Name: 2x GT-evA
Author: evA-01

This model is far from perfect, but it does a decent job on removing dot crawl and dehalo\deblock old anime at fast rate without removing many details. chaining it with models like 2x-anifilm-compact or 2xLD-ANIME or 2x_AnimeClassics_UltraLite_510K will give good results i think.

Epsilon-one compact

Upscale 90s and early 2000 American cartoons

90s Cartoon v1

Upscaling of Animation based on The Legend of Korra.

ATLA KORRA

Purpose: Anime/Pretrained

A 2x Ultra Lite model coming in under 8MB. Trained with over 15 sets of LRs ranging in a wide amount of issues. Handles Rainbows, Dot Crawl, MPEG/H.264 Compression, and may even assist in removing halos, and fixing blurriness in certain cases. This is my first public model for everyone. Best when used on old anime that is grainy. I can't say what anime it's best suited for as I have tried multiple series, and have found it does a good job on most all the tests. I wouldn't say use this for Western Animation, but it may work. I have done a few tests that I have shown in the upscale results, but that was chained with other models to achieve such a result. This model is meant to retain the more natural look of a series. There is a color shift on the end result, not drastic, but still noticable. I figure you should fix any color issues in post that way to give a more polished upscale. Big thanks to @SaurusX for the model name, and just helping out in general with anything.

AnimeClassics UltraLite

As the name might suggest, this model aims to upscale text with less distortion that other models. It seems to do a good job generally, but don't expect it to be a state of the art model that can upscale magazines and stuff. It makes things more readable but since it was train on B/W pictures it desaturates them.

BSTexty

Pretrained: 4x_muy4_035_1.pth

This is my first model, so it's not perfect, but I wanted to see if I could train an upscaling model that didn't result in a lot of detail loss and deblurring like the current Compact upscaling models. I believe I accomplished this, but I was unable to reduce contrast shifting. The contrast shifting may cause skin tones to appear incorrect on bright frames, but it's not too bad overall! I'll list a few examples below; more can be found by clicking the Overview link on the Github release page.

Pretrained model: Kim2091_CrappyCompactV2.pth

Bubble AnimeScale Compact v1

2x_Bubble_AnimeScale_SwinIR_Small_v1 was trained to upscale anime frames faithfully without major contrast shifting compared to my compact model. Although much slower compared to my compact model, the results look significantly better! A few example upscales are listed below; more can be found by clicking the Overview link on the Github release page.

Bubble AnimeScale SwinIR Small v1

Using the Kineko 4K scan the hope was to clean up the Funi DVD releases and upscale to something comparable. This model degrains the series pretty damn well, but what's revealed beneath is a lot of moving noise that's probably best dealt with in pre- or post- with a video editor like AVISynth. So while the model is remarkably temporally stable, the DBZ sources certainly aren't. The movies look really nice when upscaled with raw input, though.

2x_DBZScanLite

Category: Cel Animation
Purpose: Traditional Animation

Upscaling Dragon Ball Z DBox DVD's. - grainy sources. It keeps some grain, but also doing some cleaning, sharpening, and fixing.

DigitalFilmV5 Lite

Category: Digital Animation


This was trained on the dataset that OptimusPrimal used for his DigitalFilm models. This model cleans up the image removing some noise while upscaling. This model is very fast, running around 200x the speed of a standard ESRGAN model on my system. This is primarily a proof of concept for how fast Real-ESRGAN models can get while still producing nice results.

DigitalFlim SuperUltraCompact

This model is designed to upscale the standard definition digital era of the Pokémon anime, which runs from late season 5 (Master Quest) to early season 12 (Galactic Battles). During this time, the show was animated digitally in a 4:3 ratio. This process was also used for Mewtwo Returns, most of Pokémon Chronicles, and the Mystery Dungeon specials.

Advice/Known Limitations:
* This OmniSR model can occasionally produce black frames when run in fp16 mode. This seems to be more common in the TPCi era (seasons 9 and later). The issue is sporadic enough that it probably makes sense to do a first pass in fp16, then re-upscale any affected shots in fp32.
* I recommend using QTGMC on a preset of "Slow" or slower for deinterlacing. While the show is primarily animated at 12/24 fps, some elements like backgrounds are animated at a full 60i.
* The model is not great at handling fonts, particularly the italicized text in the episode credits. This is despite including font images in the training data,.

Digital Pokémon-Large

This model is designed to upscale the standard definition digital era of the Pokémon anime, which runs from late season 5 (Master Quest) to early season 12 (Galactic Battles). During this time, the show was animated digitally in a 4:3 ratio. This process was also used for Mewtwo Returns, most of Pokémon Chronicles, and the Mystery Dungeon specials.

Advice/Known Limitations:
* I recommend using QTGMC on a preset of "Slow" or slower for deinterlacing. While the show is primarily animated at 12/24 fps, some elements like backgrounds are animated at a full 60i.
* The model is not great at handling fonts, particularly the italicized text in the episode credits. This is despite including font images in the training data,.

Digital Pokémon-Small

This model upscales while doing some sharpening and line darkening. Can also clean up some minor artifacts of various types. It is intended to to be a good general purpose upscaler that will work well with most animation.

Futsuu Anime

This is my first 2xcompact model, the main purpose of it is to upscale Dragon ball GT. for upscaling videos that have grain I would recommend denoising and dehaloing it before passing it to the model for temporal stability.

GT-evA

This is the v2 of my 2xGT model, the main purpose of it is to improve upon the v1 model and make more it generalized.
for upscaling videos that have grain I would recommend denoising and de-haloing it before passing it through  the model.

GT-v2-evA

Meant to preserve original 4:3 framing of G&F while upscaling. Trained to handle all seven seasons, which drastically differ in quality. Fixes include rainbowing, dot-crawl, halos, general noise, and of course MPEG-2 artifacts. It should be generally flexible in dealing with different degrees of those artifacts, but as always the cleaner the source the better. The model could be useful with other shows from the '80s and '90s with ugly video sources. Maybe.

2x_Garfield1_308k

Purpose: A lightweight anime 2x upscaling model with realistic degradations, based on musl's HFA2k_LUDVAE dataset

2x lightweight anime upscaler with realistic degradations (compression, noise, blur) based on musl's HFA2k_LUDVAE dataset.

Original Link: https://drive.google.com/drive/folders/1Fe1Uu3-L5YWaVSwPGBTIPG4xU7kK9rZK?usp=drive_link

HFA2k LUDVAE SPAN

Purpose: A lightweight anime 2x upscaling model with realistic degradations, based on musl's HFA2k_LUDVAE dataset

2x lightweight anime upscaler with realistic degradations (compression, noise, blur) based on musl's HFA2k_LUDVAE dataset.

HFA2k LUDVAE compact

Purpose: 2x anime upscaler

2x span version of the hfa2k model.

Original Link: https://drive.google.com/drive/folders/1Fe1Uu3-L5YWaVSwPGBTIPG4xU7kK9rZK?usp=drive_link

HFA2kSPAN

Purpose: 2x anime upscaler

2x shallow esrgan version of the HFA2kCompact model.  
This model should be usable with [FAST_Anime_VSR ](https://github.com/Kiteretsu77/FAST_Anime_VSR) using TensorRT for fast inference, as should my [2xHFA2kReal-CUGAN](https://drive.google.com/file/d/1wqlK-rQjPGKJ5pNoVgnK9gcNF1tA8EjV/view?usp=drive_link) model.  

Original Link: https://drive.google.com/drive/folders/1_gtYqZGQgrpq55gsGf17MG_QUP4XeFJD

Slow Pics examples:  
[Example 1](https://slow.pics/c/RZj6GMwS)  
[Example 2](https://slow.pics/c/Q3DHaU45)  
[Ludvae1](https://slow.pics/c/fJi4IphY)  
[Ludvae2](https://slow.pics/c/iIhgHokD)

HFA2kShallowESRGAN

Purpose: Upscale text in very low quality to normal quality.

The upscale model is specifically designed to enhance lower-quality text images, improving their clarity and readability by upscaling them by 2x. It excels at processing moderately sized text, effectively transforming it into high-quality, legible scans. However, the model may encounter challenges when dealing with very small text, as its performance is optimized for text of a certain minimum size. For best results, input images should contain text that is not excessively small.

Text2HD v.1

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 (2x)

I recommend filtering the source before passing it to the model. 

Note: if the original trainers of the models i used as teachers for this model are not cool with using them in this way, i will remove this model

2xken-v1-eva-01

Interpolation between 4x-UltraSharp and 4x-TextSharp-v0.5. Works amazingly on anime. It also upscales text, but it's far better with anime content. I rebranded this model on 2/10/22 to 4x-AnimeSharp from 4x-TextSharpV1.

Pretrained model: Interpolation between 4x-UltraSharp and 4x-TextSharp-v0.5

AnimeSharp

Low-resolution text/typography and symbols

Architecture	Compact
Scale	2x
Size	64nf16nc
Color Mode	RGB
License	CC-BY-NC-SA-4.0 Private use Distribution Modifications Credit required Same License State Changes No Liability & Warranty Disclaimer
Date	2022-12-14
Dataset	German blu ray of detective Conan and other shows
Dataset size	2710
Training iterations	120000
Training batch size	20
Training HR size	128
Training OTF	No

GT-evA

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