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Running
on
Zero
File size: 2,886 Bytes
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import os
from typing import List, Tuple
from urllib.parse import urlparse
from torch.hub import download_url_to_file, get_dir
def load_file_list(file_list_path: str) -> List[str]:
files = []
# each line in file list contains a path of an image
with open(file_list_path, "r") as fin:
for line in fin:
path = line.strip()
if path:
files.append(path)
return files
def list_image_files(
img_dir: str,
exts: Tuple[str]=(".jpg", ".png", ".jpeg"),
follow_links: bool=False,
log_progress: bool=False,
log_every_n_files: int=10000,
max_size: int=-1
) -> List[str]:
files = []
for dir_path, _, file_names in os.walk(img_dir, followlinks=follow_links):
early_stop = False
for file_name in file_names:
if os.path.splitext(file_name)[1].lower() in exts:
if max_size >= 0 and len(files) >= max_size:
early_stop = True
break
files.append(os.path.join(dir_path, file_name))
if log_progress and len(files) % log_every_n_files == 0:
print(f"find {len(files)} images in {img_dir}")
if early_stop:
break
return files
def get_file_name_parts(file_path: str) -> Tuple[str, str, str]:
parent_path, file_name = os.path.split(file_path)
stem, ext = os.path.splitext(file_name)
return parent_path, stem, ext
# https://github.com/XPixelGroup/BasicSR/blob/master/basicsr/utils/download_util.py/
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: # 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 |