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import argparse
import os
from os import path as osp
# from basicsr.utils.download_util import download_file_from_google_drive
import gdown
def download_pretrained_models(method, file_ids):
save_path_root = f'./weights/{method}'
os.makedirs(save_path_root, exist_ok=True)
for file_name, file_id in file_ids.items():
file_url = 'https://drive.google.com/uc?id='+file_id
save_path = osp.abspath(osp.join(save_path_root, file_name))
if osp.exists(save_path):
user_response = input(f'{file_name} already exist. Do you want to cover it? Y/N\n')
if user_response.lower() == 'y':
print(f'Covering {file_name} to {save_path}')
gdown.download(file_url, save_path, quiet=False)
# download_file_from_google_drive(file_id, save_path)
elif user_response.lower() == 'n':
print(f'Skipping {file_name}')
else:
raise ValueError('Wrong input. Only accepts Y/N.')
else:
print(f'Downloading {file_name} to {save_path}')
gdown.download(file_url, save_path, quiet=False)
# download_file_from_google_drive(file_id, save_path)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'method',
type=str,
help=("Options: 'CodeFormer' 'facelib'. Set to 'all' to download all the models."))
args = parser.parse_args()
# file name: file id
# 'dlib': {
# 'mmod_human_face_detector-4cb19393.dat': '1qD-OqY8M6j4PWUP_FtqfwUPFPRMu6ubX',
# 'shape_predictor_5_face_landmarks-c4b1e980.dat': '1vF3WBUApw4662v9Pw6wke3uk1qxnmLdg',
# 'shape_predictor_68_face_landmarks-fbdc2cb8.dat': '1tJyIVdCHaU6IDMDx86BZCxLGZfsWB8yq'
# }
file_ids = {
'CodeFormer': {
'codeformer.pth': '1v_E_vZvP-dQPF55Kc5SRCjaKTQXDz-JB'
},
'facelib': {
'yolov5l-face.pth': '131578zMA6B2x8VQHyHfa6GEPtulMCNzV',
'parsing_parsenet.pth': '16pkohyZZ8ViHGBk3QtVqxLZKzdo466bK'
}
}
if args.method == 'all':
for method in file_ids.keys():
download_pretrained_models(method, file_ids[method])
else:
download_pretrained_models(args.method, file_ids[args.method]) |