I’ve been looking into it and it looks like the pre-trained model really just gets me a jump on the needed convolutions for detecting features, and that if I want, for example “person”, “chicken”, and “frog” classes, I’ll need to include all of them in my training data set and not just “chicken” and “frog”.
Does that sound about right?
Thanks.