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on
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Running
on
Zero
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 |