mirror of https://github.com/open-mmlab/mmocr.git
53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
# The official annotations of CUTE80 has some typos, and we have provided
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# the fixed version as done in
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# https://github.com/clovaai/deep-text-recognition-benchmark by default.
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# If you want to use the original version, please comment out the following
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# lines: L31-L38, and uncomment L23-L30, L40-L49.
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data_root = 'data/cute80'
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cache_path = 'data/cache'
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data_obtainer = dict(
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type='NaiveDataObtainer',
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cache_path=cache_path,
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data_root=data_root,
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files=[
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dict(
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url='https://download.openmmlab.com/mmocr/data/mixture/ct80/'
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'timage.tar.gz',
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save_name='ct80.tar.gz',
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md5='9f3b1fe0e76f1fdfc70de3a365603d5e',
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split=['test'],
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content=['image'],
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mapping=[['ct80/timage', 'textrecog_imgs/test']]),
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# dict(
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# url='https://download.openmmlab.com/mmocr/data/mixture/ct80/'
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# 'test_label.txt',
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# save_name='ct80_test.txt',
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# md5='f679dec62916d3268aff9cd81990d260',
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# split=['test'],
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# content=['annotation'],
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# mapping=[['ct80_test.txt', 'annotations/test.txt']])
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dict(
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url='https://download.openmmlab.com/mmocr/data/1.x/recog/ct80/'
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'textrecog_test.json',
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save_name='textrecog_test.json',
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md5='9c5c79d843b900325e7fd453b318cad9',
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split=['test'],
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content=['annotation'])
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])
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# data_converter = dict(
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# type='TextRecogDataConverter',
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# splits=['test'],
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# data_root=data_root,
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# gatherer=dict(type='mono_gather', test_ann='test.txt'),
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# parser=dict(
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# type='ICDARTxtTextRecogAnnParser',
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# separator=' ',
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# format='img text ignore1 ignore2'),
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# dumper=dict(type='JsonDumper'))
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config_generator = dict(
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type='TextRecogConfigGenerator', data_root=data_root, train_anns=None)
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