---
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_label
    dtype: string
  - name: character_rotation_yaw
    dtype: int64
  - name: character_rotation_roll
    dtype: int64
  - name: character_rotation_pitch
    dtype: int64
  - name: character_scale
    dtype: float64
  - name: camera_roll
    dtype: int64
  - name: camera_pitch
    dtype: int64
  - name: camera_yaw
    dtype: int64
  - name: character_texture
    dtype: string
  - name: scene_light
    dtype: string
  splits:
  - name: train
    num_bytes: 29382707151.112
    num_examples: 88328
  download_size: 29358745565
  dataset_size: 29382707151.112
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

## PUG ImageNet
The PUG: ImageNet dataset contains 88,328 pre-rendered images based on Unreal Engine using 724 assets representing 151 ImageNet classes with 64 environments, 7 sizes, 9 textures, 18 different camera orientations, 18 different character orientations and 7 light intensities. In contrast to PUG: Animals, PUG: ImageNet was created by varying only a single factor at a time (which explains the lower number of images than PUG: Animals despite using more factors). The main purpose of this dataset is to provide a novel, useful benchmark, paralleling ImageNet, but for fine-grained evaluation of the robustness of image classifiers, along several factors of variation.

## 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)