This model corrects jagged lines on animation that has been deinterlaced. It handles simple line doubling, line interpolation, and even Yadif-style artifacts. It can also handle sources that were resized after deinterlacing, for example resizing from ntsc to pal resolutions. If a source has been upscaled after deinterlacing, it will need to be downsized before applying this model.

AnimeUndeint Compact

This model helps repair color bleed and heavy chroma noise that may be present on some older footage, particularly that which was recorded on VHS. It also cleans up rainbows if they are present.

BleedOut Compact

Purpose: "binarization" for scanned books.

A compact, lightweight version trained for general-purpose cleanup. While it performs well, RealPLSKR delivers superior results for more complex cases. 
- Strengths (Handles Well): 
✔ Color bleed 
✔ Spots & small speckles 
✔ Mould stains 
✔ Fine hair & scratches – Good at thin, faint lines. 
✔ Light pencil marks 
✔ Dividers & text preservation 
- Weaknesses (Struggles With): 
✖ Large speckles 
✖ Thick hair/clumps – May leave remnants or blurring. 
✖ Photographs – Bad lighting; noisy/dark images degrade quality.

Book Compact

Improvement of low-quality cartoons from broadcast sources.
Will greatly increase the visual quality of bad broadcast tape sources of '80s and '90s cartoons (e.g. Garfield and Friends, Heathcliff, DuckTales, etc). Directly addresses chroma blur, dot crawl, and rainbowing. You're highly advised to take care of haloing beforehand in your favorite video editor as the model will not fix it and may make existing halos more noticeable.

BroadcastToStudio Lite

Create realistic noise and compression artifacts on images. This is meant to synthesize paired dataset for SISR training.

DM600_LUDVAE

Halo Removal + edge removal. This model softens edges without blurring other parts of the image.

Comparison and use case: https://imgsli.com/MjgxMDU

DeEdge

This is a 1x model for removing halos in animation. I was training this a while back and considered it a failed project, but I recently found it useful on a few things I was working on, so I decided to release it. I don't remember any details regarding how it was trained.

Dehalo_v1_Compact

Wipes out dot crawl and rainbows in animation.

Dotzilla Compact

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

This is a sharpening/deblurring model for anime video. It was created with three goals in mind:
Be blazing fast
Try to avoid enhancing noise and compression artifacts
Try to avoid over-enhancing intentionally blurred parts of the image

Despite that last point, this is not intended to be used on modern anime which makes heavy of use depth-of-field effects.

HurrDeblur SuperUltraCompact

Upscale Anime while keeping as much of the original detail as possible. Isn't among the sharpest models and if the anime is somewhat blurry it will retain that detail but add more pixels to give a smoother edge. Doesn't change the color very much and may make some scene's very slightly darker.

Pretrained model: Pony Models

Loyaldk SharpKeroro

Model designed exclusively to remove compression artifacts while preserving noise in Manhwa, Manhua, Webtoons etc.

1x Manhwa Null

Restoring frames from the show "Sheeep"

This model was trained to restore "Sheeep" while retaining and enhancing the noise present in the show. The model amazingly finished training in only 8.8k iterations with no pretrain, with a dataset of only 4 image pairs. This model should work well for animes and cartoons with a lot of grain present. There are some slight haloing issues in dark colors unfortunately, but I was unable to fix it.

SheeepIt!

Purpose: Animation - Quantized

Removed color quantization/indexing and dithering from cartoon style images and textures

Pretrained model: 1x_1xDEDITHER_32_512_126900_G

Spongebob De-Quantize

Fix vertical blur / split lines / shadowing. A 1x lite model of my 2xSwatKats. Resolves the same video problems as before, but 1x and faster and meant for chaining to other 2x models (or whatever). Input MUST be 540 vertical as the blur problem is very resolution sensitive.

SwatKats Lite

2x general purpose anime upscaler, with a focus on cleaning up scuffed sources while enhancing texture detail. While the model was trained on DVDs, it still works well on modern anime. The model is trained to deal with noise, compression artifacts, blur, bleeding, haloing and scuffed line art. Apparently, it also learned to deal with some dotcrawl.

AniScale

upscaling old anime. help to denoise and find lines and dehalo

BIGOLDIES

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

Purpose: Digital Animation

Meant as a versatile model for upscaling high detail digital anime and cartoons. Has debanding, MPEG-2 correction, and halo reduction. Trained to handle both 4:3 and 16:9 DVD material with equal efficacy. Will retain a lot of textures except for the really high freq stuff.

Digitoon Lite

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

I trained Skr's great LD-Anime model on compact architecture. It upscales while fixing numerous video problems, including: noise/grain, compression artifacts, rainbows, dot crawl, halos and color bleed. This compact version may look slightly worse than Skr's original model, but runs significantly faster and also retains the correct colors better than the original model did.

LD-Anime Compact

Purpose: Denoise/Dehalo

Denoise, dehalo, derainbow old anime

LD-Anime_Skr v1.0

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

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

Architecture	Compact
Scale	1x
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	2022-12-03
Dataset	frames from remastered 80s-90s anime
Training iterations	98500
Training batch size	20
Training HR size	128
Training OTF	No

Epsilon-one compact

Similar Models