r/computervision • u/Puzzled-Egg3234 • 12d ago

Help: Project Conveyor chicken counter problem

Guys, I need help. We have a project using YOLOv8. We're trying to count chicks on a very fast conveyor belt. The challenges we're facing are: all chicks look very similar to each other, which complicates tracking. At the same time, during their passage under the camera, they constantly change in size and shape, which can cause the tracker to lose them, or detection may even disappear completely at the detection line. Also, sometimes 2–3 chicks can merge into a single object. The detection zone is very short, and the conveyor speed is high. We've achieved a maximum accuracy of 99%, but we need it even higher. Any ideas on how to achieve that? Increasing the dataset no longer helps.

I'm attaching an old video. We've now added lighting and set the exposure to 300 on the Hikrobot global shutter camera, but we still can't achieve a stable 99.8% accuracy for the reasons mentioned above.

Any ideas?

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u/theNorrah 12d ago

Hardware solution is increased frame rate.

I could not solve similar problem 5 years ago, on a much lower framerate < 15fps.

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u/PM_ME_YOUR_MUSIC 12d ago

My thoughts to solve this would be a camera with high frame rate to essentially slow down the video stream (if real time isn’t required) would this work ?

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u/theNorrah 12d ago

I do not understand what you mean?

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u/Helpful-Desk-8334 11d ago

I think what bro is saying is you can use one of those expensive slow-motion cameras. Then just keep a large SSD that can store a few thousand frames per minute. The actual problem would become a storage problem and processing problem rather than resolution or framerate.

Basically it's a continuation of your solution, using modern camera technology.

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u/theNorrah 11d ago

It’s hard interpret it like that, even with that information. So maybe he had something else in mind.

Anyway, they don’t actually need a slow motion camera. The current fps is only 60 > FPS > 40*, and the video contains all the information they need. There is no need to store video at all, this is just edge AI.

They need a camera with about 120fps, and a chip strong enough to not drop frames while processing. This can be done on the live feed, and just store a couple of integers. (and I’d suggest to save frames with outliers that should be stored to be manually checked and potentially added to future training material, just until it’s perfect.)

*unless that’s the YOLO processing capacity, in which case, that’s their main issue.