YOLOv9: How to Train on Custom Dataset from Scratch with Ultralytics

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  • Опубліковано 30 вер 2024

КОМЕНТАРІ • 54

  • @NicolaiAI
    @NicolaiAI  5 місяців тому +2

    Join My AI Career Program
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  • @errrbrrr3821
    @errrbrrr3821 5 місяців тому +6

    how to deploy these models into a raspberry pi or any edge device?

    • @Mrsmith0119
      @Mrsmith0119 5 місяців тому +3

      Same question i also want to ask

    • @Player-oz2nk
      @Player-oz2nk 5 місяців тому +2

      Yeah same here!

    • @NicolaiAI
      @NicolaiAI  5 місяців тому +6

      Will definitely do it on both raspberry pi and jetson nano. Ultralytics have some nice guides on their documentation but I should definitely cover it since it looks like a lot of people want to see that. Thanks a lot for commenting!

    • @nachiadhi
      @nachiadhi 4 місяці тому +1

      Yeah pls do it

  • @techgarage7898
    @techgarage7898 Місяць тому +1

    Its amazing brother , biggest thankssssssssssssssssssss.........

    • @NicolaiAI
      @NicolaiAI  Місяць тому

      Thanks for watching brother!

  • @nachiadhi
    @nachiadhi 4 місяці тому +1

    Also after training custom dataset , the best. pt file, when I give any image(I.e things that I didn’t train) it’s still detecting it (I.e it’s detecting a bike as a car) ps I trained only car and not bike.. so I suppose my result image should not be predicted… please send help

    • @NicolaiAI
      @NicolaiAI  4 місяці тому

      Comes down to the dataset you are training on

  • @Mrsmith0119
    @Mrsmith0119 5 місяців тому +2

    How to use this model results for practical use like autonomous robots

    • @NicolaiAI
      @NicolaiAI  5 місяців тому

      In what way do you want to use it for? Any specific objects?

    • @Mrsmith0119
      @Mrsmith0119 5 місяців тому +1

      @@NicolaiAI I have certain types of obstacles and want to apply obstacles avoidance and by also identifying them and want to feed the results obtained from prediction to computer or microprocessor for performing tasks

    • @NicolaiAI
      @NicolaiAI  5 місяців тому

      @Mrsmith0119 definitely check out the yolo world model as well here on my channel

    • @nachiadhi
      @nachiadhi 4 місяці тому

      Well even I want to deploy this model on a practical bot !

  • @jigglejogglers2606
    @jigglejogglers2606 2 місяці тому +1

    Great video guide. Question though, is YOLOv9 possible to run on a video live stream instead of just uploading single images?

    • @NicolaiAI
      @NicolaiAI  2 місяці тому +1

      Yeah for sure! Have tons of videos around that as well

    • @jigglejogglers2606
      @jigglejogglers2606 2 місяці тому

      @@NicolaiAI Ive been playing around with using my GPU to speed up the video streaming perhaps? Could you make a guide that perhaps itulizes Nvidia CUDA to run these algorithms for object detection?

  • @ignis.valorant
    @ignis.valorant 5 місяців тому +1

    loving your video! is it possible to just train the model locally and not on google colab?

    • @NicolaiAI
      @NicolaiAI  5 місяців тому

      Yup you can do it locally as well. Exact same code. And it will use the hardware available. Either GPU or CPU directly

  • @harshbhatt8250
    @harshbhatt8250 5 місяців тому +1

    I am working on FSC 147 dataset and I will combine SAM and YOLO for counting and segmentation tasks, for trial of custom YOLO I was trying it on CarPK dataset and was facing some errors, but your video just released on the right time and I was able to solve ther problems I was facing with trial. The results I acheived were pretty good and therefore my professor agreed to my idea of combining SAM + YOLO for counting and segmentation tasks. I know YOLO can perform both segmentation and counting task, but we want to use SAM for counting, and my idea was a to add a layer of YOLO/ CNN model to accurately predict the objects.
    Thank you so much for this.

    • @LokeshLokesh-sf7so
      @LokeshLokesh-sf7so 5 місяців тому

      Papa papa aree q

    • @farhanonymous8666
      @farhanonymous8666 5 місяців тому

      Hello Harsh, I am also kinda working on a similar project. Right now, I am using only YOLO for both segmentation and counting tasks but I want to use SAM for counting purposes and I really need help on this. Can we please connect somewhere and discuss it?

  • @viniciusgardim5154
    @viniciusgardim5154 Місяць тому

    Hey Nicolai, nice video! Can you make an video on how to estimate car’s speed?

  • @chukwumakingsley8790
    @chukwumakingsley8790 Місяць тому

    I trained i to detect refuse dumps, the prediction works perfectly fine only when I provide one of the pictures that I trained the model with, but when I provide a different picture that is not part of the pictures that I trained the model with, it doesn't show anything

  • @chukwumakingsley8790
    @chukwumakingsley8790 Місяць тому

    Thank you for this tutorial, but it seems the model can only predict from the pictures it was trained with if you bring different pictures it can not predict from it, what is the difference between predict and detect in Yolo?

  • @rololop34
    @rololop34 4 місяці тому +1

    What is the point of training a yolov9 model if the foundation model can already do almost perfect predicitons? Just knowledge distillation?

    • @NicolaiAI
      @NicolaiAI  4 місяці тому +1

      Depends on what classes you want to detect. The pre trained model is only able to detect 80 different classes from the coco dataset

    • @rololop34
      @rololop34 4 місяці тому

      @@NicolaiAI Sorry, I meant the foundation model from roboflow, which annotated the cars.

    • @NicolaiAI
      @NicolaiAI  4 місяці тому +1

      Ohh in that way. Those foundation models are too large to run in real-time and too expensive for the task. They are way too overkill and requires significantly more processing power which is unnecessary @@rololop34

    • @rololop34
      @rololop34 4 місяці тому

      @@NicolaiAI Thank you for answering. I just read on the ultraytics docs that YOLOv8 is approx. 866x faster than SAM-b on CPU.

  • @khouloudbelkhodja4586
    @khouloudbelkhodja4586 4 місяці тому

    hello , How to resume YOLOv9 training an after interruption?

  • @gatharajayaweera3169
    @gatharajayaweera3169 4 місяці тому +1

    Thank you for this amazing video this is very useful.

    • @NicolaiAI
      @NicolaiAI  4 місяці тому

      Thanks a ton for watching!

    • @gatharajayaweera3169
      @gatharajayaweera3169 4 місяці тому

      @@NicolaiAI can I know how to integrate this to a live video captured from an esp32-cam? Do you have any videos on that?

  • @AlirezaFazeli-i7y
    @AlirezaFazeli-i7y 2 місяці тому

    How can I use gelan-c or gelan-e in Python?
    not cli

  • @miguelvalverde7873
    @miguelvalverde7873 5 місяців тому

    Hey. Do you have any idea why YOLOV9-t (the tiny model) weights are not available?

  • @tamilgenius7684
    @tamilgenius7684 4 місяці тому

    how to evaluate the yolo model in google colab notebook

  • @tamilgenius7684
    @tamilgenius7684 4 місяці тому

    how to evaluate the yolo model in google colab notebook

  • @tamilgenius7684
    @tamilgenius7684 4 місяці тому

    how to evaluate the yolo model in google colab notebook

  • @Mica_No
    @Mica_No 2 місяці тому

    what about live video detection?

  • @oguzkurtoglu
    @oguzkurtoglu 5 місяців тому

    Can you make video about semantic segmentation?

  • @yameenkhan127
    @yameenkhan127 4 місяці тому

    how about video and live footage

  • @binhphan2928
    @binhphan2928 3 місяці тому

    You can instruct yolov8 pruning with torch-pruning ?

  • @chvitaalston7110
    @chvitaalston7110 5 місяців тому

    Hey!The following error occurred while I was running, what should I do?
    RuntimeError:
    An attempt has been made to start a new process before the
    current process has finished its bootstrapping phase.
    This probably means that you are not using fork to start your
    child processes and you have forgotten to use the proper idiom
    in the main module:
    if __name__ == '__main__':
    freeze_support()
    ...
    The "freeze_support()" line can be omitted if the program
    is not going to be frozen to produce an executable.

  • @akhilsajeevan1192
    @akhilsajeevan1192 3 місяці тому

    Hi i have a doubt,
    if i have 4 classes and and train yolo v8 model with my custom data set .
    and i want to add 2 more new classes in the trained yolo model with new classes without loosing the weight of the first trained model.
    How to do that ? show me step by step procedure in simple steps.
    Do freezing can be done?
    If so show me that technique also .

    • @NicolaiAI
      @NicolaiAI  3 місяці тому

      Show me show me. But no you can’t do that. You have to retrain

    • @akhilsajeevan1192
      @akhilsajeevan1192 3 місяці тому

      @@NicolaiAI when retraining i have lost weight of first traiing.
      The model now only knows the classes of last training.
      I don't want like that i want model to have both weights of first training and the last traing also.
      Is there any solutions for that?

  • @HarisKhan-ph9jl
    @HarisKhan-ph9jl 4 місяці тому

    You have written yolov9 in the video and you are training yolov8. 😔 😔

    • @NicolaiAI
      @NicolaiAI  4 місяці тому +1

      Nope 14:21 it’s yolov9 and training right after. Yolov8 from the code example from Ultralytics and then changed the model name

    • @HarisKhan-ph9jl
      @HarisKhan-ph9jl 4 місяці тому +1

      @@NicolaiAI Thanks for your quick response! You are absolutely right. I just watched the full video, and I apologize for the misunderstanding. I'm planning to run it on Kaggle and would love your assistance with that. Thank you so much! I just subscribed to your channel-keep up the great work!

    • @NicolaiAI
      @NicolaiAI  4 місяці тому +1

      @HarisKhan-ph9jl thanks a ton!

  • @LukasSmith827
    @LukasSmith827 5 місяців тому +1