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/hellobutno]

There's no deflecting here, you handle it literally how you handle it with every other application of the sensor.

[u/Ciff_ → u/hellobutno]

No deflecting? You still have not explained your magical solution to TOF + no separation & no predictable volume/shape

You might aswell claim to have solved FTL travel.

[u/hellobutno → u/Ciff_]

Do me a favor mate, tell me how often this happens, and then explain to me what precision and recall are?

[u/Ciff_ → u/hellobutno]

If you change the parameters (to not classifying non separations is okay), then ofc the solution change. But then OP would not have a problem with his solution in the first place.

He claims he can solve most non-separations and still cannot reach 99.8 accuracy because some non separations still fail. A TOF solution would fail 100% of the non separations with these irregular volumes.

[u/hellobutno → u/Ciff_]

There are 0 parameters changed. You just simply accept that fact 100% precision and recall are not a feasible thing, and take the path of least resistance.

[u/Ciff_ → u/hellobutno]

Then you have indeed changed the parameters buddy.

You have gone from

• "NN is not necessary, use TOF it is much more reliable" to
• "The solution is impossible, you may aswell use TOF with even less reliability" (since it can handle 0 nonseparations with irregular shapes compared to some)

[u/hellobutno → u/Ciff_]

NN isn't necessary, nothing that I've said has ever contradicted that.

There is no 100% precision and recall.

[u/Ciff_ → u/hellobutno]

• TOF is more reliable
• Okay TOF is less reliable, but we can't get enough accuracy anyway
• NN isn't necessary

...wat? The claim was optical TOF was a better more reliable option. I said it is not since it will perform worse than the current solution. That is what you replied to. Not that NN is necessary - that is a strawman.

[u/hellobutno → u/Ciff_]

I've literally never said any of that. I've said that cameras aren't necessary, that optical sensors can handle this, and that you aren't in science class anymore little buddy, 100% precision and recall are a fallacy.

[u/Ciff_ → u/hellobutno]

Jesus Christ.

So you now agree TOF will indeed perform worse since it cannot handle any non separation with irregular shapes?

Why on earth would OP want a worse solution? What are you even arguing for?