - INFO - Epoch(train) [886][60/63] lr: 2.0961e-03 eta: 6:36:40 time: 0.8471 data_time: 0.0283 memory: 16201 loss_prob: 0.3735 loss_thr: 0.2679 loss_db: 0.0666 loss: 0.7080 2022/08/30 18:52:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:52:56 - mmengine - INFO - Epoch(train) [887][5/63] lr: 2.0901e-03 eta: 6:36:40 time: 1.1160 data_time: 0.2225 memory: 16201 loss_prob: 0.3366 loss_thr: 0.2615 loss_db: 0.0604 loss: 0.6585 2022/08/30 18:53:01 - mmengine - INFO - Epoch(train) [887][10/63] lr: 2.0901e-03 eta: 6:36:24 time: 1.2431 data_time: 0.2278 memory: 16201 loss_prob: 0.3558 loss_thr: 0.2501 loss_db: 0.0645 loss: 0.6704 2022/08/30 18:53:06 - mmengine - INFO - Epoch(train) [887][15/63] lr: 2.0901e-03 eta: 6:36:24 time: 1.0442 data_time: 0.0294 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2364 loss_db: 0.0618 loss: 0.6481 2022/08/30 18:53:11 - mmengine - INFO - Epoch(train) [887][20/63] lr: 2.0901e-03 eta: 6:36:11 time: 1.0522 data_time: 0.0367 memory: 16201 loss_prob: 0.3296 loss_thr: 0.2370 loss_db: 0.0589 loss: 0.6255 2022/08/30 18:53:16 - mmengine - INFO - Epoch(train) [887][25/63] lr: 2.0901e-03 eta: 6:36:11 time: 1.0149 data_time: 0.0325 memory: 16201 loss_prob: 0.3463 loss_thr: 0.2464 loss_db: 0.0612 loss: 0.6538 2022/08/30 18:53:22 - mmengine - INFO - Epoch(train) [887][30/63] lr: 2.0901e-03 eta: 6:35:58 time: 1.0505 data_time: 0.0295 memory: 16201 loss_prob: 0.3643 loss_thr: 0.2505 loss_db: 0.0635 loss: 0.6783 2022/08/30 18:53:26 - mmengine - INFO - Epoch(train) [887][35/63] lr: 2.0901e-03 eta: 6:35:58 time: 0.9818 data_time: 0.0326 memory: 16201 loss_prob: 0.4073 loss_thr: 0.2726 loss_db: 0.0715 loss: 0.7514 2022/08/30 18:53:30 - mmengine - INFO - Epoch(train) [887][40/63] lr: 2.0901e-03 eta: 6:35:45 time: 0.8343 data_time: 0.0185 memory: 16201 loss_prob: 0.4039 loss_thr: 0.2773 loss_db: 0.0715 loss: 0.7527 2022/08/30 18:53:34 - mmengine - INFO - Epoch(train) [887][45/63] lr: 2.0901e-03 eta: 6:35:45 time: 0.8043 data_time: 0.0265 memory: 16201 loss_prob: 0.3737 loss_thr: 0.2679 loss_db: 0.0659 loss: 0.7075 2022/08/30 18:53:38 - mmengine - INFO - Epoch(train) [887][50/63] lr: 2.0901e-03 eta: 6:35:32 time: 0.7963 data_time: 0.0285 memory: 16201 loss_prob: 0.3715 loss_thr: 0.2658 loss_db: 0.0651 loss: 0.7024 2022/08/30 18:53:43 - mmengine - INFO - Epoch(train) [887][55/63] lr: 2.0901e-03 eta: 6:35:32 time: 0.8478 data_time: 0.0354 memory: 16201 loss_prob: 0.3633 loss_thr: 0.2759 loss_db: 0.0644 loss: 0.7037 2022/08/30 18:53:47 - mmengine - INFO - Epoch(train) [887][60/63] lr: 2.0901e-03 eta: 6:35:18 time: 0.8680 data_time: 0.0472 memory: 16201 loss_prob: 0.3226 loss_thr: 0.2466 loss_db: 0.0585 loss: 0.6277 2022/08/30 18:53:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:53:56 - mmengine - INFO - Epoch(train) [888][5/63] lr: 2.0841e-03 eta: 6:35:18 time: 1.1008 data_time: 0.2584 memory: 16201 loss_prob: 0.3444 loss_thr: 0.2499 loss_db: 0.0598 loss: 0.6542 2022/08/30 18:54:02 - mmengine - INFO - Epoch(train) [888][10/63] lr: 2.0841e-03 eta: 6:35:02 time: 1.2632 data_time: 0.2718 memory: 16201 loss_prob: 0.3824 loss_thr: 0.2673 loss_db: 0.0660 loss: 0.7157 2022/08/30 18:54:06 - mmengine - INFO - Epoch(train) [888][15/63] lr: 2.0841e-03 eta: 6:35:02 time: 0.9340 data_time: 0.0343 memory: 16201 loss_prob: 0.3788 loss_thr: 0.2669 loss_db: 0.0664 loss: 0.7121 2022/08/30 18:54:10 - mmengine - INFO - Epoch(train) [888][20/63] lr: 2.0841e-03 eta: 6:34:49 time: 0.8811 data_time: 0.0208 memory: 16201 loss_prob: 0.3788 loss_thr: 0.2745 loss_db: 0.0682 loss: 0.7216 2022/08/30 18:54:15 - mmengine - INFO - Epoch(train) [888][25/63] lr: 2.0841e-03 eta: 6:34:49 time: 0.9753 data_time: 0.0290 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2607 loss_db: 0.0608 loss: 0.6680 2022/08/30 18:54:21 - mmengine - INFO - Epoch(train) [888][30/63] lr: 2.0841e-03 eta: 6:34:36 time: 1.0099 data_time: 0.0283 memory: 16201 loss_prob: 0.3475 loss_thr: 0.2600 loss_db: 0.0608 loss: 0.6683 2022/08/30 18:54:26 - mmengine - INFO - Epoch(train) [888][35/63] lr: 2.0841e-03 eta: 6:34:36 time: 1.0262 data_time: 0.0336 memory: 16201 loss_prob: 0.3992 loss_thr: 0.2791 loss_db: 0.0712 loss: 0.7494 2022/08/30 18:54:31 - mmengine - INFO - Epoch(train) [888][40/63] lr: 2.0841e-03 eta: 6:34:23 time: 1.0121 data_time: 0.0310 memory: 16201 loss_prob: 0.4246 loss_thr: 0.2869 loss_db: 0.0742 loss: 0.7856 2022/08/30 18:54:36 - mmengine - INFO - Epoch(train) [888][45/63] lr: 2.0841e-03 eta: 6:34:23 time: 0.9940 data_time: 0.0291 memory: 16201 loss_prob: 0.3960 loss_thr: 0.2859 loss_db: 0.0691 loss: 0.7510 2022/08/30 18:54:41 - mmengine - INFO - Epoch(train) [888][50/63] lr: 2.0841e-03 eta: 6:34:11 time: 1.0509 data_time: 0.0401 memory: 16201 loss_prob: 0.3694 loss_thr: 0.2702 loss_db: 0.0665 loss: 0.7062 2022/08/30 18:54:46 - mmengine - INFO - Epoch(train) [888][55/63] lr: 2.0841e-03 eta: 6:34:11 time: 1.0663 data_time: 0.0336 memory: 16201 loss_prob: 0.3602 loss_thr: 0.2512 loss_db: 0.0659 loss: 0.6773 2022/08/30 18:54:51 - mmengine - INFO - Epoch(train) [888][60/63] lr: 2.0841e-03 eta: 6:33:58 time: 0.9837 data_time: 0.0277 memory: 16201 loss_prob: 0.3769 loss_thr: 0.2679 loss_db: 0.0677 loss: 0.7125 2022/08/30 18:54:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:54:59 - mmengine - INFO - Epoch(train) [889][5/63] lr: 2.0781e-03 eta: 6:33:58 time: 1.0286 data_time: 0.2162 memory: 16201 loss_prob: 0.3626 loss_thr: 0.2559 loss_db: 0.0621 loss: 0.6805 2022/08/30 18:55:03 - mmengine - INFO - Epoch(train) [889][10/63] lr: 2.0781e-03 eta: 6:33:40 time: 0.9949 data_time: 0.2257 memory: 16201 loss_prob: 0.3654 loss_thr: 0.2527 loss_db: 0.0641 loss: 0.6823 2022/08/30 18:55:07 - mmengine - INFO - Epoch(train) [889][15/63] lr: 2.0781e-03 eta: 6:33:40 time: 0.7911 data_time: 0.0250 memory: 16201 loss_prob: 0.3627 loss_thr: 0.2555 loss_db: 0.0646 loss: 0.6828 2022/08/30 18:55:12 - mmengine - INFO - Epoch(train) [889][20/63] lr: 2.0781e-03 eta: 6:33:27 time: 0.8217 data_time: 0.0192 memory: 16201 loss_prob: 0.3581 loss_thr: 0.2591 loss_db: 0.0633 loss: 0.6805 2022/08/30 18:55:16 - mmengine - INFO - Epoch(train) [889][25/63] lr: 2.0781e-03 eta: 6:33:27 time: 0.8209 data_time: 0.0310 memory: 16201 loss_prob: 0.3892 loss_thr: 0.2849 loss_db: 0.0683 loss: 0.7424 2022/08/30 18:55:20 - mmengine - INFO - Epoch(train) [889][30/63] lr: 2.0781e-03 eta: 6:33:14 time: 0.8554 data_time: 0.0344 memory: 16201 loss_prob: 0.4030 loss_thr: 0.2929 loss_db: 0.0716 loss: 0.7675 2022/08/30 18:55:25 - mmengine - INFO - Epoch(train) [889][35/63] lr: 2.0781e-03 eta: 6:33:14 time: 0.9341 data_time: 0.0234 memory: 16201 loss_prob: 0.3842 loss_thr: 0.2717 loss_db: 0.0676 loss: 0.7234 2022/08/30 18:55:31 - mmengine - INFO - Epoch(train) [889][40/63] lr: 2.0781e-03 eta: 6:33:01 time: 1.0440 data_time: 0.0284 memory: 16201 loss_prob: 0.3606 loss_thr: 0.2588 loss_db: 0.0621 loss: 0.6815 2022/08/30 18:55:35 - mmengine - INFO - Epoch(train) [889][45/63] lr: 2.0781e-03 eta: 6:33:01 time: 1.0214 data_time: 0.0358 memory: 16201 loss_prob: 0.3541 loss_thr: 0.2566 loss_db: 0.0628 loss: 0.6735 2022/08/30 18:55:39 - mmengine - INFO - Epoch(train) [889][50/63] lr: 2.0781e-03 eta: 6:32:48 time: 0.8531 data_time: 0.0321 memory: 16201 loss_prob: 0.3724 loss_thr: 0.2642 loss_db: 0.0686 loss: 0.7052 2022/08/30 18:55:43 - mmengine - INFO - Epoch(train) [889][55/63] lr: 2.0781e-03 eta: 6:32:48 time: 0.8047 data_time: 0.0240 memory: 16201 loss_prob: 0.3759 loss_thr: 0.2637 loss_db: 0.0668 loss: 0.7064 2022/08/30 18:55:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:55:48 - mmengine - INFO - Epoch(train) [889][60/63] lr: 2.0781e-03 eta: 6:32:35 time: 0.8488 data_time: 0.0200 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2619 loss_db: 0.0638 loss: 0.6995 2022/08/30 18:55:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:55:58 - mmengine - INFO - Epoch(train) [890][5/63] lr: 2.0721e-03 eta: 6:32:35 time: 1.1744 data_time: 0.2412 memory: 16201 loss_prob: 0.4013 loss_thr: 0.2977 loss_db: 0.0717 loss: 0.7707 2022/08/30 18:56:03 - mmengine - INFO - Epoch(train) [890][10/63] lr: 2.0721e-03 eta: 6:32:18 time: 1.2537 data_time: 0.2541 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2921 loss_db: 0.0690 loss: 0.7531 2022/08/30 18:56:08 - mmengine - INFO - Epoch(train) [890][15/63] lr: 2.0721e-03 eta: 6:32:18 time: 1.0218 data_time: 0.0326 memory: 16201 loss_prob: 0.3689 loss_thr: 0.2756 loss_db: 0.0654 loss: 0.7099 2022/08/30 18:56:13 - mmengine - INFO - Epoch(train) [890][20/63] lr: 2.0721e-03 eta: 6:32:05 time: 1.0217 data_time: 0.0296 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2527 loss_db: 0.0619 loss: 0.6579 2022/08/30 18:56:17 - mmengine - INFO - Epoch(train) [890][25/63] lr: 2.0721e-03 eta: 6:32:05 time: 0.9053 data_time: 0.0393 memory: 16201 loss_prob: 0.3469 loss_thr: 0.2445 loss_db: 0.0604 loss: 0.6518 2022/08/30 18:56:21 - mmengine - INFO - Epoch(train) [890][30/63] lr: 2.0721e-03 eta: 6:31:52 time: 0.7940 data_time: 0.0213 memory: 16201 loss_prob: 0.3307 loss_thr: 0.2347 loss_db: 0.0559 loss: 0.6213 2022/08/30 18:56:25 - mmengine - INFO - Epoch(train) [890][35/63] lr: 2.0721e-03 eta: 6:31:52 time: 0.7854 data_time: 0.0254 memory: 16201 loss_prob: 0.3333 loss_thr: 0.2562 loss_db: 0.0592 loss: 0.6487 2022/08/30 18:56:29 - mmengine - INFO - Epoch(train) [890][40/63] lr: 2.0721e-03 eta: 6:31:38 time: 0.7833 data_time: 0.0257 memory: 16201 loss_prob: 0.3474 loss_thr: 0.2695 loss_db: 0.0630 loss: 0.6799 2022/08/30 18:56:34 - mmengine - INFO - Epoch(train) [890][45/63] lr: 2.0721e-03 eta: 6:31:38 time: 0.8775 data_time: 0.0240 memory: 16201 loss_prob: 0.3825 loss_thr: 0.2728 loss_db: 0.0684 loss: 0.7237 2022/08/30 18:56:38 - mmengine - INFO - Epoch(train) [890][50/63] lr: 2.0721e-03 eta: 6:31:25 time: 0.9374 data_time: 0.0396 memory: 16201 loss_prob: 0.4051 loss_thr: 0.2805 loss_db: 0.0712 loss: 0.7568 2022/08/30 18:56:43 - mmengine - INFO - Epoch(train) [890][55/63] lr: 2.0721e-03 eta: 6:31:25 time: 0.8894 data_time: 0.0251 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2626 loss_db: 0.0676 loss: 0.7073 2022/08/30 18:56:47 - mmengine - INFO - Epoch(train) [890][60/63] lr: 2.0721e-03 eta: 6:31:12 time: 0.9034 data_time: 0.0244 memory: 16201 loss_prob: 0.3401 loss_thr: 0.2457 loss_db: 0.0609 loss: 0.6466 2022/08/30 18:56:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:56:57 - mmengine - INFO - Epoch(train) [891][5/63] lr: 2.0660e-03 eta: 6:31:12 time: 1.1614 data_time: 0.2699 memory: 16201 loss_prob: 0.3862 loss_thr: 0.2657 loss_db: 0.0663 loss: 0.7183 2022/08/30 18:57:03 - mmengine - INFO - Epoch(train) [891][10/63] lr: 2.0660e-03 eta: 6:30:56 time: 1.3125 data_time: 0.2689 memory: 16201 loss_prob: 0.3841 loss_thr: 0.2660 loss_db: 0.0684 loss: 0.7185 2022/08/30 18:57:08 - mmengine - INFO - Epoch(train) [891][15/63] lr: 2.0660e-03 eta: 6:30:56 time: 1.0496 data_time: 0.0279 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2555 loss_db: 0.0624 loss: 0.6615 2022/08/30 18:57:12 - mmengine - INFO - Epoch(train) [891][20/63] lr: 2.0660e-03 eta: 6:30:43 time: 0.9466 data_time: 0.0355 memory: 16201 loss_prob: 0.3540 loss_thr: 0.2700 loss_db: 0.0634 loss: 0.6874 2022/08/30 18:57:16 - mmengine - INFO - Epoch(train) [891][25/63] lr: 2.0660e-03 eta: 6:30:43 time: 0.8532 data_time: 0.0257 memory: 16201 loss_prob: 0.3733 loss_thr: 0.2762 loss_db: 0.0673 loss: 0.7168 2022/08/30 18:57:21 - mmengine - INFO - Epoch(train) [891][30/63] lr: 2.0660e-03 eta: 6:30:30 time: 0.8397 data_time: 0.0559 memory: 16201 loss_prob: 0.3838 loss_thr: 0.2634 loss_db: 0.0676 loss: 0.7148 2022/08/30 18:57:25 - mmengine - INFO - Epoch(train) [891][35/63] lr: 2.0660e-03 eta: 6:30:30 time: 0.8722 data_time: 0.0666 memory: 16201 loss_prob: 0.3708 loss_thr: 0.2551 loss_db: 0.0638 loss: 0.6897 2022/08/30 18:57:30 - mmengine - INFO - Epoch(train) [891][40/63] lr: 2.0660e-03 eta: 6:30:17 time: 0.9521 data_time: 0.0232 memory: 16201 loss_prob: 0.3809 loss_thr: 0.2595 loss_db: 0.0665 loss: 0.7069 2022/08/30 18:57:36 - mmengine - INFO - Epoch(train) [891][45/63] lr: 2.0660e-03 eta: 6:30:17 time: 1.0482 data_time: 0.0303 memory: 16201 loss_prob: 0.3876 loss_thr: 0.2643 loss_db: 0.0680 loss: 0.7199 2022/08/30 18:57:40 - mmengine - INFO - Epoch(train) [891][50/63] lr: 2.0660e-03 eta: 6:30:04 time: 1.0208 data_time: 0.0353 memory: 16201 loss_prob: 0.3667 loss_thr: 0.2604 loss_db: 0.0649 loss: 0.6920 2022/08/30 18:57:45 - mmengine - INFO - Epoch(train) [891][55/63] lr: 2.0660e-03 eta: 6:30:04 time: 0.9924 data_time: 0.0287 memory: 16201 loss_prob: 0.3637 loss_thr: 0.2548 loss_db: 0.0646 loss: 0.6831 2022/08/30 18:57:50 - mmengine - INFO - Epoch(train) [891][60/63] lr: 2.0660e-03 eta: 6:29:51 time: 0.9848 data_time: 0.0327 memory: 16201 loss_prob: 0.3669 loss_thr: 0.2645 loss_db: 0.0669 loss: 0.6982 2022/08/30 18:57:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:57:59 - mmengine - INFO - Epoch(train) [892][5/63] lr: 2.0600e-03 eta: 6:29:51 time: 0.9967 data_time: 0.2233 memory: 16201 loss_prob: 0.3764 loss_thr: 0.2774 loss_db: 0.0694 loss: 0.7232 2022/08/30 18:58:03 - mmengine - INFO - Epoch(train) [892][10/63] lr: 2.0600e-03 eta: 6:29:34 time: 1.0084 data_time: 0.2357 memory: 16201 loss_prob: 0.3822 loss_thr: 0.2770 loss_db: 0.0688 loss: 0.7279 2022/08/30 18:58:07 - mmengine - INFO - Epoch(train) [892][15/63] lr: 2.0600e-03 eta: 6:29:34 time: 0.8367 data_time: 0.0306 memory: 16201 loss_prob: 0.3448 loss_thr: 0.2564 loss_db: 0.0608 loss: 0.6619 2022/08/30 18:58:13 - mmengine - INFO - Epoch(train) [892][20/63] lr: 2.0600e-03 eta: 6:29:21 time: 1.0024 data_time: 0.0215 memory: 16201 loss_prob: 0.3443 loss_thr: 0.2715 loss_db: 0.0606 loss: 0.6764 2022/08/30 18:58:18 - mmengine - INFO - Epoch(train) [892][25/63] lr: 2.0600e-03 eta: 6:29:21 time: 1.0562 data_time: 0.0342 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2694 loss_db: 0.0642 loss: 0.6915 2022/08/30 18:58:23 - mmengine - INFO - Epoch(train) [892][30/63] lr: 2.0600e-03 eta: 6:29:08 time: 0.9768 data_time: 0.0301 memory: 16201 loss_prob: 0.3866 loss_thr: 0.2721 loss_db: 0.0695 loss: 0.7283 2022/08/30 18:58:27 - mmengine - INFO - Epoch(train) [892][35/63] lr: 2.0600e-03 eta: 6:29:08 time: 0.8975 data_time: 0.0199 memory: 16201 loss_prob: 0.3770 loss_thr: 0.2644 loss_db: 0.0670 loss: 0.7083 2022/08/30 18:58:31 - mmengine - INFO - Epoch(train) [892][40/63] lr: 2.0600e-03 eta: 6:28:55 time: 0.8091 data_time: 0.0261 memory: 16201 loss_prob: 0.3414 loss_thr: 0.2500 loss_db: 0.0609 loss: 0.6523 2022/08/30 18:58:35 - mmengine - INFO - Epoch(train) [892][45/63] lr: 2.0600e-03 eta: 6:28:55 time: 0.8511 data_time: 0.0284 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2592 loss_db: 0.0635 loss: 0.6796 2022/08/30 18:58:40 - mmengine - INFO - Epoch(train) [892][50/63] lr: 2.0600e-03 eta: 6:28:42 time: 0.9574 data_time: 0.0269 memory: 16201 loss_prob: 0.3545 loss_thr: 0.2534 loss_db: 0.0628 loss: 0.6708 2022/08/30 18:58:46 - mmengine - INFO - Epoch(train) [892][55/63] lr: 2.0600e-03 eta: 6:28:42 time: 1.0429 data_time: 0.0337 memory: 16201 loss_prob: 0.3547 loss_thr: 0.2479 loss_db: 0.0614 loss: 0.6640 2022/08/30 18:58:51 - mmengine - INFO - Epoch(train) [892][60/63] lr: 2.0600e-03 eta: 6:28:29 time: 1.0237 data_time: 0.0371 memory: 16201 loss_prob: 0.3640 loss_thr: 0.2551 loss_db: 0.0613 loss: 0.6804 2022/08/30 18:58:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 18:58:59 - mmengine - INFO - Epoch(train) [893][5/63] lr: 2.0540e-03 eta: 6:28:29 time: 1.0534 data_time: 0.2329 memory: 16201 loss_prob: 0.3582 loss_thr: 0.2540 loss_db: 0.0610 loss: 0.6732 2022/08/30 18:59:03 - mmengine - INFO - Epoch(train) [893][10/63] lr: 2.0540e-03 eta: 6:28:12 time: 1.0240 data_time: 0.2375 memory: 16201 loss_prob: 0.3331 loss_thr: 0.2390 loss_db: 0.0598 loss: 0.6319 2022/08/30 18:59:07 - mmengine - INFO - Epoch(train) [893][15/63] lr: 2.0540e-03 eta: 6:28:12 time: 0.8062 data_time: 0.0287 memory: 16201 loss_prob: 0.3344 loss_thr: 0.2395 loss_db: 0.0578 loss: 0.6317 2022/08/30 18:59:11 - mmengine - INFO - Epoch(train) [893][20/63] lr: 2.0540e-03 eta: 6:27:59 time: 0.8151 data_time: 0.0253 memory: 16201 loss_prob: 0.3428 loss_thr: 0.2442 loss_db: 0.0609 loss: 0.6479 2022/08/30 18:59:16 - mmengine - INFO - Epoch(train) [893][25/63] lr: 2.0540e-03 eta: 6:27:59 time: 0.9174 data_time: 0.0316 memory: 16201 loss_prob: 0.3334 loss_thr: 0.2332 loss_db: 0.0597 loss: 0.6264 2022/08/30 18:59:22 - mmengine - INFO - Epoch(train) [893][30/63] lr: 2.0540e-03 eta: 6:27:46 time: 1.0100 data_time: 0.0292 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2415 loss_db: 0.0565 loss: 0.6231 2022/08/30 18:59:27 - mmengine - INFO - Epoch(train) [893][35/63] lr: 2.0540e-03 eta: 6:27:46 time: 1.0619 data_time: 0.0274 memory: 16201 loss_prob: 0.3624 loss_thr: 0.2644 loss_db: 0.0646 loss: 0.6913 2022/08/30 18:59:32 - mmengine - INFO - Epoch(train) [893][40/63] lr: 2.0540e-03 eta: 6:27:33 time: 1.0419 data_time: 0.0287 memory: 16201 loss_prob: 0.3660 loss_thr: 0.2598 loss_db: 0.0653 loss: 0.6912 2022/08/30 18:59:36 - mmengine - INFO - Epoch(train) [893][45/63] lr: 2.0540e-03 eta: 6:27:33 time: 0.8907 data_time: 0.0261 memory: 16201 loss_prob: 0.3334 loss_thr: 0.2529 loss_db: 0.0590 loss: 0.6452 2022/08/30 18:59:40 - mmengine - INFO - Epoch(train) [893][50/63] lr: 2.0540e-03 eta: 6:27:20 time: 0.7979 data_time: 0.0267 memory: 16201 loss_prob: 0.3371 loss_thr: 0.2554 loss_db: 0.0589 loss: 0.6513 2022/08/30 18:59:44 - mmengine - INFO - Epoch(train) [893][55/63] lr: 2.0540e-03 eta: 6:27:20 time: 0.8400 data_time: 0.0254 memory: 16201 loss_prob: 0.3572 loss_thr: 0.2532 loss_db: 0.0624 loss: 0.6728 2022/08/30 18:59:50 - mmengine - INFO - Epoch(train) [893][60/63] lr: 2.0540e-03 eta: 6:27:07 time: 0.9668 data_time: 0.0244 memory: 16201 loss_prob: 0.3803 loss_thr: 0.2738 loss_db: 0.0685 loss: 0.7227 2022/08/30 18:59:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:00:00 - mmengine - INFO - Epoch(train) [894][5/63] lr: 2.0480e-03 eta: 6:27:07 time: 1.2048 data_time: 0.2369 memory: 16201 loss_prob: 0.4069 loss_thr: 0.2865 loss_db: 0.0718 loss: 0.7652 2022/08/30 19:00:04 - mmengine - INFO - Epoch(train) [894][10/63] lr: 2.0480e-03 eta: 6:26:50 time: 1.1073 data_time: 0.2366 memory: 16201 loss_prob: 0.4194 loss_thr: 0.2963 loss_db: 0.0757 loss: 0.7915 2022/08/30 19:00:08 - mmengine - INFO - Epoch(train) [894][15/63] lr: 2.0480e-03 eta: 6:26:50 time: 0.7879 data_time: 0.0234 memory: 16201 loss_prob: 0.4111 loss_thr: 0.2935 loss_db: 0.0742 loss: 0.7788 2022/08/30 19:00:12 - mmengine - INFO - Epoch(train) [894][20/63] lr: 2.0480e-03 eta: 6:26:37 time: 0.8110 data_time: 0.0197 memory: 16201 loss_prob: 0.3442 loss_thr: 0.2591 loss_db: 0.0618 loss: 0.6652 2022/08/30 19:00:16 - mmengine - INFO - Epoch(train) [894][25/63] lr: 2.0480e-03 eta: 6:26:37 time: 0.8654 data_time: 0.0310 memory: 16201 loss_prob: 0.3317 loss_thr: 0.2569 loss_db: 0.0594 loss: 0.6480 2022/08/30 19:00:21 - mmengine - INFO - Epoch(train) [894][30/63] lr: 2.0480e-03 eta: 6:26:24 time: 0.8951 data_time: 0.0313 memory: 16201 loss_prob: 0.3711 loss_thr: 0.2606 loss_db: 0.0655 loss: 0.6971 2022/08/30 19:00:26 - mmengine - INFO - Epoch(train) [894][35/63] lr: 2.0480e-03 eta: 6:26:24 time: 0.9639 data_time: 0.0246 memory: 16201 loss_prob: 0.3700 loss_thr: 0.2519 loss_db: 0.0640 loss: 0.6859 2022/08/30 19:00:31 - mmengine - INFO - Epoch(train) [894][40/63] lr: 2.0480e-03 eta: 6:26:11 time: 0.9931 data_time: 0.0286 memory: 16201 loss_prob: 0.3895 loss_thr: 0.2698 loss_db: 0.0675 loss: 0.7268 2022/08/30 19:00:35 - mmengine - INFO - Epoch(train) [894][45/63] lr: 2.0480e-03 eta: 6:26:11 time: 0.8701 data_time: 0.0305 memory: 16201 loss_prob: 0.4222 loss_thr: 0.2913 loss_db: 0.0741 loss: 0.7875 2022/08/30 19:00:39 - mmengine - INFO - Epoch(train) [894][50/63] lr: 2.0480e-03 eta: 6:25:58 time: 0.7975 data_time: 0.0255 memory: 16201 loss_prob: 0.3778 loss_thr: 0.2708 loss_db: 0.0673 loss: 0.7160 2022/08/30 19:00:44 - mmengine - INFO - Epoch(train) [894][55/63] lr: 2.0480e-03 eta: 6:25:58 time: 0.9121 data_time: 0.0287 memory: 16201 loss_prob: 0.3706 loss_thr: 0.2561 loss_db: 0.0682 loss: 0.6949 2022/08/30 19:00:49 - mmengine - INFO - Epoch(train) [894][60/63] lr: 2.0480e-03 eta: 6:25:45 time: 1.0281 data_time: 0.0316 memory: 16201 loss_prob: 0.3577 loss_thr: 0.2418 loss_db: 0.0660 loss: 0.6654 2022/08/30 19:00:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:00:59 - mmengine - INFO - Epoch(train) [895][5/63] lr: 2.0420e-03 eta: 6:25:45 time: 1.2011 data_time: 0.2189 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2450 loss_db: 0.0608 loss: 0.6539 2022/08/30 19:01:04 - mmengine - INFO - Epoch(train) [895][10/63] lr: 2.0420e-03 eta: 6:25:28 time: 1.2026 data_time: 0.2216 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2476 loss_db: 0.0601 loss: 0.6525 2022/08/30 19:01:08 - mmengine - INFO - Epoch(train) [895][15/63] lr: 2.0420e-03 eta: 6:25:28 time: 0.8676 data_time: 0.0301 memory: 16201 loss_prob: 0.3531 loss_thr: 0.2527 loss_db: 0.0629 loss: 0.6688 2022/08/30 19:01:13 - mmengine - INFO - Epoch(train) [895][20/63] lr: 2.0420e-03 eta: 6:25:15 time: 0.8957 data_time: 0.0249 memory: 16201 loss_prob: 0.3270 loss_thr: 0.2417 loss_db: 0.0581 loss: 0.6268 2022/08/30 19:01:17 - mmengine - INFO - Epoch(train) [895][25/63] lr: 2.0420e-03 eta: 6:25:15 time: 0.8999 data_time: 0.0331 memory: 16201 loss_prob: 0.3662 loss_thr: 0.2663 loss_db: 0.0639 loss: 0.6964 2022/08/30 19:01:21 - mmengine - INFO - Epoch(train) [895][30/63] lr: 2.0420e-03 eta: 6:25:02 time: 0.8501 data_time: 0.0324 memory: 16201 loss_prob: 0.3951 loss_thr: 0.2815 loss_db: 0.0704 loss: 0.7470 2022/08/30 19:01:26 - mmengine - INFO - Epoch(train) [895][35/63] lr: 2.0420e-03 eta: 6:25:02 time: 0.9743 data_time: 0.0281 memory: 16201 loss_prob: 0.3974 loss_thr: 0.2868 loss_db: 0.0703 loss: 0.7545 2022/08/30 19:01:32 - mmengine - INFO - Epoch(train) [895][40/63] lr: 2.0420e-03 eta: 6:24:50 time: 1.1122 data_time: 0.0274 memory: 16201 loss_prob: 0.3796 loss_thr: 0.2804 loss_db: 0.0661 loss: 0.7260 2022/08/30 19:01:37 - mmengine - INFO - Epoch(train) [895][45/63] lr: 2.0420e-03 eta: 6:24:50 time: 1.0819 data_time: 0.0305 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2649 loss_db: 0.0638 loss: 0.6866 2022/08/30 19:01:42 - mmengine - INFO - Epoch(train) [895][50/63] lr: 2.0420e-03 eta: 6:24:37 time: 0.9343 data_time: 0.0442 memory: 16201 loss_prob: 0.3810 loss_thr: 0.2635 loss_db: 0.0683 loss: 0.7129 2022/08/30 19:01:46 - mmengine - INFO - Epoch(train) [895][55/63] lr: 2.0420e-03 eta: 6:24:37 time: 0.8388 data_time: 0.0347 memory: 16201 loss_prob: 0.3628 loss_thr: 0.2548 loss_db: 0.0655 loss: 0.6832 2022/08/30 19:01:50 - mmengine - INFO - Epoch(train) [895][60/63] lr: 2.0420e-03 eta: 6:24:23 time: 0.7960 data_time: 0.0195 memory: 16201 loss_prob: 0.3672 loss_thr: 0.2665 loss_db: 0.0654 loss: 0.6990 2022/08/30 19:01:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:01:59 - mmengine - INFO - Epoch(train) [896][5/63] lr: 2.0359e-03 eta: 6:24:23 time: 1.0941 data_time: 0.2230 memory: 16201 loss_prob: 0.3597 loss_thr: 0.2485 loss_db: 0.0647 loss: 0.6730 2022/08/30 19:02:04 - mmengine - INFO - Epoch(train) [896][10/63] lr: 2.0359e-03 eta: 6:24:07 time: 1.2747 data_time: 0.2268 memory: 16201 loss_prob: 0.3329 loss_thr: 0.2353 loss_db: 0.0596 loss: 0.6278 2022/08/30 19:02:09 - mmengine - INFO - Epoch(train) [896][15/63] lr: 2.0359e-03 eta: 6:24:07 time: 1.0321 data_time: 0.0290 memory: 16201 loss_prob: 0.3417 loss_thr: 0.2490 loss_db: 0.0608 loss: 0.6515 2022/08/30 19:02:14 - mmengine - INFO - Epoch(train) [896][20/63] lr: 2.0359e-03 eta: 6:23:54 time: 0.9762 data_time: 0.0299 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2701 loss_db: 0.0709 loss: 0.7331 2022/08/30 19:02:19 - mmengine - INFO - Epoch(train) [896][25/63] lr: 2.0359e-03 eta: 6:23:54 time: 0.9522 data_time: 0.0329 memory: 16201 loss_prob: 0.3838 loss_thr: 0.2682 loss_db: 0.0694 loss: 0.7214 2022/08/30 19:02:23 - mmengine - INFO - Epoch(train) [896][30/63] lr: 2.0359e-03 eta: 6:23:41 time: 0.8730 data_time: 0.0227 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2618 loss_db: 0.0662 loss: 0.7133 2022/08/30 19:02:27 - mmengine - INFO - Epoch(train) [896][35/63] lr: 2.0359e-03 eta: 6:23:41 time: 0.8121 data_time: 0.0292 memory: 16201 loss_prob: 0.3820 loss_thr: 0.2628 loss_db: 0.0659 loss: 0.7108 2022/08/30 19:02:31 - mmengine - INFO - Epoch(train) [896][40/63] lr: 2.0359e-03 eta: 6:23:28 time: 0.8255 data_time: 0.0295 memory: 16201 loss_prob: 0.3392 loss_thr: 0.2420 loss_db: 0.0606 loss: 0.6419 2022/08/30 19:02:37 - mmengine - INFO - Epoch(train) [896][45/63] lr: 2.0359e-03 eta: 6:23:28 time: 0.9493 data_time: 0.0291 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2357 loss_db: 0.0590 loss: 0.6198 2022/08/30 19:02:42 - mmengine - INFO - Epoch(train) [896][50/63] lr: 2.0359e-03 eta: 6:23:15 time: 1.0648 data_time: 0.0385 memory: 16201 loss_prob: 0.3523 loss_thr: 0.2589 loss_db: 0.0635 loss: 0.6747 2022/08/30 19:02:47 - mmengine - INFO - Epoch(train) [896][55/63] lr: 2.0359e-03 eta: 6:23:15 time: 1.0520 data_time: 0.0320 memory: 16201 loss_prob: 0.3638 loss_thr: 0.2660 loss_db: 0.0638 loss: 0.6936 2022/08/30 19:02:53 - mmengine - INFO - Epoch(train) [896][60/63] lr: 2.0359e-03 eta: 6:23:03 time: 1.1305 data_time: 0.0334 memory: 16201 loss_prob: 0.3418 loss_thr: 0.2489 loss_db: 0.0590 loss: 0.6497 2022/08/30 19:02:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:03:01 - mmengine - INFO - Epoch(train) [897][5/63] lr: 2.0299e-03 eta: 6:23:03 time: 1.0124 data_time: 0.2004 memory: 16201 loss_prob: 0.3517 loss_thr: 0.2648 loss_db: 0.0628 loss: 0.6794 2022/08/30 19:03:06 - mmengine - INFO - Epoch(train) [897][10/63] lr: 2.0299e-03 eta: 6:22:45 time: 1.0212 data_time: 0.2029 memory: 16201 loss_prob: 0.3750 loss_thr: 0.2754 loss_db: 0.0666 loss: 0.7170 2022/08/30 19:03:11 - mmengine - INFO - Epoch(train) [897][15/63] lr: 2.0299e-03 eta: 6:22:45 time: 0.9613 data_time: 0.0308 memory: 16201 loss_prob: 0.4415 loss_thr: 0.2976 loss_db: 0.0773 loss: 0.8164 2022/08/30 19:03:16 - mmengine - INFO - Epoch(train) [897][20/63] lr: 2.0299e-03 eta: 6:22:33 time: 1.0259 data_time: 0.0284 memory: 16201 loss_prob: 0.3961 loss_thr: 0.2634 loss_db: 0.0696 loss: 0.7292 2022/08/30 19:03:20 - mmengine - INFO - Epoch(train) [897][25/63] lr: 2.0299e-03 eta: 6:22:33 time: 0.9017 data_time: 0.0347 memory: 16201 loss_prob: 0.3215 loss_thr: 0.2321 loss_db: 0.0564 loss: 0.6099 2022/08/30 19:03:24 - mmengine - INFO - Epoch(train) [897][30/63] lr: 2.0299e-03 eta: 6:22:20 time: 0.8232 data_time: 0.0371 memory: 16201 loss_prob: 0.3358 loss_thr: 0.2477 loss_db: 0.0597 loss: 0.6432 2022/08/30 19:03:29 - mmengine - INFO - Epoch(train) [897][35/63] lr: 2.0299e-03 eta: 6:22:20 time: 0.8950 data_time: 0.0307 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2680 loss_db: 0.0656 loss: 0.6987 2022/08/30 19:03:34 - mmengine - INFO - Epoch(train) [897][40/63] lr: 2.0299e-03 eta: 6:22:07 time: 1.0123 data_time: 0.0304 memory: 16201 loss_prob: 0.3797 loss_thr: 0.2803 loss_db: 0.0672 loss: 0.7273 2022/08/30 19:03:39 - mmengine - INFO - Epoch(train) [897][45/63] lr: 2.0299e-03 eta: 6:22:07 time: 1.0519 data_time: 0.0310 memory: 16201 loss_prob: 0.3882 loss_thr: 0.2663 loss_db: 0.0677 loss: 0.7222 2022/08/30 19:03:45 - mmengine - INFO - Epoch(train) [897][50/63] lr: 2.0299e-03 eta: 6:21:54 time: 1.0403 data_time: 0.0382 memory: 16201 loss_prob: 0.3931 loss_thr: 0.2564 loss_db: 0.0682 loss: 0.7177 2022/08/30 19:03:49 - mmengine - INFO - Epoch(train) [897][55/63] lr: 2.0299e-03 eta: 6:21:54 time: 0.9375 data_time: 0.0296 memory: 16201 loss_prob: 0.4126 loss_thr: 0.2680 loss_db: 0.0721 loss: 0.7528 2022/08/30 19:03:53 - mmengine - INFO - Epoch(train) [897][60/63] lr: 2.0299e-03 eta: 6:21:41 time: 0.8197 data_time: 0.0187 memory: 16201 loss_prob: 0.3799 loss_thr: 0.2550 loss_db: 0.0677 loss: 0.7026 2022/08/30 19:03:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:04:01 - mmengine - INFO - Epoch(train) [898][5/63] lr: 2.0239e-03 eta: 6:21:41 time: 1.0143 data_time: 0.1911 memory: 16201 loss_prob: 0.3405 loss_thr: 0.2531 loss_db: 0.0605 loss: 0.6541 2022/08/30 19:04:06 - mmengine - INFO - Epoch(train) [898][10/63] lr: 2.0239e-03 eta: 6:21:24 time: 1.1164 data_time: 0.2012 memory: 16201 loss_prob: 0.3913 loss_thr: 0.2706 loss_db: 0.0679 loss: 0.7298 2022/08/30 19:04:11 - mmengine - INFO - Epoch(train) [898][15/63] lr: 2.0239e-03 eta: 6:21:24 time: 0.9217 data_time: 0.0331 memory: 16201 loss_prob: 0.4072 loss_thr: 0.2864 loss_db: 0.0710 loss: 0.7645 2022/08/30 19:04:16 - mmengine - INFO - Epoch(train) [898][20/63] lr: 2.0239e-03 eta: 6:21:11 time: 0.9557 data_time: 0.0256 memory: 16201 loss_prob: 0.3509 loss_thr: 0.2560 loss_db: 0.0634 loss: 0.6703 2022/08/30 19:04:21 - mmengine - INFO - Epoch(train) [898][25/63] lr: 2.0239e-03 eta: 6:21:11 time: 1.0337 data_time: 0.0399 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2430 loss_db: 0.0620 loss: 0.6510 2022/08/30 19:04:26 - mmengine - INFO - Epoch(train) [898][30/63] lr: 2.0239e-03 eta: 6:20:59 time: 1.0169 data_time: 0.0358 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2598 loss_db: 0.0638 loss: 0.6831 2022/08/30 19:04:30 - mmengine - INFO - Epoch(train) [898][35/63] lr: 2.0239e-03 eta: 6:20:59 time: 0.9544 data_time: 0.0267 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2628 loss_db: 0.0642 loss: 0.6838 2022/08/30 19:04:35 - mmengine - INFO - Epoch(train) [898][40/63] lr: 2.0239e-03 eta: 6:20:46 time: 0.9772 data_time: 0.0243 memory: 16201 loss_prob: 0.3318 loss_thr: 0.2346 loss_db: 0.0591 loss: 0.6254 2022/08/30 19:04:40 - mmengine - INFO - Epoch(train) [898][45/63] lr: 2.0239e-03 eta: 6:20:46 time: 0.9997 data_time: 0.0277 memory: 16201 loss_prob: 0.3657 loss_thr: 0.2492 loss_db: 0.0642 loss: 0.6790 2022/08/30 19:04:44 - mmengine - INFO - Epoch(train) [898][50/63] lr: 2.0239e-03 eta: 6:20:33 time: 0.8864 data_time: 0.0332 memory: 16201 loss_prob: 0.3908 loss_thr: 0.2742 loss_db: 0.0697 loss: 0.7346 2022/08/30 19:04:48 - mmengine - INFO - Epoch(train) [898][55/63] lr: 2.0239e-03 eta: 6:20:33 time: 0.7763 data_time: 0.0178 memory: 16201 loss_prob: 0.3417 loss_thr: 0.2554 loss_db: 0.0622 loss: 0.6592 2022/08/30 19:04:53 - mmengine - INFO - Epoch(train) [898][60/63] lr: 2.0239e-03 eta: 6:20:20 time: 0.8410 data_time: 0.0228 memory: 16201 loss_prob: 0.3634 loss_thr: 0.2557 loss_db: 0.0644 loss: 0.6835 2022/08/30 19:04:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:05:00 - mmengine - INFO - Epoch(train) [899][5/63] lr: 2.0178e-03 eta: 6:20:20 time: 0.9340 data_time: 0.1739 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2595 loss_db: 0.0629 loss: 0.6877 2022/08/30 19:05:04 - mmengine - INFO - Epoch(train) [899][10/63] lr: 2.0178e-03 eta: 6:20:02 time: 0.9720 data_time: 0.1868 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2486 loss_db: 0.0605 loss: 0.6532 2022/08/30 19:05:09 - mmengine - INFO - Epoch(train) [899][15/63] lr: 2.0178e-03 eta: 6:20:02 time: 0.8589 data_time: 0.0252 memory: 16201 loss_prob: 0.3557 loss_thr: 0.2624 loss_db: 0.0626 loss: 0.6808 2022/08/30 19:05:15 - mmengine - INFO - Epoch(train) [899][20/63] lr: 2.0178e-03 eta: 6:19:50 time: 1.0689 data_time: 0.0361 memory: 16201 loss_prob: 0.3652 loss_thr: 0.2688 loss_db: 0.0655 loss: 0.6995 2022/08/30 19:05:20 - mmengine - INFO - Epoch(train) [899][25/63] lr: 2.0178e-03 eta: 6:19:50 time: 1.1109 data_time: 0.0434 memory: 16201 loss_prob: 0.3528 loss_thr: 0.2498 loss_db: 0.0647 loss: 0.6673 2022/08/30 19:05:25 - mmengine - INFO - Epoch(train) [899][30/63] lr: 2.0178e-03 eta: 6:19:37 time: 1.0328 data_time: 0.0286 memory: 16201 loss_prob: 0.3501 loss_thr: 0.2488 loss_db: 0.0629 loss: 0.6617 2022/08/30 19:05:31 - mmengine - INFO - Epoch(train) [899][35/63] lr: 2.0178e-03 eta: 6:19:37 time: 1.0599 data_time: 0.0451 memory: 16201 loss_prob: 0.3443 loss_thr: 0.2483 loss_db: 0.0607 loss: 0.6533 2022/08/30 19:05:36 - mmengine - INFO - Epoch(train) [899][40/63] lr: 2.0178e-03 eta: 6:19:24 time: 1.0078 data_time: 0.0338 memory: 16201 loss_prob: 0.3716 loss_thr: 0.2569 loss_db: 0.0633 loss: 0.6918 2022/08/30 19:05:40 - mmengine - INFO - Epoch(train) [899][45/63] lr: 2.0178e-03 eta: 6:19:24 time: 0.8933 data_time: 0.0280 memory: 16201 loss_prob: 0.4404 loss_thr: 0.2922 loss_db: 0.0752 loss: 0.8079 2022/08/30 19:05:44 - mmengine - INFO - Epoch(train) [899][50/63] lr: 2.0178e-03 eta: 6:19:11 time: 0.8254 data_time: 0.0387 memory: 16201 loss_prob: 0.4369 loss_thr: 0.2914 loss_db: 0.0755 loss: 0.8037 2022/08/30 19:05:48 - mmengine - INFO - Epoch(train) [899][55/63] lr: 2.0178e-03 eta: 6:19:11 time: 0.8251 data_time: 0.0207 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2660 loss_db: 0.0674 loss: 0.7170 2022/08/30 19:05:52 - mmengine - INFO - Epoch(train) [899][60/63] lr: 2.0178e-03 eta: 6:18:58 time: 0.8130 data_time: 0.0221 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2603 loss_db: 0.0663 loss: 0.7026 2022/08/30 19:05:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:06:01 - mmengine - INFO - Epoch(train) [900][5/63] lr: 2.0118e-03 eta: 6:18:58 time: 1.0656 data_time: 0.2181 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2575 loss_db: 0.0645 loss: 0.6813 2022/08/30 19:06:07 - mmengine - INFO - Epoch(train) [900][10/63] lr: 2.0118e-03 eta: 6:18:41 time: 1.3013 data_time: 0.2469 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2721 loss_db: 0.0706 loss: 0.7392 2022/08/30 19:06:12 - mmengine - INFO - Epoch(train) [900][15/63] lr: 2.0118e-03 eta: 6:18:41 time: 1.1048 data_time: 0.0466 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2540 loss_db: 0.0644 loss: 0.6757 2022/08/30 19:06:17 - mmengine - INFO - Epoch(train) [900][20/63] lr: 2.0118e-03 eta: 6:18:29 time: 0.9749 data_time: 0.0288 memory: 16201 loss_prob: 0.3184 loss_thr: 0.2372 loss_db: 0.0573 loss: 0.6129 2022/08/30 19:06:22 - mmengine - INFO - Epoch(train) [900][25/63] lr: 2.0118e-03 eta: 6:18:29 time: 0.9694 data_time: 0.0328 memory: 16201 loss_prob: 0.3238 loss_thr: 0.2389 loss_db: 0.0573 loss: 0.6200 2022/08/30 19:06:26 - mmengine - INFO - Epoch(train) [900][30/63] lr: 2.0118e-03 eta: 6:18:16 time: 0.9659 data_time: 0.0284 memory: 16201 loss_prob: 0.3572 loss_thr: 0.2556 loss_db: 0.0623 loss: 0.6751 2022/08/30 19:06:32 - mmengine - INFO - Epoch(train) [900][35/63] lr: 2.0118e-03 eta: 6:18:16 time: 1.0121 data_time: 0.0383 memory: 16201 loss_prob: 0.3485 loss_thr: 0.2551 loss_db: 0.0617 loss: 0.6654 2022/08/30 19:06:37 - mmengine - INFO - Epoch(train) [900][40/63] lr: 2.0118e-03 eta: 6:18:03 time: 1.0469 data_time: 0.0290 memory: 16201 loss_prob: 0.3399 loss_thr: 0.2557 loss_db: 0.0621 loss: 0.6577 2022/08/30 19:06:42 - mmengine - INFO - Epoch(train) [900][45/63] lr: 2.0118e-03 eta: 6:18:03 time: 1.0326 data_time: 0.0277 memory: 16201 loss_prob: 0.3273 loss_thr: 0.2446 loss_db: 0.0587 loss: 0.6307 2022/08/30 19:06:46 - mmengine - INFO - Epoch(train) [900][50/63] lr: 2.0118e-03 eta: 6:17:51 time: 0.9490 data_time: 0.0376 memory: 16201 loss_prob: 0.3575 loss_thr: 0.2570 loss_db: 0.0629 loss: 0.6774 2022/08/30 19:06:50 - mmengine - INFO - Epoch(train) [900][55/63] lr: 2.0118e-03 eta: 6:17:51 time: 0.8087 data_time: 0.0223 memory: 16201 loss_prob: 0.3705 loss_thr: 0.2595 loss_db: 0.0661 loss: 0.6962 2022/08/30 19:06:55 - mmengine - INFO - Epoch(train) [900][60/63] lr: 2.0118e-03 eta: 6:17:37 time: 0.8462 data_time: 0.0233 memory: 16201 loss_prob: 0.3392 loss_thr: 0.2342 loss_db: 0.0596 loss: 0.6330 2022/08/30 19:06:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:06:57 - mmengine - INFO - Saving checkpoint at 900 epochs 2022/08/30 19:07:05 - mmengine - INFO - Epoch(val) [900][5/32] eta: 6:17:37 time: 0.6564 data_time: 0.1090 memory: 16201 2022/08/30 19:07:08 - mmengine - INFO - Epoch(val) [900][10/32] eta: 0:00:15 time: 0.7260 data_time: 0.1471 memory: 15734 2022/08/30 19:07:11 - mmengine - INFO - Epoch(val) [900][15/32] eta: 0:00:15 time: 0.6421 data_time: 0.0581 memory: 15734 2022/08/30 19:07:15 - mmengine - INFO - Epoch(val) [900][20/32] eta: 0:00:07 time: 0.6638 data_time: 0.0846 memory: 15734 2022/08/30 19:07:18 - mmengine - INFO - Epoch(val) [900][25/32] eta: 0:00:07 time: 0.6852 data_time: 0.0881 memory: 15734 2022/08/30 19:07:22 - mmengine - INFO - Epoch(val) [900][30/32] eta: 0:00:01 time: 0.7185 data_time: 0.0349 memory: 15734 2022/08/30 19:07:23 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 19:07:23 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8421, precision: 0.8001, hmean: 0.8205 2022/08/30 19:07:23 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8421, precision: 0.8281, hmean: 0.8350 2022/08/30 19:07:23 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8416, precision: 0.8506, hmean: 0.8461 2022/08/30 19:07:23 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8402, precision: 0.8682, hmean: 0.8539 2022/08/30 19:07:23 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8329, precision: 0.8849, hmean: 0.8581 2022/08/30 19:07:23 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8026, precision: 0.9050, hmean: 0.8507 2022/08/30 19:07:23 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4165, precision: 0.9537, hmean: 0.5798 2022/08/30 19:07:23 - mmengine - INFO - Epoch(val) [900][32/32] icdar/precision: 0.8849 icdar/recall: 0.8329 icdar/hmean: 0.8581 2022/08/30 19:07:30 - mmengine - INFO - Epoch(train) [901][5/63] lr: 2.0058e-03 eta: 0:00:01 time: 1.0918 data_time: 0.2362 memory: 16201 loss_prob: 0.3876 loss_thr: 0.2672 loss_db: 0.0680 loss: 0.7229 2022/08/30 19:07:35 - mmengine - INFO - Epoch(train) [901][10/63] lr: 2.0058e-03 eta: 6:17:21 time: 1.2340 data_time: 0.2446 memory: 16201 loss_prob: 0.3554 loss_thr: 0.2530 loss_db: 0.0628 loss: 0.6713 2022/08/30 19:07:41 - mmengine - INFO - Epoch(train) [901][15/63] lr: 2.0058e-03 eta: 6:17:21 time: 1.0348 data_time: 0.0279 memory: 16201 loss_prob: 0.3750 loss_thr: 0.2645 loss_db: 0.0663 loss: 0.7058 2022/08/30 19:07:46 - mmengine - INFO - Epoch(train) [901][20/63] lr: 2.0058e-03 eta: 6:17:08 time: 1.0789 data_time: 0.0331 memory: 16201 loss_prob: 0.3876 loss_thr: 0.2650 loss_db: 0.0679 loss: 0.7205 2022/08/30 19:07:51 - mmengine - INFO - Epoch(train) [901][25/63] lr: 2.0058e-03 eta: 6:17:08 time: 0.9880 data_time: 0.0443 memory: 16201 loss_prob: 0.3729 loss_thr: 0.2667 loss_db: 0.0664 loss: 0.7060 2022/08/30 19:07:55 - mmengine - INFO - Epoch(train) [901][30/63] lr: 2.0058e-03 eta: 6:16:55 time: 0.8431 data_time: 0.0267 memory: 16201 loss_prob: 0.3944 loss_thr: 0.2798 loss_db: 0.0703 loss: 0.7445 2022/08/30 19:07:59 - mmengine - INFO - Epoch(train) [901][35/63] lr: 2.0058e-03 eta: 6:16:55 time: 0.8188 data_time: 0.0178 memory: 16201 loss_prob: 0.3754 loss_thr: 0.2698 loss_db: 0.0660 loss: 0.7112 2022/08/30 19:08:03 - mmengine - INFO - Epoch(train) [901][40/63] lr: 2.0058e-03 eta: 6:16:42 time: 0.8149 data_time: 0.0276 memory: 16201 loss_prob: 0.3497 loss_thr: 0.2584 loss_db: 0.0637 loss: 0.6717 2022/08/30 19:08:07 - mmengine - INFO - Epoch(train) [901][45/63] lr: 2.0058e-03 eta: 6:16:42 time: 0.8236 data_time: 0.0274 memory: 16201 loss_prob: 0.3687 loss_thr: 0.2634 loss_db: 0.0665 loss: 0.6986 2022/08/30 19:08:11 - mmengine - INFO - Epoch(train) [901][50/63] lr: 2.0058e-03 eta: 6:16:29 time: 0.8278 data_time: 0.0249 memory: 16201 loss_prob: 0.3635 loss_thr: 0.2629 loss_db: 0.0651 loss: 0.6915 2022/08/30 19:08:16 - mmengine - INFO - Epoch(train) [901][55/63] lr: 2.0058e-03 eta: 6:16:29 time: 0.9414 data_time: 0.0240 memory: 16201 loss_prob: 0.3668 loss_thr: 0.2603 loss_db: 0.0654 loss: 0.6925 2022/08/30 19:08:22 - mmengine - INFO - Epoch(train) [901][60/63] lr: 2.0058e-03 eta: 6:16:16 time: 1.0983 data_time: 0.0269 memory: 16201 loss_prob: 0.3665 loss_thr: 0.2640 loss_db: 0.0649 loss: 0.6955 2022/08/30 19:08:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:08:33 - mmengine - INFO - Epoch(train) [902][5/63] lr: 1.9997e-03 eta: 6:16:16 time: 1.2990 data_time: 0.2722 memory: 16201 loss_prob: 0.3827 loss_thr: 0.2778 loss_db: 0.0677 loss: 0.7282 2022/08/30 19:08:37 - mmengine - INFO - Epoch(train) [902][10/63] lr: 1.9997e-03 eta: 6:16:00 time: 1.2443 data_time: 0.2660 memory: 16201 loss_prob: 0.3714 loss_thr: 0.2649 loss_db: 0.0660 loss: 0.7023 2022/08/30 19:08:41 - mmengine - INFO - Epoch(train) [902][15/63] lr: 1.9997e-03 eta: 6:16:00 time: 0.8948 data_time: 0.0308 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2697 loss_db: 0.0694 loss: 0.7244 2022/08/30 19:08:45 - mmengine - INFO - Epoch(train) [902][20/63] lr: 1.9997e-03 eta: 6:15:47 time: 0.8179 data_time: 0.0224 memory: 16201 loss_prob: 0.4099 loss_thr: 0.2814 loss_db: 0.0714 loss: 0.7626 2022/08/30 19:08:49 - mmengine - INFO - Epoch(train) [902][25/63] lr: 1.9997e-03 eta: 6:15:47 time: 0.8034 data_time: 0.0277 memory: 16201 loss_prob: 0.3968 loss_thr: 0.2812 loss_db: 0.0676 loss: 0.7456 2022/08/30 19:08:54 - mmengine - INFO - Epoch(train) [902][30/63] lr: 1.9997e-03 eta: 6:15:33 time: 0.8279 data_time: 0.0323 memory: 16201 loss_prob: 0.3829 loss_thr: 0.2750 loss_db: 0.0670 loss: 0.7249 2022/08/30 19:08:58 - mmengine - INFO - Epoch(train) [902][35/63] lr: 1.9997e-03 eta: 6:15:33 time: 0.8199 data_time: 0.0330 memory: 16201 loss_prob: 0.3882 loss_thr: 0.2763 loss_db: 0.0705 loss: 0.7350 2022/08/30 19:09:03 - mmengine - INFO - Epoch(train) [902][40/63] lr: 1.9997e-03 eta: 6:15:20 time: 0.8947 data_time: 0.0247 memory: 16201 loss_prob: 0.3948 loss_thr: 0.2810 loss_db: 0.0726 loss: 0.7484 2022/08/30 19:09:08 - mmengine - INFO - Epoch(train) [902][45/63] lr: 1.9997e-03 eta: 6:15:20 time: 1.0504 data_time: 0.0347 memory: 16201 loss_prob: 0.3921 loss_thr: 0.2733 loss_db: 0.0701 loss: 0.7355 2022/08/30 19:09:13 - mmengine - INFO - Epoch(train) [902][50/63] lr: 1.9997e-03 eta: 6:15:08 time: 1.0167 data_time: 0.0445 memory: 16201 loss_prob: 0.3500 loss_thr: 0.2465 loss_db: 0.0619 loss: 0.6583 2022/08/30 19:09:17 - mmengine - INFO - Epoch(train) [902][55/63] lr: 1.9997e-03 eta: 6:15:08 time: 0.8974 data_time: 0.0263 memory: 16201 loss_prob: 0.3117 loss_thr: 0.2351 loss_db: 0.0559 loss: 0.6027 2022/08/30 19:09:22 - mmengine - INFO - Epoch(train) [902][60/63] lr: 1.9997e-03 eta: 6:14:55 time: 0.8858 data_time: 0.0210 memory: 16201 loss_prob: 0.3343 loss_thr: 0.2457 loss_db: 0.0576 loss: 0.6375 2022/08/30 19:09:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:09:32 - mmengine - INFO - Epoch(train) [903][5/63] lr: 1.9937e-03 eta: 6:14:55 time: 1.2196 data_time: 0.2393 memory: 16201 loss_prob: 0.3803 loss_thr: 0.2651 loss_db: 0.0650 loss: 0.7105 2022/08/30 19:09:38 - mmengine - INFO - Epoch(train) [903][10/63] lr: 1.9937e-03 eta: 6:14:39 time: 1.3252 data_time: 0.2517 memory: 16201 loss_prob: 0.9934 loss_thr: 0.2995 loss_db: 0.1188 loss: 1.4116 2022/08/30 19:09:44 - mmengine - INFO - Epoch(train) [903][15/63] lr: 1.9937e-03 eta: 6:14:39 time: 1.1883 data_time: 0.0311 memory: 16201 loss_prob: 1.0161 loss_thr: 0.3091 loss_db: 0.1194 loss: 1.4446 2022/08/30 19:09:48 - mmengine - INFO - Epoch(train) [903][20/63] lr: 1.9937e-03 eta: 6:14:26 time: 1.0222 data_time: 0.0356 memory: 16201 loss_prob: 0.4845 loss_thr: 0.3216 loss_db: 0.0821 loss: 0.8881 2022/08/30 19:09:52 - mmengine - INFO - Epoch(train) [903][25/63] lr: 1.9937e-03 eta: 6:14:26 time: 0.8130 data_time: 0.0323 memory: 16201 loss_prob: 0.5543 loss_thr: 0.3544 loss_db: 0.0962 loss: 1.0049 2022/08/30 19:09:56 - mmengine - INFO - Epoch(train) [903][30/63] lr: 1.9937e-03 eta: 6:14:13 time: 0.7959 data_time: 0.0185 memory: 16201 loss_prob: 0.5216 loss_thr: 0.3266 loss_db: 0.0870 loss: 0.9351 2022/08/30 19:10:00 - mmengine - INFO - Epoch(train) [903][35/63] lr: 1.9937e-03 eta: 6:14:13 time: 0.8422 data_time: 0.0299 memory: 16201 loss_prob: 0.4680 loss_thr: 0.3076 loss_db: 0.0772 loss: 0.8527 2022/08/30 19:10:06 - mmengine - INFO - Epoch(train) [903][40/63] lr: 1.9937e-03 eta: 6:14:00 time: 1.0127 data_time: 0.0282 memory: 16201 loss_prob: 0.6941 loss_thr: 0.3136 loss_db: 0.1090 loss: 1.1168 2022/08/30 19:10:12 - mmengine - INFO - Epoch(train) [903][45/63] lr: 1.9937e-03 eta: 6:14:00 time: 1.1251 data_time: 0.0346 memory: 16201 loss_prob: 0.7502 loss_thr: 0.3222 loss_db: 0.1130 loss: 1.1854 2022/08/30 19:10:16 - mmengine - INFO - Epoch(train) [903][50/63] lr: 1.9937e-03 eta: 6:13:47 time: 1.0227 data_time: 0.0393 memory: 16201 loss_prob: 0.5314 loss_thr: 0.3103 loss_db: 0.0802 loss: 0.9220 2022/08/30 19:10:20 - mmengine - INFO - Epoch(train) [903][55/63] lr: 1.9937e-03 eta: 6:13:47 time: 0.8756 data_time: 0.0281 memory: 16201 loss_prob: 0.5317 loss_thr: 0.3087 loss_db: 0.0851 loss: 0.9255 2022/08/30 19:10:24 - mmengine - INFO - Epoch(train) [903][60/63] lr: 1.9937e-03 eta: 6:13:34 time: 0.7976 data_time: 0.0267 memory: 16201 loss_prob: 0.5174 loss_thr: 0.3201 loss_db: 0.0901 loss: 0.9277 2022/08/30 19:10:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:10:34 - mmengine - INFO - Epoch(train) [904][5/63] lr: 1.9876e-03 eta: 6:13:34 time: 1.1219 data_time: 0.2291 memory: 16201 loss_prob: 0.5552 loss_thr: 0.3379 loss_db: 0.0977 loss: 0.9908 2022/08/30 19:10:39 - mmengine - INFO - Epoch(train) [904][10/63] lr: 1.9876e-03 eta: 6:13:18 time: 1.3241 data_time: 0.2440 memory: 16201 loss_prob: 0.4302 loss_thr: 0.2986 loss_db: 0.0773 loss: 0.8060 2022/08/30 19:10:45 - mmengine - INFO - Epoch(train) [904][15/63] lr: 1.9876e-03 eta: 6:13:18 time: 1.1147 data_time: 0.0356 memory: 16201 loss_prob: 0.4320 loss_thr: 0.3007 loss_db: 0.0758 loss: 0.8085 2022/08/30 19:10:51 - mmengine - INFO - Epoch(train) [904][20/63] lr: 1.9876e-03 eta: 6:13:06 time: 1.1408 data_time: 0.0307 memory: 16201 loss_prob: 0.4452 loss_thr: 0.3200 loss_db: 0.0772 loss: 0.8425 2022/08/30 19:10:56 - mmengine - INFO - Epoch(train) [904][25/63] lr: 1.9876e-03 eta: 6:13:06 time: 1.1024 data_time: 0.0356 memory: 16201 loss_prob: 0.4214 loss_thr: 0.3088 loss_db: 0.0741 loss: 0.8044 2022/08/30 19:11:01 - mmengine - INFO - Epoch(train) [904][30/63] lr: 1.9876e-03 eta: 6:12:53 time: 0.9848 data_time: 0.0388 memory: 16201 loss_prob: 0.3933 loss_thr: 0.2805 loss_db: 0.0713 loss: 0.7451 2022/08/30 19:11:05 - mmengine - INFO - Epoch(train) [904][35/63] lr: 1.9876e-03 eta: 6:12:53 time: 0.8874 data_time: 0.0359 memory: 16201 loss_prob: 0.3835 loss_thr: 0.2764 loss_db: 0.0687 loss: 0.7286 2022/08/30 19:11:09 - mmengine - INFO - Epoch(train) [904][40/63] lr: 1.9876e-03 eta: 6:12:40 time: 0.8214 data_time: 0.0233 memory: 16201 loss_prob: 0.4123 loss_thr: 0.2850 loss_db: 0.0699 loss: 0.7671 2022/08/30 19:11:13 - mmengine - INFO - Epoch(train) [904][45/63] lr: 1.9876e-03 eta: 6:12:40 time: 0.8029 data_time: 0.0298 memory: 16201 loss_prob: 0.4248 loss_thr: 0.2961 loss_db: 0.0726 loss: 0.7935 2022/08/30 19:11:17 - mmengine - INFO - Epoch(train) [904][50/63] lr: 1.9876e-03 eta: 6:12:27 time: 0.8235 data_time: 0.0315 memory: 16201 loss_prob: 0.3967 loss_thr: 0.2896 loss_db: 0.0712 loss: 0.7575 2022/08/30 19:11:22 - mmengine - INFO - Epoch(train) [904][55/63] lr: 1.9876e-03 eta: 6:12:27 time: 0.8471 data_time: 0.0217 memory: 16201 loss_prob: 0.4292 loss_thr: 0.3017 loss_db: 0.0764 loss: 0.8073 2022/08/30 19:11:27 - mmengine - INFO - Epoch(train) [904][60/63] lr: 1.9876e-03 eta: 6:12:14 time: 0.9648 data_time: 0.0356 memory: 16201 loss_prob: 0.4199 loss_thr: 0.2980 loss_db: 0.0749 loss: 0.7929 2022/08/30 19:11:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:11:37 - mmengine - INFO - Epoch(train) [905][5/63] lr: 1.9816e-03 eta: 6:12:14 time: 1.2638 data_time: 0.2354 memory: 16201 loss_prob: 0.3707 loss_thr: 0.2671 loss_db: 0.0648 loss: 0.7026 2022/08/30 19:11:42 - mmengine - INFO - Epoch(train) [905][10/63] lr: 1.9816e-03 eta: 6:11:57 time: 1.1915 data_time: 0.2502 memory: 16201 loss_prob: 0.3839 loss_thr: 0.2751 loss_db: 0.0679 loss: 0.7268 2022/08/30 19:11:46 - mmengine - INFO - Epoch(train) [905][15/63] lr: 1.9816e-03 eta: 6:11:57 time: 0.8559 data_time: 0.0412 memory: 16201 loss_prob: 0.3834 loss_thr: 0.2697 loss_db: 0.0683 loss: 0.7215 2022/08/30 19:11:50 - mmengine - INFO - Epoch(train) [905][20/63] lr: 1.9816e-03 eta: 6:11:44 time: 0.8202 data_time: 0.0263 memory: 16201 loss_prob: 0.4405 loss_thr: 0.2967 loss_db: 0.0761 loss: 0.8132 2022/08/30 19:11:55 - mmengine - INFO - Epoch(train) [905][25/63] lr: 1.9816e-03 eta: 6:11:44 time: 0.9303 data_time: 0.0326 memory: 16201 loss_prob: 0.4364 loss_thr: 0.3018 loss_db: 0.0761 loss: 0.8143 2022/08/30 19:12:01 - mmengine - INFO - Epoch(train) [905][30/63] lr: 1.9816e-03 eta: 6:11:32 time: 1.1199 data_time: 0.0276 memory: 16201 loss_prob: 0.4235 loss_thr: 0.2892 loss_db: 0.0715 loss: 0.7842 2022/08/30 19:12:06 - mmengine - INFO - Epoch(train) [905][35/63] lr: 1.9816e-03 eta: 6:11:32 time: 1.0667 data_time: 0.0352 memory: 16201 loss_prob: 0.4019 loss_thr: 0.2695 loss_db: 0.0680 loss: 0.7393 2022/08/30 19:12:12 - mmengine - INFO - Epoch(train) [905][40/63] lr: 1.9816e-03 eta: 6:11:19 time: 1.0423 data_time: 0.0371 memory: 16201 loss_prob: 0.3776 loss_thr: 0.2694 loss_db: 0.0677 loss: 0.7147 2022/08/30 19:12:16 - mmengine - INFO - Epoch(train) [905][45/63] lr: 1.9816e-03 eta: 6:11:19 time: 0.9975 data_time: 0.0280 memory: 16201 loss_prob: 0.4125 loss_thr: 0.2926 loss_db: 0.0744 loss: 0.7795 2022/08/30 19:12:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:12:20 - mmengine - INFO - Epoch(train) [905][50/63] lr: 1.9816e-03 eta: 6:11:06 time: 0.8245 data_time: 0.0336 memory: 16201 loss_prob: 0.4227 loss_thr: 0.2945 loss_db: 0.0762 loss: 0.7934 2022/08/30 19:12:24 - mmengine - INFO - Epoch(train) [905][55/63] lr: 1.9816e-03 eta: 6:11:06 time: 0.8068 data_time: 0.0215 memory: 16201 loss_prob: 0.4460 loss_thr: 0.3096 loss_db: 0.0791 loss: 0.8347 2022/08/30 19:12:29 - mmengine - INFO - Epoch(train) [905][60/63] lr: 1.9816e-03 eta: 6:10:53 time: 0.9384 data_time: 0.0307 memory: 16201 loss_prob: 0.4307 loss_thr: 0.2952 loss_db: 0.0749 loss: 0.8008 2022/08/30 19:12:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:12:38 - mmengine - INFO - Epoch(train) [906][5/63] lr: 1.9756e-03 eta: 6:10:53 time: 1.1536 data_time: 0.1875 memory: 16201 loss_prob: 0.4371 loss_thr: 0.3024 loss_db: 0.0755 loss: 0.8150 2022/08/30 19:12:43 - mmengine - INFO - Epoch(train) [906][10/63] lr: 1.9756e-03 eta: 6:10:36 time: 0.9785 data_time: 0.2023 memory: 16201 loss_prob: 0.4235 loss_thr: 0.3095 loss_db: 0.0752 loss: 0.8082 2022/08/30 19:12:47 - mmengine - INFO - Epoch(train) [906][15/63] lr: 1.9756e-03 eta: 6:10:36 time: 0.8750 data_time: 0.0271 memory: 16201 loss_prob: 0.3705 loss_thr: 0.2646 loss_db: 0.0671 loss: 0.7023 2022/08/30 19:12:53 - mmengine - INFO - Epoch(train) [906][20/63] lr: 1.9756e-03 eta: 6:10:23 time: 1.0249 data_time: 0.0219 memory: 16201 loss_prob: 0.3452 loss_thr: 0.2451 loss_db: 0.0610 loss: 0.6512 2022/08/30 19:12:58 - mmengine - INFO - Epoch(train) [906][25/63] lr: 1.9756e-03 eta: 6:10:23 time: 1.0798 data_time: 0.0366 memory: 16201 loss_prob: 0.3428 loss_thr: 0.2614 loss_db: 0.0597 loss: 0.6640 2022/08/30 19:13:03 - mmengine - INFO - Epoch(train) [906][30/63] lr: 1.9756e-03 eta: 6:10:11 time: 0.9811 data_time: 0.0387 memory: 16201 loss_prob: 0.3479 loss_thr: 0.2599 loss_db: 0.0628 loss: 0.6707 2022/08/30 19:13:07 - mmengine - INFO - Epoch(train) [906][35/63] lr: 1.9756e-03 eta: 6:10:11 time: 0.8594 data_time: 0.0258 memory: 16201 loss_prob: 0.3939 loss_thr: 0.2844 loss_db: 0.0708 loss: 0.7491 2022/08/30 19:13:11 - mmengine - INFO - Epoch(train) [906][40/63] lr: 1.9756e-03 eta: 6:09:57 time: 0.8183 data_time: 0.0247 memory: 16201 loss_prob: 0.3948 loss_thr: 0.2854 loss_db: 0.0700 loss: 0.7502 2022/08/30 19:13:16 - mmengine - INFO - Epoch(train) [906][45/63] lr: 1.9756e-03 eta: 6:09:57 time: 0.9091 data_time: 0.0352 memory: 16201 loss_prob: 0.3604 loss_thr: 0.2533 loss_db: 0.0632 loss: 0.6769 2022/08/30 19:13:21 - mmengine - INFO - Epoch(train) [906][50/63] lr: 1.9756e-03 eta: 6:09:45 time: 1.0213 data_time: 0.0359 memory: 16201 loss_prob: 0.3616 loss_thr: 0.2555 loss_db: 0.0629 loss: 0.6800 2022/08/30 19:13:26 - mmengine - INFO - Epoch(train) [906][55/63] lr: 1.9756e-03 eta: 6:09:45 time: 1.0607 data_time: 0.0335 memory: 16201 loss_prob: 0.3810 loss_thr: 0.2709 loss_db: 0.0683 loss: 0.7202 2022/08/30 19:13:32 - mmengine - INFO - Epoch(train) [906][60/63] lr: 1.9756e-03 eta: 6:09:32 time: 1.0943 data_time: 0.0721 memory: 16201 loss_prob: 0.4212 loss_thr: 0.2986 loss_db: 0.0749 loss: 0.7947 2022/08/30 19:13:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:13:40 - mmengine - INFO - Epoch(train) [907][5/63] lr: 1.9695e-03 eta: 6:09:32 time: 1.0513 data_time: 0.2061 memory: 16201 loss_prob: 0.4031 loss_thr: 0.2720 loss_db: 0.0713 loss: 0.7464 2022/08/30 19:13:44 - mmengine - INFO - Epoch(train) [907][10/63] lr: 1.9695e-03 eta: 6:09:15 time: 0.9882 data_time: 0.2053 memory: 16201 loss_prob: 0.3980 loss_thr: 0.2690 loss_db: 0.0694 loss: 0.7364 2022/08/30 19:13:49 - mmengine - INFO - Epoch(train) [907][15/63] lr: 1.9695e-03 eta: 6:09:15 time: 0.8636 data_time: 0.0311 memory: 16201 loss_prob: 0.4349 loss_thr: 0.2934 loss_db: 0.0772 loss: 0.8055 2022/08/30 19:13:54 - mmengine - INFO - Epoch(train) [907][20/63] lr: 1.9695e-03 eta: 6:09:02 time: 0.9766 data_time: 0.0384 memory: 16201 loss_prob: 0.4407 loss_thr: 0.2992 loss_db: 0.0771 loss: 0.8170 2022/08/30 19:13:59 - mmengine - INFO - Epoch(train) [907][25/63] lr: 1.9695e-03 eta: 6:09:02 time: 0.9957 data_time: 0.0301 memory: 16201 loss_prob: 0.3795 loss_thr: 0.2802 loss_db: 0.0672 loss: 0.7269 2022/08/30 19:14:05 - mmengine - INFO - Epoch(train) [907][30/63] lr: 1.9695e-03 eta: 6:08:50 time: 1.0838 data_time: 0.0347 memory: 16201 loss_prob: 0.3596 loss_thr: 0.2698 loss_db: 0.0642 loss: 0.6936 2022/08/30 19:14:10 - mmengine - INFO - Epoch(train) [907][35/63] lr: 1.9695e-03 eta: 6:08:50 time: 1.0954 data_time: 0.0385 memory: 16201 loss_prob: 0.3812 loss_thr: 0.2621 loss_db: 0.0657 loss: 0.7090 2022/08/30 19:14:14 - mmengine - INFO - Epoch(train) [907][40/63] lr: 1.9695e-03 eta: 6:08:37 time: 0.8990 data_time: 0.0340 memory: 16201 loss_prob: 0.4221 loss_thr: 0.2521 loss_db: 0.0793 loss: 0.7535 2022/08/30 19:14:18 - mmengine - INFO - Epoch(train) [907][45/63] lr: 1.9695e-03 eta: 6:08:37 time: 0.8283 data_time: 0.0341 memory: 16201 loss_prob: 0.4180 loss_thr: 0.2562 loss_db: 0.0789 loss: 0.7531 2022/08/30 19:14:22 - mmengine - INFO - Epoch(train) [907][50/63] lr: 1.9695e-03 eta: 6:08:24 time: 0.8278 data_time: 0.0226 memory: 16201 loss_prob: 0.3917 loss_thr: 0.2742 loss_db: 0.0671 loss: 0.7329 2022/08/30 19:14:27 - mmengine - INFO - Epoch(train) [907][55/63] lr: 1.9695e-03 eta: 6:08:24 time: 0.8516 data_time: 0.0291 memory: 16201 loss_prob: 0.4109 loss_thr: 0.2786 loss_db: 0.0702 loss: 0.7596 2022/08/30 19:14:32 - mmengine - INFO - Epoch(train) [907][60/63] lr: 1.9695e-03 eta: 6:08:11 time: 1.0060 data_time: 0.0338 memory: 16201 loss_prob: 0.4813 loss_thr: 0.3024 loss_db: 0.0786 loss: 0.8623 2022/08/30 19:14:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:14:42 - mmengine - INFO - Epoch(train) [908][5/63] lr: 1.9635e-03 eta: 6:08:11 time: 1.2031 data_time: 0.2118 memory: 16201 loss_prob: 0.4631 loss_thr: 0.3255 loss_db: 0.0803 loss: 0.8688 2022/08/30 19:14:48 - mmengine - INFO - Epoch(train) [908][10/63] lr: 1.9635e-03 eta: 6:07:55 time: 1.3184 data_time: 0.2123 memory: 16201 loss_prob: 0.4031 loss_thr: 0.2845 loss_db: 0.0701 loss: 0.7577 2022/08/30 19:14:54 - mmengine - INFO - Epoch(train) [908][15/63] lr: 1.9635e-03 eta: 6:07:55 time: 1.1746 data_time: 0.0300 memory: 16201 loss_prob: 0.4498 loss_thr: 0.3158 loss_db: 0.0770 loss: 0.8426 2022/08/30 19:14:58 - mmengine - INFO - Epoch(train) [908][20/63] lr: 1.9635e-03 eta: 6:07:43 time: 1.0240 data_time: 0.0285 memory: 16201 loss_prob: 0.4463 loss_thr: 0.3140 loss_db: 0.0796 loss: 0.8399 2022/08/30 19:15:02 - mmengine - INFO - Epoch(train) [908][25/63] lr: 1.9635e-03 eta: 6:07:43 time: 0.8409 data_time: 0.0275 memory: 16201 loss_prob: 0.3791 loss_thr: 0.2742 loss_db: 0.0695 loss: 0.7228 2022/08/30 19:15:06 - mmengine - INFO - Epoch(train) [908][30/63] lr: 1.9635e-03 eta: 6:07:29 time: 0.7936 data_time: 0.0260 memory: 16201 loss_prob: 0.3727 loss_thr: 0.2731 loss_db: 0.0654 loss: 0.7111 2022/08/30 19:15:10 - mmengine - INFO - Epoch(train) [908][35/63] lr: 1.9635e-03 eta: 6:07:29 time: 0.7945 data_time: 0.0294 memory: 16201 loss_prob: 0.4491 loss_thr: 0.2789 loss_db: 0.0760 loss: 0.8040 2022/08/30 19:15:14 - mmengine - INFO - Epoch(train) [908][40/63] lr: 1.9635e-03 eta: 6:07:16 time: 0.7989 data_time: 0.0252 memory: 16201 loss_prob: 0.4711 loss_thr: 0.2821 loss_db: 0.0816 loss: 0.8348 2022/08/30 19:15:19 - mmengine - INFO - Epoch(train) [908][45/63] lr: 1.9635e-03 eta: 6:07:16 time: 0.9019 data_time: 0.0258 memory: 16201 loss_prob: 0.4463 loss_thr: 0.3003 loss_db: 0.0792 loss: 0.8259 2022/08/30 19:15:24 - mmengine - INFO - Epoch(train) [908][50/63] lr: 1.9635e-03 eta: 6:07:03 time: 0.9972 data_time: 0.0326 memory: 16201 loss_prob: 0.4579 loss_thr: 0.3068 loss_db: 0.0808 loss: 0.8455 2022/08/30 19:15:30 - mmengine - INFO - Epoch(train) [908][55/63] lr: 1.9635e-03 eta: 6:07:03 time: 1.0458 data_time: 0.0282 memory: 16201 loss_prob: 0.5592 loss_thr: 0.2991 loss_db: 0.0961 loss: 0.9544 2022/08/30 19:15:35 - mmengine - INFO - Epoch(train) [908][60/63] lr: 1.9635e-03 eta: 6:06:51 time: 1.1161 data_time: 0.0318 memory: 16201 loss_prob: 0.5194 loss_thr: 0.2883 loss_db: 0.0899 loss: 0.8976 2022/08/30 19:15:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:15:45 - mmengine - INFO - Epoch(train) [909][5/63] lr: 1.9574e-03 eta: 6:06:51 time: 1.2080 data_time: 0.1901 memory: 16201 loss_prob: 0.4500 loss_thr: 0.2912 loss_db: 0.0802 loss: 0.8214 2022/08/30 19:15:50 - mmengine - INFO - Epoch(train) [909][10/63] lr: 1.9574e-03 eta: 6:06:35 time: 1.2155 data_time: 0.2015 memory: 16201 loss_prob: 0.5035 loss_thr: 0.3055 loss_db: 0.0852 loss: 0.8943 2022/08/30 19:15:55 - mmengine - INFO - Epoch(train) [909][15/63] lr: 1.9574e-03 eta: 6:06:35 time: 0.9236 data_time: 0.0324 memory: 16201 loss_prob: 0.6551 loss_thr: 0.3288 loss_db: 0.1000 loss: 1.0839 2022/08/30 19:15:59 - mmengine - INFO - Epoch(train) [909][20/63] lr: 1.9574e-03 eta: 6:06:21 time: 0.8391 data_time: 0.0247 memory: 16201 loss_prob: 0.5948 loss_thr: 0.3230 loss_db: 0.0948 loss: 1.0126 2022/08/30 19:16:03 - mmengine - INFO - Epoch(train) [909][25/63] lr: 1.9574e-03 eta: 6:06:21 time: 0.7906 data_time: 0.0294 memory: 16201 loss_prob: 0.5065 loss_thr: 0.3173 loss_db: 0.0947 loss: 0.9184 2022/08/30 19:16:08 - mmengine - INFO - Epoch(train) [909][30/63] lr: 1.9574e-03 eta: 6:06:09 time: 0.8981 data_time: 0.0313 memory: 16201 loss_prob: 0.5282 loss_thr: 0.3178 loss_db: 0.0933 loss: 0.9394 2022/08/30 19:16:13 - mmengine - INFO - Epoch(train) [909][35/63] lr: 1.9574e-03 eta: 6:06:09 time: 1.0415 data_time: 0.0294 memory: 16201 loss_prob: 0.4853 loss_thr: 0.3155 loss_db: 0.0818 loss: 0.8826 2022/08/30 19:16:19 - mmengine - INFO - Epoch(train) [909][40/63] lr: 1.9574e-03 eta: 6:05:56 time: 1.1012 data_time: 0.0298 memory: 16201 loss_prob: 0.4596 loss_thr: 0.3154 loss_db: 0.0809 loss: 0.8559 2022/08/30 19:16:24 - mmengine - INFO - Epoch(train) [909][45/63] lr: 1.9574e-03 eta: 6:05:56 time: 1.0681 data_time: 0.0296 memory: 16201 loss_prob: 0.4848 loss_thr: 0.3310 loss_db: 0.0859 loss: 0.9016 2022/08/30 19:16:29 - mmengine - INFO - Epoch(train) [909][50/63] lr: 1.9574e-03 eta: 6:05:44 time: 0.9982 data_time: 0.0368 memory: 16201 loss_prob: 0.4879 loss_thr: 0.3341 loss_db: 0.0861 loss: 0.9081 2022/08/30 19:16:33 - mmengine - INFO - Epoch(train) [909][55/63] lr: 1.9574e-03 eta: 6:05:44 time: 0.9318 data_time: 0.0320 memory: 16201 loss_prob: 0.4350 loss_thr: 0.3075 loss_db: 0.0766 loss: 0.8191 2022/08/30 19:16:37 - mmengine - INFO - Epoch(train) [909][60/63] lr: 1.9574e-03 eta: 6:05:31 time: 0.8631 data_time: 0.0224 memory: 16201 loss_prob: 0.4892 loss_thr: 0.3272 loss_db: 0.0834 loss: 0.8998 2022/08/30 19:16:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:16:45 - mmengine - INFO - Epoch(train) [910][5/63] lr: 1.9513e-03 eta: 6:05:31 time: 0.9532 data_time: 0.1590 memory: 16201 loss_prob: 0.4650 loss_thr: 0.3420 loss_db: 0.0806 loss: 0.8876 2022/08/30 19:16:51 - mmengine - INFO - Epoch(train) [910][10/63] lr: 1.9513e-03 eta: 6:05:14 time: 1.1507 data_time: 0.1634 memory: 16201 loss_prob: 0.4258 loss_thr: 0.3119 loss_db: 0.0744 loss: 0.8120 2022/08/30 19:16:57 - mmengine - INFO - Epoch(train) [910][15/63] lr: 1.9513e-03 eta: 6:05:14 time: 1.1400 data_time: 0.0345 memory: 16201 loss_prob: 0.4878 loss_thr: 0.3038 loss_db: 0.0861 loss: 0.8776 2022/08/30 19:17:01 - mmengine - INFO - Epoch(train) [910][20/63] lr: 1.9513e-03 eta: 6:05:01 time: 1.0631 data_time: 0.0371 memory: 16201 loss_prob: 0.5193 loss_thr: 0.3190 loss_db: 0.0890 loss: 0.9273 2022/08/30 19:17:05 - mmengine - INFO - Epoch(train) [910][25/63] lr: 1.9513e-03 eta: 6:05:01 time: 0.8844 data_time: 0.0352 memory: 16201 loss_prob: 0.4422 loss_thr: 0.3103 loss_db: 0.0757 loss: 0.8283 2022/08/30 19:17:09 - mmengine - INFO - Epoch(train) [910][30/63] lr: 1.9513e-03 eta: 6:04:48 time: 0.7982 data_time: 0.0268 memory: 16201 loss_prob: 0.4111 loss_thr: 0.2898 loss_db: 0.0735 loss: 0.7744 2022/08/30 19:17:14 - mmengine - INFO - Epoch(train) [910][35/63] lr: 1.9513e-03 eta: 6:04:48 time: 0.8756 data_time: 0.0288 memory: 16201 loss_prob: 0.3897 loss_thr: 0.2776 loss_db: 0.0717 loss: 0.7390 2022/08/30 19:17:20 - mmengine - INFO - Epoch(train) [910][40/63] lr: 1.9513e-03 eta: 6:04:36 time: 1.0097 data_time: 0.0321 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2832 loss_db: 0.0695 loss: 0.7372 2022/08/30 19:17:25 - mmengine - INFO - Epoch(train) [910][45/63] lr: 1.9513e-03 eta: 6:04:36 time: 1.1119 data_time: 0.0365 memory: 16201 loss_prob: 0.3667 loss_thr: 0.2696 loss_db: 0.0641 loss: 0.7005 2022/08/30 19:17:30 - mmengine - INFO - Epoch(train) [910][50/63] lr: 1.9513e-03 eta: 6:04:23 time: 1.0445 data_time: 0.0385 memory: 16201 loss_prob: 0.3438 loss_thr: 0.2584 loss_db: 0.0608 loss: 0.6630 2022/08/30 19:17:35 - mmengine - INFO - Epoch(train) [910][55/63] lr: 1.9513e-03 eta: 6:04:23 time: 0.9210 data_time: 0.0251 memory: 16201 loss_prob: 0.4081 loss_thr: 0.2912 loss_db: 0.0716 loss: 0.7708 2022/08/30 19:17:39 - mmengine - INFO - Epoch(train) [910][60/63] lr: 1.9513e-03 eta: 6:04:10 time: 0.8779 data_time: 0.0359 memory: 16201 loss_prob: 0.4383 loss_thr: 0.2946 loss_db: 0.0763 loss: 0.8091 2022/08/30 19:17:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:17:50 - mmengine - INFO - Epoch(train) [911][5/63] lr: 1.9453e-03 eta: 6:04:10 time: 1.2765 data_time: 0.2368 memory: 16201 loss_prob: 0.3788 loss_thr: 0.2783 loss_db: 0.0688 loss: 0.7259 2022/08/30 19:17:55 - mmengine - INFO - Epoch(train) [911][10/63] lr: 1.9453e-03 eta: 6:03:54 time: 1.2222 data_time: 0.2532 memory: 16201 loss_prob: 0.3637 loss_thr: 0.2766 loss_db: 0.0663 loss: 0.7066 2022/08/30 19:17:59 - mmengine - INFO - Epoch(train) [911][15/63] lr: 1.9453e-03 eta: 6:03:54 time: 0.9230 data_time: 0.0478 memory: 16201 loss_prob: 0.3695 loss_thr: 0.2696 loss_db: 0.0651 loss: 0.7042 2022/08/30 19:18:03 - mmengine - INFO - Epoch(train) [911][20/63] lr: 1.9453e-03 eta: 6:03:40 time: 0.8165 data_time: 0.0319 memory: 16201 loss_prob: 0.3963 loss_thr: 0.2783 loss_db: 0.0695 loss: 0.7441 2022/08/30 19:18:08 - mmengine - INFO - Epoch(train) [911][25/63] lr: 1.9453e-03 eta: 6:03:40 time: 0.8856 data_time: 0.0388 memory: 16201 loss_prob: 0.4395 loss_thr: 0.3021 loss_db: 0.0784 loss: 0.8201 2022/08/30 19:18:14 - mmengine - INFO - Epoch(train) [911][30/63] lr: 1.9453e-03 eta: 6:03:28 time: 1.1254 data_time: 0.0338 memory: 16201 loss_prob: 0.4595 loss_thr: 0.3047 loss_db: 0.0815 loss: 0.8456 2022/08/30 19:18:20 - mmengine - INFO - Epoch(train) [911][35/63] lr: 1.9453e-03 eta: 6:03:28 time: 1.1736 data_time: 0.0342 memory: 16201 loss_prob: 0.4211 loss_thr: 0.2808 loss_db: 0.0720 loss: 0.7739 2022/08/30 19:18:24 - mmengine - INFO - Epoch(train) [911][40/63] lr: 1.9453e-03 eta: 6:03:16 time: 0.9381 data_time: 0.0317 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2731 loss_db: 0.0680 loss: 0.7376 2022/08/30 19:18:28 - mmengine - INFO - Epoch(train) [911][45/63] lr: 1.9453e-03 eta: 6:03:16 time: 0.8023 data_time: 0.0193 memory: 16201 loss_prob: 0.4182 loss_thr: 0.2847 loss_db: 0.0742 loss: 0.7772 2022/08/30 19:18:32 - mmengine - INFO - Epoch(train) [911][50/63] lr: 1.9453e-03 eta: 6:03:02 time: 0.8257 data_time: 0.0339 memory: 16201 loss_prob: 0.4127 loss_thr: 0.2801 loss_db: 0.0740 loss: 0.7668 2022/08/30 19:18:37 - mmengine - INFO - Epoch(train) [911][55/63] lr: 1.9453e-03 eta: 6:03:02 time: 0.9570 data_time: 0.0265 memory: 16201 loss_prob: 0.4045 loss_thr: 0.2729 loss_db: 0.0726 loss: 0.7500 2022/08/30 19:18:43 - mmengine - INFO - Epoch(train) [911][60/63] lr: 1.9453e-03 eta: 6:02:50 time: 1.1326 data_time: 0.0312 memory: 16201 loss_prob: 0.3989 loss_thr: 0.2792 loss_db: 0.0719 loss: 0.7500 2022/08/30 19:18:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:18:51 - mmengine - INFO - Epoch(train) [912][5/63] lr: 1.9392e-03 eta: 6:02:50 time: 0.9392 data_time: 0.1762 memory: 16201 loss_prob: 0.4631 loss_thr: 0.2921 loss_db: 0.0815 loss: 0.8368 2022/08/30 19:18:55 - mmengine - INFO - Epoch(train) [912][10/63] lr: 1.9392e-03 eta: 6:02:33 time: 0.9467 data_time: 0.1808 memory: 16201 loss_prob: 0.4329 loss_thr: 0.2797 loss_db: 0.0761 loss: 0.7887 2022/08/30 19:18:59 - mmengine - INFO - Epoch(train) [912][15/63] lr: 1.9392e-03 eta: 6:02:33 time: 0.8226 data_time: 0.0241 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2796 loss_db: 0.0709 loss: 0.7533 2022/08/30 19:19:03 - mmengine - INFO - Epoch(train) [912][20/63] lr: 1.9392e-03 eta: 6:02:20 time: 0.8557 data_time: 0.0246 memory: 16201 loss_prob: 0.3872 loss_thr: 0.2811 loss_db: 0.0683 loss: 0.7366 2022/08/30 19:19:07 - mmengine - INFO - Epoch(train) [912][25/63] lr: 1.9392e-03 eta: 6:02:20 time: 0.8410 data_time: 0.0313 memory: 16201 loss_prob: 0.4094 loss_thr: 0.2910 loss_db: 0.0710 loss: 0.7714 2022/08/30 19:19:11 - mmengine - INFO - Epoch(train) [912][30/63] lr: 1.9392e-03 eta: 6:02:07 time: 0.8176 data_time: 0.0263 memory: 16201 loss_prob: 0.4175 loss_thr: 0.2947 loss_db: 0.0733 loss: 0.7855 2022/08/30 19:19:15 - mmengine - INFO - Epoch(train) [912][35/63] lr: 1.9392e-03 eta: 6:02:07 time: 0.7883 data_time: 0.0224 memory: 16201 loss_prob: 0.4048 loss_thr: 0.2867 loss_db: 0.0725 loss: 0.7639 2022/08/30 19:19:19 - mmengine - INFO - Epoch(train) [912][40/63] lr: 1.9392e-03 eta: 6:01:53 time: 0.7845 data_time: 0.0189 memory: 16201 loss_prob: 0.4480 loss_thr: 0.3036 loss_db: 0.0799 loss: 0.8315 2022/08/30 19:19:24 - mmengine - INFO - Epoch(train) [912][45/63] lr: 1.9392e-03 eta: 6:01:53 time: 0.8849 data_time: 0.0246 memory: 16201 loss_prob: 0.4381 loss_thr: 0.2960 loss_db: 0.0765 loss: 0.8106 2022/08/30 19:19:28 - mmengine - INFO - Epoch(train) [912][50/63] lr: 1.9392e-03 eta: 6:01:40 time: 0.8892 data_time: 0.0365 memory: 16201 loss_prob: 0.3799 loss_thr: 0.2753 loss_db: 0.0662 loss: 0.7214 2022/08/30 19:19:32 - mmengine - INFO - Epoch(train) [912][55/63] lr: 1.9392e-03 eta: 6:01:40 time: 0.7892 data_time: 0.0242 memory: 16201 loss_prob: 0.4357 loss_thr: 0.2918 loss_db: 0.0789 loss: 0.8063 2022/08/30 19:19:36 - mmengine - INFO - Epoch(train) [912][60/63] lr: 1.9392e-03 eta: 6:01:27 time: 0.7859 data_time: 0.0239 memory: 16201 loss_prob: 0.4412 loss_thr: 0.2814 loss_db: 0.0784 loss: 0.8009 2022/08/30 19:19:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:19:44 - mmengine - INFO - Epoch(train) [913][5/63] lr: 1.9332e-03 eta: 6:01:27 time: 0.9869 data_time: 0.2065 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2819 loss_db: 0.0700 loss: 0.7505 2022/08/30 19:19:49 - mmengine - INFO - Epoch(train) [913][10/63] lr: 1.9332e-03 eta: 6:01:10 time: 1.1151 data_time: 0.2237 memory: 16201 loss_prob: 0.4240 loss_thr: 0.2932 loss_db: 0.0747 loss: 0.7920 2022/08/30 19:19:53 - mmengine - INFO - Epoch(train) [913][15/63] lr: 1.9332e-03 eta: 6:01:10 time: 0.8921 data_time: 0.0302 memory: 16201 loss_prob: 0.4100 loss_thr: 0.2822 loss_db: 0.0728 loss: 0.7650 2022/08/30 19:19:58 - mmengine - INFO - Epoch(train) [913][20/63] lr: 1.9332e-03 eta: 6:00:57 time: 0.8459 data_time: 0.0217 memory: 16201 loss_prob: 0.3889 loss_thr: 0.2761 loss_db: 0.0682 loss: 0.7332 2022/08/30 19:20:02 - mmengine - INFO - Epoch(train) [913][25/63] lr: 1.9332e-03 eta: 6:00:57 time: 0.8475 data_time: 0.0336 memory: 16201 loss_prob: 0.3773 loss_thr: 0.2760 loss_db: 0.0662 loss: 0.7196 2022/08/30 19:20:06 - mmengine - INFO - Epoch(train) [913][30/63] lr: 1.9332e-03 eta: 6:00:44 time: 0.8243 data_time: 0.0287 memory: 16201 loss_prob: 0.3679 loss_thr: 0.2720 loss_db: 0.0659 loss: 0.7058 2022/08/30 19:20:10 - mmengine - INFO - Epoch(train) [913][35/63] lr: 1.9332e-03 eta: 6:00:44 time: 0.7857 data_time: 0.0197 memory: 16201 loss_prob: 0.3628 loss_thr: 0.2611 loss_db: 0.0630 loss: 0.6870 2022/08/30 19:20:14 - mmengine - INFO - Epoch(train) [913][40/63] lr: 1.9332e-03 eta: 6:00:31 time: 0.7890 data_time: 0.0241 memory: 16201 loss_prob: 0.4063 loss_thr: 0.2847 loss_db: 0.0704 loss: 0.7613 2022/08/30 19:20:18 - mmengine - INFO - Epoch(train) [913][45/63] lr: 1.9332e-03 eta: 6:00:31 time: 0.7973 data_time: 0.0217 memory: 16201 loss_prob: 0.4654 loss_thr: 0.3165 loss_db: 0.0815 loss: 0.8634 2022/08/30 19:20:23 - mmengine - INFO - Epoch(train) [913][50/63] lr: 1.9332e-03 eta: 6:00:18 time: 0.9054 data_time: 0.0254 memory: 16201 loss_prob: 0.4298 loss_thr: 0.2975 loss_db: 0.0752 loss: 0.8025 2022/08/30 19:20:27 - mmengine - INFO - Epoch(train) [913][55/63] lr: 1.9332e-03 eta: 6:00:18 time: 0.9494 data_time: 0.0380 memory: 16201 loss_prob: 0.3848 loss_thr: 0.2735 loss_db: 0.0682 loss: 0.7264 2022/08/30 19:20:31 - mmengine - INFO - Epoch(train) [913][60/63] lr: 1.9332e-03 eta: 6:00:05 time: 0.8392 data_time: 0.0333 memory: 16201 loss_prob: 0.3816 loss_thr: 0.2693 loss_db: 0.0694 loss: 0.7202 2022/08/30 19:20:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:20:39 - mmengine - INFO - Epoch(train) [914][5/63] lr: 1.9271e-03 eta: 6:00:05 time: 0.9684 data_time: 0.1785 memory: 16201 loss_prob: 0.4073 loss_thr: 0.2807 loss_db: 0.0723 loss: 0.7603 2022/08/30 19:20:43 - mmengine - INFO - Epoch(train) [914][10/63] lr: 1.9271e-03 eta: 5:59:48 time: 1.0269 data_time: 0.1883 memory: 16201 loss_prob: 0.4281 loss_thr: 0.2853 loss_db: 0.0758 loss: 0.7892 2022/08/30 19:20:47 - mmengine - INFO - Epoch(train) [914][15/63] lr: 1.9271e-03 eta: 5:59:48 time: 0.8165 data_time: 0.0229 memory: 16201 loss_prob: 0.3896 loss_thr: 0.2782 loss_db: 0.0687 loss: 0.7365 2022/08/30 19:20:52 - mmengine - INFO - Epoch(train) [914][20/63] lr: 1.9271e-03 eta: 5:59:35 time: 0.7986 data_time: 0.0185 memory: 16201 loss_prob: 0.3724 loss_thr: 0.2713 loss_db: 0.0637 loss: 0.7074 2022/08/30 19:20:56 - mmengine - INFO - Epoch(train) [914][25/63] lr: 1.9271e-03 eta: 5:59:35 time: 0.8455 data_time: 0.0381 memory: 16201 loss_prob: 0.3811 loss_thr: 0.2766 loss_db: 0.0669 loss: 0.7246 2022/08/30 19:21:00 - mmengine - INFO - Epoch(train) [914][30/63] lr: 1.9271e-03 eta: 5:59:22 time: 0.8820 data_time: 0.0318 memory: 16201 loss_prob: 0.4017 loss_thr: 0.2923 loss_db: 0.0731 loss: 0.7671 2022/08/30 19:21:04 - mmengine - INFO - Epoch(train) [914][35/63] lr: 1.9271e-03 eta: 5:59:22 time: 0.8517 data_time: 0.0208 memory: 16201 loss_prob: 0.3850 loss_thr: 0.2726 loss_db: 0.0692 loss: 0.7268 2022/08/30 19:21:08 - mmengine - INFO - Epoch(train) [914][40/63] lr: 1.9271e-03 eta: 5:59:08 time: 0.8112 data_time: 0.0272 memory: 16201 loss_prob: 0.3803 loss_thr: 0.2505 loss_db: 0.0640 loss: 0.6948 2022/08/30 19:21:13 - mmengine - INFO - Epoch(train) [914][45/63] lr: 1.9271e-03 eta: 5:59:08 time: 0.8304 data_time: 0.0286 memory: 16201 loss_prob: 0.3963 loss_thr: 0.2554 loss_db: 0.0668 loss: 0.7184 2022/08/30 19:21:17 - mmengine - INFO - Epoch(train) [914][50/63] lr: 1.9271e-03 eta: 5:58:55 time: 0.8326 data_time: 0.0296 memory: 16201 loss_prob: 0.3764 loss_thr: 0.2620 loss_db: 0.0670 loss: 0.7053 2022/08/30 19:21:21 - mmengine - INFO - Epoch(train) [914][55/63] lr: 1.9271e-03 eta: 5:58:55 time: 0.8036 data_time: 0.0240 memory: 16201 loss_prob: 0.4001 loss_thr: 0.2819 loss_db: 0.0713 loss: 0.7533 2022/08/30 19:21:25 - mmengine - INFO - Epoch(train) [914][60/63] lr: 1.9271e-03 eta: 5:58:42 time: 0.8245 data_time: 0.0233 memory: 16201 loss_prob: 0.3940 loss_thr: 0.2764 loss_db: 0.0690 loss: 0.7394 2022/08/30 19:21:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:21:33 - mmengine - INFO - Epoch(train) [915][5/63] lr: 1.9210e-03 eta: 5:58:42 time: 0.9864 data_time: 0.1957 memory: 16201 loss_prob: 0.3689 loss_thr: 0.2669 loss_db: 0.0654 loss: 0.7013 2022/08/30 19:21:38 - mmengine - INFO - Epoch(train) [915][10/63] lr: 1.9210e-03 eta: 5:58:25 time: 1.0898 data_time: 0.2128 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2754 loss_db: 0.0688 loss: 0.7210 2022/08/30 19:21:42 - mmengine - INFO - Epoch(train) [915][15/63] lr: 1.9210e-03 eta: 5:58:25 time: 0.8858 data_time: 0.0419 memory: 16201 loss_prob: 0.3925 loss_thr: 0.2760 loss_db: 0.0703 loss: 0.7387 2022/08/30 19:21:46 - mmengine - INFO - Epoch(train) [915][20/63] lr: 1.9210e-03 eta: 5:58:12 time: 0.8138 data_time: 0.0251 memory: 16201 loss_prob: 0.3941 loss_thr: 0.2829 loss_db: 0.0698 loss: 0.7468 2022/08/30 19:21:50 - mmengine - INFO - Epoch(train) [915][25/63] lr: 1.9210e-03 eta: 5:58:12 time: 0.8068 data_time: 0.0291 memory: 16201 loss_prob: 0.3807 loss_thr: 0.2728 loss_db: 0.0676 loss: 0.7211 2022/08/30 19:21:54 - mmengine - INFO - Epoch(train) [915][30/63] lr: 1.9210e-03 eta: 5:57:59 time: 0.8011 data_time: 0.0228 memory: 16201 loss_prob: 0.3684 loss_thr: 0.2628 loss_db: 0.0651 loss: 0.6964 2022/08/30 19:21:58 - mmengine - INFO - Epoch(train) [915][35/63] lr: 1.9210e-03 eta: 5:57:59 time: 0.8316 data_time: 0.0232 memory: 16201 loss_prob: 0.3892 loss_thr: 0.2747 loss_db: 0.0691 loss: 0.7330 2022/08/30 19:22:03 - mmengine - INFO - Epoch(train) [915][40/63] lr: 1.9210e-03 eta: 5:57:46 time: 0.9218 data_time: 0.0309 memory: 16201 loss_prob: 0.3865 loss_thr: 0.2686 loss_db: 0.0695 loss: 0.7247 2022/08/30 19:22:07 - mmengine - INFO - Epoch(train) [915][45/63] lr: 1.9210e-03 eta: 5:57:46 time: 0.8974 data_time: 0.0261 memory: 16201 loss_prob: 0.3615 loss_thr: 0.2550 loss_db: 0.0647 loss: 0.6812 2022/08/30 19:22:12 - mmengine - INFO - Epoch(train) [915][50/63] lr: 1.9210e-03 eta: 5:57:33 time: 0.8446 data_time: 0.0300 memory: 16201 loss_prob: 0.3757 loss_thr: 0.2639 loss_db: 0.0660 loss: 0.7056 2022/08/30 19:22:16 - mmengine - INFO - Epoch(train) [915][55/63] lr: 1.9210e-03 eta: 5:57:33 time: 0.8483 data_time: 0.0317 memory: 16201 loss_prob: 0.3755 loss_thr: 0.2627 loss_db: 0.0654 loss: 0.7036 2022/08/30 19:22:20 - mmengine - INFO - Epoch(train) [915][60/63] lr: 1.9210e-03 eta: 5:57:20 time: 0.8153 data_time: 0.0260 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2549 loss_db: 0.0658 loss: 0.6967 2022/08/30 19:22:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:22:28 - mmengine - INFO - Epoch(train) [916][5/63] lr: 1.9150e-03 eta: 5:57:20 time: 0.9928 data_time: 0.1879 memory: 16201 loss_prob: 0.3472 loss_thr: 0.2600 loss_db: 0.0623 loss: 0.6695 2022/08/30 19:22:32 - mmengine - INFO - Epoch(train) [916][10/63] lr: 1.9150e-03 eta: 5:57:03 time: 1.0228 data_time: 0.1947 memory: 16201 loss_prob: 0.3784 loss_thr: 0.2905 loss_db: 0.0662 loss: 0.7351 2022/08/30 19:22:36 - mmengine - INFO - Epoch(train) [916][15/63] lr: 1.9150e-03 eta: 5:57:03 time: 0.8183 data_time: 0.0253 memory: 16201 loss_prob: 0.4035 loss_thr: 0.2898 loss_db: 0.0689 loss: 0.7622 2022/08/30 19:22:41 - mmengine - INFO - Epoch(train) [916][20/63] lr: 1.9150e-03 eta: 5:56:50 time: 0.8142 data_time: 0.0225 memory: 16201 loss_prob: 0.3850 loss_thr: 0.2805 loss_db: 0.0659 loss: 0.7314 2022/08/30 19:22:45 - mmengine - INFO - Epoch(train) [916][25/63] lr: 1.9150e-03 eta: 5:56:50 time: 0.8602 data_time: 0.0302 memory: 16201 loss_prob: 0.4219 loss_thr: 0.2887 loss_db: 0.0741 loss: 0.7847 2022/08/30 19:22:49 - mmengine - INFO - Epoch(train) [916][30/63] lr: 1.9150e-03 eta: 5:56:37 time: 0.8543 data_time: 0.0292 memory: 16201 loss_prob: 0.4262 loss_thr: 0.2838 loss_db: 0.0753 loss: 0.7853 2022/08/30 19:22:54 - mmengine - INFO - Epoch(train) [916][35/63] lr: 1.9150e-03 eta: 5:56:37 time: 0.8473 data_time: 0.0250 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2682 loss_db: 0.0661 loss: 0.7102 2022/08/30 19:22:58 - mmengine - INFO - Epoch(train) [916][40/63] lr: 1.9150e-03 eta: 5:56:24 time: 0.8486 data_time: 0.0262 memory: 16201 loss_prob: 0.3739 loss_thr: 0.2586 loss_db: 0.0639 loss: 0.6964 2022/08/30 19:23:02 - mmengine - INFO - Epoch(train) [916][45/63] lr: 1.9150e-03 eta: 5:56:24 time: 0.8224 data_time: 0.0277 memory: 16201 loss_prob: 0.4043 loss_thr: 0.2652 loss_db: 0.0682 loss: 0.7376 2022/08/30 19:23:06 - mmengine - INFO - Epoch(train) [916][50/63] lr: 1.9150e-03 eta: 5:56:11 time: 0.8270 data_time: 0.0245 memory: 16201 loss_prob: 0.3879 loss_thr: 0.2584 loss_db: 0.0675 loss: 0.7139 2022/08/30 19:23:10 - mmengine - INFO - Epoch(train) [916][55/63] lr: 1.9150e-03 eta: 5:56:11 time: 0.8143 data_time: 0.0264 memory: 16201 loss_prob: 0.3949 loss_thr: 0.2723 loss_db: 0.0692 loss: 0.7365 2022/08/30 19:23:14 - mmengine - INFO - Epoch(train) [916][60/63] lr: 1.9150e-03 eta: 5:55:58 time: 0.8085 data_time: 0.0290 memory: 16201 loss_prob: 0.3954 loss_thr: 0.2785 loss_db: 0.0701 loss: 0.7440 2022/08/30 19:23:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:23:22 - mmengine - INFO - Epoch(train) [917][5/63] lr: 1.9089e-03 eta: 5:55:58 time: 0.9669 data_time: 0.1778 memory: 16201 loss_prob: 0.3958 loss_thr: 0.2786 loss_db: 0.0705 loss: 0.7449 2022/08/30 19:23:27 - mmengine - INFO - Epoch(train) [917][10/63] lr: 1.9089e-03 eta: 5:55:40 time: 1.0319 data_time: 0.1920 memory: 16201 loss_prob: 0.3974 loss_thr: 0.2962 loss_db: 0.0717 loss: 0.7654 2022/08/30 19:23:31 - mmengine - INFO - Epoch(train) [917][15/63] lr: 1.9089e-03 eta: 5:55:40 time: 0.8931 data_time: 0.0346 memory: 16201 loss_prob: 0.3919 loss_thr: 0.2809 loss_db: 0.0710 loss: 0.7438 2022/08/30 19:23:35 - mmengine - INFO - Epoch(train) [917][20/63] lr: 1.9089e-03 eta: 5:55:27 time: 0.8577 data_time: 0.0191 memory: 16201 loss_prob: 0.4074 loss_thr: 0.2740 loss_db: 0.0701 loss: 0.7515 2022/08/30 19:23:39 - mmengine - INFO - Epoch(train) [917][25/63] lr: 1.9089e-03 eta: 5:55:27 time: 0.8290 data_time: 0.0338 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2604 loss_db: 0.0647 loss: 0.7022 2022/08/30 19:23:43 - mmengine - INFO - Epoch(train) [917][30/63] lr: 1.9089e-03 eta: 5:55:14 time: 0.8142 data_time: 0.0245 memory: 16201 loss_prob: 0.3332 loss_thr: 0.2487 loss_db: 0.0599 loss: 0.6419 2022/08/30 19:23:47 - mmengine - INFO - Epoch(train) [917][35/63] lr: 1.9089e-03 eta: 5:55:14 time: 0.8196 data_time: 0.0179 memory: 16201 loss_prob: 0.3438 loss_thr: 0.2560 loss_db: 0.0612 loss: 0.6610 2022/08/30 19:23:51 - mmengine - INFO - Epoch(train) [917][40/63] lr: 1.9089e-03 eta: 5:55:01 time: 0.8146 data_time: 0.0248 memory: 16201 loss_prob: 0.3446 loss_thr: 0.2474 loss_db: 0.0609 loss: 0.6529 2022/08/30 19:23:56 - mmengine - INFO - Epoch(train) [917][45/63] lr: 1.9089e-03 eta: 5:55:01 time: 0.8028 data_time: 0.0232 memory: 16201 loss_prob: 0.3662 loss_thr: 0.2668 loss_db: 0.0659 loss: 0.6989 2022/08/30 19:24:00 - mmengine - INFO - Epoch(train) [917][50/63] lr: 1.9089e-03 eta: 5:54:48 time: 0.8375 data_time: 0.0312 memory: 16201 loss_prob: 0.3632 loss_thr: 0.2796 loss_db: 0.0653 loss: 0.7081 2022/08/30 19:24:04 - mmengine - INFO - Epoch(train) [917][55/63] lr: 1.9089e-03 eta: 5:54:48 time: 0.8779 data_time: 0.0291 memory: 16201 loss_prob: 0.3554 loss_thr: 0.2654 loss_db: 0.0629 loss: 0.6838 2022/08/30 19:24:08 - mmengine - INFO - Epoch(train) [917][60/63] lr: 1.9089e-03 eta: 5:54:35 time: 0.8375 data_time: 0.0237 memory: 16201 loss_prob: 0.3844 loss_thr: 0.2613 loss_db: 0.0677 loss: 0.7134 2022/08/30 19:24:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:24:16 - mmengine - INFO - Epoch(train) [918][5/63] lr: 1.9028e-03 eta: 5:54:35 time: 0.8905 data_time: 0.1558 memory: 16201 loss_prob: 0.3667 loss_thr: 0.2520 loss_db: 0.0647 loss: 0.6834 2022/08/30 19:24:20 - mmengine - INFO - Epoch(train) [918][10/63] lr: 1.9028e-03 eta: 5:54:18 time: 0.9601 data_time: 0.1687 memory: 16201 loss_prob: 0.3829 loss_thr: 0.2610 loss_db: 0.0666 loss: 0.7105 2022/08/30 19:24:24 - mmengine - INFO - Epoch(train) [918][15/63] lr: 1.9028e-03 eta: 5:54:18 time: 0.8890 data_time: 0.0244 memory: 16201 loss_prob: 0.3834 loss_thr: 0.2722 loss_db: 0.0667 loss: 0.7223 2022/08/30 19:24:29 - mmengine - INFO - Epoch(train) [918][20/63] lr: 1.9028e-03 eta: 5:54:05 time: 0.9018 data_time: 0.0226 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2711 loss_db: 0.0627 loss: 0.6991 2022/08/30 19:24:33 - mmengine - INFO - Epoch(train) [918][25/63] lr: 1.9028e-03 eta: 5:54:05 time: 0.8356 data_time: 0.0249 memory: 16201 loss_prob: 0.4034 loss_thr: 0.2834 loss_db: 0.0700 loss: 0.7568 2022/08/30 19:24:37 - mmengine - INFO - Epoch(train) [918][30/63] lr: 1.9028e-03 eta: 5:53:52 time: 0.8270 data_time: 0.0242 memory: 16201 loss_prob: 0.3767 loss_thr: 0.2730 loss_db: 0.0690 loss: 0.7187 2022/08/30 19:24:41 - mmengine - INFO - Epoch(train) [918][35/63] lr: 1.9028e-03 eta: 5:53:52 time: 0.8079 data_time: 0.0270 memory: 16201 loss_prob: 0.3831 loss_thr: 0.2770 loss_db: 0.0692 loss: 0.7293 2022/08/30 19:24:45 - mmengine - INFO - Epoch(train) [918][40/63] lr: 1.9028e-03 eta: 5:53:39 time: 0.7868 data_time: 0.0219 memory: 16201 loss_prob: 0.4101 loss_thr: 0.2999 loss_db: 0.0718 loss: 0.7819 2022/08/30 19:24:49 - mmengine - INFO - Epoch(train) [918][45/63] lr: 1.9028e-03 eta: 5:53:39 time: 0.8163 data_time: 0.0263 memory: 16201 loss_prob: 0.4078 loss_thr: 0.2997 loss_db: 0.0710 loss: 0.7786 2022/08/30 19:24:54 - mmengine - INFO - Epoch(train) [918][50/63] lr: 1.9028e-03 eta: 5:53:26 time: 0.8692 data_time: 0.0298 memory: 16201 loss_prob: 0.3939 loss_thr: 0.2815 loss_db: 0.0699 loss: 0.7453 2022/08/30 19:24:58 - mmengine - INFO - Epoch(train) [918][55/63] lr: 1.9028e-03 eta: 5:53:26 time: 0.8500 data_time: 0.0247 memory: 16201 loss_prob: 0.3733 loss_thr: 0.2740 loss_db: 0.0675 loss: 0.7148 2022/08/30 19:25:02 - mmengine - INFO - Epoch(train) [918][60/63] lr: 1.9028e-03 eta: 5:53:13 time: 0.7974 data_time: 0.0230 memory: 16201 loss_prob: 0.3779 loss_thr: 0.2704 loss_db: 0.0670 loss: 0.7153 2022/08/30 19:25:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:25:10 - mmengine - INFO - Epoch(train) [919][5/63] lr: 1.8968e-03 eta: 5:53:13 time: 0.9998 data_time: 0.1781 memory: 16201 loss_prob: 0.4141 loss_thr: 0.2884 loss_db: 0.0744 loss: 0.7769 2022/08/30 19:25:14 - mmengine - INFO - Epoch(train) [919][10/63] lr: 1.8968e-03 eta: 5:52:56 time: 1.0014 data_time: 0.1893 memory: 16201 loss_prob: 0.4405 loss_thr: 0.2982 loss_db: 0.0762 loss: 0.8150 2022/08/30 19:25:18 - mmengine - INFO - Epoch(train) [919][15/63] lr: 1.8968e-03 eta: 5:52:56 time: 0.8175 data_time: 0.0257 memory: 16201 loss_prob: 0.4457 loss_thr: 0.2990 loss_db: 0.0765 loss: 0.8212 2022/08/30 19:25:22 - mmengine - INFO - Epoch(train) [919][20/63] lr: 1.8968e-03 eta: 5:52:42 time: 0.8150 data_time: 0.0212 memory: 16201 loss_prob: 0.4034 loss_thr: 0.2844 loss_db: 0.0709 loss: 0.7587 2022/08/30 19:25:26 - mmengine - INFO - Epoch(train) [919][25/63] lr: 1.8968e-03 eta: 5:52:42 time: 0.8248 data_time: 0.0371 memory: 16201 loss_prob: 0.3947 loss_thr: 0.2811 loss_db: 0.0707 loss: 0.7464 2022/08/30 19:25:30 - mmengine - INFO - Epoch(train) [919][30/63] lr: 1.8968e-03 eta: 5:52:29 time: 0.7943 data_time: 0.0251 memory: 16201 loss_prob: 0.3861 loss_thr: 0.2721 loss_db: 0.0681 loss: 0.7263 2022/08/30 19:25:34 - mmengine - INFO - Epoch(train) [919][35/63] lr: 1.8968e-03 eta: 5:52:29 time: 0.7991 data_time: 0.0181 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2546 loss_db: 0.0609 loss: 0.6602 2022/08/30 19:25:38 - mmengine - INFO - Epoch(train) [919][40/63] lr: 1.8968e-03 eta: 5:52:16 time: 0.8143 data_time: 0.0267 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2520 loss_db: 0.0611 loss: 0.6496 2022/08/30 19:25:43 - mmengine - INFO - Epoch(train) [919][45/63] lr: 1.8968e-03 eta: 5:52:16 time: 0.8237 data_time: 0.0250 memory: 16201 loss_prob: 0.3395 loss_thr: 0.2431 loss_db: 0.0616 loss: 0.6442 2022/08/30 19:25:47 - mmengine - INFO - Epoch(train) [919][50/63] lr: 1.8968e-03 eta: 5:52:03 time: 0.8226 data_time: 0.0297 memory: 16201 loss_prob: 0.3727 loss_thr: 0.2605 loss_db: 0.0668 loss: 0.7000 2022/08/30 19:25:50 - mmengine - INFO - Epoch(train) [919][55/63] lr: 1.8968e-03 eta: 5:52:03 time: 0.7912 data_time: 0.0264 memory: 16201 loss_prob: 0.3997 loss_thr: 0.2858 loss_db: 0.0688 loss: 0.7544 2022/08/30 19:25:55 - mmengine - INFO - Epoch(train) [919][60/63] lr: 1.8968e-03 eta: 5:51:50 time: 0.7894 data_time: 0.0209 memory: 16201 loss_prob: 0.3909 loss_thr: 0.2837 loss_db: 0.0692 loss: 0.7438 2022/08/30 19:25:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:26:02 - mmengine - INFO - Epoch(train) [920][5/63] lr: 1.8907e-03 eta: 5:51:50 time: 0.9066 data_time: 0.1659 memory: 16201 loss_prob: 0.3952 loss_thr: 0.2791 loss_db: 0.0712 loss: 0.7454 2022/08/30 19:26:06 - mmengine - INFO - Epoch(train) [920][10/63] lr: 1.8907e-03 eta: 5:51:33 time: 0.9639 data_time: 0.1819 memory: 16201 loss_prob: 0.3944 loss_thr: 0.2788 loss_db: 0.0715 loss: 0.7448 2022/08/30 19:26:10 - mmengine - INFO - Epoch(train) [920][15/63] lr: 1.8907e-03 eta: 5:51:33 time: 0.8050 data_time: 0.0261 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2636 loss_db: 0.0654 loss: 0.6943 2022/08/30 19:26:14 - mmengine - INFO - Epoch(train) [920][20/63] lr: 1.8907e-03 eta: 5:51:20 time: 0.7924 data_time: 0.0207 memory: 16201 loss_prob: 0.4028 loss_thr: 0.2743 loss_db: 0.0721 loss: 0.7493 2022/08/30 19:26:18 - mmengine - INFO - Epoch(train) [920][25/63] lr: 1.8907e-03 eta: 5:51:20 time: 0.8014 data_time: 0.0294 memory: 16201 loss_prob: 0.4348 loss_thr: 0.2874 loss_db: 0.0773 loss: 0.7995 2022/08/30 19:26:22 - mmengine - INFO - Epoch(train) [920][30/63] lr: 1.8907e-03 eta: 5:51:06 time: 0.8021 data_time: 0.0219 memory: 16201 loss_prob: 0.4473 loss_thr: 0.2958 loss_db: 0.0800 loss: 0.8232 2022/08/30 19:26:26 - mmengine - INFO - Epoch(train) [920][35/63] lr: 1.8907e-03 eta: 5:51:06 time: 0.8252 data_time: 0.0272 memory: 16201 loss_prob: 0.3808 loss_thr: 0.2712 loss_db: 0.0679 loss: 0.7199 2022/08/30 19:26:30 - mmengine - INFO - Epoch(train) [920][40/63] lr: 1.8907e-03 eta: 5:50:53 time: 0.8153 data_time: 0.0320 memory: 16201 loss_prob: 0.3206 loss_thr: 0.2463 loss_db: 0.0568 loss: 0.6237 2022/08/30 19:26:34 - mmengine - INFO - Epoch(train) [920][45/63] lr: 1.8907e-03 eta: 5:50:53 time: 0.7968 data_time: 0.0253 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2390 loss_db: 0.0568 loss: 0.6182 2022/08/30 19:26:38 - mmengine - INFO - Epoch(train) [920][50/63] lr: 1.8907e-03 eta: 5:50:40 time: 0.8029 data_time: 0.0263 memory: 16201 loss_prob: 0.3648 loss_thr: 0.2581 loss_db: 0.0634 loss: 0.6863 2022/08/30 19:26:43 - mmengine - INFO - Epoch(train) [920][55/63] lr: 1.8907e-03 eta: 5:50:40 time: 0.8293 data_time: 0.0260 memory: 16201 loss_prob: 0.3821 loss_thr: 0.2680 loss_db: 0.0684 loss: 0.7185 2022/08/30 19:26:47 - mmengine - INFO - Epoch(train) [920][60/63] lr: 1.8907e-03 eta: 5:50:27 time: 0.8544 data_time: 0.0341 memory: 16201 loss_prob: 0.3673 loss_thr: 0.2658 loss_db: 0.0653 loss: 0.6985 2022/08/30 19:26:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:26:49 - mmengine - INFO - Saving checkpoint at 920 epochs 2022/08/30 19:26:57 - mmengine - INFO - Epoch(val) [920][5/32] eta: 5:50:27 time: 0.7361 data_time: 0.1045 memory: 16201 2022/08/30 19:27:00 - mmengine - INFO - Epoch(val) [920][10/32] eta: 0:00:15 time: 0.6956 data_time: 0.1267 memory: 15734 2022/08/30 19:27:03 - mmengine - INFO - Epoch(val) [920][15/32] eta: 0:00:15 time: 0.6039 data_time: 0.0568 memory: 15734 2022/08/30 19:27:07 - mmengine - INFO - Epoch(val) [920][20/32] eta: 0:00:08 time: 0.6694 data_time: 0.0721 memory: 15734 2022/08/30 19:27:10 - mmengine - INFO - Epoch(val) [920][25/32] eta: 0:00:08 time: 0.6952 data_time: 0.0706 memory: 15734 2022/08/30 19:27:13 - mmengine - INFO - Epoch(val) [920][30/32] eta: 0:00:01 time: 0.5995 data_time: 0.0270 memory: 15734 2022/08/30 19:27:13 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 19:27:13 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8488, precision: 0.7988, hmean: 0.8231 2022/08/30 19:27:13 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8488, precision: 0.8324, hmean: 0.8405 2022/08/30 19:27:13 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8483, precision: 0.8537, hmean: 0.8510 2022/08/30 19:27:13 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8450, precision: 0.8701, hmean: 0.8574 2022/08/30 19:27:13 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8377, precision: 0.8946, hmean: 0.8652 2022/08/30 19:27:13 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8065, precision: 0.9183, hmean: 0.8588 2022/08/30 19:27:13 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.3770, precision: 0.9607, hmean: 0.5415 2022/08/30 19:27:13 - mmengine - INFO - Epoch(val) [920][32/32] icdar/precision: 0.8946 icdar/recall: 0.8377 icdar/hmean: 0.8652 2022/08/30 19:27:20 - mmengine - INFO - Epoch(train) [921][5/63] lr: 1.8846e-03 eta: 0:00:01 time: 0.9528 data_time: 0.1802 memory: 16201 loss_prob: 0.3631 loss_thr: 0.2764 loss_db: 0.0657 loss: 0.7053 2022/08/30 19:27:24 - mmengine - INFO - Epoch(train) [921][10/63] lr: 1.8846e-03 eta: 5:50:10 time: 1.0151 data_time: 0.1918 memory: 16201 loss_prob: 0.3658 loss_thr: 0.2776 loss_db: 0.0655 loss: 0.7089 2022/08/30 19:27:28 - mmengine - INFO - Epoch(train) [921][15/63] lr: 1.8846e-03 eta: 5:50:10 time: 0.8059 data_time: 0.0347 memory: 16201 loss_prob: 0.3850 loss_thr: 0.2737 loss_db: 0.0676 loss: 0.7263 2022/08/30 19:27:32 - mmengine - INFO - Epoch(train) [921][20/63] lr: 1.8846e-03 eta: 5:49:57 time: 0.7892 data_time: 0.0280 memory: 16201 loss_prob: 0.3775 loss_thr: 0.2653 loss_db: 0.0663 loss: 0.7092 2022/08/30 19:27:36 - mmengine - INFO - Epoch(train) [921][25/63] lr: 1.8846e-03 eta: 5:49:57 time: 0.7848 data_time: 0.0215 memory: 16201 loss_prob: 0.4292 loss_thr: 0.3065 loss_db: 0.0746 loss: 0.8103 2022/08/30 19:27:39 - mmengine - INFO - Epoch(train) [921][30/63] lr: 1.8846e-03 eta: 5:49:44 time: 0.7946 data_time: 0.0278 memory: 16201 loss_prob: 0.4383 loss_thr: 0.3099 loss_db: 0.0778 loss: 0.8260 2022/08/30 19:27:44 - mmengine - INFO - Epoch(train) [921][35/63] lr: 1.8846e-03 eta: 5:49:44 time: 0.8028 data_time: 0.0273 memory: 16201 loss_prob: 0.3739 loss_thr: 0.2651 loss_db: 0.0673 loss: 0.7063 2022/08/30 19:27:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:27:48 - mmengine - INFO - Epoch(train) [921][40/63] lr: 1.8846e-03 eta: 5:49:31 time: 0.8092 data_time: 0.0199 memory: 16201 loss_prob: 0.3580 loss_thr: 0.2585 loss_db: 0.0630 loss: 0.6795 2022/08/30 19:27:52 - mmengine - INFO - Epoch(train) [921][45/63] lr: 1.8846e-03 eta: 5:49:31 time: 0.8046 data_time: 0.0272 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2604 loss_db: 0.0623 loss: 0.6790 2022/08/30 19:27:56 - mmengine - INFO - Epoch(train) [921][50/63] lr: 1.8846e-03 eta: 5:49:18 time: 0.8010 data_time: 0.0261 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2604 loss_db: 0.0633 loss: 0.6767 2022/08/30 19:28:00 - mmengine - INFO - Epoch(train) [921][55/63] lr: 1.8846e-03 eta: 5:49:18 time: 0.8244 data_time: 0.0230 memory: 16201 loss_prob: 0.3532 loss_thr: 0.2490 loss_db: 0.0644 loss: 0.6665 2022/08/30 19:28:04 - mmengine - INFO - Epoch(train) [921][60/63] lr: 1.8846e-03 eta: 5:49:05 time: 0.8502 data_time: 0.0421 memory: 16201 loss_prob: 0.3719 loss_thr: 0.2471 loss_db: 0.0659 loss: 0.6848 2022/08/30 19:28:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:28:11 - mmengine - INFO - Epoch(train) [922][5/63] lr: 1.8785e-03 eta: 5:49:05 time: 0.8924 data_time: 0.1588 memory: 16201 loss_prob: 0.4282 loss_thr: 0.2882 loss_db: 0.0741 loss: 0.7905 2022/08/30 19:28:15 - mmengine - INFO - Epoch(train) [922][10/63] lr: 1.8785e-03 eta: 5:48:48 time: 0.9354 data_time: 0.1629 memory: 16201 loss_prob: 0.4258 loss_thr: 0.2903 loss_db: 0.0722 loss: 0.7883 2022/08/30 19:28:19 - mmengine - INFO - Epoch(train) [922][15/63] lr: 1.8785e-03 eta: 5:48:48 time: 0.7908 data_time: 0.0244 memory: 16201 loss_prob: 0.4232 loss_thr: 0.2915 loss_db: 0.0730 loss: 0.7877 2022/08/30 19:28:23 - mmengine - INFO - Epoch(train) [922][20/63] lr: 1.8785e-03 eta: 5:48:34 time: 0.8070 data_time: 0.0241 memory: 16201 loss_prob: 0.4219 loss_thr: 0.2822 loss_db: 0.0736 loss: 0.7777 2022/08/30 19:28:27 - mmengine - INFO - Epoch(train) [922][25/63] lr: 1.8785e-03 eta: 5:48:34 time: 0.8067 data_time: 0.0265 memory: 16201 loss_prob: 0.3930 loss_thr: 0.2708 loss_db: 0.0679 loss: 0.7317 2022/08/30 19:28:31 - mmengine - INFO - Epoch(train) [922][30/63] lr: 1.8785e-03 eta: 5:48:21 time: 0.7979 data_time: 0.0275 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2693 loss_db: 0.0630 loss: 0.6917 2022/08/30 19:28:35 - mmengine - INFO - Epoch(train) [922][35/63] lr: 1.8785e-03 eta: 5:48:21 time: 0.8119 data_time: 0.0283 memory: 16201 loss_prob: 0.3722 loss_thr: 0.2675 loss_db: 0.0657 loss: 0.7054 2022/08/30 19:28:39 - mmengine - INFO - Epoch(train) [922][40/63] lr: 1.8785e-03 eta: 5:48:08 time: 0.7979 data_time: 0.0233 memory: 16201 loss_prob: 0.3893 loss_thr: 0.2719 loss_db: 0.0688 loss: 0.7299 2022/08/30 19:28:43 - mmengine - INFO - Epoch(train) [922][45/63] lr: 1.8785e-03 eta: 5:48:08 time: 0.7925 data_time: 0.0253 memory: 16201 loss_prob: 0.3713 loss_thr: 0.2640 loss_db: 0.0680 loss: 0.7032 2022/08/30 19:28:48 - mmengine - INFO - Epoch(train) [922][50/63] lr: 1.8785e-03 eta: 5:47:55 time: 0.8174 data_time: 0.0270 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2591 loss_db: 0.0660 loss: 0.6870 2022/08/30 19:28:52 - mmengine - INFO - Epoch(train) [922][55/63] lr: 1.8785e-03 eta: 5:47:55 time: 0.8308 data_time: 0.0327 memory: 16201 loss_prob: 0.3849 loss_thr: 0.2700 loss_db: 0.0683 loss: 0.7233 2022/08/30 19:28:56 - mmengine - INFO - Epoch(train) [922][60/63] lr: 1.8785e-03 eta: 5:47:42 time: 0.8132 data_time: 0.0348 memory: 16201 loss_prob: 0.3745 loss_thr: 0.2562 loss_db: 0.0632 loss: 0.6939 2022/08/30 19:28:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:29:03 - mmengine - INFO - Epoch(train) [923][5/63] lr: 1.8724e-03 eta: 5:47:42 time: 0.9043 data_time: 0.1931 memory: 16201 loss_prob: 0.3817 loss_thr: 0.2560 loss_db: 0.0647 loss: 0.7024 2022/08/30 19:29:07 - mmengine - INFO - Epoch(train) [923][10/63] lr: 1.8724e-03 eta: 5:47:25 time: 0.9746 data_time: 0.2031 memory: 16201 loss_prob: 0.3538 loss_thr: 0.2506 loss_db: 0.0638 loss: 0.6682 2022/08/30 19:29:11 - mmengine - INFO - Epoch(train) [923][15/63] lr: 1.8724e-03 eta: 5:47:25 time: 0.8046 data_time: 0.0262 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2487 loss_db: 0.0624 loss: 0.6532 2022/08/30 19:29:15 - mmengine - INFO - Epoch(train) [923][20/63] lr: 1.8724e-03 eta: 5:47:12 time: 0.7989 data_time: 0.0239 memory: 16201 loss_prob: 0.3645 loss_thr: 0.2649 loss_db: 0.0643 loss: 0.6937 2022/08/30 19:29:19 - mmengine - INFO - Epoch(train) [923][25/63] lr: 1.8724e-03 eta: 5:47:12 time: 0.8192 data_time: 0.0305 memory: 16201 loss_prob: 0.3574 loss_thr: 0.2595 loss_db: 0.0643 loss: 0.6812 2022/08/30 19:29:24 - mmengine - INFO - Epoch(train) [923][30/63] lr: 1.8724e-03 eta: 5:46:59 time: 0.8909 data_time: 0.0224 memory: 16201 loss_prob: 0.3278 loss_thr: 0.2333 loss_db: 0.0596 loss: 0.6207 2022/08/30 19:29:28 - mmengine - INFO - Epoch(train) [923][35/63] lr: 1.8724e-03 eta: 5:46:59 time: 0.8801 data_time: 0.0237 memory: 16201 loss_prob: 0.3485 loss_thr: 0.2451 loss_db: 0.0619 loss: 0.6555 2022/08/30 19:29:32 - mmengine - INFO - Epoch(train) [923][40/63] lr: 1.8724e-03 eta: 5:46:46 time: 0.7999 data_time: 0.0267 memory: 16201 loss_prob: 0.3844 loss_thr: 0.2709 loss_db: 0.0675 loss: 0.7229 2022/08/30 19:29:36 - mmengine - INFO - Epoch(train) [923][45/63] lr: 1.8724e-03 eta: 5:46:46 time: 0.7929 data_time: 0.0278 memory: 16201 loss_prob: 0.3662 loss_thr: 0.2622 loss_db: 0.0649 loss: 0.6933 2022/08/30 19:29:40 - mmengine - INFO - Epoch(train) [923][50/63] lr: 1.8724e-03 eta: 5:46:33 time: 0.7782 data_time: 0.0245 memory: 16201 loss_prob: 0.3528 loss_thr: 0.2613 loss_db: 0.0628 loss: 0.6768 2022/08/30 19:29:45 - mmengine - INFO - Epoch(train) [923][55/63] lr: 1.8724e-03 eta: 5:46:33 time: 0.8343 data_time: 0.0236 memory: 16201 loss_prob: 0.3830 loss_thr: 0.2765 loss_db: 0.0675 loss: 0.7270 2022/08/30 19:29:49 - mmengine - INFO - Epoch(train) [923][60/63] lr: 1.8724e-03 eta: 5:46:20 time: 0.8554 data_time: 0.0385 memory: 16201 loss_prob: 0.4054 loss_thr: 0.2890 loss_db: 0.0711 loss: 0.7655 2022/08/30 19:29:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:29:56 - mmengine - INFO - Epoch(train) [924][5/63] lr: 1.8664e-03 eta: 5:46:20 time: 0.8919 data_time: 0.1579 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2662 loss_db: 0.0664 loss: 0.7107 2022/08/30 19:30:01 - mmengine - INFO - Epoch(train) [924][10/63] lr: 1.8664e-03 eta: 5:46:03 time: 0.9954 data_time: 0.2042 memory: 16201 loss_prob: 0.3812 loss_thr: 0.2697 loss_db: 0.0658 loss: 0.7166 2022/08/30 19:30:05 - mmengine - INFO - Epoch(train) [924][15/63] lr: 1.8664e-03 eta: 5:46:03 time: 0.8841 data_time: 0.0642 memory: 16201 loss_prob: 0.3834 loss_thr: 0.2675 loss_db: 0.0663 loss: 0.7172 2022/08/30 19:30:09 - mmengine - INFO - Epoch(train) [924][20/63] lr: 1.8664e-03 eta: 5:45:50 time: 0.8237 data_time: 0.0209 memory: 16201 loss_prob: 0.3808 loss_thr: 0.2653 loss_db: 0.0675 loss: 0.7136 2022/08/30 19:30:13 - mmengine - INFO - Epoch(train) [924][25/63] lr: 1.8664e-03 eta: 5:45:50 time: 0.7980 data_time: 0.0310 memory: 16201 loss_prob: 0.3794 loss_thr: 0.2790 loss_db: 0.0674 loss: 0.7258 2022/08/30 19:30:17 - mmengine - INFO - Epoch(train) [924][30/63] lr: 1.8664e-03 eta: 5:45:37 time: 0.7841 data_time: 0.0268 memory: 16201 loss_prob: 0.3626 loss_thr: 0.2695 loss_db: 0.0649 loss: 0.6971 2022/08/30 19:30:21 - mmengine - INFO - Epoch(train) [924][35/63] lr: 1.8664e-03 eta: 5:45:37 time: 0.8119 data_time: 0.0204 memory: 16201 loss_prob: 0.3707 loss_thr: 0.2691 loss_db: 0.0663 loss: 0.7061 2022/08/30 19:30:25 - mmengine - INFO - Epoch(train) [924][40/63] lr: 1.8664e-03 eta: 5:45:24 time: 0.8208 data_time: 0.0254 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2582 loss_db: 0.0612 loss: 0.6605 2022/08/30 19:30:29 - mmengine - INFO - Epoch(train) [924][45/63] lr: 1.8664e-03 eta: 5:45:24 time: 0.7803 data_time: 0.0224 memory: 16201 loss_prob: 0.3237 loss_thr: 0.2449 loss_db: 0.0595 loss: 0.6281 2022/08/30 19:30:33 - mmengine - INFO - Epoch(train) [924][50/63] lr: 1.8664e-03 eta: 5:45:11 time: 0.8076 data_time: 0.0241 memory: 16201 loss_prob: 0.3672 loss_thr: 0.2632 loss_db: 0.0663 loss: 0.6967 2022/08/30 19:30:37 - mmengine - INFO - Epoch(train) [924][55/63] lr: 1.8664e-03 eta: 5:45:11 time: 0.8198 data_time: 0.0330 memory: 16201 loss_prob: 0.3799 loss_thr: 0.2693 loss_db: 0.0656 loss: 0.7149 2022/08/30 19:30:41 - mmengine - INFO - Epoch(train) [924][60/63] lr: 1.8664e-03 eta: 5:44:57 time: 0.7914 data_time: 0.0312 memory: 16201 loss_prob: 0.3826 loss_thr: 0.2818 loss_db: 0.0664 loss: 0.7308 2022/08/30 19:30:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:30:49 - mmengine - INFO - Epoch(train) [925][5/63] lr: 1.8603e-03 eta: 5:44:57 time: 0.9434 data_time: 0.2109 memory: 16201 loss_prob: 0.3872 loss_thr: 0.2751 loss_db: 0.0712 loss: 0.7335 2022/08/30 19:30:53 - mmengine - INFO - Epoch(train) [925][10/63] lr: 1.8603e-03 eta: 5:44:40 time: 0.9946 data_time: 0.2255 memory: 16201 loss_prob: 0.3549 loss_thr: 0.2567 loss_db: 0.0632 loss: 0.6748 2022/08/30 19:30:57 - mmengine - INFO - Epoch(train) [925][15/63] lr: 1.8603e-03 eta: 5:44:40 time: 0.7861 data_time: 0.0259 memory: 16201 loss_prob: 0.4072 loss_thr: 0.2891 loss_db: 0.0713 loss: 0.7676 2022/08/30 19:31:01 - mmengine - INFO - Epoch(train) [925][20/63] lr: 1.8603e-03 eta: 5:44:27 time: 0.7823 data_time: 0.0178 memory: 16201 loss_prob: 0.3965 loss_thr: 0.2841 loss_db: 0.0701 loss: 0.7507 2022/08/30 19:31:05 - mmengine - INFO - Epoch(train) [925][25/63] lr: 1.8603e-03 eta: 5:44:27 time: 0.8518 data_time: 0.0328 memory: 16201 loss_prob: 0.3700 loss_thr: 0.2671 loss_db: 0.0649 loss: 0.7020 2022/08/30 19:31:10 - mmengine - INFO - Epoch(train) [925][30/63] lr: 1.8603e-03 eta: 5:44:14 time: 0.8886 data_time: 0.0260 memory: 16201 loss_prob: 0.3431 loss_thr: 0.2595 loss_db: 0.0612 loss: 0.6638 2022/08/30 19:31:13 - mmengine - INFO - Epoch(train) [925][35/63] lr: 1.8603e-03 eta: 5:44:14 time: 0.8196 data_time: 0.0219 memory: 16201 loss_prob: 0.3135 loss_thr: 0.2403 loss_db: 0.0580 loss: 0.6119 2022/08/30 19:31:17 - mmengine - INFO - Epoch(train) [925][40/63] lr: 1.8603e-03 eta: 5:44:01 time: 0.7943 data_time: 0.0284 memory: 16201 loss_prob: 0.3351 loss_thr: 0.2639 loss_db: 0.0602 loss: 0.6592 2022/08/30 19:31:21 - mmengine - INFO - Epoch(train) [925][45/63] lr: 1.8603e-03 eta: 5:44:01 time: 0.7999 data_time: 0.0246 memory: 16201 loss_prob: 0.3459 loss_thr: 0.2674 loss_db: 0.0608 loss: 0.6741 2022/08/30 19:31:26 - mmengine - INFO - Epoch(train) [925][50/63] lr: 1.8603e-03 eta: 5:43:48 time: 0.8504 data_time: 0.0254 memory: 16201 loss_prob: 0.3696 loss_thr: 0.2592 loss_db: 0.0657 loss: 0.6945 2022/08/30 19:31:30 - mmengine - INFO - Epoch(train) [925][55/63] lr: 1.8603e-03 eta: 5:43:48 time: 0.8499 data_time: 0.0240 memory: 16201 loss_prob: 0.3552 loss_thr: 0.2490 loss_db: 0.0620 loss: 0.6662 2022/08/30 19:31:34 - mmengine - INFO - Epoch(train) [925][60/63] lr: 1.8603e-03 eta: 5:43:35 time: 0.8052 data_time: 0.0222 memory: 16201 loss_prob: 0.3545 loss_thr: 0.2547 loss_db: 0.0616 loss: 0.6708 2022/08/30 19:31:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:31:41 - mmengine - INFO - Epoch(train) [926][5/63] lr: 1.8542e-03 eta: 5:43:35 time: 0.9131 data_time: 0.1591 memory: 16201 loss_prob: 0.3605 loss_thr: 0.2641 loss_db: 0.0644 loss: 0.6890 2022/08/30 19:31:45 - mmengine - INFO - Epoch(train) [926][10/63] lr: 1.8542e-03 eta: 5:43:18 time: 0.9485 data_time: 0.1724 memory: 16201 loss_prob: 0.3578 loss_thr: 0.2553 loss_db: 0.0633 loss: 0.6764 2022/08/30 19:31:49 - mmengine - INFO - Epoch(train) [926][15/63] lr: 1.8542e-03 eta: 5:43:18 time: 0.7952 data_time: 0.0236 memory: 16201 loss_prob: 0.3593 loss_thr: 0.2509 loss_db: 0.0629 loss: 0.6731 2022/08/30 19:31:53 - mmengine - INFO - Epoch(train) [926][20/63] lr: 1.8542e-03 eta: 5:43:05 time: 0.7890 data_time: 0.0213 memory: 16201 loss_prob: 0.3902 loss_thr: 0.2624 loss_db: 0.0675 loss: 0.7201 2022/08/30 19:31:57 - mmengine - INFO - Epoch(train) [926][25/63] lr: 1.8542e-03 eta: 5:43:05 time: 0.7961 data_time: 0.0321 memory: 16201 loss_prob: 0.3888 loss_thr: 0.2654 loss_db: 0.0683 loss: 0.7225 2022/08/30 19:32:01 - mmengine - INFO - Epoch(train) [926][30/63] lr: 1.8542e-03 eta: 5:42:52 time: 0.7969 data_time: 0.0238 memory: 16201 loss_prob: 0.3633 loss_thr: 0.2651 loss_db: 0.0648 loss: 0.6932 2022/08/30 19:32:06 - mmengine - INFO - Epoch(train) [926][35/63] lr: 1.8542e-03 eta: 5:42:52 time: 0.8512 data_time: 0.0303 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2575 loss_db: 0.0633 loss: 0.6807 2022/08/30 19:32:10 - mmengine - INFO - Epoch(train) [926][40/63] lr: 1.8542e-03 eta: 5:42:39 time: 0.8604 data_time: 0.0373 memory: 16201 loss_prob: 0.3583 loss_thr: 0.2572 loss_db: 0.0640 loss: 0.6794 2022/08/30 19:32:14 - mmengine - INFO - Epoch(train) [926][45/63] lr: 1.8542e-03 eta: 5:42:39 time: 0.7933 data_time: 0.0261 memory: 16201 loss_prob: 0.4182 loss_thr: 0.3095 loss_db: 0.0747 loss: 0.8023 2022/08/30 19:32:18 - mmengine - INFO - Epoch(train) [926][50/63] lr: 1.8542e-03 eta: 5:42:26 time: 0.7978 data_time: 0.0238 memory: 16201 loss_prob: 0.4089 loss_thr: 0.3017 loss_db: 0.0725 loss: 0.7830 2022/08/30 19:32:22 - mmengine - INFO - Epoch(train) [926][55/63] lr: 1.8542e-03 eta: 5:42:26 time: 0.8097 data_time: 0.0235 memory: 16201 loss_prob: 0.3765 loss_thr: 0.2741 loss_db: 0.0662 loss: 0.7168 2022/08/30 19:32:27 - mmengine - INFO - Epoch(train) [926][60/63] lr: 1.8542e-03 eta: 5:42:13 time: 0.8676 data_time: 0.0294 memory: 16201 loss_prob: 0.3996 loss_thr: 0.2777 loss_db: 0.0694 loss: 0.7467 2022/08/30 19:32:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:32:35 - mmengine - INFO - Epoch(train) [927][5/63] lr: 1.8481e-03 eta: 5:42:13 time: 0.9934 data_time: 0.2320 memory: 16201 loss_prob: 0.3719 loss_thr: 0.2588 loss_db: 0.0647 loss: 0.6954 2022/08/30 19:32:39 - mmengine - INFO - Epoch(train) [927][10/63] lr: 1.8481e-03 eta: 5:41:56 time: 1.0169 data_time: 0.2336 memory: 16201 loss_prob: 0.3146 loss_thr: 0.2421 loss_db: 0.0559 loss: 0.6126 2022/08/30 19:32:43 - mmengine - INFO - Epoch(train) [927][15/63] lr: 1.8481e-03 eta: 5:41:56 time: 0.8308 data_time: 0.0246 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2592 loss_db: 0.0622 loss: 0.6754 2022/08/30 19:32:47 - mmengine - INFO - Epoch(train) [927][20/63] lr: 1.8481e-03 eta: 5:41:43 time: 0.8273 data_time: 0.0188 memory: 16201 loss_prob: 0.3713 loss_thr: 0.2653 loss_db: 0.0657 loss: 0.7024 2022/08/30 19:32:51 - mmengine - INFO - Epoch(train) [927][25/63] lr: 1.8481e-03 eta: 5:41:43 time: 0.8091 data_time: 0.0296 memory: 16201 loss_prob: 0.3413 loss_thr: 0.2520 loss_db: 0.0617 loss: 0.6550 2022/08/30 19:32:55 - mmengine - INFO - Epoch(train) [927][30/63] lr: 1.8481e-03 eta: 5:41:30 time: 0.7917 data_time: 0.0272 memory: 16201 loss_prob: 0.3578 loss_thr: 0.2599 loss_db: 0.0649 loss: 0.6826 2022/08/30 19:33:00 - mmengine - INFO - Epoch(train) [927][35/63] lr: 1.8481e-03 eta: 5:41:30 time: 0.8565 data_time: 0.0200 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2612 loss_db: 0.0653 loss: 0.6863 2022/08/30 19:33:04 - mmengine - INFO - Epoch(train) [927][40/63] lr: 1.8481e-03 eta: 5:41:17 time: 0.8847 data_time: 0.0260 memory: 16201 loss_prob: 0.4099 loss_thr: 0.2741 loss_db: 0.0702 loss: 0.7541 2022/08/30 19:33:08 - mmengine - INFO - Epoch(train) [927][45/63] lr: 1.8481e-03 eta: 5:41:17 time: 0.8296 data_time: 0.0304 memory: 16201 loss_prob: 0.4237 loss_thr: 0.2792 loss_db: 0.0724 loss: 0.7754 2022/08/30 19:33:12 - mmengine - INFO - Epoch(train) [927][50/63] lr: 1.8481e-03 eta: 5:41:04 time: 0.8070 data_time: 0.0256 memory: 16201 loss_prob: 0.3685 loss_thr: 0.2668 loss_db: 0.0671 loss: 0.7024 2022/08/30 19:33:16 - mmengine - INFO - Epoch(train) [927][55/63] lr: 1.8481e-03 eta: 5:41:04 time: 0.8084 data_time: 0.0265 memory: 16201 loss_prob: 0.3722 loss_thr: 0.2724 loss_db: 0.0659 loss: 0.7105 2022/08/30 19:33:20 - mmengine - INFO - Epoch(train) [927][60/63] lr: 1.8481e-03 eta: 5:40:51 time: 0.8140 data_time: 0.0290 memory: 16201 loss_prob: 0.3699 loss_thr: 0.2643 loss_db: 0.0652 loss: 0.6995 2022/08/30 19:33:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:33:28 - mmengine - INFO - Epoch(train) [928][5/63] lr: 1.8420e-03 eta: 5:40:51 time: 0.9206 data_time: 0.1964 memory: 16201 loss_prob: 0.3550 loss_thr: 0.2638 loss_db: 0.0632 loss: 0.6820 2022/08/30 19:33:32 - mmengine - INFO - Epoch(train) [928][10/63] lr: 1.8420e-03 eta: 5:40:34 time: 0.9861 data_time: 0.2106 memory: 16201 loss_prob: 0.3919 loss_thr: 0.2834 loss_db: 0.0700 loss: 0.7453 2022/08/30 19:33:36 - mmengine - INFO - Epoch(train) [928][15/63] lr: 1.8420e-03 eta: 5:40:34 time: 0.8116 data_time: 0.0264 memory: 16201 loss_prob: 0.3801 loss_thr: 0.2714 loss_db: 0.0679 loss: 0.7194 2022/08/30 19:33:40 - mmengine - INFO - Epoch(train) [928][20/63] lr: 1.8420e-03 eta: 5:40:21 time: 0.8152 data_time: 0.0207 memory: 16201 loss_prob: 0.3638 loss_thr: 0.2557 loss_db: 0.0640 loss: 0.6835 2022/08/30 19:33:45 - mmengine - INFO - Epoch(train) [928][25/63] lr: 1.8420e-03 eta: 5:40:21 time: 0.8626 data_time: 0.0533 memory: 16201 loss_prob: 0.3497 loss_thr: 0.2509 loss_db: 0.0610 loss: 0.6616 2022/08/30 19:33:49 - mmengine - INFO - Epoch(train) [928][30/63] lr: 1.8420e-03 eta: 5:40:08 time: 0.8616 data_time: 0.0442 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2364 loss_db: 0.0574 loss: 0.6159 2022/08/30 19:33:53 - mmengine - INFO - Epoch(train) [928][35/63] lr: 1.8420e-03 eta: 5:40:08 time: 0.8088 data_time: 0.0189 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2248 loss_db: 0.0594 loss: 0.6133 2022/08/30 19:33:57 - mmengine - INFO - Epoch(train) [928][40/63] lr: 1.8420e-03 eta: 5:39:55 time: 0.7945 data_time: 0.0283 memory: 16201 loss_prob: 0.3813 loss_thr: 0.2647 loss_db: 0.0677 loss: 0.7136 2022/08/30 19:34:01 - mmengine - INFO - Epoch(train) [928][45/63] lr: 1.8420e-03 eta: 5:39:55 time: 0.8054 data_time: 0.0298 memory: 16201 loss_prob: 0.3961 loss_thr: 0.2838 loss_db: 0.0701 loss: 0.7500 2022/08/30 19:34:06 - mmengine - INFO - Epoch(train) [928][50/63] lr: 1.8420e-03 eta: 5:39:43 time: 0.8781 data_time: 0.0293 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2558 loss_db: 0.0653 loss: 0.6971 2022/08/30 19:34:10 - mmengine - INFO - Epoch(train) [928][55/63] lr: 1.8420e-03 eta: 5:39:43 time: 0.8707 data_time: 0.0354 memory: 16201 loss_prob: 0.3729 loss_thr: 0.2498 loss_db: 0.0635 loss: 0.6862 2022/08/30 19:34:13 - mmengine - INFO - Epoch(train) [928][60/63] lr: 1.8420e-03 eta: 5:39:30 time: 0.7863 data_time: 0.0321 memory: 16201 loss_prob: 0.3692 loss_thr: 0.2531 loss_db: 0.0642 loss: 0.6865 2022/08/30 19:34:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:34:21 - mmengine - INFO - Epoch(train) [929][5/63] lr: 1.8359e-03 eta: 5:39:30 time: 0.9507 data_time: 0.1964 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2533 loss_db: 0.0633 loss: 0.6732 2022/08/30 19:34:25 - mmengine - INFO - Epoch(train) [929][10/63] lr: 1.8359e-03 eta: 5:39:13 time: 0.9995 data_time: 0.2067 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2591 loss_db: 0.0650 loss: 0.6835 2022/08/30 19:34:30 - mmengine - INFO - Epoch(train) [929][15/63] lr: 1.8359e-03 eta: 5:39:13 time: 0.8130 data_time: 0.0274 memory: 16201 loss_prob: 0.4103 loss_thr: 0.2786 loss_db: 0.0730 loss: 0.7620 2022/08/30 19:34:34 - mmengine - INFO - Epoch(train) [929][20/63] lr: 1.8359e-03 eta: 5:39:00 time: 0.8733 data_time: 0.0267 memory: 16201 loss_prob: 0.3809 loss_thr: 0.2593 loss_db: 0.0668 loss: 0.7070 2022/08/30 19:34:38 - mmengine - INFO - Epoch(train) [929][25/63] lr: 1.8359e-03 eta: 5:39:00 time: 0.8585 data_time: 0.0284 memory: 16201 loss_prob: 0.3724 loss_thr: 0.2628 loss_db: 0.0649 loss: 0.7001 2022/08/30 19:34:42 - mmengine - INFO - Epoch(train) [929][30/63] lr: 1.8359e-03 eta: 5:38:47 time: 0.7949 data_time: 0.0251 memory: 16201 loss_prob: 0.4046 loss_thr: 0.2782 loss_db: 0.0717 loss: 0.7545 2022/08/30 19:34:46 - mmengine - INFO - Epoch(train) [929][35/63] lr: 1.8359e-03 eta: 5:38:47 time: 0.8114 data_time: 0.0281 memory: 16201 loss_prob: 0.3485 loss_thr: 0.2514 loss_db: 0.0635 loss: 0.6635 2022/08/30 19:34:50 - mmengine - INFO - Epoch(train) [929][40/63] lr: 1.8359e-03 eta: 5:38:34 time: 0.8127 data_time: 0.0270 memory: 16201 loss_prob: 0.3355 loss_thr: 0.2453 loss_db: 0.0598 loss: 0.6406 2022/08/30 19:34:55 - mmengine - INFO - Epoch(train) [929][45/63] lr: 1.8359e-03 eta: 5:38:34 time: 0.8522 data_time: 0.0240 memory: 16201 loss_prob: 0.3764 loss_thr: 0.2696 loss_db: 0.0663 loss: 0.7123 2022/08/30 19:34:59 - mmengine - INFO - Epoch(train) [929][50/63] lr: 1.8359e-03 eta: 5:38:21 time: 0.8523 data_time: 0.0213 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2716 loss_db: 0.0654 loss: 0.7154 2022/08/30 19:35:03 - mmengine - INFO - Epoch(train) [929][55/63] lr: 1.8359e-03 eta: 5:38:21 time: 0.8098 data_time: 0.0234 memory: 16201 loss_prob: 0.3759 loss_thr: 0.2670 loss_db: 0.0656 loss: 0.7085 2022/08/30 19:35:07 - mmengine - INFO - Epoch(train) [929][60/63] lr: 1.8359e-03 eta: 5:38:08 time: 0.8180 data_time: 0.0330 memory: 16201 loss_prob: 0.4004 loss_thr: 0.2875 loss_db: 0.0722 loss: 0.7600 2022/08/30 19:35:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:35:15 - mmengine - INFO - Epoch(train) [930][5/63] lr: 1.8298e-03 eta: 5:38:08 time: 0.9188 data_time: 0.1586 memory: 16201 loss_prob: 0.4578 loss_thr: 0.3109 loss_db: 0.0788 loss: 0.8475 2022/08/30 19:35:19 - mmengine - INFO - Epoch(train) [930][10/63] lr: 1.8298e-03 eta: 5:37:51 time: 0.9646 data_time: 0.1681 memory: 16201 loss_prob: 0.4029 loss_thr: 0.2750 loss_db: 0.0678 loss: 0.7458 2022/08/30 19:35:22 - mmengine - INFO - Epoch(train) [930][15/63] lr: 1.8298e-03 eta: 5:37:51 time: 0.7886 data_time: 0.0252 memory: 16201 loss_prob: 0.3484 loss_thr: 0.2488 loss_db: 0.0626 loss: 0.6598 2022/08/30 19:35:27 - mmengine - INFO - Epoch(train) [930][20/63] lr: 1.8298e-03 eta: 5:37:38 time: 0.8536 data_time: 0.0237 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2405 loss_db: 0.0608 loss: 0.6316 2022/08/30 19:35:31 - mmengine - INFO - Epoch(train) [930][25/63] lr: 1.8298e-03 eta: 5:37:38 time: 0.8567 data_time: 0.0307 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2469 loss_db: 0.0616 loss: 0.6495 2022/08/30 19:35:35 - mmengine - INFO - Epoch(train) [930][30/63] lr: 1.8298e-03 eta: 5:37:25 time: 0.8231 data_time: 0.0226 memory: 16201 loss_prob: 0.3572 loss_thr: 0.2592 loss_db: 0.0630 loss: 0.6795 2022/08/30 19:35:39 - mmengine - INFO - Epoch(train) [930][35/63] lr: 1.8298e-03 eta: 5:37:25 time: 0.8260 data_time: 0.0264 memory: 16201 loss_prob: 0.3991 loss_thr: 0.2730 loss_db: 0.0703 loss: 0.7425 2022/08/30 19:35:43 - mmengine - INFO - Epoch(train) [930][40/63] lr: 1.8298e-03 eta: 5:37:12 time: 0.7977 data_time: 0.0259 memory: 16201 loss_prob: 0.3904 loss_thr: 0.2657 loss_db: 0.0704 loss: 0.7265 2022/08/30 19:35:47 - mmengine - INFO - Epoch(train) [930][45/63] lr: 1.8298e-03 eta: 5:37:12 time: 0.8145 data_time: 0.0269 memory: 16201 loss_prob: 0.3857 loss_thr: 0.2672 loss_db: 0.0687 loss: 0.7216 2022/08/30 19:35:51 - mmengine - INFO - Epoch(train) [930][50/63] lr: 1.8298e-03 eta: 5:36:59 time: 0.8109 data_time: 0.0297 memory: 16201 loss_prob: 0.4091 loss_thr: 0.2694 loss_db: 0.0694 loss: 0.7479 2022/08/30 19:35:55 - mmengine - INFO - Epoch(train) [930][55/63] lr: 1.8298e-03 eta: 5:36:59 time: 0.7956 data_time: 0.0236 memory: 16201 loss_prob: 0.3710 loss_thr: 0.2556 loss_db: 0.0641 loss: 0.6907 2022/08/30 19:35:59 - mmengine - INFO - Epoch(train) [930][60/63] lr: 1.8298e-03 eta: 5:36:46 time: 0.7827 data_time: 0.0243 memory: 16201 loss_prob: 0.3848 loss_thr: 0.2763 loss_db: 0.0658 loss: 0.7268 2022/08/30 19:36:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:36:07 - mmengine - INFO - Epoch(train) [931][5/63] lr: 1.8237e-03 eta: 5:36:46 time: 0.9571 data_time: 0.2097 memory: 16201 loss_prob: 0.3840 loss_thr: 0.2722 loss_db: 0.0688 loss: 0.7249 2022/08/30 19:36:11 - mmengine - INFO - Epoch(train) [931][10/63] lr: 1.8237e-03 eta: 5:36:29 time: 0.9901 data_time: 0.2236 memory: 16201 loss_prob: 0.3712 loss_thr: 0.2583 loss_db: 0.0669 loss: 0.6963 2022/08/30 19:36:15 - mmengine - INFO - Epoch(train) [931][15/63] lr: 1.8237e-03 eta: 5:36:29 time: 0.8171 data_time: 0.0272 memory: 16201 loss_prob: 0.3785 loss_thr: 0.2622 loss_db: 0.0670 loss: 0.7077 2022/08/30 19:36:19 - mmengine - INFO - Epoch(train) [931][20/63] lr: 1.8237e-03 eta: 5:36:16 time: 0.8267 data_time: 0.0204 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2606 loss_db: 0.0616 loss: 0.6670 2022/08/30 19:36:24 - mmengine - INFO - Epoch(train) [931][25/63] lr: 1.8237e-03 eta: 5:36:16 time: 0.8307 data_time: 0.0297 memory: 16201 loss_prob: 0.3529 loss_thr: 0.2664 loss_db: 0.0618 loss: 0.6810 2022/08/30 19:36:28 - mmengine - INFO - Epoch(train) [931][30/63] lr: 1.8237e-03 eta: 5:36:03 time: 0.8282 data_time: 0.0252 memory: 16201 loss_prob: 0.4033 loss_thr: 0.2722 loss_db: 0.0686 loss: 0.7441 2022/08/30 19:36:32 - mmengine - INFO - Epoch(train) [931][35/63] lr: 1.8237e-03 eta: 5:36:03 time: 0.7998 data_time: 0.0215 memory: 16201 loss_prob: 0.3714 loss_thr: 0.2581 loss_db: 0.0645 loss: 0.6941 2022/08/30 19:36:36 - mmengine - INFO - Epoch(train) [931][40/63] lr: 1.8237e-03 eta: 5:35:50 time: 0.8136 data_time: 0.0245 memory: 16201 loss_prob: 0.3525 loss_thr: 0.2602 loss_db: 0.0630 loss: 0.6758 2022/08/30 19:36:40 - mmengine - INFO - Epoch(train) [931][45/63] lr: 1.8237e-03 eta: 5:35:50 time: 0.8016 data_time: 0.0249 memory: 16201 loss_prob: 0.3786 loss_thr: 0.2615 loss_db: 0.0672 loss: 0.7073 2022/08/30 19:36:44 - mmengine - INFO - Epoch(train) [931][50/63] lr: 1.8237e-03 eta: 5:35:37 time: 0.8548 data_time: 0.0252 memory: 16201 loss_prob: 0.3644 loss_thr: 0.2612 loss_db: 0.0651 loss: 0.6907 2022/08/30 19:36:48 - mmengine - INFO - Epoch(train) [931][55/63] lr: 1.8237e-03 eta: 5:35:37 time: 0.8629 data_time: 0.0262 memory: 16201 loss_prob: 0.3304 loss_thr: 0.2403 loss_db: 0.0586 loss: 0.6293 2022/08/30 19:36:52 - mmengine - INFO - Epoch(train) [931][60/63] lr: 1.8237e-03 eta: 5:35:24 time: 0.7994 data_time: 0.0273 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2459 loss_db: 0.0582 loss: 0.6344 2022/08/30 19:36:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:37:00 - mmengine - INFO - Epoch(train) [932][5/63] lr: 1.8176e-03 eta: 5:35:24 time: 0.9367 data_time: 0.1928 memory: 16201 loss_prob: 0.3962 loss_thr: 0.2744 loss_db: 0.0703 loss: 0.7409 2022/08/30 19:37:04 - mmengine - INFO - Epoch(train) [932][10/63] lr: 1.8176e-03 eta: 5:35:07 time: 0.9735 data_time: 0.2069 memory: 16201 loss_prob: 0.3841 loss_thr: 0.2671 loss_db: 0.0692 loss: 0.7204 2022/08/30 19:37:08 - mmengine - INFO - Epoch(train) [932][15/63] lr: 1.8176e-03 eta: 5:35:07 time: 0.7875 data_time: 0.0258 memory: 16201 loss_prob: 0.3479 loss_thr: 0.2589 loss_db: 0.0625 loss: 0.6692 2022/08/30 19:37:12 - mmengine - INFO - Epoch(train) [932][20/63] lr: 1.8176e-03 eta: 5:34:54 time: 0.7864 data_time: 0.0166 memory: 16201 loss_prob: 0.3473 loss_thr: 0.2549 loss_db: 0.0607 loss: 0.6629 2022/08/30 19:37:17 - mmengine - INFO - Epoch(train) [932][25/63] lr: 1.8176e-03 eta: 5:34:54 time: 0.8583 data_time: 0.0415 memory: 16201 loss_prob: 0.3681 loss_thr: 0.2702 loss_db: 0.0666 loss: 0.7049 2022/08/30 19:37:21 - mmengine - INFO - Epoch(train) [932][30/63] lr: 1.8176e-03 eta: 5:34:41 time: 0.8603 data_time: 0.0414 memory: 16201 loss_prob: 0.3548 loss_thr: 0.2661 loss_db: 0.0641 loss: 0.6850 2022/08/30 19:37:25 - mmengine - INFO - Epoch(train) [932][35/63] lr: 1.8176e-03 eta: 5:34:41 time: 0.7975 data_time: 0.0212 memory: 16201 loss_prob: 0.3475 loss_thr: 0.2448 loss_db: 0.0606 loss: 0.6529 2022/08/30 19:37:29 - mmengine - INFO - Epoch(train) [932][40/63] lr: 1.8176e-03 eta: 5:34:28 time: 0.7873 data_time: 0.0230 memory: 16201 loss_prob: 0.4369 loss_thr: 0.2645 loss_db: 0.0741 loss: 0.7755 2022/08/30 19:37:33 - mmengine - INFO - Epoch(train) [932][45/63] lr: 1.8176e-03 eta: 5:34:28 time: 0.7850 data_time: 0.0248 memory: 16201 loss_prob: 0.4385 loss_thr: 0.2692 loss_db: 0.0764 loss: 0.7842 2022/08/30 19:37:37 - mmengine - INFO - Epoch(train) [932][50/63] lr: 1.8176e-03 eta: 5:34:15 time: 0.8640 data_time: 0.0315 memory: 16201 loss_prob: 0.3560 loss_thr: 0.2554 loss_db: 0.0650 loss: 0.6764 2022/08/30 19:37:41 - mmengine - INFO - Epoch(train) [932][55/63] lr: 1.8176e-03 eta: 5:34:15 time: 0.8701 data_time: 0.0293 memory: 16201 loss_prob: 0.3892 loss_thr: 0.2560 loss_db: 0.0663 loss: 0.7115 2022/08/30 19:37:45 - mmengine - INFO - Epoch(train) [932][60/63] lr: 1.8176e-03 eta: 5:34:03 time: 0.8119 data_time: 0.0213 memory: 16201 loss_prob: 0.3960 loss_thr: 0.2552 loss_db: 0.0671 loss: 0.7183 2022/08/30 19:37:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:37:53 - mmengine - INFO - Epoch(train) [933][5/63] lr: 1.8115e-03 eta: 5:34:03 time: 0.8881 data_time: 0.1315 memory: 16201 loss_prob: 0.3777 loss_thr: 0.2587 loss_db: 0.0644 loss: 0.7008 2022/08/30 19:37:57 - mmengine - INFO - Epoch(train) [933][10/63] lr: 1.8115e-03 eta: 5:33:45 time: 0.9356 data_time: 0.1389 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2424 loss_db: 0.0579 loss: 0.6467 2022/08/30 19:38:01 - mmengine - INFO - Epoch(train) [933][15/63] lr: 1.8115e-03 eta: 5:33:45 time: 0.8391 data_time: 0.0241 memory: 16201 loss_prob: 0.3329 loss_thr: 0.2507 loss_db: 0.0601 loss: 0.6437 2022/08/30 19:38:05 - mmengine - INFO - Epoch(train) [933][20/63] lr: 1.8115e-03 eta: 5:33:33 time: 0.8530 data_time: 0.0248 memory: 16201 loss_prob: 0.3561 loss_thr: 0.2636 loss_db: 0.0647 loss: 0.6843 2022/08/30 19:38:09 - mmengine - INFO - Epoch(train) [933][25/63] lr: 1.8115e-03 eta: 5:33:33 time: 0.8200 data_time: 0.0285 memory: 16201 loss_prob: 0.4046 loss_thr: 0.2814 loss_db: 0.0706 loss: 0.7566 2022/08/30 19:38:13 - mmengine - INFO - Epoch(train) [933][30/63] lr: 1.8115e-03 eta: 5:33:20 time: 0.7910 data_time: 0.0261 memory: 16201 loss_prob: 0.3937 loss_thr: 0.2672 loss_db: 0.0688 loss: 0.7297 2022/08/30 19:38:17 - mmengine - INFO - Epoch(train) [933][35/63] lr: 1.8115e-03 eta: 5:33:20 time: 0.7896 data_time: 0.0243 memory: 16201 loss_prob: 0.3509 loss_thr: 0.2482 loss_db: 0.0628 loss: 0.6619 2022/08/30 19:38:21 - mmengine - INFO - Epoch(train) [933][40/63] lr: 1.8115e-03 eta: 5:33:07 time: 0.8105 data_time: 0.0270 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2567 loss_db: 0.0628 loss: 0.6698 2022/08/30 19:38:25 - mmengine - INFO - Epoch(train) [933][45/63] lr: 1.8115e-03 eta: 5:33:07 time: 0.8034 data_time: 0.0275 memory: 16201 loss_prob: 0.3532 loss_thr: 0.2554 loss_db: 0.0622 loss: 0.6709 2022/08/30 19:38:30 - mmengine - INFO - Epoch(train) [933][50/63] lr: 1.8115e-03 eta: 5:32:54 time: 0.8239 data_time: 0.0192 memory: 16201 loss_prob: 0.3393 loss_thr: 0.2489 loss_db: 0.0590 loss: 0.6472 2022/08/30 19:38:34 - mmengine - INFO - Epoch(train) [933][55/63] lr: 1.8115e-03 eta: 5:32:54 time: 0.8765 data_time: 0.0273 memory: 16201 loss_prob: 0.3357 loss_thr: 0.2537 loss_db: 0.0589 loss: 0.6482 2022/08/30 19:38:38 - mmengine - INFO - Epoch(train) [933][60/63] lr: 1.8115e-03 eta: 5:32:41 time: 0.8396 data_time: 0.0317 memory: 16201 loss_prob: 0.3334 loss_thr: 0.2546 loss_db: 0.0588 loss: 0.6467 2022/08/30 19:38:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:38:46 - mmengine - INFO - Epoch(train) [934][5/63] lr: 1.8054e-03 eta: 5:32:41 time: 0.9264 data_time: 0.1858 memory: 16201 loss_prob: 0.3516 loss_thr: 0.2534 loss_db: 0.0644 loss: 0.6693 2022/08/30 19:38:50 - mmengine - INFO - Epoch(train) [934][10/63] lr: 1.8054e-03 eta: 5:32:24 time: 0.9602 data_time: 0.1898 memory: 16201 loss_prob: 0.3274 loss_thr: 0.2464 loss_db: 0.0592 loss: 0.6330 2022/08/30 19:38:54 - mmengine - INFO - Epoch(train) [934][15/63] lr: 1.8054e-03 eta: 5:32:24 time: 0.8424 data_time: 0.0257 memory: 16201 loss_prob: 0.3609 loss_thr: 0.2650 loss_db: 0.0630 loss: 0.6889 2022/08/30 19:38:58 - mmengine - INFO - Epoch(train) [934][20/63] lr: 1.8054e-03 eta: 5:32:11 time: 0.8448 data_time: 0.0230 memory: 16201 loss_prob: 0.3687 loss_thr: 0.2602 loss_db: 0.0645 loss: 0.6934 2022/08/30 19:39:02 - mmengine - INFO - Epoch(train) [934][25/63] lr: 1.8054e-03 eta: 5:32:11 time: 0.7924 data_time: 0.0266 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2536 loss_db: 0.0642 loss: 0.6798 2022/08/30 19:39:06 - mmengine - INFO - Epoch(train) [934][30/63] lr: 1.8054e-03 eta: 5:31:58 time: 0.7760 data_time: 0.0244 memory: 16201 loss_prob: 0.3828 loss_thr: 0.2669 loss_db: 0.0682 loss: 0.7179 2022/08/30 19:39:10 - mmengine - INFO - Epoch(train) [934][35/63] lr: 1.8054e-03 eta: 5:31:58 time: 0.7777 data_time: 0.0207 memory: 16201 loss_prob: 0.3764 loss_thr: 0.2750 loss_db: 0.0672 loss: 0.7187 2022/08/30 19:39:14 - mmengine - INFO - Epoch(train) [934][40/63] lr: 1.8054e-03 eta: 5:31:45 time: 0.8495 data_time: 0.0236 memory: 16201 loss_prob: 0.3700 loss_thr: 0.2765 loss_db: 0.0648 loss: 0.7113 2022/08/30 19:39:18 - mmengine - INFO - Epoch(train) [934][45/63] lr: 1.8054e-03 eta: 5:31:45 time: 0.8722 data_time: 0.0291 memory: 16201 loss_prob: 0.3750 loss_thr: 0.2737 loss_db: 0.0667 loss: 0.7153 2022/08/30 19:39:22 - mmengine - INFO - Epoch(train) [934][50/63] lr: 1.8054e-03 eta: 5:31:32 time: 0.8065 data_time: 0.0279 memory: 16201 loss_prob: 0.3674 loss_thr: 0.2774 loss_db: 0.0652 loss: 0.7100 2022/08/30 19:39:27 - mmengine - INFO - Epoch(train) [934][55/63] lr: 1.8054e-03 eta: 5:31:32 time: 0.8171 data_time: 0.0259 memory: 16201 loss_prob: 0.3534 loss_thr: 0.2527 loss_db: 0.0618 loss: 0.6679 2022/08/30 19:39:31 - mmengine - INFO - Epoch(train) [934][60/63] lr: 1.8054e-03 eta: 5:31:19 time: 0.8411 data_time: 0.0362 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2553 loss_db: 0.0673 loss: 0.6998 2022/08/30 19:39:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:39:39 - mmengine - INFO - Epoch(train) [935][5/63] lr: 1.7993e-03 eta: 5:31:19 time: 0.9431 data_time: 0.1991 memory: 16201 loss_prob: 0.3721 loss_thr: 0.2617 loss_db: 0.0652 loss: 0.6989 2022/08/30 19:39:43 - mmengine - INFO - Epoch(train) [935][10/63] lr: 1.7993e-03 eta: 5:31:02 time: 0.9796 data_time: 0.2084 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2627 loss_db: 0.0637 loss: 0.6851 2022/08/30 19:39:47 - mmengine - INFO - Epoch(train) [935][15/63] lr: 1.7993e-03 eta: 5:31:02 time: 0.8313 data_time: 0.0243 memory: 16201 loss_prob: 0.3786 loss_thr: 0.2805 loss_db: 0.0674 loss: 0.7265 2022/08/30 19:39:51 - mmengine - INFO - Epoch(train) [935][20/63] lr: 1.7993e-03 eta: 5:30:49 time: 0.8389 data_time: 0.0260 memory: 16201 loss_prob: 0.3957 loss_thr: 0.2920 loss_db: 0.0705 loss: 0.7582 2022/08/30 19:39:55 - mmengine - INFO - Epoch(train) [935][25/63] lr: 1.7993e-03 eta: 5:30:49 time: 0.8011 data_time: 0.0320 memory: 16201 loss_prob: 0.4022 loss_thr: 0.2930 loss_db: 0.0710 loss: 0.7663 2022/08/30 19:39:59 - mmengine - INFO - Epoch(train) [935][30/63] lr: 1.7993e-03 eta: 5:30:36 time: 0.7982 data_time: 0.0240 memory: 16201 loss_prob: 0.3890 loss_thr: 0.2827 loss_db: 0.0693 loss: 0.7410 2022/08/30 19:40:03 - mmengine - INFO - Epoch(train) [935][35/63] lr: 1.7993e-03 eta: 5:30:36 time: 0.8097 data_time: 0.0234 memory: 16201 loss_prob: 0.3229 loss_thr: 0.2433 loss_db: 0.0583 loss: 0.6245 2022/08/30 19:40:08 - mmengine - INFO - Epoch(train) [935][40/63] lr: 1.7993e-03 eta: 5:30:24 time: 0.8699 data_time: 0.0323 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2423 loss_db: 0.0594 loss: 0.6316 2022/08/30 19:40:12 - mmengine - INFO - Epoch(train) [935][45/63] lr: 1.7993e-03 eta: 5:30:24 time: 0.8752 data_time: 0.0355 memory: 16201 loss_prob: 0.3776 loss_thr: 0.2680 loss_db: 0.0664 loss: 0.7120 2022/08/30 19:40:16 - mmengine - INFO - Epoch(train) [935][50/63] lr: 1.7993e-03 eta: 5:30:11 time: 0.8085 data_time: 0.0237 memory: 16201 loss_prob: 0.3369 loss_thr: 0.2487 loss_db: 0.0586 loss: 0.6442 2022/08/30 19:40:20 - mmengine - INFO - Epoch(train) [935][55/63] lr: 1.7993e-03 eta: 5:30:11 time: 0.7901 data_time: 0.0215 memory: 16201 loss_prob: 0.3155 loss_thr: 0.2420 loss_db: 0.0574 loss: 0.6149 2022/08/30 19:40:25 - mmengine - INFO - Epoch(train) [935][60/63] lr: 1.7993e-03 eta: 5:29:58 time: 0.8715 data_time: 0.0253 memory: 16201 loss_prob: 0.3423 loss_thr: 0.2643 loss_db: 0.0614 loss: 0.6680 2022/08/30 19:40:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:40:32 - mmengine - INFO - Epoch(train) [936][5/63] lr: 1.7932e-03 eta: 5:29:58 time: 0.9729 data_time: 0.1590 memory: 16201 loss_prob: 0.3814 loss_thr: 0.2709 loss_db: 0.0680 loss: 0.7204 2022/08/30 19:40:36 - mmengine - INFO - Epoch(train) [936][10/63] lr: 1.7932e-03 eta: 5:29:41 time: 0.9398 data_time: 0.1660 memory: 16201 loss_prob: 0.3836 loss_thr: 0.2683 loss_db: 0.0685 loss: 0.7203 2022/08/30 19:40:40 - mmengine - INFO - Epoch(train) [936][15/63] lr: 1.7932e-03 eta: 5:29:41 time: 0.7956 data_time: 0.0232 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2574 loss_db: 0.0633 loss: 0.6738 2022/08/30 19:40:44 - mmengine - INFO - Epoch(train) [936][20/63] lr: 1.7932e-03 eta: 5:29:28 time: 0.8271 data_time: 0.0242 memory: 16201 loss_prob: 0.3560 loss_thr: 0.2574 loss_db: 0.0636 loss: 0.6770 2022/08/30 19:40:48 - mmengine - INFO - Epoch(train) [936][25/63] lr: 1.7932e-03 eta: 5:29:28 time: 0.8256 data_time: 0.0303 memory: 16201 loss_prob: 0.3602 loss_thr: 0.2573 loss_db: 0.0640 loss: 0.6816 2022/08/30 19:40:52 - mmengine - INFO - Epoch(train) [936][30/63] lr: 1.7932e-03 eta: 5:29:15 time: 0.7920 data_time: 0.0256 memory: 16201 loss_prob: 0.3860 loss_thr: 0.2679 loss_db: 0.0676 loss: 0.7215 2022/08/30 19:40:56 - mmengine - INFO - Epoch(train) [936][35/63] lr: 1.7932e-03 eta: 5:29:15 time: 0.7977 data_time: 0.0261 memory: 16201 loss_prob: 0.3960 loss_thr: 0.2847 loss_db: 0.0693 loss: 0.7501 2022/08/30 19:41:00 - mmengine - INFO - Epoch(train) [936][40/63] lr: 1.7932e-03 eta: 5:29:02 time: 0.7945 data_time: 0.0227 memory: 16201 loss_prob: 0.3605 loss_thr: 0.2711 loss_db: 0.0647 loss: 0.6963 2022/08/30 19:41:04 - mmengine - INFO - Epoch(train) [936][45/63] lr: 1.7932e-03 eta: 5:29:02 time: 0.8304 data_time: 0.0258 memory: 16201 loss_prob: 0.3706 loss_thr: 0.2572 loss_db: 0.0643 loss: 0.6921 2022/08/30 19:41:08 - mmengine - INFO - Epoch(train) [936][50/63] lr: 1.7932e-03 eta: 5:28:49 time: 0.8266 data_time: 0.0303 memory: 16201 loss_prob: 0.3865 loss_thr: 0.2583 loss_db: 0.0665 loss: 0.7113 2022/08/30 19:41:12 - mmengine - INFO - Epoch(train) [936][55/63] lr: 1.7932e-03 eta: 5:28:49 time: 0.7892 data_time: 0.0257 memory: 16201 loss_prob: 0.3412 loss_thr: 0.2429 loss_db: 0.0610 loss: 0.6451 2022/08/30 19:41:17 - mmengine - INFO - Epoch(train) [936][60/63] lr: 1.7932e-03 eta: 5:28:36 time: 0.8287 data_time: 0.0238 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2437 loss_db: 0.0592 loss: 0.6376 2022/08/30 19:41:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:41:24 - mmengine - INFO - Epoch(train) [937][5/63] lr: 1.7871e-03 eta: 5:28:36 time: 0.9172 data_time: 0.1754 memory: 16201 loss_prob: 0.3664 loss_thr: 0.2745 loss_db: 0.0659 loss: 0.7069 2022/08/30 19:41:28 - mmengine - INFO - Epoch(train) [937][10/63] lr: 1.7871e-03 eta: 5:28:19 time: 0.9732 data_time: 0.1876 memory: 16201 loss_prob: 0.3661 loss_thr: 0.2759 loss_db: 0.0660 loss: 0.7079 2022/08/30 19:41:32 - mmengine - INFO - Epoch(train) [937][15/63] lr: 1.7871e-03 eta: 5:28:19 time: 0.7891 data_time: 0.0237 memory: 16201 loss_prob: 0.3558 loss_thr: 0.2603 loss_db: 0.0636 loss: 0.6797 2022/08/30 19:41:37 - mmengine - INFO - Epoch(train) [937][20/63] lr: 1.7871e-03 eta: 5:28:07 time: 0.8418 data_time: 0.0223 memory: 16201 loss_prob: 0.3551 loss_thr: 0.2585 loss_db: 0.0620 loss: 0.6756 2022/08/30 19:41:41 - mmengine - INFO - Epoch(train) [937][25/63] lr: 1.7871e-03 eta: 5:28:07 time: 0.8669 data_time: 0.0318 memory: 16201 loss_prob: 0.3931 loss_thr: 0.2861 loss_db: 0.0691 loss: 0.7484 2022/08/30 19:41:45 - mmengine - INFO - Epoch(train) [937][30/63] lr: 1.7871e-03 eta: 5:27:54 time: 0.8109 data_time: 0.0224 memory: 16201 loss_prob: 0.3864 loss_thr: 0.2699 loss_db: 0.0699 loss: 0.7263 2022/08/30 19:41:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:41:49 - mmengine - INFO - Epoch(train) [937][35/63] lr: 1.7871e-03 eta: 5:27:54 time: 0.8173 data_time: 0.0235 memory: 16201 loss_prob: 0.3821 loss_thr: 0.2659 loss_db: 0.0676 loss: 0.7155 2022/08/30 19:41:53 - mmengine - INFO - Epoch(train) [937][40/63] lr: 1.7871e-03 eta: 5:27:41 time: 0.8016 data_time: 0.0235 memory: 16201 loss_prob: 0.4131 loss_thr: 0.2805 loss_db: 0.0695 loss: 0.7631 2022/08/30 19:41:57 - mmengine - INFO - Epoch(train) [937][45/63] lr: 1.7871e-03 eta: 5:27:41 time: 0.8040 data_time: 0.0242 memory: 16201 loss_prob: 0.4127 loss_thr: 0.2818 loss_db: 0.0700 loss: 0.7644 2022/08/30 19:42:01 - mmengine - INFO - Epoch(train) [937][50/63] lr: 1.7871e-03 eta: 5:27:28 time: 0.8170 data_time: 0.0294 memory: 16201 loss_prob: 0.3663 loss_thr: 0.2609 loss_db: 0.0646 loss: 0.6917 2022/08/30 19:42:05 - mmengine - INFO - Epoch(train) [937][55/63] lr: 1.7871e-03 eta: 5:27:28 time: 0.8107 data_time: 0.0249 memory: 16201 loss_prob: 0.3039 loss_thr: 0.2291 loss_db: 0.0547 loss: 0.5876 2022/08/30 19:42:09 - mmengine - INFO - Epoch(train) [937][60/63] lr: 1.7871e-03 eta: 5:27:15 time: 0.8123 data_time: 0.0268 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2467 loss_db: 0.0588 loss: 0.6295 2022/08/30 19:42:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:42:17 - mmengine - INFO - Epoch(train) [938][5/63] lr: 1.7809e-03 eta: 5:27:15 time: 0.9087 data_time: 0.1773 memory: 16201 loss_prob: 0.3772 loss_thr: 0.2678 loss_db: 0.0663 loss: 0.7113 2022/08/30 19:42:21 - mmengine - INFO - Epoch(train) [938][10/63] lr: 1.7809e-03 eta: 5:26:58 time: 0.9800 data_time: 0.1940 memory: 16201 loss_prob: 0.3414 loss_thr: 0.2490 loss_db: 0.0604 loss: 0.6508 2022/08/30 19:42:25 - mmengine - INFO - Epoch(train) [938][15/63] lr: 1.7809e-03 eta: 5:26:58 time: 0.8301 data_time: 0.0239 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2512 loss_db: 0.0602 loss: 0.6440 2022/08/30 19:42:29 - mmengine - INFO - Epoch(train) [938][20/63] lr: 1.7809e-03 eta: 5:26:45 time: 0.8113 data_time: 0.0159 memory: 16201 loss_prob: 0.3317 loss_thr: 0.2436 loss_db: 0.0597 loss: 0.6350 2022/08/30 19:42:33 - mmengine - INFO - Epoch(train) [938][25/63] lr: 1.7809e-03 eta: 5:26:45 time: 0.7961 data_time: 0.0298 memory: 16201 loss_prob: 0.3280 loss_thr: 0.2337 loss_db: 0.0582 loss: 0.6199 2022/08/30 19:42:37 - mmengine - INFO - Epoch(train) [938][30/63] lr: 1.7809e-03 eta: 5:26:32 time: 0.8043 data_time: 0.0237 memory: 16201 loss_prob: 0.3588 loss_thr: 0.2463 loss_db: 0.0623 loss: 0.6675 2022/08/30 19:42:41 - mmengine - INFO - Epoch(train) [938][35/63] lr: 1.7809e-03 eta: 5:26:32 time: 0.8120 data_time: 0.0207 memory: 16201 loss_prob: 0.3875 loss_thr: 0.2690 loss_db: 0.0671 loss: 0.7236 2022/08/30 19:42:45 - mmengine - INFO - Epoch(train) [938][40/63] lr: 1.7809e-03 eta: 5:26:19 time: 0.8185 data_time: 0.0256 memory: 16201 loss_prob: 0.4456 loss_thr: 0.2979 loss_db: 0.0770 loss: 0.8205 2022/08/30 19:42:49 - mmengine - INFO - Epoch(train) [938][45/63] lr: 1.7809e-03 eta: 5:26:19 time: 0.8078 data_time: 0.0253 memory: 16201 loss_prob: 0.3996 loss_thr: 0.2710 loss_db: 0.0694 loss: 0.7399 2022/08/30 19:42:53 - mmengine - INFO - Epoch(train) [938][50/63] lr: 1.7809e-03 eta: 5:26:06 time: 0.8033 data_time: 0.0268 memory: 16201 loss_prob: 0.3233 loss_thr: 0.2406 loss_db: 0.0580 loss: 0.6219 2022/08/30 19:42:57 - mmengine - INFO - Epoch(train) [938][55/63] lr: 1.7809e-03 eta: 5:26:06 time: 0.7930 data_time: 0.0216 memory: 16201 loss_prob: 0.3556 loss_thr: 0.2576 loss_db: 0.0619 loss: 0.6751 2022/08/30 19:43:01 - mmengine - INFO - Epoch(train) [938][60/63] lr: 1.7809e-03 eta: 5:25:53 time: 0.7754 data_time: 0.0215 memory: 16201 loss_prob: 0.3517 loss_thr: 0.2564 loss_db: 0.0613 loss: 0.6694 2022/08/30 19:43:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:43:10 - mmengine - INFO - Epoch(train) [939][5/63] lr: 1.7748e-03 eta: 5:25:53 time: 0.9903 data_time: 0.2493 memory: 16201 loss_prob: 0.3334 loss_thr: 0.2402 loss_db: 0.0604 loss: 0.6340 2022/08/30 19:43:13 - mmengine - INFO - Epoch(train) [939][10/63] lr: 1.7748e-03 eta: 5:25:37 time: 1.0366 data_time: 0.2608 memory: 16201 loss_prob: 0.3736 loss_thr: 0.2627 loss_db: 0.0670 loss: 0.7033 2022/08/30 19:43:18 - mmengine - INFO - Epoch(train) [939][15/63] lr: 1.7748e-03 eta: 5:25:37 time: 0.8342 data_time: 0.0245 memory: 16201 loss_prob: 0.3762 loss_thr: 0.2699 loss_db: 0.0676 loss: 0.7136 2022/08/30 19:43:22 - mmengine - INFO - Epoch(train) [939][20/63] lr: 1.7748e-03 eta: 5:25:24 time: 0.8389 data_time: 0.0201 memory: 16201 loss_prob: 0.3487 loss_thr: 0.2462 loss_db: 0.0624 loss: 0.6572 2022/08/30 19:43:26 - mmengine - INFO - Epoch(train) [939][25/63] lr: 1.7748e-03 eta: 5:25:24 time: 0.8043 data_time: 0.0295 memory: 16201 loss_prob: 0.3389 loss_thr: 0.2383 loss_db: 0.0606 loss: 0.6378 2022/08/30 19:43:30 - mmengine - INFO - Epoch(train) [939][30/63] lr: 1.7748e-03 eta: 5:25:11 time: 0.8063 data_time: 0.0249 memory: 16201 loss_prob: 0.3550 loss_thr: 0.2632 loss_db: 0.0645 loss: 0.6828 2022/08/30 19:43:34 - mmengine - INFO - Epoch(train) [939][35/63] lr: 1.7748e-03 eta: 5:25:11 time: 0.8100 data_time: 0.0191 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2644 loss_db: 0.0635 loss: 0.6767 2022/08/30 19:43:38 - mmengine - INFO - Epoch(train) [939][40/63] lr: 1.7748e-03 eta: 5:24:58 time: 0.8149 data_time: 0.0252 memory: 16201 loss_prob: 0.3486 loss_thr: 0.2561 loss_db: 0.0619 loss: 0.6667 2022/08/30 19:43:42 - mmengine - INFO - Epoch(train) [939][45/63] lr: 1.7748e-03 eta: 5:24:58 time: 0.7848 data_time: 0.0263 memory: 16201 loss_prob: 0.3785 loss_thr: 0.2686 loss_db: 0.0662 loss: 0.7133 2022/08/30 19:43:46 - mmengine - INFO - Epoch(train) [939][50/63] lr: 1.7748e-03 eta: 5:24:45 time: 0.8177 data_time: 0.0278 memory: 16201 loss_prob: 0.4073 loss_thr: 0.2857 loss_db: 0.0725 loss: 0.7655 2022/08/30 19:43:50 - mmengine - INFO - Epoch(train) [939][55/63] lr: 1.7748e-03 eta: 5:24:45 time: 0.8313 data_time: 0.0257 memory: 16201 loss_prob: 0.4121 loss_thr: 0.2853 loss_db: 0.0735 loss: 0.7708 2022/08/30 19:43:54 - mmengine - INFO - Epoch(train) [939][60/63] lr: 1.7748e-03 eta: 5:24:32 time: 0.8129 data_time: 0.0235 memory: 16201 loss_prob: 0.3713 loss_thr: 0.2636 loss_db: 0.0645 loss: 0.6995 2022/08/30 19:43:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:44:03 - mmengine - INFO - Epoch(train) [940][5/63] lr: 1.7687e-03 eta: 5:24:32 time: 0.9975 data_time: 0.2149 memory: 16201 loss_prob: 0.3416 loss_thr: 0.2428 loss_db: 0.0610 loss: 0.6453 2022/08/30 19:44:07 - mmengine - INFO - Epoch(train) [940][10/63] lr: 1.7687e-03 eta: 5:24:15 time: 1.0242 data_time: 0.2244 memory: 16201 loss_prob: 0.3492 loss_thr: 0.2530 loss_db: 0.0638 loss: 0.6660 2022/08/30 19:44:10 - mmengine - INFO - Epoch(train) [940][15/63] lr: 1.7687e-03 eta: 5:24:15 time: 0.7990 data_time: 0.0258 memory: 16201 loss_prob: 0.3711 loss_thr: 0.2621 loss_db: 0.0645 loss: 0.6977 2022/08/30 19:44:15 - mmengine - INFO - Epoch(train) [940][20/63] lr: 1.7687e-03 eta: 5:24:03 time: 0.8818 data_time: 0.0221 memory: 16201 loss_prob: 0.4086 loss_thr: 0.2674 loss_db: 0.0670 loss: 0.7430 2022/08/30 19:44:19 - mmengine - INFO - Epoch(train) [940][25/63] lr: 1.7687e-03 eta: 5:24:03 time: 0.8860 data_time: 0.0287 memory: 16201 loss_prob: 0.4272 loss_thr: 0.2802 loss_db: 0.0722 loss: 0.7795 2022/08/30 19:44:23 - mmengine - INFO - Epoch(train) [940][30/63] lr: 1.7687e-03 eta: 5:23:50 time: 0.7964 data_time: 0.0255 memory: 16201 loss_prob: 0.4000 loss_thr: 0.2868 loss_db: 0.0709 loss: 0.7577 2022/08/30 19:44:27 - mmengine - INFO - Epoch(train) [940][35/63] lr: 1.7687e-03 eta: 5:23:50 time: 0.8008 data_time: 0.0235 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2686 loss_db: 0.0632 loss: 0.6891 2022/08/30 19:44:31 - mmengine - INFO - Epoch(train) [940][40/63] lr: 1.7687e-03 eta: 5:23:37 time: 0.8103 data_time: 0.0240 memory: 16201 loss_prob: 0.3271 loss_thr: 0.2421 loss_db: 0.0585 loss: 0.6277 2022/08/30 19:44:35 - mmengine - INFO - Epoch(train) [940][45/63] lr: 1.7687e-03 eta: 5:23:37 time: 0.7972 data_time: 0.0246 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2461 loss_db: 0.0589 loss: 0.6375 2022/08/30 19:44:39 - mmengine - INFO - Epoch(train) [940][50/63] lr: 1.7687e-03 eta: 5:23:24 time: 0.7743 data_time: 0.0271 memory: 16201 loss_prob: 0.3546 loss_thr: 0.2596 loss_db: 0.0618 loss: 0.6760 2022/08/30 19:44:43 - mmengine - INFO - Epoch(train) [940][55/63] lr: 1.7687e-03 eta: 5:23:24 time: 0.7700 data_time: 0.0243 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2650 loss_db: 0.0682 loss: 0.7100 2022/08/30 19:44:47 - mmengine - INFO - Epoch(train) [940][60/63] lr: 1.7687e-03 eta: 5:23:11 time: 0.8064 data_time: 0.0283 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2468 loss_db: 0.0654 loss: 0.6685 2022/08/30 19:44:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:44:49 - mmengine - INFO - Saving checkpoint at 940 epochs 2022/08/30 19:44:57 - mmengine - INFO - Epoch(val) [940][5/32] eta: 5:23:11 time: 0.5974 data_time: 0.0918 memory: 16201 2022/08/30 19:44:59 - mmengine - INFO - Epoch(val) [940][10/32] eta: 0:00:14 time: 0.6498 data_time: 0.1000 memory: 15734 2022/08/30 19:45:02 - mmengine - INFO - Epoch(val) [940][15/32] eta: 0:00:14 time: 0.5951 data_time: 0.0474 memory: 15734 2022/08/30 19:45:06 - mmengine - INFO - Epoch(val) [940][20/32] eta: 0:00:08 time: 0.6669 data_time: 0.0629 memory: 15734 2022/08/30 19:45:09 - mmengine - INFO - Epoch(val) [940][25/32] eta: 0:00:08 time: 0.6710 data_time: 0.0609 memory: 15734 2022/08/30 19:45:12 - mmengine - INFO - Epoch(val) [940][30/32] eta: 0:00:01 time: 0.6068 data_time: 0.0388 memory: 15734 2022/08/30 19:45:13 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 19:45:13 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8334, precision: 0.8096, hmean: 0.8214 2022/08/30 19:45:13 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8334, precision: 0.8395, hmean: 0.8364 2022/08/30 19:45:13 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8329, precision: 0.8628, hmean: 0.8476 2022/08/30 19:45:13 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8305, precision: 0.8801, hmean: 0.8546 2022/08/30 19:45:13 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8204, precision: 0.8954, hmean: 0.8563 2022/08/30 19:45:13 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7901, precision: 0.9152, hmean: 0.8481 2022/08/30 19:45:13 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4064, precision: 0.9580, hmean: 0.5707 2022/08/30 19:45:13 - mmengine - INFO - Epoch(val) [940][32/32] icdar/precision: 0.8954 icdar/recall: 0.8204 icdar/hmean: 0.8563 2022/08/30 19:45:19 - mmengine - INFO - Epoch(train) [941][5/63] lr: 1.7626e-03 eta: 0:00:01 time: 0.9453 data_time: 0.1950 memory: 16201 loss_prob: 0.3817 loss_thr: 0.2566 loss_db: 0.0645 loss: 0.7027 2022/08/30 19:45:23 - mmengine - INFO - Epoch(train) [941][10/63] lr: 1.7626e-03 eta: 5:22:54 time: 0.9953 data_time: 0.2042 memory: 16201 loss_prob: 0.3926 loss_thr: 0.2758 loss_db: 0.0678 loss: 0.7362 2022/08/30 19:45:27 - mmengine - INFO - Epoch(train) [941][15/63] lr: 1.7626e-03 eta: 5:22:54 time: 0.7841 data_time: 0.0274 memory: 16201 loss_prob: 0.3935 loss_thr: 0.2683 loss_db: 0.0680 loss: 0.7298 2022/08/30 19:45:31 - mmengine - INFO - Epoch(train) [941][20/63] lr: 1.7626e-03 eta: 5:22:41 time: 0.7986 data_time: 0.0297 memory: 16201 loss_prob: 0.3891 loss_thr: 0.2651 loss_db: 0.0670 loss: 0.7211 2022/08/30 19:45:35 - mmengine - INFO - Epoch(train) [941][25/63] lr: 1.7626e-03 eta: 5:22:41 time: 0.7898 data_time: 0.0217 memory: 16201 loss_prob: 0.3901 loss_thr: 0.2800 loss_db: 0.0698 loss: 0.7399 2022/08/30 19:45:39 - mmengine - INFO - Epoch(train) [941][30/63] lr: 1.7626e-03 eta: 5:22:28 time: 0.7862 data_time: 0.0229 memory: 16201 loss_prob: 0.3844 loss_thr: 0.2791 loss_db: 0.0676 loss: 0.7311 2022/08/30 19:45:43 - mmengine - INFO - Epoch(train) [941][35/63] lr: 1.7626e-03 eta: 5:22:28 time: 0.7970 data_time: 0.0322 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2777 loss_db: 0.0652 loss: 0.7209 2022/08/30 19:45:48 - mmengine - INFO - Epoch(train) [941][40/63] lr: 1.7626e-03 eta: 5:22:16 time: 0.8746 data_time: 0.0245 memory: 16201 loss_prob: 0.3448 loss_thr: 0.2564 loss_db: 0.0612 loss: 0.6624 2022/08/30 19:45:52 - mmengine - INFO - Epoch(train) [941][45/63] lr: 1.7626e-03 eta: 5:22:16 time: 0.8826 data_time: 0.0291 memory: 16201 loss_prob: 0.3556 loss_thr: 0.2568 loss_db: 0.0631 loss: 0.6756 2022/08/30 19:45:56 - mmengine - INFO - Epoch(train) [941][50/63] lr: 1.7626e-03 eta: 5:22:03 time: 0.8123 data_time: 0.0373 memory: 16201 loss_prob: 0.3552 loss_thr: 0.2538 loss_db: 0.0633 loss: 0.6723 2022/08/30 19:46:00 - mmengine - INFO - Epoch(train) [941][55/63] lr: 1.7626e-03 eta: 5:22:03 time: 0.7898 data_time: 0.0222 memory: 16201 loss_prob: 0.3448 loss_thr: 0.2623 loss_db: 0.0613 loss: 0.6685 2022/08/30 19:46:04 - mmengine - INFO - Epoch(train) [941][60/63] lr: 1.7626e-03 eta: 5:21:50 time: 0.7819 data_time: 0.0195 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2800 loss_db: 0.0677 loss: 0.7237 2022/08/30 19:46:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:46:12 - mmengine - INFO - Epoch(train) [942][5/63] lr: 1.7565e-03 eta: 5:21:50 time: 1.0006 data_time: 0.1982 memory: 16201 loss_prob: 0.3627 loss_thr: 0.2555 loss_db: 0.0669 loss: 0.6851 2022/08/30 19:46:16 - mmengine - INFO - Epoch(train) [942][10/63] lr: 1.7565e-03 eta: 5:21:33 time: 0.9935 data_time: 0.2141 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2709 loss_db: 0.0677 loss: 0.7238 2022/08/30 19:46:20 - mmengine - INFO - Epoch(train) [942][15/63] lr: 1.7565e-03 eta: 5:21:33 time: 0.7980 data_time: 0.0281 memory: 16201 loss_prob: 0.3685 loss_thr: 0.2568 loss_db: 0.0633 loss: 0.6885 2022/08/30 19:46:25 - mmengine - INFO - Epoch(train) [942][20/63] lr: 1.7565e-03 eta: 5:21:20 time: 0.8482 data_time: 0.0220 memory: 16201 loss_prob: 0.3586 loss_thr: 0.2511 loss_db: 0.0635 loss: 0.6733 2022/08/30 19:46:29 - mmengine - INFO - Epoch(train) [942][25/63] lr: 1.7565e-03 eta: 5:21:20 time: 0.9030 data_time: 0.0339 memory: 16201 loss_prob: 0.3719 loss_thr: 0.2626 loss_db: 0.0668 loss: 0.7013 2022/08/30 19:46:33 - mmengine - INFO - Epoch(train) [942][30/63] lr: 1.7565e-03 eta: 5:21:07 time: 0.8357 data_time: 0.0285 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2557 loss_db: 0.0643 loss: 0.6794 2022/08/30 19:46:37 - mmengine - INFO - Epoch(train) [942][35/63] lr: 1.7565e-03 eta: 5:21:07 time: 0.7896 data_time: 0.0200 memory: 16201 loss_prob: 0.3580 loss_thr: 0.2432 loss_db: 0.0630 loss: 0.6643 2022/08/30 19:46:42 - mmengine - INFO - Epoch(train) [942][40/63] lr: 1.7565e-03 eta: 5:20:55 time: 0.8809 data_time: 0.0261 memory: 16201 loss_prob: 0.3805 loss_thr: 0.2591 loss_db: 0.0671 loss: 0.7068 2022/08/30 19:46:46 - mmengine - INFO - Epoch(train) [942][45/63] lr: 1.7565e-03 eta: 5:20:55 time: 0.8928 data_time: 0.0314 memory: 16201 loss_prob: 0.3538 loss_thr: 0.2480 loss_db: 0.0630 loss: 0.6648 2022/08/30 19:46:50 - mmengine - INFO - Epoch(train) [942][50/63] lr: 1.7565e-03 eta: 5:20:42 time: 0.8065 data_time: 0.0272 memory: 16201 loss_prob: 0.3341 loss_thr: 0.2351 loss_db: 0.0593 loss: 0.6285 2022/08/30 19:46:54 - mmengine - INFO - Epoch(train) [942][55/63] lr: 1.7565e-03 eta: 5:20:42 time: 0.8054 data_time: 0.0229 memory: 16201 loss_prob: 0.3407 loss_thr: 0.2454 loss_db: 0.0617 loss: 0.6479 2022/08/30 19:46:58 - mmengine - INFO - Epoch(train) [942][60/63] lr: 1.7565e-03 eta: 5:20:29 time: 0.8449 data_time: 0.0466 memory: 16201 loss_prob: 0.3503 loss_thr: 0.2492 loss_db: 0.0625 loss: 0.6621 2022/08/30 19:47:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:47:06 - mmengine - INFO - Epoch(train) [943][5/63] lr: 1.7503e-03 eta: 5:20:29 time: 0.8981 data_time: 0.1604 memory: 16201 loss_prob: 0.3463 loss_thr: 0.2507 loss_db: 0.0602 loss: 0.6571 2022/08/30 19:47:10 - mmengine - INFO - Epoch(train) [943][10/63] lr: 1.7503e-03 eta: 5:20:12 time: 0.9538 data_time: 0.1746 memory: 16201 loss_prob: 0.4054 loss_thr: 0.2835 loss_db: 0.0729 loss: 0.7618 2022/08/30 19:47:14 - mmengine - INFO - Epoch(train) [943][15/63] lr: 1.7503e-03 eta: 5:20:12 time: 0.8070 data_time: 0.0275 memory: 16201 loss_prob: 0.4106 loss_thr: 0.2862 loss_db: 0.0732 loss: 0.7700 2022/08/30 19:47:19 - mmengine - INFO - Epoch(train) [943][20/63] lr: 1.7503e-03 eta: 5:20:00 time: 0.8859 data_time: 0.0244 memory: 16201 loss_prob: 0.3591 loss_thr: 0.2591 loss_db: 0.0653 loss: 0.6835 2022/08/30 19:47:23 - mmengine - INFO - Epoch(train) [943][25/63] lr: 1.7503e-03 eta: 5:20:00 time: 0.8891 data_time: 0.0394 memory: 16201 loss_prob: 0.3510 loss_thr: 0.2490 loss_db: 0.0639 loss: 0.6639 2022/08/30 19:47:27 - mmengine - INFO - Epoch(train) [943][30/63] lr: 1.7503e-03 eta: 5:19:47 time: 0.7988 data_time: 0.0265 memory: 16201 loss_prob: 0.3301 loss_thr: 0.2457 loss_db: 0.0577 loss: 0.6334 2022/08/30 19:47:31 - mmengine - INFO - Epoch(train) [943][35/63] lr: 1.7503e-03 eta: 5:19:47 time: 0.7943 data_time: 0.0196 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2462 loss_db: 0.0564 loss: 0.6236 2022/08/30 19:47:35 - mmengine - INFO - Epoch(train) [943][40/63] lr: 1.7503e-03 eta: 5:19:34 time: 0.8747 data_time: 0.0310 memory: 16201 loss_prob: 0.3486 loss_thr: 0.2496 loss_db: 0.0627 loss: 0.6609 2022/08/30 19:47:39 - mmengine - INFO - Epoch(train) [943][45/63] lr: 1.7503e-03 eta: 5:19:34 time: 0.8664 data_time: 0.0302 memory: 16201 loss_prob: 0.3782 loss_thr: 0.2649 loss_db: 0.0678 loss: 0.7110 2022/08/30 19:47:43 - mmengine - INFO - Epoch(train) [943][50/63] lr: 1.7503e-03 eta: 5:19:21 time: 0.7786 data_time: 0.0255 memory: 16201 loss_prob: 0.3603 loss_thr: 0.2592 loss_db: 0.0644 loss: 0.6840 2022/08/30 19:47:48 - mmengine - INFO - Epoch(train) [943][55/63] lr: 1.7503e-03 eta: 5:19:21 time: 0.8254 data_time: 0.0325 memory: 16201 loss_prob: 0.3719 loss_thr: 0.2604 loss_db: 0.0656 loss: 0.6979 2022/08/30 19:47:51 - mmengine - INFO - Epoch(train) [943][60/63] lr: 1.7503e-03 eta: 5:19:08 time: 0.8248 data_time: 0.0313 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2632 loss_db: 0.0672 loss: 0.7087 2022/08/30 19:47:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:48:00 - mmengine - INFO - Epoch(train) [944][5/63] lr: 1.7442e-03 eta: 5:19:08 time: 0.9598 data_time: 0.2024 memory: 16201 loss_prob: 0.3242 loss_thr: 0.2315 loss_db: 0.0579 loss: 0.6136 2022/08/30 19:48:04 - mmengine - INFO - Epoch(train) [944][10/63] lr: 1.7442e-03 eta: 5:18:52 time: 1.0236 data_time: 0.2184 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2440 loss_db: 0.0594 loss: 0.6387 2022/08/30 19:48:08 - mmengine - INFO - Epoch(train) [944][15/63] lr: 1.7442e-03 eta: 5:18:52 time: 0.8478 data_time: 0.0244 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2507 loss_db: 0.0619 loss: 0.6614 2022/08/30 19:48:12 - mmengine - INFO - Epoch(train) [944][20/63] lr: 1.7442e-03 eta: 5:18:39 time: 0.8310 data_time: 0.0165 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2381 loss_db: 0.0576 loss: 0.6260 2022/08/30 19:48:16 - mmengine - INFO - Epoch(train) [944][25/63] lr: 1.7442e-03 eta: 5:18:39 time: 0.8176 data_time: 0.0358 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2403 loss_db: 0.0618 loss: 0.6607 2022/08/30 19:48:20 - mmengine - INFO - Epoch(train) [944][30/63] lr: 1.7442e-03 eta: 5:18:26 time: 0.8080 data_time: 0.0304 memory: 16201 loss_prob: 0.3997 loss_thr: 0.2583 loss_db: 0.0696 loss: 0.7276 2022/08/30 19:48:24 - mmengine - INFO - Epoch(train) [944][35/63] lr: 1.7442e-03 eta: 5:18:26 time: 0.7708 data_time: 0.0191 memory: 16201 loss_prob: 0.3917 loss_thr: 0.2724 loss_db: 0.0698 loss: 0.7339 2022/08/30 19:48:28 - mmengine - INFO - Epoch(train) [944][40/63] lr: 1.7442e-03 eta: 5:18:13 time: 0.7939 data_time: 0.0242 memory: 16201 loss_prob: 0.3996 loss_thr: 0.2759 loss_db: 0.0706 loss: 0.7461 2022/08/30 19:48:32 - mmengine - INFO - Epoch(train) [944][45/63] lr: 1.7442e-03 eta: 5:18:13 time: 0.7889 data_time: 0.0225 memory: 16201 loss_prob: 0.3864 loss_thr: 0.2596 loss_db: 0.0685 loss: 0.7145 2022/08/30 19:48:36 - mmengine - INFO - Epoch(train) [944][50/63] lr: 1.7442e-03 eta: 5:18:00 time: 0.8389 data_time: 0.0356 memory: 16201 loss_prob: 0.3501 loss_thr: 0.2386 loss_db: 0.0629 loss: 0.6517 2022/08/30 19:48:40 - mmengine - INFO - Epoch(train) [944][55/63] lr: 1.7442e-03 eta: 5:18:00 time: 0.8405 data_time: 0.0369 memory: 16201 loss_prob: 0.3485 loss_thr: 0.2475 loss_db: 0.0617 loss: 0.6577 2022/08/30 19:48:45 - mmengine - INFO - Epoch(train) [944][60/63] lr: 1.7442e-03 eta: 5:17:48 time: 0.8332 data_time: 0.0243 memory: 16201 loss_prob: 0.4123 loss_thr: 0.2724 loss_db: 0.0705 loss: 0.7551 2022/08/30 19:48:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:48:53 - mmengine - INFO - Epoch(train) [945][5/63] lr: 1.7381e-03 eta: 5:17:48 time: 1.0080 data_time: 0.2077 memory: 16201 loss_prob: 0.3721 loss_thr: 0.2578 loss_db: 0.0645 loss: 0.6944 2022/08/30 19:48:57 - mmengine - INFO - Epoch(train) [945][10/63] lr: 1.7381e-03 eta: 5:17:31 time: 0.9936 data_time: 0.2184 memory: 16201 loss_prob: 0.3605 loss_thr: 0.2524 loss_db: 0.0627 loss: 0.6756 2022/08/30 19:49:00 - mmengine - INFO - Epoch(train) [945][15/63] lr: 1.7381e-03 eta: 5:17:31 time: 0.7708 data_time: 0.0233 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2536 loss_db: 0.0615 loss: 0.6585 2022/08/30 19:49:05 - mmengine - INFO - Epoch(train) [945][20/63] lr: 1.7381e-03 eta: 5:17:18 time: 0.8144 data_time: 0.0190 memory: 16201 loss_prob: 0.3165 loss_thr: 0.2290 loss_db: 0.0562 loss: 0.6017 2022/08/30 19:49:09 - mmengine - INFO - Epoch(train) [945][25/63] lr: 1.7381e-03 eta: 5:17:18 time: 0.8630 data_time: 0.0371 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2323 loss_db: 0.0596 loss: 0.6282 2022/08/30 19:49:13 - mmengine - INFO - Epoch(train) [945][30/63] lr: 1.7381e-03 eta: 5:17:05 time: 0.8109 data_time: 0.0283 memory: 16201 loss_prob: 0.3955 loss_thr: 0.2651 loss_db: 0.0695 loss: 0.7301 2022/08/30 19:49:17 - mmengine - INFO - Epoch(train) [945][35/63] lr: 1.7381e-03 eta: 5:17:05 time: 0.7744 data_time: 0.0178 memory: 16201 loss_prob: 0.3999 loss_thr: 0.2729 loss_db: 0.0703 loss: 0.7431 2022/08/30 19:49:21 - mmengine - INFO - Epoch(train) [945][40/63] lr: 1.7381e-03 eta: 5:16:52 time: 0.7851 data_time: 0.0236 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2552 loss_db: 0.0620 loss: 0.6660 2022/08/30 19:49:25 - mmengine - INFO - Epoch(train) [945][45/63] lr: 1.7381e-03 eta: 5:16:52 time: 0.8339 data_time: 0.0231 memory: 16201 loss_prob: 0.3432 loss_thr: 0.2569 loss_db: 0.0626 loss: 0.6627 2022/08/30 19:49:29 - mmengine - INFO - Epoch(train) [945][50/63] lr: 1.7381e-03 eta: 5:16:39 time: 0.8365 data_time: 0.0306 memory: 16201 loss_prob: 0.3868 loss_thr: 0.2674 loss_db: 0.0668 loss: 0.7210 2022/08/30 19:49:33 - mmengine - INFO - Epoch(train) [945][55/63] lr: 1.7381e-03 eta: 5:16:39 time: 0.7924 data_time: 0.0266 memory: 16201 loss_prob: 0.3766 loss_thr: 0.2591 loss_db: 0.0638 loss: 0.6995 2022/08/30 19:49:37 - mmengine - INFO - Epoch(train) [945][60/63] lr: 1.7381e-03 eta: 5:16:27 time: 0.7939 data_time: 0.0221 memory: 16201 loss_prob: 0.3652 loss_thr: 0.2620 loss_db: 0.0649 loss: 0.6921 2022/08/30 19:49:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:49:45 - mmengine - INFO - Epoch(train) [946][5/63] lr: 1.7319e-03 eta: 5:16:27 time: 0.8943 data_time: 0.1567 memory: 16201 loss_prob: 0.3621 loss_thr: 0.2567 loss_db: 0.0640 loss: 0.6828 2022/08/30 19:49:49 - mmengine - INFO - Epoch(train) [946][10/63] lr: 1.7319e-03 eta: 5:16:10 time: 0.9582 data_time: 0.1721 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2517 loss_db: 0.0641 loss: 0.6696 2022/08/30 19:49:53 - mmengine - INFO - Epoch(train) [946][15/63] lr: 1.7319e-03 eta: 5:16:10 time: 0.8009 data_time: 0.0285 memory: 16201 loss_prob: 0.3441 loss_thr: 0.2568 loss_db: 0.0629 loss: 0.6639 2022/08/30 19:49:57 - mmengine - INFO - Epoch(train) [946][20/63] lr: 1.7319e-03 eta: 5:15:57 time: 0.7925 data_time: 0.0187 memory: 16201 loss_prob: 0.3520 loss_thr: 0.2646 loss_db: 0.0629 loss: 0.6795 2022/08/30 19:50:01 - mmengine - INFO - Epoch(train) [946][25/63] lr: 1.7319e-03 eta: 5:15:57 time: 0.8249 data_time: 0.0320 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2389 loss_db: 0.0586 loss: 0.6225 2022/08/30 19:50:05 - mmengine - INFO - Epoch(train) [946][30/63] lr: 1.7319e-03 eta: 5:15:44 time: 0.8423 data_time: 0.0254 memory: 16201 loss_prob: 0.3122 loss_thr: 0.2172 loss_db: 0.0563 loss: 0.5857 2022/08/30 19:50:09 - mmengine - INFO - Epoch(train) [946][35/63] lr: 1.7319e-03 eta: 5:15:44 time: 0.8627 data_time: 0.0209 memory: 16201 loss_prob: 0.3352 loss_thr: 0.2380 loss_db: 0.0600 loss: 0.6333 2022/08/30 19:50:13 - mmengine - INFO - Epoch(train) [946][40/63] lr: 1.7319e-03 eta: 5:15:31 time: 0.8423 data_time: 0.0279 memory: 16201 loss_prob: 0.3169 loss_thr: 0.2404 loss_db: 0.0567 loss: 0.6140 2022/08/30 19:50:17 - mmengine - INFO - Epoch(train) [946][45/63] lr: 1.7319e-03 eta: 5:15:31 time: 0.7915 data_time: 0.0237 memory: 16201 loss_prob: 0.3121 loss_thr: 0.2297 loss_db: 0.0555 loss: 0.5974 2022/08/30 19:50:21 - mmengine - INFO - Epoch(train) [946][50/63] lr: 1.7319e-03 eta: 5:15:18 time: 0.7880 data_time: 0.0231 memory: 16201 loss_prob: 0.3581 loss_thr: 0.2591 loss_db: 0.0626 loss: 0.6798 2022/08/30 19:50:26 - mmengine - INFO - Epoch(train) [946][55/63] lr: 1.7319e-03 eta: 5:15:18 time: 0.8346 data_time: 0.0310 memory: 16201 loss_prob: 0.3635 loss_thr: 0.2680 loss_db: 0.0636 loss: 0.6952 2022/08/30 19:50:30 - mmengine - INFO - Epoch(train) [946][60/63] lr: 1.7319e-03 eta: 5:15:06 time: 0.8288 data_time: 0.0323 memory: 16201 loss_prob: 0.3555 loss_thr: 0.2584 loss_db: 0.0640 loss: 0.6779 2022/08/30 19:50:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:50:37 - mmengine - INFO - Epoch(train) [947][5/63] lr: 1.7258e-03 eta: 5:15:06 time: 0.8907 data_time: 0.1584 memory: 16201 loss_prob: 0.3641 loss_thr: 0.2637 loss_db: 0.0648 loss: 0.6926 2022/08/30 19:50:41 - mmengine - INFO - Epoch(train) [947][10/63] lr: 1.7258e-03 eta: 5:14:49 time: 0.9350 data_time: 0.1678 memory: 16201 loss_prob: 0.3607 loss_thr: 0.2606 loss_db: 0.0619 loss: 0.6831 2022/08/30 19:50:46 - mmengine - INFO - Epoch(train) [947][15/63] lr: 1.7258e-03 eta: 5:14:49 time: 0.8871 data_time: 0.0246 memory: 16201 loss_prob: 0.3709 loss_thr: 0.2631 loss_db: 0.0648 loss: 0.6988 2022/08/30 19:50:50 - mmengine - INFO - Epoch(train) [947][20/63] lr: 1.7258e-03 eta: 5:14:36 time: 0.8976 data_time: 0.0271 memory: 16201 loss_prob: 0.3774 loss_thr: 0.2635 loss_db: 0.0668 loss: 0.7078 2022/08/30 19:50:54 - mmengine - INFO - Epoch(train) [947][25/63] lr: 1.7258e-03 eta: 5:14:36 time: 0.8167 data_time: 0.0358 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2637 loss_db: 0.0674 loss: 0.7091 2022/08/30 19:50:58 - mmengine - INFO - Epoch(train) [947][30/63] lr: 1.7258e-03 eta: 5:14:23 time: 0.7903 data_time: 0.0249 memory: 16201 loss_prob: 0.3983 loss_thr: 0.2691 loss_db: 0.0708 loss: 0.7382 2022/08/30 19:51:02 - mmengine - INFO - Epoch(train) [947][35/63] lr: 1.7258e-03 eta: 5:14:23 time: 0.7869 data_time: 0.0201 memory: 16201 loss_prob: 0.4042 loss_thr: 0.2746 loss_db: 0.0692 loss: 0.7480 2022/08/30 19:51:06 - mmengine - INFO - Epoch(train) [947][40/63] lr: 1.7258e-03 eta: 5:14:11 time: 0.8467 data_time: 0.0280 memory: 16201 loss_prob: 0.3604 loss_thr: 0.2568 loss_db: 0.0617 loss: 0.6788 2022/08/30 19:51:10 - mmengine - INFO - Epoch(train) [947][45/63] lr: 1.7258e-03 eta: 5:14:11 time: 0.8383 data_time: 0.0269 memory: 16201 loss_prob: 0.3418 loss_thr: 0.2456 loss_db: 0.0617 loss: 0.6491 2022/08/30 19:51:14 - mmengine - INFO - Epoch(train) [947][50/63] lr: 1.7258e-03 eta: 5:13:58 time: 0.7861 data_time: 0.0242 memory: 16201 loss_prob: 0.3370 loss_thr: 0.2368 loss_db: 0.0607 loss: 0.6346 2022/08/30 19:51:18 - mmengine - INFO - Epoch(train) [947][55/63] lr: 1.7258e-03 eta: 5:13:58 time: 0.7797 data_time: 0.0241 memory: 16201 loss_prob: 0.3449 loss_thr: 0.2493 loss_db: 0.0613 loss: 0.6555 2022/08/30 19:51:22 - mmengine - INFO - Epoch(train) [947][60/63] lr: 1.7258e-03 eta: 5:13:45 time: 0.7784 data_time: 0.0243 memory: 16201 loss_prob: 0.3408 loss_thr: 0.2486 loss_db: 0.0617 loss: 0.6512 2022/08/30 19:51:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:51:30 - mmengine - INFO - Epoch(train) [948][5/63] lr: 1.7197e-03 eta: 5:13:45 time: 0.9600 data_time: 0.2217 memory: 16201 loss_prob: 0.4097 loss_thr: 0.2709 loss_db: 0.0708 loss: 0.7514 2022/08/30 19:51:34 - mmengine - INFO - Epoch(train) [948][10/63] lr: 1.7197e-03 eta: 5:13:28 time: 1.0171 data_time: 0.2328 memory: 16201 loss_prob: 0.3944 loss_thr: 0.2749 loss_db: 0.0695 loss: 0.7388 2022/08/30 19:51:39 - mmengine - INFO - Epoch(train) [948][15/63] lr: 1.7197e-03 eta: 5:13:28 time: 0.8425 data_time: 0.0281 memory: 16201 loss_prob: 0.3693 loss_thr: 0.2609 loss_db: 0.0660 loss: 0.6962 2022/08/30 19:51:43 - mmengine - INFO - Epoch(train) [948][20/63] lr: 1.7197e-03 eta: 5:13:15 time: 0.8355 data_time: 0.0253 memory: 16201 loss_prob: 0.3964 loss_thr: 0.2730 loss_db: 0.0697 loss: 0.7390 2022/08/30 19:51:47 - mmengine - INFO - Epoch(train) [948][25/63] lr: 1.7197e-03 eta: 5:13:15 time: 0.8126 data_time: 0.0288 memory: 16201 loss_prob: 0.3828 loss_thr: 0.2662 loss_db: 0.0692 loss: 0.7182 2022/08/30 19:51:51 - mmengine - INFO - Epoch(train) [948][30/63] lr: 1.7197e-03 eta: 5:13:03 time: 0.8266 data_time: 0.0237 memory: 16201 loss_prob: 0.3527 loss_thr: 0.2479 loss_db: 0.0636 loss: 0.6641 2022/08/30 19:51:55 - mmengine - INFO - Epoch(train) [948][35/63] lr: 1.7197e-03 eta: 5:13:03 time: 0.8207 data_time: 0.0201 memory: 16201 loss_prob: 0.3763 loss_thr: 0.2682 loss_db: 0.0662 loss: 0.7106 2022/08/30 19:51:59 - mmengine - INFO - Epoch(train) [948][40/63] lr: 1.7197e-03 eta: 5:12:50 time: 0.8063 data_time: 0.0264 memory: 16201 loss_prob: 0.3831 loss_thr: 0.2809 loss_db: 0.0681 loss: 0.7322 2022/08/30 19:52:03 - mmengine - INFO - Epoch(train) [948][45/63] lr: 1.7197e-03 eta: 5:12:50 time: 0.7865 data_time: 0.0267 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2678 loss_db: 0.0667 loss: 0.7105 2022/08/30 19:52:07 - mmengine - INFO - Epoch(train) [948][50/63] lr: 1.7197e-03 eta: 5:12:37 time: 0.8163 data_time: 0.0234 memory: 16201 loss_prob: 0.3840 loss_thr: 0.2752 loss_db: 0.0687 loss: 0.7279 2022/08/30 19:52:11 - mmengine - INFO - Epoch(train) [948][55/63] lr: 1.7197e-03 eta: 5:12:37 time: 0.8200 data_time: 0.0268 memory: 16201 loss_prob: 0.3637 loss_thr: 0.2691 loss_db: 0.0664 loss: 0.6992 2022/08/30 19:52:15 - mmengine - INFO - Epoch(train) [948][60/63] lr: 1.7197e-03 eta: 5:12:24 time: 0.7911 data_time: 0.0264 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2453 loss_db: 0.0606 loss: 0.6422 2022/08/30 19:52:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:52:23 - mmengine - INFO - Epoch(train) [949][5/63] lr: 1.7135e-03 eta: 5:12:24 time: 0.9698 data_time: 0.2043 memory: 16201 loss_prob: 0.3574 loss_thr: 0.2491 loss_db: 0.0647 loss: 0.6712 2022/08/30 19:52:27 - mmengine - INFO - Epoch(train) [949][10/63] lr: 1.7135e-03 eta: 5:12:07 time: 1.0117 data_time: 0.2170 memory: 16201 loss_prob: 0.3712 loss_thr: 0.2571 loss_db: 0.0658 loss: 0.6941 2022/08/30 19:52:31 - mmengine - INFO - Epoch(train) [949][15/63] lr: 1.7135e-03 eta: 5:12:07 time: 0.8115 data_time: 0.0266 memory: 16201 loss_prob: 0.3443 loss_thr: 0.2506 loss_db: 0.0618 loss: 0.6567 2022/08/30 19:52:36 - mmengine - INFO - Epoch(train) [949][20/63] lr: 1.7135e-03 eta: 5:11:55 time: 0.8453 data_time: 0.0162 memory: 16201 loss_prob: 0.3238 loss_thr: 0.2355 loss_db: 0.0586 loss: 0.6179 2022/08/30 19:52:40 - mmengine - INFO - Epoch(train) [949][25/63] lr: 1.7135e-03 eta: 5:11:55 time: 0.8572 data_time: 0.0335 memory: 16201 loss_prob: 0.3578 loss_thr: 0.2458 loss_db: 0.0640 loss: 0.6676 2022/08/30 19:52:44 - mmengine - INFO - Epoch(train) [949][30/63] lr: 1.7135e-03 eta: 5:11:42 time: 0.8011 data_time: 0.0296 memory: 16201 loss_prob: 0.3540 loss_thr: 0.2499 loss_db: 0.0625 loss: 0.6664 2022/08/30 19:52:48 - mmengine - INFO - Epoch(train) [949][35/63] lr: 1.7135e-03 eta: 5:11:42 time: 0.7889 data_time: 0.0204 memory: 16201 loss_prob: 0.3592 loss_thr: 0.2497 loss_db: 0.0636 loss: 0.6726 2022/08/30 19:52:52 - mmengine - INFO - Epoch(train) [949][40/63] lr: 1.7135e-03 eta: 5:11:29 time: 0.8083 data_time: 0.0250 memory: 16201 loss_prob: 0.3910 loss_thr: 0.2677 loss_db: 0.0692 loss: 0.7279 2022/08/30 19:52:56 - mmengine - INFO - Epoch(train) [949][45/63] lr: 1.7135e-03 eta: 5:11:29 time: 0.8285 data_time: 0.0231 memory: 16201 loss_prob: 0.3558 loss_thr: 0.2583 loss_db: 0.0634 loss: 0.6774 2022/08/30 19:53:00 - mmengine - INFO - Epoch(train) [949][50/63] lr: 1.7135e-03 eta: 5:11:16 time: 0.8141 data_time: 0.0249 memory: 16201 loss_prob: 0.3458 loss_thr: 0.2460 loss_db: 0.0604 loss: 0.6521 2022/08/30 19:53:04 - mmengine - INFO - Epoch(train) [949][55/63] lr: 1.7135e-03 eta: 5:11:16 time: 0.7977 data_time: 0.0263 memory: 16201 loss_prob: 0.3499 loss_thr: 0.2382 loss_db: 0.0596 loss: 0.6478 2022/08/30 19:53:08 - mmengine - INFO - Epoch(train) [949][60/63] lr: 1.7135e-03 eta: 5:11:04 time: 0.7931 data_time: 0.0260 memory: 16201 loss_prob: 0.3524 loss_thr: 0.2460 loss_db: 0.0620 loss: 0.6605 2022/08/30 19:53:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:53:15 - mmengine - INFO - Epoch(train) [950][5/63] lr: 1.7074e-03 eta: 5:11:04 time: 0.9044 data_time: 0.1608 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2711 loss_db: 0.0634 loss: 0.6924 2022/08/30 19:53:19 - mmengine - INFO - Epoch(train) [950][10/63] lr: 1.7074e-03 eta: 5:10:47 time: 0.9523 data_time: 0.1675 memory: 16201 loss_prob: 0.3543 loss_thr: 0.2553 loss_db: 0.0620 loss: 0.6717 2022/08/30 19:53:23 - mmengine - INFO - Epoch(train) [950][15/63] lr: 1.7074e-03 eta: 5:10:47 time: 0.7967 data_time: 0.0220 memory: 16201 loss_prob: 0.4223 loss_thr: 0.2680 loss_db: 0.0692 loss: 0.7596 2022/08/30 19:53:27 - mmengine - INFO - Epoch(train) [950][20/63] lr: 1.7074e-03 eta: 5:10:34 time: 0.8025 data_time: 0.0219 memory: 16201 loss_prob: 0.4135 loss_thr: 0.2685 loss_db: 0.0682 loss: 0.7503 2022/08/30 19:53:31 - mmengine - INFO - Epoch(train) [950][25/63] lr: 1.7074e-03 eta: 5:10:34 time: 0.8080 data_time: 0.0275 memory: 16201 loss_prob: 0.3737 loss_thr: 0.2833 loss_db: 0.0656 loss: 0.7226 2022/08/30 19:53:35 - mmengine - INFO - Epoch(train) [950][30/63] lr: 1.7074e-03 eta: 5:10:21 time: 0.7984 data_time: 0.0258 memory: 16201 loss_prob: 0.3835 loss_thr: 0.2799 loss_db: 0.0671 loss: 0.7305 2022/08/30 19:53:39 - mmengine - INFO - Epoch(train) [950][35/63] lr: 1.7074e-03 eta: 5:10:21 time: 0.7903 data_time: 0.0258 memory: 16201 loss_prob: 0.3941 loss_thr: 0.2635 loss_db: 0.0697 loss: 0.7273 2022/08/30 19:53:43 - mmengine - INFO - Epoch(train) [950][40/63] lr: 1.7074e-03 eta: 5:10:08 time: 0.7845 data_time: 0.0236 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2527 loss_db: 0.0648 loss: 0.6816 2022/08/30 19:53:47 - mmengine - INFO - Epoch(train) [950][45/63] lr: 1.7074e-03 eta: 5:10:08 time: 0.7930 data_time: 0.0219 memory: 16201 loss_prob: 0.3049 loss_thr: 0.2189 loss_db: 0.0556 loss: 0.5795 2022/08/30 19:53:51 - mmengine - INFO - Epoch(train) [950][50/63] lr: 1.7074e-03 eta: 5:09:55 time: 0.8047 data_time: 0.0223 memory: 16201 loss_prob: 0.3149 loss_thr: 0.2184 loss_db: 0.0563 loss: 0.5895 2022/08/30 19:53:56 - mmengine - INFO - Epoch(train) [950][55/63] lr: 1.7074e-03 eta: 5:09:55 time: 0.8497 data_time: 0.0253 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2650 loss_db: 0.0633 loss: 0.6856 2022/08/30 19:54:00 - mmengine - INFO - Epoch(train) [950][60/63] lr: 1.7074e-03 eta: 5:09:43 time: 0.8607 data_time: 0.0329 memory: 16201 loss_prob: 0.3589 loss_thr: 0.2792 loss_db: 0.0638 loss: 0.7019 2022/08/30 19:54:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:54:08 - mmengine - INFO - Epoch(train) [951][5/63] lr: 1.7012e-03 eta: 5:09:43 time: 0.9365 data_time: 0.2027 memory: 16201 loss_prob: 0.3439 loss_thr: 0.2558 loss_db: 0.0619 loss: 0.6616 2022/08/30 19:54:12 - mmengine - INFO - Epoch(train) [951][10/63] lr: 1.7012e-03 eta: 5:09:26 time: 0.9840 data_time: 0.2093 memory: 16201 loss_prob: 0.4260 loss_thr: 0.2892 loss_db: 0.0739 loss: 0.7891 2022/08/30 19:54:16 - mmengine - INFO - Epoch(train) [951][15/63] lr: 1.7012e-03 eta: 5:09:26 time: 0.8490 data_time: 0.0226 memory: 16201 loss_prob: 0.4291 loss_thr: 0.2914 loss_db: 0.0743 loss: 0.7948 2022/08/30 19:54:20 - mmengine - INFO - Epoch(train) [951][20/63] lr: 1.7012e-03 eta: 5:09:13 time: 0.8514 data_time: 0.0216 memory: 16201 loss_prob: 0.4001 loss_thr: 0.2718 loss_db: 0.0699 loss: 0.7419 2022/08/30 19:54:24 - mmengine - INFO - Epoch(train) [951][25/63] lr: 1.7012e-03 eta: 5:09:13 time: 0.7952 data_time: 0.0265 memory: 16201 loss_prob: 0.4492 loss_thr: 0.2777 loss_db: 0.0814 loss: 0.8083 2022/08/30 19:54:28 - mmengine - INFO - Epoch(train) [951][30/63] lr: 1.7012e-03 eta: 5:09:01 time: 0.7842 data_time: 0.0228 memory: 16201 loss_prob: 0.4173 loss_thr: 0.2727 loss_db: 0.0773 loss: 0.7673 2022/08/30 19:54:32 - mmengine - INFO - Epoch(train) [951][35/63] lr: 1.7012e-03 eta: 5:09:01 time: 0.7846 data_time: 0.0233 memory: 16201 loss_prob: 0.3649 loss_thr: 0.2627 loss_db: 0.0645 loss: 0.6921 2022/08/30 19:54:36 - mmengine - INFO - Epoch(train) [951][40/63] lr: 1.7012e-03 eta: 5:08:48 time: 0.8171 data_time: 0.0233 memory: 16201 loss_prob: 0.3613 loss_thr: 0.2595 loss_db: 0.0640 loss: 0.6849 2022/08/30 19:54:40 - mmengine - INFO - Epoch(train) [951][45/63] lr: 1.7012e-03 eta: 5:08:48 time: 0.8208 data_time: 0.0254 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2669 loss_db: 0.0658 loss: 0.6963 2022/08/30 19:54:44 - mmengine - INFO - Epoch(train) [951][50/63] lr: 1.7012e-03 eta: 5:08:35 time: 0.7749 data_time: 0.0239 memory: 16201 loss_prob: 0.3960 loss_thr: 0.2834 loss_db: 0.0698 loss: 0.7492 2022/08/30 19:54:48 - mmengine - INFO - Epoch(train) [951][55/63] lr: 1.7012e-03 eta: 5:08:35 time: 0.7833 data_time: 0.0214 memory: 16201 loss_prob: 0.3639 loss_thr: 0.2536 loss_db: 0.0630 loss: 0.6805 2022/08/30 19:54:52 - mmengine - INFO - Epoch(train) [951][60/63] lr: 1.7012e-03 eta: 5:08:22 time: 0.8070 data_time: 0.0241 memory: 16201 loss_prob: 0.3421 loss_thr: 0.2372 loss_db: 0.0601 loss: 0.6394 2022/08/30 19:54:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:55:00 - mmengine - INFO - Epoch(train) [952][5/63] lr: 1.6951e-03 eta: 5:08:22 time: 0.9466 data_time: 0.2031 memory: 16201 loss_prob: 0.3672 loss_thr: 0.2699 loss_db: 0.0651 loss: 0.7023 2022/08/30 19:55:04 - mmengine - INFO - Epoch(train) [952][10/63] lr: 1.6951e-03 eta: 5:08:05 time: 1.0105 data_time: 0.2192 memory: 16201 loss_prob: 0.3456 loss_thr: 0.2574 loss_db: 0.0618 loss: 0.6648 2022/08/30 19:55:08 - mmengine - INFO - Epoch(train) [952][15/63] lr: 1.6951e-03 eta: 5:08:05 time: 0.8307 data_time: 0.0285 memory: 16201 loss_prob: 0.3894 loss_thr: 0.2750 loss_db: 0.0709 loss: 0.7354 2022/08/30 19:55:12 - mmengine - INFO - Epoch(train) [952][20/63] lr: 1.6951e-03 eta: 5:07:53 time: 0.8194 data_time: 0.0200 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2512 loss_db: 0.0645 loss: 0.6744 2022/08/30 19:55:16 - mmengine - INFO - Epoch(train) [952][25/63] lr: 1.6951e-03 eta: 5:07:53 time: 0.8168 data_time: 0.0351 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2517 loss_db: 0.0606 loss: 0.6663 2022/08/30 19:55:20 - mmengine - INFO - Epoch(train) [952][30/63] lr: 1.6951e-03 eta: 5:07:40 time: 0.8069 data_time: 0.0256 memory: 16201 loss_prob: 0.3859 loss_thr: 0.2817 loss_db: 0.0670 loss: 0.7347 2022/08/30 19:55:24 - mmengine - INFO - Epoch(train) [952][35/63] lr: 1.6951e-03 eta: 5:07:40 time: 0.7851 data_time: 0.0165 memory: 16201 loss_prob: 0.3593 loss_thr: 0.2617 loss_db: 0.0638 loss: 0.6848 2022/08/30 19:55:28 - mmengine - INFO - Epoch(train) [952][40/63] lr: 1.6951e-03 eta: 5:07:27 time: 0.7923 data_time: 0.0241 memory: 16201 loss_prob: 0.3269 loss_thr: 0.2383 loss_db: 0.0576 loss: 0.6228 2022/08/30 19:55:32 - mmengine - INFO - Epoch(train) [952][45/63] lr: 1.6951e-03 eta: 5:07:27 time: 0.7893 data_time: 0.0242 memory: 16201 loss_prob: 0.3258 loss_thr: 0.2324 loss_db: 0.0577 loss: 0.6159 2022/08/30 19:55:37 - mmengine - INFO - Epoch(train) [952][50/63] lr: 1.6951e-03 eta: 5:07:15 time: 0.8581 data_time: 0.0256 memory: 16201 loss_prob: 0.3322 loss_thr: 0.2378 loss_db: 0.0608 loss: 0.6307 2022/08/30 19:55:41 - mmengine - INFO - Epoch(train) [952][55/63] lr: 1.6951e-03 eta: 5:07:15 time: 0.8598 data_time: 0.0248 memory: 16201 loss_prob: 0.3416 loss_thr: 0.2470 loss_db: 0.0624 loss: 0.6509 2022/08/30 19:55:45 - mmengine - INFO - Epoch(train) [952][60/63] lr: 1.6951e-03 eta: 5:07:02 time: 0.7984 data_time: 0.0253 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2288 loss_db: 0.0564 loss: 0.6018 2022/08/30 19:55:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:55:52 - mmengine - INFO - Epoch(train) [953][5/63] lr: 1.6889e-03 eta: 5:07:02 time: 0.9307 data_time: 0.1925 memory: 16201 loss_prob: 0.3701 loss_thr: 0.2613 loss_db: 0.0655 loss: 0.6969 2022/08/30 19:55:56 - mmengine - INFO - Epoch(train) [953][10/63] lr: 1.6889e-03 eta: 5:06:45 time: 0.9577 data_time: 0.1990 memory: 16201 loss_prob: 0.3812 loss_thr: 0.2639 loss_db: 0.0661 loss: 0.7112 2022/08/30 19:56:00 - mmengine - INFO - Epoch(train) [953][15/63] lr: 1.6889e-03 eta: 5:06:45 time: 0.7824 data_time: 0.0248 memory: 16201 loss_prob: 0.3630 loss_thr: 0.2538 loss_db: 0.0632 loss: 0.6800 2022/08/30 19:56:04 - mmengine - INFO - Epoch(train) [953][20/63] lr: 1.6889e-03 eta: 5:06:32 time: 0.7746 data_time: 0.0208 memory: 16201 loss_prob: 0.3417 loss_thr: 0.2471 loss_db: 0.0611 loss: 0.6499 2022/08/30 19:56:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:56:08 - mmengine - INFO - Epoch(train) [953][25/63] lr: 1.6889e-03 eta: 5:06:32 time: 0.8086 data_time: 0.0281 memory: 16201 loss_prob: 0.3286 loss_thr: 0.2479 loss_db: 0.0592 loss: 0.6357 2022/08/30 19:56:12 - mmengine - INFO - Epoch(train) [953][30/63] lr: 1.6889e-03 eta: 5:06:19 time: 0.8266 data_time: 0.0302 memory: 16201 loss_prob: 0.3290 loss_thr: 0.2467 loss_db: 0.0596 loss: 0.6353 2022/08/30 19:56:16 - mmengine - INFO - Epoch(train) [953][35/63] lr: 1.6889e-03 eta: 5:06:19 time: 0.8024 data_time: 0.0273 memory: 16201 loss_prob: 0.3306 loss_thr: 0.2438 loss_db: 0.0599 loss: 0.6343 2022/08/30 19:56:20 - mmengine - INFO - Epoch(train) [953][40/63] lr: 1.6889e-03 eta: 5:06:07 time: 0.7892 data_time: 0.0271 memory: 16201 loss_prob: 0.3439 loss_thr: 0.2451 loss_db: 0.0629 loss: 0.6518 2022/08/30 19:56:24 - mmengine - INFO - Epoch(train) [953][45/63] lr: 1.6889e-03 eta: 5:06:07 time: 0.7973 data_time: 0.0255 memory: 16201 loss_prob: 0.3575 loss_thr: 0.2614 loss_db: 0.0647 loss: 0.6836 2022/08/30 19:56:29 - mmengine - INFO - Epoch(train) [953][50/63] lr: 1.6889e-03 eta: 5:05:54 time: 0.8493 data_time: 0.0236 memory: 16201 loss_prob: 0.3522 loss_thr: 0.2658 loss_db: 0.0626 loss: 0.6806 2022/08/30 19:56:33 - mmengine - INFO - Epoch(train) [953][55/63] lr: 1.6889e-03 eta: 5:05:54 time: 0.8429 data_time: 0.0257 memory: 16201 loss_prob: 0.3702 loss_thr: 0.2669 loss_db: 0.0647 loss: 0.7018 2022/08/30 19:56:37 - mmengine - INFO - Epoch(train) [953][60/63] lr: 1.6889e-03 eta: 5:05:41 time: 0.7968 data_time: 0.0267 memory: 16201 loss_prob: 0.3839 loss_thr: 0.2694 loss_db: 0.0668 loss: 0.7201 2022/08/30 19:56:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:56:44 - mmengine - INFO - Epoch(train) [954][5/63] lr: 1.6828e-03 eta: 5:05:41 time: 0.8894 data_time: 0.1681 memory: 16201 loss_prob: 0.3469 loss_thr: 0.2509 loss_db: 0.0616 loss: 0.6595 2022/08/30 19:56:48 - mmengine - INFO - Epoch(train) [954][10/63] lr: 1.6828e-03 eta: 5:05:24 time: 0.9381 data_time: 0.1801 memory: 16201 loss_prob: 0.3528 loss_thr: 0.2556 loss_db: 0.0626 loss: 0.6709 2022/08/30 19:56:52 - mmengine - INFO - Epoch(train) [954][15/63] lr: 1.6828e-03 eta: 5:05:24 time: 0.7904 data_time: 0.0253 memory: 16201 loss_prob: 0.3403 loss_thr: 0.2499 loss_db: 0.0608 loss: 0.6510 2022/08/30 19:56:56 - mmengine - INFO - Epoch(train) [954][20/63] lr: 1.6828e-03 eta: 5:05:12 time: 0.7734 data_time: 0.0162 memory: 16201 loss_prob: 0.3380 loss_thr: 0.2467 loss_db: 0.0596 loss: 0.6443 2022/08/30 19:57:00 - mmengine - INFO - Epoch(train) [954][25/63] lr: 1.6828e-03 eta: 5:05:12 time: 0.7781 data_time: 0.0317 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2358 loss_db: 0.0592 loss: 0.6315 2022/08/30 19:57:04 - mmengine - INFO - Epoch(train) [954][30/63] lr: 1.6828e-03 eta: 5:04:59 time: 0.7839 data_time: 0.0228 memory: 16201 loss_prob: 0.3126 loss_thr: 0.2344 loss_db: 0.0569 loss: 0.6039 2022/08/30 19:57:08 - mmengine - INFO - Epoch(train) [954][35/63] lr: 1.6828e-03 eta: 5:04:59 time: 0.8100 data_time: 0.0175 memory: 16201 loss_prob: 0.3186 loss_thr: 0.2482 loss_db: 0.0581 loss: 0.6249 2022/08/30 19:57:12 - mmengine - INFO - Epoch(train) [954][40/63] lr: 1.6828e-03 eta: 5:04:46 time: 0.7983 data_time: 0.0240 memory: 16201 loss_prob: 0.3494 loss_thr: 0.2496 loss_db: 0.0637 loss: 0.6627 2022/08/30 19:57:16 - mmengine - INFO - Epoch(train) [954][45/63] lr: 1.6828e-03 eta: 5:04:46 time: 0.7764 data_time: 0.0217 memory: 16201 loss_prob: 0.3781 loss_thr: 0.2625 loss_db: 0.0669 loss: 0.7075 2022/08/30 19:57:20 - mmengine - INFO - Epoch(train) [954][50/63] lr: 1.6828e-03 eta: 5:04:33 time: 0.7857 data_time: 0.0259 memory: 16201 loss_prob: 0.4064 loss_thr: 0.2718 loss_db: 0.0680 loss: 0.7462 2022/08/30 19:57:24 - mmengine - INFO - Epoch(train) [954][55/63] lr: 1.6828e-03 eta: 5:04:33 time: 0.7948 data_time: 0.0241 memory: 16201 loss_prob: 0.3998 loss_thr: 0.2713 loss_db: 0.0681 loss: 0.7392 2022/08/30 19:57:28 - mmengine - INFO - Epoch(train) [954][60/63] lr: 1.6828e-03 eta: 5:04:21 time: 0.8860 data_time: 0.0698 memory: 16201 loss_prob: 0.3881 loss_thr: 0.2815 loss_db: 0.0696 loss: 0.7392 2022/08/30 19:57:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:57:36 - mmengine - INFO - Epoch(train) [955][5/63] lr: 1.6766e-03 eta: 5:04:21 time: 0.9074 data_time: 0.1762 memory: 16201 loss_prob: 0.4339 loss_thr: 0.3037 loss_db: 0.0778 loss: 0.8155 2022/08/30 19:57:40 - mmengine - INFO - Epoch(train) [955][10/63] lr: 1.6766e-03 eta: 5:04:04 time: 0.9553 data_time: 0.1852 memory: 16201 loss_prob: 0.3887 loss_thr: 0.2698 loss_db: 0.0683 loss: 0.7268 2022/08/30 19:57:44 - mmengine - INFO - Epoch(train) [955][15/63] lr: 1.6766e-03 eta: 5:04:04 time: 0.7762 data_time: 0.0249 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2526 loss_db: 0.0598 loss: 0.6604 2022/08/30 19:57:48 - mmengine - INFO - Epoch(train) [955][20/63] lr: 1.6766e-03 eta: 5:03:51 time: 0.7919 data_time: 0.0256 memory: 16201 loss_prob: 0.3480 loss_thr: 0.2499 loss_db: 0.0611 loss: 0.6591 2022/08/30 19:57:52 - mmengine - INFO - Epoch(train) [955][25/63] lr: 1.6766e-03 eta: 5:03:51 time: 0.8099 data_time: 0.0282 memory: 16201 loss_prob: 0.3547 loss_thr: 0.2520 loss_db: 0.0651 loss: 0.6718 2022/08/30 19:57:56 - mmengine - INFO - Epoch(train) [955][30/63] lr: 1.6766e-03 eta: 5:03:38 time: 0.7913 data_time: 0.0288 memory: 16201 loss_prob: 0.3428 loss_thr: 0.2403 loss_db: 0.0624 loss: 0.6456 2022/08/30 19:58:00 - mmengine - INFO - Epoch(train) [955][35/63] lr: 1.6766e-03 eta: 5:03:38 time: 0.7810 data_time: 0.0254 memory: 16201 loss_prob: 0.3466 loss_thr: 0.2417 loss_db: 0.0601 loss: 0.6483 2022/08/30 19:58:04 - mmengine - INFO - Epoch(train) [955][40/63] lr: 1.6766e-03 eta: 5:03:25 time: 0.7891 data_time: 0.0213 memory: 16201 loss_prob: 0.3496 loss_thr: 0.2549 loss_db: 0.0605 loss: 0.6649 2022/08/30 19:58:08 - mmengine - INFO - Epoch(train) [955][45/63] lr: 1.6766e-03 eta: 5:03:25 time: 0.8494 data_time: 0.0264 memory: 16201 loss_prob: 0.3663 loss_thr: 0.2610 loss_db: 0.0655 loss: 0.6929 2022/08/30 19:58:12 - mmengine - INFO - Epoch(train) [955][50/63] lr: 1.6766e-03 eta: 5:03:13 time: 0.8540 data_time: 0.0217 memory: 16201 loss_prob: 0.3959 loss_thr: 0.2690 loss_db: 0.0700 loss: 0.7350 2022/08/30 19:58:16 - mmengine - INFO - Epoch(train) [955][55/63] lr: 1.6766e-03 eta: 5:03:13 time: 0.7955 data_time: 0.0302 memory: 16201 loss_prob: 0.3985 loss_thr: 0.2716 loss_db: 0.0694 loss: 0.7394 2022/08/30 19:58:20 - mmengine - INFO - Epoch(train) [955][60/63] lr: 1.6766e-03 eta: 5:03:00 time: 0.8327 data_time: 0.0592 memory: 16201 loss_prob: 0.3853 loss_thr: 0.2711 loss_db: 0.0681 loss: 0.7245 2022/08/30 19:58:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:58:28 - mmengine - INFO - Epoch(train) [956][5/63] lr: 1.6704e-03 eta: 5:03:00 time: 0.9765 data_time: 0.2344 memory: 16201 loss_prob: 0.3763 loss_thr: 0.2670 loss_db: 0.0671 loss: 0.7104 2022/08/30 19:58:33 - mmengine - INFO - Epoch(train) [956][10/63] lr: 1.6704e-03 eta: 5:02:44 time: 1.0022 data_time: 0.2234 memory: 16201 loss_prob: 0.3773 loss_thr: 0.2652 loss_db: 0.0659 loss: 0.7084 2022/08/30 19:58:37 - mmengine - INFO - Epoch(train) [956][15/63] lr: 1.6704e-03 eta: 5:02:44 time: 0.8836 data_time: 0.0402 memory: 16201 loss_prob: 0.3415 loss_thr: 0.2531 loss_db: 0.0608 loss: 0.6554 2022/08/30 19:58:41 - mmengine - INFO - Epoch(train) [956][20/63] lr: 1.6704e-03 eta: 5:02:31 time: 0.8668 data_time: 0.0331 memory: 16201 loss_prob: 0.3428 loss_thr: 0.2530 loss_db: 0.0613 loss: 0.6571 2022/08/30 19:58:45 - mmengine - INFO - Epoch(train) [956][25/63] lr: 1.6704e-03 eta: 5:02:31 time: 0.8027 data_time: 0.0423 memory: 16201 loss_prob: 0.3451 loss_thr: 0.2501 loss_db: 0.0614 loss: 0.6566 2022/08/30 19:58:49 - mmengine - INFO - Epoch(train) [956][30/63] lr: 1.6704e-03 eta: 5:02:18 time: 0.8073 data_time: 0.0393 memory: 16201 loss_prob: 0.3170 loss_thr: 0.2339 loss_db: 0.0567 loss: 0.6076 2022/08/30 19:58:53 - mmengine - INFO - Epoch(train) [956][35/63] lr: 1.6704e-03 eta: 5:02:18 time: 0.7952 data_time: 0.0322 memory: 16201 loss_prob: 0.3243 loss_thr: 0.2444 loss_db: 0.0571 loss: 0.6258 2022/08/30 19:58:58 - mmengine - INFO - Epoch(train) [956][40/63] lr: 1.6704e-03 eta: 5:02:06 time: 0.8392 data_time: 0.0504 memory: 16201 loss_prob: 0.3535 loss_thr: 0.2591 loss_db: 0.0631 loss: 0.6757 2022/08/30 19:59:02 - mmengine - INFO - Epoch(train) [956][45/63] lr: 1.6704e-03 eta: 5:02:06 time: 0.8376 data_time: 0.0583 memory: 16201 loss_prob: 0.3480 loss_thr: 0.2509 loss_db: 0.0619 loss: 0.6608 2022/08/30 19:59:06 - mmengine - INFO - Epoch(train) [956][50/63] lr: 1.6704e-03 eta: 5:01:53 time: 0.7983 data_time: 0.0374 memory: 16201 loss_prob: 0.3371 loss_thr: 0.2430 loss_db: 0.0596 loss: 0.6397 2022/08/30 19:59:10 - mmengine - INFO - Epoch(train) [956][55/63] lr: 1.6704e-03 eta: 5:01:53 time: 0.8145 data_time: 0.0423 memory: 16201 loss_prob: 0.3565 loss_thr: 0.2554 loss_db: 0.0640 loss: 0.6760 2022/08/30 19:59:14 - mmengine - INFO - Epoch(train) [956][60/63] lr: 1.6704e-03 eta: 5:01:40 time: 0.8058 data_time: 0.0481 memory: 16201 loss_prob: 0.3655 loss_thr: 0.2629 loss_db: 0.0660 loss: 0.6944 2022/08/30 19:59:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 19:59:22 - mmengine - INFO - Epoch(train) [957][5/63] lr: 1.6643e-03 eta: 5:01:40 time: 1.0230 data_time: 0.2119 memory: 16201 loss_prob: 0.4001 loss_thr: 0.2767 loss_db: 0.0713 loss: 0.7480 2022/08/30 19:59:27 - mmengine - INFO - Epoch(train) [957][10/63] lr: 1.6643e-03 eta: 5:01:24 time: 1.0279 data_time: 0.2410 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2546 loss_db: 0.0624 loss: 0.6738 2022/08/30 19:59:31 - mmengine - INFO - Epoch(train) [957][15/63] lr: 1.6643e-03 eta: 5:01:24 time: 0.8146 data_time: 0.0503 memory: 16201 loss_prob: 0.3586 loss_thr: 0.2538 loss_db: 0.0634 loss: 0.6759 2022/08/30 19:59:35 - mmengine - INFO - Epoch(train) [957][20/63] lr: 1.6643e-03 eta: 5:01:11 time: 0.8522 data_time: 0.0325 memory: 16201 loss_prob: 0.3727 loss_thr: 0.2518 loss_db: 0.0639 loss: 0.6884 2022/08/30 19:59:39 - mmengine - INFO - Epoch(train) [957][25/63] lr: 1.6643e-03 eta: 5:01:11 time: 0.8647 data_time: 0.0375 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2661 loss_db: 0.0661 loss: 0.7126 2022/08/30 19:59:43 - mmengine - INFO - Epoch(train) [957][30/63] lr: 1.6643e-03 eta: 5:00:58 time: 0.7794 data_time: 0.0233 memory: 16201 loss_prob: 0.3513 loss_thr: 0.2644 loss_db: 0.0624 loss: 0.6782 2022/08/30 19:59:47 - mmengine - INFO - Epoch(train) [957][35/63] lr: 1.6643e-03 eta: 5:00:58 time: 0.7950 data_time: 0.0196 memory: 16201 loss_prob: 0.3644 loss_thr: 0.2697 loss_db: 0.0634 loss: 0.6975 2022/08/30 19:59:51 - mmengine - INFO - Epoch(train) [957][40/63] lr: 1.6643e-03 eta: 5:00:45 time: 0.7971 data_time: 0.0259 memory: 16201 loss_prob: 0.3609 loss_thr: 0.2627 loss_db: 0.0641 loss: 0.6877 2022/08/30 19:59:55 - mmengine - INFO - Epoch(train) [957][45/63] lr: 1.6643e-03 eta: 5:00:45 time: 0.7876 data_time: 0.0248 memory: 16201 loss_prob: 0.3277 loss_thr: 0.2427 loss_db: 0.0582 loss: 0.6286 2022/08/30 19:59:59 - mmengine - INFO - Epoch(train) [957][50/63] lr: 1.6643e-03 eta: 5:00:33 time: 0.8302 data_time: 0.0265 memory: 16201 loss_prob: 0.3483 loss_thr: 0.2463 loss_db: 0.0622 loss: 0.6568 2022/08/30 20:00:03 - mmengine - INFO - Epoch(train) [957][55/63] lr: 1.6643e-03 eta: 5:00:33 time: 0.8231 data_time: 0.0297 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2572 loss_db: 0.0687 loss: 0.7039 2022/08/30 20:00:07 - mmengine - INFO - Epoch(train) [957][60/63] lr: 1.6643e-03 eta: 5:00:20 time: 0.8060 data_time: 0.0285 memory: 16201 loss_prob: 0.3631 loss_thr: 0.2524 loss_db: 0.0653 loss: 0.6808 2022/08/30 20:00:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:00:15 - mmengine - INFO - Epoch(train) [958][5/63] lr: 1.6581e-03 eta: 5:00:20 time: 0.9184 data_time: 0.1786 memory: 16201 loss_prob: 0.3674 loss_thr: 0.2642 loss_db: 0.0638 loss: 0.6954 2022/08/30 20:00:19 - mmengine - INFO - Epoch(train) [958][10/63] lr: 1.6581e-03 eta: 5:00:03 time: 0.9496 data_time: 0.1857 memory: 16201 loss_prob: 0.3842 loss_thr: 0.2733 loss_db: 0.0674 loss: 0.7249 2022/08/30 20:00:23 - mmengine - INFO - Epoch(train) [958][15/63] lr: 1.6581e-03 eta: 5:00:03 time: 0.7798 data_time: 0.0229 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2640 loss_db: 0.0657 loss: 0.6890 2022/08/30 20:00:27 - mmengine - INFO - Epoch(train) [958][20/63] lr: 1.6581e-03 eta: 4:59:51 time: 0.8583 data_time: 0.0288 memory: 16201 loss_prob: 0.3524 loss_thr: 0.2635 loss_db: 0.0635 loss: 0.6794 2022/08/30 20:00:32 - mmengine - INFO - Epoch(train) [958][25/63] lr: 1.6581e-03 eta: 4:59:51 time: 0.8893 data_time: 0.0319 memory: 16201 loss_prob: 0.3925 loss_thr: 0.2701 loss_db: 0.0667 loss: 0.7293 2022/08/30 20:00:36 - mmengine - INFO - Epoch(train) [958][30/63] lr: 1.6581e-03 eta: 4:59:38 time: 0.8181 data_time: 0.0263 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2684 loss_db: 0.0658 loss: 0.7187 2022/08/30 20:00:40 - mmengine - INFO - Epoch(train) [958][35/63] lr: 1.6581e-03 eta: 4:59:38 time: 0.8104 data_time: 0.0294 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2434 loss_db: 0.0589 loss: 0.6320 2022/08/30 20:00:44 - mmengine - INFO - Epoch(train) [958][40/63] lr: 1.6581e-03 eta: 4:59:25 time: 0.8104 data_time: 0.0247 memory: 16201 loss_prob: 0.3105 loss_thr: 0.2302 loss_db: 0.0560 loss: 0.5966 2022/08/30 20:00:48 - mmengine - INFO - Epoch(train) [958][45/63] lr: 1.6581e-03 eta: 4:59:25 time: 0.8036 data_time: 0.0223 memory: 16201 loss_prob: 0.3344 loss_thr: 0.2404 loss_db: 0.0607 loss: 0.6354 2022/08/30 20:00:52 - mmengine - INFO - Epoch(train) [958][50/63] lr: 1.6581e-03 eta: 4:59:13 time: 0.8268 data_time: 0.0211 memory: 16201 loss_prob: 0.3788 loss_thr: 0.2647 loss_db: 0.0688 loss: 0.7124 2022/08/30 20:00:56 - mmengine - INFO - Epoch(train) [958][55/63] lr: 1.6581e-03 eta: 4:59:13 time: 0.8254 data_time: 0.0289 memory: 16201 loss_prob: 0.4087 loss_thr: 0.2761 loss_db: 0.0728 loss: 0.7576 2022/08/30 20:01:00 - mmengine - INFO - Epoch(train) [958][60/63] lr: 1.6581e-03 eta: 4:59:00 time: 0.7919 data_time: 0.0313 memory: 16201 loss_prob: 0.3736 loss_thr: 0.2509 loss_db: 0.0670 loss: 0.6915 2022/08/30 20:01:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:01:08 - mmengine - INFO - Epoch(train) [959][5/63] lr: 1.6519e-03 eta: 4:59:00 time: 0.9056 data_time: 0.1731 memory: 16201 loss_prob: 0.3553 loss_thr: 0.2539 loss_db: 0.0637 loss: 0.6729 2022/08/30 20:01:12 - mmengine - INFO - Epoch(train) [959][10/63] lr: 1.6519e-03 eta: 4:58:43 time: 0.9748 data_time: 0.1892 memory: 16201 loss_prob: 0.3461 loss_thr: 0.2456 loss_db: 0.0616 loss: 0.6533 2022/08/30 20:01:16 - mmengine - INFO - Epoch(train) [959][15/63] lr: 1.6519e-03 eta: 4:58:43 time: 0.8568 data_time: 0.0300 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2416 loss_db: 0.0618 loss: 0.6400 2022/08/30 20:01:20 - mmengine - INFO - Epoch(train) [959][20/63] lr: 1.6519e-03 eta: 4:58:31 time: 0.8677 data_time: 0.0243 memory: 16201 loss_prob: 0.3661 loss_thr: 0.2739 loss_db: 0.0653 loss: 0.7053 2022/08/30 20:01:24 - mmengine - INFO - Epoch(train) [959][25/63] lr: 1.6519e-03 eta: 4:58:31 time: 0.8312 data_time: 0.0376 memory: 16201 loss_prob: 0.3640 loss_thr: 0.2645 loss_db: 0.0628 loss: 0.6913 2022/08/30 20:01:28 - mmengine - INFO - Epoch(train) [959][30/63] lr: 1.6519e-03 eta: 4:58:18 time: 0.8042 data_time: 0.0234 memory: 16201 loss_prob: 0.3455 loss_thr: 0.2422 loss_db: 0.0611 loss: 0.6488 2022/08/30 20:01:32 - mmengine - INFO - Epoch(train) [959][35/63] lr: 1.6519e-03 eta: 4:58:18 time: 0.7976 data_time: 0.0182 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2345 loss_db: 0.0578 loss: 0.6138 2022/08/30 20:01:37 - mmengine - INFO - Epoch(train) [959][40/63] lr: 1.6519e-03 eta: 4:58:05 time: 0.8393 data_time: 0.0271 memory: 16201 loss_prob: 0.3053 loss_thr: 0.2253 loss_db: 0.0541 loss: 0.5846 2022/08/30 20:01:41 - mmengine - INFO - Epoch(train) [959][45/63] lr: 1.6519e-03 eta: 4:58:05 time: 0.8579 data_time: 0.0267 memory: 16201 loss_prob: 0.3369 loss_thr: 0.2441 loss_db: 0.0593 loss: 0.6403 2022/08/30 20:01:45 - mmengine - INFO - Epoch(train) [959][50/63] lr: 1.6519e-03 eta: 4:57:53 time: 0.8227 data_time: 0.0296 memory: 16201 loss_prob: 0.3621 loss_thr: 0.2585 loss_db: 0.0612 loss: 0.6818 2022/08/30 20:01:49 - mmengine - INFO - Epoch(train) [959][55/63] lr: 1.6519e-03 eta: 4:57:53 time: 0.8498 data_time: 0.0261 memory: 16201 loss_prob: 0.3485 loss_thr: 0.2456 loss_db: 0.0602 loss: 0.6543 2022/08/30 20:01:54 - mmengine - INFO - Epoch(train) [959][60/63] lr: 1.6519e-03 eta: 4:57:40 time: 0.8593 data_time: 0.0329 memory: 16201 loss_prob: 0.3535 loss_thr: 0.2435 loss_db: 0.0638 loss: 0.6608 2022/08/30 20:01:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:02:02 - mmengine - INFO - Epoch(train) [960][5/63] lr: 1.6458e-03 eta: 4:57:40 time: 0.9530 data_time: 0.2121 memory: 16201 loss_prob: 0.4138 loss_thr: 0.2908 loss_db: 0.0731 loss: 0.7777 2022/08/30 20:02:06 - mmengine - INFO - Epoch(train) [960][10/63] lr: 1.6458e-03 eta: 4:57:24 time: 1.0107 data_time: 0.2356 memory: 16201 loss_prob: 0.3373 loss_thr: 0.2542 loss_db: 0.0598 loss: 0.6513 2022/08/30 20:02:10 - mmengine - INFO - Epoch(train) [960][15/63] lr: 1.6458e-03 eta: 4:57:24 time: 0.8371 data_time: 0.0512 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2553 loss_db: 0.0615 loss: 0.6634 2022/08/30 20:02:14 - mmengine - INFO - Epoch(train) [960][20/63] lr: 1.6458e-03 eta: 4:57:11 time: 0.8259 data_time: 0.0334 memory: 16201 loss_prob: 0.3768 loss_thr: 0.2651 loss_db: 0.0678 loss: 0.7097 2022/08/30 20:02:18 - mmengine - INFO - Epoch(train) [960][25/63] lr: 1.6458e-03 eta: 4:57:11 time: 0.8436 data_time: 0.0479 memory: 16201 loss_prob: 0.3501 loss_thr: 0.2373 loss_db: 0.0639 loss: 0.6512 2022/08/30 20:02:22 - mmengine - INFO - Epoch(train) [960][30/63] lr: 1.6458e-03 eta: 4:56:58 time: 0.8183 data_time: 0.0378 memory: 16201 loss_prob: 0.3418 loss_thr: 0.2362 loss_db: 0.0608 loss: 0.6388 2022/08/30 20:02:26 - mmengine - INFO - Epoch(train) [960][35/63] lr: 1.6458e-03 eta: 4:56:58 time: 0.8050 data_time: 0.0280 memory: 16201 loss_prob: 0.3374 loss_thr: 0.2328 loss_db: 0.0594 loss: 0.6296 2022/08/30 20:02:31 - mmengine - INFO - Epoch(train) [960][40/63] lr: 1.6458e-03 eta: 4:56:46 time: 0.8319 data_time: 0.0481 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2173 loss_db: 0.0541 loss: 0.5834 2022/08/30 20:02:35 - mmengine - INFO - Epoch(train) [960][45/63] lr: 1.6458e-03 eta: 4:56:46 time: 0.8268 data_time: 0.0498 memory: 16201 loss_prob: 0.3322 loss_thr: 0.2335 loss_db: 0.0584 loss: 0.6241 2022/08/30 20:02:39 - mmengine - INFO - Epoch(train) [960][50/63] lr: 1.6458e-03 eta: 4:56:33 time: 0.8166 data_time: 0.0413 memory: 16201 loss_prob: 0.3772 loss_thr: 0.2658 loss_db: 0.0658 loss: 0.7088 2022/08/30 20:02:43 - mmengine - INFO - Epoch(train) [960][55/63] lr: 1.6458e-03 eta: 4:56:33 time: 0.8251 data_time: 0.0505 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2593 loss_db: 0.0631 loss: 0.6822 2022/08/30 20:02:48 - mmengine - INFO - Epoch(train) [960][60/63] lr: 1.6458e-03 eta: 4:56:21 time: 0.9007 data_time: 0.0540 memory: 16201 loss_prob: 0.3637 loss_thr: 0.2557 loss_db: 0.0642 loss: 0.6836 2022/08/30 20:02:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:02:50 - mmengine - INFO - Saving checkpoint at 960 epochs 2022/08/30 20:02:58 - mmengine - INFO - Epoch(val) [960][5/32] eta: 4:56:21 time: 0.6389 data_time: 0.1333 memory: 16201 2022/08/30 20:03:01 - mmengine - INFO - Epoch(val) [960][10/32] eta: 0:00:15 time: 0.7252 data_time: 0.1698 memory: 15734 2022/08/30 20:03:04 - mmengine - INFO - Epoch(val) [960][15/32] eta: 0:00:15 time: 0.6046 data_time: 0.0514 memory: 15734 2022/08/30 20:03:08 - mmengine - INFO - Epoch(val) [960][20/32] eta: 0:00:07 time: 0.6384 data_time: 0.0517 memory: 15734 2022/08/30 20:03:11 - mmengine - INFO - Epoch(val) [960][25/32] eta: 0:00:07 time: 0.6568 data_time: 0.0586 memory: 15734 2022/08/30 20:03:13 - mmengine - INFO - Epoch(val) [960][30/32] eta: 0:00:01 time: 0.5836 data_time: 0.0249 memory: 15734 2022/08/30 20:03:14 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 20:03:14 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8618, precision: 0.7892, hmean: 0.8239 2022/08/30 20:03:14 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8618, precision: 0.8245, hmean: 0.8427 2022/08/30 20:03:14 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8618, precision: 0.8463, hmean: 0.8540 2022/08/30 20:03:14 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8594, precision: 0.8636, hmean: 0.8615 2022/08/30 20:03:14 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8536, precision: 0.8812, hmean: 0.8672 2022/08/30 20:03:14 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8291, precision: 0.9116, hmean: 0.8684 2022/08/30 20:03:14 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4386, precision: 0.9499, hmean: 0.6001 2022/08/30 20:03:14 - mmengine - INFO - Epoch(val) [960][32/32] icdar/precision: 0.9116 icdar/recall: 0.8291 icdar/hmean: 0.8684 2022/08/30 20:03:21 - mmengine - INFO - Epoch(train) [961][5/63] lr: 1.6396e-03 eta: 0:00:01 time: 1.0502 data_time: 0.2045 memory: 16201 loss_prob: 0.3683 loss_thr: 0.2620 loss_db: 0.0653 loss: 0.6956 2022/08/30 20:03:25 - mmengine - INFO - Epoch(train) [961][10/63] lr: 1.6396e-03 eta: 4:56:04 time: 1.0474 data_time: 0.2051 memory: 16201 loss_prob: 0.3766 loss_thr: 0.2724 loss_db: 0.0669 loss: 0.7159 2022/08/30 20:03:29 - mmengine - INFO - Epoch(train) [961][15/63] lr: 1.6396e-03 eta: 4:56:04 time: 0.8373 data_time: 0.0367 memory: 16201 loss_prob: 0.3559 loss_thr: 0.2545 loss_db: 0.0641 loss: 0.6745 2022/08/30 20:03:33 - mmengine - INFO - Epoch(train) [961][20/63] lr: 1.6396e-03 eta: 4:55:52 time: 0.8352 data_time: 0.0364 memory: 16201 loss_prob: 0.3359 loss_thr: 0.2279 loss_db: 0.0593 loss: 0.6232 2022/08/30 20:03:37 - mmengine - INFO - Epoch(train) [961][25/63] lr: 1.6396e-03 eta: 4:55:52 time: 0.8227 data_time: 0.0266 memory: 16201 loss_prob: 0.3393 loss_thr: 0.2297 loss_db: 0.0602 loss: 0.6291 2022/08/30 20:03:42 - mmengine - INFO - Epoch(train) [961][30/63] lr: 1.6396e-03 eta: 4:55:39 time: 0.8493 data_time: 0.0309 memory: 16201 loss_prob: 0.3266 loss_thr: 0.2379 loss_db: 0.0588 loss: 0.6233 2022/08/30 20:03:46 - mmengine - INFO - Epoch(train) [961][35/63] lr: 1.6396e-03 eta: 4:55:39 time: 0.8367 data_time: 0.0271 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2618 loss_db: 0.0619 loss: 0.6804 2022/08/30 20:03:50 - mmengine - INFO - Epoch(train) [961][40/63] lr: 1.6396e-03 eta: 4:55:26 time: 0.8226 data_time: 0.0233 memory: 16201 loss_prob: 0.3527 loss_thr: 0.2539 loss_db: 0.0629 loss: 0.6694 2022/08/30 20:03:54 - mmengine - INFO - Epoch(train) [961][45/63] lr: 1.6396e-03 eta: 4:55:26 time: 0.8337 data_time: 0.0304 memory: 16201 loss_prob: 0.3555 loss_thr: 0.2454 loss_db: 0.0637 loss: 0.6646 2022/08/30 20:03:58 - mmengine - INFO - Epoch(train) [961][50/63] lr: 1.6396e-03 eta: 4:55:14 time: 0.8278 data_time: 0.0366 memory: 16201 loss_prob: 0.3615 loss_thr: 0.2591 loss_db: 0.0640 loss: 0.6846 2022/08/30 20:04:02 - mmengine - INFO - Epoch(train) [961][55/63] lr: 1.6396e-03 eta: 4:55:14 time: 0.8101 data_time: 0.0259 memory: 16201 loss_prob: 0.3627 loss_thr: 0.2536 loss_db: 0.0646 loss: 0.6809 2022/08/30 20:04:07 - mmengine - INFO - Epoch(train) [961][60/63] lr: 1.6396e-03 eta: 4:55:01 time: 0.8305 data_time: 0.0269 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2560 loss_db: 0.0622 loss: 0.6686 2022/08/30 20:04:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:04:14 - mmengine - INFO - Epoch(train) [962][5/63] lr: 1.6334e-03 eta: 4:55:01 time: 0.9603 data_time: 0.1869 memory: 16201 loss_prob: 0.3696 loss_thr: 0.2683 loss_db: 0.0652 loss: 0.7031 2022/08/30 20:04:19 - mmengine - INFO - Epoch(train) [962][10/63] lr: 1.6334e-03 eta: 4:54:44 time: 0.9936 data_time: 0.1978 memory: 16201 loss_prob: 0.3756 loss_thr: 0.2616 loss_db: 0.0660 loss: 0.7033 2022/08/30 20:04:23 - mmengine - INFO - Epoch(train) [962][15/63] lr: 1.6334e-03 eta: 4:54:44 time: 0.8492 data_time: 0.0286 memory: 16201 loss_prob: 0.3572 loss_thr: 0.2577 loss_db: 0.0623 loss: 0.6772 2022/08/30 20:04:27 - mmengine - INFO - Epoch(train) [962][20/63] lr: 1.6334e-03 eta: 4:54:32 time: 0.8577 data_time: 0.0198 memory: 16201 loss_prob: 0.3439 loss_thr: 0.2463 loss_db: 0.0620 loss: 0.6523 2022/08/30 20:04:32 - mmengine - INFO - Epoch(train) [962][25/63] lr: 1.6334e-03 eta: 4:54:32 time: 0.8662 data_time: 0.0393 memory: 16201 loss_prob: 0.3735 loss_thr: 0.2591 loss_db: 0.0669 loss: 0.6996 2022/08/30 20:04:36 - mmengine - INFO - Epoch(train) [962][30/63] lr: 1.6334e-03 eta: 4:54:19 time: 0.8633 data_time: 0.0361 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2461 loss_db: 0.0580 loss: 0.6366 2022/08/30 20:04:40 - mmengine - INFO - Epoch(train) [962][35/63] lr: 1.6334e-03 eta: 4:54:19 time: 0.8551 data_time: 0.0225 memory: 16201 loss_prob: 0.3098 loss_thr: 0.2294 loss_db: 0.0552 loss: 0.5944 2022/08/30 20:04:44 - mmengine - INFO - Epoch(train) [962][40/63] lr: 1.6334e-03 eta: 4:54:07 time: 0.8413 data_time: 0.0321 memory: 16201 loss_prob: 0.3454 loss_thr: 0.2354 loss_db: 0.0609 loss: 0.6417 2022/08/30 20:04:49 - mmengine - INFO - Epoch(train) [962][45/63] lr: 1.6334e-03 eta: 4:54:07 time: 0.8436 data_time: 0.0321 memory: 16201 loss_prob: 0.3389 loss_thr: 0.2395 loss_db: 0.0614 loss: 0.6397 2022/08/30 20:04:53 - mmengine - INFO - Epoch(train) [962][50/63] lr: 1.6334e-03 eta: 4:53:54 time: 0.8432 data_time: 0.0288 memory: 16201 loss_prob: 0.3451 loss_thr: 0.2506 loss_db: 0.0615 loss: 0.6572 2022/08/30 20:04:57 - mmengine - INFO - Epoch(train) [962][55/63] lr: 1.6334e-03 eta: 4:53:54 time: 0.8376 data_time: 0.0326 memory: 16201 loss_prob: 0.3508 loss_thr: 0.2541 loss_db: 0.0602 loss: 0.6652 2022/08/30 20:05:01 - mmengine - INFO - Epoch(train) [962][60/63] lr: 1.6334e-03 eta: 4:53:42 time: 0.8284 data_time: 0.0309 memory: 16201 loss_prob: 0.3457 loss_thr: 0.2539 loss_db: 0.0607 loss: 0.6603 2022/08/30 20:05:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:05:09 - mmengine - INFO - Epoch(train) [963][5/63] lr: 1.6273e-03 eta: 4:53:42 time: 0.9475 data_time: 0.1988 memory: 16201 loss_prob: 0.3553 loss_thr: 0.2564 loss_db: 0.0636 loss: 0.6753 2022/08/30 20:05:13 - mmengine - INFO - Epoch(train) [963][10/63] lr: 1.6273e-03 eta: 4:53:25 time: 0.9853 data_time: 0.2091 memory: 16201 loss_prob: 0.3619 loss_thr: 0.2543 loss_db: 0.0646 loss: 0.6808 2022/08/30 20:05:18 - mmengine - INFO - Epoch(train) [963][15/63] lr: 1.6273e-03 eta: 4:53:25 time: 0.8756 data_time: 0.0284 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2598 loss_db: 0.0632 loss: 0.6872 2022/08/30 20:05:22 - mmengine - INFO - Epoch(train) [963][20/63] lr: 1.6273e-03 eta: 4:53:13 time: 0.8834 data_time: 0.0214 memory: 16201 loss_prob: 0.3449 loss_thr: 0.2447 loss_db: 0.0607 loss: 0.6503 2022/08/30 20:05:26 - mmengine - INFO - Epoch(train) [963][25/63] lr: 1.6273e-03 eta: 4:53:13 time: 0.8252 data_time: 0.0359 memory: 16201 loss_prob: 0.3173 loss_thr: 0.2272 loss_db: 0.0582 loss: 0.6028 2022/08/30 20:05:30 - mmengine - INFO - Epoch(train) [963][30/63] lr: 1.6273e-03 eta: 4:53:00 time: 0.8229 data_time: 0.0296 memory: 16201 loss_prob: 0.3360 loss_thr: 0.2362 loss_db: 0.0614 loss: 0.6337 2022/08/30 20:05:34 - mmengine - INFO - Epoch(train) [963][35/63] lr: 1.6273e-03 eta: 4:53:00 time: 0.8405 data_time: 0.0281 memory: 16201 loss_prob: 0.3454 loss_thr: 0.2324 loss_db: 0.0635 loss: 0.6413 2022/08/30 20:05:39 - mmengine - INFO - Epoch(train) [963][40/63] lr: 1.6273e-03 eta: 4:52:47 time: 0.8651 data_time: 0.0332 memory: 16201 loss_prob: 0.3493 loss_thr: 0.2432 loss_db: 0.0630 loss: 0.6555 2022/08/30 20:05:43 - mmengine - INFO - Epoch(train) [963][45/63] lr: 1.6273e-03 eta: 4:52:47 time: 0.8413 data_time: 0.0278 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2502 loss_db: 0.0590 loss: 0.6411 2022/08/30 20:05:47 - mmengine - INFO - Epoch(train) [963][50/63] lr: 1.6273e-03 eta: 4:52:35 time: 0.8128 data_time: 0.0285 memory: 16201 loss_prob: 0.3617 loss_thr: 0.2621 loss_db: 0.0655 loss: 0.6893 2022/08/30 20:05:51 - mmengine - INFO - Epoch(train) [963][55/63] lr: 1.6273e-03 eta: 4:52:35 time: 0.8211 data_time: 0.0249 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2600 loss_db: 0.0653 loss: 0.6894 2022/08/30 20:05:55 - mmengine - INFO - Epoch(train) [963][60/63] lr: 1.6273e-03 eta: 4:52:22 time: 0.8187 data_time: 0.0238 memory: 16201 loss_prob: 0.3398 loss_thr: 0.2411 loss_db: 0.0612 loss: 0.6420 2022/08/30 20:05:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:06:03 - mmengine - INFO - Epoch(train) [964][5/63] lr: 1.6211e-03 eta: 4:52:22 time: 0.9637 data_time: 0.1903 memory: 16201 loss_prob: 0.3565 loss_thr: 0.2454 loss_db: 0.0634 loss: 0.6653 2022/08/30 20:06:07 - mmengine - INFO - Epoch(train) [964][10/63] lr: 1.6211e-03 eta: 4:52:06 time: 1.0171 data_time: 0.2034 memory: 16201 loss_prob: 0.3994 loss_thr: 0.2652 loss_db: 0.0686 loss: 0.7332 2022/08/30 20:06:12 - mmengine - INFO - Epoch(train) [964][15/63] lr: 1.6211e-03 eta: 4:52:06 time: 0.8558 data_time: 0.0266 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2559 loss_db: 0.0666 loss: 0.7063 2022/08/30 20:06:16 - mmengine - INFO - Epoch(train) [964][20/63] lr: 1.6211e-03 eta: 4:51:53 time: 0.8508 data_time: 0.0252 memory: 16201 loss_prob: 0.3420 loss_thr: 0.2455 loss_db: 0.0606 loss: 0.6481 2022/08/30 20:06:20 - mmengine - INFO - Epoch(train) [964][25/63] lr: 1.6211e-03 eta: 4:51:53 time: 0.8818 data_time: 0.0363 memory: 16201 loss_prob: 0.3432 loss_thr: 0.2479 loss_db: 0.0621 loss: 0.6531 2022/08/30 20:06:25 - mmengine - INFO - Epoch(train) [964][30/63] lr: 1.6211e-03 eta: 4:51:41 time: 0.8949 data_time: 0.0311 memory: 16201 loss_prob: 0.3314 loss_thr: 0.2374 loss_db: 0.0592 loss: 0.6280 2022/08/30 20:06:29 - mmengine - INFO - Epoch(train) [964][35/63] lr: 1.6211e-03 eta: 4:51:41 time: 0.8366 data_time: 0.0248 memory: 16201 loss_prob: 0.3276 loss_thr: 0.2334 loss_db: 0.0579 loss: 0.6189 2022/08/30 20:06:33 - mmengine - INFO - Epoch(train) [964][40/63] lr: 1.6211e-03 eta: 4:51:28 time: 0.8332 data_time: 0.0363 memory: 16201 loss_prob: 0.3294 loss_thr: 0.2452 loss_db: 0.0595 loss: 0.6341 2022/08/30 20:06:38 - mmengine - INFO - Epoch(train) [964][45/63] lr: 1.6211e-03 eta: 4:51:28 time: 0.9100 data_time: 0.0416 memory: 16201 loss_prob: 0.3454 loss_thr: 0.2623 loss_db: 0.0612 loss: 0.6689 2022/08/30 20:06:42 - mmengine - INFO - Epoch(train) [964][50/63] lr: 1.6211e-03 eta: 4:51:16 time: 0.9012 data_time: 0.0352 memory: 16201 loss_prob: 0.3457 loss_thr: 0.2613 loss_db: 0.0599 loss: 0.6668 2022/08/30 20:06:46 - mmengine - INFO - Epoch(train) [964][55/63] lr: 1.6211e-03 eta: 4:51:16 time: 0.8415 data_time: 0.0301 memory: 16201 loss_prob: 0.4420 loss_thr: 0.2483 loss_db: 0.0669 loss: 0.7573 2022/08/30 20:06:50 - mmengine - INFO - Epoch(train) [964][60/63] lr: 1.6211e-03 eta: 4:51:03 time: 0.8442 data_time: 0.0341 memory: 16201 loss_prob: 0.4715 loss_thr: 0.2581 loss_db: 0.0714 loss: 0.8010 2022/08/30 20:06:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:06:58 - mmengine - INFO - Epoch(train) [965][5/63] lr: 1.6149e-03 eta: 4:51:03 time: 0.9570 data_time: 0.2023 memory: 16201 loss_prob: 0.3804 loss_thr: 0.2757 loss_db: 0.0684 loss: 0.7245 2022/08/30 20:07:03 - mmengine - INFO - Epoch(train) [965][10/63] lr: 1.6149e-03 eta: 4:50:47 time: 1.0289 data_time: 0.2170 memory: 16201 loss_prob: 0.3934 loss_thr: 0.2775 loss_db: 0.0701 loss: 0.7410 2022/08/30 20:07:07 - mmengine - INFO - Epoch(train) [965][15/63] lr: 1.6149e-03 eta: 4:50:47 time: 0.8534 data_time: 0.0273 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2570 loss_db: 0.0649 loss: 0.6957 2022/08/30 20:07:11 - mmengine - INFO - Epoch(train) [965][20/63] lr: 1.6149e-03 eta: 4:50:34 time: 0.8570 data_time: 0.0258 memory: 16201 loss_prob: 0.3240 loss_thr: 0.2325 loss_db: 0.0569 loss: 0.6134 2022/08/30 20:07:16 - mmengine - INFO - Epoch(train) [965][25/63] lr: 1.6149e-03 eta: 4:50:34 time: 0.8807 data_time: 0.0443 memory: 16201 loss_prob: 0.3242 loss_thr: 0.2459 loss_db: 0.0579 loss: 0.6280 2022/08/30 20:07:20 - mmengine - INFO - Epoch(train) [965][30/63] lr: 1.6149e-03 eta: 4:50:22 time: 0.8582 data_time: 0.0323 memory: 16201 loss_prob: 0.3556 loss_thr: 0.2664 loss_db: 0.0649 loss: 0.6868 2022/08/30 20:07:24 - mmengine - INFO - Epoch(train) [965][35/63] lr: 1.6149e-03 eta: 4:50:22 time: 0.8267 data_time: 0.0213 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2579 loss_db: 0.0663 loss: 0.6861 2022/08/30 20:07:28 - mmengine - INFO - Epoch(train) [965][40/63] lr: 1.6149e-03 eta: 4:50:09 time: 0.8316 data_time: 0.0332 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2346 loss_db: 0.0593 loss: 0.6468 2022/08/30 20:07:33 - mmengine - INFO - Epoch(train) [965][45/63] lr: 1.6149e-03 eta: 4:50:09 time: 0.8490 data_time: 0.0331 memory: 16201 loss_prob: 0.3351 loss_thr: 0.2311 loss_db: 0.0546 loss: 0.6208 2022/08/30 20:07:37 - mmengine - INFO - Epoch(train) [965][50/63] lr: 1.6149e-03 eta: 4:49:57 time: 0.8790 data_time: 0.0267 memory: 16201 loss_prob: 0.3260 loss_thr: 0.2427 loss_db: 0.0591 loss: 0.6278 2022/08/30 20:07:42 - mmengine - INFO - Epoch(train) [965][55/63] lr: 1.6149e-03 eta: 4:49:57 time: 0.8901 data_time: 0.0380 memory: 16201 loss_prob: 0.3273 loss_thr: 0.2431 loss_db: 0.0588 loss: 0.6292 2022/08/30 20:07:46 - mmengine - INFO - Epoch(train) [965][60/63] lr: 1.6149e-03 eta: 4:49:44 time: 0.8478 data_time: 0.0436 memory: 16201 loss_prob: 0.3143 loss_thr: 0.2354 loss_db: 0.0550 loss: 0.6046 2022/08/30 20:07:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:07:54 - mmengine - INFO - Epoch(train) [966][5/63] lr: 1.6087e-03 eta: 4:49:44 time: 0.9778 data_time: 0.1947 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2452 loss_db: 0.0559 loss: 0.6125 2022/08/30 20:07:58 - mmengine - INFO - Epoch(train) [966][10/63] lr: 1.6087e-03 eta: 4:49:28 time: 1.0548 data_time: 0.2140 memory: 16201 loss_prob: 0.3209 loss_thr: 0.2458 loss_db: 0.0585 loss: 0.6252 2022/08/30 20:08:03 - mmengine - INFO - Epoch(train) [966][15/63] lr: 1.6087e-03 eta: 4:49:28 time: 0.8965 data_time: 0.0364 memory: 16201 loss_prob: 0.3430 loss_thr: 0.2551 loss_db: 0.0613 loss: 0.6593 2022/08/30 20:08:07 - mmengine - INFO - Epoch(train) [966][20/63] lr: 1.6087e-03 eta: 4:49:15 time: 0.8806 data_time: 0.0253 memory: 16201 loss_prob: 0.3605 loss_thr: 0.2420 loss_db: 0.0649 loss: 0.6674 2022/08/30 20:08:11 - mmengine - INFO - Epoch(train) [966][25/63] lr: 1.6087e-03 eta: 4:49:15 time: 0.8381 data_time: 0.0340 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2281 loss_db: 0.0623 loss: 0.6364 2022/08/30 20:08:15 - mmengine - INFO - Epoch(train) [966][30/63] lr: 1.6087e-03 eta: 4:49:03 time: 0.8455 data_time: 0.0314 memory: 16201 loss_prob: 0.3444 loss_thr: 0.2469 loss_db: 0.0619 loss: 0.6533 2022/08/30 20:08:20 - mmengine - INFO - Epoch(train) [966][35/63] lr: 1.6087e-03 eta: 4:49:03 time: 0.8648 data_time: 0.0281 memory: 16201 loss_prob: 0.3805 loss_thr: 0.2612 loss_db: 0.0686 loss: 0.7103 2022/08/30 20:08:24 - mmengine - INFO - Epoch(train) [966][40/63] lr: 1.6087e-03 eta: 4:48:50 time: 0.8772 data_time: 0.0251 memory: 16201 loss_prob: 0.3759 loss_thr: 0.2573 loss_db: 0.0668 loss: 0.7000 2022/08/30 20:08:29 - mmengine - INFO - Epoch(train) [966][45/63] lr: 1.6087e-03 eta: 4:48:50 time: 0.8768 data_time: 0.0286 memory: 16201 loss_prob: 0.3610 loss_thr: 0.2442 loss_db: 0.0633 loss: 0.6685 2022/08/30 20:08:33 - mmengine - INFO - Epoch(train) [966][50/63] lr: 1.6087e-03 eta: 4:48:38 time: 0.8405 data_time: 0.0304 memory: 16201 loss_prob: 0.3664 loss_thr: 0.2558 loss_db: 0.0640 loss: 0.6861 2022/08/30 20:08:37 - mmengine - INFO - Epoch(train) [966][55/63] lr: 1.6087e-03 eta: 4:48:38 time: 0.8411 data_time: 0.0269 memory: 16201 loss_prob: 0.3343 loss_thr: 0.2400 loss_db: 0.0591 loss: 0.6335 2022/08/30 20:08:41 - mmengine - INFO - Epoch(train) [966][60/63] lr: 1.6087e-03 eta: 4:48:25 time: 0.8503 data_time: 0.0369 memory: 16201 loss_prob: 0.3277 loss_thr: 0.2269 loss_db: 0.0579 loss: 0.6125 2022/08/30 20:08:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:08:49 - mmengine - INFO - Epoch(train) [967][5/63] lr: 1.6025e-03 eta: 4:48:25 time: 0.9102 data_time: 0.1784 memory: 16201 loss_prob: 0.3619 loss_thr: 0.2549 loss_db: 0.0640 loss: 0.6809 2022/08/30 20:08:53 - mmengine - INFO - Epoch(train) [967][10/63] lr: 1.6025e-03 eta: 4:48:09 time: 0.9996 data_time: 0.1939 memory: 16201 loss_prob: 0.4250 loss_thr: 0.2784 loss_db: 0.0709 loss: 0.7742 2022/08/30 20:08:57 - mmengine - INFO - Epoch(train) [967][15/63] lr: 1.6025e-03 eta: 4:48:09 time: 0.8480 data_time: 0.0306 memory: 16201 loss_prob: 0.4257 loss_thr: 0.2776 loss_db: 0.0705 loss: 0.7738 2022/08/30 20:09:01 - mmengine - INFO - Epoch(train) [967][20/63] lr: 1.6025e-03 eta: 4:47:56 time: 0.8182 data_time: 0.0228 memory: 16201 loss_prob: 0.3671 loss_thr: 0.2589 loss_db: 0.0653 loss: 0.6914 2022/08/30 20:09:06 - mmengine - INFO - Epoch(train) [967][25/63] lr: 1.6025e-03 eta: 4:47:56 time: 0.8339 data_time: 0.0313 memory: 16201 loss_prob: 0.3646 loss_thr: 0.2519 loss_db: 0.0662 loss: 0.6827 2022/08/30 20:09:10 - mmengine - INFO - Epoch(train) [967][30/63] lr: 1.6025e-03 eta: 4:47:43 time: 0.8501 data_time: 0.0351 memory: 16201 loss_prob: 0.3792 loss_thr: 0.2471 loss_db: 0.0640 loss: 0.6903 2022/08/30 20:09:14 - mmengine - INFO - Epoch(train) [967][35/63] lr: 1.6025e-03 eta: 4:47:43 time: 0.8540 data_time: 0.0382 memory: 16201 loss_prob: 0.4066 loss_thr: 0.2632 loss_db: 0.0694 loss: 0.7392 2022/08/30 20:09:19 - mmengine - INFO - Epoch(train) [967][40/63] lr: 1.6025e-03 eta: 4:47:31 time: 0.8867 data_time: 0.0368 memory: 16201 loss_prob: 0.3824 loss_thr: 0.2655 loss_db: 0.0679 loss: 0.7157 2022/08/30 20:09:23 - mmengine - INFO - Epoch(train) [967][45/63] lr: 1.6025e-03 eta: 4:47:31 time: 0.8904 data_time: 0.0335 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2565 loss_db: 0.0635 loss: 0.6852 2022/08/30 20:09:27 - mmengine - INFO - Epoch(train) [967][50/63] lr: 1.6025e-03 eta: 4:47:18 time: 0.8263 data_time: 0.0277 memory: 16201 loss_prob: 0.3615 loss_thr: 0.2553 loss_db: 0.0646 loss: 0.6815 2022/08/30 20:09:31 - mmengine - INFO - Epoch(train) [967][55/63] lr: 1.6025e-03 eta: 4:47:18 time: 0.8078 data_time: 0.0287 memory: 16201 loss_prob: 0.3421 loss_thr: 0.2485 loss_db: 0.0613 loss: 0.6519 2022/08/30 20:09:35 - mmengine - INFO - Epoch(train) [967][60/63] lr: 1.6025e-03 eta: 4:47:06 time: 0.8227 data_time: 0.0325 memory: 16201 loss_prob: 0.3319 loss_thr: 0.2457 loss_db: 0.0589 loss: 0.6365 2022/08/30 20:09:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:09:44 - mmengine - INFO - Epoch(train) [968][5/63] lr: 1.5963e-03 eta: 4:47:06 time: 1.0622 data_time: 0.2570 memory: 16201 loss_prob: 0.3470 loss_thr: 0.2543 loss_db: 0.0609 loss: 0.6622 2022/08/30 20:09:49 - mmengine - INFO - Epoch(train) [968][10/63] lr: 1.5963e-03 eta: 4:46:50 time: 1.0803 data_time: 0.2669 memory: 16201 loss_prob: 0.3583 loss_thr: 0.2503 loss_db: 0.0642 loss: 0.6728 2022/08/30 20:09:53 - mmengine - INFO - Epoch(train) [968][15/63] lr: 1.5963e-03 eta: 4:46:50 time: 0.8302 data_time: 0.0253 memory: 16201 loss_prob: 0.3709 loss_thr: 0.2649 loss_db: 0.0674 loss: 0.7032 2022/08/30 20:09:57 - mmengine - INFO - Epoch(train) [968][20/63] lr: 1.5963e-03 eta: 4:46:37 time: 0.8357 data_time: 0.0232 memory: 16201 loss_prob: 0.3635 loss_thr: 0.2692 loss_db: 0.0649 loss: 0.6976 2022/08/30 20:10:01 - mmengine - INFO - Epoch(train) [968][25/63] lr: 1.5963e-03 eta: 4:46:37 time: 0.8621 data_time: 0.0377 memory: 16201 loss_prob: 0.3625 loss_thr: 0.2647 loss_db: 0.0642 loss: 0.6913 2022/08/30 20:10:05 - mmengine - INFO - Epoch(train) [968][30/63] lr: 1.5963e-03 eta: 4:46:24 time: 0.8302 data_time: 0.0306 memory: 16201 loss_prob: 0.3462 loss_thr: 0.2548 loss_db: 0.0619 loss: 0.6630 2022/08/30 20:10:10 - mmengine - INFO - Epoch(train) [968][35/63] lr: 1.5963e-03 eta: 4:46:24 time: 0.8351 data_time: 0.0242 memory: 16201 loss_prob: 0.3336 loss_thr: 0.2435 loss_db: 0.0590 loss: 0.6360 2022/08/30 20:10:14 - mmengine - INFO - Epoch(train) [968][40/63] lr: 1.5963e-03 eta: 4:46:12 time: 0.8378 data_time: 0.0363 memory: 16201 loss_prob: 0.3053 loss_thr: 0.2240 loss_db: 0.0544 loss: 0.5838 2022/08/30 20:10:18 - mmengine - INFO - Epoch(train) [968][45/63] lr: 1.5963e-03 eta: 4:46:12 time: 0.8462 data_time: 0.0338 memory: 16201 loss_prob: 0.3240 loss_thr: 0.2333 loss_db: 0.0584 loss: 0.6157 2022/08/30 20:10:22 - mmengine - INFO - Epoch(train) [968][50/63] lr: 1.5963e-03 eta: 4:45:59 time: 0.8478 data_time: 0.0279 memory: 16201 loss_prob: 0.3645 loss_thr: 0.2605 loss_db: 0.0650 loss: 0.6900 2022/08/30 20:10:26 - mmengine - INFO - Epoch(train) [968][55/63] lr: 1.5963e-03 eta: 4:45:59 time: 0.8276 data_time: 0.0271 memory: 16201 loss_prob: 0.3454 loss_thr: 0.2541 loss_db: 0.0613 loss: 0.6608 2022/08/30 20:10:30 - mmengine - INFO - Epoch(train) [968][60/63] lr: 1.5963e-03 eta: 4:45:47 time: 0.8256 data_time: 0.0238 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2559 loss_db: 0.0626 loss: 0.7043 2022/08/30 20:10:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:10:38 - mmengine - INFO - Epoch(train) [969][5/63] lr: 1.5901e-03 eta: 4:45:47 time: 0.9504 data_time: 0.1990 memory: 16201 loss_prob: 0.3513 loss_thr: 0.2639 loss_db: 0.0633 loss: 0.6785 2022/08/30 20:10:43 - mmengine - INFO - Epoch(train) [969][10/63] lr: 1.5901e-03 eta: 4:45:30 time: 1.0149 data_time: 0.2158 memory: 16201 loss_prob: 0.3521 loss_thr: 0.2711 loss_db: 0.0633 loss: 0.6865 2022/08/30 20:10:47 - mmengine - INFO - Epoch(train) [969][15/63] lr: 1.5901e-03 eta: 4:45:30 time: 0.9010 data_time: 0.0327 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2524 loss_db: 0.0604 loss: 0.6495 2022/08/30 20:10:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:10:52 - mmengine - INFO - Epoch(train) [969][20/63] lr: 1.5901e-03 eta: 4:45:18 time: 0.8948 data_time: 0.0224 memory: 16201 loss_prob: 0.3298 loss_thr: 0.2354 loss_db: 0.0587 loss: 0.6240 2022/08/30 20:10:56 - mmengine - INFO - Epoch(train) [969][25/63] lr: 1.5901e-03 eta: 4:45:18 time: 0.8614 data_time: 0.0418 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2356 loss_db: 0.0585 loss: 0.6240 2022/08/30 20:11:00 - mmengine - INFO - Epoch(train) [969][30/63] lr: 1.5901e-03 eta: 4:45:05 time: 0.8288 data_time: 0.0318 memory: 16201 loss_prob: 0.3724 loss_thr: 0.2555 loss_db: 0.0660 loss: 0.6938 2022/08/30 20:11:04 - mmengine - INFO - Epoch(train) [969][35/63] lr: 1.5901e-03 eta: 4:45:05 time: 0.8059 data_time: 0.0227 memory: 16201 loss_prob: 0.4044 loss_thr: 0.2713 loss_db: 0.0724 loss: 0.7481 2022/08/30 20:11:09 - mmengine - INFO - Epoch(train) [969][40/63] lr: 1.5901e-03 eta: 4:44:53 time: 0.8707 data_time: 0.0398 memory: 16201 loss_prob: 0.3692 loss_thr: 0.2545 loss_db: 0.0663 loss: 0.6900 2022/08/30 20:11:13 - mmengine - INFO - Epoch(train) [969][45/63] lr: 1.5901e-03 eta: 4:44:53 time: 0.8981 data_time: 0.0597 memory: 16201 loss_prob: 0.3431 loss_thr: 0.2481 loss_db: 0.0609 loss: 0.6521 2022/08/30 20:11:17 - mmengine - INFO - Epoch(train) [969][50/63] lr: 1.5901e-03 eta: 4:44:40 time: 0.8526 data_time: 0.0517 memory: 16201 loss_prob: 0.3553 loss_thr: 0.2503 loss_db: 0.0625 loss: 0.6682 2022/08/30 20:11:21 - mmengine - INFO - Epoch(train) [969][55/63] lr: 1.5901e-03 eta: 4:44:40 time: 0.8193 data_time: 0.0253 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2450 loss_db: 0.0647 loss: 0.6695 2022/08/30 20:11:25 - mmengine - INFO - Epoch(train) [969][60/63] lr: 1.5901e-03 eta: 4:44:28 time: 0.8276 data_time: 0.0279 memory: 16201 loss_prob: 0.3390 loss_thr: 0.2377 loss_db: 0.0604 loss: 0.6372 2022/08/30 20:11:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:11:34 - mmengine - INFO - Epoch(train) [970][5/63] lr: 1.5839e-03 eta: 4:44:28 time: 1.0278 data_time: 0.1811 memory: 16201 loss_prob: 0.3715 loss_thr: 0.2628 loss_db: 0.0647 loss: 0.6990 2022/08/30 20:11:38 - mmengine - INFO - Epoch(train) [970][10/63] lr: 1.5839e-03 eta: 4:44:12 time: 1.0268 data_time: 0.2196 memory: 16201 loss_prob: 0.3754 loss_thr: 0.2628 loss_db: 0.0651 loss: 0.7033 2022/08/30 20:11:43 - mmengine - INFO - Epoch(train) [970][15/63] lr: 1.5839e-03 eta: 4:44:12 time: 0.8770 data_time: 0.0591 memory: 16201 loss_prob: 0.3323 loss_thr: 0.2355 loss_db: 0.0592 loss: 0.6270 2022/08/30 20:11:48 - mmengine - INFO - Epoch(train) [970][20/63] lr: 1.5839e-03 eta: 4:43:59 time: 0.9038 data_time: 0.0342 memory: 16201 loss_prob: 0.3295 loss_thr: 0.2428 loss_db: 0.0598 loss: 0.6321 2022/08/30 20:11:52 - mmengine - INFO - Epoch(train) [970][25/63] lr: 1.5839e-03 eta: 4:43:59 time: 0.8970 data_time: 0.0352 memory: 16201 loss_prob: 0.3565 loss_thr: 0.2568 loss_db: 0.0638 loss: 0.6771 2022/08/30 20:11:56 - mmengine - INFO - Epoch(train) [970][30/63] lr: 1.5839e-03 eta: 4:43:47 time: 0.8418 data_time: 0.0309 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2404 loss_db: 0.0591 loss: 0.6341 2022/08/30 20:12:00 - mmengine - INFO - Epoch(train) [970][35/63] lr: 1.5839e-03 eta: 4:43:47 time: 0.8624 data_time: 0.0291 memory: 16201 loss_prob: 0.3647 loss_thr: 0.2598 loss_db: 0.0636 loss: 0.6882 2022/08/30 20:12:04 - mmengine - INFO - Epoch(train) [970][40/63] lr: 1.5839e-03 eta: 4:43:34 time: 0.8476 data_time: 0.0319 memory: 16201 loss_prob: 0.3897 loss_thr: 0.2734 loss_db: 0.0683 loss: 0.7314 2022/08/30 20:12:09 - mmengine - INFO - Epoch(train) [970][45/63] lr: 1.5839e-03 eta: 4:43:34 time: 0.8444 data_time: 0.0356 memory: 16201 loss_prob: 0.3514 loss_thr: 0.2524 loss_db: 0.0629 loss: 0.6667 2022/08/30 20:12:13 - mmengine - INFO - Epoch(train) [970][50/63] lr: 1.5839e-03 eta: 4:43:22 time: 0.8448 data_time: 0.0256 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2301 loss_db: 0.0585 loss: 0.6097 2022/08/30 20:12:17 - mmengine - INFO - Epoch(train) [970][55/63] lr: 1.5839e-03 eta: 4:43:22 time: 0.8365 data_time: 0.0278 memory: 16201 loss_prob: 0.3259 loss_thr: 0.2378 loss_db: 0.0584 loss: 0.6221 2022/08/30 20:12:21 - mmengine - INFO - Epoch(train) [970][60/63] lr: 1.5839e-03 eta: 4:43:09 time: 0.8614 data_time: 0.0330 memory: 16201 loss_prob: 0.3522 loss_thr: 0.2629 loss_db: 0.0626 loss: 0.6778 2022/08/30 20:12:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:12:29 - mmengine - INFO - Epoch(train) [971][5/63] lr: 1.5777e-03 eta: 4:43:09 time: 0.9608 data_time: 0.1876 memory: 16201 loss_prob: 0.3458 loss_thr: 0.2584 loss_db: 0.0609 loss: 0.6651 2022/08/30 20:12:34 - mmengine - INFO - Epoch(train) [971][10/63] lr: 1.5777e-03 eta: 4:42:53 time: 1.0183 data_time: 0.2110 memory: 16201 loss_prob: 0.3588 loss_thr: 0.2614 loss_db: 0.0630 loss: 0.6832 2022/08/30 20:12:38 - mmengine - INFO - Epoch(train) [971][15/63] lr: 1.5777e-03 eta: 4:42:53 time: 0.8976 data_time: 0.0399 memory: 16201 loss_prob: 0.3545 loss_thr: 0.2516 loss_db: 0.0612 loss: 0.6673 2022/08/30 20:12:42 - mmengine - INFO - Epoch(train) [971][20/63] lr: 1.5777e-03 eta: 4:42:40 time: 0.8661 data_time: 0.0219 memory: 16201 loss_prob: 0.3704 loss_thr: 0.2550 loss_db: 0.0653 loss: 0.6907 2022/08/30 20:12:47 - mmengine - INFO - Epoch(train) [971][25/63] lr: 1.5777e-03 eta: 4:42:40 time: 0.8405 data_time: 0.0293 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2422 loss_db: 0.0605 loss: 0.6438 2022/08/30 20:12:51 - mmengine - INFO - Epoch(train) [971][30/63] lr: 1.5777e-03 eta: 4:42:28 time: 0.8491 data_time: 0.0296 memory: 16201 loss_prob: 0.3160 loss_thr: 0.2249 loss_db: 0.0567 loss: 0.5976 2022/08/30 20:12:55 - mmengine - INFO - Epoch(train) [971][35/63] lr: 1.5777e-03 eta: 4:42:28 time: 0.8423 data_time: 0.0396 memory: 16201 loss_prob: 0.3148 loss_thr: 0.2253 loss_db: 0.0561 loss: 0.5962 2022/08/30 20:12:59 - mmengine - INFO - Epoch(train) [971][40/63] lr: 1.5777e-03 eta: 4:42:15 time: 0.8364 data_time: 0.0327 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2451 loss_db: 0.0581 loss: 0.6379 2022/08/30 20:13:04 - mmengine - INFO - Epoch(train) [971][45/63] lr: 1.5777e-03 eta: 4:42:15 time: 0.8583 data_time: 0.0275 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2550 loss_db: 0.0612 loss: 0.6643 2022/08/30 20:13:08 - mmengine - INFO - Epoch(train) [971][50/63] lr: 1.5777e-03 eta: 4:42:03 time: 0.8959 data_time: 0.0364 memory: 16201 loss_prob: 0.3281 loss_thr: 0.2421 loss_db: 0.0592 loss: 0.6294 2022/08/30 20:13:12 - mmengine - INFO - Epoch(train) [971][55/63] lr: 1.5777e-03 eta: 4:42:03 time: 0.8616 data_time: 0.0342 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2365 loss_db: 0.0606 loss: 0.6310 2022/08/30 20:13:17 - mmengine - INFO - Epoch(train) [971][60/63] lr: 1.5777e-03 eta: 4:41:50 time: 0.8312 data_time: 0.0305 memory: 16201 loss_prob: 0.3448 loss_thr: 0.2402 loss_db: 0.0614 loss: 0.6464 2022/08/30 20:13:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:13:25 - mmengine - INFO - Epoch(train) [972][5/63] lr: 1.5715e-03 eta: 4:41:50 time: 0.9779 data_time: 0.1831 memory: 16201 loss_prob: 0.3708 loss_thr: 0.2545 loss_db: 0.0657 loss: 0.6911 2022/08/30 20:13:29 - mmengine - INFO - Epoch(train) [972][10/63] lr: 1.5715e-03 eta: 4:41:34 time: 1.0178 data_time: 0.2005 memory: 16201 loss_prob: 0.3627 loss_thr: 0.2514 loss_db: 0.0658 loss: 0.6798 2022/08/30 20:13:33 - mmengine - INFO - Epoch(train) [972][15/63] lr: 1.5715e-03 eta: 4:41:34 time: 0.8299 data_time: 0.0297 memory: 16201 loss_prob: 0.3808 loss_thr: 0.2594 loss_db: 0.0671 loss: 0.7073 2022/08/30 20:13:38 - mmengine - INFO - Epoch(train) [972][20/63] lr: 1.5715e-03 eta: 4:41:22 time: 0.8652 data_time: 0.0225 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2371 loss_db: 0.0614 loss: 0.6522 2022/08/30 20:13:42 - mmengine - INFO - Epoch(train) [972][25/63] lr: 1.5715e-03 eta: 4:41:22 time: 0.9060 data_time: 0.0415 memory: 16201 loss_prob: 0.3222 loss_thr: 0.2284 loss_db: 0.0579 loss: 0.6085 2022/08/30 20:13:46 - mmengine - INFO - Epoch(train) [972][30/63] lr: 1.5715e-03 eta: 4:41:09 time: 0.8447 data_time: 0.0287 memory: 16201 loss_prob: 0.3425 loss_thr: 0.2455 loss_db: 0.0610 loss: 0.6490 2022/08/30 20:13:50 - mmengine - INFO - Epoch(train) [972][35/63] lr: 1.5715e-03 eta: 4:41:09 time: 0.8116 data_time: 0.0195 memory: 16201 loss_prob: 0.3819 loss_thr: 0.2658 loss_db: 0.0659 loss: 0.7136 2022/08/30 20:13:54 - mmengine - INFO - Epoch(train) [972][40/63] lr: 1.5715e-03 eta: 4:40:57 time: 0.8403 data_time: 0.0285 memory: 16201 loss_prob: 0.3777 loss_thr: 0.2609 loss_db: 0.0675 loss: 0.7061 2022/08/30 20:13:59 - mmengine - INFO - Epoch(train) [972][45/63] lr: 1.5715e-03 eta: 4:40:57 time: 0.9023 data_time: 0.0273 memory: 16201 loss_prob: 0.3535 loss_thr: 0.2600 loss_db: 0.0646 loss: 0.6780 2022/08/30 20:14:04 - mmengine - INFO - Epoch(train) [972][50/63] lr: 1.5715e-03 eta: 4:40:44 time: 0.9160 data_time: 0.0362 memory: 16201 loss_prob: 0.3356 loss_thr: 0.2476 loss_db: 0.0603 loss: 0.6435 2022/08/30 20:14:08 - mmengine - INFO - Epoch(train) [972][55/63] lr: 1.5715e-03 eta: 4:40:44 time: 0.8571 data_time: 0.0326 memory: 16201 loss_prob: 0.3196 loss_thr: 0.2307 loss_db: 0.0572 loss: 0.6075 2022/08/30 20:14:12 - mmengine - INFO - Epoch(train) [972][60/63] lr: 1.5715e-03 eta: 4:40:32 time: 0.8299 data_time: 0.0279 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2245 loss_db: 0.0542 loss: 0.5886 2022/08/30 20:14:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:14:20 - mmengine - INFO - Epoch(train) [973][5/63] lr: 1.5653e-03 eta: 4:40:32 time: 0.9815 data_time: 0.2029 memory: 16201 loss_prob: 0.3543 loss_thr: 0.2572 loss_db: 0.0623 loss: 0.6738 2022/08/30 20:14:24 - mmengine - INFO - Epoch(train) [973][10/63] lr: 1.5653e-03 eta: 4:40:15 time: 0.9923 data_time: 0.2218 memory: 16201 loss_prob: 0.3351 loss_thr: 0.2447 loss_db: 0.0598 loss: 0.6395 2022/08/30 20:14:28 - mmengine - INFO - Epoch(train) [973][15/63] lr: 1.5653e-03 eta: 4:40:15 time: 0.8326 data_time: 0.0305 memory: 16201 loss_prob: 0.3334 loss_thr: 0.2444 loss_db: 0.0611 loss: 0.6389 2022/08/30 20:14:33 - mmengine - INFO - Epoch(train) [973][20/63] lr: 1.5653e-03 eta: 4:40:03 time: 0.8443 data_time: 0.0202 memory: 16201 loss_prob: 0.3354 loss_thr: 0.2409 loss_db: 0.0588 loss: 0.6352 2022/08/30 20:14:37 - mmengine - INFO - Epoch(train) [973][25/63] lr: 1.5653e-03 eta: 4:40:03 time: 0.8662 data_time: 0.0389 memory: 16201 loss_prob: 0.3442 loss_thr: 0.2427 loss_db: 0.0584 loss: 0.6453 2022/08/30 20:14:41 - mmengine - INFO - Epoch(train) [973][30/63] lr: 1.5653e-03 eta: 4:39:50 time: 0.8658 data_time: 0.0346 memory: 16201 loss_prob: 0.3427 loss_thr: 0.2456 loss_db: 0.0605 loss: 0.6489 2022/08/30 20:14:46 - mmengine - INFO - Epoch(train) [973][35/63] lr: 1.5653e-03 eta: 4:39:50 time: 0.8432 data_time: 0.0329 memory: 16201 loss_prob: 0.3755 loss_thr: 0.2603 loss_db: 0.0681 loss: 0.7038 2022/08/30 20:14:51 - mmengine - INFO - Epoch(train) [973][40/63] lr: 1.5653e-03 eta: 4:39:38 time: 0.9206 data_time: 0.0355 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2677 loss_db: 0.0679 loss: 0.7138 2022/08/30 20:14:55 - mmengine - INFO - Epoch(train) [973][45/63] lr: 1.5653e-03 eta: 4:39:38 time: 0.8943 data_time: 0.0274 memory: 16201 loss_prob: 0.3640 loss_thr: 0.2593 loss_db: 0.0639 loss: 0.6871 2022/08/30 20:14:59 - mmengine - INFO - Epoch(train) [973][50/63] lr: 1.5653e-03 eta: 4:39:26 time: 0.8284 data_time: 0.0333 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2634 loss_db: 0.0670 loss: 0.7084 2022/08/30 20:15:03 - mmengine - INFO - Epoch(train) [973][55/63] lr: 1.5653e-03 eta: 4:39:26 time: 0.8441 data_time: 0.0378 memory: 16201 loss_prob: 0.3675 loss_thr: 0.2622 loss_db: 0.0671 loss: 0.6969 2022/08/30 20:15:08 - mmengine - INFO - Epoch(train) [973][60/63] lr: 1.5653e-03 eta: 4:39:13 time: 0.8767 data_time: 0.0523 memory: 16201 loss_prob: 0.3435 loss_thr: 0.2582 loss_db: 0.0600 loss: 0.6617 2022/08/30 20:15:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:15:16 - mmengine - INFO - Epoch(train) [974][5/63] lr: 1.5591e-03 eta: 4:39:13 time: 0.9792 data_time: 0.1976 memory: 16201 loss_prob: 0.3312 loss_thr: 0.2330 loss_db: 0.0580 loss: 0.6223 2022/08/30 20:15:20 - mmengine - INFO - Epoch(train) [974][10/63] lr: 1.5591e-03 eta: 4:38:57 time: 1.0666 data_time: 0.2184 memory: 16201 loss_prob: 0.3269 loss_thr: 0.2341 loss_db: 0.0579 loss: 0.6189 2022/08/30 20:15:24 - mmengine - INFO - Epoch(train) [974][15/63] lr: 1.5591e-03 eta: 4:38:57 time: 0.8439 data_time: 0.0314 memory: 16201 loss_prob: 0.3552 loss_thr: 0.2525 loss_db: 0.0619 loss: 0.6697 2022/08/30 20:15:29 - mmengine - INFO - Epoch(train) [974][20/63] lr: 1.5591e-03 eta: 4:38:44 time: 0.8622 data_time: 0.0231 memory: 16201 loss_prob: 0.3680 loss_thr: 0.2638 loss_db: 0.0652 loss: 0.6970 2022/08/30 20:15:33 - mmengine - INFO - Epoch(train) [974][25/63] lr: 1.5591e-03 eta: 4:38:44 time: 0.8981 data_time: 0.0428 memory: 16201 loss_prob: 0.3270 loss_thr: 0.2452 loss_db: 0.0594 loss: 0.6316 2022/08/30 20:15:37 - mmengine - INFO - Epoch(train) [974][30/63] lr: 1.5591e-03 eta: 4:38:32 time: 0.8611 data_time: 0.0300 memory: 16201 loss_prob: 0.3424 loss_thr: 0.2516 loss_db: 0.0610 loss: 0.6550 2022/08/30 20:15:41 - mmengine - INFO - Epoch(train) [974][35/63] lr: 1.5591e-03 eta: 4:38:32 time: 0.8296 data_time: 0.0213 memory: 16201 loss_prob: 0.3494 loss_thr: 0.2522 loss_db: 0.0626 loss: 0.6642 2022/08/30 20:15:46 - mmengine - INFO - Epoch(train) [974][40/63] lr: 1.5591e-03 eta: 4:38:19 time: 0.8138 data_time: 0.0344 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2424 loss_db: 0.0616 loss: 0.6406 2022/08/30 20:15:51 - mmengine - INFO - Epoch(train) [974][45/63] lr: 1.5591e-03 eta: 4:38:19 time: 0.9038 data_time: 0.0381 memory: 16201 loss_prob: 0.3574 loss_thr: 0.2531 loss_db: 0.0638 loss: 0.6743 2022/08/30 20:15:55 - mmengine - INFO - Epoch(train) [974][50/63] lr: 1.5591e-03 eta: 4:38:07 time: 0.9102 data_time: 0.0373 memory: 16201 loss_prob: 0.3927 loss_thr: 0.2578 loss_db: 0.0642 loss: 0.7147 2022/08/30 20:15:59 - mmengine - INFO - Epoch(train) [974][55/63] lr: 1.5591e-03 eta: 4:38:07 time: 0.8327 data_time: 0.0290 memory: 16201 loss_prob: 0.3737 loss_thr: 0.2484 loss_db: 0.0621 loss: 0.6843 2022/08/30 20:16:03 - mmengine - INFO - Epoch(train) [974][60/63] lr: 1.5591e-03 eta: 4:37:55 time: 0.8190 data_time: 0.0281 memory: 16201 loss_prob: 0.3483 loss_thr: 0.2486 loss_db: 0.0629 loss: 0.6598 2022/08/30 20:16:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:16:11 - mmengine - INFO - Epoch(train) [975][5/63] lr: 1.5529e-03 eta: 4:37:55 time: 0.9670 data_time: 0.1919 memory: 16201 loss_prob: 0.3381 loss_thr: 0.2471 loss_db: 0.0615 loss: 0.6466 2022/08/30 20:16:15 - mmengine - INFO - Epoch(train) [975][10/63] lr: 1.5529e-03 eta: 4:37:38 time: 1.0290 data_time: 0.2049 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2400 loss_db: 0.0621 loss: 0.6583 2022/08/30 20:16:20 - mmengine - INFO - Epoch(train) [975][15/63] lr: 1.5529e-03 eta: 4:37:38 time: 0.8698 data_time: 0.0428 memory: 16201 loss_prob: 0.4060 loss_thr: 0.2591 loss_db: 0.0699 loss: 0.7350 2022/08/30 20:16:24 - mmengine - INFO - Epoch(train) [975][20/63] lr: 1.5529e-03 eta: 4:37:26 time: 0.8605 data_time: 0.0327 memory: 16201 loss_prob: 0.3814 loss_thr: 0.2568 loss_db: 0.0677 loss: 0.7060 2022/08/30 20:16:28 - mmengine - INFO - Epoch(train) [975][25/63] lr: 1.5529e-03 eta: 4:37:26 time: 0.8576 data_time: 0.0375 memory: 16201 loss_prob: 0.3660 loss_thr: 0.2528 loss_db: 0.0661 loss: 0.6850 2022/08/30 20:16:33 - mmengine - INFO - Epoch(train) [975][30/63] lr: 1.5529e-03 eta: 4:37:13 time: 0.8691 data_time: 0.0427 memory: 16201 loss_prob: 0.3865 loss_thr: 0.2618 loss_db: 0.0678 loss: 0.7161 2022/08/30 20:16:37 - mmengine - INFO - Epoch(train) [975][35/63] lr: 1.5529e-03 eta: 4:37:13 time: 0.8500 data_time: 0.0267 memory: 16201 loss_prob: 0.3548 loss_thr: 0.2477 loss_db: 0.0618 loss: 0.6643 2022/08/30 20:16:41 - mmengine - INFO - Epoch(train) [975][40/63] lr: 1.5529e-03 eta: 4:37:01 time: 0.8633 data_time: 0.0335 memory: 16201 loss_prob: 0.3147 loss_thr: 0.2243 loss_db: 0.0560 loss: 0.5950 2022/08/30 20:16:45 - mmengine - INFO - Epoch(train) [975][45/63] lr: 1.5529e-03 eta: 4:37:01 time: 0.8551 data_time: 0.0398 memory: 16201 loss_prob: 0.3463 loss_thr: 0.2389 loss_db: 0.0629 loss: 0.6481 2022/08/30 20:16:49 - mmengine - INFO - Epoch(train) [975][50/63] lr: 1.5529e-03 eta: 4:36:48 time: 0.8212 data_time: 0.0268 memory: 16201 loss_prob: 0.3566 loss_thr: 0.2445 loss_db: 0.0639 loss: 0.6651 2022/08/30 20:16:54 - mmengine - INFO - Epoch(train) [975][55/63] lr: 1.5529e-03 eta: 4:36:48 time: 0.8212 data_time: 0.0294 memory: 16201 loss_prob: 0.3511 loss_thr: 0.2415 loss_db: 0.0626 loss: 0.6552 2022/08/30 20:16:58 - mmengine - INFO - Epoch(train) [975][60/63] lr: 1.5529e-03 eta: 4:36:36 time: 0.8432 data_time: 0.0334 memory: 16201 loss_prob: 0.3735 loss_thr: 0.2614 loss_db: 0.0671 loss: 0.7020 2022/08/30 20:17:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:17:06 - mmengine - INFO - Epoch(train) [976][5/63] lr: 1.5467e-03 eta: 4:36:36 time: 0.9811 data_time: 0.1956 memory: 16201 loss_prob: 0.3267 loss_thr: 0.2397 loss_db: 0.0572 loss: 0.6236 2022/08/30 20:17:10 - mmengine - INFO - Epoch(train) [976][10/63] lr: 1.5467e-03 eta: 4:36:20 time: 1.0122 data_time: 0.2104 memory: 16201 loss_prob: 0.3784 loss_thr: 0.2659 loss_db: 0.0673 loss: 0.7116 2022/08/30 20:17:14 - mmengine - INFO - Epoch(train) [976][15/63] lr: 1.5467e-03 eta: 4:36:20 time: 0.8128 data_time: 0.0337 memory: 16201 loss_prob: 0.3848 loss_thr: 0.2682 loss_db: 0.0694 loss: 0.7224 2022/08/30 20:17:19 - mmengine - INFO - Epoch(train) [976][20/63] lr: 1.5467e-03 eta: 4:36:07 time: 0.9012 data_time: 0.0214 memory: 16201 loss_prob: 0.3464 loss_thr: 0.2459 loss_db: 0.0627 loss: 0.6550 2022/08/30 20:17:23 - mmengine - INFO - Epoch(train) [976][25/63] lr: 1.5467e-03 eta: 4:36:07 time: 0.9360 data_time: 0.0369 memory: 16201 loss_prob: 0.3373 loss_thr: 0.2413 loss_db: 0.0595 loss: 0.6381 2022/08/30 20:17:28 - mmengine - INFO - Epoch(train) [976][30/63] lr: 1.5467e-03 eta: 4:35:55 time: 0.8812 data_time: 0.0347 memory: 16201 loss_prob: 0.3538 loss_thr: 0.2492 loss_db: 0.0623 loss: 0.6653 2022/08/30 20:17:32 - mmengine - INFO - Epoch(train) [976][35/63] lr: 1.5467e-03 eta: 4:35:55 time: 0.8589 data_time: 0.0261 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2479 loss_db: 0.0637 loss: 0.6620 2022/08/30 20:17:36 - mmengine - INFO - Epoch(train) [976][40/63] lr: 1.5467e-03 eta: 4:35:42 time: 0.8427 data_time: 0.0234 memory: 16201 loss_prob: 0.3548 loss_thr: 0.2591 loss_db: 0.0637 loss: 0.6776 2022/08/30 20:17:41 - mmengine - INFO - Epoch(train) [976][45/63] lr: 1.5467e-03 eta: 4:35:42 time: 0.8687 data_time: 0.0307 memory: 16201 loss_prob: 0.3706 loss_thr: 0.2711 loss_db: 0.0642 loss: 0.7059 2022/08/30 20:17:45 - mmengine - INFO - Epoch(train) [976][50/63] lr: 1.5467e-03 eta: 4:35:30 time: 0.8410 data_time: 0.0342 memory: 16201 loss_prob: 0.3305 loss_thr: 0.2462 loss_db: 0.0587 loss: 0.6355 2022/08/30 20:17:50 - mmengine - INFO - Epoch(train) [976][55/63] lr: 1.5467e-03 eta: 4:35:30 time: 0.8838 data_time: 0.0295 memory: 16201 loss_prob: 0.3416 loss_thr: 0.2432 loss_db: 0.0623 loss: 0.6471 2022/08/30 20:17:54 - mmengine - INFO - Epoch(train) [976][60/63] lr: 1.5467e-03 eta: 4:35:18 time: 0.8978 data_time: 0.0326 memory: 16201 loss_prob: 0.3219 loss_thr: 0.2263 loss_db: 0.0577 loss: 0.6059 2022/08/30 20:17:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:18:02 - mmengine - INFO - Epoch(train) [977][5/63] lr: 1.5405e-03 eta: 4:35:18 time: 0.9363 data_time: 0.1827 memory: 16201 loss_prob: 0.3545 loss_thr: 0.2435 loss_db: 0.0608 loss: 0.6587 2022/08/30 20:18:06 - mmengine - INFO - Epoch(train) [977][10/63] lr: 1.5405e-03 eta: 4:35:01 time: 1.0042 data_time: 0.2006 memory: 16201 loss_prob: 0.3333 loss_thr: 0.2286 loss_db: 0.0583 loss: 0.6202 2022/08/30 20:18:10 - mmengine - INFO - Epoch(train) [977][15/63] lr: 1.5405e-03 eta: 4:35:01 time: 0.8767 data_time: 0.0307 memory: 16201 loss_prob: 0.3431 loss_thr: 0.2408 loss_db: 0.0605 loss: 0.6444 2022/08/30 20:18:14 - mmengine - INFO - Epoch(train) [977][20/63] lr: 1.5405e-03 eta: 4:34:49 time: 0.8699 data_time: 0.0233 memory: 16201 loss_prob: 0.3456 loss_thr: 0.2401 loss_db: 0.0622 loss: 0.6479 2022/08/30 20:18:19 - mmengine - INFO - Epoch(train) [977][25/63] lr: 1.5405e-03 eta: 4:34:49 time: 0.8382 data_time: 0.0401 memory: 16201 loss_prob: 0.3671 loss_thr: 0.2547 loss_db: 0.0639 loss: 0.6857 2022/08/30 20:18:23 - mmengine - INFO - Epoch(train) [977][30/63] lr: 1.5405e-03 eta: 4:34:36 time: 0.8204 data_time: 0.0313 memory: 16201 loss_prob: 0.3562 loss_thr: 0.2595 loss_db: 0.0619 loss: 0.6776 2022/08/30 20:18:27 - mmengine - INFO - Epoch(train) [977][35/63] lr: 1.5405e-03 eta: 4:34:36 time: 0.8254 data_time: 0.0247 memory: 16201 loss_prob: 0.3335 loss_thr: 0.2487 loss_db: 0.0610 loss: 0.6432 2022/08/30 20:18:31 - mmengine - INFO - Epoch(train) [977][40/63] lr: 1.5405e-03 eta: 4:34:24 time: 0.8685 data_time: 0.0373 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2435 loss_db: 0.0616 loss: 0.6414 2022/08/30 20:18:35 - mmengine - INFO - Epoch(train) [977][45/63] lr: 1.5405e-03 eta: 4:34:24 time: 0.8461 data_time: 0.0365 memory: 16201 loss_prob: 0.3535 loss_thr: 0.2400 loss_db: 0.0626 loss: 0.6560 2022/08/30 20:18:40 - mmengine - INFO - Epoch(train) [977][50/63] lr: 1.5405e-03 eta: 4:34:12 time: 0.8449 data_time: 0.0285 memory: 16201 loss_prob: 0.3608 loss_thr: 0.2407 loss_db: 0.0639 loss: 0.6655 2022/08/30 20:18:44 - mmengine - INFO - Epoch(train) [977][55/63] lr: 1.5405e-03 eta: 4:34:12 time: 0.8829 data_time: 0.0333 memory: 16201 loss_prob: 0.3379 loss_thr: 0.2387 loss_db: 0.0599 loss: 0.6364 2022/08/30 20:18:48 - mmengine - INFO - Epoch(train) [977][60/63] lr: 1.5405e-03 eta: 4:33:59 time: 0.8605 data_time: 0.0340 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2592 loss_db: 0.0622 loss: 0.6745 2022/08/30 20:18:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:18:57 - mmengine - INFO - Epoch(train) [978][5/63] lr: 1.5343e-03 eta: 4:33:59 time: 0.9800 data_time: 0.1967 memory: 16201 loss_prob: 0.3654 loss_thr: 0.2629 loss_db: 0.0663 loss: 0.6947 2022/08/30 20:19:01 - mmengine - INFO - Epoch(train) [978][10/63] lr: 1.5343e-03 eta: 4:33:43 time: 1.0197 data_time: 0.2148 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2467 loss_db: 0.0615 loss: 0.6516 2022/08/30 20:19:05 - mmengine - INFO - Epoch(train) [978][15/63] lr: 1.5343e-03 eta: 4:33:43 time: 0.8381 data_time: 0.0359 memory: 16201 loss_prob: 0.3327 loss_thr: 0.2362 loss_db: 0.0596 loss: 0.6284 2022/08/30 20:19:09 - mmengine - INFO - Epoch(train) [978][20/63] lr: 1.5343e-03 eta: 4:33:30 time: 0.8483 data_time: 0.0266 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2431 loss_db: 0.0605 loss: 0.6472 2022/08/30 20:19:14 - mmengine - INFO - Epoch(train) [978][25/63] lr: 1.5343e-03 eta: 4:33:30 time: 0.8655 data_time: 0.0363 memory: 16201 loss_prob: 0.3319 loss_thr: 0.2357 loss_db: 0.0580 loss: 0.6256 2022/08/30 20:19:18 - mmengine - INFO - Epoch(train) [978][30/63] lr: 1.5343e-03 eta: 4:33:18 time: 0.9184 data_time: 0.0275 memory: 16201 loss_prob: 0.3226 loss_thr: 0.2341 loss_db: 0.0585 loss: 0.6153 2022/08/30 20:19:23 - mmengine - INFO - Epoch(train) [978][35/63] lr: 1.5343e-03 eta: 4:33:18 time: 0.9132 data_time: 0.0260 memory: 16201 loss_prob: 0.3283 loss_thr: 0.2400 loss_db: 0.0592 loss: 0.6275 2022/08/30 20:19:27 - mmengine - INFO - Epoch(train) [978][40/63] lr: 1.5343e-03 eta: 4:33:06 time: 0.8237 data_time: 0.0286 memory: 16201 loss_prob: 0.3618 loss_thr: 0.2634 loss_db: 0.0646 loss: 0.6899 2022/08/30 20:19:31 - mmengine - INFO - Epoch(train) [978][45/63] lr: 1.5343e-03 eta: 4:33:06 time: 0.8317 data_time: 0.0282 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2637 loss_db: 0.0640 loss: 0.6856 2022/08/30 20:19:35 - mmengine - INFO - Epoch(train) [978][50/63] lr: 1.5343e-03 eta: 4:32:53 time: 0.8360 data_time: 0.0332 memory: 16201 loss_prob: 0.3350 loss_thr: 0.2429 loss_db: 0.0589 loss: 0.6368 2022/08/30 20:19:40 - mmengine - INFO - Epoch(train) [978][55/63] lr: 1.5343e-03 eta: 4:32:53 time: 0.9183 data_time: 0.0297 memory: 16201 loss_prob: 0.3386 loss_thr: 0.2390 loss_db: 0.0593 loss: 0.6369 2022/08/30 20:19:45 - mmengine - INFO - Epoch(train) [978][60/63] lr: 1.5343e-03 eta: 4:32:41 time: 0.9415 data_time: 0.0378 memory: 16201 loss_prob: 0.3448 loss_thr: 0.2447 loss_db: 0.0613 loss: 0.6508 2022/08/30 20:19:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:19:52 - mmengine - INFO - Epoch(train) [979][5/63] lr: 1.5280e-03 eta: 4:32:41 time: 0.9394 data_time: 0.1810 memory: 16201 loss_prob: 0.3334 loss_thr: 0.2330 loss_db: 0.0602 loss: 0.6267 2022/08/30 20:19:57 - mmengine - INFO - Epoch(train) [979][10/63] lr: 1.5280e-03 eta: 4:32:25 time: 1.0190 data_time: 0.2024 memory: 16201 loss_prob: 0.3181 loss_thr: 0.2289 loss_db: 0.0565 loss: 0.6034 2022/08/30 20:20:01 - mmengine - INFO - Epoch(train) [979][15/63] lr: 1.5280e-03 eta: 4:32:25 time: 0.9100 data_time: 0.0385 memory: 16201 loss_prob: 0.3220 loss_thr: 0.2268 loss_db: 0.0578 loss: 0.6065 2022/08/30 20:20:05 - mmengine - INFO - Epoch(train) [979][20/63] lr: 1.5280e-03 eta: 4:32:12 time: 0.8739 data_time: 0.0295 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2417 loss_db: 0.0610 loss: 0.6495 2022/08/30 20:20:10 - mmengine - INFO - Epoch(train) [979][25/63] lr: 1.5280e-03 eta: 4:32:12 time: 0.8483 data_time: 0.0394 memory: 16201 loss_prob: 0.3753 loss_thr: 0.2530 loss_db: 0.0656 loss: 0.6938 2022/08/30 20:20:14 - mmengine - INFO - Epoch(train) [979][30/63] lr: 1.5280e-03 eta: 4:32:00 time: 0.8411 data_time: 0.0303 memory: 16201 loss_prob: 0.3533 loss_thr: 0.2441 loss_db: 0.0617 loss: 0.6592 2022/08/30 20:20:19 - mmengine - INFO - Epoch(train) [979][35/63] lr: 1.5280e-03 eta: 4:32:00 time: 0.8751 data_time: 0.0189 memory: 16201 loss_prob: 0.3676 loss_thr: 0.2597 loss_db: 0.0659 loss: 0.6933 2022/08/30 20:20:23 - mmengine - INFO - Epoch(train) [979][40/63] lr: 1.5280e-03 eta: 4:31:47 time: 0.9023 data_time: 0.0314 memory: 16201 loss_prob: 0.3675 loss_thr: 0.2578 loss_db: 0.0668 loss: 0.6920 2022/08/30 20:20:27 - mmengine - INFO - Epoch(train) [979][45/63] lr: 1.5280e-03 eta: 4:31:47 time: 0.8341 data_time: 0.0302 memory: 16201 loss_prob: 0.3534 loss_thr: 0.2538 loss_db: 0.0610 loss: 0.6683 2022/08/30 20:20:31 - mmengine - INFO - Epoch(train) [979][50/63] lr: 1.5280e-03 eta: 4:31:35 time: 0.8111 data_time: 0.0237 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2610 loss_db: 0.0624 loss: 0.6900 2022/08/30 20:20:37 - mmengine - INFO - Epoch(train) [979][55/63] lr: 1.5280e-03 eta: 4:31:35 time: 0.9834 data_time: 0.0307 memory: 16201 loss_prob: 0.3675 loss_thr: 0.2617 loss_db: 0.0659 loss: 0.6951 2022/08/30 20:20:43 - mmengine - INFO - Epoch(train) [979][60/63] lr: 1.5280e-03 eta: 4:31:23 time: 1.1881 data_time: 0.0323 memory: 16201 loss_prob: 0.3757 loss_thr: 0.2657 loss_db: 0.0673 loss: 0.7087 2022/08/30 20:20:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:20:51 - mmengine - INFO - Epoch(train) [980][5/63] lr: 1.5218e-03 eta: 4:31:23 time: 0.9474 data_time: 0.1829 memory: 16201 loss_prob: 0.3740 loss_thr: 0.2636 loss_db: 0.0658 loss: 0.7034 2022/08/30 20:20:55 - mmengine - INFO - Epoch(train) [980][10/63] lr: 1.5218e-03 eta: 4:31:07 time: 0.9815 data_time: 0.1770 memory: 16201 loss_prob: 0.3187 loss_thr: 0.2390 loss_db: 0.0576 loss: 0.6154 2022/08/30 20:21:00 - mmengine - INFO - Epoch(train) [980][15/63] lr: 1.5218e-03 eta: 4:31:07 time: 0.8917 data_time: 0.0306 memory: 16201 loss_prob: 0.2903 loss_thr: 0.2209 loss_db: 0.0532 loss: 0.5645 2022/08/30 20:21:04 - mmengine - INFO - Epoch(train) [980][20/63] lr: 1.5218e-03 eta: 4:30:55 time: 0.8952 data_time: 0.0338 memory: 16201 loss_prob: 0.3151 loss_thr: 0.2306 loss_db: 0.0566 loss: 0.6023 2022/08/30 20:21:08 - mmengine - INFO - Epoch(train) [980][25/63] lr: 1.5218e-03 eta: 4:30:55 time: 0.8390 data_time: 0.0270 memory: 16201 loss_prob: 0.3840 loss_thr: 0.2754 loss_db: 0.0675 loss: 0.7270 2022/08/30 20:21:12 - mmengine - INFO - Epoch(train) [980][30/63] lr: 1.5218e-03 eta: 4:30:42 time: 0.8429 data_time: 0.0235 memory: 16201 loss_prob: 0.3886 loss_thr: 0.2758 loss_db: 0.0682 loss: 0.7327 2022/08/30 20:21:17 - mmengine - INFO - Epoch(train) [980][35/63] lr: 1.5218e-03 eta: 4:30:42 time: 0.8595 data_time: 0.0247 memory: 16201 loss_prob: 0.3540 loss_thr: 0.2466 loss_db: 0.0619 loss: 0.6624 2022/08/30 20:21:21 - mmengine - INFO - Epoch(train) [980][40/63] lr: 1.5218e-03 eta: 4:30:30 time: 0.8625 data_time: 0.0204 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2593 loss_db: 0.0672 loss: 0.7102 2022/08/30 20:21:25 - mmengine - INFO - Epoch(train) [980][45/63] lr: 1.5218e-03 eta: 4:30:30 time: 0.8478 data_time: 0.0288 memory: 16201 loss_prob: 0.3928 loss_thr: 0.2651 loss_db: 0.0709 loss: 0.7288 2022/08/30 20:21:30 - mmengine - INFO - Epoch(train) [980][50/63] lr: 1.5218e-03 eta: 4:30:17 time: 0.8776 data_time: 0.0328 memory: 16201 loss_prob: 0.3617 loss_thr: 0.2491 loss_db: 0.0656 loss: 0.6764 2022/08/30 20:21:34 - mmengine - INFO - Epoch(train) [980][55/63] lr: 1.5218e-03 eta: 4:30:17 time: 0.8738 data_time: 0.0208 memory: 16201 loss_prob: 0.3324 loss_thr: 0.2295 loss_db: 0.0582 loss: 0.6201 2022/08/30 20:21:38 - mmengine - INFO - Epoch(train) [980][60/63] lr: 1.5218e-03 eta: 4:30:05 time: 0.8622 data_time: 0.0327 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2398 loss_db: 0.0650 loss: 0.6684 2022/08/30 20:21:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:21:40 - mmengine - INFO - Saving checkpoint at 980 epochs 2022/08/30 20:21:49 - mmengine - INFO - Epoch(val) [980][5/32] eta: 4:30:05 time: 0.6240 data_time: 0.1021 memory: 16201 2022/08/30 20:21:52 - mmengine - INFO - Epoch(val) [980][10/32] eta: 0:00:15 time: 0.7025 data_time: 0.1388 memory: 15734 2022/08/30 20:21:55 - mmengine - INFO - Epoch(val) [980][15/32] eta: 0:00:15 time: 0.5981 data_time: 0.0499 memory: 15734 2022/08/30 20:21:58 - mmengine - INFO - Epoch(val) [980][20/32] eta: 0:00:07 time: 0.6229 data_time: 0.0509 memory: 15734 2022/08/30 20:22:01 - mmengine - INFO - Epoch(val) [980][25/32] eta: 0:00:07 time: 0.6555 data_time: 0.0612 memory: 15734 2022/08/30 20:22:04 - mmengine - INFO - Epoch(val) [980][30/32] eta: 0:00:01 time: 0.5927 data_time: 0.0309 memory: 15734 2022/08/30 20:22:05 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 20:22:05 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8368, precision: 0.8183, hmean: 0.8274 2022/08/30 20:22:05 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8368, precision: 0.8392, hmean: 0.8380 2022/08/30 20:22:05 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8368, precision: 0.8604, hmean: 0.8484 2022/08/30 20:22:05 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8344, precision: 0.8792, hmean: 0.8562 2022/08/30 20:22:05 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8310, precision: 0.8952, hmean: 0.8619 2022/08/30 20:22:05 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8060, precision: 0.9163, hmean: 0.8576 2022/08/30 20:22:05 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4449, precision: 0.9595, hmean: 0.6079 2022/08/30 20:22:05 - mmengine - INFO - Epoch(val) [980][32/32] icdar/precision: 0.8952 icdar/recall: 0.8310 icdar/hmean: 0.8619 2022/08/30 20:22:11 - mmengine - INFO - Epoch(train) [981][5/63] lr: 1.5156e-03 eta: 0:00:01 time: 0.9868 data_time: 0.1908 memory: 16201 loss_prob: 0.3867 loss_thr: 0.2644 loss_db: 0.0682 loss: 0.7193 2022/08/30 20:22:15 - mmengine - INFO - Epoch(train) [981][10/63] lr: 1.5156e-03 eta: 4:29:49 time: 0.9972 data_time: 0.1917 memory: 16201 loss_prob: 0.3661 loss_thr: 0.2554 loss_db: 0.0632 loss: 0.6847 2022/08/30 20:22:20 - mmengine - INFO - Epoch(train) [981][15/63] lr: 1.5156e-03 eta: 4:29:49 time: 0.9137 data_time: 0.0315 memory: 16201 loss_prob: 0.3390 loss_thr: 0.2418 loss_db: 0.0605 loss: 0.6413 2022/08/30 20:22:24 - mmengine - INFO - Epoch(train) [981][20/63] lr: 1.5156e-03 eta: 4:29:36 time: 0.9294 data_time: 0.0313 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2552 loss_db: 0.0643 loss: 0.6794 2022/08/30 20:22:28 - mmengine - INFO - Epoch(train) [981][25/63] lr: 1.5156e-03 eta: 4:29:36 time: 0.8381 data_time: 0.0289 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2605 loss_db: 0.0637 loss: 0.6810 2022/08/30 20:22:32 - mmengine - INFO - Epoch(train) [981][30/63] lr: 1.5156e-03 eta: 4:29:24 time: 0.8404 data_time: 0.0279 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2597 loss_db: 0.0623 loss: 0.6679 2022/08/30 20:22:37 - mmengine - INFO - Epoch(train) [981][35/63] lr: 1.5156e-03 eta: 4:29:24 time: 0.8388 data_time: 0.0302 memory: 16201 loss_prob: 0.3448 loss_thr: 0.2504 loss_db: 0.0613 loss: 0.6565 2022/08/30 20:22:42 - mmengine - INFO - Epoch(train) [981][40/63] lr: 1.5156e-03 eta: 4:29:12 time: 0.9176 data_time: 0.0278 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2418 loss_db: 0.0611 loss: 0.6450 2022/08/30 20:22:46 - mmengine - INFO - Epoch(train) [981][45/63] lr: 1.5156e-03 eta: 4:29:12 time: 0.9177 data_time: 0.0335 memory: 16201 loss_prob: 0.3386 loss_thr: 0.2429 loss_db: 0.0598 loss: 0.6413 2022/08/30 20:22:50 - mmengine - INFO - Epoch(train) [981][50/63] lr: 1.5156e-03 eta: 4:28:59 time: 0.8645 data_time: 0.0398 memory: 16201 loss_prob: 0.3190 loss_thr: 0.2325 loss_db: 0.0574 loss: 0.6089 2022/08/30 20:22:54 - mmengine - INFO - Epoch(train) [981][55/63] lr: 1.5156e-03 eta: 4:28:59 time: 0.8429 data_time: 0.0247 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2394 loss_db: 0.0597 loss: 0.6287 2022/08/30 20:22:59 - mmengine - INFO - Epoch(train) [981][60/63] lr: 1.5156e-03 eta: 4:28:47 time: 0.8420 data_time: 0.0262 memory: 16201 loss_prob: 0.3399 loss_thr: 0.2494 loss_db: 0.0590 loss: 0.6483 2022/08/30 20:23:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:23:07 - mmengine - INFO - Epoch(train) [982][5/63] lr: 1.5094e-03 eta: 4:28:47 time: 0.9882 data_time: 0.1924 memory: 16201 loss_prob: 0.3707 loss_thr: 0.2797 loss_db: 0.0669 loss: 0.7172 2022/08/30 20:23:11 - mmengine - INFO - Epoch(train) [982][10/63] lr: 1.5094e-03 eta: 4:28:31 time: 1.0084 data_time: 0.1985 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2478 loss_db: 0.0606 loss: 0.6430 2022/08/30 20:23:15 - mmengine - INFO - Epoch(train) [982][15/63] lr: 1.5094e-03 eta: 4:28:31 time: 0.8348 data_time: 0.0244 memory: 16201 loss_prob: 0.3456 loss_thr: 0.2588 loss_db: 0.0618 loss: 0.6662 2022/08/30 20:23:20 - mmengine - INFO - Epoch(train) [982][20/63] lr: 1.5094e-03 eta: 4:28:18 time: 0.8859 data_time: 0.0216 memory: 16201 loss_prob: 0.3602 loss_thr: 0.2575 loss_db: 0.0642 loss: 0.6819 2022/08/30 20:23:24 - mmengine - INFO - Epoch(train) [982][25/63] lr: 1.5094e-03 eta: 4:28:18 time: 0.8982 data_time: 0.0370 memory: 16201 loss_prob: 0.3554 loss_thr: 0.2409 loss_db: 0.0638 loss: 0.6601 2022/08/30 20:23:28 - mmengine - INFO - Epoch(train) [982][30/63] lr: 1.5094e-03 eta: 4:28:06 time: 0.8623 data_time: 0.0333 memory: 16201 loss_prob: 0.3449 loss_thr: 0.2371 loss_db: 0.0605 loss: 0.6425 2022/08/30 20:23:32 - mmengine - INFO - Epoch(train) [982][35/63] lr: 1.5094e-03 eta: 4:28:06 time: 0.8456 data_time: 0.0297 memory: 16201 loss_prob: 0.3049 loss_thr: 0.2143 loss_db: 0.0535 loss: 0.5727 2022/08/30 20:23:37 - mmengine - INFO - Epoch(train) [982][40/63] lr: 1.5094e-03 eta: 4:27:54 time: 0.8337 data_time: 0.0255 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2162 loss_db: 0.0544 loss: 0.5753 2022/08/30 20:23:41 - mmengine - INFO - Epoch(train) [982][45/63] lr: 1.5094e-03 eta: 4:27:54 time: 0.8828 data_time: 0.0273 memory: 16201 loss_prob: 0.3123 loss_thr: 0.2276 loss_db: 0.0553 loss: 0.5952 2022/08/30 20:23:45 - mmengine - INFO - Epoch(train) [982][50/63] lr: 1.5094e-03 eta: 4:27:41 time: 0.8693 data_time: 0.0318 memory: 16201 loss_prob: 0.3244 loss_thr: 0.2404 loss_db: 0.0581 loss: 0.6229 2022/08/30 20:23:50 - mmengine - INFO - Epoch(train) [982][55/63] lr: 1.5094e-03 eta: 4:27:41 time: 0.8344 data_time: 0.0239 memory: 16201 loss_prob: 0.3522 loss_thr: 0.2491 loss_db: 0.0639 loss: 0.6652 2022/08/30 20:23:54 - mmengine - INFO - Epoch(train) [982][60/63] lr: 1.5094e-03 eta: 4:27:29 time: 0.8432 data_time: 0.0240 memory: 16201 loss_prob: 0.3392 loss_thr: 0.2373 loss_db: 0.0614 loss: 0.6379 2022/08/30 20:23:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:24:02 - mmengine - INFO - Epoch(train) [983][5/63] lr: 1.5031e-03 eta: 4:27:29 time: 0.9494 data_time: 0.1769 memory: 16201 loss_prob: 0.3090 loss_thr: 0.2317 loss_db: 0.0544 loss: 0.5951 2022/08/30 20:24:06 - mmengine - INFO - Epoch(train) [983][10/63] lr: 1.5031e-03 eta: 4:27:13 time: 1.0241 data_time: 0.2031 memory: 16201 loss_prob: 0.3348 loss_thr: 0.2451 loss_db: 0.0591 loss: 0.6389 2022/08/30 20:24:11 - mmengine - INFO - Epoch(train) [983][15/63] lr: 1.5031e-03 eta: 4:27:13 time: 0.8909 data_time: 0.0428 memory: 16201 loss_prob: 0.4091 loss_thr: 0.2669 loss_db: 0.0684 loss: 0.7444 2022/08/30 20:24:15 - mmengine - INFO - Epoch(train) [983][20/63] lr: 1.5031e-03 eta: 4:27:00 time: 0.8647 data_time: 0.0288 memory: 16201 loss_prob: 0.3993 loss_thr: 0.2652 loss_db: 0.0675 loss: 0.7320 2022/08/30 20:24:19 - mmengine - INFO - Epoch(train) [983][25/63] lr: 1.5031e-03 eta: 4:27:00 time: 0.8660 data_time: 0.0357 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2394 loss_db: 0.0594 loss: 0.6290 2022/08/30 20:24:23 - mmengine - INFO - Epoch(train) [983][30/63] lr: 1.5031e-03 eta: 4:26:48 time: 0.8767 data_time: 0.0334 memory: 16201 loss_prob: 0.3315 loss_thr: 0.2324 loss_db: 0.0595 loss: 0.6234 2022/08/30 20:24:28 - mmengine - INFO - Epoch(train) [983][35/63] lr: 1.5031e-03 eta: 4:26:48 time: 0.8492 data_time: 0.0305 memory: 16201 loss_prob: 0.3589 loss_thr: 0.2382 loss_db: 0.0639 loss: 0.6611 2022/08/30 20:24:32 - mmengine - INFO - Epoch(train) [983][40/63] lr: 1.5031e-03 eta: 4:26:35 time: 0.8558 data_time: 0.0350 memory: 16201 loss_prob: 0.3688 loss_thr: 0.2384 loss_db: 0.0636 loss: 0.6708 2022/08/30 20:24:36 - mmengine - INFO - Epoch(train) [983][45/63] lr: 1.5031e-03 eta: 4:26:35 time: 0.8484 data_time: 0.0355 memory: 16201 loss_prob: 0.3783 loss_thr: 0.2590 loss_db: 0.0659 loss: 0.7031 2022/08/30 20:24:41 - mmengine - INFO - Epoch(train) [983][50/63] lr: 1.5031e-03 eta: 4:26:23 time: 0.8534 data_time: 0.0380 memory: 16201 loss_prob: 0.3692 loss_thr: 0.2623 loss_db: 0.0674 loss: 0.6989 2022/08/30 20:24:45 - mmengine - INFO - Epoch(train) [983][55/63] lr: 1.5031e-03 eta: 4:26:23 time: 0.8540 data_time: 0.0318 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2425 loss_db: 0.0628 loss: 0.6540 2022/08/30 20:24:49 - mmengine - INFO - Epoch(train) [983][60/63] lr: 1.5031e-03 eta: 4:26:11 time: 0.8737 data_time: 0.0227 memory: 16201 loss_prob: 0.3385 loss_thr: 0.2486 loss_db: 0.0593 loss: 0.6464 2022/08/30 20:24:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:24:57 - mmengine - INFO - Epoch(train) [984][5/63] lr: 1.4969e-03 eta: 4:26:11 time: 1.0093 data_time: 0.1776 memory: 16201 loss_prob: 0.3329 loss_thr: 0.2436 loss_db: 0.0597 loss: 0.6361 2022/08/30 20:25:01 - mmengine - INFO - Epoch(train) [984][10/63] lr: 1.4969e-03 eta: 4:25:54 time: 0.9992 data_time: 0.1926 memory: 16201 loss_prob: 0.3639 loss_thr: 0.2616 loss_db: 0.0648 loss: 0.6903 2022/08/30 20:25:05 - mmengine - INFO - Epoch(train) [984][15/63] lr: 1.4969e-03 eta: 4:25:54 time: 0.8170 data_time: 0.0342 memory: 16201 loss_prob: 0.3918 loss_thr: 0.2861 loss_db: 0.0693 loss: 0.7472 2022/08/30 20:25:11 - mmengine - INFO - Epoch(train) [984][20/63] lr: 1.4969e-03 eta: 4:25:42 time: 0.9085 data_time: 0.0799 memory: 16201 loss_prob: 0.3599 loss_thr: 0.2604 loss_db: 0.0638 loss: 0.6840 2022/08/30 20:25:15 - mmengine - INFO - Epoch(train) [984][25/63] lr: 1.4969e-03 eta: 4:25:42 time: 0.9382 data_time: 0.0915 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2469 loss_db: 0.0633 loss: 0.6584 2022/08/30 20:25:19 - mmengine - INFO - Epoch(train) [984][30/63] lr: 1.4969e-03 eta: 4:25:30 time: 0.8849 data_time: 0.0410 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2384 loss_db: 0.0610 loss: 0.6313 2022/08/30 20:25:24 - mmengine - INFO - Epoch(train) [984][35/63] lr: 1.4969e-03 eta: 4:25:30 time: 0.8660 data_time: 0.0341 memory: 16201 loss_prob: 0.3217 loss_thr: 0.2283 loss_db: 0.0576 loss: 0.6076 2022/08/30 20:25:28 - mmengine - INFO - Epoch(train) [984][40/63] lr: 1.4969e-03 eta: 4:25:17 time: 0.8321 data_time: 0.0367 memory: 16201 loss_prob: 0.3509 loss_thr: 0.2463 loss_db: 0.0622 loss: 0.6593 2022/08/30 20:25:32 - mmengine - INFO - Epoch(train) [984][45/63] lr: 1.4969e-03 eta: 4:25:17 time: 0.8569 data_time: 0.0335 memory: 16201 loss_prob: 0.3581 loss_thr: 0.2562 loss_db: 0.0640 loss: 0.6783 2022/08/30 20:25:36 - mmengine - INFO - Epoch(train) [984][50/63] lr: 1.4969e-03 eta: 4:25:05 time: 0.8671 data_time: 0.0301 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2651 loss_db: 0.0644 loss: 0.6832 2022/08/30 20:25:41 - mmengine - INFO - Epoch(train) [984][55/63] lr: 1.4969e-03 eta: 4:25:05 time: 0.8548 data_time: 0.0288 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2524 loss_db: 0.0622 loss: 0.6582 2022/08/30 20:25:45 - mmengine - INFO - Epoch(train) [984][60/63] lr: 1.4969e-03 eta: 4:24:53 time: 0.8425 data_time: 0.0264 memory: 16201 loss_prob: 0.3343 loss_thr: 0.2368 loss_db: 0.0596 loss: 0.6306 2022/08/30 20:25:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:25:53 - mmengine - INFO - Epoch(train) [985][5/63] lr: 1.4907e-03 eta: 4:24:53 time: 0.9561 data_time: 0.1792 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2436 loss_db: 0.0611 loss: 0.6484 2022/08/30 20:25:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:25:57 - mmengine - INFO - Epoch(train) [985][10/63] lr: 1.4907e-03 eta: 4:24:36 time: 0.9987 data_time: 0.1905 memory: 16201 loss_prob: 0.3374 loss_thr: 0.2460 loss_db: 0.0592 loss: 0.6426 2022/08/30 20:26:01 - mmengine - INFO - Epoch(train) [985][15/63] lr: 1.4907e-03 eta: 4:24:36 time: 0.8342 data_time: 0.0290 memory: 16201 loss_prob: 0.3292 loss_thr: 0.2392 loss_db: 0.0573 loss: 0.6256 2022/08/30 20:26:05 - mmengine - INFO - Epoch(train) [985][20/63] lr: 1.4907e-03 eta: 4:24:24 time: 0.8521 data_time: 0.0277 memory: 16201 loss_prob: 0.3330 loss_thr: 0.2456 loss_db: 0.0587 loss: 0.6373 2022/08/30 20:26:10 - mmengine - INFO - Epoch(train) [985][25/63] lr: 1.4907e-03 eta: 4:24:24 time: 0.8501 data_time: 0.0384 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2527 loss_db: 0.0608 loss: 0.6481 2022/08/30 20:26:14 - mmengine - INFO - Epoch(train) [985][30/63] lr: 1.4907e-03 eta: 4:24:12 time: 0.8409 data_time: 0.0297 memory: 16201 loss_prob: 0.3466 loss_thr: 0.2586 loss_db: 0.0625 loss: 0.6677 2022/08/30 20:26:18 - mmengine - INFO - Epoch(train) [985][35/63] lr: 1.4907e-03 eta: 4:24:12 time: 0.8370 data_time: 0.0249 memory: 16201 loss_prob: 0.3705 loss_thr: 0.2716 loss_db: 0.0668 loss: 0.7089 2022/08/30 20:26:22 - mmengine - INFO - Epoch(train) [985][40/63] lr: 1.4907e-03 eta: 4:23:59 time: 0.8340 data_time: 0.0330 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2548 loss_db: 0.0645 loss: 0.6732 2022/08/30 20:26:26 - mmengine - INFO - Epoch(train) [985][45/63] lr: 1.4907e-03 eta: 4:23:59 time: 0.8180 data_time: 0.0314 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2734 loss_db: 0.0673 loss: 0.7243 2022/08/30 20:26:31 - mmengine - INFO - Epoch(train) [985][50/63] lr: 1.4907e-03 eta: 4:23:47 time: 0.8585 data_time: 0.0303 memory: 16201 loss_prob: 0.3760 loss_thr: 0.2714 loss_db: 0.0654 loss: 0.7127 2022/08/30 20:26:35 - mmengine - INFO - Epoch(train) [985][55/63] lr: 1.4907e-03 eta: 4:23:47 time: 0.8838 data_time: 0.0434 memory: 16201 loss_prob: 0.3531 loss_thr: 0.2448 loss_db: 0.0631 loss: 0.6609 2022/08/30 20:26:39 - mmengine - INFO - Epoch(train) [985][60/63] lr: 1.4907e-03 eta: 4:23:35 time: 0.8432 data_time: 0.0413 memory: 16201 loss_prob: 0.3580 loss_thr: 0.2422 loss_db: 0.0637 loss: 0.6639 2022/08/30 20:26:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:26:47 - mmengine - INFO - Epoch(train) [986][5/63] lr: 1.4844e-03 eta: 4:23:35 time: 1.0005 data_time: 0.1994 memory: 16201 loss_prob: 0.3322 loss_thr: 0.2313 loss_db: 0.0597 loss: 0.6232 2022/08/30 20:26:52 - mmengine - INFO - Epoch(train) [986][10/63] lr: 1.4844e-03 eta: 4:23:18 time: 1.0358 data_time: 0.2095 memory: 16201 loss_prob: 0.2900 loss_thr: 0.2117 loss_db: 0.0512 loss: 0.5530 2022/08/30 20:26:56 - mmengine - INFO - Epoch(train) [986][15/63] lr: 1.4844e-03 eta: 4:23:18 time: 0.8482 data_time: 0.0273 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2191 loss_db: 0.0539 loss: 0.5778 2022/08/30 20:27:01 - mmengine - INFO - Epoch(train) [986][20/63] lr: 1.4844e-03 eta: 4:23:06 time: 0.8912 data_time: 0.0225 memory: 16201 loss_prob: 0.3441 loss_thr: 0.2431 loss_db: 0.0625 loss: 0.6496 2022/08/30 20:27:05 - mmengine - INFO - Epoch(train) [986][25/63] lr: 1.4844e-03 eta: 4:23:06 time: 0.8973 data_time: 0.0283 memory: 16201 loss_prob: 0.3683 loss_thr: 0.2702 loss_db: 0.0673 loss: 0.7058 2022/08/30 20:27:09 - mmengine - INFO - Epoch(train) [986][30/63] lr: 1.4844e-03 eta: 4:22:54 time: 0.8300 data_time: 0.0262 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2680 loss_db: 0.0643 loss: 0.6896 2022/08/30 20:27:13 - mmengine - INFO - Epoch(train) [986][35/63] lr: 1.4844e-03 eta: 4:22:54 time: 0.8156 data_time: 0.0282 memory: 16201 loss_prob: 0.3513 loss_thr: 0.2630 loss_db: 0.0632 loss: 0.6776 2022/08/30 20:27:17 - mmengine - INFO - Epoch(train) [986][40/63] lr: 1.4844e-03 eta: 4:22:41 time: 0.8258 data_time: 0.0300 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2581 loss_db: 0.0638 loss: 0.6749 2022/08/30 20:27:23 - mmengine - INFO - Epoch(train) [986][45/63] lr: 1.4844e-03 eta: 4:22:41 time: 0.9671 data_time: 0.0332 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2364 loss_db: 0.0602 loss: 0.6353 2022/08/30 20:27:27 - mmengine - INFO - Epoch(train) [986][50/63] lr: 1.4844e-03 eta: 4:22:29 time: 0.9575 data_time: 0.0343 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2383 loss_db: 0.0601 loss: 0.6381 2022/08/30 20:27:32 - mmengine - INFO - Epoch(train) [986][55/63] lr: 1.4844e-03 eta: 4:22:29 time: 0.9195 data_time: 0.0331 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2438 loss_db: 0.0631 loss: 0.6636 2022/08/30 20:27:36 - mmengine - INFO - Epoch(train) [986][60/63] lr: 1.4844e-03 eta: 4:22:17 time: 0.9326 data_time: 0.0360 memory: 16201 loss_prob: 0.3427 loss_thr: 0.2418 loss_db: 0.0616 loss: 0.6461 2022/08/30 20:27:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:27:44 - mmengine - INFO - Epoch(train) [987][5/63] lr: 1.4782e-03 eta: 4:22:17 time: 0.9781 data_time: 0.1861 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2443 loss_db: 0.0601 loss: 0.6389 2022/08/30 20:27:49 - mmengine - INFO - Epoch(train) [987][10/63] lr: 1.4782e-03 eta: 4:22:01 time: 1.0291 data_time: 0.2050 memory: 16201 loss_prob: 0.3324 loss_thr: 0.2419 loss_db: 0.0585 loss: 0.6328 2022/08/30 20:27:53 - mmengine - INFO - Epoch(train) [987][15/63] lr: 1.4782e-03 eta: 4:22:01 time: 0.8783 data_time: 0.0320 memory: 16201 loss_prob: 0.3667 loss_thr: 0.2657 loss_db: 0.0643 loss: 0.6966 2022/08/30 20:27:57 - mmengine - INFO - Epoch(train) [987][20/63] lr: 1.4782e-03 eta: 4:21:48 time: 0.8665 data_time: 0.0288 memory: 16201 loss_prob: 0.3430 loss_thr: 0.2409 loss_db: 0.0599 loss: 0.6437 2022/08/30 20:28:02 - mmengine - INFO - Epoch(train) [987][25/63] lr: 1.4782e-03 eta: 4:21:48 time: 0.8633 data_time: 0.0405 memory: 16201 loss_prob: 0.3400 loss_thr: 0.2308 loss_db: 0.0613 loss: 0.6321 2022/08/30 20:28:06 - mmengine - INFO - Epoch(train) [987][30/63] lr: 1.4782e-03 eta: 4:21:36 time: 0.8711 data_time: 0.0323 memory: 16201 loss_prob: 0.3357 loss_thr: 0.2496 loss_db: 0.0601 loss: 0.6455 2022/08/30 20:28:11 - mmengine - INFO - Epoch(train) [987][35/63] lr: 1.4782e-03 eta: 4:21:36 time: 0.8884 data_time: 0.0301 memory: 16201 loss_prob: 0.3263 loss_thr: 0.2453 loss_db: 0.0579 loss: 0.6294 2022/08/30 20:28:15 - mmengine - INFO - Epoch(train) [987][40/63] lr: 1.4782e-03 eta: 4:21:24 time: 0.8568 data_time: 0.0265 memory: 16201 loss_prob: 0.3517 loss_thr: 0.2470 loss_db: 0.0636 loss: 0.6622 2022/08/30 20:28:19 - mmengine - INFO - Epoch(train) [987][45/63] lr: 1.4782e-03 eta: 4:21:24 time: 0.8777 data_time: 0.0248 memory: 16201 loss_prob: 0.3443 loss_thr: 0.2477 loss_db: 0.0607 loss: 0.6526 2022/08/30 20:28:23 - mmengine - INFO - Epoch(train) [987][50/63] lr: 1.4782e-03 eta: 4:21:11 time: 0.8815 data_time: 0.0330 memory: 16201 loss_prob: 0.3487 loss_thr: 0.2549 loss_db: 0.0611 loss: 0.6647 2022/08/30 20:28:27 - mmengine - INFO - Epoch(train) [987][55/63] lr: 1.4782e-03 eta: 4:21:11 time: 0.8096 data_time: 0.0317 memory: 16201 loss_prob: 0.3683 loss_thr: 0.2616 loss_db: 0.0651 loss: 0.6950 2022/08/30 20:28:32 - mmengine - INFO - Epoch(train) [987][60/63] lr: 1.4782e-03 eta: 4:20:59 time: 0.8306 data_time: 0.0293 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2519 loss_db: 0.0647 loss: 0.6789 2022/08/30 20:28:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:28:39 - mmengine - INFO - Epoch(train) [988][5/63] lr: 1.4719e-03 eta: 4:20:59 time: 0.9424 data_time: 0.1739 memory: 16201 loss_prob: 0.3275 loss_thr: 0.2430 loss_db: 0.0589 loss: 0.6294 2022/08/30 20:28:44 - mmengine - INFO - Epoch(train) [988][10/63] lr: 1.4719e-03 eta: 4:20:43 time: 0.9989 data_time: 0.1846 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2408 loss_db: 0.0609 loss: 0.6363 2022/08/30 20:28:48 - mmengine - INFO - Epoch(train) [988][15/63] lr: 1.4719e-03 eta: 4:20:43 time: 0.8276 data_time: 0.0264 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2405 loss_db: 0.0627 loss: 0.6498 2022/08/30 20:28:53 - mmengine - INFO - Epoch(train) [988][20/63] lr: 1.4719e-03 eta: 4:20:30 time: 0.8992 data_time: 0.0266 memory: 16201 loss_prob: 0.3582 loss_thr: 0.2485 loss_db: 0.0634 loss: 0.6701 2022/08/30 20:28:57 - mmengine - INFO - Epoch(train) [988][25/63] lr: 1.4719e-03 eta: 4:20:30 time: 0.9126 data_time: 0.0346 memory: 16201 loss_prob: 0.3350 loss_thr: 0.2414 loss_db: 0.0598 loss: 0.6361 2022/08/30 20:29:01 - mmengine - INFO - Epoch(train) [988][30/63] lr: 1.4719e-03 eta: 4:20:18 time: 0.8492 data_time: 0.0274 memory: 16201 loss_prob: 0.3037 loss_thr: 0.2294 loss_db: 0.0543 loss: 0.5875 2022/08/30 20:29:05 - mmengine - INFO - Epoch(train) [988][35/63] lr: 1.4719e-03 eta: 4:20:18 time: 0.8402 data_time: 0.0253 memory: 16201 loss_prob: 0.3280 loss_thr: 0.2352 loss_db: 0.0581 loss: 0.6214 2022/08/30 20:29:10 - mmengine - INFO - Epoch(train) [988][40/63] lr: 1.4719e-03 eta: 4:20:06 time: 0.8979 data_time: 0.0298 memory: 16201 loss_prob: 0.3218 loss_thr: 0.2220 loss_db: 0.0575 loss: 0.6012 2022/08/30 20:29:14 - mmengine - INFO - Epoch(train) [988][45/63] lr: 1.4719e-03 eta: 4:20:06 time: 0.9100 data_time: 0.0347 memory: 16201 loss_prob: 0.3446 loss_thr: 0.2438 loss_db: 0.0610 loss: 0.6494 2022/08/30 20:29:18 - mmengine - INFO - Epoch(train) [988][50/63] lr: 1.4719e-03 eta: 4:19:54 time: 0.8357 data_time: 0.0366 memory: 16201 loss_prob: 0.3630 loss_thr: 0.2551 loss_db: 0.0637 loss: 0.6819 2022/08/30 20:29:23 - mmengine - INFO - Epoch(train) [988][55/63] lr: 1.4719e-03 eta: 4:19:54 time: 0.8436 data_time: 0.0353 memory: 16201 loss_prob: 0.3686 loss_thr: 0.2456 loss_db: 0.0649 loss: 0.6791 2022/08/30 20:29:27 - mmengine - INFO - Epoch(train) [988][60/63] lr: 1.4719e-03 eta: 4:19:41 time: 0.8380 data_time: 0.0315 memory: 16201 loss_prob: 0.3718 loss_thr: 0.2485 loss_db: 0.0648 loss: 0.6850 2022/08/30 20:29:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:29:36 - mmengine - INFO - Epoch(train) [989][5/63] lr: 1.4657e-03 eta: 4:19:41 time: 1.0827 data_time: 0.2045 memory: 16201 loss_prob: 0.3288 loss_thr: 0.2282 loss_db: 0.0587 loss: 0.6157 2022/08/30 20:29:40 - mmengine - INFO - Epoch(train) [989][10/63] lr: 1.4657e-03 eta: 4:19:25 time: 1.0358 data_time: 0.2098 memory: 16201 loss_prob: 0.3518 loss_thr: 0.2354 loss_db: 0.0585 loss: 0.6457 2022/08/30 20:29:44 - mmengine - INFO - Epoch(train) [989][15/63] lr: 1.4657e-03 eta: 4:19:25 time: 0.8218 data_time: 0.0284 memory: 16201 loss_prob: 0.3678 loss_thr: 0.2432 loss_db: 0.0633 loss: 0.6743 2022/08/30 20:29:49 - mmengine - INFO - Epoch(train) [989][20/63] lr: 1.4657e-03 eta: 4:19:13 time: 0.8908 data_time: 0.0209 memory: 16201 loss_prob: 0.3532 loss_thr: 0.2495 loss_db: 0.0632 loss: 0.6659 2022/08/30 20:29:53 - mmengine - INFO - Epoch(train) [989][25/63] lr: 1.4657e-03 eta: 4:19:13 time: 0.9095 data_time: 0.0296 memory: 16201 loss_prob: 0.3513 loss_thr: 0.2524 loss_db: 0.0615 loss: 0.6652 2022/08/30 20:29:58 - mmengine - INFO - Epoch(train) [989][30/63] lr: 1.4657e-03 eta: 4:19:00 time: 0.8337 data_time: 0.0280 memory: 16201 loss_prob: 0.3461 loss_thr: 0.2481 loss_db: 0.0615 loss: 0.6556 2022/08/30 20:30:02 - mmengine - INFO - Epoch(train) [989][35/63] lr: 1.4657e-03 eta: 4:19:00 time: 0.8139 data_time: 0.0281 memory: 16201 loss_prob: 0.3327 loss_thr: 0.2496 loss_db: 0.0589 loss: 0.6412 2022/08/30 20:30:06 - mmengine - INFO - Epoch(train) [989][40/63] lr: 1.4657e-03 eta: 4:18:48 time: 0.8286 data_time: 0.0242 memory: 16201 loss_prob: 0.3494 loss_thr: 0.2516 loss_db: 0.0633 loss: 0.6643 2022/08/30 20:30:10 - mmengine - INFO - Epoch(train) [989][45/63] lr: 1.4657e-03 eta: 4:18:48 time: 0.8870 data_time: 0.0252 memory: 16201 loss_prob: 0.3428 loss_thr: 0.2446 loss_db: 0.0614 loss: 0.6488 2022/08/30 20:30:15 - mmengine - INFO - Epoch(train) [989][50/63] lr: 1.4657e-03 eta: 4:18:36 time: 0.8882 data_time: 0.0302 memory: 16201 loss_prob: 0.3126 loss_thr: 0.2371 loss_db: 0.0545 loss: 0.6043 2022/08/30 20:30:19 - mmengine - INFO - Epoch(train) [989][55/63] lr: 1.4657e-03 eta: 4:18:36 time: 0.8669 data_time: 0.0258 memory: 16201 loss_prob: 0.3224 loss_thr: 0.2453 loss_db: 0.0582 loss: 0.6259 2022/08/30 20:30:23 - mmengine - INFO - Epoch(train) [989][60/63] lr: 1.4657e-03 eta: 4:18:23 time: 0.8512 data_time: 0.0275 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2557 loss_db: 0.0602 loss: 0.6456 2022/08/30 20:30:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:30:31 - mmengine - INFO - Epoch(train) [990][5/63] lr: 1.4594e-03 eta: 4:18:23 time: 0.9297 data_time: 0.1710 memory: 16201 loss_prob: 0.3188 loss_thr: 0.2402 loss_db: 0.0580 loss: 0.6170 2022/08/30 20:30:35 - mmengine - INFO - Epoch(train) [990][10/63] lr: 1.4594e-03 eta: 4:18:07 time: 0.9945 data_time: 0.1916 memory: 16201 loss_prob: 0.3496 loss_thr: 0.2411 loss_db: 0.0618 loss: 0.6524 2022/08/30 20:30:40 - mmengine - INFO - Epoch(train) [990][15/63] lr: 1.4594e-03 eta: 4:18:07 time: 0.8975 data_time: 0.0344 memory: 16201 loss_prob: 0.3669 loss_thr: 0.2596 loss_db: 0.0641 loss: 0.6906 2022/08/30 20:30:44 - mmengine - INFO - Epoch(train) [990][20/63] lr: 1.4594e-03 eta: 4:17:55 time: 0.9088 data_time: 0.0211 memory: 16201 loss_prob: 0.3324 loss_thr: 0.2423 loss_db: 0.0591 loss: 0.6338 2022/08/30 20:30:49 - mmengine - INFO - Epoch(train) [990][25/63] lr: 1.4594e-03 eta: 4:17:55 time: 0.8736 data_time: 0.0314 memory: 16201 loss_prob: 0.3316 loss_thr: 0.2386 loss_db: 0.0589 loss: 0.6291 2022/08/30 20:30:53 - mmengine - INFO - Epoch(train) [990][30/63] lr: 1.4594e-03 eta: 4:17:43 time: 0.8643 data_time: 0.0246 memory: 16201 loss_prob: 0.3578 loss_thr: 0.2545 loss_db: 0.0639 loss: 0.6761 2022/08/30 20:30:57 - mmengine - INFO - Epoch(train) [990][35/63] lr: 1.4594e-03 eta: 4:17:43 time: 0.8358 data_time: 0.0193 memory: 16201 loss_prob: 0.3356 loss_thr: 0.2432 loss_db: 0.0610 loss: 0.6398 2022/08/30 20:31:01 - mmengine - INFO - Epoch(train) [990][40/63] lr: 1.4594e-03 eta: 4:17:30 time: 0.8360 data_time: 0.0274 memory: 16201 loss_prob: 0.3017 loss_thr: 0.2264 loss_db: 0.0537 loss: 0.5819 2022/08/30 20:31:05 - mmengine - INFO - Epoch(train) [990][45/63] lr: 1.4594e-03 eta: 4:17:30 time: 0.8368 data_time: 0.0268 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2430 loss_db: 0.0577 loss: 0.6298 2022/08/30 20:31:10 - mmengine - INFO - Epoch(train) [990][50/63] lr: 1.4594e-03 eta: 4:17:18 time: 0.8544 data_time: 0.0283 memory: 16201 loss_prob: 0.3486 loss_thr: 0.2605 loss_db: 0.0616 loss: 0.6708 2022/08/30 20:31:14 - mmengine - INFO - Epoch(train) [990][55/63] lr: 1.4594e-03 eta: 4:17:18 time: 0.8688 data_time: 0.0329 memory: 16201 loss_prob: 0.3244 loss_thr: 0.2470 loss_db: 0.0581 loss: 0.6294 2022/08/30 20:31:18 - mmengine - INFO - Epoch(train) [990][60/63] lr: 1.4594e-03 eta: 4:17:06 time: 0.8490 data_time: 0.0337 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2382 loss_db: 0.0585 loss: 0.6091 2022/08/30 20:31:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:31:26 - mmengine - INFO - Epoch(train) [991][5/63] lr: 1.4532e-03 eta: 4:17:06 time: 0.9646 data_time: 0.1853 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2423 loss_db: 0.0581 loss: 0.6293 2022/08/30 20:31:30 - mmengine - INFO - Epoch(train) [991][10/63] lr: 1.4532e-03 eta: 4:16:49 time: 0.9897 data_time: 0.1947 memory: 16201 loss_prob: 0.3392 loss_thr: 0.2369 loss_db: 0.0594 loss: 0.6354 2022/08/30 20:31:35 - mmengine - INFO - Epoch(train) [991][15/63] lr: 1.4532e-03 eta: 4:16:49 time: 0.8409 data_time: 0.0330 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2435 loss_db: 0.0626 loss: 0.6798 2022/08/30 20:31:39 - mmengine - INFO - Epoch(train) [991][20/63] lr: 1.4532e-03 eta: 4:16:37 time: 0.8858 data_time: 0.0278 memory: 16201 loss_prob: 0.4041 loss_thr: 0.2815 loss_db: 0.0663 loss: 0.7519 2022/08/30 20:31:44 - mmengine - INFO - Epoch(train) [991][25/63] lr: 1.4532e-03 eta: 4:16:37 time: 0.8853 data_time: 0.0311 memory: 16201 loss_prob: 0.3547 loss_thr: 0.2706 loss_db: 0.0617 loss: 0.6870 2022/08/30 20:31:48 - mmengine - INFO - Epoch(train) [991][30/63] lr: 1.4532e-03 eta: 4:16:25 time: 0.8231 data_time: 0.0291 memory: 16201 loss_prob: 0.3223 loss_thr: 0.2334 loss_db: 0.0583 loss: 0.6140 2022/08/30 20:31:52 - mmengine - INFO - Epoch(train) [991][35/63] lr: 1.4532e-03 eta: 4:16:25 time: 0.8404 data_time: 0.0289 memory: 16201 loss_prob: 0.3394 loss_thr: 0.2392 loss_db: 0.0608 loss: 0.6394 2022/08/30 20:31:56 - mmengine - INFO - Epoch(train) [991][40/63] lr: 1.4532e-03 eta: 4:16:12 time: 0.8343 data_time: 0.0287 memory: 16201 loss_prob: 0.3589 loss_thr: 0.2596 loss_db: 0.0624 loss: 0.6809 2022/08/30 20:32:01 - mmengine - INFO - Epoch(train) [991][45/63] lr: 1.4532e-03 eta: 4:16:12 time: 0.8609 data_time: 0.0290 memory: 16201 loss_prob: 0.3770 loss_thr: 0.2783 loss_db: 0.0654 loss: 0.7208 2022/08/30 20:32:05 - mmengine - INFO - Epoch(train) [991][50/63] lr: 1.4532e-03 eta: 4:16:00 time: 0.8720 data_time: 0.0230 memory: 16201 loss_prob: 0.3430 loss_thr: 0.2594 loss_db: 0.0619 loss: 0.6643 2022/08/30 20:32:09 - mmengine - INFO - Epoch(train) [991][55/63] lr: 1.4532e-03 eta: 4:16:00 time: 0.8633 data_time: 0.0242 memory: 16201 loss_prob: 0.3240 loss_thr: 0.2438 loss_db: 0.0594 loss: 0.6272 2022/08/30 20:32:13 - mmengine - INFO - Epoch(train) [991][60/63] lr: 1.4532e-03 eta: 4:15:48 time: 0.8733 data_time: 0.0312 memory: 16201 loss_prob: 0.3232 loss_thr: 0.2450 loss_db: 0.0585 loss: 0.6267 2022/08/30 20:32:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:32:22 - mmengine - INFO - Epoch(train) [992][5/63] lr: 1.4469e-03 eta: 4:15:48 time: 0.9845 data_time: 0.1912 memory: 16201 loss_prob: 0.3244 loss_thr: 0.2540 loss_db: 0.0563 loss: 0.6347 2022/08/30 20:32:26 - mmengine - INFO - Epoch(train) [992][10/63] lr: 1.4469e-03 eta: 4:15:32 time: 1.0263 data_time: 0.2073 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2324 loss_db: 0.0534 loss: 0.5957 2022/08/30 20:32:31 - mmengine - INFO - Epoch(train) [992][15/63] lr: 1.4469e-03 eta: 4:15:32 time: 0.9065 data_time: 0.0355 memory: 16201 loss_prob: 0.3352 loss_thr: 0.2447 loss_db: 0.0591 loss: 0.6391 2022/08/30 20:32:35 - mmengine - INFO - Epoch(train) [992][20/63] lr: 1.4469e-03 eta: 4:15:19 time: 0.9152 data_time: 0.0227 memory: 16201 loss_prob: 0.3415 loss_thr: 0.2421 loss_db: 0.0621 loss: 0.6457 2022/08/30 20:32:39 - mmengine - INFO - Epoch(train) [992][25/63] lr: 1.4469e-03 eta: 4:15:19 time: 0.8802 data_time: 0.0376 memory: 16201 loss_prob: 0.3862 loss_thr: 0.2546 loss_db: 0.0681 loss: 0.7089 2022/08/30 20:32:44 - mmengine - INFO - Epoch(train) [992][30/63] lr: 1.4469e-03 eta: 4:15:07 time: 0.9227 data_time: 0.0297 memory: 16201 loss_prob: 0.4372 loss_thr: 0.2878 loss_db: 0.0760 loss: 0.8011 2022/08/30 20:32:48 - mmengine - INFO - Epoch(train) [992][35/63] lr: 1.4469e-03 eta: 4:15:07 time: 0.8764 data_time: 0.0248 memory: 16201 loss_prob: 0.3942 loss_thr: 0.2812 loss_db: 0.0698 loss: 0.7452 2022/08/30 20:32:52 - mmengine - INFO - Epoch(train) [992][40/63] lr: 1.4469e-03 eta: 4:14:55 time: 0.8418 data_time: 0.0328 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2433 loss_db: 0.0575 loss: 0.6252 2022/08/30 20:32:57 - mmengine - INFO - Epoch(train) [992][45/63] lr: 1.4469e-03 eta: 4:14:55 time: 0.8378 data_time: 0.0286 memory: 16201 loss_prob: 0.3395 loss_thr: 0.2499 loss_db: 0.0606 loss: 0.6500 2022/08/30 20:33:01 - mmengine - INFO - Epoch(train) [992][50/63] lr: 1.4469e-03 eta: 4:14:43 time: 0.8569 data_time: 0.0335 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2479 loss_db: 0.0621 loss: 0.6560 2022/08/30 20:33:05 - mmengine - INFO - Epoch(train) [992][55/63] lr: 1.4469e-03 eta: 4:14:43 time: 0.8628 data_time: 0.0327 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2309 loss_db: 0.0582 loss: 0.6212 2022/08/30 20:33:10 - mmengine - INFO - Epoch(train) [992][60/63] lr: 1.4469e-03 eta: 4:14:30 time: 0.8682 data_time: 0.0284 memory: 16201 loss_prob: 0.3250 loss_thr: 0.2318 loss_db: 0.0570 loss: 0.6138 2022/08/30 20:33:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:33:18 - mmengine - INFO - Epoch(train) [993][5/63] lr: 1.4406e-03 eta: 4:14:30 time: 0.9939 data_time: 0.2041 memory: 16201 loss_prob: 0.3157 loss_thr: 0.2341 loss_db: 0.0575 loss: 0.6073 2022/08/30 20:33:22 - mmengine - INFO - Epoch(train) [993][10/63] lr: 1.4406e-03 eta: 4:14:14 time: 1.0331 data_time: 0.2206 memory: 16201 loss_prob: 0.3084 loss_thr: 0.2270 loss_db: 0.0561 loss: 0.5915 2022/08/30 20:33:26 - mmengine - INFO - Epoch(train) [993][15/63] lr: 1.4406e-03 eta: 4:14:14 time: 0.8555 data_time: 0.0366 memory: 16201 loss_prob: 0.2847 loss_thr: 0.2088 loss_db: 0.0499 loss: 0.5435 2022/08/30 20:33:31 - mmengine - INFO - Epoch(train) [993][20/63] lr: 1.4406e-03 eta: 4:14:02 time: 0.8467 data_time: 0.0206 memory: 16201 loss_prob: 0.2989 loss_thr: 0.2188 loss_db: 0.0527 loss: 0.5704 2022/08/30 20:33:35 - mmengine - INFO - Epoch(train) [993][25/63] lr: 1.4406e-03 eta: 4:14:02 time: 0.8740 data_time: 0.0445 memory: 16201 loss_prob: 0.3375 loss_thr: 0.2378 loss_db: 0.0610 loss: 0.6363 2022/08/30 20:33:39 - mmengine - INFO - Epoch(train) [993][30/63] lr: 1.4406e-03 eta: 4:13:50 time: 0.8644 data_time: 0.0396 memory: 16201 loss_prob: 0.3457 loss_thr: 0.2375 loss_db: 0.0615 loss: 0.6447 2022/08/30 20:33:43 - mmengine - INFO - Epoch(train) [993][35/63] lr: 1.4406e-03 eta: 4:13:50 time: 0.8308 data_time: 0.0252 memory: 16201 loss_prob: 0.3443 loss_thr: 0.2431 loss_db: 0.0594 loss: 0.6468 2022/08/30 20:33:48 - mmengine - INFO - Epoch(train) [993][40/63] lr: 1.4406e-03 eta: 4:13:37 time: 0.8363 data_time: 0.0306 memory: 16201 loss_prob: 0.3919 loss_thr: 0.2567 loss_db: 0.0679 loss: 0.7165 2022/08/30 20:33:52 - mmengine - INFO - Epoch(train) [993][45/63] lr: 1.4406e-03 eta: 4:13:37 time: 0.8870 data_time: 0.0295 memory: 16201 loss_prob: 0.3880 loss_thr: 0.2531 loss_db: 0.0690 loss: 0.7101 2022/08/30 20:33:56 - mmengine - INFO - Epoch(train) [993][50/63] lr: 1.4406e-03 eta: 4:13:25 time: 0.8682 data_time: 0.0292 memory: 16201 loss_prob: 0.3342 loss_thr: 0.2340 loss_db: 0.0604 loss: 0.6287 2022/08/30 20:34:01 - mmengine - INFO - Epoch(train) [993][55/63] lr: 1.4406e-03 eta: 4:13:25 time: 0.8514 data_time: 0.0283 memory: 16201 loss_prob: 0.3471 loss_thr: 0.2452 loss_db: 0.0615 loss: 0.6537 2022/08/30 20:34:05 - mmengine - INFO - Epoch(train) [993][60/63] lr: 1.4406e-03 eta: 4:13:13 time: 0.8596 data_time: 0.0264 memory: 16201 loss_prob: 0.3676 loss_thr: 0.2571 loss_db: 0.0656 loss: 0.6903 2022/08/30 20:34:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:34:13 - mmengine - INFO - Epoch(train) [994][5/63] lr: 1.4344e-03 eta: 4:13:13 time: 0.9824 data_time: 0.1842 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2327 loss_db: 0.0584 loss: 0.6257 2022/08/30 20:34:18 - mmengine - INFO - Epoch(train) [994][10/63] lr: 1.4344e-03 eta: 4:12:57 time: 1.0465 data_time: 0.1989 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2307 loss_db: 0.0580 loss: 0.6108 2022/08/30 20:34:22 - mmengine - INFO - Epoch(train) [994][15/63] lr: 1.4344e-03 eta: 4:12:57 time: 0.8780 data_time: 0.0399 memory: 16201 loss_prob: 0.3234 loss_thr: 0.2320 loss_db: 0.0591 loss: 0.6144 2022/08/30 20:34:26 - mmengine - INFO - Epoch(train) [994][20/63] lr: 1.4344e-03 eta: 4:12:44 time: 0.8504 data_time: 0.0317 memory: 16201 loss_prob: 0.3674 loss_thr: 0.2548 loss_db: 0.0656 loss: 0.6878 2022/08/30 20:34:30 - mmengine - INFO - Epoch(train) [994][25/63] lr: 1.4344e-03 eta: 4:12:44 time: 0.8149 data_time: 0.0336 memory: 16201 loss_prob: 0.3907 loss_thr: 0.2774 loss_db: 0.0685 loss: 0.7366 2022/08/30 20:34:34 - mmengine - INFO - Epoch(train) [994][30/63] lr: 1.4344e-03 eta: 4:12:32 time: 0.8421 data_time: 0.0415 memory: 16201 loss_prob: 0.3484 loss_thr: 0.2541 loss_db: 0.0609 loss: 0.6634 2022/08/30 20:34:39 - mmengine - INFO - Epoch(train) [994][35/63] lr: 1.4344e-03 eta: 4:12:32 time: 0.8401 data_time: 0.0349 memory: 16201 loss_prob: 0.3378 loss_thr: 0.2488 loss_db: 0.0597 loss: 0.6462 2022/08/30 20:34:43 - mmengine - INFO - Epoch(train) [994][40/63] lr: 1.4344e-03 eta: 4:12:20 time: 0.8662 data_time: 0.0306 memory: 16201 loss_prob: 0.3323 loss_thr: 0.2454 loss_db: 0.0607 loss: 0.6384 2022/08/30 20:34:47 - mmengine - INFO - Epoch(train) [994][45/63] lr: 1.4344e-03 eta: 4:12:20 time: 0.8882 data_time: 0.0341 memory: 16201 loss_prob: 0.3002 loss_thr: 0.2275 loss_db: 0.0541 loss: 0.5818 2022/08/30 20:34:52 - mmengine - INFO - Epoch(train) [994][50/63] lr: 1.4344e-03 eta: 4:12:07 time: 0.8755 data_time: 0.0315 memory: 16201 loss_prob: 0.3296 loss_thr: 0.2512 loss_db: 0.0577 loss: 0.6384 2022/08/30 20:34:56 - mmengine - INFO - Epoch(train) [994][55/63] lr: 1.4344e-03 eta: 4:12:07 time: 0.8806 data_time: 0.0384 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2547 loss_db: 0.0612 loss: 0.6596 2022/08/30 20:35:01 - mmengine - INFO - Epoch(train) [994][60/63] lr: 1.4344e-03 eta: 4:11:55 time: 0.8673 data_time: 0.0395 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2430 loss_db: 0.0602 loss: 0.6398 2022/08/30 20:35:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:35:09 - mmengine - INFO - Epoch(train) [995][5/63] lr: 1.4281e-03 eta: 4:11:55 time: 1.0078 data_time: 0.2025 memory: 16201 loss_prob: 0.3619 loss_thr: 0.2452 loss_db: 0.0660 loss: 0.6732 2022/08/30 20:35:13 - mmengine - INFO - Epoch(train) [995][10/63] lr: 1.4281e-03 eta: 4:11:39 time: 1.0307 data_time: 0.2081 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2360 loss_db: 0.0597 loss: 0.6321 2022/08/30 20:35:17 - mmengine - INFO - Epoch(train) [995][15/63] lr: 1.4281e-03 eta: 4:11:39 time: 0.8158 data_time: 0.0229 memory: 16201 loss_prob: 0.3130 loss_thr: 0.2296 loss_db: 0.0553 loss: 0.5979 2022/08/30 20:35:21 - mmengine - INFO - Epoch(train) [995][20/63] lr: 1.4281e-03 eta: 4:11:27 time: 0.8361 data_time: 0.0237 memory: 16201 loss_prob: 0.3029 loss_thr: 0.2191 loss_db: 0.0550 loss: 0.5770 2022/08/30 20:35:26 - mmengine - INFO - Epoch(train) [995][25/63] lr: 1.4281e-03 eta: 4:11:27 time: 0.8764 data_time: 0.0418 memory: 16201 loss_prob: 0.3011 loss_thr: 0.2128 loss_db: 0.0538 loss: 0.5677 2022/08/30 20:35:30 - mmengine - INFO - Epoch(train) [995][30/63] lr: 1.4281e-03 eta: 4:11:14 time: 0.8330 data_time: 0.0325 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2518 loss_db: 0.0625 loss: 0.6809 2022/08/30 20:35:34 - mmengine - INFO - Epoch(train) [995][35/63] lr: 1.4281e-03 eta: 4:11:14 time: 0.8151 data_time: 0.0250 memory: 16201 loss_prob: 0.3750 loss_thr: 0.2611 loss_db: 0.0653 loss: 0.7014 2022/08/30 20:35:38 - mmengine - INFO - Epoch(train) [995][40/63] lr: 1.4281e-03 eta: 4:11:02 time: 0.8564 data_time: 0.0312 memory: 16201 loss_prob: 0.3157 loss_thr: 0.2280 loss_db: 0.0567 loss: 0.6003 2022/08/30 20:35:43 - mmengine - INFO - Epoch(train) [995][45/63] lr: 1.4281e-03 eta: 4:11:02 time: 0.9050 data_time: 0.0266 memory: 16201 loss_prob: 0.3333 loss_thr: 0.2431 loss_db: 0.0592 loss: 0.6356 2022/08/30 20:35:47 - mmengine - INFO - Epoch(train) [995][50/63] lr: 1.4281e-03 eta: 4:10:50 time: 0.8811 data_time: 0.0270 memory: 16201 loss_prob: 0.3494 loss_thr: 0.2569 loss_db: 0.0624 loss: 0.6688 2022/08/30 20:35:51 - mmengine - INFO - Epoch(train) [995][55/63] lr: 1.4281e-03 eta: 4:10:50 time: 0.8283 data_time: 0.0299 memory: 16201 loss_prob: 0.3348 loss_thr: 0.2474 loss_db: 0.0594 loss: 0.6417 2022/08/30 20:35:55 - mmengine - INFO - Epoch(train) [995][60/63] lr: 1.4281e-03 eta: 4:10:38 time: 0.8379 data_time: 0.0283 memory: 16201 loss_prob: 0.3883 loss_thr: 0.2768 loss_db: 0.0697 loss: 0.7348 2022/08/30 20:35:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:36:04 - mmengine - INFO - Epoch(train) [996][5/63] lr: 1.4218e-03 eta: 4:10:38 time: 0.9983 data_time: 0.1953 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2550 loss_db: 0.0649 loss: 0.6841 2022/08/30 20:36:08 - mmengine - INFO - Epoch(train) [996][10/63] lr: 1.4218e-03 eta: 4:10:21 time: 1.0159 data_time: 0.2045 memory: 16201 loss_prob: 0.3540 loss_thr: 0.2405 loss_db: 0.0633 loss: 0.6578 2022/08/30 20:36:12 - mmengine - INFO - Epoch(train) [996][15/63] lr: 1.4218e-03 eta: 4:10:21 time: 0.8584 data_time: 0.0314 memory: 16201 loss_prob: 0.3570 loss_thr: 0.2409 loss_db: 0.0647 loss: 0.6627 2022/08/30 20:36:16 - mmengine - INFO - Epoch(train) [996][20/63] lr: 1.4218e-03 eta: 4:10:09 time: 0.8622 data_time: 0.0374 memory: 16201 loss_prob: 0.3677 loss_thr: 0.2513 loss_db: 0.0665 loss: 0.6855 2022/08/30 20:36:21 - mmengine - INFO - Epoch(train) [996][25/63] lr: 1.4218e-03 eta: 4:10:09 time: 0.8388 data_time: 0.0434 memory: 16201 loss_prob: 0.3606 loss_thr: 0.2521 loss_db: 0.0636 loss: 0.6763 2022/08/30 20:36:25 - mmengine - INFO - Epoch(train) [996][30/63] lr: 1.4218e-03 eta: 4:09:57 time: 0.8483 data_time: 0.0414 memory: 16201 loss_prob: 0.3942 loss_thr: 0.2680 loss_db: 0.0670 loss: 0.7291 2022/08/30 20:36:29 - mmengine - INFO - Epoch(train) [996][35/63] lr: 1.4218e-03 eta: 4:09:57 time: 0.8336 data_time: 0.0304 memory: 16201 loss_prob: 0.3961 loss_thr: 0.2674 loss_db: 0.0683 loss: 0.7318 2022/08/30 20:36:33 - mmengine - INFO - Epoch(train) [996][40/63] lr: 1.4218e-03 eta: 4:09:45 time: 0.8324 data_time: 0.0256 memory: 16201 loss_prob: 0.3538 loss_thr: 0.2487 loss_db: 0.0634 loss: 0.6659 2022/08/30 20:36:38 - mmengine - INFO - Epoch(train) [996][45/63] lr: 1.4218e-03 eta: 4:09:45 time: 0.8517 data_time: 0.0299 memory: 16201 loss_prob: 0.3463 loss_thr: 0.2366 loss_db: 0.0626 loss: 0.6456 2022/08/30 20:36:42 - mmengine - INFO - Epoch(train) [996][50/63] lr: 1.4218e-03 eta: 4:09:32 time: 0.9042 data_time: 0.0264 memory: 16201 loss_prob: 0.3811 loss_thr: 0.2644 loss_db: 0.0679 loss: 0.7134 2022/08/30 20:36:46 - mmengine - INFO - Epoch(train) [996][55/63] lr: 1.4218e-03 eta: 4:09:32 time: 0.8818 data_time: 0.0304 memory: 16201 loss_prob: 0.3904 loss_thr: 0.2764 loss_db: 0.0688 loss: 0.7357 2022/08/30 20:36:51 - mmengine - INFO - Epoch(train) [996][60/63] lr: 1.4218e-03 eta: 4:09:20 time: 0.8241 data_time: 0.0331 memory: 16201 loss_prob: 0.3397 loss_thr: 0.2392 loss_db: 0.0602 loss: 0.6391 2022/08/30 20:36:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:36:58 - mmengine - INFO - Epoch(train) [997][5/63] lr: 1.4156e-03 eta: 4:09:20 time: 0.9413 data_time: 0.1839 memory: 16201 loss_prob: 0.3301 loss_thr: 0.2369 loss_db: 0.0604 loss: 0.6274 2022/08/30 20:37:03 - mmengine - INFO - Epoch(train) [997][10/63] lr: 1.4156e-03 eta: 4:09:04 time: 0.9969 data_time: 0.1984 memory: 16201 loss_prob: 0.3139 loss_thr: 0.2218 loss_db: 0.0572 loss: 0.5929 2022/08/30 20:37:07 - mmengine - INFO - Epoch(train) [997][15/63] lr: 1.4156e-03 eta: 4:09:04 time: 0.8385 data_time: 0.0306 memory: 16201 loss_prob: 0.3137 loss_thr: 0.2291 loss_db: 0.0549 loss: 0.5978 2022/08/30 20:37:11 - mmengine - INFO - Epoch(train) [997][20/63] lr: 1.4156e-03 eta: 4:08:52 time: 0.8240 data_time: 0.0173 memory: 16201 loss_prob: 0.3474 loss_thr: 0.2466 loss_db: 0.0605 loss: 0.6544 2022/08/30 20:37:15 - mmengine - INFO - Epoch(train) [997][25/63] lr: 1.4156e-03 eta: 4:08:52 time: 0.8291 data_time: 0.0331 memory: 16201 loss_prob: 0.3215 loss_thr: 0.2385 loss_db: 0.0569 loss: 0.6169 2022/08/30 20:37:19 - mmengine - INFO - Epoch(train) [997][30/63] lr: 1.4156e-03 eta: 4:08:39 time: 0.8256 data_time: 0.0284 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2351 loss_db: 0.0561 loss: 0.6027 2022/08/30 20:37:23 - mmengine - INFO - Epoch(train) [997][35/63] lr: 1.4156e-03 eta: 4:08:39 time: 0.8373 data_time: 0.0205 memory: 16201 loss_prob: 0.3900 loss_thr: 0.2630 loss_db: 0.0661 loss: 0.7191 2022/08/30 20:37:28 - mmengine - INFO - Epoch(train) [997][40/63] lr: 1.4156e-03 eta: 4:08:27 time: 0.8445 data_time: 0.0281 memory: 16201 loss_prob: 0.4123 loss_thr: 0.2715 loss_db: 0.0697 loss: 0.7536 2022/08/30 20:37:32 - mmengine - INFO - Epoch(train) [997][45/63] lr: 1.4156e-03 eta: 4:08:27 time: 0.8309 data_time: 0.0256 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2470 loss_db: 0.0610 loss: 0.6540 2022/08/30 20:37:36 - mmengine - INFO - Epoch(train) [997][50/63] lr: 1.4156e-03 eta: 4:08:15 time: 0.8338 data_time: 0.0243 memory: 16201 loss_prob: 0.3207 loss_thr: 0.2411 loss_db: 0.0569 loss: 0.6187 2022/08/30 20:37:41 - mmengine - INFO - Epoch(train) [997][55/63] lr: 1.4156e-03 eta: 4:08:15 time: 0.9244 data_time: 0.0304 memory: 16201 loss_prob: 0.3278 loss_thr: 0.2426 loss_db: 0.0592 loss: 0.6296 2022/08/30 20:37:45 - mmengine - INFO - Epoch(train) [997][60/63] lr: 1.4156e-03 eta: 4:08:03 time: 0.9309 data_time: 0.0325 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2441 loss_db: 0.0607 loss: 0.6393 2022/08/30 20:37:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:37:53 - mmengine - INFO - Epoch(train) [998][5/63] lr: 1.4093e-03 eta: 4:08:03 time: 0.9859 data_time: 0.1863 memory: 16201 loss_prob: 0.3401 loss_thr: 0.2398 loss_db: 0.0588 loss: 0.6388 2022/08/30 20:37:58 - mmengine - INFO - Epoch(train) [998][10/63] lr: 1.4093e-03 eta: 4:07:46 time: 1.0380 data_time: 0.2047 memory: 16201 loss_prob: 0.3069 loss_thr: 0.2291 loss_db: 0.0550 loss: 0.5909 2022/08/30 20:38:03 - mmengine - INFO - Epoch(train) [998][15/63] lr: 1.4093e-03 eta: 4:07:46 time: 0.9264 data_time: 0.0320 memory: 16201 loss_prob: 0.3554 loss_thr: 0.2540 loss_db: 0.0645 loss: 0.6739 2022/08/30 20:38:07 - mmengine - INFO - Epoch(train) [998][20/63] lr: 1.4093e-03 eta: 4:07:34 time: 0.8959 data_time: 0.0217 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2360 loss_db: 0.0606 loss: 0.6265 2022/08/30 20:38:11 - mmengine - INFO - Epoch(train) [998][25/63] lr: 1.4093e-03 eta: 4:07:34 time: 0.8315 data_time: 0.0293 memory: 16201 loss_prob: 0.3004 loss_thr: 0.2212 loss_db: 0.0546 loss: 0.5762 2022/08/30 20:38:15 - mmengine - INFO - Epoch(train) [998][30/63] lr: 1.4093e-03 eta: 4:07:22 time: 0.8303 data_time: 0.0302 memory: 16201 loss_prob: 0.3271 loss_thr: 0.2320 loss_db: 0.0576 loss: 0.6167 2022/08/30 20:38:20 - mmengine - INFO - Epoch(train) [998][35/63] lr: 1.4093e-03 eta: 4:07:22 time: 0.8557 data_time: 0.0340 memory: 16201 loss_prob: 0.3390 loss_thr: 0.2415 loss_db: 0.0589 loss: 0.6394 2022/08/30 20:38:24 - mmengine - INFO - Epoch(train) [998][40/63] lr: 1.4093e-03 eta: 4:07:10 time: 0.8905 data_time: 0.0349 memory: 16201 loss_prob: 0.3232 loss_thr: 0.2341 loss_db: 0.0584 loss: 0.6157 2022/08/30 20:38:28 - mmengine - INFO - Epoch(train) [998][45/63] lr: 1.4093e-03 eta: 4:07:10 time: 0.8715 data_time: 0.0295 memory: 16201 loss_prob: 0.3429 loss_thr: 0.2429 loss_db: 0.0626 loss: 0.6483 2022/08/30 20:38:32 - mmengine - INFO - Epoch(train) [998][50/63] lr: 1.4093e-03 eta: 4:06:57 time: 0.8463 data_time: 0.0293 memory: 16201 loss_prob: 0.3811 loss_thr: 0.2689 loss_db: 0.0686 loss: 0.7186 2022/08/30 20:38:37 - mmengine - INFO - Epoch(train) [998][55/63] lr: 1.4093e-03 eta: 4:06:57 time: 0.8272 data_time: 0.0273 memory: 16201 loss_prob: 0.4027 loss_thr: 0.2775 loss_db: 0.0698 loss: 0.7500 2022/08/30 20:38:41 - mmengine - INFO - Epoch(train) [998][60/63] lr: 1.4093e-03 eta: 4:06:45 time: 0.8732 data_time: 0.0263 memory: 16201 loss_prob: 0.3670 loss_thr: 0.2543 loss_db: 0.0623 loss: 0.6836 2022/08/30 20:38:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:38:49 - mmengine - INFO - Epoch(train) [999][5/63] lr: 1.4030e-03 eta: 4:06:45 time: 1.0060 data_time: 0.1871 memory: 16201 loss_prob: 0.3227 loss_thr: 0.2289 loss_db: 0.0584 loss: 0.6100 2022/08/30 20:38:53 - mmengine - INFO - Epoch(train) [999][10/63] lr: 1.4030e-03 eta: 4:06:29 time: 0.9893 data_time: 0.1968 memory: 16201 loss_prob: 0.3375 loss_thr: 0.2395 loss_db: 0.0609 loss: 0.6379 2022/08/30 20:38:57 - mmengine - INFO - Epoch(train) [999][15/63] lr: 1.4030e-03 eta: 4:06:29 time: 0.8156 data_time: 0.0337 memory: 16201 loss_prob: 0.3131 loss_thr: 0.2261 loss_db: 0.0552 loss: 0.5944 2022/08/30 20:39:02 - mmengine - INFO - Epoch(train) [999][20/63] lr: 1.4030e-03 eta: 4:06:17 time: 0.8773 data_time: 0.0291 memory: 16201 loss_prob: 0.3139 loss_thr: 0.2210 loss_db: 0.0562 loss: 0.5911 2022/08/30 20:39:06 - mmengine - INFO - Epoch(train) [999][25/63] lr: 1.4030e-03 eta: 4:06:17 time: 0.8829 data_time: 0.0340 memory: 16201 loss_prob: 0.3705 loss_thr: 0.2713 loss_db: 0.0666 loss: 0.7084 2022/08/30 20:39:10 - mmengine - INFO - Epoch(train) [999][30/63] lr: 1.4030e-03 eta: 4:06:05 time: 0.8251 data_time: 0.0265 memory: 16201 loss_prob: 0.3817 loss_thr: 0.2765 loss_db: 0.0666 loss: 0.7248 2022/08/30 20:39:14 - mmengine - INFO - Epoch(train) [999][35/63] lr: 1.4030e-03 eta: 4:06:05 time: 0.8318 data_time: 0.0236 memory: 16201 loss_prob: 0.3747 loss_thr: 0.2517 loss_db: 0.0669 loss: 0.6934 2022/08/30 20:39:19 - mmengine - INFO - Epoch(train) [999][40/63] lr: 1.4030e-03 eta: 4:05:52 time: 0.8403 data_time: 0.0284 memory: 16201 loss_prob: 0.3818 loss_thr: 0.2618 loss_db: 0.0689 loss: 0.7124 2022/08/30 20:39:23 - mmengine - INFO - Epoch(train) [999][45/63] lr: 1.4030e-03 eta: 4:05:52 time: 0.8443 data_time: 0.0299 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2557 loss_db: 0.0638 loss: 0.6789 2022/08/30 20:39:27 - mmengine - INFO - Epoch(train) [999][50/63] lr: 1.4030e-03 eta: 4:05:40 time: 0.8476 data_time: 0.0360 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2523 loss_db: 0.0633 loss: 0.6695 2022/08/30 20:39:31 - mmengine - INFO - Epoch(train) [999][55/63] lr: 1.4030e-03 eta: 4:05:40 time: 0.8305 data_time: 0.0338 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2556 loss_db: 0.0622 loss: 0.6666 2022/08/30 20:39:35 - mmengine - INFO - Epoch(train) [999][60/63] lr: 1.4030e-03 eta: 4:05:28 time: 0.8164 data_time: 0.0276 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2397 loss_db: 0.0598 loss: 0.6286 2022/08/30 20:39:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:39:43 - mmengine - INFO - Epoch(train) [1000][5/63] lr: 1.3967e-03 eta: 4:05:28 time: 0.9433 data_time: 0.1829 memory: 16201 loss_prob: 0.3359 loss_thr: 0.2382 loss_db: 0.0592 loss: 0.6333 2022/08/30 20:39:47 - mmengine - INFO - Epoch(train) [1000][10/63] lr: 1.3967e-03 eta: 4:05:12 time: 0.9975 data_time: 0.1969 memory: 16201 loss_prob: 0.3173 loss_thr: 0.2318 loss_db: 0.0567 loss: 0.6058 2022/08/30 20:39:52 - mmengine - INFO - Epoch(train) [1000][15/63] lr: 1.3967e-03 eta: 4:05:12 time: 0.8471 data_time: 0.0303 memory: 16201 loss_prob: 0.3105 loss_thr: 0.2303 loss_db: 0.0553 loss: 0.5961 2022/08/30 20:39:56 - mmengine - INFO - Epoch(train) [1000][20/63] lr: 1.3967e-03 eta: 4:04:59 time: 0.8371 data_time: 0.0214 memory: 16201 loss_prob: 0.3242 loss_thr: 0.2367 loss_db: 0.0571 loss: 0.6180 2022/08/30 20:40:00 - mmengine - INFO - Epoch(train) [1000][25/63] lr: 1.3967e-03 eta: 4:04:59 time: 0.8466 data_time: 0.0324 memory: 16201 loss_prob: 0.3340 loss_thr: 0.2427 loss_db: 0.0612 loss: 0.6378 2022/08/30 20:40:04 - mmengine - INFO - Epoch(train) [1000][30/63] lr: 1.3967e-03 eta: 4:04:47 time: 0.8594 data_time: 0.0310 memory: 16201 loss_prob: 0.3199 loss_thr: 0.2311 loss_db: 0.0583 loss: 0.6092 2022/08/30 20:40:09 - mmengine - INFO - Epoch(train) [1000][35/63] lr: 1.3967e-03 eta: 4:04:47 time: 0.8629 data_time: 0.0535 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2343 loss_db: 0.0589 loss: 0.6368 2022/08/30 20:40:13 - mmengine - INFO - Epoch(train) [1000][40/63] lr: 1.3967e-03 eta: 4:04:35 time: 0.8759 data_time: 0.0600 memory: 16201 loss_prob: 0.3876 loss_thr: 0.2654 loss_db: 0.0675 loss: 0.7205 2022/08/30 20:40:17 - mmengine - INFO - Epoch(train) [1000][45/63] lr: 1.3967e-03 eta: 4:04:35 time: 0.8583 data_time: 0.0312 memory: 16201 loss_prob: 0.3638 loss_thr: 0.2656 loss_db: 0.0656 loss: 0.6950 2022/08/30 20:40:22 - mmengine - INFO - Epoch(train) [1000][50/63] lr: 1.3967e-03 eta: 4:04:23 time: 0.9079 data_time: 0.0343 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2332 loss_db: 0.0607 loss: 0.6361 2022/08/30 20:40:26 - mmengine - INFO - Epoch(train) [1000][55/63] lr: 1.3967e-03 eta: 4:04:23 time: 0.9066 data_time: 0.0346 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2389 loss_db: 0.0629 loss: 0.6585 2022/08/30 20:40:30 - mmengine - INFO - Epoch(train) [1000][60/63] lr: 1.3967e-03 eta: 4:04:10 time: 0.8306 data_time: 0.0303 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2447 loss_db: 0.0594 loss: 0.6361 2022/08/30 20:40:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:40:32 - mmengine - INFO - Saving checkpoint at 1000 epochs 2022/08/30 20:40:41 - mmengine - INFO - Epoch(val) [1000][5/32] eta: 4:04:10 time: 0.6242 data_time: 0.1107 memory: 16201 2022/08/30 20:40:44 - mmengine - INFO - Epoch(val) [1000][10/32] eta: 0:00:15 time: 0.6858 data_time: 0.1230 memory: 15734 2022/08/30 20:40:47 - mmengine - INFO - Epoch(val) [1000][15/32] eta: 0:00:15 time: 0.5985 data_time: 0.0434 memory: 15734 2022/08/30 20:40:50 - mmengine - INFO - Epoch(val) [1000][20/32] eta: 0:00:07 time: 0.6633 data_time: 0.0663 memory: 15734 2022/08/30 20:40:53 - mmengine - INFO - Epoch(val) [1000][25/32] eta: 0:00:07 time: 0.6705 data_time: 0.0612 memory: 15734 2022/08/30 20:40:56 - mmengine - INFO - Epoch(val) [1000][30/32] eta: 0:00:01 time: 0.5900 data_time: 0.0332 memory: 15734 2022/08/30 20:40:57 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 20:40:57 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8397, precision: 0.8000, hmean: 0.8194 2022/08/30 20:40:57 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8397, precision: 0.8369, hmean: 0.8383 2022/08/30 20:40:57 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8382, precision: 0.8572, hmean: 0.8476 2022/08/30 20:40:57 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8353, precision: 0.8736, hmean: 0.8540 2022/08/30 20:40:57 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8286, precision: 0.8903, hmean: 0.8584 2022/08/30 20:40:57 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8031, precision: 0.9160, hmean: 0.8558 2022/08/30 20:40:57 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4482, precision: 0.9539, hmean: 0.6099 2022/08/30 20:40:57 - mmengine - INFO - Epoch(val) [1000][32/32] icdar/precision: 0.8903 icdar/recall: 0.8286 icdar/hmean: 0.8584 2022/08/30 20:41:03 - mmengine - INFO - Epoch(train) [1001][5/63] lr: 1.3904e-03 eta: 0:00:01 time: 0.9501 data_time: 0.1568 memory: 16201 loss_prob: 0.3412 loss_thr: 0.2470 loss_db: 0.0606 loss: 0.6488 2022/08/30 20:41:07 - mmengine - INFO - Epoch(train) [1001][10/63] lr: 1.3904e-03 eta: 4:03:54 time: 0.9795 data_time: 0.1623 memory: 16201 loss_prob: 0.3514 loss_thr: 0.2477 loss_db: 0.0634 loss: 0.6624 2022/08/30 20:41:11 - mmengine - INFO - Epoch(train) [1001][15/63] lr: 1.3904e-03 eta: 4:03:54 time: 0.8665 data_time: 0.0757 memory: 16201 loss_prob: 0.3311 loss_thr: 0.2290 loss_db: 0.0596 loss: 0.6197 2022/08/30 20:41:16 - mmengine - INFO - Epoch(train) [1001][20/63] lr: 1.3904e-03 eta: 4:03:42 time: 0.8977 data_time: 0.0898 memory: 16201 loss_prob: 0.3673 loss_thr: 0.2507 loss_db: 0.0648 loss: 0.6827 2022/08/30 20:41:20 - mmengine - INFO - Epoch(train) [1001][25/63] lr: 1.3904e-03 eta: 4:03:42 time: 0.8524 data_time: 0.0347 memory: 16201 loss_prob: 0.3511 loss_thr: 0.2470 loss_db: 0.0627 loss: 0.6607 2022/08/30 20:41:24 - mmengine - INFO - Epoch(train) [1001][30/63] lr: 1.3904e-03 eta: 4:03:30 time: 0.8395 data_time: 0.0220 memory: 16201 loss_prob: 0.3697 loss_thr: 0.2394 loss_db: 0.0650 loss: 0.6741 2022/08/30 20:41:28 - mmengine - INFO - Epoch(train) [1001][35/63] lr: 1.3904e-03 eta: 4:03:30 time: 0.8258 data_time: 0.0314 memory: 16201 loss_prob: 0.3725 loss_thr: 0.2446 loss_db: 0.0643 loss: 0.6813 2022/08/30 20:41:32 - mmengine - INFO - Epoch(train) [1001][40/63] lr: 1.3904e-03 eta: 4:03:18 time: 0.8241 data_time: 0.0308 memory: 16201 loss_prob: 0.3512 loss_thr: 0.2518 loss_db: 0.0620 loss: 0.6650 2022/08/30 20:41:36 - mmengine - INFO - Epoch(train) [1001][45/63] lr: 1.3904e-03 eta: 4:03:18 time: 0.8165 data_time: 0.0241 memory: 16201 loss_prob: 0.3703 loss_thr: 0.2583 loss_db: 0.0669 loss: 0.6955 2022/08/30 20:41:41 - mmengine - INFO - Epoch(train) [1001][50/63] lr: 1.3904e-03 eta: 4:03:05 time: 0.8251 data_time: 0.0325 memory: 16201 loss_prob: 0.3479 loss_thr: 0.2407 loss_db: 0.0631 loss: 0.6517 2022/08/30 20:41:45 - mmengine - INFO - Epoch(train) [1001][55/63] lr: 1.3904e-03 eta: 4:03:05 time: 0.8324 data_time: 0.0310 memory: 16201 loss_prob: 0.2997 loss_thr: 0.2173 loss_db: 0.0537 loss: 0.5706 2022/08/30 20:41:49 - mmengine - INFO - Epoch(train) [1001][60/63] lr: 1.3904e-03 eta: 4:02:53 time: 0.8179 data_time: 0.0229 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2337 loss_db: 0.0556 loss: 0.6090 2022/08/30 20:41:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:41:57 - mmengine - INFO - Epoch(train) [1002][5/63] lr: 1.3842e-03 eta: 4:02:53 time: 0.9547 data_time: 0.1869 memory: 16201 loss_prob: 0.3622 loss_thr: 0.2650 loss_db: 0.0651 loss: 0.6922 2022/08/30 20:42:01 - mmengine - INFO - Epoch(train) [1002][10/63] lr: 1.3842e-03 eta: 4:02:37 time: 0.9686 data_time: 0.1846 memory: 16201 loss_prob: 0.3400 loss_thr: 0.2501 loss_db: 0.0613 loss: 0.6514 2022/08/30 20:42:05 - mmengine - INFO - Epoch(train) [1002][15/63] lr: 1.3842e-03 eta: 4:02:37 time: 0.8144 data_time: 0.0277 memory: 16201 loss_prob: 0.3566 loss_thr: 0.2500 loss_db: 0.0637 loss: 0.6703 2022/08/30 20:42:09 - mmengine - INFO - Epoch(train) [1002][20/63] lr: 1.3842e-03 eta: 4:02:24 time: 0.8237 data_time: 0.0246 memory: 16201 loss_prob: 0.3408 loss_thr: 0.2334 loss_db: 0.0604 loss: 0.6345 2022/08/30 20:42:13 - mmengine - INFO - Epoch(train) [1002][25/63] lr: 1.3842e-03 eta: 4:02:24 time: 0.8592 data_time: 0.0231 memory: 16201 loss_prob: 0.3218 loss_thr: 0.2238 loss_db: 0.0573 loss: 0.6029 2022/08/30 20:42:18 - mmengine - INFO - Epoch(train) [1002][30/63] lr: 1.3842e-03 eta: 4:02:12 time: 0.8673 data_time: 0.0307 memory: 16201 loss_prob: 0.3735 loss_thr: 0.2572 loss_db: 0.0660 loss: 0.6967 2022/08/30 20:42:22 - mmengine - INFO - Epoch(train) [1002][35/63] lr: 1.3842e-03 eta: 4:02:12 time: 0.8371 data_time: 0.0343 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2695 loss_db: 0.0687 loss: 0.7240 2022/08/30 20:42:26 - mmengine - INFO - Epoch(train) [1002][40/63] lr: 1.3842e-03 eta: 4:02:00 time: 0.8428 data_time: 0.0207 memory: 16201 loss_prob: 0.3571 loss_thr: 0.2393 loss_db: 0.0611 loss: 0.6575 2022/08/30 20:42:30 - mmengine - INFO - Epoch(train) [1002][45/63] lr: 1.3842e-03 eta: 4:02:00 time: 0.8385 data_time: 0.0319 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2402 loss_db: 0.0607 loss: 0.6512 2022/08/30 20:42:34 - mmengine - INFO - Epoch(train) [1002][50/63] lr: 1.3842e-03 eta: 4:01:48 time: 0.8172 data_time: 0.0389 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2363 loss_db: 0.0595 loss: 0.6183 2022/08/30 20:42:38 - mmengine - INFO - Epoch(train) [1002][55/63] lr: 1.3842e-03 eta: 4:01:48 time: 0.8191 data_time: 0.0199 memory: 16201 loss_prob: 0.3226 loss_thr: 0.2297 loss_db: 0.0590 loss: 0.6114 2022/08/30 20:42:43 - mmengine - INFO - Epoch(train) [1002][60/63] lr: 1.3842e-03 eta: 4:01:36 time: 0.8848 data_time: 0.0261 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2496 loss_db: 0.0634 loss: 0.6699 2022/08/30 20:42:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:42:51 - mmengine - INFO - Epoch(train) [1003][5/63] lr: 1.3779e-03 eta: 4:01:36 time: 0.9365 data_time: 0.1762 memory: 16201 loss_prob: 0.3404 loss_thr: 0.2460 loss_db: 0.0591 loss: 0.6455 2022/08/30 20:42:55 - mmengine - INFO - Epoch(train) [1003][10/63] lr: 1.3779e-03 eta: 4:01:19 time: 1.0028 data_time: 0.1967 memory: 16201 loss_prob: 0.3248 loss_thr: 0.2295 loss_db: 0.0573 loss: 0.6116 2022/08/30 20:42:59 - mmengine - INFO - Epoch(train) [1003][15/63] lr: 1.3779e-03 eta: 4:01:19 time: 0.8250 data_time: 0.0298 memory: 16201 loss_prob: 0.3213 loss_thr: 0.2297 loss_db: 0.0576 loss: 0.6086 2022/08/30 20:43:04 - mmengine - INFO - Epoch(train) [1003][20/63] lr: 1.3779e-03 eta: 4:01:07 time: 0.8577 data_time: 0.0200 memory: 16201 loss_prob: 0.3332 loss_thr: 0.2358 loss_db: 0.0600 loss: 0.6290 2022/08/30 20:43:08 - mmengine - INFO - Epoch(train) [1003][25/63] lr: 1.3779e-03 eta: 4:01:07 time: 0.8801 data_time: 0.0343 memory: 16201 loss_prob: 0.3194 loss_thr: 0.2224 loss_db: 0.0579 loss: 0.5998 2022/08/30 20:43:12 - mmengine - INFO - Epoch(train) [1003][30/63] lr: 1.3779e-03 eta: 4:00:55 time: 0.8182 data_time: 0.0244 memory: 16201 loss_prob: 0.3113 loss_thr: 0.2214 loss_db: 0.0548 loss: 0.5876 2022/08/30 20:43:16 - mmengine - INFO - Epoch(train) [1003][35/63] lr: 1.3779e-03 eta: 4:00:55 time: 0.8033 data_time: 0.0221 memory: 16201 loss_prob: 0.3164 loss_thr: 0.2191 loss_db: 0.0565 loss: 0.5920 2022/08/30 20:43:20 - mmengine - INFO - Epoch(train) [1003][40/63] lr: 1.3779e-03 eta: 4:00:43 time: 0.8538 data_time: 0.0335 memory: 16201 loss_prob: 0.3128 loss_thr: 0.2216 loss_db: 0.0576 loss: 0.5919 2022/08/30 20:43:25 - mmengine - INFO - Epoch(train) [1003][45/63] lr: 1.3779e-03 eta: 4:00:43 time: 0.8829 data_time: 0.0324 memory: 16201 loss_prob: 0.3584 loss_thr: 0.2589 loss_db: 0.0627 loss: 0.6799 2022/08/30 20:43:29 - mmengine - INFO - Epoch(train) [1003][50/63] lr: 1.3779e-03 eta: 4:00:30 time: 0.8481 data_time: 0.0272 memory: 16201 loss_prob: 0.3457 loss_thr: 0.2543 loss_db: 0.0603 loss: 0.6603 2022/08/30 20:43:33 - mmengine - INFO - Epoch(train) [1003][55/63] lr: 1.3779e-03 eta: 4:00:30 time: 0.8242 data_time: 0.0217 memory: 16201 loss_prob: 0.3182 loss_thr: 0.2424 loss_db: 0.0577 loss: 0.6183 2022/08/30 20:43:37 - mmengine - INFO - Epoch(train) [1003][60/63] lr: 1.3779e-03 eta: 4:00:18 time: 0.8417 data_time: 0.0242 memory: 16201 loss_prob: 0.3630 loss_thr: 0.2601 loss_db: 0.0639 loss: 0.6870 2022/08/30 20:43:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:43:45 - mmengine - INFO - Epoch(train) [1004][5/63] lr: 1.3716e-03 eta: 4:00:18 time: 0.9679 data_time: 0.1975 memory: 16201 loss_prob: 0.3560 loss_thr: 0.2465 loss_db: 0.0631 loss: 0.6655 2022/08/30 20:43:49 - mmengine - INFO - Epoch(train) [1004][10/63] lr: 1.3716e-03 eta: 4:00:02 time: 0.9956 data_time: 0.2079 memory: 16201 loss_prob: 0.3381 loss_thr: 0.2470 loss_db: 0.0612 loss: 0.6462 2022/08/30 20:43:54 - mmengine - INFO - Epoch(train) [1004][15/63] lr: 1.3716e-03 eta: 4:00:02 time: 0.8447 data_time: 0.0257 memory: 16201 loss_prob: 0.3112 loss_thr: 0.2346 loss_db: 0.0557 loss: 0.6015 2022/08/30 20:43:58 - mmengine - INFO - Epoch(train) [1004][20/63] lr: 1.3716e-03 eta: 3:59:50 time: 0.8625 data_time: 0.0283 memory: 16201 loss_prob: 0.3305 loss_thr: 0.2356 loss_db: 0.0590 loss: 0.6251 2022/08/30 20:44:02 - mmengine - INFO - Epoch(train) [1004][25/63] lr: 1.3716e-03 eta: 3:59:50 time: 0.8340 data_time: 0.0327 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2471 loss_db: 0.0643 loss: 0.6651 2022/08/30 20:44:06 - mmengine - INFO - Epoch(train) [1004][30/63] lr: 1.3716e-03 eta: 3:59:38 time: 0.8294 data_time: 0.0255 memory: 16201 loss_prob: 0.3632 loss_thr: 0.2518 loss_db: 0.0639 loss: 0.6789 2022/08/30 20:44:10 - mmengine - INFO - Epoch(train) [1004][35/63] lr: 1.3716e-03 eta: 3:59:38 time: 0.8127 data_time: 0.0211 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2563 loss_db: 0.0617 loss: 0.6951 2022/08/30 20:44:15 - mmengine - INFO - Epoch(train) [1004][40/63] lr: 1.3716e-03 eta: 3:59:25 time: 0.8126 data_time: 0.0253 memory: 16201 loss_prob: 0.3408 loss_thr: 0.2438 loss_db: 0.0578 loss: 0.6424 2022/08/30 20:44:19 - mmengine - INFO - Epoch(train) [1004][45/63] lr: 1.3716e-03 eta: 3:59:25 time: 0.8860 data_time: 0.0295 memory: 16201 loss_prob: 0.3162 loss_thr: 0.2313 loss_db: 0.0576 loss: 0.6050 2022/08/30 20:44:23 - mmengine - INFO - Epoch(train) [1004][50/63] lr: 1.3716e-03 eta: 3:59:13 time: 0.8845 data_time: 0.0258 memory: 16201 loss_prob: 0.3041 loss_thr: 0.2252 loss_db: 0.0539 loss: 0.5832 2022/08/30 20:44:27 - mmengine - INFO - Epoch(train) [1004][55/63] lr: 1.3716e-03 eta: 3:59:13 time: 0.8114 data_time: 0.0272 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2522 loss_db: 0.0610 loss: 0.6565 2022/08/30 20:44:32 - mmengine - INFO - Epoch(train) [1004][60/63] lr: 1.3716e-03 eta: 3:59:01 time: 0.8199 data_time: 0.0316 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2501 loss_db: 0.0614 loss: 0.6537 2022/08/30 20:44:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:44:39 - mmengine - INFO - Epoch(train) [1005][5/63] lr: 1.3653e-03 eta: 3:59:01 time: 0.9652 data_time: 0.1971 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2288 loss_db: 0.0573 loss: 0.6100 2022/08/30 20:44:44 - mmengine - INFO - Epoch(train) [1005][10/63] lr: 1.3653e-03 eta: 3:58:45 time: 1.0027 data_time: 0.2099 memory: 16201 loss_prob: 0.3604 loss_thr: 0.2439 loss_db: 0.0621 loss: 0.6664 2022/08/30 20:44:48 - mmengine - INFO - Epoch(train) [1005][15/63] lr: 1.3653e-03 eta: 3:58:45 time: 0.8169 data_time: 0.0281 memory: 16201 loss_prob: 0.3746 loss_thr: 0.2690 loss_db: 0.0654 loss: 0.7091 2022/08/30 20:44:52 - mmengine - INFO - Epoch(train) [1005][20/63] lr: 1.3653e-03 eta: 3:58:33 time: 0.8196 data_time: 0.0180 memory: 16201 loss_prob: 0.3636 loss_thr: 0.2580 loss_db: 0.0658 loss: 0.6874 2022/08/30 20:44:56 - mmengine - INFO - Epoch(train) [1005][25/63] lr: 1.3653e-03 eta: 3:58:33 time: 0.8125 data_time: 0.0306 memory: 16201 loss_prob: 0.3280 loss_thr: 0.2352 loss_db: 0.0584 loss: 0.6216 2022/08/30 20:45:00 - mmengine - INFO - Epoch(train) [1005][30/63] lr: 1.3653e-03 eta: 3:58:20 time: 0.7835 data_time: 0.0250 memory: 16201 loss_prob: 0.3055 loss_thr: 0.2210 loss_db: 0.0531 loss: 0.5796 2022/08/30 20:45:04 - mmengine - INFO - Epoch(train) [1005][35/63] lr: 1.3653e-03 eta: 3:58:20 time: 0.7920 data_time: 0.0248 memory: 16201 loss_prob: 0.3280 loss_thr: 0.2305 loss_db: 0.0589 loss: 0.6174 2022/08/30 20:45:08 - mmengine - INFO - Epoch(train) [1005][40/63] lr: 1.3653e-03 eta: 3:58:08 time: 0.8100 data_time: 0.0285 memory: 16201 loss_prob: 0.3493 loss_thr: 0.2440 loss_db: 0.0631 loss: 0.6565 2022/08/30 20:45:12 - mmengine - INFO - Epoch(train) [1005][45/63] lr: 1.3653e-03 eta: 3:58:08 time: 0.8360 data_time: 0.0230 memory: 16201 loss_prob: 0.3866 loss_thr: 0.2612 loss_db: 0.0677 loss: 0.7155 2022/08/30 20:45:16 - mmengine - INFO - Epoch(train) [1005][50/63] lr: 1.3653e-03 eta: 3:57:56 time: 0.8308 data_time: 0.0283 memory: 16201 loss_prob: 0.3784 loss_thr: 0.2510 loss_db: 0.0657 loss: 0.6951 2022/08/30 20:45:20 - mmengine - INFO - Epoch(train) [1005][55/63] lr: 1.3653e-03 eta: 3:57:56 time: 0.8170 data_time: 0.0250 memory: 16201 loss_prob: 0.3943 loss_thr: 0.2577 loss_db: 0.0669 loss: 0.7189 2022/08/30 20:45:24 - mmengine - INFO - Epoch(train) [1005][60/63] lr: 1.3653e-03 eta: 3:57:43 time: 0.8230 data_time: 0.0275 memory: 16201 loss_prob: 0.3953 loss_thr: 0.2611 loss_db: 0.0673 loss: 0.7236 2022/08/30 20:45:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:45:32 - mmengine - INFO - Epoch(train) [1006][5/63] lr: 1.3590e-03 eta: 3:57:43 time: 0.9489 data_time: 0.1881 memory: 16201 loss_prob: 0.3586 loss_thr: 0.2439 loss_db: 0.0631 loss: 0.6656 2022/08/30 20:45:36 - mmengine - INFO - Epoch(train) [1006][10/63] lr: 1.3590e-03 eta: 3:57:27 time: 1.0019 data_time: 0.2023 memory: 16201 loss_prob: 0.3386 loss_thr: 0.2288 loss_db: 0.0601 loss: 0.6275 2022/08/30 20:45:41 - mmengine - INFO - Epoch(train) [1006][15/63] lr: 1.3590e-03 eta: 3:57:27 time: 0.8399 data_time: 0.0253 memory: 16201 loss_prob: 0.3412 loss_thr: 0.2301 loss_db: 0.0607 loss: 0.6320 2022/08/30 20:45:45 - mmengine - INFO - Epoch(train) [1006][20/63] lr: 1.3590e-03 eta: 3:57:15 time: 0.8589 data_time: 0.0240 memory: 16201 loss_prob: 0.3579 loss_thr: 0.2376 loss_db: 0.0629 loss: 0.6584 2022/08/30 20:45:49 - mmengine - INFO - Epoch(train) [1006][25/63] lr: 1.3590e-03 eta: 3:57:15 time: 0.8474 data_time: 0.0401 memory: 16201 loss_prob: 0.3315 loss_thr: 0.2294 loss_db: 0.0581 loss: 0.6189 2022/08/30 20:45:53 - mmengine - INFO - Epoch(train) [1006][30/63] lr: 1.3590e-03 eta: 3:57:03 time: 0.8205 data_time: 0.0270 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2451 loss_db: 0.0608 loss: 0.6481 2022/08/30 20:45:57 - mmengine - INFO - Epoch(train) [1006][35/63] lr: 1.3590e-03 eta: 3:57:03 time: 0.8122 data_time: 0.0223 memory: 16201 loss_prob: 0.3429 loss_thr: 0.2525 loss_db: 0.0623 loss: 0.6577 2022/08/30 20:46:02 - mmengine - INFO - Epoch(train) [1006][40/63] lr: 1.3590e-03 eta: 3:56:51 time: 0.8373 data_time: 0.0325 memory: 16201 loss_prob: 0.3341 loss_thr: 0.2520 loss_db: 0.0600 loss: 0.6462 2022/08/30 20:46:06 - mmengine - INFO - Epoch(train) [1006][45/63] lr: 1.3590e-03 eta: 3:56:51 time: 0.8329 data_time: 0.0302 memory: 16201 loss_prob: 0.3457 loss_thr: 0.2554 loss_db: 0.0613 loss: 0.6624 2022/08/30 20:46:10 - mmengine - INFO - Epoch(train) [1006][50/63] lr: 1.3590e-03 eta: 3:56:38 time: 0.8053 data_time: 0.0288 memory: 16201 loss_prob: 0.3350 loss_thr: 0.2541 loss_db: 0.0593 loss: 0.6485 2022/08/30 20:46:14 - mmengine - INFO - Epoch(train) [1006][55/63] lr: 1.3590e-03 eta: 3:56:38 time: 0.8099 data_time: 0.0263 memory: 16201 loss_prob: 0.3525 loss_thr: 0.2677 loss_db: 0.0624 loss: 0.6826 2022/08/30 20:46:18 - mmengine - INFO - Epoch(train) [1006][60/63] lr: 1.3590e-03 eta: 3:56:26 time: 0.8201 data_time: 0.0272 memory: 16201 loss_prob: 0.3586 loss_thr: 0.2522 loss_db: 0.0604 loss: 0.6712 2022/08/30 20:46:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:46:26 - mmengine - INFO - Epoch(train) [1007][5/63] lr: 1.3527e-03 eta: 3:56:26 time: 0.9265 data_time: 0.1764 memory: 16201 loss_prob: 0.3228 loss_thr: 0.2335 loss_db: 0.0577 loss: 0.6140 2022/08/30 20:46:30 - mmengine - INFO - Epoch(train) [1007][10/63] lr: 1.3527e-03 eta: 3:56:10 time: 0.9787 data_time: 0.1941 memory: 16201 loss_prob: 0.3081 loss_thr: 0.2288 loss_db: 0.0558 loss: 0.5928 2022/08/30 20:46:34 - mmengine - INFO - Epoch(train) [1007][15/63] lr: 1.3527e-03 eta: 3:56:10 time: 0.7986 data_time: 0.0263 memory: 16201 loss_prob: 0.3063 loss_thr: 0.2365 loss_db: 0.0546 loss: 0.5974 2022/08/30 20:46:38 - mmengine - INFO - Epoch(train) [1007][20/63] lr: 1.3527e-03 eta: 3:55:58 time: 0.8112 data_time: 0.0181 memory: 16201 loss_prob: 0.3208 loss_thr: 0.2373 loss_db: 0.0579 loss: 0.6161 2022/08/30 20:46:42 - mmengine - INFO - Epoch(train) [1007][25/63] lr: 1.3527e-03 eta: 3:55:58 time: 0.8436 data_time: 0.0258 memory: 16201 loss_prob: 0.3246 loss_thr: 0.2407 loss_db: 0.0580 loss: 0.6234 2022/08/30 20:46:46 - mmengine - INFO - Epoch(train) [1007][30/63] lr: 1.3527e-03 eta: 3:55:45 time: 0.8377 data_time: 0.0282 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2463 loss_db: 0.0587 loss: 0.6341 2022/08/30 20:46:50 - mmengine - INFO - Epoch(train) [1007][35/63] lr: 1.3527e-03 eta: 3:55:45 time: 0.8196 data_time: 0.0338 memory: 16201 loss_prob: 0.3109 loss_thr: 0.2308 loss_db: 0.0564 loss: 0.5981 2022/08/30 20:46:54 - mmengine - INFO - Epoch(train) [1007][40/63] lr: 1.3527e-03 eta: 3:55:33 time: 0.8172 data_time: 0.0265 memory: 16201 loss_prob: 0.3100 loss_thr: 0.2347 loss_db: 0.0562 loss: 0.6009 2022/08/30 20:46:58 - mmengine - INFO - Epoch(train) [1007][45/63] lr: 1.3527e-03 eta: 3:55:33 time: 0.8070 data_time: 0.0246 memory: 16201 loss_prob: 0.3557 loss_thr: 0.2520 loss_db: 0.0633 loss: 0.6710 2022/08/30 20:47:03 - mmengine - INFO - Epoch(train) [1007][50/63] lr: 1.3527e-03 eta: 3:55:21 time: 0.8417 data_time: 0.0311 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2365 loss_db: 0.0609 loss: 0.6441 2022/08/30 20:47:07 - mmengine - INFO - Epoch(train) [1007][55/63] lr: 1.3527e-03 eta: 3:55:21 time: 0.8553 data_time: 0.0245 memory: 16201 loss_prob: 0.3263 loss_thr: 0.2296 loss_db: 0.0570 loss: 0.6130 2022/08/30 20:47:11 - mmengine - INFO - Epoch(train) [1007][60/63] lr: 1.3527e-03 eta: 3:55:09 time: 0.8153 data_time: 0.0233 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2362 loss_db: 0.0576 loss: 0.6240 2022/08/30 20:47:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:47:19 - mmengine - INFO - Epoch(train) [1008][5/63] lr: 1.3463e-03 eta: 3:55:09 time: 0.9329 data_time: 0.1856 memory: 16201 loss_prob: 0.3834 loss_thr: 0.2656 loss_db: 0.0692 loss: 0.7182 2022/08/30 20:47:23 - mmengine - INFO - Epoch(train) [1008][10/63] lr: 1.3463e-03 eta: 3:54:53 time: 0.9666 data_time: 0.1947 memory: 16201 loss_prob: 0.3191 loss_thr: 0.2231 loss_db: 0.0576 loss: 0.5998 2022/08/30 20:47:27 - mmengine - INFO - Epoch(train) [1008][15/63] lr: 1.3463e-03 eta: 3:54:53 time: 0.8043 data_time: 0.0270 memory: 16201 loss_prob: 0.3450 loss_thr: 0.2510 loss_db: 0.0607 loss: 0.6568 2022/08/30 20:47:31 - mmengine - INFO - Epoch(train) [1008][20/63] lr: 1.3463e-03 eta: 3:54:40 time: 0.8055 data_time: 0.0285 memory: 16201 loss_prob: 0.3719 loss_thr: 0.2733 loss_db: 0.0663 loss: 0.7115 2022/08/30 20:47:35 - mmengine - INFO - Epoch(train) [1008][25/63] lr: 1.3463e-03 eta: 3:54:40 time: 0.8085 data_time: 0.0292 memory: 16201 loss_prob: 0.3274 loss_thr: 0.2446 loss_db: 0.0588 loss: 0.6308 2022/08/30 20:47:39 - mmengine - INFO - Epoch(train) [1008][30/63] lr: 1.3463e-03 eta: 3:54:28 time: 0.8024 data_time: 0.0252 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2411 loss_db: 0.0567 loss: 0.6155 2022/08/30 20:47:43 - mmengine - INFO - Epoch(train) [1008][35/63] lr: 1.3463e-03 eta: 3:54:28 time: 0.8261 data_time: 0.0230 memory: 16201 loss_prob: 0.3496 loss_thr: 0.2518 loss_db: 0.0623 loss: 0.6637 2022/08/30 20:47:47 - mmengine - INFO - Epoch(train) [1008][40/63] lr: 1.3463e-03 eta: 3:54:16 time: 0.8400 data_time: 0.0265 memory: 16201 loss_prob: 0.3072 loss_thr: 0.2245 loss_db: 0.0555 loss: 0.5872 2022/08/30 20:47:51 - mmengine - INFO - Epoch(train) [1008][45/63] lr: 1.3463e-03 eta: 3:54:16 time: 0.8210 data_time: 0.0258 memory: 16201 loss_prob: 0.2714 loss_thr: 0.2092 loss_db: 0.0501 loss: 0.5307 2022/08/30 20:47:55 - mmengine - INFO - Epoch(train) [1008][50/63] lr: 1.3463e-03 eta: 3:54:04 time: 0.8011 data_time: 0.0205 memory: 16201 loss_prob: 0.3404 loss_thr: 0.2498 loss_db: 0.0614 loss: 0.6516 2022/08/30 20:47:59 - mmengine - INFO - Epoch(train) [1008][55/63] lr: 1.3463e-03 eta: 3:54:04 time: 0.8024 data_time: 0.0261 memory: 16201 loss_prob: 0.3421 loss_thr: 0.2483 loss_db: 0.0601 loss: 0.6504 2022/08/30 20:48:04 - mmengine - INFO - Epoch(train) [1008][60/63] lr: 1.3463e-03 eta: 3:53:51 time: 0.8531 data_time: 0.0363 memory: 16201 loss_prob: 0.3262 loss_thr: 0.2352 loss_db: 0.0567 loss: 0.6180 2022/08/30 20:48:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:48:11 - mmengine - INFO - Epoch(train) [1009][5/63] lr: 1.3400e-03 eta: 3:53:51 time: 0.9213 data_time: 0.1866 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2341 loss_db: 0.0596 loss: 0.6247 2022/08/30 20:48:15 - mmengine - INFO - Epoch(train) [1009][10/63] lr: 1.3400e-03 eta: 3:53:35 time: 0.9658 data_time: 0.1904 memory: 16201 loss_prob: 0.3655 loss_thr: 0.2627 loss_db: 0.0659 loss: 0.6941 2022/08/30 20:48:19 - mmengine - INFO - Epoch(train) [1009][15/63] lr: 1.3400e-03 eta: 3:53:35 time: 0.7938 data_time: 0.0261 memory: 16201 loss_prob: 0.3845 loss_thr: 0.2775 loss_db: 0.0693 loss: 0.7312 2022/08/30 20:48:23 - mmengine - INFO - Epoch(train) [1009][20/63] lr: 1.3400e-03 eta: 3:53:23 time: 0.7991 data_time: 0.0220 memory: 16201 loss_prob: 0.3584 loss_thr: 0.2637 loss_db: 0.0626 loss: 0.6848 2022/08/30 20:48:27 - mmengine - INFO - Epoch(train) [1009][25/63] lr: 1.3400e-03 eta: 3:53:23 time: 0.8221 data_time: 0.0250 memory: 16201 loss_prob: 0.3490 loss_thr: 0.2523 loss_db: 0.0604 loss: 0.6616 2022/08/30 20:48:31 - mmengine - INFO - Epoch(train) [1009][30/63] lr: 1.3400e-03 eta: 3:53:11 time: 0.8252 data_time: 0.0287 memory: 16201 loss_prob: 0.3333 loss_thr: 0.2414 loss_db: 0.0600 loss: 0.6348 2022/08/30 20:48:35 - mmengine - INFO - Epoch(train) [1009][35/63] lr: 1.3400e-03 eta: 3:53:11 time: 0.8046 data_time: 0.0289 memory: 16201 loss_prob: 0.3113 loss_thr: 0.2434 loss_db: 0.0561 loss: 0.6108 2022/08/30 20:48:40 - mmengine - INFO - Epoch(train) [1009][40/63] lr: 1.3400e-03 eta: 3:52:58 time: 0.8098 data_time: 0.0236 memory: 16201 loss_prob: 0.3499 loss_thr: 0.2557 loss_db: 0.0621 loss: 0.6677 2022/08/30 20:48:44 - mmengine - INFO - Epoch(train) [1009][45/63] lr: 1.3400e-03 eta: 3:52:58 time: 0.8589 data_time: 0.0254 memory: 16201 loss_prob: 0.3286 loss_thr: 0.2321 loss_db: 0.0585 loss: 0.6191 2022/08/30 20:48:48 - mmengine - INFO - Epoch(train) [1009][50/63] lr: 1.3400e-03 eta: 3:52:46 time: 0.8315 data_time: 0.0224 memory: 16201 loss_prob: 0.3054 loss_thr: 0.2250 loss_db: 0.0538 loss: 0.5842 2022/08/30 20:48:52 - mmengine - INFO - Epoch(train) [1009][55/63] lr: 1.3400e-03 eta: 3:52:46 time: 0.7823 data_time: 0.0243 memory: 16201 loss_prob: 0.3373 loss_thr: 0.2517 loss_db: 0.0603 loss: 0.6493 2022/08/30 20:48:56 - mmengine - INFO - Epoch(train) [1009][60/63] lr: 1.3400e-03 eta: 3:52:34 time: 0.7948 data_time: 0.0318 memory: 16201 loss_prob: 0.3223 loss_thr: 0.2417 loss_db: 0.0590 loss: 0.6231 2022/08/30 20:48:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:49:03 - mmengine - INFO - Epoch(train) [1010][5/63] lr: 1.3337e-03 eta: 3:52:34 time: 0.8860 data_time: 0.1662 memory: 16201 loss_prob: 0.3407 loss_thr: 0.2455 loss_db: 0.0623 loss: 0.6485 2022/08/30 20:49:07 - mmengine - INFO - Epoch(train) [1010][10/63] lr: 1.3337e-03 eta: 3:52:18 time: 0.9435 data_time: 0.1764 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2676 loss_db: 0.0666 loss: 0.7122 2022/08/30 20:49:11 - mmengine - INFO - Epoch(train) [1010][15/63] lr: 1.3337e-03 eta: 3:52:18 time: 0.8107 data_time: 0.0266 memory: 16201 loss_prob: 0.3661 loss_thr: 0.2511 loss_db: 0.0634 loss: 0.6806 2022/08/30 20:49:15 - mmengine - INFO - Epoch(train) [1010][20/63] lr: 1.3337e-03 eta: 3:52:06 time: 0.7867 data_time: 0.0192 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2348 loss_db: 0.0635 loss: 0.6448 2022/08/30 20:49:19 - mmengine - INFO - Epoch(train) [1010][25/63] lr: 1.3337e-03 eta: 3:52:06 time: 0.7899 data_time: 0.0311 memory: 16201 loss_prob: 0.3533 loss_thr: 0.2497 loss_db: 0.0652 loss: 0.6682 2022/08/30 20:49:23 - mmengine - INFO - Epoch(train) [1010][30/63] lr: 1.3337e-03 eta: 3:51:53 time: 0.8371 data_time: 0.0273 memory: 16201 loss_prob: 0.3542 loss_thr: 0.2584 loss_db: 0.0625 loss: 0.6751 2022/08/30 20:49:27 - mmengine - INFO - Epoch(train) [1010][35/63] lr: 1.3337e-03 eta: 3:51:53 time: 0.8221 data_time: 0.0213 memory: 16201 loss_prob: 0.3576 loss_thr: 0.2510 loss_db: 0.0630 loss: 0.6715 2022/08/30 20:49:31 - mmengine - INFO - Epoch(train) [1010][40/63] lr: 1.3337e-03 eta: 3:51:41 time: 0.7900 data_time: 0.0249 memory: 16201 loss_prob: 0.3478 loss_thr: 0.2484 loss_db: 0.0625 loss: 0.6587 2022/08/30 20:49:35 - mmengine - INFO - Epoch(train) [1010][45/63] lr: 1.3337e-03 eta: 3:51:41 time: 0.7923 data_time: 0.0232 memory: 16201 loss_prob: 0.2981 loss_thr: 0.2260 loss_db: 0.0542 loss: 0.5783 2022/08/30 20:49:39 - mmengine - INFO - Epoch(train) [1010][50/63] lr: 1.3337e-03 eta: 3:51:29 time: 0.7945 data_time: 0.0260 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2414 loss_db: 0.0588 loss: 0.6247 2022/08/30 20:49:43 - mmengine - INFO - Epoch(train) [1010][55/63] lr: 1.3337e-03 eta: 3:51:29 time: 0.7955 data_time: 0.0266 memory: 16201 loss_prob: 0.3606 loss_thr: 0.2589 loss_db: 0.0638 loss: 0.6834 2022/08/30 20:49:47 - mmengine - INFO - Epoch(train) [1010][60/63] lr: 1.3337e-03 eta: 3:51:16 time: 0.7901 data_time: 0.0293 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2468 loss_db: 0.0606 loss: 0.6507 2022/08/30 20:49:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:49:55 - mmengine - INFO - Epoch(train) [1011][5/63] lr: 1.3274e-03 eta: 3:51:16 time: 0.9145 data_time: 0.1949 memory: 16201 loss_prob: 0.3709 loss_thr: 0.2544 loss_db: 0.0657 loss: 0.6910 2022/08/30 20:49:59 - mmengine - INFO - Epoch(train) [1011][10/63] lr: 1.3274e-03 eta: 3:51:00 time: 0.9772 data_time: 0.2107 memory: 16201 loss_prob: 0.3822 loss_thr: 0.2707 loss_db: 0.0662 loss: 0.7190 2022/08/30 20:50:03 - mmengine - INFO - Epoch(train) [1011][15/63] lr: 1.3274e-03 eta: 3:51:00 time: 0.7921 data_time: 0.0282 memory: 16201 loss_prob: 0.3606 loss_thr: 0.2553 loss_db: 0.0640 loss: 0.6799 2022/08/30 20:50:07 - mmengine - INFO - Epoch(train) [1011][20/63] lr: 1.3274e-03 eta: 3:50:48 time: 0.7834 data_time: 0.0175 memory: 16201 loss_prob: 0.3234 loss_thr: 0.2302 loss_db: 0.0594 loss: 0.6130 2022/08/30 20:50:11 - mmengine - INFO - Epoch(train) [1011][25/63] lr: 1.3274e-03 eta: 3:50:48 time: 0.7838 data_time: 0.0274 memory: 16201 loss_prob: 0.3161 loss_thr: 0.2292 loss_db: 0.0578 loss: 0.6030 2022/08/30 20:50:15 - mmengine - INFO - Epoch(train) [1011][30/63] lr: 1.3274e-03 eta: 3:50:36 time: 0.7993 data_time: 0.0266 memory: 16201 loss_prob: 0.3357 loss_thr: 0.2413 loss_db: 0.0587 loss: 0.6357 2022/08/30 20:50:19 - mmengine - INFO - Epoch(train) [1011][35/63] lr: 1.3274e-03 eta: 3:50:36 time: 0.7967 data_time: 0.0198 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2421 loss_db: 0.0588 loss: 0.6362 2022/08/30 20:50:22 - mmengine - INFO - Epoch(train) [1011][40/63] lr: 1.3274e-03 eta: 3:50:24 time: 0.7837 data_time: 0.0253 memory: 16201 loss_prob: 0.3445 loss_thr: 0.2454 loss_db: 0.0611 loss: 0.6510 2022/08/30 20:50:26 - mmengine - INFO - Epoch(train) [1011][45/63] lr: 1.3274e-03 eta: 3:50:24 time: 0.7768 data_time: 0.0258 memory: 16201 loss_prob: 0.3635 loss_thr: 0.2511 loss_db: 0.0633 loss: 0.6778 2022/08/30 20:50:30 - mmengine - INFO - Epoch(train) [1011][50/63] lr: 1.3274e-03 eta: 3:50:11 time: 0.7828 data_time: 0.0226 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2494 loss_db: 0.0615 loss: 0.6590 2022/08/30 20:50:34 - mmengine - INFO - Epoch(train) [1011][55/63] lr: 1.3274e-03 eta: 3:50:11 time: 0.7974 data_time: 0.0295 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2617 loss_db: 0.0621 loss: 0.6736 2022/08/30 20:50:38 - mmengine - INFO - Epoch(train) [1011][60/63] lr: 1.3274e-03 eta: 3:49:59 time: 0.8120 data_time: 0.0298 memory: 16201 loss_prob: 0.3327 loss_thr: 0.2495 loss_db: 0.0603 loss: 0.6425 2022/08/30 20:50:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:50:46 - mmengine - INFO - Epoch(train) [1012][5/63] lr: 1.3211e-03 eta: 3:49:59 time: 0.9177 data_time: 0.1984 memory: 16201 loss_prob: 0.3593 loss_thr: 0.2602 loss_db: 0.0635 loss: 0.6829 2022/08/30 20:50:50 - mmengine - INFO - Epoch(train) [1012][10/63] lr: 1.3211e-03 eta: 3:49:43 time: 0.9780 data_time: 0.2106 memory: 16201 loss_prob: 0.3399 loss_thr: 0.2502 loss_db: 0.0582 loss: 0.6482 2022/08/30 20:50:54 - mmengine - INFO - Epoch(train) [1012][15/63] lr: 1.3211e-03 eta: 3:49:43 time: 0.8024 data_time: 0.0257 memory: 16201 loss_prob: 0.3351 loss_thr: 0.2435 loss_db: 0.0607 loss: 0.6394 2022/08/30 20:50:58 - mmengine - INFO - Epoch(train) [1012][20/63] lr: 1.3211e-03 eta: 3:49:31 time: 0.7878 data_time: 0.0185 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2530 loss_db: 0.0643 loss: 0.6654 2022/08/30 20:51:02 - mmengine - INFO - Epoch(train) [1012][25/63] lr: 1.3211e-03 eta: 3:49:31 time: 0.7929 data_time: 0.0270 memory: 16201 loss_prob: 0.3242 loss_thr: 0.2408 loss_db: 0.0586 loss: 0.6236 2022/08/30 20:51:06 - mmengine - INFO - Epoch(train) [1012][30/63] lr: 1.3211e-03 eta: 3:49:18 time: 0.7934 data_time: 0.0238 memory: 16201 loss_prob: 0.3427 loss_thr: 0.2471 loss_db: 0.0611 loss: 0.6508 2022/08/30 20:51:10 - mmengine - INFO - Epoch(train) [1012][35/63] lr: 1.3211e-03 eta: 3:49:18 time: 0.7875 data_time: 0.0249 memory: 16201 loss_prob: 0.3837 loss_thr: 0.2732 loss_db: 0.0682 loss: 0.7250 2022/08/30 20:51:14 - mmengine - INFO - Epoch(train) [1012][40/63] lr: 1.3211e-03 eta: 3:49:06 time: 0.8174 data_time: 0.0294 memory: 16201 loss_prob: 0.3480 loss_thr: 0.2511 loss_db: 0.0613 loss: 0.6604 2022/08/30 20:51:18 - mmengine - INFO - Epoch(train) [1012][45/63] lr: 1.3211e-03 eta: 3:49:06 time: 0.8118 data_time: 0.0265 memory: 16201 loss_prob: 0.3414 loss_thr: 0.2376 loss_db: 0.0596 loss: 0.6386 2022/08/30 20:51:22 - mmengine - INFO - Epoch(train) [1012][50/63] lr: 1.3211e-03 eta: 3:48:54 time: 0.7827 data_time: 0.0277 memory: 16201 loss_prob: 0.3823 loss_thr: 0.2659 loss_db: 0.0671 loss: 0.7152 2022/08/30 20:51:26 - mmengine - INFO - Epoch(train) [1012][55/63] lr: 1.3211e-03 eta: 3:48:54 time: 0.7864 data_time: 0.0252 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2681 loss_db: 0.0662 loss: 0.7102 2022/08/30 20:51:30 - mmengine - INFO - Epoch(train) [1012][60/63] lr: 1.3211e-03 eta: 3:48:42 time: 0.7827 data_time: 0.0219 memory: 16201 loss_prob: 0.3300 loss_thr: 0.2390 loss_db: 0.0599 loss: 0.6290 2022/08/30 20:51:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:51:38 - mmengine - INFO - Epoch(train) [1013][5/63] lr: 1.3148e-03 eta: 3:48:42 time: 0.9962 data_time: 0.1943 memory: 16201 loss_prob: 0.3416 loss_thr: 0.2472 loss_db: 0.0606 loss: 0.6494 2022/08/30 20:51:42 - mmengine - INFO - Epoch(train) [1013][10/63] lr: 1.3148e-03 eta: 3:48:26 time: 0.9845 data_time: 0.2125 memory: 16201 loss_prob: 0.3710 loss_thr: 0.2500 loss_db: 0.0656 loss: 0.6865 2022/08/30 20:51:46 - mmengine - INFO - Epoch(train) [1013][15/63] lr: 1.3148e-03 eta: 3:48:26 time: 0.7853 data_time: 0.0264 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2272 loss_db: 0.0591 loss: 0.6166 2022/08/30 20:51:50 - mmengine - INFO - Epoch(train) [1013][20/63] lr: 1.3148e-03 eta: 3:48:13 time: 0.7595 data_time: 0.0166 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2258 loss_db: 0.0602 loss: 0.6269 2022/08/30 20:51:54 - mmengine - INFO - Epoch(train) [1013][25/63] lr: 1.3148e-03 eta: 3:48:13 time: 0.7893 data_time: 0.0311 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2382 loss_db: 0.0604 loss: 0.6446 2022/08/30 20:51:58 - mmengine - INFO - Epoch(train) [1013][30/63] lr: 1.3148e-03 eta: 3:48:01 time: 0.7864 data_time: 0.0229 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2491 loss_db: 0.0568 loss: 0.6258 2022/08/30 20:52:02 - mmengine - INFO - Epoch(train) [1013][35/63] lr: 1.3148e-03 eta: 3:48:01 time: 0.7750 data_time: 0.0168 memory: 16201 loss_prob: 0.3024 loss_thr: 0.2308 loss_db: 0.0535 loss: 0.5867 2022/08/30 20:52:06 - mmengine - INFO - Epoch(train) [1013][40/63] lr: 1.3148e-03 eta: 3:47:49 time: 0.7762 data_time: 0.0232 memory: 16201 loss_prob: 0.3172 loss_thr: 0.2288 loss_db: 0.0561 loss: 0.6021 2022/08/30 20:52:10 - mmengine - INFO - Epoch(train) [1013][45/63] lr: 1.3148e-03 eta: 3:47:49 time: 0.7805 data_time: 0.0229 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2547 loss_db: 0.0648 loss: 0.6818 2022/08/30 20:52:13 - mmengine - INFO - Epoch(train) [1013][50/63] lr: 1.3148e-03 eta: 3:47:37 time: 0.7852 data_time: 0.0248 memory: 16201 loss_prob: 0.3427 loss_thr: 0.2458 loss_db: 0.0619 loss: 0.6505 2022/08/30 20:52:17 - mmengine - INFO - Epoch(train) [1013][55/63] lr: 1.3148e-03 eta: 3:47:37 time: 0.7656 data_time: 0.0213 memory: 16201 loss_prob: 0.3160 loss_thr: 0.2284 loss_db: 0.0563 loss: 0.6006 2022/08/30 20:52:21 - mmengine - INFO - Epoch(train) [1013][60/63] lr: 1.3148e-03 eta: 3:47:24 time: 0.7826 data_time: 0.0207 memory: 16201 loss_prob: 0.3380 loss_thr: 0.2374 loss_db: 0.0602 loss: 0.6357 2022/08/30 20:52:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:52:28 - mmengine - INFO - Epoch(train) [1014][5/63] lr: 1.3084e-03 eta: 3:47:24 time: 0.8795 data_time: 0.1426 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2262 loss_db: 0.0552 loss: 0.5913 2022/08/30 20:52:32 - mmengine - INFO - Epoch(train) [1014][10/63] lr: 1.3084e-03 eta: 3:47:08 time: 0.9306 data_time: 0.1506 memory: 16201 loss_prob: 0.2733 loss_thr: 0.2065 loss_db: 0.0486 loss: 0.5285 2022/08/30 20:52:36 - mmengine - INFO - Epoch(train) [1014][15/63] lr: 1.3084e-03 eta: 3:47:08 time: 0.7848 data_time: 0.0231 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2390 loss_db: 0.0583 loss: 0.6223 2022/08/30 20:52:40 - mmengine - INFO - Epoch(train) [1014][20/63] lr: 1.3084e-03 eta: 3:46:56 time: 0.7615 data_time: 0.0204 memory: 16201 loss_prob: 0.3362 loss_thr: 0.2423 loss_db: 0.0599 loss: 0.6384 2022/08/30 20:52:45 - mmengine - INFO - Epoch(train) [1014][25/63] lr: 1.3084e-03 eta: 3:46:56 time: 0.8364 data_time: 0.0380 memory: 16201 loss_prob: 0.3519 loss_thr: 0.2424 loss_db: 0.0617 loss: 0.6559 2022/08/30 20:52:49 - mmengine - INFO - Epoch(train) [1014][30/63] lr: 1.3084e-03 eta: 3:46:44 time: 0.8551 data_time: 0.0382 memory: 16201 loss_prob: 0.3633 loss_thr: 0.2494 loss_db: 0.0639 loss: 0.6766 2022/08/30 20:52:53 - mmengine - INFO - Epoch(train) [1014][35/63] lr: 1.3084e-03 eta: 3:46:44 time: 0.7865 data_time: 0.0236 memory: 16201 loss_prob: 0.3573 loss_thr: 0.2503 loss_db: 0.0636 loss: 0.6712 2022/08/30 20:52:57 - mmengine - INFO - Epoch(train) [1014][40/63] lr: 1.3084e-03 eta: 3:46:31 time: 0.7853 data_time: 0.0252 memory: 16201 loss_prob: 0.3782 loss_thr: 0.2705 loss_db: 0.0660 loss: 0.7148 2022/08/30 20:53:00 - mmengine - INFO - Epoch(train) [1014][45/63] lr: 1.3084e-03 eta: 3:46:31 time: 0.7800 data_time: 0.0221 memory: 16201 loss_prob: 0.3771 loss_thr: 0.2734 loss_db: 0.0663 loss: 0.7168 2022/08/30 20:53:04 - mmengine - INFO - Epoch(train) [1014][50/63] lr: 1.3084e-03 eta: 3:46:19 time: 0.7829 data_time: 0.0214 memory: 16201 loss_prob: 0.3386 loss_thr: 0.2340 loss_db: 0.0617 loss: 0.6343 2022/08/30 20:53:08 - mmengine - INFO - Epoch(train) [1014][55/63] lr: 1.3084e-03 eta: 3:46:19 time: 0.8131 data_time: 0.0269 memory: 16201 loss_prob: 0.3207 loss_thr: 0.2278 loss_db: 0.0567 loss: 0.6052 2022/08/30 20:53:12 - mmengine - INFO - Epoch(train) [1014][60/63] lr: 1.3084e-03 eta: 3:46:07 time: 0.8071 data_time: 0.0247 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2432 loss_db: 0.0585 loss: 0.6343 2022/08/30 20:53:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:53:20 - mmengine - INFO - Epoch(train) [1015][5/63] lr: 1.3021e-03 eta: 3:46:07 time: 0.9032 data_time: 0.1749 memory: 16201 loss_prob: 0.3402 loss_thr: 0.2401 loss_db: 0.0601 loss: 0.6404 2022/08/30 20:53:24 - mmengine - INFO - Epoch(train) [1015][10/63] lr: 1.3021e-03 eta: 3:45:51 time: 0.9525 data_time: 0.1864 memory: 16201 loss_prob: 0.3620 loss_thr: 0.2551 loss_db: 0.0646 loss: 0.6817 2022/08/30 20:53:28 - mmengine - INFO - Epoch(train) [1015][15/63] lr: 1.3021e-03 eta: 3:45:51 time: 0.7898 data_time: 0.0249 memory: 16201 loss_prob: 0.3603 loss_thr: 0.2486 loss_db: 0.0630 loss: 0.6720 2022/08/30 20:53:32 - mmengine - INFO - Epoch(train) [1015][20/63] lr: 1.3021e-03 eta: 3:45:39 time: 0.8492 data_time: 0.0173 memory: 16201 loss_prob: 0.3407 loss_thr: 0.2354 loss_db: 0.0593 loss: 0.6353 2022/08/30 20:53:36 - mmengine - INFO - Epoch(train) [1015][25/63] lr: 1.3021e-03 eta: 3:45:39 time: 0.8561 data_time: 0.0329 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2422 loss_db: 0.0607 loss: 0.6416 2022/08/30 20:53:40 - mmengine - INFO - Epoch(train) [1015][30/63] lr: 1.3021e-03 eta: 3:45:26 time: 0.7872 data_time: 0.0268 memory: 16201 loss_prob: 0.3031 loss_thr: 0.2227 loss_db: 0.0548 loss: 0.5806 2022/08/30 20:53:45 - mmengine - INFO - Epoch(train) [1015][35/63] lr: 1.3021e-03 eta: 3:45:26 time: 0.8193 data_time: 0.0426 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2304 loss_db: 0.0570 loss: 0.6194 2022/08/30 20:53:48 - mmengine - INFO - Epoch(train) [1015][40/63] lr: 1.3021e-03 eta: 3:45:14 time: 0.8206 data_time: 0.0502 memory: 16201 loss_prob: 0.3755 loss_thr: 0.2558 loss_db: 0.0636 loss: 0.6949 2022/08/30 20:53:52 - mmengine - INFO - Epoch(train) [1015][45/63] lr: 1.3021e-03 eta: 3:45:14 time: 0.7863 data_time: 0.0257 memory: 16201 loss_prob: 0.3468 loss_thr: 0.2481 loss_db: 0.0603 loss: 0.6552 2022/08/30 20:53:56 - mmengine - INFO - Epoch(train) [1015][50/63] lr: 1.3021e-03 eta: 3:45:02 time: 0.7830 data_time: 0.0282 memory: 16201 loss_prob: 0.3475 loss_thr: 0.2445 loss_db: 0.0613 loss: 0.6533 2022/08/30 20:54:00 - mmengine - INFO - Epoch(train) [1015][55/63] lr: 1.3021e-03 eta: 3:45:02 time: 0.7692 data_time: 0.0261 memory: 16201 loss_prob: 0.3652 loss_thr: 0.2513 loss_db: 0.0656 loss: 0.6821 2022/08/30 20:54:04 - mmengine - INFO - Epoch(train) [1015][60/63] lr: 1.3021e-03 eta: 3:44:50 time: 0.8001 data_time: 0.0220 memory: 16201 loss_prob: 0.3708 loss_thr: 0.2530 loss_db: 0.0674 loss: 0.6912 2022/08/30 20:54:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:54:12 - mmengine - INFO - Epoch(train) [1016][5/63] lr: 1.2958e-03 eta: 3:44:50 time: 0.8914 data_time: 0.1639 memory: 16201 loss_prob: 0.3497 loss_thr: 0.2462 loss_db: 0.0617 loss: 0.6576 2022/08/30 20:54:16 - mmengine - INFO - Epoch(train) [1016][10/63] lr: 1.2958e-03 eta: 3:44:34 time: 0.9422 data_time: 0.1780 memory: 16201 loss_prob: 0.3012 loss_thr: 0.2284 loss_db: 0.0543 loss: 0.5839 2022/08/30 20:54:19 - mmengine - INFO - Epoch(train) [1016][15/63] lr: 1.2958e-03 eta: 3:44:34 time: 0.7707 data_time: 0.0234 memory: 16201 loss_prob: 0.3058 loss_thr: 0.2245 loss_db: 0.0552 loss: 0.5854 2022/08/30 20:54:24 - mmengine - INFO - Epoch(train) [1016][20/63] lr: 1.2958e-03 eta: 3:44:22 time: 0.8246 data_time: 0.0215 memory: 16201 loss_prob: 0.3525 loss_thr: 0.2426 loss_db: 0.0620 loss: 0.6572 2022/08/30 20:54:28 - mmengine - INFO - Epoch(train) [1016][25/63] lr: 1.2958e-03 eta: 3:44:22 time: 0.8420 data_time: 0.0339 memory: 16201 loss_prob: 0.3572 loss_thr: 0.2493 loss_db: 0.0638 loss: 0.6702 2022/08/30 20:54:32 - mmengine - INFO - Epoch(train) [1016][30/63] lr: 1.2958e-03 eta: 3:44:09 time: 0.7752 data_time: 0.0217 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2476 loss_db: 0.0637 loss: 0.6736 2022/08/30 20:54:36 - mmengine - INFO - Epoch(train) [1016][35/63] lr: 1.2958e-03 eta: 3:44:09 time: 0.7734 data_time: 0.0204 memory: 16201 loss_prob: 0.3625 loss_thr: 0.2559 loss_db: 0.0629 loss: 0.6813 2022/08/30 20:54:40 - mmengine - INFO - Epoch(train) [1016][40/63] lr: 1.2958e-03 eta: 3:43:57 time: 0.7848 data_time: 0.0249 memory: 16201 loss_prob: 0.3254 loss_thr: 0.2364 loss_db: 0.0581 loss: 0.6198 2022/08/30 20:54:44 - mmengine - INFO - Epoch(train) [1016][45/63] lr: 1.2958e-03 eta: 3:43:57 time: 0.8135 data_time: 0.0220 memory: 16201 loss_prob: 0.3348 loss_thr: 0.2364 loss_db: 0.0594 loss: 0.6306 2022/08/30 20:54:48 - mmengine - INFO - Epoch(train) [1016][50/63] lr: 1.2958e-03 eta: 3:43:45 time: 0.7995 data_time: 0.0258 memory: 16201 loss_prob: 0.3633 loss_thr: 0.2579 loss_db: 0.0635 loss: 0.6847 2022/08/30 20:54:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:54:51 - mmengine - INFO - Epoch(train) [1016][55/63] lr: 1.2958e-03 eta: 3:43:45 time: 0.7649 data_time: 0.0236 memory: 16201 loss_prob: 0.3590 loss_thr: 0.2637 loss_db: 0.0632 loss: 0.6859 2022/08/30 20:54:55 - mmengine - INFO - Epoch(train) [1016][60/63] lr: 1.2958e-03 eta: 3:43:33 time: 0.7658 data_time: 0.0223 memory: 16201 loss_prob: 0.3292 loss_thr: 0.2415 loss_db: 0.0590 loss: 0.6298 2022/08/30 20:54:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:55:03 - mmengine - INFO - Epoch(train) [1017][5/63] lr: 1.2894e-03 eta: 3:43:33 time: 0.9033 data_time: 0.1687 memory: 16201 loss_prob: 0.3986 loss_thr: 0.2665 loss_db: 0.0692 loss: 0.7344 2022/08/30 20:55:07 - mmengine - INFO - Epoch(train) [1017][10/63] lr: 1.2894e-03 eta: 3:43:17 time: 0.9471 data_time: 0.1825 memory: 16201 loss_prob: 0.3924 loss_thr: 0.2648 loss_db: 0.0690 loss: 0.7262 2022/08/30 20:55:11 - mmengine - INFO - Epoch(train) [1017][15/63] lr: 1.2894e-03 eta: 3:43:17 time: 0.7843 data_time: 0.0239 memory: 16201 loss_prob: 0.3372 loss_thr: 0.2358 loss_db: 0.0608 loss: 0.6338 2022/08/30 20:55:14 - mmengine - INFO - Epoch(train) [1017][20/63] lr: 1.2894e-03 eta: 3:43:04 time: 0.7937 data_time: 0.0171 memory: 16201 loss_prob: 0.2951 loss_thr: 0.2191 loss_db: 0.0535 loss: 0.5677 2022/08/30 20:55:18 - mmengine - INFO - Epoch(train) [1017][25/63] lr: 1.2894e-03 eta: 3:43:04 time: 0.7808 data_time: 0.0241 memory: 16201 loss_prob: 0.3331 loss_thr: 0.2366 loss_db: 0.0594 loss: 0.6292 2022/08/30 20:55:22 - mmengine - INFO - Epoch(train) [1017][30/63] lr: 1.2894e-03 eta: 3:42:52 time: 0.7828 data_time: 0.0275 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2440 loss_db: 0.0610 loss: 0.6486 2022/08/30 20:55:26 - mmengine - INFO - Epoch(train) [1017][35/63] lr: 1.2894e-03 eta: 3:42:52 time: 0.7918 data_time: 0.0278 memory: 16201 loss_prob: 0.3050 loss_thr: 0.2273 loss_db: 0.0546 loss: 0.5869 2022/08/30 20:55:30 - mmengine - INFO - Epoch(train) [1017][40/63] lr: 1.2894e-03 eta: 3:42:40 time: 0.7844 data_time: 0.0231 memory: 16201 loss_prob: 0.3746 loss_thr: 0.2527 loss_db: 0.0665 loss: 0.6938 2022/08/30 20:55:34 - mmengine - INFO - Epoch(train) [1017][45/63] lr: 1.2894e-03 eta: 3:42:40 time: 0.7841 data_time: 0.0227 memory: 16201 loss_prob: 0.3874 loss_thr: 0.2627 loss_db: 0.0687 loss: 0.7188 2022/08/30 20:55:38 - mmengine - INFO - Epoch(train) [1017][50/63] lr: 1.2894e-03 eta: 3:42:28 time: 0.8208 data_time: 0.0277 memory: 16201 loss_prob: 0.3130 loss_thr: 0.2271 loss_db: 0.0569 loss: 0.5970 2022/08/30 20:55:42 - mmengine - INFO - Epoch(train) [1017][55/63] lr: 1.2894e-03 eta: 3:42:28 time: 0.8161 data_time: 0.0267 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2305 loss_db: 0.0605 loss: 0.6220 2022/08/30 20:55:46 - mmengine - INFO - Epoch(train) [1017][60/63] lr: 1.2894e-03 eta: 3:42:15 time: 0.7857 data_time: 0.0247 memory: 16201 loss_prob: 0.3593 loss_thr: 0.2471 loss_db: 0.0645 loss: 0.6708 2022/08/30 20:55:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:55:54 - mmengine - INFO - Epoch(train) [1018][5/63] lr: 1.2831e-03 eta: 3:42:15 time: 0.8924 data_time: 0.1716 memory: 16201 loss_prob: 0.3522 loss_thr: 0.2463 loss_db: 0.0615 loss: 0.6599 2022/08/30 20:55:58 - mmengine - INFO - Epoch(train) [1018][10/63] lr: 1.2831e-03 eta: 3:41:59 time: 0.9390 data_time: 0.1801 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2460 loss_db: 0.0595 loss: 0.6535 2022/08/30 20:56:02 - mmengine - INFO - Epoch(train) [1018][15/63] lr: 1.2831e-03 eta: 3:41:59 time: 0.8159 data_time: 0.0245 memory: 16201 loss_prob: 0.3211 loss_thr: 0.2321 loss_db: 0.0565 loss: 0.6098 2022/08/30 20:56:06 - mmengine - INFO - Epoch(train) [1018][20/63] lr: 1.2831e-03 eta: 3:41:47 time: 0.8235 data_time: 0.0242 memory: 16201 loss_prob: 0.3366 loss_thr: 0.2420 loss_db: 0.0605 loss: 0.6390 2022/08/30 20:56:10 - mmengine - INFO - Epoch(train) [1018][25/63] lr: 1.2831e-03 eta: 3:41:47 time: 0.7927 data_time: 0.0284 memory: 16201 loss_prob: 0.3493 loss_thr: 0.2521 loss_db: 0.0616 loss: 0.6630 2022/08/30 20:56:14 - mmengine - INFO - Epoch(train) [1018][30/63] lr: 1.2831e-03 eta: 3:41:35 time: 0.7924 data_time: 0.0285 memory: 16201 loss_prob: 0.3503 loss_thr: 0.2544 loss_db: 0.0623 loss: 0.6670 2022/08/30 20:56:17 - mmengine - INFO - Epoch(train) [1018][35/63] lr: 1.2831e-03 eta: 3:41:35 time: 0.7776 data_time: 0.0226 memory: 16201 loss_prob: 0.3493 loss_thr: 0.2391 loss_db: 0.0635 loss: 0.6519 2022/08/30 20:56:22 - mmengine - INFO - Epoch(train) [1018][40/63] lr: 1.2831e-03 eta: 3:41:23 time: 0.7964 data_time: 0.0250 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2385 loss_db: 0.0672 loss: 0.6795 2022/08/30 20:56:26 - mmengine - INFO - Epoch(train) [1018][45/63] lr: 1.2831e-03 eta: 3:41:23 time: 0.8034 data_time: 0.0296 memory: 16201 loss_prob: 0.3812 loss_thr: 0.2525 loss_db: 0.0672 loss: 0.7010 2022/08/30 20:56:29 - mmengine - INFO - Epoch(train) [1018][50/63] lr: 1.2831e-03 eta: 3:41:11 time: 0.7763 data_time: 0.0216 memory: 16201 loss_prob: 0.3233 loss_thr: 0.2396 loss_db: 0.0582 loss: 0.6210 2022/08/30 20:56:33 - mmengine - INFO - Epoch(train) [1018][55/63] lr: 1.2831e-03 eta: 3:41:11 time: 0.7854 data_time: 0.0231 memory: 16201 loss_prob: 0.3063 loss_thr: 0.2317 loss_db: 0.0559 loss: 0.5938 2022/08/30 20:56:37 - mmengine - INFO - Epoch(train) [1018][60/63] lr: 1.2831e-03 eta: 3:40:58 time: 0.7817 data_time: 0.0255 memory: 16201 loss_prob: 0.3285 loss_thr: 0.2363 loss_db: 0.0595 loss: 0.6243 2022/08/30 20:56:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:56:45 - mmengine - INFO - Epoch(train) [1019][5/63] lr: 1.2767e-03 eta: 3:40:58 time: 0.9175 data_time: 0.1955 memory: 16201 loss_prob: 0.3116 loss_thr: 0.2256 loss_db: 0.0564 loss: 0.5936 2022/08/30 20:56:49 - mmengine - INFO - Epoch(train) [1019][10/63] lr: 1.2767e-03 eta: 3:40:42 time: 0.9621 data_time: 0.2042 memory: 16201 loss_prob: 0.3284 loss_thr: 0.2279 loss_db: 0.0587 loss: 0.6151 2022/08/30 20:56:53 - mmengine - INFO - Epoch(train) [1019][15/63] lr: 1.2767e-03 eta: 3:40:42 time: 0.8166 data_time: 0.0266 memory: 16201 loss_prob: 0.3519 loss_thr: 0.2349 loss_db: 0.0614 loss: 0.6482 2022/08/30 20:56:57 - mmengine - INFO - Epoch(train) [1019][20/63] lr: 1.2767e-03 eta: 3:40:30 time: 0.8165 data_time: 0.0219 memory: 16201 loss_prob: 0.3453 loss_thr: 0.2360 loss_db: 0.0623 loss: 0.6435 2022/08/30 20:57:01 - mmengine - INFO - Epoch(train) [1019][25/63] lr: 1.2767e-03 eta: 3:40:30 time: 0.7903 data_time: 0.0282 memory: 16201 loss_prob: 0.3420 loss_thr: 0.2353 loss_db: 0.0593 loss: 0.6366 2022/08/30 20:57:05 - mmengine - INFO - Epoch(train) [1019][30/63] lr: 1.2767e-03 eta: 3:40:18 time: 0.7945 data_time: 0.0261 memory: 16201 loss_prob: 0.3442 loss_thr: 0.2416 loss_db: 0.0594 loss: 0.6453 2022/08/30 20:57:09 - mmengine - INFO - Epoch(train) [1019][35/63] lr: 1.2767e-03 eta: 3:40:18 time: 0.7915 data_time: 0.0217 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2371 loss_db: 0.0601 loss: 0.6291 2022/08/30 20:57:13 - mmengine - INFO - Epoch(train) [1019][40/63] lr: 1.2767e-03 eta: 3:40:06 time: 0.8002 data_time: 0.0257 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2343 loss_db: 0.0571 loss: 0.6124 2022/08/30 20:57:17 - mmengine - INFO - Epoch(train) [1019][45/63] lr: 1.2767e-03 eta: 3:40:06 time: 0.8066 data_time: 0.0259 memory: 16201 loss_prob: 0.3137 loss_thr: 0.2410 loss_db: 0.0555 loss: 0.6102 2022/08/30 20:57:21 - mmengine - INFO - Epoch(train) [1019][50/63] lr: 1.2767e-03 eta: 3:39:54 time: 0.7947 data_time: 0.0217 memory: 16201 loss_prob: 0.3231 loss_thr: 0.2382 loss_db: 0.0574 loss: 0.6187 2022/08/30 20:57:25 - mmengine - INFO - Epoch(train) [1019][55/63] lr: 1.2767e-03 eta: 3:39:54 time: 0.8171 data_time: 0.0327 memory: 16201 loss_prob: 0.3349 loss_thr: 0.2384 loss_db: 0.0597 loss: 0.6330 2022/08/30 20:57:29 - mmengine - INFO - Epoch(train) [1019][60/63] lr: 1.2767e-03 eta: 3:39:41 time: 0.8027 data_time: 0.0317 memory: 16201 loss_prob: 0.3525 loss_thr: 0.2534 loss_db: 0.0635 loss: 0.6694 2022/08/30 20:57:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:57:37 - mmengine - INFO - Epoch(train) [1020][5/63] lr: 1.2704e-03 eta: 3:39:41 time: 0.9117 data_time: 0.1811 memory: 16201 loss_prob: 0.3257 loss_thr: 0.2243 loss_db: 0.0569 loss: 0.6070 2022/08/30 20:57:41 - mmengine - INFO - Epoch(train) [1020][10/63] lr: 1.2704e-03 eta: 3:39:25 time: 0.9627 data_time: 0.1888 memory: 16201 loss_prob: 0.3663 loss_thr: 0.2494 loss_db: 0.0639 loss: 0.6795 2022/08/30 20:57:44 - mmengine - INFO - Epoch(train) [1020][15/63] lr: 1.2704e-03 eta: 3:39:25 time: 0.7935 data_time: 0.0240 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2506 loss_db: 0.0622 loss: 0.6668 2022/08/30 20:57:48 - mmengine - INFO - Epoch(train) [1020][20/63] lr: 1.2704e-03 eta: 3:39:13 time: 0.7784 data_time: 0.0223 memory: 16201 loss_prob: 0.3538 loss_thr: 0.2435 loss_db: 0.0630 loss: 0.6603 2022/08/30 20:57:53 - mmengine - INFO - Epoch(train) [1020][25/63] lr: 1.2704e-03 eta: 3:39:13 time: 0.8250 data_time: 0.0300 memory: 16201 loss_prob: 0.3541 loss_thr: 0.2384 loss_db: 0.0624 loss: 0.6548 2022/08/30 20:57:57 - mmengine - INFO - Epoch(train) [1020][30/63] lr: 1.2704e-03 eta: 3:39:01 time: 0.8354 data_time: 0.0247 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2329 loss_db: 0.0589 loss: 0.6283 2022/08/30 20:58:01 - mmengine - INFO - Epoch(train) [1020][35/63] lr: 1.2704e-03 eta: 3:39:01 time: 0.7804 data_time: 0.0180 memory: 16201 loss_prob: 0.3372 loss_thr: 0.2364 loss_db: 0.0598 loss: 0.6334 2022/08/30 20:58:05 - mmengine - INFO - Epoch(train) [1020][40/63] lr: 1.2704e-03 eta: 3:38:49 time: 0.7844 data_time: 0.0229 memory: 16201 loss_prob: 0.3305 loss_thr: 0.2318 loss_db: 0.0595 loss: 0.6218 2022/08/30 20:58:08 - mmengine - INFO - Epoch(train) [1020][45/63] lr: 1.2704e-03 eta: 3:38:49 time: 0.7885 data_time: 0.0285 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2303 loss_db: 0.0617 loss: 0.6285 2022/08/30 20:58:13 - mmengine - INFO - Epoch(train) [1020][50/63] lr: 1.2704e-03 eta: 3:38:37 time: 0.8024 data_time: 0.0260 memory: 16201 loss_prob: 0.3858 loss_thr: 0.2551 loss_db: 0.0677 loss: 0.7086 2022/08/30 20:58:16 - mmengine - INFO - Epoch(train) [1020][55/63] lr: 1.2704e-03 eta: 3:38:37 time: 0.8030 data_time: 0.0264 memory: 16201 loss_prob: 0.3747 loss_thr: 0.2611 loss_db: 0.0654 loss: 0.7012 2022/08/30 20:58:20 - mmengine - INFO - Epoch(train) [1020][60/63] lr: 1.2704e-03 eta: 3:38:24 time: 0.7743 data_time: 0.0260 memory: 16201 loss_prob: 0.3230 loss_thr: 0.2352 loss_db: 0.0583 loss: 0.6165 2022/08/30 20:58:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:58:22 - mmengine - INFO - Saving checkpoint at 1020 epochs 2022/08/30 20:58:31 - mmengine - INFO - Epoch(val) [1020][5/32] eta: 3:38:24 time: 0.6677 data_time: 0.1604 memory: 16201 2022/08/30 20:58:34 - mmengine - INFO - Epoch(val) [1020][10/32] eta: 0:00:16 time: 0.7448 data_time: 0.1911 memory: 15734 2022/08/30 20:58:36 - mmengine - INFO - Epoch(val) [1020][15/32] eta: 0:00:16 time: 0.5865 data_time: 0.0439 memory: 15734 2022/08/30 20:58:39 - mmengine - INFO - Epoch(val) [1020][20/32] eta: 0:00:06 time: 0.5787 data_time: 0.0445 memory: 15734 2022/08/30 20:58:43 - mmengine - INFO - Epoch(val) [1020][25/32] eta: 0:00:06 time: 0.6262 data_time: 0.0510 memory: 15734 2022/08/30 20:58:45 - mmengine - INFO - Epoch(val) [1020][30/32] eta: 0:00:01 time: 0.6023 data_time: 0.0264 memory: 15734 2022/08/30 20:58:46 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 20:58:46 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8488, precision: 0.7995, hmean: 0.8234 2022/08/30 20:58:46 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8488, precision: 0.8351, hmean: 0.8419 2022/08/30 20:58:46 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8483, precision: 0.8558, hmean: 0.8520 2022/08/30 20:58:46 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8469, precision: 0.8751, hmean: 0.8608 2022/08/30 20:58:46 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8392, precision: 0.8925, hmean: 0.8650 2022/08/30 20:58:46 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8185, precision: 0.9159, hmean: 0.8645 2022/08/30 20:58:46 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4757, precision: 0.9509, hmean: 0.6341 2022/08/30 20:58:46 - mmengine - INFO - Epoch(val) [1020][32/32] icdar/precision: 0.8925 icdar/recall: 0.8392 icdar/hmean: 0.8650 2022/08/30 20:58:52 - mmengine - INFO - Epoch(train) [1021][5/63] lr: 1.2640e-03 eta: 0:00:01 time: 0.9415 data_time: 0.1929 memory: 16201 loss_prob: 0.3126 loss_thr: 0.2250 loss_db: 0.0543 loss: 0.5918 2022/08/30 20:58:56 - mmengine - INFO - Epoch(train) [1021][10/63] lr: 1.2640e-03 eta: 3:38:08 time: 0.9723 data_time: 0.1978 memory: 16201 loss_prob: 0.3370 loss_thr: 0.2371 loss_db: 0.0598 loss: 0.6339 2022/08/30 20:59:00 - mmengine - INFO - Epoch(train) [1021][15/63] lr: 1.2640e-03 eta: 3:38:08 time: 0.7688 data_time: 0.0185 memory: 16201 loss_prob: 0.3565 loss_thr: 0.2551 loss_db: 0.0646 loss: 0.6762 2022/08/30 20:59:04 - mmengine - INFO - Epoch(train) [1021][20/63] lr: 1.2640e-03 eta: 3:37:56 time: 0.8229 data_time: 0.0225 memory: 16201 loss_prob: 0.3330 loss_thr: 0.2487 loss_db: 0.0601 loss: 0.6418 2022/08/30 20:59:08 - mmengine - INFO - Epoch(train) [1021][25/63] lr: 1.2640e-03 eta: 3:37:56 time: 0.8426 data_time: 0.0322 memory: 16201 loss_prob: 0.3476 loss_thr: 0.2403 loss_db: 0.0631 loss: 0.6511 2022/08/30 20:59:12 - mmengine - INFO - Epoch(train) [1021][30/63] lr: 1.2640e-03 eta: 3:37:44 time: 0.7897 data_time: 0.0224 memory: 16201 loss_prob: 0.3414 loss_thr: 0.2340 loss_db: 0.0608 loss: 0.6362 2022/08/30 20:59:16 - mmengine - INFO - Epoch(train) [1021][35/63] lr: 1.2640e-03 eta: 3:37:44 time: 0.7860 data_time: 0.0240 memory: 16201 loss_prob: 0.3361 loss_thr: 0.2381 loss_db: 0.0586 loss: 0.6328 2022/08/30 20:59:20 - mmengine - INFO - Epoch(train) [1021][40/63] lr: 1.2640e-03 eta: 3:37:32 time: 0.7831 data_time: 0.0254 memory: 16201 loss_prob: 0.3500 loss_thr: 0.2490 loss_db: 0.0623 loss: 0.6613 2022/08/30 20:59:24 - mmengine - INFO - Epoch(train) [1021][45/63] lr: 1.2640e-03 eta: 3:37:32 time: 0.8081 data_time: 0.0190 memory: 16201 loss_prob: 0.3308 loss_thr: 0.2378 loss_db: 0.0597 loss: 0.6283 2022/08/30 20:59:28 - mmengine - INFO - Epoch(train) [1021][50/63] lr: 1.2640e-03 eta: 3:37:20 time: 0.8081 data_time: 0.0291 memory: 16201 loss_prob: 0.3065 loss_thr: 0.2256 loss_db: 0.0548 loss: 0.5868 2022/08/30 20:59:32 - mmengine - INFO - Epoch(train) [1021][55/63] lr: 1.2640e-03 eta: 3:37:20 time: 0.7834 data_time: 0.0281 memory: 16201 loss_prob: 0.3158 loss_thr: 0.2284 loss_db: 0.0551 loss: 0.5992 2022/08/30 20:59:36 - mmengine - INFO - Epoch(train) [1021][60/63] lr: 1.2640e-03 eta: 3:37:08 time: 0.7741 data_time: 0.0218 memory: 16201 loss_prob: 0.3394 loss_thr: 0.2321 loss_db: 0.0585 loss: 0.6300 2022/08/30 20:59:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 20:59:43 - mmengine - INFO - Epoch(train) [1022][5/63] lr: 1.2577e-03 eta: 3:37:08 time: 0.8831 data_time: 0.1543 memory: 16201 loss_prob: 0.3670 loss_thr: 0.2569 loss_db: 0.0653 loss: 0.6893 2022/08/30 20:59:47 - mmengine - INFO - Epoch(train) [1022][10/63] lr: 1.2577e-03 eta: 3:36:52 time: 0.9261 data_time: 0.1615 memory: 16201 loss_prob: 0.3894 loss_thr: 0.2617 loss_db: 0.0683 loss: 0.7194 2022/08/30 20:59:51 - mmengine - INFO - Epoch(train) [1022][15/63] lr: 1.2577e-03 eta: 3:36:52 time: 0.8013 data_time: 0.0285 memory: 16201 loss_prob: 0.3621 loss_thr: 0.2544 loss_db: 0.0637 loss: 0.6802 2022/08/30 20:59:55 - mmengine - INFO - Epoch(train) [1022][20/63] lr: 1.2577e-03 eta: 3:36:39 time: 0.8085 data_time: 0.0246 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2444 loss_db: 0.0614 loss: 0.6497 2022/08/30 20:59:59 - mmengine - INFO - Epoch(train) [1022][25/63] lr: 1.2577e-03 eta: 3:36:39 time: 0.7967 data_time: 0.0274 memory: 16201 loss_prob: 0.3417 loss_thr: 0.2293 loss_db: 0.0606 loss: 0.6316 2022/08/30 21:00:03 - mmengine - INFO - Epoch(train) [1022][30/63] lr: 1.2577e-03 eta: 3:36:27 time: 0.7849 data_time: 0.0230 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2200 loss_db: 0.0582 loss: 0.5980 2022/08/30 21:00:07 - mmengine - INFO - Epoch(train) [1022][35/63] lr: 1.2577e-03 eta: 3:36:27 time: 0.7861 data_time: 0.0232 memory: 16201 loss_prob: 0.3381 loss_thr: 0.2390 loss_db: 0.0617 loss: 0.6388 2022/08/30 21:00:11 - mmengine - INFO - Epoch(train) [1022][40/63] lr: 1.2577e-03 eta: 3:36:15 time: 0.7734 data_time: 0.0194 memory: 16201 loss_prob: 0.3080 loss_thr: 0.2271 loss_db: 0.0545 loss: 0.5896 2022/08/30 21:00:15 - mmengine - INFO - Epoch(train) [1022][45/63] lr: 1.2577e-03 eta: 3:36:15 time: 0.8331 data_time: 0.0315 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2224 loss_db: 0.0560 loss: 0.5899 2022/08/30 21:00:19 - mmengine - INFO - Epoch(train) [1022][50/63] lr: 1.2577e-03 eta: 3:36:03 time: 0.8547 data_time: 0.0425 memory: 16201 loss_prob: 0.3155 loss_thr: 0.2216 loss_db: 0.0579 loss: 0.5950 2022/08/30 21:00:23 - mmengine - INFO - Epoch(train) [1022][55/63] lr: 1.2577e-03 eta: 3:36:03 time: 0.7824 data_time: 0.0200 memory: 16201 loss_prob: 0.3274 loss_thr: 0.2334 loss_db: 0.0584 loss: 0.6193 2022/08/30 21:00:27 - mmengine - INFO - Epoch(train) [1022][60/63] lr: 1.2577e-03 eta: 3:35:51 time: 0.7962 data_time: 0.0231 memory: 16201 loss_prob: 0.3483 loss_thr: 0.2369 loss_db: 0.0601 loss: 0.6453 2022/08/30 21:00:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:00:35 - mmengine - INFO - Epoch(train) [1023][5/63] lr: 1.2513e-03 eta: 3:35:51 time: 0.9366 data_time: 0.2043 memory: 16201 loss_prob: 0.3241 loss_thr: 0.2267 loss_db: 0.0570 loss: 0.6078 2022/08/30 21:00:39 - mmengine - INFO - Epoch(train) [1023][10/63] lr: 1.2513e-03 eta: 3:35:35 time: 0.9833 data_time: 0.2158 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2372 loss_db: 0.0604 loss: 0.6363 2022/08/30 21:00:44 - mmengine - INFO - Epoch(train) [1023][15/63] lr: 1.2513e-03 eta: 3:35:35 time: 0.8431 data_time: 0.0244 memory: 16201 loss_prob: 0.3594 loss_thr: 0.2463 loss_db: 0.0612 loss: 0.6669 2022/08/30 21:00:47 - mmengine - INFO - Epoch(train) [1023][20/63] lr: 1.2513e-03 eta: 3:35:23 time: 0.8348 data_time: 0.0212 memory: 16201 loss_prob: 0.3808 loss_thr: 0.2652 loss_db: 0.0643 loss: 0.7103 2022/08/30 21:00:51 - mmengine - INFO - Epoch(train) [1023][25/63] lr: 1.2513e-03 eta: 3:35:23 time: 0.7883 data_time: 0.0355 memory: 16201 loss_prob: 0.3344 loss_thr: 0.2417 loss_db: 0.0599 loss: 0.6360 2022/08/30 21:00:55 - mmengine - INFO - Epoch(train) [1023][30/63] lr: 1.2513e-03 eta: 3:35:11 time: 0.7839 data_time: 0.0245 memory: 16201 loss_prob: 0.2977 loss_thr: 0.2229 loss_db: 0.0559 loss: 0.5765 2022/08/30 21:00:59 - mmengine - INFO - Epoch(train) [1023][35/63] lr: 1.2513e-03 eta: 3:35:11 time: 0.7897 data_time: 0.0177 memory: 16201 loss_prob: 0.3608 loss_thr: 0.2607 loss_db: 0.0639 loss: 0.6854 2022/08/30 21:01:03 - mmengine - INFO - Epoch(train) [1023][40/63] lr: 1.2513e-03 eta: 3:34:58 time: 0.8124 data_time: 0.0248 memory: 16201 loss_prob: 0.3868 loss_thr: 0.2645 loss_db: 0.0677 loss: 0.7190 2022/08/30 21:01:07 - mmengine - INFO - Epoch(train) [1023][45/63] lr: 1.2513e-03 eta: 3:34:58 time: 0.7978 data_time: 0.0259 memory: 16201 loss_prob: 0.3621 loss_thr: 0.2485 loss_db: 0.0656 loss: 0.6762 2022/08/30 21:01:11 - mmengine - INFO - Epoch(train) [1023][50/63] lr: 1.2513e-03 eta: 3:34:46 time: 0.7698 data_time: 0.0264 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2379 loss_db: 0.0592 loss: 0.6271 2022/08/30 21:01:15 - mmengine - INFO - Epoch(train) [1023][55/63] lr: 1.2513e-03 eta: 3:34:46 time: 0.7883 data_time: 0.0253 memory: 16201 loss_prob: 0.3167 loss_thr: 0.2336 loss_db: 0.0555 loss: 0.6057 2022/08/30 21:01:19 - mmengine - INFO - Epoch(train) [1023][60/63] lr: 1.2513e-03 eta: 3:34:34 time: 0.7937 data_time: 0.0256 memory: 16201 loss_prob: 0.3257 loss_thr: 0.2406 loss_db: 0.0582 loss: 0.6245 2022/08/30 21:01:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:01:27 - mmengine - INFO - Epoch(train) [1024][5/63] lr: 1.2449e-03 eta: 3:34:34 time: 0.9185 data_time: 0.1990 memory: 16201 loss_prob: 0.3172 loss_thr: 0.2274 loss_db: 0.0562 loss: 0.6008 2022/08/30 21:01:31 - mmengine - INFO - Epoch(train) [1024][10/63] lr: 1.2449e-03 eta: 3:34:18 time: 0.9733 data_time: 0.2149 memory: 16201 loss_prob: 0.3456 loss_thr: 0.2382 loss_db: 0.0609 loss: 0.6448 2022/08/30 21:01:35 - mmengine - INFO - Epoch(train) [1024][15/63] lr: 1.2449e-03 eta: 3:34:18 time: 0.7727 data_time: 0.0247 memory: 16201 loss_prob: 0.3689 loss_thr: 0.2524 loss_db: 0.0669 loss: 0.6882 2022/08/30 21:01:38 - mmengine - INFO - Epoch(train) [1024][20/63] lr: 1.2449e-03 eta: 3:34:06 time: 0.7747 data_time: 0.0201 memory: 16201 loss_prob: 0.3452 loss_thr: 0.2500 loss_db: 0.0627 loss: 0.6579 2022/08/30 21:01:42 - mmengine - INFO - Epoch(train) [1024][25/63] lr: 1.2449e-03 eta: 3:34:06 time: 0.7975 data_time: 0.0276 memory: 16201 loss_prob: 0.3338 loss_thr: 0.2479 loss_db: 0.0585 loss: 0.6402 2022/08/30 21:01:47 - mmengine - INFO - Epoch(train) [1024][30/63] lr: 1.2449e-03 eta: 3:33:54 time: 0.8076 data_time: 0.0259 memory: 16201 loss_prob: 0.3473 loss_thr: 0.2526 loss_db: 0.0597 loss: 0.6595 2022/08/30 21:01:50 - mmengine - INFO - Epoch(train) [1024][35/63] lr: 1.2449e-03 eta: 3:33:54 time: 0.7921 data_time: 0.0255 memory: 16201 loss_prob: 0.3293 loss_thr: 0.2402 loss_db: 0.0568 loss: 0.6263 2022/08/30 21:01:54 - mmengine - INFO - Epoch(train) [1024][40/63] lr: 1.2449e-03 eta: 3:33:42 time: 0.7979 data_time: 0.0230 memory: 16201 loss_prob: 0.3106 loss_thr: 0.2251 loss_db: 0.0547 loss: 0.5904 2022/08/30 21:01:58 - mmengine - INFO - Epoch(train) [1024][45/63] lr: 1.2449e-03 eta: 3:33:42 time: 0.7965 data_time: 0.0242 memory: 16201 loss_prob: 0.3546 loss_thr: 0.2454 loss_db: 0.0639 loss: 0.6639 2022/08/30 21:02:03 - mmengine - INFO - Epoch(train) [1024][50/63] lr: 1.2449e-03 eta: 3:33:29 time: 0.8076 data_time: 0.0281 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2444 loss_db: 0.0625 loss: 0.6606 2022/08/30 21:02:06 - mmengine - INFO - Epoch(train) [1024][55/63] lr: 1.2449e-03 eta: 3:33:29 time: 0.8065 data_time: 0.0267 memory: 16201 loss_prob: 0.3304 loss_thr: 0.2370 loss_db: 0.0581 loss: 0.6255 2022/08/30 21:02:11 - mmengine - INFO - Epoch(train) [1024][60/63] lr: 1.2449e-03 eta: 3:33:17 time: 0.7943 data_time: 0.0288 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2550 loss_db: 0.0616 loss: 0.6706 2022/08/30 21:02:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:02:18 - mmengine - INFO - Epoch(train) [1025][5/63] lr: 1.2386e-03 eta: 3:33:17 time: 0.9388 data_time: 0.2141 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2315 loss_db: 0.0590 loss: 0.6208 2022/08/30 21:02:22 - mmengine - INFO - Epoch(train) [1025][10/63] lr: 1.2386e-03 eta: 3:33:01 time: 0.9833 data_time: 0.2238 memory: 16201 loss_prob: 0.3545 loss_thr: 0.2385 loss_db: 0.0619 loss: 0.6548 2022/08/30 21:02:26 - mmengine - INFO - Epoch(train) [1025][15/63] lr: 1.2386e-03 eta: 3:33:01 time: 0.7831 data_time: 0.0236 memory: 16201 loss_prob: 0.3505 loss_thr: 0.2390 loss_db: 0.0604 loss: 0.6499 2022/08/30 21:02:30 - mmengine - INFO - Epoch(train) [1025][20/63] lr: 1.2386e-03 eta: 3:32:49 time: 0.7772 data_time: 0.0187 memory: 16201 loss_prob: 0.3264 loss_thr: 0.2458 loss_db: 0.0576 loss: 0.6298 2022/08/30 21:02:34 - mmengine - INFO - Epoch(train) [1025][25/63] lr: 1.2386e-03 eta: 3:32:49 time: 0.7908 data_time: 0.0291 memory: 16201 loss_prob: 0.3403 loss_thr: 0.2544 loss_db: 0.0612 loss: 0.6559 2022/08/30 21:02:38 - mmengine - INFO - Epoch(train) [1025][30/63] lr: 1.2386e-03 eta: 3:32:37 time: 0.7891 data_time: 0.0258 memory: 16201 loss_prob: 0.3308 loss_thr: 0.2429 loss_db: 0.0595 loss: 0.6333 2022/08/30 21:02:42 - mmengine - INFO - Epoch(train) [1025][35/63] lr: 1.2386e-03 eta: 3:32:37 time: 0.7935 data_time: 0.0252 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2362 loss_db: 0.0567 loss: 0.6169 2022/08/30 21:02:46 - mmengine - INFO - Epoch(train) [1025][40/63] lr: 1.2386e-03 eta: 3:32:25 time: 0.7934 data_time: 0.0235 memory: 16201 loss_prob: 0.3215 loss_thr: 0.2335 loss_db: 0.0573 loss: 0.6123 2022/08/30 21:02:50 - mmengine - INFO - Epoch(train) [1025][45/63] lr: 1.2386e-03 eta: 3:32:25 time: 0.7760 data_time: 0.0234 memory: 16201 loss_prob: 0.3600 loss_thr: 0.2530 loss_db: 0.0633 loss: 0.6762 2022/08/30 21:02:54 - mmengine - INFO - Epoch(train) [1025][50/63] lr: 1.2386e-03 eta: 3:32:13 time: 0.7831 data_time: 0.0279 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2489 loss_db: 0.0637 loss: 0.6779 2022/08/30 21:02:58 - mmengine - INFO - Epoch(train) [1025][55/63] lr: 1.2386e-03 eta: 3:32:13 time: 0.7922 data_time: 0.0232 memory: 16201 loss_prob: 0.3540 loss_thr: 0.2408 loss_db: 0.0622 loss: 0.6569 2022/08/30 21:03:02 - mmengine - INFO - Epoch(train) [1025][60/63] lr: 1.2386e-03 eta: 3:32:01 time: 0.8285 data_time: 0.0205 memory: 16201 loss_prob: 0.3240 loss_thr: 0.2387 loss_db: 0.0573 loss: 0.6201 2022/08/30 21:03:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:03:09 - mmengine - INFO - Epoch(train) [1026][5/63] lr: 1.2322e-03 eta: 3:32:01 time: 0.9243 data_time: 0.1568 memory: 16201 loss_prob: 0.3254 loss_thr: 0.2273 loss_db: 0.0568 loss: 0.6094 2022/08/30 21:03:13 - mmengine - INFO - Epoch(train) [1026][10/63] lr: 1.2322e-03 eta: 3:31:45 time: 0.9273 data_time: 0.1725 memory: 16201 loss_prob: 0.3687 loss_thr: 0.2523 loss_db: 0.0641 loss: 0.6852 2022/08/30 21:03:17 - mmengine - INFO - Epoch(train) [1026][15/63] lr: 1.2322e-03 eta: 3:31:45 time: 0.7800 data_time: 0.0250 memory: 16201 loss_prob: 0.3758 loss_thr: 0.2618 loss_db: 0.0671 loss: 0.7048 2022/08/30 21:03:21 - mmengine - INFO - Epoch(train) [1026][20/63] lr: 1.2322e-03 eta: 3:31:33 time: 0.7812 data_time: 0.0160 memory: 16201 loss_prob: 0.3372 loss_thr: 0.2410 loss_db: 0.0609 loss: 0.6390 2022/08/30 21:03:25 - mmengine - INFO - Epoch(train) [1026][25/63] lr: 1.2322e-03 eta: 3:31:33 time: 0.8159 data_time: 0.0351 memory: 16201 loss_prob: 0.3211 loss_thr: 0.2302 loss_db: 0.0581 loss: 0.6094 2022/08/30 21:03:29 - mmengine - INFO - Epoch(train) [1026][30/63] lr: 1.2322e-03 eta: 3:31:20 time: 0.8098 data_time: 0.0285 memory: 16201 loss_prob: 0.3212 loss_thr: 0.2342 loss_db: 0.0572 loss: 0.6126 2022/08/30 21:03:33 - mmengine - INFO - Epoch(train) [1026][35/63] lr: 1.2322e-03 eta: 3:31:20 time: 0.7976 data_time: 0.0204 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2432 loss_db: 0.0578 loss: 0.6262 2022/08/30 21:03:37 - mmengine - INFO - Epoch(train) [1026][40/63] lr: 1.2322e-03 eta: 3:31:08 time: 0.7909 data_time: 0.0272 memory: 16201 loss_prob: 0.3574 loss_thr: 0.2491 loss_db: 0.0644 loss: 0.6708 2022/08/30 21:03:41 - mmengine - INFO - Epoch(train) [1026][45/63] lr: 1.2322e-03 eta: 3:31:08 time: 0.7644 data_time: 0.0233 memory: 16201 loss_prob: 0.3446 loss_thr: 0.2371 loss_db: 0.0620 loss: 0.6438 2022/08/30 21:03:45 - mmengine - INFO - Epoch(train) [1026][50/63] lr: 1.2322e-03 eta: 3:30:56 time: 0.7972 data_time: 0.0262 memory: 16201 loss_prob: 0.3261 loss_thr: 0.2233 loss_db: 0.0579 loss: 0.6072 2022/08/30 21:03:49 - mmengine - INFO - Epoch(train) [1026][55/63] lr: 1.2322e-03 eta: 3:30:56 time: 0.8036 data_time: 0.0239 memory: 16201 loss_prob: 0.3065 loss_thr: 0.2133 loss_db: 0.0537 loss: 0.5735 2022/08/30 21:03:53 - mmengine - INFO - Epoch(train) [1026][60/63] lr: 1.2322e-03 eta: 3:30:44 time: 0.7991 data_time: 0.0222 memory: 16201 loss_prob: 0.3083 loss_thr: 0.2305 loss_db: 0.0541 loss: 0.5929 2022/08/30 21:03:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:04:01 - mmengine - INFO - Epoch(train) [1027][5/63] lr: 1.2258e-03 eta: 3:30:44 time: 0.9326 data_time: 0.1867 memory: 16201 loss_prob: 0.3505 loss_thr: 0.2546 loss_db: 0.0639 loss: 0.6690 2022/08/30 21:04:05 - mmengine - INFO - Epoch(train) [1027][10/63] lr: 1.2258e-03 eta: 3:30:28 time: 0.9725 data_time: 0.1978 memory: 16201 loss_prob: 0.3374 loss_thr: 0.2524 loss_db: 0.0609 loss: 0.6507 2022/08/30 21:04:09 - mmengine - INFO - Epoch(train) [1027][15/63] lr: 1.2258e-03 eta: 3:30:28 time: 0.7875 data_time: 0.0243 memory: 16201 loss_prob: 0.3611 loss_thr: 0.2658 loss_db: 0.0640 loss: 0.6910 2022/08/30 21:04:13 - mmengine - INFO - Epoch(train) [1027][20/63] lr: 1.2258e-03 eta: 3:30:16 time: 0.8613 data_time: 0.0268 memory: 16201 loss_prob: 0.3478 loss_thr: 0.2459 loss_db: 0.0616 loss: 0.6552 2022/08/30 21:04:17 - mmengine - INFO - Epoch(train) [1027][25/63] lr: 1.2258e-03 eta: 3:30:16 time: 0.8585 data_time: 0.0311 memory: 16201 loss_prob: 0.3238 loss_thr: 0.2340 loss_db: 0.0569 loss: 0.6146 2022/08/30 21:04:21 - mmengine - INFO - Epoch(train) [1027][30/63] lr: 1.2258e-03 eta: 3:30:04 time: 0.7719 data_time: 0.0248 memory: 16201 loss_prob: 0.3325 loss_thr: 0.2463 loss_db: 0.0585 loss: 0.6372 2022/08/30 21:04:25 - mmengine - INFO - Epoch(train) [1027][35/63] lr: 1.2258e-03 eta: 3:30:04 time: 0.7841 data_time: 0.0227 memory: 16201 loss_prob: 0.3340 loss_thr: 0.2443 loss_db: 0.0598 loss: 0.6381 2022/08/30 21:04:29 - mmengine - INFO - Epoch(train) [1027][40/63] lr: 1.2258e-03 eta: 3:29:52 time: 0.7847 data_time: 0.0220 memory: 16201 loss_prob: 0.3526 loss_thr: 0.2373 loss_db: 0.0634 loss: 0.6533 2022/08/30 21:04:33 - mmengine - INFO - Epoch(train) [1027][45/63] lr: 1.2258e-03 eta: 3:29:52 time: 0.8338 data_time: 0.0268 memory: 16201 loss_prob: 0.3355 loss_thr: 0.2346 loss_db: 0.0595 loss: 0.6296 2022/08/30 21:04:37 - mmengine - INFO - Epoch(train) [1027][50/63] lr: 1.2258e-03 eta: 3:29:40 time: 0.8396 data_time: 0.0267 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2336 loss_db: 0.0568 loss: 0.6153 2022/08/30 21:04:41 - mmengine - INFO - Epoch(train) [1027][55/63] lr: 1.2258e-03 eta: 3:29:40 time: 0.7865 data_time: 0.0240 memory: 16201 loss_prob: 0.3276 loss_thr: 0.2274 loss_db: 0.0595 loss: 0.6145 2022/08/30 21:04:45 - mmengine - INFO - Epoch(train) [1027][60/63] lr: 1.2258e-03 eta: 3:29:28 time: 0.7956 data_time: 0.0276 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2327 loss_db: 0.0588 loss: 0.6125 2022/08/30 21:04:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:04:53 - mmengine - INFO - Epoch(train) [1028][5/63] lr: 1.2195e-03 eta: 3:29:28 time: 0.8841 data_time: 0.1529 memory: 16201 loss_prob: 0.3423 loss_thr: 0.2366 loss_db: 0.0583 loss: 0.6372 2022/08/30 21:04:57 - mmengine - INFO - Epoch(train) [1028][10/63] lr: 1.2195e-03 eta: 3:29:12 time: 0.9185 data_time: 0.1555 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2407 loss_db: 0.0606 loss: 0.6460 2022/08/30 21:05:00 - mmengine - INFO - Epoch(train) [1028][15/63] lr: 1.2195e-03 eta: 3:29:12 time: 0.7723 data_time: 0.0235 memory: 16201 loss_prob: 0.3543 loss_thr: 0.2555 loss_db: 0.0647 loss: 0.6746 2022/08/30 21:05:05 - mmengine - INFO - Epoch(train) [1028][20/63] lr: 1.2195e-03 eta: 3:29:00 time: 0.8333 data_time: 0.0187 memory: 16201 loss_prob: 0.3489 loss_thr: 0.2496 loss_db: 0.0635 loss: 0.6620 2022/08/30 21:05:09 - mmengine - INFO - Epoch(train) [1028][25/63] lr: 1.2195e-03 eta: 3:29:00 time: 0.8608 data_time: 0.0333 memory: 16201 loss_prob: 0.3244 loss_thr: 0.2358 loss_db: 0.0575 loss: 0.6177 2022/08/30 21:05:13 - mmengine - INFO - Epoch(train) [1028][30/63] lr: 1.2195e-03 eta: 3:28:47 time: 0.7813 data_time: 0.0272 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2354 loss_db: 0.0583 loss: 0.6247 2022/08/30 21:05:17 - mmengine - INFO - Epoch(train) [1028][35/63] lr: 1.2195e-03 eta: 3:28:47 time: 0.7647 data_time: 0.0167 memory: 16201 loss_prob: 0.3287 loss_thr: 0.2364 loss_db: 0.0591 loss: 0.6241 2022/08/30 21:05:20 - mmengine - INFO - Epoch(train) [1028][40/63] lr: 1.2195e-03 eta: 3:28:35 time: 0.7796 data_time: 0.0246 memory: 16201 loss_prob: 0.3005 loss_thr: 0.2185 loss_db: 0.0540 loss: 0.5729 2022/08/30 21:05:25 - mmengine - INFO - Epoch(train) [1028][45/63] lr: 1.2195e-03 eta: 3:28:35 time: 0.8366 data_time: 0.0267 memory: 16201 loss_prob: 0.3047 loss_thr: 0.2188 loss_db: 0.0540 loss: 0.5774 2022/08/30 21:05:29 - mmengine - INFO - Epoch(train) [1028][50/63] lr: 1.2195e-03 eta: 3:28:23 time: 0.8450 data_time: 0.0260 memory: 16201 loss_prob: 0.3128 loss_thr: 0.2294 loss_db: 0.0553 loss: 0.5975 2022/08/30 21:05:33 - mmengine - INFO - Epoch(train) [1028][55/63] lr: 1.2195e-03 eta: 3:28:23 time: 0.7974 data_time: 0.0264 memory: 16201 loss_prob: 0.3503 loss_thr: 0.2473 loss_db: 0.0621 loss: 0.6598 2022/08/30 21:05:37 - mmengine - INFO - Epoch(train) [1028][60/63] lr: 1.2195e-03 eta: 3:28:11 time: 0.7933 data_time: 0.0257 memory: 16201 loss_prob: 0.3937 loss_thr: 0.2687 loss_db: 0.0692 loss: 0.7316 2022/08/30 21:05:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:05:44 - mmengine - INFO - Epoch(train) [1029][5/63] lr: 1.2131e-03 eta: 3:28:11 time: 0.8775 data_time: 0.1497 memory: 16201 loss_prob: 0.3159 loss_thr: 0.2402 loss_db: 0.0567 loss: 0.6127 2022/08/30 21:05:48 - mmengine - INFO - Epoch(train) [1029][10/63] lr: 1.2131e-03 eta: 3:27:55 time: 0.9288 data_time: 0.1574 memory: 16201 loss_prob: 0.3069 loss_thr: 0.2397 loss_db: 0.0555 loss: 0.6020 2022/08/30 21:05:52 - mmengine - INFO - Epoch(train) [1029][15/63] lr: 1.2131e-03 eta: 3:27:55 time: 0.8385 data_time: 0.0236 memory: 16201 loss_prob: 0.3047 loss_thr: 0.2299 loss_db: 0.0545 loss: 0.5890 2022/08/30 21:05:56 - mmengine - INFO - Epoch(train) [1029][20/63] lr: 1.2131e-03 eta: 3:27:43 time: 0.8334 data_time: 0.0234 memory: 16201 loss_prob: 0.3078 loss_thr: 0.2184 loss_db: 0.0545 loss: 0.5808 2022/08/30 21:06:00 - mmengine - INFO - Epoch(train) [1029][25/63] lr: 1.2131e-03 eta: 3:27:43 time: 0.7777 data_time: 0.0260 memory: 16201 loss_prob: 0.3486 loss_thr: 0.2447 loss_db: 0.0606 loss: 0.6539 2022/08/30 21:06:04 - mmengine - INFO - Epoch(train) [1029][30/63] lr: 1.2131e-03 eta: 3:27:31 time: 0.7708 data_time: 0.0252 memory: 16201 loss_prob: 0.3960 loss_thr: 0.2764 loss_db: 0.0690 loss: 0.7414 2022/08/30 21:06:08 - mmengine - INFO - Epoch(train) [1029][35/63] lr: 1.2131e-03 eta: 3:27:31 time: 0.7806 data_time: 0.0260 memory: 16201 loss_prob: 0.3536 loss_thr: 0.2527 loss_db: 0.0629 loss: 0.6692 2022/08/30 21:06:12 - mmengine - INFO - Epoch(train) [1029][40/63] lr: 1.2131e-03 eta: 3:27:19 time: 0.7809 data_time: 0.0238 memory: 16201 loss_prob: 0.2937 loss_thr: 0.2158 loss_db: 0.0528 loss: 0.5624 2022/08/30 21:06:16 - mmengine - INFO - Epoch(train) [1029][45/63] lr: 1.2131e-03 eta: 3:27:19 time: 0.7867 data_time: 0.0237 memory: 16201 loss_prob: 0.3104 loss_thr: 0.2218 loss_db: 0.0558 loss: 0.5880 2022/08/30 21:06:20 - mmengine - INFO - Epoch(train) [1029][50/63] lr: 1.2131e-03 eta: 3:27:07 time: 0.7913 data_time: 0.0201 memory: 16201 loss_prob: 0.3425 loss_thr: 0.2422 loss_db: 0.0613 loss: 0.6460 2022/08/30 21:06:24 - mmengine - INFO - Epoch(train) [1029][55/63] lr: 1.2131e-03 eta: 3:27:07 time: 0.8134 data_time: 0.0262 memory: 16201 loss_prob: 0.3460 loss_thr: 0.2349 loss_db: 0.0629 loss: 0.6438 2022/08/30 21:06:28 - mmengine - INFO - Epoch(train) [1029][60/63] lr: 1.2131e-03 eta: 3:26:55 time: 0.8077 data_time: 0.0298 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2398 loss_db: 0.0609 loss: 0.6373 2022/08/30 21:06:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:06:36 - mmengine - INFO - Epoch(train) [1030][5/63] lr: 1.2067e-03 eta: 3:26:55 time: 0.9347 data_time: 0.2075 memory: 16201 loss_prob: 0.3482 loss_thr: 0.2636 loss_db: 0.0618 loss: 0.6736 2022/08/30 21:06:40 - mmengine - INFO - Epoch(train) [1030][10/63] lr: 1.2067e-03 eta: 3:26:39 time: 0.9694 data_time: 0.2154 memory: 16201 loss_prob: 0.3341 loss_thr: 0.2327 loss_db: 0.0600 loss: 0.6268 2022/08/30 21:06:44 - mmengine - INFO - Epoch(train) [1030][15/63] lr: 1.2067e-03 eta: 3:26:39 time: 0.7932 data_time: 0.0241 memory: 16201 loss_prob: 0.3335 loss_thr: 0.2348 loss_db: 0.0603 loss: 0.6286 2022/08/30 21:06:48 - mmengine - INFO - Epoch(train) [1030][20/63] lr: 1.2067e-03 eta: 3:26:27 time: 0.7963 data_time: 0.0222 memory: 16201 loss_prob: 0.3454 loss_thr: 0.2473 loss_db: 0.0621 loss: 0.6548 2022/08/30 21:06:52 - mmengine - INFO - Epoch(train) [1030][25/63] lr: 1.2067e-03 eta: 3:26:27 time: 0.7943 data_time: 0.0285 memory: 16201 loss_prob: 0.3278 loss_thr: 0.2345 loss_db: 0.0582 loss: 0.6206 2022/08/30 21:06:56 - mmengine - INFO - Epoch(train) [1030][30/63] lr: 1.2067e-03 eta: 3:26:14 time: 0.7888 data_time: 0.0239 memory: 16201 loss_prob: 0.3186 loss_thr: 0.2280 loss_db: 0.0557 loss: 0.6023 2022/08/30 21:07:00 - mmengine - INFO - Epoch(train) [1030][35/63] lr: 1.2067e-03 eta: 3:26:14 time: 0.7922 data_time: 0.0234 memory: 16201 loss_prob: 0.2936 loss_thr: 0.2154 loss_db: 0.0520 loss: 0.5610 2022/08/30 21:07:04 - mmengine - INFO - Epoch(train) [1030][40/63] lr: 1.2067e-03 eta: 3:26:02 time: 0.8460 data_time: 0.0235 memory: 16201 loss_prob: 0.3008 loss_thr: 0.2200 loss_db: 0.0542 loss: 0.5750 2022/08/30 21:07:08 - mmengine - INFO - Epoch(train) [1030][45/63] lr: 1.2067e-03 eta: 3:26:02 time: 0.8361 data_time: 0.0264 memory: 16201 loss_prob: 0.3359 loss_thr: 0.2436 loss_db: 0.0588 loss: 0.6384 2022/08/30 21:07:12 - mmengine - INFO - Epoch(train) [1030][50/63] lr: 1.2067e-03 eta: 3:25:50 time: 0.7770 data_time: 0.0265 memory: 16201 loss_prob: 0.3534 loss_thr: 0.2523 loss_db: 0.0617 loss: 0.6674 2022/08/30 21:07:16 - mmengine - INFO - Epoch(train) [1030][55/63] lr: 1.2067e-03 eta: 3:25:50 time: 0.7743 data_time: 0.0216 memory: 16201 loss_prob: 0.3679 loss_thr: 0.2548 loss_db: 0.0666 loss: 0.6893 2022/08/30 21:07:20 - mmengine - INFO - Epoch(train) [1030][60/63] lr: 1.2067e-03 eta: 3:25:38 time: 0.7786 data_time: 0.0219 memory: 16201 loss_prob: 0.3778 loss_thr: 0.2596 loss_db: 0.0669 loss: 0.7043 2022/08/30 21:07:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:07:28 - mmengine - INFO - Epoch(train) [1031][5/63] lr: 1.2003e-03 eta: 3:25:38 time: 0.9764 data_time: 0.2421 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2645 loss_db: 0.0656 loss: 0.6951 2022/08/30 21:07:32 - mmengine - INFO - Epoch(train) [1031][10/63] lr: 1.2003e-03 eta: 3:25:22 time: 1.0192 data_time: 0.2545 memory: 16201 loss_prob: 0.3490 loss_thr: 0.2639 loss_db: 0.0628 loss: 0.6757 2022/08/30 21:07:36 - mmengine - INFO - Epoch(train) [1031][15/63] lr: 1.2003e-03 eta: 3:25:22 time: 0.7847 data_time: 0.0243 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2460 loss_db: 0.0615 loss: 0.6512 2022/08/30 21:07:39 - mmengine - INFO - Epoch(train) [1031][20/63] lr: 1.2003e-03 eta: 3:25:10 time: 0.7814 data_time: 0.0198 memory: 16201 loss_prob: 0.3399 loss_thr: 0.2386 loss_db: 0.0610 loss: 0.6395 2022/08/30 21:07:44 - mmengine - INFO - Epoch(train) [1031][25/63] lr: 1.2003e-03 eta: 3:25:10 time: 0.7981 data_time: 0.0333 memory: 16201 loss_prob: 0.3348 loss_thr: 0.2423 loss_db: 0.0588 loss: 0.6359 2022/08/30 21:07:48 - mmengine - INFO - Epoch(train) [1031][30/63] lr: 1.2003e-03 eta: 3:24:58 time: 0.8016 data_time: 0.0249 memory: 16201 loss_prob: 0.3162 loss_thr: 0.2285 loss_db: 0.0555 loss: 0.6002 2022/08/30 21:07:51 - mmengine - INFO - Epoch(train) [1031][35/63] lr: 1.2003e-03 eta: 3:24:58 time: 0.7775 data_time: 0.0162 memory: 16201 loss_prob: 0.3201 loss_thr: 0.2361 loss_db: 0.0577 loss: 0.6138 2022/08/30 21:07:56 - mmengine - INFO - Epoch(train) [1031][40/63] lr: 1.2003e-03 eta: 3:24:46 time: 0.8264 data_time: 0.0246 memory: 16201 loss_prob: 0.3593 loss_thr: 0.2567 loss_db: 0.0652 loss: 0.6811 2022/08/30 21:08:00 - mmengine - INFO - Epoch(train) [1031][45/63] lr: 1.2003e-03 eta: 3:24:46 time: 0.8449 data_time: 0.0255 memory: 16201 loss_prob: 0.3676 loss_thr: 0.2541 loss_db: 0.0651 loss: 0.6869 2022/08/30 21:08:04 - mmengine - INFO - Epoch(train) [1031][50/63] lr: 1.2003e-03 eta: 3:24:34 time: 0.8027 data_time: 0.0272 memory: 16201 loss_prob: 0.3536 loss_thr: 0.2335 loss_db: 0.0578 loss: 0.6449 2022/08/30 21:08:08 - mmengine - INFO - Epoch(train) [1031][55/63] lr: 1.2003e-03 eta: 3:24:34 time: 0.7916 data_time: 0.0253 memory: 16201 loss_prob: 0.3196 loss_thr: 0.2140 loss_db: 0.0523 loss: 0.5858 2022/08/30 21:08:12 - mmengine - INFO - Epoch(train) [1031][60/63] lr: 1.2003e-03 eta: 3:24:22 time: 0.7878 data_time: 0.0244 memory: 16201 loss_prob: 0.3217 loss_thr: 0.2304 loss_db: 0.0581 loss: 0.6102 2022/08/30 21:08:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:08:20 - mmengine - INFO - Epoch(train) [1032][5/63] lr: 1.1939e-03 eta: 3:24:22 time: 0.9737 data_time: 0.2107 memory: 16201 loss_prob: 0.3472 loss_thr: 0.2482 loss_db: 0.0631 loss: 0.6585 2022/08/30 21:08:24 - mmengine - INFO - Epoch(train) [1032][10/63] lr: 1.1939e-03 eta: 3:24:06 time: 0.9935 data_time: 0.2155 memory: 16201 loss_prob: 0.3411 loss_thr: 0.2604 loss_db: 0.0604 loss: 0.6619 2022/08/30 21:08:28 - mmengine - INFO - Epoch(train) [1032][15/63] lr: 1.1939e-03 eta: 3:24:06 time: 0.7905 data_time: 0.0274 memory: 16201 loss_prob: 0.3351 loss_thr: 0.2488 loss_db: 0.0602 loss: 0.6442 2022/08/30 21:08:32 - mmengine - INFO - Epoch(train) [1032][20/63] lr: 1.1939e-03 eta: 3:23:54 time: 0.7727 data_time: 0.0185 memory: 16201 loss_prob: 0.3247 loss_thr: 0.2324 loss_db: 0.0586 loss: 0.6157 2022/08/30 21:08:36 - mmengine - INFO - Epoch(train) [1032][25/63] lr: 1.1939e-03 eta: 3:23:54 time: 0.8151 data_time: 0.0359 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2294 loss_db: 0.0583 loss: 0.6116 2022/08/30 21:08:40 - mmengine - INFO - Epoch(train) [1032][30/63] lr: 1.1939e-03 eta: 3:23:42 time: 0.8012 data_time: 0.0257 memory: 16201 loss_prob: 0.3423 loss_thr: 0.2315 loss_db: 0.0595 loss: 0.6333 2022/08/30 21:08:44 - mmengine - INFO - Epoch(train) [1032][35/63] lr: 1.1939e-03 eta: 3:23:42 time: 0.7785 data_time: 0.0189 memory: 16201 loss_prob: 0.3372 loss_thr: 0.2333 loss_db: 0.0575 loss: 0.6280 2022/08/30 21:08:48 - mmengine - INFO - Epoch(train) [1032][40/63] lr: 1.1939e-03 eta: 3:23:30 time: 0.7948 data_time: 0.0253 memory: 16201 loss_prob: 0.3275 loss_thr: 0.2299 loss_db: 0.0576 loss: 0.6149 2022/08/30 21:08:52 - mmengine - INFO - Epoch(train) [1032][45/63] lr: 1.1939e-03 eta: 3:23:30 time: 0.8021 data_time: 0.0256 memory: 16201 loss_prob: 0.3164 loss_thr: 0.2276 loss_db: 0.0566 loss: 0.6006 2022/08/30 21:08:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:08:56 - mmengine - INFO - Epoch(train) [1032][50/63] lr: 1.1939e-03 eta: 3:23:18 time: 0.8077 data_time: 0.0311 memory: 16201 loss_prob: 0.3071 loss_thr: 0.2287 loss_db: 0.0553 loss: 0.5910 2022/08/30 21:09:00 - mmengine - INFO - Epoch(train) [1032][55/63] lr: 1.1939e-03 eta: 3:23:18 time: 0.7863 data_time: 0.0251 memory: 16201 loss_prob: 0.3405 loss_thr: 0.2463 loss_db: 0.0608 loss: 0.6476 2022/08/30 21:09:04 - mmengine - INFO - Epoch(train) [1032][60/63] lr: 1.1939e-03 eta: 3:23:06 time: 0.7765 data_time: 0.0213 memory: 16201 loss_prob: 0.3352 loss_thr: 0.2413 loss_db: 0.0599 loss: 0.6364 2022/08/30 21:09:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:09:11 - mmengine - INFO - Epoch(train) [1033][5/63] lr: 1.1875e-03 eta: 3:23:06 time: 0.8657 data_time: 0.1443 memory: 16201 loss_prob: 0.3552 loss_thr: 0.2527 loss_db: 0.0627 loss: 0.6706 2022/08/30 21:09:15 - mmengine - INFO - Epoch(train) [1033][10/63] lr: 1.1875e-03 eta: 3:22:50 time: 0.9132 data_time: 0.1539 memory: 16201 loss_prob: 0.3404 loss_thr: 0.2316 loss_db: 0.0602 loss: 0.6322 2022/08/30 21:09:19 - mmengine - INFO - Epoch(train) [1033][15/63] lr: 1.1875e-03 eta: 3:22:50 time: 0.7983 data_time: 0.0251 memory: 16201 loss_prob: 0.3589 loss_thr: 0.2468 loss_db: 0.0640 loss: 0.6698 2022/08/30 21:09:23 - mmengine - INFO - Epoch(train) [1033][20/63] lr: 1.1875e-03 eta: 3:22:38 time: 0.7899 data_time: 0.0246 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2502 loss_db: 0.0637 loss: 0.6707 2022/08/30 21:09:27 - mmengine - INFO - Epoch(train) [1033][25/63] lr: 1.1875e-03 eta: 3:22:38 time: 0.7876 data_time: 0.0281 memory: 16201 loss_prob: 0.3201 loss_thr: 0.2236 loss_db: 0.0575 loss: 0.6011 2022/08/30 21:09:30 - mmengine - INFO - Epoch(train) [1033][30/63] lr: 1.1875e-03 eta: 3:22:26 time: 0.7845 data_time: 0.0261 memory: 16201 loss_prob: 0.3456 loss_thr: 0.2418 loss_db: 0.0610 loss: 0.6485 2022/08/30 21:09:35 - mmengine - INFO - Epoch(train) [1033][35/63] lr: 1.1875e-03 eta: 3:22:26 time: 0.8122 data_time: 0.0249 memory: 16201 loss_prob: 0.3362 loss_thr: 0.2435 loss_db: 0.0592 loss: 0.6389 2022/08/30 21:09:39 - mmengine - INFO - Epoch(train) [1033][40/63] lr: 1.1875e-03 eta: 3:22:13 time: 0.8131 data_time: 0.0242 memory: 16201 loss_prob: 0.3070 loss_thr: 0.2270 loss_db: 0.0547 loss: 0.5887 2022/08/30 21:09:42 - mmengine - INFO - Epoch(train) [1033][45/63] lr: 1.1875e-03 eta: 3:22:13 time: 0.7777 data_time: 0.0221 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2309 loss_db: 0.0575 loss: 0.6070 2022/08/30 21:09:47 - mmengine - INFO - Epoch(train) [1033][50/63] lr: 1.1875e-03 eta: 3:22:01 time: 0.8096 data_time: 0.0306 memory: 16201 loss_prob: 0.3275 loss_thr: 0.2366 loss_db: 0.0573 loss: 0.6214 2022/08/30 21:09:51 - mmengine - INFO - Epoch(train) [1033][55/63] lr: 1.1875e-03 eta: 3:22:01 time: 0.8086 data_time: 0.0335 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2480 loss_db: 0.0591 loss: 0.6505 2022/08/30 21:09:55 - mmengine - INFO - Epoch(train) [1033][60/63] lr: 1.1875e-03 eta: 3:21:49 time: 0.7899 data_time: 0.0284 memory: 16201 loss_prob: 0.3323 loss_thr: 0.2410 loss_db: 0.0581 loss: 0.6314 2022/08/30 21:09:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:10:02 - mmengine - INFO - Epoch(train) [1034][5/63] lr: 1.1811e-03 eta: 3:21:49 time: 0.9053 data_time: 0.1812 memory: 16201 loss_prob: 0.2955 loss_thr: 0.2220 loss_db: 0.0529 loss: 0.5704 2022/08/30 21:10:06 - mmengine - INFO - Epoch(train) [1034][10/63] lr: 1.1811e-03 eta: 3:21:33 time: 0.9480 data_time: 0.1886 memory: 16201 loss_prob: 0.2873 loss_thr: 0.2078 loss_db: 0.0519 loss: 0.5471 2022/08/30 21:10:10 - mmengine - INFO - Epoch(train) [1034][15/63] lr: 1.1811e-03 eta: 3:21:33 time: 0.7771 data_time: 0.0226 memory: 16201 loss_prob: 0.3148 loss_thr: 0.2242 loss_db: 0.0572 loss: 0.5962 2022/08/30 21:10:14 - mmengine - INFO - Epoch(train) [1034][20/63] lr: 1.1811e-03 eta: 3:21:21 time: 0.8036 data_time: 0.0228 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2462 loss_db: 0.0602 loss: 0.6409 2022/08/30 21:10:18 - mmengine - INFO - Epoch(train) [1034][25/63] lr: 1.1811e-03 eta: 3:21:21 time: 0.8102 data_time: 0.0276 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2376 loss_db: 0.0574 loss: 0.6149 2022/08/30 21:10:22 - mmengine - INFO - Epoch(train) [1034][30/63] lr: 1.1811e-03 eta: 3:21:09 time: 0.7840 data_time: 0.0233 memory: 16201 loss_prob: 0.3217 loss_thr: 0.2315 loss_db: 0.0588 loss: 0.6120 2022/08/30 21:10:26 - mmengine - INFO - Epoch(train) [1034][35/63] lr: 1.1811e-03 eta: 3:21:09 time: 0.7793 data_time: 0.0287 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2444 loss_db: 0.0640 loss: 0.6681 2022/08/30 21:10:30 - mmengine - INFO - Epoch(train) [1034][40/63] lr: 1.1811e-03 eta: 3:20:57 time: 0.7797 data_time: 0.0251 memory: 16201 loss_prob: 0.3403 loss_thr: 0.2376 loss_db: 0.0591 loss: 0.6369 2022/08/30 21:10:34 - mmengine - INFO - Epoch(train) [1034][45/63] lr: 1.1811e-03 eta: 3:20:57 time: 0.7987 data_time: 0.0267 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2308 loss_db: 0.0551 loss: 0.6073 2022/08/30 21:10:38 - mmengine - INFO - Epoch(train) [1034][50/63] lr: 1.1811e-03 eta: 3:20:45 time: 0.8010 data_time: 0.0296 memory: 16201 loss_prob: 0.3397 loss_thr: 0.2357 loss_db: 0.0598 loss: 0.6352 2022/08/30 21:10:42 - mmengine - INFO - Epoch(train) [1034][55/63] lr: 1.1811e-03 eta: 3:20:45 time: 0.7824 data_time: 0.0227 memory: 16201 loss_prob: 0.3342 loss_thr: 0.2310 loss_db: 0.0606 loss: 0.6258 2022/08/30 21:10:45 - mmengine - INFO - Epoch(train) [1034][60/63] lr: 1.1811e-03 eta: 3:20:33 time: 0.7766 data_time: 0.0213 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2316 loss_db: 0.0587 loss: 0.6202 2022/08/30 21:10:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:10:53 - mmengine - INFO - Epoch(train) [1035][5/63] lr: 1.1747e-03 eta: 3:20:33 time: 0.8818 data_time: 0.1394 memory: 16201 loss_prob: 0.3194 loss_thr: 0.2402 loss_db: 0.0578 loss: 0.6173 2022/08/30 21:10:57 - mmengine - INFO - Epoch(train) [1035][10/63] lr: 1.1747e-03 eta: 3:20:17 time: 0.9350 data_time: 0.1519 memory: 16201 loss_prob: 0.3399 loss_thr: 0.2473 loss_db: 0.0610 loss: 0.6482 2022/08/30 21:11:01 - mmengine - INFO - Epoch(train) [1035][15/63] lr: 1.1747e-03 eta: 3:20:17 time: 0.7881 data_time: 0.0283 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2346 loss_db: 0.0590 loss: 0.6174 2022/08/30 21:11:05 - mmengine - INFO - Epoch(train) [1035][20/63] lr: 1.1747e-03 eta: 3:20:05 time: 0.7836 data_time: 0.0182 memory: 16201 loss_prob: 0.2877 loss_thr: 0.2141 loss_db: 0.0515 loss: 0.5533 2022/08/30 21:11:08 - mmengine - INFO - Epoch(train) [1035][25/63] lr: 1.1747e-03 eta: 3:20:05 time: 0.7869 data_time: 0.0280 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2275 loss_db: 0.0558 loss: 0.6019 2022/08/30 21:11:12 - mmengine - INFO - Epoch(train) [1035][30/63] lr: 1.1747e-03 eta: 3:19:53 time: 0.7701 data_time: 0.0264 memory: 16201 loss_prob: 0.3688 loss_thr: 0.2583 loss_db: 0.0659 loss: 0.6930 2022/08/30 21:11:16 - mmengine - INFO - Epoch(train) [1035][35/63] lr: 1.1747e-03 eta: 3:19:53 time: 0.7986 data_time: 0.0204 memory: 16201 loss_prob: 0.3442 loss_thr: 0.2476 loss_db: 0.0614 loss: 0.6532 2022/08/30 21:11:20 - mmengine - INFO - Epoch(train) [1035][40/63] lr: 1.1747e-03 eta: 3:19:41 time: 0.8069 data_time: 0.0260 memory: 16201 loss_prob: 0.3246 loss_thr: 0.2274 loss_db: 0.0584 loss: 0.6103 2022/08/30 21:11:24 - mmengine - INFO - Epoch(train) [1035][45/63] lr: 1.1747e-03 eta: 3:19:41 time: 0.7872 data_time: 0.0270 memory: 16201 loss_prob: 0.3341 loss_thr: 0.2291 loss_db: 0.0603 loss: 0.6235 2022/08/30 21:11:28 - mmengine - INFO - Epoch(train) [1035][50/63] lr: 1.1747e-03 eta: 3:19:29 time: 0.7894 data_time: 0.0263 memory: 16201 loss_prob: 0.3250 loss_thr: 0.2329 loss_db: 0.0576 loss: 0.6156 2022/08/30 21:11:32 - mmengine - INFO - Epoch(train) [1035][55/63] lr: 1.1747e-03 eta: 3:19:29 time: 0.7912 data_time: 0.0255 memory: 16201 loss_prob: 0.3322 loss_thr: 0.2307 loss_db: 0.0564 loss: 0.6194 2022/08/30 21:11:37 - mmengine - INFO - Epoch(train) [1035][60/63] lr: 1.1747e-03 eta: 3:19:17 time: 0.8338 data_time: 0.0329 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2300 loss_db: 0.0568 loss: 0.6208 2022/08/30 21:11:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:11:44 - mmengine - INFO - Epoch(train) [1036][5/63] lr: 1.1683e-03 eta: 3:19:17 time: 0.9400 data_time: 0.1928 memory: 16201 loss_prob: 0.3352 loss_thr: 0.2474 loss_db: 0.0607 loss: 0.6434 2022/08/30 21:11:48 - mmengine - INFO - Epoch(train) [1036][10/63] lr: 1.1683e-03 eta: 3:19:01 time: 0.9774 data_time: 0.2055 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2452 loss_db: 0.0617 loss: 0.6534 2022/08/30 21:11:52 - mmengine - INFO - Epoch(train) [1036][15/63] lr: 1.1683e-03 eta: 3:19:01 time: 0.7933 data_time: 0.0262 memory: 16201 loss_prob: 0.3223 loss_thr: 0.2248 loss_db: 0.0563 loss: 0.6033 2022/08/30 21:11:56 - mmengine - INFO - Epoch(train) [1036][20/63] lr: 1.1683e-03 eta: 3:18:49 time: 0.8039 data_time: 0.0192 memory: 16201 loss_prob: 0.3011 loss_thr: 0.2171 loss_db: 0.0531 loss: 0.5713 2022/08/30 21:12:00 - mmengine - INFO - Epoch(train) [1036][25/63] lr: 1.1683e-03 eta: 3:18:49 time: 0.8030 data_time: 0.0318 memory: 16201 loss_prob: 0.3063 loss_thr: 0.2238 loss_db: 0.0560 loss: 0.5860 2022/08/30 21:12:04 - mmengine - INFO - Epoch(train) [1036][30/63] lr: 1.1683e-03 eta: 3:18:37 time: 0.8015 data_time: 0.0244 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2454 loss_db: 0.0625 loss: 0.6514 2022/08/30 21:12:08 - mmengine - INFO - Epoch(train) [1036][35/63] lr: 1.1683e-03 eta: 3:18:37 time: 0.8101 data_time: 0.0212 memory: 16201 loss_prob: 0.3652 loss_thr: 0.2527 loss_db: 0.0652 loss: 0.6831 2022/08/30 21:12:12 - mmengine - INFO - Epoch(train) [1036][40/63] lr: 1.1683e-03 eta: 3:18:25 time: 0.7848 data_time: 0.0246 memory: 16201 loss_prob: 0.3468 loss_thr: 0.2357 loss_db: 0.0623 loss: 0.6448 2022/08/30 21:12:16 - mmengine - INFO - Epoch(train) [1036][45/63] lr: 1.1683e-03 eta: 3:18:25 time: 0.7847 data_time: 0.0222 memory: 16201 loss_prob: 0.3337 loss_thr: 0.2287 loss_db: 0.0600 loss: 0.6224 2022/08/30 21:12:20 - mmengine - INFO - Epoch(train) [1036][50/63] lr: 1.1683e-03 eta: 3:18:13 time: 0.7875 data_time: 0.0241 memory: 16201 loss_prob: 0.3445 loss_thr: 0.2424 loss_db: 0.0620 loss: 0.6489 2022/08/30 21:12:24 - mmengine - INFO - Epoch(train) [1036][55/63] lr: 1.1683e-03 eta: 3:18:13 time: 0.7992 data_time: 0.0223 memory: 16201 loss_prob: 0.3501 loss_thr: 0.2543 loss_db: 0.0625 loss: 0.6668 2022/08/30 21:12:28 - mmengine - INFO - Epoch(train) [1036][60/63] lr: 1.1683e-03 eta: 3:18:01 time: 0.8011 data_time: 0.0251 memory: 16201 loss_prob: 0.3449 loss_thr: 0.2502 loss_db: 0.0608 loss: 0.6559 2022/08/30 21:12:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:12:36 - mmengine - INFO - Epoch(train) [1037][5/63] lr: 1.1619e-03 eta: 3:18:01 time: 0.9250 data_time: 0.1774 memory: 16201 loss_prob: 0.3290 loss_thr: 0.2338 loss_db: 0.0589 loss: 0.6217 2022/08/30 21:12:40 - mmengine - INFO - Epoch(train) [1037][10/63] lr: 1.1619e-03 eta: 3:17:45 time: 0.9842 data_time: 0.1881 memory: 16201 loss_prob: 0.2827 loss_thr: 0.2136 loss_db: 0.0522 loss: 0.5484 2022/08/30 21:12:44 - mmengine - INFO - Epoch(train) [1037][15/63] lr: 1.1619e-03 eta: 3:17:45 time: 0.7955 data_time: 0.0268 memory: 16201 loss_prob: 0.3335 loss_thr: 0.2418 loss_db: 0.0598 loss: 0.6351 2022/08/30 21:12:48 - mmengine - INFO - Epoch(train) [1037][20/63] lr: 1.1619e-03 eta: 3:17:33 time: 0.7869 data_time: 0.0224 memory: 16201 loss_prob: 0.3723 loss_thr: 0.2634 loss_db: 0.0646 loss: 0.7003 2022/08/30 21:12:52 - mmengine - INFO - Epoch(train) [1037][25/63] lr: 1.1619e-03 eta: 3:17:33 time: 0.7911 data_time: 0.0279 memory: 16201 loss_prob: 0.3468 loss_thr: 0.2360 loss_db: 0.0616 loss: 0.6443 2022/08/30 21:12:56 - mmengine - INFO - Epoch(train) [1037][30/63] lr: 1.1619e-03 eta: 3:17:21 time: 0.7745 data_time: 0.0242 memory: 16201 loss_prob: 0.3403 loss_thr: 0.2283 loss_db: 0.0609 loss: 0.6295 2022/08/30 21:12:59 - mmengine - INFO - Epoch(train) [1037][35/63] lr: 1.1619e-03 eta: 3:17:21 time: 0.7696 data_time: 0.0192 memory: 16201 loss_prob: 0.3550 loss_thr: 0.2413 loss_db: 0.0624 loss: 0.6587 2022/08/30 21:13:04 - mmengine - INFO - Epoch(train) [1037][40/63] lr: 1.1619e-03 eta: 3:17:09 time: 0.8078 data_time: 0.0252 memory: 16201 loss_prob: 0.3640 loss_thr: 0.2484 loss_db: 0.0643 loss: 0.6767 2022/08/30 21:13:08 - mmengine - INFO - Epoch(train) [1037][45/63] lr: 1.1619e-03 eta: 3:17:09 time: 0.8189 data_time: 0.0284 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2272 loss_db: 0.0566 loss: 0.6004 2022/08/30 21:13:12 - mmengine - INFO - Epoch(train) [1037][50/63] lr: 1.1619e-03 eta: 3:16:57 time: 0.7987 data_time: 0.0251 memory: 16201 loss_prob: 0.3049 loss_thr: 0.2289 loss_db: 0.0551 loss: 0.5888 2022/08/30 21:13:16 - mmengine - INFO - Epoch(train) [1037][55/63] lr: 1.1619e-03 eta: 3:16:57 time: 0.7937 data_time: 0.0270 memory: 16201 loss_prob: 0.3097 loss_thr: 0.2300 loss_db: 0.0552 loss: 0.5949 2022/08/30 21:13:19 - mmengine - INFO - Epoch(train) [1037][60/63] lr: 1.1619e-03 eta: 3:16:45 time: 0.7915 data_time: 0.0267 memory: 16201 loss_prob: 0.3022 loss_thr: 0.2214 loss_db: 0.0542 loss: 0.5778 2022/08/30 21:13:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:13:27 - mmengine - INFO - Epoch(train) [1038][5/63] lr: 1.1555e-03 eta: 3:16:45 time: 0.9311 data_time: 0.1916 memory: 16201 loss_prob: 0.3311 loss_thr: 0.2250 loss_db: 0.0606 loss: 0.6167 2022/08/30 21:13:31 - mmengine - INFO - Epoch(train) [1038][10/63] lr: 1.1555e-03 eta: 3:16:29 time: 0.9791 data_time: 0.2041 memory: 16201 loss_prob: 0.3154 loss_thr: 0.2243 loss_db: 0.0559 loss: 0.5956 2022/08/30 21:13:35 - mmengine - INFO - Epoch(train) [1038][15/63] lr: 1.1555e-03 eta: 3:16:29 time: 0.7887 data_time: 0.0250 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2376 loss_db: 0.0545 loss: 0.6040 2022/08/30 21:13:39 - mmengine - INFO - Epoch(train) [1038][20/63] lr: 1.1555e-03 eta: 3:16:17 time: 0.7894 data_time: 0.0211 memory: 16201 loss_prob: 0.3248 loss_thr: 0.2367 loss_db: 0.0594 loss: 0.6210 2022/08/30 21:13:43 - mmengine - INFO - Epoch(train) [1038][25/63] lr: 1.1555e-03 eta: 3:16:17 time: 0.8019 data_time: 0.0262 memory: 16201 loss_prob: 0.3052 loss_thr: 0.2287 loss_db: 0.0561 loss: 0.5899 2022/08/30 21:13:47 - mmengine - INFO - Epoch(train) [1038][30/63] lr: 1.1555e-03 eta: 3:16:05 time: 0.8101 data_time: 0.0280 memory: 16201 loss_prob: 0.3012 loss_thr: 0.2360 loss_db: 0.0533 loss: 0.5905 2022/08/30 21:13:51 - mmengine - INFO - Epoch(train) [1038][35/63] lr: 1.1555e-03 eta: 3:16:05 time: 0.8004 data_time: 0.0258 memory: 16201 loss_prob: 0.3109 loss_thr: 0.2283 loss_db: 0.0560 loss: 0.5952 2022/08/30 21:13:55 - mmengine - INFO - Epoch(train) [1038][40/63] lr: 1.1555e-03 eta: 3:15:53 time: 0.7751 data_time: 0.0216 memory: 16201 loss_prob: 0.3350 loss_thr: 0.2363 loss_db: 0.0609 loss: 0.6322 2022/08/30 21:13:59 - mmengine - INFO - Epoch(train) [1038][45/63] lr: 1.1555e-03 eta: 3:15:53 time: 0.7718 data_time: 0.0252 memory: 16201 loss_prob: 0.3551 loss_thr: 0.2450 loss_db: 0.0632 loss: 0.6633 2022/08/30 21:14:03 - mmengine - INFO - Epoch(train) [1038][50/63] lr: 1.1555e-03 eta: 3:15:41 time: 0.8005 data_time: 0.0242 memory: 16201 loss_prob: 0.3739 loss_thr: 0.2550 loss_db: 0.0662 loss: 0.6951 2022/08/30 21:14:07 - mmengine - INFO - Epoch(train) [1038][55/63] lr: 1.1555e-03 eta: 3:15:41 time: 0.8032 data_time: 0.0242 memory: 16201 loss_prob: 0.3439 loss_thr: 0.2419 loss_db: 0.0604 loss: 0.6463 2022/08/30 21:14:11 - mmengine - INFO - Epoch(train) [1038][60/63] lr: 1.1555e-03 eta: 3:15:29 time: 0.7839 data_time: 0.0248 memory: 16201 loss_prob: 0.3194 loss_thr: 0.2286 loss_db: 0.0567 loss: 0.6046 2022/08/30 21:14:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:14:19 - mmengine - INFO - Epoch(train) [1039][5/63] lr: 1.1490e-03 eta: 3:15:29 time: 0.9420 data_time: 0.2043 memory: 16201 loss_prob: 0.3341 loss_thr: 0.2391 loss_db: 0.0610 loss: 0.6342 2022/08/30 21:14:23 - mmengine - INFO - Epoch(train) [1039][10/63] lr: 1.1490e-03 eta: 3:15:13 time: 0.9817 data_time: 0.2149 memory: 16201 loss_prob: 0.3403 loss_thr: 0.2377 loss_db: 0.0596 loss: 0.6376 2022/08/30 21:14:27 - mmengine - INFO - Epoch(train) [1039][15/63] lr: 1.1490e-03 eta: 3:15:13 time: 0.7871 data_time: 0.0276 memory: 16201 loss_prob: 0.3602 loss_thr: 0.2470 loss_db: 0.0631 loss: 0.6703 2022/08/30 21:14:31 - mmengine - INFO - Epoch(train) [1039][20/63] lr: 1.1490e-03 eta: 3:15:01 time: 0.7809 data_time: 0.0212 memory: 16201 loss_prob: 0.3619 loss_thr: 0.2410 loss_db: 0.0647 loss: 0.6676 2022/08/30 21:14:35 - mmengine - INFO - Epoch(train) [1039][25/63] lr: 1.1490e-03 eta: 3:15:01 time: 0.7932 data_time: 0.0256 memory: 16201 loss_prob: 0.3420 loss_thr: 0.2324 loss_db: 0.0593 loss: 0.6338 2022/08/30 21:14:38 - mmengine - INFO - Epoch(train) [1039][30/63] lr: 1.1490e-03 eta: 3:14:49 time: 0.7953 data_time: 0.0230 memory: 16201 loss_prob: 0.3209 loss_thr: 0.2291 loss_db: 0.0568 loss: 0.6067 2022/08/30 21:14:43 - mmengine - INFO - Epoch(train) [1039][35/63] lr: 1.1490e-03 eta: 3:14:49 time: 0.7948 data_time: 0.0210 memory: 16201 loss_prob: 0.3204 loss_thr: 0.2367 loss_db: 0.0584 loss: 0.6155 2022/08/30 21:14:47 - mmengine - INFO - Epoch(train) [1039][40/63] lr: 1.1490e-03 eta: 3:14:37 time: 0.8079 data_time: 0.0278 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2401 loss_db: 0.0613 loss: 0.6543 2022/08/30 21:14:50 - mmengine - INFO - Epoch(train) [1039][45/63] lr: 1.1490e-03 eta: 3:14:37 time: 0.7916 data_time: 0.0264 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2317 loss_db: 0.0606 loss: 0.6411 2022/08/30 21:14:54 - mmengine - INFO - Epoch(train) [1039][50/63] lr: 1.1490e-03 eta: 3:14:25 time: 0.7834 data_time: 0.0243 memory: 16201 loss_prob: 0.3168 loss_thr: 0.2274 loss_db: 0.0564 loss: 0.6006 2022/08/30 21:14:58 - mmengine - INFO - Epoch(train) [1039][55/63] lr: 1.1490e-03 eta: 3:14:25 time: 0.7903 data_time: 0.0261 memory: 16201 loss_prob: 0.3316 loss_thr: 0.2373 loss_db: 0.0585 loss: 0.6275 2022/08/30 21:15:02 - mmengine - INFO - Epoch(train) [1039][60/63] lr: 1.1490e-03 eta: 3:14:13 time: 0.7822 data_time: 0.0249 memory: 16201 loss_prob: 0.3058 loss_thr: 0.2251 loss_db: 0.0546 loss: 0.5855 2022/08/30 21:15:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:15:10 - mmengine - INFO - Epoch(train) [1040][5/63] lr: 1.1426e-03 eta: 3:14:13 time: 0.9298 data_time: 0.1948 memory: 16201 loss_prob: 0.3737 loss_thr: 0.2577 loss_db: 0.0669 loss: 0.6983 2022/08/30 21:15:14 - mmengine - INFO - Epoch(train) [1040][10/63] lr: 1.1426e-03 eta: 3:13:57 time: 0.9879 data_time: 0.2101 memory: 16201 loss_prob: 0.3405 loss_thr: 0.2353 loss_db: 0.0595 loss: 0.6354 2022/08/30 21:15:18 - mmengine - INFO - Epoch(train) [1040][15/63] lr: 1.1426e-03 eta: 3:13:57 time: 0.8039 data_time: 0.0270 memory: 16201 loss_prob: 0.3531 loss_thr: 0.2409 loss_db: 0.0613 loss: 0.6554 2022/08/30 21:15:22 - mmengine - INFO - Epoch(train) [1040][20/63] lr: 1.1426e-03 eta: 3:13:45 time: 0.7923 data_time: 0.0242 memory: 16201 loss_prob: 0.3424 loss_thr: 0.2476 loss_db: 0.0610 loss: 0.6509 2022/08/30 21:15:26 - mmengine - INFO - Epoch(train) [1040][25/63] lr: 1.1426e-03 eta: 3:13:45 time: 0.7992 data_time: 0.0418 memory: 16201 loss_prob: 0.3550 loss_thr: 0.2556 loss_db: 0.0624 loss: 0.6729 2022/08/30 21:15:30 - mmengine - INFO - Epoch(train) [1040][30/63] lr: 1.1426e-03 eta: 3:13:33 time: 0.7901 data_time: 0.0290 memory: 16201 loss_prob: 0.3509 loss_thr: 0.2514 loss_db: 0.0607 loss: 0.6631 2022/08/30 21:15:34 - mmengine - INFO - Epoch(train) [1040][35/63] lr: 1.1426e-03 eta: 3:13:33 time: 0.8123 data_time: 0.0231 memory: 16201 loss_prob: 0.3383 loss_thr: 0.2458 loss_db: 0.0598 loss: 0.6438 2022/08/30 21:15:38 - mmengine - INFO - Epoch(train) [1040][40/63] lr: 1.1426e-03 eta: 3:13:21 time: 0.8164 data_time: 0.0278 memory: 16201 loss_prob: 0.3366 loss_thr: 0.2463 loss_db: 0.0618 loss: 0.6447 2022/08/30 21:15:42 - mmengine - INFO - Epoch(train) [1040][45/63] lr: 1.1426e-03 eta: 3:13:21 time: 0.7931 data_time: 0.0261 memory: 16201 loss_prob: 0.3298 loss_thr: 0.2341 loss_db: 0.0613 loss: 0.6251 2022/08/30 21:15:46 - mmengine - INFO - Epoch(train) [1040][50/63] lr: 1.1426e-03 eta: 3:13:09 time: 0.8043 data_time: 0.0276 memory: 16201 loss_prob: 0.3212 loss_thr: 0.2302 loss_db: 0.0578 loss: 0.6092 2022/08/30 21:15:50 - mmengine - INFO - Epoch(train) [1040][55/63] lr: 1.1426e-03 eta: 3:13:09 time: 0.7964 data_time: 0.0227 memory: 16201 loss_prob: 0.3283 loss_thr: 0.2330 loss_db: 0.0574 loss: 0.6187 2022/08/30 21:15:54 - mmengine - INFO - Epoch(train) [1040][60/63] lr: 1.1426e-03 eta: 3:12:57 time: 0.7946 data_time: 0.0248 memory: 16201 loss_prob: 0.3484 loss_thr: 0.2359 loss_db: 0.0609 loss: 0.6452 2022/08/30 21:15:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:15:56 - mmengine - INFO - Saving checkpoint at 1040 epochs 2022/08/30 21:16:04 - mmengine - INFO - Epoch(val) [1040][5/32] eta: 3:12:57 time: 0.5972 data_time: 0.0771 memory: 16201 2022/08/30 21:16:07 - mmengine - INFO - Epoch(val) [1040][10/32] eta: 0:00:14 time: 0.6663 data_time: 0.1074 memory: 15734 2022/08/30 21:16:10 - mmengine - INFO - Epoch(val) [1040][15/32] eta: 0:00:14 time: 0.5836 data_time: 0.0474 memory: 15734 2022/08/30 21:16:13 - mmengine - INFO - Epoch(val) [1040][20/32] eta: 0:00:07 time: 0.5946 data_time: 0.0477 memory: 15734 2022/08/30 21:16:16 - mmengine - INFO - Epoch(val) [1040][25/32] eta: 0:00:07 time: 0.6187 data_time: 0.0636 memory: 15734 2022/08/30 21:16:19 - mmengine - INFO - Epoch(val) [1040][30/32] eta: 0:00:01 time: 0.5637 data_time: 0.0329 memory: 15734 2022/08/30 21:16:19 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 21:16:20 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8387, precision: 0.8319, hmean: 0.8353 2022/08/30 21:16:20 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8387, precision: 0.8539, hmean: 0.8462 2022/08/30 21:16:20 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8382, precision: 0.8727, hmean: 0.8551 2022/08/30 21:16:20 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8377, precision: 0.8878, hmean: 0.8620 2022/08/30 21:16:20 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8276, precision: 0.9019, hmean: 0.8632 2022/08/30 21:16:20 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8012, precision: 0.9239, hmean: 0.8582 2022/08/30 21:16:20 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4665, precision: 0.9566, hmean: 0.6272 2022/08/30 21:16:20 - mmengine - INFO - Epoch(val) [1040][32/32] icdar/precision: 0.9019 icdar/recall: 0.8276 icdar/hmean: 0.8632 2022/08/30 21:16:25 - mmengine - INFO - Epoch(train) [1041][5/63] lr: 1.1362e-03 eta: 0:00:01 time: 0.9252 data_time: 0.1986 memory: 16201 loss_prob: 0.3499 loss_thr: 0.2477 loss_db: 0.0637 loss: 0.6612 2022/08/30 21:16:29 - mmengine - INFO - Epoch(train) [1041][10/63] lr: 1.1362e-03 eta: 3:12:41 time: 0.9720 data_time: 0.1990 memory: 16201 loss_prob: 0.3629 loss_thr: 0.2553 loss_db: 0.0656 loss: 0.6838 2022/08/30 21:16:34 - mmengine - INFO - Epoch(train) [1041][15/63] lr: 1.1362e-03 eta: 3:12:41 time: 0.8713 data_time: 0.0203 memory: 16201 loss_prob: 0.3480 loss_thr: 0.2556 loss_db: 0.0619 loss: 0.6655 2022/08/30 21:16:38 - mmengine - INFO - Epoch(train) [1041][20/63] lr: 1.1362e-03 eta: 3:12:29 time: 0.8767 data_time: 0.0310 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2553 loss_db: 0.0621 loss: 0.6678 2022/08/30 21:16:42 - mmengine - INFO - Epoch(train) [1041][25/63] lr: 1.1362e-03 eta: 3:12:29 time: 0.7889 data_time: 0.0257 memory: 16201 loss_prob: 0.3344 loss_thr: 0.2468 loss_db: 0.0605 loss: 0.6416 2022/08/30 21:16:46 - mmengine - INFO - Epoch(train) [1041][30/63] lr: 1.1362e-03 eta: 3:12:17 time: 0.7896 data_time: 0.0178 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2447 loss_db: 0.0609 loss: 0.6382 2022/08/30 21:16:50 - mmengine - INFO - Epoch(train) [1041][35/63] lr: 1.1362e-03 eta: 3:12:17 time: 0.7893 data_time: 0.0309 memory: 16201 loss_prob: 0.3592 loss_thr: 0.2522 loss_db: 0.0631 loss: 0.6745 2022/08/30 21:16:54 - mmengine - INFO - Epoch(train) [1041][40/63] lr: 1.1362e-03 eta: 3:12:05 time: 0.8090 data_time: 0.0242 memory: 16201 loss_prob: 0.3476 loss_thr: 0.2361 loss_db: 0.0608 loss: 0.6445 2022/08/30 21:16:58 - mmengine - INFO - Epoch(train) [1041][45/63] lr: 1.1362e-03 eta: 3:12:05 time: 0.8087 data_time: 0.0223 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2251 loss_db: 0.0592 loss: 0.6068 2022/08/30 21:17:02 - mmengine - INFO - Epoch(train) [1041][50/63] lr: 1.1362e-03 eta: 3:11:53 time: 0.7741 data_time: 0.0307 memory: 16201 loss_prob: 0.3325 loss_thr: 0.2336 loss_db: 0.0590 loss: 0.6250 2022/08/30 21:17:06 - mmengine - INFO - Epoch(train) [1041][55/63] lr: 1.1362e-03 eta: 3:11:53 time: 0.7684 data_time: 0.0210 memory: 16201 loss_prob: 0.3295 loss_thr: 0.2318 loss_db: 0.0575 loss: 0.6189 2022/08/30 21:17:10 - mmengine - INFO - Epoch(train) [1041][60/63] lr: 1.1362e-03 eta: 3:11:41 time: 0.7766 data_time: 0.0187 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2206 loss_db: 0.0554 loss: 0.5893 2022/08/30 21:17:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:17:17 - mmengine - INFO - Epoch(train) [1042][5/63] lr: 1.1298e-03 eta: 3:11:41 time: 0.9223 data_time: 0.1904 memory: 16201 loss_prob: 0.2809 loss_thr: 0.2022 loss_db: 0.0506 loss: 0.5336 2022/08/30 21:17:21 - mmengine - INFO - Epoch(train) [1042][10/63] lr: 1.1298e-03 eta: 3:11:26 time: 0.9662 data_time: 0.1910 memory: 16201 loss_prob: 0.2939 loss_thr: 0.2194 loss_db: 0.0525 loss: 0.5657 2022/08/30 21:17:25 - mmengine - INFO - Epoch(train) [1042][15/63] lr: 1.1298e-03 eta: 3:11:26 time: 0.7949 data_time: 0.0286 memory: 16201 loss_prob: 0.3325 loss_thr: 0.2409 loss_db: 0.0588 loss: 0.6321 2022/08/30 21:17:29 - mmengine - INFO - Epoch(train) [1042][20/63] lr: 1.1298e-03 eta: 3:11:13 time: 0.7915 data_time: 0.0291 memory: 16201 loss_prob: 0.3515 loss_thr: 0.2450 loss_db: 0.0622 loss: 0.6587 2022/08/30 21:17:33 - mmengine - INFO - Epoch(train) [1042][25/63] lr: 1.1298e-03 eta: 3:11:13 time: 0.7935 data_time: 0.0228 memory: 16201 loss_prob: 0.3671 loss_thr: 0.2467 loss_db: 0.0640 loss: 0.6778 2022/08/30 21:17:37 - mmengine - INFO - Epoch(train) [1042][30/63] lr: 1.1298e-03 eta: 3:11:02 time: 0.8195 data_time: 0.0262 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2423 loss_db: 0.0603 loss: 0.6492 2022/08/30 21:17:41 - mmengine - INFO - Epoch(train) [1042][35/63] lr: 1.1298e-03 eta: 3:11:02 time: 0.8058 data_time: 0.0263 memory: 16201 loss_prob: 0.3268 loss_thr: 0.2386 loss_db: 0.0577 loss: 0.6231 2022/08/30 21:17:45 - mmengine - INFO - Epoch(train) [1042][40/63] lr: 1.1298e-03 eta: 3:10:49 time: 0.7770 data_time: 0.0208 memory: 16201 loss_prob: 0.3331 loss_thr: 0.2340 loss_db: 0.0606 loss: 0.6277 2022/08/30 21:17:49 - mmengine - INFO - Epoch(train) [1042][45/63] lr: 1.1298e-03 eta: 3:10:49 time: 0.7895 data_time: 0.0286 memory: 16201 loss_prob: 0.3312 loss_thr: 0.2350 loss_db: 0.0600 loss: 0.6262 2022/08/30 21:17:53 - mmengine - INFO - Epoch(train) [1042][50/63] lr: 1.1298e-03 eta: 3:10:37 time: 0.7936 data_time: 0.0259 memory: 16201 loss_prob: 0.3328 loss_thr: 0.2399 loss_db: 0.0590 loss: 0.6317 2022/08/30 21:17:57 - mmengine - INFO - Epoch(train) [1042][55/63] lr: 1.1298e-03 eta: 3:10:37 time: 0.8058 data_time: 0.0245 memory: 16201 loss_prob: 0.3163 loss_thr: 0.2353 loss_db: 0.0561 loss: 0.6077 2022/08/30 21:18:01 - mmengine - INFO - Epoch(train) [1042][60/63] lr: 1.1298e-03 eta: 3:10:25 time: 0.8107 data_time: 0.0324 memory: 16201 loss_prob: 0.3261 loss_thr: 0.2458 loss_db: 0.0582 loss: 0.6302 2022/08/30 21:18:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:18:09 - mmengine - INFO - Epoch(train) [1043][5/63] lr: 1.1233e-03 eta: 3:10:25 time: 0.9244 data_time: 0.2009 memory: 16201 loss_prob: 0.3755 loss_thr: 0.2641 loss_db: 0.0671 loss: 0.7067 2022/08/30 21:18:13 - mmengine - INFO - Epoch(train) [1043][10/63] lr: 1.1233e-03 eta: 3:10:10 time: 0.9813 data_time: 0.2100 memory: 16201 loss_prob: 0.3273 loss_thr: 0.2389 loss_db: 0.0589 loss: 0.6251 2022/08/30 21:18:17 - mmengine - INFO - Epoch(train) [1043][15/63] lr: 1.1233e-03 eta: 3:10:10 time: 0.7917 data_time: 0.0235 memory: 16201 loss_prob: 0.3325 loss_thr: 0.2321 loss_db: 0.0603 loss: 0.6249 2022/08/30 21:18:21 - mmengine - INFO - Epoch(train) [1043][20/63] lr: 1.1233e-03 eta: 3:09:58 time: 0.7914 data_time: 0.0218 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2384 loss_db: 0.0608 loss: 0.6389 2022/08/30 21:18:25 - mmengine - INFO - Epoch(train) [1043][25/63] lr: 1.1233e-03 eta: 3:09:58 time: 0.7893 data_time: 0.0277 memory: 16201 loss_prob: 0.3131 loss_thr: 0.2248 loss_db: 0.0560 loss: 0.5939 2022/08/30 21:18:29 - mmengine - INFO - Epoch(train) [1043][30/63] lr: 1.1233e-03 eta: 3:09:46 time: 0.7793 data_time: 0.0253 memory: 16201 loss_prob: 0.3338 loss_thr: 0.2414 loss_db: 0.0607 loss: 0.6360 2022/08/30 21:18:33 - mmengine - INFO - Epoch(train) [1043][35/63] lr: 1.1233e-03 eta: 3:09:46 time: 0.7878 data_time: 0.0258 memory: 16201 loss_prob: 0.3117 loss_thr: 0.2301 loss_db: 0.0560 loss: 0.5978 2022/08/30 21:18:37 - mmengine - INFO - Epoch(train) [1043][40/63] lr: 1.1233e-03 eta: 3:09:34 time: 0.8112 data_time: 0.0347 memory: 16201 loss_prob: 0.3071 loss_thr: 0.2222 loss_db: 0.0544 loss: 0.5837 2022/08/30 21:18:41 - mmengine - INFO - Epoch(train) [1043][45/63] lr: 1.1233e-03 eta: 3:09:34 time: 0.8082 data_time: 0.0359 memory: 16201 loss_prob: 0.3204 loss_thr: 0.2275 loss_db: 0.0562 loss: 0.6041 2022/08/30 21:18:45 - mmengine - INFO - Epoch(train) [1043][50/63] lr: 1.1233e-03 eta: 3:09:22 time: 0.7885 data_time: 0.0288 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2332 loss_db: 0.0557 loss: 0.6055 2022/08/30 21:18:48 - mmengine - INFO - Epoch(train) [1043][55/63] lr: 1.1233e-03 eta: 3:09:22 time: 0.7794 data_time: 0.0254 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2391 loss_db: 0.0590 loss: 0.6230 2022/08/30 21:18:52 - mmengine - INFO - Epoch(train) [1043][60/63] lr: 1.1233e-03 eta: 3:09:10 time: 0.7761 data_time: 0.0200 memory: 16201 loss_prob: 0.3173 loss_thr: 0.2296 loss_db: 0.0576 loss: 0.6045 2022/08/30 21:18:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:19:01 - mmengine - INFO - Epoch(train) [1044][5/63] lr: 1.1169e-03 eta: 3:09:10 time: 0.9681 data_time: 0.1951 memory: 16201 loss_prob: 0.3152 loss_thr: 0.2328 loss_db: 0.0569 loss: 0.6049 2022/08/30 21:19:04 - mmengine - INFO - Epoch(train) [1044][10/63] lr: 1.1169e-03 eta: 3:08:54 time: 0.9749 data_time: 0.2025 memory: 16201 loss_prob: 0.3084 loss_thr: 0.2309 loss_db: 0.0551 loss: 0.5945 2022/08/30 21:19:08 - mmengine - INFO - Epoch(train) [1044][15/63] lr: 1.1169e-03 eta: 3:08:54 time: 0.7690 data_time: 0.0236 memory: 16201 loss_prob: 0.3442 loss_thr: 0.2443 loss_db: 0.0614 loss: 0.6499 2022/08/30 21:19:12 - mmengine - INFO - Epoch(train) [1044][20/63] lr: 1.1169e-03 eta: 3:08:42 time: 0.7743 data_time: 0.0205 memory: 16201 loss_prob: 0.3583 loss_thr: 0.2438 loss_db: 0.0631 loss: 0.6652 2022/08/30 21:19:16 - mmengine - INFO - Epoch(train) [1044][25/63] lr: 1.1169e-03 eta: 3:08:42 time: 0.7900 data_time: 0.0264 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2309 loss_db: 0.0618 loss: 0.6415 2022/08/30 21:19:20 - mmengine - INFO - Epoch(train) [1044][30/63] lr: 1.1169e-03 eta: 3:08:30 time: 0.7863 data_time: 0.0305 memory: 16201 loss_prob: 0.3293 loss_thr: 0.2269 loss_db: 0.0588 loss: 0.6151 2022/08/30 21:19:24 - mmengine - INFO - Epoch(train) [1044][35/63] lr: 1.1169e-03 eta: 3:08:30 time: 0.7886 data_time: 0.0229 memory: 16201 loss_prob: 0.3061 loss_thr: 0.2219 loss_db: 0.0539 loss: 0.5819 2022/08/30 21:19:28 - mmengine - INFO - Epoch(train) [1044][40/63] lr: 1.1169e-03 eta: 3:08:18 time: 0.7933 data_time: 0.0230 memory: 16201 loss_prob: 0.2975 loss_thr: 0.2237 loss_db: 0.0528 loss: 0.5739 2022/08/30 21:19:32 - mmengine - INFO - Epoch(train) [1044][45/63] lr: 1.1169e-03 eta: 3:08:18 time: 0.7897 data_time: 0.0253 memory: 16201 loss_prob: 0.3121 loss_thr: 0.2266 loss_db: 0.0564 loss: 0.5952 2022/08/30 21:19:36 - mmengine - INFO - Epoch(train) [1044][50/63] lr: 1.1169e-03 eta: 3:08:06 time: 0.8501 data_time: 0.0253 memory: 16201 loss_prob: 0.3000 loss_thr: 0.2108 loss_db: 0.0542 loss: 0.5650 2022/08/30 21:19:40 - mmengine - INFO - Epoch(train) [1044][55/63] lr: 1.1169e-03 eta: 3:08:06 time: 0.8448 data_time: 0.0301 memory: 16201 loss_prob: 0.3196 loss_thr: 0.2202 loss_db: 0.0554 loss: 0.5952 2022/08/30 21:19:44 - mmengine - INFO - Epoch(train) [1044][60/63] lr: 1.1169e-03 eta: 3:07:54 time: 0.7873 data_time: 0.0266 memory: 16201 loss_prob: 0.3489 loss_thr: 0.2392 loss_db: 0.0608 loss: 0.6490 2022/08/30 21:19:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:19:52 - mmengine - INFO - Epoch(train) [1045][5/63] lr: 1.1104e-03 eta: 3:07:54 time: 0.9410 data_time: 0.1785 memory: 16201 loss_prob: 0.3305 loss_thr: 0.2377 loss_db: 0.0591 loss: 0.6273 2022/08/30 21:19:56 - mmengine - INFO - Epoch(train) [1045][10/63] lr: 1.1104e-03 eta: 3:07:38 time: 0.9670 data_time: 0.1853 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2235 loss_db: 0.0562 loss: 0.5918 2022/08/30 21:20:03 - mmengine - INFO - Epoch(train) [1045][15/63] lr: 1.1104e-03 eta: 3:07:38 time: 1.0496 data_time: 0.0549 memory: 16201 loss_prob: 0.3394 loss_thr: 0.2474 loss_db: 0.0603 loss: 0.6472 2022/08/30 21:20:07 - mmengine - INFO - Epoch(train) [1045][20/63] lr: 1.1104e-03 eta: 3:07:27 time: 1.0480 data_time: 0.0580 memory: 16201 loss_prob: 0.3349 loss_thr: 0.2539 loss_db: 0.0602 loss: 0.6490 2022/08/30 21:20:14 - mmengine - INFO - Epoch(train) [1045][25/63] lr: 1.1104e-03 eta: 3:07:27 time: 1.1326 data_time: 0.0408 memory: 16201 loss_prob: 0.3203 loss_thr: 0.2330 loss_db: 0.0578 loss: 0.6110 2022/08/30 21:20:18 - mmengine - INFO - Epoch(train) [1045][30/63] lr: 1.1104e-03 eta: 3:07:15 time: 1.1499 data_time: 0.0429 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2242 loss_db: 0.0559 loss: 0.5985 2022/08/30 21:20:22 - mmengine - INFO - Epoch(train) [1045][35/63] lr: 1.1104e-03 eta: 3:07:15 time: 0.8142 data_time: 0.0326 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2300 loss_db: 0.0586 loss: 0.6239 2022/08/30 21:20:26 - mmengine - INFO - Epoch(train) [1045][40/63] lr: 1.1104e-03 eta: 3:07:03 time: 0.7837 data_time: 0.0223 memory: 16201 loss_prob: 0.3415 loss_thr: 0.2317 loss_db: 0.0605 loss: 0.6337 2022/08/30 21:20:30 - mmengine - INFO - Epoch(train) [1045][45/63] lr: 1.1104e-03 eta: 3:07:03 time: 0.7882 data_time: 0.0270 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2236 loss_db: 0.0566 loss: 0.5987 2022/08/30 21:20:34 - mmengine - INFO - Epoch(train) [1045][50/63] lr: 1.1104e-03 eta: 3:06:51 time: 0.7952 data_time: 0.0280 memory: 16201 loss_prob: 0.3147 loss_thr: 0.2088 loss_db: 0.0566 loss: 0.5801 2022/08/30 21:20:38 - mmengine - INFO - Epoch(train) [1045][55/63] lr: 1.1104e-03 eta: 3:06:51 time: 0.7822 data_time: 0.0219 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2276 loss_db: 0.0597 loss: 0.6239 2022/08/30 21:20:42 - mmengine - INFO - Epoch(train) [1045][60/63] lr: 1.1104e-03 eta: 3:06:39 time: 0.7841 data_time: 0.0270 memory: 16201 loss_prob: 0.3527 loss_thr: 0.2446 loss_db: 0.0611 loss: 0.6584 2022/08/30 21:20:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:20:49 - mmengine - INFO - Epoch(train) [1046][5/63] lr: 1.1040e-03 eta: 3:06:39 time: 0.9241 data_time: 0.1962 memory: 16201 loss_prob: 0.3725 loss_thr: 0.2457 loss_db: 0.0637 loss: 0.6819 2022/08/30 21:20:54 - mmengine - INFO - Epoch(train) [1046][10/63] lr: 1.1040e-03 eta: 3:06:24 time: 0.9755 data_time: 0.2074 memory: 16201 loss_prob: 0.3450 loss_thr: 0.2393 loss_db: 0.0614 loss: 0.6456 2022/08/30 21:20:58 - mmengine - INFO - Epoch(train) [1046][15/63] lr: 1.1040e-03 eta: 3:06:24 time: 0.8030 data_time: 0.0258 memory: 16201 loss_prob: 0.2942 loss_thr: 0.2131 loss_db: 0.0540 loss: 0.5614 2022/08/30 21:21:02 - mmengine - INFO - Epoch(train) [1046][20/63] lr: 1.1040e-03 eta: 3:06:12 time: 0.7957 data_time: 0.0180 memory: 16201 loss_prob: 0.3003 loss_thr: 0.2157 loss_db: 0.0544 loss: 0.5705 2022/08/30 21:21:06 - mmengine - INFO - Epoch(train) [1046][25/63] lr: 1.1040e-03 eta: 3:06:12 time: 0.8128 data_time: 0.0313 memory: 16201 loss_prob: 0.2777 loss_thr: 0.2079 loss_db: 0.0495 loss: 0.5351 2022/08/30 21:21:10 - mmengine - INFO - Epoch(train) [1046][30/63] lr: 1.1040e-03 eta: 3:06:00 time: 0.8156 data_time: 0.0277 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2341 loss_db: 0.0561 loss: 0.6067 2022/08/30 21:21:14 - mmengine - INFO - Epoch(train) [1046][35/63] lr: 1.1040e-03 eta: 3:06:00 time: 0.8283 data_time: 0.0233 memory: 16201 loss_prob: 0.4319 loss_thr: 0.2726 loss_db: 0.0701 loss: 0.7746 2022/08/30 21:21:18 - mmengine - INFO - Epoch(train) [1046][40/63] lr: 1.1040e-03 eta: 3:05:48 time: 0.8109 data_time: 0.0256 memory: 16201 loss_prob: 0.4420 loss_thr: 0.2628 loss_db: 0.0684 loss: 0.7732 2022/08/30 21:21:22 - mmengine - INFO - Epoch(train) [1046][45/63] lr: 1.1040e-03 eta: 3:05:48 time: 0.7742 data_time: 0.0217 memory: 16201 loss_prob: 0.3600 loss_thr: 0.2418 loss_db: 0.0614 loss: 0.6632 2022/08/30 21:21:26 - mmengine - INFO - Epoch(train) [1046][50/63] lr: 1.1040e-03 eta: 3:05:36 time: 0.7956 data_time: 0.0275 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2296 loss_db: 0.0579 loss: 0.6088 2022/08/30 21:21:30 - mmengine - INFO - Epoch(train) [1046][55/63] lr: 1.1040e-03 eta: 3:05:36 time: 0.8322 data_time: 0.0638 memory: 16201 loss_prob: 0.3290 loss_thr: 0.2352 loss_db: 0.0576 loss: 0.6218 2022/08/30 21:21:34 - mmengine - INFO - Epoch(train) [1046][60/63] lr: 1.1040e-03 eta: 3:05:24 time: 0.8355 data_time: 0.0601 memory: 16201 loss_prob: 0.3521 loss_thr: 0.2518 loss_db: 0.0618 loss: 0.6657 2022/08/30 21:21:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:21:41 - mmengine - INFO - Epoch(train) [1047][5/63] lr: 1.0975e-03 eta: 3:05:24 time: 0.8927 data_time: 0.1510 memory: 16201 loss_prob: 0.3207 loss_thr: 0.2249 loss_db: 0.0582 loss: 0.6037 2022/08/30 21:21:46 - mmengine - INFO - Epoch(train) [1047][10/63] lr: 1.0975e-03 eta: 3:05:08 time: 0.9486 data_time: 0.1719 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2364 loss_db: 0.0597 loss: 0.6212 2022/08/30 21:21:49 - mmengine - INFO - Epoch(train) [1047][15/63] lr: 1.0975e-03 eta: 3:05:08 time: 0.7979 data_time: 0.0321 memory: 16201 loss_prob: 0.3307 loss_thr: 0.2414 loss_db: 0.0597 loss: 0.6318 2022/08/30 21:21:53 - mmengine - INFO - Epoch(train) [1047][20/63] lr: 1.0975e-03 eta: 3:04:56 time: 0.7737 data_time: 0.0171 memory: 16201 loss_prob: 0.3351 loss_thr: 0.2333 loss_db: 0.0596 loss: 0.6280 2022/08/30 21:21:57 - mmengine - INFO - Epoch(train) [1047][25/63] lr: 1.0975e-03 eta: 3:04:56 time: 0.7942 data_time: 0.0328 memory: 16201 loss_prob: 0.3238 loss_thr: 0.2197 loss_db: 0.0578 loss: 0.6013 2022/08/30 21:22:01 - mmengine - INFO - Epoch(train) [1047][30/63] lr: 1.0975e-03 eta: 3:04:44 time: 0.7836 data_time: 0.0234 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2371 loss_db: 0.0600 loss: 0.6368 2022/08/30 21:22:05 - mmengine - INFO - Epoch(train) [1047][35/63] lr: 1.0975e-03 eta: 3:04:44 time: 0.7970 data_time: 0.0190 memory: 16201 loss_prob: 0.3746 loss_thr: 0.2642 loss_db: 0.0653 loss: 0.7041 2022/08/30 21:22:09 - mmengine - INFO - Epoch(train) [1047][40/63] lr: 1.0975e-03 eta: 3:04:32 time: 0.8101 data_time: 0.0272 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2521 loss_db: 0.0625 loss: 0.6683 2022/08/30 21:22:13 - mmengine - INFO - Epoch(train) [1047][45/63] lr: 1.0975e-03 eta: 3:04:32 time: 0.7797 data_time: 0.0235 memory: 16201 loss_prob: 0.3446 loss_thr: 0.2549 loss_db: 0.0612 loss: 0.6606 2022/08/30 21:22:17 - mmengine - INFO - Epoch(train) [1047][50/63] lr: 1.0975e-03 eta: 3:04:20 time: 0.7967 data_time: 0.0282 memory: 16201 loss_prob: 0.3473 loss_thr: 0.2503 loss_db: 0.0613 loss: 0.6590 2022/08/30 21:22:21 - mmengine - INFO - Epoch(train) [1047][55/63] lr: 1.0975e-03 eta: 3:04:20 time: 0.8089 data_time: 0.0259 memory: 16201 loss_prob: 0.3329 loss_thr: 0.2346 loss_db: 0.0595 loss: 0.6271 2022/08/30 21:22:25 - mmengine - INFO - Epoch(train) [1047][60/63] lr: 1.0975e-03 eta: 3:04:08 time: 0.7943 data_time: 0.0211 memory: 16201 loss_prob: 0.3521 loss_thr: 0.2450 loss_db: 0.0626 loss: 0.6596 2022/08/30 21:22:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:22:33 - mmengine - INFO - Epoch(train) [1048][5/63] lr: 1.0911e-03 eta: 3:04:08 time: 0.9368 data_time: 0.1923 memory: 16201 loss_prob: 0.2964 loss_thr: 0.2176 loss_db: 0.0526 loss: 0.5665 2022/08/30 21:22:37 - mmengine - INFO - Epoch(train) [1048][10/63] lr: 1.0911e-03 eta: 3:03:53 time: 0.9670 data_time: 0.1997 memory: 16201 loss_prob: 0.3102 loss_thr: 0.2214 loss_db: 0.0547 loss: 0.5864 2022/08/30 21:22:41 - mmengine - INFO - Epoch(train) [1048][15/63] lr: 1.0911e-03 eta: 3:03:53 time: 0.7951 data_time: 0.0280 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2382 loss_db: 0.0605 loss: 0.6354 2022/08/30 21:22:46 - mmengine - INFO - Epoch(train) [1048][20/63] lr: 1.0911e-03 eta: 3:03:41 time: 0.8726 data_time: 0.0259 memory: 16201 loss_prob: 0.3195 loss_thr: 0.2294 loss_db: 0.0581 loss: 0.6070 2022/08/30 21:22:50 - mmengine - INFO - Epoch(train) [1048][25/63] lr: 1.0911e-03 eta: 3:03:41 time: 0.8788 data_time: 0.0373 memory: 16201 loss_prob: 0.2891 loss_thr: 0.2154 loss_db: 0.0519 loss: 0.5564 2022/08/30 21:22:53 - mmengine - INFO - Epoch(train) [1048][30/63] lr: 1.0911e-03 eta: 3:03:29 time: 0.7767 data_time: 0.0265 memory: 16201 loss_prob: 0.2836 loss_thr: 0.2188 loss_db: 0.0502 loss: 0.5526 2022/08/30 21:22:57 - mmengine - INFO - Epoch(train) [1048][35/63] lr: 1.0911e-03 eta: 3:03:29 time: 0.7750 data_time: 0.0196 memory: 16201 loss_prob: 0.3242 loss_thr: 0.2395 loss_db: 0.0572 loss: 0.6210 2022/08/30 21:23:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:23:02 - mmengine - INFO - Epoch(train) [1048][40/63] lr: 1.0911e-03 eta: 3:03:17 time: 0.8320 data_time: 0.0239 memory: 16201 loss_prob: 0.3419 loss_thr: 0.2388 loss_db: 0.0616 loss: 0.6423 2022/08/30 21:23:06 - mmengine - INFO - Epoch(train) [1048][45/63] lr: 1.0911e-03 eta: 3:03:17 time: 0.8481 data_time: 0.0282 memory: 16201 loss_prob: 0.3215 loss_thr: 0.2274 loss_db: 0.0576 loss: 0.6064 2022/08/30 21:23:10 - mmengine - INFO - Epoch(train) [1048][50/63] lr: 1.0911e-03 eta: 3:03:05 time: 0.7914 data_time: 0.0253 memory: 16201 loss_prob: 0.3401 loss_thr: 0.2352 loss_db: 0.0594 loss: 0.6348 2022/08/30 21:23:14 - mmengine - INFO - Epoch(train) [1048][55/63] lr: 1.0911e-03 eta: 3:03:05 time: 0.8344 data_time: 0.0259 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2503 loss_db: 0.0634 loss: 0.6724 2022/08/30 21:23:18 - mmengine - INFO - Epoch(train) [1048][60/63] lr: 1.0911e-03 eta: 3:02:53 time: 0.8485 data_time: 0.0312 memory: 16201 loss_prob: 0.3583 loss_thr: 0.2547 loss_db: 0.0637 loss: 0.6766 2022/08/30 21:23:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:23:26 - mmengine - INFO - Epoch(train) [1049][5/63] lr: 1.0846e-03 eta: 3:02:53 time: 0.8895 data_time: 0.1588 memory: 16201 loss_prob: 0.3421 loss_thr: 0.2378 loss_db: 0.0607 loss: 0.6406 2022/08/30 21:23:29 - mmengine - INFO - Epoch(train) [1049][10/63] lr: 1.0846e-03 eta: 3:02:37 time: 0.9300 data_time: 0.1682 memory: 16201 loss_prob: 0.3643 loss_thr: 0.2511 loss_db: 0.0641 loss: 0.6795 2022/08/30 21:23:34 - mmengine - INFO - Epoch(train) [1049][15/63] lr: 1.0846e-03 eta: 3:02:37 time: 0.8427 data_time: 0.0287 memory: 16201 loss_prob: 0.3431 loss_thr: 0.2381 loss_db: 0.0613 loss: 0.6425 2022/08/30 21:23:38 - mmengine - INFO - Epoch(train) [1049][20/63] lr: 1.0846e-03 eta: 3:02:25 time: 0.8454 data_time: 0.0229 memory: 16201 loss_prob: 0.3352 loss_thr: 0.2333 loss_db: 0.0603 loss: 0.6288 2022/08/30 21:23:42 - mmengine - INFO - Epoch(train) [1049][25/63] lr: 1.0846e-03 eta: 3:02:25 time: 0.7923 data_time: 0.0305 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2420 loss_db: 0.0629 loss: 0.6547 2022/08/30 21:23:46 - mmengine - INFO - Epoch(train) [1049][30/63] lr: 1.0846e-03 eta: 3:02:13 time: 0.7994 data_time: 0.0335 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2375 loss_db: 0.0622 loss: 0.6431 2022/08/30 21:23:50 - mmengine - INFO - Epoch(train) [1049][35/63] lr: 1.0846e-03 eta: 3:02:13 time: 0.7940 data_time: 0.0213 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2379 loss_db: 0.0600 loss: 0.6270 2022/08/30 21:23:54 - mmengine - INFO - Epoch(train) [1049][40/63] lr: 1.0846e-03 eta: 3:02:01 time: 0.8057 data_time: 0.0260 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2270 loss_db: 0.0566 loss: 0.5923 2022/08/30 21:23:58 - mmengine - INFO - Epoch(train) [1049][45/63] lr: 1.0846e-03 eta: 3:02:01 time: 0.8042 data_time: 0.0314 memory: 16201 loss_prob: 0.3332 loss_thr: 0.2321 loss_db: 0.0578 loss: 0.6231 2022/08/30 21:24:02 - mmengine - INFO - Epoch(train) [1049][50/63] lr: 1.0846e-03 eta: 3:01:50 time: 0.8030 data_time: 0.0283 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2491 loss_db: 0.0582 loss: 0.6538 2022/08/30 21:24:06 - mmengine - INFO - Epoch(train) [1049][55/63] lr: 1.0846e-03 eta: 3:01:50 time: 0.7959 data_time: 0.0272 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2436 loss_db: 0.0579 loss: 0.6317 2022/08/30 21:24:10 - mmengine - INFO - Epoch(train) [1049][60/63] lr: 1.0846e-03 eta: 3:01:38 time: 0.7844 data_time: 0.0214 memory: 16201 loss_prob: 0.3330 loss_thr: 0.2356 loss_db: 0.0603 loss: 0.6289 2022/08/30 21:24:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:24:18 - mmengine - INFO - Epoch(train) [1050][5/63] lr: 1.0781e-03 eta: 3:01:38 time: 0.9638 data_time: 0.2109 memory: 16201 loss_prob: 0.3294 loss_thr: 0.2389 loss_db: 0.0585 loss: 0.6268 2022/08/30 21:24:22 - mmengine - INFO - Epoch(train) [1050][10/63] lr: 1.0781e-03 eta: 3:01:22 time: 0.9743 data_time: 0.2132 memory: 16201 loss_prob: 0.3357 loss_thr: 0.2323 loss_db: 0.0591 loss: 0.6270 2022/08/30 21:24:26 - mmengine - INFO - Epoch(train) [1050][15/63] lr: 1.0781e-03 eta: 3:01:22 time: 0.7823 data_time: 0.0240 memory: 16201 loss_prob: 0.3238 loss_thr: 0.2225 loss_db: 0.0574 loss: 0.6037 2022/08/30 21:24:30 - mmengine - INFO - Epoch(train) [1050][20/63] lr: 1.0781e-03 eta: 3:01:10 time: 0.7883 data_time: 0.0272 memory: 16201 loss_prob: 0.3560 loss_thr: 0.2494 loss_db: 0.0628 loss: 0.6681 2022/08/30 21:24:34 - mmengine - INFO - Epoch(train) [1050][25/63] lr: 1.0781e-03 eta: 3:01:10 time: 0.7846 data_time: 0.0294 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2540 loss_db: 0.0649 loss: 0.6841 2022/08/30 21:24:38 - mmengine - INFO - Epoch(train) [1050][30/63] lr: 1.0781e-03 eta: 3:00:58 time: 0.7783 data_time: 0.0232 memory: 16201 loss_prob: 0.3327 loss_thr: 0.2377 loss_db: 0.0589 loss: 0.6293 2022/08/30 21:24:41 - mmengine - INFO - Epoch(train) [1050][35/63] lr: 1.0781e-03 eta: 3:00:58 time: 0.7802 data_time: 0.0218 memory: 16201 loss_prob: 0.3301 loss_thr: 0.2346 loss_db: 0.0585 loss: 0.6232 2022/08/30 21:24:46 - mmengine - INFO - Epoch(train) [1050][40/63] lr: 1.0781e-03 eta: 3:00:46 time: 0.8144 data_time: 0.0257 memory: 16201 loss_prob: 0.3267 loss_thr: 0.2352 loss_db: 0.0600 loss: 0.6220 2022/08/30 21:24:50 - mmengine - INFO - Epoch(train) [1050][45/63] lr: 1.0781e-03 eta: 3:00:46 time: 0.8339 data_time: 0.0304 memory: 16201 loss_prob: 0.3586 loss_thr: 0.2540 loss_db: 0.0624 loss: 0.6750 2022/08/30 21:24:54 - mmengine - INFO - Epoch(train) [1050][50/63] lr: 1.0781e-03 eta: 3:00:34 time: 0.8140 data_time: 0.0227 memory: 16201 loss_prob: 0.3466 loss_thr: 0.2448 loss_db: 0.0583 loss: 0.6497 2022/08/30 21:24:58 - mmengine - INFO - Epoch(train) [1050][55/63] lr: 1.0781e-03 eta: 3:00:34 time: 0.8201 data_time: 0.0274 memory: 16201 loss_prob: 0.3023 loss_thr: 0.2261 loss_db: 0.0535 loss: 0.5819 2022/08/30 21:25:02 - mmengine - INFO - Epoch(train) [1050][60/63] lr: 1.0781e-03 eta: 3:00:22 time: 0.8133 data_time: 0.0297 memory: 16201 loss_prob: 0.3293 loss_thr: 0.2356 loss_db: 0.0592 loss: 0.6241 2022/08/30 21:25:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:25:10 - mmengine - INFO - Epoch(train) [1051][5/63] lr: 1.0717e-03 eta: 3:00:22 time: 0.9868 data_time: 0.2062 memory: 16201 loss_prob: 0.3250 loss_thr: 0.2386 loss_db: 0.0600 loss: 0.6236 2022/08/30 21:25:14 - mmengine - INFO - Epoch(train) [1051][10/63] lr: 1.0717e-03 eta: 3:00:07 time: 1.0160 data_time: 0.2155 memory: 16201 loss_prob: 0.3325 loss_thr: 0.2357 loss_db: 0.0590 loss: 0.6272 2022/08/30 21:25:18 - mmengine - INFO - Epoch(train) [1051][15/63] lr: 1.0717e-03 eta: 3:00:07 time: 0.7741 data_time: 0.0247 memory: 16201 loss_prob: 0.3287 loss_thr: 0.2327 loss_db: 0.0574 loss: 0.6187 2022/08/30 21:25:22 - mmengine - INFO - Epoch(train) [1051][20/63] lr: 1.0717e-03 eta: 2:59:55 time: 0.7753 data_time: 0.0182 memory: 16201 loss_prob: 0.3338 loss_thr: 0.2377 loss_db: 0.0599 loss: 0.6314 2022/08/30 21:25:26 - mmengine - INFO - Epoch(train) [1051][25/63] lr: 1.0717e-03 eta: 2:59:55 time: 0.8046 data_time: 0.0310 memory: 16201 loss_prob: 0.3352 loss_thr: 0.2445 loss_db: 0.0608 loss: 0.6405 2022/08/30 21:25:30 - mmengine - INFO - Epoch(train) [1051][30/63] lr: 1.0717e-03 eta: 2:59:43 time: 0.8184 data_time: 0.0266 memory: 16201 loss_prob: 0.3335 loss_thr: 0.2377 loss_db: 0.0591 loss: 0.6302 2022/08/30 21:25:34 - mmengine - INFO - Epoch(train) [1051][35/63] lr: 1.0717e-03 eta: 2:59:43 time: 0.8062 data_time: 0.0207 memory: 16201 loss_prob: 0.3183 loss_thr: 0.2309 loss_db: 0.0563 loss: 0.6056 2022/08/30 21:25:38 - mmengine - INFO - Epoch(train) [1051][40/63] lr: 1.0717e-03 eta: 2:59:31 time: 0.7906 data_time: 0.0263 memory: 16201 loss_prob: 0.3382 loss_thr: 0.2399 loss_db: 0.0609 loss: 0.6391 2022/08/30 21:25:42 - mmengine - INFO - Epoch(train) [1051][45/63] lr: 1.0717e-03 eta: 2:59:31 time: 0.7803 data_time: 0.0267 memory: 16201 loss_prob: 0.3426 loss_thr: 0.2364 loss_db: 0.0611 loss: 0.6401 2022/08/30 21:25:46 - mmengine - INFO - Epoch(train) [1051][50/63] lr: 1.0717e-03 eta: 2:59:19 time: 0.7839 data_time: 0.0257 memory: 16201 loss_prob: 0.3187 loss_thr: 0.2277 loss_db: 0.0570 loss: 0.6035 2022/08/30 21:25:50 - mmengine - INFO - Epoch(train) [1051][55/63] lr: 1.0717e-03 eta: 2:59:19 time: 0.7858 data_time: 0.0235 memory: 16201 loss_prob: 0.3308 loss_thr: 0.2373 loss_db: 0.0599 loss: 0.6280 2022/08/30 21:25:54 - mmengine - INFO - Epoch(train) [1051][60/63] lr: 1.0717e-03 eta: 2:59:07 time: 0.8074 data_time: 0.0245 memory: 16201 loss_prob: 0.3380 loss_thr: 0.2364 loss_db: 0.0597 loss: 0.6341 2022/08/30 21:25:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:26:02 - mmengine - INFO - Epoch(train) [1052][5/63] lr: 1.0652e-03 eta: 2:59:07 time: 0.9449 data_time: 0.2026 memory: 16201 loss_prob: 0.3038 loss_thr: 0.2190 loss_db: 0.0546 loss: 0.5774 2022/08/30 21:26:06 - mmengine - INFO - Epoch(train) [1052][10/63] lr: 1.0652e-03 eta: 2:58:51 time: 0.9769 data_time: 0.2150 memory: 16201 loss_prob: 0.3397 loss_thr: 0.2489 loss_db: 0.0617 loss: 0.6502 2022/08/30 21:26:10 - mmengine - INFO - Epoch(train) [1052][15/63] lr: 1.0652e-03 eta: 2:58:51 time: 0.8080 data_time: 0.0244 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2576 loss_db: 0.0640 loss: 0.6778 2022/08/30 21:26:14 - mmengine - INFO - Epoch(train) [1052][20/63] lr: 1.0652e-03 eta: 2:58:39 time: 0.8107 data_time: 0.0193 memory: 16201 loss_prob: 0.3223 loss_thr: 0.2287 loss_db: 0.0581 loss: 0.6092 2022/08/30 21:26:18 - mmengine - INFO - Epoch(train) [1052][25/63] lr: 1.0652e-03 eta: 2:58:39 time: 0.8095 data_time: 0.0302 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2280 loss_db: 0.0588 loss: 0.6165 2022/08/30 21:26:22 - mmengine - INFO - Epoch(train) [1052][30/63] lr: 1.0652e-03 eta: 2:58:27 time: 0.7899 data_time: 0.0226 memory: 16201 loss_prob: 0.3023 loss_thr: 0.2204 loss_db: 0.0539 loss: 0.5766 2022/08/30 21:26:26 - mmengine - INFO - Epoch(train) [1052][35/63] lr: 1.0652e-03 eta: 2:58:27 time: 0.7857 data_time: 0.0259 memory: 16201 loss_prob: 0.2765 loss_thr: 0.2103 loss_db: 0.0509 loss: 0.5377 2022/08/30 21:26:30 - mmengine - INFO - Epoch(train) [1052][40/63] lr: 1.0652e-03 eta: 2:58:16 time: 0.7898 data_time: 0.0294 memory: 16201 loss_prob: 0.3192 loss_thr: 0.2341 loss_db: 0.0583 loss: 0.6116 2022/08/30 21:26:34 - mmengine - INFO - Epoch(train) [1052][45/63] lr: 1.0652e-03 eta: 2:58:16 time: 0.7877 data_time: 0.0241 memory: 16201 loss_prob: 0.3844 loss_thr: 0.2671 loss_db: 0.0678 loss: 0.7194 2022/08/30 21:26:38 - mmengine - INFO - Epoch(train) [1052][50/63] lr: 1.0652e-03 eta: 2:58:04 time: 0.7881 data_time: 0.0261 memory: 16201 loss_prob: 0.3738 loss_thr: 0.2571 loss_db: 0.0650 loss: 0.6959 2022/08/30 21:26:42 - mmengine - INFO - Epoch(train) [1052][55/63] lr: 1.0652e-03 eta: 2:58:04 time: 0.7917 data_time: 0.0245 memory: 16201 loss_prob: 0.3170 loss_thr: 0.2308 loss_db: 0.0565 loss: 0.6043 2022/08/30 21:26:46 - mmengine - INFO - Epoch(train) [1052][60/63] lr: 1.0652e-03 eta: 2:57:52 time: 0.7975 data_time: 0.0270 memory: 16201 loss_prob: 0.3096 loss_thr: 0.2285 loss_db: 0.0558 loss: 0.5940 2022/08/30 21:26:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:26:53 - mmengine - INFO - Epoch(train) [1053][5/63] lr: 1.0587e-03 eta: 2:57:52 time: 0.9023 data_time: 0.1562 memory: 16201 loss_prob: 0.3252 loss_thr: 0.2392 loss_db: 0.0572 loss: 0.6216 2022/08/30 21:26:57 - mmengine - INFO - Epoch(train) [1053][10/63] lr: 1.0587e-03 eta: 2:57:36 time: 0.9447 data_time: 0.1757 memory: 16201 loss_prob: 0.2968 loss_thr: 0.2200 loss_db: 0.0514 loss: 0.5682 2022/08/30 21:27:01 - mmengine - INFO - Epoch(train) [1053][15/63] lr: 1.0587e-03 eta: 2:57:36 time: 0.7963 data_time: 0.0286 memory: 16201 loss_prob: 0.2703 loss_thr: 0.2001 loss_db: 0.0478 loss: 0.5182 2022/08/30 21:27:06 - mmengine - INFO - Epoch(train) [1053][20/63] lr: 1.0587e-03 eta: 2:57:24 time: 0.8536 data_time: 0.0181 memory: 16201 loss_prob: 0.2650 loss_thr: 0.2044 loss_db: 0.0489 loss: 0.5183 2022/08/30 21:27:10 - mmengine - INFO - Epoch(train) [1053][25/63] lr: 1.0587e-03 eta: 2:57:24 time: 0.8597 data_time: 0.0342 memory: 16201 loss_prob: 0.3106 loss_thr: 0.2335 loss_db: 0.0564 loss: 0.6005 2022/08/30 21:27:13 - mmengine - INFO - Epoch(train) [1053][30/63] lr: 1.0587e-03 eta: 2:57:12 time: 0.7758 data_time: 0.0254 memory: 16201 loss_prob: 0.3338 loss_thr: 0.2427 loss_db: 0.0598 loss: 0.6363 2022/08/30 21:27:17 - mmengine - INFO - Epoch(train) [1053][35/63] lr: 1.0587e-03 eta: 2:57:12 time: 0.7786 data_time: 0.0267 memory: 16201 loss_prob: 0.3600 loss_thr: 0.2478 loss_db: 0.0646 loss: 0.6724 2022/08/30 21:27:22 - mmengine - INFO - Epoch(train) [1053][40/63] lr: 1.0587e-03 eta: 2:57:00 time: 0.8212 data_time: 0.0342 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2288 loss_db: 0.0628 loss: 0.6414 2022/08/30 21:27:25 - mmengine - INFO - Epoch(train) [1053][45/63] lr: 1.0587e-03 eta: 2:57:00 time: 0.8135 data_time: 0.0270 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2272 loss_db: 0.0566 loss: 0.6015 2022/08/30 21:27:29 - mmengine - INFO - Epoch(train) [1053][50/63] lr: 1.0587e-03 eta: 2:56:48 time: 0.7851 data_time: 0.0298 memory: 16201 loss_prob: 0.3269 loss_thr: 0.2442 loss_db: 0.0575 loss: 0.6286 2022/08/30 21:27:33 - mmengine - INFO - Epoch(train) [1053][55/63] lr: 1.0587e-03 eta: 2:56:48 time: 0.7940 data_time: 0.0234 memory: 16201 loss_prob: 0.3091 loss_thr: 0.2249 loss_db: 0.0563 loss: 0.5904 2022/08/30 21:27:37 - mmengine - INFO - Epoch(train) [1053][60/63] lr: 1.0587e-03 eta: 2:56:36 time: 0.7984 data_time: 0.0223 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2300 loss_db: 0.0585 loss: 0.6238 2022/08/30 21:27:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:27:45 - mmengine - INFO - Epoch(train) [1054][5/63] lr: 1.0522e-03 eta: 2:56:36 time: 0.9313 data_time: 0.1972 memory: 16201 loss_prob: 0.3502 loss_thr: 0.2510 loss_db: 0.0618 loss: 0.6630 2022/08/30 21:27:49 - mmengine - INFO - Epoch(train) [1054][10/63] lr: 1.0522e-03 eta: 2:56:21 time: 0.9770 data_time: 0.2135 memory: 16201 loss_prob: 0.4495 loss_thr: 0.2604 loss_db: 0.0720 loss: 0.7819 2022/08/30 21:27:53 - mmengine - INFO - Epoch(train) [1054][15/63] lr: 1.0522e-03 eta: 2:56:21 time: 0.7950 data_time: 0.0264 memory: 16201 loss_prob: 0.4575 loss_thr: 0.2744 loss_db: 0.0737 loss: 0.8056 2022/08/30 21:27:57 - mmengine - INFO - Epoch(train) [1054][20/63] lr: 1.0522e-03 eta: 2:56:09 time: 0.7952 data_time: 0.0195 memory: 16201 loss_prob: 0.3688 loss_thr: 0.2624 loss_db: 0.0664 loss: 0.6977 2022/08/30 21:28:01 - mmengine - INFO - Epoch(train) [1054][25/63] lr: 1.0522e-03 eta: 2:56:09 time: 0.8042 data_time: 0.0339 memory: 16201 loss_prob: 0.3782 loss_thr: 0.2583 loss_db: 0.0682 loss: 0.7047 2022/08/30 21:28:05 - mmengine - INFO - Epoch(train) [1054][30/63] lr: 1.0522e-03 eta: 2:55:57 time: 0.7894 data_time: 0.0243 memory: 16201 loss_prob: 0.3821 loss_thr: 0.2585 loss_db: 0.0677 loss: 0.7083 2022/08/30 21:28:09 - mmengine - INFO - Epoch(train) [1054][35/63] lr: 1.0522e-03 eta: 2:55:57 time: 0.7832 data_time: 0.0196 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2334 loss_db: 0.0613 loss: 0.6381 2022/08/30 21:28:13 - mmengine - INFO - Epoch(train) [1054][40/63] lr: 1.0522e-03 eta: 2:55:45 time: 0.7789 data_time: 0.0254 memory: 16201 loss_prob: 0.3263 loss_thr: 0.2215 loss_db: 0.0593 loss: 0.6070 2022/08/30 21:28:17 - mmengine - INFO - Epoch(train) [1054][45/63] lr: 1.0522e-03 eta: 2:55:45 time: 0.7867 data_time: 0.0222 memory: 16201 loss_prob: 0.3448 loss_thr: 0.2370 loss_db: 0.0612 loss: 0.6430 2022/08/30 21:28:21 - mmengine - INFO - Epoch(train) [1054][50/63] lr: 1.0522e-03 eta: 2:55:33 time: 0.8063 data_time: 0.0246 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2350 loss_db: 0.0570 loss: 0.6245 2022/08/30 21:28:25 - mmengine - INFO - Epoch(train) [1054][55/63] lr: 1.0522e-03 eta: 2:55:33 time: 0.7934 data_time: 0.0225 memory: 16201 loss_prob: 0.3313 loss_thr: 0.2369 loss_db: 0.0581 loss: 0.6263 2022/08/30 21:28:29 - mmengine - INFO - Epoch(train) [1054][60/63] lr: 1.0522e-03 eta: 2:55:21 time: 0.7743 data_time: 0.0256 memory: 16201 loss_prob: 0.3208 loss_thr: 0.2369 loss_db: 0.0590 loss: 0.6167 2022/08/30 21:28:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:28:36 - mmengine - INFO - Epoch(train) [1055][5/63] lr: 1.0457e-03 eta: 2:55:21 time: 0.8779 data_time: 0.1571 memory: 16201 loss_prob: 0.2886 loss_thr: 0.2172 loss_db: 0.0525 loss: 0.5582 2022/08/30 21:28:40 - mmengine - INFO - Epoch(train) [1055][10/63] lr: 1.0457e-03 eta: 2:55:06 time: 0.9343 data_time: 0.1734 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2327 loss_db: 0.0547 loss: 0.5961 2022/08/30 21:28:44 - mmengine - INFO - Epoch(train) [1055][15/63] lr: 1.0457e-03 eta: 2:55:06 time: 0.8080 data_time: 0.0251 memory: 16201 loss_prob: 0.3649 loss_thr: 0.2519 loss_db: 0.0644 loss: 0.6812 2022/08/30 21:28:48 - mmengine - INFO - Epoch(train) [1055][20/63] lr: 1.0457e-03 eta: 2:54:54 time: 0.8008 data_time: 0.0178 memory: 16201 loss_prob: 0.3682 loss_thr: 0.2406 loss_db: 0.0658 loss: 0.6746 2022/08/30 21:28:52 - mmengine - INFO - Epoch(train) [1055][25/63] lr: 1.0457e-03 eta: 2:54:54 time: 0.8014 data_time: 0.0323 memory: 16201 loss_prob: 0.3342 loss_thr: 0.2224 loss_db: 0.0602 loss: 0.6168 2022/08/30 21:28:56 - mmengine - INFO - Epoch(train) [1055][30/63] lr: 1.0457e-03 eta: 2:54:42 time: 0.7992 data_time: 0.0231 memory: 16201 loss_prob: 0.3386 loss_thr: 0.2318 loss_db: 0.0596 loss: 0.6300 2022/08/30 21:29:00 - mmengine - INFO - Epoch(train) [1055][35/63] lr: 1.0457e-03 eta: 2:54:42 time: 0.7749 data_time: 0.0173 memory: 16201 loss_prob: 0.3526 loss_thr: 0.2419 loss_db: 0.0628 loss: 0.6573 2022/08/30 21:29:04 - mmengine - INFO - Epoch(train) [1055][40/63] lr: 1.0457e-03 eta: 2:54:30 time: 0.7782 data_time: 0.0253 memory: 16201 loss_prob: 0.3485 loss_thr: 0.2427 loss_db: 0.0629 loss: 0.6541 2022/08/30 21:29:08 - mmengine - INFO - Epoch(train) [1055][45/63] lr: 1.0457e-03 eta: 2:54:30 time: 0.8103 data_time: 0.0265 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2283 loss_db: 0.0579 loss: 0.6101 2022/08/30 21:29:12 - mmengine - INFO - Epoch(train) [1055][50/63] lr: 1.0457e-03 eta: 2:54:18 time: 0.8134 data_time: 0.0263 memory: 16201 loss_prob: 0.3014 loss_thr: 0.2207 loss_db: 0.0540 loss: 0.5761 2022/08/30 21:29:16 - mmengine - INFO - Epoch(train) [1055][55/63] lr: 1.0457e-03 eta: 2:54:18 time: 0.8024 data_time: 0.0213 memory: 16201 loss_prob: 0.2950 loss_thr: 0.2207 loss_db: 0.0509 loss: 0.5666 2022/08/30 21:29:20 - mmengine - INFO - Epoch(train) [1055][60/63] lr: 1.0457e-03 eta: 2:54:06 time: 0.7945 data_time: 0.0257 memory: 16201 loss_prob: 0.3149 loss_thr: 0.2301 loss_db: 0.0557 loss: 0.6007 2022/08/30 21:29:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:29:27 - mmengine - INFO - Epoch(train) [1056][5/63] lr: 1.0393e-03 eta: 2:54:06 time: 0.9156 data_time: 0.1851 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2334 loss_db: 0.0616 loss: 0.6384 2022/08/30 21:29:31 - mmengine - INFO - Epoch(train) [1056][10/63] lr: 1.0393e-03 eta: 2:53:50 time: 0.9721 data_time: 0.1995 memory: 16201 loss_prob: 0.3679 loss_thr: 0.2574 loss_db: 0.0640 loss: 0.6892 2022/08/30 21:29:36 - mmengine - INFO - Epoch(train) [1056][15/63] lr: 1.0393e-03 eta: 2:53:50 time: 0.8203 data_time: 0.0264 memory: 16201 loss_prob: 0.3607 loss_thr: 0.2567 loss_db: 0.0628 loss: 0.6801 2022/08/30 21:29:40 - mmengine - INFO - Epoch(train) [1056][20/63] lr: 1.0393e-03 eta: 2:53:39 time: 0.8122 data_time: 0.0187 memory: 16201 loss_prob: 0.3441 loss_thr: 0.2514 loss_db: 0.0615 loss: 0.6569 2022/08/30 21:29:44 - mmengine - INFO - Epoch(train) [1056][25/63] lr: 1.0393e-03 eta: 2:53:39 time: 0.7856 data_time: 0.0285 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2350 loss_db: 0.0602 loss: 0.6244 2022/08/30 21:29:47 - mmengine - INFO - Epoch(train) [1056][30/63] lr: 1.0393e-03 eta: 2:53:27 time: 0.7860 data_time: 0.0249 memory: 16201 loss_prob: 0.3371 loss_thr: 0.2390 loss_db: 0.0619 loss: 0.6380 2022/08/30 21:29:51 - mmengine - INFO - Epoch(train) [1056][35/63] lr: 1.0393e-03 eta: 2:53:27 time: 0.7732 data_time: 0.0205 memory: 16201 loss_prob: 0.3523 loss_thr: 0.2675 loss_db: 0.0622 loss: 0.6820 2022/08/30 21:29:55 - mmengine - INFO - Epoch(train) [1056][40/63] lr: 1.0393e-03 eta: 2:53:15 time: 0.7866 data_time: 0.0285 memory: 16201 loss_prob: 0.3423 loss_thr: 0.2564 loss_db: 0.0586 loss: 0.6573 2022/08/30 21:29:59 - mmengine - INFO - Epoch(train) [1056][45/63] lr: 1.0393e-03 eta: 2:53:15 time: 0.7966 data_time: 0.0248 memory: 16201 loss_prob: 0.3159 loss_thr: 0.2254 loss_db: 0.0564 loss: 0.5977 2022/08/30 21:30:03 - mmengine - INFO - Epoch(train) [1056][50/63] lr: 1.0393e-03 eta: 2:53:03 time: 0.7756 data_time: 0.0222 memory: 16201 loss_prob: 0.3263 loss_thr: 0.2312 loss_db: 0.0589 loss: 0.6164 2022/08/30 21:30:07 - mmengine - INFO - Epoch(train) [1056][55/63] lr: 1.0393e-03 eta: 2:53:03 time: 0.8015 data_time: 0.0278 memory: 16201 loss_prob: 0.3050 loss_thr: 0.2142 loss_db: 0.0552 loss: 0.5744 2022/08/30 21:30:11 - mmengine - INFO - Epoch(train) [1056][60/63] lr: 1.0393e-03 eta: 2:52:51 time: 0.8090 data_time: 0.0258 memory: 16201 loss_prob: 0.2944 loss_thr: 0.2069 loss_db: 0.0531 loss: 0.5543 2022/08/30 21:30:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:30:19 - mmengine - INFO - Epoch(train) [1057][5/63] lr: 1.0328e-03 eta: 2:52:51 time: 0.9511 data_time: 0.1958 memory: 16201 loss_prob: 0.3172 loss_thr: 0.2297 loss_db: 0.0564 loss: 0.6033 2022/08/30 21:30:23 - mmengine - INFO - Epoch(train) [1057][10/63] lr: 1.0328e-03 eta: 2:52:35 time: 0.9696 data_time: 0.2048 memory: 16201 loss_prob: 0.3203 loss_thr: 0.2258 loss_db: 0.0570 loss: 0.6031 2022/08/30 21:30:27 - mmengine - INFO - Epoch(train) [1057][15/63] lr: 1.0328e-03 eta: 2:52:35 time: 0.8297 data_time: 0.0274 memory: 16201 loss_prob: 0.3140 loss_thr: 0.2250 loss_db: 0.0559 loss: 0.5948 2022/08/30 21:30:31 - mmengine - INFO - Epoch(train) [1057][20/63] lr: 1.0328e-03 eta: 2:52:24 time: 0.8341 data_time: 0.0224 memory: 16201 loss_prob: 0.3162 loss_thr: 0.2323 loss_db: 0.0560 loss: 0.6044 2022/08/30 21:30:35 - mmengine - INFO - Epoch(train) [1057][25/63] lr: 1.0328e-03 eta: 2:52:24 time: 0.7985 data_time: 0.0311 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2442 loss_db: 0.0598 loss: 0.6337 2022/08/30 21:30:39 - mmengine - INFO - Epoch(train) [1057][30/63] lr: 1.0328e-03 eta: 2:52:12 time: 0.7934 data_time: 0.0301 memory: 16201 loss_prob: 0.3252 loss_thr: 0.2395 loss_db: 0.0604 loss: 0.6251 2022/08/30 21:30:43 - mmengine - INFO - Epoch(train) [1057][35/63] lr: 1.0328e-03 eta: 2:52:12 time: 0.7846 data_time: 0.0174 memory: 16201 loss_prob: 0.3040 loss_thr: 0.2243 loss_db: 0.0550 loss: 0.5834 2022/08/30 21:30:48 - mmengine - INFO - Epoch(train) [1057][40/63] lr: 1.0328e-03 eta: 2:52:00 time: 0.8223 data_time: 0.0245 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2332 loss_db: 0.0562 loss: 0.6092 2022/08/30 21:30:52 - mmengine - INFO - Epoch(train) [1057][45/63] lr: 1.0328e-03 eta: 2:52:00 time: 0.8323 data_time: 0.0286 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2380 loss_db: 0.0581 loss: 0.6250 2022/08/30 21:30:55 - mmengine - INFO - Epoch(train) [1057][50/63] lr: 1.0328e-03 eta: 2:51:48 time: 0.7899 data_time: 0.0239 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2249 loss_db: 0.0558 loss: 0.5906 2022/08/30 21:31:00 - mmengine - INFO - Epoch(train) [1057][55/63] lr: 1.0328e-03 eta: 2:51:48 time: 0.7940 data_time: 0.0269 memory: 16201 loss_prob: 0.3269 loss_thr: 0.2335 loss_db: 0.0604 loss: 0.6208 2022/08/30 21:31:03 - mmengine - INFO - Epoch(train) [1057][60/63] lr: 1.0328e-03 eta: 2:51:36 time: 0.8015 data_time: 0.0240 memory: 16201 loss_prob: 0.3526 loss_thr: 0.2462 loss_db: 0.0637 loss: 0.6625 2022/08/30 21:31:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:31:12 - mmengine - INFO - Epoch(train) [1058][5/63] lr: 1.0263e-03 eta: 2:51:36 time: 0.9597 data_time: 0.1997 memory: 16201 loss_prob: 0.3780 loss_thr: 0.2615 loss_db: 0.0656 loss: 0.7051 2022/08/30 21:31:16 - mmengine - INFO - Epoch(train) [1058][10/63] lr: 1.0263e-03 eta: 2:51:20 time: 0.9685 data_time: 0.2077 memory: 16201 loss_prob: 0.4006 loss_thr: 0.2767 loss_db: 0.0706 loss: 0.7479 2022/08/30 21:31:19 - mmengine - INFO - Epoch(train) [1058][15/63] lr: 1.0263e-03 eta: 2:51:20 time: 0.7883 data_time: 0.0251 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2327 loss_db: 0.0583 loss: 0.6161 2022/08/30 21:31:23 - mmengine - INFO - Epoch(train) [1058][20/63] lr: 1.0263e-03 eta: 2:51:09 time: 0.7936 data_time: 0.0198 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2437 loss_db: 0.0610 loss: 0.6528 2022/08/30 21:31:28 - mmengine - INFO - Epoch(train) [1058][25/63] lr: 1.0263e-03 eta: 2:51:09 time: 0.8503 data_time: 0.0285 memory: 16201 loss_prob: 0.3309 loss_thr: 0.2395 loss_db: 0.0577 loss: 0.6282 2022/08/30 21:31:32 - mmengine - INFO - Epoch(train) [1058][30/63] lr: 1.0263e-03 eta: 2:50:57 time: 0.8382 data_time: 0.0244 memory: 16201 loss_prob: 0.3018 loss_thr: 0.2154 loss_db: 0.0543 loss: 0.5715 2022/08/30 21:31:36 - mmengine - INFO - Epoch(train) [1058][35/63] lr: 1.0263e-03 eta: 2:50:57 time: 0.8044 data_time: 0.0252 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2492 loss_db: 0.0643 loss: 0.6759 2022/08/30 21:31:40 - mmengine - INFO - Epoch(train) [1058][40/63] lr: 1.0263e-03 eta: 2:50:45 time: 0.8076 data_time: 0.0269 memory: 16201 loss_prob: 0.3458 loss_thr: 0.2421 loss_db: 0.0607 loss: 0.6485 2022/08/30 21:31:44 - mmengine - INFO - Epoch(train) [1058][45/63] lr: 1.0263e-03 eta: 2:50:45 time: 0.8117 data_time: 0.0245 memory: 16201 loss_prob: 0.3205 loss_thr: 0.2194 loss_db: 0.0558 loss: 0.5957 2022/08/30 21:31:48 - mmengine - INFO - Epoch(train) [1058][50/63] lr: 1.0263e-03 eta: 2:50:33 time: 0.8182 data_time: 0.0264 memory: 16201 loss_prob: 0.3106 loss_thr: 0.2172 loss_db: 0.0540 loss: 0.5818 2022/08/30 21:31:52 - mmengine - INFO - Epoch(train) [1058][55/63] lr: 1.0263e-03 eta: 2:50:33 time: 0.8114 data_time: 0.0265 memory: 16201 loss_prob: 0.3017 loss_thr: 0.2217 loss_db: 0.0536 loss: 0.5771 2022/08/30 21:31:56 - mmengine - INFO - Epoch(train) [1058][60/63] lr: 1.0263e-03 eta: 2:50:21 time: 0.8070 data_time: 0.0300 memory: 16201 loss_prob: 0.3226 loss_thr: 0.2470 loss_db: 0.0574 loss: 0.6270 2022/08/30 21:31:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:32:04 - mmengine - INFO - Epoch(train) [1059][5/63] lr: 1.0198e-03 eta: 2:50:21 time: 0.9026 data_time: 0.1582 memory: 16201 loss_prob: 0.3271 loss_thr: 0.2342 loss_db: 0.0585 loss: 0.6198 2022/08/30 21:32:08 - mmengine - INFO - Epoch(train) [1059][10/63] lr: 1.0198e-03 eta: 2:50:06 time: 0.9578 data_time: 0.1710 memory: 16201 loss_prob: 0.3095 loss_thr: 0.2149 loss_db: 0.0555 loss: 0.5799 2022/08/30 21:32:12 - mmengine - INFO - Epoch(train) [1059][15/63] lr: 1.0198e-03 eta: 2:50:06 time: 0.7959 data_time: 0.0250 memory: 16201 loss_prob: 0.3388 loss_thr: 0.2410 loss_db: 0.0593 loss: 0.6391 2022/08/30 21:32:16 - mmengine - INFO - Epoch(train) [1059][20/63] lr: 1.0198e-03 eta: 2:49:54 time: 0.8491 data_time: 0.0189 memory: 16201 loss_prob: 0.3661 loss_thr: 0.2595 loss_db: 0.0648 loss: 0.6903 2022/08/30 21:32:20 - mmengine - INFO - Epoch(train) [1059][25/63] lr: 1.0198e-03 eta: 2:49:54 time: 0.8561 data_time: 0.0310 memory: 16201 loss_prob: 0.3513 loss_thr: 0.2354 loss_db: 0.0634 loss: 0.6502 2022/08/30 21:32:24 - mmengine - INFO - Epoch(train) [1059][30/63] lr: 1.0198e-03 eta: 2:49:42 time: 0.7787 data_time: 0.0242 memory: 16201 loss_prob: 0.3405 loss_thr: 0.2323 loss_db: 0.0612 loss: 0.6340 2022/08/30 21:32:28 - mmengine - INFO - Epoch(train) [1059][35/63] lr: 1.0198e-03 eta: 2:49:42 time: 0.7860 data_time: 0.0223 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2433 loss_db: 0.0629 loss: 0.6568 2022/08/30 21:32:32 - mmengine - INFO - Epoch(train) [1059][40/63] lr: 1.0198e-03 eta: 2:49:30 time: 0.7914 data_time: 0.0233 memory: 16201 loss_prob: 0.3552 loss_thr: 0.2374 loss_db: 0.0631 loss: 0.6557 2022/08/30 21:32:36 - mmengine - INFO - Epoch(train) [1059][45/63] lr: 1.0198e-03 eta: 2:49:30 time: 0.8211 data_time: 0.0246 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2327 loss_db: 0.0611 loss: 0.6436 2022/08/30 21:32:40 - mmengine - INFO - Epoch(train) [1059][50/63] lr: 1.0198e-03 eta: 2:49:18 time: 0.8302 data_time: 0.0299 memory: 16201 loss_prob: 0.3683 loss_thr: 0.2481 loss_db: 0.0648 loss: 0.6812 2022/08/30 21:32:44 - mmengine - INFO - Epoch(train) [1059][55/63] lr: 1.0198e-03 eta: 2:49:18 time: 0.7829 data_time: 0.0235 memory: 16201 loss_prob: 0.3648 loss_thr: 0.2499 loss_db: 0.0654 loss: 0.6801 2022/08/30 21:32:48 - mmengine - INFO - Epoch(train) [1059][60/63] lr: 1.0198e-03 eta: 2:49:06 time: 0.7814 data_time: 0.0258 memory: 16201 loss_prob: 0.3351 loss_thr: 0.2413 loss_db: 0.0599 loss: 0.6363 2022/08/30 21:32:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:32:55 - mmengine - INFO - Epoch(train) [1060][5/63] lr: 1.0132e-03 eta: 2:49:06 time: 0.8852 data_time: 0.1517 memory: 16201 loss_prob: 0.3025 loss_thr: 0.2297 loss_db: 0.0554 loss: 0.5876 2022/08/30 21:32:59 - mmengine - INFO - Epoch(train) [1060][10/63] lr: 1.0132e-03 eta: 2:48:51 time: 0.9243 data_time: 0.1601 memory: 16201 loss_prob: 0.3027 loss_thr: 0.2288 loss_db: 0.0542 loss: 0.5857 2022/08/30 21:33:03 - mmengine - INFO - Epoch(train) [1060][15/63] lr: 1.0132e-03 eta: 2:48:51 time: 0.7881 data_time: 0.0236 memory: 16201 loss_prob: 0.3183 loss_thr: 0.2413 loss_db: 0.0571 loss: 0.6167 2022/08/30 21:33:08 - mmengine - INFO - Epoch(train) [1060][20/63] lr: 1.0132e-03 eta: 2:48:39 time: 0.8464 data_time: 0.0255 memory: 16201 loss_prob: 0.3397 loss_thr: 0.2497 loss_db: 0.0617 loss: 0.6511 2022/08/30 21:33:12 - mmengine - INFO - Epoch(train) [1060][25/63] lr: 1.0132e-03 eta: 2:48:39 time: 0.8531 data_time: 0.0265 memory: 16201 loss_prob: 0.3265 loss_thr: 0.2416 loss_db: 0.0586 loss: 0.6267 2022/08/30 21:33:16 - mmengine - INFO - Epoch(train) [1060][30/63] lr: 1.0132e-03 eta: 2:48:27 time: 0.7954 data_time: 0.0233 memory: 16201 loss_prob: 0.3085 loss_thr: 0.2320 loss_db: 0.0550 loss: 0.5955 2022/08/30 21:33:20 - mmengine - INFO - Epoch(train) [1060][35/63] lr: 1.0132e-03 eta: 2:48:27 time: 0.7867 data_time: 0.0208 memory: 16201 loss_prob: 0.3157 loss_thr: 0.2332 loss_db: 0.0571 loss: 0.6060 2022/08/30 21:33:24 - mmengine - INFO - Epoch(train) [1060][40/63] lr: 1.0132e-03 eta: 2:48:15 time: 0.7882 data_time: 0.0249 memory: 16201 loss_prob: 0.3111 loss_thr: 0.2276 loss_db: 0.0566 loss: 0.5953 2022/08/30 21:33:27 - mmengine - INFO - Epoch(train) [1060][45/63] lr: 1.0132e-03 eta: 2:48:15 time: 0.7824 data_time: 0.0273 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2240 loss_db: 0.0573 loss: 0.6280 2022/08/30 21:33:31 - mmengine - INFO - Epoch(train) [1060][50/63] lr: 1.0132e-03 eta: 2:48:03 time: 0.7723 data_time: 0.0209 memory: 16201 loss_prob: 0.3730 loss_thr: 0.2397 loss_db: 0.0603 loss: 0.6731 2022/08/30 21:33:35 - mmengine - INFO - Epoch(train) [1060][55/63] lr: 1.0132e-03 eta: 2:48:03 time: 0.7974 data_time: 0.0265 memory: 16201 loss_prob: 0.3496 loss_thr: 0.2386 loss_db: 0.0610 loss: 0.6493 2022/08/30 21:33:40 - mmengine - INFO - Epoch(train) [1060][60/63] lr: 1.0132e-03 eta: 2:47:51 time: 0.8245 data_time: 0.0319 memory: 16201 loss_prob: 0.3231 loss_thr: 0.2227 loss_db: 0.0575 loss: 0.6033 2022/08/30 21:33:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:33:41 - mmengine - INFO - Saving checkpoint at 1060 epochs 2022/08/30 21:33:50 - mmengine - INFO - Epoch(val) [1060][5/32] eta: 2:47:51 time: 0.6305 data_time: 0.1243 memory: 16201 2022/08/30 21:33:53 - mmengine - INFO - Epoch(val) [1060][10/32] eta: 0:00:15 time: 0.6937 data_time: 0.1526 memory: 15734 2022/08/30 21:33:55 - mmengine - INFO - Epoch(val) [1060][15/32] eta: 0:00:15 time: 0.5780 data_time: 0.0430 memory: 15734 2022/08/30 21:33:58 - mmengine - INFO - Epoch(val) [1060][20/32] eta: 0:00:06 time: 0.5794 data_time: 0.0465 memory: 15734 2022/08/30 21:34:02 - mmengine - INFO - Epoch(val) [1060][25/32] eta: 0:00:06 time: 0.6127 data_time: 0.0492 memory: 15734 2022/08/30 21:34:04 - mmengine - INFO - Epoch(val) [1060][30/32] eta: 0:00:01 time: 0.5932 data_time: 0.0202 memory: 15734 2022/08/30 21:34:05 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 21:34:05 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8512, precision: 0.8029, hmean: 0.8264 2022/08/30 21:34:05 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8512, precision: 0.8340, hmean: 0.8425 2022/08/30 21:34:05 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8512, precision: 0.8520, hmean: 0.8516 2022/08/30 21:34:05 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8488, precision: 0.8680, hmean: 0.8583 2022/08/30 21:34:05 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8426, precision: 0.8870, hmean: 0.8642 2022/08/30 21:34:05 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8252, precision: 0.9161, hmean: 0.8683 2022/08/30 21:34:05 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.4954, precision: 0.9510, hmean: 0.6515 2022/08/30 21:34:05 - mmengine - INFO - Epoch(val) [1060][32/32] icdar/precision: 0.9161 icdar/recall: 0.8252 icdar/hmean: 0.8683 2022/08/30 21:34:11 - mmengine - INFO - Epoch(train) [1061][5/63] lr: 1.0067e-03 eta: 0:00:01 time: 0.9563 data_time: 0.2018 memory: 16201 loss_prob: 0.3219 loss_thr: 0.2316 loss_db: 0.0577 loss: 0.6112 2022/08/30 21:34:15 - mmengine - INFO - Epoch(train) [1061][10/63] lr: 1.0067e-03 eta: 2:47:36 time: 0.9720 data_time: 0.2019 memory: 16201 loss_prob: 0.3798 loss_thr: 0.2686 loss_db: 0.0671 loss: 0.7156 2022/08/30 21:34:19 - mmengine - INFO - Epoch(train) [1061][15/63] lr: 1.0067e-03 eta: 2:47:36 time: 0.8120 data_time: 0.0185 memory: 16201 loss_prob: 0.3784 loss_thr: 0.2684 loss_db: 0.0669 loss: 0.7137 2022/08/30 21:34:23 - mmengine - INFO - Epoch(train) [1061][20/63] lr: 1.0067e-03 eta: 2:47:24 time: 0.8355 data_time: 0.0299 memory: 16201 loss_prob: 0.3215 loss_thr: 0.2346 loss_db: 0.0574 loss: 0.6135 2022/08/30 21:34:27 - mmengine - INFO - Epoch(train) [1061][25/63] lr: 1.0067e-03 eta: 2:47:24 time: 0.7849 data_time: 0.0314 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2331 loss_db: 0.0564 loss: 0.6192 2022/08/30 21:34:31 - mmengine - INFO - Epoch(train) [1061][30/63] lr: 1.0067e-03 eta: 2:47:12 time: 0.7806 data_time: 0.0174 memory: 16201 loss_prob: 0.3323 loss_thr: 0.2225 loss_db: 0.0578 loss: 0.6126 2022/08/30 21:34:35 - mmengine - INFO - Epoch(train) [1061][35/63] lr: 1.0067e-03 eta: 2:47:12 time: 0.7988 data_time: 0.0236 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2275 loss_db: 0.0566 loss: 0.6091 2022/08/30 21:34:39 - mmengine - INFO - Epoch(train) [1061][40/63] lr: 1.0067e-03 eta: 2:47:00 time: 0.7908 data_time: 0.0237 memory: 16201 loss_prob: 0.3425 loss_thr: 0.2400 loss_db: 0.0591 loss: 0.6417 2022/08/30 21:34:43 - mmengine - INFO - Epoch(train) [1061][45/63] lr: 1.0067e-03 eta: 2:47:00 time: 0.7963 data_time: 0.0207 memory: 16201 loss_prob: 0.3317 loss_thr: 0.2384 loss_db: 0.0595 loss: 0.6296 2022/08/30 21:34:48 - mmengine - INFO - Epoch(train) [1061][50/63] lr: 1.0067e-03 eta: 2:46:48 time: 0.8449 data_time: 0.0287 memory: 16201 loss_prob: 0.3023 loss_thr: 0.2234 loss_db: 0.0542 loss: 0.5799 2022/08/30 21:34:51 - mmengine - INFO - Epoch(train) [1061][55/63] lr: 1.0067e-03 eta: 2:46:48 time: 0.8296 data_time: 0.0235 memory: 16201 loss_prob: 0.3105 loss_thr: 0.2284 loss_db: 0.0557 loss: 0.5947 2022/08/30 21:34:56 - mmengine - INFO - Epoch(train) [1061][60/63] lr: 1.0067e-03 eta: 2:46:37 time: 0.8106 data_time: 0.0269 memory: 16201 loss_prob: 0.3368 loss_thr: 0.2368 loss_db: 0.0599 loss: 0.6335 2022/08/30 21:34:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:35:03 - mmengine - INFO - Epoch(train) [1062][5/63] lr: 1.0002e-03 eta: 2:46:37 time: 0.9006 data_time: 0.1662 memory: 16201 loss_prob: 0.3657 loss_thr: 0.2537 loss_db: 0.0645 loss: 0.6839 2022/08/30 21:35:07 - mmengine - INFO - Epoch(train) [1062][10/63] lr: 1.0002e-03 eta: 2:46:21 time: 0.9444 data_time: 0.1693 memory: 16201 loss_prob: 0.3276 loss_thr: 0.2376 loss_db: 0.0594 loss: 0.6246 2022/08/30 21:35:11 - mmengine - INFO - Epoch(train) [1062][15/63] lr: 1.0002e-03 eta: 2:46:21 time: 0.7984 data_time: 0.0261 memory: 16201 loss_prob: 0.3111 loss_thr: 0.2275 loss_db: 0.0572 loss: 0.5958 2022/08/30 21:35:15 - mmengine - INFO - Epoch(train) [1062][20/63] lr: 1.0002e-03 eta: 2:46:09 time: 0.7944 data_time: 0.0234 memory: 16201 loss_prob: 0.3257 loss_thr: 0.2289 loss_db: 0.0583 loss: 0.6129 2022/08/30 21:35:19 - mmengine - INFO - Epoch(train) [1062][25/63] lr: 1.0002e-03 eta: 2:46:09 time: 0.7907 data_time: 0.0240 memory: 16201 loss_prob: 0.3376 loss_thr: 0.2363 loss_db: 0.0606 loss: 0.6344 2022/08/30 21:35:23 - mmengine - INFO - Epoch(train) [1062][30/63] lr: 1.0002e-03 eta: 2:45:57 time: 0.7947 data_time: 0.0242 memory: 16201 loss_prob: 0.3318 loss_thr: 0.2363 loss_db: 0.0601 loss: 0.6282 2022/08/30 21:35:27 - mmengine - INFO - Epoch(train) [1062][35/63] lr: 1.0002e-03 eta: 2:45:57 time: 0.8057 data_time: 0.0267 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2374 loss_db: 0.0600 loss: 0.6370 2022/08/30 21:35:31 - mmengine - INFO - Epoch(train) [1062][40/63] lr: 1.0002e-03 eta: 2:45:45 time: 0.7907 data_time: 0.0240 memory: 16201 loss_prob: 0.3402 loss_thr: 0.2361 loss_db: 0.0600 loss: 0.6363 2022/08/30 21:35:35 - mmengine - INFO - Epoch(train) [1062][45/63] lr: 1.0002e-03 eta: 2:45:45 time: 0.8020 data_time: 0.0282 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2264 loss_db: 0.0570 loss: 0.6019 2022/08/30 21:35:39 - mmengine - INFO - Epoch(train) [1062][50/63] lr: 1.0002e-03 eta: 2:45:34 time: 0.8073 data_time: 0.0303 memory: 16201 loss_prob: 0.3404 loss_thr: 0.2356 loss_db: 0.0608 loss: 0.6368 2022/08/30 21:35:43 - mmengine - INFO - Epoch(train) [1062][55/63] lr: 1.0002e-03 eta: 2:45:34 time: 0.7896 data_time: 0.0209 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2303 loss_db: 0.0585 loss: 0.6187 2022/08/30 21:35:47 - mmengine - INFO - Epoch(train) [1062][60/63] lr: 1.0002e-03 eta: 2:45:22 time: 0.8035 data_time: 0.0299 memory: 16201 loss_prob: 0.3470 loss_thr: 0.2469 loss_db: 0.0609 loss: 0.6548 2022/08/30 21:35:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:35:55 - mmengine - INFO - Epoch(train) [1063][5/63] lr: 9.9368e-04 eta: 2:45:22 time: 0.8879 data_time: 0.1583 memory: 16201 loss_prob: 0.3104 loss_thr: 0.2295 loss_db: 0.0560 loss: 0.5960 2022/08/30 21:35:59 - mmengine - INFO - Epoch(train) [1063][10/63] lr: 9.9368e-04 eta: 2:45:06 time: 0.9484 data_time: 0.1733 memory: 16201 loss_prob: 0.3061 loss_thr: 0.2225 loss_db: 0.0541 loss: 0.5827 2022/08/30 21:36:03 - mmengine - INFO - Epoch(train) [1063][15/63] lr: 9.9368e-04 eta: 2:45:06 time: 0.8021 data_time: 0.0274 memory: 16201 loss_prob: 0.2912 loss_thr: 0.2187 loss_db: 0.0517 loss: 0.5616 2022/08/30 21:36:07 - mmengine - INFO - Epoch(train) [1063][20/63] lr: 9.9368e-04 eta: 2:44:54 time: 0.8187 data_time: 0.0205 memory: 16201 loss_prob: 0.3073 loss_thr: 0.2258 loss_db: 0.0553 loss: 0.5884 2022/08/30 21:36:11 - mmengine - INFO - Epoch(train) [1063][25/63] lr: 9.9368e-04 eta: 2:44:54 time: 0.8246 data_time: 0.0272 memory: 16201 loss_prob: 0.3248 loss_thr: 0.2361 loss_db: 0.0593 loss: 0.6202 2022/08/30 21:36:15 - mmengine - INFO - Epoch(train) [1063][30/63] lr: 9.9368e-04 eta: 2:44:42 time: 0.7868 data_time: 0.0246 memory: 16201 loss_prob: 0.3267 loss_thr: 0.2353 loss_db: 0.0599 loss: 0.6219 2022/08/30 21:36:19 - mmengine - INFO - Epoch(train) [1063][35/63] lr: 9.9368e-04 eta: 2:44:42 time: 0.7987 data_time: 0.0317 memory: 16201 loss_prob: 0.3208 loss_thr: 0.2226 loss_db: 0.0574 loss: 0.6008 2022/08/30 21:36:23 - mmengine - INFO - Epoch(train) [1063][40/63] lr: 9.9368e-04 eta: 2:44:31 time: 0.8113 data_time: 0.0293 memory: 16201 loss_prob: 0.2972 loss_thr: 0.2188 loss_db: 0.0521 loss: 0.5681 2022/08/30 21:36:27 - mmengine - INFO - Epoch(train) [1063][45/63] lr: 9.9368e-04 eta: 2:44:31 time: 0.7965 data_time: 0.0213 memory: 16201 loss_prob: 0.3111 loss_thr: 0.2285 loss_db: 0.0550 loss: 0.5945 2022/08/30 21:36:31 - mmengine - INFO - Epoch(train) [1063][50/63] lr: 9.9368e-04 eta: 2:44:19 time: 0.8055 data_time: 0.0264 memory: 16201 loss_prob: 0.3384 loss_thr: 0.2357 loss_db: 0.0604 loss: 0.6345 2022/08/30 21:36:35 - mmengine - INFO - Epoch(train) [1063][55/63] lr: 9.9368e-04 eta: 2:44:19 time: 0.8119 data_time: 0.0284 memory: 16201 loss_prob: 0.3568 loss_thr: 0.2456 loss_db: 0.0631 loss: 0.6655 2022/08/30 21:36:39 - mmengine - INFO - Epoch(train) [1063][60/63] lr: 9.9368e-04 eta: 2:44:07 time: 0.7973 data_time: 0.0262 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2445 loss_db: 0.0647 loss: 0.6745 2022/08/30 21:36:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:36:47 - mmengine - INFO - Epoch(train) [1064][5/63] lr: 9.8715e-04 eta: 2:44:07 time: 0.9330 data_time: 0.1937 memory: 16201 loss_prob: 0.3407 loss_thr: 0.2409 loss_db: 0.0591 loss: 0.6407 2022/08/30 21:36:51 - mmengine - INFO - Epoch(train) [1064][10/63] lr: 9.8715e-04 eta: 2:43:51 time: 0.9859 data_time: 0.2090 memory: 16201 loss_prob: 0.3597 loss_thr: 0.2522 loss_db: 0.0635 loss: 0.6754 2022/08/30 21:36:55 - mmengine - INFO - Epoch(train) [1064][15/63] lr: 9.8715e-04 eta: 2:43:51 time: 0.8473 data_time: 0.0260 memory: 16201 loss_prob: 0.3382 loss_thr: 0.2409 loss_db: 0.0617 loss: 0.6408 2022/08/30 21:36:59 - mmengine - INFO - Epoch(train) [1064][20/63] lr: 9.8715e-04 eta: 2:43:40 time: 0.8494 data_time: 0.0220 memory: 16201 loss_prob: 0.3183 loss_thr: 0.2264 loss_db: 0.0577 loss: 0.6024 2022/08/30 21:37:03 - mmengine - INFO - Epoch(train) [1064][25/63] lr: 9.8715e-04 eta: 2:43:40 time: 0.8004 data_time: 0.0320 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2434 loss_db: 0.0622 loss: 0.6643 2022/08/30 21:37:07 - mmengine - INFO - Epoch(train) [1064][30/63] lr: 9.8715e-04 eta: 2:43:28 time: 0.8001 data_time: 0.0233 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2278 loss_db: 0.0569 loss: 0.6093 2022/08/30 21:37:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:37:11 - mmengine - INFO - Epoch(train) [1064][35/63] lr: 9.8715e-04 eta: 2:43:28 time: 0.8176 data_time: 0.0204 memory: 16201 loss_prob: 0.2778 loss_thr: 0.2078 loss_db: 0.0502 loss: 0.5357 2022/08/30 21:37:15 - mmengine - INFO - Epoch(train) [1064][40/63] lr: 9.8715e-04 eta: 2:43:16 time: 0.8194 data_time: 0.0262 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2169 loss_db: 0.0563 loss: 0.5830 2022/08/30 21:37:19 - mmengine - INFO - Epoch(train) [1064][45/63] lr: 9.8715e-04 eta: 2:43:16 time: 0.8027 data_time: 0.0244 memory: 16201 loss_prob: 0.3077 loss_thr: 0.2168 loss_db: 0.0558 loss: 0.5802 2022/08/30 21:37:24 - mmengine - INFO - Epoch(train) [1064][50/63] lr: 9.8715e-04 eta: 2:43:04 time: 0.8931 data_time: 0.0671 memory: 16201 loss_prob: 0.2823 loss_thr: 0.2050 loss_db: 0.0505 loss: 0.5377 2022/08/30 21:37:28 - mmengine - INFO - Epoch(train) [1064][55/63] lr: 9.8715e-04 eta: 2:43:04 time: 0.9170 data_time: 0.0760 memory: 16201 loss_prob: 0.3017 loss_thr: 0.2125 loss_db: 0.0536 loss: 0.5678 2022/08/30 21:37:33 - mmengine - INFO - Epoch(train) [1064][60/63] lr: 9.8715e-04 eta: 2:42:53 time: 0.8257 data_time: 0.0308 memory: 16201 loss_prob: 0.3395 loss_thr: 0.2346 loss_db: 0.0609 loss: 0.6349 2022/08/30 21:37:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:37:41 - mmengine - INFO - Epoch(train) [1065][5/63] lr: 9.8062e-04 eta: 2:42:53 time: 0.9636 data_time: 0.2005 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2268 loss_db: 0.0578 loss: 0.6095 2022/08/30 21:37:44 - mmengine - INFO - Epoch(train) [1065][10/63] lr: 9.8062e-04 eta: 2:42:37 time: 0.9867 data_time: 0.2115 memory: 16201 loss_prob: 0.3268 loss_thr: 0.2284 loss_db: 0.0566 loss: 0.6118 2022/08/30 21:37:48 - mmengine - INFO - Epoch(train) [1065][15/63] lr: 9.8062e-04 eta: 2:42:37 time: 0.7938 data_time: 0.0242 memory: 16201 loss_prob: 0.3258 loss_thr: 0.2329 loss_db: 0.0578 loss: 0.6165 2022/08/30 21:37:53 - mmengine - INFO - Epoch(train) [1065][20/63] lr: 9.8062e-04 eta: 2:42:25 time: 0.8069 data_time: 0.0193 memory: 16201 loss_prob: 0.3040 loss_thr: 0.2306 loss_db: 0.0556 loss: 0.5902 2022/08/30 21:37:57 - mmengine - INFO - Epoch(train) [1065][25/63] lr: 9.8062e-04 eta: 2:42:25 time: 0.8053 data_time: 0.0309 memory: 16201 loss_prob: 0.2975 loss_thr: 0.2224 loss_db: 0.0540 loss: 0.5739 2022/08/30 21:38:00 - mmengine - INFO - Epoch(train) [1065][30/63] lr: 9.8062e-04 eta: 2:42:13 time: 0.7934 data_time: 0.0260 memory: 16201 loss_prob: 0.3181 loss_thr: 0.2308 loss_db: 0.0571 loss: 0.6061 2022/08/30 21:38:04 - mmengine - INFO - Epoch(train) [1065][35/63] lr: 9.8062e-04 eta: 2:42:13 time: 0.7919 data_time: 0.0172 memory: 16201 loss_prob: 0.3408 loss_thr: 0.2442 loss_db: 0.0592 loss: 0.6442 2022/08/30 21:38:08 - mmengine - INFO - Epoch(train) [1065][40/63] lr: 9.8062e-04 eta: 2:42:02 time: 0.7871 data_time: 0.0257 memory: 16201 loss_prob: 0.3361 loss_thr: 0.2492 loss_db: 0.0589 loss: 0.6442 2022/08/30 21:38:12 - mmengine - INFO - Epoch(train) [1065][45/63] lr: 9.8062e-04 eta: 2:42:02 time: 0.7852 data_time: 0.0258 memory: 16201 loss_prob: 0.3250 loss_thr: 0.2414 loss_db: 0.0578 loss: 0.6242 2022/08/30 21:38:16 - mmengine - INFO - Epoch(train) [1065][50/63] lr: 9.8062e-04 eta: 2:41:50 time: 0.7962 data_time: 0.0281 memory: 16201 loss_prob: 0.3250 loss_thr: 0.2268 loss_db: 0.0575 loss: 0.6093 2022/08/30 21:38:20 - mmengine - INFO - Epoch(train) [1065][55/63] lr: 9.8062e-04 eta: 2:41:50 time: 0.7963 data_time: 0.0314 memory: 16201 loss_prob: 0.3280 loss_thr: 0.2225 loss_db: 0.0596 loss: 0.6101 2022/08/30 21:38:25 - mmengine - INFO - Epoch(train) [1065][60/63] lr: 9.8062e-04 eta: 2:41:38 time: 0.8877 data_time: 0.0264 memory: 16201 loss_prob: 0.3141 loss_thr: 0.2202 loss_db: 0.0565 loss: 0.5907 2022/08/30 21:38:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:38:33 - mmengine - INFO - Epoch(train) [1066][5/63] lr: 9.7408e-04 eta: 2:41:38 time: 0.9600 data_time: 0.2030 memory: 16201 loss_prob: 0.3119 loss_thr: 0.2094 loss_db: 0.0526 loss: 0.5740 2022/08/30 21:38:37 - mmengine - INFO - Epoch(train) [1066][10/63] lr: 9.7408e-04 eta: 2:41:23 time: 1.0102 data_time: 0.2322 memory: 16201 loss_prob: 0.3376 loss_thr: 0.2306 loss_db: 0.0575 loss: 0.6257 2022/08/30 21:38:41 - mmengine - INFO - Epoch(train) [1066][15/63] lr: 9.7408e-04 eta: 2:41:23 time: 0.8082 data_time: 0.0473 memory: 16201 loss_prob: 0.3381 loss_thr: 0.2508 loss_db: 0.0596 loss: 0.6485 2022/08/30 21:38:45 - mmengine - INFO - Epoch(train) [1066][20/63] lr: 9.7408e-04 eta: 2:41:11 time: 0.8159 data_time: 0.0181 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2519 loss_db: 0.0579 loss: 0.6387 2022/08/30 21:38:49 - mmengine - INFO - Epoch(train) [1066][25/63] lr: 9.7408e-04 eta: 2:41:11 time: 0.8261 data_time: 0.0320 memory: 16201 loss_prob: 0.3430 loss_thr: 0.2597 loss_db: 0.0599 loss: 0.6626 2022/08/30 21:38:53 - mmengine - INFO - Epoch(train) [1066][30/63] lr: 9.7408e-04 eta: 2:40:59 time: 0.7847 data_time: 0.0256 memory: 16201 loss_prob: 0.3316 loss_thr: 0.2423 loss_db: 0.0589 loss: 0.6328 2022/08/30 21:38:57 - mmengine - INFO - Epoch(train) [1066][35/63] lr: 9.7408e-04 eta: 2:40:59 time: 0.7762 data_time: 0.0179 memory: 16201 loss_prob: 0.3113 loss_thr: 0.2244 loss_db: 0.0575 loss: 0.5932 2022/08/30 21:39:01 - mmengine - INFO - Epoch(train) [1066][40/63] lr: 9.7408e-04 eta: 2:40:47 time: 0.7836 data_time: 0.0236 memory: 16201 loss_prob: 0.3653 loss_thr: 0.2513 loss_db: 0.0633 loss: 0.6799 2022/08/30 21:39:05 - mmengine - INFO - Epoch(train) [1066][45/63] lr: 9.7408e-04 eta: 2:40:47 time: 0.7885 data_time: 0.0245 memory: 16201 loss_prob: 0.3707 loss_thr: 0.2489 loss_db: 0.0640 loss: 0.6836 2022/08/30 21:39:09 - mmengine - INFO - Epoch(train) [1066][50/63] lr: 9.7408e-04 eta: 2:40:35 time: 0.8067 data_time: 0.0284 memory: 16201 loss_prob: 0.3514 loss_thr: 0.2389 loss_db: 0.0629 loss: 0.6532 2022/08/30 21:39:14 - mmengine - INFO - Epoch(train) [1066][55/63] lr: 9.7408e-04 eta: 2:40:35 time: 0.8725 data_time: 0.0269 memory: 16201 loss_prob: 0.3443 loss_thr: 0.2397 loss_db: 0.0604 loss: 0.6444 2022/08/30 21:39:18 - mmengine - INFO - Epoch(train) [1066][60/63] lr: 9.7408e-04 eta: 2:40:24 time: 0.8610 data_time: 0.0298 memory: 16201 loss_prob: 0.3406 loss_thr: 0.2482 loss_db: 0.0604 loss: 0.6491 2022/08/30 21:39:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:39:26 - mmengine - INFO - Epoch(train) [1067][5/63] lr: 9.6753e-04 eta: 2:40:24 time: 0.9199 data_time: 0.1824 memory: 16201 loss_prob: 0.3487 loss_thr: 0.2452 loss_db: 0.0606 loss: 0.6545 2022/08/30 21:39:29 - mmengine - INFO - Epoch(train) [1067][10/63] lr: 9.6753e-04 eta: 2:40:08 time: 0.9639 data_time: 0.1939 memory: 16201 loss_prob: 0.3863 loss_thr: 0.2466 loss_db: 0.0659 loss: 0.6988 2022/08/30 21:39:33 - mmengine - INFO - Epoch(train) [1067][15/63] lr: 9.6753e-04 eta: 2:40:08 time: 0.7864 data_time: 0.0283 memory: 16201 loss_prob: 0.3691 loss_thr: 0.2439 loss_db: 0.0644 loss: 0.6775 2022/08/30 21:39:37 - mmengine - INFO - Epoch(train) [1067][20/63] lr: 9.6753e-04 eta: 2:39:56 time: 0.7912 data_time: 0.0228 memory: 16201 loss_prob: 0.3512 loss_thr: 0.2443 loss_db: 0.0622 loss: 0.6577 2022/08/30 21:39:41 - mmengine - INFO - Epoch(train) [1067][25/63] lr: 9.6753e-04 eta: 2:39:56 time: 0.7985 data_time: 0.0272 memory: 16201 loss_prob: 0.3608 loss_thr: 0.2515 loss_db: 0.0633 loss: 0.6756 2022/08/30 21:39:45 - mmengine - INFO - Epoch(train) [1067][30/63] lr: 9.6753e-04 eta: 2:39:44 time: 0.8029 data_time: 0.0235 memory: 16201 loss_prob: 0.3556 loss_thr: 0.2576 loss_db: 0.0617 loss: 0.6749 2022/08/30 21:39:49 - mmengine - INFO - Epoch(train) [1067][35/63] lr: 9.6753e-04 eta: 2:39:44 time: 0.7900 data_time: 0.0204 memory: 16201 loss_prob: 0.3445 loss_thr: 0.2499 loss_db: 0.0589 loss: 0.6532 2022/08/30 21:39:53 - mmengine - INFO - Epoch(train) [1067][40/63] lr: 9.6753e-04 eta: 2:39:33 time: 0.8077 data_time: 0.0236 memory: 16201 loss_prob: 0.3409 loss_thr: 0.2400 loss_db: 0.0600 loss: 0.6409 2022/08/30 21:39:58 - mmengine - INFO - Epoch(train) [1067][45/63] lr: 9.6753e-04 eta: 2:39:33 time: 0.8186 data_time: 0.0279 memory: 16201 loss_prob: 0.3279 loss_thr: 0.2463 loss_db: 0.0605 loss: 0.6347 2022/08/30 21:40:01 - mmengine - INFO - Epoch(train) [1067][50/63] lr: 9.6753e-04 eta: 2:39:21 time: 0.7995 data_time: 0.0326 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2402 loss_db: 0.0612 loss: 0.6378 2022/08/30 21:40:06 - mmengine - INFO - Epoch(train) [1067][55/63] lr: 9.6753e-04 eta: 2:39:21 time: 0.8100 data_time: 0.0315 memory: 16201 loss_prob: 0.3319 loss_thr: 0.2265 loss_db: 0.0583 loss: 0.6167 2022/08/30 21:40:10 - mmengine - INFO - Epoch(train) [1067][60/63] lr: 9.6753e-04 eta: 2:39:09 time: 0.8026 data_time: 0.0268 memory: 16201 loss_prob: 0.3191 loss_thr: 0.2244 loss_db: 0.0551 loss: 0.5987 2022/08/30 21:40:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:40:18 - mmengine - INFO - Epoch(train) [1068][5/63] lr: 9.6098e-04 eta: 2:39:09 time: 0.9570 data_time: 0.1962 memory: 16201 loss_prob: 0.2966 loss_thr: 0.2183 loss_db: 0.0526 loss: 0.5676 2022/08/30 21:40:22 - mmengine - INFO - Epoch(train) [1068][10/63] lr: 9.6098e-04 eta: 2:38:54 time: 0.9871 data_time: 0.2059 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2429 loss_db: 0.0610 loss: 0.6402 2022/08/30 21:40:26 - mmengine - INFO - Epoch(train) [1068][15/63] lr: 9.6098e-04 eta: 2:38:54 time: 0.8071 data_time: 0.0230 memory: 16201 loss_prob: 0.3350 loss_thr: 0.2373 loss_db: 0.0597 loss: 0.6320 2022/08/30 21:40:30 - mmengine - INFO - Epoch(train) [1068][20/63] lr: 9.6098e-04 eta: 2:38:42 time: 0.8008 data_time: 0.0170 memory: 16201 loss_prob: 0.2926 loss_thr: 0.2052 loss_db: 0.0529 loss: 0.5508 2022/08/30 21:40:34 - mmengine - INFO - Epoch(train) [1068][25/63] lr: 9.6098e-04 eta: 2:38:42 time: 0.8001 data_time: 0.0273 memory: 16201 loss_prob: 0.3190 loss_thr: 0.2152 loss_db: 0.0573 loss: 0.5915 2022/08/30 21:40:38 - mmengine - INFO - Epoch(train) [1068][30/63] lr: 9.6098e-04 eta: 2:38:30 time: 0.8082 data_time: 0.0262 memory: 16201 loss_prob: 0.3499 loss_thr: 0.2440 loss_db: 0.0616 loss: 0.6555 2022/08/30 21:40:41 - mmengine - INFO - Epoch(train) [1068][35/63] lr: 9.6098e-04 eta: 2:38:30 time: 0.7866 data_time: 0.0200 memory: 16201 loss_prob: 0.3557 loss_thr: 0.2460 loss_db: 0.0632 loss: 0.6649 2022/08/30 21:40:45 - mmengine - INFO - Epoch(train) [1068][40/63] lr: 9.6098e-04 eta: 2:38:18 time: 0.7850 data_time: 0.0252 memory: 16201 loss_prob: 0.3262 loss_thr: 0.2259 loss_db: 0.0591 loss: 0.6112 2022/08/30 21:40:50 - mmengine - INFO - Epoch(train) [1068][45/63] lr: 9.6098e-04 eta: 2:38:18 time: 0.8024 data_time: 0.0303 memory: 16201 loss_prob: 0.3226 loss_thr: 0.2282 loss_db: 0.0579 loss: 0.6087 2022/08/30 21:40:53 - mmengine - INFO - Epoch(train) [1068][50/63] lr: 9.6098e-04 eta: 2:38:06 time: 0.7912 data_time: 0.0253 memory: 16201 loss_prob: 0.3236 loss_thr: 0.2268 loss_db: 0.0567 loss: 0.6070 2022/08/30 21:40:57 - mmengine - INFO - Epoch(train) [1068][55/63] lr: 9.6098e-04 eta: 2:38:06 time: 0.7893 data_time: 0.0238 memory: 16201 loss_prob: 0.3234 loss_thr: 0.2293 loss_db: 0.0579 loss: 0.6106 2022/08/30 21:41:01 - mmengine - INFO - Epoch(train) [1068][60/63] lr: 9.6098e-04 eta: 2:37:54 time: 0.7992 data_time: 0.0239 memory: 16201 loss_prob: 0.3253 loss_thr: 0.2311 loss_db: 0.0584 loss: 0.6148 2022/08/30 21:41:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:41:09 - mmengine - INFO - Epoch(train) [1069][5/63] lr: 9.5443e-04 eta: 2:37:54 time: 0.9282 data_time: 0.1756 memory: 16201 loss_prob: 0.3348 loss_thr: 0.2439 loss_db: 0.0584 loss: 0.6371 2022/08/30 21:41:13 - mmengine - INFO - Epoch(train) [1069][10/63] lr: 9.5443e-04 eta: 2:37:39 time: 0.9771 data_time: 0.1889 memory: 16201 loss_prob: 0.3450 loss_thr: 0.2460 loss_db: 0.0606 loss: 0.6516 2022/08/30 21:41:17 - mmengine - INFO - Epoch(train) [1069][15/63] lr: 9.5443e-04 eta: 2:37:39 time: 0.7972 data_time: 0.0264 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2450 loss_db: 0.0615 loss: 0.6505 2022/08/30 21:41:21 - mmengine - INFO - Epoch(train) [1069][20/63] lr: 9.5443e-04 eta: 2:37:27 time: 0.7907 data_time: 0.0211 memory: 16201 loss_prob: 0.3413 loss_thr: 0.2451 loss_db: 0.0620 loss: 0.6484 2022/08/30 21:41:25 - mmengine - INFO - Epoch(train) [1069][25/63] lr: 9.5443e-04 eta: 2:37:27 time: 0.7958 data_time: 0.0267 memory: 16201 loss_prob: 0.3686 loss_thr: 0.2578 loss_db: 0.0656 loss: 0.6920 2022/08/30 21:41:29 - mmengine - INFO - Epoch(train) [1069][30/63] lr: 9.5443e-04 eta: 2:37:15 time: 0.7938 data_time: 0.0254 memory: 16201 loss_prob: 0.3671 loss_thr: 0.2545 loss_db: 0.0647 loss: 0.6863 2022/08/30 21:41:33 - mmengine - INFO - Epoch(train) [1069][35/63] lr: 9.5443e-04 eta: 2:37:15 time: 0.7874 data_time: 0.0270 memory: 16201 loss_prob: 0.2991 loss_thr: 0.2202 loss_db: 0.0545 loss: 0.5739 2022/08/30 21:41:37 - mmengine - INFO - Epoch(train) [1069][40/63] lr: 9.5443e-04 eta: 2:37:04 time: 0.7915 data_time: 0.0252 memory: 16201 loss_prob: 0.2879 loss_thr: 0.2136 loss_db: 0.0538 loss: 0.5553 2022/08/30 21:41:41 - mmengine - INFO - Epoch(train) [1069][45/63] lr: 9.5443e-04 eta: 2:37:04 time: 0.8020 data_time: 0.0266 memory: 16201 loss_prob: 0.3132 loss_thr: 0.2274 loss_db: 0.0558 loss: 0.5964 2022/08/30 21:41:45 - mmengine - INFO - Epoch(train) [1069][50/63] lr: 9.5443e-04 eta: 2:36:52 time: 0.7880 data_time: 0.0248 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2443 loss_db: 0.0573 loss: 0.6305 2022/08/30 21:41:49 - mmengine - INFO - Epoch(train) [1069][55/63] lr: 9.5443e-04 eta: 2:36:52 time: 0.7866 data_time: 0.0243 memory: 16201 loss_prob: 0.3429 loss_thr: 0.2427 loss_db: 0.0614 loss: 0.6471 2022/08/30 21:41:53 - mmengine - INFO - Epoch(train) [1069][60/63] lr: 9.5443e-04 eta: 2:36:40 time: 0.7967 data_time: 0.0250 memory: 16201 loss_prob: 0.3645 loss_thr: 0.2423 loss_db: 0.0646 loss: 0.6714 2022/08/30 21:41:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:42:01 - mmengine - INFO - Epoch(train) [1070][5/63] lr: 9.4787e-04 eta: 2:36:40 time: 0.9997 data_time: 0.2035 memory: 16201 loss_prob: 0.3311 loss_thr: 0.2304 loss_db: 0.0592 loss: 0.6207 2022/08/30 21:42:05 - mmengine - INFO - Epoch(train) [1070][10/63] lr: 9.4787e-04 eta: 2:36:25 time: 0.9772 data_time: 0.2125 memory: 16201 loss_prob: 0.3294 loss_thr: 0.2321 loss_db: 0.0581 loss: 0.6196 2022/08/30 21:42:09 - mmengine - INFO - Epoch(train) [1070][15/63] lr: 9.4787e-04 eta: 2:36:25 time: 0.7860 data_time: 0.0268 memory: 16201 loss_prob: 0.3261 loss_thr: 0.2343 loss_db: 0.0573 loss: 0.6177 2022/08/30 21:42:13 - mmengine - INFO - Epoch(train) [1070][20/63] lr: 9.4787e-04 eta: 2:36:13 time: 0.7882 data_time: 0.0173 memory: 16201 loss_prob: 0.3077 loss_thr: 0.2231 loss_db: 0.0551 loss: 0.5859 2022/08/30 21:42:17 - mmengine - INFO - Epoch(train) [1070][25/63] lr: 9.4787e-04 eta: 2:36:13 time: 0.8025 data_time: 0.0279 memory: 16201 loss_prob: 0.2999 loss_thr: 0.2118 loss_db: 0.0540 loss: 0.5658 2022/08/30 21:42:21 - mmengine - INFO - Epoch(train) [1070][30/63] lr: 9.4787e-04 eta: 2:36:01 time: 0.7928 data_time: 0.0220 memory: 16201 loss_prob: 0.3197 loss_thr: 0.2224 loss_db: 0.0573 loss: 0.5993 2022/08/30 21:42:25 - mmengine - INFO - Epoch(train) [1070][35/63] lr: 9.4787e-04 eta: 2:36:01 time: 0.7858 data_time: 0.0196 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2402 loss_db: 0.0585 loss: 0.6286 2022/08/30 21:42:29 - mmengine - INFO - Epoch(train) [1070][40/63] lr: 9.4787e-04 eta: 2:35:49 time: 0.8555 data_time: 0.0427 memory: 16201 loss_prob: 0.3205 loss_thr: 0.2344 loss_db: 0.0569 loss: 0.6117 2022/08/30 21:42:33 - mmengine - INFO - Epoch(train) [1070][45/63] lr: 9.4787e-04 eta: 2:35:49 time: 0.8580 data_time: 0.0398 memory: 16201 loss_prob: 0.3252 loss_thr: 0.2271 loss_db: 0.0577 loss: 0.6100 2022/08/30 21:42:37 - mmengine - INFO - Epoch(train) [1070][50/63] lr: 9.4787e-04 eta: 2:35:37 time: 0.7845 data_time: 0.0247 memory: 16201 loss_prob: 0.3499 loss_thr: 0.2372 loss_db: 0.0618 loss: 0.6488 2022/08/30 21:42:41 - mmengine - INFO - Epoch(train) [1070][55/63] lr: 9.4787e-04 eta: 2:35:37 time: 0.7767 data_time: 0.0247 memory: 16201 loss_prob: 0.3424 loss_thr: 0.2362 loss_db: 0.0608 loss: 0.6394 2022/08/30 21:42:45 - mmengine - INFO - Epoch(train) [1070][60/63] lr: 9.4787e-04 eta: 2:35:26 time: 0.7816 data_time: 0.0219 memory: 16201 loss_prob: 0.3196 loss_thr: 0.2290 loss_db: 0.0570 loss: 0.6055 2022/08/30 21:42:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:42:53 - mmengine - INFO - Epoch(train) [1071][5/63] lr: 9.4131e-04 eta: 2:35:26 time: 0.9238 data_time: 0.1556 memory: 16201 loss_prob: 0.3625 loss_thr: 0.2634 loss_db: 0.0646 loss: 0.6905 2022/08/30 21:42:57 - mmengine - INFO - Epoch(train) [1071][10/63] lr: 9.4131e-04 eta: 2:35:10 time: 0.9265 data_time: 0.1555 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2495 loss_db: 0.0593 loss: 0.6441 2022/08/30 21:43:01 - mmengine - INFO - Epoch(train) [1071][15/63] lr: 9.4131e-04 eta: 2:35:10 time: 0.7892 data_time: 0.0221 memory: 16201 loss_prob: 0.3244 loss_thr: 0.2351 loss_db: 0.0578 loss: 0.6173 2022/08/30 21:43:05 - mmengine - INFO - Epoch(train) [1071][20/63] lr: 9.4131e-04 eta: 2:34:58 time: 0.8462 data_time: 0.0225 memory: 16201 loss_prob: 0.2813 loss_thr: 0.2109 loss_db: 0.0497 loss: 0.5419 2022/08/30 21:43:09 - mmengine - INFO - Epoch(train) [1071][25/63] lr: 9.4131e-04 eta: 2:34:58 time: 0.8617 data_time: 0.0330 memory: 16201 loss_prob: 0.2982 loss_thr: 0.2248 loss_db: 0.0527 loss: 0.5757 2022/08/30 21:43:13 - mmengine - INFO - Epoch(train) [1071][30/63] lr: 9.4131e-04 eta: 2:34:47 time: 0.8068 data_time: 0.0308 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2419 loss_db: 0.0589 loss: 0.6311 2022/08/30 21:43:17 - mmengine - INFO - Epoch(train) [1071][35/63] lr: 9.4131e-04 eta: 2:34:47 time: 0.7990 data_time: 0.0266 memory: 16201 loss_prob: 0.3206 loss_thr: 0.2326 loss_db: 0.0579 loss: 0.6111 2022/08/30 21:43:21 - mmengine - INFO - Epoch(train) [1071][40/63] lr: 9.4131e-04 eta: 2:34:35 time: 0.7933 data_time: 0.0233 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2336 loss_db: 0.0604 loss: 0.6265 2022/08/30 21:43:25 - mmengine - INFO - Epoch(train) [1071][45/63] lr: 9.4131e-04 eta: 2:34:35 time: 0.7832 data_time: 0.0233 memory: 16201 loss_prob: 0.3428 loss_thr: 0.2320 loss_db: 0.0612 loss: 0.6359 2022/08/30 21:43:30 - mmengine - INFO - Epoch(train) [1071][50/63] lr: 9.4131e-04 eta: 2:34:23 time: 0.8308 data_time: 0.0263 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2440 loss_db: 0.0597 loss: 0.6458 2022/08/30 21:43:33 - mmengine - INFO - Epoch(train) [1071][55/63] lr: 9.4131e-04 eta: 2:34:23 time: 0.8277 data_time: 0.0255 memory: 16201 loss_prob: 0.3192 loss_thr: 0.2449 loss_db: 0.0569 loss: 0.6210 2022/08/30 21:43:37 - mmengine - INFO - Epoch(train) [1071][60/63] lr: 9.4131e-04 eta: 2:34:11 time: 0.7854 data_time: 0.0262 memory: 16201 loss_prob: 0.2890 loss_thr: 0.2208 loss_db: 0.0534 loss: 0.5632 2022/08/30 21:43:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:43:45 - mmengine - INFO - Epoch(train) [1072][5/63] lr: 9.3474e-04 eta: 2:34:11 time: 0.8682 data_time: 0.1552 memory: 16201 loss_prob: 0.3733 loss_thr: 0.2474 loss_db: 0.0630 loss: 0.6837 2022/08/30 21:43:49 - mmengine - INFO - Epoch(train) [1072][10/63] lr: 9.3474e-04 eta: 2:33:56 time: 0.9253 data_time: 0.1635 memory: 16201 loss_prob: 0.3420 loss_thr: 0.2372 loss_db: 0.0615 loss: 0.6408 2022/08/30 21:43:52 - mmengine - INFO - Epoch(train) [1072][15/63] lr: 9.3474e-04 eta: 2:33:56 time: 0.7840 data_time: 0.0227 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2416 loss_db: 0.0631 loss: 0.6487 2022/08/30 21:43:57 - mmengine - INFO - Epoch(train) [1072][20/63] lr: 9.3474e-04 eta: 2:33:44 time: 0.7913 data_time: 0.0227 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2363 loss_db: 0.0598 loss: 0.6328 2022/08/30 21:44:00 - mmengine - INFO - Epoch(train) [1072][25/63] lr: 9.3474e-04 eta: 2:33:44 time: 0.7988 data_time: 0.0254 memory: 16201 loss_prob: 0.2865 loss_thr: 0.2104 loss_db: 0.0505 loss: 0.5474 2022/08/30 21:44:04 - mmengine - INFO - Epoch(train) [1072][30/63] lr: 9.3474e-04 eta: 2:33:32 time: 0.7732 data_time: 0.0228 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2349 loss_db: 0.0580 loss: 0.6150 2022/08/30 21:44:08 - mmengine - INFO - Epoch(train) [1072][35/63] lr: 9.3474e-04 eta: 2:33:32 time: 0.7722 data_time: 0.0255 memory: 16201 loss_prob: 0.3502 loss_thr: 0.2515 loss_db: 0.0632 loss: 0.6650 2022/08/30 21:44:12 - mmengine - INFO - Epoch(train) [1072][40/63] lr: 9.3474e-04 eta: 2:33:20 time: 0.8118 data_time: 0.0267 memory: 16201 loss_prob: 0.3136 loss_thr: 0.2261 loss_db: 0.0555 loss: 0.5952 2022/08/30 21:44:16 - mmengine - INFO - Epoch(train) [1072][45/63] lr: 9.3474e-04 eta: 2:33:20 time: 0.8239 data_time: 0.0263 memory: 16201 loss_prob: 0.3098 loss_thr: 0.2215 loss_db: 0.0540 loss: 0.5853 2022/08/30 21:44:20 - mmengine - INFO - Epoch(train) [1072][50/63] lr: 9.3474e-04 eta: 2:33:09 time: 0.7843 data_time: 0.0220 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2190 loss_db: 0.0566 loss: 0.5923 2022/08/30 21:44:25 - mmengine - INFO - Epoch(train) [1072][55/63] lr: 9.3474e-04 eta: 2:33:09 time: 0.8117 data_time: 0.0231 memory: 16201 loss_prob: 0.3053 loss_thr: 0.2110 loss_db: 0.0564 loss: 0.5727 2022/08/30 21:44:29 - mmengine - INFO - Epoch(train) [1072][60/63] lr: 9.3474e-04 eta: 2:32:57 time: 0.8343 data_time: 0.0295 memory: 16201 loss_prob: 0.3238 loss_thr: 0.2329 loss_db: 0.0586 loss: 0.6153 2022/08/30 21:44:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:44:36 - mmengine - INFO - Epoch(train) [1073][5/63] lr: 9.2816e-04 eta: 2:32:57 time: 0.9132 data_time: 0.1761 memory: 16201 loss_prob: 0.3312 loss_thr: 0.2436 loss_db: 0.0582 loss: 0.6330 2022/08/30 21:44:40 - mmengine - INFO - Epoch(train) [1073][10/63] lr: 9.2816e-04 eta: 2:32:41 time: 0.9560 data_time: 0.1882 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2334 loss_db: 0.0580 loss: 0.6211 2022/08/30 21:44:44 - mmengine - INFO - Epoch(train) [1073][15/63] lr: 9.2816e-04 eta: 2:32:41 time: 0.7863 data_time: 0.0245 memory: 16201 loss_prob: 0.3171 loss_thr: 0.2331 loss_db: 0.0560 loss: 0.6063 2022/08/30 21:44:49 - mmengine - INFO - Epoch(train) [1073][20/63] lr: 9.2816e-04 eta: 2:32:30 time: 0.8533 data_time: 0.0165 memory: 16201 loss_prob: 0.3016 loss_thr: 0.2222 loss_db: 0.0551 loss: 0.5789 2022/08/30 21:44:53 - mmengine - INFO - Epoch(train) [1073][25/63] lr: 9.2816e-04 eta: 2:32:30 time: 0.8655 data_time: 0.0312 memory: 16201 loss_prob: 0.2890 loss_thr: 0.2147 loss_db: 0.0539 loss: 0.5576 2022/08/30 21:44:56 - mmengine - INFO - Epoch(train) [1073][30/63] lr: 9.2816e-04 eta: 2:32:18 time: 0.7753 data_time: 0.0245 memory: 16201 loss_prob: 0.3227 loss_thr: 0.2332 loss_db: 0.0576 loss: 0.6135 2022/08/30 21:45:00 - mmengine - INFO - Epoch(train) [1073][35/63] lr: 9.2816e-04 eta: 2:32:18 time: 0.7756 data_time: 0.0201 memory: 16201 loss_prob: 0.3507 loss_thr: 0.2487 loss_db: 0.0604 loss: 0.6599 2022/08/30 21:45:05 - mmengine - INFO - Epoch(train) [1073][40/63] lr: 9.2816e-04 eta: 2:32:06 time: 0.8048 data_time: 0.0258 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2319 loss_db: 0.0569 loss: 0.6114 2022/08/30 21:45:08 - mmengine - INFO - Epoch(train) [1073][45/63] lr: 9.2816e-04 eta: 2:32:06 time: 0.8031 data_time: 0.0248 memory: 16201 loss_prob: 0.3046 loss_thr: 0.2082 loss_db: 0.0549 loss: 0.5676 2022/08/30 21:45:12 - mmengine - INFO - Epoch(train) [1073][50/63] lr: 9.2816e-04 eta: 2:31:54 time: 0.7900 data_time: 0.0268 memory: 16201 loss_prob: 0.3442 loss_thr: 0.2310 loss_db: 0.0605 loss: 0.6357 2022/08/30 21:45:16 - mmengine - INFO - Epoch(train) [1073][55/63] lr: 9.2816e-04 eta: 2:31:54 time: 0.7985 data_time: 0.0253 memory: 16201 loss_prob: 0.3716 loss_thr: 0.2495 loss_db: 0.0664 loss: 0.6875 2022/08/30 21:45:20 - mmengine - INFO - Epoch(train) [1073][60/63] lr: 9.2816e-04 eta: 2:31:43 time: 0.7909 data_time: 0.0271 memory: 16201 loss_prob: 0.3616 loss_thr: 0.2480 loss_db: 0.0641 loss: 0.6738 2022/08/30 21:45:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:45:28 - mmengine - INFO - Epoch(train) [1074][5/63] lr: 9.2158e-04 eta: 2:31:43 time: 0.9474 data_time: 0.1997 memory: 16201 loss_prob: 0.3311 loss_thr: 0.2315 loss_db: 0.0592 loss: 0.6219 2022/08/30 21:45:32 - mmengine - INFO - Epoch(train) [1074][10/63] lr: 9.2158e-04 eta: 2:31:27 time: 1.0032 data_time: 0.2163 memory: 16201 loss_prob: 0.3552 loss_thr: 0.2469 loss_db: 0.0633 loss: 0.6654 2022/08/30 21:45:36 - mmengine - INFO - Epoch(train) [1074][15/63] lr: 9.2158e-04 eta: 2:31:27 time: 0.8016 data_time: 0.0275 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2315 loss_db: 0.0556 loss: 0.6003 2022/08/30 21:45:40 - mmengine - INFO - Epoch(train) [1074][20/63] lr: 9.2158e-04 eta: 2:31:15 time: 0.7885 data_time: 0.0193 memory: 16201 loss_prob: 0.3265 loss_thr: 0.2379 loss_db: 0.0583 loss: 0.6228 2022/08/30 21:45:44 - mmengine - INFO - Epoch(train) [1074][25/63] lr: 9.2158e-04 eta: 2:31:15 time: 0.7970 data_time: 0.0323 memory: 16201 loss_prob: 0.3508 loss_thr: 0.2463 loss_db: 0.0622 loss: 0.6594 2022/08/30 21:45:48 - mmengine - INFO - Epoch(train) [1074][30/63] lr: 9.2158e-04 eta: 2:31:04 time: 0.7903 data_time: 0.0228 memory: 16201 loss_prob: 0.3097 loss_thr: 0.2237 loss_db: 0.0543 loss: 0.5877 2022/08/30 21:45:52 - mmengine - INFO - Epoch(train) [1074][35/63] lr: 9.2158e-04 eta: 2:31:04 time: 0.7754 data_time: 0.0198 memory: 16201 loss_prob: 0.3173 loss_thr: 0.2252 loss_db: 0.0570 loss: 0.5995 2022/08/30 21:45:56 - mmengine - INFO - Epoch(train) [1074][40/63] lr: 9.2158e-04 eta: 2:30:52 time: 0.8240 data_time: 0.0303 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2390 loss_db: 0.0593 loss: 0.6222 2022/08/30 21:46:00 - mmengine - INFO - Epoch(train) [1074][45/63] lr: 9.2158e-04 eta: 2:30:52 time: 0.8282 data_time: 0.0276 memory: 16201 loss_prob: 0.3229 loss_thr: 0.2330 loss_db: 0.0572 loss: 0.6131 2022/08/30 21:46:04 - mmengine - INFO - Epoch(train) [1074][50/63] lr: 9.2158e-04 eta: 2:30:40 time: 0.7939 data_time: 0.0259 memory: 16201 loss_prob: 0.3288 loss_thr: 0.2269 loss_db: 0.0577 loss: 0.6135 2022/08/30 21:46:08 - mmengine - INFO - Epoch(train) [1074][55/63] lr: 9.2158e-04 eta: 2:30:40 time: 0.7936 data_time: 0.0244 memory: 16201 loss_prob: 0.2960 loss_thr: 0.2173 loss_db: 0.0542 loss: 0.5675 2022/08/30 21:46:12 - mmengine - INFO - Epoch(train) [1074][60/63] lr: 9.2158e-04 eta: 2:30:28 time: 0.7936 data_time: 0.0253 memory: 16201 loss_prob: 0.3206 loss_thr: 0.2344 loss_db: 0.0581 loss: 0.6131 2022/08/30 21:46:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:46:20 - mmengine - INFO - Epoch(train) [1075][5/63] lr: 9.1500e-04 eta: 2:30:28 time: 0.9196 data_time: 0.1896 memory: 16201 loss_prob: 0.3109 loss_thr: 0.2320 loss_db: 0.0559 loss: 0.5988 2022/08/30 21:46:24 - mmengine - INFO - Epoch(train) [1075][10/63] lr: 9.1500e-04 eta: 2:30:13 time: 0.9630 data_time: 0.1972 memory: 16201 loss_prob: 0.3235 loss_thr: 0.2331 loss_db: 0.0570 loss: 0.6135 2022/08/30 21:46:28 - mmengine - INFO - Epoch(train) [1075][15/63] lr: 9.1500e-04 eta: 2:30:13 time: 0.7915 data_time: 0.0258 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2504 loss_db: 0.0623 loss: 0.6713 2022/08/30 21:46:32 - mmengine - INFO - Epoch(train) [1075][20/63] lr: 9.1500e-04 eta: 2:30:01 time: 0.8028 data_time: 0.0234 memory: 16201 loss_prob: 0.3373 loss_thr: 0.2411 loss_db: 0.0598 loss: 0.6381 2022/08/30 21:46:36 - mmengine - INFO - Epoch(train) [1075][25/63] lr: 9.1500e-04 eta: 2:30:01 time: 0.8490 data_time: 0.0262 memory: 16201 loss_prob: 0.3067 loss_thr: 0.2202 loss_db: 0.0548 loss: 0.5817 2022/08/30 21:46:40 - mmengine - INFO - Epoch(train) [1075][30/63] lr: 9.1500e-04 eta: 2:29:50 time: 0.8413 data_time: 0.0252 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2400 loss_db: 0.0612 loss: 0.6447 2022/08/30 21:46:44 - mmengine - INFO - Epoch(train) [1075][35/63] lr: 9.1500e-04 eta: 2:29:50 time: 0.7681 data_time: 0.0197 memory: 16201 loss_prob: 0.3695 loss_thr: 0.2585 loss_db: 0.0651 loss: 0.6931 2022/08/30 21:46:48 - mmengine - INFO - Epoch(train) [1075][40/63] lr: 9.1500e-04 eta: 2:29:38 time: 0.7830 data_time: 0.0223 memory: 16201 loss_prob: 0.3207 loss_thr: 0.2294 loss_db: 0.0572 loss: 0.6073 2022/08/30 21:46:53 - mmengine - INFO - Epoch(train) [1075][45/63] lr: 9.1500e-04 eta: 2:29:38 time: 0.8519 data_time: 0.0276 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2230 loss_db: 0.0560 loss: 0.5905 2022/08/30 21:46:56 - mmengine - INFO - Epoch(train) [1075][50/63] lr: 9.1500e-04 eta: 2:29:26 time: 0.8291 data_time: 0.0253 memory: 16201 loss_prob: 0.3163 loss_thr: 0.2285 loss_db: 0.0567 loss: 0.6016 2022/08/30 21:47:00 - mmengine - INFO - Epoch(train) [1075][55/63] lr: 9.1500e-04 eta: 2:29:26 time: 0.7769 data_time: 0.0246 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2186 loss_db: 0.0564 loss: 0.5849 2022/08/30 21:47:04 - mmengine - INFO - Epoch(train) [1075][60/63] lr: 9.1500e-04 eta: 2:29:14 time: 0.7828 data_time: 0.0234 memory: 16201 loss_prob: 0.3134 loss_thr: 0.2336 loss_db: 0.0564 loss: 0.6034 2022/08/30 21:47:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:47:13 - mmengine - INFO - Epoch(train) [1076][5/63] lr: 9.0841e-04 eta: 2:29:14 time: 0.9800 data_time: 0.2088 memory: 16201 loss_prob: 0.3281 loss_thr: 0.2330 loss_db: 0.0565 loss: 0.6177 2022/08/30 21:47:17 - mmengine - INFO - Epoch(train) [1076][10/63] lr: 9.0841e-04 eta: 2:28:59 time: 0.9821 data_time: 0.2197 memory: 16201 loss_prob: 0.3522 loss_thr: 0.2444 loss_db: 0.0607 loss: 0.6573 2022/08/30 21:47:20 - mmengine - INFO - Epoch(train) [1076][15/63] lr: 9.0841e-04 eta: 2:28:59 time: 0.7899 data_time: 0.0241 memory: 16201 loss_prob: 0.3464 loss_thr: 0.2457 loss_db: 0.0615 loss: 0.6537 2022/08/30 21:47:24 - mmengine - INFO - Epoch(train) [1076][20/63] lr: 9.0841e-04 eta: 2:28:47 time: 0.7898 data_time: 0.0190 memory: 16201 loss_prob: 0.3093 loss_thr: 0.2261 loss_db: 0.0557 loss: 0.5912 2022/08/30 21:47:29 - mmengine - INFO - Epoch(train) [1076][25/63] lr: 9.0841e-04 eta: 2:28:47 time: 0.8036 data_time: 0.0289 memory: 16201 loss_prob: 0.3101 loss_thr: 0.2223 loss_db: 0.0557 loss: 0.5881 2022/08/30 21:47:32 - mmengine - INFO - Epoch(train) [1076][30/63] lr: 9.0841e-04 eta: 2:28:35 time: 0.7985 data_time: 0.0261 memory: 16201 loss_prob: 0.3272 loss_thr: 0.2266 loss_db: 0.0577 loss: 0.6115 2022/08/30 21:47:37 - mmengine - INFO - Epoch(train) [1076][35/63] lr: 9.0841e-04 eta: 2:28:35 time: 0.8134 data_time: 0.0260 memory: 16201 loss_prob: 0.3017 loss_thr: 0.2208 loss_db: 0.0539 loss: 0.5764 2022/08/30 21:47:41 - mmengine - INFO - Epoch(train) [1076][40/63] lr: 9.0841e-04 eta: 2:28:24 time: 0.8226 data_time: 0.0251 memory: 16201 loss_prob: 0.2842 loss_thr: 0.2209 loss_db: 0.0518 loss: 0.5569 2022/08/30 21:47:45 - mmengine - INFO - Epoch(train) [1076][45/63] lr: 9.0841e-04 eta: 2:28:24 time: 0.7978 data_time: 0.0284 memory: 16201 loss_prob: 0.3056 loss_thr: 0.2260 loss_db: 0.0544 loss: 0.5859 2022/08/30 21:47:49 - mmengine - INFO - Epoch(train) [1076][50/63] lr: 9.0841e-04 eta: 2:28:12 time: 0.8099 data_time: 0.0332 memory: 16201 loss_prob: 0.3341 loss_thr: 0.2407 loss_db: 0.0599 loss: 0.6348 2022/08/30 21:47:53 - mmengine - INFO - Epoch(train) [1076][55/63] lr: 9.0841e-04 eta: 2:28:12 time: 0.8015 data_time: 0.0235 memory: 16201 loss_prob: 0.2974 loss_thr: 0.2219 loss_db: 0.0549 loss: 0.5743 2022/08/30 21:47:57 - mmengine - INFO - Epoch(train) [1076][60/63] lr: 9.0841e-04 eta: 2:28:00 time: 0.7879 data_time: 0.0236 memory: 16201 loss_prob: 0.2800 loss_thr: 0.2119 loss_db: 0.0500 loss: 0.5419 2022/08/30 21:47:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:48:04 - mmengine - INFO - Epoch(train) [1077][5/63] lr: 9.0181e-04 eta: 2:28:00 time: 0.8994 data_time: 0.1526 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2191 loss_db: 0.0560 loss: 0.5870 2022/08/30 21:48:08 - mmengine - INFO - Epoch(train) [1077][10/63] lr: 9.0181e-04 eta: 2:27:45 time: 0.9379 data_time: 0.1643 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2343 loss_db: 0.0578 loss: 0.6224 2022/08/30 21:48:12 - mmengine - INFO - Epoch(train) [1077][15/63] lr: 9.0181e-04 eta: 2:27:45 time: 0.7744 data_time: 0.0223 memory: 16201 loss_prob: 0.3402 loss_thr: 0.2351 loss_db: 0.0599 loss: 0.6353 2022/08/30 21:48:16 - mmengine - INFO - Epoch(train) [1077][20/63] lr: 9.0181e-04 eta: 2:27:33 time: 0.7741 data_time: 0.0156 memory: 16201 loss_prob: 0.3144 loss_thr: 0.2240 loss_db: 0.0567 loss: 0.5951 2022/08/30 21:48:20 - mmengine - INFO - Epoch(train) [1077][25/63] lr: 9.0181e-04 eta: 2:27:33 time: 0.8073 data_time: 0.0310 memory: 16201 loss_prob: 0.3217 loss_thr: 0.2279 loss_db: 0.0560 loss: 0.6057 2022/08/30 21:48:24 - mmengine - INFO - Epoch(train) [1077][30/63] lr: 9.0181e-04 eta: 2:27:21 time: 0.7988 data_time: 0.0249 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2291 loss_db: 0.0556 loss: 0.6068 2022/08/30 21:48:28 - mmengine - INFO - Epoch(train) [1077][35/63] lr: 9.0181e-04 eta: 2:27:21 time: 0.7791 data_time: 0.0179 memory: 16201 loss_prob: 0.2843 loss_thr: 0.2169 loss_db: 0.0516 loss: 0.5528 2022/08/30 21:48:32 - mmengine - INFO - Epoch(train) [1077][40/63] lr: 9.0181e-04 eta: 2:27:09 time: 0.7869 data_time: 0.0251 memory: 16201 loss_prob: 0.3088 loss_thr: 0.2278 loss_db: 0.0566 loss: 0.5932 2022/08/30 21:48:36 - mmengine - INFO - Epoch(train) [1077][45/63] lr: 9.0181e-04 eta: 2:27:09 time: 0.7920 data_time: 0.0224 memory: 16201 loss_prob: 0.3382 loss_thr: 0.2444 loss_db: 0.0610 loss: 0.6436 2022/08/30 21:48:39 - mmengine - INFO - Epoch(train) [1077][50/63] lr: 9.0181e-04 eta: 2:26:58 time: 0.7877 data_time: 0.0251 memory: 16201 loss_prob: 0.2903 loss_thr: 0.2177 loss_db: 0.0522 loss: 0.5602 2022/08/30 21:48:43 - mmengine - INFO - Epoch(train) [1077][55/63] lr: 9.0181e-04 eta: 2:26:58 time: 0.7834 data_time: 0.0256 memory: 16201 loss_prob: 0.2781 loss_thr: 0.2127 loss_db: 0.0498 loss: 0.5406 2022/08/30 21:48:48 - mmengine - INFO - Epoch(train) [1077][60/63] lr: 9.0181e-04 eta: 2:26:46 time: 0.8059 data_time: 0.0267 memory: 16201 loss_prob: 0.3272 loss_thr: 0.2323 loss_db: 0.0588 loss: 0.6183 2022/08/30 21:48:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:48:55 - mmengine - INFO - Epoch(train) [1078][5/63] lr: 8.9521e-04 eta: 2:26:46 time: 0.9169 data_time: 0.1864 memory: 16201 loss_prob: 0.3017 loss_thr: 0.2205 loss_db: 0.0544 loss: 0.5767 2022/08/30 21:48:59 - mmengine - INFO - Epoch(train) [1078][10/63] lr: 8.9521e-04 eta: 2:26:31 time: 0.9570 data_time: 0.1965 memory: 16201 loss_prob: 0.2788 loss_thr: 0.2208 loss_db: 0.0505 loss: 0.5501 2022/08/30 21:49:03 - mmengine - INFO - Epoch(train) [1078][15/63] lr: 8.9521e-04 eta: 2:26:31 time: 0.7760 data_time: 0.0229 memory: 16201 loss_prob: 0.3152 loss_thr: 0.2378 loss_db: 0.0553 loss: 0.6084 2022/08/30 21:49:07 - mmengine - INFO - Epoch(train) [1078][20/63] lr: 8.9521e-04 eta: 2:26:19 time: 0.7955 data_time: 0.0227 memory: 16201 loss_prob: 0.3272 loss_thr: 0.2293 loss_db: 0.0580 loss: 0.6145 2022/08/30 21:49:11 - mmengine - INFO - Epoch(train) [1078][25/63] lr: 8.9521e-04 eta: 2:26:19 time: 0.7957 data_time: 0.0256 memory: 16201 loss_prob: 0.3307 loss_thr: 0.2157 loss_db: 0.0597 loss: 0.6062 2022/08/30 21:49:15 - mmengine - INFO - Epoch(train) [1078][30/63] lr: 8.9521e-04 eta: 2:26:07 time: 0.7920 data_time: 0.0276 memory: 16201 loss_prob: 0.3622 loss_thr: 0.2401 loss_db: 0.0653 loss: 0.6676 2022/08/30 21:49:19 - mmengine - INFO - Epoch(train) [1078][35/63] lr: 8.9521e-04 eta: 2:26:07 time: 0.8356 data_time: 0.0612 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2458 loss_db: 0.0633 loss: 0.6597 2022/08/30 21:49:23 - mmengine - INFO - Epoch(train) [1078][40/63] lr: 8.9521e-04 eta: 2:25:55 time: 0.8139 data_time: 0.0552 memory: 16201 loss_prob: 0.3543 loss_thr: 0.2451 loss_db: 0.0628 loss: 0.6621 2022/08/30 21:49:27 - mmengine - INFO - Epoch(train) [1078][45/63] lr: 8.9521e-04 eta: 2:25:55 time: 0.8228 data_time: 0.0232 memory: 16201 loss_prob: 0.3528 loss_thr: 0.2402 loss_db: 0.0620 loss: 0.6550 2022/08/30 21:49:31 - mmengine - INFO - Epoch(train) [1078][50/63] lr: 8.9521e-04 eta: 2:25:44 time: 0.8273 data_time: 0.0218 memory: 16201 loss_prob: 0.3373 loss_thr: 0.2320 loss_db: 0.0607 loss: 0.6300 2022/08/30 21:49:35 - mmengine - INFO - Epoch(train) [1078][55/63] lr: 8.9521e-04 eta: 2:25:44 time: 0.7929 data_time: 0.0264 memory: 16201 loss_prob: 0.4188 loss_thr: 0.2624 loss_db: 0.0695 loss: 0.7508 2022/08/30 21:49:39 - mmengine - INFO - Epoch(train) [1078][60/63] lr: 8.9521e-04 eta: 2:25:32 time: 0.8017 data_time: 0.0283 memory: 16201 loss_prob: 0.4227 loss_thr: 0.2600 loss_db: 0.0682 loss: 0.7509 2022/08/30 21:49:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:49:47 - mmengine - INFO - Epoch(train) [1079][5/63] lr: 8.8861e-04 eta: 2:25:32 time: 0.9040 data_time: 0.1774 memory: 16201 loss_prob: 0.3043 loss_thr: 0.2250 loss_db: 0.0547 loss: 0.5840 2022/08/30 21:49:51 - mmengine - INFO - Epoch(train) [1079][10/63] lr: 8.8861e-04 eta: 2:25:17 time: 0.9701 data_time: 0.1928 memory: 16201 loss_prob: 0.2992 loss_thr: 0.2194 loss_db: 0.0541 loss: 0.5727 2022/08/30 21:49:55 - mmengine - INFO - Epoch(train) [1079][15/63] lr: 8.8861e-04 eta: 2:25:17 time: 0.8270 data_time: 0.0292 memory: 16201 loss_prob: 0.3152 loss_thr: 0.2340 loss_db: 0.0578 loss: 0.6070 2022/08/30 21:49:59 - mmengine - INFO - Epoch(train) [1079][20/63] lr: 8.8861e-04 eta: 2:25:05 time: 0.8239 data_time: 0.0227 memory: 16201 loss_prob: 0.3057 loss_thr: 0.2305 loss_db: 0.0558 loss: 0.5920 2022/08/30 21:50:03 - mmengine - INFO - Epoch(train) [1079][25/63] lr: 8.8861e-04 eta: 2:25:05 time: 0.8122 data_time: 0.0362 memory: 16201 loss_prob: 0.3046 loss_thr: 0.2242 loss_db: 0.0531 loss: 0.5818 2022/08/30 21:50:07 - mmengine - INFO - Epoch(train) [1079][30/63] lr: 8.8861e-04 eta: 2:24:53 time: 0.8079 data_time: 0.0253 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2368 loss_db: 0.0585 loss: 0.6292 2022/08/30 21:50:11 - mmengine - INFO - Epoch(train) [1079][35/63] lr: 8.8861e-04 eta: 2:24:53 time: 0.7960 data_time: 0.0192 memory: 16201 loss_prob: 0.3222 loss_thr: 0.2248 loss_db: 0.0582 loss: 0.6053 2022/08/30 21:50:15 - mmengine - INFO - Epoch(train) [1079][40/63] lr: 8.8861e-04 eta: 2:24:41 time: 0.7845 data_time: 0.0256 memory: 16201 loss_prob: 0.2992 loss_thr: 0.2134 loss_db: 0.0541 loss: 0.5667 2022/08/30 21:50:19 - mmengine - INFO - Epoch(train) [1079][45/63] lr: 8.8861e-04 eta: 2:24:41 time: 0.7905 data_time: 0.0258 memory: 16201 loss_prob: 0.3151 loss_thr: 0.2237 loss_db: 0.0585 loss: 0.5973 2022/08/30 21:50:23 - mmengine - INFO - Epoch(train) [1079][50/63] lr: 8.8861e-04 eta: 2:24:30 time: 0.8133 data_time: 0.0247 memory: 16201 loss_prob: 0.3094 loss_thr: 0.2244 loss_db: 0.0568 loss: 0.5906 2022/08/30 21:50:27 - mmengine - INFO - Epoch(train) [1079][55/63] lr: 8.8861e-04 eta: 2:24:30 time: 0.8067 data_time: 0.0261 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2307 loss_db: 0.0566 loss: 0.6099 2022/08/30 21:50:31 - mmengine - INFO - Epoch(train) [1079][60/63] lr: 8.8861e-04 eta: 2:24:18 time: 0.7899 data_time: 0.0244 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2322 loss_db: 0.0610 loss: 0.6328 2022/08/30 21:50:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:50:39 - mmengine - INFO - Epoch(train) [1080][5/63] lr: 8.8200e-04 eta: 2:24:18 time: 0.8994 data_time: 0.1566 memory: 16201 loss_prob: 0.2923 loss_thr: 0.2173 loss_db: 0.0526 loss: 0.5622 2022/08/30 21:50:42 - mmengine - INFO - Epoch(train) [1080][10/63] lr: 8.8200e-04 eta: 2:24:03 time: 0.9240 data_time: 0.1676 memory: 16201 loss_prob: 0.3107 loss_thr: 0.2143 loss_db: 0.0566 loss: 0.5816 2022/08/30 21:50:46 - mmengine - INFO - Epoch(train) [1080][15/63] lr: 8.8200e-04 eta: 2:24:03 time: 0.7710 data_time: 0.0233 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2319 loss_db: 0.0596 loss: 0.6279 2022/08/30 21:50:50 - mmengine - INFO - Epoch(train) [1080][20/63] lr: 8.8200e-04 eta: 2:23:51 time: 0.7727 data_time: 0.0162 memory: 16201 loss_prob: 0.3402 loss_thr: 0.2455 loss_db: 0.0586 loss: 0.6442 2022/08/30 21:50:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:50:54 - mmengine - INFO - Epoch(train) [1080][25/63] lr: 8.8200e-04 eta: 2:23:51 time: 0.7979 data_time: 0.0304 memory: 16201 loss_prob: 0.3307 loss_thr: 0.2363 loss_db: 0.0576 loss: 0.6246 2022/08/30 21:50:58 - mmengine - INFO - Epoch(train) [1080][30/63] lr: 8.8200e-04 eta: 2:23:39 time: 0.7836 data_time: 0.0213 memory: 16201 loss_prob: 0.3371 loss_thr: 0.2374 loss_db: 0.0600 loss: 0.6345 2022/08/30 21:51:02 - mmengine - INFO - Epoch(train) [1080][35/63] lr: 8.8200e-04 eta: 2:23:39 time: 0.7807 data_time: 0.0187 memory: 16201 loss_prob: 0.3416 loss_thr: 0.2466 loss_db: 0.0603 loss: 0.6485 2022/08/30 21:51:06 - mmengine - INFO - Epoch(train) [1080][40/63] lr: 8.8200e-04 eta: 2:23:27 time: 0.8015 data_time: 0.0259 memory: 16201 loss_prob: 0.3220 loss_thr: 0.2365 loss_db: 0.0567 loss: 0.6153 2022/08/30 21:51:10 - mmengine - INFO - Epoch(train) [1080][45/63] lr: 8.8200e-04 eta: 2:23:27 time: 0.7936 data_time: 0.0235 memory: 16201 loss_prob: 0.3175 loss_thr: 0.2257 loss_db: 0.0566 loss: 0.5998 2022/08/30 21:51:14 - mmengine - INFO - Epoch(train) [1080][50/63] lr: 8.8200e-04 eta: 2:23:16 time: 0.7833 data_time: 0.0257 memory: 16201 loss_prob: 0.3202 loss_thr: 0.2167 loss_db: 0.0553 loss: 0.5922 2022/08/30 21:51:18 - mmengine - INFO - Epoch(train) [1080][55/63] lr: 8.8200e-04 eta: 2:23:16 time: 0.7977 data_time: 0.0219 memory: 16201 loss_prob: 0.3235 loss_thr: 0.2157 loss_db: 0.0557 loss: 0.5950 2022/08/30 21:51:22 - mmengine - INFO - Epoch(train) [1080][60/63] lr: 8.8200e-04 eta: 2:23:04 time: 0.7925 data_time: 0.0266 memory: 16201 loss_prob: 0.3375 loss_thr: 0.2337 loss_db: 0.0601 loss: 0.6313 2022/08/30 21:51:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:51:24 - mmengine - INFO - Saving checkpoint at 1080 epochs 2022/08/30 21:51:31 - mmengine - INFO - Epoch(val) [1080][5/32] eta: 2:23:04 time: 0.6509 data_time: 0.1089 memory: 16201 2022/08/30 21:51:35 - mmengine - INFO - Epoch(val) [1080][10/32] eta: 0:00:15 time: 0.7006 data_time: 0.1372 memory: 15734 2022/08/30 21:51:37 - mmengine - INFO - Epoch(val) [1080][15/32] eta: 0:00:15 time: 0.5829 data_time: 0.0462 memory: 15734 2022/08/30 21:51:41 - mmengine - INFO - Epoch(val) [1080][20/32] eta: 0:00:07 time: 0.6021 data_time: 0.0696 memory: 15734 2022/08/30 21:51:44 - mmengine - INFO - Epoch(val) [1080][25/32] eta: 0:00:07 time: 0.6791 data_time: 0.0995 memory: 15734 2022/08/30 21:51:47 - mmengine - INFO - Epoch(val) [1080][30/32] eta: 0:00:01 time: 0.6287 data_time: 0.0476 memory: 15734 2022/08/30 21:51:47 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 21:51:48 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8551, precision: 0.8124, hmean: 0.8332 2022/08/30 21:51:48 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8551, precision: 0.8381, hmean: 0.8465 2022/08/30 21:51:48 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8541, precision: 0.8607, hmean: 0.8574 2022/08/30 21:51:48 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8512, precision: 0.8744, hmean: 0.8626 2022/08/30 21:51:48 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8426, precision: 0.8892, hmean: 0.8653 2022/08/30 21:51:48 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8238, precision: 0.9111, hmean: 0.8652 2022/08/30 21:51:48 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.5219, precision: 0.9534, hmean: 0.6745 2022/08/30 21:51:48 - mmengine - INFO - Epoch(val) [1080][32/32] icdar/precision: 0.8892 icdar/recall: 0.8426 icdar/hmean: 0.8653 2022/08/30 21:51:53 - mmengine - INFO - Epoch(train) [1081][5/63] lr: 8.7538e-04 eta: 0:00:01 time: 0.9208 data_time: 0.1819 memory: 16201 loss_prob: 0.2990 loss_thr: 0.2138 loss_db: 0.0544 loss: 0.5672 2022/08/30 21:51:57 - mmengine - INFO - Epoch(train) [1081][10/63] lr: 8.7538e-04 eta: 2:22:49 time: 0.9864 data_time: 0.1899 memory: 16201 loss_prob: 0.3158 loss_thr: 0.2156 loss_db: 0.0559 loss: 0.5873 2022/08/30 21:52:01 - mmengine - INFO - Epoch(train) [1081][15/63] lr: 8.7538e-04 eta: 2:22:49 time: 0.7871 data_time: 0.0181 memory: 16201 loss_prob: 0.3309 loss_thr: 0.2214 loss_db: 0.0573 loss: 0.6096 2022/08/30 21:52:05 - mmengine - INFO - Epoch(train) [1081][20/63] lr: 8.7538e-04 eta: 2:22:37 time: 0.7828 data_time: 0.0251 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2323 loss_db: 0.0600 loss: 0.6362 2022/08/30 21:52:10 - mmengine - INFO - Epoch(train) [1081][25/63] lr: 8.7538e-04 eta: 2:22:37 time: 0.8401 data_time: 0.0264 memory: 16201 loss_prob: 0.3567 loss_thr: 0.2547 loss_db: 0.0637 loss: 0.6751 2022/08/30 21:52:14 - mmengine - INFO - Epoch(train) [1081][30/63] lr: 8.7538e-04 eta: 2:22:25 time: 0.8360 data_time: 0.0199 memory: 16201 loss_prob: 0.3375 loss_thr: 0.2455 loss_db: 0.0625 loss: 0.6455 2022/08/30 21:52:18 - mmengine - INFO - Epoch(train) [1081][35/63] lr: 8.7538e-04 eta: 2:22:25 time: 0.7884 data_time: 0.0287 memory: 16201 loss_prob: 0.3159 loss_thr: 0.2271 loss_db: 0.0580 loss: 0.6010 2022/08/30 21:52:22 - mmengine - INFO - Epoch(train) [1081][40/63] lr: 8.7538e-04 eta: 2:22:13 time: 0.7831 data_time: 0.0229 memory: 16201 loss_prob: 0.3271 loss_thr: 0.2335 loss_db: 0.0570 loss: 0.6176 2022/08/30 21:52:26 - mmengine - INFO - Epoch(train) [1081][45/63] lr: 8.7538e-04 eta: 2:22:13 time: 0.7871 data_time: 0.0212 memory: 16201 loss_prob: 0.3148 loss_thr: 0.2249 loss_db: 0.0541 loss: 0.5939 2022/08/30 21:52:29 - mmengine - INFO - Epoch(train) [1081][50/63] lr: 8.7538e-04 eta: 2:22:02 time: 0.7841 data_time: 0.0302 memory: 16201 loss_prob: 0.3330 loss_thr: 0.2287 loss_db: 0.0582 loss: 0.6199 2022/08/30 21:52:34 - mmengine - INFO - Epoch(train) [1081][55/63] lr: 8.7538e-04 eta: 2:22:02 time: 0.8060 data_time: 0.0243 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2354 loss_db: 0.0626 loss: 0.6510 2022/08/30 21:52:38 - mmengine - INFO - Epoch(train) [1081][60/63] lr: 8.7538e-04 eta: 2:21:50 time: 0.8431 data_time: 0.0239 memory: 16201 loss_prob: 0.3379 loss_thr: 0.2375 loss_db: 0.0611 loss: 0.6364 2022/08/30 21:52:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:52:46 - mmengine - INFO - Epoch(train) [1082][5/63] lr: 8.6876e-04 eta: 2:21:50 time: 0.9307 data_time: 0.1834 memory: 16201 loss_prob: 0.3316 loss_thr: 0.2257 loss_db: 0.0583 loss: 0.6157 2022/08/30 21:52:49 - mmengine - INFO - Epoch(train) [1082][10/63] lr: 8.6876e-04 eta: 2:21:35 time: 0.9600 data_time: 0.1877 memory: 16201 loss_prob: 0.3307 loss_thr: 0.2218 loss_db: 0.0578 loss: 0.6103 2022/08/30 21:52:54 - mmengine - INFO - Epoch(train) [1082][15/63] lr: 8.6876e-04 eta: 2:21:35 time: 0.8066 data_time: 0.0270 memory: 16201 loss_prob: 0.3360 loss_thr: 0.2333 loss_db: 0.0599 loss: 0.6292 2022/08/30 21:52:58 - mmengine - INFO - Epoch(train) [1082][20/63] lr: 8.6876e-04 eta: 2:21:23 time: 0.8248 data_time: 0.0241 memory: 16201 loss_prob: 0.3444 loss_thr: 0.2376 loss_db: 0.0614 loss: 0.6435 2022/08/30 21:53:02 - mmengine - INFO - Epoch(train) [1082][25/63] lr: 8.6876e-04 eta: 2:21:23 time: 0.8019 data_time: 0.0255 memory: 16201 loss_prob: 0.3257 loss_thr: 0.2280 loss_db: 0.0576 loss: 0.6113 2022/08/30 21:53:05 - mmengine - INFO - Epoch(train) [1082][30/63] lr: 8.6876e-04 eta: 2:21:11 time: 0.7785 data_time: 0.0221 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2309 loss_db: 0.0582 loss: 0.6193 2022/08/30 21:53:09 - mmengine - INFO - Epoch(train) [1082][35/63] lr: 8.6876e-04 eta: 2:21:11 time: 0.7851 data_time: 0.0235 memory: 16201 loss_prob: 0.3230 loss_thr: 0.2310 loss_db: 0.0585 loss: 0.6125 2022/08/30 21:53:13 - mmengine - INFO - Epoch(train) [1082][40/63] lr: 8.6876e-04 eta: 2:21:00 time: 0.7913 data_time: 0.0190 memory: 16201 loss_prob: 0.3150 loss_thr: 0.2328 loss_db: 0.0571 loss: 0.6049 2022/08/30 21:53:18 - mmengine - INFO - Epoch(train) [1082][45/63] lr: 8.6876e-04 eta: 2:21:00 time: 0.8090 data_time: 0.0240 memory: 16201 loss_prob: 0.3369 loss_thr: 0.2422 loss_db: 0.0609 loss: 0.6399 2022/08/30 21:53:22 - mmengine - INFO - Epoch(train) [1082][50/63] lr: 8.6876e-04 eta: 2:20:48 time: 0.8146 data_time: 0.0316 memory: 16201 loss_prob: 0.3415 loss_thr: 0.2426 loss_db: 0.0613 loss: 0.6454 2022/08/30 21:53:25 - mmengine - INFO - Epoch(train) [1082][55/63] lr: 8.6876e-04 eta: 2:20:48 time: 0.7788 data_time: 0.0183 memory: 16201 loss_prob: 0.3219 loss_thr: 0.2353 loss_db: 0.0567 loss: 0.6138 2022/08/30 21:53:29 - mmengine - INFO - Epoch(train) [1082][60/63] lr: 8.6876e-04 eta: 2:20:36 time: 0.7760 data_time: 0.0245 memory: 16201 loss_prob: 0.3219 loss_thr: 0.2320 loss_db: 0.0572 loss: 0.6110 2022/08/30 21:53:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:53:37 - mmengine - INFO - Epoch(train) [1083][5/63] lr: 8.6213e-04 eta: 2:20:36 time: 0.9118 data_time: 0.1729 memory: 16201 loss_prob: 0.3507 loss_thr: 0.2388 loss_db: 0.0621 loss: 0.6516 2022/08/30 21:53:41 - mmengine - INFO - Epoch(train) [1083][10/63] lr: 8.6213e-04 eta: 2:20:21 time: 0.9563 data_time: 0.1841 memory: 16201 loss_prob: 0.3557 loss_thr: 0.2380 loss_db: 0.0639 loss: 0.6576 2022/08/30 21:53:45 - mmengine - INFO - Epoch(train) [1083][15/63] lr: 8.6213e-04 eta: 2:20:21 time: 0.8053 data_time: 0.0271 memory: 16201 loss_prob: 0.3737 loss_thr: 0.2457 loss_db: 0.0662 loss: 0.6856 2022/08/30 21:53:49 - mmengine - INFO - Epoch(train) [1083][20/63] lr: 8.6213e-04 eta: 2:20:09 time: 0.8059 data_time: 0.0182 memory: 16201 loss_prob: 0.3657 loss_thr: 0.2472 loss_db: 0.0640 loss: 0.6769 2022/08/30 21:53:53 - mmengine - INFO - Epoch(train) [1083][25/63] lr: 8.6213e-04 eta: 2:20:09 time: 0.7990 data_time: 0.0284 memory: 16201 loss_prob: 0.3266 loss_thr: 0.2254 loss_db: 0.0582 loss: 0.6103 2022/08/30 21:53:57 - mmengine - INFO - Epoch(train) [1083][30/63] lr: 8.6213e-04 eta: 2:19:57 time: 0.8031 data_time: 0.0317 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2225 loss_db: 0.0569 loss: 0.5972 2022/08/30 21:54:01 - mmengine - INFO - Epoch(train) [1083][35/63] lr: 8.6213e-04 eta: 2:19:57 time: 0.7938 data_time: 0.0222 memory: 16201 loss_prob: 0.3273 loss_thr: 0.2317 loss_db: 0.0587 loss: 0.6177 2022/08/30 21:54:05 - mmengine - INFO - Epoch(train) [1083][40/63] lr: 8.6213e-04 eta: 2:19:46 time: 0.7992 data_time: 0.0245 memory: 16201 loss_prob: 0.3271 loss_thr: 0.2334 loss_db: 0.0588 loss: 0.6193 2022/08/30 21:54:09 - mmengine - INFO - Epoch(train) [1083][45/63] lr: 8.6213e-04 eta: 2:19:46 time: 0.7956 data_time: 0.0308 memory: 16201 loss_prob: 0.3179 loss_thr: 0.2300 loss_db: 0.0576 loss: 0.6055 2022/08/30 21:54:13 - mmengine - INFO - Epoch(train) [1083][50/63] lr: 8.6213e-04 eta: 2:19:34 time: 0.7801 data_time: 0.0230 memory: 16201 loss_prob: 0.3286 loss_thr: 0.2388 loss_db: 0.0585 loss: 0.6259 2022/08/30 21:54:17 - mmengine - INFO - Epoch(train) [1083][55/63] lr: 8.6213e-04 eta: 2:19:34 time: 0.7864 data_time: 0.0225 memory: 16201 loss_prob: 0.3447 loss_thr: 0.2468 loss_db: 0.0614 loss: 0.6529 2022/08/30 21:54:21 - mmengine - INFO - Epoch(train) [1083][60/63] lr: 8.6213e-04 eta: 2:19:22 time: 0.7815 data_time: 0.0245 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2349 loss_db: 0.0591 loss: 0.6250 2022/08/30 21:54:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:54:28 - mmengine - INFO - Epoch(train) [1084][5/63] lr: 8.5550e-04 eta: 2:19:22 time: 0.9403 data_time: 0.1763 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2284 loss_db: 0.0601 loss: 0.6239 2022/08/30 21:54:32 - mmengine - INFO - Epoch(train) [1084][10/63] lr: 8.5550e-04 eta: 2:19:07 time: 1.0042 data_time: 0.1909 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2335 loss_db: 0.0605 loss: 0.6336 2022/08/30 21:54:36 - mmengine - INFO - Epoch(train) [1084][15/63] lr: 8.5550e-04 eta: 2:19:07 time: 0.8032 data_time: 0.0252 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2249 loss_db: 0.0591 loss: 0.6149 2022/08/30 21:54:40 - mmengine - INFO - Epoch(train) [1084][20/63] lr: 8.5550e-04 eta: 2:18:55 time: 0.7925 data_time: 0.0157 memory: 16201 loss_prob: 0.3027 loss_thr: 0.2155 loss_db: 0.0549 loss: 0.5731 2022/08/30 21:54:44 - mmengine - INFO - Epoch(train) [1084][25/63] lr: 8.5550e-04 eta: 2:18:55 time: 0.7995 data_time: 0.0317 memory: 16201 loss_prob: 0.2951 loss_thr: 0.2144 loss_db: 0.0536 loss: 0.5630 2022/08/30 21:54:48 - mmengine - INFO - Epoch(train) [1084][30/63] lr: 8.5550e-04 eta: 2:18:44 time: 0.8043 data_time: 0.0235 memory: 16201 loss_prob: 0.3112 loss_thr: 0.2275 loss_db: 0.0559 loss: 0.5945 2022/08/30 21:54:52 - mmengine - INFO - Epoch(train) [1084][35/63] lr: 8.5550e-04 eta: 2:18:44 time: 0.7975 data_time: 0.0184 memory: 16201 loss_prob: 0.3442 loss_thr: 0.2399 loss_db: 0.0622 loss: 0.6462 2022/08/30 21:54:57 - mmengine - INFO - Epoch(train) [1084][40/63] lr: 8.5550e-04 eta: 2:18:32 time: 0.8109 data_time: 0.0248 memory: 16201 loss_prob: 0.3412 loss_thr: 0.2317 loss_db: 0.0616 loss: 0.6345 2022/08/30 21:55:00 - mmengine - INFO - Epoch(train) [1084][45/63] lr: 8.5550e-04 eta: 2:18:32 time: 0.8067 data_time: 0.0227 memory: 16201 loss_prob: 0.3095 loss_thr: 0.2217 loss_db: 0.0545 loss: 0.5857 2022/08/30 21:55:04 - mmengine - INFO - Epoch(train) [1084][50/63] lr: 8.5550e-04 eta: 2:18:20 time: 0.7907 data_time: 0.0300 memory: 16201 loss_prob: 0.3119 loss_thr: 0.2196 loss_db: 0.0552 loss: 0.5867 2022/08/30 21:55:08 - mmengine - INFO - Epoch(train) [1084][55/63] lr: 8.5550e-04 eta: 2:18:20 time: 0.7927 data_time: 0.0274 memory: 16201 loss_prob: 0.3485 loss_thr: 0.2481 loss_db: 0.0622 loss: 0.6588 2022/08/30 21:55:12 - mmengine - INFO - Epoch(train) [1084][60/63] lr: 8.5550e-04 eta: 2:18:08 time: 0.7822 data_time: 0.0234 memory: 16201 loss_prob: 0.3458 loss_thr: 0.2528 loss_db: 0.0621 loss: 0.6607 2022/08/30 21:55:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:55:20 - mmengine - INFO - Epoch(train) [1085][5/63] lr: 8.4886e-04 eta: 2:18:08 time: 0.8787 data_time: 0.1575 memory: 16201 loss_prob: 0.3044 loss_thr: 0.2173 loss_db: 0.0544 loss: 0.5762 2022/08/30 21:55:24 - mmengine - INFO - Epoch(train) [1085][10/63] lr: 8.4886e-04 eta: 2:17:53 time: 0.9276 data_time: 0.1643 memory: 16201 loss_prob: 0.3031 loss_thr: 0.2219 loss_db: 0.0543 loss: 0.5793 2022/08/30 21:55:28 - mmengine - INFO - Epoch(train) [1085][15/63] lr: 8.4886e-04 eta: 2:17:53 time: 0.8142 data_time: 0.0219 memory: 16201 loss_prob: 0.3281 loss_thr: 0.2436 loss_db: 0.0571 loss: 0.6288 2022/08/30 21:55:32 - mmengine - INFO - Epoch(train) [1085][20/63] lr: 8.4886e-04 eta: 2:17:41 time: 0.8133 data_time: 0.0249 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2240 loss_db: 0.0545 loss: 0.5899 2022/08/30 21:55:36 - mmengine - INFO - Epoch(train) [1085][25/63] lr: 8.4886e-04 eta: 2:17:41 time: 0.7795 data_time: 0.0260 memory: 16201 loss_prob: 0.3011 loss_thr: 0.2119 loss_db: 0.0553 loss: 0.5683 2022/08/30 21:55:40 - mmengine - INFO - Epoch(train) [1085][30/63] lr: 8.4886e-04 eta: 2:17:30 time: 0.7826 data_time: 0.0245 memory: 16201 loss_prob: 0.3043 loss_thr: 0.2151 loss_db: 0.0571 loss: 0.5765 2022/08/30 21:55:43 - mmengine - INFO - Epoch(train) [1085][35/63] lr: 8.4886e-04 eta: 2:17:30 time: 0.7694 data_time: 0.0248 memory: 16201 loss_prob: 0.3053 loss_thr: 0.2237 loss_db: 0.0547 loss: 0.5837 2022/08/30 21:55:48 - mmengine - INFO - Epoch(train) [1085][40/63] lr: 8.4886e-04 eta: 2:17:18 time: 0.8211 data_time: 0.0208 memory: 16201 loss_prob: 0.2984 loss_thr: 0.2253 loss_db: 0.0521 loss: 0.5758 2022/08/30 21:55:52 - mmengine - INFO - Epoch(train) [1085][45/63] lr: 8.4886e-04 eta: 2:17:18 time: 0.8349 data_time: 0.0232 memory: 16201 loss_prob: 0.3298 loss_thr: 0.2310 loss_db: 0.0587 loss: 0.6195 2022/08/30 21:55:55 - mmengine - INFO - Epoch(train) [1085][50/63] lr: 8.4886e-04 eta: 2:17:06 time: 0.7706 data_time: 0.0211 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2355 loss_db: 0.0616 loss: 0.6436 2022/08/30 21:55:59 - mmengine - INFO - Epoch(train) [1085][55/63] lr: 8.4886e-04 eta: 2:17:06 time: 0.7783 data_time: 0.0251 memory: 16201 loss_prob: 0.3288 loss_thr: 0.2293 loss_db: 0.0589 loss: 0.6171 2022/08/30 21:56:03 - mmengine - INFO - Epoch(train) [1085][60/63] lr: 8.4886e-04 eta: 2:16:55 time: 0.7814 data_time: 0.0293 memory: 16201 loss_prob: 0.3436 loss_thr: 0.2314 loss_db: 0.0623 loss: 0.6373 2022/08/30 21:56:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:56:11 - mmengine - INFO - Epoch(train) [1086][5/63] lr: 8.4221e-04 eta: 2:16:55 time: 0.9159 data_time: 0.1898 memory: 16201 loss_prob: 0.3488 loss_thr: 0.2452 loss_db: 0.0629 loss: 0.6569 2022/08/30 21:56:15 - mmengine - INFO - Epoch(train) [1086][10/63] lr: 8.4221e-04 eta: 2:16:39 time: 0.9635 data_time: 0.1985 memory: 16201 loss_prob: 0.3355 loss_thr: 0.2426 loss_db: 0.0600 loss: 0.6381 2022/08/30 21:56:19 - mmengine - INFO - Epoch(train) [1086][15/63] lr: 8.4221e-04 eta: 2:16:39 time: 0.7830 data_time: 0.0216 memory: 16201 loss_prob: 0.3057 loss_thr: 0.2319 loss_db: 0.0551 loss: 0.5927 2022/08/30 21:56:23 - mmengine - INFO - Epoch(train) [1086][20/63] lr: 8.4221e-04 eta: 2:16:28 time: 0.7796 data_time: 0.0172 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2249 loss_db: 0.0546 loss: 0.5843 2022/08/30 21:56:26 - mmengine - INFO - Epoch(train) [1086][25/63] lr: 8.4221e-04 eta: 2:16:28 time: 0.7798 data_time: 0.0286 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2270 loss_db: 0.0558 loss: 0.6005 2022/08/30 21:56:31 - mmengine - INFO - Epoch(train) [1086][30/63] lr: 8.4221e-04 eta: 2:16:16 time: 0.8047 data_time: 0.0285 memory: 16201 loss_prob: 0.2970 loss_thr: 0.2166 loss_db: 0.0527 loss: 0.5663 2022/08/30 21:56:34 - mmengine - INFO - Epoch(train) [1086][35/63] lr: 8.4221e-04 eta: 2:16:16 time: 0.7976 data_time: 0.0267 memory: 16201 loss_prob: 0.3062 loss_thr: 0.2224 loss_db: 0.0561 loss: 0.5847 2022/08/30 21:56:38 - mmengine - INFO - Epoch(train) [1086][40/63] lr: 8.4221e-04 eta: 2:16:04 time: 0.7776 data_time: 0.0244 memory: 16201 loss_prob: 0.3406 loss_thr: 0.2400 loss_db: 0.0612 loss: 0.6418 2022/08/30 21:56:42 - mmengine - INFO - Epoch(train) [1086][45/63] lr: 8.4221e-04 eta: 2:16:04 time: 0.7915 data_time: 0.0233 memory: 16201 loss_prob: 0.3451 loss_thr: 0.2484 loss_db: 0.0597 loss: 0.6531 2022/08/30 21:56:46 - mmengine - INFO - Epoch(train) [1086][50/63] lr: 8.4221e-04 eta: 2:15:53 time: 0.7951 data_time: 0.0251 memory: 16201 loss_prob: 0.3154 loss_thr: 0.2343 loss_db: 0.0561 loss: 0.6058 2022/08/30 21:56:51 - mmengine - INFO - Epoch(train) [1086][55/63] lr: 8.4221e-04 eta: 2:15:53 time: 0.8645 data_time: 0.0295 memory: 16201 loss_prob: 0.3005 loss_thr: 0.2207 loss_db: 0.0549 loss: 0.5762 2022/08/30 21:56:55 - mmengine - INFO - Epoch(train) [1086][60/63] lr: 8.4221e-04 eta: 2:15:41 time: 0.8566 data_time: 0.0292 memory: 16201 loss_prob: 0.3041 loss_thr: 0.2160 loss_db: 0.0551 loss: 0.5752 2022/08/30 21:56:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:57:03 - mmengine - INFO - Epoch(train) [1087][5/63] lr: 8.3556e-04 eta: 2:15:41 time: 0.9191 data_time: 0.1872 memory: 16201 loss_prob: 0.3564 loss_thr: 0.2363 loss_db: 0.0635 loss: 0.6562 2022/08/30 21:57:07 - mmengine - INFO - Epoch(train) [1087][10/63] lr: 8.3556e-04 eta: 2:15:26 time: 0.9786 data_time: 0.2025 memory: 16201 loss_prob: 0.3029 loss_thr: 0.2122 loss_db: 0.0541 loss: 0.5692 2022/08/30 21:57:10 - mmengine - INFO - Epoch(train) [1087][15/63] lr: 8.3556e-04 eta: 2:15:26 time: 0.7800 data_time: 0.0258 memory: 16201 loss_prob: 0.2919 loss_thr: 0.2107 loss_db: 0.0525 loss: 0.5552 2022/08/30 21:57:14 - mmengine - INFO - Epoch(train) [1087][20/63] lr: 8.3556e-04 eta: 2:15:14 time: 0.7777 data_time: 0.0212 memory: 16201 loss_prob: 0.3220 loss_thr: 0.2241 loss_db: 0.0576 loss: 0.6038 2022/08/30 21:57:18 - mmengine - INFO - Epoch(train) [1087][25/63] lr: 8.3556e-04 eta: 2:15:14 time: 0.8022 data_time: 0.0328 memory: 16201 loss_prob: 0.3176 loss_thr: 0.2170 loss_db: 0.0562 loss: 0.5909 2022/08/30 21:57:22 - mmengine - INFO - Epoch(train) [1087][30/63] lr: 8.3556e-04 eta: 2:15:02 time: 0.7872 data_time: 0.0250 memory: 16201 loss_prob: 0.3187 loss_thr: 0.2198 loss_db: 0.0560 loss: 0.5945 2022/08/30 21:57:26 - mmengine - INFO - Epoch(train) [1087][35/63] lr: 8.3556e-04 eta: 2:15:02 time: 0.7659 data_time: 0.0191 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2389 loss_db: 0.0618 loss: 0.6472 2022/08/30 21:57:30 - mmengine - INFO - Epoch(train) [1087][40/63] lr: 8.3556e-04 eta: 2:14:51 time: 0.7724 data_time: 0.0250 memory: 16201 loss_prob: 0.3651 loss_thr: 0.2509 loss_db: 0.0665 loss: 0.6825 2022/08/30 21:57:34 - mmengine - INFO - Epoch(train) [1087][45/63] lr: 8.3556e-04 eta: 2:14:51 time: 0.7787 data_time: 0.0224 memory: 16201 loss_prob: 0.3344 loss_thr: 0.2335 loss_db: 0.0615 loss: 0.6293 2022/08/30 21:57:38 - mmengine - INFO - Epoch(train) [1087][50/63] lr: 8.3556e-04 eta: 2:14:39 time: 0.8132 data_time: 0.0224 memory: 16201 loss_prob: 0.2922 loss_thr: 0.2096 loss_db: 0.0523 loss: 0.5541 2022/08/30 21:57:42 - mmengine - INFO - Epoch(train) [1087][55/63] lr: 8.3556e-04 eta: 2:14:39 time: 0.8130 data_time: 0.0276 memory: 16201 loss_prob: 0.3516 loss_thr: 0.2382 loss_db: 0.0606 loss: 0.6504 2022/08/30 21:57:46 - mmengine - INFO - Epoch(train) [1087][60/63] lr: 8.3556e-04 eta: 2:14:27 time: 0.7858 data_time: 0.0261 memory: 16201 loss_prob: 0.3604 loss_thr: 0.2469 loss_db: 0.0623 loss: 0.6696 2022/08/30 21:57:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:57:54 - mmengine - INFO - Epoch(train) [1088][5/63] lr: 8.2890e-04 eta: 2:14:27 time: 0.9396 data_time: 0.1952 memory: 16201 loss_prob: 0.3359 loss_thr: 0.2466 loss_db: 0.0591 loss: 0.6415 2022/08/30 21:57:58 - mmengine - INFO - Epoch(train) [1088][10/63] lr: 8.2890e-04 eta: 2:14:12 time: 0.9706 data_time: 0.2062 memory: 16201 loss_prob: 0.3119 loss_thr: 0.2294 loss_db: 0.0556 loss: 0.5969 2022/08/30 21:58:02 - mmengine - INFO - Epoch(train) [1088][15/63] lr: 8.2890e-04 eta: 2:14:12 time: 0.7835 data_time: 0.0235 memory: 16201 loss_prob: 0.3024 loss_thr: 0.2206 loss_db: 0.0548 loss: 0.5778 2022/08/30 21:58:05 - mmengine - INFO - Epoch(train) [1088][20/63] lr: 8.2890e-04 eta: 2:14:00 time: 0.7730 data_time: 0.0151 memory: 16201 loss_prob: 0.3284 loss_thr: 0.2243 loss_db: 0.0597 loss: 0.6123 2022/08/30 21:58:10 - mmengine - INFO - Epoch(train) [1088][25/63] lr: 8.2890e-04 eta: 2:14:00 time: 0.8360 data_time: 0.0286 memory: 16201 loss_prob: 0.3365 loss_thr: 0.2279 loss_db: 0.0612 loss: 0.6256 2022/08/30 21:58:14 - mmengine - INFO - Epoch(train) [1088][30/63] lr: 8.2890e-04 eta: 2:13:49 time: 0.8381 data_time: 0.0243 memory: 16201 loss_prob: 0.3431 loss_thr: 0.2474 loss_db: 0.0616 loss: 0.6520 2022/08/30 21:58:18 - mmengine - INFO - Epoch(train) [1088][35/63] lr: 8.2890e-04 eta: 2:13:49 time: 0.7786 data_time: 0.0162 memory: 16201 loss_prob: 0.3417 loss_thr: 0.2447 loss_db: 0.0601 loss: 0.6465 2022/08/30 21:58:22 - mmengine - INFO - Epoch(train) [1088][40/63] lr: 8.2890e-04 eta: 2:13:37 time: 0.8249 data_time: 0.0254 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2276 loss_db: 0.0586 loss: 0.6172 2022/08/30 21:58:26 - mmengine - INFO - Epoch(train) [1088][45/63] lr: 8.2890e-04 eta: 2:13:37 time: 0.8151 data_time: 0.0251 memory: 16201 loss_prob: 0.3509 loss_thr: 0.2418 loss_db: 0.0639 loss: 0.6566 2022/08/30 21:58:30 - mmengine - INFO - Epoch(train) [1088][50/63] lr: 8.2890e-04 eta: 2:13:25 time: 0.7752 data_time: 0.0226 memory: 16201 loss_prob: 0.3473 loss_thr: 0.2480 loss_db: 0.0635 loss: 0.6588 2022/08/30 21:58:34 - mmengine - INFO - Epoch(train) [1088][55/63] lr: 8.2890e-04 eta: 2:13:25 time: 0.7818 data_time: 0.0231 memory: 16201 loss_prob: 0.3257 loss_thr: 0.2208 loss_db: 0.0577 loss: 0.6043 2022/08/30 21:58:38 - mmengine - INFO - Epoch(train) [1088][60/63] lr: 8.2890e-04 eta: 2:13:14 time: 0.7990 data_time: 0.0230 memory: 16201 loss_prob: 0.3004 loss_thr: 0.2048 loss_db: 0.0524 loss: 0.5575 2022/08/30 21:58:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:58:45 - mmengine - INFO - Epoch(train) [1089][5/63] lr: 8.2224e-04 eta: 2:13:14 time: 0.8932 data_time: 0.1456 memory: 16201 loss_prob: 0.2921 loss_thr: 0.2187 loss_db: 0.0522 loss: 0.5630 2022/08/30 21:58:49 - mmengine - INFO - Epoch(train) [1089][10/63] lr: 8.2224e-04 eta: 2:12:58 time: 0.9272 data_time: 0.1558 memory: 16201 loss_prob: 0.3379 loss_thr: 0.2417 loss_db: 0.0588 loss: 0.6384 2022/08/30 21:58:53 - mmengine - INFO - Epoch(train) [1089][15/63] lr: 8.2224e-04 eta: 2:12:58 time: 0.7854 data_time: 0.0245 memory: 16201 loss_prob: 0.3603 loss_thr: 0.2445 loss_db: 0.0624 loss: 0.6673 2022/08/30 21:58:57 - mmengine - INFO - Epoch(train) [1089][20/63] lr: 8.2224e-04 eta: 2:12:47 time: 0.7945 data_time: 0.0193 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2375 loss_db: 0.0612 loss: 0.6421 2022/08/30 21:59:01 - mmengine - INFO - Epoch(train) [1089][25/63] lr: 8.2224e-04 eta: 2:12:47 time: 0.8311 data_time: 0.0269 memory: 16201 loss_prob: 0.3093 loss_thr: 0.2228 loss_db: 0.0559 loss: 0.5880 2022/08/30 21:59:05 - mmengine - INFO - Epoch(train) [1089][30/63] lr: 8.2224e-04 eta: 2:12:35 time: 0.8096 data_time: 0.0264 memory: 16201 loss_prob: 0.3167 loss_thr: 0.2182 loss_db: 0.0578 loss: 0.5927 2022/08/30 21:59:09 - mmengine - INFO - Epoch(train) [1089][35/63] lr: 8.2224e-04 eta: 2:12:35 time: 0.7899 data_time: 0.0254 memory: 16201 loss_prob: 0.3321 loss_thr: 0.2260 loss_db: 0.0595 loss: 0.6176 2022/08/30 21:59:13 - mmengine - INFO - Epoch(train) [1089][40/63] lr: 8.2224e-04 eta: 2:12:23 time: 0.7977 data_time: 0.0247 memory: 16201 loss_prob: 0.3356 loss_thr: 0.2357 loss_db: 0.0598 loss: 0.6311 2022/08/30 21:59:17 - mmengine - INFO - Epoch(train) [1089][45/63] lr: 8.2224e-04 eta: 2:12:23 time: 0.8015 data_time: 0.0252 memory: 16201 loss_prob: 0.3333 loss_thr: 0.2358 loss_db: 0.0586 loss: 0.6278 2022/08/30 21:59:21 - mmengine - INFO - Epoch(train) [1089][50/63] lr: 8.2224e-04 eta: 2:12:12 time: 0.8000 data_time: 0.0276 memory: 16201 loss_prob: 0.2954 loss_thr: 0.2150 loss_db: 0.0515 loss: 0.5619 2022/08/30 21:59:25 - mmengine - INFO - Epoch(train) [1089][55/63] lr: 8.2224e-04 eta: 2:12:12 time: 0.7876 data_time: 0.0258 memory: 16201 loss_prob: 0.3141 loss_thr: 0.2271 loss_db: 0.0562 loss: 0.5974 2022/08/30 21:59:29 - mmengine - INFO - Epoch(train) [1089][60/63] lr: 8.2224e-04 eta: 2:12:00 time: 0.7960 data_time: 0.0232 memory: 16201 loss_prob: 0.3340 loss_thr: 0.2421 loss_db: 0.0602 loss: 0.6363 2022/08/30 21:59:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 21:59:37 - mmengine - INFO - Epoch(train) [1090][5/63] lr: 8.1557e-04 eta: 2:12:00 time: 0.9253 data_time: 0.2032 memory: 16201 loss_prob: 0.3446 loss_thr: 0.2456 loss_db: 0.0628 loss: 0.6529 2022/08/30 21:59:41 - mmengine - INFO - Epoch(train) [1090][10/63] lr: 8.1557e-04 eta: 2:11:45 time: 0.9767 data_time: 0.2162 memory: 16201 loss_prob: 0.3384 loss_thr: 0.2385 loss_db: 0.0608 loss: 0.6378 2022/08/30 21:59:45 - mmengine - INFO - Epoch(train) [1090][15/63] lr: 8.1557e-04 eta: 2:11:45 time: 0.7865 data_time: 0.0290 memory: 16201 loss_prob: 0.3072 loss_thr: 0.2153 loss_db: 0.0549 loss: 0.5774 2022/08/30 21:59:49 - mmengine - INFO - Epoch(train) [1090][20/63] lr: 8.1557e-04 eta: 2:11:33 time: 0.7928 data_time: 0.0159 memory: 16201 loss_prob: 0.2938 loss_thr: 0.2034 loss_db: 0.0522 loss: 0.5494 2022/08/30 21:59:53 - mmengine - INFO - Epoch(train) [1090][25/63] lr: 8.1557e-04 eta: 2:11:33 time: 0.8118 data_time: 0.0314 memory: 16201 loss_prob: 0.3008 loss_thr: 0.2123 loss_db: 0.0541 loss: 0.5671 2022/08/30 21:59:57 - mmengine - INFO - Epoch(train) [1090][30/63] lr: 8.1557e-04 eta: 2:11:22 time: 0.7913 data_time: 0.0246 memory: 16201 loss_prob: 0.2962 loss_thr: 0.2104 loss_db: 0.0529 loss: 0.5595 2022/08/30 22:00:01 - mmengine - INFO - Epoch(train) [1090][35/63] lr: 8.1557e-04 eta: 2:11:22 time: 0.7973 data_time: 0.0204 memory: 16201 loss_prob: 0.2885 loss_thr: 0.2049 loss_db: 0.0511 loss: 0.5445 2022/08/30 22:00:05 - mmengine - INFO - Epoch(train) [1090][40/63] lr: 8.1557e-04 eta: 2:11:10 time: 0.8174 data_time: 0.0319 memory: 16201 loss_prob: 0.3224 loss_thr: 0.2334 loss_db: 0.0570 loss: 0.6128 2022/08/30 22:00:09 - mmengine - INFO - Epoch(train) [1090][45/63] lr: 8.1557e-04 eta: 2:11:10 time: 0.8069 data_time: 0.0280 memory: 16201 loss_prob: 0.3322 loss_thr: 0.2372 loss_db: 0.0596 loss: 0.6289 2022/08/30 22:00:13 - mmengine - INFO - Epoch(train) [1090][50/63] lr: 8.1557e-04 eta: 2:10:58 time: 0.7907 data_time: 0.0267 memory: 16201 loss_prob: 0.3243 loss_thr: 0.2293 loss_db: 0.0587 loss: 0.6123 2022/08/30 22:00:17 - mmengine - INFO - Epoch(train) [1090][55/63] lr: 8.1557e-04 eta: 2:10:58 time: 0.7844 data_time: 0.0243 memory: 16201 loss_prob: 0.3340 loss_thr: 0.2198 loss_db: 0.0619 loss: 0.6156 2022/08/30 22:00:21 - mmengine - INFO - Epoch(train) [1090][60/63] lr: 8.1557e-04 eta: 2:10:47 time: 0.7912 data_time: 0.0217 memory: 16201 loss_prob: 0.3066 loss_thr: 0.2011 loss_db: 0.0574 loss: 0.5651 2022/08/30 22:00:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:00:29 - mmengine - INFO - Epoch(train) [1091][5/63] lr: 8.0889e-04 eta: 2:10:47 time: 0.9392 data_time: 0.1936 memory: 16201 loss_prob: 0.3213 loss_thr: 0.2204 loss_db: 0.0583 loss: 0.6000 2022/08/30 22:00:33 - mmengine - INFO - Epoch(train) [1091][10/63] lr: 8.0889e-04 eta: 2:10:31 time: 0.9920 data_time: 0.2080 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2349 loss_db: 0.0599 loss: 0.6268 2022/08/30 22:00:36 - mmengine - INFO - Epoch(train) [1091][15/63] lr: 8.0889e-04 eta: 2:10:31 time: 0.7912 data_time: 0.0242 memory: 16201 loss_prob: 0.3248 loss_thr: 0.2302 loss_db: 0.0584 loss: 0.6135 2022/08/30 22:00:41 - mmengine - INFO - Epoch(train) [1091][20/63] lr: 8.0889e-04 eta: 2:10:20 time: 0.8116 data_time: 0.0217 memory: 16201 loss_prob: 0.3159 loss_thr: 0.2226 loss_db: 0.0554 loss: 0.5939 2022/08/30 22:00:45 - mmengine - INFO - Epoch(train) [1091][25/63] lr: 8.0889e-04 eta: 2:10:20 time: 0.8129 data_time: 0.0261 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2362 loss_db: 0.0621 loss: 0.6514 2022/08/30 22:00:49 - mmengine - INFO - Epoch(train) [1091][30/63] lr: 8.0889e-04 eta: 2:10:08 time: 0.7982 data_time: 0.0232 memory: 16201 loss_prob: 0.3323 loss_thr: 0.2280 loss_db: 0.0598 loss: 0.6201 2022/08/30 22:00:53 - mmengine - INFO - Epoch(train) [1091][35/63] lr: 8.0889e-04 eta: 2:10:08 time: 0.8045 data_time: 0.0272 memory: 16201 loss_prob: 0.2888 loss_thr: 0.2164 loss_db: 0.0518 loss: 0.5570 2022/08/30 22:00:56 - mmengine - INFO - Epoch(train) [1091][40/63] lr: 8.0889e-04 eta: 2:09:56 time: 0.7822 data_time: 0.0230 memory: 16201 loss_prob: 0.3047 loss_thr: 0.2139 loss_db: 0.0538 loss: 0.5724 2022/08/30 22:01:01 - mmengine - INFO - Epoch(train) [1091][45/63] lr: 8.0889e-04 eta: 2:09:56 time: 0.7941 data_time: 0.0224 memory: 16201 loss_prob: 0.3168 loss_thr: 0.2180 loss_db: 0.0559 loss: 0.5907 2022/08/30 22:01:05 - mmengine - INFO - Epoch(train) [1091][50/63] lr: 8.0889e-04 eta: 2:09:45 time: 0.8083 data_time: 0.0262 memory: 16201 loss_prob: 0.3169 loss_thr: 0.2235 loss_db: 0.0585 loss: 0.5989 2022/08/30 22:01:09 - mmengine - INFO - Epoch(train) [1091][55/63] lr: 8.0889e-04 eta: 2:09:45 time: 0.8025 data_time: 0.0242 memory: 16201 loss_prob: 0.3139 loss_thr: 0.2349 loss_db: 0.0574 loss: 0.6061 2022/08/30 22:01:13 - mmengine - INFO - Epoch(train) [1091][60/63] lr: 8.0889e-04 eta: 2:09:33 time: 0.8063 data_time: 0.0314 memory: 16201 loss_prob: 0.3187 loss_thr: 0.2345 loss_db: 0.0562 loss: 0.6094 2022/08/30 22:01:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:01:20 - mmengine - INFO - Epoch(train) [1092][5/63] lr: 8.0221e-04 eta: 2:09:33 time: 0.9360 data_time: 0.2022 memory: 16201 loss_prob: 0.3309 loss_thr: 0.2235 loss_db: 0.0596 loss: 0.6140 2022/08/30 22:01:24 - mmengine - INFO - Epoch(train) [1092][10/63] lr: 8.0221e-04 eta: 2:09:18 time: 0.9734 data_time: 0.2068 memory: 16201 loss_prob: 0.3174 loss_thr: 0.2236 loss_db: 0.0554 loss: 0.5964 2022/08/30 22:01:29 - mmengine - INFO - Epoch(train) [1092][15/63] lr: 8.0221e-04 eta: 2:09:18 time: 0.8546 data_time: 0.0288 memory: 16201 loss_prob: 0.3244 loss_thr: 0.2275 loss_db: 0.0587 loss: 0.6106 2022/08/30 22:01:33 - mmengine - INFO - Epoch(train) [1092][20/63] lr: 8.0221e-04 eta: 2:09:06 time: 0.8532 data_time: 0.0280 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2386 loss_db: 0.0631 loss: 0.6485 2022/08/30 22:01:37 - mmengine - INFO - Epoch(train) [1092][25/63] lr: 8.0221e-04 eta: 2:09:06 time: 0.7853 data_time: 0.0251 memory: 16201 loss_prob: 0.3141 loss_thr: 0.2250 loss_db: 0.0555 loss: 0.5946 2022/08/30 22:01:41 - mmengine - INFO - Epoch(train) [1092][30/63] lr: 8.0221e-04 eta: 2:08:55 time: 0.7986 data_time: 0.0280 memory: 16201 loss_prob: 0.3008 loss_thr: 0.2173 loss_db: 0.0517 loss: 0.5698 2022/08/30 22:01:45 - mmengine - INFO - Epoch(train) [1092][35/63] lr: 8.0221e-04 eta: 2:08:55 time: 0.7937 data_time: 0.0278 memory: 16201 loss_prob: 0.3119 loss_thr: 0.2168 loss_db: 0.0558 loss: 0.5845 2022/08/30 22:01:49 - mmengine - INFO - Epoch(train) [1092][40/63] lr: 8.0221e-04 eta: 2:08:43 time: 0.7745 data_time: 0.0221 memory: 16201 loss_prob: 0.3035 loss_thr: 0.2161 loss_db: 0.0558 loss: 0.5754 2022/08/30 22:01:52 - mmengine - INFO - Epoch(train) [1092][45/63] lr: 8.0221e-04 eta: 2:08:43 time: 0.7814 data_time: 0.0231 memory: 16201 loss_prob: 0.3332 loss_thr: 0.2354 loss_db: 0.0594 loss: 0.6279 2022/08/30 22:01:56 - mmengine - INFO - Epoch(train) [1092][50/63] lr: 8.0221e-04 eta: 2:08:31 time: 0.7791 data_time: 0.0232 memory: 16201 loss_prob: 0.3631 loss_thr: 0.2543 loss_db: 0.0645 loss: 0.6819 2022/08/30 22:02:00 - mmengine - INFO - Epoch(train) [1092][55/63] lr: 8.0221e-04 eta: 2:08:31 time: 0.7777 data_time: 0.0248 memory: 16201 loss_prob: 0.3186 loss_thr: 0.2271 loss_db: 0.0583 loss: 0.6040 2022/08/30 22:02:04 - mmengine - INFO - Epoch(train) [1092][60/63] lr: 8.0221e-04 eta: 2:08:20 time: 0.7954 data_time: 0.0227 memory: 16201 loss_prob: 0.3094 loss_thr: 0.2208 loss_db: 0.0561 loss: 0.5864 2022/08/30 22:02:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:02:12 - mmengine - INFO - Epoch(train) [1093][5/63] lr: 7.9553e-04 eta: 2:08:20 time: 0.9491 data_time: 0.1936 memory: 16201 loss_prob: 0.3186 loss_thr: 0.2258 loss_db: 0.0562 loss: 0.6007 2022/08/30 22:02:16 - mmengine - INFO - Epoch(train) [1093][10/63] lr: 7.9553e-04 eta: 2:08:05 time: 0.9912 data_time: 0.2094 memory: 16201 loss_prob: 0.3094 loss_thr: 0.2193 loss_db: 0.0542 loss: 0.5828 2022/08/30 22:02:20 - mmengine - INFO - Epoch(train) [1093][15/63] lr: 7.9553e-04 eta: 2:08:05 time: 0.7932 data_time: 0.0272 memory: 16201 loss_prob: 0.3275 loss_thr: 0.2305 loss_db: 0.0595 loss: 0.6176 2022/08/30 22:02:24 - mmengine - INFO - Epoch(train) [1093][20/63] lr: 7.9553e-04 eta: 2:07:53 time: 0.8092 data_time: 0.0190 memory: 16201 loss_prob: 0.3052 loss_thr: 0.2198 loss_db: 0.0568 loss: 0.5817 2022/08/30 22:02:28 - mmengine - INFO - Epoch(train) [1093][25/63] lr: 7.9553e-04 eta: 2:07:53 time: 0.8332 data_time: 0.0288 memory: 16201 loss_prob: 0.3067 loss_thr: 0.2205 loss_db: 0.0553 loss: 0.5825 2022/08/30 22:02:32 - mmengine - INFO - Epoch(train) [1093][30/63] lr: 7.9553e-04 eta: 2:07:41 time: 0.7982 data_time: 0.0253 memory: 16201 loss_prob: 0.3550 loss_thr: 0.2432 loss_db: 0.0626 loss: 0.6609 2022/08/30 22:02:37 - mmengine - INFO - Epoch(train) [1093][35/63] lr: 7.9553e-04 eta: 2:07:41 time: 0.8071 data_time: 0.0486 memory: 16201 loss_prob: 0.3503 loss_thr: 0.2382 loss_db: 0.0611 loss: 0.6496 2022/08/30 22:02:41 - mmengine - INFO - Epoch(train) [1093][40/63] lr: 7.9553e-04 eta: 2:07:30 time: 0.8272 data_time: 0.0501 memory: 16201 loss_prob: 0.3175 loss_thr: 0.2194 loss_db: 0.0568 loss: 0.5937 2022/08/30 22:02:45 - mmengine - INFO - Epoch(train) [1093][45/63] lr: 7.9553e-04 eta: 2:07:30 time: 0.8144 data_time: 0.0247 memory: 16201 loss_prob: 0.3219 loss_thr: 0.2229 loss_db: 0.0586 loss: 0.6034 2022/08/30 22:02:49 - mmengine - INFO - Epoch(train) [1093][50/63] lr: 7.9553e-04 eta: 2:07:18 time: 0.8202 data_time: 0.0258 memory: 16201 loss_prob: 0.3279 loss_thr: 0.2274 loss_db: 0.0598 loss: 0.6150 2022/08/30 22:02:53 - mmengine - INFO - Epoch(train) [1093][55/63] lr: 7.9553e-04 eta: 2:07:18 time: 0.8018 data_time: 0.0251 memory: 16201 loss_prob: 0.3432 loss_thr: 0.2369 loss_db: 0.0617 loss: 0.6418 2022/08/30 22:02:57 - mmengine - INFO - Epoch(train) [1093][60/63] lr: 7.9553e-04 eta: 2:07:06 time: 0.7755 data_time: 0.0228 memory: 16201 loss_prob: 0.3292 loss_thr: 0.2314 loss_db: 0.0571 loss: 0.6177 2022/08/30 22:02:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:03:04 - mmengine - INFO - Epoch(train) [1094][5/63] lr: 7.8883e-04 eta: 2:07:06 time: 0.9223 data_time: 0.1898 memory: 16201 loss_prob: 0.3228 loss_thr: 0.2334 loss_db: 0.0568 loss: 0.6129 2022/08/30 22:03:08 - mmengine - INFO - Epoch(train) [1094][10/63] lr: 7.8883e-04 eta: 2:06:51 time: 0.9812 data_time: 0.2004 memory: 16201 loss_prob: 0.3236 loss_thr: 0.2390 loss_db: 0.0571 loss: 0.6197 2022/08/30 22:03:12 - mmengine - INFO - Epoch(train) [1094][15/63] lr: 7.8883e-04 eta: 2:06:51 time: 0.8138 data_time: 0.0367 memory: 16201 loss_prob: 0.3056 loss_thr: 0.2403 loss_db: 0.0540 loss: 0.5999 2022/08/30 22:03:16 - mmengine - INFO - Epoch(train) [1094][20/63] lr: 7.8883e-04 eta: 2:06:40 time: 0.8154 data_time: 0.0407 memory: 16201 loss_prob: 0.2986 loss_thr: 0.2264 loss_db: 0.0540 loss: 0.5790 2022/08/30 22:03:21 - mmengine - INFO - Epoch(train) [1094][25/63] lr: 7.8883e-04 eta: 2:06:40 time: 0.8789 data_time: 0.0725 memory: 16201 loss_prob: 0.2992 loss_thr: 0.2157 loss_db: 0.0548 loss: 0.5697 2022/08/30 22:03:25 - mmengine - INFO - Epoch(train) [1094][30/63] lr: 7.8883e-04 eta: 2:06:28 time: 0.8659 data_time: 0.0732 memory: 16201 loss_prob: 0.3481 loss_thr: 0.2439 loss_db: 0.0631 loss: 0.6550 2022/08/30 22:03:29 - mmengine - INFO - Epoch(train) [1094][35/63] lr: 7.8883e-04 eta: 2:06:28 time: 0.8054 data_time: 0.0461 memory: 16201 loss_prob: 0.3626 loss_thr: 0.2509 loss_db: 0.0657 loss: 0.6792 2022/08/30 22:03:34 - mmengine - INFO - Epoch(train) [1094][40/63] lr: 7.8883e-04 eta: 2:06:16 time: 0.8481 data_time: 0.0749 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2217 loss_db: 0.0576 loss: 0.6042 2022/08/30 22:03:38 - mmengine - INFO - Epoch(train) [1094][45/63] lr: 7.8883e-04 eta: 2:06:16 time: 0.8495 data_time: 0.0764 memory: 16201 loss_prob: 0.3142 loss_thr: 0.2194 loss_db: 0.0558 loss: 0.5893 2022/08/30 22:03:42 - mmengine - INFO - Epoch(train) [1094][50/63] lr: 7.8883e-04 eta: 2:06:05 time: 0.8208 data_time: 0.0476 memory: 16201 loss_prob: 0.3110 loss_thr: 0.2164 loss_db: 0.0570 loss: 0.5843 2022/08/30 22:03:46 - mmengine - INFO - Epoch(train) [1094][55/63] lr: 7.8883e-04 eta: 2:06:05 time: 0.8603 data_time: 0.0776 memory: 16201 loss_prob: 0.3008 loss_thr: 0.2052 loss_db: 0.0557 loss: 0.5616 2022/08/30 22:03:51 - mmengine - INFO - Epoch(train) [1094][60/63] lr: 7.8883e-04 eta: 2:05:53 time: 0.8776 data_time: 0.0825 memory: 16201 loss_prob: 0.3161 loss_thr: 0.2193 loss_db: 0.0573 loss: 0.5927 2022/08/30 22:03:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:03:59 - mmengine - INFO - Epoch(train) [1095][5/63] lr: 7.8213e-04 eta: 2:05:53 time: 0.9752 data_time: 0.2289 memory: 16201 loss_prob: 0.3349 loss_thr: 0.2392 loss_db: 0.0574 loss: 0.6314 2022/08/30 22:04:03 - mmengine - INFO - Epoch(train) [1095][10/63] lr: 7.8213e-04 eta: 2:05:38 time: 1.0505 data_time: 0.2724 memory: 16201 loss_prob: 0.4025 loss_thr: 0.2630 loss_db: 0.0697 loss: 0.7352 2022/08/30 22:04:07 - mmengine - INFO - Epoch(train) [1095][15/63] lr: 7.8213e-04 eta: 2:05:38 time: 0.8626 data_time: 0.0755 memory: 16201 loss_prob: 0.3996 loss_thr: 0.2648 loss_db: 0.0703 loss: 0.7347 2022/08/30 22:04:11 - mmengine - INFO - Epoch(train) [1095][20/63] lr: 7.8213e-04 eta: 2:05:27 time: 0.8083 data_time: 0.0407 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2316 loss_db: 0.0609 loss: 0.6264 2022/08/30 22:04:16 - mmengine - INFO - Epoch(train) [1095][25/63] lr: 7.8213e-04 eta: 2:05:27 time: 0.8502 data_time: 0.0840 memory: 16201 loss_prob: 0.2961 loss_thr: 0.2139 loss_db: 0.0537 loss: 0.5637 2022/08/30 22:04:20 - mmengine - INFO - Epoch(train) [1095][30/63] lr: 7.8213e-04 eta: 2:05:15 time: 0.8645 data_time: 0.0771 memory: 16201 loss_prob: 0.2885 loss_thr: 0.2121 loss_db: 0.0506 loss: 0.5512 2022/08/30 22:04:24 - mmengine - INFO - Epoch(train) [1095][35/63] lr: 7.8213e-04 eta: 2:05:15 time: 0.8240 data_time: 0.0423 memory: 16201 loss_prob: 0.3147 loss_thr: 0.2185 loss_db: 0.0567 loss: 0.5899 2022/08/30 22:04:28 - mmengine - INFO - Epoch(train) [1095][40/63] lr: 7.8213e-04 eta: 2:05:03 time: 0.8363 data_time: 0.0736 memory: 16201 loss_prob: 0.3287 loss_thr: 0.2247 loss_db: 0.0605 loss: 0.6138 2022/08/30 22:04:32 - mmengine - INFO - Epoch(train) [1095][45/63] lr: 7.8213e-04 eta: 2:05:03 time: 0.8361 data_time: 0.0740 memory: 16201 loss_prob: 0.3280 loss_thr: 0.2311 loss_db: 0.0601 loss: 0.6191 2022/08/30 22:04:37 - mmengine - INFO - Epoch(train) [1095][50/63] lr: 7.8213e-04 eta: 2:04:52 time: 0.8155 data_time: 0.0476 memory: 16201 loss_prob: 0.3322 loss_thr: 0.2366 loss_db: 0.0583 loss: 0.6272 2022/08/30 22:04:41 - mmengine - INFO - Epoch(train) [1095][55/63] lr: 7.8213e-04 eta: 2:04:52 time: 0.8707 data_time: 0.0726 memory: 16201 loss_prob: 0.3502 loss_thr: 0.2507 loss_db: 0.0600 loss: 0.6609 2022/08/30 22:04:45 - mmengine - INFO - Epoch(train) [1095][60/63] lr: 7.8213e-04 eta: 2:04:40 time: 0.8868 data_time: 0.0787 memory: 16201 loss_prob: 0.3569 loss_thr: 0.2492 loss_db: 0.0630 loss: 0.6691 2022/08/30 22:04:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:04:54 - mmengine - INFO - Epoch(train) [1096][5/63] lr: 7.7543e-04 eta: 2:04:40 time: 0.9639 data_time: 0.2268 memory: 16201 loss_prob: 0.3142 loss_thr: 0.2238 loss_db: 0.0558 loss: 0.5937 2022/08/30 22:04:58 - mmengine - INFO - Epoch(train) [1096][10/63] lr: 7.7543e-04 eta: 2:04:25 time: 1.0527 data_time: 0.2667 memory: 16201 loss_prob: 0.3157 loss_thr: 0.2231 loss_db: 0.0567 loss: 0.5955 2022/08/30 22:05:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:05:02 - mmengine - INFO - Epoch(train) [1096][15/63] lr: 7.7543e-04 eta: 2:04:25 time: 0.8570 data_time: 0.0756 memory: 16201 loss_prob: 0.3325 loss_thr: 0.2373 loss_db: 0.0605 loss: 0.6304 2022/08/30 22:05:06 - mmengine - INFO - Epoch(train) [1096][20/63] lr: 7.7543e-04 eta: 2:04:14 time: 0.8325 data_time: 0.0474 memory: 16201 loss_prob: 0.3279 loss_thr: 0.2278 loss_db: 0.0587 loss: 0.6144 2022/08/30 22:05:11 - mmengine - INFO - Epoch(train) [1096][25/63] lr: 7.7543e-04 eta: 2:04:14 time: 0.8774 data_time: 0.0888 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2408 loss_db: 0.0594 loss: 0.6368 2022/08/30 22:05:15 - mmengine - INFO - Epoch(train) [1096][30/63] lr: 7.7543e-04 eta: 2:04:02 time: 0.8463 data_time: 0.0764 memory: 16201 loss_prob: 0.3679 loss_thr: 0.2645 loss_db: 0.0654 loss: 0.6978 2022/08/30 22:05:19 - mmengine - INFO - Epoch(train) [1096][35/63] lr: 7.7543e-04 eta: 2:04:02 time: 0.8269 data_time: 0.0424 memory: 16201 loss_prob: 0.3282 loss_thr: 0.2298 loss_db: 0.0599 loss: 0.6179 2022/08/30 22:05:24 - mmengine - INFO - Epoch(train) [1096][40/63] lr: 7.7543e-04 eta: 2:03:50 time: 0.8584 data_time: 0.0835 memory: 16201 loss_prob: 0.3240 loss_thr: 0.2260 loss_db: 0.0590 loss: 0.6090 2022/08/30 22:05:28 - mmengine - INFO - Epoch(train) [1096][45/63] lr: 7.7543e-04 eta: 2:03:50 time: 0.8509 data_time: 0.0816 memory: 16201 loss_prob: 0.3222 loss_thr: 0.2336 loss_db: 0.0582 loss: 0.6140 2022/08/30 22:05:32 - mmengine - INFO - Epoch(train) [1096][50/63] lr: 7.7543e-04 eta: 2:03:39 time: 0.8241 data_time: 0.0472 memory: 16201 loss_prob: 0.2952 loss_thr: 0.2127 loss_db: 0.0536 loss: 0.5615 2022/08/30 22:05:36 - mmengine - INFO - Epoch(train) [1096][55/63] lr: 7.7543e-04 eta: 2:03:39 time: 0.8725 data_time: 0.0751 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2298 loss_db: 0.0589 loss: 0.6231 2022/08/30 22:05:40 - mmengine - INFO - Epoch(train) [1096][60/63] lr: 7.7543e-04 eta: 2:03:27 time: 0.8704 data_time: 0.0621 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2509 loss_db: 0.0644 loss: 0.6795 2022/08/30 22:05:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:05:48 - mmengine - INFO - Epoch(train) [1097][5/63] lr: 7.6871e-04 eta: 2:03:27 time: 0.9350 data_time: 0.1821 memory: 16201 loss_prob: 0.3051 loss_thr: 0.2246 loss_db: 0.0551 loss: 0.5848 2022/08/30 22:05:52 - mmengine - INFO - Epoch(train) [1097][10/63] lr: 7.6871e-04 eta: 2:03:12 time: 0.9740 data_time: 0.1948 memory: 16201 loss_prob: 0.3074 loss_thr: 0.2286 loss_db: 0.0547 loss: 0.5907 2022/08/30 22:05:56 - mmengine - INFO - Epoch(train) [1097][15/63] lr: 7.6871e-04 eta: 2:03:12 time: 0.8090 data_time: 0.0293 memory: 16201 loss_prob: 0.3205 loss_thr: 0.2347 loss_db: 0.0570 loss: 0.6122 2022/08/30 22:06:00 - mmengine - INFO - Epoch(train) [1097][20/63] lr: 7.6871e-04 eta: 2:03:01 time: 0.8005 data_time: 0.0208 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2366 loss_db: 0.0590 loss: 0.6295 2022/08/30 22:06:04 - mmengine - INFO - Epoch(train) [1097][25/63] lr: 7.6871e-04 eta: 2:03:01 time: 0.7935 data_time: 0.0302 memory: 16201 loss_prob: 0.3311 loss_thr: 0.2340 loss_db: 0.0583 loss: 0.6234 2022/08/30 22:06:08 - mmengine - INFO - Epoch(train) [1097][30/63] lr: 7.6871e-04 eta: 2:02:49 time: 0.8144 data_time: 0.0296 memory: 16201 loss_prob: 0.3158 loss_thr: 0.2237 loss_db: 0.0564 loss: 0.5959 2022/08/30 22:06:12 - mmengine - INFO - Epoch(train) [1097][35/63] lr: 7.6871e-04 eta: 2:02:49 time: 0.8106 data_time: 0.0239 memory: 16201 loss_prob: 0.2831 loss_thr: 0.2063 loss_db: 0.0516 loss: 0.5410 2022/08/30 22:06:16 - mmengine - INFO - Epoch(train) [1097][40/63] lr: 7.6871e-04 eta: 2:02:37 time: 0.7892 data_time: 0.0268 memory: 16201 loss_prob: 0.3020 loss_thr: 0.2158 loss_db: 0.0546 loss: 0.5724 2022/08/30 22:06:20 - mmengine - INFO - Epoch(train) [1097][45/63] lr: 7.6871e-04 eta: 2:02:37 time: 0.8107 data_time: 0.0264 memory: 16201 loss_prob: 0.3478 loss_thr: 0.2377 loss_db: 0.0626 loss: 0.6480 2022/08/30 22:06:25 - mmengine - INFO - Epoch(train) [1097][50/63] lr: 7.6871e-04 eta: 2:02:26 time: 0.8405 data_time: 0.0242 memory: 16201 loss_prob: 0.3252 loss_thr: 0.2277 loss_db: 0.0590 loss: 0.6119 2022/08/30 22:06:29 - mmengine - INFO - Epoch(train) [1097][55/63] lr: 7.6871e-04 eta: 2:02:26 time: 0.8289 data_time: 0.0309 memory: 16201 loss_prob: 0.3260 loss_thr: 0.2404 loss_db: 0.0581 loss: 0.6245 2022/08/30 22:06:33 - mmengine - INFO - Epoch(train) [1097][60/63] lr: 7.6871e-04 eta: 2:02:14 time: 0.7956 data_time: 0.0301 memory: 16201 loss_prob: 0.3466 loss_thr: 0.2566 loss_db: 0.0608 loss: 0.6640 2022/08/30 22:06:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:06:40 - mmengine - INFO - Epoch(train) [1098][5/63] lr: 7.6199e-04 eta: 2:02:14 time: 0.9323 data_time: 0.1903 memory: 16201 loss_prob: 0.3551 loss_thr: 0.2570 loss_db: 0.0613 loss: 0.6734 2022/08/30 22:06:44 - mmengine - INFO - Epoch(train) [1098][10/63] lr: 7.6199e-04 eta: 2:01:59 time: 0.9843 data_time: 0.2007 memory: 16201 loss_prob: 0.3172 loss_thr: 0.2383 loss_db: 0.0563 loss: 0.6117 2022/08/30 22:06:49 - mmengine - INFO - Epoch(train) [1098][15/63] lr: 7.6199e-04 eta: 2:01:59 time: 0.8115 data_time: 0.0260 memory: 16201 loss_prob: 0.3008 loss_thr: 0.2335 loss_db: 0.0542 loss: 0.5884 2022/08/30 22:06:53 - mmengine - INFO - Epoch(train) [1098][20/63] lr: 7.6199e-04 eta: 2:01:47 time: 0.8092 data_time: 0.0242 memory: 16201 loss_prob: 0.3102 loss_thr: 0.2345 loss_db: 0.0562 loss: 0.6008 2022/08/30 22:06:57 - mmengine - INFO - Epoch(train) [1098][25/63] lr: 7.6199e-04 eta: 2:01:47 time: 0.7953 data_time: 0.0274 memory: 16201 loss_prob: 0.3101 loss_thr: 0.2339 loss_db: 0.0546 loss: 0.5985 2022/08/30 22:07:01 - mmengine - INFO - Epoch(train) [1098][30/63] lr: 7.6199e-04 eta: 2:01:36 time: 0.8059 data_time: 0.0259 memory: 16201 loss_prob: 0.2972 loss_thr: 0.2180 loss_db: 0.0536 loss: 0.5688 2022/08/30 22:07:05 - mmengine - INFO - Epoch(train) [1098][35/63] lr: 7.6199e-04 eta: 2:01:36 time: 0.8001 data_time: 0.0238 memory: 16201 loss_prob: 0.3001 loss_thr: 0.2110 loss_db: 0.0553 loss: 0.5665 2022/08/30 22:07:09 - mmengine - INFO - Epoch(train) [1098][40/63] lr: 7.6199e-04 eta: 2:01:24 time: 0.8174 data_time: 0.0227 memory: 16201 loss_prob: 0.3219 loss_thr: 0.2249 loss_db: 0.0579 loss: 0.6048 2022/08/30 22:07:13 - mmengine - INFO - Epoch(train) [1098][45/63] lr: 7.6199e-04 eta: 2:01:24 time: 0.8226 data_time: 0.0268 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2390 loss_db: 0.0611 loss: 0.6388 2022/08/30 22:07:17 - mmengine - INFO - Epoch(train) [1098][50/63] lr: 7.6199e-04 eta: 2:01:13 time: 0.7917 data_time: 0.0243 memory: 16201 loss_prob: 0.3539 loss_thr: 0.2540 loss_db: 0.0639 loss: 0.6718 2022/08/30 22:07:21 - mmengine - INFO - Epoch(train) [1098][55/63] lr: 7.6199e-04 eta: 2:01:13 time: 0.7945 data_time: 0.0251 memory: 16201 loss_prob: 0.3482 loss_thr: 0.2494 loss_db: 0.0626 loss: 0.6602 2022/08/30 22:07:25 - mmengine - INFO - Epoch(train) [1098][60/63] lr: 7.6199e-04 eta: 2:01:01 time: 0.8031 data_time: 0.0260 memory: 16201 loss_prob: 0.3337 loss_thr: 0.2310 loss_db: 0.0579 loss: 0.6226 2022/08/30 22:07:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:07:33 - mmengine - INFO - Epoch(train) [1099][5/63] lr: 7.5527e-04 eta: 2:01:01 time: 0.9648 data_time: 0.2016 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2355 loss_db: 0.0569 loss: 0.6215 2022/08/30 22:07:37 - mmengine - INFO - Epoch(train) [1099][10/63] lr: 7.5527e-04 eta: 2:00:46 time: 1.0009 data_time: 0.2122 memory: 16201 loss_prob: 0.3035 loss_thr: 0.2301 loss_db: 0.0553 loss: 0.5889 2022/08/30 22:07:41 - mmengine - INFO - Epoch(train) [1099][15/63] lr: 7.5527e-04 eta: 2:00:46 time: 0.7883 data_time: 0.0265 memory: 16201 loss_prob: 0.3156 loss_thr: 0.2307 loss_db: 0.0580 loss: 0.6043 2022/08/30 22:07:45 - mmengine - INFO - Epoch(train) [1099][20/63] lr: 7.5527e-04 eta: 2:00:34 time: 0.7859 data_time: 0.0196 memory: 16201 loss_prob: 0.3098 loss_thr: 0.2272 loss_db: 0.0561 loss: 0.5930 2022/08/30 22:07:49 - mmengine - INFO - Epoch(train) [1099][25/63] lr: 7.5527e-04 eta: 2:00:34 time: 0.8714 data_time: 0.0311 memory: 16201 loss_prob: 0.3084 loss_thr: 0.2282 loss_db: 0.0544 loss: 0.5910 2022/08/30 22:07:53 - mmengine - INFO - Epoch(train) [1099][30/63] lr: 7.5527e-04 eta: 2:00:23 time: 0.8698 data_time: 0.0276 memory: 16201 loss_prob: 0.3237 loss_thr: 0.2394 loss_db: 0.0579 loss: 0.6209 2022/08/30 22:07:57 - mmengine - INFO - Epoch(train) [1099][35/63] lr: 7.5527e-04 eta: 2:00:23 time: 0.7903 data_time: 0.0227 memory: 16201 loss_prob: 0.3294 loss_thr: 0.2386 loss_db: 0.0606 loss: 0.6285 2022/08/30 22:08:01 - mmengine - INFO - Epoch(train) [1099][40/63] lr: 7.5527e-04 eta: 2:00:11 time: 0.7916 data_time: 0.0243 memory: 16201 loss_prob: 0.3130 loss_thr: 0.2269 loss_db: 0.0580 loss: 0.5979 2022/08/30 22:08:05 - mmengine - INFO - Epoch(train) [1099][45/63] lr: 7.5527e-04 eta: 2:00:11 time: 0.8000 data_time: 0.0240 memory: 16201 loss_prob: 0.3100 loss_thr: 0.2193 loss_db: 0.0552 loss: 0.5845 2022/08/30 22:08:09 - mmengine - INFO - Epoch(train) [1099][50/63] lr: 7.5527e-04 eta: 2:00:00 time: 0.7964 data_time: 0.0230 memory: 16201 loss_prob: 0.3248 loss_thr: 0.2249 loss_db: 0.0555 loss: 0.6053 2022/08/30 22:08:13 - mmengine - INFO - Epoch(train) [1099][55/63] lr: 7.5527e-04 eta: 2:00:00 time: 0.7980 data_time: 0.0236 memory: 16201 loss_prob: 0.3283 loss_thr: 0.2259 loss_db: 0.0574 loss: 0.6116 2022/08/30 22:08:17 - mmengine - INFO - Epoch(train) [1099][60/63] lr: 7.5527e-04 eta: 1:59:48 time: 0.7955 data_time: 0.0262 memory: 16201 loss_prob: 0.3054 loss_thr: 0.2228 loss_db: 0.0557 loss: 0.5838 2022/08/30 22:08:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:08:25 - mmengine - INFO - Epoch(train) [1100][5/63] lr: 7.4854e-04 eta: 1:59:48 time: 0.9660 data_time: 0.1926 memory: 16201 loss_prob: 0.2972 loss_thr: 0.2172 loss_db: 0.0545 loss: 0.5689 2022/08/30 22:08:29 - mmengine - INFO - Epoch(train) [1100][10/63] lr: 7.4854e-04 eta: 1:59:33 time: 0.9674 data_time: 0.1982 memory: 16201 loss_prob: 0.3173 loss_thr: 0.2236 loss_db: 0.0566 loss: 0.5975 2022/08/30 22:08:33 - mmengine - INFO - Epoch(train) [1100][15/63] lr: 7.4854e-04 eta: 1:59:33 time: 0.7781 data_time: 0.0243 memory: 16201 loss_prob: 0.3152 loss_thr: 0.2205 loss_db: 0.0556 loss: 0.5914 2022/08/30 22:08:37 - mmengine - INFO - Epoch(train) [1100][20/63] lr: 7.4854e-04 eta: 1:59:21 time: 0.7794 data_time: 0.0199 memory: 16201 loss_prob: 0.3203 loss_thr: 0.2233 loss_db: 0.0575 loss: 0.6011 2022/08/30 22:08:42 - mmengine - INFO - Epoch(train) [1100][25/63] lr: 7.4854e-04 eta: 1:59:21 time: 0.8721 data_time: 0.0279 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2234 loss_db: 0.0570 loss: 0.5982 2022/08/30 22:08:46 - mmengine - INFO - Epoch(train) [1100][30/63] lr: 7.4854e-04 eta: 1:59:10 time: 0.8713 data_time: 0.0301 memory: 16201 loss_prob: 0.3229 loss_thr: 0.2205 loss_db: 0.0584 loss: 0.6018 2022/08/30 22:08:50 - mmengine - INFO - Epoch(train) [1100][35/63] lr: 7.4854e-04 eta: 1:59:10 time: 0.8128 data_time: 0.0195 memory: 16201 loss_prob: 0.3189 loss_thr: 0.2192 loss_db: 0.0580 loss: 0.5960 2022/08/30 22:08:54 - mmengine - INFO - Epoch(train) [1100][40/63] lr: 7.4854e-04 eta: 1:58:58 time: 0.8339 data_time: 0.0237 memory: 16201 loss_prob: 0.3034 loss_thr: 0.2154 loss_db: 0.0539 loss: 0.5727 2022/08/30 22:08:58 - mmengine - INFO - Epoch(train) [1100][45/63] lr: 7.4854e-04 eta: 1:58:58 time: 0.8125 data_time: 0.0309 memory: 16201 loss_prob: 0.3093 loss_thr: 0.2347 loss_db: 0.0543 loss: 0.5982 2022/08/30 22:09:02 - mmengine - INFO - Epoch(train) [1100][50/63] lr: 7.4854e-04 eta: 1:58:47 time: 0.7990 data_time: 0.0256 memory: 16201 loss_prob: 0.3103 loss_thr: 0.2442 loss_db: 0.0553 loss: 0.6098 2022/08/30 22:09:06 - mmengine - INFO - Epoch(train) [1100][55/63] lr: 7.4854e-04 eta: 1:58:47 time: 0.8122 data_time: 0.0257 memory: 16201 loss_prob: 0.3042 loss_thr: 0.2205 loss_db: 0.0558 loss: 0.5805 2022/08/30 22:09:10 - mmengine - INFO - Epoch(train) [1100][60/63] lr: 7.4854e-04 eta: 1:58:35 time: 0.8128 data_time: 0.0274 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2361 loss_db: 0.0616 loss: 0.6388 2022/08/30 22:09:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:09:13 - mmengine - INFO - Saving checkpoint at 1100 epochs 2022/08/30 22:09:21 - mmengine - INFO - Epoch(val) [1100][5/32] eta: 1:58:35 time: 0.6432 data_time: 0.1212 memory: 16201 2022/08/30 22:09:24 - mmengine - INFO - Epoch(val) [1100][10/32] eta: 0:00:15 time: 0.6978 data_time: 0.1336 memory: 15734 2022/08/30 22:09:27 - mmengine - INFO - Epoch(val) [1100][15/32] eta: 0:00:15 time: 0.5943 data_time: 0.0481 memory: 15734 2022/08/30 22:09:31 - mmengine - INFO - Epoch(val) [1100][20/32] eta: 0:00:07 time: 0.6461 data_time: 0.0663 memory: 15734 2022/08/30 22:09:34 - mmengine - INFO - Epoch(val) [1100][25/32] eta: 0:00:07 time: 0.6569 data_time: 0.0601 memory: 15734 2022/08/30 22:09:36 - mmengine - INFO - Epoch(val) [1100][30/32] eta: 0:00:01 time: 0.5865 data_time: 0.0363 memory: 15734 2022/08/30 22:09:37 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 22:09:37 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8459, precision: 0.8153, hmean: 0.8303 2022/08/30 22:09:37 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8459, precision: 0.8391, hmean: 0.8425 2022/08/30 22:09:37 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8459, precision: 0.8583, hmean: 0.8521 2022/08/30 22:09:37 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8421, precision: 0.8758, hmean: 0.8586 2022/08/30 22:09:37 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8373, precision: 0.8900, hmean: 0.8628 2022/08/30 22:09:37 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8204, precision: 0.9161, hmean: 0.8656 2022/08/30 22:09:37 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.5142, precision: 0.9536, hmean: 0.6681 2022/08/30 22:09:37 - mmengine - INFO - Epoch(val) [1100][32/32] icdar/precision: 0.9161 icdar/recall: 0.8204 icdar/hmean: 0.8656 2022/08/30 22:09:43 - mmengine - INFO - Epoch(train) [1101][5/63] lr: 7.4180e-04 eta: 0:00:01 time: 0.9969 data_time: 0.2015 memory: 16201 loss_prob: 0.3384 loss_thr: 0.2314 loss_db: 0.0597 loss: 0.6295 2022/08/30 22:09:47 - mmengine - INFO - Epoch(train) [1101][10/63] lr: 7.4180e-04 eta: 1:58:20 time: 0.9873 data_time: 0.2095 memory: 16201 loss_prob: 0.3312 loss_thr: 0.2287 loss_db: 0.0594 loss: 0.6192 2022/08/30 22:09:51 - mmengine - INFO - Epoch(train) [1101][15/63] lr: 7.4180e-04 eta: 1:58:20 time: 0.8022 data_time: 0.0206 memory: 16201 loss_prob: 0.3136 loss_thr: 0.2223 loss_db: 0.0569 loss: 0.5928 2022/08/30 22:09:55 - mmengine - INFO - Epoch(train) [1101][20/63] lr: 7.4180e-04 eta: 1:58:08 time: 0.8097 data_time: 0.0258 memory: 16201 loss_prob: 0.2782 loss_thr: 0.2108 loss_db: 0.0502 loss: 0.5392 2022/08/30 22:09:59 - mmengine - INFO - Epoch(train) [1101][25/63] lr: 7.4180e-04 eta: 1:58:08 time: 0.8104 data_time: 0.0349 memory: 16201 loss_prob: 0.3077 loss_thr: 0.2264 loss_db: 0.0547 loss: 0.5889 2022/08/30 22:10:03 - mmengine - INFO - Epoch(train) [1101][30/63] lr: 7.4180e-04 eta: 1:57:57 time: 0.7935 data_time: 0.0185 memory: 16201 loss_prob: 0.2845 loss_thr: 0.2100 loss_db: 0.0517 loss: 0.5462 2022/08/30 22:10:07 - mmengine - INFO - Epoch(train) [1101][35/63] lr: 7.4180e-04 eta: 1:57:57 time: 0.8096 data_time: 0.0272 memory: 16201 loss_prob: 0.3129 loss_thr: 0.2209 loss_db: 0.0562 loss: 0.5900 2022/08/30 22:10:11 - mmengine - INFO - Epoch(train) [1101][40/63] lr: 7.4180e-04 eta: 1:57:45 time: 0.8088 data_time: 0.0276 memory: 16201 loss_prob: 0.3446 loss_thr: 0.2393 loss_db: 0.0605 loss: 0.6445 2022/08/30 22:10:15 - mmengine - INFO - Epoch(train) [1101][45/63] lr: 7.4180e-04 eta: 1:57:45 time: 0.7967 data_time: 0.0174 memory: 16201 loss_prob: 0.3066 loss_thr: 0.2218 loss_db: 0.0557 loss: 0.5840 2022/08/30 22:10:19 - mmengine - INFO - Epoch(train) [1101][50/63] lr: 7.4180e-04 eta: 1:57:34 time: 0.8114 data_time: 0.0321 memory: 16201 loss_prob: 0.3292 loss_thr: 0.2307 loss_db: 0.0591 loss: 0.6190 2022/08/30 22:10:23 - mmengine - INFO - Epoch(train) [1101][55/63] lr: 7.4180e-04 eta: 1:57:34 time: 0.7940 data_time: 0.0273 memory: 16201 loss_prob: 0.3434 loss_thr: 0.2282 loss_db: 0.0608 loss: 0.6324 2022/08/30 22:10:27 - mmengine - INFO - Epoch(train) [1101][60/63] lr: 7.4180e-04 eta: 1:57:22 time: 0.8185 data_time: 0.0267 memory: 16201 loss_prob: 0.3083 loss_thr: 0.2085 loss_db: 0.0554 loss: 0.5722 2022/08/30 22:10:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:10:35 - mmengine - INFO - Epoch(train) [1102][5/63] lr: 7.3505e-04 eta: 1:57:22 time: 0.9295 data_time: 0.1951 memory: 16201 loss_prob: 0.3121 loss_thr: 0.2181 loss_db: 0.0559 loss: 0.5861 2022/08/30 22:10:39 - mmengine - INFO - Epoch(train) [1102][10/63] lr: 7.3505e-04 eta: 1:57:07 time: 0.9756 data_time: 0.1976 memory: 16201 loss_prob: 0.3309 loss_thr: 0.2257 loss_db: 0.0581 loss: 0.6147 2022/08/30 22:10:43 - mmengine - INFO - Epoch(train) [1102][15/63] lr: 7.3505e-04 eta: 1:57:07 time: 0.8203 data_time: 0.0237 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2253 loss_db: 0.0581 loss: 0.6086 2022/08/30 22:10:47 - mmengine - INFO - Epoch(train) [1102][20/63] lr: 7.3505e-04 eta: 1:56:55 time: 0.8071 data_time: 0.0257 memory: 16201 loss_prob: 0.3246 loss_thr: 0.2210 loss_db: 0.0579 loss: 0.6036 2022/08/30 22:10:51 - mmengine - INFO - Epoch(train) [1102][25/63] lr: 7.3505e-04 eta: 1:56:55 time: 0.7954 data_time: 0.0289 memory: 16201 loss_prob: 0.3263 loss_thr: 0.2230 loss_db: 0.0579 loss: 0.6073 2022/08/30 22:10:55 - mmengine - INFO - Epoch(train) [1102][30/63] lr: 7.3505e-04 eta: 1:56:44 time: 0.8105 data_time: 0.0266 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2293 loss_db: 0.0584 loss: 0.6176 2022/08/30 22:11:00 - mmengine - INFO - Epoch(train) [1102][35/63] lr: 7.3505e-04 eta: 1:56:44 time: 0.8094 data_time: 0.0262 memory: 16201 loss_prob: 0.3131 loss_thr: 0.2206 loss_db: 0.0552 loss: 0.5889 2022/08/30 22:11:03 - mmengine - INFO - Epoch(train) [1102][40/63] lr: 7.3505e-04 eta: 1:56:32 time: 0.7995 data_time: 0.0237 memory: 16201 loss_prob: 0.2864 loss_thr: 0.2130 loss_db: 0.0517 loss: 0.5511 2022/08/30 22:11:07 - mmengine - INFO - Epoch(train) [1102][45/63] lr: 7.3505e-04 eta: 1:56:32 time: 0.7901 data_time: 0.0244 memory: 16201 loss_prob: 0.2972 loss_thr: 0.2203 loss_db: 0.0539 loss: 0.5715 2022/08/30 22:11:11 - mmengine - INFO - Epoch(train) [1102][50/63] lr: 7.3505e-04 eta: 1:56:21 time: 0.7893 data_time: 0.0263 memory: 16201 loss_prob: 0.3192 loss_thr: 0.2320 loss_db: 0.0573 loss: 0.6085 2022/08/30 22:11:15 - mmengine - INFO - Epoch(train) [1102][55/63] lr: 7.3505e-04 eta: 1:56:21 time: 0.7923 data_time: 0.0232 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2441 loss_db: 0.0628 loss: 0.6575 2022/08/30 22:11:20 - mmengine - INFO - Epoch(train) [1102][60/63] lr: 7.3505e-04 eta: 1:56:09 time: 0.8175 data_time: 0.0294 memory: 16201 loss_prob: 0.3265 loss_thr: 0.2288 loss_db: 0.0597 loss: 0.6150 2022/08/30 22:11:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:11:27 - mmengine - INFO - Epoch(train) [1103][5/63] lr: 7.2830e-04 eta: 1:56:09 time: 0.8869 data_time: 0.1574 memory: 16201 loss_prob: 0.3200 loss_thr: 0.2208 loss_db: 0.0577 loss: 0.5985 2022/08/30 22:11:31 - mmengine - INFO - Epoch(train) [1103][10/63] lr: 7.2830e-04 eta: 1:55:54 time: 0.9448 data_time: 0.1714 memory: 16201 loss_prob: 0.3153 loss_thr: 0.2164 loss_db: 0.0542 loss: 0.5859 2022/08/30 22:11:35 - mmengine - INFO - Epoch(train) [1103][15/63] lr: 7.2830e-04 eta: 1:55:54 time: 0.8052 data_time: 0.0297 memory: 16201 loss_prob: 0.3153 loss_thr: 0.2228 loss_db: 0.0545 loss: 0.5926 2022/08/30 22:11:39 - mmengine - INFO - Epoch(train) [1103][20/63] lr: 7.2830e-04 eta: 1:55:42 time: 0.7915 data_time: 0.0195 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2264 loss_db: 0.0580 loss: 0.6058 2022/08/30 22:11:43 - mmengine - INFO - Epoch(train) [1103][25/63] lr: 7.2830e-04 eta: 1:55:42 time: 0.8002 data_time: 0.0280 memory: 16201 loss_prob: 0.3161 loss_thr: 0.2203 loss_db: 0.0582 loss: 0.5946 2022/08/30 22:11:47 - mmengine - INFO - Epoch(train) [1103][30/63] lr: 7.2830e-04 eta: 1:55:31 time: 0.7953 data_time: 0.0226 memory: 16201 loss_prob: 0.3259 loss_thr: 0.2216 loss_db: 0.0591 loss: 0.6066 2022/08/30 22:11:51 - mmengine - INFO - Epoch(train) [1103][35/63] lr: 7.2830e-04 eta: 1:55:31 time: 0.8239 data_time: 0.0178 memory: 16201 loss_prob: 0.3138 loss_thr: 0.2145 loss_db: 0.0566 loss: 0.5849 2022/08/30 22:11:55 - mmengine - INFO - Epoch(train) [1103][40/63] lr: 7.2830e-04 eta: 1:55:19 time: 0.8164 data_time: 0.0239 memory: 16201 loss_prob: 0.3121 loss_thr: 0.2194 loss_db: 0.0567 loss: 0.5882 2022/08/30 22:11:59 - mmengine - INFO - Epoch(train) [1103][45/63] lr: 7.2830e-04 eta: 1:55:19 time: 0.7990 data_time: 0.0247 memory: 16201 loss_prob: 0.3070 loss_thr: 0.2218 loss_db: 0.0548 loss: 0.5835 2022/08/30 22:12:03 - mmengine - INFO - Epoch(train) [1103][50/63] lr: 7.2830e-04 eta: 1:55:08 time: 0.8006 data_time: 0.0230 memory: 16201 loss_prob: 0.3007 loss_thr: 0.2155 loss_db: 0.0520 loss: 0.5683 2022/08/30 22:12:07 - mmengine - INFO - Epoch(train) [1103][55/63] lr: 7.2830e-04 eta: 1:55:08 time: 0.7779 data_time: 0.0226 memory: 16201 loss_prob: 0.3383 loss_thr: 0.2378 loss_db: 0.0597 loss: 0.6359 2022/08/30 22:12:11 - mmengine - INFO - Epoch(train) [1103][60/63] lr: 7.2830e-04 eta: 1:54:56 time: 0.8344 data_time: 0.0261 memory: 16201 loss_prob: 0.3368 loss_thr: 0.2410 loss_db: 0.0613 loss: 0.6392 2022/08/30 22:12:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:12:19 - mmengine - INFO - Epoch(train) [1104][5/63] lr: 7.2154e-04 eta: 1:54:56 time: 0.9365 data_time: 0.1906 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2492 loss_db: 0.0615 loss: 0.6454 2022/08/30 22:12:23 - mmengine - INFO - Epoch(train) [1104][10/63] lr: 7.2154e-04 eta: 1:54:41 time: 0.9804 data_time: 0.2022 memory: 16201 loss_prob: 0.3597 loss_thr: 0.2516 loss_db: 0.0642 loss: 0.6754 2022/08/30 22:12:27 - mmengine - INFO - Epoch(train) [1104][15/63] lr: 7.2154e-04 eta: 1:54:41 time: 0.7845 data_time: 0.0237 memory: 16201 loss_prob: 0.3301 loss_thr: 0.2279 loss_db: 0.0590 loss: 0.6170 2022/08/30 22:12:31 - mmengine - INFO - Epoch(train) [1104][20/63] lr: 7.2154e-04 eta: 1:54:29 time: 0.8159 data_time: 0.0172 memory: 16201 loss_prob: 0.3159 loss_thr: 0.2185 loss_db: 0.0549 loss: 0.5893 2022/08/30 22:12:35 - mmengine - INFO - Epoch(train) [1104][25/63] lr: 7.2154e-04 eta: 1:54:29 time: 0.8225 data_time: 0.0247 memory: 16201 loss_prob: 0.3028 loss_thr: 0.2076 loss_db: 0.0519 loss: 0.5623 2022/08/30 22:12:39 - mmengine - INFO - Epoch(train) [1104][30/63] lr: 7.2154e-04 eta: 1:54:18 time: 0.8063 data_time: 0.0242 memory: 16201 loss_prob: 0.3038 loss_thr: 0.2218 loss_db: 0.0542 loss: 0.5798 2022/08/30 22:12:43 - mmengine - INFO - Epoch(train) [1104][35/63] lr: 7.2154e-04 eta: 1:54:18 time: 0.8184 data_time: 0.0278 memory: 16201 loss_prob: 0.3235 loss_thr: 0.2338 loss_db: 0.0585 loss: 0.6158 2022/08/30 22:12:47 - mmengine - INFO - Epoch(train) [1104][40/63] lr: 7.2154e-04 eta: 1:54:06 time: 0.7918 data_time: 0.0232 memory: 16201 loss_prob: 0.3118 loss_thr: 0.2173 loss_db: 0.0551 loss: 0.5842 2022/08/30 22:12:51 - mmengine - INFO - Epoch(train) [1104][45/63] lr: 7.2154e-04 eta: 1:54:06 time: 0.7912 data_time: 0.0230 memory: 16201 loss_prob: 0.3081 loss_thr: 0.2165 loss_db: 0.0546 loss: 0.5792 2022/08/30 22:12:55 - mmengine - INFO - Epoch(train) [1104][50/63] lr: 7.2154e-04 eta: 1:53:55 time: 0.7941 data_time: 0.0261 memory: 16201 loss_prob: 0.3118 loss_thr: 0.2237 loss_db: 0.0556 loss: 0.5912 2022/08/30 22:12:59 - mmengine - INFO - Epoch(train) [1104][55/63] lr: 7.2154e-04 eta: 1:53:55 time: 0.8110 data_time: 0.0229 memory: 16201 loss_prob: 0.3071 loss_thr: 0.2328 loss_db: 0.0551 loss: 0.5951 2022/08/30 22:13:03 - mmengine - INFO - Epoch(train) [1104][60/63] lr: 7.2154e-04 eta: 1:53:43 time: 0.8112 data_time: 0.0238 memory: 16201 loss_prob: 0.3149 loss_thr: 0.2337 loss_db: 0.0567 loss: 0.6053 2022/08/30 22:13:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:13:10 - mmengine - INFO - Epoch(train) [1105][5/63] lr: 7.1477e-04 eta: 1:53:43 time: 0.8695 data_time: 0.1411 memory: 16201 loss_prob: 0.3175 loss_thr: 0.2255 loss_db: 0.0555 loss: 0.5985 2022/08/30 22:13:15 - mmengine - INFO - Epoch(train) [1105][10/63] lr: 7.1477e-04 eta: 1:53:28 time: 0.9337 data_time: 0.1525 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2297 loss_db: 0.0606 loss: 0.6266 2022/08/30 22:13:19 - mmengine - INFO - Epoch(train) [1105][15/63] lr: 7.1477e-04 eta: 1:53:28 time: 0.8472 data_time: 0.0235 memory: 16201 loss_prob: 0.3491 loss_thr: 0.2351 loss_db: 0.0624 loss: 0.6466 2022/08/30 22:13:23 - mmengine - INFO - Epoch(train) [1105][20/63] lr: 7.1477e-04 eta: 1:53:16 time: 0.8494 data_time: 0.0211 memory: 16201 loss_prob: 0.3451 loss_thr: 0.2261 loss_db: 0.0618 loss: 0.6331 2022/08/30 22:13:27 - mmengine - INFO - Epoch(train) [1105][25/63] lr: 7.1477e-04 eta: 1:53:16 time: 0.7952 data_time: 0.0273 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2271 loss_db: 0.0610 loss: 0.6321 2022/08/30 22:13:31 - mmengine - INFO - Epoch(train) [1105][30/63] lr: 7.1477e-04 eta: 1:53:05 time: 0.7733 data_time: 0.0245 memory: 16201 loss_prob: 0.3294 loss_thr: 0.2250 loss_db: 0.0584 loss: 0.6128 2022/08/30 22:13:35 - mmengine - INFO - Epoch(train) [1105][35/63] lr: 7.1477e-04 eta: 1:53:05 time: 0.8027 data_time: 0.0260 memory: 16201 loss_prob: 0.3059 loss_thr: 0.2149 loss_db: 0.0558 loss: 0.5766 2022/08/30 22:13:39 - mmengine - INFO - Epoch(train) [1105][40/63] lr: 7.1477e-04 eta: 1:52:53 time: 0.8248 data_time: 0.0270 memory: 16201 loss_prob: 0.2992 loss_thr: 0.2184 loss_db: 0.0544 loss: 0.5720 2022/08/30 22:13:43 - mmengine - INFO - Epoch(train) [1105][45/63] lr: 7.1477e-04 eta: 1:52:53 time: 0.8022 data_time: 0.0261 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2193 loss_db: 0.0552 loss: 0.5869 2022/08/30 22:13:47 - mmengine - INFO - Epoch(train) [1105][50/63] lr: 7.1477e-04 eta: 1:52:42 time: 0.7888 data_time: 0.0234 memory: 16201 loss_prob: 0.3426 loss_thr: 0.2401 loss_db: 0.0599 loss: 0.6425 2022/08/30 22:13:51 - mmengine - INFO - Epoch(train) [1105][55/63] lr: 7.1477e-04 eta: 1:52:42 time: 0.8079 data_time: 0.0249 memory: 16201 loss_prob: 0.3369 loss_thr: 0.2419 loss_db: 0.0606 loss: 0.6394 2022/08/30 22:13:55 - mmengine - INFO - Epoch(train) [1105][60/63] lr: 7.1477e-04 eta: 1:52:30 time: 0.8015 data_time: 0.0261 memory: 16201 loss_prob: 0.3182 loss_thr: 0.2292 loss_db: 0.0578 loss: 0.6052 2022/08/30 22:13:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:14:03 - mmengine - INFO - Epoch(train) [1106][5/63] lr: 7.0800e-04 eta: 1:52:30 time: 0.9248 data_time: 0.1905 memory: 16201 loss_prob: 0.2936 loss_thr: 0.2075 loss_db: 0.0530 loss: 0.5540 2022/08/30 22:14:07 - mmengine - INFO - Epoch(train) [1106][10/63] lr: 7.0800e-04 eta: 1:52:15 time: 0.9730 data_time: 0.1962 memory: 16201 loss_prob: 0.2796 loss_thr: 0.1962 loss_db: 0.0496 loss: 0.5254 2022/08/30 22:14:11 - mmengine - INFO - Epoch(train) [1106][15/63] lr: 7.0800e-04 eta: 1:52:15 time: 0.8219 data_time: 0.0252 memory: 16201 loss_prob: 0.2867 loss_thr: 0.2036 loss_db: 0.0518 loss: 0.5421 2022/08/30 22:14:15 - mmengine - INFO - Epoch(train) [1106][20/63] lr: 7.0800e-04 eta: 1:52:04 time: 0.8320 data_time: 0.0292 memory: 16201 loss_prob: 0.2914 loss_thr: 0.2084 loss_db: 0.0534 loss: 0.5532 2022/08/30 22:14:19 - mmengine - INFO - Epoch(train) [1106][25/63] lr: 7.0800e-04 eta: 1:52:04 time: 0.8066 data_time: 0.0267 memory: 16201 loss_prob: 0.3011 loss_thr: 0.2169 loss_db: 0.0538 loss: 0.5718 2022/08/30 22:14:23 - mmengine - INFO - Epoch(train) [1106][30/63] lr: 7.0800e-04 eta: 1:51:52 time: 0.7882 data_time: 0.0248 memory: 16201 loss_prob: 0.3131 loss_thr: 0.2217 loss_db: 0.0555 loss: 0.5904 2022/08/30 22:14:27 - mmengine - INFO - Epoch(train) [1106][35/63] lr: 7.0800e-04 eta: 1:51:52 time: 0.7888 data_time: 0.0251 memory: 16201 loss_prob: 0.3234 loss_thr: 0.2252 loss_db: 0.0581 loss: 0.6067 2022/08/30 22:14:31 - mmengine - INFO - Epoch(train) [1106][40/63] lr: 7.0800e-04 eta: 1:51:41 time: 0.8090 data_time: 0.0258 memory: 16201 loss_prob: 0.3164 loss_thr: 0.2297 loss_db: 0.0572 loss: 0.6034 2022/08/30 22:14:35 - mmengine - INFO - Epoch(train) [1106][45/63] lr: 7.0800e-04 eta: 1:51:41 time: 0.8065 data_time: 0.0300 memory: 16201 loss_prob: 0.2979 loss_thr: 0.2242 loss_db: 0.0538 loss: 0.5759 2022/08/30 22:14:39 - mmengine - INFO - Epoch(train) [1106][50/63] lr: 7.0800e-04 eta: 1:51:29 time: 0.7888 data_time: 0.0220 memory: 16201 loss_prob: 0.2984 loss_thr: 0.2167 loss_db: 0.0532 loss: 0.5684 2022/08/30 22:14:43 - mmengine - INFO - Epoch(train) [1106][55/63] lr: 7.0800e-04 eta: 1:51:29 time: 0.7994 data_time: 0.0220 memory: 16201 loss_prob: 0.3255 loss_thr: 0.2209 loss_db: 0.0569 loss: 0.6034 2022/08/30 22:14:47 - mmengine - INFO - Epoch(train) [1106][60/63] lr: 7.0800e-04 eta: 1:51:17 time: 0.7950 data_time: 0.0257 memory: 16201 loss_prob: 0.3308 loss_thr: 0.2332 loss_db: 0.0579 loss: 0.6218 2022/08/30 22:14:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:14:55 - mmengine - INFO - Epoch(train) [1107][5/63] lr: 7.0121e-04 eta: 1:51:17 time: 0.9787 data_time: 0.2099 memory: 16201 loss_prob: 0.3137 loss_thr: 0.2351 loss_db: 0.0556 loss: 0.6044 2022/08/30 22:14:59 - mmengine - INFO - Epoch(train) [1107][10/63] lr: 7.0121e-04 eta: 1:51:02 time: 0.9888 data_time: 0.2164 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2492 loss_db: 0.0611 loss: 0.6540 2022/08/30 22:15:03 - mmengine - INFO - Epoch(train) [1107][15/63] lr: 7.0121e-04 eta: 1:51:02 time: 0.7870 data_time: 0.0269 memory: 16201 loss_prob: 0.3869 loss_thr: 0.2375 loss_db: 0.0624 loss: 0.6868 2022/08/30 22:15:07 - mmengine - INFO - Epoch(train) [1107][20/63] lr: 7.0121e-04 eta: 1:50:51 time: 0.7719 data_time: 0.0210 memory: 16201 loss_prob: 0.3861 loss_thr: 0.2340 loss_db: 0.0617 loss: 0.6818 2022/08/30 22:15:11 - mmengine - INFO - Epoch(train) [1107][25/63] lr: 7.0121e-04 eta: 1:50:51 time: 0.7967 data_time: 0.0244 memory: 16201 loss_prob: 0.3328 loss_thr: 0.2311 loss_db: 0.0586 loss: 0.6224 2022/08/30 22:15:15 - mmengine - INFO - Epoch(train) [1107][30/63] lr: 7.0121e-04 eta: 1:50:39 time: 0.8169 data_time: 0.0256 memory: 16201 loss_prob: 0.3376 loss_thr: 0.2290 loss_db: 0.0591 loss: 0.6257 2022/08/30 22:15:19 - mmengine - INFO - Epoch(train) [1107][35/63] lr: 7.0121e-04 eta: 1:50:39 time: 0.8121 data_time: 0.0234 memory: 16201 loss_prob: 0.3331 loss_thr: 0.2284 loss_db: 0.0585 loss: 0.6200 2022/08/30 22:15:23 - mmengine - INFO - Epoch(train) [1107][40/63] lr: 7.0121e-04 eta: 1:50:28 time: 0.8065 data_time: 0.0254 memory: 16201 loss_prob: 0.3037 loss_thr: 0.2184 loss_db: 0.0550 loss: 0.5771 2022/08/30 22:15:27 - mmengine - INFO - Epoch(train) [1107][45/63] lr: 7.0121e-04 eta: 1:50:28 time: 0.7926 data_time: 0.0267 memory: 16201 loss_prob: 0.2797 loss_thr: 0.2066 loss_db: 0.0523 loss: 0.5386 2022/08/30 22:15:31 - mmengine - INFO - Epoch(train) [1107][50/63] lr: 7.0121e-04 eta: 1:50:16 time: 0.7915 data_time: 0.0240 memory: 16201 loss_prob: 0.3105 loss_thr: 0.2271 loss_db: 0.0568 loss: 0.5944 2022/08/30 22:15:35 - mmengine - INFO - Epoch(train) [1107][55/63] lr: 7.0121e-04 eta: 1:50:16 time: 0.7860 data_time: 0.0253 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2490 loss_db: 0.0617 loss: 0.6572 2022/08/30 22:15:39 - mmengine - INFO - Epoch(train) [1107][60/63] lr: 7.0121e-04 eta: 1:50:05 time: 0.7784 data_time: 0.0222 memory: 16201 loss_prob: 0.3370 loss_thr: 0.2404 loss_db: 0.0596 loss: 0.6369 2022/08/30 22:15:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:15:46 - mmengine - INFO - Epoch(train) [1108][5/63] lr: 6.9443e-04 eta: 1:50:05 time: 0.9367 data_time: 0.2022 memory: 16201 loss_prob: 0.3035 loss_thr: 0.2174 loss_db: 0.0552 loss: 0.5761 2022/08/30 22:15:50 - mmengine - INFO - Epoch(train) [1108][10/63] lr: 6.9443e-04 eta: 1:49:50 time: 0.9776 data_time: 0.2059 memory: 16201 loss_prob: 0.3028 loss_thr: 0.2131 loss_db: 0.0562 loss: 0.5721 2022/08/30 22:15:54 - mmengine - INFO - Epoch(train) [1108][15/63] lr: 6.9443e-04 eta: 1:49:50 time: 0.8011 data_time: 0.0257 memory: 16201 loss_prob: 0.3049 loss_thr: 0.2107 loss_db: 0.0556 loss: 0.5713 2022/08/30 22:15:59 - mmengine - INFO - Epoch(train) [1108][20/63] lr: 6.9443e-04 eta: 1:49:38 time: 0.8140 data_time: 0.0159 memory: 16201 loss_prob: 0.2914 loss_thr: 0.2080 loss_db: 0.0525 loss: 0.5519 2022/08/30 22:16:03 - mmengine - INFO - Epoch(train) [1108][25/63] lr: 6.9443e-04 eta: 1:49:38 time: 0.8387 data_time: 0.0283 memory: 16201 loss_prob: 0.3023 loss_thr: 0.2213 loss_db: 0.0538 loss: 0.5774 2022/08/30 22:16:07 - mmengine - INFO - Epoch(train) [1108][30/63] lr: 6.9443e-04 eta: 1:49:26 time: 0.8087 data_time: 0.0322 memory: 16201 loss_prob: 0.3116 loss_thr: 0.2200 loss_db: 0.0554 loss: 0.5870 2022/08/30 22:16:11 - mmengine - INFO - Epoch(train) [1108][35/63] lr: 6.9443e-04 eta: 1:49:26 time: 0.7666 data_time: 0.0189 memory: 16201 loss_prob: 0.3206 loss_thr: 0.2211 loss_db: 0.0568 loss: 0.5985 2022/08/30 22:16:15 - mmengine - INFO - Epoch(train) [1108][40/63] lr: 6.9443e-04 eta: 1:49:15 time: 0.7818 data_time: 0.0221 memory: 16201 loss_prob: 0.3469 loss_thr: 0.2374 loss_db: 0.0615 loss: 0.6459 2022/08/30 22:16:19 - mmengine - INFO - Epoch(train) [1108][45/63] lr: 6.9443e-04 eta: 1:49:15 time: 0.8023 data_time: 0.0238 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2307 loss_db: 0.0604 loss: 0.6278 2022/08/30 22:16:23 - mmengine - INFO - Epoch(train) [1108][50/63] lr: 6.9443e-04 eta: 1:49:03 time: 0.8177 data_time: 0.0247 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2197 loss_db: 0.0562 loss: 0.5883 2022/08/30 22:16:27 - mmengine - INFO - Epoch(train) [1108][55/63] lr: 6.9443e-04 eta: 1:49:03 time: 0.8018 data_time: 0.0286 memory: 16201 loss_prob: 0.3176 loss_thr: 0.2294 loss_db: 0.0561 loss: 0.6032 2022/08/30 22:16:31 - mmengine - INFO - Epoch(train) [1108][60/63] lr: 6.9443e-04 eta: 1:48:52 time: 0.8660 data_time: 0.0230 memory: 16201 loss_prob: 0.3114 loss_thr: 0.2287 loss_db: 0.0555 loss: 0.5956 2022/08/30 22:16:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:16:39 - mmengine - INFO - Epoch(train) [1109][5/63] lr: 6.8763e-04 eta: 1:48:52 time: 0.9839 data_time: 0.1703 memory: 16201 loss_prob: 0.3704 loss_thr: 0.2607 loss_db: 0.0658 loss: 0.6969 2022/08/30 22:16:43 - mmengine - INFO - Epoch(train) [1109][10/63] lr: 6.8763e-04 eta: 1:48:37 time: 0.9569 data_time: 0.1759 memory: 16201 loss_prob: 0.3598 loss_thr: 0.2579 loss_db: 0.0640 loss: 0.6817 2022/08/30 22:16:47 - mmengine - INFO - Epoch(train) [1109][15/63] lr: 6.8763e-04 eta: 1:48:37 time: 0.8140 data_time: 0.0265 memory: 16201 loss_prob: 0.2871 loss_thr: 0.2117 loss_db: 0.0508 loss: 0.5496 2022/08/30 22:16:51 - mmengine - INFO - Epoch(train) [1109][20/63] lr: 6.8763e-04 eta: 1:48:25 time: 0.7940 data_time: 0.0237 memory: 16201 loss_prob: 0.3057 loss_thr: 0.2153 loss_db: 0.0553 loss: 0.5763 2022/08/30 22:16:55 - mmengine - INFO - Epoch(train) [1109][25/63] lr: 6.8763e-04 eta: 1:48:25 time: 0.8050 data_time: 0.0348 memory: 16201 loss_prob: 0.3227 loss_thr: 0.2291 loss_db: 0.0588 loss: 0.6106 2022/08/30 22:16:59 - mmengine - INFO - Epoch(train) [1109][30/63] lr: 6.8763e-04 eta: 1:48:14 time: 0.8491 data_time: 0.0262 memory: 16201 loss_prob: 0.3090 loss_thr: 0.2173 loss_db: 0.0558 loss: 0.5821 2022/08/30 22:17:04 - mmengine - INFO - Epoch(train) [1109][35/63] lr: 6.8763e-04 eta: 1:48:14 time: 0.8559 data_time: 0.0256 memory: 16201 loss_prob: 0.3256 loss_thr: 0.2252 loss_db: 0.0582 loss: 0.6090 2022/08/30 22:17:07 - mmengine - INFO - Epoch(train) [1109][40/63] lr: 6.8763e-04 eta: 1:48:02 time: 0.8007 data_time: 0.0271 memory: 16201 loss_prob: 0.3391 loss_thr: 0.2369 loss_db: 0.0593 loss: 0.6354 2022/08/30 22:17:11 - mmengine - INFO - Epoch(train) [1109][45/63] lr: 6.8763e-04 eta: 1:48:02 time: 0.7816 data_time: 0.0236 memory: 16201 loss_prob: 0.3337 loss_thr: 0.2289 loss_db: 0.0590 loss: 0.6216 2022/08/30 22:17:15 - mmengine - INFO - Epoch(train) [1109][50/63] lr: 6.8763e-04 eta: 1:47:51 time: 0.8055 data_time: 0.0285 memory: 16201 loss_prob: 0.2818 loss_thr: 0.2037 loss_db: 0.0510 loss: 0.5365 2022/08/30 22:17:20 - mmengine - INFO - Epoch(train) [1109][55/63] lr: 6.8763e-04 eta: 1:47:51 time: 0.8292 data_time: 0.0314 memory: 16201 loss_prob: 0.2670 loss_thr: 0.2126 loss_db: 0.0480 loss: 0.5275 2022/08/30 22:17:24 - mmengine - INFO - Epoch(train) [1109][60/63] lr: 6.8763e-04 eta: 1:47:39 time: 0.8213 data_time: 0.0306 memory: 16201 loss_prob: 0.3168 loss_thr: 0.2389 loss_db: 0.0563 loss: 0.6120 2022/08/30 22:17:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:17:31 - mmengine - INFO - Epoch(train) [1110][5/63] lr: 6.8083e-04 eta: 1:47:39 time: 0.9142 data_time: 0.1742 memory: 16201 loss_prob: 0.2961 loss_thr: 0.2090 loss_db: 0.0523 loss: 0.5575 2022/08/30 22:17:35 - mmengine - INFO - Epoch(train) [1110][10/63] lr: 6.8083e-04 eta: 1:47:24 time: 0.9539 data_time: 0.1850 memory: 16201 loss_prob: 0.3026 loss_thr: 0.2098 loss_db: 0.0541 loss: 0.5664 2022/08/30 22:17:40 - mmengine - INFO - Epoch(train) [1110][15/63] lr: 6.8083e-04 eta: 1:47:24 time: 0.8352 data_time: 0.0240 memory: 16201 loss_prob: 0.3035 loss_thr: 0.2133 loss_db: 0.0543 loss: 0.5711 2022/08/30 22:17:44 - mmengine - INFO - Epoch(train) [1110][20/63] lr: 6.8083e-04 eta: 1:47:13 time: 0.8340 data_time: 0.0217 memory: 16201 loss_prob: 0.2928 loss_thr: 0.2200 loss_db: 0.0533 loss: 0.5660 2022/08/30 22:17:48 - mmengine - INFO - Epoch(train) [1110][25/63] lr: 6.8083e-04 eta: 1:47:13 time: 0.7966 data_time: 0.0317 memory: 16201 loss_prob: 0.2899 loss_thr: 0.2134 loss_db: 0.0538 loss: 0.5570 2022/08/30 22:17:51 - mmengine - INFO - Epoch(train) [1110][30/63] lr: 6.8083e-04 eta: 1:47:01 time: 0.7949 data_time: 0.0260 memory: 16201 loss_prob: 0.3150 loss_thr: 0.2142 loss_db: 0.0572 loss: 0.5864 2022/08/30 22:17:56 - mmengine - INFO - Epoch(train) [1110][35/63] lr: 6.8083e-04 eta: 1:47:01 time: 0.8039 data_time: 0.0344 memory: 16201 loss_prob: 0.3356 loss_thr: 0.2243 loss_db: 0.0603 loss: 0.6201 2022/08/30 22:18:00 - mmengine - INFO - Epoch(train) [1110][40/63] lr: 6.8083e-04 eta: 1:46:50 time: 0.8171 data_time: 0.0368 memory: 16201 loss_prob: 0.3175 loss_thr: 0.2214 loss_db: 0.0562 loss: 0.5950 2022/08/30 22:18:04 - mmengine - INFO - Epoch(train) [1110][45/63] lr: 6.8083e-04 eta: 1:46:50 time: 0.7974 data_time: 0.0245 memory: 16201 loss_prob: 0.3315 loss_thr: 0.2338 loss_db: 0.0576 loss: 0.6229 2022/08/30 22:18:08 - mmengine - INFO - Epoch(train) [1110][50/63] lr: 6.8083e-04 eta: 1:46:38 time: 0.7926 data_time: 0.0229 memory: 16201 loss_prob: 0.3216 loss_thr: 0.2365 loss_db: 0.0564 loss: 0.6144 2022/08/30 22:18:12 - mmengine - INFO - Epoch(train) [1110][55/63] lr: 6.8083e-04 eta: 1:46:38 time: 0.8019 data_time: 0.0232 memory: 16201 loss_prob: 0.2731 loss_thr: 0.2152 loss_db: 0.0492 loss: 0.5374 2022/08/30 22:18:16 - mmengine - INFO - Epoch(train) [1110][60/63] lr: 6.8083e-04 eta: 1:46:27 time: 0.8074 data_time: 0.0303 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2222 loss_db: 0.0553 loss: 0.5824 2022/08/30 22:18:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:18:24 - mmengine - INFO - Epoch(train) [1111][5/63] lr: 6.7402e-04 eta: 1:46:27 time: 0.9441 data_time: 0.1958 memory: 16201 loss_prob: 0.3276 loss_thr: 0.2258 loss_db: 0.0586 loss: 0.6120 2022/08/30 22:18:28 - mmengine - INFO - Epoch(train) [1111][10/63] lr: 6.7402e-04 eta: 1:46:12 time: 0.9955 data_time: 0.2106 memory: 16201 loss_prob: 0.3657 loss_thr: 0.2522 loss_db: 0.0660 loss: 0.6839 2022/08/30 22:18:32 - mmengine - INFO - Epoch(train) [1111][15/63] lr: 6.7402e-04 eta: 1:46:12 time: 0.8107 data_time: 0.0293 memory: 16201 loss_prob: 0.3259 loss_thr: 0.2363 loss_db: 0.0592 loss: 0.6214 2022/08/30 22:18:36 - mmengine - INFO - Epoch(train) [1111][20/63] lr: 6.7402e-04 eta: 1:46:00 time: 0.8081 data_time: 0.0186 memory: 16201 loss_prob: 0.2878 loss_thr: 0.2071 loss_db: 0.0510 loss: 0.5460 2022/08/30 22:18:40 - mmengine - INFO - Epoch(train) [1111][25/63] lr: 6.7402e-04 eta: 1:46:00 time: 0.7929 data_time: 0.0286 memory: 16201 loss_prob: 0.3078 loss_thr: 0.2302 loss_db: 0.0544 loss: 0.5924 2022/08/30 22:18:44 - mmengine - INFO - Epoch(train) [1111][30/63] lr: 6.7402e-04 eta: 1:45:49 time: 0.7873 data_time: 0.0260 memory: 16201 loss_prob: 0.3149 loss_thr: 0.2360 loss_db: 0.0566 loss: 0.6074 2022/08/30 22:18:48 - mmengine - INFO - Epoch(train) [1111][35/63] lr: 6.7402e-04 eta: 1:45:49 time: 0.8474 data_time: 0.0595 memory: 16201 loss_prob: 0.2987 loss_thr: 0.2096 loss_db: 0.0534 loss: 0.5617 2022/08/30 22:18:52 - mmengine - INFO - Epoch(train) [1111][40/63] lr: 6.7402e-04 eta: 1:45:37 time: 0.8508 data_time: 0.0628 memory: 16201 loss_prob: 0.2785 loss_thr: 0.1947 loss_db: 0.0497 loss: 0.5229 2022/08/30 22:18:56 - mmengine - INFO - Epoch(train) [1111][45/63] lr: 6.7402e-04 eta: 1:45:37 time: 0.7955 data_time: 0.0221 memory: 16201 loss_prob: 0.3068 loss_thr: 0.2091 loss_db: 0.0551 loss: 0.5710 2022/08/30 22:19:00 - mmengine - INFO - Epoch(train) [1111][50/63] lr: 6.7402e-04 eta: 1:45:26 time: 0.8146 data_time: 0.0302 memory: 16201 loss_prob: 0.3458 loss_thr: 0.2359 loss_db: 0.0610 loss: 0.6427 2022/08/30 22:19:04 - mmengine - INFO - Epoch(train) [1111][55/63] lr: 6.7402e-04 eta: 1:45:26 time: 0.8104 data_time: 0.0318 memory: 16201 loss_prob: 0.3509 loss_thr: 0.2510 loss_db: 0.0621 loss: 0.6639 2022/08/30 22:19:08 - mmengine - INFO - Epoch(train) [1111][60/63] lr: 6.7402e-04 eta: 1:45:14 time: 0.7868 data_time: 0.0245 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2391 loss_db: 0.0573 loss: 0.6203 2022/08/30 22:19:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:19:16 - mmengine - INFO - Epoch(train) [1112][5/63] lr: 6.6720e-04 eta: 1:45:14 time: 0.9561 data_time: 0.2146 memory: 16201 loss_prob: 0.2913 loss_thr: 0.2186 loss_db: 0.0534 loss: 0.5633 2022/08/30 22:19:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:19:20 - mmengine - INFO - Epoch(train) [1112][10/63] lr: 6.6720e-04 eta: 1:44:59 time: 0.9856 data_time: 0.2225 memory: 16201 loss_prob: 0.3275 loss_thr: 0.2312 loss_db: 0.0607 loss: 0.6194 2022/08/30 22:19:24 - mmengine - INFO - Epoch(train) [1112][15/63] lr: 6.6720e-04 eta: 1:44:59 time: 0.7862 data_time: 0.0236 memory: 16201 loss_prob: 0.3212 loss_thr: 0.2205 loss_db: 0.0575 loss: 0.5992 2022/08/30 22:19:28 - mmengine - INFO - Epoch(train) [1112][20/63] lr: 6.6720e-04 eta: 1:44:47 time: 0.7938 data_time: 0.0181 memory: 16201 loss_prob: 0.3108 loss_thr: 0.2134 loss_db: 0.0550 loss: 0.5792 2022/08/30 22:19:32 - mmengine - INFO - Epoch(train) [1112][25/63] lr: 6.6720e-04 eta: 1:44:47 time: 0.8049 data_time: 0.0316 memory: 16201 loss_prob: 0.3252 loss_thr: 0.2224 loss_db: 0.0580 loss: 0.6057 2022/08/30 22:19:36 - mmengine - INFO - Epoch(train) [1112][30/63] lr: 6.6720e-04 eta: 1:44:36 time: 0.7896 data_time: 0.0261 memory: 16201 loss_prob: 0.3016 loss_thr: 0.2136 loss_db: 0.0541 loss: 0.5694 2022/08/30 22:19:40 - mmengine - INFO - Epoch(train) [1112][35/63] lr: 6.6720e-04 eta: 1:44:36 time: 0.8194 data_time: 0.0192 memory: 16201 loss_prob: 0.3045 loss_thr: 0.2124 loss_db: 0.0544 loss: 0.5713 2022/08/30 22:19:44 - mmengine - INFO - Epoch(train) [1112][40/63] lr: 6.6720e-04 eta: 1:44:24 time: 0.8340 data_time: 0.0297 memory: 16201 loss_prob: 0.3065 loss_thr: 0.2103 loss_db: 0.0549 loss: 0.5717 2022/08/30 22:19:48 - mmengine - INFO - Epoch(train) [1112][45/63] lr: 6.6720e-04 eta: 1:44:24 time: 0.7993 data_time: 0.0283 memory: 16201 loss_prob: 0.3060 loss_thr: 0.2181 loss_db: 0.0551 loss: 0.5792 2022/08/30 22:19:52 - mmengine - INFO - Epoch(train) [1112][50/63] lr: 6.6720e-04 eta: 1:44:13 time: 0.7825 data_time: 0.0238 memory: 16201 loss_prob: 0.3127 loss_thr: 0.2273 loss_db: 0.0567 loss: 0.5966 2022/08/30 22:19:56 - mmengine - INFO - Epoch(train) [1112][55/63] lr: 6.6720e-04 eta: 1:44:13 time: 0.7779 data_time: 0.0244 memory: 16201 loss_prob: 0.3324 loss_thr: 0.2337 loss_db: 0.0599 loss: 0.6260 2022/08/30 22:20:01 - mmengine - INFO - Epoch(train) [1112][60/63] lr: 6.6720e-04 eta: 1:44:01 time: 0.8488 data_time: 0.0286 memory: 16201 loss_prob: 0.3340 loss_thr: 0.2290 loss_db: 0.0598 loss: 0.6228 2022/08/30 22:20:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:20:08 - mmengine - INFO - Epoch(train) [1113][5/63] lr: 6.6037e-04 eta: 1:44:01 time: 0.9917 data_time: 0.2084 memory: 16201 loss_prob: 0.3075 loss_thr: 0.2165 loss_db: 0.0550 loss: 0.5790 2022/08/30 22:20:12 - mmengine - INFO - Epoch(train) [1113][10/63] lr: 6.6037e-04 eta: 1:43:46 time: 0.9737 data_time: 0.2104 memory: 16201 loss_prob: 0.3028 loss_thr: 0.2084 loss_db: 0.0543 loss: 0.5656 2022/08/30 22:20:16 - mmengine - INFO - Epoch(train) [1113][15/63] lr: 6.6037e-04 eta: 1:43:46 time: 0.7888 data_time: 0.0238 memory: 16201 loss_prob: 0.3155 loss_thr: 0.2193 loss_db: 0.0574 loss: 0.5923 2022/08/30 22:20:21 - mmengine - INFO - Epoch(train) [1113][20/63] lr: 6.6037e-04 eta: 1:43:35 time: 0.8366 data_time: 0.0280 memory: 16201 loss_prob: 0.3275 loss_thr: 0.2330 loss_db: 0.0596 loss: 0.6202 2022/08/30 22:20:25 - mmengine - INFO - Epoch(train) [1113][25/63] lr: 6.6037e-04 eta: 1:43:35 time: 0.8306 data_time: 0.0317 memory: 16201 loss_prob: 0.3354 loss_thr: 0.2356 loss_db: 0.0597 loss: 0.6307 2022/08/30 22:20:28 - mmengine - INFO - Epoch(train) [1113][30/63] lr: 6.6037e-04 eta: 1:43:23 time: 0.7837 data_time: 0.0230 memory: 16201 loss_prob: 0.3376 loss_thr: 0.2309 loss_db: 0.0592 loss: 0.6277 2022/08/30 22:20:32 - mmengine - INFO - Epoch(train) [1113][35/63] lr: 6.6037e-04 eta: 1:43:23 time: 0.7866 data_time: 0.0218 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2292 loss_db: 0.0585 loss: 0.6197 2022/08/30 22:20:36 - mmengine - INFO - Epoch(train) [1113][40/63] lr: 6.6037e-04 eta: 1:43:12 time: 0.7777 data_time: 0.0241 memory: 16201 loss_prob: 0.3350 loss_thr: 0.2265 loss_db: 0.0595 loss: 0.6209 2022/08/30 22:20:41 - mmengine - INFO - Epoch(train) [1113][45/63] lr: 6.6037e-04 eta: 1:43:12 time: 0.8852 data_time: 0.0272 memory: 16201 loss_prob: 0.3194 loss_thr: 0.2223 loss_db: 0.0573 loss: 0.5990 2022/08/30 22:20:45 - mmengine - INFO - Epoch(train) [1113][50/63] lr: 6.6037e-04 eta: 1:43:01 time: 0.8980 data_time: 0.0261 memory: 16201 loss_prob: 0.3203 loss_thr: 0.2253 loss_db: 0.0573 loss: 0.6029 2022/08/30 22:20:49 - mmengine - INFO - Epoch(train) [1113][55/63] lr: 6.6037e-04 eta: 1:43:01 time: 0.8035 data_time: 0.0267 memory: 16201 loss_prob: 0.3265 loss_thr: 0.2287 loss_db: 0.0572 loss: 0.6125 2022/08/30 22:20:53 - mmengine - INFO - Epoch(train) [1113][60/63] lr: 6.6037e-04 eta: 1:42:49 time: 0.7924 data_time: 0.0273 memory: 16201 loss_prob: 0.3136 loss_thr: 0.2305 loss_db: 0.0552 loss: 0.5992 2022/08/30 22:20:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:21:00 - mmengine - INFO - Epoch(train) [1114][5/63] lr: 6.5354e-04 eta: 1:42:49 time: 0.8857 data_time: 0.1429 memory: 16201 loss_prob: 0.3216 loss_thr: 0.2221 loss_db: 0.0545 loss: 0.5982 2022/08/30 22:21:04 - mmengine - INFO - Epoch(train) [1114][10/63] lr: 6.5354e-04 eta: 1:42:34 time: 0.9243 data_time: 0.1496 memory: 16201 loss_prob: 0.3252 loss_thr: 0.2307 loss_db: 0.0576 loss: 0.6135 2022/08/30 22:21:08 - mmengine - INFO - Epoch(train) [1114][15/63] lr: 6.5354e-04 eta: 1:42:34 time: 0.7971 data_time: 0.0260 memory: 16201 loss_prob: 0.3571 loss_thr: 0.2402 loss_db: 0.0635 loss: 0.6608 2022/08/30 22:21:13 - mmengine - INFO - Epoch(train) [1114][20/63] lr: 6.5354e-04 eta: 1:42:22 time: 0.8113 data_time: 0.0237 memory: 16201 loss_prob: 0.3529 loss_thr: 0.2410 loss_db: 0.0624 loss: 0.6563 2022/08/30 22:21:16 - mmengine - INFO - Epoch(train) [1114][25/63] lr: 6.5354e-04 eta: 1:42:22 time: 0.8039 data_time: 0.0242 memory: 16201 loss_prob: 0.3261 loss_thr: 0.2318 loss_db: 0.0583 loss: 0.6161 2022/08/30 22:21:20 - mmengine - INFO - Epoch(train) [1114][30/63] lr: 6.5354e-04 eta: 1:42:11 time: 0.7905 data_time: 0.0241 memory: 16201 loss_prob: 0.2908 loss_thr: 0.2071 loss_db: 0.0536 loss: 0.5515 2022/08/30 22:21:24 - mmengine - INFO - Epoch(train) [1114][35/63] lr: 6.5354e-04 eta: 1:42:11 time: 0.7969 data_time: 0.0304 memory: 16201 loss_prob: 0.3190 loss_thr: 0.2214 loss_db: 0.0582 loss: 0.5986 2022/08/30 22:21:28 - mmengine - INFO - Epoch(train) [1114][40/63] lr: 6.5354e-04 eta: 1:41:59 time: 0.7968 data_time: 0.0268 memory: 16201 loss_prob: 0.3498 loss_thr: 0.2460 loss_db: 0.0625 loss: 0.6583 2022/08/30 22:21:32 - mmengine - INFO - Epoch(train) [1114][45/63] lr: 6.5354e-04 eta: 1:41:59 time: 0.7998 data_time: 0.0232 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2279 loss_db: 0.0558 loss: 0.5951 2022/08/30 22:21:37 - mmengine - INFO - Epoch(train) [1114][50/63] lr: 6.5354e-04 eta: 1:41:48 time: 0.8282 data_time: 0.0209 memory: 16201 loss_prob: 0.2953 loss_thr: 0.2123 loss_db: 0.0537 loss: 0.5613 2022/08/30 22:21:41 - mmengine - INFO - Epoch(train) [1114][55/63] lr: 6.5354e-04 eta: 1:41:48 time: 0.8381 data_time: 0.0235 memory: 16201 loss_prob: 0.3065 loss_thr: 0.2149 loss_db: 0.0550 loss: 0.5763 2022/08/30 22:21:45 - mmengine - INFO - Epoch(train) [1114][60/63] lr: 6.5354e-04 eta: 1:41:36 time: 0.8127 data_time: 0.0352 memory: 16201 loss_prob: 0.3061 loss_thr: 0.2195 loss_db: 0.0547 loss: 0.5804 2022/08/30 22:21:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:21:53 - mmengine - INFO - Epoch(train) [1115][5/63] lr: 6.4669e-04 eta: 1:41:36 time: 0.9452 data_time: 0.2074 memory: 16201 loss_prob: 0.2854 loss_thr: 0.2102 loss_db: 0.0516 loss: 0.5472 2022/08/30 22:21:57 - mmengine - INFO - Epoch(train) [1115][10/63] lr: 6.4669e-04 eta: 1:41:22 time: 0.9873 data_time: 0.2196 memory: 16201 loss_prob: 0.3153 loss_thr: 0.2278 loss_db: 0.0556 loss: 0.5986 2022/08/30 22:22:01 - mmengine - INFO - Epoch(train) [1115][15/63] lr: 6.4669e-04 eta: 1:41:22 time: 0.7844 data_time: 0.0258 memory: 16201 loss_prob: 0.3412 loss_thr: 0.2362 loss_db: 0.0614 loss: 0.6388 2022/08/30 22:22:04 - mmengine - INFO - Epoch(train) [1115][20/63] lr: 6.4669e-04 eta: 1:41:10 time: 0.7771 data_time: 0.0198 memory: 16201 loss_prob: 0.3563 loss_thr: 0.2375 loss_db: 0.0636 loss: 0.6574 2022/08/30 22:22:08 - mmengine - INFO - Epoch(train) [1115][25/63] lr: 6.4669e-04 eta: 1:41:10 time: 0.7760 data_time: 0.0269 memory: 16201 loss_prob: 0.3610 loss_thr: 0.2467 loss_db: 0.0640 loss: 0.6718 2022/08/30 22:22:12 - mmengine - INFO - Epoch(train) [1115][30/63] lr: 6.4669e-04 eta: 1:40:58 time: 0.7923 data_time: 0.0230 memory: 16201 loss_prob: 0.3391 loss_thr: 0.2344 loss_db: 0.0606 loss: 0.6341 2022/08/30 22:22:16 - mmengine - INFO - Epoch(train) [1115][35/63] lr: 6.4669e-04 eta: 1:40:58 time: 0.8061 data_time: 0.0264 memory: 16201 loss_prob: 0.2987 loss_thr: 0.2073 loss_db: 0.0527 loss: 0.5588 2022/08/30 22:22:20 - mmengine - INFO - Epoch(train) [1115][40/63] lr: 6.4669e-04 eta: 1:40:47 time: 0.8138 data_time: 0.0248 memory: 16201 loss_prob: 0.2780 loss_thr: 0.2020 loss_db: 0.0492 loss: 0.5291 2022/08/30 22:22:24 - mmengine - INFO - Epoch(train) [1115][45/63] lr: 6.4669e-04 eta: 1:40:47 time: 0.8096 data_time: 0.0238 memory: 16201 loss_prob: 0.3085 loss_thr: 0.2134 loss_db: 0.0544 loss: 0.5763 2022/08/30 22:22:28 - mmengine - INFO - Epoch(train) [1115][50/63] lr: 6.4669e-04 eta: 1:40:36 time: 0.7850 data_time: 0.0277 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2189 loss_db: 0.0581 loss: 0.6020 2022/08/30 22:22:32 - mmengine - INFO - Epoch(train) [1115][55/63] lr: 6.4669e-04 eta: 1:40:36 time: 0.7880 data_time: 0.0268 memory: 16201 loss_prob: 0.3103 loss_thr: 0.2116 loss_db: 0.0562 loss: 0.5782 2022/08/30 22:22:36 - mmengine - INFO - Epoch(train) [1115][60/63] lr: 6.4669e-04 eta: 1:40:24 time: 0.7936 data_time: 0.0256 memory: 16201 loss_prob: 0.3169 loss_thr: 0.2165 loss_db: 0.0556 loss: 0.5890 2022/08/30 22:22:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:22:44 - mmengine - INFO - Epoch(train) [1116][5/63] lr: 6.3984e-04 eta: 1:40:24 time: 0.9252 data_time: 0.1876 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2333 loss_db: 0.0568 loss: 0.6125 2022/08/30 22:22:48 - mmengine - INFO - Epoch(train) [1116][10/63] lr: 6.3984e-04 eta: 1:40:09 time: 0.9717 data_time: 0.1975 memory: 16201 loss_prob: 0.2902 loss_thr: 0.2190 loss_db: 0.0530 loss: 0.5622 2022/08/30 22:22:52 - mmengine - INFO - Epoch(train) [1116][15/63] lr: 6.3984e-04 eta: 1:40:09 time: 0.8022 data_time: 0.0221 memory: 16201 loss_prob: 0.2799 loss_thr: 0.2084 loss_db: 0.0514 loss: 0.5397 2022/08/30 22:22:56 - mmengine - INFO - Epoch(train) [1116][20/63] lr: 6.3984e-04 eta: 1:39:58 time: 0.8160 data_time: 0.0255 memory: 16201 loss_prob: 0.3084 loss_thr: 0.2153 loss_db: 0.0566 loss: 0.5803 2022/08/30 22:23:00 - mmengine - INFO - Epoch(train) [1116][25/63] lr: 6.3984e-04 eta: 1:39:58 time: 0.8117 data_time: 0.0301 memory: 16201 loss_prob: 0.2983 loss_thr: 0.2038 loss_db: 0.0545 loss: 0.5566 2022/08/30 22:23:04 - mmengine - INFO - Epoch(train) [1116][30/63] lr: 6.3984e-04 eta: 1:39:46 time: 0.7990 data_time: 0.0249 memory: 16201 loss_prob: 0.3096 loss_thr: 0.2117 loss_db: 0.0538 loss: 0.5751 2022/08/30 22:23:08 - mmengine - INFO - Epoch(train) [1116][35/63] lr: 6.3984e-04 eta: 1:39:46 time: 0.7918 data_time: 0.0265 memory: 16201 loss_prob: 0.3508 loss_thr: 0.2346 loss_db: 0.0601 loss: 0.6455 2022/08/30 22:23:12 - mmengine - INFO - Epoch(train) [1116][40/63] lr: 6.3984e-04 eta: 1:39:35 time: 0.8010 data_time: 0.0254 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2351 loss_db: 0.0618 loss: 0.6405 2022/08/30 22:23:16 - mmengine - INFO - Epoch(train) [1116][45/63] lr: 6.3984e-04 eta: 1:39:35 time: 0.8092 data_time: 0.0265 memory: 16201 loss_prob: 0.3335 loss_thr: 0.2350 loss_db: 0.0596 loss: 0.6281 2022/08/30 22:23:20 - mmengine - INFO - Epoch(train) [1116][50/63] lr: 6.3984e-04 eta: 1:39:23 time: 0.8109 data_time: 0.0296 memory: 16201 loss_prob: 0.3258 loss_thr: 0.2294 loss_db: 0.0570 loss: 0.6121 2022/08/30 22:23:24 - mmengine - INFO - Epoch(train) [1116][55/63] lr: 6.3984e-04 eta: 1:39:23 time: 0.8014 data_time: 0.0295 memory: 16201 loss_prob: 0.3356 loss_thr: 0.2350 loss_db: 0.0592 loss: 0.6299 2022/08/30 22:23:28 - mmengine - INFO - Epoch(train) [1116][60/63] lr: 6.3984e-04 eta: 1:39:12 time: 0.7818 data_time: 0.0267 memory: 16201 loss_prob: 0.3255 loss_thr: 0.2283 loss_db: 0.0587 loss: 0.6124 2022/08/30 22:23:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:23:36 - mmengine - INFO - Epoch(train) [1117][5/63] lr: 6.3299e-04 eta: 1:39:12 time: 0.9609 data_time: 0.2024 memory: 16201 loss_prob: 0.3154 loss_thr: 0.2251 loss_db: 0.0567 loss: 0.5971 2022/08/30 22:23:40 - mmengine - INFO - Epoch(train) [1117][10/63] lr: 6.3299e-04 eta: 1:38:57 time: 0.9920 data_time: 0.2146 memory: 16201 loss_prob: 0.3192 loss_thr: 0.2269 loss_db: 0.0582 loss: 0.6042 2022/08/30 22:23:44 - mmengine - INFO - Epoch(train) [1117][15/63] lr: 6.3299e-04 eta: 1:38:57 time: 0.8181 data_time: 0.0373 memory: 16201 loss_prob: 0.3209 loss_thr: 0.2221 loss_db: 0.0574 loss: 0.6005 2022/08/30 22:23:48 - mmengine - INFO - Epoch(train) [1117][20/63] lr: 6.3299e-04 eta: 1:38:45 time: 0.8133 data_time: 0.0284 memory: 16201 loss_prob: 0.3024 loss_thr: 0.2249 loss_db: 0.0538 loss: 0.5811 2022/08/30 22:23:52 - mmengine - INFO - Epoch(train) [1117][25/63] lr: 6.3299e-04 eta: 1:38:45 time: 0.7941 data_time: 0.0285 memory: 16201 loss_prob: 0.3079 loss_thr: 0.2282 loss_db: 0.0554 loss: 0.5915 2022/08/30 22:23:56 - mmengine - INFO - Epoch(train) [1117][30/63] lr: 6.3299e-04 eta: 1:38:34 time: 0.7947 data_time: 0.0273 memory: 16201 loss_prob: 0.3642 loss_thr: 0.2486 loss_db: 0.0653 loss: 0.6782 2022/08/30 22:24:00 - mmengine - INFO - Epoch(train) [1117][35/63] lr: 6.3299e-04 eta: 1:38:34 time: 0.7891 data_time: 0.0222 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2323 loss_db: 0.0600 loss: 0.6262 2022/08/30 22:24:04 - mmengine - INFO - Epoch(train) [1117][40/63] lr: 6.3299e-04 eta: 1:38:22 time: 0.8105 data_time: 0.0305 memory: 16201 loss_prob: 0.2713 loss_thr: 0.2008 loss_db: 0.0489 loss: 0.5209 2022/08/30 22:24:08 - mmengine - INFO - Epoch(train) [1117][45/63] lr: 6.3299e-04 eta: 1:38:22 time: 0.8105 data_time: 0.0281 memory: 16201 loss_prob: 0.2967 loss_thr: 0.2127 loss_db: 0.0528 loss: 0.5622 2022/08/30 22:24:12 - mmengine - INFO - Epoch(train) [1117][50/63] lr: 6.3299e-04 eta: 1:38:11 time: 0.7862 data_time: 0.0216 memory: 16201 loss_prob: 0.2923 loss_thr: 0.2081 loss_db: 0.0517 loss: 0.5521 2022/08/30 22:24:16 - mmengine - INFO - Epoch(train) [1117][55/63] lr: 6.3299e-04 eta: 1:38:11 time: 0.7853 data_time: 0.0254 memory: 16201 loss_prob: 0.3019 loss_thr: 0.2159 loss_db: 0.0542 loss: 0.5720 2022/08/30 22:24:20 - mmengine - INFO - Epoch(train) [1117][60/63] lr: 6.3299e-04 eta: 1:37:59 time: 0.8084 data_time: 0.0255 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2244 loss_db: 0.0583 loss: 0.6076 2022/08/30 22:24:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:24:28 - mmengine - INFO - Epoch(train) [1118][5/63] lr: 6.2612e-04 eta: 1:37:59 time: 0.9063 data_time: 0.1561 memory: 16201 loss_prob: 0.3122 loss_thr: 0.2208 loss_db: 0.0558 loss: 0.5887 2022/08/30 22:24:32 - mmengine - INFO - Epoch(train) [1118][10/63] lr: 6.2612e-04 eta: 1:37:44 time: 0.9423 data_time: 0.1738 memory: 16201 loss_prob: 0.3072 loss_thr: 0.2216 loss_db: 0.0554 loss: 0.5842 2022/08/30 22:24:36 - mmengine - INFO - Epoch(train) [1118][15/63] lr: 6.2612e-04 eta: 1:37:44 time: 0.8130 data_time: 0.0334 memory: 16201 loss_prob: 0.3132 loss_thr: 0.2251 loss_db: 0.0559 loss: 0.5942 2022/08/30 22:24:40 - mmengine - INFO - Epoch(train) [1118][20/63] lr: 6.2612e-04 eta: 1:37:33 time: 0.8010 data_time: 0.0175 memory: 16201 loss_prob: 0.3074 loss_thr: 0.2246 loss_db: 0.0551 loss: 0.5870 2022/08/30 22:24:44 - mmengine - INFO - Epoch(train) [1118][25/63] lr: 6.2612e-04 eta: 1:37:33 time: 0.7905 data_time: 0.0304 memory: 16201 loss_prob: 0.2875 loss_thr: 0.2067 loss_db: 0.0526 loss: 0.5468 2022/08/30 22:24:48 - mmengine - INFO - Epoch(train) [1118][30/63] lr: 6.2612e-04 eta: 1:37:21 time: 0.8110 data_time: 0.0234 memory: 16201 loss_prob: 0.2504 loss_thr: 0.1814 loss_db: 0.0454 loss: 0.4772 2022/08/30 22:24:52 - mmengine - INFO - Epoch(train) [1118][35/63] lr: 6.2612e-04 eta: 1:37:21 time: 0.8084 data_time: 0.0197 memory: 16201 loss_prob: 0.2715 loss_thr: 0.1945 loss_db: 0.0488 loss: 0.5148 2022/08/30 22:24:56 - mmengine - INFO - Epoch(train) [1118][40/63] lr: 6.2612e-04 eta: 1:37:10 time: 0.7921 data_time: 0.0252 memory: 16201 loss_prob: 0.3180 loss_thr: 0.2193 loss_db: 0.0571 loss: 0.5944 2022/08/30 22:25:00 - mmengine - INFO - Epoch(train) [1118][45/63] lr: 6.2612e-04 eta: 1:37:10 time: 0.7976 data_time: 0.0230 memory: 16201 loss_prob: 0.3386 loss_thr: 0.2323 loss_db: 0.0582 loss: 0.6291 2022/08/30 22:25:04 - mmengine - INFO - Epoch(train) [1118][50/63] lr: 6.2612e-04 eta: 1:36:58 time: 0.7847 data_time: 0.0286 memory: 16201 loss_prob: 0.3272 loss_thr: 0.2218 loss_db: 0.0565 loss: 0.6056 2022/08/30 22:25:07 - mmengine - INFO - Epoch(train) [1118][55/63] lr: 6.2612e-04 eta: 1:36:58 time: 0.7724 data_time: 0.0262 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2065 loss_db: 0.0558 loss: 0.5671 2022/08/30 22:25:12 - mmengine - INFO - Epoch(train) [1118][60/63] lr: 6.2612e-04 eta: 1:36:47 time: 0.8051 data_time: 0.0236 memory: 16201 loss_prob: 0.2974 loss_thr: 0.2157 loss_db: 0.0544 loss: 0.5675 2022/08/30 22:25:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:25:20 - mmengine - INFO - Epoch(train) [1119][5/63] lr: 6.1924e-04 eta: 1:36:47 time: 0.9478 data_time: 0.1954 memory: 16201 loss_prob: 0.3492 loss_thr: 0.2476 loss_db: 0.0618 loss: 0.6587 2022/08/30 22:25:24 - mmengine - INFO - Epoch(train) [1119][10/63] lr: 6.1924e-04 eta: 1:36:32 time: 0.9880 data_time: 0.2039 memory: 16201 loss_prob: 0.3512 loss_thr: 0.2555 loss_db: 0.0638 loss: 0.6705 2022/08/30 22:25:28 - mmengine - INFO - Epoch(train) [1119][15/63] lr: 6.1924e-04 eta: 1:36:32 time: 0.7986 data_time: 0.0265 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2615 loss_db: 0.0630 loss: 0.6782 2022/08/30 22:25:32 - mmengine - INFO - Epoch(train) [1119][20/63] lr: 6.1924e-04 eta: 1:36:20 time: 0.8362 data_time: 0.0211 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2350 loss_db: 0.0565 loss: 0.6101 2022/08/30 22:25:36 - mmengine - INFO - Epoch(train) [1119][25/63] lr: 6.1924e-04 eta: 1:36:20 time: 0.8484 data_time: 0.0376 memory: 16201 loss_prob: 0.3288 loss_thr: 0.2373 loss_db: 0.0574 loss: 0.6236 2022/08/30 22:25:40 - mmengine - INFO - Epoch(train) [1119][30/63] lr: 6.1924e-04 eta: 1:36:09 time: 0.7916 data_time: 0.0275 memory: 16201 loss_prob: 0.3220 loss_thr: 0.2342 loss_db: 0.0571 loss: 0.6133 2022/08/30 22:25:44 - mmengine - INFO - Epoch(train) [1119][35/63] lr: 6.1924e-04 eta: 1:36:09 time: 0.7909 data_time: 0.0222 memory: 16201 loss_prob: 0.2847 loss_thr: 0.2093 loss_db: 0.0505 loss: 0.5445 2022/08/30 22:25:48 - mmengine - INFO - Epoch(train) [1119][40/63] lr: 6.1924e-04 eta: 1:35:58 time: 0.7919 data_time: 0.0312 memory: 16201 loss_prob: 0.3040 loss_thr: 0.2189 loss_db: 0.0538 loss: 0.5766 2022/08/30 22:25:52 - mmengine - INFO - Epoch(train) [1119][45/63] lr: 6.1924e-04 eta: 1:35:58 time: 0.7915 data_time: 0.0295 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2247 loss_db: 0.0589 loss: 0.6045 2022/08/30 22:25:56 - mmengine - INFO - Epoch(train) [1119][50/63] lr: 6.1924e-04 eta: 1:35:46 time: 0.7898 data_time: 0.0273 memory: 16201 loss_prob: 0.3064 loss_thr: 0.2116 loss_db: 0.0553 loss: 0.5733 2022/08/30 22:26:00 - mmengine - INFO - Epoch(train) [1119][55/63] lr: 6.1924e-04 eta: 1:35:46 time: 0.8144 data_time: 0.0229 memory: 16201 loss_prob: 0.3149 loss_thr: 0.2170 loss_db: 0.0563 loss: 0.5882 2022/08/30 22:26:04 - mmengine - INFO - Epoch(train) [1119][60/63] lr: 6.1924e-04 eta: 1:35:35 time: 0.8372 data_time: 0.0304 memory: 16201 loss_prob: 0.3147 loss_thr: 0.2154 loss_db: 0.0572 loss: 0.5873 2022/08/30 22:26:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:26:12 - mmengine - INFO - Epoch(train) [1120][5/63] lr: 6.1236e-04 eta: 1:35:35 time: 0.9608 data_time: 0.1982 memory: 16201 loss_prob: 0.3277 loss_thr: 0.2308 loss_db: 0.0588 loss: 0.6173 2022/08/30 22:26:16 - mmengine - INFO - Epoch(train) [1120][10/63] lr: 6.1236e-04 eta: 1:35:20 time: 1.0008 data_time: 0.2149 memory: 16201 loss_prob: 0.3227 loss_thr: 0.2264 loss_db: 0.0585 loss: 0.6076 2022/08/30 22:26:21 - mmengine - INFO - Epoch(train) [1120][15/63] lr: 6.1236e-04 eta: 1:35:20 time: 0.8388 data_time: 0.0243 memory: 16201 loss_prob: 0.3137 loss_thr: 0.2137 loss_db: 0.0559 loss: 0.5834 2022/08/30 22:26:25 - mmengine - INFO - Epoch(train) [1120][20/63] lr: 6.1236e-04 eta: 1:35:08 time: 0.8270 data_time: 0.0157 memory: 16201 loss_prob: 0.2774 loss_thr: 0.1974 loss_db: 0.0494 loss: 0.5242 2022/08/30 22:26:29 - mmengine - INFO - Epoch(train) [1120][25/63] lr: 6.1236e-04 eta: 1:35:08 time: 0.8167 data_time: 0.0331 memory: 16201 loss_prob: 0.2948 loss_thr: 0.2162 loss_db: 0.0525 loss: 0.5635 2022/08/30 22:26:33 - mmengine - INFO - Epoch(train) [1120][30/63] lr: 6.1236e-04 eta: 1:34:57 time: 0.8074 data_time: 0.0301 memory: 16201 loss_prob: 0.3183 loss_thr: 0.2327 loss_db: 0.0568 loss: 0.6078 2022/08/30 22:26:37 - mmengine - INFO - Epoch(train) [1120][35/63] lr: 6.1236e-04 eta: 1:34:57 time: 0.7923 data_time: 0.0226 memory: 16201 loss_prob: 0.3455 loss_thr: 0.2374 loss_db: 0.0603 loss: 0.6433 2022/08/30 22:26:41 - mmengine - INFO - Epoch(train) [1120][40/63] lr: 6.1236e-04 eta: 1:34:45 time: 0.8142 data_time: 0.0269 memory: 16201 loss_prob: 0.3439 loss_thr: 0.2350 loss_db: 0.0603 loss: 0.6392 2022/08/30 22:26:45 - mmengine - INFO - Epoch(train) [1120][45/63] lr: 6.1236e-04 eta: 1:34:45 time: 0.8122 data_time: 0.0287 memory: 16201 loss_prob: 0.2841 loss_thr: 0.2093 loss_db: 0.0519 loss: 0.5453 2022/08/30 22:26:49 - mmengine - INFO - Epoch(train) [1120][50/63] lr: 6.1236e-04 eta: 1:34:34 time: 0.8082 data_time: 0.0309 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2158 loss_db: 0.0578 loss: 0.5975 2022/08/30 22:26:53 - mmengine - INFO - Epoch(train) [1120][55/63] lr: 6.1236e-04 eta: 1:34:34 time: 0.8587 data_time: 0.0286 memory: 16201 loss_prob: 0.3286 loss_thr: 0.2202 loss_db: 0.0580 loss: 0.6068 2022/08/30 22:26:57 - mmengine - INFO - Epoch(train) [1120][60/63] lr: 6.1236e-04 eta: 1:34:22 time: 0.8549 data_time: 0.0266 memory: 16201 loss_prob: 0.3064 loss_thr: 0.2225 loss_db: 0.0559 loss: 0.5848 2022/08/30 22:26:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:26:59 - mmengine - INFO - Saving checkpoint at 1120 epochs 2022/08/30 22:27:08 - mmengine - INFO - Epoch(val) [1120][5/32] eta: 1:34:22 time: 0.6150 data_time: 0.1113 memory: 16201 2022/08/30 22:27:11 - mmengine - INFO - Epoch(val) [1120][10/32] eta: 0:00:15 time: 0.7023 data_time: 0.1407 memory: 15734 2022/08/30 22:27:14 - mmengine - INFO - Epoch(val) [1120][15/32] eta: 0:00:15 time: 0.6004 data_time: 0.0451 memory: 15734 2022/08/30 22:27:17 - mmengine - INFO - Epoch(val) [1120][20/32] eta: 0:00:07 time: 0.6175 data_time: 0.0478 memory: 15734 2022/08/30 22:27:21 - mmengine - INFO - Epoch(val) [1120][25/32] eta: 0:00:07 time: 0.6848 data_time: 0.0595 memory: 15734 2022/08/30 22:27:23 - mmengine - INFO - Epoch(val) [1120][30/32] eta: 0:00:01 time: 0.6308 data_time: 0.0302 memory: 15734 2022/08/30 22:27:24 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 22:27:24 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8565, precision: 0.7981, hmean: 0.8263 2022/08/30 22:27:24 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8565, precision: 0.8210, hmean: 0.8384 2022/08/30 22:27:24 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8565, precision: 0.8435, hmean: 0.8500 2022/08/30 22:27:24 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8541, precision: 0.8624, hmean: 0.8582 2022/08/30 22:27:24 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8474, precision: 0.8849, hmean: 0.8657 2022/08/30 22:27:24 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8286, precision: 0.9101, hmean: 0.8674 2022/08/30 22:27:24 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.5243, precision: 0.9478, hmean: 0.6751 2022/08/30 22:27:24 - mmengine - INFO - Epoch(val) [1120][32/32] icdar/precision: 0.9101 icdar/recall: 0.8286 icdar/hmean: 0.8674 2022/08/30 22:27:31 - mmengine - INFO - Epoch(train) [1121][5/63] lr: 6.0547e-04 eta: 0:00:01 time: 1.0184 data_time: 0.2197 memory: 16201 loss_prob: 0.3169 loss_thr: 0.2236 loss_db: 0.0557 loss: 0.5962 2022/08/30 22:27:35 - mmengine - INFO - Epoch(train) [1121][10/63] lr: 6.0547e-04 eta: 1:34:08 time: 1.0434 data_time: 0.2219 memory: 16201 loss_prob: 0.3544 loss_thr: 0.2484 loss_db: 0.0622 loss: 0.6650 2022/08/30 22:27:39 - mmengine - INFO - Epoch(train) [1121][15/63] lr: 6.0547e-04 eta: 1:34:08 time: 0.7884 data_time: 0.0256 memory: 16201 loss_prob: 0.3414 loss_thr: 0.2314 loss_db: 0.0581 loss: 0.6309 2022/08/30 22:27:43 - mmengine - INFO - Epoch(train) [1121][20/63] lr: 6.0547e-04 eta: 1:33:56 time: 0.8230 data_time: 0.0276 memory: 16201 loss_prob: 0.3202 loss_thr: 0.2202 loss_db: 0.0561 loss: 0.5964 2022/08/30 22:27:47 - mmengine - INFO - Epoch(train) [1121][25/63] lr: 6.0547e-04 eta: 1:33:56 time: 0.8302 data_time: 0.0264 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2286 loss_db: 0.0594 loss: 0.6119 2022/08/30 22:27:51 - mmengine - INFO - Epoch(train) [1121][30/63] lr: 6.0547e-04 eta: 1:33:45 time: 0.8091 data_time: 0.0225 memory: 16201 loss_prob: 0.3003 loss_thr: 0.2104 loss_db: 0.0552 loss: 0.5660 2022/08/30 22:27:55 - mmengine - INFO - Epoch(train) [1121][35/63] lr: 6.0547e-04 eta: 1:33:45 time: 0.7967 data_time: 0.0272 memory: 16201 loss_prob: 0.3229 loss_thr: 0.2266 loss_db: 0.0575 loss: 0.6069 2022/08/30 22:27:59 - mmengine - INFO - Epoch(train) [1121][40/63] lr: 6.0547e-04 eta: 1:33:33 time: 0.7874 data_time: 0.0237 memory: 16201 loss_prob: 0.3423 loss_thr: 0.2456 loss_db: 0.0593 loss: 0.6472 2022/08/30 22:28:03 - mmengine - INFO - Epoch(train) [1121][45/63] lr: 6.0547e-04 eta: 1:33:33 time: 0.8309 data_time: 0.0256 memory: 16201 loss_prob: 0.3293 loss_thr: 0.2360 loss_db: 0.0578 loss: 0.6232 2022/08/30 22:28:07 - mmengine - INFO - Epoch(train) [1121][50/63] lr: 6.0547e-04 eta: 1:33:22 time: 0.8477 data_time: 0.0495 memory: 16201 loss_prob: 0.3345 loss_thr: 0.2321 loss_db: 0.0596 loss: 0.6262 2022/08/30 22:28:11 - mmengine - INFO - Epoch(train) [1121][55/63] lr: 6.0547e-04 eta: 1:33:22 time: 0.7996 data_time: 0.0442 memory: 16201 loss_prob: 0.3428 loss_thr: 0.2411 loss_db: 0.0615 loss: 0.6454 2022/08/30 22:28:16 - mmengine - INFO - Epoch(train) [1121][60/63] lr: 6.0547e-04 eta: 1:33:10 time: 0.8257 data_time: 0.0675 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2223 loss_db: 0.0569 loss: 0.5925 2022/08/30 22:28:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:28:24 - mmengine - INFO - Epoch(train) [1122][5/63] lr: 5.9857e-04 eta: 1:33:10 time: 0.9542 data_time: 0.2259 memory: 16201 loss_prob: 0.2911 loss_thr: 0.2016 loss_db: 0.0534 loss: 0.5460 2022/08/30 22:28:28 - mmengine - INFO - Epoch(train) [1122][10/63] lr: 5.9857e-04 eta: 1:32:55 time: 1.0480 data_time: 0.2675 memory: 16201 loss_prob: 0.3276 loss_thr: 0.2363 loss_db: 0.0582 loss: 0.6221 2022/08/30 22:28:32 - mmengine - INFO - Epoch(train) [1122][15/63] lr: 5.9857e-04 eta: 1:32:55 time: 0.8444 data_time: 0.0693 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2384 loss_db: 0.0561 loss: 0.6155 2022/08/30 22:28:36 - mmengine - INFO - Epoch(train) [1122][20/63] lr: 5.9857e-04 eta: 1:32:44 time: 0.7988 data_time: 0.0402 memory: 16201 loss_prob: 0.3252 loss_thr: 0.2280 loss_db: 0.0585 loss: 0.6117 2022/08/30 22:28:41 - mmengine - INFO - Epoch(train) [1122][25/63] lr: 5.9857e-04 eta: 1:32:44 time: 0.8501 data_time: 0.0810 memory: 16201 loss_prob: 0.3317 loss_thr: 0.2290 loss_db: 0.0603 loss: 0.6210 2022/08/30 22:28:45 - mmengine - INFO - Epoch(train) [1122][30/63] lr: 5.9857e-04 eta: 1:32:33 time: 0.8464 data_time: 0.0708 memory: 16201 loss_prob: 0.3040 loss_thr: 0.2146 loss_db: 0.0555 loss: 0.5741 2022/08/30 22:28:49 - mmengine - INFO - Epoch(train) [1122][35/63] lr: 5.9857e-04 eta: 1:32:33 time: 0.8043 data_time: 0.0383 memory: 16201 loss_prob: 0.2906 loss_thr: 0.2018 loss_db: 0.0524 loss: 0.5447 2022/08/30 22:28:53 - mmengine - INFO - Epoch(train) [1122][40/63] lr: 5.9857e-04 eta: 1:32:21 time: 0.8516 data_time: 0.0770 memory: 16201 loss_prob: 0.3201 loss_thr: 0.2167 loss_db: 0.0565 loss: 0.5934 2022/08/30 22:28:57 - mmengine - INFO - Epoch(train) [1122][45/63] lr: 5.9857e-04 eta: 1:32:21 time: 0.8579 data_time: 0.0768 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2267 loss_db: 0.0597 loss: 0.6217 2022/08/30 22:29:02 - mmengine - INFO - Epoch(train) [1122][50/63] lr: 5.9857e-04 eta: 1:32:10 time: 0.8584 data_time: 0.0493 memory: 16201 loss_prob: 0.3154 loss_thr: 0.2196 loss_db: 0.0559 loss: 0.5910 2022/08/30 22:29:06 - mmengine - INFO - Epoch(train) [1122][55/63] lr: 5.9857e-04 eta: 1:32:10 time: 0.8717 data_time: 0.0738 memory: 16201 loss_prob: 0.3190 loss_thr: 0.2189 loss_db: 0.0559 loss: 0.5938 2022/08/30 22:29:10 - mmengine - INFO - Epoch(train) [1122][60/63] lr: 5.9857e-04 eta: 1:31:58 time: 0.8376 data_time: 0.0687 memory: 16201 loss_prob: 0.3152 loss_thr: 0.2223 loss_db: 0.0562 loss: 0.5937 2022/08/30 22:29:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:29:19 - mmengine - INFO - Epoch(train) [1123][5/63] lr: 5.9166e-04 eta: 1:31:58 time: 1.0206 data_time: 0.2606 memory: 16201 loss_prob: 0.3101 loss_thr: 0.2218 loss_db: 0.0560 loss: 0.5880 2022/08/30 22:29:23 - mmengine - INFO - Epoch(train) [1123][10/63] lr: 5.9166e-04 eta: 1:31:43 time: 1.1064 data_time: 0.3058 memory: 16201 loss_prob: 0.3030 loss_thr: 0.2220 loss_db: 0.0525 loss: 0.5774 2022/08/30 22:29:27 - mmengine - INFO - Epoch(train) [1123][15/63] lr: 5.9166e-04 eta: 1:31:43 time: 0.8529 data_time: 0.0750 memory: 16201 loss_prob: 0.3009 loss_thr: 0.2153 loss_db: 0.0529 loss: 0.5691 2022/08/30 22:29:31 - mmengine - INFO - Epoch(train) [1123][20/63] lr: 5.9166e-04 eta: 1:31:32 time: 0.8313 data_time: 0.0375 memory: 16201 loss_prob: 0.3247 loss_thr: 0.2288 loss_db: 0.0580 loss: 0.6116 2022/08/30 22:29:36 - mmengine - INFO - Epoch(train) [1123][25/63] lr: 5.9166e-04 eta: 1:31:32 time: 0.8715 data_time: 0.0820 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2308 loss_db: 0.0579 loss: 0.6096 2022/08/30 22:29:40 - mmengine - INFO - Epoch(train) [1123][30/63] lr: 5.9166e-04 eta: 1:31:21 time: 0.8676 data_time: 0.0746 memory: 16201 loss_prob: 0.3044 loss_thr: 0.2219 loss_db: 0.0541 loss: 0.5804 2022/08/30 22:29:44 - mmengine - INFO - Epoch(train) [1123][35/63] lr: 5.9166e-04 eta: 1:31:21 time: 0.8298 data_time: 0.0419 memory: 16201 loss_prob: 0.3274 loss_thr: 0.2221 loss_db: 0.0582 loss: 0.6077 2022/08/30 22:29:49 - mmengine - INFO - Epoch(train) [1123][40/63] lr: 5.9166e-04 eta: 1:31:09 time: 0.8559 data_time: 0.0763 memory: 16201 loss_prob: 0.3713 loss_thr: 0.2283 loss_db: 0.0622 loss: 0.6619 2022/08/30 22:29:53 - mmengine - INFO - Epoch(train) [1123][45/63] lr: 5.9166e-04 eta: 1:31:09 time: 0.8650 data_time: 0.0726 memory: 16201 loss_prob: 0.3873 loss_thr: 0.2449 loss_db: 0.0644 loss: 0.6966 2022/08/30 22:29:57 - mmengine - INFO - Epoch(train) [1123][50/63] lr: 5.9166e-04 eta: 1:30:58 time: 0.8386 data_time: 0.0490 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2346 loss_db: 0.0607 loss: 0.6374 2022/08/30 22:30:02 - mmengine - INFO - Epoch(train) [1123][55/63] lr: 5.9166e-04 eta: 1:30:58 time: 0.8738 data_time: 0.0791 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2412 loss_db: 0.0613 loss: 0.6489 2022/08/30 22:30:06 - mmengine - INFO - Epoch(train) [1123][60/63] lr: 5.9166e-04 eta: 1:30:46 time: 0.9080 data_time: 0.0802 memory: 16201 loss_prob: 0.3648 loss_thr: 0.2513 loss_db: 0.0649 loss: 0.6809 2022/08/30 22:30:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:30:15 - mmengine - INFO - Epoch(train) [1124][5/63] lr: 5.8474e-04 eta: 1:30:46 time: 1.0100 data_time: 0.2564 memory: 16201 loss_prob: 0.3237 loss_thr: 0.2265 loss_db: 0.0581 loss: 0.6083 2022/08/30 22:30:19 - mmengine - INFO - Epoch(train) [1124][10/63] lr: 5.8474e-04 eta: 1:30:32 time: 1.0369 data_time: 0.2590 memory: 16201 loss_prob: 0.3073 loss_thr: 0.2221 loss_db: 0.0569 loss: 0.5863 2022/08/30 22:30:23 - mmengine - INFO - Epoch(train) [1124][15/63] lr: 5.8474e-04 eta: 1:30:32 time: 0.8488 data_time: 0.0391 memory: 16201 loss_prob: 0.3058 loss_thr: 0.2167 loss_db: 0.0561 loss: 0.5786 2022/08/30 22:30:27 - mmengine - INFO - Epoch(train) [1124][20/63] lr: 5.8474e-04 eta: 1:30:20 time: 0.8613 data_time: 0.0453 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2136 loss_db: 0.0560 loss: 0.5796 2022/08/30 22:30:32 - mmengine - INFO - Epoch(train) [1124][25/63] lr: 5.8474e-04 eta: 1:30:20 time: 0.8539 data_time: 0.0772 memory: 16201 loss_prob: 0.3052 loss_thr: 0.2183 loss_db: 0.0554 loss: 0.5788 2022/08/30 22:30:36 - mmengine - INFO - Epoch(train) [1124][30/63] lr: 5.8474e-04 eta: 1:30:09 time: 0.8456 data_time: 0.0784 memory: 16201 loss_prob: 0.3045 loss_thr: 0.2257 loss_db: 0.0543 loss: 0.5845 2022/08/30 22:30:40 - mmengine - INFO - Epoch(train) [1124][35/63] lr: 5.8474e-04 eta: 1:30:09 time: 0.8353 data_time: 0.0477 memory: 16201 loss_prob: 0.3141 loss_thr: 0.2238 loss_db: 0.0555 loss: 0.5934 2022/08/30 22:30:44 - mmengine - INFO - Epoch(train) [1124][40/63] lr: 5.8474e-04 eta: 1:29:57 time: 0.8557 data_time: 0.0498 memory: 16201 loss_prob: 0.3262 loss_thr: 0.2350 loss_db: 0.0587 loss: 0.6199 2022/08/30 22:30:48 - mmengine - INFO - Epoch(train) [1124][45/63] lr: 5.8474e-04 eta: 1:29:57 time: 0.8201 data_time: 0.0405 memory: 16201 loss_prob: 0.3181 loss_thr: 0.2290 loss_db: 0.0576 loss: 0.6047 2022/08/30 22:30:52 - mmengine - INFO - Epoch(train) [1124][50/63] lr: 5.8474e-04 eta: 1:29:46 time: 0.7920 data_time: 0.0279 memory: 16201 loss_prob: 0.3386 loss_thr: 0.2300 loss_db: 0.0572 loss: 0.6258 2022/08/30 22:30:56 - mmengine - INFO - Epoch(train) [1124][55/63] lr: 5.8474e-04 eta: 1:29:46 time: 0.8103 data_time: 0.0281 memory: 16201 loss_prob: 0.3258 loss_thr: 0.2303 loss_db: 0.0550 loss: 0.6110 2022/08/30 22:31:00 - mmengine - INFO - Epoch(train) [1124][60/63] lr: 5.8474e-04 eta: 1:29:35 time: 0.8128 data_time: 0.0223 memory: 16201 loss_prob: 0.2955 loss_thr: 0.2196 loss_db: 0.0534 loss: 0.5685 2022/08/30 22:31:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:31:08 - mmengine - INFO - Epoch(train) [1125][5/63] lr: 5.7781e-04 eta: 1:29:35 time: 0.9576 data_time: 0.2072 memory: 16201 loss_prob: 0.3153 loss_thr: 0.2296 loss_db: 0.0548 loss: 0.5997 2022/08/30 22:31:12 - mmengine - INFO - Epoch(train) [1125][10/63] lr: 5.7781e-04 eta: 1:29:20 time: 1.0002 data_time: 0.2176 memory: 16201 loss_prob: 0.2991 loss_thr: 0.2102 loss_db: 0.0541 loss: 0.5635 2022/08/30 22:31:16 - mmengine - INFO - Epoch(train) [1125][15/63] lr: 5.7781e-04 eta: 1:29:20 time: 0.8029 data_time: 0.0258 memory: 16201 loss_prob: 0.2983 loss_thr: 0.2082 loss_db: 0.0553 loss: 0.5618 2022/08/30 22:31:21 - mmengine - INFO - Epoch(train) [1125][20/63] lr: 5.7781e-04 eta: 1:29:08 time: 0.8378 data_time: 0.0221 memory: 16201 loss_prob: 0.3041 loss_thr: 0.2218 loss_db: 0.0544 loss: 0.5803 2022/08/30 22:31:25 - mmengine - INFO - Epoch(train) [1125][25/63] lr: 5.7781e-04 eta: 1:29:08 time: 0.8454 data_time: 0.0296 memory: 16201 loss_prob: 0.2930 loss_thr: 0.2194 loss_db: 0.0522 loss: 0.5646 2022/08/30 22:31:29 - mmengine - INFO - Epoch(train) [1125][30/63] lr: 5.7781e-04 eta: 1:28:57 time: 0.7907 data_time: 0.0259 memory: 16201 loss_prob: 0.2851 loss_thr: 0.2097 loss_db: 0.0508 loss: 0.5456 2022/08/30 22:31:33 - mmengine - INFO - Epoch(train) [1125][35/63] lr: 5.7781e-04 eta: 1:28:57 time: 0.8004 data_time: 0.0247 memory: 16201 loss_prob: 0.3220 loss_thr: 0.2204 loss_db: 0.0577 loss: 0.6000 2022/08/30 22:31:37 - mmengine - INFO - Epoch(train) [1125][40/63] lr: 5.7781e-04 eta: 1:28:45 time: 0.8094 data_time: 0.0281 memory: 16201 loss_prob: 0.3293 loss_thr: 0.2178 loss_db: 0.0602 loss: 0.6073 2022/08/30 22:31:41 - mmengine - INFO - Epoch(train) [1125][45/63] lr: 5.7781e-04 eta: 1:28:45 time: 0.7920 data_time: 0.0272 memory: 16201 loss_prob: 0.3380 loss_thr: 0.2296 loss_db: 0.0601 loss: 0.6278 2022/08/30 22:31:45 - mmengine - INFO - Epoch(train) [1125][50/63] lr: 5.7781e-04 eta: 1:28:34 time: 0.8061 data_time: 0.0277 memory: 16201 loss_prob: 0.3363 loss_thr: 0.2341 loss_db: 0.0603 loss: 0.6307 2022/08/30 22:31:49 - mmengine - INFO - Epoch(train) [1125][55/63] lr: 5.7781e-04 eta: 1:28:34 time: 0.8016 data_time: 0.0237 memory: 16201 loss_prob: 0.3507 loss_thr: 0.2460 loss_db: 0.0626 loss: 0.6593 2022/08/30 22:31:53 - mmengine - INFO - Epoch(train) [1125][60/63] lr: 5.7781e-04 eta: 1:28:23 time: 0.8534 data_time: 0.0228 memory: 16201 loss_prob: 0.3234 loss_thr: 0.2430 loss_db: 0.0569 loss: 0.6233 2022/08/30 22:31:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:32:01 - mmengine - INFO - Epoch(train) [1126][5/63] lr: 5.7087e-04 eta: 1:28:23 time: 0.9093 data_time: 0.1510 memory: 16201 loss_prob: 0.2852 loss_thr: 0.2198 loss_db: 0.0515 loss: 0.5565 2022/08/30 22:32:05 - mmengine - INFO - Epoch(train) [1126][10/63] lr: 5.7087e-04 eta: 1:28:08 time: 0.9424 data_time: 0.1664 memory: 16201 loss_prob: 0.3457 loss_thr: 0.2371 loss_db: 0.0603 loss: 0.6432 2022/08/30 22:32:09 - mmengine - INFO - Epoch(train) [1126][15/63] lr: 5.7087e-04 eta: 1:28:08 time: 0.7983 data_time: 0.0263 memory: 16201 loss_prob: 0.3537 loss_thr: 0.2307 loss_db: 0.0614 loss: 0.6457 2022/08/30 22:32:13 - mmengine - INFO - Epoch(train) [1126][20/63] lr: 5.7087e-04 eta: 1:27:56 time: 0.7987 data_time: 0.0243 memory: 16201 loss_prob: 0.3157 loss_thr: 0.2160 loss_db: 0.0566 loss: 0.5883 2022/08/30 22:32:17 - mmengine - INFO - Epoch(train) [1126][25/63] lr: 5.7087e-04 eta: 1:27:56 time: 0.8097 data_time: 0.0363 memory: 16201 loss_prob: 0.3265 loss_thr: 0.2201 loss_db: 0.0582 loss: 0.6048 2022/08/30 22:32:22 - mmengine - INFO - Epoch(train) [1126][30/63] lr: 5.7087e-04 eta: 1:27:45 time: 0.8897 data_time: 0.0243 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2150 loss_db: 0.0556 loss: 0.5904 2022/08/30 22:32:26 - mmengine - INFO - Epoch(train) [1126][35/63] lr: 5.7087e-04 eta: 1:27:45 time: 0.8794 data_time: 0.0216 memory: 16201 loss_prob: 0.3231 loss_thr: 0.2248 loss_db: 0.0567 loss: 0.6047 2022/08/30 22:32:30 - mmengine - INFO - Epoch(train) [1126][40/63] lr: 5.7087e-04 eta: 1:27:33 time: 0.8008 data_time: 0.0287 memory: 16201 loss_prob: 0.3285 loss_thr: 0.2292 loss_db: 0.0571 loss: 0.6148 2022/08/30 22:32:34 - mmengine - INFO - Epoch(train) [1126][45/63] lr: 5.7087e-04 eta: 1:27:33 time: 0.8372 data_time: 0.0274 memory: 16201 loss_prob: 0.3065 loss_thr: 0.2194 loss_db: 0.0542 loss: 0.5802 2022/08/30 22:32:38 - mmengine - INFO - Epoch(train) [1126][50/63] lr: 5.7087e-04 eta: 1:27:22 time: 0.8411 data_time: 0.0292 memory: 16201 loss_prob: 0.2893 loss_thr: 0.2068 loss_db: 0.0540 loss: 0.5501 2022/08/30 22:32:42 - mmengine - INFO - Epoch(train) [1126][55/63] lr: 5.7087e-04 eta: 1:27:22 time: 0.8136 data_time: 0.0258 memory: 16201 loss_prob: 0.3016 loss_thr: 0.2097 loss_db: 0.0559 loss: 0.5672 2022/08/30 22:32:46 - mmengine - INFO - Epoch(train) [1126][60/63] lr: 5.7087e-04 eta: 1:27:11 time: 0.8107 data_time: 0.0263 memory: 16201 loss_prob: 0.3276 loss_thr: 0.2309 loss_db: 0.0584 loss: 0.6169 2022/08/30 22:32:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:32:54 - mmengine - INFO - Epoch(train) [1127][5/63] lr: 5.6393e-04 eta: 1:27:11 time: 0.9592 data_time: 0.2088 memory: 16201 loss_prob: 0.3260 loss_thr: 0.2343 loss_db: 0.0587 loss: 0.6189 2022/08/30 22:32:59 - mmengine - INFO - Epoch(train) [1127][10/63] lr: 5.6393e-04 eta: 1:26:56 time: 1.0352 data_time: 0.2503 memory: 16201 loss_prob: 0.2990 loss_thr: 0.2109 loss_db: 0.0547 loss: 0.5647 2022/08/30 22:33:03 - mmengine - INFO - Epoch(train) [1127][15/63] lr: 5.6393e-04 eta: 1:26:56 time: 0.8593 data_time: 0.0636 memory: 16201 loss_prob: 0.3426 loss_thr: 0.2382 loss_db: 0.0621 loss: 0.6428 2022/08/30 22:33:07 - mmengine - INFO - Epoch(train) [1127][20/63] lr: 5.6393e-04 eta: 1:26:44 time: 0.8030 data_time: 0.0210 memory: 16201 loss_prob: 0.3528 loss_thr: 0.2482 loss_db: 0.0615 loss: 0.6624 2022/08/30 22:33:11 - mmengine - INFO - Epoch(train) [1127][25/63] lr: 5.6393e-04 eta: 1:26:44 time: 0.8295 data_time: 0.0336 memory: 16201 loss_prob: 0.3478 loss_thr: 0.2375 loss_db: 0.0599 loss: 0.6452 2022/08/30 22:33:15 - mmengine - INFO - Epoch(train) [1127][30/63] lr: 5.6393e-04 eta: 1:26:33 time: 0.8349 data_time: 0.0288 memory: 16201 loss_prob: 0.3281 loss_thr: 0.2292 loss_db: 0.0571 loss: 0.6144 2022/08/30 22:33:19 - mmengine - INFO - Epoch(train) [1127][35/63] lr: 5.6393e-04 eta: 1:26:33 time: 0.7864 data_time: 0.0197 memory: 16201 loss_prob: 0.3092 loss_thr: 0.2244 loss_db: 0.0546 loss: 0.5883 2022/08/30 22:33:23 - mmengine - INFO - Epoch(train) [1127][40/63] lr: 5.6393e-04 eta: 1:26:21 time: 0.8252 data_time: 0.0249 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2370 loss_db: 0.0599 loss: 0.6380 2022/08/30 22:33:27 - mmengine - INFO - Epoch(train) [1127][45/63] lr: 5.6393e-04 eta: 1:26:21 time: 0.8389 data_time: 0.0267 memory: 16201 loss_prob: 0.3455 loss_thr: 0.2390 loss_db: 0.0596 loss: 0.6440 2022/08/30 22:33:32 - mmengine - INFO - Epoch(train) [1127][50/63] lr: 5.6393e-04 eta: 1:26:10 time: 0.8338 data_time: 0.0340 memory: 16201 loss_prob: 0.3056 loss_thr: 0.2108 loss_db: 0.0543 loss: 0.5708 2022/08/30 22:33:36 - mmengine - INFO - Epoch(train) [1127][55/63] lr: 5.6393e-04 eta: 1:26:10 time: 0.8196 data_time: 0.0346 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2197 loss_db: 0.0588 loss: 0.6035 2022/08/30 22:33:40 - mmengine - INFO - Epoch(train) [1127][60/63] lr: 5.6393e-04 eta: 1:25:59 time: 0.8073 data_time: 0.0285 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2287 loss_db: 0.0615 loss: 0.6408 2022/08/30 22:33:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:33:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:33:48 - mmengine - INFO - Epoch(train) [1128][5/63] lr: 5.5697e-04 eta: 1:25:59 time: 0.9608 data_time: 0.2055 memory: 16201 loss_prob: 0.3307 loss_thr: 0.2302 loss_db: 0.0591 loss: 0.6200 2022/08/30 22:33:52 - mmengine - INFO - Epoch(train) [1128][10/63] lr: 5.5697e-04 eta: 1:25:44 time: 1.0000 data_time: 0.2230 memory: 16201 loss_prob: 0.3163 loss_thr: 0.2272 loss_db: 0.0579 loss: 0.6015 2022/08/30 22:33:56 - mmengine - INFO - Epoch(train) [1128][15/63] lr: 5.5697e-04 eta: 1:25:44 time: 0.7927 data_time: 0.0278 memory: 16201 loss_prob: 0.3375 loss_thr: 0.2350 loss_db: 0.0602 loss: 0.6326 2022/08/30 22:34:00 - mmengine - INFO - Epoch(train) [1128][20/63] lr: 5.5697e-04 eta: 1:25:32 time: 0.7811 data_time: 0.0167 memory: 16201 loss_prob: 0.3406 loss_thr: 0.2373 loss_db: 0.0594 loss: 0.6373 2022/08/30 22:34:05 - mmengine - INFO - Epoch(train) [1128][25/63] lr: 5.5697e-04 eta: 1:25:32 time: 0.8962 data_time: 0.0326 memory: 16201 loss_prob: 0.3117 loss_thr: 0.2166 loss_db: 0.0561 loss: 0.5844 2022/08/30 22:34:08 - mmengine - INFO - Epoch(train) [1128][30/63] lr: 5.5697e-04 eta: 1:25:21 time: 0.8775 data_time: 0.0266 memory: 16201 loss_prob: 0.2983 loss_thr: 0.2033 loss_db: 0.0547 loss: 0.5563 2022/08/30 22:34:12 - mmengine - INFO - Epoch(train) [1128][35/63] lr: 5.5697e-04 eta: 1:25:21 time: 0.7707 data_time: 0.0192 memory: 16201 loss_prob: 0.3123 loss_thr: 0.2136 loss_db: 0.0567 loss: 0.5826 2022/08/30 22:34:16 - mmengine - INFO - Epoch(train) [1128][40/63] lr: 5.5697e-04 eta: 1:25:10 time: 0.7793 data_time: 0.0236 memory: 16201 loss_prob: 0.3305 loss_thr: 0.2250 loss_db: 0.0596 loss: 0.6151 2022/08/30 22:34:21 - mmengine - INFO - Epoch(train) [1128][45/63] lr: 5.5697e-04 eta: 1:25:10 time: 0.8499 data_time: 0.0241 memory: 16201 loss_prob: 0.2958 loss_thr: 0.2077 loss_db: 0.0530 loss: 0.5565 2022/08/30 22:34:25 - mmengine - INFO - Epoch(train) [1128][50/63] lr: 5.5697e-04 eta: 1:24:58 time: 0.8595 data_time: 0.0291 memory: 16201 loss_prob: 0.2879 loss_thr: 0.2033 loss_db: 0.0507 loss: 0.5420 2022/08/30 22:34:29 - mmengine - INFO - Epoch(train) [1128][55/63] lr: 5.5697e-04 eta: 1:24:58 time: 0.7878 data_time: 0.0245 memory: 16201 loss_prob: 0.3173 loss_thr: 0.2287 loss_db: 0.0548 loss: 0.6008 2022/08/30 22:34:33 - mmengine - INFO - Epoch(train) [1128][60/63] lr: 5.5697e-04 eta: 1:24:47 time: 0.8071 data_time: 0.0242 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2349 loss_db: 0.0563 loss: 0.6157 2022/08/30 22:34:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:34:40 - mmengine - INFO - Epoch(train) [1129][5/63] lr: 5.5000e-04 eta: 1:24:47 time: 0.8718 data_time: 0.1547 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2327 loss_db: 0.0590 loss: 0.6156 2022/08/30 22:34:44 - mmengine - INFO - Epoch(train) [1129][10/63] lr: 5.5000e-04 eta: 1:24:32 time: 0.9336 data_time: 0.1680 memory: 16201 loss_prob: 0.3201 loss_thr: 0.2353 loss_db: 0.0581 loss: 0.6135 2022/08/30 22:34:48 - mmengine - INFO - Epoch(train) [1129][15/63] lr: 5.5000e-04 eta: 1:24:32 time: 0.8145 data_time: 0.0280 memory: 16201 loss_prob: 0.3381 loss_thr: 0.2491 loss_db: 0.0599 loss: 0.6470 2022/08/30 22:34:52 - mmengine - INFO - Epoch(train) [1129][20/63] lr: 5.5000e-04 eta: 1:24:20 time: 0.8141 data_time: 0.0222 memory: 16201 loss_prob: 0.3099 loss_thr: 0.2275 loss_db: 0.0543 loss: 0.5917 2022/08/30 22:34:56 - mmengine - INFO - Epoch(train) [1129][25/63] lr: 5.5000e-04 eta: 1:24:20 time: 0.8059 data_time: 0.0297 memory: 16201 loss_prob: 0.3182 loss_thr: 0.2267 loss_db: 0.0568 loss: 0.6017 2022/08/30 22:35:00 - mmengine - INFO - Epoch(train) [1129][30/63] lr: 5.5000e-04 eta: 1:24:09 time: 0.8023 data_time: 0.0292 memory: 16201 loss_prob: 0.3182 loss_thr: 0.2262 loss_db: 0.0581 loss: 0.6025 2022/08/30 22:35:05 - mmengine - INFO - Epoch(train) [1129][35/63] lr: 5.5000e-04 eta: 1:24:09 time: 0.8219 data_time: 0.0244 memory: 16201 loss_prob: 0.2657 loss_thr: 0.1943 loss_db: 0.0478 loss: 0.5077 2022/08/30 22:35:08 - mmengine - INFO - Epoch(train) [1129][40/63] lr: 5.5000e-04 eta: 1:23:58 time: 0.8153 data_time: 0.0254 memory: 16201 loss_prob: 0.2772 loss_thr: 0.1995 loss_db: 0.0491 loss: 0.5258 2022/08/30 22:35:13 - mmengine - INFO - Epoch(train) [1129][45/63] lr: 5.5000e-04 eta: 1:23:58 time: 0.8269 data_time: 0.0296 memory: 16201 loss_prob: 0.3139 loss_thr: 0.2277 loss_db: 0.0566 loss: 0.5982 2022/08/30 22:35:17 - mmengine - INFO - Epoch(train) [1129][50/63] lr: 5.5000e-04 eta: 1:23:46 time: 0.8225 data_time: 0.0291 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2347 loss_db: 0.0565 loss: 0.6046 2022/08/30 22:35:21 - mmengine - INFO - Epoch(train) [1129][55/63] lr: 5.5000e-04 eta: 1:23:46 time: 0.8181 data_time: 0.0280 memory: 16201 loss_prob: 0.3052 loss_thr: 0.2178 loss_db: 0.0546 loss: 0.5776 2022/08/30 22:35:25 - mmengine - INFO - Epoch(train) [1129][60/63] lr: 5.5000e-04 eta: 1:23:35 time: 0.8240 data_time: 0.0264 memory: 16201 loss_prob: 0.3164 loss_thr: 0.2208 loss_db: 0.0566 loss: 0.5938 2022/08/30 22:35:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:35:33 - mmengine - INFO - Epoch(train) [1130][5/63] lr: 5.4303e-04 eta: 1:23:35 time: 0.9307 data_time: 0.1915 memory: 16201 loss_prob: 0.3189 loss_thr: 0.2201 loss_db: 0.0578 loss: 0.5968 2022/08/30 22:35:37 - mmengine - INFO - Epoch(train) [1130][10/63] lr: 5.4303e-04 eta: 1:23:20 time: 0.9820 data_time: 0.1988 memory: 16201 loss_prob: 0.3188 loss_thr: 0.2259 loss_db: 0.0569 loss: 0.6017 2022/08/30 22:35:41 - mmengine - INFO - Epoch(train) [1130][15/63] lr: 5.4303e-04 eta: 1:23:20 time: 0.8389 data_time: 0.0231 memory: 16201 loss_prob: 0.3390 loss_thr: 0.2404 loss_db: 0.0599 loss: 0.6393 2022/08/30 22:35:45 - mmengine - INFO - Epoch(train) [1130][20/63] lr: 5.4303e-04 eta: 1:23:09 time: 0.8401 data_time: 0.0228 memory: 16201 loss_prob: 0.2981 loss_thr: 0.2136 loss_db: 0.0533 loss: 0.5650 2022/08/30 22:35:49 - mmengine - INFO - Epoch(train) [1130][25/63] lr: 5.4303e-04 eta: 1:23:09 time: 0.8030 data_time: 0.0292 memory: 16201 loss_prob: 0.3079 loss_thr: 0.2154 loss_db: 0.0550 loss: 0.5783 2022/08/30 22:35:53 - mmengine - INFO - Epoch(train) [1130][30/63] lr: 5.4303e-04 eta: 1:22:57 time: 0.8185 data_time: 0.0228 memory: 16201 loss_prob: 0.3258 loss_thr: 0.2246 loss_db: 0.0590 loss: 0.6094 2022/08/30 22:35:57 - mmengine - INFO - Epoch(train) [1130][35/63] lr: 5.4303e-04 eta: 1:22:57 time: 0.8252 data_time: 0.0232 memory: 16201 loss_prob: 0.3123 loss_thr: 0.2098 loss_db: 0.0560 loss: 0.5782 2022/08/30 22:36:01 - mmengine - INFO - Epoch(train) [1130][40/63] lr: 5.4303e-04 eta: 1:22:46 time: 0.8034 data_time: 0.0254 memory: 16201 loss_prob: 0.3208 loss_thr: 0.2127 loss_db: 0.0547 loss: 0.5882 2022/08/30 22:36:05 - mmengine - INFO - Epoch(train) [1130][45/63] lr: 5.4303e-04 eta: 1:22:46 time: 0.7900 data_time: 0.0264 memory: 16201 loss_prob: 0.3293 loss_thr: 0.2229 loss_db: 0.0568 loss: 0.6089 2022/08/30 22:36:09 - mmengine - INFO - Epoch(train) [1130][50/63] lr: 5.4303e-04 eta: 1:22:34 time: 0.7766 data_time: 0.0229 memory: 16201 loss_prob: 0.3472 loss_thr: 0.2409 loss_db: 0.0611 loss: 0.6493 2022/08/30 22:36:14 - mmengine - INFO - Epoch(train) [1130][55/63] lr: 5.4303e-04 eta: 1:22:34 time: 0.8771 data_time: 0.0212 memory: 16201 loss_prob: 0.3290 loss_thr: 0.2431 loss_db: 0.0577 loss: 0.6298 2022/08/30 22:36:18 - mmengine - INFO - Epoch(train) [1130][60/63] lr: 5.4303e-04 eta: 1:22:23 time: 0.8997 data_time: 0.0339 memory: 16201 loss_prob: 0.3005 loss_thr: 0.2241 loss_db: 0.0536 loss: 0.5781 2022/08/30 22:36:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:36:26 - mmengine - INFO - Epoch(train) [1131][5/63] lr: 5.3604e-04 eta: 1:22:23 time: 0.9726 data_time: 0.2273 memory: 16201 loss_prob: 0.3652 loss_thr: 0.2527 loss_db: 0.0649 loss: 0.6828 2022/08/30 22:36:30 - mmengine - INFO - Epoch(train) [1131][10/63] lr: 5.3604e-04 eta: 1:22:08 time: 1.0313 data_time: 0.2388 memory: 16201 loss_prob: 0.3751 loss_thr: 0.2543 loss_db: 0.0669 loss: 0.6963 2022/08/30 22:36:34 - mmengine - INFO - Epoch(train) [1131][15/63] lr: 5.3604e-04 eta: 1:22:08 time: 0.7943 data_time: 0.0244 memory: 16201 loss_prob: 0.3090 loss_thr: 0.2187 loss_db: 0.0543 loss: 0.5820 2022/08/30 22:36:38 - mmengine - INFO - Epoch(train) [1131][20/63] lr: 5.3604e-04 eta: 1:21:57 time: 0.7977 data_time: 0.0201 memory: 16201 loss_prob: 0.2824 loss_thr: 0.2020 loss_db: 0.0499 loss: 0.5343 2022/08/30 22:36:42 - mmengine - INFO - Epoch(train) [1131][25/63] lr: 5.3604e-04 eta: 1:21:57 time: 0.8164 data_time: 0.0304 memory: 16201 loss_prob: 0.3118 loss_thr: 0.2105 loss_db: 0.0567 loss: 0.5789 2022/08/30 22:36:47 - mmengine - INFO - Epoch(train) [1131][30/63] lr: 5.3604e-04 eta: 1:21:45 time: 0.8088 data_time: 0.0240 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2295 loss_db: 0.0595 loss: 0.6210 2022/08/30 22:36:50 - mmengine - INFO - Epoch(train) [1131][35/63] lr: 5.3604e-04 eta: 1:21:45 time: 0.8009 data_time: 0.0250 memory: 16201 loss_prob: 0.3171 loss_thr: 0.2255 loss_db: 0.0557 loss: 0.5982 2022/08/30 22:36:54 - mmengine - INFO - Epoch(train) [1131][40/63] lr: 5.3604e-04 eta: 1:21:34 time: 0.7855 data_time: 0.0270 memory: 16201 loss_prob: 0.3337 loss_thr: 0.2306 loss_db: 0.0600 loss: 0.6243 2022/08/30 22:36:58 - mmengine - INFO - Epoch(train) [1131][45/63] lr: 5.3604e-04 eta: 1:21:34 time: 0.7895 data_time: 0.0238 memory: 16201 loss_prob: 0.3242 loss_thr: 0.2283 loss_db: 0.0593 loss: 0.6118 2022/08/30 22:37:04 - mmengine - INFO - Epoch(train) [1131][50/63] lr: 5.3604e-04 eta: 1:21:23 time: 0.9168 data_time: 0.0333 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2248 loss_db: 0.0593 loss: 0.6086 2022/08/30 22:37:08 - mmengine - INFO - Epoch(train) [1131][55/63] lr: 5.3604e-04 eta: 1:21:23 time: 0.9198 data_time: 0.0339 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2183 loss_db: 0.0563 loss: 0.5879 2022/08/30 22:37:12 - mmengine - INFO - Epoch(train) [1131][60/63] lr: 5.3604e-04 eta: 1:21:11 time: 0.8058 data_time: 0.0226 memory: 16201 loss_prob: 0.3039 loss_thr: 0.2110 loss_db: 0.0538 loss: 0.5686 2022/08/30 22:37:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:37:20 - mmengine - INFO - Epoch(train) [1132][5/63] lr: 5.2905e-04 eta: 1:21:11 time: 0.9566 data_time: 0.2035 memory: 16201 loss_prob: 0.3052 loss_thr: 0.2158 loss_db: 0.0553 loss: 0.5763 2022/08/30 22:37:24 - mmengine - INFO - Epoch(train) [1132][10/63] lr: 5.2905e-04 eta: 1:20:57 time: 0.9962 data_time: 0.2125 memory: 16201 loss_prob: 0.3042 loss_thr: 0.2175 loss_db: 0.0554 loss: 0.5771 2022/08/30 22:37:28 - mmengine - INFO - Epoch(train) [1132][15/63] lr: 5.2905e-04 eta: 1:20:57 time: 0.8202 data_time: 0.0283 memory: 16201 loss_prob: 0.3296 loss_thr: 0.2314 loss_db: 0.0579 loss: 0.6189 2022/08/30 22:37:32 - mmengine - INFO - Epoch(train) [1132][20/63] lr: 5.2905e-04 eta: 1:20:45 time: 0.8068 data_time: 0.0244 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2290 loss_db: 0.0608 loss: 0.6335 2022/08/30 22:37:36 - mmengine - INFO - Epoch(train) [1132][25/63] lr: 5.2905e-04 eta: 1:20:45 time: 0.8068 data_time: 0.0342 memory: 16201 loss_prob: 0.3155 loss_thr: 0.2145 loss_db: 0.0568 loss: 0.5868 2022/08/30 22:37:40 - mmengine - INFO - Epoch(train) [1132][30/63] lr: 5.2905e-04 eta: 1:20:34 time: 0.8163 data_time: 0.0280 memory: 16201 loss_prob: 0.3077 loss_thr: 0.2101 loss_db: 0.0549 loss: 0.5728 2022/08/30 22:37:45 - mmengine - INFO - Epoch(train) [1132][35/63] lr: 5.2905e-04 eta: 1:20:34 time: 0.8767 data_time: 0.0244 memory: 16201 loss_prob: 0.3083 loss_thr: 0.2161 loss_db: 0.0565 loss: 0.5809 2022/08/30 22:37:49 - mmengine - INFO - Epoch(train) [1132][40/63] lr: 5.2905e-04 eta: 1:20:22 time: 0.8687 data_time: 0.0257 memory: 16201 loss_prob: 0.2871 loss_thr: 0.2091 loss_db: 0.0519 loss: 0.5481 2022/08/30 22:37:53 - mmengine - INFO - Epoch(train) [1132][45/63] lr: 5.2905e-04 eta: 1:20:22 time: 0.7996 data_time: 0.0306 memory: 16201 loss_prob: 0.2941 loss_thr: 0.2186 loss_db: 0.0521 loss: 0.5648 2022/08/30 22:37:57 - mmengine - INFO - Epoch(train) [1132][50/63] lr: 5.2905e-04 eta: 1:20:11 time: 0.8818 data_time: 0.0351 memory: 16201 loss_prob: 0.3054 loss_thr: 0.2237 loss_db: 0.0539 loss: 0.5830 2022/08/30 22:38:01 - mmengine - INFO - Epoch(train) [1132][55/63] lr: 5.2905e-04 eta: 1:20:11 time: 0.8818 data_time: 0.0287 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2219 loss_db: 0.0556 loss: 0.5940 2022/08/30 22:38:05 - mmengine - INFO - Epoch(train) [1132][60/63] lr: 5.2905e-04 eta: 1:20:00 time: 0.8098 data_time: 0.0269 memory: 16201 loss_prob: 0.3223 loss_thr: 0.2261 loss_db: 0.0577 loss: 0.6061 2022/08/30 22:38:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:38:13 - mmengine - INFO - Epoch(train) [1133][5/63] lr: 5.2204e-04 eta: 1:20:00 time: 0.9351 data_time: 0.1719 memory: 16201 loss_prob: 0.3130 loss_thr: 0.2243 loss_db: 0.0555 loss: 0.5928 2022/08/30 22:38:17 - mmengine - INFO - Epoch(train) [1133][10/63] lr: 5.2204e-04 eta: 1:19:45 time: 0.9875 data_time: 0.1915 memory: 16201 loss_prob: 0.3069 loss_thr: 0.2179 loss_db: 0.0537 loss: 0.5785 2022/08/30 22:38:22 - mmengine - INFO - Epoch(train) [1133][15/63] lr: 5.2204e-04 eta: 1:19:45 time: 0.8268 data_time: 0.0316 memory: 16201 loss_prob: 0.3168 loss_thr: 0.2189 loss_db: 0.0572 loss: 0.5929 2022/08/30 22:38:26 - mmengine - INFO - Epoch(train) [1133][20/63] lr: 5.2204e-04 eta: 1:19:33 time: 0.8204 data_time: 0.0220 memory: 16201 loss_prob: 0.3071 loss_thr: 0.2106 loss_db: 0.0554 loss: 0.5731 2022/08/30 22:38:30 - mmengine - INFO - Epoch(train) [1133][25/63] lr: 5.2204e-04 eta: 1:19:33 time: 0.8095 data_time: 0.0318 memory: 16201 loss_prob: 0.3155 loss_thr: 0.2127 loss_db: 0.0558 loss: 0.5841 2022/08/30 22:38:34 - mmengine - INFO - Epoch(train) [1133][30/63] lr: 5.2204e-04 eta: 1:19:22 time: 0.8252 data_time: 0.0298 memory: 16201 loss_prob: 0.3427 loss_thr: 0.2315 loss_db: 0.0609 loss: 0.6351 2022/08/30 22:38:38 - mmengine - INFO - Epoch(train) [1133][35/63] lr: 5.2204e-04 eta: 1:19:22 time: 0.8169 data_time: 0.0281 memory: 16201 loss_prob: 0.3300 loss_thr: 0.2345 loss_db: 0.0587 loss: 0.6233 2022/08/30 22:38:42 - mmengine - INFO - Epoch(train) [1133][40/63] lr: 5.2204e-04 eta: 1:19:11 time: 0.8087 data_time: 0.0227 memory: 16201 loss_prob: 0.3134 loss_thr: 0.2292 loss_db: 0.0558 loss: 0.5985 2022/08/30 22:38:46 - mmengine - INFO - Epoch(train) [1133][45/63] lr: 5.2204e-04 eta: 1:19:11 time: 0.7993 data_time: 0.0254 memory: 16201 loss_prob: 0.3258 loss_thr: 0.2294 loss_db: 0.0590 loss: 0.6143 2022/08/30 22:38:50 - mmengine - INFO - Epoch(train) [1133][50/63] lr: 5.2204e-04 eta: 1:18:59 time: 0.8045 data_time: 0.0338 memory: 16201 loss_prob: 0.3288 loss_thr: 0.2263 loss_db: 0.0593 loss: 0.6144 2022/08/30 22:38:54 - mmengine - INFO - Epoch(train) [1133][55/63] lr: 5.2204e-04 eta: 1:18:59 time: 0.8280 data_time: 0.0275 memory: 16201 loss_prob: 0.3290 loss_thr: 0.2289 loss_db: 0.0578 loss: 0.6157 2022/08/30 22:38:58 - mmengine - INFO - Epoch(train) [1133][60/63] lr: 5.2204e-04 eta: 1:18:48 time: 0.8264 data_time: 0.0242 memory: 16201 loss_prob: 0.3416 loss_thr: 0.2377 loss_db: 0.0602 loss: 0.6394 2022/08/30 22:39:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:39:06 - mmengine - INFO - Epoch(train) [1134][5/63] lr: 5.1503e-04 eta: 1:18:48 time: 0.9364 data_time: 0.1979 memory: 16201 loss_prob: 0.3340 loss_thr: 0.2372 loss_db: 0.0619 loss: 0.6331 2022/08/30 22:39:10 - mmengine - INFO - Epoch(train) [1134][10/63] lr: 5.1503e-04 eta: 1:18:33 time: 0.9879 data_time: 0.2092 memory: 16201 loss_prob: 0.3167 loss_thr: 0.2205 loss_db: 0.0595 loss: 0.5966 2022/08/30 22:39:14 - mmengine - INFO - Epoch(train) [1134][15/63] lr: 5.1503e-04 eta: 1:18:33 time: 0.7911 data_time: 0.0237 memory: 16201 loss_prob: 0.3055 loss_thr: 0.2136 loss_db: 0.0555 loss: 0.5745 2022/08/30 22:39:18 - mmengine - INFO - Epoch(train) [1134][20/63] lr: 5.1503e-04 eta: 1:18:22 time: 0.7932 data_time: 0.0204 memory: 16201 loss_prob: 0.3175 loss_thr: 0.2289 loss_db: 0.0558 loss: 0.6022 2022/08/30 22:39:22 - mmengine - INFO - Epoch(train) [1134][25/63] lr: 5.1503e-04 eta: 1:18:22 time: 0.8121 data_time: 0.0349 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2309 loss_db: 0.0570 loss: 0.6181 2022/08/30 22:39:26 - mmengine - INFO - Epoch(train) [1134][30/63] lr: 5.1503e-04 eta: 1:18:10 time: 0.8137 data_time: 0.0251 memory: 16201 loss_prob: 0.3330 loss_thr: 0.2256 loss_db: 0.0585 loss: 0.6170 2022/08/30 22:39:30 - mmengine - INFO - Epoch(train) [1134][35/63] lr: 5.1503e-04 eta: 1:18:10 time: 0.7993 data_time: 0.0195 memory: 16201 loss_prob: 0.3286 loss_thr: 0.2328 loss_db: 0.0599 loss: 0.6212 2022/08/30 22:39:34 - mmengine - INFO - Epoch(train) [1134][40/63] lr: 5.1503e-04 eta: 1:17:59 time: 0.7857 data_time: 0.0245 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2424 loss_db: 0.0609 loss: 0.6379 2022/08/30 22:39:38 - mmengine - INFO - Epoch(train) [1134][45/63] lr: 5.1503e-04 eta: 1:17:59 time: 0.7937 data_time: 0.0245 memory: 16201 loss_prob: 0.3411 loss_thr: 0.2429 loss_db: 0.0613 loss: 0.6452 2022/08/30 22:39:42 - mmengine - INFO - Epoch(train) [1134][50/63] lr: 5.1503e-04 eta: 1:17:48 time: 0.8176 data_time: 0.0294 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2167 loss_db: 0.0557 loss: 0.5844 2022/08/30 22:39:46 - mmengine - INFO - Epoch(train) [1134][55/63] lr: 5.1503e-04 eta: 1:17:48 time: 0.8059 data_time: 0.0253 memory: 16201 loss_prob: 0.2911 loss_thr: 0.2018 loss_db: 0.0511 loss: 0.5440 2022/08/30 22:39:50 - mmengine - INFO - Epoch(train) [1134][60/63] lr: 5.1503e-04 eta: 1:17:36 time: 0.8035 data_time: 0.0241 memory: 16201 loss_prob: 0.3072 loss_thr: 0.2139 loss_db: 0.0546 loss: 0.5757 2022/08/30 22:39:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:39:58 - mmengine - INFO - Epoch(train) [1135][5/63] lr: 5.0800e-04 eta: 1:17:36 time: 0.9461 data_time: 0.1928 memory: 16201 loss_prob: 0.2932 loss_thr: 0.2124 loss_db: 0.0535 loss: 0.5591 2022/08/30 22:40:02 - mmengine - INFO - Epoch(train) [1135][10/63] lr: 5.0800e-04 eta: 1:17:21 time: 0.9920 data_time: 0.2025 memory: 16201 loss_prob: 0.3109 loss_thr: 0.2148 loss_db: 0.0563 loss: 0.5820 2022/08/30 22:40:06 - mmengine - INFO - Epoch(train) [1135][15/63] lr: 5.0800e-04 eta: 1:17:21 time: 0.8310 data_time: 0.0250 memory: 16201 loss_prob: 0.3147 loss_thr: 0.2194 loss_db: 0.0565 loss: 0.5906 2022/08/30 22:40:10 - mmengine - INFO - Epoch(train) [1135][20/63] lr: 5.0800e-04 eta: 1:17:10 time: 0.8295 data_time: 0.0221 memory: 16201 loss_prob: 0.2978 loss_thr: 0.2131 loss_db: 0.0527 loss: 0.5636 2022/08/30 22:40:14 - mmengine - INFO - Epoch(train) [1135][25/63] lr: 5.0800e-04 eta: 1:17:10 time: 0.8075 data_time: 0.0316 memory: 16201 loss_prob: 0.3012 loss_thr: 0.2133 loss_db: 0.0532 loss: 0.5677 2022/08/30 22:40:18 - mmengine - INFO - Epoch(train) [1135][30/63] lr: 5.0800e-04 eta: 1:16:59 time: 0.7943 data_time: 0.0265 memory: 16201 loss_prob: 0.3064 loss_thr: 0.2236 loss_db: 0.0548 loss: 0.5848 2022/08/30 22:40:22 - mmengine - INFO - Epoch(train) [1135][35/63] lr: 5.0800e-04 eta: 1:16:59 time: 0.7976 data_time: 0.0204 memory: 16201 loss_prob: 0.3098 loss_thr: 0.2187 loss_db: 0.0556 loss: 0.5841 2022/08/30 22:40:26 - mmengine - INFO - Epoch(train) [1135][40/63] lr: 5.0800e-04 eta: 1:16:47 time: 0.8032 data_time: 0.0259 memory: 16201 loss_prob: 0.3083 loss_thr: 0.2094 loss_db: 0.0555 loss: 0.5732 2022/08/30 22:40:30 - mmengine - INFO - Epoch(train) [1135][45/63] lr: 5.0800e-04 eta: 1:16:47 time: 0.7955 data_time: 0.0258 memory: 16201 loss_prob: 0.3079 loss_thr: 0.2164 loss_db: 0.0558 loss: 0.5800 2022/08/30 22:40:35 - mmengine - INFO - Epoch(train) [1135][50/63] lr: 5.0800e-04 eta: 1:16:36 time: 0.8288 data_time: 0.0400 memory: 16201 loss_prob: 0.3307 loss_thr: 0.2366 loss_db: 0.0600 loss: 0.6274 2022/08/30 22:40:39 - mmengine - INFO - Epoch(train) [1135][55/63] lr: 5.0800e-04 eta: 1:16:36 time: 0.8379 data_time: 0.0402 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2308 loss_db: 0.0572 loss: 0.6101 2022/08/30 22:40:43 - mmengine - INFO - Epoch(train) [1135][60/63] lr: 5.0800e-04 eta: 1:16:25 time: 0.8092 data_time: 0.0249 memory: 16201 loss_prob: 0.2993 loss_thr: 0.2197 loss_db: 0.0525 loss: 0.5715 2022/08/30 22:40:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:40:50 - mmengine - INFO - Epoch(train) [1136][5/63] lr: 5.0096e-04 eta: 1:16:25 time: 0.9056 data_time: 0.1631 memory: 16201 loss_prob: 0.2748 loss_thr: 0.1998 loss_db: 0.0499 loss: 0.5246 2022/08/30 22:40:54 - mmengine - INFO - Epoch(train) [1136][10/63] lr: 5.0096e-04 eta: 1:16:10 time: 0.9536 data_time: 0.1718 memory: 16201 loss_prob: 0.2880 loss_thr: 0.2037 loss_db: 0.0518 loss: 0.5435 2022/08/30 22:40:58 - mmengine - INFO - Epoch(train) [1136][15/63] lr: 5.0096e-04 eta: 1:16:10 time: 0.7941 data_time: 0.0248 memory: 16201 loss_prob: 0.3112 loss_thr: 0.2116 loss_db: 0.0549 loss: 0.5778 2022/08/30 22:41:02 - mmengine - INFO - Epoch(train) [1136][20/63] lr: 5.0096e-04 eta: 1:15:58 time: 0.7964 data_time: 0.0201 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2218 loss_db: 0.0569 loss: 0.5972 2022/08/30 22:41:06 - mmengine - INFO - Epoch(train) [1136][25/63] lr: 5.0096e-04 eta: 1:15:58 time: 0.7984 data_time: 0.0309 memory: 16201 loss_prob: 0.3297 loss_thr: 0.2310 loss_db: 0.0599 loss: 0.6206 2022/08/30 22:41:10 - mmengine - INFO - Epoch(train) [1136][30/63] lr: 5.0096e-04 eta: 1:15:47 time: 0.7959 data_time: 0.0260 memory: 16201 loss_prob: 0.3183 loss_thr: 0.2331 loss_db: 0.0571 loss: 0.6085 2022/08/30 22:41:14 - mmengine - INFO - Epoch(train) [1136][35/63] lr: 5.0096e-04 eta: 1:15:47 time: 0.7974 data_time: 0.0236 memory: 16201 loss_prob: 0.3264 loss_thr: 0.2397 loss_db: 0.0587 loss: 0.6249 2022/08/30 22:41:18 - mmengine - INFO - Epoch(train) [1136][40/63] lr: 5.0096e-04 eta: 1:15:36 time: 0.7943 data_time: 0.0298 memory: 16201 loss_prob: 0.3246 loss_thr: 0.2255 loss_db: 0.0586 loss: 0.6087 2022/08/30 22:41:22 - mmengine - INFO - Epoch(train) [1136][45/63] lr: 5.0096e-04 eta: 1:15:36 time: 0.7988 data_time: 0.0288 memory: 16201 loss_prob: 0.3247 loss_thr: 0.2261 loss_db: 0.0578 loss: 0.6086 2022/08/30 22:41:26 - mmengine - INFO - Epoch(train) [1136][50/63] lr: 5.0096e-04 eta: 1:15:24 time: 0.7960 data_time: 0.0241 memory: 16201 loss_prob: 0.3438 loss_thr: 0.2382 loss_db: 0.0607 loss: 0.6428 2022/08/30 22:41:30 - mmengine - INFO - Epoch(train) [1136][55/63] lr: 5.0096e-04 eta: 1:15:24 time: 0.7917 data_time: 0.0246 memory: 16201 loss_prob: 0.3321 loss_thr: 0.2279 loss_db: 0.0592 loss: 0.6191 2022/08/30 22:41:34 - mmengine - INFO - Epoch(train) [1136][60/63] lr: 5.0096e-04 eta: 1:15:13 time: 0.8217 data_time: 0.0271 memory: 16201 loss_prob: 0.3180 loss_thr: 0.2224 loss_db: 0.0567 loss: 0.5971 2022/08/30 22:41:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:41:44 - mmengine - INFO - Epoch(train) [1137][5/63] lr: 4.9391e-04 eta: 1:15:13 time: 1.1195 data_time: 0.2214 memory: 16201 loss_prob: 0.3248 loss_thr: 0.2238 loss_db: 0.0572 loss: 0.6058 2022/08/30 22:41:48 - mmengine - INFO - Epoch(train) [1137][10/63] lr: 4.9391e-04 eta: 1:14:58 time: 1.0220 data_time: 0.2298 memory: 16201 loss_prob: 0.3810 loss_thr: 0.2474 loss_db: 0.0648 loss: 0.6932 2022/08/30 22:41:52 - mmengine - INFO - Epoch(train) [1137][15/63] lr: 4.9391e-04 eta: 1:14:58 time: 0.8451 data_time: 0.0324 memory: 16201 loss_prob: 0.3963 loss_thr: 0.2567 loss_db: 0.0681 loss: 0.7211 2022/08/30 22:41:56 - mmengine - INFO - Epoch(train) [1137][20/63] lr: 4.9391e-04 eta: 1:14:47 time: 0.8440 data_time: 0.0239 memory: 16201 loss_prob: 0.3368 loss_thr: 0.2339 loss_db: 0.0603 loss: 0.6309 2022/08/30 22:42:01 - mmengine - INFO - Epoch(train) [1137][25/63] lr: 4.9391e-04 eta: 1:14:47 time: 0.8320 data_time: 0.0286 memory: 16201 loss_prob: 0.3104 loss_thr: 0.2295 loss_db: 0.0576 loss: 0.5975 2022/08/30 22:42:05 - mmengine - INFO - Epoch(train) [1137][30/63] lr: 4.9391e-04 eta: 1:14:35 time: 0.8614 data_time: 0.0285 memory: 16201 loss_prob: 0.2815 loss_thr: 0.2072 loss_db: 0.0513 loss: 0.5400 2022/08/30 22:42:09 - mmengine - INFO - Epoch(train) [1137][35/63] lr: 4.9391e-04 eta: 1:14:35 time: 0.8315 data_time: 0.0263 memory: 16201 loss_prob: 0.2899 loss_thr: 0.1986 loss_db: 0.0507 loss: 0.5392 2022/08/30 22:42:13 - mmengine - INFO - Epoch(train) [1137][40/63] lr: 4.9391e-04 eta: 1:14:24 time: 0.8001 data_time: 0.0297 memory: 16201 loss_prob: 0.3086 loss_thr: 0.2108 loss_db: 0.0552 loss: 0.5747 2022/08/30 22:42:17 - mmengine - INFO - Epoch(train) [1137][45/63] lr: 4.9391e-04 eta: 1:14:24 time: 0.8047 data_time: 0.0256 memory: 16201 loss_prob: 0.3367 loss_thr: 0.2315 loss_db: 0.0615 loss: 0.6297 2022/08/30 22:42:21 - mmengine - INFO - Epoch(train) [1137][50/63] lr: 4.9391e-04 eta: 1:14:13 time: 0.7955 data_time: 0.0236 memory: 16201 loss_prob: 0.3170 loss_thr: 0.2226 loss_db: 0.0577 loss: 0.5972 2022/08/30 22:42:25 - mmengine - INFO - Epoch(train) [1137][55/63] lr: 4.9391e-04 eta: 1:14:13 time: 0.8089 data_time: 0.0332 memory: 16201 loss_prob: 0.3013 loss_thr: 0.2166 loss_db: 0.0542 loss: 0.5721 2022/08/30 22:42:29 - mmengine - INFO - Epoch(train) [1137][60/63] lr: 4.9391e-04 eta: 1:14:01 time: 0.8017 data_time: 0.0296 memory: 16201 loss_prob: 0.3424 loss_thr: 0.2361 loss_db: 0.0608 loss: 0.6393 2022/08/30 22:42:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:42:37 - mmengine - INFO - Epoch(train) [1138][5/63] lr: 4.8685e-04 eta: 1:14:01 time: 0.9413 data_time: 0.1987 memory: 16201 loss_prob: 0.3391 loss_thr: 0.2307 loss_db: 0.0610 loss: 0.6308 2022/08/30 22:42:41 - mmengine - INFO - Epoch(train) [1138][10/63] lr: 4.8685e-04 eta: 1:13:47 time: 0.9842 data_time: 0.2115 memory: 16201 loss_prob: 0.3418 loss_thr: 0.2288 loss_db: 0.0619 loss: 0.6326 2022/08/30 22:42:45 - mmengine - INFO - Epoch(train) [1138][15/63] lr: 4.8685e-04 eta: 1:13:47 time: 0.7965 data_time: 0.0242 memory: 16201 loss_prob: 0.3535 loss_thr: 0.2350 loss_db: 0.0641 loss: 0.6526 2022/08/30 22:42:49 - mmengine - INFO - Epoch(train) [1138][20/63] lr: 4.8685e-04 eta: 1:13:35 time: 0.8060 data_time: 0.0212 memory: 16201 loss_prob: 0.3294 loss_thr: 0.2305 loss_db: 0.0586 loss: 0.6186 2022/08/30 22:42:53 - mmengine - INFO - Epoch(train) [1138][25/63] lr: 4.8685e-04 eta: 1:13:35 time: 0.8425 data_time: 0.0430 memory: 16201 loss_prob: 0.3242 loss_thr: 0.2296 loss_db: 0.0566 loss: 0.6104 2022/08/30 22:42:57 - mmengine - INFO - Epoch(train) [1138][30/63] lr: 4.8685e-04 eta: 1:13:24 time: 0.8252 data_time: 0.0319 memory: 16201 loss_prob: 0.3113 loss_thr: 0.2184 loss_db: 0.0545 loss: 0.5842 2022/08/30 22:43:01 - mmengine - INFO - Epoch(train) [1138][35/63] lr: 4.8685e-04 eta: 1:13:24 time: 0.7922 data_time: 0.0189 memory: 16201 loss_prob: 0.2647 loss_thr: 0.2018 loss_db: 0.0466 loss: 0.5130 2022/08/30 22:43:05 - mmengine - INFO - Epoch(train) [1138][40/63] lr: 4.8685e-04 eta: 1:13:13 time: 0.8254 data_time: 0.0264 memory: 16201 loss_prob: 0.3052 loss_thr: 0.2278 loss_db: 0.0546 loss: 0.5876 2022/08/30 22:43:09 - mmengine - INFO - Epoch(train) [1138][45/63] lr: 4.8685e-04 eta: 1:13:13 time: 0.8234 data_time: 0.0263 memory: 16201 loss_prob: 0.3445 loss_thr: 0.2419 loss_db: 0.0628 loss: 0.6492 2022/08/30 22:43:14 - mmengine - INFO - Epoch(train) [1138][50/63] lr: 4.8685e-04 eta: 1:13:01 time: 0.8107 data_time: 0.0276 memory: 16201 loss_prob: 0.3369 loss_thr: 0.2300 loss_db: 0.0593 loss: 0.6262 2022/08/30 22:43:17 - mmengine - INFO - Epoch(train) [1138][55/63] lr: 4.8685e-04 eta: 1:13:01 time: 0.8065 data_time: 0.0246 memory: 16201 loss_prob: 0.3462 loss_thr: 0.2323 loss_db: 0.0604 loss: 0.6388 2022/08/30 22:43:22 - mmengine - INFO - Epoch(train) [1138][60/63] lr: 4.8685e-04 eta: 1:12:50 time: 0.8029 data_time: 0.0262 memory: 16201 loss_prob: 0.3492 loss_thr: 0.2356 loss_db: 0.0630 loss: 0.6478 2022/08/30 22:43:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:43:29 - mmengine - INFO - Epoch(train) [1139][5/63] lr: 4.7978e-04 eta: 1:12:50 time: 0.9172 data_time: 0.1761 memory: 16201 loss_prob: 0.3707 loss_thr: 0.2595 loss_db: 0.0681 loss: 0.6983 2022/08/30 22:43:33 - mmengine - INFO - Epoch(train) [1139][10/63] lr: 4.7978e-04 eta: 1:12:35 time: 0.9737 data_time: 0.1956 memory: 16201 loss_prob: 0.3396 loss_thr: 0.2403 loss_db: 0.0609 loss: 0.6407 2022/08/30 22:43:37 - mmengine - INFO - Epoch(train) [1139][15/63] lr: 4.7978e-04 eta: 1:12:35 time: 0.8150 data_time: 0.0287 memory: 16201 loss_prob: 0.3410 loss_thr: 0.2389 loss_db: 0.0601 loss: 0.6399 2022/08/30 22:43:42 - mmengine - INFO - Epoch(train) [1139][20/63] lr: 4.7978e-04 eta: 1:12:24 time: 0.8408 data_time: 0.0184 memory: 16201 loss_prob: 0.3091 loss_thr: 0.2221 loss_db: 0.0553 loss: 0.5866 2022/08/30 22:43:46 - mmengine - INFO - Epoch(train) [1139][25/63] lr: 4.7978e-04 eta: 1:12:24 time: 0.8661 data_time: 0.0363 memory: 16201 loss_prob: 0.3074 loss_thr: 0.2107 loss_db: 0.0536 loss: 0.5718 2022/08/30 22:43:50 - mmengine - INFO - Epoch(train) [1139][30/63] lr: 4.7978e-04 eta: 1:12:12 time: 0.8163 data_time: 0.0308 memory: 16201 loss_prob: 0.3578 loss_thr: 0.2406 loss_db: 0.0625 loss: 0.6608 2022/08/30 22:43:54 - mmengine - INFO - Epoch(train) [1139][35/63] lr: 4.7978e-04 eta: 1:12:12 time: 0.7981 data_time: 0.0229 memory: 16201 loss_prob: 0.3368 loss_thr: 0.2447 loss_db: 0.0599 loss: 0.6414 2022/08/30 22:43:58 - mmengine - INFO - Epoch(train) [1139][40/63] lr: 4.7978e-04 eta: 1:12:01 time: 0.8128 data_time: 0.0316 memory: 16201 loss_prob: 0.3079 loss_thr: 0.2302 loss_db: 0.0564 loss: 0.5945 2022/08/30 22:44:02 - mmengine - INFO - Epoch(train) [1139][45/63] lr: 4.7978e-04 eta: 1:12:01 time: 0.8201 data_time: 0.0277 memory: 16201 loss_prob: 0.2914 loss_thr: 0.2091 loss_db: 0.0538 loss: 0.5543 2022/08/30 22:44:06 - mmengine - INFO - Epoch(train) [1139][50/63] lr: 4.7978e-04 eta: 1:11:50 time: 0.8200 data_time: 0.0264 memory: 16201 loss_prob: 0.3073 loss_thr: 0.2115 loss_db: 0.0547 loss: 0.5735 2022/08/30 22:44:10 - mmengine - INFO - Epoch(train) [1139][55/63] lr: 4.7978e-04 eta: 1:11:50 time: 0.8147 data_time: 0.0308 memory: 16201 loss_prob: 0.3130 loss_thr: 0.2158 loss_db: 0.0551 loss: 0.5839 2022/08/30 22:44:14 - mmengine - INFO - Epoch(train) [1139][60/63] lr: 4.7978e-04 eta: 1:11:38 time: 0.8116 data_time: 0.0287 memory: 16201 loss_prob: 0.2885 loss_thr: 0.2120 loss_db: 0.0519 loss: 0.5523 2022/08/30 22:44:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:44:23 - mmengine - INFO - Epoch(train) [1140][5/63] lr: 4.7270e-04 eta: 1:11:38 time: 0.9843 data_time: 0.1915 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2411 loss_db: 0.0612 loss: 0.6553 2022/08/30 22:44:27 - mmengine - INFO - Epoch(train) [1140][10/63] lr: 4.7270e-04 eta: 1:11:24 time: 0.9792 data_time: 0.1971 memory: 16201 loss_prob: 0.3666 loss_thr: 0.2429 loss_db: 0.0642 loss: 0.6737 2022/08/30 22:44:31 - mmengine - INFO - Epoch(train) [1140][15/63] lr: 4.7270e-04 eta: 1:11:24 time: 0.7876 data_time: 0.0240 memory: 16201 loss_prob: 0.3320 loss_thr: 0.2384 loss_db: 0.0588 loss: 0.6292 2022/08/30 22:44:35 - mmengine - INFO - Epoch(train) [1140][20/63] lr: 4.7270e-04 eta: 1:11:12 time: 0.8104 data_time: 0.0270 memory: 16201 loss_prob: 0.3422 loss_thr: 0.2395 loss_db: 0.0606 loss: 0.6423 2022/08/30 22:44:39 - mmengine - INFO - Epoch(train) [1140][25/63] lr: 4.7270e-04 eta: 1:11:12 time: 0.8177 data_time: 0.0285 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2185 loss_db: 0.0578 loss: 0.6008 2022/08/30 22:44:43 - mmengine - INFO - Epoch(train) [1140][30/63] lr: 4.7270e-04 eta: 1:11:01 time: 0.7974 data_time: 0.0306 memory: 16201 loss_prob: 0.3110 loss_thr: 0.2188 loss_db: 0.0552 loss: 0.5850 2022/08/30 22:44:47 - mmengine - INFO - Epoch(train) [1140][35/63] lr: 4.7270e-04 eta: 1:11:01 time: 0.8104 data_time: 0.0394 memory: 16201 loss_prob: 0.3217 loss_thr: 0.2278 loss_db: 0.0571 loss: 0.6066 2022/08/30 22:44:51 - mmengine - INFO - Epoch(train) [1140][40/63] lr: 4.7270e-04 eta: 1:10:50 time: 0.8078 data_time: 0.0286 memory: 16201 loss_prob: 0.2938 loss_thr: 0.2101 loss_db: 0.0532 loss: 0.5571 2022/08/30 22:44:55 - mmengine - INFO - Epoch(train) [1140][45/63] lr: 4.7270e-04 eta: 1:10:50 time: 0.8331 data_time: 0.0283 memory: 16201 loss_prob: 0.2854 loss_thr: 0.2117 loss_db: 0.0517 loss: 0.5488 2022/08/30 22:44:59 - mmengine - INFO - Epoch(train) [1140][50/63] lr: 4.7270e-04 eta: 1:10:38 time: 0.8285 data_time: 0.0314 memory: 16201 loss_prob: 0.2923 loss_thr: 0.2117 loss_db: 0.0523 loss: 0.5563 2022/08/30 22:45:03 - mmengine - INFO - Epoch(train) [1140][55/63] lr: 4.7270e-04 eta: 1:10:38 time: 0.8006 data_time: 0.0261 memory: 16201 loss_prob: 0.2839 loss_thr: 0.2010 loss_db: 0.0505 loss: 0.5354 2022/08/30 22:45:07 - mmengine - INFO - Epoch(train) [1140][60/63] lr: 4.7270e-04 eta: 1:10:27 time: 0.8032 data_time: 0.0269 memory: 16201 loss_prob: 0.3027 loss_thr: 0.2101 loss_db: 0.0552 loss: 0.5680 2022/08/30 22:45:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:45:09 - mmengine - INFO - Saving checkpoint at 1140 epochs 2022/08/30 22:45:17 - mmengine - INFO - Epoch(val) [1140][5/32] eta: 1:10:27 time: 0.6229 data_time: 0.0960 memory: 16201 2022/08/30 22:45:21 - mmengine - INFO - Epoch(val) [1140][10/32] eta: 0:00:15 time: 0.7195 data_time: 0.1465 memory: 15734 2022/08/30 22:45:23 - mmengine - INFO - Epoch(val) [1140][15/32] eta: 0:00:15 time: 0.6274 data_time: 0.0666 memory: 15734 2022/08/30 22:45:27 - mmengine - INFO - Epoch(val) [1140][20/32] eta: 0:00:07 time: 0.6260 data_time: 0.0564 memory: 15734 2022/08/30 22:45:30 - mmengine - INFO - Epoch(val) [1140][25/32] eta: 0:00:07 time: 0.6490 data_time: 0.0597 memory: 15734 2022/08/30 22:45:33 - mmengine - INFO - Epoch(val) [1140][30/32] eta: 0:00:01 time: 0.6380 data_time: 0.0297 memory: 15734 2022/08/30 22:45:34 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 22:45:34 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8469, precision: 0.8084, hmean: 0.8272 2022/08/30 22:45:34 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8469, precision: 0.8445, hmean: 0.8457 2022/08/30 22:45:34 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8464, precision: 0.8635, hmean: 0.8549 2022/08/30 22:45:34 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8450, precision: 0.8775, hmean: 0.8609 2022/08/30 22:45:34 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8402, precision: 0.8930, hmean: 0.8658 2022/08/30 22:45:34 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8214, precision: 0.9182, hmean: 0.8671 2022/08/30 22:45:34 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.5171, precision: 0.9538, hmean: 0.6706 2022/08/30 22:45:34 - mmengine - INFO - Epoch(val) [1140][32/32] icdar/precision: 0.9182 icdar/recall: 0.8214 icdar/hmean: 0.8671 2022/08/30 22:45:40 - mmengine - INFO - Epoch(train) [1141][5/63] lr: 4.6560e-04 eta: 0:00:01 time: 0.9879 data_time: 0.2297 memory: 16201 loss_prob: 0.3470 loss_thr: 0.2436 loss_db: 0.0611 loss: 0.6517 2022/08/30 22:45:44 - mmengine - INFO - Epoch(train) [1141][10/63] lr: 4.6560e-04 eta: 1:10:12 time: 1.0359 data_time: 0.2398 memory: 16201 loss_prob: 0.3461 loss_thr: 0.2518 loss_db: 0.0619 loss: 0.6598 2022/08/30 22:45:49 - mmengine - INFO - Epoch(train) [1141][15/63] lr: 4.6560e-04 eta: 1:10:12 time: 0.8113 data_time: 0.0347 memory: 16201 loss_prob: 0.3286 loss_thr: 0.2376 loss_db: 0.0594 loss: 0.6256 2022/08/30 22:45:53 - mmengine - INFO - Epoch(train) [1141][20/63] lr: 4.6560e-04 eta: 1:10:01 time: 0.8440 data_time: 0.0338 memory: 16201 loss_prob: 0.3036 loss_thr: 0.2259 loss_db: 0.0544 loss: 0.5840 2022/08/30 22:45:57 - mmengine - INFO - Epoch(train) [1141][25/63] lr: 4.6560e-04 eta: 1:10:01 time: 0.8230 data_time: 0.0284 memory: 16201 loss_prob: 0.3180 loss_thr: 0.2324 loss_db: 0.0567 loss: 0.6071 2022/08/30 22:46:01 - mmengine - INFO - Epoch(train) [1141][30/63] lr: 4.6560e-04 eta: 1:09:49 time: 0.7952 data_time: 0.0280 memory: 16201 loss_prob: 0.3339 loss_thr: 0.2424 loss_db: 0.0594 loss: 0.6357 2022/08/30 22:46:05 - mmengine - INFO - Epoch(train) [1141][35/63] lr: 4.6560e-04 eta: 1:09:49 time: 0.8479 data_time: 0.0304 memory: 16201 loss_prob: 0.3208 loss_thr: 0.2354 loss_db: 0.0585 loss: 0.6147 2022/08/30 22:46:09 - mmengine - INFO - Epoch(train) [1141][40/63] lr: 4.6560e-04 eta: 1:09:38 time: 0.8432 data_time: 0.0222 memory: 16201 loss_prob: 0.3168 loss_thr: 0.2254 loss_db: 0.0585 loss: 0.6007 2022/08/30 22:46:13 - mmengine - INFO - Epoch(train) [1141][45/63] lr: 4.6560e-04 eta: 1:09:38 time: 0.8120 data_time: 0.0287 memory: 16201 loss_prob: 0.3304 loss_thr: 0.2301 loss_db: 0.0598 loss: 0.6202 2022/08/30 22:46:17 - mmengine - INFO - Epoch(train) [1141][50/63] lr: 4.6560e-04 eta: 1:09:27 time: 0.8194 data_time: 0.0310 memory: 16201 loss_prob: 0.3244 loss_thr: 0.2286 loss_db: 0.0570 loss: 0.6100 2022/08/30 22:46:22 - mmengine - INFO - Epoch(train) [1141][55/63] lr: 4.6560e-04 eta: 1:09:27 time: 0.8154 data_time: 0.0237 memory: 16201 loss_prob: 0.3046 loss_thr: 0.2166 loss_db: 0.0521 loss: 0.5733 2022/08/30 22:46:26 - mmengine - INFO - Epoch(train) [1141][60/63] lr: 4.6560e-04 eta: 1:09:15 time: 0.8267 data_time: 0.0287 memory: 16201 loss_prob: 0.2974 loss_thr: 0.2211 loss_db: 0.0511 loss: 0.5696 2022/08/30 22:46:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:46:33 - mmengine - INFO - Epoch(train) [1142][5/63] lr: 4.5849e-04 eta: 1:09:15 time: 0.9287 data_time: 0.1832 memory: 16201 loss_prob: 0.3098 loss_thr: 0.2365 loss_db: 0.0567 loss: 0.6030 2022/08/30 22:46:37 - mmengine - INFO - Epoch(train) [1142][10/63] lr: 4.5849e-04 eta: 1:09:01 time: 0.9705 data_time: 0.1989 memory: 16201 loss_prob: 0.3128 loss_thr: 0.2269 loss_db: 0.0569 loss: 0.5966 2022/08/30 22:46:41 - mmengine - INFO - Epoch(train) [1142][15/63] lr: 4.5849e-04 eta: 1:09:01 time: 0.8095 data_time: 0.0296 memory: 16201 loss_prob: 0.2958 loss_thr: 0.2130 loss_db: 0.0527 loss: 0.5615 2022/08/30 22:46:46 - mmengine - INFO - Epoch(train) [1142][20/63] lr: 4.5849e-04 eta: 1:08:49 time: 0.8626 data_time: 0.0656 memory: 16201 loss_prob: 0.3211 loss_thr: 0.2271 loss_db: 0.0566 loss: 0.6048 2022/08/30 22:46:50 - mmengine - INFO - Epoch(train) [1142][25/63] lr: 4.5849e-04 eta: 1:08:49 time: 0.8509 data_time: 0.0760 memory: 16201 loss_prob: 0.3638 loss_thr: 0.2628 loss_db: 0.0650 loss: 0.6916 2022/08/30 22:46:54 - mmengine - INFO - Epoch(train) [1142][30/63] lr: 4.5849e-04 eta: 1:08:38 time: 0.7979 data_time: 0.0241 memory: 16201 loss_prob: 0.3405 loss_thr: 0.2472 loss_db: 0.0612 loss: 0.6489 2022/08/30 22:46:58 - mmengine - INFO - Epoch(train) [1142][35/63] lr: 4.5849e-04 eta: 1:08:38 time: 0.8156 data_time: 0.0295 memory: 16201 loss_prob: 0.2964 loss_thr: 0.2137 loss_db: 0.0539 loss: 0.5639 2022/08/30 22:47:02 - mmengine - INFO - Epoch(train) [1142][40/63] lr: 4.5849e-04 eta: 1:08:27 time: 0.8257 data_time: 0.0306 memory: 16201 loss_prob: 0.2896 loss_thr: 0.2096 loss_db: 0.0538 loss: 0.5530 2022/08/30 22:47:06 - mmengine - INFO - Epoch(train) [1142][45/63] lr: 4.5849e-04 eta: 1:08:27 time: 0.8364 data_time: 0.0339 memory: 16201 loss_prob: 0.3213 loss_thr: 0.2151 loss_db: 0.0590 loss: 0.5953 2022/08/30 22:47:10 - mmengine - INFO - Epoch(train) [1142][50/63] lr: 4.5849e-04 eta: 1:08:15 time: 0.8229 data_time: 0.0381 memory: 16201 loss_prob: 0.3334 loss_thr: 0.2232 loss_db: 0.0593 loss: 0.6158 2022/08/30 22:47:15 - mmengine - INFO - Epoch(train) [1142][55/63] lr: 4.5849e-04 eta: 1:08:15 time: 0.8075 data_time: 0.0266 memory: 16201 loss_prob: 0.3355 loss_thr: 0.2339 loss_db: 0.0586 loss: 0.6279 2022/08/30 22:47:19 - mmengine - INFO - Epoch(train) [1142][60/63] lr: 4.5849e-04 eta: 1:08:04 time: 0.8095 data_time: 0.0302 memory: 16201 loss_prob: 0.3431 loss_thr: 0.2410 loss_db: 0.0595 loss: 0.6437 2022/08/30 22:47:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:47:27 - mmengine - INFO - Epoch(train) [1143][5/63] lr: 4.5138e-04 eta: 1:08:04 time: 0.9803 data_time: 0.2292 memory: 16201 loss_prob: 0.3292 loss_thr: 0.2305 loss_db: 0.0599 loss: 0.6196 2022/08/30 22:47:31 - mmengine - INFO - Epoch(train) [1143][10/63] lr: 4.5138e-04 eta: 1:07:49 time: 1.0364 data_time: 0.2408 memory: 16201 loss_prob: 0.3608 loss_thr: 0.2448 loss_db: 0.0653 loss: 0.6709 2022/08/30 22:47:35 - mmengine - INFO - Epoch(train) [1143][15/63] lr: 4.5138e-04 eta: 1:07:49 time: 0.8486 data_time: 0.0272 memory: 16201 loss_prob: 0.3232 loss_thr: 0.2245 loss_db: 0.0580 loss: 0.6056 2022/08/30 22:47:39 - mmengine - INFO - Epoch(train) [1143][20/63] lr: 4.5138e-04 eta: 1:07:38 time: 0.8362 data_time: 0.0299 memory: 16201 loss_prob: 0.3180 loss_thr: 0.2271 loss_db: 0.0574 loss: 0.6025 2022/08/30 22:47:43 - mmengine - INFO - Epoch(train) [1143][25/63] lr: 4.5138e-04 eta: 1:07:38 time: 0.8041 data_time: 0.0310 memory: 16201 loss_prob: 0.3237 loss_thr: 0.2280 loss_db: 0.0581 loss: 0.6098 2022/08/30 22:47:47 - mmengine - INFO - Epoch(train) [1143][30/63] lr: 4.5138e-04 eta: 1:07:27 time: 0.8081 data_time: 0.0262 memory: 16201 loss_prob: 0.2952 loss_thr: 0.2107 loss_db: 0.0532 loss: 0.5591 2022/08/30 22:47:52 - mmengine - INFO - Epoch(train) [1143][35/63] lr: 4.5138e-04 eta: 1:07:27 time: 0.8201 data_time: 0.0308 memory: 16201 loss_prob: 0.3070 loss_thr: 0.2144 loss_db: 0.0546 loss: 0.5760 2022/08/30 22:47:56 - mmengine - INFO - Epoch(train) [1143][40/63] lr: 4.5138e-04 eta: 1:07:15 time: 0.8358 data_time: 0.0296 memory: 16201 loss_prob: 0.3137 loss_thr: 0.2168 loss_db: 0.0562 loss: 0.5866 2022/08/30 22:48:00 - mmengine - INFO - Epoch(train) [1143][45/63] lr: 4.5138e-04 eta: 1:07:15 time: 0.8400 data_time: 0.0285 memory: 16201 loss_prob: 0.3130 loss_thr: 0.2224 loss_db: 0.0562 loss: 0.5916 2022/08/30 22:48:04 - mmengine - INFO - Epoch(train) [1143][50/63] lr: 4.5138e-04 eta: 1:07:04 time: 0.8227 data_time: 0.0275 memory: 16201 loss_prob: 0.3232 loss_thr: 0.2329 loss_db: 0.0563 loss: 0.6123 2022/08/30 22:48:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:48:08 - mmengine - INFO - Epoch(train) [1143][55/63] lr: 4.5138e-04 eta: 1:07:04 time: 0.8224 data_time: 0.0249 memory: 16201 loss_prob: 0.3018 loss_thr: 0.2235 loss_db: 0.0528 loss: 0.5782 2022/08/30 22:48:12 - mmengine - INFO - Epoch(train) [1143][60/63] lr: 4.5138e-04 eta: 1:06:53 time: 0.8193 data_time: 0.0281 memory: 16201 loss_prob: 0.2979 loss_thr: 0.2162 loss_db: 0.0531 loss: 0.5671 2022/08/30 22:48:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:48:20 - mmengine - INFO - Epoch(train) [1144][5/63] lr: 4.4424e-04 eta: 1:06:53 time: 0.9450 data_time: 0.1938 memory: 16201 loss_prob: 0.3096 loss_thr: 0.2239 loss_db: 0.0564 loss: 0.5900 2022/08/30 22:48:24 - mmengine - INFO - Epoch(train) [1144][10/63] lr: 4.4424e-04 eta: 1:06:38 time: 1.0180 data_time: 0.2068 memory: 16201 loss_prob: 0.3038 loss_thr: 0.2205 loss_db: 0.0552 loss: 0.5795 2022/08/30 22:48:28 - mmengine - INFO - Epoch(train) [1144][15/63] lr: 4.4424e-04 eta: 1:06:38 time: 0.8373 data_time: 0.0332 memory: 16201 loss_prob: 0.3445 loss_thr: 0.2342 loss_db: 0.0630 loss: 0.6417 2022/08/30 22:48:33 - mmengine - INFO - Epoch(train) [1144][20/63] lr: 4.4424e-04 eta: 1:06:27 time: 0.8083 data_time: 0.0251 memory: 16201 loss_prob: 0.3368 loss_thr: 0.2350 loss_db: 0.0610 loss: 0.6328 2022/08/30 22:48:37 - mmengine - INFO - Epoch(train) [1144][25/63] lr: 4.4424e-04 eta: 1:06:27 time: 0.8170 data_time: 0.0298 memory: 16201 loss_prob: 0.3111 loss_thr: 0.2280 loss_db: 0.0545 loss: 0.5935 2022/08/30 22:48:41 - mmengine - INFO - Epoch(train) [1144][30/63] lr: 4.4424e-04 eta: 1:06:15 time: 0.8308 data_time: 0.0266 memory: 16201 loss_prob: 0.3183 loss_thr: 0.2388 loss_db: 0.0556 loss: 0.6127 2022/08/30 22:48:45 - mmengine - INFO - Epoch(train) [1144][35/63] lr: 4.4424e-04 eta: 1:06:15 time: 0.8262 data_time: 0.0309 memory: 16201 loss_prob: 0.3164 loss_thr: 0.2295 loss_db: 0.0565 loss: 0.6024 2022/08/30 22:48:49 - mmengine - INFO - Epoch(train) [1144][40/63] lr: 4.4424e-04 eta: 1:06:04 time: 0.8162 data_time: 0.0326 memory: 16201 loss_prob: 0.2940 loss_thr: 0.2156 loss_db: 0.0532 loss: 0.5628 2022/08/30 22:48:54 - mmengine - INFO - Epoch(train) [1144][45/63] lr: 4.4424e-04 eta: 1:06:04 time: 0.8678 data_time: 0.0344 memory: 16201 loss_prob: 0.2993 loss_thr: 0.2187 loss_db: 0.0545 loss: 0.5725 2022/08/30 22:48:58 - mmengine - INFO - Epoch(train) [1144][50/63] lr: 4.4424e-04 eta: 1:05:53 time: 0.8682 data_time: 0.0320 memory: 16201 loss_prob: 0.3095 loss_thr: 0.2162 loss_db: 0.0565 loss: 0.5823 2022/08/30 22:49:02 - mmengine - INFO - Epoch(train) [1144][55/63] lr: 4.4424e-04 eta: 1:05:53 time: 0.8077 data_time: 0.0267 memory: 16201 loss_prob: 0.3240 loss_thr: 0.2205 loss_db: 0.0579 loss: 0.6024 2022/08/30 22:49:06 - mmengine - INFO - Epoch(train) [1144][60/63] lr: 4.4424e-04 eta: 1:05:42 time: 0.8227 data_time: 0.0334 memory: 16201 loss_prob: 0.3235 loss_thr: 0.2258 loss_db: 0.0574 loss: 0.6066 2022/08/30 22:49:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:49:14 - mmengine - INFO - Epoch(train) [1145][5/63] lr: 4.3710e-04 eta: 1:05:42 time: 0.9794 data_time: 0.2150 memory: 16201 loss_prob: 0.2669 loss_thr: 0.1986 loss_db: 0.0486 loss: 0.5141 2022/08/30 22:49:18 - mmengine - INFO - Epoch(train) [1145][10/63] lr: 4.3710e-04 eta: 1:05:27 time: 1.0360 data_time: 0.2161 memory: 16201 loss_prob: 0.2985 loss_thr: 0.2125 loss_db: 0.0539 loss: 0.5648 2022/08/30 22:49:22 - mmengine - INFO - Epoch(train) [1145][15/63] lr: 4.3710e-04 eta: 1:05:27 time: 0.8410 data_time: 0.0248 memory: 16201 loss_prob: 0.3402 loss_thr: 0.2326 loss_db: 0.0595 loss: 0.6324 2022/08/30 22:49:27 - mmengine - INFO - Epoch(train) [1145][20/63] lr: 4.3710e-04 eta: 1:05:16 time: 0.8268 data_time: 0.0239 memory: 16201 loss_prob: 0.3349 loss_thr: 0.2237 loss_db: 0.0587 loss: 0.6173 2022/08/30 22:49:31 - mmengine - INFO - Epoch(train) [1145][25/63] lr: 4.3710e-04 eta: 1:05:16 time: 0.8117 data_time: 0.0293 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2346 loss_db: 0.0618 loss: 0.6397 2022/08/30 22:49:35 - mmengine - INFO - Epoch(train) [1145][30/63] lr: 4.3710e-04 eta: 1:05:04 time: 0.8675 data_time: 0.0322 memory: 16201 loss_prob: 0.3465 loss_thr: 0.2422 loss_db: 0.0621 loss: 0.6508 2022/08/30 22:49:39 - mmengine - INFO - Epoch(train) [1145][35/63] lr: 4.3710e-04 eta: 1:05:04 time: 0.8767 data_time: 0.0273 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2221 loss_db: 0.0555 loss: 0.5908 2022/08/30 22:49:43 - mmengine - INFO - Epoch(train) [1145][40/63] lr: 4.3710e-04 eta: 1:04:53 time: 0.8200 data_time: 0.0319 memory: 16201 loss_prob: 0.2952 loss_thr: 0.2072 loss_db: 0.0534 loss: 0.5559 2022/08/30 22:49:48 - mmengine - INFO - Epoch(train) [1145][45/63] lr: 4.3710e-04 eta: 1:04:53 time: 0.8203 data_time: 0.0336 memory: 16201 loss_prob: 0.2893 loss_thr: 0.2019 loss_db: 0.0539 loss: 0.5451 2022/08/30 22:49:52 - mmengine - INFO - Epoch(train) [1145][50/63] lr: 4.3710e-04 eta: 1:04:42 time: 0.8379 data_time: 0.0282 memory: 16201 loss_prob: 0.3110 loss_thr: 0.2148 loss_db: 0.0566 loss: 0.5823 2022/08/30 22:49:56 - mmengine - INFO - Epoch(train) [1145][55/63] lr: 4.3710e-04 eta: 1:04:42 time: 0.8647 data_time: 0.0326 memory: 16201 loss_prob: 0.3308 loss_thr: 0.2318 loss_db: 0.0588 loss: 0.6214 2022/08/30 22:50:00 - mmengine - INFO - Epoch(train) [1145][60/63] lr: 4.3710e-04 eta: 1:04:30 time: 0.8614 data_time: 0.0325 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2174 loss_db: 0.0550 loss: 0.5811 2022/08/30 22:50:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:50:08 - mmengine - INFO - Epoch(train) [1146][5/63] lr: 4.2994e-04 eta: 1:04:30 time: 0.9588 data_time: 0.2069 memory: 16201 loss_prob: 0.3132 loss_thr: 0.2237 loss_db: 0.0553 loss: 0.5922 2022/08/30 22:50:12 - mmengine - INFO - Epoch(train) [1146][10/63] lr: 4.2994e-04 eta: 1:04:16 time: 0.9918 data_time: 0.2187 memory: 16201 loss_prob: 0.3587 loss_thr: 0.2478 loss_db: 0.0625 loss: 0.6691 2022/08/30 22:50:17 - mmengine - INFO - Epoch(train) [1146][15/63] lr: 4.2994e-04 eta: 1:04:16 time: 0.8344 data_time: 0.0336 memory: 16201 loss_prob: 0.3362 loss_thr: 0.2367 loss_db: 0.0600 loss: 0.6328 2022/08/30 22:50:21 - mmengine - INFO - Epoch(train) [1146][20/63] lr: 4.2994e-04 eta: 1:04:04 time: 0.8341 data_time: 0.0242 memory: 16201 loss_prob: 0.2898 loss_thr: 0.2137 loss_db: 0.0522 loss: 0.5557 2022/08/30 22:50:25 - mmengine - INFO - Epoch(train) [1146][25/63] lr: 4.2994e-04 eta: 1:04:04 time: 0.8019 data_time: 0.0322 memory: 16201 loss_prob: 0.3015 loss_thr: 0.2140 loss_db: 0.0539 loss: 0.5694 2022/08/30 22:50:29 - mmengine - INFO - Epoch(train) [1146][30/63] lr: 4.2994e-04 eta: 1:03:53 time: 0.8357 data_time: 0.0280 memory: 16201 loss_prob: 0.2931 loss_thr: 0.2091 loss_db: 0.0529 loss: 0.5552 2022/08/30 22:50:33 - mmengine - INFO - Epoch(train) [1146][35/63] lr: 4.2994e-04 eta: 1:03:53 time: 0.8462 data_time: 0.0298 memory: 16201 loss_prob: 0.3107 loss_thr: 0.2281 loss_db: 0.0555 loss: 0.5943 2022/08/30 22:50:37 - mmengine - INFO - Epoch(train) [1146][40/63] lr: 4.2994e-04 eta: 1:03:42 time: 0.8096 data_time: 0.0395 memory: 16201 loss_prob: 0.3281 loss_thr: 0.2340 loss_db: 0.0599 loss: 0.6221 2022/08/30 22:50:41 - mmengine - INFO - Epoch(train) [1146][45/63] lr: 4.2994e-04 eta: 1:03:42 time: 0.8039 data_time: 0.0346 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2177 loss_db: 0.0572 loss: 0.5873 2022/08/30 22:50:46 - mmengine - INFO - Epoch(train) [1146][50/63] lr: 4.2994e-04 eta: 1:03:30 time: 0.8337 data_time: 0.0291 memory: 16201 loss_prob: 0.3204 loss_thr: 0.2175 loss_db: 0.0567 loss: 0.5946 2022/08/30 22:50:50 - mmengine - INFO - Epoch(train) [1146][55/63] lr: 4.2994e-04 eta: 1:03:30 time: 0.8294 data_time: 0.0270 memory: 16201 loss_prob: 0.2977 loss_thr: 0.2085 loss_db: 0.0530 loss: 0.5592 2022/08/30 22:50:54 - mmengine - INFO - Epoch(train) [1146][60/63] lr: 4.2994e-04 eta: 1:03:19 time: 0.8020 data_time: 0.0272 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2166 loss_db: 0.0557 loss: 0.5771 2022/08/30 22:50:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:51:01 - mmengine - INFO - Epoch(train) [1147][5/63] lr: 4.2277e-04 eta: 1:03:19 time: 0.9381 data_time: 0.1902 memory: 16201 loss_prob: 0.2791 loss_thr: 0.2009 loss_db: 0.0486 loss: 0.5286 2022/08/30 22:51:05 - mmengine - INFO - Epoch(train) [1147][10/63] lr: 4.2277e-04 eta: 1:03:04 time: 0.9872 data_time: 0.2066 memory: 16201 loss_prob: 0.2774 loss_thr: 0.2025 loss_db: 0.0486 loss: 0.5286 2022/08/30 22:51:10 - mmengine - INFO - Epoch(train) [1147][15/63] lr: 4.2277e-04 eta: 1:03:04 time: 0.8566 data_time: 0.0309 memory: 16201 loss_prob: 0.2619 loss_thr: 0.1979 loss_db: 0.0477 loss: 0.5075 2022/08/30 22:51:14 - mmengine - INFO - Epoch(train) [1147][20/63] lr: 4.2277e-04 eta: 1:02:53 time: 0.8731 data_time: 0.0254 memory: 16201 loss_prob: 0.3061 loss_thr: 0.2221 loss_db: 0.0562 loss: 0.5845 2022/08/30 22:51:18 - mmengine - INFO - Epoch(train) [1147][25/63] lr: 4.2277e-04 eta: 1:02:53 time: 0.8348 data_time: 0.0345 memory: 16201 loss_prob: 0.3541 loss_thr: 0.2501 loss_db: 0.0634 loss: 0.6675 2022/08/30 22:51:23 - mmengine - INFO - Epoch(train) [1147][30/63] lr: 4.2277e-04 eta: 1:02:42 time: 0.8484 data_time: 0.0250 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2296 loss_db: 0.0569 loss: 0.6103 2022/08/30 22:51:27 - mmengine - INFO - Epoch(train) [1147][35/63] lr: 4.2277e-04 eta: 1:02:42 time: 0.8527 data_time: 0.0279 memory: 16201 loss_prob: 0.2872 loss_thr: 0.2077 loss_db: 0.0505 loss: 0.5453 2022/08/30 22:51:31 - mmengine - INFO - Epoch(train) [1147][40/63] lr: 4.2277e-04 eta: 1:02:31 time: 0.8058 data_time: 0.0277 memory: 16201 loss_prob: 0.2999 loss_thr: 0.2169 loss_db: 0.0540 loss: 0.5708 2022/08/30 22:51:35 - mmengine - INFO - Epoch(train) [1147][45/63] lr: 4.2277e-04 eta: 1:02:31 time: 0.8043 data_time: 0.0249 memory: 16201 loss_prob: 0.2945 loss_thr: 0.2163 loss_db: 0.0529 loss: 0.5637 2022/08/30 22:51:39 - mmengine - INFO - Epoch(train) [1147][50/63] lr: 4.2277e-04 eta: 1:02:19 time: 0.8121 data_time: 0.0326 memory: 16201 loss_prob: 0.2959 loss_thr: 0.2177 loss_db: 0.0530 loss: 0.5666 2022/08/30 22:51:43 - mmengine - INFO - Epoch(train) [1147][55/63] lr: 4.2277e-04 eta: 1:02:19 time: 0.8269 data_time: 0.0306 memory: 16201 loss_prob: 0.3281 loss_thr: 0.2332 loss_db: 0.0590 loss: 0.6203 2022/08/30 22:51:47 - mmengine - INFO - Epoch(train) [1147][60/63] lr: 4.2277e-04 eta: 1:02:08 time: 0.8335 data_time: 0.0281 memory: 16201 loss_prob: 0.3230 loss_thr: 0.2346 loss_db: 0.0578 loss: 0.6155 2022/08/30 22:51:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:51:55 - mmengine - INFO - Epoch(train) [1148][5/63] lr: 4.1559e-04 eta: 1:02:08 time: 0.9060 data_time: 0.1590 memory: 16201 loss_prob: 0.3125 loss_thr: 0.2231 loss_db: 0.0568 loss: 0.5924 2022/08/30 22:51:59 - mmengine - INFO - Epoch(train) [1148][10/63] lr: 4.1559e-04 eta: 1:01:53 time: 0.9522 data_time: 0.1716 memory: 16201 loss_prob: 0.2999 loss_thr: 0.2144 loss_db: 0.0526 loss: 0.5668 2022/08/30 22:52:03 - mmengine - INFO - Epoch(train) [1148][15/63] lr: 4.1559e-04 eta: 1:01:53 time: 0.8207 data_time: 0.0268 memory: 16201 loss_prob: 0.3227 loss_thr: 0.2388 loss_db: 0.0572 loss: 0.6188 2022/08/30 22:52:07 - mmengine - INFO - Epoch(train) [1148][20/63] lr: 4.1559e-04 eta: 1:01:42 time: 0.8430 data_time: 0.0261 memory: 16201 loss_prob: 0.3043 loss_thr: 0.2231 loss_db: 0.0544 loss: 0.5818 2022/08/30 22:52:11 - mmengine - INFO - Epoch(train) [1148][25/63] lr: 4.1559e-04 eta: 1:01:42 time: 0.8311 data_time: 0.0328 memory: 16201 loss_prob: 0.3180 loss_thr: 0.2225 loss_db: 0.0561 loss: 0.5966 2022/08/30 22:52:15 - mmengine - INFO - Epoch(train) [1148][30/63] lr: 4.1559e-04 eta: 1:01:31 time: 0.7959 data_time: 0.0267 memory: 16201 loss_prob: 0.3332 loss_thr: 0.2270 loss_db: 0.0596 loss: 0.6199 2022/08/30 22:52:19 - mmengine - INFO - Epoch(train) [1148][35/63] lr: 4.1559e-04 eta: 1:01:31 time: 0.7951 data_time: 0.0240 memory: 16201 loss_prob: 0.3251 loss_thr: 0.2210 loss_db: 0.0582 loss: 0.6043 2022/08/30 22:52:24 - mmengine - INFO - Epoch(train) [1148][40/63] lr: 4.1559e-04 eta: 1:01:19 time: 0.8630 data_time: 0.0262 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2255 loss_db: 0.0576 loss: 0.6056 2022/08/30 22:52:28 - mmengine - INFO - Epoch(train) [1148][45/63] lr: 4.1559e-04 eta: 1:01:19 time: 0.8700 data_time: 0.0303 memory: 16201 loss_prob: 0.3003 loss_thr: 0.2137 loss_db: 0.0550 loss: 0.5691 2022/08/30 22:52:32 - mmengine - INFO - Epoch(train) [1148][50/63] lr: 4.1559e-04 eta: 1:01:08 time: 0.8090 data_time: 0.0255 memory: 16201 loss_prob: 0.3142 loss_thr: 0.2212 loss_db: 0.0567 loss: 0.5921 2022/08/30 22:52:36 - mmengine - INFO - Epoch(train) [1148][55/63] lr: 4.1559e-04 eta: 1:01:08 time: 0.8115 data_time: 0.0278 memory: 16201 loss_prob: 0.3394 loss_thr: 0.2392 loss_db: 0.0593 loss: 0.6378 2022/08/30 22:52:40 - mmengine - INFO - Epoch(train) [1148][60/63] lr: 4.1559e-04 eta: 1:00:57 time: 0.8083 data_time: 0.0340 memory: 16201 loss_prob: 0.3361 loss_thr: 0.2362 loss_db: 0.0584 loss: 0.6307 2022/08/30 22:52:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:52:48 - mmengine - INFO - Epoch(train) [1149][5/63] lr: 4.0839e-04 eta: 1:00:57 time: 0.9913 data_time: 0.1975 memory: 16201 loss_prob: 0.3356 loss_thr: 0.2371 loss_db: 0.0596 loss: 0.6323 2022/08/30 22:52:52 - mmengine - INFO - Epoch(train) [1149][10/63] lr: 4.0839e-04 eta: 1:00:42 time: 0.9952 data_time: 0.2022 memory: 16201 loss_prob: 0.3398 loss_thr: 0.2310 loss_db: 0.0603 loss: 0.6311 2022/08/30 22:52:56 - mmengine - INFO - Epoch(train) [1149][15/63] lr: 4.0839e-04 eta: 1:00:42 time: 0.8033 data_time: 0.0296 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2171 loss_db: 0.0560 loss: 0.5851 2022/08/30 22:53:00 - mmengine - INFO - Epoch(train) [1149][20/63] lr: 4.0839e-04 eta: 1:00:31 time: 0.8152 data_time: 0.0248 memory: 16201 loss_prob: 0.2965 loss_thr: 0.2109 loss_db: 0.0542 loss: 0.5615 2022/08/30 22:53:05 - mmengine - INFO - Epoch(train) [1149][25/63] lr: 4.0839e-04 eta: 1:00:31 time: 0.8442 data_time: 0.0313 memory: 16201 loss_prob: 0.3119 loss_thr: 0.2230 loss_db: 0.0559 loss: 0.5908 2022/08/30 22:53:09 - mmengine - INFO - Epoch(train) [1149][30/63] lr: 4.0839e-04 eta: 1:00:20 time: 0.8319 data_time: 0.0489 memory: 16201 loss_prob: 0.3135 loss_thr: 0.2240 loss_db: 0.0555 loss: 0.5931 2022/08/30 22:53:13 - mmengine - INFO - Epoch(train) [1149][35/63] lr: 4.0839e-04 eta: 1:00:20 time: 0.8063 data_time: 0.0497 memory: 16201 loss_prob: 0.3172 loss_thr: 0.2219 loss_db: 0.0572 loss: 0.5963 2022/08/30 22:53:17 - mmengine - INFO - Epoch(train) [1149][40/63] lr: 4.0839e-04 eta: 1:00:08 time: 0.8470 data_time: 0.0478 memory: 16201 loss_prob: 0.3105 loss_thr: 0.2193 loss_db: 0.0559 loss: 0.5857 2022/08/30 22:53:21 - mmengine - INFO - Epoch(train) [1149][45/63] lr: 4.0839e-04 eta: 1:00:08 time: 0.8513 data_time: 0.0496 memory: 16201 loss_prob: 0.3057 loss_thr: 0.2187 loss_db: 0.0545 loss: 0.5789 2022/08/30 22:53:25 - mmengine - INFO - Epoch(train) [1149][50/63] lr: 4.0839e-04 eta: 0:59:57 time: 0.8246 data_time: 0.0315 memory: 16201 loss_prob: 0.3067 loss_thr: 0.2165 loss_db: 0.0550 loss: 0.5782 2022/08/30 22:53:30 - mmengine - INFO - Epoch(train) [1149][55/63] lr: 4.0839e-04 eta: 0:59:57 time: 0.8435 data_time: 0.0412 memory: 16201 loss_prob: 0.3287 loss_thr: 0.2307 loss_db: 0.0585 loss: 0.6179 2022/08/30 22:53:34 - mmengine - INFO - Epoch(train) [1149][60/63] lr: 4.0839e-04 eta: 0:59:46 time: 0.8333 data_time: 0.0474 memory: 16201 loss_prob: 0.3238 loss_thr: 0.2306 loss_db: 0.0578 loss: 0.6121 2022/08/30 22:53:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:53:42 - mmengine - INFO - Epoch(train) [1150][5/63] lr: 4.0118e-04 eta: 0:59:46 time: 0.9904 data_time: 0.2199 memory: 16201 loss_prob: 0.2966 loss_thr: 0.2104 loss_db: 0.0533 loss: 0.5602 2022/08/30 22:53:46 - mmengine - INFO - Epoch(train) [1150][10/63] lr: 4.0118e-04 eta: 0:59:31 time: 1.0400 data_time: 0.2522 memory: 16201 loss_prob: 0.3042 loss_thr: 0.2154 loss_db: 0.0544 loss: 0.5740 2022/08/30 22:53:51 - mmengine - INFO - Epoch(train) [1150][15/63] lr: 4.0118e-04 eta: 0:59:31 time: 0.8561 data_time: 0.0731 memory: 16201 loss_prob: 0.2940 loss_thr: 0.2117 loss_db: 0.0526 loss: 0.5582 2022/08/30 22:53:55 - mmengine - INFO - Epoch(train) [1150][20/63] lr: 4.0118e-04 eta: 0:59:20 time: 0.8392 data_time: 0.0464 memory: 16201 loss_prob: 0.3009 loss_thr: 0.2132 loss_db: 0.0541 loss: 0.5682 2022/08/30 22:53:59 - mmengine - INFO - Epoch(train) [1150][25/63] lr: 4.0118e-04 eta: 0:59:20 time: 0.8584 data_time: 0.0746 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2115 loss_db: 0.0542 loss: 0.5744 2022/08/30 22:54:04 - mmengine - INFO - Epoch(train) [1150][30/63] lr: 4.0118e-04 eta: 0:59:08 time: 0.8709 data_time: 0.0773 memory: 16201 loss_prob: 0.2889 loss_thr: 0.2095 loss_db: 0.0510 loss: 0.5494 2022/08/30 22:54:08 - mmengine - INFO - Epoch(train) [1150][35/63] lr: 4.0118e-04 eta: 0:59:08 time: 0.8487 data_time: 0.0496 memory: 16201 loss_prob: 0.2832 loss_thr: 0.2065 loss_db: 0.0514 loss: 0.5410 2022/08/30 22:54:12 - mmengine - INFO - Epoch(train) [1150][40/63] lr: 4.0118e-04 eta: 0:58:57 time: 0.8710 data_time: 0.0674 memory: 16201 loss_prob: 0.3102 loss_thr: 0.2182 loss_db: 0.0551 loss: 0.5835 2022/08/30 22:54:17 - mmengine - INFO - Epoch(train) [1150][45/63] lr: 4.0118e-04 eta: 0:58:57 time: 0.8892 data_time: 0.0629 memory: 16201 loss_prob: 0.3199 loss_thr: 0.2264 loss_db: 0.0576 loss: 0.6039 2022/08/30 22:54:21 - mmengine - INFO - Epoch(train) [1150][50/63] lr: 4.0118e-04 eta: 0:58:46 time: 0.8421 data_time: 0.0398 memory: 16201 loss_prob: 0.3232 loss_thr: 0.2184 loss_db: 0.0582 loss: 0.5998 2022/08/30 22:54:25 - mmengine - INFO - Epoch(train) [1150][55/63] lr: 4.0118e-04 eta: 0:58:46 time: 0.8691 data_time: 0.0812 memory: 16201 loss_prob: 0.3231 loss_thr: 0.2212 loss_db: 0.0578 loss: 0.6021 2022/08/30 22:54:29 - mmengine - INFO - Epoch(train) [1150][60/63] lr: 4.0118e-04 eta: 0:58:35 time: 0.8717 data_time: 0.0838 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2280 loss_db: 0.0563 loss: 0.5963 2022/08/30 22:54:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:54:38 - mmengine - INFO - Epoch(train) [1151][5/63] lr: 3.9395e-04 eta: 0:58:35 time: 0.9876 data_time: 0.2297 memory: 16201 loss_prob: 0.2989 loss_thr: 0.2227 loss_db: 0.0528 loss: 0.5745 2022/08/30 22:54:42 - mmengine - INFO - Epoch(train) [1151][10/63] lr: 3.9395e-04 eta: 0:58:20 time: 1.0523 data_time: 0.2677 memory: 16201 loss_prob: 0.3181 loss_thr: 0.2204 loss_db: 0.0575 loss: 0.5960 2022/08/30 22:54:46 - mmengine - INFO - Epoch(train) [1151][15/63] lr: 3.9395e-04 eta: 0:58:20 time: 0.8530 data_time: 0.0803 memory: 16201 loss_prob: 0.3398 loss_thr: 0.2214 loss_db: 0.0595 loss: 0.6207 2022/08/30 22:54:50 - mmengine - INFO - Epoch(train) [1151][20/63] lr: 3.9395e-04 eta: 0:58:09 time: 0.8309 data_time: 0.0454 memory: 16201 loss_prob: 0.3344 loss_thr: 0.2223 loss_db: 0.0580 loss: 0.6148 2022/08/30 22:54:55 - mmengine - INFO - Epoch(train) [1151][25/63] lr: 3.9395e-04 eta: 0:58:09 time: 0.8644 data_time: 0.0736 memory: 16201 loss_prob: 0.3299 loss_thr: 0.2251 loss_db: 0.0573 loss: 0.6123 2022/08/30 22:54:59 - mmengine - INFO - Epoch(train) [1151][30/63] lr: 3.9395e-04 eta: 0:57:58 time: 0.8660 data_time: 0.0732 memory: 16201 loss_prob: 0.2967 loss_thr: 0.2139 loss_db: 0.0524 loss: 0.5630 2022/08/30 22:55:03 - mmengine - INFO - Epoch(train) [1151][35/63] lr: 3.9395e-04 eta: 0:57:58 time: 0.8397 data_time: 0.0481 memory: 16201 loss_prob: 0.3092 loss_thr: 0.2170 loss_db: 0.0566 loss: 0.5828 2022/08/30 22:55:08 - mmengine - INFO - Epoch(train) [1151][40/63] lr: 3.9395e-04 eta: 0:57:46 time: 0.8644 data_time: 0.0788 memory: 16201 loss_prob: 0.3267 loss_thr: 0.2231 loss_db: 0.0579 loss: 0.6078 2022/08/30 22:55:12 - mmengine - INFO - Epoch(train) [1151][45/63] lr: 3.9395e-04 eta: 0:57:46 time: 0.8702 data_time: 0.0734 memory: 16201 loss_prob: 0.3518 loss_thr: 0.2302 loss_db: 0.0597 loss: 0.6417 2022/08/30 22:55:16 - mmengine - INFO - Epoch(train) [1151][50/63] lr: 3.9395e-04 eta: 0:57:35 time: 0.8698 data_time: 0.0598 memory: 16201 loss_prob: 0.3689 loss_thr: 0.2380 loss_db: 0.0637 loss: 0.6705 2022/08/30 22:55:21 - mmengine - INFO - Epoch(train) [1151][55/63] lr: 3.9395e-04 eta: 0:57:35 time: 0.8773 data_time: 0.0857 memory: 16201 loss_prob: 0.3467 loss_thr: 0.2349 loss_db: 0.0614 loss: 0.6430 2022/08/30 22:55:25 - mmengine - INFO - Epoch(train) [1151][60/63] lr: 3.9395e-04 eta: 0:57:24 time: 0.8626 data_time: 0.0698 memory: 16201 loss_prob: 0.3156 loss_thr: 0.2205 loss_db: 0.0567 loss: 0.5927 2022/08/30 22:55:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:55:33 - mmengine - INFO - Epoch(train) [1152][5/63] lr: 3.8671e-04 eta: 0:57:24 time: 0.9825 data_time: 0.2216 memory: 16201 loss_prob: 0.3026 loss_thr: 0.2167 loss_db: 0.0530 loss: 0.5723 2022/08/30 22:55:38 - mmengine - INFO - Epoch(train) [1152][10/63] lr: 3.8671e-04 eta: 0:57:09 time: 1.0391 data_time: 0.2618 memory: 16201 loss_prob: 0.2903 loss_thr: 0.2119 loss_db: 0.0509 loss: 0.5531 2022/08/30 22:55:42 - mmengine - INFO - Epoch(train) [1152][15/63] lr: 3.8671e-04 eta: 0:57:09 time: 0.8441 data_time: 0.0780 memory: 16201 loss_prob: 0.3349 loss_thr: 0.2299 loss_db: 0.0598 loss: 0.6245 2022/08/30 22:55:46 - mmengine - INFO - Epoch(train) [1152][20/63] lr: 3.8671e-04 eta: 0:56:58 time: 0.8322 data_time: 0.0391 memory: 16201 loss_prob: 0.3440 loss_thr: 0.2294 loss_db: 0.0620 loss: 0.6353 2022/08/30 22:55:51 - mmengine - INFO - Epoch(train) [1152][25/63] lr: 3.8671e-04 eta: 0:56:58 time: 0.8858 data_time: 0.0916 memory: 16201 loss_prob: 0.3254 loss_thr: 0.2270 loss_db: 0.0591 loss: 0.6115 2022/08/30 22:55:55 - mmengine - INFO - Epoch(train) [1152][30/63] lr: 3.8671e-04 eta: 0:56:47 time: 0.8720 data_time: 0.0757 memory: 16201 loss_prob: 0.3209 loss_thr: 0.2326 loss_db: 0.0575 loss: 0.6109 2022/08/30 22:55:59 - mmengine - INFO - Epoch(train) [1152][35/63] lr: 3.8671e-04 eta: 0:56:47 time: 0.8583 data_time: 0.0445 memory: 16201 loss_prob: 0.3013 loss_thr: 0.2202 loss_db: 0.0534 loss: 0.5750 2022/08/30 22:56:04 - mmengine - INFO - Epoch(train) [1152][40/63] lr: 3.8671e-04 eta: 0:56:35 time: 0.8855 data_time: 0.0824 memory: 16201 loss_prob: 0.3185 loss_thr: 0.2261 loss_db: 0.0561 loss: 0.6007 2022/08/30 22:56:08 - mmengine - INFO - Epoch(train) [1152][45/63] lr: 3.8671e-04 eta: 0:56:35 time: 0.8785 data_time: 0.0810 memory: 16201 loss_prob: 0.2954 loss_thr: 0.2098 loss_db: 0.0522 loss: 0.5574 2022/08/30 22:56:12 - mmengine - INFO - Epoch(train) [1152][50/63] lr: 3.8671e-04 eta: 0:56:24 time: 0.8506 data_time: 0.0555 memory: 16201 loss_prob: 0.2798 loss_thr: 0.2029 loss_db: 0.0499 loss: 0.5326 2022/08/30 22:56:16 - mmengine - INFO - Epoch(train) [1152][55/63] lr: 3.8671e-04 eta: 0:56:24 time: 0.8175 data_time: 0.0385 memory: 16201 loss_prob: 0.3199 loss_thr: 0.2233 loss_db: 0.0568 loss: 0.5999 2022/08/30 22:56:20 - mmengine - INFO - Epoch(train) [1152][60/63] lr: 3.8671e-04 eta: 0:56:13 time: 0.8116 data_time: 0.0289 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2340 loss_db: 0.0602 loss: 0.6268 2022/08/30 22:56:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:56:29 - mmengine - INFO - Epoch(train) [1153][5/63] lr: 3.7945e-04 eta: 0:56:13 time: 0.9979 data_time: 0.2299 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2302 loss_db: 0.0589 loss: 0.6111 2022/08/30 22:56:33 - mmengine - INFO - Epoch(train) [1153][10/63] lr: 3.7945e-04 eta: 0:55:58 time: 1.0215 data_time: 0.2377 memory: 16201 loss_prob: 0.3208 loss_thr: 0.2264 loss_db: 0.0568 loss: 0.6039 2022/08/30 22:56:37 - mmengine - INFO - Epoch(train) [1153][15/63] lr: 3.7945e-04 eta: 0:55:58 time: 0.8046 data_time: 0.0244 memory: 16201 loss_prob: 0.3132 loss_thr: 0.2187 loss_db: 0.0550 loss: 0.5868 2022/08/30 22:56:41 - mmengine - INFO - Epoch(train) [1153][20/63] lr: 3.7945e-04 eta: 0:55:47 time: 0.8060 data_time: 0.0240 memory: 16201 loss_prob: 0.3030 loss_thr: 0.2209 loss_db: 0.0530 loss: 0.5770 2022/08/30 22:56:45 - mmengine - INFO - Epoch(train) [1153][25/63] lr: 3.7945e-04 eta: 0:55:47 time: 0.8279 data_time: 0.0305 memory: 16201 loss_prob: 0.2987 loss_thr: 0.2162 loss_db: 0.0523 loss: 0.5672 2022/08/30 22:56:49 - mmengine - INFO - Epoch(train) [1153][30/63] lr: 3.7945e-04 eta: 0:55:36 time: 0.8637 data_time: 0.0273 memory: 16201 loss_prob: 0.2869 loss_thr: 0.2064 loss_db: 0.0515 loss: 0.5448 2022/08/30 22:56:53 - mmengine - INFO - Epoch(train) [1153][35/63] lr: 3.7945e-04 eta: 0:55:36 time: 0.8464 data_time: 0.0222 memory: 16201 loss_prob: 0.3218 loss_thr: 0.2246 loss_db: 0.0581 loss: 0.6044 2022/08/30 22:56:58 - mmengine - INFO - Epoch(train) [1153][40/63] lr: 3.7945e-04 eta: 0:55:24 time: 0.8119 data_time: 0.0272 memory: 16201 loss_prob: 0.3234 loss_thr: 0.2267 loss_db: 0.0580 loss: 0.6080 2022/08/30 22:57:02 - mmengine - INFO - Epoch(train) [1153][45/63] lr: 3.7945e-04 eta: 0:55:24 time: 0.8383 data_time: 0.0383 memory: 16201 loss_prob: 0.2893 loss_thr: 0.2148 loss_db: 0.0525 loss: 0.5566 2022/08/30 22:57:06 - mmengine - INFO - Epoch(train) [1153][50/63] lr: 3.7945e-04 eta: 0:55:13 time: 0.8339 data_time: 0.0319 memory: 16201 loss_prob: 0.2795 loss_thr: 0.2076 loss_db: 0.0514 loss: 0.5384 2022/08/30 22:57:10 - mmengine - INFO - Epoch(train) [1153][55/63] lr: 3.7945e-04 eta: 0:55:13 time: 0.8225 data_time: 0.0262 memory: 16201 loss_prob: 0.2914 loss_thr: 0.2115 loss_db: 0.0526 loss: 0.5555 2022/08/30 22:57:14 - mmengine - INFO - Epoch(train) [1153][60/63] lr: 3.7945e-04 eta: 0:55:02 time: 0.8251 data_time: 0.0286 memory: 16201 loss_prob: 0.2874 loss_thr: 0.2077 loss_db: 0.0503 loss: 0.5454 2022/08/30 22:57:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:57:22 - mmengine - INFO - Epoch(train) [1154][5/63] lr: 3.7218e-04 eta: 0:55:02 time: 0.9814 data_time: 0.2138 memory: 16201 loss_prob: 0.2934 loss_thr: 0.2178 loss_db: 0.0527 loss: 0.5638 2022/08/30 22:57:27 - mmengine - INFO - Epoch(train) [1154][10/63] lr: 3.7218e-04 eta: 0:54:47 time: 1.0381 data_time: 0.2274 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2261 loss_db: 0.0558 loss: 0.5996 2022/08/30 22:57:31 - mmengine - INFO - Epoch(train) [1154][15/63] lr: 3.7218e-04 eta: 0:54:47 time: 0.8489 data_time: 0.0290 memory: 16201 loss_prob: 0.3040 loss_thr: 0.2180 loss_db: 0.0530 loss: 0.5749 2022/08/30 22:57:35 - mmengine - INFO - Epoch(train) [1154][20/63] lr: 3.7218e-04 eta: 0:54:36 time: 0.8401 data_time: 0.0204 memory: 16201 loss_prob: 0.3171 loss_thr: 0.2184 loss_db: 0.0575 loss: 0.5930 2022/08/30 22:57:39 - mmengine - INFO - Epoch(train) [1154][25/63] lr: 3.7218e-04 eta: 0:54:36 time: 0.8470 data_time: 0.0385 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2102 loss_db: 0.0578 loss: 0.5813 2022/08/30 22:57:44 - mmengine - INFO - Epoch(train) [1154][30/63] lr: 3.7218e-04 eta: 0:54:25 time: 0.8704 data_time: 0.0304 memory: 16201 loss_prob: 0.2875 loss_thr: 0.2051 loss_db: 0.0519 loss: 0.5446 2022/08/30 22:57:48 - mmengine - INFO - Epoch(train) [1154][35/63] lr: 3.7218e-04 eta: 0:54:25 time: 0.8508 data_time: 0.0255 memory: 16201 loss_prob: 0.3091 loss_thr: 0.2261 loss_db: 0.0555 loss: 0.5907 2022/08/30 22:57:52 - mmengine - INFO - Epoch(train) [1154][40/63] lr: 3.7218e-04 eta: 0:54:13 time: 0.8149 data_time: 0.0311 memory: 16201 loss_prob: 0.3138 loss_thr: 0.2264 loss_db: 0.0553 loss: 0.5956 2022/08/30 22:57:56 - mmengine - INFO - Epoch(train) [1154][45/63] lr: 3.7218e-04 eta: 0:54:13 time: 0.8183 data_time: 0.0267 memory: 16201 loss_prob: 0.3197 loss_thr: 0.2192 loss_db: 0.0549 loss: 0.5938 2022/08/30 22:58:00 - mmengine - INFO - Epoch(train) [1154][50/63] lr: 3.7218e-04 eta: 0:54:02 time: 0.8298 data_time: 0.0318 memory: 16201 loss_prob: 0.3009 loss_thr: 0.2137 loss_db: 0.0532 loss: 0.5679 2022/08/30 22:58:04 - mmengine - INFO - Epoch(train) [1154][55/63] lr: 3.7218e-04 eta: 0:54:02 time: 0.8084 data_time: 0.0267 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2399 loss_db: 0.0588 loss: 0.6289 2022/08/30 22:58:08 - mmengine - INFO - Epoch(train) [1154][60/63] lr: 3.7218e-04 eta: 0:53:51 time: 0.8068 data_time: 0.0250 memory: 16201 loss_prob: 0.3555 loss_thr: 0.2555 loss_db: 0.0638 loss: 0.6748 2022/08/30 22:58:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:58:16 - mmengine - INFO - Epoch(train) [1155][5/63] lr: 3.6489e-04 eta: 0:53:51 time: 0.9419 data_time: 0.1958 memory: 16201 loss_prob: 0.2978 loss_thr: 0.2029 loss_db: 0.0538 loss: 0.5546 2022/08/30 22:58:20 - mmengine - INFO - Epoch(train) [1155][10/63] lr: 3.6489e-04 eta: 0:53:36 time: 0.9924 data_time: 0.2124 memory: 16201 loss_prob: 0.3010 loss_thr: 0.2121 loss_db: 0.0541 loss: 0.5672 2022/08/30 22:58:24 - mmengine - INFO - Epoch(train) [1155][15/63] lr: 3.6489e-04 eta: 0:53:36 time: 0.8009 data_time: 0.0314 memory: 16201 loss_prob: 0.3388 loss_thr: 0.2563 loss_db: 0.0617 loss: 0.6568 2022/08/30 22:58:28 - mmengine - INFO - Epoch(train) [1155][20/63] lr: 3.6489e-04 eta: 0:53:25 time: 0.7858 data_time: 0.0191 memory: 16201 loss_prob: 0.3335 loss_thr: 0.2511 loss_db: 0.0608 loss: 0.6454 2022/08/30 22:58:32 - mmengine - INFO - Epoch(train) [1155][25/63] lr: 3.6489e-04 eta: 0:53:25 time: 0.8056 data_time: 0.0242 memory: 16201 loss_prob: 0.2880 loss_thr: 0.2107 loss_db: 0.0514 loss: 0.5500 2022/08/30 22:58:36 - mmengine - INFO - Epoch(train) [1155][30/63] lr: 3.6489e-04 eta: 0:53:14 time: 0.8370 data_time: 0.0315 memory: 16201 loss_prob: 0.2729 loss_thr: 0.2013 loss_db: 0.0489 loss: 0.5231 2022/08/30 22:58:40 - mmengine - INFO - Epoch(train) [1155][35/63] lr: 3.6489e-04 eta: 0:53:14 time: 0.8261 data_time: 0.0280 memory: 16201 loss_prob: 0.3038 loss_thr: 0.2190 loss_db: 0.0548 loss: 0.5776 2022/08/30 22:58:44 - mmengine - INFO - Epoch(train) [1155][40/63] lr: 3.6489e-04 eta: 0:53:02 time: 0.8132 data_time: 0.0263 memory: 16201 loss_prob: 0.3400 loss_thr: 0.2313 loss_db: 0.0601 loss: 0.6313 2022/08/30 22:58:49 - mmengine - INFO - Epoch(train) [1155][45/63] lr: 3.6489e-04 eta: 0:53:02 time: 0.8223 data_time: 0.0304 memory: 16201 loss_prob: 0.3053 loss_thr: 0.2144 loss_db: 0.0539 loss: 0.5736 2022/08/30 22:58:53 - mmengine - INFO - Epoch(train) [1155][50/63] lr: 3.6489e-04 eta: 0:52:51 time: 0.8084 data_time: 0.0263 memory: 16201 loss_prob: 0.2884 loss_thr: 0.2065 loss_db: 0.0493 loss: 0.5442 2022/08/30 22:58:57 - mmengine - INFO - Epoch(train) [1155][55/63] lr: 3.6489e-04 eta: 0:52:51 time: 0.8013 data_time: 0.0271 memory: 16201 loss_prob: 0.3181 loss_thr: 0.2212 loss_db: 0.0539 loss: 0.5933 2022/08/30 22:59:01 - mmengine - INFO - Epoch(train) [1155][60/63] lr: 3.6489e-04 eta: 0:52:40 time: 0.8293 data_time: 0.0271 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2237 loss_db: 0.0593 loss: 0.6140 2022/08/30 22:59:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 22:59:09 - mmengine - INFO - Epoch(train) [1156][5/63] lr: 3.5759e-04 eta: 0:52:40 time: 0.9536 data_time: 0.2034 memory: 16201 loss_prob: 0.3239 loss_thr: 0.2259 loss_db: 0.0593 loss: 0.6092 2022/08/30 22:59:13 - mmengine - INFO - Epoch(train) [1156][10/63] lr: 3.5759e-04 eta: 0:52:25 time: 1.0037 data_time: 0.2155 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2346 loss_db: 0.0604 loss: 0.6337 2022/08/30 22:59:17 - mmengine - INFO - Epoch(train) [1156][15/63] lr: 3.5759e-04 eta: 0:52:25 time: 0.8013 data_time: 0.0300 memory: 16201 loss_prob: 0.3623 loss_thr: 0.2419 loss_db: 0.0650 loss: 0.6693 2022/08/30 22:59:21 - mmengine - INFO - Epoch(train) [1156][20/63] lr: 3.5759e-04 eta: 0:52:14 time: 0.8196 data_time: 0.0210 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2095 loss_db: 0.0556 loss: 0.5738 2022/08/30 22:59:25 - mmengine - INFO - Epoch(train) [1156][25/63] lr: 3.5759e-04 eta: 0:52:14 time: 0.8385 data_time: 0.0309 memory: 16201 loss_prob: 0.2897 loss_thr: 0.2018 loss_db: 0.0523 loss: 0.5439 2022/08/30 22:59:29 - mmengine - INFO - Epoch(train) [1156][30/63] lr: 3.5759e-04 eta: 0:52:03 time: 0.8181 data_time: 0.0335 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2224 loss_db: 0.0574 loss: 0.5975 2022/08/30 22:59:33 - mmengine - INFO - Epoch(train) [1156][35/63] lr: 3.5759e-04 eta: 0:52:03 time: 0.8186 data_time: 0.0253 memory: 16201 loss_prob: 0.2924 loss_thr: 0.2182 loss_db: 0.0519 loss: 0.5625 2022/08/30 22:59:38 - mmengine - INFO - Epoch(train) [1156][40/63] lr: 3.5759e-04 eta: 0:51:52 time: 0.8363 data_time: 0.0304 memory: 16201 loss_prob: 0.2561 loss_thr: 0.1985 loss_db: 0.0448 loss: 0.4994 2022/08/30 22:59:42 - mmengine - INFO - Epoch(train) [1156][45/63] lr: 3.5759e-04 eta: 0:51:52 time: 0.8278 data_time: 0.0375 memory: 16201 loss_prob: 0.2886 loss_thr: 0.2045 loss_db: 0.0514 loss: 0.5446 2022/08/30 22:59:46 - mmengine - INFO - Epoch(train) [1156][50/63] lr: 3.5759e-04 eta: 0:51:40 time: 0.8023 data_time: 0.0288 memory: 16201 loss_prob: 0.3310 loss_thr: 0.2242 loss_db: 0.0585 loss: 0.6136 2022/08/30 22:59:50 - mmengine - INFO - Epoch(train) [1156][55/63] lr: 3.5759e-04 eta: 0:51:40 time: 0.8476 data_time: 0.0274 memory: 16201 loss_prob: 0.3308 loss_thr: 0.2165 loss_db: 0.0580 loss: 0.6054 2022/08/30 22:59:54 - mmengine - INFO - Epoch(train) [1156][60/63] lr: 3.5759e-04 eta: 0:51:29 time: 0.8462 data_time: 0.0269 memory: 16201 loss_prob: 0.3063 loss_thr: 0.2041 loss_db: 0.0546 loss: 0.5651 2022/08/30 22:59:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:00:02 - mmengine - INFO - Epoch(train) [1157][5/63] lr: 3.5027e-04 eta: 0:51:29 time: 0.9165 data_time: 0.1794 memory: 16201 loss_prob: 0.3122 loss_thr: 0.2243 loss_db: 0.0557 loss: 0.5922 2022/08/30 23:00:06 - mmengine - INFO - Epoch(train) [1157][10/63] lr: 3.5027e-04 eta: 0:51:14 time: 0.9682 data_time: 0.1945 memory: 16201 loss_prob: 0.2881 loss_thr: 0.2058 loss_db: 0.0513 loss: 0.5452 2022/08/30 23:00:10 - mmengine - INFO - Epoch(train) [1157][15/63] lr: 3.5027e-04 eta: 0:51:14 time: 0.8296 data_time: 0.0302 memory: 16201 loss_prob: 0.3154 loss_thr: 0.2199 loss_db: 0.0566 loss: 0.5918 2022/08/30 23:00:14 - mmengine - INFO - Epoch(train) [1157][20/63] lr: 3.5027e-04 eta: 0:51:03 time: 0.8060 data_time: 0.0202 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2319 loss_db: 0.0601 loss: 0.6267 2022/08/30 23:00:18 - mmengine - INFO - Epoch(train) [1157][25/63] lr: 3.5027e-04 eta: 0:51:03 time: 0.8115 data_time: 0.0341 memory: 16201 loss_prob: 0.3186 loss_thr: 0.2213 loss_db: 0.0575 loss: 0.5974 2022/08/30 23:00:22 - mmengine - INFO - Epoch(train) [1157][30/63] lr: 3.5027e-04 eta: 0:50:52 time: 0.8153 data_time: 0.0298 memory: 16201 loss_prob: 0.2973 loss_thr: 0.2076 loss_db: 0.0535 loss: 0.5584 2022/08/30 23:00:27 - mmengine - INFO - Epoch(train) [1157][35/63] lr: 3.5027e-04 eta: 0:50:52 time: 0.8830 data_time: 0.0224 memory: 16201 loss_prob: 0.3066 loss_thr: 0.2131 loss_db: 0.0554 loss: 0.5751 2022/08/30 23:00:31 - mmengine - INFO - Epoch(train) [1157][40/63] lr: 3.5027e-04 eta: 0:50:41 time: 0.8851 data_time: 0.0277 memory: 16201 loss_prob: 0.3212 loss_thr: 0.2242 loss_db: 0.0580 loss: 0.6034 2022/08/30 23:00:35 - mmengine - INFO - Epoch(train) [1157][45/63] lr: 3.5027e-04 eta: 0:50:41 time: 0.8425 data_time: 0.0713 memory: 16201 loss_prob: 0.2943 loss_thr: 0.2058 loss_db: 0.0526 loss: 0.5527 2022/08/30 23:00:40 - mmengine - INFO - Epoch(train) [1157][50/63] lr: 3.5027e-04 eta: 0:50:30 time: 0.8813 data_time: 0.0708 memory: 16201 loss_prob: 0.3136 loss_thr: 0.2241 loss_db: 0.0557 loss: 0.5933 2022/08/30 23:00:44 - mmengine - INFO - Epoch(train) [1157][55/63] lr: 3.5027e-04 eta: 0:50:30 time: 0.8504 data_time: 0.0269 memory: 16201 loss_prob: 0.3731 loss_thr: 0.2612 loss_db: 0.0662 loss: 0.7005 2022/08/30 23:00:48 - mmengine - INFO - Epoch(train) [1157][60/63] lr: 3.5027e-04 eta: 0:50:18 time: 0.8238 data_time: 0.0284 memory: 16201 loss_prob: 0.3575 loss_thr: 0.2425 loss_db: 0.0636 loss: 0.6636 2022/08/30 23:00:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:00:56 - mmengine - INFO - Epoch(train) [1158][5/63] lr: 3.4293e-04 eta: 0:50:18 time: 0.9223 data_time: 0.1819 memory: 16201 loss_prob: 0.3419 loss_thr: 0.2269 loss_db: 0.0613 loss: 0.6300 2022/08/30 23:01:00 - mmengine - INFO - Epoch(train) [1158][10/63] lr: 3.4293e-04 eta: 0:50:04 time: 0.9694 data_time: 0.1904 memory: 16201 loss_prob: 0.3370 loss_thr: 0.2302 loss_db: 0.0615 loss: 0.6288 2022/08/30 23:01:05 - mmengine - INFO - Epoch(train) [1158][15/63] lr: 3.4293e-04 eta: 0:50:04 time: 0.8957 data_time: 0.0282 memory: 16201 loss_prob: 0.3075 loss_thr: 0.2178 loss_db: 0.0562 loss: 0.5816 2022/08/30 23:01:09 - mmengine - INFO - Epoch(train) [1158][20/63] lr: 3.4293e-04 eta: 0:49:52 time: 0.8961 data_time: 0.0287 memory: 16201 loss_prob: 0.3033 loss_thr: 0.2156 loss_db: 0.0534 loss: 0.5722 2022/08/30 23:01:13 - mmengine - INFO - Epoch(train) [1158][25/63] lr: 3.4293e-04 eta: 0:49:52 time: 0.8131 data_time: 0.0291 memory: 16201 loss_prob: 0.2976 loss_thr: 0.2176 loss_db: 0.0515 loss: 0.5667 2022/08/30 23:01:17 - mmengine - INFO - Epoch(train) [1158][30/63] lr: 3.4293e-04 eta: 0:49:41 time: 0.8468 data_time: 0.0306 memory: 16201 loss_prob: 0.2676 loss_thr: 0.1972 loss_db: 0.0467 loss: 0.5115 2022/08/30 23:01:21 - mmengine - INFO - Epoch(train) [1158][35/63] lr: 3.4293e-04 eta: 0:49:41 time: 0.8212 data_time: 0.0257 memory: 16201 loss_prob: 0.2947 loss_thr: 0.2086 loss_db: 0.0511 loss: 0.5543 2022/08/30 23:01:25 - mmengine - INFO - Epoch(train) [1158][40/63] lr: 3.4293e-04 eta: 0:49:30 time: 0.8073 data_time: 0.0243 memory: 16201 loss_prob: 0.3135 loss_thr: 0.2210 loss_db: 0.0555 loss: 0.5900 2022/08/30 23:01:29 - mmengine - INFO - Epoch(train) [1158][45/63] lr: 3.4293e-04 eta: 0:49:30 time: 0.8399 data_time: 0.0323 memory: 16201 loss_prob: 0.3007 loss_thr: 0.2112 loss_db: 0.0543 loss: 0.5663 2022/08/30 23:01:34 - mmengine - INFO - Epoch(train) [1158][50/63] lr: 3.4293e-04 eta: 0:49:19 time: 0.8274 data_time: 0.0258 memory: 16201 loss_prob: 0.3177 loss_thr: 0.2298 loss_db: 0.0569 loss: 0.6044 2022/08/30 23:01:38 - mmengine - INFO - Epoch(train) [1158][55/63] lr: 3.4293e-04 eta: 0:49:19 time: 0.8244 data_time: 0.0273 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2404 loss_db: 0.0582 loss: 0.6183 2022/08/30 23:01:42 - mmengine - INFO - Epoch(train) [1158][60/63] lr: 3.4293e-04 eta: 0:49:07 time: 0.8229 data_time: 0.0294 memory: 16201 loss_prob: 0.3209 loss_thr: 0.2288 loss_db: 0.0576 loss: 0.6072 2022/08/30 23:01:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:01:50 - mmengine - INFO - Epoch(train) [1159][5/63] lr: 3.3557e-04 eta: 0:49:07 time: 0.9797 data_time: 0.2135 memory: 16201 loss_prob: 0.3601 loss_thr: 0.2499 loss_db: 0.0629 loss: 0.6729 2022/08/30 23:01:54 - mmengine - INFO - Epoch(train) [1159][10/63] lr: 3.3557e-04 eta: 0:48:53 time: 1.0051 data_time: 0.2167 memory: 16201 loss_prob: 0.3216 loss_thr: 0.2262 loss_db: 0.0557 loss: 0.6036 2022/08/30 23:01:58 - mmengine - INFO - Epoch(train) [1159][15/63] lr: 3.3557e-04 eta: 0:48:53 time: 0.8092 data_time: 0.0267 memory: 16201 loss_prob: 0.3044 loss_thr: 0.2105 loss_db: 0.0539 loss: 0.5688 2022/08/30 23:02:02 - mmengine - INFO - Epoch(train) [1159][20/63] lr: 3.3557e-04 eta: 0:48:42 time: 0.8229 data_time: 0.0275 memory: 16201 loss_prob: 0.2905 loss_thr: 0.1994 loss_db: 0.0527 loss: 0.5425 2022/08/30 23:02:06 - mmengine - INFO - Epoch(train) [1159][25/63] lr: 3.3557e-04 eta: 0:48:42 time: 0.8359 data_time: 0.0329 memory: 16201 loss_prob: 0.3145 loss_thr: 0.2207 loss_db: 0.0567 loss: 0.5918 2022/08/30 23:02:10 - mmengine - INFO - Epoch(train) [1159][30/63] lr: 3.3557e-04 eta: 0:48:30 time: 0.8229 data_time: 0.0268 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2228 loss_db: 0.0576 loss: 0.6014 2022/08/30 23:02:15 - mmengine - INFO - Epoch(train) [1159][35/63] lr: 3.3557e-04 eta: 0:48:30 time: 0.8096 data_time: 0.0312 memory: 16201 loss_prob: 0.2924 loss_thr: 0.2092 loss_db: 0.0527 loss: 0.5542 2022/08/30 23:02:19 - mmengine - INFO - Epoch(train) [1159][40/63] lr: 3.3557e-04 eta: 0:48:19 time: 0.8238 data_time: 0.0292 memory: 16201 loss_prob: 0.2868 loss_thr: 0.2087 loss_db: 0.0518 loss: 0.5472 2022/08/30 23:02:23 - mmengine - INFO - Epoch(train) [1159][45/63] lr: 3.3557e-04 eta: 0:48:19 time: 0.8333 data_time: 0.0243 memory: 16201 loss_prob: 0.3069 loss_thr: 0.2166 loss_db: 0.0550 loss: 0.5785 2022/08/30 23:02:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:02:27 - mmengine - INFO - Epoch(train) [1159][50/63] lr: 3.3557e-04 eta: 0:48:08 time: 0.8233 data_time: 0.0255 memory: 16201 loss_prob: 0.3168 loss_thr: 0.2199 loss_db: 0.0566 loss: 0.5932 2022/08/30 23:02:31 - mmengine - INFO - Epoch(train) [1159][55/63] lr: 3.3557e-04 eta: 0:48:08 time: 0.8031 data_time: 0.0258 memory: 16201 loss_prob: 0.3163 loss_thr: 0.2154 loss_db: 0.0571 loss: 0.5888 2022/08/30 23:02:35 - mmengine - INFO - Epoch(train) [1159][60/63] lr: 3.3557e-04 eta: 0:47:57 time: 0.8189 data_time: 0.0294 memory: 16201 loss_prob: 0.3270 loss_thr: 0.2226 loss_db: 0.0588 loss: 0.6084 2022/08/30 23:02:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:02:43 - mmengine - INFO - Epoch(train) [1160][5/63] lr: 3.2820e-04 eta: 0:47:57 time: 0.9219 data_time: 0.1928 memory: 16201 loss_prob: 0.3272 loss_thr: 0.2250 loss_db: 0.0580 loss: 0.6102 2022/08/30 23:02:47 - mmengine - INFO - Epoch(train) [1160][10/63] lr: 3.2820e-04 eta: 0:47:42 time: 0.9787 data_time: 0.2034 memory: 16201 loss_prob: 0.3116 loss_thr: 0.2157 loss_db: 0.0559 loss: 0.5833 2022/08/30 23:02:51 - mmengine - INFO - Epoch(train) [1160][15/63] lr: 3.2820e-04 eta: 0:47:42 time: 0.8444 data_time: 0.0317 memory: 16201 loss_prob: 0.2881 loss_thr: 0.2140 loss_db: 0.0518 loss: 0.5539 2022/08/30 23:02:55 - mmengine - INFO - Epoch(train) [1160][20/63] lr: 3.2820e-04 eta: 0:47:31 time: 0.8610 data_time: 0.0238 memory: 16201 loss_prob: 0.2686 loss_thr: 0.2001 loss_db: 0.0481 loss: 0.5167 2022/08/30 23:03:00 - mmengine - INFO - Epoch(train) [1160][25/63] lr: 3.2820e-04 eta: 0:47:31 time: 0.9046 data_time: 0.0494 memory: 16201 loss_prob: 0.2876 loss_thr: 0.2066 loss_db: 0.0510 loss: 0.5451 2022/08/30 23:03:04 - mmengine - INFO - Epoch(train) [1160][30/63] lr: 3.2820e-04 eta: 0:47:20 time: 0.8952 data_time: 0.0484 memory: 16201 loss_prob: 0.3226 loss_thr: 0.2183 loss_db: 0.0571 loss: 0.5980 2022/08/30 23:03:09 - mmengine - INFO - Epoch(train) [1160][35/63] lr: 3.2820e-04 eta: 0:47:20 time: 0.8374 data_time: 0.0275 memory: 16201 loss_prob: 0.3262 loss_thr: 0.2151 loss_db: 0.0574 loss: 0.5987 2022/08/30 23:03:13 - mmengine - INFO - Epoch(train) [1160][40/63] lr: 3.2820e-04 eta: 0:47:08 time: 0.8279 data_time: 0.0288 memory: 16201 loss_prob: 0.3257 loss_thr: 0.2233 loss_db: 0.0581 loss: 0.6071 2022/08/30 23:03:18 - mmengine - INFO - Epoch(train) [1160][45/63] lr: 3.2820e-04 eta: 0:47:08 time: 0.9461 data_time: 0.0349 memory: 16201 loss_prob: 0.2815 loss_thr: 0.2041 loss_db: 0.0513 loss: 0.5370 2022/08/30 23:03:22 - mmengine - INFO - Epoch(train) [1160][50/63] lr: 3.2820e-04 eta: 0:46:57 time: 0.9407 data_time: 0.0365 memory: 16201 loss_prob: 0.3008 loss_thr: 0.2151 loss_db: 0.0548 loss: 0.5707 2022/08/30 23:03:26 - mmengine - INFO - Epoch(train) [1160][55/63] lr: 3.2820e-04 eta: 0:46:57 time: 0.8030 data_time: 0.0281 memory: 16201 loss_prob: 0.3433 loss_thr: 0.2359 loss_db: 0.0605 loss: 0.6397 2022/08/30 23:03:30 - mmengine - INFO - Epoch(train) [1160][60/63] lr: 3.2820e-04 eta: 0:46:46 time: 0.8189 data_time: 0.0330 memory: 16201 loss_prob: 0.3138 loss_thr: 0.2206 loss_db: 0.0542 loss: 0.5886 2022/08/30 23:03:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:03:32 - mmengine - INFO - Saving checkpoint at 1160 epochs 2022/08/30 23:03:40 - mmengine - INFO - Epoch(val) [1160][5/32] eta: 0:46:46 time: 0.6688 data_time: 0.1205 memory: 16201 2022/08/30 23:03:44 - mmengine - INFO - Epoch(val) [1160][10/32] eta: 0:00:17 time: 0.7783 data_time: 0.1532 memory: 15734 2022/08/30 23:03:47 - mmengine - INFO - Epoch(val) [1160][15/32] eta: 0:00:17 time: 0.6602 data_time: 0.0547 memory: 15734 2022/08/30 23:03:50 - mmengine - INFO - Epoch(val) [1160][20/32] eta: 0:00:07 time: 0.6193 data_time: 0.0547 memory: 15734 2022/08/30 23:03:54 - mmengine - INFO - Epoch(val) [1160][25/32] eta: 0:00:07 time: 0.7094 data_time: 0.0702 memory: 15734 2022/08/30 23:03:57 - mmengine - INFO - Epoch(val) [1160][30/32] eta: 0:00:01 time: 0.6747 data_time: 0.0426 memory: 15734 2022/08/30 23:03:58 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 23:03:58 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8507, precision: 0.8039, hmean: 0.8267 2022/08/30 23:03:58 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8507, precision: 0.8366, hmean: 0.8436 2022/08/30 23:03:58 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8507, precision: 0.8632, hmean: 0.8569 2022/08/30 23:03:58 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8483, precision: 0.8771, hmean: 0.8625 2022/08/30 23:03:58 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8445, precision: 0.8904, hmean: 0.8668 2022/08/30 23:03:58 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8238, precision: 0.9125, hmean: 0.8659 2022/08/30 23:03:58 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.5272, precision: 0.9530, hmean: 0.6789 2022/08/30 23:03:58 - mmengine - INFO - Epoch(val) [1160][32/32] icdar/precision: 0.8904 icdar/recall: 0.8445 icdar/hmean: 0.8668 2022/08/30 23:04:04 - mmengine - INFO - Epoch(train) [1161][5/63] lr: 3.2081e-04 eta: 0:00:01 time: 0.9888 data_time: 0.2124 memory: 16201 loss_prob: 0.3037 loss_thr: 0.2316 loss_db: 0.0543 loss: 0.5895 2022/08/30 23:04:08 - mmengine - INFO - Epoch(train) [1161][10/63] lr: 3.2081e-04 eta: 0:46:31 time: 1.0217 data_time: 0.2149 memory: 16201 loss_prob: 0.2975 loss_thr: 0.2186 loss_db: 0.0538 loss: 0.5699 2022/08/30 23:04:12 - mmengine - INFO - Epoch(train) [1161][15/63] lr: 3.2081e-04 eta: 0:46:31 time: 0.8003 data_time: 0.0280 memory: 16201 loss_prob: 0.3090 loss_thr: 0.2148 loss_db: 0.0569 loss: 0.5806 2022/08/30 23:04:17 - mmengine - INFO - Epoch(train) [1161][20/63] lr: 3.2081e-04 eta: 0:46:20 time: 0.8467 data_time: 0.0301 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2180 loss_db: 0.0564 loss: 0.5877 2022/08/30 23:04:21 - mmengine - INFO - Epoch(train) [1161][25/63] lr: 3.2081e-04 eta: 0:46:20 time: 0.8430 data_time: 0.0268 memory: 16201 loss_prob: 0.2856 loss_thr: 0.2018 loss_db: 0.0512 loss: 0.5386 2022/08/30 23:04:25 - mmengine - INFO - Epoch(train) [1161][30/63] lr: 3.2081e-04 eta: 0:46:09 time: 0.8274 data_time: 0.0308 memory: 16201 loss_prob: 0.2892 loss_thr: 0.2027 loss_db: 0.0518 loss: 0.5437 2022/08/30 23:04:29 - mmengine - INFO - Epoch(train) [1161][35/63] lr: 3.2081e-04 eta: 0:46:09 time: 0.8419 data_time: 0.0386 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2106 loss_db: 0.0550 loss: 0.5780 2022/08/30 23:04:33 - mmengine - INFO - Epoch(train) [1161][40/63] lr: 3.2081e-04 eta: 0:45:58 time: 0.8121 data_time: 0.0255 memory: 16201 loss_prob: 0.3030 loss_thr: 0.1994 loss_db: 0.0521 loss: 0.5545 2022/08/30 23:04:38 - mmengine - INFO - Epoch(train) [1161][45/63] lr: 3.2081e-04 eta: 0:45:58 time: 0.8560 data_time: 0.0272 memory: 16201 loss_prob: 0.3049 loss_thr: 0.2098 loss_db: 0.0520 loss: 0.5666 2022/08/30 23:04:42 - mmengine - INFO - Epoch(train) [1161][50/63] lr: 3.2081e-04 eta: 0:45:47 time: 0.8547 data_time: 0.0311 memory: 16201 loss_prob: 0.3393 loss_thr: 0.2420 loss_db: 0.0593 loss: 0.6407 2022/08/30 23:04:46 - mmengine - INFO - Epoch(train) [1161][55/63] lr: 3.2081e-04 eta: 0:45:47 time: 0.8138 data_time: 0.0219 memory: 16201 loss_prob: 0.3143 loss_thr: 0.2265 loss_db: 0.0563 loss: 0.5971 2022/08/30 23:04:50 - mmengine - INFO - Epoch(train) [1161][60/63] lr: 3.2081e-04 eta: 0:45:35 time: 0.8380 data_time: 0.0418 memory: 16201 loss_prob: 0.3028 loss_thr: 0.2217 loss_db: 0.0546 loss: 0.5792 2022/08/30 23:04:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:04:58 - mmengine - INFO - Epoch(train) [1162][5/63] lr: 3.1340e-04 eta: 0:45:35 time: 0.9734 data_time: 0.2309 memory: 16201 loss_prob: 0.3116 loss_thr: 0.2250 loss_db: 0.0568 loss: 0.5934 2022/08/30 23:05:02 - mmengine - INFO - Epoch(train) [1162][10/63] lr: 3.1340e-04 eta: 0:45:21 time: 1.0268 data_time: 0.2427 memory: 16201 loss_prob: 0.3033 loss_thr: 0.2042 loss_db: 0.0555 loss: 0.5630 2022/08/30 23:05:06 - mmengine - INFO - Epoch(train) [1162][15/63] lr: 3.1340e-04 eta: 0:45:21 time: 0.8288 data_time: 0.0317 memory: 16201 loss_prob: 0.2840 loss_thr: 0.1986 loss_db: 0.0511 loss: 0.5337 2022/08/30 23:05:10 - mmengine - INFO - Epoch(train) [1162][20/63] lr: 3.1340e-04 eta: 0:45:10 time: 0.8333 data_time: 0.0234 memory: 16201 loss_prob: 0.3011 loss_thr: 0.2119 loss_db: 0.0548 loss: 0.5678 2022/08/30 23:05:15 - mmengine - INFO - Epoch(train) [1162][25/63] lr: 3.1340e-04 eta: 0:45:10 time: 0.8243 data_time: 0.0309 memory: 16201 loss_prob: 0.3547 loss_thr: 0.2452 loss_db: 0.0645 loss: 0.6644 2022/08/30 23:05:18 - mmengine - INFO - Epoch(train) [1162][30/63] lr: 3.1340e-04 eta: 0:44:58 time: 0.8019 data_time: 0.0251 memory: 16201 loss_prob: 0.3504 loss_thr: 0.2420 loss_db: 0.0627 loss: 0.6551 2022/08/30 23:05:22 - mmengine - INFO - Epoch(train) [1162][35/63] lr: 3.1340e-04 eta: 0:44:58 time: 0.7945 data_time: 0.0243 memory: 16201 loss_prob: 0.3207 loss_thr: 0.2188 loss_db: 0.0559 loss: 0.5954 2022/08/30 23:05:27 - mmengine - INFO - Epoch(train) [1162][40/63] lr: 3.1340e-04 eta: 0:44:47 time: 0.8682 data_time: 0.0313 memory: 16201 loss_prob: 0.3366 loss_thr: 0.2344 loss_db: 0.0598 loss: 0.6309 2022/08/30 23:05:31 - mmengine - INFO - Epoch(train) [1162][45/63] lr: 3.1340e-04 eta: 0:44:47 time: 0.8909 data_time: 0.0310 memory: 16201 loss_prob: 0.3617 loss_thr: 0.2470 loss_db: 0.0638 loss: 0.6725 2022/08/30 23:05:35 - mmengine - INFO - Epoch(train) [1162][50/63] lr: 3.1340e-04 eta: 0:44:36 time: 0.8208 data_time: 0.0303 memory: 16201 loss_prob: 0.3406 loss_thr: 0.2297 loss_db: 0.0568 loss: 0.6271 2022/08/30 23:05:40 - mmengine - INFO - Epoch(train) [1162][55/63] lr: 3.1340e-04 eta: 0:44:36 time: 0.8166 data_time: 0.0296 memory: 16201 loss_prob: 0.3096 loss_thr: 0.2239 loss_db: 0.0524 loss: 0.5859 2022/08/30 23:05:44 - mmengine - INFO - Epoch(train) [1162][60/63] lr: 3.1340e-04 eta: 0:44:25 time: 0.8748 data_time: 0.0257 memory: 16201 loss_prob: 0.3236 loss_thr: 0.2332 loss_db: 0.0566 loss: 0.6134 2022/08/30 23:05:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:05:52 - mmengine - INFO - Epoch(train) [1163][5/63] lr: 3.0597e-04 eta: 0:44:25 time: 1.0336 data_time: 0.1992 memory: 16201 loss_prob: 0.3199 loss_thr: 0.2272 loss_db: 0.0582 loss: 0.6053 2022/08/30 23:05:56 - mmengine - INFO - Epoch(train) [1163][10/63] lr: 3.0597e-04 eta: 0:44:10 time: 0.9891 data_time: 0.1975 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2354 loss_db: 0.0611 loss: 0.6352 2022/08/30 23:06:00 - mmengine - INFO - Epoch(train) [1163][15/63] lr: 3.0597e-04 eta: 0:44:10 time: 0.8028 data_time: 0.0279 memory: 16201 loss_prob: 0.3429 loss_thr: 0.2387 loss_db: 0.0621 loss: 0.6437 2022/08/30 23:06:05 - mmengine - INFO - Epoch(train) [1163][20/63] lr: 3.0597e-04 eta: 0:43:59 time: 0.8575 data_time: 0.0264 memory: 16201 loss_prob: 0.3293 loss_thr: 0.2274 loss_db: 0.0588 loss: 0.6155 2022/08/30 23:06:09 - mmengine - INFO - Epoch(train) [1163][25/63] lr: 3.0597e-04 eta: 0:43:59 time: 0.8494 data_time: 0.0299 memory: 16201 loss_prob: 0.2944 loss_thr: 0.2056 loss_db: 0.0521 loss: 0.5522 2022/08/30 23:06:13 - mmengine - INFO - Epoch(train) [1163][30/63] lr: 3.0597e-04 eta: 0:43:48 time: 0.7915 data_time: 0.0251 memory: 16201 loss_prob: 0.2941 loss_thr: 0.2070 loss_db: 0.0531 loss: 0.5543 2022/08/30 23:06:17 - mmengine - INFO - Epoch(train) [1163][35/63] lr: 3.0597e-04 eta: 0:43:48 time: 0.7880 data_time: 0.0209 memory: 16201 loss_prob: 0.3298 loss_thr: 0.2252 loss_db: 0.0600 loss: 0.6151 2022/08/30 23:06:21 - mmengine - INFO - Epoch(train) [1163][40/63] lr: 3.0597e-04 eta: 0:43:36 time: 0.7924 data_time: 0.0257 memory: 16201 loss_prob: 0.3318 loss_thr: 0.2228 loss_db: 0.0587 loss: 0.6132 2022/08/30 23:06:26 - mmengine - INFO - Epoch(train) [1163][45/63] lr: 3.0597e-04 eta: 0:43:36 time: 0.8784 data_time: 0.0316 memory: 16201 loss_prob: 0.3736 loss_thr: 0.2156 loss_db: 0.0601 loss: 0.6494 2022/08/30 23:06:30 - mmengine - INFO - Epoch(train) [1163][50/63] lr: 3.0597e-04 eta: 0:43:25 time: 0.8788 data_time: 0.0263 memory: 16201 loss_prob: 0.3591 loss_thr: 0.2187 loss_db: 0.0580 loss: 0.6357 2022/08/30 23:06:34 - mmengine - INFO - Epoch(train) [1163][55/63] lr: 3.0597e-04 eta: 0:43:25 time: 0.8156 data_time: 0.0274 memory: 16201 loss_prob: 0.3197 loss_thr: 0.2216 loss_db: 0.0566 loss: 0.5979 2022/08/30 23:06:38 - mmengine - INFO - Epoch(train) [1163][60/63] lr: 3.0597e-04 eta: 0:43:14 time: 0.8295 data_time: 0.0379 memory: 16201 loss_prob: 0.3285 loss_thr: 0.2127 loss_db: 0.0580 loss: 0.5991 2022/08/30 23:06:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:06:46 - mmengine - INFO - Epoch(train) [1164][5/63] lr: 2.9852e-04 eta: 0:43:14 time: 0.9538 data_time: 0.2046 memory: 16201 loss_prob: 0.3085 loss_thr: 0.2141 loss_db: 0.0554 loss: 0.5780 2022/08/30 23:06:50 - mmengine - INFO - Epoch(train) [1164][10/63] lr: 2.9852e-04 eta: 0:42:59 time: 1.0183 data_time: 0.2233 memory: 16201 loss_prob: 0.3195 loss_thr: 0.2146 loss_db: 0.0575 loss: 0.5916 2022/08/30 23:06:54 - mmengine - INFO - Epoch(train) [1164][15/63] lr: 2.9852e-04 eta: 0:42:59 time: 0.8082 data_time: 0.0324 memory: 16201 loss_prob: 0.3178 loss_thr: 0.2162 loss_db: 0.0565 loss: 0.5905 2022/08/30 23:06:58 - mmengine - INFO - Epoch(train) [1164][20/63] lr: 2.9852e-04 eta: 0:42:48 time: 0.7854 data_time: 0.0174 memory: 16201 loss_prob: 0.2949 loss_thr: 0.2124 loss_db: 0.0511 loss: 0.5584 2022/08/30 23:07:02 - mmengine - INFO - Epoch(train) [1164][25/63] lr: 2.9852e-04 eta: 0:42:48 time: 0.8012 data_time: 0.0322 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2377 loss_db: 0.0579 loss: 0.6244 2022/08/30 23:07:07 - mmengine - INFO - Epoch(train) [1164][30/63] lr: 2.9852e-04 eta: 0:42:37 time: 0.8758 data_time: 0.0291 memory: 16201 loss_prob: 0.3228 loss_thr: 0.2331 loss_db: 0.0582 loss: 0.6142 2022/08/30 23:07:11 - mmengine - INFO - Epoch(train) [1164][35/63] lr: 2.9852e-04 eta: 0:42:37 time: 0.8802 data_time: 0.0310 memory: 16201 loss_prob: 0.3046 loss_thr: 0.2167 loss_db: 0.0562 loss: 0.5775 2022/08/30 23:07:15 - mmengine - INFO - Epoch(train) [1164][40/63] lr: 2.9852e-04 eta: 0:42:26 time: 0.8249 data_time: 0.0326 memory: 16201 loss_prob: 0.3144 loss_thr: 0.2179 loss_db: 0.0578 loss: 0.5900 2022/08/30 23:07:19 - mmengine - INFO - Epoch(train) [1164][45/63] lr: 2.9852e-04 eta: 0:42:26 time: 0.8276 data_time: 0.0383 memory: 16201 loss_prob: 0.2916 loss_thr: 0.2078 loss_db: 0.0529 loss: 0.5523 2022/08/30 23:07:23 - mmengine - INFO - Epoch(train) [1164][50/63] lr: 2.9852e-04 eta: 0:42:15 time: 0.8337 data_time: 0.0371 memory: 16201 loss_prob: 0.2990 loss_thr: 0.2194 loss_db: 0.0544 loss: 0.5728 2022/08/30 23:07:28 - mmengine - INFO - Epoch(train) [1164][55/63] lr: 2.9852e-04 eta: 0:42:15 time: 0.8843 data_time: 0.0229 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2352 loss_db: 0.0587 loss: 0.6228 2022/08/30 23:07:32 - mmengine - INFO - Epoch(train) [1164][60/63] lr: 2.9852e-04 eta: 0:42:03 time: 0.8630 data_time: 0.0284 memory: 16201 loss_prob: 0.3383 loss_thr: 0.2331 loss_db: 0.0582 loss: 0.6295 2022/08/30 23:07:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:07:40 - mmengine - INFO - Epoch(train) [1165][5/63] lr: 2.9105e-04 eta: 0:42:03 time: 0.9554 data_time: 0.2051 memory: 16201 loss_prob: 0.3028 loss_thr: 0.2182 loss_db: 0.0534 loss: 0.5744 2022/08/30 23:07:44 - mmengine - INFO - Epoch(train) [1165][10/63] lr: 2.9105e-04 eta: 0:41:49 time: 0.9990 data_time: 0.2160 memory: 16201 loss_prob: 0.2982 loss_thr: 0.2190 loss_db: 0.0539 loss: 0.5710 2022/08/30 23:07:48 - mmengine - INFO - Epoch(train) [1165][15/63] lr: 2.9105e-04 eta: 0:41:49 time: 0.8129 data_time: 0.0277 memory: 16201 loss_prob: 0.3050 loss_thr: 0.2168 loss_db: 0.0554 loss: 0.5771 2022/08/30 23:07:52 - mmengine - INFO - Epoch(train) [1165][20/63] lr: 2.9105e-04 eta: 0:41:38 time: 0.7974 data_time: 0.0218 memory: 16201 loss_prob: 0.3103 loss_thr: 0.2198 loss_db: 0.0555 loss: 0.5857 2022/08/30 23:07:57 - mmengine - INFO - Epoch(train) [1165][25/63] lr: 2.9105e-04 eta: 0:41:38 time: 0.8721 data_time: 0.0311 memory: 16201 loss_prob: 0.3058 loss_thr: 0.2187 loss_db: 0.0546 loss: 0.5792 2022/08/30 23:08:01 - mmengine - INFO - Epoch(train) [1165][30/63] lr: 2.9105e-04 eta: 0:41:26 time: 0.8757 data_time: 0.0332 memory: 16201 loss_prob: 0.3599 loss_thr: 0.2403 loss_db: 0.0648 loss: 0.6650 2022/08/30 23:08:05 - mmengine - INFO - Epoch(train) [1165][35/63] lr: 2.9105e-04 eta: 0:41:26 time: 0.7842 data_time: 0.0216 memory: 16201 loss_prob: 0.3432 loss_thr: 0.2330 loss_db: 0.0615 loss: 0.6377 2022/08/30 23:08:09 - mmengine - INFO - Epoch(train) [1165][40/63] lr: 2.9105e-04 eta: 0:41:15 time: 0.8030 data_time: 0.0284 memory: 16201 loss_prob: 0.2891 loss_thr: 0.2065 loss_db: 0.0517 loss: 0.5473 2022/08/30 23:08:13 - mmengine - INFO - Epoch(train) [1165][45/63] lr: 2.9105e-04 eta: 0:41:15 time: 0.8591 data_time: 0.0373 memory: 16201 loss_prob: 0.3283 loss_thr: 0.2298 loss_db: 0.0583 loss: 0.6164 2022/08/30 23:08:17 - mmengine - INFO - Epoch(train) [1165][50/63] lr: 2.9105e-04 eta: 0:41:04 time: 0.8508 data_time: 0.0289 memory: 16201 loss_prob: 0.3321 loss_thr: 0.2350 loss_db: 0.0603 loss: 0.6274 2022/08/30 23:08:21 - mmengine - INFO - Epoch(train) [1165][55/63] lr: 2.9105e-04 eta: 0:41:04 time: 0.8187 data_time: 0.0313 memory: 16201 loss_prob: 0.3169 loss_thr: 0.2331 loss_db: 0.0580 loss: 0.6080 2022/08/30 23:08:26 - mmengine - INFO - Epoch(train) [1165][60/63] lr: 2.9105e-04 eta: 0:40:53 time: 0.8458 data_time: 0.0336 memory: 16201 loss_prob: 0.3182 loss_thr: 0.2419 loss_db: 0.0563 loss: 0.6163 2022/08/30 23:08:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:08:34 - mmengine - INFO - Epoch(train) [1166][5/63] lr: 2.8356e-04 eta: 0:40:53 time: 0.9673 data_time: 0.1997 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2242 loss_db: 0.0547 loss: 0.5913 2022/08/30 23:08:38 - mmengine - INFO - Epoch(train) [1166][10/63] lr: 2.8356e-04 eta: 0:40:38 time: 0.9902 data_time: 0.2009 memory: 16201 loss_prob: 0.3179 loss_thr: 0.2210 loss_db: 0.0578 loss: 0.5967 2022/08/30 23:08:42 - mmengine - INFO - Epoch(train) [1166][15/63] lr: 2.8356e-04 eta: 0:40:38 time: 0.8198 data_time: 0.0241 memory: 16201 loss_prob: 0.3249 loss_thr: 0.2174 loss_db: 0.0591 loss: 0.6014 2022/08/30 23:08:46 - mmengine - INFO - Epoch(train) [1166][20/63] lr: 2.8356e-04 eta: 0:40:27 time: 0.8554 data_time: 0.0302 memory: 16201 loss_prob: 0.3050 loss_thr: 0.2075 loss_db: 0.0547 loss: 0.5673 2022/08/30 23:08:50 - mmengine - INFO - Epoch(train) [1166][25/63] lr: 2.8356e-04 eta: 0:40:27 time: 0.8386 data_time: 0.0285 memory: 16201 loss_prob: 0.2897 loss_thr: 0.2108 loss_db: 0.0507 loss: 0.5512 2022/08/30 23:08:54 - mmengine - INFO - Epoch(train) [1166][30/63] lr: 2.8356e-04 eta: 0:40:16 time: 0.8103 data_time: 0.0258 memory: 16201 loss_prob: 0.3070 loss_thr: 0.2180 loss_db: 0.0535 loss: 0.5784 2022/08/30 23:08:58 - mmengine - INFO - Epoch(train) [1166][35/63] lr: 2.8356e-04 eta: 0:40:16 time: 0.8159 data_time: 0.0264 memory: 16201 loss_prob: 0.3063 loss_thr: 0.2171 loss_db: 0.0554 loss: 0.5787 2022/08/30 23:09:03 - mmengine - INFO - Epoch(train) [1166][40/63] lr: 2.8356e-04 eta: 0:40:05 time: 0.8398 data_time: 0.0259 memory: 16201 loss_prob: 0.2691 loss_thr: 0.2075 loss_db: 0.0496 loss: 0.5261 2022/08/30 23:09:07 - mmengine - INFO - Epoch(train) [1166][45/63] lr: 2.8356e-04 eta: 0:40:05 time: 0.8568 data_time: 0.0335 memory: 16201 loss_prob: 0.2689 loss_thr: 0.2018 loss_db: 0.0490 loss: 0.5196 2022/08/30 23:09:11 - mmengine - INFO - Epoch(train) [1166][50/63] lr: 2.8356e-04 eta: 0:39:54 time: 0.8175 data_time: 0.0280 memory: 16201 loss_prob: 0.3047 loss_thr: 0.2171 loss_db: 0.0560 loss: 0.5777 2022/08/30 23:09:15 - mmengine - INFO - Epoch(train) [1166][55/63] lr: 2.8356e-04 eta: 0:39:54 time: 0.8391 data_time: 0.0290 memory: 16201 loss_prob: 0.3278 loss_thr: 0.2277 loss_db: 0.0595 loss: 0.6150 2022/08/30 23:09:20 - mmengine - INFO - Epoch(train) [1166][60/63] lr: 2.8356e-04 eta: 0:39:42 time: 0.8891 data_time: 0.0458 memory: 16201 loss_prob: 0.3409 loss_thr: 0.2335 loss_db: 0.0601 loss: 0.6345 2022/08/30 23:09:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:09:28 - mmengine - INFO - Epoch(train) [1167][5/63] lr: 2.7604e-04 eta: 0:39:42 time: 0.9947 data_time: 0.2089 memory: 16201 loss_prob: 0.2921 loss_thr: 0.2092 loss_db: 0.0512 loss: 0.5526 2022/08/30 23:09:32 - mmengine - INFO - Epoch(train) [1167][10/63] lr: 2.7604e-04 eta: 0:39:28 time: 1.0090 data_time: 0.2122 memory: 16201 loss_prob: 0.2867 loss_thr: 0.2046 loss_db: 0.0518 loss: 0.5431 2022/08/30 23:09:36 - mmengine - INFO - Epoch(train) [1167][15/63] lr: 2.7604e-04 eta: 0:39:28 time: 0.7894 data_time: 0.0246 memory: 16201 loss_prob: 0.3246 loss_thr: 0.2295 loss_db: 0.0581 loss: 0.6122 2022/08/30 23:09:40 - mmengine - INFO - Epoch(train) [1167][20/63] lr: 2.7604e-04 eta: 0:39:17 time: 0.7910 data_time: 0.0251 memory: 16201 loss_prob: 0.3347 loss_thr: 0.2264 loss_db: 0.0588 loss: 0.6199 2022/08/30 23:09:44 - mmengine - INFO - Epoch(train) [1167][25/63] lr: 2.7604e-04 eta: 0:39:17 time: 0.8240 data_time: 0.0298 memory: 16201 loss_prob: 0.3171 loss_thr: 0.2188 loss_db: 0.0567 loss: 0.5925 2022/08/30 23:09:48 - mmengine - INFO - Epoch(train) [1167][30/63] lr: 2.7604e-04 eta: 0:39:05 time: 0.8362 data_time: 0.0296 memory: 16201 loss_prob: 0.3253 loss_thr: 0.2356 loss_db: 0.0578 loss: 0.6187 2022/08/30 23:09:52 - mmengine - INFO - Epoch(train) [1167][35/63] lr: 2.7604e-04 eta: 0:39:05 time: 0.8317 data_time: 0.0280 memory: 16201 loss_prob: 0.3181 loss_thr: 0.2311 loss_db: 0.0557 loss: 0.6050 2022/08/30 23:09:57 - mmengine - INFO - Epoch(train) [1167][40/63] lr: 2.7604e-04 eta: 0:38:54 time: 0.8380 data_time: 0.0229 memory: 16201 loss_prob: 0.3125 loss_thr: 0.2237 loss_db: 0.0543 loss: 0.5905 2022/08/30 23:10:01 - mmengine - INFO - Epoch(train) [1167][45/63] lr: 2.7604e-04 eta: 0:38:54 time: 0.8392 data_time: 0.0259 memory: 16201 loss_prob: 0.2971 loss_thr: 0.2254 loss_db: 0.0522 loss: 0.5746 2022/08/30 23:10:05 - mmengine - INFO - Epoch(train) [1167][50/63] lr: 2.7604e-04 eta: 0:38:43 time: 0.8621 data_time: 0.0283 memory: 16201 loss_prob: 0.2996 loss_thr: 0.2261 loss_db: 0.0542 loss: 0.5799 2022/08/30 23:10:09 - mmengine - INFO - Epoch(train) [1167][55/63] lr: 2.7604e-04 eta: 0:38:43 time: 0.8553 data_time: 0.0302 memory: 16201 loss_prob: 0.3057 loss_thr: 0.2136 loss_db: 0.0549 loss: 0.5743 2022/08/30 23:10:13 - mmengine - INFO - Epoch(train) [1167][60/63] lr: 2.7604e-04 eta: 0:38:32 time: 0.8169 data_time: 0.0307 memory: 16201 loss_prob: 0.2959 loss_thr: 0.2110 loss_db: 0.0530 loss: 0.5599 2022/08/30 23:10:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:10:22 - mmengine - INFO - Epoch(train) [1168][5/63] lr: 2.6850e-04 eta: 0:38:32 time: 0.9808 data_time: 0.2349 memory: 16201 loss_prob: 0.2988 loss_thr: 0.2038 loss_db: 0.0535 loss: 0.5561 2022/08/30 23:10:26 - mmengine - INFO - Epoch(train) [1168][10/63] lr: 2.6850e-04 eta: 0:38:17 time: 1.0241 data_time: 0.2446 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2171 loss_db: 0.0554 loss: 0.5849 2022/08/30 23:10:30 - mmengine - INFO - Epoch(train) [1168][15/63] lr: 2.6850e-04 eta: 0:38:17 time: 0.8292 data_time: 0.0324 memory: 16201 loss_prob: 0.3170 loss_thr: 0.2289 loss_db: 0.0555 loss: 0.6014 2022/08/30 23:10:35 - mmengine - INFO - Epoch(train) [1168][20/63] lr: 2.6850e-04 eta: 0:38:06 time: 0.8645 data_time: 0.0200 memory: 16201 loss_prob: 0.3324 loss_thr: 0.2360 loss_db: 0.0588 loss: 0.6272 2022/08/30 23:10:39 - mmengine - INFO - Epoch(train) [1168][25/63] lr: 2.6850e-04 eta: 0:38:06 time: 0.8994 data_time: 0.0379 memory: 16201 loss_prob: 0.3419 loss_thr: 0.2265 loss_db: 0.0616 loss: 0.6299 2022/08/30 23:10:43 - mmengine - INFO - Epoch(train) [1168][30/63] lr: 2.6850e-04 eta: 0:37:55 time: 0.8544 data_time: 0.0275 memory: 16201 loss_prob: 0.3201 loss_thr: 0.2128 loss_db: 0.0583 loss: 0.5911 2022/08/30 23:10:47 - mmengine - INFO - Epoch(train) [1168][35/63] lr: 2.6850e-04 eta: 0:37:55 time: 0.8225 data_time: 0.0234 memory: 16201 loss_prob: 0.3198 loss_thr: 0.2251 loss_db: 0.0572 loss: 0.6021 2022/08/30 23:10:51 - mmengine - INFO - Epoch(train) [1168][40/63] lr: 2.6850e-04 eta: 0:37:44 time: 0.8100 data_time: 0.0312 memory: 16201 loss_prob: 0.3148 loss_thr: 0.2249 loss_db: 0.0555 loss: 0.5951 2022/08/30 23:10:56 - mmengine - INFO - Epoch(train) [1168][45/63] lr: 2.6850e-04 eta: 0:37:44 time: 0.8658 data_time: 0.0249 memory: 16201 loss_prob: 0.2656 loss_thr: 0.1956 loss_db: 0.0482 loss: 0.5093 2022/08/30 23:11:00 - mmengine - INFO - Epoch(train) [1168][50/63] lr: 2.6850e-04 eta: 0:37:33 time: 0.8615 data_time: 0.0275 memory: 16201 loss_prob: 0.2939 loss_thr: 0.2121 loss_db: 0.0530 loss: 0.5591 2022/08/30 23:11:04 - mmengine - INFO - Epoch(train) [1168][55/63] lr: 2.6850e-04 eta: 0:37:33 time: 0.8002 data_time: 0.0307 memory: 16201 loss_prob: 0.3171 loss_thr: 0.2267 loss_db: 0.0567 loss: 0.6004 2022/08/30 23:11:08 - mmengine - INFO - Epoch(train) [1168][60/63] lr: 2.6850e-04 eta: 0:37:21 time: 0.8237 data_time: 0.0281 memory: 16201 loss_prob: 0.3132 loss_thr: 0.2365 loss_db: 0.0567 loss: 0.6064 2022/08/30 23:11:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:11:16 - mmengine - INFO - Epoch(train) [1169][5/63] lr: 2.6094e-04 eta: 0:37:21 time: 1.0086 data_time: 0.2105 memory: 16201 loss_prob: 0.3005 loss_thr: 0.2228 loss_db: 0.0538 loss: 0.5771 2022/08/30 23:11:21 - mmengine - INFO - Epoch(train) [1169][10/63] lr: 2.6094e-04 eta: 0:37:07 time: 1.1082 data_time: 0.2302 memory: 16201 loss_prob: 0.2905 loss_thr: 0.2081 loss_db: 0.0540 loss: 0.5526 2022/08/30 23:11:25 - mmengine - INFO - Epoch(train) [1169][15/63] lr: 2.6094e-04 eta: 0:37:07 time: 0.8829 data_time: 0.0308 memory: 16201 loss_prob: 0.2952 loss_thr: 0.2042 loss_db: 0.0534 loss: 0.5529 2022/08/30 23:11:29 - mmengine - INFO - Epoch(train) [1169][20/63] lr: 2.6094e-04 eta: 0:36:56 time: 0.8206 data_time: 0.0249 memory: 16201 loss_prob: 0.3063 loss_thr: 0.2100 loss_db: 0.0536 loss: 0.5700 2022/08/30 23:11:33 - mmengine - INFO - Epoch(train) [1169][25/63] lr: 2.6094e-04 eta: 0:36:56 time: 0.8071 data_time: 0.0359 memory: 16201 loss_prob: 0.3260 loss_thr: 0.2270 loss_db: 0.0579 loss: 0.6109 2022/08/30 23:11:38 - mmengine - INFO - Epoch(train) [1169][30/63] lr: 2.6094e-04 eta: 0:36:45 time: 0.8571 data_time: 0.0268 memory: 16201 loss_prob: 0.3233 loss_thr: 0.2315 loss_db: 0.0573 loss: 0.6121 2022/08/30 23:11:42 - mmengine - INFO - Epoch(train) [1169][35/63] lr: 2.6094e-04 eta: 0:36:45 time: 0.8602 data_time: 0.0252 memory: 16201 loss_prob: 0.3108 loss_thr: 0.2234 loss_db: 0.0565 loss: 0.5907 2022/08/30 23:11:46 - mmengine - INFO - Epoch(train) [1169][40/63] lr: 2.6094e-04 eta: 0:36:33 time: 0.8186 data_time: 0.0281 memory: 16201 loss_prob: 0.3247 loss_thr: 0.2253 loss_db: 0.0578 loss: 0.6078 2022/08/30 23:11:50 - mmengine - INFO - Epoch(train) [1169][45/63] lr: 2.6094e-04 eta: 0:36:33 time: 0.8255 data_time: 0.0285 memory: 16201 loss_prob: 0.3084 loss_thr: 0.2174 loss_db: 0.0545 loss: 0.5804 2022/08/30 23:11:55 - mmengine - INFO - Epoch(train) [1169][50/63] lr: 2.6094e-04 eta: 0:36:22 time: 0.8842 data_time: 0.0330 memory: 16201 loss_prob: 0.3112 loss_thr: 0.2221 loss_db: 0.0566 loss: 0.5899 2022/08/30 23:11:59 - mmengine - INFO - Epoch(train) [1169][55/63] lr: 2.6094e-04 eta: 0:36:22 time: 0.9019 data_time: 0.0285 memory: 16201 loss_prob: 0.3282 loss_thr: 0.2343 loss_db: 0.0593 loss: 0.6217 2022/08/30 23:12:04 - mmengine - INFO - Epoch(train) [1169][60/63] lr: 2.6094e-04 eta: 0:36:11 time: 0.8555 data_time: 0.0303 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2325 loss_db: 0.0590 loss: 0.6204 2022/08/30 23:12:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:12:12 - mmengine - INFO - Epoch(train) [1170][5/63] lr: 2.5336e-04 eta: 0:36:11 time: 0.9837 data_time: 0.1972 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2264 loss_db: 0.0577 loss: 0.6056 2022/08/30 23:12:16 - mmengine - INFO - Epoch(train) [1170][10/63] lr: 2.5336e-04 eta: 0:35:56 time: 1.0229 data_time: 0.2126 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2147 loss_db: 0.0532 loss: 0.5727 2022/08/30 23:12:20 - mmengine - INFO - Epoch(train) [1170][15/63] lr: 2.5336e-04 eta: 0:35:56 time: 0.8448 data_time: 0.0329 memory: 16201 loss_prob: 0.3026 loss_thr: 0.2145 loss_db: 0.0533 loss: 0.5705 2022/08/30 23:12:24 - mmengine - INFO - Epoch(train) [1170][20/63] lr: 2.5336e-04 eta: 0:35:45 time: 0.8403 data_time: 0.0233 memory: 16201 loss_prob: 0.2976 loss_thr: 0.2098 loss_db: 0.0520 loss: 0.5594 2022/08/30 23:12:28 - mmengine - INFO - Epoch(train) [1170][25/63] lr: 2.5336e-04 eta: 0:35:45 time: 0.8251 data_time: 0.0320 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2193 loss_db: 0.0548 loss: 0.5856 2022/08/30 23:12:32 - mmengine - INFO - Epoch(train) [1170][30/63] lr: 2.5336e-04 eta: 0:35:34 time: 0.8088 data_time: 0.0326 memory: 16201 loss_prob: 0.3416 loss_thr: 0.2428 loss_db: 0.0608 loss: 0.6452 2022/08/30 23:12:37 - mmengine - INFO - Epoch(train) [1170][35/63] lr: 2.5336e-04 eta: 0:35:34 time: 0.8507 data_time: 0.0273 memory: 16201 loss_prob: 0.3316 loss_thr: 0.2426 loss_db: 0.0594 loss: 0.6336 2022/08/30 23:12:41 - mmengine - INFO - Epoch(train) [1170][40/63] lr: 2.5336e-04 eta: 0:35:23 time: 0.8762 data_time: 0.0302 memory: 16201 loss_prob: 0.3092 loss_thr: 0.2290 loss_db: 0.0560 loss: 0.5941 2022/08/30 23:12:45 - mmengine - INFO - Epoch(train) [1170][45/63] lr: 2.5336e-04 eta: 0:35:23 time: 0.8201 data_time: 0.0271 memory: 16201 loss_prob: 0.3116 loss_thr: 0.2209 loss_db: 0.0554 loss: 0.5878 2022/08/30 23:12:49 - mmengine - INFO - Epoch(train) [1170][50/63] lr: 2.5336e-04 eta: 0:35:12 time: 0.8249 data_time: 0.0287 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2244 loss_db: 0.0561 loss: 0.6019 2022/08/30 23:12:53 - mmengine - INFO - Epoch(train) [1170][55/63] lr: 2.5336e-04 eta: 0:35:12 time: 0.8264 data_time: 0.0328 memory: 16201 loss_prob: 0.3113 loss_thr: 0.2195 loss_db: 0.0543 loss: 0.5851 2022/08/30 23:12:58 - mmengine - INFO - Epoch(train) [1170][60/63] lr: 2.5336e-04 eta: 0:35:01 time: 0.9095 data_time: 0.0301 memory: 16201 loss_prob: 0.3256 loss_thr: 0.2268 loss_db: 0.0580 loss: 0.6105 2022/08/30 23:13:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:13:06 - mmengine - INFO - Epoch(train) [1171][5/63] lr: 2.4575e-04 eta: 0:35:01 time: 0.9459 data_time: 0.1817 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2296 loss_db: 0.0592 loss: 0.6180 2022/08/30 23:13:10 - mmengine - INFO - Epoch(train) [1171][10/63] lr: 2.4575e-04 eta: 0:34:46 time: 0.9796 data_time: 0.1890 memory: 16201 loss_prob: 0.3195 loss_thr: 0.2263 loss_db: 0.0556 loss: 0.6014 2022/08/30 23:13:15 - mmengine - INFO - Epoch(train) [1171][15/63] lr: 2.4575e-04 eta: 0:34:46 time: 0.8733 data_time: 0.0350 memory: 16201 loss_prob: 0.3196 loss_thr: 0.2296 loss_db: 0.0561 loss: 0.6052 2022/08/30 23:13:19 - mmengine - INFO - Epoch(train) [1171][20/63] lr: 2.4575e-04 eta: 0:34:35 time: 0.8879 data_time: 0.0331 memory: 16201 loss_prob: 0.2792 loss_thr: 0.2029 loss_db: 0.0502 loss: 0.5322 2022/08/30 23:13:23 - mmengine - INFO - Epoch(train) [1171][25/63] lr: 2.4575e-04 eta: 0:34:35 time: 0.8403 data_time: 0.0335 memory: 16201 loss_prob: 0.2749 loss_thr: 0.2007 loss_db: 0.0492 loss: 0.5248 2022/08/30 23:13:28 - mmengine - INFO - Epoch(train) [1171][30/63] lr: 2.4575e-04 eta: 0:34:24 time: 0.9204 data_time: 0.0481 memory: 16201 loss_prob: 0.2986 loss_thr: 0.2188 loss_db: 0.0531 loss: 0.5704 2022/08/30 23:13:33 - mmengine - INFO - Epoch(train) [1171][35/63] lr: 2.4575e-04 eta: 0:34:24 time: 0.9119 data_time: 0.0421 memory: 16201 loss_prob: 0.2746 loss_thr: 0.2030 loss_db: 0.0486 loss: 0.5262 2022/08/30 23:13:37 - mmengine - INFO - Epoch(train) [1171][40/63] lr: 2.4575e-04 eta: 0:34:13 time: 0.8097 data_time: 0.0272 memory: 16201 loss_prob: 0.2769 loss_thr: 0.2017 loss_db: 0.0498 loss: 0.5283 2022/08/30 23:13:41 - mmengine - INFO - Epoch(train) [1171][45/63] lr: 2.4575e-04 eta: 0:34:13 time: 0.8149 data_time: 0.0274 memory: 16201 loss_prob: 0.3181 loss_thr: 0.2207 loss_db: 0.0571 loss: 0.5959 2022/08/30 23:13:46 - mmengine - INFO - Epoch(train) [1171][50/63] lr: 2.4575e-04 eta: 0:34:01 time: 0.9171 data_time: 0.0297 memory: 16201 loss_prob: 0.3706 loss_thr: 0.2495 loss_db: 0.0653 loss: 0.6854 2022/08/30 23:13:50 - mmengine - INFO - Epoch(train) [1171][55/63] lr: 2.4575e-04 eta: 0:34:01 time: 0.9199 data_time: 0.0383 memory: 16201 loss_prob: 0.3530 loss_thr: 0.2433 loss_db: 0.0627 loss: 0.6590 2022/08/30 23:13:54 - mmengine - INFO - Epoch(train) [1171][60/63] lr: 2.4575e-04 eta: 0:33:50 time: 0.8182 data_time: 0.0323 memory: 16201 loss_prob: 0.2964 loss_thr: 0.2195 loss_db: 0.0537 loss: 0.5697 2022/08/30 23:13:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:14:02 - mmengine - INFO - Epoch(train) [1172][5/63] lr: 2.3811e-04 eta: 0:33:50 time: 0.9672 data_time: 0.2018 memory: 16201 loss_prob: 0.2858 loss_thr: 0.2161 loss_db: 0.0513 loss: 0.5531 2022/08/30 23:14:06 - mmengine - INFO - Epoch(train) [1172][10/63] lr: 2.3811e-04 eta: 0:33:36 time: 1.0116 data_time: 0.2066 memory: 16201 loss_prob: 0.3141 loss_thr: 0.2190 loss_db: 0.0566 loss: 0.5898 2022/08/30 23:14:10 - mmengine - INFO - Epoch(train) [1172][15/63] lr: 2.3811e-04 eta: 0:33:36 time: 0.8325 data_time: 0.0298 memory: 16201 loss_prob: 0.2980 loss_thr: 0.2132 loss_db: 0.0543 loss: 0.5655 2022/08/30 23:14:15 - mmengine - INFO - Epoch(train) [1172][20/63] lr: 2.3811e-04 eta: 0:33:25 time: 0.8551 data_time: 0.0267 memory: 16201 loss_prob: 0.2726 loss_thr: 0.1934 loss_db: 0.0497 loss: 0.5157 2022/08/30 23:14:19 - mmengine - INFO - Epoch(train) [1172][25/63] lr: 2.3811e-04 eta: 0:33:25 time: 0.8659 data_time: 0.0384 memory: 16201 loss_prob: 0.2846 loss_thr: 0.2008 loss_db: 0.0515 loss: 0.5369 2022/08/30 23:14:23 - mmengine - INFO - Epoch(train) [1172][30/63] lr: 2.3811e-04 eta: 0:33:13 time: 0.8418 data_time: 0.0341 memory: 16201 loss_prob: 0.3049 loss_thr: 0.2178 loss_db: 0.0554 loss: 0.5780 2022/08/30 23:14:27 - mmengine - INFO - Epoch(train) [1172][35/63] lr: 2.3811e-04 eta: 0:33:13 time: 0.8347 data_time: 0.0245 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2220 loss_db: 0.0551 loss: 0.5857 2022/08/30 23:14:31 - mmengine - INFO - Epoch(train) [1172][40/63] lr: 2.3811e-04 eta: 0:33:02 time: 0.8348 data_time: 0.0268 memory: 16201 loss_prob: 0.3084 loss_thr: 0.2226 loss_db: 0.0545 loss: 0.5855 2022/08/30 23:14:37 - mmengine - INFO - Epoch(train) [1172][45/63] lr: 2.3811e-04 eta: 0:33:02 time: 0.9678 data_time: 0.0410 memory: 16201 loss_prob: 0.2768 loss_thr: 0.2041 loss_db: 0.0495 loss: 0.5304 2022/08/30 23:14:41 - mmengine - INFO - Epoch(train) [1172][50/63] lr: 2.3811e-04 eta: 0:32:51 time: 0.9464 data_time: 0.0381 memory: 16201 loss_prob: 0.2628 loss_thr: 0.1922 loss_db: 0.0461 loss: 0.5012 2022/08/30 23:14:45 - mmengine - INFO - Epoch(train) [1172][55/63] lr: 2.3811e-04 eta: 0:32:51 time: 0.8061 data_time: 0.0257 memory: 16201 loss_prob: 0.2954 loss_thr: 0.2089 loss_db: 0.0526 loss: 0.5568 2022/08/30 23:14:50 - mmengine - INFO - Epoch(train) [1172][60/63] lr: 2.3811e-04 eta: 0:32:40 time: 0.8627 data_time: 0.0445 memory: 16201 loss_prob: 0.3312 loss_thr: 0.2241 loss_db: 0.0599 loss: 0.6152 2022/08/30 23:14:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:14:58 - mmengine - INFO - Epoch(train) [1173][5/63] lr: 2.3045e-04 eta: 0:32:40 time: 1.0247 data_time: 0.2229 memory: 16201 loss_prob: 0.3404 loss_thr: 0.2377 loss_db: 0.0610 loss: 0.6391 2022/08/30 23:15:02 - mmengine - INFO - Epoch(train) [1173][10/63] lr: 2.3045e-04 eta: 0:32:25 time: 1.0631 data_time: 0.2259 memory: 16201 loss_prob: 0.2733 loss_thr: 0.2026 loss_db: 0.0489 loss: 0.5248 2022/08/30 23:15:07 - mmengine - INFO - Epoch(train) [1173][15/63] lr: 2.3045e-04 eta: 0:32:25 time: 0.8568 data_time: 0.0277 memory: 16201 loss_prob: 0.2592 loss_thr: 0.1930 loss_db: 0.0470 loss: 0.4992 2022/08/30 23:15:11 - mmengine - INFO - Epoch(train) [1173][20/63] lr: 2.3045e-04 eta: 0:32:14 time: 0.8312 data_time: 0.0208 memory: 16201 loss_prob: 0.3043 loss_thr: 0.2126 loss_db: 0.0546 loss: 0.5715 2022/08/30 23:15:15 - mmengine - INFO - Epoch(train) [1173][25/63] lr: 2.3045e-04 eta: 0:32:14 time: 0.8274 data_time: 0.0398 memory: 16201 loss_prob: 0.3182 loss_thr: 0.2259 loss_db: 0.0560 loss: 0.6001 2022/08/30 23:15:19 - mmengine - INFO - Epoch(train) [1173][30/63] lr: 2.3045e-04 eta: 0:32:03 time: 0.8332 data_time: 0.0291 memory: 16201 loss_prob: 0.3088 loss_thr: 0.2241 loss_db: 0.0552 loss: 0.5880 2022/08/30 23:15:23 - mmengine - INFO - Epoch(train) [1173][35/63] lr: 2.3045e-04 eta: 0:32:03 time: 0.8130 data_time: 0.0197 memory: 16201 loss_prob: 0.3044 loss_thr: 0.2204 loss_db: 0.0547 loss: 0.5795 2022/08/30 23:15:28 - mmengine - INFO - Epoch(train) [1173][40/63] lr: 2.3045e-04 eta: 0:31:52 time: 0.8642 data_time: 0.0311 memory: 16201 loss_prob: 0.2825 loss_thr: 0.2069 loss_db: 0.0497 loss: 0.5391 2022/08/30 23:15:32 - mmengine - INFO - Epoch(train) [1173][45/63] lr: 2.3045e-04 eta: 0:31:52 time: 0.8826 data_time: 0.0307 memory: 16201 loss_prob: 0.3370 loss_thr: 0.2379 loss_db: 0.0593 loss: 0.6341 2022/08/30 23:15:36 - mmengine - INFO - Epoch(train) [1173][50/63] lr: 2.3045e-04 eta: 0:31:41 time: 0.8781 data_time: 0.0616 memory: 16201 loss_prob: 0.3669 loss_thr: 0.2543 loss_db: 0.0650 loss: 0.6862 2022/08/30 23:15:41 - mmengine - INFO - Epoch(train) [1173][55/63] lr: 2.3045e-04 eta: 0:31:41 time: 0.8675 data_time: 0.0561 memory: 16201 loss_prob: 0.3535 loss_thr: 0.2428 loss_db: 0.0631 loss: 0.6595 2022/08/30 23:15:45 - mmengine - INFO - Epoch(train) [1173][60/63] lr: 2.3045e-04 eta: 0:31:30 time: 0.8427 data_time: 0.0251 memory: 16201 loss_prob: 0.3693 loss_thr: 0.2408 loss_db: 0.0634 loss: 0.6735 2022/08/30 23:15:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:15:53 - mmengine - INFO - Epoch(train) [1174][5/63] lr: 2.2275e-04 eta: 0:31:30 time: 0.9882 data_time: 0.1973 memory: 16201 loss_prob: 0.3361 loss_thr: 0.2272 loss_db: 0.0602 loss: 0.6234 2022/08/30 23:15:57 - mmengine - INFO - Epoch(train) [1174][10/63] lr: 2.2275e-04 eta: 0:31:15 time: 1.0116 data_time: 0.2120 memory: 16201 loss_prob: 0.2939 loss_thr: 0.2074 loss_db: 0.0524 loss: 0.5537 2022/08/30 23:16:01 - mmengine - INFO - Epoch(train) [1174][15/63] lr: 2.2275e-04 eta: 0:31:15 time: 0.8298 data_time: 0.0306 memory: 16201 loss_prob: 0.2802 loss_thr: 0.1994 loss_db: 0.0496 loss: 0.5292 2022/08/30 23:16:06 - mmengine - INFO - Epoch(train) [1174][20/63] lr: 2.2275e-04 eta: 0:31:04 time: 0.8542 data_time: 0.0308 memory: 16201 loss_prob: 0.2901 loss_thr: 0.2066 loss_db: 0.0516 loss: 0.5483 2022/08/30 23:16:10 - mmengine - INFO - Epoch(train) [1174][25/63] lr: 2.2275e-04 eta: 0:31:04 time: 0.8410 data_time: 0.0358 memory: 16201 loss_prob: 0.2941 loss_thr: 0.2138 loss_db: 0.0538 loss: 0.5617 2022/08/30 23:16:14 - mmengine - INFO - Epoch(train) [1174][30/63] lr: 2.2275e-04 eta: 0:30:53 time: 0.8005 data_time: 0.0249 memory: 16201 loss_prob: 0.2959 loss_thr: 0.2129 loss_db: 0.0541 loss: 0.5628 2022/08/30 23:16:18 - mmengine - INFO - Epoch(train) [1174][35/63] lr: 2.2275e-04 eta: 0:30:53 time: 0.7964 data_time: 0.0221 memory: 16201 loss_prob: 0.3073 loss_thr: 0.2204 loss_db: 0.0553 loss: 0.5830 2022/08/30 23:16:22 - mmengine - INFO - Epoch(train) [1174][40/63] lr: 2.2275e-04 eta: 0:30:42 time: 0.8004 data_time: 0.0240 memory: 16201 loss_prob: 0.3583 loss_thr: 0.2506 loss_db: 0.0643 loss: 0.6732 2022/08/30 23:16:26 - mmengine - INFO - Epoch(train) [1174][45/63] lr: 2.2275e-04 eta: 0:30:42 time: 0.8271 data_time: 0.0329 memory: 16201 loss_prob: 0.3696 loss_thr: 0.2426 loss_db: 0.0663 loss: 0.6785 2022/08/30 23:16:30 - mmengine - INFO - Epoch(train) [1174][50/63] lr: 2.2275e-04 eta: 0:30:31 time: 0.8277 data_time: 0.0303 memory: 16201 loss_prob: 0.3383 loss_thr: 0.2283 loss_db: 0.0612 loss: 0.6278 2022/08/30 23:16:34 - mmengine - INFO - Epoch(train) [1174][55/63] lr: 2.2275e-04 eta: 0:30:31 time: 0.8323 data_time: 0.0254 memory: 16201 loss_prob: 0.3120 loss_thr: 0.2314 loss_db: 0.0560 loss: 0.5995 2022/08/30 23:16:39 - mmengine - INFO - Epoch(train) [1174][60/63] lr: 2.2275e-04 eta: 0:30:19 time: 0.9375 data_time: 0.0408 memory: 16201 loss_prob: 0.3025 loss_thr: 0.2203 loss_db: 0.0532 loss: 0.5759 2022/08/30 23:16:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:16:47 - mmengine - INFO - Epoch(train) [1175][5/63] lr: 2.1503e-04 eta: 0:30:19 time: 0.9632 data_time: 0.1963 memory: 16201 loss_prob: 0.2843 loss_thr: 0.2116 loss_db: 0.0518 loss: 0.5477 2022/08/30 23:16:51 - mmengine - INFO - Epoch(train) [1175][10/63] lr: 2.1503e-04 eta: 0:30:05 time: 1.0122 data_time: 0.2053 memory: 16201 loss_prob: 0.2691 loss_thr: 0.1972 loss_db: 0.0499 loss: 0.5162 2022/08/30 23:16:56 - mmengine - INFO - Epoch(train) [1175][15/63] lr: 2.1503e-04 eta: 0:30:05 time: 0.8721 data_time: 0.0257 memory: 16201 loss_prob: 0.3060 loss_thr: 0.2169 loss_db: 0.0556 loss: 0.5785 2022/08/30 23:17:00 - mmengine - INFO - Epoch(train) [1175][20/63] lr: 2.1503e-04 eta: 0:29:54 time: 0.8564 data_time: 0.0265 memory: 16201 loss_prob: 0.3444 loss_thr: 0.2374 loss_db: 0.0603 loss: 0.6421 2022/08/30 23:17:04 - mmengine - INFO - Epoch(train) [1175][25/63] lr: 2.1503e-04 eta: 0:29:54 time: 0.7987 data_time: 0.0265 memory: 16201 loss_prob: 0.3298 loss_thr: 0.2260 loss_db: 0.0576 loss: 0.6134 2022/08/30 23:17:08 - mmengine - INFO - Epoch(train) [1175][30/63] lr: 2.1503e-04 eta: 0:29:43 time: 0.8072 data_time: 0.0251 memory: 16201 loss_prob: 0.3359 loss_thr: 0.2281 loss_db: 0.0599 loss: 0.6239 2022/08/30 23:17:12 - mmengine - INFO - Epoch(train) [1175][35/63] lr: 2.1503e-04 eta: 0:29:43 time: 0.8342 data_time: 0.0272 memory: 16201 loss_prob: 0.3161 loss_thr: 0.2180 loss_db: 0.0571 loss: 0.5912 2022/08/30 23:17:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:17:17 - mmengine - INFO - Epoch(train) [1175][40/63] lr: 2.1503e-04 eta: 0:29:31 time: 0.8439 data_time: 0.0303 memory: 16201 loss_prob: 0.2711 loss_thr: 0.2125 loss_db: 0.0486 loss: 0.5322 2022/08/30 23:17:21 - mmengine - INFO - Epoch(train) [1175][45/63] lr: 2.1503e-04 eta: 0:29:31 time: 0.8326 data_time: 0.0346 memory: 16201 loss_prob: 0.2717 loss_thr: 0.2119 loss_db: 0.0490 loss: 0.5326 2022/08/30 23:17:25 - mmengine - INFO - Epoch(train) [1175][50/63] lr: 2.1503e-04 eta: 0:29:20 time: 0.8362 data_time: 0.0252 memory: 16201 loss_prob: 0.2947 loss_thr: 0.2108 loss_db: 0.0531 loss: 0.5586 2022/08/30 23:17:29 - mmengine - INFO - Epoch(train) [1175][55/63] lr: 2.1503e-04 eta: 0:29:20 time: 0.8384 data_time: 0.0312 memory: 16201 loss_prob: 0.2950 loss_thr: 0.2156 loss_db: 0.0534 loss: 0.5640 2022/08/30 23:17:33 - mmengine - INFO - Epoch(train) [1175][60/63] lr: 2.1503e-04 eta: 0:29:09 time: 0.8270 data_time: 0.0393 memory: 16201 loss_prob: 0.2704 loss_thr: 0.1978 loss_db: 0.0494 loss: 0.5175 2022/08/30 23:17:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:17:42 - mmengine - INFO - Epoch(train) [1176][5/63] lr: 2.0728e-04 eta: 0:29:09 time: 1.0267 data_time: 0.2043 memory: 16201 loss_prob: 0.2621 loss_thr: 0.1947 loss_db: 0.0480 loss: 0.5048 2022/08/30 23:17:46 - mmengine - INFO - Epoch(train) [1176][10/63] lr: 2.0728e-04 eta: 0:28:55 time: 1.0007 data_time: 0.2181 memory: 16201 loss_prob: 0.3066 loss_thr: 0.2154 loss_db: 0.0566 loss: 0.5786 2022/08/30 23:17:50 - mmengine - INFO - Epoch(train) [1176][15/63] lr: 2.0728e-04 eta: 0:28:55 time: 0.8149 data_time: 0.0296 memory: 16201 loss_prob: 0.2916 loss_thr: 0.2030 loss_db: 0.0528 loss: 0.5474 2022/08/30 23:17:54 - mmengine - INFO - Epoch(train) [1176][20/63] lr: 2.0728e-04 eta: 0:28:44 time: 0.8357 data_time: 0.0279 memory: 16201 loss_prob: 0.2828 loss_thr: 0.1994 loss_db: 0.0493 loss: 0.5315 2022/08/30 23:17:59 - mmengine - INFO - Epoch(train) [1176][25/63] lr: 2.0728e-04 eta: 0:28:44 time: 0.8604 data_time: 0.0362 memory: 16201 loss_prob: 0.3437 loss_thr: 0.2388 loss_db: 0.0600 loss: 0.6425 2022/08/30 23:18:03 - mmengine - INFO - Epoch(train) [1176][30/63] lr: 2.0728e-04 eta: 0:28:32 time: 0.8382 data_time: 0.0288 memory: 16201 loss_prob: 0.3519 loss_thr: 0.2460 loss_db: 0.0629 loss: 0.6608 2022/08/30 23:18:07 - mmengine - INFO - Epoch(train) [1176][35/63] lr: 2.0728e-04 eta: 0:28:32 time: 0.8172 data_time: 0.0317 memory: 16201 loss_prob: 0.3101 loss_thr: 0.2215 loss_db: 0.0558 loss: 0.5873 2022/08/30 23:18:11 - mmengine - INFO - Epoch(train) [1176][40/63] lr: 2.0728e-04 eta: 0:28:21 time: 0.8003 data_time: 0.0295 memory: 16201 loss_prob: 0.3049 loss_thr: 0.2194 loss_db: 0.0543 loss: 0.5785 2022/08/30 23:18:15 - mmengine - INFO - Epoch(train) [1176][45/63] lr: 2.0728e-04 eta: 0:28:21 time: 0.8069 data_time: 0.0247 memory: 16201 loss_prob: 0.2925 loss_thr: 0.2257 loss_db: 0.0521 loss: 0.5704 2022/08/30 23:18:19 - mmengine - INFO - Epoch(train) [1176][50/63] lr: 2.0728e-04 eta: 0:28:10 time: 0.8373 data_time: 0.0273 memory: 16201 loss_prob: 0.2968 loss_thr: 0.2236 loss_db: 0.0528 loss: 0.5732 2022/08/30 23:18:23 - mmengine - INFO - Epoch(train) [1176][55/63] lr: 2.0728e-04 eta: 0:28:10 time: 0.8336 data_time: 0.0273 memory: 16201 loss_prob: 0.2930 loss_thr: 0.2045 loss_db: 0.0520 loss: 0.5496 2022/08/30 23:18:27 - mmengine - INFO - Epoch(train) [1176][60/63] lr: 2.0728e-04 eta: 0:27:59 time: 0.8467 data_time: 0.0310 memory: 16201 loss_prob: 0.2792 loss_thr: 0.2043 loss_db: 0.0503 loss: 0.5338 2022/08/30 23:18:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:18:36 - mmengine - INFO - Epoch(train) [1177][5/63] lr: 1.9949e-04 eta: 0:27:59 time: 0.9998 data_time: 0.2327 memory: 16201 loss_prob: 0.2985 loss_thr: 0.2202 loss_db: 0.0560 loss: 0.5746 2022/08/30 23:18:40 - mmengine - INFO - Epoch(train) [1177][10/63] lr: 1.9949e-04 eta: 0:27:44 time: 1.0435 data_time: 0.2444 memory: 16201 loss_prob: 0.3142 loss_thr: 0.2265 loss_db: 0.0576 loss: 0.5982 2022/08/30 23:18:44 - mmengine - INFO - Epoch(train) [1177][15/63] lr: 1.9949e-04 eta: 0:27:44 time: 0.8042 data_time: 0.0279 memory: 16201 loss_prob: 0.3129 loss_thr: 0.2205 loss_db: 0.0561 loss: 0.5895 2022/08/30 23:18:48 - mmengine - INFO - Epoch(train) [1177][20/63] lr: 1.9949e-04 eta: 0:27:33 time: 0.8053 data_time: 0.0232 memory: 16201 loss_prob: 0.3101 loss_thr: 0.2202 loss_db: 0.0562 loss: 0.5864 2022/08/30 23:18:52 - mmengine - INFO - Epoch(train) [1177][25/63] lr: 1.9949e-04 eta: 0:27:33 time: 0.8293 data_time: 0.0374 memory: 16201 loss_prob: 0.3404 loss_thr: 0.2358 loss_db: 0.0608 loss: 0.6370 2022/08/30 23:18:57 - mmengine - INFO - Epoch(train) [1177][30/63] lr: 1.9949e-04 eta: 0:27:22 time: 0.8711 data_time: 0.0284 memory: 16201 loss_prob: 0.3287 loss_thr: 0.2186 loss_db: 0.0578 loss: 0.6051 2022/08/30 23:19:01 - mmengine - INFO - Epoch(train) [1177][35/63] lr: 1.9949e-04 eta: 0:27:22 time: 0.8715 data_time: 0.0289 memory: 16201 loss_prob: 0.3057 loss_thr: 0.2114 loss_db: 0.0544 loss: 0.5716 2022/08/30 23:19:05 - mmengine - INFO - Epoch(train) [1177][40/63] lr: 1.9949e-04 eta: 0:27:11 time: 0.8763 data_time: 0.0744 memory: 16201 loss_prob: 0.2939 loss_thr: 0.2106 loss_db: 0.0522 loss: 0.5567 2022/08/30 23:19:10 - mmengine - INFO - Epoch(train) [1177][45/63] lr: 1.9949e-04 eta: 0:27:11 time: 0.8977 data_time: 0.0818 memory: 16201 loss_prob: 0.3308 loss_thr: 0.2245 loss_db: 0.0585 loss: 0.6138 2022/08/30 23:19:14 - mmengine - INFO - Epoch(train) [1177][50/63] lr: 1.9949e-04 eta: 0:27:00 time: 0.8677 data_time: 0.0584 memory: 16201 loss_prob: 0.3572 loss_thr: 0.2397 loss_db: 0.0612 loss: 0.6581 2022/08/30 23:19:19 - mmengine - INFO - Epoch(train) [1177][55/63] lr: 1.9949e-04 eta: 0:27:00 time: 0.9333 data_time: 0.0723 memory: 16201 loss_prob: 0.3005 loss_thr: 0.2152 loss_db: 0.0509 loss: 0.5666 2022/08/30 23:19:23 - mmengine - INFO - Epoch(train) [1177][60/63] lr: 1.9949e-04 eta: 0:26:49 time: 0.9185 data_time: 0.0660 memory: 16201 loss_prob: 0.2880 loss_thr: 0.2090 loss_db: 0.0520 loss: 0.5489 2022/08/30 23:19:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:19:32 - mmengine - INFO - Epoch(train) [1178][5/63] lr: 1.9167e-04 eta: 0:26:49 time: 1.0161 data_time: 0.2522 memory: 16201 loss_prob: 0.3025 loss_thr: 0.2129 loss_db: 0.0550 loss: 0.5703 2022/08/30 23:19:37 - mmengine - INFO - Epoch(train) [1178][10/63] lr: 1.9167e-04 eta: 0:26:34 time: 1.1092 data_time: 0.2981 memory: 16201 loss_prob: 0.3191 loss_thr: 0.2186 loss_db: 0.0570 loss: 0.5947 2022/08/30 23:19:41 - mmengine - INFO - Epoch(train) [1178][15/63] lr: 1.9167e-04 eta: 0:26:34 time: 0.8803 data_time: 0.0783 memory: 16201 loss_prob: 0.3018 loss_thr: 0.2148 loss_db: 0.0534 loss: 0.5699 2022/08/30 23:19:46 - mmengine - INFO - Epoch(train) [1178][20/63] lr: 1.9167e-04 eta: 0:26:23 time: 0.9019 data_time: 0.0497 memory: 16201 loss_prob: 0.3083 loss_thr: 0.2232 loss_db: 0.0558 loss: 0.5872 2022/08/30 23:19:50 - mmengine - INFO - Epoch(train) [1178][25/63] lr: 1.9167e-04 eta: 0:26:23 time: 0.9377 data_time: 0.0922 memory: 16201 loss_prob: 0.3260 loss_thr: 0.2091 loss_db: 0.0601 loss: 0.5952 2022/08/30 23:19:54 - mmengine - INFO - Epoch(train) [1178][30/63] lr: 1.9167e-04 eta: 0:26:12 time: 0.8850 data_time: 0.0739 memory: 16201 loss_prob: 0.2818 loss_thr: 0.1855 loss_db: 0.0511 loss: 0.5185 2022/08/30 23:19:59 - mmengine - INFO - Epoch(train) [1178][35/63] lr: 1.9167e-04 eta: 0:26:12 time: 0.8633 data_time: 0.0494 memory: 16201 loss_prob: 0.2793 loss_thr: 0.2118 loss_db: 0.0495 loss: 0.5406 2022/08/30 23:20:03 - mmengine - INFO - Epoch(train) [1178][40/63] lr: 1.9167e-04 eta: 0:26:01 time: 0.8759 data_time: 0.0857 memory: 16201 loss_prob: 0.3335 loss_thr: 0.2381 loss_db: 0.0608 loss: 0.6324 2022/08/30 23:20:08 - mmengine - INFO - Epoch(train) [1178][45/63] lr: 1.9167e-04 eta: 0:26:01 time: 0.9516 data_time: 0.0802 memory: 16201 loss_prob: 0.3483 loss_thr: 0.2333 loss_db: 0.0617 loss: 0.6434 2022/08/30 23:20:12 - mmengine - INFO - Epoch(train) [1178][50/63] lr: 1.9167e-04 eta: 0:25:50 time: 0.9258 data_time: 0.0609 memory: 16201 loss_prob: 0.3326 loss_thr: 0.2300 loss_db: 0.0575 loss: 0.6201 2022/08/30 23:20:17 - mmengine - INFO - Epoch(train) [1178][55/63] lr: 1.9167e-04 eta: 0:25:50 time: 0.8724 data_time: 0.0806 memory: 16201 loss_prob: 0.3106 loss_thr: 0.2269 loss_db: 0.0555 loss: 0.5929 2022/08/30 23:20:21 - mmengine - INFO - Epoch(train) [1178][60/63] lr: 1.9167e-04 eta: 0:25:39 time: 0.8737 data_time: 0.0716 memory: 16201 loss_prob: 0.2901 loss_thr: 0.2076 loss_db: 0.0519 loss: 0.5496 2022/08/30 23:20:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:20:30 - mmengine - INFO - Epoch(train) [1179][5/63] lr: 1.8382e-04 eta: 0:25:39 time: 1.0425 data_time: 0.2144 memory: 16201 loss_prob: 0.2675 loss_thr: 0.2060 loss_db: 0.0471 loss: 0.5206 2022/08/30 23:20:35 - mmengine - INFO - Epoch(train) [1179][10/63] lr: 1.8382e-04 eta: 0:25:24 time: 1.0349 data_time: 0.2553 memory: 16201 loss_prob: 0.3088 loss_thr: 0.2248 loss_db: 0.0545 loss: 0.5882 2022/08/30 23:20:39 - mmengine - INFO - Epoch(train) [1179][15/63] lr: 1.8382e-04 eta: 0:25:24 time: 0.8755 data_time: 0.0864 memory: 16201 loss_prob: 0.3421 loss_thr: 0.2402 loss_db: 0.0606 loss: 0.6430 2022/08/30 23:20:43 - mmengine - INFO - Epoch(train) [1179][20/63] lr: 1.8382e-04 eta: 0:25:13 time: 0.8501 data_time: 0.0516 memory: 16201 loss_prob: 0.3323 loss_thr: 0.2352 loss_db: 0.0596 loss: 0.6270 2022/08/30 23:20:48 - mmengine - INFO - Epoch(train) [1179][25/63] lr: 1.8382e-04 eta: 0:25:13 time: 0.9160 data_time: 0.0788 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2151 loss_db: 0.0569 loss: 0.5886 2022/08/30 23:20:52 - mmengine - INFO - Epoch(train) [1179][30/63] lr: 1.8382e-04 eta: 0:25:02 time: 0.9180 data_time: 0.0768 memory: 16201 loss_prob: 0.3051 loss_thr: 0.1996 loss_db: 0.0549 loss: 0.5596 2022/08/30 23:20:56 - mmengine - INFO - Epoch(train) [1179][35/63] lr: 1.8382e-04 eta: 0:25:02 time: 0.8297 data_time: 0.0523 memory: 16201 loss_prob: 0.2980 loss_thr: 0.2073 loss_db: 0.0541 loss: 0.5595 2022/08/30 23:21:01 - mmengine - INFO - Epoch(train) [1179][40/63] lr: 1.8382e-04 eta: 0:24:51 time: 0.8610 data_time: 0.0666 memory: 16201 loss_prob: 0.2872 loss_thr: 0.2145 loss_db: 0.0525 loss: 0.5542 2022/08/30 23:21:06 - mmengine - INFO - Epoch(train) [1179][45/63] lr: 1.8382e-04 eta: 0:24:51 time: 0.9758 data_time: 0.0694 memory: 16201 loss_prob: 0.3050 loss_thr: 0.2215 loss_db: 0.0557 loss: 0.5822 2022/08/30 23:21:11 - mmengine - INFO - Epoch(train) [1179][50/63] lr: 1.8382e-04 eta: 0:24:40 time: 0.9830 data_time: 0.0583 memory: 16201 loss_prob: 0.3153 loss_thr: 0.2267 loss_db: 0.0566 loss: 0.5986 2022/08/30 23:21:15 - mmengine - INFO - Epoch(train) [1179][55/63] lr: 1.8382e-04 eta: 0:24:40 time: 0.8957 data_time: 0.0851 memory: 16201 loss_prob: 0.2909 loss_thr: 0.2206 loss_db: 0.0517 loss: 0.5632 2022/08/30 23:21:19 - mmengine - INFO - Epoch(train) [1179][60/63] lr: 1.8382e-04 eta: 0:24:29 time: 0.8505 data_time: 0.0829 memory: 16201 loss_prob: 0.2989 loss_thr: 0.2248 loss_db: 0.0534 loss: 0.5772 2022/08/30 23:21:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:21:28 - mmengine - INFO - Epoch(train) [1180][5/63] lr: 1.7593e-04 eta: 0:24:29 time: 1.0299 data_time: 0.2732 memory: 16201 loss_prob: 0.3456 loss_thr: 0.2373 loss_db: 0.0613 loss: 0.6442 2022/08/30 23:21:33 - mmengine - INFO - Epoch(train) [1180][10/63] lr: 1.7593e-04 eta: 0:24:14 time: 1.1381 data_time: 0.3137 memory: 16201 loss_prob: 0.3139 loss_thr: 0.2152 loss_db: 0.0556 loss: 0.5848 2022/08/30 23:21:37 - mmengine - INFO - Epoch(train) [1180][15/63] lr: 1.7593e-04 eta: 0:24:14 time: 0.8956 data_time: 0.0871 memory: 16201 loss_prob: 0.3051 loss_thr: 0.2119 loss_db: 0.0540 loss: 0.5710 2022/08/30 23:21:41 - mmengine - INFO - Epoch(train) [1180][20/63] lr: 1.7593e-04 eta: 0:24:03 time: 0.8295 data_time: 0.0419 memory: 16201 loss_prob: 0.3073 loss_thr: 0.2210 loss_db: 0.0548 loss: 0.5831 2022/08/30 23:21:46 - mmengine - INFO - Epoch(train) [1180][25/63] lr: 1.7593e-04 eta: 0:24:03 time: 0.9141 data_time: 0.0426 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2338 loss_db: 0.0573 loss: 0.6043 2022/08/30 23:21:50 - mmengine - INFO - Epoch(train) [1180][30/63] lr: 1.7593e-04 eta: 0:23:52 time: 0.9110 data_time: 0.0336 memory: 16201 loss_prob: 0.3078 loss_thr: 0.2219 loss_db: 0.0564 loss: 0.5861 2022/08/30 23:21:54 - mmengine - INFO - Epoch(train) [1180][35/63] lr: 1.7593e-04 eta: 0:23:52 time: 0.8167 data_time: 0.0221 memory: 16201 loss_prob: 0.2957 loss_thr: 0.2100 loss_db: 0.0538 loss: 0.5594 2022/08/30 23:21:58 - mmengine - INFO - Epoch(train) [1180][40/63] lr: 1.7593e-04 eta: 0:23:41 time: 0.8235 data_time: 0.0307 memory: 16201 loss_prob: 0.2863 loss_thr: 0.2062 loss_db: 0.0515 loss: 0.5440 2022/08/30 23:22:03 - mmengine - INFO - Epoch(train) [1180][45/63] lr: 1.7593e-04 eta: 0:23:41 time: 0.8357 data_time: 0.0350 memory: 16201 loss_prob: 0.3100 loss_thr: 0.2178 loss_db: 0.0544 loss: 0.5822 2022/08/30 23:22:07 - mmengine - INFO - Epoch(train) [1180][50/63] lr: 1.7593e-04 eta: 0:23:30 time: 0.8474 data_time: 0.0372 memory: 16201 loss_prob: 0.3122 loss_thr: 0.2220 loss_db: 0.0552 loss: 0.5894 2022/08/30 23:22:11 - mmengine - INFO - Epoch(train) [1180][55/63] lr: 1.7593e-04 eta: 0:23:30 time: 0.8441 data_time: 0.0347 memory: 16201 loss_prob: 0.3018 loss_thr: 0.2197 loss_db: 0.0543 loss: 0.5758 2022/08/30 23:22:15 - mmengine - INFO - Epoch(train) [1180][60/63] lr: 1.7593e-04 eta: 0:23:19 time: 0.8517 data_time: 0.0357 memory: 16201 loss_prob: 0.2983 loss_thr: 0.2217 loss_db: 0.0534 loss: 0.5734 2022/08/30 23:22:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:22:17 - mmengine - INFO - Saving checkpoint at 1180 epochs 2022/08/30 23:22:25 - mmengine - INFO - Epoch(val) [1180][5/32] eta: 0:23:19 time: 0.6167 data_time: 0.0969 memory: 16201 2022/08/30 23:22:29 - mmengine - INFO - Epoch(val) [1180][10/32] eta: 0:00:15 time: 0.6900 data_time: 0.1222 memory: 15734 2022/08/30 23:22:32 - mmengine - INFO - Epoch(val) [1180][15/32] eta: 0:00:15 time: 0.6105 data_time: 0.0547 memory: 15734 2022/08/30 23:22:36 - mmengine - INFO - Epoch(val) [1180][20/32] eta: 0:00:08 time: 0.6974 data_time: 0.0730 memory: 15734 2022/08/30 23:22:39 - mmengine - INFO - Epoch(val) [1180][25/32] eta: 0:00:08 time: 0.6994 data_time: 0.0692 memory: 15734 2022/08/30 23:22:41 - mmengine - INFO - Epoch(val) [1180][30/32] eta: 0:00:01 time: 0.5814 data_time: 0.0290 memory: 15734 2022/08/30 23:22:42 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 23:22:42 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8474, precision: 0.8175, hmean: 0.8322 2022/08/30 23:22:42 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8474, precision: 0.8462, hmean: 0.8468 2022/08/30 23:22:42 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8469, precision: 0.8665, hmean: 0.8566 2022/08/30 23:22:42 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8435, precision: 0.8782, hmean: 0.8605 2022/08/30 23:22:42 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8387, precision: 0.8920, hmean: 0.8645 2022/08/30 23:22:42 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8161, precision: 0.9152, hmean: 0.8628 2022/08/30 23:22:42 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.5277, precision: 0.9539, hmean: 0.6795 2022/08/30 23:22:42 - mmengine - INFO - Epoch(val) [1180][32/32] icdar/precision: 0.8920 icdar/recall: 0.8387 icdar/hmean: 0.8645 2022/08/30 23:22:48 - mmengine - INFO - Epoch(train) [1181][5/63] lr: 1.6799e-04 eta: 0:00:01 time: 1.0156 data_time: 0.2136 memory: 16201 loss_prob: 0.2938 loss_thr: 0.2175 loss_db: 0.0534 loss: 0.5647 2022/08/30 23:22:53 - mmengine - INFO - Epoch(train) [1181][10/63] lr: 1.6799e-04 eta: 0:23:04 time: 1.0455 data_time: 0.2358 memory: 16201 loss_prob: 0.3004 loss_thr: 0.2226 loss_db: 0.0539 loss: 0.5769 2022/08/30 23:22:57 - mmengine - INFO - Epoch(train) [1181][15/63] lr: 1.6799e-04 eta: 0:23:04 time: 0.8412 data_time: 0.0430 memory: 16201 loss_prob: 0.3144 loss_thr: 0.2274 loss_db: 0.0555 loss: 0.5973 2022/08/30 23:23:01 - mmengine - INFO - Epoch(train) [1181][20/63] lr: 1.6799e-04 eta: 0:22:53 time: 0.8226 data_time: 0.0262 memory: 16201 loss_prob: 0.3170 loss_thr: 0.2220 loss_db: 0.0559 loss: 0.5949 2022/08/30 23:23:05 - mmengine - INFO - Epoch(train) [1181][25/63] lr: 1.6799e-04 eta: 0:22:53 time: 0.7964 data_time: 0.0188 memory: 16201 loss_prob: 0.2861 loss_thr: 0.2085 loss_db: 0.0504 loss: 0.5451 2022/08/30 23:23:09 - mmengine - INFO - Epoch(train) [1181][30/63] lr: 1.6799e-04 eta: 0:22:42 time: 0.8171 data_time: 0.0264 memory: 16201 loss_prob: 0.3008 loss_thr: 0.2197 loss_db: 0.0539 loss: 0.5744 2022/08/30 23:23:13 - mmengine - INFO - Epoch(train) [1181][35/63] lr: 1.6799e-04 eta: 0:22:42 time: 0.8271 data_time: 0.0367 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2253 loss_db: 0.0579 loss: 0.6046 2022/08/30 23:23:17 - mmengine - INFO - Epoch(train) [1181][40/63] lr: 1.6799e-04 eta: 0:22:31 time: 0.8176 data_time: 0.0254 memory: 16201 loss_prob: 0.3377 loss_thr: 0.2309 loss_db: 0.0605 loss: 0.6291 2022/08/30 23:23:21 - mmengine - INFO - Epoch(train) [1181][45/63] lr: 1.6799e-04 eta: 0:22:31 time: 0.8286 data_time: 0.0340 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2143 loss_db: 0.0556 loss: 0.5786 2022/08/30 23:23:26 - mmengine - INFO - Epoch(train) [1181][50/63] lr: 1.6799e-04 eta: 0:22:20 time: 0.9221 data_time: 0.0437 memory: 16201 loss_prob: 0.3051 loss_thr: 0.2055 loss_db: 0.0546 loss: 0.5653 2022/08/30 23:23:30 - mmengine - INFO - Epoch(train) [1181][55/63] lr: 1.6799e-04 eta: 0:22:20 time: 0.8998 data_time: 0.0233 memory: 16201 loss_prob: 0.3289 loss_thr: 0.2114 loss_db: 0.0579 loss: 0.5982 2022/08/30 23:23:35 - mmengine - INFO - Epoch(train) [1181][60/63] lr: 1.6799e-04 eta: 0:22:08 time: 0.8176 data_time: 0.0232 memory: 16201 loss_prob: 0.3108 loss_thr: 0.2248 loss_db: 0.0553 loss: 0.5909 2022/08/30 23:23:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:23:43 - mmengine - INFO - Epoch(train) [1182][5/63] lr: 1.6002e-04 eta: 0:22:08 time: 1.0004 data_time: 0.2569 memory: 16201 loss_prob: 0.3048 loss_thr: 0.2211 loss_db: 0.0559 loss: 0.5818 2022/08/30 23:23:47 - mmengine - INFO - Epoch(train) [1182][10/63] lr: 1.6002e-04 eta: 0:21:54 time: 1.0631 data_time: 0.2748 memory: 16201 loss_prob: 0.3167 loss_thr: 0.2209 loss_db: 0.0574 loss: 0.5950 2022/08/30 23:23:51 - mmengine - INFO - Epoch(train) [1182][15/63] lr: 1.6002e-04 eta: 0:21:54 time: 0.8156 data_time: 0.0296 memory: 16201 loss_prob: 0.3324 loss_thr: 0.2312 loss_db: 0.0596 loss: 0.6233 2022/08/30 23:23:56 - mmengine - INFO - Epoch(train) [1182][20/63] lr: 1.6002e-04 eta: 0:21:43 time: 0.8750 data_time: 0.0184 memory: 16201 loss_prob: 0.3191 loss_thr: 0.2318 loss_db: 0.0563 loss: 0.6072 2022/08/30 23:24:00 - mmengine - INFO - Epoch(train) [1182][25/63] lr: 1.6002e-04 eta: 0:21:43 time: 0.8968 data_time: 0.0376 memory: 16201 loss_prob: 0.3010 loss_thr: 0.2175 loss_db: 0.0526 loss: 0.5711 2022/08/30 23:24:04 - mmengine - INFO - Epoch(train) [1182][30/63] lr: 1.6002e-04 eta: 0:21:32 time: 0.8179 data_time: 0.0290 memory: 16201 loss_prob: 0.3233 loss_thr: 0.2247 loss_db: 0.0557 loss: 0.6037 2022/08/30 23:24:08 - mmengine - INFO - Epoch(train) [1182][35/63] lr: 1.6002e-04 eta: 0:21:32 time: 0.7930 data_time: 0.0197 memory: 16201 loss_prob: 0.3291 loss_thr: 0.2269 loss_db: 0.0593 loss: 0.6153 2022/08/30 23:24:12 - mmengine - INFO - Epoch(train) [1182][40/63] lr: 1.6002e-04 eta: 0:21:21 time: 0.7858 data_time: 0.0263 memory: 16201 loss_prob: 0.3318 loss_thr: 0.2188 loss_db: 0.0601 loss: 0.6106 2022/08/30 23:24:16 - mmengine - INFO - Epoch(train) [1182][45/63] lr: 1.6002e-04 eta: 0:21:21 time: 0.8154 data_time: 0.0262 memory: 16201 loss_prob: 0.3222 loss_thr: 0.2175 loss_db: 0.0567 loss: 0.5964 2022/08/30 23:24:20 - mmengine - INFO - Epoch(train) [1182][50/63] lr: 1.6002e-04 eta: 0:21:10 time: 0.8335 data_time: 0.0323 memory: 16201 loss_prob: 0.2952 loss_thr: 0.2138 loss_db: 0.0524 loss: 0.5613 2022/08/30 23:24:25 - mmengine - INFO - Epoch(train) [1182][55/63] lr: 1.6002e-04 eta: 0:21:10 time: 0.8309 data_time: 0.0279 memory: 16201 loss_prob: 0.2556 loss_thr: 0.1898 loss_db: 0.0462 loss: 0.4917 2022/08/30 23:24:29 - mmengine - INFO - Epoch(train) [1182][60/63] lr: 1.6002e-04 eta: 0:20:58 time: 0.8371 data_time: 0.0236 memory: 16201 loss_prob: 0.2765 loss_thr: 0.1981 loss_db: 0.0504 loss: 0.5250 2022/08/30 23:24:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:24:38 - mmengine - INFO - Epoch(train) [1183][5/63] lr: 1.5200e-04 eta: 0:20:58 time: 1.0337 data_time: 0.2204 memory: 16201 loss_prob: 0.3506 loss_thr: 0.2343 loss_db: 0.0615 loss: 0.6464 2022/08/30 23:24:42 - mmengine - INFO - Epoch(train) [1183][10/63] lr: 1.5200e-04 eta: 0:20:44 time: 1.0694 data_time: 0.2370 memory: 16201 loss_prob: 0.2926 loss_thr: 0.2020 loss_db: 0.0517 loss: 0.5463 2022/08/30 23:24:46 - mmengine - INFO - Epoch(train) [1183][15/63] lr: 1.5200e-04 eta: 0:20:44 time: 0.8566 data_time: 0.0515 memory: 16201 loss_prob: 0.3131 loss_thr: 0.2201 loss_db: 0.0556 loss: 0.5888 2022/08/30 23:24:50 - mmengine - INFO - Epoch(train) [1183][20/63] lr: 1.5200e-04 eta: 0:20:33 time: 0.8352 data_time: 0.0300 memory: 16201 loss_prob: 0.3069 loss_thr: 0.2135 loss_db: 0.0559 loss: 0.5763 2022/08/30 23:24:54 - mmengine - INFO - Epoch(train) [1183][25/63] lr: 1.5200e-04 eta: 0:20:33 time: 0.8211 data_time: 0.0284 memory: 16201 loss_prob: 0.2771 loss_thr: 0.1984 loss_db: 0.0509 loss: 0.5263 2022/08/30 23:24:58 - mmengine - INFO - Epoch(train) [1183][30/63] lr: 1.5200e-04 eta: 0:20:22 time: 0.8114 data_time: 0.0285 memory: 16201 loss_prob: 0.2864 loss_thr: 0.2107 loss_db: 0.0514 loss: 0.5485 2022/08/30 23:25:03 - mmengine - INFO - Epoch(train) [1183][35/63] lr: 1.5200e-04 eta: 0:20:22 time: 0.8162 data_time: 0.0317 memory: 16201 loss_prob: 0.3175 loss_thr: 0.2200 loss_db: 0.0564 loss: 0.5939 2022/08/30 23:25:07 - mmengine - INFO - Epoch(train) [1183][40/63] lr: 1.5200e-04 eta: 0:20:11 time: 0.8133 data_time: 0.0297 memory: 16201 loss_prob: 0.3210 loss_thr: 0.2207 loss_db: 0.0572 loss: 0.5989 2022/08/30 23:25:11 - mmengine - INFO - Epoch(train) [1183][45/63] lr: 1.5200e-04 eta: 0:20:11 time: 0.8108 data_time: 0.0327 memory: 16201 loss_prob: 0.3274 loss_thr: 0.2280 loss_db: 0.0587 loss: 0.6141 2022/08/30 23:25:15 - mmengine - INFO - Epoch(train) [1183][50/63] lr: 1.5200e-04 eta: 0:20:00 time: 0.8412 data_time: 0.0266 memory: 16201 loss_prob: 0.3139 loss_thr: 0.2202 loss_db: 0.0559 loss: 0.5900 2022/08/30 23:25:19 - mmengine - INFO - Epoch(train) [1183][55/63] lr: 1.5200e-04 eta: 0:20:00 time: 0.8528 data_time: 0.0314 memory: 16201 loss_prob: 0.3027 loss_thr: 0.2109 loss_db: 0.0541 loss: 0.5676 2022/08/30 23:25:23 - mmengine - INFO - Epoch(train) [1183][60/63] lr: 1.5200e-04 eta: 0:19:48 time: 0.8416 data_time: 0.0347 memory: 16201 loss_prob: 0.3178 loss_thr: 0.2239 loss_db: 0.0573 loss: 0.5989 2022/08/30 23:25:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:25:32 - mmengine - INFO - Epoch(train) [1184][5/63] lr: 1.4393e-04 eta: 0:19:48 time: 0.9994 data_time: 0.2087 memory: 16201 loss_prob: 0.2992 loss_thr: 0.2112 loss_db: 0.0533 loss: 0.5637 2022/08/30 23:25:36 - mmengine - INFO - Epoch(train) [1184][10/63] lr: 1.4393e-04 eta: 0:19:34 time: 1.0256 data_time: 0.2130 memory: 16201 loss_prob: 0.2879 loss_thr: 0.2075 loss_db: 0.0523 loss: 0.5477 2022/08/30 23:25:40 - mmengine - INFO - Epoch(train) [1184][15/63] lr: 1.4393e-04 eta: 0:19:34 time: 0.8172 data_time: 0.0330 memory: 16201 loss_prob: 0.3032 loss_thr: 0.2253 loss_db: 0.0534 loss: 0.5820 2022/08/30 23:25:44 - mmengine - INFO - Epoch(train) [1184][20/63] lr: 1.4393e-04 eta: 0:19:23 time: 0.8137 data_time: 0.0307 memory: 16201 loss_prob: 0.3387 loss_thr: 0.2380 loss_db: 0.0592 loss: 0.6359 2022/08/30 23:25:48 - mmengine - INFO - Epoch(train) [1184][25/63] lr: 1.4393e-04 eta: 0:19:23 time: 0.8242 data_time: 0.0308 memory: 16201 loss_prob: 0.3613 loss_thr: 0.2353 loss_db: 0.0645 loss: 0.6610 2022/08/30 23:25:52 - mmengine - INFO - Epoch(train) [1184][30/63] lr: 1.4393e-04 eta: 0:19:12 time: 0.8252 data_time: 0.0314 memory: 16201 loss_prob: 0.3377 loss_thr: 0.2279 loss_db: 0.0598 loss: 0.6254 2022/08/30 23:25:56 - mmengine - INFO - Epoch(train) [1184][35/63] lr: 1.4393e-04 eta: 0:19:12 time: 0.8156 data_time: 0.0287 memory: 16201 loss_prob: 0.2992 loss_thr: 0.2061 loss_db: 0.0538 loss: 0.5590 2022/08/30 23:26:00 - mmengine - INFO - Epoch(train) [1184][40/63] lr: 1.4393e-04 eta: 0:19:01 time: 0.8154 data_time: 0.0256 memory: 16201 loss_prob: 0.2958 loss_thr: 0.2074 loss_db: 0.0535 loss: 0.5568 2022/08/30 23:26:04 - mmengine - INFO - Epoch(train) [1184][45/63] lr: 1.4393e-04 eta: 0:19:01 time: 0.8158 data_time: 0.0292 memory: 16201 loss_prob: 0.2953 loss_thr: 0.2166 loss_db: 0.0525 loss: 0.5644 2022/08/30 23:26:08 - mmengine - INFO - Epoch(train) [1184][50/63] lr: 1.4393e-04 eta: 0:18:50 time: 0.8168 data_time: 0.0291 memory: 16201 loss_prob: 0.3117 loss_thr: 0.2270 loss_db: 0.0567 loss: 0.5955 2022/08/30 23:26:13 - mmengine - INFO - Epoch(train) [1184][55/63] lr: 1.4393e-04 eta: 0:18:50 time: 0.8226 data_time: 0.0284 memory: 16201 loss_prob: 0.3401 loss_thr: 0.2397 loss_db: 0.0615 loss: 0.6413 2022/08/30 23:26:17 - mmengine - INFO - Epoch(train) [1184][60/63] lr: 1.4393e-04 eta: 0:18:38 time: 0.8881 data_time: 0.0279 memory: 16201 loss_prob: 0.3377 loss_thr: 0.2418 loss_db: 0.0593 loss: 0.6388 2022/08/30 23:26:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:26:25 - mmengine - INFO - Epoch(train) [1185][5/63] lr: 1.3582e-04 eta: 0:18:38 time: 0.9509 data_time: 0.2049 memory: 16201 loss_prob: 0.3114 loss_thr: 0.2265 loss_db: 0.0567 loss: 0.5946 2022/08/30 23:26:29 - mmengine - INFO - Epoch(train) [1185][10/63] lr: 1.3582e-04 eta: 0:18:24 time: 1.0053 data_time: 0.2207 memory: 16201 loss_prob: 0.3124 loss_thr: 0.2174 loss_db: 0.0564 loss: 0.5862 2022/08/30 23:26:33 - mmengine - INFO - Epoch(train) [1185][15/63] lr: 1.3582e-04 eta: 0:18:24 time: 0.8141 data_time: 0.0337 memory: 16201 loss_prob: 0.2830 loss_thr: 0.2001 loss_db: 0.0518 loss: 0.5349 2022/08/30 23:26:38 - mmengine - INFO - Epoch(train) [1185][20/63] lr: 1.3582e-04 eta: 0:18:13 time: 0.8389 data_time: 0.0246 memory: 16201 loss_prob: 0.2879 loss_thr: 0.2041 loss_db: 0.0530 loss: 0.5450 2022/08/30 23:26:42 - mmengine - INFO - Epoch(train) [1185][25/63] lr: 1.3582e-04 eta: 0:18:13 time: 0.8737 data_time: 0.0429 memory: 16201 loss_prob: 0.3035 loss_thr: 0.2168 loss_db: 0.0544 loss: 0.5748 2022/08/30 23:26:46 - mmengine - INFO - Epoch(train) [1185][30/63] lr: 1.3582e-04 eta: 0:18:02 time: 0.8372 data_time: 0.0336 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2329 loss_db: 0.0572 loss: 0.6114 2022/08/30 23:26:50 - mmengine - INFO - Epoch(train) [1185][35/63] lr: 1.3582e-04 eta: 0:18:02 time: 0.8144 data_time: 0.0233 memory: 16201 loss_prob: 0.3016 loss_thr: 0.2226 loss_db: 0.0540 loss: 0.5782 2022/08/30 23:26:54 - mmengine - INFO - Epoch(train) [1185][40/63] lr: 1.3582e-04 eta: 0:17:51 time: 0.8100 data_time: 0.0290 memory: 16201 loss_prob: 0.3344 loss_thr: 0.2405 loss_db: 0.0587 loss: 0.6336 2022/08/30 23:26:59 - mmengine - INFO - Epoch(train) [1185][45/63] lr: 1.3582e-04 eta: 0:17:51 time: 0.8323 data_time: 0.0288 memory: 16201 loss_prob: 0.3656 loss_thr: 0.2570 loss_db: 0.0651 loss: 0.6877 2022/08/30 23:27:03 - mmengine - INFO - Epoch(train) [1185][50/63] lr: 1.3582e-04 eta: 0:17:40 time: 0.8338 data_time: 0.0286 memory: 16201 loss_prob: 0.3358 loss_thr: 0.2368 loss_db: 0.0603 loss: 0.6329 2022/08/30 23:27:07 - mmengine - INFO - Epoch(train) [1185][55/63] lr: 1.3582e-04 eta: 0:17:40 time: 0.8212 data_time: 0.0278 memory: 16201 loss_prob: 0.3286 loss_thr: 0.2321 loss_db: 0.0581 loss: 0.6189 2022/08/30 23:27:11 - mmengine - INFO - Epoch(train) [1185][60/63] lr: 1.3582e-04 eta: 0:17:28 time: 0.8439 data_time: 0.0304 memory: 16201 loss_prob: 0.3135 loss_thr: 0.2137 loss_db: 0.0566 loss: 0.5838 2022/08/30 23:27:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:27:19 - mmengine - INFO - Epoch(train) [1186][5/63] lr: 1.2765e-04 eta: 0:17:28 time: 0.9853 data_time: 0.2107 memory: 16201 loss_prob: 0.2962 loss_thr: 0.2140 loss_db: 0.0532 loss: 0.5634 2022/08/30 23:27:23 - mmengine - INFO - Epoch(train) [1186][10/63] lr: 1.2765e-04 eta: 0:17:14 time: 1.0165 data_time: 0.2184 memory: 16201 loss_prob: 0.2943 loss_thr: 0.2044 loss_db: 0.0531 loss: 0.5517 2022/08/30 23:27:28 - mmengine - INFO - Epoch(train) [1186][15/63] lr: 1.2765e-04 eta: 0:17:14 time: 0.8609 data_time: 0.0338 memory: 16201 loss_prob: 0.3030 loss_thr: 0.2125 loss_db: 0.0552 loss: 0.5708 2022/08/30 23:27:32 - mmengine - INFO - Epoch(train) [1186][20/63] lr: 1.2765e-04 eta: 0:17:03 time: 0.8804 data_time: 0.0313 memory: 16201 loss_prob: 0.3476 loss_thr: 0.2410 loss_db: 0.0628 loss: 0.6513 2022/08/30 23:27:36 - mmengine - INFO - Epoch(train) [1186][25/63] lr: 1.2765e-04 eta: 0:17:03 time: 0.8718 data_time: 0.0415 memory: 16201 loss_prob: 0.3411 loss_thr: 0.2358 loss_db: 0.0614 loss: 0.6382 2022/08/30 23:27:40 - mmengine - INFO - Epoch(train) [1186][30/63] lr: 1.2765e-04 eta: 0:16:52 time: 0.8415 data_time: 0.0340 memory: 16201 loss_prob: 0.3114 loss_thr: 0.2231 loss_db: 0.0557 loss: 0.5902 2022/08/30 23:27:45 - mmengine - INFO - Epoch(train) [1186][35/63] lr: 1.2765e-04 eta: 0:16:52 time: 0.8101 data_time: 0.0229 memory: 16201 loss_prob: 0.3284 loss_thr: 0.2308 loss_db: 0.0585 loss: 0.6177 2022/08/30 23:27:49 - mmengine - INFO - Epoch(train) [1186][40/63] lr: 1.2765e-04 eta: 0:16:41 time: 0.8920 data_time: 0.0271 memory: 16201 loss_prob: 0.3364 loss_thr: 0.2330 loss_db: 0.0591 loss: 0.6285 2022/08/30 23:27:53 - mmengine - INFO - Epoch(train) [1186][45/63] lr: 1.2765e-04 eta: 0:16:41 time: 0.8772 data_time: 0.0251 memory: 16201 loss_prob: 0.3072 loss_thr: 0.2179 loss_db: 0.0533 loss: 0.5783 2022/08/30 23:27:58 - mmengine - INFO - Epoch(train) [1186][50/63] lr: 1.2765e-04 eta: 0:16:30 time: 0.8464 data_time: 0.0276 memory: 16201 loss_prob: 0.2861 loss_thr: 0.2062 loss_db: 0.0507 loss: 0.5429 2022/08/30 23:28:02 - mmengine - INFO - Epoch(train) [1186][55/63] lr: 1.2765e-04 eta: 0:16:30 time: 0.8580 data_time: 0.0342 memory: 16201 loss_prob: 0.3045 loss_thr: 0.2215 loss_db: 0.0544 loss: 0.5804 2022/08/30 23:28:06 - mmengine - INFO - Epoch(train) [1186][60/63] lr: 1.2765e-04 eta: 0:16:19 time: 0.8252 data_time: 0.0316 memory: 16201 loss_prob: 0.3095 loss_thr: 0.2265 loss_db: 0.0556 loss: 0.5915 2022/08/30 23:28:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:28:15 - mmengine - INFO - Epoch(train) [1187][5/63] lr: 1.1942e-04 eta: 0:16:19 time: 1.0103 data_time: 0.2089 memory: 16201 loss_prob: 0.3098 loss_thr: 0.2166 loss_db: 0.0552 loss: 0.5816 2022/08/30 23:28:19 - mmengine - INFO - Epoch(train) [1187][10/63] lr: 1.1942e-04 eta: 0:16:04 time: 1.0229 data_time: 0.2213 memory: 16201 loss_prob: 0.3196 loss_thr: 0.2280 loss_db: 0.0575 loss: 0.6051 2022/08/30 23:28:23 - mmengine - INFO - Epoch(train) [1187][15/63] lr: 1.1942e-04 eta: 0:16:04 time: 0.8108 data_time: 0.0289 memory: 16201 loss_prob: 0.2957 loss_thr: 0.2112 loss_db: 0.0538 loss: 0.5607 2022/08/30 23:28:28 - mmengine - INFO - Epoch(train) [1187][20/63] lr: 1.1942e-04 eta: 0:15:53 time: 0.9098 data_time: 0.0297 memory: 16201 loss_prob: 0.3179 loss_thr: 0.2283 loss_db: 0.0577 loss: 0.6038 2022/08/30 23:28:32 - mmengine - INFO - Epoch(train) [1187][25/63] lr: 1.1942e-04 eta: 0:15:53 time: 0.9303 data_time: 0.0450 memory: 16201 loss_prob: 0.3223 loss_thr: 0.2382 loss_db: 0.0576 loss: 0.6181 2022/08/30 23:28:36 - mmengine - INFO - Epoch(train) [1187][30/63] lr: 1.1942e-04 eta: 0:15:42 time: 0.8530 data_time: 0.0293 memory: 16201 loss_prob: 0.2965 loss_thr: 0.2156 loss_db: 0.0534 loss: 0.5654 2022/08/30 23:28:41 - mmengine - INFO - Epoch(train) [1187][35/63] lr: 1.1942e-04 eta: 0:15:42 time: 0.8588 data_time: 0.0287 memory: 16201 loss_prob: 0.3047 loss_thr: 0.2111 loss_db: 0.0552 loss: 0.5711 2022/08/30 23:28:45 - mmengine - INFO - Epoch(train) [1187][40/63] lr: 1.1942e-04 eta: 0:15:31 time: 0.8316 data_time: 0.0305 memory: 16201 loss_prob: 0.2886 loss_thr: 0.2050 loss_db: 0.0521 loss: 0.5457 2022/08/30 23:28:49 - mmengine - INFO - Epoch(train) [1187][45/63] lr: 1.1942e-04 eta: 0:15:31 time: 0.8516 data_time: 0.0255 memory: 16201 loss_prob: 0.2672 loss_thr: 0.1975 loss_db: 0.0481 loss: 0.5129 2022/08/30 23:28:53 - mmengine - INFO - Epoch(train) [1187][50/63] lr: 1.1942e-04 eta: 0:15:20 time: 0.8444 data_time: 0.0343 memory: 16201 loss_prob: 0.2940 loss_thr: 0.2098 loss_db: 0.0529 loss: 0.5568 2022/08/30 23:28:57 - mmengine - INFO - Epoch(train) [1187][55/63] lr: 1.1942e-04 eta: 0:15:20 time: 0.8119 data_time: 0.0286 memory: 16201 loss_prob: 0.3087 loss_thr: 0.2130 loss_db: 0.0565 loss: 0.5782 2022/08/30 23:29:01 - mmengine - INFO - Epoch(train) [1187][60/63] lr: 1.1942e-04 eta: 0:15:09 time: 0.8253 data_time: 0.0240 memory: 16201 loss_prob: 0.3149 loss_thr: 0.2180 loss_db: 0.0570 loss: 0.5900 2022/08/30 23:29:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:29:09 - mmengine - INFO - Epoch(train) [1188][5/63] lr: 1.1112e-04 eta: 0:15:09 time: 0.9595 data_time: 0.1884 memory: 16201 loss_prob: 0.3189 loss_thr: 0.2223 loss_db: 0.0561 loss: 0.5973 2022/08/30 23:29:13 - mmengine - INFO - Epoch(train) [1188][10/63] lr: 1.1112e-04 eta: 0:14:54 time: 0.9955 data_time: 0.2017 memory: 16201 loss_prob: 0.3105 loss_thr: 0.2173 loss_db: 0.0558 loss: 0.5836 2022/08/30 23:29:19 - mmengine - INFO - Epoch(train) [1188][15/63] lr: 1.1112e-04 eta: 0:14:54 time: 0.9408 data_time: 0.0314 memory: 16201 loss_prob: 0.3243 loss_thr: 0.2313 loss_db: 0.0574 loss: 0.6130 2022/08/30 23:29:23 - mmengine - INFO - Epoch(train) [1188][20/63] lr: 1.1112e-04 eta: 0:14:43 time: 0.9252 data_time: 0.0271 memory: 16201 loss_prob: 0.3280 loss_thr: 0.2334 loss_db: 0.0584 loss: 0.6198 2022/08/30 23:29:27 - mmengine - INFO - Epoch(train) [1188][25/63] lr: 1.1112e-04 eta: 0:14:43 time: 0.8063 data_time: 0.0323 memory: 16201 loss_prob: 0.3121 loss_thr: 0.2181 loss_db: 0.0569 loss: 0.5871 2022/08/30 23:29:31 - mmengine - INFO - Epoch(train) [1188][30/63] lr: 1.1112e-04 eta: 0:14:32 time: 0.8341 data_time: 0.0317 memory: 16201 loss_prob: 0.2995 loss_thr: 0.2139 loss_db: 0.0538 loss: 0.5672 2022/08/30 23:29:35 - mmengine - INFO - Epoch(train) [1188][35/63] lr: 1.1112e-04 eta: 0:14:32 time: 0.8424 data_time: 0.0270 memory: 16201 loss_prob: 0.3090 loss_thr: 0.2154 loss_db: 0.0562 loss: 0.5805 2022/08/30 23:29:39 - mmengine - INFO - Epoch(train) [1188][40/63] lr: 1.1112e-04 eta: 0:14:21 time: 0.8291 data_time: 0.0294 memory: 16201 loss_prob: 0.3385 loss_thr: 0.2288 loss_db: 0.0621 loss: 0.6294 2022/08/30 23:29:43 - mmengine - INFO - Epoch(train) [1188][45/63] lr: 1.1112e-04 eta: 0:14:21 time: 0.8140 data_time: 0.0279 memory: 16201 loss_prob: 0.3245 loss_thr: 0.2217 loss_db: 0.0588 loss: 0.6050 2022/08/30 23:29:48 - mmengine - INFO - Epoch(train) [1188][50/63] lr: 1.1112e-04 eta: 0:14:10 time: 0.8412 data_time: 0.0296 memory: 16201 loss_prob: 0.3051 loss_thr: 0.2184 loss_db: 0.0550 loss: 0.5785 2022/08/30 23:29:52 - mmengine - INFO - Epoch(train) [1188][55/63] lr: 1.1112e-04 eta: 0:14:10 time: 0.8533 data_time: 0.0373 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2370 loss_db: 0.0596 loss: 0.6312 2022/08/30 23:29:56 - mmengine - INFO - Epoch(train) [1188][60/63] lr: 1.1112e-04 eta: 0:13:59 time: 0.8609 data_time: 0.0329 memory: 16201 loss_prob: 0.3232 loss_thr: 0.2177 loss_db: 0.0566 loss: 0.5975 2022/08/30 23:29:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:30:05 - mmengine - INFO - Epoch(train) [1189][5/63] lr: 1.0276e-04 eta: 0:13:59 time: 1.0128 data_time: 0.2348 memory: 16201 loss_prob: 0.3233 loss_thr: 0.2318 loss_db: 0.0578 loss: 0.6129 2022/08/30 23:30:09 - mmengine - INFO - Epoch(train) [1189][10/63] lr: 1.0276e-04 eta: 0:13:44 time: 1.0437 data_time: 0.2417 memory: 16201 loss_prob: 0.3057 loss_thr: 0.2178 loss_db: 0.0554 loss: 0.5789 2022/08/30 23:30:13 - mmengine - INFO - Epoch(train) [1189][15/63] lr: 1.0276e-04 eta: 0:13:44 time: 0.8828 data_time: 0.0254 memory: 16201 loss_prob: 0.3214 loss_thr: 0.2134 loss_db: 0.0568 loss: 0.5916 2022/08/30 23:30:18 - mmengine - INFO - Epoch(train) [1189][20/63] lr: 1.0276e-04 eta: 0:13:33 time: 0.9002 data_time: 0.0269 memory: 16201 loss_prob: 0.3215 loss_thr: 0.2199 loss_db: 0.0578 loss: 0.5992 2022/08/30 23:30:22 - mmengine - INFO - Epoch(train) [1189][25/63] lr: 1.0276e-04 eta: 0:13:33 time: 0.8431 data_time: 0.0412 memory: 16201 loss_prob: 0.3318 loss_thr: 0.2295 loss_db: 0.0608 loss: 0.6220 2022/08/30 23:30:26 - mmengine - INFO - Epoch(train) [1189][30/63] lr: 1.0276e-04 eta: 0:13:22 time: 0.8404 data_time: 0.0302 memory: 16201 loss_prob: 0.2979 loss_thr: 0.2142 loss_db: 0.0544 loss: 0.5665 2022/08/30 23:30:30 - mmengine - INFO - Epoch(train) [1189][35/63] lr: 1.0276e-04 eta: 0:13:22 time: 0.8340 data_time: 0.0201 memory: 16201 loss_prob: 0.2750 loss_thr: 0.1995 loss_db: 0.0493 loss: 0.5239 2022/08/30 23:30:34 - mmengine - INFO - Epoch(train) [1189][40/63] lr: 1.0276e-04 eta: 0:13:11 time: 0.8121 data_time: 0.0286 memory: 16201 loss_prob: 0.3014 loss_thr: 0.2098 loss_db: 0.0545 loss: 0.5657 2022/08/30 23:30:39 - mmengine - INFO - Epoch(train) [1189][45/63] lr: 1.0276e-04 eta: 0:13:11 time: 0.8618 data_time: 0.0289 memory: 16201 loss_prob: 0.3232 loss_thr: 0.2243 loss_db: 0.0568 loss: 0.6043 2022/08/30 23:30:43 - mmengine - INFO - Epoch(train) [1189][50/63] lr: 1.0276e-04 eta: 0:13:00 time: 0.8580 data_time: 0.0243 memory: 16201 loss_prob: 0.3115 loss_thr: 0.2211 loss_db: 0.0546 loss: 0.5872 2022/08/30 23:30:48 - mmengine - INFO - Epoch(train) [1189][55/63] lr: 1.0276e-04 eta: 0:13:00 time: 0.8825 data_time: 0.0277 memory: 16201 loss_prob: 0.3021 loss_thr: 0.2190 loss_db: 0.0545 loss: 0.5756 2022/08/30 23:30:52 - mmengine - INFO - Epoch(train) [1189][60/63] lr: 1.0276e-04 eta: 0:12:49 time: 0.8989 data_time: 0.0364 memory: 16201 loss_prob: 0.3013 loss_thr: 0.2207 loss_db: 0.0529 loss: 0.5748 2022/08/30 23:30:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:31:00 - mmengine - INFO - Epoch(train) [1190][5/63] lr: 9.4322e-05 eta: 0:12:49 time: 1.0001 data_time: 0.2309 memory: 16201 loss_prob: 0.3262 loss_thr: 0.2189 loss_db: 0.0588 loss: 0.6039 2022/08/30 23:31:04 - mmengine - INFO - Epoch(train) [1190][10/63] lr: 9.4322e-05 eta: 0:12:35 time: 1.0287 data_time: 0.2373 memory: 16201 loss_prob: 0.3213 loss_thr: 0.2149 loss_db: 0.0581 loss: 0.5943 2022/08/30 23:31:09 - mmengine - INFO - Epoch(train) [1190][15/63] lr: 9.4322e-05 eta: 0:12:35 time: 0.8934 data_time: 0.0321 memory: 16201 loss_prob: 0.3112 loss_thr: 0.2158 loss_db: 0.0544 loss: 0.5814 2022/08/30 23:31:13 - mmengine - INFO - Epoch(train) [1190][20/63] lr: 9.4322e-05 eta: 0:12:24 time: 0.9067 data_time: 0.0316 memory: 16201 loss_prob: 0.3025 loss_thr: 0.2117 loss_db: 0.0538 loss: 0.5680 2022/08/30 23:31:17 - mmengine - INFO - Epoch(train) [1190][25/63] lr: 9.4322e-05 eta: 0:12:24 time: 0.8123 data_time: 0.0324 memory: 16201 loss_prob: 0.3237 loss_thr: 0.2201 loss_db: 0.0588 loss: 0.6026 2022/08/30 23:31:21 - mmengine - INFO - Epoch(train) [1190][30/63] lr: 9.4322e-05 eta: 0:12:12 time: 0.8020 data_time: 0.0313 memory: 16201 loss_prob: 0.3258 loss_thr: 0.2233 loss_db: 0.0580 loss: 0.6072 2022/08/30 23:31:25 - mmengine - INFO - Epoch(train) [1190][35/63] lr: 9.4322e-05 eta: 0:12:12 time: 0.7886 data_time: 0.0287 memory: 16201 loss_prob: 0.3102 loss_thr: 0.2182 loss_db: 0.0549 loss: 0.5834 2022/08/30 23:31:31 - mmengine - INFO - Epoch(train) [1190][40/63] lr: 9.4322e-05 eta: 0:12:01 time: 0.9167 data_time: 0.0319 memory: 16201 loss_prob: 0.2997 loss_thr: 0.2119 loss_db: 0.0536 loss: 0.5651 2022/08/30 23:31:35 - mmengine - INFO - Epoch(train) [1190][45/63] lr: 9.4322e-05 eta: 0:12:01 time: 0.9315 data_time: 0.0303 memory: 16201 loss_prob: 0.2934 loss_thr: 0.2076 loss_db: 0.0525 loss: 0.5536 2022/08/30 23:31:39 - mmengine - INFO - Epoch(train) [1190][50/63] lr: 9.4322e-05 eta: 0:11:50 time: 0.8328 data_time: 0.0272 memory: 16201 loss_prob: 0.2986 loss_thr: 0.2158 loss_db: 0.0535 loss: 0.5680 2022/08/30 23:31:43 - mmengine - INFO - Epoch(train) [1190][55/63] lr: 9.4322e-05 eta: 0:11:50 time: 0.8312 data_time: 0.0289 memory: 16201 loss_prob: 0.3016 loss_thr: 0.2143 loss_db: 0.0542 loss: 0.5701 2022/08/30 23:31:47 - mmengine - INFO - Epoch(train) [1190][60/63] lr: 9.4322e-05 eta: 0:11:39 time: 0.8547 data_time: 0.0278 memory: 16201 loss_prob: 0.3360 loss_thr: 0.2274 loss_db: 0.0589 loss: 0.6224 2022/08/30 23:31:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:31:55 - mmengine - INFO - Epoch(train) [1191][5/63] lr: 8.5798e-05 eta: 0:11:39 time: 1.0263 data_time: 0.2054 memory: 16201 loss_prob: 0.3287 loss_thr: 0.2200 loss_db: 0.0562 loss: 0.6049 2022/08/30 23:31:59 - mmengine - INFO - Epoch(train) [1191][10/63] lr: 8.5798e-05 eta: 0:11:25 time: 0.9877 data_time: 0.2058 memory: 16201 loss_prob: 0.3110 loss_thr: 0.2023 loss_db: 0.0533 loss: 0.5666 2022/08/30 23:32:03 - mmengine - INFO - Epoch(train) [1191][15/63] lr: 8.5798e-05 eta: 0:11:25 time: 0.7865 data_time: 0.0287 memory: 16201 loss_prob: 0.3062 loss_thr: 0.2058 loss_db: 0.0542 loss: 0.5662 2022/08/30 23:32:08 - mmengine - INFO - Epoch(train) [1191][20/63] lr: 8.5798e-05 eta: 0:11:14 time: 0.8679 data_time: 0.0269 memory: 16201 loss_prob: 0.2827 loss_thr: 0.1922 loss_db: 0.0505 loss: 0.5254 2022/08/30 23:32:12 - mmengine - INFO - Epoch(train) [1191][25/63] lr: 8.5798e-05 eta: 0:11:14 time: 0.8781 data_time: 0.0317 memory: 16201 loss_prob: 0.2780 loss_thr: 0.1987 loss_db: 0.0504 loss: 0.5271 2022/08/30 23:32:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:32:16 - mmengine - INFO - Epoch(train) [1191][30/63] lr: 8.5798e-05 eta: 0:11:03 time: 0.7992 data_time: 0.0281 memory: 16201 loss_prob: 0.2919 loss_thr: 0.2131 loss_db: 0.0525 loss: 0.5574 2022/08/30 23:32:20 - mmengine - INFO - Epoch(train) [1191][35/63] lr: 8.5798e-05 eta: 0:11:03 time: 0.8056 data_time: 0.0285 memory: 16201 loss_prob: 0.3035 loss_thr: 0.2080 loss_db: 0.0535 loss: 0.5651 2022/08/30 23:32:24 - mmengine - INFO - Epoch(train) [1191][40/63] lr: 8.5798e-05 eta: 0:10:52 time: 0.7936 data_time: 0.0248 memory: 16201 loss_prob: 0.2826 loss_thr: 0.1972 loss_db: 0.0503 loss: 0.5301 2022/08/30 23:32:28 - mmengine - INFO - Epoch(train) [1191][45/63] lr: 8.5798e-05 eta: 0:10:52 time: 0.8305 data_time: 0.0306 memory: 16201 loss_prob: 0.2921 loss_thr: 0.2148 loss_db: 0.0537 loss: 0.5606 2022/08/30 23:32:33 - mmengine - INFO - Epoch(train) [1191][50/63] lr: 8.5798e-05 eta: 0:10:41 time: 0.8559 data_time: 0.0346 memory: 16201 loss_prob: 0.3404 loss_thr: 0.2486 loss_db: 0.0614 loss: 0.6503 2022/08/30 23:32:37 - mmengine - INFO - Epoch(train) [1191][55/63] lr: 8.5798e-05 eta: 0:10:41 time: 0.8460 data_time: 0.0294 memory: 16201 loss_prob: 0.3500 loss_thr: 0.2446 loss_db: 0.0611 loss: 0.6557 2022/08/30 23:32:41 - mmengine - INFO - Epoch(train) [1191][60/63] lr: 8.5798e-05 eta: 0:10:29 time: 0.8234 data_time: 0.0256 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2299 loss_db: 0.0581 loss: 0.6183 2022/08/30 23:32:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:32:49 - mmengine - INFO - Epoch(train) [1192][5/63] lr: 7.7179e-05 eta: 0:10:29 time: 0.9546 data_time: 0.1841 memory: 16201 loss_prob: 0.3102 loss_thr: 0.2202 loss_db: 0.0556 loss: 0.5860 2022/08/30 23:32:53 - mmengine - INFO - Epoch(train) [1192][10/63] lr: 7.7179e-05 eta: 0:10:15 time: 1.0212 data_time: 0.1994 memory: 16201 loss_prob: 0.2970 loss_thr: 0.2030 loss_db: 0.0532 loss: 0.5532 2022/08/30 23:32:57 - mmengine - INFO - Epoch(train) [1192][15/63] lr: 7.7179e-05 eta: 0:10:15 time: 0.8455 data_time: 0.0306 memory: 16201 loss_prob: 0.2729 loss_thr: 0.1945 loss_db: 0.0490 loss: 0.5164 2022/08/30 23:33:02 - mmengine - INFO - Epoch(train) [1192][20/63] lr: 7.7179e-05 eta: 0:10:04 time: 0.8486 data_time: 0.0209 memory: 16201 loss_prob: 0.3081 loss_thr: 0.2119 loss_db: 0.0551 loss: 0.5751 2022/08/30 23:33:06 - mmengine - INFO - Epoch(train) [1192][25/63] lr: 7.7179e-05 eta: 0:10:04 time: 0.8477 data_time: 0.0361 memory: 16201 loss_prob: 0.3201 loss_thr: 0.2175 loss_db: 0.0572 loss: 0.5949 2022/08/30 23:33:10 - mmengine - INFO - Epoch(train) [1192][30/63] lr: 7.7179e-05 eta: 0:09:53 time: 0.8532 data_time: 0.0324 memory: 16201 loss_prob: 0.3044 loss_thr: 0.2161 loss_db: 0.0545 loss: 0.5750 2022/08/30 23:33:14 - mmengine - INFO - Epoch(train) [1192][35/63] lr: 7.7179e-05 eta: 0:09:53 time: 0.8577 data_time: 0.0241 memory: 16201 loss_prob: 0.2952 loss_thr: 0.2185 loss_db: 0.0525 loss: 0.5662 2022/08/30 23:33:19 - mmengine - INFO - Epoch(train) [1192][40/63] lr: 7.7179e-05 eta: 0:09:42 time: 0.8718 data_time: 0.0295 memory: 16201 loss_prob: 0.3077 loss_thr: 0.2195 loss_db: 0.0550 loss: 0.5822 2022/08/30 23:33:23 - mmengine - INFO - Epoch(train) [1192][45/63] lr: 7.7179e-05 eta: 0:09:42 time: 0.8475 data_time: 0.0307 memory: 16201 loss_prob: 0.3193 loss_thr: 0.2174 loss_db: 0.0565 loss: 0.5932 2022/08/30 23:33:27 - mmengine - INFO - Epoch(train) [1192][50/63] lr: 7.7179e-05 eta: 0:09:31 time: 0.8287 data_time: 0.0299 memory: 16201 loss_prob: 0.3222 loss_thr: 0.2290 loss_db: 0.0568 loss: 0.6079 2022/08/30 23:33:31 - mmengine - INFO - Epoch(train) [1192][55/63] lr: 7.7179e-05 eta: 0:09:31 time: 0.8317 data_time: 0.0286 memory: 16201 loss_prob: 0.3111 loss_thr: 0.2286 loss_db: 0.0547 loss: 0.5944 2022/08/30 23:33:35 - mmengine - INFO - Epoch(train) [1192][60/63] lr: 7.7179e-05 eta: 0:09:20 time: 0.8281 data_time: 0.0293 memory: 16201 loss_prob: 0.2800 loss_thr: 0.2120 loss_db: 0.0494 loss: 0.5415 2022/08/30 23:33:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:33:43 - mmengine - INFO - Epoch(train) [1193][5/63] lr: 6.8451e-05 eta: 0:09:20 time: 0.9654 data_time: 0.1873 memory: 16201 loss_prob: 0.2892 loss_thr: 0.2096 loss_db: 0.0510 loss: 0.5499 2022/08/30 23:33:48 - mmengine - INFO - Epoch(train) [1193][10/63] lr: 6.8451e-05 eta: 0:09:05 time: 1.0098 data_time: 0.2031 memory: 16201 loss_prob: 0.3213 loss_thr: 0.2263 loss_db: 0.0546 loss: 0.6023 2022/08/30 23:33:52 - mmengine - INFO - Epoch(train) [1193][15/63] lr: 6.8451e-05 eta: 0:09:05 time: 0.8295 data_time: 0.0295 memory: 16201 loss_prob: 0.3097 loss_thr: 0.2309 loss_db: 0.0533 loss: 0.5939 2022/08/30 23:33:56 - mmengine - INFO - Epoch(train) [1193][20/63] lr: 6.8451e-05 eta: 0:08:54 time: 0.8748 data_time: 0.0246 memory: 16201 loss_prob: 0.2833 loss_thr: 0.2113 loss_db: 0.0505 loss: 0.5452 2022/08/30 23:34:01 - mmengine - INFO - Epoch(train) [1193][25/63] lr: 6.8451e-05 eta: 0:08:54 time: 0.8827 data_time: 0.0342 memory: 16201 loss_prob: 0.2750 loss_thr: 0.2075 loss_db: 0.0505 loss: 0.5330 2022/08/30 23:34:05 - mmengine - INFO - Epoch(train) [1193][30/63] lr: 6.8451e-05 eta: 0:08:43 time: 0.8488 data_time: 0.0347 memory: 16201 loss_prob: 0.2762 loss_thr: 0.2048 loss_db: 0.0509 loss: 0.5319 2022/08/30 23:34:09 - mmengine - INFO - Epoch(train) [1193][35/63] lr: 6.8451e-05 eta: 0:08:43 time: 0.8611 data_time: 0.0324 memory: 16201 loss_prob: 0.3063 loss_thr: 0.2118 loss_db: 0.0559 loss: 0.5740 2022/08/30 23:34:13 - mmengine - INFO - Epoch(train) [1193][40/63] lr: 6.8451e-05 eta: 0:08:32 time: 0.8578 data_time: 0.0323 memory: 16201 loss_prob: 0.3133 loss_thr: 0.2190 loss_db: 0.0574 loss: 0.5897 2022/08/30 23:34:17 - mmengine - INFO - Epoch(train) [1193][45/63] lr: 6.8451e-05 eta: 0:08:32 time: 0.8306 data_time: 0.0332 memory: 16201 loss_prob: 0.3047 loss_thr: 0.2160 loss_db: 0.0545 loss: 0.5752 2022/08/30 23:34:21 - mmengine - INFO - Epoch(train) [1193][50/63] lr: 6.8451e-05 eta: 0:08:21 time: 0.8115 data_time: 0.0289 memory: 16201 loss_prob: 0.3147 loss_thr: 0.2149 loss_db: 0.0562 loss: 0.5857 2022/08/30 23:34:26 - mmengine - INFO - Epoch(train) [1193][55/63] lr: 6.8451e-05 eta: 0:08:21 time: 0.8141 data_time: 0.0250 memory: 16201 loss_prob: 0.3542 loss_thr: 0.2374 loss_db: 0.0650 loss: 0.6566 2022/08/30 23:34:30 - mmengine - INFO - Epoch(train) [1193][60/63] lr: 6.8451e-05 eta: 0:08:10 time: 0.8508 data_time: 0.0301 memory: 16201 loss_prob: 0.3472 loss_thr: 0.2368 loss_db: 0.0629 loss: 0.6469 2022/08/30 23:34:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:34:38 - mmengine - INFO - Epoch(train) [1194][5/63] lr: 5.9596e-05 eta: 0:08:10 time: 0.9455 data_time: 0.1959 memory: 16201 loss_prob: 0.3174 loss_thr: 0.2185 loss_db: 0.0575 loss: 0.5933 2022/08/30 23:34:42 - mmengine - INFO - Epoch(train) [1194][10/63] lr: 5.9596e-05 eta: 0:07:56 time: 1.0117 data_time: 0.2050 memory: 16201 loss_prob: 0.2945 loss_thr: 0.2036 loss_db: 0.0536 loss: 0.5517 2022/08/30 23:34:47 - mmengine - INFO - Epoch(train) [1194][15/63] lr: 5.9596e-05 eta: 0:07:56 time: 0.8521 data_time: 0.0295 memory: 16201 loss_prob: 0.2777 loss_thr: 0.2028 loss_db: 0.0500 loss: 0.5304 2022/08/30 23:34:51 - mmengine - INFO - Epoch(train) [1194][20/63] lr: 5.9596e-05 eta: 0:07:45 time: 0.8508 data_time: 0.0272 memory: 16201 loss_prob: 0.2811 loss_thr: 0.1992 loss_db: 0.0495 loss: 0.5298 2022/08/30 23:34:55 - mmengine - INFO - Epoch(train) [1194][25/63] lr: 5.9596e-05 eta: 0:07:45 time: 0.8460 data_time: 0.0328 memory: 16201 loss_prob: 0.3018 loss_thr: 0.2031 loss_db: 0.0514 loss: 0.5562 2022/08/30 23:34:59 - mmengine - INFO - Epoch(train) [1194][30/63] lr: 5.9596e-05 eta: 0:07:33 time: 0.8361 data_time: 0.0271 memory: 16201 loss_prob: 0.3271 loss_thr: 0.2203 loss_db: 0.0560 loss: 0.6035 2022/08/30 23:35:03 - mmengine - INFO - Epoch(train) [1194][35/63] lr: 5.9596e-05 eta: 0:07:33 time: 0.8234 data_time: 0.0212 memory: 16201 loss_prob: 0.3237 loss_thr: 0.2217 loss_db: 0.0573 loss: 0.6027 2022/08/30 23:35:08 - mmengine - INFO - Epoch(train) [1194][40/63] lr: 5.9596e-05 eta: 0:07:22 time: 0.8744 data_time: 0.0318 memory: 16201 loss_prob: 0.3022 loss_thr: 0.2072 loss_db: 0.0542 loss: 0.5636 2022/08/30 23:35:12 - mmengine - INFO - Epoch(train) [1194][45/63] lr: 5.9596e-05 eta: 0:07:22 time: 0.8598 data_time: 0.0343 memory: 16201 loss_prob: 0.2882 loss_thr: 0.2051 loss_db: 0.0518 loss: 0.5452 2022/08/30 23:35:16 - mmengine - INFO - Epoch(train) [1194][50/63] lr: 5.9596e-05 eta: 0:07:11 time: 0.8012 data_time: 0.0269 memory: 16201 loss_prob: 0.2934 loss_thr: 0.2068 loss_db: 0.0525 loss: 0.5526 2022/08/30 23:35:20 - mmengine - INFO - Epoch(train) [1194][55/63] lr: 5.9596e-05 eta: 0:07:11 time: 0.8155 data_time: 0.0296 memory: 16201 loss_prob: 0.2980 loss_thr: 0.2074 loss_db: 0.0533 loss: 0.5587 2022/08/30 23:35:24 - mmengine - INFO - Epoch(train) [1194][60/63] lr: 5.9596e-05 eta: 0:07:00 time: 0.8350 data_time: 0.0300 memory: 16201 loss_prob: 0.3010 loss_thr: 0.2168 loss_db: 0.0536 loss: 0.5715 2022/08/30 23:35:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:35:33 - mmengine - INFO - Epoch(train) [1195][5/63] lr: 5.0593e-05 eta: 0:07:00 time: 1.0392 data_time: 0.2010 memory: 16201 loss_prob: 0.3425 loss_thr: 0.2313 loss_db: 0.0613 loss: 0.6351 2022/08/30 23:35:37 - mmengine - INFO - Epoch(train) [1195][10/63] lr: 5.0593e-05 eta: 0:06:46 time: 0.9976 data_time: 0.2086 memory: 16201 loss_prob: 0.3276 loss_thr: 0.2180 loss_db: 0.0582 loss: 0.6039 2022/08/30 23:35:42 - mmengine - INFO - Epoch(train) [1195][15/63] lr: 5.0593e-05 eta: 0:06:46 time: 0.8718 data_time: 0.0285 memory: 16201 loss_prob: 0.2836 loss_thr: 0.2041 loss_db: 0.0510 loss: 0.5387 2022/08/30 23:35:46 - mmengine - INFO - Epoch(train) [1195][20/63] lr: 5.0593e-05 eta: 0:06:35 time: 0.8695 data_time: 0.0265 memory: 16201 loss_prob: 0.2955 loss_thr: 0.2152 loss_db: 0.0529 loss: 0.5637 2022/08/30 23:35:50 - mmengine - INFO - Epoch(train) [1195][25/63] lr: 5.0593e-05 eta: 0:06:35 time: 0.8181 data_time: 0.0297 memory: 16201 loss_prob: 0.3213 loss_thr: 0.2277 loss_db: 0.0570 loss: 0.6060 2022/08/30 23:35:55 - mmengine - INFO - Epoch(train) [1195][30/63] lr: 5.0593e-05 eta: 0:06:24 time: 0.9002 data_time: 0.0260 memory: 16201 loss_prob: 0.3250 loss_thr: 0.2254 loss_db: 0.0569 loss: 0.6074 2022/08/30 23:35:59 - mmengine - INFO - Epoch(train) [1195][35/63] lr: 5.0593e-05 eta: 0:06:24 time: 0.9125 data_time: 0.0287 memory: 16201 loss_prob: 0.3158 loss_thr: 0.2217 loss_db: 0.0555 loss: 0.5930 2022/08/30 23:36:03 - mmengine - INFO - Epoch(train) [1195][40/63] lr: 5.0593e-05 eta: 0:06:13 time: 0.8162 data_time: 0.0297 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2344 loss_db: 0.0591 loss: 0.6238 2022/08/30 23:36:07 - mmengine - INFO - Epoch(train) [1195][45/63] lr: 5.0593e-05 eta: 0:06:13 time: 0.8025 data_time: 0.0263 memory: 16201 loss_prob: 0.3303 loss_thr: 0.2306 loss_db: 0.0596 loss: 0.6205 2022/08/30 23:36:11 - mmengine - INFO - Epoch(train) [1195][50/63] lr: 5.0593e-05 eta: 0:06:02 time: 0.8310 data_time: 0.0303 memory: 16201 loss_prob: 0.3346 loss_thr: 0.2342 loss_db: 0.0596 loss: 0.6284 2022/08/30 23:36:15 - mmengine - INFO - Epoch(train) [1195][55/63] lr: 5.0593e-05 eta: 0:06:02 time: 0.8470 data_time: 0.0344 memory: 16201 loss_prob: 0.2952 loss_thr: 0.2237 loss_db: 0.0524 loss: 0.5713 2022/08/30 23:36:20 - mmengine - INFO - Epoch(train) [1195][60/63] lr: 5.0593e-05 eta: 0:05:51 time: 0.8454 data_time: 0.0365 memory: 16201 loss_prob: 0.2655 loss_thr: 0.2012 loss_db: 0.0475 loss: 0.5143 2022/08/30 23:36:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:36:28 - mmengine - INFO - Epoch(train) [1196][5/63] lr: 4.1406e-05 eta: 0:05:51 time: 0.9939 data_time: 0.2264 memory: 16201 loss_prob: 0.3140 loss_thr: 0.2351 loss_db: 0.0564 loss: 0.6055 2022/08/30 23:36:32 - mmengine - INFO - Epoch(train) [1196][10/63] lr: 4.1406e-05 eta: 0:05:36 time: 1.0285 data_time: 0.2353 memory: 16201 loss_prob: 0.3236 loss_thr: 0.2453 loss_db: 0.0571 loss: 0.6259 2022/08/30 23:36:36 - mmengine - INFO - Epoch(train) [1196][15/63] lr: 4.1406e-05 eta: 0:05:36 time: 0.8333 data_time: 0.0313 memory: 16201 loss_prob: 0.3209 loss_thr: 0.2294 loss_db: 0.0570 loss: 0.6073 2022/08/30 23:36:40 - mmengine - INFO - Epoch(train) [1196][20/63] lr: 4.1406e-05 eta: 0:05:25 time: 0.8274 data_time: 0.0260 memory: 16201 loss_prob: 0.3111 loss_thr: 0.2176 loss_db: 0.0552 loss: 0.5839 2022/08/30 23:36:44 - mmengine - INFO - Epoch(train) [1196][25/63] lr: 4.1406e-05 eta: 0:05:25 time: 0.8258 data_time: 0.0392 memory: 16201 loss_prob: 0.3126 loss_thr: 0.2194 loss_db: 0.0556 loss: 0.5877 2022/08/30 23:36:48 - mmengine - INFO - Epoch(train) [1196][30/63] lr: 4.1406e-05 eta: 0:05:14 time: 0.8059 data_time: 0.0239 memory: 16201 loss_prob: 0.3203 loss_thr: 0.2199 loss_db: 0.0576 loss: 0.5978 2022/08/30 23:36:53 - mmengine - INFO - Epoch(train) [1196][35/63] lr: 4.1406e-05 eta: 0:05:14 time: 0.8436 data_time: 0.0280 memory: 16201 loss_prob: 0.3129 loss_thr: 0.2141 loss_db: 0.0578 loss: 0.5848 2022/08/30 23:36:57 - mmengine - INFO - Epoch(train) [1196][40/63] lr: 4.1406e-05 eta: 0:05:03 time: 0.8727 data_time: 0.0362 memory: 16201 loss_prob: 0.3275 loss_thr: 0.2195 loss_db: 0.0599 loss: 0.6069 2022/08/30 23:37:01 - mmengine - INFO - Epoch(train) [1196][45/63] lr: 4.1406e-05 eta: 0:05:03 time: 0.8631 data_time: 0.0303 memory: 16201 loss_prob: 0.3369 loss_thr: 0.2311 loss_db: 0.0602 loss: 0.6281 2022/08/30 23:37:06 - mmengine - INFO - Epoch(train) [1196][50/63] lr: 4.1406e-05 eta: 0:04:52 time: 0.8570 data_time: 0.0334 memory: 16201 loss_prob: 0.3399 loss_thr: 0.2307 loss_db: 0.0609 loss: 0.6315 2022/08/30 23:37:10 - mmengine - INFO - Epoch(train) [1196][55/63] lr: 4.1406e-05 eta: 0:04:52 time: 0.8275 data_time: 0.0269 memory: 16201 loss_prob: 0.3225 loss_thr: 0.2090 loss_db: 0.0584 loss: 0.5898 2022/08/30 23:37:14 - mmengine - INFO - Epoch(train) [1196][60/63] lr: 4.1406e-05 eta: 0:04:41 time: 0.8283 data_time: 0.0304 memory: 16201 loss_prob: 0.3139 loss_thr: 0.2058 loss_db: 0.0571 loss: 0.5767 2022/08/30 23:37:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:37:22 - mmengine - INFO - Epoch(train) [1197][5/63] lr: 3.1983e-05 eta: 0:04:41 time: 1.0062 data_time: 0.2426 memory: 16201 loss_prob: 0.3338 loss_thr: 0.2267 loss_db: 0.0587 loss: 0.6192 2022/08/30 23:37:27 - mmengine - INFO - Epoch(train) [1197][10/63] lr: 3.1983e-05 eta: 0:04:27 time: 1.0604 data_time: 0.2605 memory: 16201 loss_prob: 0.3282 loss_thr: 0.2194 loss_db: 0.0567 loss: 0.6043 2022/08/30 23:37:31 - mmengine - INFO - Epoch(train) [1197][15/63] lr: 3.1983e-05 eta: 0:04:27 time: 0.8040 data_time: 0.0302 memory: 16201 loss_prob: 0.3180 loss_thr: 0.2157 loss_db: 0.0563 loss: 0.5899 2022/08/30 23:37:35 - mmengine - INFO - Epoch(train) [1197][20/63] lr: 3.1983e-05 eta: 0:04:16 time: 0.8100 data_time: 0.0192 memory: 16201 loss_prob: 0.3373 loss_thr: 0.2317 loss_db: 0.0598 loss: 0.6289 2022/08/30 23:37:39 - mmengine - INFO - Epoch(train) [1197][25/63] lr: 3.1983e-05 eta: 0:04:16 time: 0.8627 data_time: 0.0378 memory: 16201 loss_prob: 0.3254 loss_thr: 0.2264 loss_db: 0.0567 loss: 0.6085 2022/08/30 23:37:43 - mmengine - INFO - Epoch(train) [1197][30/63] lr: 3.1983e-05 eta: 0:04:05 time: 0.8359 data_time: 0.0313 memory: 16201 loss_prob: 0.2973 loss_thr: 0.2141 loss_db: 0.0511 loss: 0.5626 2022/08/30 23:37:47 - mmengine - INFO - Epoch(train) [1197][35/63] lr: 3.1983e-05 eta: 0:04:05 time: 0.8125 data_time: 0.0240 memory: 16201 loss_prob: 0.2926 loss_thr: 0.2162 loss_db: 0.0511 loss: 0.5598 2022/08/30 23:37:51 - mmengine - INFO - Epoch(train) [1197][40/63] lr: 3.1983e-05 eta: 0:03:54 time: 0.8269 data_time: 0.0311 memory: 16201 loss_prob: 0.2802 loss_thr: 0.1987 loss_db: 0.0505 loss: 0.5294 2022/08/30 23:37:56 - mmengine - INFO - Epoch(train) [1197][45/63] lr: 3.1983e-05 eta: 0:03:54 time: 0.8685 data_time: 0.0313 memory: 16201 loss_prob: 0.2964 loss_thr: 0.2151 loss_db: 0.0541 loss: 0.5656 2022/08/30 23:38:00 - mmengine - INFO - Epoch(train) [1197][50/63] lr: 3.1983e-05 eta: 0:03:42 time: 0.8587 data_time: 0.0307 memory: 16201 loss_prob: 0.3095 loss_thr: 0.2250 loss_db: 0.0547 loss: 0.5892 2022/08/30 23:38:04 - mmengine - INFO - Epoch(train) [1197][55/63] lr: 3.1983e-05 eta: 0:03:42 time: 0.8428 data_time: 0.0327 memory: 16201 loss_prob: 0.3353 loss_thr: 0.2295 loss_db: 0.0583 loss: 0.6231 2022/08/30 23:38:09 - mmengine - INFO - Epoch(train) [1197][60/63] lr: 3.1983e-05 eta: 0:03:31 time: 0.8523 data_time: 0.0363 memory: 16201 loss_prob: 0.3254 loss_thr: 0.2255 loss_db: 0.0582 loss: 0.6091 2022/08/30 23:38:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:38:17 - mmengine - INFO - Epoch(train) [1198][5/63] lr: 2.2235e-05 eta: 0:03:31 time: 0.9668 data_time: 0.2044 memory: 16201 loss_prob: 0.3241 loss_thr: 0.2253 loss_db: 0.0575 loss: 0.6069 2022/08/30 23:38:21 - mmengine - INFO - Epoch(train) [1198][10/63] lr: 2.2235e-05 eta: 0:03:17 time: 1.0150 data_time: 0.2090 memory: 16201 loss_prob: 0.3004 loss_thr: 0.2142 loss_db: 0.0533 loss: 0.5679 2022/08/30 23:38:25 - mmengine - INFO - Epoch(train) [1198][15/63] lr: 2.2235e-05 eta: 0:03:17 time: 0.8578 data_time: 0.0281 memory: 16201 loss_prob: 0.2937 loss_thr: 0.1982 loss_db: 0.0526 loss: 0.5445 2022/08/30 23:38:29 - mmengine - INFO - Epoch(train) [1198][20/63] lr: 2.2235e-05 eta: 0:03:06 time: 0.8614 data_time: 0.0429 memory: 16201 loss_prob: 0.3146 loss_thr: 0.2131 loss_db: 0.0568 loss: 0.5845 2022/08/30 23:38:33 - mmengine - INFO - Epoch(train) [1198][25/63] lr: 2.2235e-05 eta: 0:03:06 time: 0.8284 data_time: 0.0450 memory: 16201 loss_prob: 0.3032 loss_thr: 0.2075 loss_db: 0.0548 loss: 0.5655 2022/08/30 23:38:38 - mmengine - INFO - Epoch(train) [1198][30/63] lr: 2.2235e-05 eta: 0:02:55 time: 0.8143 data_time: 0.0247 memory: 16201 loss_prob: 0.2838 loss_thr: 0.1994 loss_db: 0.0510 loss: 0.5342 2022/08/30 23:38:42 - mmengine - INFO - Epoch(train) [1198][35/63] lr: 2.2235e-05 eta: 0:02:55 time: 0.8541 data_time: 0.0267 memory: 16201 loss_prob: 0.2733 loss_thr: 0.2093 loss_db: 0.0492 loss: 0.5318 2022/08/30 23:38:46 - mmengine - INFO - Epoch(train) [1198][40/63] lr: 2.2235e-05 eta: 0:02:44 time: 0.8606 data_time: 0.0293 memory: 16201 loss_prob: 0.3287 loss_thr: 0.2449 loss_db: 0.0585 loss: 0.6320 2022/08/30 23:38:50 - mmengine - INFO - Epoch(train) [1198][45/63] lr: 2.2235e-05 eta: 0:02:44 time: 0.8279 data_time: 0.0300 memory: 16201 loss_prob: 0.3446 loss_thr: 0.2543 loss_db: 0.0620 loss: 0.6609 2022/08/30 23:38:54 - mmengine - INFO - Epoch(train) [1198][50/63] lr: 2.2235e-05 eta: 0:02:33 time: 0.8146 data_time: 0.0289 memory: 16201 loss_prob: 0.3146 loss_thr: 0.2279 loss_db: 0.0569 loss: 0.5994 2022/08/30 23:38:59 - mmengine - INFO - Epoch(train) [1198][55/63] lr: 2.2235e-05 eta: 0:02:33 time: 0.8788 data_time: 0.0268 memory: 16201 loss_prob: 0.3254 loss_thr: 0.2263 loss_db: 0.0575 loss: 0.6092 2022/08/30 23:39:03 - mmengine - INFO - Epoch(train) [1198][60/63] lr: 2.2235e-05 eta: 0:02:22 time: 0.8811 data_time: 0.0342 memory: 16201 loss_prob: 0.3119 loss_thr: 0.2235 loss_db: 0.0563 loss: 0.5918 2022/08/30 23:39:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:39:11 - mmengine - INFO - Epoch(train) [1199][5/63] lr: 1.1962e-05 eta: 0:02:22 time: 0.9315 data_time: 0.1880 memory: 16201 loss_prob: 0.3166 loss_thr: 0.2269 loss_db: 0.0583 loss: 0.6018 2022/08/30 23:39:15 - mmengine - INFO - Epoch(train) [1199][10/63] lr: 1.1962e-05 eta: 0:02:08 time: 0.9838 data_time: 0.2034 memory: 16201 loss_prob: 0.2999 loss_thr: 0.2155 loss_db: 0.0540 loss: 0.5693 2022/08/30 23:39:20 - mmengine - INFO - Epoch(train) [1199][15/63] lr: 1.1962e-05 eta: 0:02:08 time: 0.8580 data_time: 0.0321 memory: 16201 loss_prob: 0.2842 loss_thr: 0.2147 loss_db: 0.0495 loss: 0.5484 2022/08/30 23:39:24 - mmengine - INFO - Epoch(train) [1199][20/63] lr: 1.1962e-05 eta: 0:01:56 time: 0.8573 data_time: 0.0246 memory: 16201 loss_prob: 0.3175 loss_thr: 0.2258 loss_db: 0.0573 loss: 0.6006 2022/08/30 23:39:28 - mmengine - INFO - Epoch(train) [1199][25/63] lr: 1.1962e-05 eta: 0:01:56 time: 0.8196 data_time: 0.0328 memory: 16201 loss_prob: 0.3354 loss_thr: 0.2290 loss_db: 0.0616 loss: 0.6260 2022/08/30 23:39:32 - mmengine - INFO - Epoch(train) [1199][30/63] lr: 1.1962e-05 eta: 0:01:45 time: 0.8215 data_time: 0.0280 memory: 16201 loss_prob: 0.3189 loss_thr: 0.2230 loss_db: 0.0568 loss: 0.5987 2022/08/30 23:39:36 - mmengine - INFO - Epoch(train) [1199][35/63] lr: 1.1962e-05 eta: 0:01:45 time: 0.7972 data_time: 0.0227 memory: 16201 loss_prob: 0.3221 loss_thr: 0.2183 loss_db: 0.0581 loss: 0.5986 2022/08/30 23:39:40 - mmengine - INFO - Epoch(train) [1199][40/63] lr: 1.1962e-05 eta: 0:01:34 time: 0.8031 data_time: 0.0276 memory: 16201 loss_prob: 0.3231 loss_thr: 0.2214 loss_db: 0.0599 loss: 0.6045 2022/08/30 23:39:44 - mmengine - INFO - Epoch(train) [1199][45/63] lr: 1.1962e-05 eta: 0:01:34 time: 0.8164 data_time: 0.0295 memory: 16201 loss_prob: 0.3034 loss_thr: 0.2153 loss_db: 0.0563 loss: 0.5749 2022/08/30 23:39:48 - mmengine - INFO - Epoch(train) [1199][50/63] lr: 1.1962e-05 eta: 0:01:23 time: 0.8462 data_time: 0.0310 memory: 16201 loss_prob: 0.2801 loss_thr: 0.1994 loss_db: 0.0520 loss: 0.5316 2022/08/30 23:39:52 - mmengine - INFO - Epoch(train) [1199][55/63] lr: 1.1962e-05 eta: 0:01:23 time: 0.8416 data_time: 0.0308 memory: 16201 loss_prob: 0.2853 loss_thr: 0.2029 loss_db: 0.0522 loss: 0.5405 2022/08/30 23:39:56 - mmengine - INFO - Epoch(train) [1199][60/63] lr: 1.1962e-05 eta: 0:01:12 time: 0.8112 data_time: 0.0312 memory: 16201 loss_prob: 0.2975 loss_thr: 0.2092 loss_db: 0.0543 loss: 0.5610 2022/08/30 23:39:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:40:05 - mmengine - INFO - Epoch(train) [1200][5/63] lr: 1.0000e-07 eta: 0:01:12 time: 1.0398 data_time: 0.2319 memory: 16201 loss_prob: 0.2921 loss_thr: 0.2083 loss_db: 0.0532 loss: 0.5536 2022/08/30 23:40:09 - mmengine - INFO - Epoch(train) [1200][10/63] lr: 1.0000e-07 eta: 0:00:58 time: 1.0538 data_time: 0.2405 memory: 16201 loss_prob: 0.3162 loss_thr: 0.2186 loss_db: 0.0566 loss: 0.5914 2022/08/30 23:40:13 - mmengine - INFO - Epoch(train) [1200][15/63] lr: 1.0000e-07 eta: 0:00:58 time: 0.8213 data_time: 0.0324 memory: 16201 loss_prob: 0.3090 loss_thr: 0.2156 loss_db: 0.0542 loss: 0.5789 2022/08/30 23:40:18 - mmengine - INFO - Epoch(train) [1200][20/63] lr: 1.0000e-07 eta: 0:00:47 time: 0.8646 data_time: 0.0228 memory: 16201 loss_prob: 0.3159 loss_thr: 0.2100 loss_db: 0.0559 loss: 0.5819 2022/08/30 23:40:22 - mmengine - INFO - Epoch(train) [1200][25/63] lr: 1.0000e-07 eta: 0:00:47 time: 0.8781 data_time: 0.0373 memory: 16201 loss_prob: 0.2974 loss_thr: 0.2074 loss_db: 0.0535 loss: 0.5583 2022/08/30 23:40:26 - mmengine - INFO - Epoch(train) [1200][30/63] lr: 1.0000e-07 eta: 0:00:36 time: 0.8212 data_time: 0.0280 memory: 16201 loss_prob: 0.3267 loss_thr: 0.2353 loss_db: 0.0589 loss: 0.6209 2022/08/30 23:40:30 - mmengine - INFO - Epoch(train) [1200][35/63] lr: 1.0000e-07 eta: 0:00:36 time: 0.8318 data_time: 0.0213 memory: 16201 loss_prob: 0.3302 loss_thr: 0.2321 loss_db: 0.0600 loss: 0.6223 2022/08/30 23:40:35 - mmengine - INFO - Epoch(train) [1200][40/63] lr: 1.0000e-07 eta: 0:00:25 time: 0.8401 data_time: 0.0298 memory: 16201 loss_prob: 0.2929 loss_thr: 0.2082 loss_db: 0.0526 loss: 0.5537 2022/08/30 23:40:39 - mmengine - INFO - Epoch(train) [1200][45/63] lr: 1.0000e-07 eta: 0:00:25 time: 0.8265 data_time: 0.0318 memory: 16201 loss_prob: 0.2950 loss_thr: 0.2140 loss_db: 0.0515 loss: 0.5605 2022/08/30 23:40:43 - mmengine - INFO - Epoch(train) [1200][50/63] lr: 1.0000e-07 eta: 0:00:14 time: 0.8299 data_time: 0.0343 memory: 16201 loss_prob: 0.2674 loss_thr: 0.2009 loss_db: 0.0470 loss: 0.5153 2022/08/30 23:40:47 - mmengine - INFO - Epoch(train) [1200][55/63] lr: 1.0000e-07 eta: 0:00:14 time: 0.8396 data_time: 0.0268 memory: 16201 loss_prob: 0.2797 loss_thr: 0.2070 loss_db: 0.0490 loss: 0.5357 2022/08/30 23:40:51 - mmengine - INFO - Epoch(train) [1200][60/63] lr: 1.0000e-07 eta: 0:00:03 time: 0.8375 data_time: 0.0273 memory: 16201 loss_prob: 0.3050 loss_thr: 0.2120 loss_db: 0.0541 loss: 0.5711 2022/08/30 23:40:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-dcnv2_fpnc_1200e_icdar2015_20220829_230108 2022/08/30 23:40:53 - mmengine - INFO - Saving checkpoint at 1200 epochs 2022/08/30 23:41:02 - mmengine - INFO - Epoch(val) [1200][5/32] eta: 0:00:03 time: 0.6544 data_time: 0.1130 memory: 16201 2022/08/30 23:41:05 - mmengine - INFO - Epoch(val) [1200][10/32] eta: 0:00:16 time: 0.7305 data_time: 0.1332 memory: 15734 2022/08/30 23:41:08 - mmengine - INFO - Epoch(val) [1200][15/32] eta: 0:00:16 time: 0.6220 data_time: 0.0546 memory: 15734 2022/08/30 23:41:12 - mmengine - INFO - Epoch(val) [1200][20/32] eta: 0:00:07 time: 0.6641 data_time: 0.0636 memory: 15734 2022/08/30 23:41:15 - mmengine - INFO - Epoch(val) [1200][25/32] eta: 0:00:07 time: 0.6831 data_time: 0.0692 memory: 15734 2022/08/30 23:41:18 - mmengine - INFO - Epoch(val) [1200][30/32] eta: 0:00:01 time: 0.6531 data_time: 0.0524 memory: 15734 2022/08/30 23:41:19 - mmengine - INFO - Evaluating hmean-iou... 2022/08/30 23:41:19 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8517, precision: 0.8096, hmean: 0.8301 2022/08/30 23:41:19 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8517, precision: 0.8376, hmean: 0.8446 2022/08/30 23:41:19 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8517, precision: 0.8600, hmean: 0.8558 2022/08/30 23:41:19 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8498, precision: 0.8759, hmean: 0.8627 2022/08/30 23:41:19 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8450, precision: 0.8909, hmean: 0.8673 2022/08/30 23:41:19 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.8238, precision: 0.9135, hmean: 0.8663 2022/08/30 23:41:19 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.5383, precision: 0.9531, hmean: 0.6880 2022/08/30 23:41:19 - mmengine - INFO - Epoch(val) [1200][32/32] icdar/precision: 0.8909 icdar/recall: 0.8450 icdar/hmean: 0.8673