_base_ = [ '../../_base_/default_runtime.py', '../../_base_/schedules/schedule_sgd_100k_iters.py', '../../_base_/det_models/dbnet_r50dcnv2_fpnc.py', '../../_base_/det_datasets/synthtext.py', '../../_base_/det_pipelines/dbnet_pipeline.py' ] train_list = {{_base_.train_list}} test_list = {{_base_.test_list}} img_norm_cfg_r50dcnv2 = dict( mean=[122.67891434, 116.66876762, 104.00698793], std=[58.395, 57.12, 57.375], to_rgb=True) train_pipeline_r50dcnv2 = [ dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), dict( type='LoadTextAnnotations', with_bbox=True, with_mask=True, poly2mask=False), dict(type='ColorJitter', brightness=32.0 / 255, saturation=0.5), dict(type='Normalize', **img_norm_cfg_r50dcnv2), dict( type='ImgAug', args=[['Fliplr', 0.5], dict(cls='Affine', rotate=[-10, 10]), ['Resize', [0.5, 3.0]]], clip_invalid_ploys=False), dict(type='EastRandomCrop', target_size=(640, 640)), dict(type='DBNetTargets', shrink_ratio=0.4), dict(type='Pad', size_divisor=32), dict( type='CustomFormatBundle', keys=['gt_shrink', 'gt_shrink_mask', 'gt_thr', 'gt_thr_mask'], visualize=dict(flag=False, boundary_key='gt_shrink')), dict( type='Collect', keys=['img', 'gt_shrink', 'gt_shrink_mask', 'gt_thr', 'gt_thr_mask']) ] test_pipeline_4068_1024 = {{_base_.test_pipeline_4068_1024}} data = dict( samples_per_gpu=16, workers_per_gpu=8, val_dataloader=dict(samples_per_gpu=1), test_dataloader=dict(samples_per_gpu=1), train=dict( type='UniformConcatDataset', datasets=train_list, pipeline=train_pipeline_r50dcnv2), val=dict( type='UniformConcatDataset', datasets=test_list, pipeline=test_pipeline_4068_1024), test=dict( type='UniformConcatDataset', datasets=test_list, pipeline=test_pipeline_4068_1024)) evaluation = dict(interval=999999, metric='hmean-iou') # do not evaluate