The docker image (respectively Ubuntu 22.04) comes with Python3.10, no older version of Python is installed. No local CUDA installation is required or will be affected by using the docker image. The container currently is based on nvidia/cuda:11.8.0-devel-ubuntu22.04, consequently it comes with CUDA 11.8 which must be supported by the nvidia driver. The user inside the container is called ‘user’ and is mapped to the local user with ID 1000 (usually the first non-root user on Linux systems). Always do all your tasks and output folder in workdir! Ensure to use the correct paths when mounting folders or providing paths as parameters.Īlways use full paths, relative paths are known to create issues when being used in mounts into docker.Įverything inside the container, what is not in a mounted folder (workspace in the above example), will be permanently removed after destroying the container.
Alternatively, mounts can be quoted (e.g. Paths on Windows use backslash ‘' while unix based systems use a frontslash ‘/’ for paths, where backslashes might require an escape character depending on where they are used (e.g. The container works on Linux and Windows, depending on your OS some additional setup steps might be required to provide access to your GPU inside containers. dromni/nerfstudio: \ # Docker image name ns-process-data video -data /workspace/video.mp4 # Smaple command of nerfstudio. Call nerfstudio commands directly #īesides, the container can also directly be used by adding the nerfstudio command to the end.ĭocker run -gpus all -v /folder/of/your/data:/workspace/ -v /home//.cache/:/home/user/.cache/ -p 7007:7007 -rm -it -shm-size =12gb # Parameters. Nerfstudio # Docker image tag if you built the image from the Dockerfile by yourself using the command from above. dromni/nerfstudio: # Docker image name if you pulled from docker hub. shm-size =12gb \ # Increase memory assigned to container to avoid memory limitations, default is 64 MB (recommended). it \ # Start container in interactive mode.
rm \ # Remove container after it is closed (recommended). p 7007:7007 \ # Map port from local machine to docker container (required to access the web interface/UI). v /home//.cache/:/home/user/.cache/ \ # Mount cache folder to avoid re-downloading of models everytime (recommended). v /folder/of/your/data:/workspace/ \ # Mount a folder from the local machine into the container to be able to process them (required). Docker run -gpus all \ # Give the container access to nvidia GPU (required).
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