import os
from typing import Callable, Optional
from torchvision.datasets import ImageFolder
from torchvision.datasets.utils import check_integrity, download_and_extract_archive
[docs]class Places365(ImageFolder):
base_folder = "places365"
filename = "val_256.tar"
file_md5 = "e27b17d8d44f4af9a78502beb927f808"
url = "http://data.csail.mit.edu/places/places365/val_256.tar"
# size: 36500
def __init__(
self, root: str, split=None, transform: Optional[Callable] = None, download: bool = False, **kwargs
) -> None:
self.root = os.path.expanduser(root)
self.dataset_folder = os.path.join(self.root, self.base_folder)
self.archive = os.path.join(self.root, self.filename)
if download:
self.download()
if not self._check_integrity():
raise RuntimeError("Dataset not found or corrupted." + " You can use download=True to download it")
super().__init__(self.dataset_folder, transform=transform, **kwargs)
def _check_integrity(self) -> bool:
return check_integrity(self.archive, self.file_md5)
def _check_exists(self) -> bool:
return os.path.exists(self.dataset_folder)
[docs] def download(self) -> None:
if self._check_integrity() and self._check_exists():
return
download_and_extract_archive(
self.url, download_root=self.root, extract_root=self.dataset_folder, md5=self.file_md5
)