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Documentation on using virtual webcam in Docker #51
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.
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.
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.
@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
@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?
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allo- commentedon Dec 9, 2020
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.
allo- commentedon Dec 9, 2020
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.
arjdroid commentedon May 9, 2021
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.
arjdroid commentedon May 10, 2021
Thank you for your response! I will check it out
allo- commentedon May 22, 2021
@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.shscript that creates a config file and then starts the program?allo- commentedon May 22, 2021
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.