November 13, 2020
Pixelmator Team unveils Pixelmator Pro 2.0 with support for M1-powered Macs
This is Pixelmator Pro 2.0. Redesigned from the ground up, it’s more powerful than ever, more beautiful than ever, and it will be available in just six days, on Thursday, November 19th.
Support for M1-powered Macs
The Pixelmator Pro editing engine is powered by high-performance Metal code, so we can take advantage of the unified memory architecture of the M1 chip to bring you much speedier and much more responsive image editing. Machine learning tasks like ML Super Resolution are now up to a staggering 15 times faster on the new Macs. And, as a Universal app, Pixelmator Pro 2.0 runs natively on both M1 and Intel-based devices, so we’re completely ready for the new era of Mac.
Up to 15x faster ML Super Resolution
macOS Big Sur
Pixelmator Pro 2.0 is also fully compatible with macOS Big Sur with a new unified toolbar and a gorgeous new app icon.
All-New Design
Oh, and there’s one more thing – one more pretty huge new feature. That’s the all-new, more refined, and more modern design. Almost every tool, every menu, and every button has been updated to make the app more intuitive and more fun to use, making it easier for you to be creative. You can now customize the Pixelmator Pro interface, the list of tools, and the toolbar. We’ve also added a new Effects Browser, a new Presets Browser, over 200 beautiful new presets for the Color Adjustment, Effect, Style, Shape, and Gradient tools, and more.
In fact, this update is so big our full release notes didn’t even fit under the App Store’s 4,000 character limit. But you can read them in full on our Updates page!
You can get all the details about what’s coming on November 19th on our all-new Pixelmator Pro page. And make sure to sign up for our newsletter to be notified as soon as the update goes live.
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September 21, 2020
Pixelmator Photo featured in September Apple Event
Pixelmator Photo and our magical ML Super Resolution recently had the honor of being featured in the “Time Flies” Apple Event. It was incredibly rewarding seeing our hard work being recognized and is great motivation to keep making our apps better and better! Just in case you missed it, you can catch our 15 (OK, 30) seconds of glory below.
If you’d like to rewatch the entire event, you can catch it here. And if you’d like to check out ML Super Resolution and Pixelmator Photo 1.4, you can download it below.
September 17, 2020
Pixelmator Pro gets AppleScript support
Hey everyone! Big news from the Pixelmator Team, today we’re releasing a major update to Pixelmator Pro. Version 1.8, codenamed Lynx, is now here, bringing incredibly full-featured support for AppleScript.
AppleScript is the Apple-created scripting language that lets you directly control apps using instructions written in intuitive, English-like terms. And almost every part of Pixelmator Pro is now scriptable, so for pretty much anything you can do with the app, you can now script those same tasks. Say you have tens or even hundreds of images. You might need to export and optimize them, or change the color of certain objects in them, or maybe even add annotations, taking the text from a Numbers spreadsheet and automatically placing it in Pixelmator Pro. Thanks to AppleScript support, you can now do all that, plus a whole lot more.
In our quest to make AppleScript support as great and full-featured as possible, we collaborated with Sal Soghoian, the legendary user automation guru, who served at Apple for 20 years as the Product Manager of Automation Technologies, including AppleScript, Services, the Terminal, Apple Configurator and Automator, among others. We’re super glad to have had the opportunity to work with Sal. He was a big help with our scripting dictionary and we think the extra attention to detail really paid off!
Sal Soghoian
Sal told us: “AppleScript support in Pixelmator Pro is a game-changer, making this amazing app an essential component of everyone’s workflows. Whether you run scripts or write them, the depth and scope of the AppleScript automation in Pixelmator Pro makes magic happen. Kudos to the Pixelmator Team for their commitment and service to the Mac community.” We’ve also created a tutorial with a quick overview of AppleScript itself, some example scripts, and links to useful resources. Happy scripting!
The update is free for existing Pixelmator Pro users. And, for new users, our sale is still running, so you can get the app for 30% off its usual price.
Now, we’ll be getting back to working on Pixelmator Pro 2.0. Nothing to share yet, but development is going well and it’s looking like 2.0 will be an amazing release. Stay tuned!
July 16, 2020
Pixelmator Pro 1.7 major update adds text on a path (and more!)
We’ve been very busy over the last few months and we’re finally ready to share with you another great major update to Pixelmator Pro. Pixelmator Pro 1.7 Sequoia brings text on a path, canvas rotation, a new welcome screen, and version 3 of ML Super Resolution. Let’s dive right into each of those features!
Type text on a path, in a circle, or any other shape
This long-awaited and much-requested feature is now available in Pixelmator Pro! And we spent a long time refining every detail to make it the simplest and most intuitive tool of its kind.
In Pixelmator Pro 1.7 Sequoia, you’ll find three new tools grouped together with the regular type tool. There’s the Circular Type, Path Type, and the Freeform Type tools. You can use those to quickly and easily create text layers on paths. And you can also create your own shapes or paths and then click them with any of the type tools to add text on a path. Here are a few neat facts about our new type tools:
- We use the native macOS text system, so things like SVG fonts and emoji are fully supported!
- The – keyboard shortcut will now cycle through the currently selected type tool
- We’ve also added support for the standard Shift and Option modifier keys when resizing text boxes on paths
Freely rotate the image canvas to any angle
Canvas rotation might be one of the most important features for digital painters and illustrators and it’s something we’ve wanted to add for a long time. We also spent a long time making sure it’s easy to find, and almost as importantly, easy to reset!
To rotate the canvas, you can use the standard rotate Multi-Touch gesture. Or, if you’re using a graphics tablet or mouse, you can also press and hold the – keyboard shortcut and drag your canvas to rotate it. You’ll notice that, when the canvas is rotated, some very handy canvas rotation controls automatically appear, disappearing once the canvas rotation is set back to 0°.
A friendly new welcome screen
The first thing you see when you open an app makes a big impression. And we wanted to make it easier for new users to open and create images. That’s what this new welcome screen is all about! You’ll find quick ways to create an empty new document, open images from your Photos library, and browse images saved on your Mac.
If you’d rather see the native Open dialog, that hasn’t gone anywhere — simply turn off the “Show this window when Pixelmator Pro launches” option in the welcome screen.
Improvements to ML Super Resolution and RAW support
ML Super Resolution has been improved once more, this time, we’ve worked on the quality, added a progress bar, and added support for upscaling RAW photos while preserving all their RAW data!
The update is available today from the Mac App Store and is free to all existing Pixelmator Pro users. Visit the App Store to make sure you’re all up to date and let us know what you make of the additions and improvements!
June 18, 2020
Automation with AppleScript and Pixelmator Pro 1.8 public beta
What what what, Pixelmator Pro 1.8?! Oh yes, we’re feeling extra generous after the recent sneak peek at Pixelmator Pro 1.7 and we have some more great news about another great feature coming to Pixelmator Pro. That great feature is incredibly extensive support for AppleScript, the powerful and easy to use English-like scripting language for macOS.
Using AppleScript, you can control most of the tools and features in Pixelmator Pro and speed up repetitive tasks or even write scripts to create special effects. And because AppleScript is based on English, you don’t even need much programming experience to get started with it!
Here’s a quick example of something you can do with AppleScript.
Or, remember the tutorial for the Groovy text effect we released not too long ago? You can use AppleScript to automate that too! If you’d like to test this out, you can download both that sample script and the “Hello, world!” script below.
And to help us polish off AppleScript support, we’re going to need your help. So, starting today, we’re releasing the 1.8 update as a public beta. You can sign up for the beta by emailing us at [email protected]. And we’ll be waiting for your feedback at the same address!
March 30, 2020
Pixelmator Pro 1.6 Magenta now available
Fresh from the Pixelmator oven, we’ve just released Pixelmator Pro 1.6 Magenta, a major update you’re sure to love. 
The all-new color picker
Pixelmator Pro now has a brand new color picker, designed to be incredibly powerful and full-featured, yet amazingly easy to use.
We love the Colors window, so why did we decide to make our own color picker? Well, for an app like Pixelmator Pro, it falls a little short in a few small ways. And those small things often make a big difference.
We wanted to give you an easy way to pick colors using the classic hue, saturation, and brightness control, hex and and RGB color codes, and good old color swatches. And we wanted everything to be in one place so it’s all super easy to find. We also wanted to have a beautiful and informative eyedropper for when you’re picking colors from your image. And this is the result:
We’ve also added a dedicated Color Picker tool, where the eyedropper is always active so you can quickly pick a series of colors from an image. You can also customize how the eyedropper works everywhere else in Pixelmator Pro. For example, you can change its sample size (so it picks an average color, rather than an exact sample), change which color code is displayed, or turn off displaying color names. We hope you’re as excited about this new picker as we are!
An easier way to select multiple objects
This is another great improvement to make Pixelmator Pro even easier to use — you can now drag over multiple objects to select them. Hint: to make this easier to use with illustrations and other images, lock the background layer.
Identify and replace missing fonts
Whenever you open an image with fonts that you don’t have installed on your Mac, you’ll see a handy notification letting you know. And, using the Replace Fonts feature, you’ll be able to replace those missing fonts in a snap!
Performance improvements and other goodies
Along with all this, we’ve also included some performance improvements. The image overlay — which includes things like guides, selection outlines, layer handles, and others — has been rewritten to use Metal, bringing obvious speed improvements. What’s more, you can now press the – – keyboard shortcut to hide or show it!
We’ve also improved the speed of layer strokes, added the ability to apply inside and outside strokes to text layers, and made a range of improvements the the shape tools, making it easier to create illustrations and drawings. All in all, it’s a pretty awesome update, even if we do say so ourselves.
If you want to know every detail about the update, head down to our What’s New page, where you’ll find the release notes and more. Otherwise, visit the Mac App Store to make sure you’re all up to date. And don’t hesitate to let us know what you think!
February 11, 2020
Pixelmator Pro update improves ML Super Resolution and ML Denoise
Howdy! Pixelmator Pro 1.5.5 has just been released and it brings some significant improvements to ML Super Resolution and ML Denoise as well as two new Automator actions for those two features. Because seeing is believing, we thought we’d whip up a blog post with some examples to highlight the changes. Let’s start with ML Super Resolution.
ML Super Resolution
Even though we released it just about two months ago, we’ve made some pretty big improvements to ML Super Resolution in that time. In this update to it (a version 2.0, if you will) we’ve focused on four things in particular:
1. Removing compression blocks in heavily compressed images
2. Improving how portrait photos are upscaled
3. Preserving sharp edges and details in illustrations
4. Making the new, smarter algorithm faster and more efficient
Compression block removal
The previous algorithm already did a great job at removing the small compression artifacts
Compression Artifacts Compression artifacts often look like small dots and appear at edge areas — where contrasting colors meet in images. that usually appear around object edges in compressed JPEG images. But JPEGs, especially ones that have been compressed quite a lot, will also feature visible compression blocks
Compression Blocks JPEG compression blocks appear when the compression algorithm reduces subtly differently colored pixels (for example, in gradients) to one color. They’re most visible in photos that include the sky or other gradients.. This new version of ML Super Resolution does an even better job with the small artifacts and it takes care of the blocks!
Original Image
ML Super Resolution(Old Algorithm)
ML Super Resolution(New Algorithm)
ML Super Resolution (Old Algorithm)
ML Super Resolution (New Algorithm)
200%
We had actually been working on this since before the original release and wanted to include it when ML Super Resolution first came out. However, adding the block removal code would cause some pretty crazy blurring issues and, honestly, we couldn’t work out why. After some digging, it became clear that certain sizes of text in our training dataset were being interpreted as compression blocks! Once we addressed that, we were good to go.
Upscaling portrait photos
How ML Super Resolution upscales extremely pixelated faces is kind of magical. We made some improvements to make sure facial features are recreated in as natural a way as possible, even from a few pixels.
Original Image
ML Super Resolution
Improved quality around edges and small details
Another thing we focused on is edge areas — especially between colors that have different hues and levels of saturation but the same lightness. These can appear in any image but are especially common in illustrations. Edges such as this weren’t quite as sharp as we would have liked and there was some slight ringing that we really wanted to get rid of, too.
Original Image
ML Super Resolution(Old Algorithm)
ML Super Resolution(New Algorithm)
Smarter and more efficient
In order to make these improvements, we retrained our algorithm and slightly increased the size of the Core ML model included in Pixelmator Pro — from 5 MB to around 7 MB. Despite being a little bigger, this version of the model is actually faster than the previous one thanks to some additional optimizations. This is also a good place for a reminder that when you use any of our machine learning features, everything is processed securely on your device by a trained model integrated using Core ML.
Algorithm improvements
50%
more intelligent1
20%
more efficient2
1. Trainable neural network parameters (more is better): 1,692,928 (new algorithm) vs. 1,185,408 (old algorithm).
2. Floating point operations per pixel (fewer is better): 903,870 (new algorithm) vs. 1,128,062 (old algorithm).
ML Denoise
It’s probably fair to say that ML Denoise, our machine learning-powered noise removal feature, has been in a kind of beta stage until today. When we create any automatic feature, one of the main goals is for it to never make any image worse. With noise removal, that’s very difficult. So we took a conservative approach and tried to avoid this. This meant that the algorithm would sometimes do nothing at all, which is a pretty frustrating experience. What’s more, sometimes some loss of quality or sharpness is worth it because there are ways to recover it. With today’s update, ML Denoise is much better at removing heavy camera noise and is a little more confident in general.
ML Denoise in action
You can see ML Denoise in action with a few example images below. Your feedback about this feature over the last few months was a great help, by the way!
Original Image
ML Denoise
200%
Original Image
ML Denoise
200%
Original Image
ML Denoise
200%
Seeing as this is a machine learning-based algorithm and requires lots of processing power, for now, this will continue to be a one-click action. Adding a slider is potentially possible but getting real-time feedback and good performance requires us to do some more research. It is still in our plans for the future, though.
Automator actions for ML Denoise and ML Super Resolution
And to round off the update, we’ve added two new Automator actions: Increase Resolution of Images and Denoise Images, bringing the total number of Pixelmator Pro actions to 9.
To learn more about using Automator, check out our tutorial on the topic. Thanks to these new actions, doing awesome things like this will now be much faster and easier.
As usual, this update also includes a number of smaller improvements and fixes. It’s free to download for every existing Pixelmator Pro user and you’ve probably already received it automatically. But, just in case you haven’t, head down to the Mac App Store to make sure you’re all up to date.
We’ll be back soon with some more news about upcoming Pixelmator Pro updates — we’ve got some new tools in the works (not ML-based this time) and some great improvements to the color picking UX that we just cannot wait to share with you. Until next time!
December 17, 2019
All about the new ML Super Resolution feature in Pixelmator Pro
It’s no secret that we’re pretty big fans of machine learning and we love thinking of new and exciting ways to use it in Pixelmator Pro. Our latest ML-powered feature is called ML Super Resolution, released in today’s update, and it makes it possible to increase the resolution of images while keeping them stunningly sharp and detailed. Yes, zooming and enhancing images like they do in all those cheesy police dramas is now a reality!
Let’s see some examples
Before we get into the nitty-gritty technical stuff, let’s get right to the point and take a look at some examples of what ML Super Resolution can do. Until now, if you had opened up the Image menu and chosen Image Size, you would’ve found three image scaling algorithms — Bilinear, Lanczos (lan-tsosh, for anyone curious), and Nearest Neighbor, so we’ll compare our new algorithm to those three.
Note that the images below are zoomed in to 200% to make the changes easier to see, but you can zoom out to 100% by clicking the magnifying glass button.
Bilinear
Lanczos
Nearest Neighbor
ML Super Resolution
200%
Bilinear
Lanczos
Nearest Neighbor
ML Super Resolution
200%
Bilinear
Lanczos
Nearest Neighbor
ML Super Resolution
200%
Pretty incredible, right? Until now, if an image was too small to be used at its original resolution, either on the web or in print, there was no way to scale it up without introducing visible image defects like pixelation, blurriness, or ringing artifacts. Now, with ML Super Resolution, scaling up an image to three times its original resolution is no problem at all.
How does it all 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.
Traditional approaches
Traditional approaches use (relatively) simple mathematics to interpolate the values of pixels when scaling images.
Nearest Neighbor
When adding new pixels, the most basic algorithm, Nearest Neighbor, simply takes the color of the closest neighboring pixel. This results in the classic blocky appearance because the previously imperceptibly small pixels are now big enough to be seen.
Bilinear
The Bilinear algorithm is a little more advanced. A texture map of the image is created according to an algorithm and the values of the 4 closest texels (texture elements) are used when recreating each pixel in the new image. The goal of this approach is to make the transition between pixels much smoother. However, when upscaling quite significantly (or upscaling small images) this algorithm creates the familiar blurry appearance.
Lanczos
Lanczos is yet more advanced, using a complicated mathematical formula to interpolate (another word for predict) the value of any newly created pixels while keeping edges as sharp as possible. Its main disadvantage is that, in its attempts to retain sharpness, the algorithm can sometimes create ringing artifacts. So, ultimately, it’s useful in certain specialized situations, but not much more.
The machine learning way
So, how does the machine learning approach work? Put simply, it takes into account the actual content of every image, attempting to recognize edges, patterns, and textures, recreating detail based on our dataset and extensive training. When upscaling, it can make much better predictions because a red pixel next to a blue pixel can be a completely different type of texture or edge in different images even though, to the primitive approaches, they’re always the same.
The ML Super Resolution convolutional neural network
To create the ML Super Resolution feature, we used a convolutional neural network. This type of deep neural network reduces raster images and their complex inter-pixel dependencies into a form that is easier to process (i.e. requires less computation) without losing important features (edges, patterns, colors, textures, gradients, and so on). The ML Super Resolution network includes 29 convolutional layers which scan the image and create an over-100-channel-deep version of it that contains a range of identified features. This is then upscaled, post-processed and turned back into a raster image. Below is a simplified representation of the neural network.
First, the input image is passed through a high pass filter for basic edge detection. Then, the first convolutional layer reduces the size of these features and pools the data. In the Descriptor Fusion block, the image is scanned to find any JPEG compression blocks within it and this is fused with the other features identified so far.
The next convolutional layers and residual blocks are where the magic happens — these detect the features (edges, patterns, colors, textures, gradients, and so on) in the image, building them up into a complex representation that is over 100 channels deep. In a convolutional neural network, more layers mean better accuracy but with a large enough number of layers, a network becomes near-impossible to train. Residual blocks are designed to increase the complexity and accuracy of networks without making them impossible to train.
Finally, all the features identified by the neural network are enlarged in the Enlarge block. After this, the two residual blocks and the final convolutional layer post-process the data and turn the features back into an image. It’s also important to note that all this happens on-device and the entire trained machine learning model is included inside the Pixelmator Pro app package.
Dealing with noise and artifacts
Small images often contain compression artifacts and noise. If we want our upscaled images to be usable, artifacts and noise shouldn’t be scaled up together with the actual contents of the image. In fact, if possible, they should be removed altogether. And, as mentioned above, ML Super Resolution is designed to do just that, borrowing some of the technologies we developed for ML Denoise to remove both camera noise and JPEG compression artifacts. By the way, in this update, ML Denoise has also been improved, bringing noise removal that is between 2 to 4 times better than before.
Nearest Neighbor
ML Super Resolution
200%
Processing power required
Naturally, the machine learning way requires a lot more processing power than the primitive approaches — between 8 to 62 thousand times more, in fact.
* When upscaling 1 pixel by 300%, creating 9 pixels.
Making this available in an app like Pixelmator Pro has only become possible in the last couple of years — even on Mac computers from 5 or so years ago, ML Super Resolution can take minutes to process a single image due to slower performance and less available memory. On the latest hardware, however, images are processing in a few seconds, and even faster on iMac Pro, Mac Pro, or any Mac with multiple GPUs thanks to our use of Core ML 3 and its multi-GPU support. For the same reasons, the performance of ML Super Resolution is also significantly improved when using an eGPU.
1. For this test, a 300,000 pixel image was upscaled to three times its original size.
2. Tested using an AMD Radeon RX 5700 XT eGPU.
3. External GPUs require a Thunderbolt 3-equipped Mac.
Using the 2012 MacBook Pro as a baseline, the latest devices are up to 200x faster!
We’re incredibly excited about ML Super Resolution and we honestly hope you’re going to love it too. If you’d like to, you can download all the images in this blog post using the link below and test everything in today’s update out for yourself.
Pixelmator Pro 1.5.4 is now available from the Mac App Store, so head on down there and make sure you’re up to date. The trial version has also been updated so if you don’t yet have a copy, you’re welcome to try it out. That’s it for now, but we hope to surprise you with one more cool new feature before the year is up — stay tuned!
Note
ML Super Resolution requires macOS Mojave or later.
October 25, 2019
CMYK proofing comes to Pixelmator Pro
Good news, everyone! We’ve just shipped a smaller Pixelmator Pro update with a big new feature called Soft Proof Colors. This one’s for all you print designers out there.
CMYK Proofing
Soft proofing lets you see what an image would look like when reproduced on a different output device — for example on a different monitor or when printed. And for most Pixelmator Pro users, the most important thing is being able to soft proof images with CMYK color profiles when working on designs that will be printed. As Pixelmator Pro already had the ability to convert to CMYK when exporting, with soft proofing, it becomes an even more powerful image editor for those of you creating designs for print.
A few days ago, we also started the Pixelmator Pro Upgrade Sale to encourage any original Pixelmator users to give Pixelmator Pro a chance and it’s been a great couple of days in many different ways! More on that later, but the sale ends on Tuesday, October 29th, so you have a few more days to take advantage of it — it really is a fantastic offer.
While we get back to working on Pixelmator Pro 2.0 (oh yes, we’ve already started and it’s going to be an amazing free upgrade), feel free to check out the full release notes for this update by visiting our What’s New page or just go ahead and view Pixelmator Pro 1.5.1 on the Mac App Store.
October 10, 2019
Pixelmator Pro 1.5 Avalon now available
Pixelmator Pro just got an awesome major update! Version 1.5 (codenamed Avalon) brings full support for macOS Catalina, the upcoming Mac Pro and Pro Display XDR, introduces intelligent, machine-learning powered noise removal, big performance improvements, and a whole lot more. Here’s a quick rundown of what we’ve added.
macOS Catalina Support
Pixelmator Pro is now fully compatible with macOS Catalina, including support for Sidecar and Apple Pencil, which means you can extend your desktop workspace using your iPad as a second Mac display! And with Apple Pencil support, you can paint, sketch, create graphic designs, and retouch your photos with pressure-sensitivity, acceleration, and tilt support as well as support for the double-tap gesture. Plus, as Pixelmator Pro fully supports Touch Bar, handy controls appear at the bottom of your iPad when using Sidecar — even if your Mac doesn’t have a Touch Bar.
Mac Pro
Thanks to its Metal-based architecture and GPU-powered editing engine, Pixelmator Pro absolutely flies on the upcoming Mac Pro. We’ve been able to optimize multi-GPU support so that with multiple graphics processors in Mac Pro, you’ll see big performance boosts in Pixelmator Pro. And performance increases even more with each additional GPU. For example, Pixelmator Pro applies the new Core ML-powered ML Denoise up to 2.5x faster and effects up to 2x faster on Mac Pro with 2 GPUs compared to iMac Pro.
EDR Mode
We’ve also added support for the upcoming Pro Display XDR. The display’s true 10-bit color depth and P3 wide color gamut are natively supported in Pixelmator Pro. And the new Extended Dynamic Range Mode lets you display clipped details in RAW photos. To do this, we use the display’s 1600-nit peak brightness to bring out details in the highlights without compressing the dynamic range of the rest of the photo, bringing a never-before-possible RAW editing and viewing experience.
ML Denoise
ML Denoise is an amazing machine learning-powered noise removal tool. Integrated via Core ML, ML Denoise effortlessly removes luminance and color noise created by cameras in low-light photos. What’s more, it can even reduce artifacts caused by image compression algorithms, improving image quality while preserving important details!
Performance Improvements
Pixelmator Pro now has an end-to-end Metal pipeline for rendering and editing and a new asynchronous zoom engine, which brings some big performance improvements. Zooming and scrolling is now at least 10x faster and always responsive, effects are up to 2.7x faster, and painting is up to 2.4x faster!
SF Symbols
SF Symbols, the new set of over 1,500 configurable vector icons designed by Apple, is fully supported in Pixelmator Pro. So you can easily open SF Symbols templates, customize them to create your own symbols, and even drag and drop symbols right into existing documents!
This fantastic fifth major update to Pixelmator Pro is free for all existing users, so download it, try it, and let us know how we did. As you might guess, we’re already working on some more really incredible additions to Pixelmator Pro and we can’t wait to share them with you. Until next time!