I want to train a model to recognize the different categories of food e.g. rice, burger, apple, pizza, orange and other things.
After the first training, I realized that the model is detecting other objects as food. e.g. hand as fish, phone as Chocolate, person as candies.
I get a very low loss because the testing dataset and validation must have at least a pictures of food. But when it comes to a picture of an object other than food, the model fails. How do label the dataset in a way that the model will not do any detection if there is no food on the picture?