Welcome to the svox documentationΒΆ
This is a PlenOctree volume rendering implementation as a PyTorch extension with CUDA acceleration.
Note this only implements octree (or more generally N^3 tree) operations and differentiable volume rendering. It does not relate to NeRF training part of the project and does not involve a neural network.
The code is available in this repo. This is part of the code release of
PlenOctrees for Real Time Rendering of Neural Radiance Fields
Alex Yu, Ruilong Li, Matthew Tancik, Hao Li, Ren Ng, Angjoo Kanazawa
Website: https://alexyu.net/plenoctrees
Source code (SVOX): https://github.com/sxyu/svox
Install with pip install svox
.
>>> import svox
>>> tree = svox.N3Tree(data_dim=4)
>>> print(tree)
svox.N3Tree(N=2, data_dim=4, depth_limit=10; capacity:1/1 max_depth:0)
>>> tree.to('cuda:0')
data_dim
is the size of data stored at each leaf.
Please see Reference for detailed per-method documentation and Quick Guide for a quick overview of features. This is the documentation of svox version: 0.2.32-dev.