I have a set of images of a specific object. I want to find if some of them have anomalies with machine learning algorithm. For example, if I have many photos of glasses, I want to find if one of them is broken or has something abnormal. Something like that:
OK!!
BADLY!!
(Obviously, I will use the same kind of glasses ...)
The problem is that I do not know every negative situation, so for training I have only positive images.
In other words, I need an algorithm that recognizes if the image has something other than a dataset. Do you have any suggestions?
In particular, is there a way to use a convolutional neural network?