YOLOv9 on Jetson Nano

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  • Опубліковано 10 бер 2024
  • Step by step tutorial to run YOLOv9 on Jetson Nano.
    OpenCV Installation guide: • L-3 Install OpenCV 4.5...
    torch and torchvision installation guide: • L-5 YOLOv5 on Jetson N...
    Yolov9 GitHub repo: github.com/WongKinYiu/yolov9
    For queries: You can comment in comment section or you can email me at aarohisingla1987@gmail.com
    Unlock the power of YOLOv9 on your Jetson Nano with this comprehensive step-by-step tutorial. Dive into the world of real-time object detection as we guide you through the process of setting up and running YOLOv9, enabling you to harness the capabilities of this cutting-edge algorithm on your compact Jetson Nano device. Whether you're a beginner or an experienced developer, this tutorial will equip you with the knowledge and skills needed to implement YOLOv9 for your own projects. Join us on this journey and unleash the full potential of your Jetson Nano!
    #yolov9 #yolov8 #yolo #computervision #jetsonnano #objectdetection
  • Наука та технологія

КОМЕНТАРІ • 49

  • @soravsingla8782
    @soravsingla8782 3 місяці тому

    Wow.. Yolo V9 on Jetson. Amazing work

  • @Sunil-ez1hx
    @Sunil-ez1hx 3 місяці тому +1

    Such an informative video ma’am. Keep on sharing such a wonderful content 👏👏👏👏

  • @KoushikL-dr4qf
    @KoushikL-dr4qf Місяць тому

    Very useful and great content ma'am and I really appreciate your work for this

  • @cetinali32
    @cetinali32 3 місяці тому +4

    Which model runs faster on the Jetson Nano, YoloV8 or YoloV9?

  • @science.20246
    @science.20246 3 місяці тому

    i need an advice to annotate automatically a frames of person doing actions , i need to have bbox and action id

  • @vedparekh1594
    @vedparekh1594 27 днів тому

    Great tutorial.
    One suggestion - You could have used a single environment throughout the videos instead of creating multiple environments with different python versions (3.6 and 3.8). It would have been more convenient to follow if you would have created only one env with python version 3.8 and did all the setup and installation in that.

  • @RanjaniAnbalagan-nl4gu
    @RanjaniAnbalagan-nl4gu 3 місяці тому

    Mam,can u please explain how to extract text from natural scene using yolo.

  • @AmandeepSingh-uq3wp
    @AmandeepSingh-uq3wp 3 місяці тому

    Is it possible to detect lanes on highway using yolov9?
    Note : Not asking for self driving cars

  • @jayeshbaviskar9251
    @jayeshbaviskar9251 3 місяці тому

    Thanks for the Video! can you make a video on tracking using yolo v8 and norfair tracking?

    • @CodeWithAarohi
      @CodeWithAarohi  3 місяці тому

      Of course! I'll add it to my list of video ideas. Stay tuned for updates!

  • @pifordtechnologiespvtltd5698
    @pifordtechnologiespvtltd5698 3 місяці тому

    👍👍

  • @OpenYTU
    @OpenYTU 3 місяці тому

    Hi, how to deploy the is made tensorrt yolov9 model into the jetson xavier? May you take a video about it please💫

  • @likeyo-yy3vj
    @likeyo-yy3vj 21 день тому

    excuse me,dose it can be used like the way of computer that train and test on conda?directly pip install -r requirement.txt and then detect

  • @mohammadtanzil8087
    @mohammadtanzil8087 3 місяці тому

    can you explain how to implement CBAM in yolov8 backbone architecture

  • @elvenkim
    @elvenkim 3 місяці тому

    Thanks for sharing! Any idea how to combine YOLOv9 with LLM?

  • @denischeriot2731
    @denischeriot2731 2 місяці тому

    Great video. Have you ever encountered such an error on Yolov8 when running on jetson nano, it returns no detections for all the frames but if I ran the same setup on google colab it's detecting the objects well ?

    • @CodeWithAarohi
      @CodeWithAarohi  2 місяці тому

      Check for any error messages or warnings when running on the Jetson Nano.

  • @akashpatel9884
    @akashpatel9884 3 місяці тому +1

    Please can you tell me how to run YOLO NAS in jetson nano . I am unable to download the dependencies related to it. Can clearly specify the version required for YOLO NAS to run on jetson
    I am unable to download ultralytics or super gradient in python 3.6 and when I downloaded python 3 8.12 in jetson , opencv is not working. PLEASE Help🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏

  • @vishalkumaryadav8192
    @vishalkumaryadav8192 3 місяці тому

    Ma'am, please make a video on how to deploy custom object detection model on Android

    • @CodeWithAarohi
      @CodeWithAarohi  3 місяці тому +1

      Of course! I'll add it to my list of video ideas. Stay tuned for updates!

  • @meher7889
    @meher7889 2 місяці тому

    Hi, I will be very helpful if you can upload a video yolov9 tflite on raspberry pi

  • @BhaskarGhosh-km1dp
    @BhaskarGhosh-km1dp 2 місяці тому

    Which specific jetson nano did you use in this madam?

  • @BhaskarGhosh-km1dp
    @BhaskarGhosh-km1dp 2 місяці тому

    Can we use yolov9 in 2GB one?

  • @rsalazar9784
    @rsalazar9784 3 місяці тому +1

    1 seg of time inference for frame ???!!!!!

    • @CodeWithAarohi
      @CodeWithAarohi  3 місяці тому

      Yes, In my next video, we will work on inference speed.

  • @asherchakupa
    @asherchakupa 23 дні тому

    YOLOv10 on Jetson Nano? :)

  • @SeregaTikhonov
    @SeregaTikhonov 3 місяці тому

    1 fps? good old deepstack could be 60% faster.

    • @CodeWithAarohi
      @CodeWithAarohi  3 місяці тому

      Switching to a lighter model variant can significantly improve performance on a Jetson Nano compared to YOLOv9-c. Additionally, applying quantization and TensorRT optimization techniques can further enhance inference speed without sacrificing much accuracy.

    • @devend8496
      @devend8496 3 місяці тому

      @@CodeWithAarohi does jetson nano require tensor lite?

  • @ponkiyaharshil6865
    @ponkiyaharshil6865 День тому

    After detecting an object, I would like to perform a specific action, like activating a Carbon laser for that object. How can I do that? @CodeWithAarohi

    • @CodeWithAarohi
      @CodeWithAarohi  День тому

      Fetch the bounding box coordinates from output and provide those coordinates to the function for next task.