import glob
import os
[docs]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 = 'datasets/REDS/train_sharp'
val_path = 'datasets/REDS/val_sharp'
regroup_reds_dataset(train_path, val_path)
# train_sharp_bicubic
train_path = 'datasets/REDS/train_sharp_bicubic/X4'
val_path = 'datasets/REDS/val_sharp_bicubic/X4'
regroup_reds_dataset(train_path, val_path)