I'm making a Car Damage Detection model which would have 2 classes to detect upon. My dataset has a total of 300 images (out of which I'd be using some for testing), which are totally insufficient to train the model from scratch.
Can I use a pre-trained model to train my dataset and detect images based on the 2 classes, and if yes, then which one should be the best on my problem set?
P.S. - I would prefer to use Faster-RCNN on my dataset