mirror of https://github.com/open-mmlab/mmocr.git
68 lines
2.5 KiB
Python
68 lines
2.5 KiB
Python
data_root = 'data/textocr'
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cache_path = 'data/cache'
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train_preparer = dict(
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obtainer=dict(
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type='NaiveDataObtainer',
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cache_path=cache_path,
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files=[
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dict(
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url='https://dl.fbaipublicfiles.com/textvqa/images/'
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'train_val_images.zip',
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save_name='textocr_textdet_img.zip',
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md5='d12dd8098899044e4ae1af34db7ecfef',
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content=['image'],
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mapping=[[
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'textocr_textdet_img/train_images', 'textdet_imgs/images'
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]]),
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dict(
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url='https://dl.fbaipublicfiles.com/textvqa/data/textocr/'
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'TextOCR_0.1_train.json',
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save_name='textocr_textdet_train.json',
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md5='0f8ba1beefd2ca4d08a4f82bcbe6cfb4',
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content=['annotation'],
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mapping=[[
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'textocr_textdet_train.json', 'annotations/train.json'
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]]),
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]),
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gatherer=dict(
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type='MonoGatherer',
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ann_name='train.json',
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img_dir='textdet_imgs/images'),
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parser=dict(type='COCOTextDetAnnParser', variant='textocr'),
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packer=dict(type='TextDetPacker'),
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dumper=dict(type='JsonDumper'))
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val_preparer = dict(
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obtainer=dict(
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type='NaiveDataObtainer',
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cache_path=cache_path,
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files=[
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dict(
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url='https://dl.fbaipublicfiles.com/textvqa/images/'
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'train_val_images.zip',
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save_name='textocr_textdet_img.zip',
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md5='d12dd8098899044e4ae1af34db7ecfef',
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content=['image'],
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mapping=[[
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'textocr_textdet_img/train_images', 'textdet_imgs/images'
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]]),
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dict(
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url='https://dl.fbaipublicfiles.com/textvqa/data/textocr/'
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'TextOCR_0.1_val.json',
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save_name='textocr_textdet_val.json',
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md5='fb151383ea7b3c530cde9ef0d5c08347',
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content=['annotation'],
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mapping=[['textocr_textdet_val.json',
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'annotations/val.json']]),
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]),
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gatherer=dict(
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type='MonoGatherer',
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ann_name='val.json',
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img_dir='textdet_imgs/images'),
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parser=dict(type='COCOTextDetAnnParser', variant='textocr'),
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packer=dict(type='TextDetPacker'),
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dumper=dict(type='JsonDumper'))
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delete = ['annotations', 'textocr_textdet_img']
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config_generator = dict(type='TextDetConfigGenerator')
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