Nice to release a model again! This one is intended for realistic imagery, and works especially well on faces, hair, and nature shots. It should only be used on somewhat clear shots, without a lot of grain. I trained this model on SPAN, which as of the time of release, you'll need chaiNNer-nightly for. I aimed for a softer, more natural look for this model with as few artifacts as possible.

In addition to the Normal model, I've included a "soft" model. The Soft model is... softer. Basically it was an earlier version of the model with a more limited dataset. It produces more natural output on games or rendered content, but suffers a bit more with realistic stuff.

Note: In shots with DOF (depth of field) or bokeh, unfortunately there will be artifacts. 

Compatibility: You'll have to use the latest chaiNNer-nightly to use this model

ClearRealityV1

DAT descreenton model, designed to reduce discrepancies on tiles due to too much loss of the first version, while getting rid of the removal of paper texture https://discord.com/channels/547949405949657098/944307589284495410/1192058535257854042

DWTP DS dat2 v3

Purpose: remove screentone

in some places an improved version 4x_DWTP_DS_dat2_v3 one of my friends likes it less than 3 and another more so here is v3_2

[raw](https://media.discordapp.net/attachments/771403403372527656/1201288063666634842/raw.png?ex=65d28031&is=65c00b31&hm=3400b1731a8907aec6315da5513e4e3b02ac162c160f990ec780d54451e39ea1&=&format=webp&quality=lossless&width=323&height=459) - [v3](https://cdn.discordapp.com/attachments/771403403372527656/1201288064077660271/dat3.png?ex=65d28031&is=65c00b31&hm=6211a2344c4b6e53cafe6f4618aecd4c48c6c48babba4ca2c9fa5c980ab1e665&) - [v3.2](https://cdn.discordapp.com/attachments/771403403372527656/1201288064492904528/dat4.png?ex=65d28031&is=65c00b31&hm=294a2145d28e31d3f9b9dbbf92cbc15ea90694e2ab18a49d386e2c8ce6969aa0&)

p.s. Sorry for the size of all this and examples with links, it was just easier with real examples, and I don’t have the opportunity to try something with all of them now

DWTP DS dat2 v3 2

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

For photos/realistic images, but worth trying on other images that have reduced colors and dithering along with fine details. Trained using the ESRGAN-FS code (https://github.com/ManuelFritsche/real-world-sr/tree/master/esrgan-fs/codes) for better details compared to plain ESRGAN.

FSDedither

Fine-tuned 4xFSDedither to upscale images from the game Riven, but should be better in general, particularly on ordered dithering. I adjusted the dataset to have a better variety of dithering parameters, and turned up the HFEN and pixel loss to get better details and color restoration with less noise.

FSDedither Riven

Category: Fabric/Cloth
Purpose: Fabric

This model set upscales fabric or cloth textures (works on cats too!). The Alt model is just an earlier iteration version. It may work better on some images.The images need to be minimally compressed or passed through a decompression model first. It works with DDS compression though.

Fabric

Fabric-Alt

Images from the Fate/Extra games. Works better on the newer ones.

Just a model I trained quickly to test traiNNer-redux and see what I could do with OTF. Works well enough

FatePlus Compact

4x realistic upscaler that may also work for general purpose usage. Trained on Bicubic downscaled tiles from very high quality images.

FrankendataPretainer_SRFormer

This model is intended to mainly handle PS2 compression and a mixture of Realistic and cartoonish textures, it's not meant to be used for very low resolution textures such as item icons.

GameAI 2.0

Gamecube and Wii textures Dumps.

https://github.com/Venomalia/HDcube/tree/main/v2

HDCube2

Purpose: Gamecube and Wii textures.
Pretrained: 4x_HDcube2

It can be used for all image formats supported by Gamecube and Wii hardware and can remove its typical artifacts like CMPR Block Compression (DXT1 algorithm, also known as BC1), color palette errors, color reduction up to 8bit color depth and 1bit alpha depth.

HDCube3

4x anime image upscaler with a bit of otf jpg compression and blur. Trained on musl's hfa2k dataset release for Anime SISR, which has been extracted from modern anime films, where the selection criteria was high SNR, no DOF and high frequency information.

Examples: https://imgsli.com/MTc2NDgx (PS Example input images are small, each around 500x280 px) \
Example input files: https://drive.google.com/drive/folders/1RI6gGqRy-KxDujbaIrpEMdvFkIWHvfPt \
Example output files: https://drive.google.com/drive/folders/1GqHwPlFp6bIQl4R1AxmrmJ6vUUD8FUxH \
All my model files can be found on my github repo https://github.com/Phhofm/models

HFA2k

[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xHFA2k_ludvae_realplksr_dysample)

4xHFA2k_ludvae_realplksr_dysample  
Scale: 4  
Architecture: [RealPLKSR with Dysample](https://github.com/muslll/neosr/?tab=readme-ov-file#supported-archs)  
Architecture Option: [realplksr](https://github.com/muslll/neosr/blob/master/neosr/archs/realplksr_arch.py)  

Author: Philip Hofmann  
License: CC-BY-0.4 
Purpose: Restoration  
Subject: Anime  
Input Type: Images  
Release Date: 13.07.2024  

Dataset: HFA2k_LUDVAE  
Dataset Size: 10'272  
OTF (on the fly augmentations): No  
Pretrained Model: [4xNomos2_realplksr_dysample](https://github.com/Phhofm/models/releases/tag/4xNomos2_realplksr_dysample)  
Iterations: 165'000  
Batch Size: 12  
GT Size: 256  

Description:  
A Dysample RealPLKSR 4x upscaling model for anime single-image resolution.  
The dataset has been degraded using DM600_LUDVAE, for more realistic noise/compression. Downscaling algorithms used were imagemagick box, triangle, catrom, lanczos and mitchell. Blurs applied were gaussian, box and lens blur (using chaiNNer). Some images were further compressed using -quality 75-92. Down-up was applied to roughly 10% of the dataset (5 to 15% variation in size). Degradations orders were shuffled, to give as many variations as possible.  

Examples are inferenced with [neosr](https://github.com/muslll/neosr) testscript and the released pth file. I include the test images also as a zip file in this release together with the model outputs, so others can test their models against these test images aswell to compare.  

onnx conversions are  static since dysample doesnt allow dynamic conversion, I tested the conversions with [chaiNNer](https://github.com/chaiNNer-org/chaiNNer).  

Showcase:  
[Slowpics](https://slow.pics/c/FKDZAcyI)

4xHFA2k_ludvae_realplksr_dysample

Category: Cel Animation
Purpose: Traditional Animation

A rougher alternative to 4xCelFrames with a focus on realistic looking cels over nice looking cels. It's trained on DetoriationFrames LRs, so if you give it an image straight from the source it will go twice as hard on it. This can be used to your advantage, though. I recommend cleaning it up before running DetoriationFrames, or else it will come out rough.

HellinaCel

The model was trained for some tests, but maybe someone will need to remove a screentone with a color image; in addition to the screentone, it can handle small halftones quite well

WTP ColorDS

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

Anime super-resolution, with real degradation.

animerd v1

This is the first community model using the OmniSR network. I trained it mostly to test this network.\nNote: the model output decreases brightness. This is a well known issue we had with OmniSR.

4x_ardo

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

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.

Architecture	DAT
Scale	4x
Size	mediums64\|8x3264nf180dim2.0ef1conv
Color Mode	RGB
License	CC-BY-4.0 Private use Commercial use Distribution Modifications Credit required State Changes No Liability & Warranty Disclaimer
Date	2024-02-06
Training OTF	No

DWTP DS dat2 v3 2

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