mmocr/dataset_zoo/sroie/textdet.py

56 lines
1.9 KiB
Python

data_root = 'data/sroie'
cache_path = 'data/cache'
data_obtainer = dict(
type='NaiveDataObtainer',
cache_path=cache_path,
data_root=data_root,
files=[
dict(
url='https://download.openmmlab.com/mmocr/data/'
'sroie/0325updated.task1train(626p).zip',
save_name='0325updated.task1train(626p).zip',
md5='16137490f6865caac75772b9111d348c',
split=['train'],
content=['image', 'annotation'],
mapping=[[
'0325updated/0325updated.task1train(626p)/*.jpg',
'textdet_imgs/train'
],
[
'0325updated/0325updated.task1train(626p)/*.txt',
'annotations/train'
]]),
dict(
url='https://download.openmmlab.com/mmocr/data/'
'sroie/task1&2_test(361p).zip',
save_name='task1&2_test(361p).zip',
md5='1bde54705db0995c57a6e34cce437fea',
split=['test'],
content=['image'],
mapping=[[
'task1&2_test(361p)/fulltext_test(361p)', 'textdet_imgs/test'
]]),
dict(
url='https://download.openmmlab.com/mmocr/data/sroie/text.zip',
save_name='text.zip',
md5='8c534653f252ff4d3943fa27a956a74b',
split=['test'],
content=['annotation'],
mapping=[['text', 'annotations/test']]),
])
data_converter = dict(
type='TextDetDataConverter',
splits=['train', 'test'],
data_root=data_root,
gatherer=dict(
type='pair_gather',
suffixes=['.jpg'],
rule=[r'X(\d+)\.([jJ][pP][gG])', r'X\1.txt']),
parser=dict(type='SROIETextDetAnnParser', encoding='utf-8-sig'),
dumper=dict(type='JsonDumper'),
delete=['text', 'task1&2_test(361p)', '0325updated', 'annotations'])
config_generator = dict(type='TextDetConfigGenerator', data_root=data_root)