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import math
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import os
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import requests
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from torch.hub import download_url_to_file, get_dir
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from tqdm import tqdm
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from urllib.parse import urlparse
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def sizeof_fmt(size, suffix='B'):
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"""Get human readable file size.
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Args:
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size (int): File size.
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suffix (str): Suffix. Default: 'B'.
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Return:
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str: Formated file siz.
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"""
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for unit in ['', 'K', 'M', 'G', 'T', 'P', 'E', 'Z']:
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if abs(size) < 1024.0:
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return f'{size:3.1f} {unit}{suffix}'
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size /= 1024.0
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return f'{size:3.1f} Y{suffix}'
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def download_file_from_google_drive(file_id, save_path):
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"""Download files from google drive.
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Ref:
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https://stackoverflow.com/questions/25010369/wget-curl-large-file-from-google-drive # noqa E501
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Args:
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file_id (str): File id.
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save_path (str): Save path.
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"""
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session = requests.Session()
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URL = 'https://docs.google.com/uc?export=download'
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params = {'id': file_id}
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response = session.get(URL, params=params, stream=True)
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token = get_confirm_token(response)
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if token:
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params['confirm'] = token
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response = session.get(URL, params=params, stream=True)
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response_file_size = session.get(URL, params=params, stream=True, headers={'Range': 'bytes=0-2'})
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print(response_file_size)
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if 'Content-Range' in response_file_size.headers:
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file_size = int(response_file_size.headers['Content-Range'].split('/')[1])
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else:
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file_size = None
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save_response_content(response, save_path, file_size)
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def get_confirm_token(response):
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for key, value in response.cookies.items():
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if key.startswith('download_warning'):
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return value
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return None
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def save_response_content(response, destination, file_size=None, chunk_size=32768):
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if file_size is not None:
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pbar = tqdm(total=math.ceil(file_size / chunk_size), unit='chunk')
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readable_file_size = sizeof_fmt(file_size)
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else:
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pbar = None
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with open(destination, 'wb') as f:
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downloaded_size = 0
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for chunk in response.iter_content(chunk_size):
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downloaded_size += chunk_size
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if pbar is not None:
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pbar.update(1)
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pbar.set_description(f'Download {sizeof_fmt(downloaded_size)} / {readable_file_size}')
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if chunk:
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f.write(chunk)
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if pbar is not None:
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pbar.close()
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def load_file_from_url(url, model_dir=None, progress=True, file_name=None):
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"""Load file form http url, will download models if necessary.
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Ref:https://github.com/1adrianb/face-alignment/blob/master/face_alignment/utils.py
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Args:
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url (str): URL to be downloaded.
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model_dir (str): The path to save the downloaded model. Should be a full path. If None, use pytorch hub_dir.
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Default: None.
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progress (bool): Whether to show the download progress. Default: True.
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file_name (str): The downloaded file name. If None, use the file name in the url. Default: None.
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Returns:
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str: The path to the downloaded file.
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"""
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if model_dir is None:
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hub_dir = get_dir()
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model_dir = os.path.join(hub_dir, 'checkpoints')
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os.makedirs(model_dir, exist_ok=True)
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parts = urlparse(url)
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filename = os.path.basename(parts.path)
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if file_name is not None:
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filename = file_name
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cached_file = os.path.abspath(os.path.join(model_dir, filename))
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if not os.path.exists(cached_file):
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print(f'Downloading: "{url}" to {cached_file}\n')
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download_url_to_file(url, cached_file, hash_prefix=None, progress=progress)
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return cached_file |
