Country211 — Torchvision 0.22 documentation (original) (raw)

class torchvision.datasets.Country211(root: ~typing.Union[str, ~pathlib.Path], split: str = 'train', transform: ~typing.Optional[~typing.Callable] = None, target_transform: ~typing.Optional[~typing.Callable] = None, download: bool = False, loader: ~typing.Callable[[str], ~typing.Any] = <function default_loader>)[source]¶

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.

Parameters:

• 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 or torch.Tensor, depends on the given loader, 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 intoroot/country211/. If dataset is already downloaded, it is not downloaded again.
• loader (callable , optional) – A function to load an image given its path. By default, it uses PIL as its image loader, but users could also pass intorchvision.io.decode_image for decoding image data into tensors directly.

Special-members:

__getitem__(index: int) → Tuple[Any, Any]¶

Parameters:

index (int) – Index

Returns:

(sample, target) where target is class_index of the target class.

Return type:

tuple