ImageNet

class torchvision.datasets.ImageNet(root: Union[str, Path], split: str = 'train', **kwargs: Any)

ImageNet 2012 Classification Dataset.

Note

Before using this class, it is required to download ImageNet 2012 dataset from here and place the files ILSVRC2012_devkit_t12.tar.gz and ILSVRC2012_img_train.tar or ILSVRC2012_img_val.tar based on split in the root directory.

Parameters:

• root (str or pathlib.Path) – Root directory of the ImageNet Dataset.

• split (string, optional) – The dataset split, supports train, or val.

• 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.

• loader – A function to load an image given its path. By default, it uses PIL as its image loader, but users could also pass in torchvision.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