| --- |
| license: cc-by-nc-4.0 |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: world_name |
| dtype: string |
| - name: character_name |
| dtype: string |
| - name: character_scale |
| dtype: float64 |
| - name: camera_yaw |
| dtype: int64 |
| - name: character_texture |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 82030062942.72 |
| num_examples: 215040 |
| download_size: 84628407574 |
| dataset_size: 82030062942.72 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
| ## PUG Animals |
| The PUG: Animals dataset contains 215,040 pre-rendered images based on Unreal-Engine using 70 animal assets, 64 environments, 3 sizes, 4 textures, under 4 camera orientations. |
| It was designed with the intent to create a dataset with variation factors available. Inspired by research on out-of-distribution generalization, PUG: Animals allows one to precisely control distribution shifts between training and testing which can provide better insight on how a deep neural network generalizes on held out variation factors. |
|
|
| ## LICENSE |
| The datasets are distributed under the CC-BY-NC, with the addenda that they should not be used to train Generative AI models. |
|
|
| ## Citing PUG |
| If you use one of 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} |
| } |
| ``` |
|
|
| ## To learn more about the PUG datasets: |
| Please visit the [website](https://pug.metademolab.com/) and the [github](https://github.com/facebookresearch/PUG) |
