myDeepFakeAI / facefusion /download.py
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import os
import subprocess
import urllib.request
from typing import List
from concurrent.futures import ThreadPoolExecutor
from functools import lru_cache
from tqdm import tqdm
import facefusion.globals
from facefusion import wording
from facefusion.filesystem import is_file
def conditional_download(download_directory_path : str, urls : List[str]) -> None:
with ThreadPoolExecutor() as executor:
for url in urls:
executor.submit(get_download_size, url)
for url in urls:
download_file_path = os.path.join(download_directory_path, os.path.basename(url))
initial = os.path.getsize(download_file_path) if is_file(download_file_path) else 0
total = get_download_size(url)
if initial < total:
with tqdm(total = total, initial = initial, desc = wording.get('downloading'), unit = 'B', unit_scale = True, unit_divisor = 1024, ascii = ' =', disable = facefusion.globals.log_level in [ 'warn', 'error' ]) as progress:
subprocess.Popen([ 'curl', '--create-dirs', '--silent', '--insecure', '--location', '--continue-at', '-', '--output', download_file_path, url ])
current = initial
while current < total:
if is_file(download_file_path):
current = os.path.getsize(download_file_path)
progress.update(current - progress.n)
@lru_cache(maxsize = None)
def get_download_size(url : str) -> int:
try:
response = urllib.request.urlopen(url, timeout = 10)
return int(response.getheader('Content-Length'))
except (OSError, ValueError):
return 0
def is_download_done(url : str, file_path : str) -> bool:
if is_file(file_path):
return get_download_size(url) == os.path.getsize(file_path)
return False