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cvat-ai / cvat

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
https://cvat.ai
MIT License
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Serverless component nuclio doesn't support nvidia-docker / GPU acceleration. #1997

Closed mhe-wyze closed 2 years ago

mhe-wyze commented 4 years ago

I've just created this issue ticket under their repo. https://github.com/nuclio/nuclio/issues/1781

Meanwhile, is there anyone knows besides asking nuclio's cooperation, do we have another quick solution for this? Thanks for your help ahead.

nmanovic commented 4 years ago

@mhe-wyze , thanks!

mhe-wyze commented 4 years ago

Hi, @nmanovic thanks for your help on this issue, the problem has been solved by changing the docker config file. /etc/docker/daemon.json from

{
    "runtimes": {
        "nvidia": {
            "path": "nvidia-container-runtime",
            "runtimeArgs": []
        }
    }
}

to

{
    "default-runtime": "nvidia",
    "runtimes": {
        "nvidia": {
            "path": "nvidia-container-runtime",
            "runtimeArgs": []
        }
    }
}
veer5551 commented 4 years ago

Hello,

Any update on using/configuring the GPU for the deployed models on the CVAT using nuclio? Currently, it is taking a considerable large amount of time. So assuming its running on CPU!

Thanks a lot!

charlescho64 commented 4 years ago

Hello @mhe-wyze @nmanovic

I can't find /etc/docker/daemon.json after installing cvat in ubuntu. Please let know how to use GPU in models.

mhe-wyze commented 4 years ago

daemon.json is docker file @charlescho64 , did you forget to install the docker or nvidia-docker?

charlescho64 commented 4 years ago

Hi @mhe-wyze

I installed following instruction guide " Ubuntu 18.04 (x86_64/amd64)

If I use GPU in severless model on my desktop which have 2 GPUs, how to set up?

nmanovic commented 2 years ago

@charlescho64 , @mhe-wyze , it was implemented. Please see documentation: https://openvinotoolkit.github.io/cvat/docs/administration/advanced/installation_automatic_annotation/#gpu-support