Torchvision provides many built-in datasets in the torchvision.datasets module, as well as utility classes for building your own datasets.

Built-in datasets

All datasets are subclasses of i.e, they have __getitem__ and __len__ methods implemented. Hence, they can all be passed to a which can load multiple samples in parallel using torch.multiprocessing workers. For example:

imagenet_data = torchvision.datasets.ImageNet('path/to/imagenet_root/')
data_loader =,

All the datasets have almost similar API. They all have two common arguments: transform and target_transform to transform the input and target respectively. You can also create your own datasets using the provided base classes.

Image classification

Caltech101(root[, target_type, transform, ...])

Caltech 101 Dataset.

Caltech256(root[, transform, ...])

Caltech 256 Dataset.

CelebA(root[, split, target_type, ...])

Large-scale CelebFaces Attributes (CelebA) Dataset Dataset.

CIFAR10(root[, train, transform, ...])

CIFAR10 Dataset.

CIFAR100(root[, train, transform, ...])

CIFAR100 Dataset.

Country211(root[, split, transform, ...])

The Country211 Data Set from OpenAI.

DTD(root[, split, partition, transform, ...])

Describable Textures Dataset (DTD).

EMNIST(root, split, **kwargs)

EMNIST Dataset.

EuroSAT(root[, transform, target_transform, ...])

RGB version of the EuroSAT Dataset.

FakeData([size, image_size, num_classes, ...])

A fake dataset that returns randomly generated images and returns them as PIL images

FashionMNIST(root[, train, transform, ...])

Fashion-MNIST Dataset.

FER2013(root[, split, transform, ...])

FER2013 Dataset.

FGVCAircraft(root[, split, ...])

FGVC Aircraft Dataset.

Flickr8k(root, ann_file[, transform, ...])

Flickr8k Entities Dataset.

Flickr30k(root, ann_file[, transform, ...])

Flickr30k Entities Dataset.

Flowers102(root[, split, transform, ...])

Oxford 102 Flower Dataset.

Food101(root[, split, transform, ...])

The Food-101 Data Set.

GTSRB(root[, split, transform, ...])

German Traffic Sign Recognition Benchmark (GTSRB) Dataset.

INaturalist(root[, version, target_type, ...])

iNaturalist Dataset.

ImageNet(root[, split])

ImageNet 2012 Classification Dataset.

Imagenette(root[, split, size, download, ...])

Imagenette image classification dataset.

KMNIST(root[, train, transform, ...])

Kuzushiji-MNIST Dataset.

LFWPeople(root[, split, image_set, ...])

LFW Dataset.

LSUN(root[, classes, transform, ...])

LSUN dataset.

MNIST(root[, train, transform, ...])

MNIST Dataset.

Omniglot(root[, background, transform, ...])

Omniglot Dataset.

OxfordIIITPet(root[, split, target_types, ...])

Oxford-IIIT Pet Dataset.

Places365(root, ~pathlib.Path], split, ...)

Places365 classification dataset.

PCAM(root[, split, transform, ...])

PCAM Dataset.

QMNIST(root[, what, compat, train])

QMNIST Dataset.

RenderedSST2(root[, split, transform, ...])

The Rendered SST2 Dataset.

SEMEION(root[, transform, target_transform, ...])

SEMEION Dataset.

SBU(root[, transform, target_transform, ...])

SBU Captioned Photo Dataset.

StanfordCars(root[, split, transform, ...])

Stanford Cars Dataset

STL10(root[, split, folds, transform, ...])

STL10 Dataset.

SUN397(root[, transform, target_transform, ...])

The SUN397 Data Set.

SVHN(root[, split, transform, ...])

SVHN Dataset.

USPS(root[, train, transform, ...])

USPS Dataset.

Image detection or segmentation

CocoDetection(root, annFile[, transform, ...])

MS Coco Detection Dataset.

CelebA(root[, split, target_type, ...])

Large-scale CelebFaces Attributes (CelebA) Dataset Dataset.

Cityscapes(root[, split, mode, target_type, ...])

Cityscapes Dataset.

Kitti(root[, train, transform, ...])

KITTI Dataset.

OxfordIIITPet(root[, split, target_types, ...])

Oxford-IIIT Pet Dataset.

SBDataset(root[, image_set, mode, download, ...])

Semantic Boundaries Dataset

VOCSegmentation(root[, year, image_set, ...])

Pascal VOC Segmentation Dataset.

VOCDetection(root[, year, image_set, ...])

Pascal VOC Detection Dataset.

WIDERFace(root[, split, transform, ...])

WIDERFace Dataset.

Optical Flow

FlyingChairs(root[, split, transforms])

FlyingChairs Dataset for optical flow.

FlyingThings3D(root[, split, pass_name, ...])

FlyingThings3D dataset for optical flow.

HD1K(root[, split, transforms])

HD1K dataset for optical flow.

KittiFlow(root[, split, transforms])

KITTI dataset for optical flow (2015).

Sintel(root[, split, pass_name, transforms])

Sintel Dataset for optical flow.

Stereo Matching

CarlaStereo(root[, transforms])

Carla simulator data linked in the CREStereo github repo.

Kitti2012Stereo(root[, split, transforms])

KITTI dataset from the 2012 stereo evaluation benchmark.

Kitti2015Stereo(root[, split, transforms])

KITTI dataset from the 2015 stereo evaluation benchmark.

CREStereo(root[, transforms])

Synthetic dataset used in training the CREStereo architecture.

FallingThingsStereo(root[, variant, transforms])

FallingThings dataset.

SceneFlowStereo(root[, variant, pass_name, ...])

Dataset interface for Scene Flow datasets.

SintelStereo(root[, pass_name, transforms])

Sintel Stereo Dataset.

InStereo2k(root[, split, transforms])

InStereo2k dataset.

ETH3DStereo(root[, split, transforms])

ETH3D Low-Res Two-View dataset.

Middlebury2014Stereo(root[, split, ...])

Publicly available scenes from the Middlebury dataset 2014 version <>.

Image pairs

LFWPairs(root[, split, image_set, ...])

LFW Dataset.

PhotoTour(root, name[, train, transform, ...])

Multi-view Stereo Correspondence Dataset.

Image captioning

CocoCaptions(root, annFile[, transform, ...])

MS Coco Captions Dataset.

Video classification

HMDB51(root, annotation_path, frames_per_clip)

HMDB51 dataset.

Kinetics(root, frames_per_clip[, ...])

Generic Kinetics dataset.

UCF101(root, annotation_path, frames_per_clip)

UCF101 dataset.

Video prediction

MovingMNIST(root[, split, split_ratio, ...])

MovingMNIST Dataset.

Base classes for custom datasets

DatasetFolder(root, loader[, extensions, ...])

A generic data loader.

ImageFolder(root, transform, ...)

A generic data loader where the images are arranged in this way by default: .

VisionDataset([root, transforms, transform, ...])

Base Class For making datasets which are compatible with torchvision.

Transforms v2

wrap_dataset_for_transforms_v2(dataset[, ...])

Wrap a torchvision.dataset for usage with torchvision.transforms.v2.


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