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To add to that point, if you manage to get screenshots you can do an image comparison using perceptual hashing [0]. The idea is to compute hashes of images and compare those, rather than scanning through each pixel.

Note that perceptual hashes should not obey the avalanche effect, so a minor difference in the two images should yield a small change in the hashes (desirable in this case). Then accept results that are within some small % error margin.

An example of a library that does this is jimp [1].

[0] https://en.wikipedia.org/wiki/Perceptual_hashing [1] https://github.com/oliver-moran/jimp#comparing-images




This is a really cool concept. Thanks.




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