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Documentation on using virtual webcam in Docker #51

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Description

Allows use for precompiled TF+CUDA+cuDNN that TF hasn't published eg. https://ngc.nvidia.com/catalog/containers/nvidia:tensorflow
Some ways to do this are:

  1. use --privileged for docker container to expose /dev/video
  2. use --device for docker container
    PS: volunteering to write doc, but would like to make sure it's something there's interest in.
    https://github.com/allo-/virtual_webcam_background/issues/34 could probably be roped in here.

Activity

  1. allo- commented on Dec 9, 2020

    @allo-
    Owner

    Is there an advantage to use docker? For the python stuff you can (and probably should) use a virtual environment and add can a user account if you want stronger isolation and the cuda driver must be installed on the host anyway. Or am missing something? I currently only see much overhead and not using docker was one of the reasons I created the project instead of using the setup with docker from the blog article, which is linked in the readme.

  2. allo- commented on Dec 9, 2020

    @allo-
    Owner

    When you like to write documentation I see no reason not to include it. I just currently do not want to test it, but when you tested your howto and it works for you, it can be included.

    I used the debian packages and installed the other libraries to /usr/local/lib/nvidia and it works for me, both with the packages and when using LD_LIBRARY_PATH=/usr/local/lib/nvidia.

    I don't think docker has a real CPU overhead. Containers have some RAM overhead (not relevant here as other things require more RAM), but I thought about the complexity. You use containers and quite complex management tools just to run something that works with a virtualenv as well.

  3. ghost closed this as completedon Feb 6, 2021
  4. arjdroid commented on May 9, 2021

    @arjdroid

    Hey, @dsingal0 , have you made any progress with that guide yet? I am also looking to run this software in an nvidia-docker instance and I was wondering whether you had any advice on how to get started because, as you have mentioned, the documentation regarding GPU accelerated virtual-webcam-background implementation is very limited as of now.

    Thanks in advance.

  5. arjdroid commented on May 10, 2021

    @arjdroid

    @arjdroid I've stopped using the project since I moved to windows on my personal machines and am using NVIDIA Broadcast now. IIRC though, using this within Docker wasn't too hard, you just needed to either launch it in privileged mode, or pass in the /dev/* devices into the container runtime. Stackoverflow

    Thank you for your response! I will check it out

  6. ghost reopened this on May 22, 2021
  7. allo- commented on May 22, 2021

    @allo-
    Owner

    @dsingal0 Can you explain the problem with the config?
    The config is one of the few things that you should be able to change without changing anything in the source. So can't you just create a docker-run.sh script that creates a config file and then starts the program?

  8. allo- commented on May 22, 2021

    @allo-
    Owner

    Ok. Just ask when there are changes needed, so we can discuss how to implement them such that they both work in docker and without docker.

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