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Categorize dataset doc page into sections #5368

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90 changes: 68 additions & 22 deletions docs/source/datasets.rst
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@ 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 :class:`torch.utils.data.Dataset`
i.e, they have ``__getitem__`` and ``__len__`` methods implemented.
Expand All @@ -25,6 +25,8 @@ 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 :ref:`base classes <base_classes_datasets>`.

Image classification
~~~~~~~~~~~~~~~~~~~~

.. autosummary::
:toctree: generated/
Expand All @@ -35,61 +37,105 @@ You can also create your own datasets using the provided :ref:`base classes <bas
CelebA
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CelebA is image generation too.

CIFAR10
CIFAR100
Cityscapes
CocoCaptions
CocoDetection
Country211
DTD
EMNIST
EuroSAT
FakeData
FashionMNIST
FER2013
FGVCAircraft
Flickr8k
Flickr30k
Flowers102
FlyingChairs
FlyingThings3D
Food101
FGVCAircraft
GTSRB
HD1K
HMDB51
ImageNet
INaturalist
Kinetics400
Kitti
KittiFlow
ImageNet
KMNIST
LFWPeople
LFWPairs
LSUN
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LSUN
Image Generation probably? This is how paperswithcode describes it as well. Also GANs are popular on this.

MNIST
Omniglot
OxfordIIITPet
PCAM
PhotoTour
Places365
RenderedSST2
PCAM
QMNIST
SBDataset
SBU
RenderedSST2
SEMEION
Sintel
SBU
StanfordCars
STL10
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I tihnk STL-10 is used for g unsupervised learning. Although it can be used for image classification too.
That's how the website describes it https://cs.stanford.edu/~acoates/stl10/

SUN397
SVHN
UCF101
USPS

Image detection or segmentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. autosummary::
:toctree: generated/
:template: class_dataset.rst

CocoDetection
CelebA
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Some datasets here also appear in the Classification section:

  • CelebA
  • GTSRB
  • OxfordIIITPet

Perhaps there are others that I missed?

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I think it is fine to have them in both categories, since they can be used for both tasks. Looking through list, nothing missing comes to mind.

Cityscapes
GTSRB
Kitti
OxfordIIITPet
SBDataset
VOCSegmentation
VOCDetection
WIDERFace

Optical Flow
~~~~~~~~~~~~

.. autosummary::
:toctree: generated/
:template: class_dataset.rst

FlyingChairs
FlyingThings3D
HD1K
KittiFlow
Sintel

Image pairs
~~~~~~~~~~~

.. autosummary::
:toctree: generated/
:template: class_dataset.rst

LFWPairs
PhotoTour

Image captioning
~~~~~~~~~~~~~~~~

.. autosummary::
:toctree: generated/
:template: class_dataset.rst

CocoCaptions
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I wasn't sure what to do with this one so I created a section just for it. There might be a better alternative?


Video classification
~~~~~~~~~~~~~~~~~~~~

.. autosummary::
:toctree: generated/
:template: class_dataset.rst

HMDB51
Kinetics400
UCF101


.. _base_classes_datasets:

Base classes for custom datasets
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
--------------------------------

.. autosummary::
:toctree: generated/
Expand Down