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And then I have both the Jupyter notebook “test” image suites and then a batch of 100s of more public domain images. It’s painful and tedious but using my eyes on these directly I’ve found is the only reliable way I have to measure progress. And even the you have to be extremely
careful about perception issues- you misremember stuff easily, and literally see things differently depending on context. So I don’t necessarily take a first go at it as the final say as to whether or not the model is great or not.
And yes this process drives me nuts and please tell me if there’s a better way lol
Your feedback to what is good, and what is great, eg. the human perceptual things you ended up focusing on, would be very interesting! I imagine trying to approximate your process with a loss function would lead to improvement in other domains.
Translating “it looks cool” to something tangible and repeatable like that is tough! But yeah it would really be beneficial.
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