Maybe do some deduplication first? https://github.com/qarmin/czkawka
czkawka
That certainly would thin the pile and cut down on the manual labor aspect. It uses a hashing method, iirc. Used it to thin out duplicate audio files, being careful not to delete files that might have the same filename but one would be a live rendition, and a studio/album rendition of the same song. Jimi Hendrix, in my experience, is notorious for this. One of the things that I dig about him, is that he never really performed the same song the same way. He sort of just really went with a stream of consciousness and pulled it off quite well.
I am unsure how you would go about that without AI. You could probably write a python script that hooks in with AI, that ranks by focus, brightness, saturation or other such criteria. However, I suspect that there would have to be a fair amount of manual labor to do that. That's an interesting request. I'll watch the thread and see what the outcome is.
The problem I see here is that the best images are those that have been edited, i.e. rotated, cropped, and adjusted brightness/contrast/saturation/white balance. Like I can have a thousand snaps from my camera, but they'll only look good once I pick them out and edit them.
I suppose, if you have a consistent camera with photos in consistent conditions, you could apply edits in bulk. And I know Google has automated crop/rotate/etc features in the Google Photos app, so maybe you could find a self-hosted tool smart enough to do that across all your photos, then make a review pass to pick out the good ones.
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