mirror of https://github.com/open-mmlab/mmocr.git
124 lines
4.1 KiB
Python
124 lines
4.1 KiB
Python
dictionary = dict(
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type='Dictionary',
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dict_file='{{ fileDirname }}/../../../dicts/english_digits_symbols.txt',
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with_start=True,
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with_end=True,
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same_start_end=True,
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with_padding=True,
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with_unknown=True)
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model = dict(
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type='RobustScanner',
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data_preprocessor=dict(
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type='TextRecogDataPreprocessor',
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mean=[127, 127, 127],
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std=[127, 127, 127]),
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backbone=dict(type='ResNet31OCR'),
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encoder=dict(
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type='ChannelReductionEncoder', in_channels=512, out_channels=128),
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decoder=dict(
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type='RobustScannerFuser',
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hybrid_decoder=dict(
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type='SequenceAttentionDecoder', dim_input=512, dim_model=128),
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position_decoder=dict(
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type='PositionAttentionDecoder', dim_input=512, dim_model=128),
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in_channels=[512, 512],
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postprocessor=dict(type='AttentionPostprocessor'),
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module_loss=dict(
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type='CEModuleLoss', ignore_first_char=True, reduction='mean'),
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dictionary=dictionary,
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max_seq_len=30))
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file_client_args = dict(backend='disk')
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train_pipeline = [
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dict(
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type='LoadImageFromFile',
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file_client_args=file_client_args,
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ignore_empty=True,
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min_size=2),
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dict(type='LoadOCRAnnotations', with_text=True),
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dict(
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type='RescaleToHeight',
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height=48,
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min_width=48,
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max_width=160,
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width_divisor=4),
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dict(type='PadToWidth', width=160),
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dict(
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type='PackTextRecogInputs',
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meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio'))
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]
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test_pipeline = [
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dict(type='LoadImageFromFile', file_client_args=file_client_args),
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dict(
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type='RescaleToHeight',
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height=48,
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min_width=48,
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max_width=160,
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width_divisor=4),
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dict(type='PadToWidth', width=160),
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# add loading annotation after ``Resize`` because ground truth
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# does not need to do resize data transform
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dict(type='LoadOCRAnnotations', with_text=True),
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dict(
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type='PackTextRecogInputs',
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meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio'))
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]
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tta_pipeline = [
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dict(type='LoadImageFromFile', file_client_args=file_client_args),
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dict(
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type='TestTimeAug',
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transforms=[
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[
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dict(
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type='ConditionApply',
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true_transforms=[
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dict(
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type='ImgAugWrapper',
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args=[dict(cls='Rot90', k=0, keep_size=False)])
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],
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condition="results['img_shape'][1]<results['img_shape'][0]"
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),
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dict(
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type='ConditionApply',
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true_transforms=[
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dict(
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type='ImgAugWrapper',
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args=[dict(cls='Rot90', k=1, keep_size=False)])
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],
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condition="results['img_shape'][1]<results['img_shape'][0]"
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),
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dict(
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type='ConditionApply',
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true_transforms=[
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dict(
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type='ImgAugWrapper',
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args=[dict(cls='Rot90', k=3, keep_size=False)])
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],
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condition="results['img_shape'][1]<results['img_shape'][0]"
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),
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],
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[
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dict(
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type='RescaleToHeight',
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height=48,
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min_width=48,
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max_width=160,
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width_divisor=4),
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],
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[dict(type='PadToWidth', width=160)],
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# add loading annotation after ``Resize`` because ground truth
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# does not need to do resize data transform
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[dict(type='LoadOCRAnnotations', with_text=True)],
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[
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dict(
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type='PackTextRecogInputs',
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meta_keys=('img_path', 'ori_shape', 'img_shape',
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'valid_ratio'))
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]
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])
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]
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