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| dictionary = dict( | |
| type='Dictionary', | |
| dict_file='{{ fileDirname }}/../../../dicts/english_digits_symbols.txt', | |
| with_padding=True, | |
| with_unknown=True, | |
| same_start_end=True, | |
| with_start=True, | |
| with_end=True) | |
| model = dict( | |
| type='ASTER', | |
| preprocessor=dict( | |
| type='STN', | |
| in_channels=3, | |
| resized_image_size=(32, 64), | |
| output_image_size=(32, 100), | |
| num_control_points=20), | |
| backbone=dict( | |
| type='ResNet', | |
| in_channels=3, | |
| stem_channels=[32], | |
| block_cfgs=dict(type='BasicBlock', use_conv1x1='True'), | |
| arch_layers=[3, 4, 6, 6, 3], | |
| arch_channels=[32, 64, 128, 256, 512], | |
| strides=[(2, 2), (2, 2), (2, 1), (2, 1), (2, 1)], | |
| init_cfg=[ | |
| dict(type='Kaiming', layer='Conv2d'), | |
| dict(type='Constant', val=1, layer='BatchNorm2d'), | |
| ]), | |
| encoder=dict(type='ASTEREncoder', in_channels=512), | |
| decoder=dict( | |
| type='ASTERDecoder', | |
| max_seq_len=25, | |
| in_channels=512, | |
| emb_dims=512, | |
| attn_dims=512, | |
| hidden_size=512, | |
| postprocessor=dict(type='AttentionPostprocessor'), | |
| module_loss=dict( | |
| type='CEModuleLoss', flatten=True, ignore_first_char=True), | |
| dictionary=dictionary, | |
| ), | |
| data_preprocessor=dict( | |
| type='TextRecogDataPreprocessor', | |
| mean=[127.5, 127.5, 127.5], | |
| std=[127.5, 127.5, 127.5])) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', ignore_empty=True, min_size=0), | |
| dict(type='LoadOCRAnnotations', with_text=True), | |
| dict(type='Resize', scale=(256, 64)), | |
| dict( | |
| type='PackTextRecogInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='Resize', scale=(256, 64)), | |
| dict(type='LoadOCRAnnotations', with_text=True), | |
| dict( | |
| type='PackTextRecogInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio', | |
| 'instances')) | |
| ] | |
| tta_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='TestTimeAug', | |
| transforms=[[ | |
| dict( | |
| type='ConditionApply', | |
| true_transforms=[ | |
| dict( | |
| type='ImgAugWrapper', | |
| args=[dict(cls='Rot90', k=0, keep_size=False)]) | |
| ], | |
| condition="results['img_shape'][1]<results['img_shape'][0]"), | |
| dict( | |
| type='ConditionApply', | |
| true_transforms=[ | |
| dict( | |
| type='ImgAugWrapper', | |
| args=[dict(cls='Rot90', k=1, keep_size=False)]) | |
| ], | |
| condition="results['img_shape'][1]<results['img_shape'][0]"), | |
| dict( | |
| type='ConditionApply', | |
| true_transforms=[ | |
| dict( | |
| type='ImgAugWrapper', | |
| args=[dict(cls='Rot90', k=3, keep_size=False)]) | |
| ], | |
| condition="results['img_shape'][1]<results['img_shape'][0]"), | |
| ], [dict(type='Resize', scale=(256, 64))], | |
| [dict(type='LoadOCRAnnotations', with_text=True)], | |
| [ | |
| dict( | |
| type='PackTextRecogInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', | |
| 'valid_ratio', 'instances')) | |
| ]]) | |
| ] | |