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