Spaces:
Running
Running
| import glob | |
| import os | |
| def regroup_reds_dataset(train_path, val_path): | |
| """Regroup original REDS datasets. | |
| We merge train and validation data into one folder, and separate the | |
| validation clips in reds_dataset.py. | |
| There are 240 training clips (starting from 0 to 239), | |
| so we name the validation clip index starting from 240 to 269 (total 30 | |
| validation clips). | |
| Args: | |
| train_path (str): Path to the train folder. | |
| val_path (str): Path to the validation folder. | |
| """ | |
| # move the validation data to the train folder | |
| val_folders = glob.glob(os.path.join(val_path, '*')) | |
| for folder in val_folders: | |
| new_folder_idx = int(folder.split('/')[-1]) + 240 | |
| os.system(f'cp -r {folder} {os.path.join(train_path, str(new_folder_idx))}') | |
| if __name__ == '__main__': | |
| # train_sharp | |
| train_path = 'trainsets/REDS/train_sharp' | |
| val_path = 'trainsets/REDS/val_sharp' | |
| regroup_reds_dataset(train_path, val_path) | |
| # train_sharp_bicubic | |
| train_path = 'trainsets/REDS/train_sharp_bicubic/X4' | |
| val_path = 'trainsets/REDS/val_sharp_bicubic/X4' | |
| regroup_reds_dataset(train_path, val_path) | |
| # train_blur (for video deblurring) | |
| train_path = 'trainsets/REDS/train_blur' | |
| val_path = 'trainsets/REDS/val_blur' | |
| regroup_reds_dataset(train_path, val_path) | |