How to handle images that don’t pertain to image classifier at all? I am trying to create a CNN model that classifies if a person is wearing a seatbelt or not to verify they drive safely. I know to get images of people wearing seatbelts and people not wearing seatbelts, but I have a problem.
What if the person doesn’t submit a picture of them in a car at all? How do I construct the rest of the dataset to determine if that picture is an actual picture of a person wearing a seatbelt?
Do I insert completely random pictures in a different category? Do I classify images that don’t have a high confidence score as &quot;wrong&quot; images? Or leave it?
Yes, a category &quot;no person&quot; or &quot;random image&quot; would make sense. Binary classification is only helpful if you know that your input always belongs to one or the other category, for example by pre-filtering the inputs.