YOLOv8: Real-Time Object Detection with Webcam

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In this video 📝 we are going to Deploy a YOLOv8 Object Detection Model in Python. We will see how to deploy a trained YOLOv8 model and run live inference on a webcam. This can actually run in real-time. You can also check out my YOLOv7 Course where we cover everything from generating a dataset, setting up the model, training, and deployment.

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Tags:
#yolov8 #yolo #objectdetection #ultralytics
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NicolaiAI
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Is it possible to use different custom trained models in a single project with webcam. I trained a model with ASL alphabet and another models with ASL action, how can I join both models together on my live webcam project so that it can detect both alphabet and action. I am using ultralytics python library.

adekojoadeyemi
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So I don’t need to worry about open cv from source for GPU support for this? Just need the PyTorch with GPU support?

Cam
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Where can I see the full yolov8 architecture for object detection?

fedorlaputin
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why when I try with the yolov8n model the fps drops and touches 15 ms?

zrlcproject
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Can you try how many FPS would you get on TensorRT Yolov5 torch as you have RTX 4090ti? You should get at least 170fps

gased
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Is it possible to proceed with the vehicle speed estimation, which is a whole project, in real time through YOLO-World?

kggsofw
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If I am trying to use yolo8 and opencv to show bbox of the objects the video starts to run in a slow motion. Any ideas why it's happening?

vovvas
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How did you know that the "zero" in model.predict( source = 0 is the webcam. I want to send live camera content from an android app to the windows machine then do Real-Time Object Detection with YOLOv8 and then in the phone screen to print labels with the prediction just like 11:35 in your video. How could I do that?
Thanks

starioa
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I want to classify different classes like types of cars model how can i achieved it?

Tolazytoedit
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Do you still have to install CUDA on your machine? Because somewhere I read that torch comes with its own toolkit. I kinda don't want to mess up my other projects, that are using CUDA 10.0

benjaminlines
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getting a syntax error at step 1.. anyone knows how to fix?

lphonehacks
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Hello I just have a question how to retrieve the processing times per image that are displayed in the terminal on yolov8?

ToezzyTV
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Hey ! I have used yolo v8 with my rtx 3050 and I am getting good training and predictions on the coco128 dataset
BUT the problem arises when I try to use a custom dataset, the training goes well, but when I see predictions it just gives the same image with no bounding boxes. The labels are correctly placed because it gives the bounding boxes for the already defined labels, but not any for predicted ones . Any solutions ?

divyejoshi
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Hello, Nicolai! Very good video. How can I count and memorise in a variable the objects that the model detects and display the maximum number of the objects from a class into the console? Thank you!

nochance
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I have a problem. When i run the vscode script i get the results printed in the terminal but the webcam isn't displayed. What can be the source of the problem? Knowing that my webcam works fine (when i execute the cv2.imshow() it's displayed)

houdabekkourialami
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results = model.predict(source="0", show=True) # accepts all formats - img/folder/vid. - what would be the rest of part?

TravelwithRasel.
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i need to do the same for a youtube video, , my problem detection happens but i need to show the video it doesnt exist

moahaimen
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how do you change the size, there are different webcams and with different resolutions, not all of them are 640. Like when an .mp4 video is processed?

cesarriat
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In the results... should be a tensor, right? Because in older versions you could do:

results = model("image.png")

And in the results would be your bounding box data. Now it tells me that there are 2 persons and 1 tie in that image (and it's also correctly saved in predict folder) but if im trying to print the result it prints none. Is there some extra method of getting results? Not working with camera right now, just an static image.

benjaminlines