1.6 KiB
1.6 KiB
NeRF Tutorial
This example code is largely inspried from the Jupyter Notebook given by the pytorch repository.
It has been adapted to be ran inside a python sheel and not a jupyer notebook. It is GPU only, there is support for CPU.
It cannot run my lab computer: NVIDIA GeForce RTX 2060 (6GiB of VRAM) and thus need to be run on the cluster which has more VRAM.
Installation (using conda)
Please refer to the original Pytorch3D project, here is a quick summary:
conda create -n pytorhc3d python=3.8
conda activate pytorch3d
conda install -c pytorch pytorch=1.7.1 torchvision cudatoolkit=10.2
conda install -c conda-forge -c fvcore -c iopath fvcore iopath
conda install -c bottler nvidiacub
conda intall numpy matplotlib plotly
You can then clone this repo and run the code
git clone https://gitea.auro.re/otthorn/nerf_tutorial.git
cd nerf_tutorial
python3 main.py
To deactivate the conda env
conda deactivate
Installation (using pip and virtualenv)
This requires Python>=3.8
First, clone the repo
git clone https://gitea.auro.re/otthorn/nerf_tutorial.git
cd nerf_tutorial
Then install pytorch3d inside a virtualenv
virtualenv -p /usr/bin/python3.8 pytorch3d
source pytorch3d/bin/activate
pip3 install pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py38_cu102_pyt171/download.html
pip3 install torch torchvision
You can then run the code
python3 main.py
To deactivate the virtualenv
deactivate