Hi,
I've built into a stock catflap, a prey sensing Raspberry Pi OpenCV camera system that will check the underside of our cat's mouth and if cascade trained prey is detected, will lock the catflap so Fluffy can't come in with her murder present.
I've spent a number of months trying different positives / scaling / neighbours. Whilst I've been able to get it to lock for some detections such as eyes and tail of the mouse, it doesn't seem to pick up noses or the claws very well.
I trained it with 200 positives and over 9000 negatives.
The best I've gotten was with the HAAR cascade, with Scale factor of 1.01 and Min Neigh of 2.
I don't need to scale much as the cat always comes through at the same distance and the mouse / bird is virtually the same size. It's a positional thing if the mouse if facing forward rather than rear etc. Hence getting as many positional positives as possible.
What I don't understand is when I tested the cascade with the images it was trained with, you'd think it would pick them all out but it doesn't.
Any recommendations on how to fine tune the Scale and Neighbours or even the images going into the cascade?
I've put the cascades, positives and tests here. https://bit.ly/2OKdP43
You're welcome to use the positives in your projects.
Many thanks
Richard