st0mpst0mp

Most tensorflow CV models using cnns start by blurring the images until only prominent features are created as it passes through the layers. I've thought about this problem quite a bit and don't think that deep learning models would really work for grading. I think what other people have mentioned actually makes more sense... where maybe you look at it from a more simplistic point of view. What i've been thinking about doing is to use something similar to crack detection as a basis for spine folds, and then finding the distribution for the various grades. Then doing edge detection to calculate how sharp/not sharp corners are, then another model for determining some of the other things listed on https://www.comicbookgradingtool.com/. Then you can "sum" up the different scores or build something like a linear regression model to make a final score prediction based on the summation of other scores.