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# Text Recognition Training set, including:
# Synthetic Datasets: SynthText, Syn90k
train_root = 'data/mixture'
train_img_prefix1 = f'{train_root}/Syn90k/mnt/ramdisk/max/90kDICT32px'
train_ann_file1 = f'{train_root}/Syn90k/label.lmdb'
train1 = dict(
type='OCRDataset',
img_prefix=train_img_prefix1,
ann_file=train_ann_file1,
loader=dict(
type='AnnFileLoader',
repeat=1,
file_format='lmdb',
parser=dict(type='LineJsonParser', keys=['filename', 'text'])),
pipeline=None,
test_mode=False)
train_img_prefix2 = f'{train_root}/SynthText/' + \
'synthtext/SynthText_patch_horizontal'
train_ann_file2 = f'{train_root}/SynthText/label.lmdb'
train_img_prefix3 = f'{train_root}/SynthText_Add'
train_ann_file3 = f'{train_root}/SynthText_Add/label.txt'
train2 = {key: value for key, value in train1.items()}
train2['img_prefix'] = train_img_prefix2
train2['ann_file'] = train_ann_file2
train3 = dict(
type='OCRDataset',
img_prefix=train_img_prefix3,
ann_file=train_ann_file3,
loader=dict(
type='AnnFileLoader',
repeat=1,
file_format='txt',
parser=dict(
type='LineStrParser',
keys=['filename', 'text'],
keys_idx=[0, 1],
separator=' ')),
pipeline=None,
test_mode=False)
train_list = [train1, train2, train3]
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