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  3. Getting CUDA and CPAI 2.9.5 working together for Blue Iris integration.

Getting CUDA and CPAI 2.9.5 working together for Blue Iris integration.

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  • F Offline
    F Offline
    Fun Fisherman 582
    wrote last edited by
    #1

    Hello everyone. I am looking for some guidance regarding getting CUDA and CPAI working together. There is ALOT of info out there and the issue I am having is that a lot of it seems 1-3 year old. Tech moves really fast so I am just wondering about current recommendations. Right now this is what I am working with...

    Server version: 2.9.5
    System: Windows
    Operating System: Windows (Windows 11 24H2)
    CPUs: Intel(R) Core(TM) i9-10900 CPU @ 2.80GHz (Intel)
    1 CPU x 10 cores. 20 logical processors (x64)
    GPU (Primary): NVIDIA GeForce RTX 3070 (8 GiB) (NVIDIA)
    Driver: 581.29, CUDA: 13.0.88 (up to: 13.0), Compute: 8.6, cuDNN: 8.5
    System RAM: 48 GiB
    Platform: Windows
    BuildConfig: Release
    Execution Env: Native
    Runtime Env: Production
    Runtimes installed:
    .NET runtime: 9.0.0
    .NET SDK: 8.0.404
    Default Python: Not found
    Go: Not found
    NodeJS: Not found
    Rust: Not found
    Video adapter info:
    Intel(R) UHD Graphics 630:
    Driver Version 31.0.101.2135
    Video Processor Intel(R) UHD Graphics Family
    Microsoft Remote Display Adapter:
    Driver Version 10.0.26100.5074
    Video Processor
    NVIDIA GeForce RTX 3070:
    Driver Version 32.0.15.8129
    Video Processor NVIDIA GeForce RTX 3070
    System GPU info:
    GPU 3D Usage 0%
    GPU RAM Usage 336 MiB
    Global Environment variables:
    CPAI_APPROOTPATH = <root>
    CPAI_PORT = 32168

    1ec2f31f-0ca6-4089-b27b-0c6fe02151bd-image.png

    I am finding that if I use the ipcam-combind model and license-plate, I have the fastest detections with Yolo5 .NET. This isn't taking advantage of my NVIDIA card CUDA option. I cannot get Yolo5 6.2 to use CUDA. When I run Yolo8, it will use the CUDA option, but I don't have the option for ipcam-combind models and the detection times are 10x higher sometimes as I am using general models.

    I would love to use the Yolo8 with ipcam-combind model.

    Given my robust GPU, do I want to just use the Yolo5 .NET? Is there a way to get custom models with Yolo8? I would like to be able to use all of the GPU I have, but would like it to preform well. Do I need to use a different version of CUDA and cuDNN so that Yolo5 6.2 will use CUDA?

    Any help is much appreciated even if it is a link to a current youtube video or other source that could address this. Thanks.

    Steve

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