Installation

Start by installing the nerfbaselines pip package on your system. We recommend using a virtual environment (venv or Conda) to avoid conflicts with other packages.

pip install nerfbaselines

Now you can use the nerfbaselines cli to interact with NerfBaselines (see available commands).

NerfBaselines requires a backend in order to install all dependencies required by various methods. Currently there are the following backends implemented:

  • conda (default): Does not require docker/apptainer to be installed, but does not offer the same level of isolation and some methods require additional dependencies to be installed. Also, some methods are not implemented for this backend because they rely on dependencies not found on conda. Please check the list of methods first to see if your method is supported.

  • docker: Offers good isolation, requires docker (with NVIDIA container toolkit) to be installed and the user to have access to it (being in the docker user group).

  • apptainer: Similar level of isolation as docker, but does not require the user to have privileged access. For all commands which use a backend, the backend can be set as the --backend <backend> argument or using the NERFBASELINES_BACKEND environment variable. Next, we will describe the installation process for each backend.

Warning

The conda backend is not available on Windows or MacOS. This is because the conda dependencies for each method can only be installed on Linux (CUDA dependency). If you are on Windows, we strongly recommend installing NerfBaselines inside WSL2 and using the conda backend.

Pre-requisites (NVIDIA GPU)

If you have an NVIDIA GPU and want to use it (with any backend), you need to install the latest NVIDIA drivers. The installation instruction can vary depending on your operating system. Please follow the instructions on the NVIDIA website or your operating system distribution to install the latest drivers for your GPU.

Conda

The conda backend is the default (and recommended) backend which is easy to install, but does not allow the same level of isolation and each method has to be built from source which can be slow. Any Conda distribution can be used. If you haven’t installed Conda yet, we recommend using the miniforge distribution. Navigate to the miniforge install page and follow the instructions for your operating system. On Linux, you can use the following commands:

curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"
bash Miniforge3-$(uname)-$(uname -m).sh

Docker

In order to use the docker backend, you need to install docker and the NVIDIA container toolkit. To install docker, please follow the instructions on the docker website. For the NVIDIA container toolkit, please follow the instructions on the NVIDIA website. Here, we give instructions for Ubuntu 22.04:

# Install docker
sudo apt-get update
sudo apt-get install -y docker.io
sudo systemctl enable --now docker
sudo usermod -aG docker $USER

# Install NVIDIA container toolkit
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
      sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
          sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
# Enable NVIDIA container toolkit in docker
sudo nvidia-ctk runtime configure --runtime=docker
# Restart docker
sudo systemctl restart docker

Apptainer

The apptainer backend is similar to docker, but does not require the user to have privileged access (to install) and is often present in HPC. To install apptainer, please follow the instructions on the apptainer website. Here, we give instructions for Ubuntu 22.04:

curl -s https://raw.githubusercontent.com/apptainer/apptainer/main/tools/install-unprivileged.sh | \
    bash -s - ~/.local

# Add the following line to your .bashrc, .bash_profile, or .zshrc
export PATH=$HOME/.local/bin:$PATH