I am curious if DL really can deliver good results in such spaces. We all see success stories for very refined and well defined problems with huge amount of tr

I am curious if DL really can deliver good results in such spaces. We all see success stories for very refined and well defined problems with huge amount of training data, with models created by 1% top engineers, but for average business such conditions may not be achievable, to train model to recognize various shelf conditions in different situations, buildings, etc. you need nontrivial set of training data, and will have unclear expectations about model performance.