ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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How I can count objects using yolov5 #6167

Closed mehar50 closed 2 years ago

mehar50 commented 2 years ago

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Question

I trained yolov5 on my custom dataset, more specifically my goal is to count roadside trees, which perfectly works for detection. Now I want to count these trees like if a tree remains in more than one frame it should not be counted multiple times.. I'll be grateful if someone can help me in this regard... Thank you for reading this

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github-actions[bot] commented 2 years ago

👋 Hello @mehar50, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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KristofferK commented 2 years ago

You could take a look at the multiple object-tracking algorithm Deep SORT. Articlies like Real Time Pear Fruit Detection and Counting Using YOLOv4 Models and Deep SORT have successfully used Deep SORT together with YOLOv4, so I assume it would also be possible to use it with YOLOv5.

ghost commented 2 years ago

maybe this helps you, even if it is for yolov4

https://www.youtube.com/watch?v=jDwC5m7c7BU

glenn-jocher commented 2 years ago

@mehar50 👋 Hello! Thanks for asking about object tracking in computer vision. YOLOv5 🚀 is an object detector that detect, localizes and classifies objects in a single image. It does not connect objects across multiple images, for this you need a tracking solution. A few possible tracking solutions are:

Good luck 🍀 and let us know if you have any other questions!

ghost commented 2 years ago

@mehar50

sorry, i misread your question. actually i also try to count objects on a single image of mine. how could you count the detected objects by classes? could you share your code please?

github-actions[bot] commented 2 years ago

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

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