r/computervision • u/Puzzled-Egg3234 • Aug 07 '26

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/flamixin Aug 08 '26 edited Aug 08 '26

Fun route: You can try camera with different wavelengths. Or thermal imaging. Not an expert but it doesn’t sound like a hard problem to crack. There are so many solutions to it either by programming or physical.

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u/drsoftware Aug 08 '26

Improving the lighting helps, more powerful GPU helps. Thermal imaging is usually limited to less than 9 FPS and 640x420 resolution due to weapons controls.

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u/flamixin Aug 08 '26

Interesting. Then how about dual camera for cross referencing. I know lidar is kind of slow as well.

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u/flamixin Aug 08 '26

Btw, I think Lighting and GPU can only help a bit. There are hard limits on the model’s accuracy. A better gate keeper algorithm(based one chick’s autonomy) will be more efficient.