swinir_psnr-x2s64w8d6e180_8xb4-lr1e-4-600k_df2k-ost.py

_base_ = ['../_base_/default_runtime.py']

experiment_name = 'swinir_psnr-x2s64w8d6e180_8xb4-lr1e-4-600k_df2k-ost'
work_dir = f'./work_dirs/{experiment_name}'
save_dir = './work_dirs/'

scale = 2
img_size = 64

# model settings
model = dict(
    type='BaseEditModel',
    generator=dict(
        type='SwinIRNet',
        upscale=scale,
        in_chans=3,
        img_size=img_size,
        window_size=8,
        img_range=1.0,
        depths=[6, 6, 6, 6, 6, 6],
        embed_dim=180,
        num_heads=[6, 6, 6, 6, 6, 6],
        mlp_ratio=2,
        upsampler='nearest+conv',
        resi_connection='1conv'),
    pixel_loss=dict(type='L1Loss', loss_weight=1.0, reduction='mean'),
    data_preprocessor=dict(
        type='DataPreprocessor', mean=[0., 0., 0.], std=[255., 255., 255.]))

test_pipeline = [
    dict(
        type='LoadImageFromFile',
        key='img',
        color_type='color',
        channel_order='rgb',
        imdecode_backend='cv2'),
    dict(
        type='LoadImageFromFile',
        key='gt',
        color_type='color',
        channel_order='rgb',
        imdecode_backend='cv2'),
    dict(type='PackInputs')
]

test_dataloader = dict(
    num_workers=4,
    persistent_workers=False,
    drop_last=False,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type='BasicImageDataset',
        metainfo=dict(dataset_type='realsrset', task_name='realsr'),
        data_root='data/RealSRSet+5images',
        data_prefix=dict(img='', gt=''),
        pipeline=test_pipeline))

test_evaluator = [dict(type='NIQE', input_order='CHW', convert_to='Y')]

test_cfg = dict(type='TestLoop')