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| _base_ = [ | |
| '../_base_/datasets/icdar2017.py', | |
| '../_base_/default_runtime.py', | |
| '../_base_/schedules/schedule_adam_600e.py', | |
| '_base_panet_resnet50_fpem-ffm.py', | |
| ] | |
| default_hooks = dict(checkpoint=dict(type='CheckpointHook', interval=20), ) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), | |
| dict( | |
| type='LoadOCRAnnotations', | |
| with_polygon=True, | |
| with_bbox=True, | |
| with_label=True, | |
| ), | |
| dict(type='ShortScaleAspectJitter', short_size=800, scale_divisor=32), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='RandomRotate', max_angle=10), | |
| dict(type='TextDetRandomCrop', target_size=(800, 800)), | |
| dict(type='Pad', size=(800, 800)), | |
| dict( | |
| type='TorchVisionWrapper', | |
| op='ColorJitter', | |
| brightness=32.0 / 255, | |
| saturation=0.5), | |
| dict( | |
| type='PackTextDetInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), | |
| # TODO Replace with mmcv.RescaleToShort when it's ready | |
| dict( | |
| type='ShortScaleAspectJitter', | |
| short_size=800, | |
| scale_divisor=1, | |
| ratio_range=(1.0, 1.0), | |
| aspect_ratio_range=(1.0, 1.0)), | |
| 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')) | |
| ] | |
| icdar2017_textdet_train = _base_.icdar2017_textdet_train | |
| icdar2017_textdet_test = _base_.icdar2017_textdet_test | |
| # pipeline settings | |
| icdar2017_textdet_train.pipeline = train_pipeline | |
| icdar2017_textdet_test.pipeline = test_pipeline | |
| train_dataloader = dict( | |
| batch_size=64, | |
| num_workers=8, | |
| persistent_workers=True, | |
| sampler=dict(type='DefaultSampler', shuffle=True), | |
| dataset=icdar2017_textdet_train) | |
| val_dataloader = dict( | |
| batch_size=1, | |
| num_workers=4, | |
| persistent_workers=True, | |
| sampler=dict(type='DefaultSampler', shuffle=False), | |
| dataset=icdar2017_textdet_test) | |
| test_dataloader = val_dataloader | |
| val_evaluator = dict( | |
| type='HmeanIOUMetric', pred_score_thrs=dict(start=0.3, stop=1, step=0.05)) | |
| test_evaluator = val_evaluator | |
| auto_scale_lr = dict(base_batch_size=64) | |