mirror of
https://github.com/open-mmlab/mmocr.git
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43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
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data_root = 'data/icdar2015'
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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://rrc.cvc.uab.es/downloads/'
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'ch4_training_word_images_gt.zip',
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save_name='ic15_textrecog_train_img_gt.zip',
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md5='600caf8c6a64a3dcf638839820edcca9',
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split=['train'],
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content=['image', 'annotation'],
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mapping=[[
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'ic15_textrecog_train_img_gt/gt.txt', 'annotations/train.txt'
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], ['ic15_textrecog_train_img_gt', 'textrecog_imgs/train']]),
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dict(
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url='https://rrc.cvc.uab.es/downloads/ch4_test_word_images_gt.zip',
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save_name='ic15_textrecog_test_img.zip',
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md5='d7a71585f4cc69f89edbe534e7706d5d',
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split=['test'],
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content=['image'],
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mapping=[['ic15_textrecog_test_img', 'textrecog_imgs/test']]),
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dict(
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url='https://rrc.cvc.uab.es/downloads/'
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'Challenge4_Test_Task3_GT.txt',
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save_name='ic15_textrecog_test_gt.txt',
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md5='d7a71585f4cc69f89edbe534e7706d5d',
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split=['test'],
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content=['annotation'],
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mapping=[['ic15_textrecog_test_gt.txt', 'annotations/test.txt']])
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])
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data_converter = dict(
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type='TextRecogDataConverter',
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splits=['train', 'test'],
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data_root=data_root,
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gatherer=dict(type='mono_gather', mapping="f'{split}.txt'"),
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parser=dict(type='ICDARTxtTextRecogAnnParser'),
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dumper=dict(type='JsonDumper'))
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