mirror of https://github.com/open-mmlab/mmocr.git
127 lines
5.0 KiB
Python
127 lines
5.0 KiB
Python
# This configuration prepares the ICDAR13 857 and 1015
|
|
# version, and uses ICDAR13 1015 version by default.
|
|
# You may uncomment the lines if you want to you the original version,
|
|
# which contains 1095 samples.
|
|
# You can check out the generated base config and use the 857
|
|
# version by using its corresponding config variables in your model.
|
|
|
|
data_root = 'data/icdar2013'
|
|
cache_path = 'data/cache'
|
|
|
|
train_preparer = dict(
|
|
obtainer=dict(
|
|
type='NaiveDataObtainer',
|
|
cache_path=cache_path,
|
|
files=[
|
|
dict(
|
|
url='https://rrc.cvc.uab.es/downloads/'
|
|
'Challenge2_Training_Task3_Images_GT.zip',
|
|
save_name='ic13_textrecog_train_img_gt.zip',
|
|
md5='6f0dbc823645968030878df7543f40a4',
|
|
content=['image'],
|
|
mapping=[
|
|
# ['ic13_textrecog_train_img_gt/gt.txt',
|
|
# 'annotations/train.txt'],
|
|
['ic13_textrecog_train_img_gt', 'textrecog_imgs/train']
|
|
]),
|
|
dict(
|
|
url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
|
|
'icdar_2013/train_labels.json',
|
|
save_name='ic13_train_labels.json',
|
|
md5='008fcd0056e72c4cf3064fb4d1fce81b',
|
|
content=['annotation'],
|
|
mapping=[['ic13_train_labels.json', 'textrecog_train.json']]),
|
|
]))
|
|
|
|
# Note that we offer two versions of test set annotations as follows.Please
|
|
# choose one of them to download and comment the other. By default, we use the
|
|
# second one.
|
|
# 1. The original official annotation, which contains 1095 test
|
|
# samples.
|
|
|
|
# Uncomment the test_preparer if you want to use the original 1095 version.
|
|
|
|
# test_preparer = dict(
|
|
# obtainer=dict(
|
|
# type='NaiveDataObtainer',
|
|
# cache_path=cache_path,
|
|
# files=[
|
|
# dict(
|
|
# url='https://rrc.cvc.uab.es/downloads/'
|
|
# 'Challenge2_Test_Task3_Images.zip',
|
|
# save_name='ic13_textrecog_test_img.zip',
|
|
# md5='3206778eebb3a5c5cc15c249010bf77f',
|
|
# split=['test'],
|
|
# content=['image'],
|
|
# mapping=[['ic13_textrecog_test_img',
|
|
# 'textrecog_imgs/test']]),
|
|
# dict(
|
|
# url='https://rrc.cvc.uab.es/downloads/'
|
|
# 'Challenge2_Test_Task3_GT.txt',
|
|
# save_name='ic13_textrecog_test_gt.txt',
|
|
# md5='2634060ed8fe6e7a4a9b8d68785835a1',
|
|
# split=['test'],
|
|
# content=['annotation'],
|
|
# mapping=[[
|
|
# 'ic13_textrecog_test_gt.txt', 'annotations/test.txt'
|
|
# ]]), # noqa
|
|
# # The 857 version further pruned words shorter than 3 characters.
|
|
# dict(
|
|
# url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
|
|
# 'icdar_2013/textrecog_test_857.json',
|
|
# save_name='textrecog_test_857.json',
|
|
# md5='3bed3985b0c51a989ad4006f6de8352b',
|
|
# split=['test'],
|
|
# content=['annotation'],
|
|
# ),
|
|
# ]),
|
|
# gatherer=dict(type='MonoGatherer', ann_name='test.txt'),
|
|
# parser=dict(
|
|
# type='ICDARTxtTextRecogAnnParser', separator=', ',
|
|
# format='img, text'), # noqa
|
|
# packer=dict(type='TextRecogPacker'),
|
|
# dumper=dict(type='JsonDumper'),
|
|
# )
|
|
|
|
# 2. The widely-used version for academic purpose, which filters
|
|
# out words with non-alphanumeric characters. This version contains
|
|
# 1015 test samples.
|
|
test_preparer = dict(
|
|
obtainer=dict(
|
|
type='NaiveDataObtainer',
|
|
cache_path=cache_path,
|
|
files=[
|
|
dict(
|
|
url='https://rrc.cvc.uab.es/downloads/'
|
|
'Challenge2_Test_Task3_Images.zip',
|
|
save_name='ic13_textrecog_test_img.zip',
|
|
md5='3206778eebb3a5c5cc15c249010bf77f',
|
|
split=['test'],
|
|
content=['image'],
|
|
mapping=[['ic13_textrecog_test_img', 'textrecog_imgs/test']]),
|
|
dict(
|
|
url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
|
|
'icdar_2013/textrecog_test_1015.json',
|
|
save_name='textrecog_test.json',
|
|
md5='68fdd818f63df8b93dc952478952009a',
|
|
split=['test'],
|
|
content=['annotation'],
|
|
),
|
|
# The 857 version further pruned words shorter than 3 characters.
|
|
dict(
|
|
url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
|
|
'icdar_2013/textrecog_test_857.json',
|
|
save_name='textrecog_test_857.json',
|
|
md5='3bed3985b0c51a989ad4006f6de8352b',
|
|
split=['test'],
|
|
content=['annotation'],
|
|
),
|
|
]))
|
|
|
|
config_generator = dict(
|
|
type='TextRecogConfigGenerator',
|
|
test_anns=[
|
|
dict(ann_file='textrecog_test.json'),
|
|
dict(dataset_postfix='857', ann_file='textrecog_test_857.json')
|
|
])
|