TIBVH - Taichi-based Linear BVH
A high-performance Python package for 3D spatial data structures and geometry processing using Taichi for GPU acceleration.
Installation
Requirements
- Python 3.10 - 3.13
- Taichi 1.7.4
- NumPy 1.26+
- PyTorch 2.7.0
Install from Source
git clone https://github.com/discoverse-dev/tibvh.git
cd tibvh
uv sync
pyproject.toml pins torch==2.7.0 and keeps NumPy in a bounded range. The
checked-in uv.lock includes wheels for macOS and Linux, including the Linux
NVIDIA runtime packages required by PyTorch on x86_64.
For development tools:
uv sync --group dev
Development
This project uses a src/tibvh package layout and keeps the local virtual
environment in .venv through uv.
uv run --only-group dev ruff format .
uv run --only-group dev ruff check .
uv build
Supported Geometry Types
- PLANE (0): Infinite planes with optional bounds
- SPHERE (2): Spheres defined by center and radius
- CAPSULE (3): Capsules (cylinders with hemispherical caps)
- ELLIPSOID (4): Ellipsoids with three different radii
- CYLINDER (5): Finite cylinders with caps
- BOX (6): Oriented bounding boxes
- TRIANGLES: Individual triangles for mesh processing
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
- Based on the Linear BVH construction algorithm by Tero Karras (NVIDIA Research)
- Powered by the Taichi programming language
- Inspired by modern GPU-accelerated spatial data structures
References
- Karras, T. (2012). "Maximizing Parallelism in the Construction of BVHs, Octrees, and k-d Trees". NVIDIA Research.
- Lauterbach, C. et al. (2009). "Fast BVH Construction on GPUs". Computer Graphics Forum.
1 maintainer
Metadata
1 maintainer
Release files for tibvh 0.1.5
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| File | Size | Uploaded | Provenance | |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tibvh-0.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 37.2 kB
Release files / tibvh-0.1.5.tar.gz
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Release files / tibvh-0.1.5-py3-none-any.whl
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