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| dictionary = dict( | |
| type='Dictionary', | |
| dict_file='{{ fileDirname }}/../../../dicts/english_digits_symbols.txt', | |
| with_start=True, | |
| with_end=True, | |
| same_start_end=True, | |
| with_padding=True, | |
| with_unknown=True) | |
| model = dict( | |
| type='RobustScanner', | |
| data_preprocessor=dict( | |
| type='TextRecogDataPreprocessor', | |
| mean=[127, 127, 127], | |
| std=[127, 127, 127]), | |
| backbone=dict(type='ResNet31OCR'), | |
| encoder=dict( | |
| type='ChannelReductionEncoder', in_channels=512, out_channels=128), | |
| decoder=dict( | |
| type='RobustScannerFuser', | |
| hybrid_decoder=dict( | |
| type='SequenceAttentionDecoder', dim_input=512, dim_model=128), | |
| position_decoder=dict( | |
| type='PositionAttentionDecoder', dim_input=512, dim_model=128), | |
| in_channels=[512, 512], | |
| postprocessor=dict(type='AttentionPostprocessor'), | |
| module_loss=dict( | |
| type='CEModuleLoss', ignore_first_char=True, reduction='mean'), | |
| dictionary=dictionary, | |
| max_seq_len=30)) | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', ignore_empty=True, min_size=2), | |
| dict(type='LoadOCRAnnotations', with_text=True), | |
| dict( | |
| type='RescaleToHeight', | |
| height=48, | |
| min_width=48, | |
| max_width=160, | |
| width_divisor=4), | |
| dict(type='PadToWidth', width=160), | |
| dict( | |
| type='PackTextRecogInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RescaleToHeight', | |
| height=48, | |
| min_width=48, | |
| max_width=160, | |
| width_divisor=4), | |
| dict(type='PadToWidth', width=160), | |
| # add loading annotation after ``Resize`` because ground truth | |
| # does not need to do resize data transform | |
| dict(type='LoadOCRAnnotations', with_text=True), | |
| dict( | |
| type='PackTextRecogInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) | |
| ] | |
| 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='RescaleToHeight', | |
| height=48, | |
| min_width=48, | |
| max_width=160, | |
| width_divisor=4), | |
| ], | |
| [dict(type='PadToWidth', width=160)], | |
| # add loading annotation after ``Resize`` because ground truth | |
| # does not need to do resize data transform | |
| [dict(type='LoadOCRAnnotations', with_text=True)], | |
| [ | |
| dict( | |
| type='PackTextRecogInputs', | |
| meta_keys=('img_path', 'ori_shape', 'img_shape', | |
| 'valid_ratio')) | |
| ] | |
| ]) | |
| ] | |