basicsr.data.reds_dataset

class basicsr.data.reds_dataset.REDSDataset(opt)[source]

Bases: Dataset

REDS dataset for training.

The keys are generated from a meta info txt file. basicsr/data/meta_info/meta_info_REDS_GT.txt

Each line contains: 1. subfolder (clip) name; 2. frame number; 3. image shape, separated by a white space. Examples: 000 100 (720,1280,3) 001 100 (720,1280,3) …

Key examples: “000/00000000” GT (gt): Ground-Truth; LQ (lq): Low-Quality, e.g., low-resolution/blurry/noisy/compressed frames.

Parameters

opt (dict) –

Config for train dataset. It contains the following keys: dataroot_gt (str): Data root path for gt. dataroot_lq (str): Data root path for lq. dataroot_flow (str, optional): Data root path for flow. meta_info_file (str): Path for meta information file. val_partition (str): Validation partition types. ‘REDS4’ or

’official’.

io_backend (dict): IO backend type and other kwarg.

num_frame (int): Window size for input frames. gt_size (int): Cropped patched size for gt patches. interval_list (list): Interval list for temporal augmentation. random_reverse (bool): Random reverse input frames. use_hflip (bool): Use horizontal flips. use_rot (bool): Use rotation (use vertical flip and transposing h

and w for implementation).

scale (bool): Scale, which will be added automatically.

class basicsr.data.reds_dataset.REDSRecurrentDataset(opt)[source]