mirror of https://github.com/open-mmlab/mmocr.git
40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
data_root = 'data/cocotextv2'
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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='http://images.cocodataset.org/zips/train2014.zip',
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save_name='cocotextv2_train_img.zip',
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md5='0da8c0bd3d6becc4dcb32757491aca88',
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content=['image'],
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mapping=[[
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'cocotextv2_train_img/train2014', 'textdet_imgs/imgs'
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]]),
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dict(
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url='https://github.com/bgshih/cocotext/releases/download/dl/'
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'cocotext.v2.zip',
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save_name='cocotextv2_annotation.zip',
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md5='5e39f7d6f2f11324c6451e63523c440c',
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content=['annotation'],
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mapping=[[
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'cocotextv2_annotation/cocotext.v2.json',
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'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/imgs'),
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parser=dict(type='COCOTextDetAnnParser', variant='cocotext'),
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packer=dict(type='TextDetPacker'),
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dumper=dict(type='JsonDumper'))
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val_preparer = train_preparer
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delete = ['annotations', 'cocotextv2_annotation', 'cocotextv2_train_img']
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config_generator = dict(type='TextDetConfigGenerator')
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