[natch]

One more thing: I tried the different hashes that would run on my system (some had a dependency on opencv-contrib that was not met, and which python -m pip couldn't find) and found they aren't what I'm looking for. They may be good at finding different versions of the same image, but what I want is more like environment similarity. So that two pictures taken on the same street would be closer than a picture of the street versus a picture of a forest. They don't seem to be tuned for this task at all. So, my search continues. Let me know if you have suggestions on this as well.

[faustomorales]

Perceptual hashes in this family will probably not be the right fit for that use case. There is work out there to build hashes that are intended to find find semantically similar content, typically using CNNs. Imagededup [1] seems to have one of these though I have never used it myself.

[1] https://idealo.github.io/imagededup/