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On 1/28/2022 at 12:12 PM, Tailwagger said:

 

What the algorithm would see as relevant in the image for providing the answer who knows. In all likelihood, we'd be surprised by the attributes it sees as crucial. But thats the magic... and irritation... of ML. 

An ML approach like you describe here, looking at an entire image in detail, may well consider depth of field.

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Adan's point about the experiment in which you cover the brightness sensor with a fingertip reminds me -- It 's also a way to see if the firmware for a new model M is still incomplete.  When you cover the brightness sensor, the aperture reported should be the maximum opening for that lens, and there is a field in the firmware for that information.  I've seen some very strange things come up, like apertures of 0.0 or 1.0 for lenses that are not that fast.

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