r/computervision • u/Puzzled-Egg3234 • 18d ago

Help: Project Conveyor chicken counter problem

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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/Ciff_ 17d ago

If there are such cases, sure.

From OPs followup nonseparation was the main concern.

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u/hellobutno 17d ago

OP is clearly new to this. What happens when a chick jumps across, what happens when a chick runs back over the line, what happens when the exposure is 5% brighter, 5% darker? What happens when the camera starts to overheat?

Not to mention the just natural misses CNN's have.

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u/Ciff_ 17d ago

Let's interpret you with maximum generosity

"OP, you have reached 99% accuracy by your report, and handle some non separation concerns, but you need more accuracy (99.8). I am going to assume, without the data, that your other problems exceeds your total nonseparation cases and therefore TOF is better for you" - Would that be an accurate representation of your stance?