ImageNet — Torchvision 0.22 documentation (original) (raw)

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

ImageNet 2012 Classification Dataset.

Note

Before using this class, it is required to download ImageNet 2012 dataset fromhere and place the files ILSVRC2012_devkit_t12.tar.gz and ILSVRC2012_img_train.taror 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 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