Heyas, big fan of your posts. I use mostly use ESRGAN via Cupscale for upscaling, and StyleTransfer/StableDiffusion WebGUI for the repaints. Manual fixes are done in Photoshop.
A variety of ESRGAN models are used, the most usual ones are:
1) Fatality_mkII
2) NMKD-UltraYandere_300k
3) BigFArt_Detail_300000_G
4) BigFace_v3
5) ArtStation1337_bloom
6) SmolFace
7) ArtClarity / ReFocus_v3
8) DoubleDetoon interpolated with ReDetail_v2
9) realesrgan-x4minus / BSRGAN
10) GainRESV3 whenever I need to use a non-pixelart model
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ESRGAN models are not trained the same, each have a specific objective they wish to achieve. In terms of models for upscaling pixel art, I gravitate towards the paint-centric models compared to anime, as they trade off line sharpness in favour of blending and more organic shapes. This is a small showcase how differently each model attempts to interpret the base image, including what happens when non-pixelart models upscale pixel-art, as well as what happens pixel art is anti-aliased first before feeding into a non-pixelart model. Finally, is the realesrgan model commonly used by people that post in reddit & YouTube to show ESRGAN upscaling.
Since I’ve gotten requests from reddit as well as on this blog itself, I’ve decided to share my workflow on how I upscale most of the images featured here. Roughly, the main program I use to upscale is ESRGAN, an open-source Python script that uses trained neural network models to process images. I also use IEU Winforms to automate most of the upscaling work (though a lot of people have migrated to Cupscale). Finally, Photoshop is the image editor I use to composite the upscale results.
So let’s get to steps involved. First and foremost is to source the image. I usually either grab them myself from whatever games I have, or get a copy from other sites such as Hardcore Gaming 101, Mobygames etc. So here’s today’s sample image sourced from Retronaissance: The Blog! is a shot from Capcom’s arcade obscurity Red Earth:
I always try to find snapshots stored in pristine pixel art form instead of resized jpeg pics whenever possible. This is because some models are very sensitive to noise and distortion.
Now firing up IEU Winforms, and you can see I have a bunch that are my go-to models when I’m upscaling specifically for No More Pixels. Since this blog is about transforming those shots into supposedly artsy-fartsy canvases, I try to avoid models that are catered to realistic images. Most of these models are obtainable via the Upscale Wiki.
After selecting a bunch of models to filter the image through, I execute the upscaling and get back the results from each model. You may now be asking why do I need that many different upscales in the first place? Well sadly, there is currently no ‘super’ model right now that can produce the best image for all occasions. Some models are good at doing certain things but bad at others. I’ll share some examples:
Normally I start with using Unholy FArt as the base image, and usually followed in conjunction with Fatality Mk II. You can see how different each model interprets various parts of the image. Fatality Faces has the best facial reconstruction, while ArtStation1337 Bloom has the best debanding capability out of all of them (observe Tessa’s fabulous balloon pants). So which model should we choose? The answer is: as many as you like! I take various parts here and there that will be combined together later.
Now let’s observe the horney T-Rex-kun. While organic, the dino has a more geometric feature, so the colour-blending should be less of a priority while having sharper features is better. You can see BigFArt Detail trying to generate some details for the background. BigFace which was trained on an anime ladies dataset made the eye into a T-Rex-chan. FArtFace has the best result here, keeping the lines and features sharp.
The last example deals with geometric non-organic shapes like this pillar. Models that do blending are an obvious no-no. Fatality Mk II looks good, but perhaps too sharp for a background element, while BigFArt Detail is adding in noise. This leaves NMKD UltraYandere as being accurate to the original shape while not being overtly sharp.
Now let’s get compositing. My personal routine is to start with UnholyFArt as base and immediately followed by Fatality MkII as a Darken layer. This gives me Fatality’s sharpness while removing the halo effects it usually produces.
Since I decided to use FArtFace on T-Rex-kun, using the Quick Selection tool helps to quickly set up a mask just for the dino.
Moving on to Tessa (and her cat), I’ll start with BigFArt Detail as base. This keeps detailings sharp.
Then masking in the blending from ArtStation1337 Bloom and transferring the details from Fatality Faces onto Tessa’s mug like one would with those transfer stickers from your childhood.
Now restoring NMKD UltraYandere to the pillars, and BigFArt Detail at 50% opacity to other parts of the background. CleanPixels for the UI and Deviance for some parts of Tessa’s portrait at the top left.
Finally, you might notice that there’s some bits of chunky pixel in the water below T-Rex-kun, which means it’d maintain itself as its angular shape for all models... save one. I originally trained BigFace to dream up hair details whenever possible, but it turned out to be a bad idea because it failed to discern what is hair and what is not. Here the bug becomes a feature, because it’s the only model deblocking that water. Beggars can’t be choosers.
The final composition at last. Normally I’ll add ArtStation1337 Bloom at the top as a soft light layer to increase the colour contrast of the composition. Before exporting, the proper aspect ratio of the original shot must be determined. Here Capcom is using tall pixels for their CPS3 games. So that 384 x 224 internal resolution is actually displayed on a standard CRT arcade monitor ratio.
Researching a bit shows it’s a bit more towards 98:72 than 4:3 standard. That means my final image dimension should be 1220 x 896 pixels. Resize while preserving details, export to web and.... done.
Click here for the full-size image.
Hope this demystifies the whole process, and perhaps spark some interest for anyone else to do upscales of their own. Cheerios!
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