https://github.com/facebookresearch/pug

This is the repository for the Photorealistic Unreal Graphics (PUG) datasets for representation learning.
https://github.com/facebookresearch/pug

Last synced: 8 days ago
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This is the repository for the Photorealistic Unreal Graphics (PUG) datasets for representation learning.

• Host: GitHub
• URL: https://github.com/facebookresearch/pug
• Owner: facebookresearch
• License: other
• Created: 2023-07-20T14:11:29.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-04-04T13:12:54.000Z (7 months ago)
• Last Synced: 2024-04-04T14:33:30.072Z (7 months ago)
• Language: Jupyter Notebook
• Size: 28.4 MB
• Stars: 218
• Watchers: 7
• Forks: 12
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

README

        
# PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning



PUG: Photorealistic Unreal Graphics


 **Website** | **Research Paper** | **Datasheet** 


https://github.com/facebookresearch/PUG/assets/5903040/5fd73746-a45b-4056-ae99-3726dadb51a8

This codebase contains:

- download links for the PUG-datasets

- dataloaders

- scripts that are needed to samples images from a running interactive environment made with the Unreal Engine.

- script to evaluate VLMs models with PUG: SPAR

- list of the assets used to create the PUG datasets (which are listed in each PUG folders)

## Downloading the PUG datasets

Here are the links to download the PUG datasets:

- [PUG: Animals (78GB)](https://dl.fbaipublicfiles.com/large_objects/pug/PUG_ANIMAL.tar.gz)

- [PUG: ImageNet (27GB)](https://dl.fbaipublicfiles.com/large_objects/pug/PUG_IMAGENET.tar.gz)

- [PUG: SPAR (16GB)](https://dl.fbaipublicfiles.com/large_objects/pug/PUG_SPAR.tar.gz)

- [PUG: AR4T (97GB)](https://dl.fbaipublicfiles.com/large_objects/pug/PUG_AR4T.tar.gz)

## Dataset loaders

Please look at each PUG subfolder to get information on how to load the datasets.

[PUG Animals](./PUG_Animals)

[PUG ImageNet](./PUG_ImageNet)

[PUG SPAR](./PUG_SPAR)

[PUG AR4T](./PUG_AR4T)

## How to create a PUG environment ?

The instruction are availables in the [torchmultiverse](./torchmultiverse) folder.

## LICENSE

The datasets are distributed under the CC-BY-NC, with the addenda that they should not be used to train Generative AI models, as found in the LICENSE file.

## Citing PUG

If you use the PUG datasets, please cite:

```

@misc{bordes2023pug,

      title={PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning}, 

      author={Florian Bordes and Shashank Shekhar and Mark Ibrahim and Diane Bouchacourt and Pascal Vincent and Ari S. Morcos},

      year={2023},

      eprint={2308.03977},

      archivePrefix={arXiv},

      primaryClass={cs.CV}

}

```