Source code for unconditional_imgs_flip_lanczos_resize_256x256

# Copyright (c) OpenMMLab. All rights reserved.
[docs]dataset_type = 'BasicImageDataset'

[docs]train_pipeline = [
    dict(type='LoadImageFromFile', key='gt'),
    dict(
        type='Resize',
        keys='gt',
        scale=(256, 256),
        interpolation='lanczos',
        backend='pillow'),
    dict(type='Flip', keys=['gt'], direction='horizontal'),
    dict(type='PackInputs')
]

# `batch_size` and `data_root` need to be set.
[docs]train_dataloader = dict(
    batch_size=None,
    num_workers=4,
    persistent_workers=True,
    sampler=dict(type='InfiniteSampler', shuffle=True),
    dataset=dict(
        type=dataset_type,
        data_prefix=dict(gt=''),
        data_root=None,  # set by user
        pipeline=train_pipeline))

[docs]val_dataloader = dict(
    batch_size=None,
    num_workers=4,
    dataset=dict(
        type=dataset_type,
        data_prefix=dict(gt=''),
        data_root=None,  # set by user
        pipeline=train_pipeline),
    sampler=dict(type='DefaultSampler', shuffle=False),
    persistent_workers=True)

[docs]test_dataloader = dict(
    batch_size=None,
    num_workers=4,
    dataset=dict(
        type=dataset_type,
        data_prefix=dict(gt=''),
        data_root=None,  # set by user
        pipeline=train_pipeline),
    sampler=dict(type='DefaultSampler', shuffle=False),
    persistent_workers=True)