Become a MacRumors Supporter for $50/year with no ads, ability to filter front page stories, and private forums.

MacRumors

macrumors bot
Original poster
Apr 12, 2001
69,015
40,049


Popular image editor app Pixelmator Pro has released version 2.0 ahead of schedule, bringing an all-new design for macOS Big Sur and native support for Macs powered by Apple's new M1 chip.

pixelmator-pro-2.jpg

The new design features a simplified Effects Browser that makes it easier to find and apply effects, and new compact layouts for the sidebars and presets.

There's also a new Workspaces feature that lets users customize the look of Pixelmator, with presets optimized for photo editing, design, illustration, and painting.

With native support for Apple's new M1-powered Macs, Pixelmator Pro 2.0 takes advantage of the chip's 16-core Neural Engine for accelerated machine learning. This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

The editing engine is powered by Metal, which makes it easy for the app to take full advantage of the unified memory architecture in Apple's system-on-a-chip. There's also a new app icon that aligns with Apple's docked apps, and a new unified toolbar with switches and menus that look native to the macOS 11 Big Sur aesthetic.



Pixelmator 2.0 is a Universal app, so it runs natively on both M1 and Intel-based Macs. The image editing app is a free upgrade for existing Pixelmator Pro users, otherwise it costs $39.99 and can be downloaded directly from the Mac App Store.

Article Link: Pixelmator Pro 2.0 Launches With All-New Design and Native Apple M1 Support
 
Last edited:
  • Like
Reactions: hagjohn
>This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.
 
  • Like
Reactions: -BigMac-
Cannot praise this app enough - good UI, good light-alternative to Photoshop. I hate subscription apps and this is a steal for $40 for a hobbyist.

Waiting for a iMac M1X to run Pixelmator on...
 
  • Like
Reactions: JDGwf
>This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.

It is a wee bit like how you can delete a object in Photoshop. It does not always work but has a good guess and a library of what it 'expects' to find.
 
>This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.
Lmao exactly. Its like the james bond movies “enhance, enhance” pulling detail out of thin air haha
 
  • Like
Reactions: BornAgainMac
>This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.

I think they us Machine-Learning to extrapolate edge-detail to make it less jagged-fuzzy. It's not like "Enhance" and the picture is magically clearer, but it makes it better.
 
>This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.
Machine Learning. I guess thru the power of guessing what pixels they should add
 
I think they us Machine-Learning to extrapolate edge-detail to make it less jagged-fuzzy. It's not like "Enhance" and the picture is magically clearer, but it makes it better.
Machine Learning. I guess thru the power of guessing what pixels they should add

Topaz Labs’ Gigapixel AI software does something similar. So it’s definitely possible.
 
  • Like
Reactions: aberamati
I wish I could like Pixelmator. I worked in Photoshop for 20 years, and most other image editors make me feel cack-handed as their tools operate differently. Pixelmator, Acorn and Affinity all confuse me.

I know what you mean, decades of Photoshop muscle memory are difficult to change. I have tried Pixelmator in the past and it is OK, i might try the Pro version out some time soon.
 
How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.

They use a lot of high resolution images with all kind of content and train a system to recognize resemblances. It can then try to "guess" what the "original" high-res image might have been. Of course you will not get the real original image, but it will produce something that looks very realistic.
 
  • Like
Reactions: DaveN and aberamati
>This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.

I think they us Machine-Learning to extrapolate edge-detail to make it less jagged-fuzzy. It's not like "Enhance" and the picture is magically clearer, but it makes it better.

Here’s a quote from their blog on how they trained it to work:

As computers get ever more powerful, the additional power opens up new possibilities. One of the uses of machine learning, on a very fundamental level, is to make predictions about things. In this case, we gathered a set of images, scaled them down, and then ‘taught’ the algorithm to go from the scaled-down version to the original resolution, high-quality image, predicting the values of each new pixel. The algorithm can’t recreate detail that is too small to be visible but it can make amazing predictions about edges, shapes, contours, and patterns that traditional algorithms simply cannot.

Blog post is here:
 
>This allows for features like Super Resolution, which intelligently increases the resolution of images while preserving details, to work up to 15x faster.

How on earth does this work?
How can you increase the size of an image, but 'preserve' details? Won't everything just be scaled up? You can't introduce resolution where there's no more data.
Yeah, you can. That is what I use this app to do.
 
  • Like
Reactions: mcdawg
Register on MacRumors! This sidebar will go away, and you'll see fewer ads.