[anigbrowl]

Shooting from the hip here, but I'd much rather you optimized for speed and allowed selection from a rotating palette of local maxima. I noticed your sadness about the limitations on the picture of the indian woman leaning against a tree whose hand came out red, presumably because of vignetting or some chemical inconsistency in the film substrate. But that superposition of possible interpretations on noisy data is something that shouldn't be thrown away - it's the same 'error' that makes optical illusions interesting when they seem to flip back and forth between being a vase and 2 faces or a duck vs. a rabbit. The model is doing such a great job that trying to push it too far in any one direction risks overfitting.

What I'd love to see in the future are compound networks where a few nodes like this can be mixed with a few nodes that extract vector data, a few others that infer depth maps from images, modulated by similarity detectors that match objects and individuals.

I'm very impressed by the work you've already done - I have a huge library of images I'd like to run it against for both forensic and aesthetic purposes.

[ekianjo]

> I noticed your sadness about the limitations on the picture of the indian woman leaning against a tree whose hand came out red,

I think the biggest problem is that picture is not the hand (its very visible and it could be easily fixed in post processing), it's the blue shade in the clothes that just should not be there. Otherwise, the colors are great (skin and all look very real).

[Mtinie]

Are we discounting the possibility of the NN calculations resolving to show her hand as it really existed? Tonally, it may have been differentiated from the general population in such a way the algorithm amplified this difference?