To upscale manga including halftones, instead of trying to smooth them out.

Pretrained model: MangaScaleV2(not released)

MangaScaleV3

Purpose: pre-workout to speed up your workouts

While experimenting with color models for cugan, I just ran into problems that the official models are not imported correctly and have additional processing in addition to resizing. As a result, for my project I trained 2 x cugans for neosr; only resizing losses were applied to the dataset `(“lanczos”, “bicubic”, “bilenear”, “HAMMING”, “NEAREST”)`

wtp manga cover pretrained

Purpose: remove paper texture and screentone from independent manga scans

Well, I don’t even know how to describe it, a small breakthrough in my war with self-scans, I’m still not very happy with it, but maybe the lump will come in handy one day https://discord.com/channels/547949405949657098/547949806761410560/1204387665798103050

DWTP DP dat2 beta

Purpose: remove paper texture and screentone from independent manga scans

This is my first model for this, it can be said to remove poorly https://discord.com/channels/547949405949657098/1159598245417332796/1185562840304721921

DWTP DS dat2 v1

I've been experimenting a lot since the last descripton was released to save even more detail, and to get rid of some of the beginner's soreness. All three models are not yet perfect and I will develop them, but what is the essence of the three models, the models on omni is just a division of VL eats less large screenton, VH is just a re-trained model on a modified dataset and with VL as a prevoritolnoy shadowing that it would demolish more screenton, while not going to demolish all the textures and very large screenton. Esrgan model was trained on a dataset VH for use in the colab, it works in some places worse than Omni, so could not fight with overlapping screenton.

DWTP_descreenton_H_esrgan

DWTP_descreenton_VH4

DWTP_descreenton_VL4

Purpose: manga screentone removal

I haven’t shared models for a long time, I think one of these days I’ll upload a dat version and a less accurate esrgan. This version of the model was meant to be an attempt to get as much detail out of the scans as possible while removing the screentone, so some things had to be sacrificed, but overall it is better than all my previous models combined in terms of accuracy and tone.

[**examples**](https://slow.pics/c/zbOGXoDv)
[colab which contains the rest of my models](https://colab.research.google.com/drive/1w8fgsmh9fcHDtpQnYy77aKgpHEWlKpj-?usp=sharing#scrollTo=aYbqM1pWkPTT)
||In general, this is a collab for convenient scaling of manga in the ru segment of translators and there are other people’s models there, if I suddenly added someone else’s model that has a license, please let me know, I’ll correct it||

DWTP ds esrgan 5

Cartoons/pixel art/other non-realistic stuff with dithering

FSDedither Manga

Manga-style images with or without dithering - cartoons, maybe pixel art, etc

FSMangaV2

Category: Art/Pixel Art
Purpose: Pixel Art/Sprites

Upscales medium resolution Sprites, dithered or undithered, can also upscale manga/anime and gameboy camera images.

Fatality 1

Fatality Comix

Fatality Comix MK3

Purpose: Illustrations, digital art, manga covers

Model for color images including manga covers and color illustrations, digital art, visual novel art, artbooks, and more. The DAT2 version is the highest quality version but also the slowest. See the ESRGAN version for faster performance. 

https://slow.pics/c/GfArurPG

IllustrationJaNai_V1_DAT2

Purpose: Illustrations, digital art, manga covers

Model for color images including manga covers and color illustrations, digital art, visual novel art, artbooks, and more. The ESRGAN version is high quality with balanced performance. See the DAT2 version for maximum quality. 

https://slow.pics/c/GfArurPG

IllustrationJaNai_V1_ESRGAN

Manga109Attempt

4x photo upscaler on the SSDIR_Sharp dataset, trained with otf, using the same settings as Real_HAT_GAN.  
These otf values are very high in my opinion. This was an experiment if I used the same settings as Real_HAT_GAN (therefore the name).   
This model will denoise very strongly and smooth out a lot (so a lot of details will be lost. But maybe this effect might be beneficial to someone)

4xReal_SSDIR_DAT_GAN

I just decided to finish off the previous one, made the manga design more clear and corrected the deviation in color temperature by adding a more diverse set of colors

WTP UDS Esrgan

This model is based on a private model by @eula 5600x 3070 named 4x_eula_anifilm_v1_225k. He sent me a copy of the model, and I decided to train a compact model based on it with his permission. This model seems to fix the majority of the issues the original model had while being far faster, it's just a tiny bit softer in some images.

The dataset consists of Dragon Ball movies converted to YUV24 with @sgdisk --zap-all /dev/sda's help to reduce artifacts, then upscaled with ArtClarity and eula_anifilm. LRs are the original frames right from DVD. As a result, this model corrects some color space issues. The 2x model's HRs were downscaled by 50% with Lanczos.

The 2x and 4x models are pretty close in output despite being trained separately. The 2x model is a bit softer overall.

The models in the Real-ESRGAN Compatible folder are the original output from Real-ESRGANs training code for compatibility reasons.

Anifilm Compact (4x)

Anime super-resolution, with real degradation.

animerd v1

Purpose: Grayscale pencil/sketch style art with paper textures (Made in Abyss specific)

Old model trained for pencil sketch style art, good at restoring the paper and pencil and other textures , specifically the Made in Abyss manga, but should work for art with a similar style.

Comparison:
https://slow.pics/c/D0MuvwLY

eula digimanga MiA 65k

Black and white digital manga with halftones.

eula digimanga bw v1

Vast improvement over v1 in low frequency detail; moiré and artifacting reduced significantly and less random noise from JPEG artefacts in the input. Also now only works on 1 channel images, so it runs slightly faster on average and resulting images are much smaller but it might not work on some ESRGAN implementations, I personally recommend using chaiNNer. v1 may still be better in some edge cases.

There's also a supplementary 1x model that denoises very low quality LRs and smooths halftones so the image works better with the 4x model. Only trained it to help build the dataset and it's useless for already decent-ish LRs but may help you in some situations.

eula digimanga bw v2 nc1

In general, what was the point? The project was conceived for a manga scale with a screentone using the method of superimposing a new screentone, but for this the old screentone must be removed, but this is not all the same important contour. With the screentone overlay method, the contour should be as close to 1 bit as possible, otherwise we will see full contours, wavy contours, etc. This is the whole idealogy of this model.

wtp_descreentone

Purpose: pre-workout to speed up your workouts

I see that many people are trying manga scale models on the Omni, and to speed up the process I decided to do preliminary training, the only loss is the resize: (“lanczos”, “bicubic”, “bilenear”, “HAMMING”)

Original link: https://drive.google.com/drive/folders/1ln1ZneTvqPbvi8nsJwzjMoYSDQ_DcHBS?usp=sharing

Architecture	ESRGAN
Scale	4x
Size	64nf23nb
Color Mode	RGB
License	CC-BY-4.0 Private use Commercial use Distribution Modifications Credit required State Changes No Liability & Warranty Disclaimer
Date	2018-12-21

Manga109Attempt

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