22 lines
679 B
Python
22 lines
679 B
Python
_base_ = ['./efficientnetv2-b0_8xb32_in1k.py']
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# model setting
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model = dict(backbone=dict(arch='b1'), head=dict(in_channels=1280, ))
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train_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(type='EfficientNetRandomCrop', scale=192),
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dict(type='RandomFlip', prob=0.5, direction='horizontal'),
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dict(type='PackInputs'),
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]
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(type='EfficientNetCenterCrop', crop_size=240, crop_padding=0),
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dict(type='PackInputs'),
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]
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train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
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val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
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test_dataloader = dict(dataset=dict(pipeline=test_pipeline))
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