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_base_ = ['textdet.py']
_base_.train_preparer.obtainer.files.append(
dict(
url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
'SynthText/subset_textrecog_train.json',
save_name='subset_textrecog_train.json',
md5='151c4edd1cc240362046d3a6f8f4b4c6',
split=['train'],
content=['annotation']))
_base_.train_preparer.obtainer.files.append(
dict(
url='https://download.openmmlab.com/mmocr/data/1.x/recog/'
'SynthText/alphanumeric_textrecog_train.json',
save_name='alphanumeric_textrecog_train.json',
md5='89b80163435794ca117a124d081d68a9',
split=['train'],
content=['annotation']))
_base_.train_preparer.gatherer.img_dir = 'textdet_imgs/train'
_base_.train_preparer.packer.type = 'TextRecogCropPacker'
config_generator = dict(
type='TextRecogConfigGenerator',
train_anns=[
dict(ann_file='textrecog_train.json', dataset_postfix=''),
dict(ann_file='subset_textrecog_train.json', dataset_postfix='sub'),
dict(
ann_file='alphanumeric_textrecog_train.json',
dataset_postfix='an'),
],
test_anns=None)
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