We recommend using conda to manage dependencies. Make sure to install Conda before preceding.
conda create --name nerfstudio -y python=3.8.13
conda activate nerfstudio
python -m pip install --upgrade pip
Install pytorch with CUDA (this repo has been tested with CUDA 11.3) and tiny-cuda-nn
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html
pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
Pip package:
pip install nerfstudio
If you want the latest and greatest:
git clone [email protected]:nerfstudio-project/nerfstudio.git
cd nerfstudio
pip install -e .
This needs to be rerun when the CLI changes, for example if nerfstudio is updated.
ns-install-cli
pip install -e.[dev]
pip install -e.[docs]
- TinyCUDA installation errors out with cuda mismatch
- Installation errors, File "setup.py" not found
- Runtime errors, "len(sources) > 0".
(tiny-cuda-error)=
While installing tiny-cuda, you run into: The detected CUDA version mismatches the version that was used to compile PyTorch (10.2). Please make sure to use the same CUDA versions.
Solution:
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html
(pip-install-error)=
When installing dependencies and nerfstudio with pip install -e .
, you run into: ERROR: File "setup.py" not found. Directory cannot be installed in editable mode
Solution: This can be fixed by upgrading pip to the latest version:
python -m pip install --upgrade pip
(cuda-sources-error)=
Runtime errors: "len(sources) > 0", "ctype = _C.ContractionType(type.value) ; TypeError: 'NoneType' object is not callable".
When running train.py
, an error occurs when installing cuda files in the backend code.
Solution: This is a problem with not being able to detect the correct CUDA version, and can be fixed by updating the CUDA path environment variables:
export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
export PATH=$PATH:$CUDA_HOME/bin