That transfers computer time to user time. It's great when you want variations, less so when you want precision and consistency. Picking the best image tires the brain quite quickly, you have to take into account the at a glance quality without it overriding the detail quality.

I'd be curious to see how a vision model would go if it were finetuned to select the best image match to a given criteria.

It's possible that you could do O1 style training to build a final stage auto-cherrypicker.