| 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
|
|
|
| def sizeof_fmt(size, suffix='B'):
|
| """Get human readable file size.
|
|
|
| Args:
|
| size (int): File size.
|
| suffix (str): Suffix. Default: 'B'.
|
|
|
| Return:
|
| str: Formated file siz.
|
| """
|
| for unit in ['', 'K', 'M', 'G', 'T', 'P', 'E', 'Z']:
|
| if abs(size) < 1024.0:
|
| return f'{size:3.1f} {unit}{suffix}'
|
| size /= 1024.0
|
| return f'{size:3.1f} Y{suffix}'
|
|
|
|
|
| def download_file_from_google_drive(file_id, save_path):
|
| """Download files from google drive.
|
| Ref:
|
| https://stackoverflow.com/questions/25010369/wget-curl-large-file-from-google-drive # noqa E501
|
| 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)
|
|
|
|
|
| response_file_size = session.get(URL, params=params, stream=True, headers={'Range': 'bytes=0-2'})
|
| print(response_file_size)
|
| 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:
|
| 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.
|
| Ref: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:
|
| 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 |
