Metadata-Version: 2.1
Name: objaverse
Version: 0.0.6
Summary: The API for downloading Objaverse from Hugging Face.
Home-page: https://github.com/allenai/objaverse
Author: Allen Institute for AI
Author-email: mattd@allenai.org
License: Apache 2.0
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown

# Objaverse

Objaverse is a Massive Dataset with 800K+ Annotated 3D Objects.

More documentation is coming soon. In the meantime, please see our [paper](https://arxiv.org/abs/2212.08051) and [website](https://objaverse.allenai.org/) for additional details.

# License

The use of the dataset as a whole is licensed under the [ODC-By v1.0](https://opendatacommons.org/licenses/by/1-0/) license. Individual objects in Objaverse are all licensed as creative commons distributable objects, and may be under the following licenses:

- [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/) - 721K objects
- [CC-BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) - 25K objects
- [CC-BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) - 52K objects
- [CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) - 16K objects
- [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) - 3.5K objects

The metadata will provide the license for each object.

The code in this repository is licensed under the Apache 2.0 license.

# Citation

To cite Objaverse, please use the following BibTeX entry:

```bibtex
@article{objaverse,
  title={Objaverse: A Universe of Annotated 3D Objects},
  author={Matt Deitke and Dustin Schwenk and Jordi Salvador and Luca Weihs and
          Oscar Michel and Eli VanderBilt and Ludwig Schmidt and
          Kiana Ehsani and Aniruddha Kembhavi and Ali Farhadi},
  journal={arXiv preprint arXiv:2212.08051},
  year={2022}
}
```


