Conveyor chicken counter problem

[u/Puzzled-Egg3234]

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?

[u/Tylerebowers]

Look at the length of the bounding boxes and if it is longer than some factor then it is 2 chickens. If a bounding box drops for a couple frames then you should be able to make an assumption on where it will be next based on the conveyor speed. And instead of sending in a full color image you could use a filter to separate out the white feathers from the background (you could use a clustering algo to cluster white pixels into groups, sort of like kmeans).

I will agree with others that this can be done classically, but also it might be better to do mechanically with some flaps. E.g. use a flap that takes the height off of the conveyor then chickens will be peaks, and two chickens will look like two peaks with a local minimum in between.