dgs-py 1.1.1

Dynamic Gaussian Splats

DGS

This is the home of the Dynamic Gaussian Splat (.dgs) file format. This repository contains:

• The reference encoder + decoder for .dgs files, implemented in C
• Utility functions for manipulating .dgs files, implemented in C
• Python bindings for the aforementioned

This library serves as both the specification and reference implementation for .dgs, and is the core of all projects within Splatkit.

Installation + Usage

To use DGS in your own project, you can install the package on pip:

pip install dgs-py

Then, it can be importated with a simple:

import dgs

Here is a full example generating a single .dgs file:

import dgs
import numpy as np

# example data:
means = np.array([
	[0.3,  0.0, 0.0], [-0.3, 0.1, 0.1], [0.0, -0.2, 0.0]
], dtype=np.float32)

scales = np.array([
	[0.2, 0.05, 0.05], [0.08, 0.3, 0.08], [0.1, 0.1, 0.25]
], dtype=np.float32)

rotations = np.array([
	[0.0, 0.0, 0.0, 1.0], [0.0, 0.0, 0.0, 1.0], [0.0, 0.0, 0.0, 1.0]
], dtype=np.float32)

opacities = np.array([
	[1.0], [1.0], [1.0]
], dtype=np.float32)

harmonics = (np.array([
	[ [1.0, 0.0, 0.0] ], [ [0.0, 1.0, 0.0] ], [ [0.0, 0.0, 1.0] ]
], dtype=np.float32) - 0.5) / 0.28209479177387814

# encode:
gaussians = dgs.Gaussians(
	means, scales, rotations, opacities, harmonics
)
metadata = dgs.Metadata()

dgs.encode(gaussians, metadata, "example.dgs")

Documentation

Coming soon!

Building

If you wish to contribute to this project, you will need to build it from source yourself. To build, you will need the tools:

• setuptools (pip install setuptools)
• pybind11 (pip install pybind11) Then, to build, you will first need to clone the repository and initialize the submodules:

git clone [e-mail]:splatsdotcom/DGS.git
cd DGS
git submodule update --init --recursive

Then, the project can be built simply with:

pip install -v .

And the dgs package will become globally available on your system. There is currently no way to build the C library without the python bindings, but this will come in the future.