I am building an image classifier that discriminates against a certain class. As a toy example, let's say the classifier checks if the image is a hotdog or not (1 or 0). My question is what images would I be using to train on the 0 (not hotdog) class? Should I just use random objects or is there a more sensible way to go about this? Thanks
Think about the context in which you want to run your classifier later on. Will you want to extract still-usable food from garbage (so you can, say, turn it into livestock feed)? Then get a lot of garbage, separate it out and train your classifier. Do you want to automatically distinguish hot dogs from hamburgers and cheeseburgers? Then train it against such images.