Source code for torchvision.datasets.country211

from pathlib import Path
from typing import Callable, Optional, Union

from .folder import ImageFolder
from .utils import download_and_extract_archive, verify_str_arg

[docs]class Country211(ImageFolder): """`The Country211 Data Set <>`_ from OpenAI. This dataset was built by filtering the images from the YFCC100m dataset that have GPS coordinate corresponding to a ISO-3166 country code. The dataset is balanced by sampling 150 train images, 50 validation images, and 100 test images for each country. Args: root (str or ``pathlib.Path``): Root directory of the dataset. split (string, optional): The dataset split, supports ``"train"`` (default), ``"valid"`` and ``"test"``. transform (callable, optional): A function/transform that takes in a PIL image and returns a transformed version. E.g, ``transforms.RandomCrop``. target_transform (callable, optional): A function/transform that takes in the target and transforms it. download (bool, optional): If True, downloads the dataset from the internet and puts it into ``root/country211/``. If dataset is already downloaded, it is not downloaded again. """ _URL = "" _MD5 = "84988d7644798601126c29e9877aab6a" def __init__( self, root: Union[str, Path], split: str = "train", transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, download: bool = False, ) -> None: self._split = verify_str_arg(split, "split", ("train", "valid", "test")) root = Path(root).expanduser() self.root = str(root) self._base_folder = root / "country211" if download: self._download() if not self._check_exists(): raise RuntimeError("Dataset not found. You can use download=True to download it") super().__init__(str(self._base_folder / self._split), transform=transform, target_transform=target_transform) self.root = str(root) def _check_exists(self) -> bool: return self._base_folder.exists() and self._base_folder.is_dir() def _download(self) -> None: if self._check_exists(): return download_and_extract_archive(self._URL, download_root=self.root, md5=self._MD5)


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