These are the most impressive results I'm aware of: https://github.com/david-gpu/srez https://github.com/alexjc/neural-enhance https://arxiv.org/pdf/1609.04802.pdf
but both gives the best results with specialized training (faces for example). The one Michael proposed seems a more generic one. No idea about performance but "execution" time is usually fast, memory may be a much bigger requirement. This one is about noise reduction: http://webdav.is.mpg.de/pixel/files/neural_denoising/paper.pdf I think in a couple of years machine learning will be the only way to achieve state of the art results for about anything. If not today already. Noise, white balance, clipping recovery, blurry/out of focus shots, color casts, lens correction, defringe, sharpening, inpainting, etc. Up to this (pose edit, content generation): https://github.com/nightrome/really-awesome-gan https://www.slideshare.net/Artifacia/generative-adversarial-networks-and- their-applications (slide 24, 27) It's going to be fun :) Lorenzo 2017-07-09 18:14 GMT+02:00 David Vincent-Jones <david...@gmail.com>: > Along the same line: Some years ago Cliff Reiter (Lafayette College) > (using Jsoftware) demonstrated and published 'lossless edge' image > rotation using fractals. > > David > > On 07/09/2017 08:16 AM, Michael Below wrote: > > Hi, > > > > last week I took a couple of images at a concert, and it turned out > > that only a small part of each image was interesting. I was too far > > away, with a wide-angle lens, so the band I wanted to photograph was in > > a small part in the center of the frame with lots of other stuff around > > them, stage, audience etc. > > > > Now this can be solved by taking better pictures, coming closer, being > > prepared with a telephoto lens etc. - but there also seems to be a > > solution that could find its way into darktable. > > > > There have been a number of media reports about machine learning > > experiments by Google etc. to add missing detail to images during > > upscaling. It seems like the results are often quite convincing. Now I > > stumbled upon a Github project for this that seems to offer a hands-on > > solution which might be a basis for implementation in darktable: > > > > https://github.com/lucasdupin/ml-image-scaling > > > > What do you think? I imagine this would be useful... > > > > Cheers > > Michael > > ____________________________________________________________ > ________________ > > darktable user mailing list > > to unsubscribe send a mail to darktable-user+unsubscribe@ > lists.darktable.org > > > ____________________________________________________________ > ________________ > darktable user mailing list > to unsubscribe send a mail to darktable-user+unsubscribe@ > lists.darktable.org > > ____________________________________________________________________________ darktable user mailing list to unsubscribe send a mail to darktable-user+unsubscr...@lists.darktable.org
