Ok, let's go for a "sharpness score" + focus peaking feature. That way, users will have a way to check which area is in focus, and compare images between them with a score.
It won't made it to next release, but maybe first minor update. Le 06/10/2019 à 17:05, Robert Krawitz a écrit : > On Sun, 6 Oct 2019 16:40:37 +0200, =?UTF-8?Q?Aur=c3=a9lien_Pierre?= wrote: >> argh. Tales of over-engineering… > I don't really disagree with you, just want to point out that getting > it anywhere near correct (i. e. without a huge number of false > positives and false negatives) is a difficult problem. > >> Just overlay the euclidean norm of the 2D laplacian on top of the >> pictures (some cameras call that focus-peaking), and let the >> photographer eyeball them. That will do for subjects at large aperture, >> when the subject is supposed to pop out of the background. For small >> apertures, the L2 norm will do a fair job. And it's a Saturday afternoon >> job, hence a very realistic project given our current resources. > That's fair, I just think that this kind of algorithm will likely > select a lot of photos that are badly out of focus (because the focus > locked on a much more expansive background) and miss ones where it's > the relatively small subject that's in focus. > >> What you ask for is AI, it's a big project for a specialist, and it's >> almost sure we will never make it work reliably. The drawback of AIs, >> even when they work, is they fail inconsistently and need to be >> double-checked anyway. >> >> So, better give users meaningful scopes and let them take their >> responsibility, rather than rely on witchcraft that works only in >> Nvidia's papers on carefully curated samples. > Or maybe just implement focus peaking, as you say, but with a UI > similar to the camera's UI (flashing regions that are in best focus). > Then it's up to the user to select the best photos based on their > knowledge of the desired subject. > >> Le 06/10/2019 à 16:18, Robert Krawitz a écrit : >>> On Sun, 6 Oct 2019 15:02:39 +0200, =?UTF-8?Q?Aur=c3=a9lien_Pierre?= wrote: >>>> That can be easily done by computing the L2 norm of the laplacian of the >>>> pictures, or the L2 norm of the first level of wavelets decomposition >>>> (which is used in the focus preview), and taking the maximum. >>>> >>>> As usual, it will be more work to wire the UI to the functionality than >>>> writing the core image processing. >>> Consider the case where the AF locks onto the background. This will >>> likely result in a very large fraction of the image being in focus, >>> but this will be exactly the wrong photo to select. >>> >>> Perhaps center-weighting, luminosity-weighting (if an assumption is >>> made that the desired subject is usually brighter than the background, >>> but not extremely light), skin tone recognition (with all of the >>> attendant problems of what constitutes "skin tone"), and face >>> recognition would have to feed into it. ___________________________________________________________________________ darktable developer mailing list to unsubscribe send a mail to [email protected]
