Online Wall Art Posters With Scandinavian Impression & Design

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 An absolute advertising favourite, Leaflets and Flyers are also great for creating Art Prints on a small budget. One of the main advantages to Leaflet printing your designs is volume. As one of our most affordable prints, they’re ideal for printing designs both quickly and in bulk.

 Not everyone is looking for Poster-sized art, so Leaflets can make perfect pocket-sized Art Prints. You’ve also got a much broader range of papers to choose from compared to Poster printing or traditional Art Printing. Soft Silk? Fine-lined Nettuno? Shimmering Pearl Oyster? The choice is yours!

 Throughout my artistic career, I had to prepare my images for printing probably thousands of times. Preparing photographs before sending them to magazines, for a gallery show, or for a fine-art print sale. But in photography, you rarely face the necessity to upscale an image.

 Or to upscale an image that has indistinct details and a lot of... uncertain spots. :) And most definitely, it is the rarest event to upscale a 1024x1024 pixel image for high-quality printing.

 Yet here we are, with Midjourney's beautiful but elusive results that, in V4, can only go as big as 1024x1536 pixels. What is the best way to upscale them and prepare them for printing?

 There are many ways to upscale an image, and it's not this study's goal to cover all of them. I will, however, try some of the most popular options, both free and paid.

 After considering each option's speed, quality, and user experience, I settled on using Gigapixel AI. Despite a hefty 99,99$ price tag, my time and mental health seemed more valuable. ¯\_(ツ)_/¯

 Someone with a stronger will, more dedication, time, and a technical mindset could squeeze better results out of some of the methods in this study. For instance, selecting a correct Upscaler model can drastically affect the upscaling outcome. But going through lists of literally hundreds of them, let alone downloading, installing, and waiting between ten to ninety minutes to see each result—that's a task for a dedicated research institute. :) Instead, I went with the most common models and (mostly) default values in most cases.

 All the initial files were sharpened in Lightroom before sending them to upscalers. After LR export (HQ PNG), each file was ~9 Mb and 1024×1536px.

 For printing, keeping files as PNG isn't necessary—JPEG with lowest compression works perfectly fine. But I kept the initial file format to make the experiments more consistent.

 I ran all tests (except for Google Collab that works in the cloud) on 2013 Mac Pro with the following configuration:

 My upscaler of choice for many good reasons—Gigapixel AI—is an all-in-one AI-based upscaler with a buy-once-own-forever license. When you launch the app, it offers to download the most recent upscaler models. Afterward, it will regularly download updates and occasionally add new models.

 Gigapixel AI offers a minimalist and clean interface. Every control is in its place, and the overall experience is straightforward and intuitive.

 You drag and drop your images to Gigapixel AI's window. They appear as a list with parameters for each position (that can be changed individually or for all images simultaneously).

 A handy Auto mode lets Gigapixel AI decide which model best applies to your images and with what parameters. Or you can set everything manually. That includes Suppress noise, Remove blur, Fix compression, Face Recovery, and Gamma Correction.

 To help you with these choices, the central part of the screen is occupied by a before-after comparison preview. You can zoom in and out and drag the loupe across your image. The preview only runs the selected upscaler model on the zoomed part of the image, so it works faster than complete upscale—to show how this particular fragment will look after you launch the upscaler.

 In this comparison, Gigapixel AI upscales are put against original images resized to have the same resolution. In all the following tests, I will be comparing the results from the upscaler in question to those of Gigapixel AI.

 Also, I won't be posting all results for each upscaler. You can download all fragments via the link at the end of this study.

 Gigapixel offers several built-in AI models (see specs below). However, I found the Standard mode the most useful, delivering the best results in each benchmark position. Here is a comparison of Lines vs Art & CG vs Standard models with Line Art test.

Online Wall Art

 PNG file size: at ~130Mb per image, Gigapixel AI is top of the list at this, too. However, with the use of a fantastic free tool ImageOptim↗︎ I could reduce the file size to 40Mb with 90% lossy optimization and to around 25Mb with 80%.

 Gigapixel AI is capable of upscaling to up to 6 times the original size—and you can set it to an even higher multiplier, but after that, "the quality is not guaranteed."

 After trying alternatives, my choice was clear: I was ready to pay for a clean design, intuitive user experience, almost no waiting time, and overall convenience.

 Most importantly: Gigapixel AI didn't make me think. I don't want to lose time and energy struggling with tons of settings, lines of code, and unexpected errors. I want the infrastructural software to

 Super Zoom is a neural filter in Adobe Photoshop that uses artificial intelligence to—as its name suggests—increase the resolution of an image. The feature uses deep learning to analyze the details of an image and generate new pixels for smooth upscaling.

 SuperZoom has an additional option called "Enhance face details." Let's check what it does: we have a benchmark exactly for that.

 A decent enhancement, especially in the hair! Let's see how Super Zoom with Face enhancement compares to Gigapixel AI with Standard model.

 A decent enhancement, especially in the hair! Let's see how Super Zoom with Face enhancement compares to Gigapixel AI with Standard model.

 It's integrated into Adobe Photoshop, so if you already have a subscription that includes PS, it comes as a bundle. And not just the Super Zoom, but other neural filters, too.

 There is a trick to making a low-resolution image appear better. You need to first upscale it—and even a medium-quality upscaler will do—and then downscale it back to its original size. For this and many other situations when you don't intend to print your upscale or won't need a high-resolution file with fine details—Photoshop Super Zoom is a good choice. Especially, if you are already a user of Adobe infrastructure.

 Google Colab is a free online platform that allows users to write and run code in a web browser. It also provides access to powerful computing resources, such as GPUs, for running complex machine-learning models. Numerous colabs can upscale images (and not only that).

 For this test, I chose SuperRes Diffusion—batch upscaling and super-resolution colab based on Latent-Diffusion. If you decide to try it yourself, I recommend this short and comprehensive article on how to use it.

 Despite some tech-savviness, setting up the SuperRes Diffusion colab was a bit of a struggle, and using it was overall a confusing experience. I encountered numerous glitches along the way. It stopped in the middle of a script's execution or showed errors, after some of which I had to restart the whole thing.

 To run SuperRes or similar colabs, you must be a Google Drive user AND grant a colab—someone else's program—access to your Drive's entire content: with modification rights. I am a trusting (or just reckless ;)) person, but for many, this can be a privacy concern.

 I'll be honest, the colab world is very new to me, and my first user experience with it wasn't smooth. Even though using SuperRes turned out to be easier than it seemed at the beginning, the environment doesn't make a non-software engineer feel comfortable. And occasional errors that explain nothing (e.g., "Cannot read properties of undefined (reading 'next'") don't help, too.

 Then there is also a GPU time limit for free users that is difficult to control and runs out too fast.

 In the end, I am sure colabs are powerful and versatile tools for those advanced enough to be able to use them. But in the case of SuperRes Diffusion, its speed and quality of its results couldn't outweigh its disadvantages.

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