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| _base_ = [ | |
| '_base_dbnet_resnet18_fpnc.py', | |
| '../_base_/datasets/totaltext.py', | |
| '../_base_/default_runtime.py', | |
| '../_base_/schedules/schedule_sgd_1200e.py', | |
| ] | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', color_type='color_ignore_orientation'), | |
| dict( | |
| type='LoadOCRAnnotations', | |
| with_polygon=True, | |
| with_bbox=True, | |
| with_label=True, | |
| ), | |
| dict(type='FixInvalidPolygon', min_poly_points=4), | |
| dict( | |
| type='TorchVisionWrapper', | |
| op='ColorJitter', | |
| brightness=32.0 / 255, | |
| saturation=0.5), | |
| dict( | |
| type='ImgAugWrapper', | |
| args=[['Fliplr', 0.5], | |
| dict(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=(1333, 736), keep_ratio=True), | |
| dict( | |
| type='LoadOCRAnnotations', | |
| with_polygon=True, | |
| with_bbox=True, | |
| with_label=True, | |
| ), | |
| dict(type='FixInvalidPolygon', min_poly_points=4), | |
| dict( | |
| type='PackTextDetInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) | |
| ] | |
| # dataset settings | |
| totaltext_textdet_train = _base_.totaltext_textdet_train | |
| totaltext_textdet_test = _base_.totaltext_textdet_test | |
| totaltext_textdet_train.pipeline = train_pipeline | |
| totaltext_textdet_test.pipeline = test_pipeline | |
| train_dataloader = dict( | |
| batch_size=16, | |
| num_workers=16, | |
| pin_memory=True, | |
| persistent_workers=True, | |
| sampler=dict(type='DefaultSampler', shuffle=True), | |
| dataset=totaltext_textdet_train) | |
| val_dataloader = dict( | |
| batch_size=1, | |
| num_workers=1, | |
| pin_memory=True, | |
| persistent_workers=True, | |
| sampler=dict(type='DefaultSampler', shuffle=False), | |
| dataset=totaltext_textdet_test) | |
| test_dataloader = val_dataloader | |
| auto_scale_lr = dict(base_batch_size=16) | |