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unpaired_imgs_256x256.py 2.54 KB
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add part mmgeneration code  
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train_dataset_type = 'UnpairedImageDataset'
val_dataset_type = 'UnpairedImageDataset'
img_norm_cfg = dict(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
domain_a = None  # set by user
domain_b = None  # set by user
train_pipeline = [
    dict(
        type='LoadImageFromFile',
        io_backend='disk',
        key=f'img_{domain_a}',
        flag='color'),
    dict(
        type='LoadImageFromFile',
        io_backend='disk',
        key=f'img_{domain_b}',
        flag='color'),
    dict(
        type='Resize',
        keys=[f'img_{domain_a}', f'img_{domain_b}'],
        scale=(286, 286),
        interpolation='bicubic'),
    dict(
        type='Crop',
        keys=[f'img_{domain_a}', f'img_{domain_b}'],
        crop_size=(256, 256),
        random_crop=True),
    dict(type='Flip', keys=[f'img_{domain_a}'], direction='horizontal'),
    dict(type='Flip', keys=[f'img_{domain_b}'], direction='horizontal'),
    dict(type='RescaleToZeroOne', keys=[f'img_{domain_a}', f'img_{domain_b}']),
    dict(
        type='Normalize',
        keys=[f'img_{domain_a}', f'img_{domain_b}'],
        to_rgb=False,
        mean=[0.5, 0.5, 0.5],
        std=[0.5, 0.5, 0.5]),
    dict(type='ImageToTensor', keys=[f'img_{domain_a}', f'img_{domain_b}']),
    dict(
        type='Collect',
        keys=[f'img_{domain_a}', f'img_{domain_b}'],
        meta_keys=[f'img_{domain_a}_path', f'img_{domain_b}_path'])
]
test_pipeline = [
    dict(
        type='LoadImageFromFile', io_backend='disk', key='image',
        flag='color'),
    dict(
        type='Resize',
        keys=['image'],
        scale=(256, 256),
        interpolation='bicubic'),
    dict(type='RescaleToZeroOne', keys=['image']),
    dict(
        type='Normalize',
        keys=['image'],
        to_rgb=False,
        mean=[0.5, 0.5, 0.5],
        std=[0.5, 0.5, 0.5]),
    dict(type='ImageToTensor', keys=['image']),
    dict(type='Collect', keys=['image'], meta_keys=['image_path'])
]
data_root = None
data = dict(
    samples_per_gpu=1,
    workers_per_gpu=4,
    drop_last=True,
    train=dict(
        type=train_dataset_type,
        dataroot=data_root,
        pipeline=train_pipeline,
        test_mode=False,
        domain_a=domain_a,
        domain_b=domain_b),
    val=dict(
        type=val_dataset_type,
        dataroot=data_root,
        pipeline=test_pipeline,
        test_mode=True,
        domain_a=domain_a,
        domain_b=domain_b),
    test=dict(
        type=val_dataset_type,
        dataroot=data_root,
        pipeline=test_pipeline,
        test_mode=True,
        domain_a=domain_a,
        domain_b=domain_b))