Metadata-Version: 2.1 Name: nvdiffrast Version: 0.2.5 Summary: nvdiffrast - modular primitives for high-performance differentiable rendering Home-page: https://github.com/NVlabs/nvdiffrast Author: Samuli Laine Author-email: slaine@nvidia.com License: UNKNOWN Platform: UNKNOWN Classifier: Programming Language :: Python :: 3 Classifier: Operating System :: OS Independent Requires-Python: >=3.6 Description-Content-Type: text/markdown License-File: LICENSE.txt ## Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering ![Teaser image](./docs/img/teaser.png) **Modular Primitives for High-Performance Differentiable Rendering**
Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, Timo Aila
[http://arxiv.org/abs/2011.03277](http://arxiv.org/abs/2011.03277) Nvdiffrast is a PyTorch/TensorFlow library that provides high-performance primitive operations for rasterization-based differentiable rendering. Please refer to ☞☞ [nvdiffrast documentation](https://nvlabs.github.io/nvdiffrast) ☜☜ for more information. ## Licenses Copyright © 2020, NVIDIA Corporation. All rights reserved. This work is made available under the [Nvidia Source Code License](https://github.com/NVlabs/nvdiffrast/blob/main/LICENSE.txt). For business inquiries, please contact [researchinquiries@nvidia.com](mailto:researchinquiries@nvidia.com) We do not currently accept outside code contributions in the form of pull requests. Environment map stored as part of `samples/data/envphong.npz` is derived from a Wave Engine [sample material](https://github.com/WaveEngine/Samples/tree/master/Materials/EnvironmentMap/Content/Assets/CubeMap.cubemap) originally shared under [MIT License](https://github.com/WaveEngine/Samples/blob/master/LICENSE.md). Mesh and texture stored as part of `samples/data/earth.npz` are derived from [3D Earth Photorealistic 2K](https://www.turbosquid.com/3d-models/3d-realistic-earth-photorealistic-2k-1279125) model originally made available under [TurboSquid 3D Model License](https://blog.turbosquid.com/turbosquid-3d-model-license/#3d-model-license). ## Citation ``` @article{Laine2020diffrast, title = {Modular Primitives for High-Performance Differentiable Rendering}, author = {Samuli Laine and Janne Hellsten and Tero Karras and Yeongho Seol and Jaakko Lehtinen and Timo Aila}, journal = {ACM Transactions on Graphics}, year = {2020}, volume = {39}, number = {6} } ```