MAERec-Gradio / configs /textrecog /nrtr /_base_nrtr_resnet31.py
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dictionary = dict(
type='Dictionary',
dict_file='{{ fileDirname }}/../../../dicts/english_digits_symbols.txt',
with_padding=True,
with_unknown=True,
same_start_end=True,
with_start=True,
with_end=True)
model = dict(
type='NRTR',
backbone=dict(
type='ResNet31OCR',
layers=[1, 2, 5, 3],
channels=[32, 64, 128, 256, 512, 512],
stage4_pool_cfg=dict(kernel_size=(2, 1), stride=(2, 1)),
last_stage_pool=True),
encoder=dict(type='NRTREncoder'),
decoder=dict(
type='NRTRDecoder',
module_loss=dict(
type='CEModuleLoss', ignore_first_char=True, flatten=True),
postprocessor=dict(type='AttentionPostprocessor'),
dictionary=dictionary,
max_seq_len=30,
),
data_preprocessor=dict(
type='TextRecogDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375]))
train_pipeline = [
dict(type='LoadImageFromFile', ignore_empty=True, min_size=0),
dict(type='LoadOCRAnnotations', with_text=True),
dict(
type='RescaleToHeight',
height=32,
min_width=32,
max_width=160,
width_divisor=4),
dict(type='PadToWidth', width=160),
dict(
type='PackTextRecogInputs',
meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio'))
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='RescaleToHeight',
height=32,
min_width=32,
max_width=160,
width_divisor=16),
dict(type='PadToWidth', width=160),
# add loading annotation after ``Resize`` because ground truth
# does not need to do resize data transform
dict(type='LoadOCRAnnotations', with_text=True),
dict(
type='PackTextRecogInputs',
meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio'))
]
tta_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='TestTimeAug',
transforms=[
[
dict(
type='ConditionApply',
true_transforms=[
dict(
type='ImgAugWrapper',
args=[dict(cls='Rot90', k=0, keep_size=False)])
],
condition="results['img_shape'][1]<results['img_shape'][0]"
),
dict(
type='ConditionApply',
true_transforms=[
dict(
type='ImgAugWrapper',
args=[dict(cls='Rot90', k=1, keep_size=False)])
],
condition="results['img_shape'][1]<results['img_shape'][0]"
),
dict(
type='ConditionApply',
true_transforms=[
dict(
type='ImgAugWrapper',
args=[dict(cls='Rot90', k=3, keep_size=False)])
],
condition="results['img_shape'][1]<results['img_shape'][0]"
),
],
[
dict(
type='RescaleToHeight',
height=32,
min_width=32,
max_width=160,
width_divisor=16)
],
[dict(type='PadToWidth', width=160)],
# add loading annotation after ``Resize`` because ground truth
# does not need to do resize data transform
[dict(type='LoadOCRAnnotations', with_text=True)],
[
dict(
type='PackTextRecogInputs',
meta_keys=('img_path', 'ori_shape', 'img_shape',
'valid_ratio'))
]
])
]