I was solving a problem recently for an insurance company in which I have to build a model to classify a Phone screen into broken or non broken followed by tempered vs screen glass classification. I have tried lot of fine tuning with different architectures but it seems that the models are Biased towards one class I spite of the training data containing equal no of classes. As both the classes are very identical.
Can you please help me out?
I’m attaching training data link
(not sure)
Actually I guess the problem is that a scratch or broken lines in a screen which is black will hardly be visible…
(Have seen some images of both classes)