mirror of https://github.com/open-mmlab/mmocr.git
101 lines
3.1 KiB
Python
101 lines
3.1 KiB
Python
_base_ = [
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'../../_base_/recog_datasets/ST_MJ_train.py',
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'../../_base_/recog_datasets/academic_test.py',
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'../../_base_/default_runtime.py',
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'../../_base_/schedules/schedule_adam_step_20e.py',
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]
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# dataset settings
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train_list = {{_base_.train_list}}
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file_client_args = dict(backend='disk')
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default_hooks = dict(logger=dict(type='LoggerHook', interval=100))
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train_pipeline = [
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dict(type='LoadImageFromFile', file_client_args=file_client_args),
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dict(type='LoadOCRAnnotations', with_text=True),
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dict(type='Resize', scale=(128, 32)),
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dict(
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type='RandomApply',
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prob=0.5,
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transforms=[
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dict(
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type='RandomChoice',
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transforms=[
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dict(
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type='RandomRotate',
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max_angle=15,
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),
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dict(
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type='TorchVisionWrapper',
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op='RandomAffine',
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degrees=15,
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translate=(0.3, 0.3),
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scale=(0.5, 2.),
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shear=(-45, 45),
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),
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dict(
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type='TorchVisionWrapper',
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op='RandomPerspective',
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distortion_scale=0.5,
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p=1,
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),
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])
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],
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),
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dict(
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type='RandomApply',
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prob=0.25,
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transforms=[
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dict(type='PyramidRescale'),
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dict(
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type='mmdet.Albu',
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transforms=[
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dict(type='GaussNoise', var_limit=(20, 20), p=0.5),
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dict(type='MotionBlur', blur_limit=6, p=0.5),
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]),
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]),
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dict(
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type='RandomApply',
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prob=0.25,
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transforms=[
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dict(
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type='TorchVisionWrapper',
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op='ColorJitter',
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brightness=0.5,
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saturation=0.5,
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contrast=0.5,
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hue=0.1),
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]),
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dict(
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type='PackTextRecogInputs',
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meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio'))
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]
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test_pipeline = [
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dict(type='LoadImageFromFile', file_client_args=file_client_args),
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dict(type='LoadOCRAnnotations', with_text=True),
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dict(type='Resize', scale=(128, 32)),
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dict(
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type='PackTextRecogInputs',
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meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio',
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'instances'))
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]
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train_dataloader = dict(
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batch_size=192 * 4,
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num_workers=32,
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persistent_workers=True,
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sampler=dict(type='DefaultSampler', shuffle=True),
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dataset=dict(
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type='ConcatDataset', datasets=train_list, pipeline=train_pipeline))
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visualizer = dict(type='TextRecogLocalVisualizer', name='visualizer')
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test_cfg = dict(type='MultiTestLoop')
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val_cfg = dict(type='MultiValLoop')
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val_dataloader = _base_.val_dataloader
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test_dataloader = _base_.test_dataloader
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for dataloader in test_dataloader:
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dataloader['dataset']['pipeline'] = test_pipeline
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for dataloader in val_dataloader:
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dataloader['dataset']['pipeline'] = test_pipeline
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