Started the day off by trying to get a siamese network to work alongside my algorithm but I didnt get any results yet. Afterwards I setup a system with my custom algorithm such that I give it a pre-made list of the best images to look at. I also actually went back to using EMD because I realized an issue with the program was that there were too few buckets. My previous way of using 12 hue buckets and 8 saturation buckets was being too lenient with EMD because a shift from orange-yellow to green in hue would just be like 1-2 buckets away. This means that the program wasn’t sensitive enough and as a result favored the extreme classes (dense and dry). I changed back to EMD, added the best list, and increased the buckets. The image used in this devlog actually is using random images from the 80 folder as the training sample, which is the eventual goal (Being able to use totally random training images to work the best) so I think this is hte most fair to post as progress. I’m thinking maybe I can add some system that automatically chooses the best images?