A CUDA-enhanced package for common NeRF model operations
Project description
nerfboost
nerfboost is a CUDA-accelerated Python package that enhances common operations required for Neural Radiance Fields (NeRF) models. It provides high-performance implementations of key functions such as positional encoding, stratified sampling, volume rendering, and more, to accelerate NeRF training and rendering.
Features
- CUDA-accelerated functions for efficient neural rendering tasks.
- Implements key operations for NeRF models like:
- Positional encoding
- Stratified, uniform, and hierarchical sampling
- Volume rendering
- MLP network processing
- Rendering loss computation
- Easy integration with PyTorch using custom CUDA kernels.
Installation
You can install nerfboost using the following command:
pip install nerfboost
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