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| import argparse | |
| from os import path as osp | |
| from basicsr.utils import scandir | |
| from basicsr.utils.lmdb_util import make_lmdb_from_imgs | |
| def prepare_keys(folder_path, suffix='png'): | |
| """Prepare image path list and keys for DIV2K dataset. | |
| Args: | |
| folder_path (str): Folder path. | |
| Returns: | |
| list[str]: Image path list. | |
| list[str]: Key list. | |
| """ | |
| print('Reading image path list ...') | |
| img_path_list = sorted( | |
| list(scandir(folder_path, suffix=suffix, recursive=False))) | |
| keys = [img_path.split('.{}'.format(suffix))[0] for img_path in sorted(img_path_list)] | |
| return img_path_list, keys | |
| def create_lmdb_for_reds(): | |
| folder_path = './datasets/REDS/val/sharp_300' | |
| lmdb_path = './datasets/REDS/val/sharp_300.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| # | |
| folder_path = './datasets/REDS/val/blur_300' | |
| lmdb_path = './datasets/REDS/val/blur_300.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'jpg') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/REDS/train/train_sharp' | |
| lmdb_path = './datasets/REDS/train/train_sharp.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/REDS/train/train_blur_jpeg' | |
| lmdb_path = './datasets/REDS/train/train_blur_jpeg.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'jpg') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| def create_lmdb_for_gopro(): | |
| folder_path = './datasets/GoPro/train/blur_crops' | |
| lmdb_path = './datasets/GoPro/train/blur_crops.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/GoPro/train/sharp_crops' | |
| lmdb_path = './datasets/GoPro/train/sharp_crops.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/GoPro/test/target' | |
| lmdb_path = './datasets/GoPro/test/target.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/GoPro/test/input' | |
| lmdb_path = './datasets/GoPro/test/input.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| def create_lmdb_for_rain13k(): | |
| folder_path = './datasets/Rain13k/train/input' | |
| lmdb_path = './datasets/Rain13k/train/input.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'jpg') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/Rain13k/train/target' | |
| lmdb_path = './datasets/Rain13k/train/target.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'jpg') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| def create_lmdb_for_SIDD(): | |
| folder_path = './datasets/SIDD/train/input_crops' | |
| lmdb_path = './datasets/SIDD/train/input_crops.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'PNG') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/SIDD/train/gt_crops' | |
| lmdb_path = './datasets/SIDD/train/gt_crops.lmdb' | |
| img_path_list, keys = prepare_keys(folder_path, 'PNG') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| #for val | |
| folder_path = './datasets/SIDD/val/input_crops' | |
| lmdb_path = './datasets/SIDD/val/input_crops.lmdb' | |
| mat_path = './datasets/SIDD/ValidationNoisyBlocksSrgb.mat' | |
| if not osp.exists(folder_path): | |
| os.makedirs(folder_path) | |
| assert osp.exists(mat_path) | |
| data = scio.loadmat(mat_path)['ValidationNoisyBlocksSrgb'] | |
| N, B, H ,W, C = data.shape | |
| data = data.reshape(N*B, H, W, C) | |
| for i in tqdm(range(N*B)): | |
| cv2.imwrite(osp.join(folder_path, 'ValidationBlocksSrgb_{}.png'.format(i)), cv2.cvtColor(data[i,...], cv2.COLOR_RGB2BGR)) | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |
| folder_path = './datasets/SIDD/val/gt_crops' | |
| lmdb_path = './datasets/SIDD/val/gt_crops.lmdb' | |
| mat_path = './datasets/SIDD/ValidationGtBlocksSrgb.mat' | |
| if not osp.exists(folder_path): | |
| os.makedirs(folder_path) | |
| assert osp.exists(mat_path) | |
| data = scio.loadmat(mat_path)['ValidationGtBlocksSrgb'] | |
| N, B, H ,W, C = data.shape | |
| data = data.reshape(N*B, H, W, C) | |
| for i in tqdm(range(N*B)): | |
| cv2.imwrite(osp.join(folder_path, 'ValidationBlocksSrgb_{}.png'.format(i)), cv2.cvtColor(data[i,...], cv2.COLOR_RGB2BGR)) | |
| img_path_list, keys = prepare_keys(folder_path, 'png') | |
| make_lmdb_from_imgs(folder_path, lmdb_path, img_path_list, keys) | |