Why not both?
Yes, and it's optimized for Core ML 3 to take advantage of multi-GPU support, making this feature much faster on devices with a dedicated GPU.
This feature is very memory-intensive so it may not be possible to bring it to iPadOS due to the differences in memory management, but we'll most certainly try.
It requires macOS Mojave or macOS Catalina, so it won't work on High Sierra — apologies for not making that clearer!
The print size of the image shouldn't change, only the resolution/pixel dimensions should — when using the ML Super Resolution menu command at least. You could also open up Image > Image Size and enter a custom size/resolution, choosing the ML Super Resolution algorithm for resizing.
It would! We might be able to do this, actually.
Yes, that's a very good point! Also, it won't do much to images that have already been enlarged and are blocky or blurry because the algorithm will interpret the blocks or blurred edges as textures. You could try downscaling the image first and then upscaling using ML Super Resolution.
You're absolutely right, fixed!
I really hate spoiling surprises but, seeing as you're asking:
1. Adjustment layers — maybe in the second half of next year? We need to finish up the color adjustment feature set first and a few foundational changes need to be made to bring the Clarity adjustment as well as improved shadows and highlights.
2. Replacing multiple colors — this is a UI thing as this feature could already work this way from a technological standpoint. And we'd also need to add it to Pixelmator Photo due to the shared codebase. But thanks for the reminder.
3. Color picker — in development at the moment but it doesn't look like it'll come before the new year. It's going to be really cool, though, so it's worth the wait.
4. ML Denoise — the 1.5.4 update brought some improvements to ML Denoise, and 1.5.5 will bring even more. The results should be much more dramatic after these updates (especially in images with heavy noise) but a slider won't appear just yet.
And I wanted to bring your attention to "Let's Enhance": https://www.youtube.com/watch?v=Vxq9yj2pVWk
ML Super Resolution is designed for upscaling images only — for downsampling, you're best off using one of the other algorithms.
Super-resolution is actually just the standard term used for any action that creates a higher-resolution image from a low-res one. This can also be done by merging multiple pixel-shifted exposures, for example, so you might also see the term there.
We're looking forward to the coming years too! And we're especially looking forward to the improvements we have lined up for the next few months.