gsplat is an open-source library for CUDA accelerated rasterization of gaussians with python bindings. It is inspired by the SIGGRAPH paper 3D Gaussian Splatting for Real-Time Rendering of Radiance Fields. This libary contains the neccessary components for efficient 3D to 2D projection, sorting, and alpha compositing of gaussians and their associated backward passes for inverse rendering.
Dependence: Please install Pytorch first.
The easist way is to install from PyPI. In this way it will build the CUDA code on the first run (JIT).
pip install gsplatOr install from source. In this way it will build the CUDA code during installation.
pip install git+https://github.com/nerfstudio-project/gsplat.gitFit a 2D image with 3D Gaussians.
pip install -r examples/requirements.txt
python examples/simple_trainer.pyThis repository was born from the curiosity of people on the Nerfstudio team trying to understand a new rendering technique. We welcome contributions of any kind and are open to feedback, bug-reports, and improvements to help expand the capabilities of this software. Please check docs/DEV.md for more info about development.