class torchvision.datasets.Places365(root: ~typing.Union[str, ~pathlib.Path], split: str = 'train-standard', small: bool = False, download: bool = False, transform: ~typing.Optional[~typing.Callable] = None, target_transform: ~typing.Optional[~typing.Callable] = None, loader: ~typing.Callable[[str], ~typing.Any] = <function default_loader>)[source]

Places365 classification dataset.

  • root (str or pathlib.Path) – Root directory of the Places365 dataset.

  • split (string, optional) – The dataset split. Can be one of train-standard (default), train-challenge, val.

  • small (bool, optional) – If True, uses the small images, i.e. resized to 256 x 256 pixels, instead of the high resolution ones.

  • download (bool, optional) – If True, downloads the dataset components and places them in root. Already downloaded archives are not downloaded again.

  • 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.

  • loader – A function to load an image given its path.

  • RuntimeError – If download is False and the meta files, i.e. the devkit, are not present or corrupted.

  • RuntimeError – If download is True and the image archive is already extracted.


__getitem__(index: int) Tuple[Any, Any][source]

index (int) – Index


Sample and meta data, optionally transformed by the respective transforms.

Return type:



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