Simple YOLOv8 Class for Object Detection with Webcam in Real-time

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In this video 📝 we are going to create a simple YOLOv8 class for 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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Timestamps:
0:00 Intro
0:42 YOLOv8 Class
4:00 Load Model
5:53 Predict
6:29 Extract Info & Visualize
11:56 Main Loop
14:37 Results

Tags:
#yolov8 #yolo #objectdetection #ultralytics

[NicolaiAI]

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[seyedamirhh]

Thank you so much, this is really helpful and well explained.

[al-musbahitechnology]

Thank you, you helped me a lot, but I still have a problem. I trained a model to recognize license plates. It identified them, but I also want it to print the number of the car that it identified. Can you explain this method?

[maiquelkappel]

Congratulations on the video. Could you make a video like this, but using monitor screen?

[qmixcnk]

I want to transfer the names of the detection objects in yolov8's real time analysis to the mobile application in real time via websocket, how do I do that?

[a.a.ardebili]

Thank you for the video. How I can set a filter to detect and draw BBox ONLY for "Person"? Is it possible to set up an area in the video frame the detector detects the objects only in that area?

[cashyc]

Can this implement in raspberry pi? Will this makes the fps drops?

[vijaypaulraj]

How can we print the objecct detected?

[athanasioschatzipanagiotou]

Great video. However I wonder how to get a very smoothly output. I have tried multithreading however the output is a bit of choppy. Not tottaly smooth. Do you have any solution on that

[nnpncpd]

where is the code can you share me the git link of your repo
pls

[mystuff]

Hi, I would like to know how to count the amount of detected object per class. Is this possible? I could only get the amount of all the detected objects.

[inteliii]

The following error comes up:
ValueError: too many values to unpack (expected 4)

It is in the following lines:
self.labels = {confidence:0.2f}"
for _, confidence, class_id, tracker_id
in detections]

[thekushalgaikwad]

Can you build an app which integrates yolov8 for object detection?

[umarmohamed]

Thanks for that Video, it's really helpful.
if possible, can you share the name of your chair plz😅.

[mystuff]

Great Video! But I unfortunately had an error occurred, "TypeError: unsupported format string passed to list.__format__". Any idea on how to fix this?

[nhatpham]

Hello, thank for your video
But i have a problem:
from supervision.tools.detections import Detections, BoxAnnotator
ModuleNotFoundError: No module named 'supervision.tools'
Can you fix it? Thank you, have a nice day!

[fassesweden]

If I only want to display bboxes with confidence >0.5 where Can I do this in the code? Great video!!

[currogonzalezfleta]

Hi, I have the next error: ColorPalette.__init__() missing 1 required positional argument: 'colors'. Any idea?

[JasonKim-yzrv]

Can YOLOv8 perform instance segmentation in real-time?

[soenwzb]

I came here after seeing your comment link.

I'm trying to load my trained best.onnx file. However, I'm getting the following error:
return self._sess.run(output_names, input_feed, run_options)
[ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Got invalid dimensions for input: images for the following indices
index: 2 Got: 640 Expected: 320
index: 3 Got: 640 Expected: 320
Please fix either the inputs or the model.

I tried adding self.img_size = (320, 320) in __init__ and modifying the predict method as follows:
def predict(self, frame):
frame = cv2.resize(frame, self.img_size)
results = self.model(frame)
return results

But I still encounter the same error. Is there any specific reason for this?