Howdy. I am working on deploying a codebase to a Jetson Nano and was hoping to containerize my work as there are some dependencies that are not correctly versioned when using Ubuntu 18.04>, which the Jetson L4T ships with. I've set up a Docker container to work with the Jetson that uses Ubuntu 20.04, and I am able to compile and build my code inside the container. When I run, I receive the [warning] skipping X_LINK_UNBOOTED device having name "<error>" message, and the code terminates with tkill(). I am working with an OAK-D USB camera, and have confirmed I am able to view and access the camera's output on the host machine properly. I've set udev rules inside the container as well, and have been able to compile and run the code with an identical workflow on a different host machine running Ubuntu 20.04.

Are there any steps I am missing here? The error above is only referenced with respect to udev rules in the Troubleshooting documentation, am I missing something about forwarding/sharing these rules inside the container? The run command I am using is as follows:

nvidia-docker run -it --rm -v /dev/bus/usb:/dev/bus/usb --device-cgroup-rule='c 198:* rmw' <container name>:latest

Can anyone point me in the right direction to access the camera from inside my container? I have searched through all documentation and depthai source, including the /ci/ folders in depthai-core and depthai-python to no avail.

  • erik replied to this.

    Hello jithub ,
    Have you used the depthai-docker repo for your container? If yes, could you please also open the Issue there (on the repo)?
    THanks, Erik

      erik Hi Erik,

      I am not using the depthai-docker repo as I have a very specific use case that requires CUDA forwarding from the host to the container, and specifically Ubuntu 20.04<. I have consulted the files therein to try to troubleshoot my setup. I am using the l4t-ubuntu20-crosscompile image from this repo as my base, building OpenCV from source with the features I need, and using that image to pull and run code that uses DepthAI libraries. Would the depthai-docker repo's issues still be the best place to get help?

      • erik replied to this.

        Hello jithub ,
        Did the image from our docker work as expected? Were there any differences between our files and yours? Regardless, I believe that would be the best place.
        Thanks, Erik

          erik I am unable to run the docker image contained in the above repo on the Jetson as its host platform (armv8) does not match the specified host platform (amd64). There are many differences in Dockerfile between what I am using and the example provided as I have many more complex dependencies and my application is written in C++ as opposed to Python. I was able to resolve my issues by running the container with --privileged and adding a udev service restart into my entrypoint.sh file to ensure that the rules reload and trigger correctly processed.