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70 lines
1.7 KiB
Python
70 lines
1.7 KiB
Python
# Text Recognition Testing set, including:
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# Regular Datasets: IIIT5K, SVT, IC13
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# Irregular Datasets: IC15, SVTP, CT80
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test_root = 'data/rec'
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test_img_prefix1 = 'IIIT5K/'
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test_img_prefix2 = 'svt/'
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test_img_prefix3 = 'icdar_2013/Challenge2_Test_Task3_Images/'
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test_img_prefix4 = 'icdar_2015/ch4_test_word_images_gt'
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test_img_prefix5 = 'svtp/'
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test_img_prefix6 = 'ct80/'
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test_ann_file1 = 'IIIT5K/test_label.json'
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test_ann_file2 = 'svt/test_label.json'
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test_ann_file3 = 'icdar_2013/test_label.json'
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test_ann_file4 = 'icdar_2015/test_label.json'
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test_ann_file5 = 'svtp/test_label.json'
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test_ann_file6 = 'ct80/test_label.json'
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IIIT5K = dict(
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type='OCRDataset',
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data_root=test_root,
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data_prefix=dict(img_path=test_img_prefix1),
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ann_file=test_ann_file1,
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test_mode=True,
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pipeline=None)
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SVT = dict(
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type='OCRDataset',
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data_root=test_root,
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data_prefix=dict(img_path=test_img_prefix2),
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ann_file=test_ann_file2,
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test_mode=True,
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pipeline=None)
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IC13 = dict(
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type='OCRDataset',
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data_root=test_root,
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data_prefix=dict(img_path=test_img_prefix3),
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ann_file=test_ann_file3,
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test_mode=True,
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pipeline=None)
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IC15 = dict(
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type='OCRDataset',
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data_root=test_root,
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data_prefix=dict(img_path=test_img_prefix4),
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ann_file=test_ann_file4,
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test_mode=True,
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pipeline=None)
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SVTP = dict(
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type='OCRDataset',
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data_root=test_root,
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data_prefix=dict(img_path=test_img_prefix5),
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ann_file=test_ann_file5,
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test_mode=True,
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pipeline=None)
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CUTE80 = dict(
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type='OCRDataset',
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data_root=test_root,
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data_prefix=dict(img_path=test_img_prefix6),
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ann_file=test_ann_file6,
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test_mode=True,
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pipeline=None)
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test_list = [IIIT5K, SVT, IC13, IC15, SVTP, CUTE80]
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