File size: 2,358 Bytes
24c4def
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
data_root = 'data/iiit5k'
cache_path = 'data/cache'

train_preparer = dict(
    obtainer=dict(
        type='NaiveDataObtainer',
        cache_path=cache_path,
        files=[
            dict(
                url='http://cvit.iiit.ac.in/projects/SceneTextUnderstanding/'
                'IIIT5K-Word_V3.0.tar.gz',
                save_name='IIIT5K.tar.gz',
                md5='56781bc327d22066aa1c239ee788fd46',
                content=['image'],
                mapping=[['IIIT5K/IIIT5K/train', 'textrecog_imgs/train']]),
            dict(
                url='https://download.openmmlab.com/mmocr/data/mixture/IIIT5K/'
                'train_label.txt',
                save_name='iiit5k_train.txt',
                md5='beee914aaf3ec5794622b843d743c5a6',
                content=['annotation'],
                mapping=[['iiit5k_train.txt', 'annotations/train.txt']])
        ]),
    gatherer=dict(type='MonoGatherer', ann_name='train.txt'),
    parser=dict(
        type='ICDARTxtTextRecogAnnParser',
        encoding='utf-8',
        separator=' ',
        format='img text'),
    packer=dict(type='TextRecogPacker'),
    dumper=dict(type='JsonDumper'),
)

test_preparer = dict(
    obtainer=dict(
        type='NaiveDataObtainer',
        cache_path=cache_path,
        files=[
            dict(
                url='http://cvit.iiit.ac.in/projects/SceneTextUnderstanding/'
                'IIIT5K-Word_V3.0.tar.gz',
                save_name='IIIT5K.tar.gz',
                md5='56781bc327d22066aa1c239ee788fd46',
                content=['image'],
                mapping=[['IIIT5K/IIIT5K/test', 'textrecog_imgs/test']]),
            dict(
                url='https://download.openmmlab.com/mmocr/data/mixture/IIIT5K/'
                'test_label.txt',
                save_name='iiit5k_test.txt',
                md5='117bcd9b4245f61fa57bfb37361674b3',
                content=['annotation'],
                mapping=[['iiit5k_test.txt', 'annotations/test.txt']])
        ]),
    gatherer=dict(type='MonoGatherer', ann_name='test.txt'),
    parser=dict(
        type='ICDARTxtTextRecogAnnParser',
        encoding='utf-8',
        separator=' ',
        format='img text'),
    packer=dict(type='TextRecogPacker'),
    dumper=dict(type='JsonDumper'),
)
delete = ['annotations', 'IIIT5K']
config_generator = dict(type='TextRecogConfigGenerator')