Awesome
<p align="left"> <!-- PyPi badge --> <a href="https://badge.fury.io/py/kplanes-nerfstudio"><img src="https://badge.fury.io/py/kplanes-nerfstudio.svg" alt="PyPI version"></a> <!-- License badge --> <a href="LICENSE.txt"> <img alt="license" src="https://img.shields.io/badge/license-BSD-blue"> </a> </p>K-Planes nerfstudio integration
This repository provides code to integrate the K-Planes model into nerfstudio.
<div align='center'> <img src="https://sarafridov.github.io/K-Planes/assets/intro_figure.jpg" height="200px"/> </div>It provides an alternative way to use k-planes in addition to the official repository, which allows access to nerfstudio's in-browser viewer and additional training capabilities. Beware that some details about the training procedure differ from the official repository.
Installation
- Install nerfstudio. This is
pip install nerfstudio, but there are a few dependencies (e.g.torch,tinycudann) which may require further steps, so make sure to check their installation guide! - Install the k-planes nerfstudio integration (this repository):
pip install kplanes-nerfstudio
Included Models
Two models are included here:
kplaneswhich is tuned for the Synthetic NeRF dataset (i.e. chair, drums, etc.)kplanes-dynamicwhich is tuned to the DNeRF dataset (dynamic, monocular video).
:exclamation: PRs are welcome for configurations tuned to different datasets :exclamation:
You can run the static model by calling (remember to use the correct data directory!)
ns-train kplanes --data <data-folder>
and connect to the viewer using the link provided in the output of the training script.
Benchmarks
Synthetic NeRF (hybrid model)
| drums | materials | ficus | ship | mic | chair | lego | hotdog | AVG | |
|---|---|---|---|---|---|---|---|---|---|
| PSNR | 26.31 | 29.82 | 32.47 | 30.27 | 33.73 | 34.98 | 36.56 | 36.77 | 32.61 |
| SSIM | 0.9394 | 0.9539 | 0.9788 | 0.8755 | 0.9857 | 0.9824 | 0.982 | 0.9792 | 0.9596 |
DNeRF (hybrid model)
| hell warrior | mutant | hook | balls | lego | t-rex | stand up | jumping jacks | AVG | |
|---|---|---|---|---|---|---|---|---|---|
| PSNR | 25.06 | 34.29 | 28.22 | 43.02 | 27.03 | 33.59 | 34.04 | 33.43 | 32.33 |
| SSIM | 0.9487 | 0.9839 | 0.9552 | 0.9954 | 0.956 | 0.9817 | 0.9835 | 0.9797 | 0.973 |
Roadmap
Expected future updates to this repository:
- Including all datasets used in the K-Planes paper
- Clarifying configuration of colliders (near-far)
- Add benchmarks and configs for linear models