Only tangentially related to this story, I've been trying for months to train the YOLO models to recognize my Prussian blue cat, with its assorted white spots, as a cat rather than a dog or a person.
However, it refuses to cooperate. It's maddening.
As a result, I receive "There is a person at your front door" notifications at all hours of the night.
I've had a Nest camera in my living room for years just to keep an eye on our dogs while we're away from home. One of the dogs, a basset hound/border collie mix, often howls and makes "squeeing" noises while we're away. Nest (or Google now, I suppose) without fail thinks that this is actually a person talking in my living room and sends us notifications alerting us to this fact. If he moves around, Nest thinks it's a person moving in my living room.
It has no problem identifying our other two dogs as actual dogs who bark and move like dogs.
Something is very wrong if the model cannot tell the difference between a Prussian blue cat and a person. I imagine you have inserted in training data the images of the cat from the camera and in similar quantities of a person from the same camera.
I have a Tapo camera which from all the cats parading from my yard, only one black cat is recognized as a person. Not other cats. Not even other black cats. It makes you think.
How exactly are you trying to train and deploy this YOLO model? What kind of accuracy are you seeing against the validation set at the end of the training process?
However, it refuses to cooperate. It's maddening.
As a result, I receive "There is a person at your front door" notifications at all hours of the night.