If like me you're using Real-ESRGAN-ncnn-vulkan [1] and are curious what upscayl-ncnn CLI [2] changed from it, there's not much and nothing substantial [3]. Not a criticism, just wanted to learn whether it's worth upgrading to for a CLI tool ($subj is a separate GUI app based on it).
Upscayl NCNN has several fixes (like latest vulkan, bug fixes, feature additions) and is coming up with more soon (we just haven't pushed the changes). Also working on CPU support.
If you're going to use Real-ESRGAN, you're going to have to deal with a lot of issues and a codebase that hasn't been updated in a long time. Afaik, Upscayl NCNN is the only project maintaining Real-ESRGAN NCNN as of now.
I've only used -i -o -n mode, but for me that just works. And when something just works, I tend to see "a codebase that hasn't been updated in a long time" as a good thing generally :)
(Don't take it personally, it's my burnout from modern software cycles.)
I understand. With Upscayl it's a little more configurable.
For example, you can add compression to the images, change the format (which Real-ESRGAN can't always do), drag and drop images, have extra models not shipped by default and in future even have face enhancement.
I have used RealESRGAN for some years now, and several pictures hang on my house that were enlarged using this.
I enlarged a lot of old pictures from family albums, and then fixed the bad spots with something like Photoroom, Snapseed, etc., and then sent them to be printed.
Works really great.
And not only that, if I find an old picture on the internet that is low res with no high res found after much google-fu, Duckduckgo, or Kagi, I use RealESRGAN to upscale, and then use it as my wallpaper, presentation background or whatever!
Yes! I Real-ESRGAN is still the best algorithm for enhancing images. The only algorithm better than it is Topaz's but that's to be expected from a paid product.
Real-ESRGAN can get better with a better trained model too, which is on Upscayl's roadmap.
Does anybody have experience training/finetuning Real-ESRGAN models? I downloaded one of their datasets to see what they are working with, and it has 800 images at ~3Mp resolution. I am curious if others have results based on higher resolutions + more/fewer images in the dataset? I would like to use it for fine art paintings by period / style, etc.
[1] https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan
[2] https://github.com/upscayl/upscayl-ncnn
[3] https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan/compare/m...