ESRGAN is developed by

Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, Chen Change Loy

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I did many tests and those are my results and experiences.

You can download the models at the bottom of the page!





Recommended Hardware: Video Card with 8GB and higher!





Tested on 1080Ti GTX 11GB

Tested on 1070 GTX 8GB

(approx. 2 minutes per 100 interpolations)







Goal: I tried to upscale low-res pixel art images to the highest quality without retouching. I trained many new models to achieve the results.





Conclusion: More interpolation is used, closer the results are to your trained images. Less interpolation means more regular PSNR, which makes it smoother and better for low-res images. More interpolation means it will get closer to images you provided for training. (it should, at least)





Zoom-in to see full resolution animated GIF images

ESRGAN calculations automatically turns off at 500 000 interpolations.





HOW to prepare images for training?





1. Find high quality images that you wanna use for training.

2. Crop them by using python script: ...codes\scripts\extract_subimgs_single.py ( change the input_folder to where your images are, set crop_sz and step to 128.) Run it.

3. Downscale cropped images to 4x of the size, (128/32 = 8GB VRAM, 256/64 = 20GB VRAM)

(important is the method of downscaling NEAREST NEIGHBOUR

if you use any other like; Bicubic, B-spline, Mitchell...you will fail!)









RESULTS (animated gifs):



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DONALD DUCK COMIC BOOK

5000 - 110 000 interpolation

HR - 256pixels / LR - 64pixels

(3 days of calculations)

110 Images total - Bicubic



Training images examples:



Indy3

(full size 2560x512 up-scaled)



Monkey Island 1

(full size 1280x800 up-scaled)



Monkey Island 2

(full size 1280x576 up-scaled)





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CARTOON PAINTED

5000 - 80 000 - 400 000 interpolation

HR - 128pixels / LR - 32pixels

(7 days of calculations)

4669 images total - Nearest





Training images examples:



Results:



Monkey Island 1









Thimbleweed Park

(full size 1712x960 up-scaled)









Monkey Island 1-2

(full size 1888x576 up-scaled)







Sam & Max

(full size 1280x800 up-scaled)









IJ Last Crusade & IJ Fate of Atlantis

(full size 1500x380 up-scaled)











Beneath a steel Sky & Day of the Tentacle

(full size 1280x800 up-scaled)

DISNEY MOVIE PINOCCHIO

5000 - 35 000 interpolation

HR - 128pixels / LR - 32pixels

(6 hours of calculations)

2409 Images total - Nearest





Training images examples:







Results:



Monkey Island 1 (full size 1280x576 up-scaled)



IJ Fate of Atlantis

(full size 1280x800 up-scaled)



Sam & Max

(full size 1280x800 up-scaled)





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DISNEY MOVIE HERCULES

5000 - 40 000 interpolation

HR - 128pixels / LR - 32pixels

(1 days of calculations)

5557 Images total - Nearest



Training images examples:





Adventure Games (full size 1K 2K 3K up-scaled)







____________________________________________________________________ DISNEY MOVIE LION KING 5000 - 60 000 interpolation HR - 128pixels / LR - 32pixels (2 days of calculations)

20528 Images total - Nearest



Training images examples:



Results:

IJ Fate of Atlantis (full size 1280x576 up-scaled)



Loom

(full size 1920x576 up-scaled)



Monkey Island 1

(full size 1280x800 up-scaled)







Monkey Island 2 (full size 1500x342 up-scaled)





____________________________________________________________________ MANGA109 my own recal 5000 - 250 000 interpolation HR - 128pixels / LR - 32pixels (5 days of calculations)

6852 Images total - Nearest



Training images examples:



Results:

Adventure Games (full size 1K 2K 3K up-scaled)



















____________________________________________________________________ MANGA109 kingdomakrillic (interp? no information provided) HR - 128pixels / LR - 32pixels (6 hours with 1050 Ti GTX ) - Nearest Neighbour



Training images examples:







Results:





Adventure Games

(full size 1K 2K 3K up-scaled)





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RRDB PSNR VS RRDB ESRGAN

Blending RRDB_PSNR with RRDB_ESRGAN models with alpha 0.1-1.0





Adventure Games (full size 1280x800 up-scaled)













Developers links and project downloads:



HOW TO: https://kingdomakrillic.tumblr.com/post/181294654011/manga109-model-attempt-for-illustrations

BASIC SRGAN GIT: https://github.com/xinntao/BasicSR

HOW TO TRAIN NEW MODELS: https://www.reddit.com/r/GameUpscale/comments/ag4ax3/instructions_for_training_esrgan_in_windows_i/