Spaces:
Running
Running
import math | |
import os | |
import requests | |
from torch.hub import download_url_to_file, get_dir | |
from tqdm import tqdm | |
from urllib.parse import urlparse | |
from .misc import sizeof_fmt | |
def download_file_from_google_drive(file_id, save_path): | |
"""Download files from google drive. | |
Reference: https://stackoverflow.com/questions/25010369/wget-curl-large-file-from-google-drive | |
Args: | |
file_id (str): File id. | |
save_path (str): Save path. | |
""" | |
session = requests.Session() | |
URL = 'https://docs.google.com/uc?export=download' | |
params = {'id': file_id} | |
response = session.get(URL, params=params, stream=True) | |
token = get_confirm_token(response) | |
if token: | |
params['confirm'] = token | |
response = session.get(URL, params=params, stream=True) | |
# get file size | |
response_file_size = session.get(URL, params=params, stream=True, headers={'Range': 'bytes=0-2'}) | |
if 'Content-Range' in response_file_size.headers: | |
file_size = int(response_file_size.headers['Content-Range'].split('/')[1]) | |
else: | |
file_size = None | |
save_response_content(response, save_path, file_size) | |
def get_confirm_token(response): | |
for key, value in response.cookies.items(): | |
if key.startswith('download_warning'): | |
return value | |
return None | |
def save_response_content(response, destination, file_size=None, chunk_size=32768): | |
if file_size is not None: | |
pbar = tqdm(total=math.ceil(file_size / chunk_size), unit='chunk') | |
readable_file_size = sizeof_fmt(file_size) | |
else: | |
pbar = None | |
with open(destination, 'wb') as f: | |
downloaded_size = 0 | |
for chunk in response.iter_content(chunk_size): | |
downloaded_size += chunk_size | |
if pbar is not None: | |
pbar.update(1) | |
pbar.set_description(f'Download {sizeof_fmt(downloaded_size)} / {readable_file_size}') | |
if chunk: # filter out keep-alive new chunks | |
f.write(chunk) | |
if pbar is not None: | |
pbar.close() | |
def load_file_from_url(url, model_dir=None, progress=True, file_name=None): | |
"""Load file form http url, will download models if necessary. | |
Reference: https://github.com/1adrianb/face-alignment/blob/master/face_alignment/utils.py | |
Args: | |
url (str): URL to be downloaded. | |
model_dir (str): The path to save the downloaded model. Should be a full path. If None, use pytorch hub_dir. | |
Default: None. | |
progress (bool): Whether to show the download progress. Default: True. | |
file_name (str): The downloaded file name. If None, use the file name in the url. Default: None. | |
Returns: | |
str: The path to the downloaded file. | |
""" | |
if model_dir is None: # use the pytorch hub_dir | |
hub_dir = get_dir() | |
model_dir = os.path.join(hub_dir, 'checkpoints') | |
os.makedirs(model_dir, exist_ok=True) | |
parts = urlparse(url) | |
filename = os.path.basename(parts.path) | |
if file_name is not None: | |
filename = file_name | |
cached_file = os.path.abspath(os.path.join(model_dir, filename)) | |
if not os.path.exists(cached_file): | |
print(f'Downloading: "{url}" to {cached_file}\n') | |
download_url_to_file(url, cached_file, hash_prefix=None, progress=progress) | |
return cached_file | |