![]() 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). Verify the system has the correct kernel headers and development packages installed.Docker run -gpus all \ # Give the container access to nvidia GPU (required).Verify the system is running a supported version of Linux.Verify the system has a CUDA-capable GPU.Some actions must be taken before the CUDA Toolkit and Driver can be installed on Linux: For more details, refer to the Linux Installation Guide. In the case of the Debian installers, the instructions for the Local and Network variants are the same. ![]() The Local Installer is a stand-alone installer with a large initial download. The Network Installer allows you to download only the files you need. The Debian Installer is available as both a Local Installer and a Network Installer. The Runfile Installer is only available as a Local Installer. When installing CUDA on Ubuntu, you can choose between the Runfile Installer and the Debian Installer. This guide covers the basic instructions needed to install CUDA and verify that a CUDA application can run on Linux.ĬUDA on Linux can be installed using an RPM, Debian, Runfile, or Conda package, depending on the platform being installed on. Handle conflicting installation methods.Verify the system has the correct kernel headers and development packages installed. ![]()
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