I’m very into the outdoors too and was wondering about this very thing not long ago when I was trying to decide between ConCamo or PenCott Greenzone for my area.

I don’t know if you would need an ML-based solution to this. One way to frame the problem is that you would be trying to find a pattern that has the closest colour channels to the environment. I can’t remember my exact thinking now, but I think there may be simpler ways to assess this, and I’m not sure that there’s any “learning” required of the system. That said, a way to measure how good a match is could be to try and maximise the number of false negatives of a simple object detection network like Faster-RCNN when shown a given camo against multiple photos of the area intended for use.