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Difference between revisions of "Model Database"
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! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
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|Streets with dense foliage in the background. Outdoor scenes. | |Streets with dense foliage in the background. Outdoor scenes. | ||
|[https://drive.google.com/drive/folders/1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 4xPSNR] | |[https://drive.google.com/drive/folders/1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 4xPSNR] | ||
− | |https://cdn.discordapp.com/attachments/547949806761410560/880291337373618236/unknown.png | + | |[https://cdn.discordapp.com/attachments/547949806761410560/880291337373618236/unknown.png Sample 1] |
+ | |||
+ | [https://media.discordapp.net/attachments/547949806761410560/880290211026853918/unknown.png Sample 2] | ||
+ | |||
+ | [https://media.discordapp.net/attachments/547949806761410560/880299665428447232/unknown.png Sample 3] | ||
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+ | [https://cdn.discordapp.com/attachments/880291340301254657/880303552315146340/unknown.png Sample 4] | ||
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| 4x | | 4x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
− | | | + | | ESRGAN |
| General Upscaler | | General Upscaler | ||
| 2021-04-09 | | 2021-04-09 | ||
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|This is my best model yet! It generates lots and lots of detail and leaves a nice texture on images. It works on most images, whether compressed or not. It does work best on JPEG compression though, as that's mostly what it was trained on. It has the ability to restore highly compressed images as well! '''If you want a more balanced output, check out the UltraMix Collection down below. It's a bunch of interpolated models based around UltraSharp and my other models''' | |This is my best model yet! It generates lots and lots of detail and leaves a nice texture on images. It works on most images, whether compressed or not. It does work best on JPEG compression though, as that's mostly what it was trained on. It has the ability to restore highly compressed images as well! '''If you want a more balanced output, check out the UltraMix Collection down below. It's a bunch of interpolated models based around UltraSharp and my other models''' | ||
|[https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | |[https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | ||
− | |[https://cdn.discordapp.com/attachments/902853011913732097/902855337705611294/unknown.png Sample 1] [https://cdn.discordapp.com/attachments/902853011913732097/902853340600360990/unknown.png Sample 2] [https://cdn.discordapp.com/attachments/902853011913732097/902855036768489512/unknown.png Sample 3] [https://cdn.discordapp.com/attachments/900506271566938122/902867618086670356/unknown.png Sample 4] | + | |[https://cdn.discordapp.com/attachments/902853011913732097/902855337705611294/unknown.png Sample 1] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/902853011913732097/902853340600360990/unknown.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/902853011913732097/902855036768489512/unknown.png Sample 3] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/900506271566938122/902867618086670356/unknown.png Sample 4] | ||
|- | |- | ||
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|UniScale_Restore has strong compression removal that helps with restoring heavily compressed or noisy images. It is intended to compete with BSRGAN. Trained with BSRGAN_Resize and Combo_Noise in traiNNer. | |UniScale_Restore has strong compression removal that helps with restoring heavily compressed or noisy images. It is intended to compete with BSRGAN. Trained with BSRGAN_Resize and Combo_Noise in traiNNer. | ||
|[https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | |[https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | ||
− | |https://cdn.discordapp.com/attachments/880826637543964712/880934732748169226/unknown.png | + | |[https://cdn.discordapp.com/attachments/880826637543964712/880934732748169226/unknown.png Sample 1] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/880826637543964712/880932754102026290/unknown.png Sample 2] | ||
|- | |- | ||
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| These models work great on game textures when interpolated 50/50 with UniScale_Restore, and work amazingly on uncompressed images. DO NOT USE FOR COMPRESSED IMAGES, use the original UniScale or UltraSharp for that. | | These models work great on game textures when interpolated 50/50 with UniScale_Restore, and work amazingly on uncompressed images. DO NOT USE FOR COMPRESSED IMAGES, use the original UniScale or UltraSharp for that. | ||
|[https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | |[https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | ||
− | |https://cdn.discordapp.com/attachments/884239326471393331/884296266857713704/unknown.png https://cdn.discordapp.com/attachments/884239326471393331/884294468709257216/unknown.png https://cdn.discordapp.com/attachments/884239326471393331/884298572894441512/unknown.png https://cdn.discordapp.com/attachments/884239326471393331/884302370136289323/unknown.png | + | |[https://cdn.discordapp.com/attachments/884239326471393331/884296266857713704/unknown.png Sample 1] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/884239326471393331/884294468709257216/unknown.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/884239326471393331/884298572894441512/unknown.png Sample 3] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/884239326471393331/884302370136289323/unknown.png Sample 4] | ||
|- | |- | ||
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! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
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| This model was made to upscale realistic low-res textures that are compressed by either JPEG or BC1. From my testing, this works rather well on realistic GameCube textures such as the ones from Shrek Extra Large and the board textures from Mario Party 4. This model could also work on some real life images, especially the ones that are taken outdoors. | | This model was made to upscale realistic low-res textures that are compressed by either JPEG or BC1. From my testing, this works rather well on realistic GameCube textures such as the ones from Shrek Extra Large and the board textures from Mario Party 4. This model could also work on some real life images, especially the ones that are taken outdoors. | ||
| RealESRGAN_x4plus | | RealESRGAN_x4plus | ||
− | | https://imgsli.com/MTQ0Mzk1 https://imgsli.com/MTQ0MTYy https://imgsli.com/MTQ0MjEx https://imgsli.com/MTQ0MTQ2 https://imgsli.com/MTQ0MTQ3 https://imgsli.com/MTQ0MTQ5 https://imgsli.com/MTQ0MTUw https://imgsli.com/MTQ0MTUx https://imgsli.com/MTQ0MTUz https://imgsli.com/MTQ0MTU1 https://imgsli.com/MTQ0MTU2 https://imgsli.com/MTQ0MTU4 https://imgsli.com/MTQ0MTU5 https://imgsli.com/MTQ0MTYw https://imgsli.com/MTQ0MTYx https://imgsli.com/MTQ0MjEz | + | | https://imgsli.com/MTQ0Mzk1 |
+ | |||
+ | https://imgsli.com/MTQ0MTYy | ||
+ | |||
+ | https://imgsli.com/MTQ0MjEx | ||
+ | |||
+ | https://imgsli.com/MTQ0MTQ2 | ||
+ | |||
+ | https://imgsli.com/MTQ0MTQ3 | ||
+ | |||
+ | https://imgsli.com/MTQ0MTQ5 | ||
+ | |||
+ | https://imgsli.com/MTQ0MTUw | ||
+ | |||
+ | https://imgsli.com/MTQ0MTUx | ||
+ | |||
+ | https://imgsli.com/MTQ0MTUz | ||
+ | |||
+ | https://imgsli.com/MTQ0MTU1 | ||
+ | |||
+ | https://imgsli.com/MTQ0MTU2 | ||
+ | |||
+ | https://imgsli.com/MTQ0MTU4 | ||
+ | |||
+ | https://imgsli.com/MTQ0MTU5 | ||
+ | |||
+ | https://imgsli.com/MTQ0MTYw | ||
+ | |||
+ | https://imgsli.com/MTQ0MTYx | ||
+ | |||
+ | https://imgsli.com/MTQ0MjEz | ||
|- | |- | ||
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! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
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− | | [https://1drv.ms/u/s!Aip-EMByJHY20xsc9EvnxVZ50Ja7 Lady0101_208000.pth] | + | | [https://1drv.ms/u/s!Aip-EMByJHY20xsc9EvnxVZ50Ja7?e=Loa5Gz Lady0101_208000.pth] |
− | | | + | | [[User:DinJerr|DinJerr]] |
| 4x | | 4x | ||
| | | | ||
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| Similar to Manga109, can be used as a general digital upscaler as well as with pixel art | | Similar to Manga109, can be used as a general digital upscaler as well as with pixel art | ||
| RRDB_PSNR_x4 | | RRDB_PSNR_x4 | ||
− | | https://www.youtube.com/channel/UCwBfuiHdSPQ-zslOmiW8OHg | + | | [https://www.youtube.com/channel/UCwBfuiHdSPQ-zslOmiW8OHg Video Samples] |
|- | |- | ||
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| [https://1drv.ms/u/s!Aip-EMByJHY26nuB0Lo0rdirfGoi?e=XI9Fa2 8x_HugePeeps_v1] | | [https://1drv.ms/u/s!Aip-EMByJHY26nuB0Lo0rdirfGoi?e=XI9Fa2 8x_HugePeeps_v1] | ||
− | | DinJerr | + | | [[User:DinJerr|DinJerr]] |
| 8x | | 8x | ||
|[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
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|- | |- | ||
− | | [https://1drv.ms/u/s!Aip- | + | | [https://1drv.ms/u/s!Aip-EMByJHY21WF47rcqn7fhr7fq?e=I8mnX6 ArtStation1337] |
− | | DinJerr | + | | [[User:DinJerr|DinJerr]] |
− | | | + | | 4x |
− | | | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | Art/People | + | | Digital Art/People |
| 2019-08-21 | | 2019-08-21 | ||
| | | | ||
− | | | + | | Mainly for digital art, but can be used to upscale pixel art. |
| | | | ||
|- | |- | ||
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| Upscaling airbrush/pencil-based artwork | | Upscaling airbrush/pencil-based artwork | ||
| 4xPSNR | | 4xPSNR | ||
− | | https://drive.google.com/drive/folders/1fyeIWInDrM6r-xxrCW4U09oafWw08u9S?usp=sharing | + | | [https://drive.google.com/drive/folders/1fyeIWInDrM6r-xxrCW4U09oafWw08u9S?usp=sharing Sample Gallery] |
|- | |- | ||
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|- | |- | ||
− | | [https://1drv.ms/u/s!Aip- | + | | [https://1drv.ms/u/s!Aip-EMByJHY23if0ac150Sj2qnbp?e=qLp7SP BigFArt] |
− | | DinJerr | + | | [[User:DinJerr|DinJerr]] |
| 4x | | 4x | ||
|[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
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|- | |- | ||
− | | [https://1drv.ms/u/s!Aip- | + | | [https://1drv.ms/u/s!Aip-EMByJHY27UIFr1mk87zFytap?e=SSxKaV UltraFArt_v3 Suite] |
− | | DinJerr | + | | [[User:DinJerr|DinJerr]] |
| 4x | | 4x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
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| Art | | Art | ||
| 2021-05-14 | | 2021-05-14 | ||
− | | | + | | Illustrations with with larger shaped features (?). |
| 4x_UltraFArt | | 4x_UltraFArt | ||
− | | | + | | |
|- | |- | ||
− | | [https://drive.google.com/drive/folders/1mYTMpwDlKQulBmjgKpcxL3-T6xAGXVxl?usp=sharing NXbrz] | + | |- |
− | | Archerpolation | + | | [https://1drv.ms/u/s!Aip-EMByJHY26wU-wOqApp7Hu7tt?e=4ihnBr HugePaint] |
− | | 4x | + | | |[[User:DinJerr|DinJerr]] |
+ | | 8x | ||
+ | | [https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
+ | | ESRGAN | ||
+ | | Digital Illustrations | ||
+ | | | ||
+ | | Trained on a variety of images from ArtStation | ||
+ | | HugePeeps | ||
+ | | | ||
+ | |- | ||
+ | |||
+ | | [https://drive.google.com/drive/folders/1mYTMpwDlKQulBmjgKpcxL3-T6xAGXVxl?usp=sharing NXbrz] | ||
+ | | Archerpolation | ||
+ | | 4x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
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| 2021-06-09 | | 2021-06-09 | ||
| Basic pixel art upscaling, for people who want a more simpler style and lightweight pixel art upscaling model. | | Basic pixel art upscaling, for people who want a more simpler style and lightweight pixel art upscaling model. | ||
− | | https://drive.google.com/drive/folders/1mYTMpwDlKQulBmjgKpcxL3-T6xAGXVxl?usp=sharing | + | | |
+ | | [https://drive.google.com/drive/folders/1mYTMpwDlKQulBmjgKpcxL3-T6xAGXVxl?usp=sharing Sample Gallery] | ||
|- | |- | ||
|} | |} | ||
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===Drawn Material=== | ===Drawn Material=== | ||
− | ====Anime==== | + | ====Anime and Cartoons==== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
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! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
− | |||
|- | |- | ||
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| 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. | | 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. | ||
| | | | ||
− | | [https://cdn.discordapp.com/attachments/903415274521374750/925533775616696340/unknown.png Text Sample] [https://cdn.discordapp.com/attachments/549525506585001985/941432207917084743/Clipboard-comparison.png Anime Sample] [https://cdn.discordapp.com/attachments/549525506585001985/941432638206541825/test_pic-comparison.png Anime Sample 2] | + | | [https://cdn.discordapp.com/attachments/903415274521374750/925533775616696340/unknown.png Text Sample] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/549525506585001985/941432207917084743/Clipboard-comparison.png Anime Sample] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/549525506585001985/941432638206541825/test_pic-comparison.png Anime Sample 2] | ||
|- | |- | ||
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| This model is a lite version of AnimeSharp. It was trained using student-teacher learning (if i'm using the term properly), where the HRs are LRs upscaled by the full size AnimeSharp ESRGAN model, and the lite model is trained on those outputs as the HR. It works best on clean or slightly blurry anime. '''Downscale by 50% first in almost all cases''' | | This model is a lite version of AnimeSharp. It was trained using student-teacher learning (if i'm using the term properly), where the HRs are LRs upscaled by the full size AnimeSharp ESRGAN model, and the lite model is trained on those outputs as the HR. It works best on clean or slightly blurry anime. '''Downscale by 50% first in almost all cases''' | ||
| | | | ||
− | | [https://cdn.discordapp.com/attachments/547949405949657100/941776512049360986/unknown.png Sample 1] [https://cdn.discordapp.com/attachments/547949405949657100/941770824543797268/unknown.png Sample 2] [https://cdn.discordapp.com/attachments/903415274521374750/941779970013925506/unknown.png Sample 3] | + | | [https://cdn.discordapp.com/attachments/547949405949657100/941776512049360986/unknown.png Sample 1] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/547949405949657100/941770824543797268/unknown.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/903415274521374750/941779970013925506/unknown.png Sample 3] | ||
|- | |- | ||
− | | [https://e1.pcloud.link/publink/show?code=kZ7rGRZW2IcOpNMQeXDTTRQ4aPVBFyyJV5X sudo_RealESRGAN2x_3.332.758_G.pth / | + | | <small>[https://e1.pcloud.link/publink/show?code=kZ7rGRZW2IcOpNMQeXDTTRQ4aPVBFyyJV5X sudo_RealESRGAN2x_3.332.758_G.pth / sudo_RealESRGAN2x_Dropout_ 3.799.042_G.pth (pcloud)]</small> |
+ | <small>[https://www.mediafire.com/folder/gk7f61e2kut0z/sudo_RealESRGAN2x sudo_RealESRGAN2x_3.332.758_G.pth / sudo_RealESRGAN2x_Dropout_ 3.799.042_G.pth (mediafire)]</small> | ||
| sudo | | sudo | ||
| 2x | | 2x | ||
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| 2022-06-25 | | 2022-06-25 | ||
| Tried to make the best 2x model there is for drawings. I think i archived that. And yes, it is nearly 3.8 million iterations (probably a record nobody will beat here), took me nearly half a year to train. It can happen that in one edge is a noisy pattern in edges. You can use padding/crop for that. I aimed for perceptual quality without zooming in like 400%. Since RealESRGAN is 4x, I downscaled these images with bicubic. I would recommend my VSGAN code though and just load the onnx. https://github.com/styler00dollar/VSGAN-tensorrt-docker I just wanted a good 2x model for animations, but that model can also be used for wallpapers and so on. Before I hear people complaining, the dropout model is a modified architecture. Stuff like cupscale or chaiNNer won't work with pth. Load the onnx with VSGAN or chaiNNer. I did add the model before switching to dropout though, which is normal ESRGAN pth, that one should work everywhere. I also converted everything into onnx, jit and ncnn, so pretty much everything there is. If you want to use ncnn, don't use nihuis code (that also includes cupscale), these codes don't include propper tiling in C++, which is very bad for this model. I think chaiNNer should have overlap/padding with ncnn, so use that instead if you really want ncnn. Plz don't steal without credits, k thx. | | Tried to make the best 2x model there is for drawings. I think i archived that. And yes, it is nearly 3.8 million iterations (probably a record nobody will beat here), took me nearly half a year to train. It can happen that in one edge is a noisy pattern in edges. You can use padding/crop for that. I aimed for perceptual quality without zooming in like 400%. Since RealESRGAN is 4x, I downscaled these images with bicubic. I would recommend my VSGAN code though and just load the onnx. https://github.com/styler00dollar/VSGAN-tensorrt-docker I just wanted a good 2x model for animations, but that model can also be used for wallpapers and so on. Before I hear people complaining, the dropout model is a modified architecture. Stuff like cupscale or chaiNNer won't work with pth. Load the onnx with VSGAN or chaiNNer. I did add the model before switching to dropout though, which is normal ESRGAN pth, that one should work everywhere. I also converted everything into onnx, jit and ncnn, so pretty much everything there is. If you want to use ncnn, don't use nihuis code (that also includes cupscale), these codes don't include propper tiling in C++, which is very bad for this model. I think chaiNNer should have overlap/padding with ncnn, so use that instead if you really want ncnn. Plz don't steal without credits, k thx. | ||
− | | Pretrained_Model_G: RealESRGAN_x4plus_anime_6B.pth / RealESRGAN_x4plus_anime_6B.pth ( | + | | Pretrained_Model_G: RealESRGAN_x4plus_anime_6B.pth / |
− | | [https://cdn.discordapp.com/attachments/579685650824036387/990323693660033045/jpg_compare.png Sample 1] [https://cdn.discordapp.com/attachments/579685650824036387/990323694196916275/test2_compare.png Sample 2] [https://cdn.discordapp.com/attachments/579685650824036387/990323694561816606/f4_compare.png Sample 3] [https://cdn.discordapp.com/attachments/579685650824036387/990323695186763884/test_compare.png Sample 4][https://cdn.discordapp.com/attachments/579685650824036387/990323695601987584/f2_compare.png Sample 5] | + | RealESRGAN_x4plus_anime_6B.pth |
+ | (sudo_RealESRGAN2x_ 3.332.758_G.pth) | ||
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/990323693660033045/jpg_compare.png Sample 1] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/990323694196916275/test2_compare.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/990323694561816606/f4_compare.png Sample 3] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/990323695186763884/test_compare.png Sample 4] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/990323695601987584/f2_compare.png Sample 5] | ||
+ | |- | ||
+ | |||
+ | | <small>[https://e1.pcloud.link/publink/show?code=kZufYRZj1INMisvFehhfS763L4ow5YUy0VV sudo_UltraCompact_2x_1.121.175_G.pth (pcloud)] / [https://www.mediafire.com/folder/7e7752gf42eky/sudo_UltraCompact_2x_1.121.175 sudo_UltraCompact_2x_1.121.175_G.pth (mediafire)]</small> | ||
+ | | sudo | ||
+ | | 2x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | Compact | ||
+ | | Realtime animation restauration and doing stuff like deblur and compression artefact removal | ||
+ | | 2022-05-29 | ||
+ | | My first attempt to make a REALTIME 2x upscaling model while also applying teacher student learning. It beats Anime4k in every way. These benchmarks use a 3060ti and it shows that everything better than a 3060ti should be able to handle 1080p input if you create engine files and use my TensorRT code. You can see in the readme how to convert onnx files into engines. The 2 right bars compare normal Compact2 and Ultracompact in speed, the 2 on the left showcase older apis I used which isn't too important for this showcase. To use this, you need to use my code which is https://github.com/styler00dollar/VSGAN-tensorrt-docker. If you use Manjaro, it is also possible to pipe the data stream directly into mpv, so you can watch it in a video player without rendering a video. Yeah the model does seem a little noisy if you zoom in a lot, but don't forget that the model itself is only 1.2mb. I think it does quite well. I still try to improve on fast models, but this is good enough to share as a first model. Plz don't steal without credits, k thx. | ||
+ | | RealESRGANv2-animevideo-xsx2.pth | ||
+ | (Teacher: RealESRGANv2-animevideo-xsx2.pth) | ||
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/980550564725260358/compare.png Sample 1] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/980550565354410066/unknown.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/980550565723529226/compare2.webp Sample 3] | ||
|- | |- | ||
|- | |- | ||
− | | [https://github.com/Bubblemint864/AI-Models/releases/tag/2x_Bubble_AnimeScale_Compact_v1 2x_Bubble_AnimeScale_Compact_v1] | + | | <small>[https://github.com/Bubblemint864/AI-Models/releases/tag/2x_Bubble_AnimeScale_Compact_v1 2x_Bubble_AnimeScale_Compact_v1]</small> |
| Bubblemint#6472 | | Bubblemint#6472 | ||
| 2x | | 2x | ||
Line 694: | Line 793: | ||
| 4x_muy4_035_1.pth | | 4x_muy4_035_1.pth | ||
| https://imgsli.com/MTM0MzMx | | https://imgsli.com/MTM0MzMx | ||
+ | |||
https://imgsli.com/MTM0MzM3 | https://imgsli.com/MTM0MzM3 | ||
+ | |||
https://imgsli.com/MTM0MzQw | https://imgsli.com/MTM0MzQw | ||
|- | |- | ||
− | | [https://github.com/Bubblemint864/AI-Models/releases/tag/2x_Bubble_AnimeScale_SwinIR_Small_v1 | + | | <small>[https://github.com/Bubblemint864/AI-Models/releases/tag/2x_Bubble_AnimeScale_SwinIR_Small_v1 2x_Bubble_AnimeScale_SwinIR_Small_ v1]</small> |
| Bubblemint#6472 | | Bubblemint#6472 | ||
| 2x | | 2x | ||
Line 705: | Line 806: | ||
| Anime or Text | | Anime or Text | ||
| 2022-11-13 | | 2022-11-13 | ||
− | | | + | | 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. |
| None | | None | ||
| https://imgsli.com/MTM2MjAx | | https://imgsli.com/MTM2MjAx | ||
+ | |||
https://imgsli.com/MTM2MjAy | https://imgsli.com/MTM2MjAy | ||
+ | |||
https://imgsli.com/MTM2MjAz | https://imgsli.com/MTM2MjAz | ||
Line 719: | Line 822: | ||
| Anime / Visual Novel Art | | Anime / Visual Novel Art | ||
| 2022-12-17 | | 2022-12-17 | ||
− | | Third iteration of my eroge upscaling model. Discriminator: https://drive.google.com/file/d/18q-4ktFNZ8tPjkszuoG6kVBhCjKl8iFa/view?usp=sharing | + | | Third iteration of my eroge upscaling model. Discriminator: [https://drive.google.com/file/d/18q-4ktFNZ8tPjkszuoG6kVBhCjKl8iFa/view?usp=sharing Google Drive] |
| | | | ||
| https://slow.pics/c/fqjAhnjH | | https://slow.pics/c/fqjAhnjH | ||
Line 733: | Line 836: | ||
| Upscaling cel animation. Trained this more than a year ago, releasing cause I've got a much better v2 and v3 now. | | Upscaling cel animation. Trained this more than a year ago, releasing cause I've got a much better v2 and v3 now. | ||
| 4xPSNR | | 4xPSNR | ||
− | | https://slow.pics/c/UrnFYuXX https://slow.pics/c/zy1Kd841 | + | | https://slow.pics/c/UrnFYuXX |
+ | |||
+ | https://slow.pics/c/zy1Kd841 | ||
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/folder/XZgSmAoa#KNKbXZVBDq4UD1NJLHm1oQ 2x / 4x-anifilm_compact] |
− | | | + | | [[User:Kim2091|Kim2091]] |
− | | 2x | + | | 2x and 4x |
| CC BY-NC-SA 4.0 | | CC BY-NC-SA 4.0 | ||
− | | | + | | Compact |
− | | | + | | Animation |
− | | 2022- | + | | 2022-08-02 |
− | | This is | + | | 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. |
− | | | + | |
− | | [https://cdn.discordapp.com/attachments/ | + | 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. | ||
+ | | 4x_Compact_Pretrain.pth | ||
+ | | 2x Comparison: | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/903415274521374750/1004152057739087972/1659478894.4425747.png Sample 1] | ||
+ | |||
+ | [https://imgsli.com/MTE5MjUz Slider Comparison 1] | ||
+ | |||
+ | 4x Comparison: | ||
− | + | [https://imgsli.com/MTE5MjU0 Sample 2] | |
− | |||
− | |||
− | |||
− | |||
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+ | [https://cdn.discordapp.com/attachments/903415274521374750/1004158991544365097/1659480539.543144.png Slider Comparison 2] | ||
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/file/xI8D2SCJ#oQ0h3k9lemeNJcuysJql7z55WV_NhOsKRpzpErIhcGc LD-Anime_Compact] |
− | | | + | | Zarxrax / Skr |
− | | | + | | 2x |
− | | | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | + | | Compact |
− | | | + | | Animation |
− | | | + | | 2022-12-22 |
− | | | + | | 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. |
− | | | + | | 2x_Compact_Pretrain.pth |
− | | | + | | https://imgsli.com/MTQyMzM3/0/1 |
+ | |||
|- | |- | ||
+ | | [https://mega.nz/file/wdszCQRZ#bs7VIgvjgRiKiL5JVPqzCLlNl0kIQnDeD48-6ltWSLw Futsuu Anime] | ||
+ | | Zarxrax | ||
+ | | 2x | ||
+ | | WTFPL | ||
+ | | Compact | ||
+ | | Animation | ||
+ | | 2023-1-18 | ||
+ | | 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. | ||
+ | | 2x_Compact_Pretrain.pth | ||
+ | | https://imgsli.com/MTQ4MDM2/ | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1bwJpBHynGTIedIaZwp5XapCrJjO4BruF/view?usp=share_link 2xGT-evA.pth] |
− | | | + | | evA-01 |
| 2x | | 2x | ||
| CC BY-NC-SA 4.0 | | CC BY-NC-SA 4.0 | ||
− | | ESRGAN | + | | Real-ESRGAN Compact |
− | | Anime | + | | Anime or Text |
− | | 2022- | + | | 2022-12-14 |
− | | | + | | 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. |
− | | | + | | 2x_Compact_Pretrain.pth |
− | | [https:// | + | | [https://cdn.discordapp.com/attachments/579685650824036387/1051753650051088384/test_6.png Sample 1] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/1051753650428588092/test_2.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/1051753651011600444/test3.png Sample 3] | ||
− | + | [https://cdn.discordapp.com/attachments/579685650824036387/1051753651376504842/test_3.png Sample 4] | |
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/drive/folders/13PhLXD3Pvo1A7LwHGIeY_ekObva_333e?usp=share_link 1xEpsilon-one-compact.pth] |
− | | | + | | evA-01 |
− | | | + | | 1x |
− | | | + | | CC BY-NC-SA 4.0 |
− | | ESRGAN | + | | Real-ESRGAN Compact |
− | | Anime | + | | Anime or Text |
− | | | + | | 2022-12-03 |
− | | This model is | + | | 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. |
− | | | + | | 1x_Compact_Pretrain.pth |
− | | | + | | https://imgsli.com/MTM3Mzgz/2/3 |
− | + | ||
+ | https://imgsli.com/MTM3Mzg1/2/3 | ||
+ | |||
+ | https://imgsli.com/MTM3Mzg2/0/1 | ||
+ | |||
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/open?id=1H3F8OVBnK2cd5NjbCyc3tGwTZJBF1gk7 Sol Levante NTSC2HD] |
− | | | + | | Phoenix |
− | | | + | | 4x |
− | | | + | | UNLICENSE |
| ESRGAN | | ESRGAN | ||
| Anime/Pretrained | | Anime/Pretrained | ||
| 2020-04-08 | | 2020-04-08 | ||
− | | Anime | + | | NTSC DVD-spec encode x4 scale super-resolution for Anime Drawing style content. The dataset has a LOT of data throughout almost every frame, so it had a lot of stuff to learn. The resulting DVD-spec encode also had some blocking at times so it also learned to fight off blocking. |
− | | | + | | RRDB_PSNR_x4 |
| | | | ||
|- | |- | ||
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|- | |- | ||
− | | [https:// | + | | <small>[https://mega.nz/file/taBFxAAR#6wW-DrGh6oy2uz6aAKJpa36ngE2eKcDNA8Psy11oK10 2x_AnimeClassics_UltraLite_510K]</small> |
− | | | + | | CG1989 |
| 2x | | 2x | ||
− | | | + | | CC BY-NC-SA 4.0 |
| ESRGAN | | ESRGAN | ||
− | | Anime | + | | Anime/Pretrained |
− | | | + | | 2022-03-08 |
− | | | + | | 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. |
− | | | + | | 2X_DigitalFilmV5_Lite.pth |
+ | | [https://imgsli.com/OTg3MjM Sample 1] | ||
+ | |||
+ | [https://imgsli.com/OTg3MjQ Sample 2] | ||
+ | |||
+ | [https://imgsli.com/OTg3MjU Sample 3] | ||
+ | |||
+ | [https://imgsli.com/OTg3Nzg Sample 4] | ||
− | |||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/file/d/1DRyqqy24OU6G_mwsGjy6Zaxan_Fy1LNU/view?usp=sharing 600k] [https://drive.google.com/file/d/1psKp2DLWscPmDuzSTC8XqXL0LWnWuTYs/view?usp=sharing 650k] BooruGan |
+ | | Tal | ||
| 4x | | 4x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
| Anime | | Anime | ||
− | | | + | | 2021-11-26 |
− | | This model | + | | This model is designed to mainly upscale anime artworks. If you have issues with chroma then try the 600k iterations release. |
− | | | + | | 4x_Manga109Attempt |
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/913500929012150323/4f012e36d686033b274261295da89b32-comparison.jpg Sample 1] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/913500929356070912/256x256fdbb-comparison.jpg Sample 2] | ||
− | + | [https://cdn.discordapp.com/attachments/579685650824036387/913500929649688617/franky-super-810x456-comparison.jpg Sample 3] | |
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/file/d/1FWzEgqaSg2z0qOSjcmAxEUB3clEkm1PG/view 2x_Byousoku_5_Centimeter.pth] |
+ | | Mystery_Bullet#0642 (Shady Adel) | ||
| 2x | | 2x | ||
− | |[https:// | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
| ESRGAN | | ESRGAN | ||
− | | Anime | + | | Anime/Pretrained |
− | | 2020- | + | | 2020-04-08 |
− | | | + | | Anime landscape upscale. Trained on Frames from BluRay of Byousoku 5 Centimeter |
− | | | + | | [https://mega.nz/#!vtgSWKQT!K7Asn2zKe4N70R2aV89KEMTKhH3aiyGAAiuQDJF09qs 2xESRGAN] |
+ | | | ||
+ | |- | ||
− | | https:// | + | | [https://1fichier.com/?tsmmdifzgwkwtdfcc5uo 4x_OLDIES_290000_G_FINAL] |
− | + | | solidd93110 | |
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| 4x | | 4x | ||
| WTFPL | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
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| Anime | | Anime | ||
− | | 2020- | + | | 2020-08-16 |
− | | | + | | i made this model to upscale old anime and denoise. |
− | | | + | | RRDB_PSNR_x4.pth |
| | | | ||
|- | |- | ||
− | + | | [https://www23.zippyshare.com/v/lhOStpVa/file.html fidelbd_pokemodel] | |
− | | [https:// | ||
| Neo-Raws#4055 | | Neo-Raws#4055 | ||
| 2x | | 2x | ||
Line 913: | Line 1,008: | ||
| ESRGAN | | ESRGAN | ||
| Anime | | Anime | ||
− | | 2020- | + | | 2020-08-29 |
− | | | + | | Made this model to upscale old anime that looks blurry. |
− | | | + | | 2xESRGAN |
− | | https://imgsli.com/ | + | | https://imgsli.com/MjExMjQ/ |
|- | |- | ||
− | + | | <small>[https://1fichier.com/?u7kwdxdn6uljha3icte8 4x_OLDIES_ALTERNATIVE_FINAL.pth]</small> | |
− | | [https://1fichier.com/? | ||
| solidd93110 | | solidd93110 | ||
− | | | + | | 4x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
| Anime | | Anime | ||
− | | 2020- | + | | 2020-09-01 |
− | | | + | | This model was made for my project captain tsubasa anime so i don't know if it works good for anything else. just try it ;) |
− | + | | RRDB_PSNR_x4.pth | |
− | | https://imgsli.com/ | + | |
+ | | https://imgsli.com/MjEzMDU | ||
|- | |- | ||
− | | [https://1fichier.com/? | + | | [https://1fichier.com/?cnw3fwws08tdoaxycimj 2x_SHARP_ANIME_V1] |
| solidd93110 | | solidd93110 | ||
| 2x | | 2x | ||
Line 939: | Line 1,034: | ||
| ESRGAN | | ESRGAN | ||
| Anime | | Anime | ||
− | | 2020-12 | + | | 2020-09-12 |
− | | | + | | this model has been trained to work on lines and details - works well on animes which have fairly fine lines at the base but also the video must be progressive or deinterlaced |
− | | | + | | 2xPSNR.pth |
− | | https://imgsli.com/ | + | |
+ | | https://imgsli.com/MjIwMDY | ||
|- | |- | ||
− | + | | [https://s.katou.pw/4x_MeguUp_150000_G.pth MeguUp] | |
− | | [https:// | + | | katoumegumi_#3231 |
− | | |[ | + | | |
− | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3]. | |
− | + | | ESRGAN | |
− | | ESRGAN | ||
| Anime | | Anime | ||
− | | | + | | 2020-09-16 |
− | | | + | | Upscaling of lossless (uncompressed) anime art. |
− | | | + | | Interpolated custom, hence the license. |
− | | https:// | + | | SYNLA: LyonHrt (bloc97 dataset, MIT license). |
+ | Fatal Pixels, Fatality Anime: twittman (CC BY-NC-SA 4.0, acquired special permission to relicense. [https://s.katou.pw/Discord_dPUiI1x3Pf.png Screencap]). | ||
+ | Deviance: BlackScout (GNU GPLv3) | ||
+ | |- | ||
+ | |||
+ | | [https://icedrive.net/1/43GNBihZyi NMKD UltraYandere] | ||
+ | | |[[User:nmkd|Nmkd]] | ||
+ | | 4x | ||
+ | | WTFPL | ||
+ | | ESRGAN | ||
+ | | Art/Anime | ||
+ | | 2020-10-08 | ||
+ | | Highly flexible 2D Art upscaling | ||
+ | | 4xESRGAN | ||
+ | | | ||
|- | |- | ||
− | | [https://icedrive.net/1/ | + | |
+ | | [https://icedrive.net/1/43GNBihZyi NMKD UltraYandere Lite] | ||
| |[[User:nmkd|Nmkd]] | | |[[User:nmkd|Nmkd]] | ||
| 4x | | 4x | ||
| WTFPL | | WTFPL | ||
− | | ESRGAN | + | | ESRGAN Lite [nf=32 nb=12] |
| Anime | | Anime | ||
− | | | + | | 2020-10-15 |
+ | | Fast Anime/Art upscaling | ||
+ | | 4x_DIV2K-Lite | ||
+ | |||
| | | | ||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | [https://www115.zippyshare.com/v/O2do1VCf/file.html 2x_pokemodel_lite_100000_G] |
− | | | + | | Neo-Raws#4055 |
| 2x | | 2x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | Anime |
− | | | + | | 2020-11-01 |
− | | | + | | Upscale old anime like pokemon |
| none | | none | ||
− | |||
− | |||
− | | | + | | https://imgsli.com/Mjc3Nzk |
− | + | ||
− | + | https://imgsli.com/Mjc3Nzg | |
− | + | ||
− | + | https://imgsli.com/Mjc3ODA | |
− | + | ||
− | + | https://imgsli.com/Mjc3ODE | |
− | + | ||
− | + | https://imgsli.com/Mjc3ODI | |
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− | | [https:// | + | | [https://1fichier.com/?020t1y83kjrusd95dh0a 2x_SHARP_ANIME_V2] |
− | | | + | | solidd93110 |
| 2x | | 2x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Anime |
− | | | + | | 2020-12-09 |
− | | | + | | 2x_PSNR.pth |
− | | | + | | |
− | | https://imgsli.com/ | + | | https://imgsli.com/MzI0MDk |
|- | |- | ||
− | | [https:// | + | | [https://1fichier.com/?23hzkj20isef5b75cw3y 2x_BIGOLDIES_415000_G.pth] |
− | | | + | | solidd93110 |
| 2x | | 2x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
| Anime | | Anime | ||
− | | | + | | 2020-12-09 |
− | | | + | | upscaling old anime. help to denoise and find lines and dehalo |
− | | | + | | 2x_PSNR.pth |
− | | https:// | + | | https://imgsli.com/MzI0MDc |
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://icedrive.net/1/f0UAiRqz3N NMKD YandereNeo] |
+ | | |[[User:nmkd|Nmkd]] | ||
+ | | 2x | ||
+ | | WTFPL | ||
+ | | ESRGAN (Lite) | ||
+ | | Anime | ||
+ | | 2021-01-26 | ||
+ | | | ||
+ | | | ||
+ | | https://i.imgur.com/oxs71v5.png | ||
+ | |||
+ | |||
+ | |- | ||
+ | | [https://icedrive.net/1/f0UAiRqz3N NMKD YandereNeo] | ||
+ | | |[[User:nmkd|Nmkd]] | ||
| 4x | | 4x | ||
| WTFPL | | WTFPL | ||
− | | ESRGAN | + | | ESRGAN (Lite) |
| Anime | | Anime | ||
− | | 2021- | + | | 2021-01-26 |
− | |||
| | | | ||
− | | | + | | 4x_DIV2K-Lite_1M |
+ | | https://i.imgur.com/oxs71v5.png | ||
|- | |- | ||
− | | [https:// | + | | [https://u.pcloud.link/publink/show?code=XZRAmuXZRy3vkvvBdTftheNOFeJ0tLLv74eX 2x_Waifaux-NL3-SuperLite] |
− | | | + | | Joey |
− | | | + | | 2x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | |||
− | |||
| | | | ||
− | | | + | | 2021-02-23 |
+ | | Trained this model to see how it would work trying to essentially get the same results as Waifu2x but with ESRGAN | ||
+ | | none | ||
| | | | ||
|- | |- | ||
− | |||
− | = | + | | [https://u.pcloud.link/publink/show?code=XZPLWuXZbQz9nPrUhlytIN0ne4UjyzQRMHmX 2x_Waifaux-NL3-SRResNet] |
− | + | | Joey | |
+ | | 2x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | EDSR (SRResNet) | ||
+ | | | ||
+ | | 2021-02-25 | ||
+ | | Emulating Waifu2x at Noise Level 3 NOTE: You can't use this with regular esrgan forks or the bot, it has to be run through basicsr | ||
+ | | none | ||
+ | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | | [https://u.pcloud.link/publink/show?code=kZcUlBXZ9egcFjtf3cjX02lDqNAr5j4l3jFX 4x_Training4Melozard_Anime] | |
− | | [https:// | + | | Joey |
− | | | ||
| 4x | | 4x | ||
− | | | + | | Whatever @B.Melozard2 wants |
| ESRGAN | | ESRGAN | ||
− | | | + | | Anime |
− | | | + | | 2021-03-17 |
− | | | + | | |
− | | | + | | RRDB_ESRGAN_x4_old_arch |
− | | | + | | |
|- | |- | ||
− | + | | [https://drive.google.com/file/d/18iWj4eWiMfUd2WyLCEzMlZK1JVT7L8nT/view?usp=sharing 2x_LD-Anime_Skr_v1.0] | |
− | | [https:// | + | | Skr |
− | | | + | | 2x |
− | | | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Denoise/Dehalo |
− | | | + | | 2021-04-17 |
− | | | + | | Denoise, dehalo, derainbow old anime |
− | | | + | | 2xESRGAN |
− | | | + | | https://imgsli.com/NTA3MDU/ |
|- | |- | ||
+ | | [https://drive.google.com/drive/u/4/folders/19IQNM5Vo5vGcoKaRJaRrLScfxBbFBVff 2x_KemonoScale_v2] | ||
+ | | EzoGaming | ||
+ | | 2x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Anime | ||
+ | | 2021-06-05 | ||
+ | | Upscaling frames from Irodori anime (namely kemono friends) from 540p (the source render resolution) to 1080p, low resolution flat shaded art, de-JPEG of the aforementioned | ||
+ | | x2_CGIMaster_v1 | ||
+ | | [https://cdn.discordapp.com/attachments/705815801290293329/850614850735439892/unknown.png Sample] | ||
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://s.katou.pw/4x_muy4_035_1.pth 4x_muy4_035_1.pth] |
+ | | katoumegumi_ | ||
| 4x | | 4x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | Anime |
− | | | + | | 2021-07-18 |
− | | | + | | Upscaling of anime art (Specifically visual novel CG art) |
− | + | | | |
− | + | | [https://cdn.knightlab.com/libs/juxtapose/latest/embed/index.html?uid=278999ec-e802-11eb-abb7-b9a7ff2ee17c Sample 1] | |
− | + | ||
+ | (Hakurei Reimu from Touhou Project illustrated by "okawa friend") | ||
+ | |||
+ | [https://cdn.knightlab.com/libs/juxtapose/latest/embed/index.html?uid=f3d4781a-e801-11eb-abb7-b9a7ff2ee17c Sample 2] | ||
+ | |||
+ | (Kitaooji Karen from Making * Lovers developed by SMEE.)(edited) | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1bqyG9llxkJ6i6MJTaNUiSgSXtrlPi0d7/view Falcon Fanart] |
− | | | + | | |[[User:LyonHrt|LyonHrt]] |
− | | | + | | 4x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
| ESRGAN | | ESRGAN | ||
− | | Anime | + | | Anime |
− | | | + | | not on discord |
− | | | + | | |
+ | | 4xPSNR | ||
| | | | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
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− | |||
− | |||
− | |||
− | |||
|- | |- | ||
Line 1,161: | Line 1,255: | ||
| Improvement of low-quality cartoons from broadcast sources. | | 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. | | 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. | ||
− | | [https://imgsli.com/OTg0MjA/6/7 Sample 1] [https://imgsli.com/OTc1OTg/2/3 Sample 2] [https://imgsli.com/OTg0Mjc/0/1 Sample 3] | + | | [https://imgsli.com/OTg0MjA/6/7 Sample 1] |
+ | |||
+ | [https://imgsli.com/OTc1OTg/2/3 Sample 2] | ||
+ | |||
+ | [https://imgsli.com/OTg0Mjc/0/1 Sample 3] | ||
|- | |- | ||
Line 1,173: | Line 1,271: | ||
| In addition to removing the vertical blur, the model upscales, sharpens and will remove MPEG-2 artifacting and a small amount of rainbowing and dot crawl. Another series afflicted with the vertical blur is Avatar the Last Airbender, which can be repaired by this model. The video fed into the model MUST be 540 vertical for the deblur to work properly. | | In addition to removing the vertical blur, the model upscales, sharpens and will remove MPEG-2 artifacting and a small amount of rainbowing and dot crawl. Another series afflicted with the vertical blur is Avatar the Last Airbender, which can be repaired by this model. The video fed into the model MUST be 540 vertical for the deblur to work properly. | ||
| 2xESRGAN | | 2xESRGAN | ||
− | | https://imgsli.com/NzM2MDY https://imgsli.com/ODIxMjU | + | | https://imgsli.com/NzM2MDY |
+ | |||
+ | https://imgsli.com/ODIxMjU | ||
|- | |- | ||
Line 1,199: | Line 1,299: | ||
| 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. | | 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. | ||
| [https://cdn.discordapp.com/attachments/903415274521374750/999820017652740176/1658446060.8526323.png Sample 1] | | [https://cdn.discordapp.com/attachments/903415274521374750/999820017652740176/1658446060.8526323.png Sample 1] | ||
+ | |||
[https://cdn.discordapp.com/attachments/903415274521374750/999821036583391292/1658446301.0955725.png Sample 2] | [https://cdn.discordapp.com/attachments/903415274521374750/999821036583391292/1658446301.0955725.png Sample 2] | ||
+ | |||
[https://cdn.discordapp.com/attachments/903415274521374750/999821212718993478/1658446346.8536465.png Sample 3] | [https://cdn.discordapp.com/attachments/903415274521374750/999821212718993478/1658446346.8536465.png Sample 3] | ||
+ | |||
[https://cdn.discordapp.com/attachments/903415274521374750/999820756043169803/1658446237.0734627.png Sample 4] | [https://cdn.discordapp.com/attachments/903415274521374750/999820756043169803/1658446237.0734627.png Sample 4] | ||
|- | |- | ||
|- | |- | ||
− | | [https://mega.nz/folder/eBwyyKbA#CApT1_CrbpGBymLmc-FCTQ 2x-UniScale_CartoonRestore-lite] | + | | <small>[https://mega.nz/folder/eBwyyKbA#CApT1_CrbpGBymLmc-FCTQ 2x-UniScale_CartoonRestore-lite]</small> |
| [[User:Kim2091|Kim2091]] | | [[User:Kim2091|Kim2091]] | ||
| 2x | | 2x | ||
Line 1,216: | Line 1,319: | ||
| Comparisons: | | Comparisons: | ||
[https://cdn.discordapp.com/attachments/880826637543964712/882136618461458462/unknown.png Sample 1] | [https://cdn.discordapp.com/attachments/880826637543964712/882136618461458462/unknown.png Sample 1] | ||
+ | |||
[https://cdn.discordapp.com/attachments/880826637543964712/882136455999262750/unknown.png Sample 2] | [https://cdn.discordapp.com/attachments/880826637543964712/882136455999262750/unknown.png Sample 2] | ||
+ | |||
[https://cdn.discordapp.com/attachments/880826637543964712/882136979410673684/unknown.png Sample 3] | [https://cdn.discordapp.com/attachments/880826637543964712/882136979410673684/unknown.png Sample 3] | ||
+ | |||
[https://cdn.discordapp.com/attachments/649861104645701637/882121519973666886/unknown.png Sample 4] | [https://cdn.discordapp.com/attachments/649861104645701637/882121519973666886/unknown.png Sample 4] | ||
+ | |||
[https://cdn.discordapp.com/attachments/649861104645701637/882124248368427078/unknown.png Sample 5] | [https://cdn.discordapp.com/attachments/649861104645701637/882124248368427078/unknown.png Sample 5] | ||
+ | |||
[https://cdn.discordapp.com/attachments/880826637543964712/882110147676221480/Spongebob_UniScale_CartoonRestore.mp4 Video Sample] | [https://cdn.discordapp.com/attachments/880826637543964712/882110147676221480/Spongebob_UniScale_CartoonRestore.mp4 Video Sample] | ||
+ | |||
[https://cdn.discordapp.com/attachments/547949806761410560/881971445813633044/Spongebob_Original.mp4 Original Video] | [https://cdn.discordapp.com/attachments/547949806761410560/881971445813633044/Spongebob_Original.mp4 Original Video] | ||
|- | |- | ||
− | | [https://www108.zippyshare.com/v/PYWFtETd/file.html 2x_ATLA_KORRA_336200_G.pth] | + | | <small>[https://www108.zippyshare.com/v/PYWFtETd/file.html 2x_ATLA_KORRA_336200_G.pth]</small> |
| aptitude | | aptitude | ||
| 2x | | 2x | ||
Line 1,233: | Line 1,342: | ||
| Upscaling of Animation based on The Legend of Korra. | | Upscaling of Animation based on The Legend of Korra. | ||
| 2xESRGAN.pth | | 2xESRGAN.pth | ||
− | | https://imgsli.com/NjIzMzU https://imgsli.com/NjIzMTY https://imgsli.com/NjIzMTc https://imgsli.com/NjIzMTg https://imgsli.com/NjIzMTk https://imgsli.com/NjIzMjA https://imgsli.com/NjIzMjE https://imgsli.com/NjIzMjQ https://imgsli.com/NjIzMjc https://imgsli.com/NjIzMjY https://imgsli.com/NjIzMjU | + | | https://imgsli.com/NjIzMzU |
+ | |||
+ | https://imgsli.com/NjIzMTY | ||
+ | |||
+ | https://imgsli.com/NjIzMTc | ||
+ | |||
+ | https://imgsli.com/NjIzMTg | ||
+ | |||
+ | https://imgsli.com/NjIzMTk | ||
+ | |||
+ | https://imgsli.com/NjIzMjA | ||
+ | |||
+ | https://imgsli.com/NjIzMjE | ||
+ | |||
+ | https://imgsli.com/NjIzMjQ | ||
+ | |||
+ | https://imgsli.com/NjIzMjc | ||
+ | |||
+ | https://imgsli.com/NjIzMjY | ||
+ | |||
+ | https://imgsli.com/NjIzMjU | ||
|- | |- | ||
Line 1,251: | Line 1,380: | ||
|- | |- | ||
− | | [https://drive.google.com/file/d/1dT7Pw0iwPkQC4-rWriibrVLuA3KS3pS4/view | + | | <small>[https://drive.google.com/file/d/1dT7Pw0iwPkQC4-rWriibrVLuA3KS3pS4/view Spongebob (4x_SpongeBob_235000_G / 4xSpongebob)]</small> |
| Joey | | Joey | ||
| 4x | | 4x | ||
Line 1,312: | Line 1,441: | ||
|- | |- | ||
− | | [https://drive.google.com/open?id=1D3AjglmYlQ2HGda7iw4JXckSGbVBqsQr SpongeBob.CEL.2.HD.125ki.499e-PHOENiX.pth] | + | | <small>[https://drive.google.com/open?id=1D3AjglmYlQ2HGda7iw4JXckSGbVBqsQr SpongeBob.CEL.2.HD.125ki.499e-PHOENiX.pth]</small> |
| Phoenix | | Phoenix | ||
| 4x | | 4x | ||
Line 1,359: | Line 1,488: | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | <small>[https://drive.google.com/file/d/1i68bWo7xh3JPFIO-zLv9UMD72E-5xNr_/view American Dad 2 (American.Dad.2.HD.150ki.5e-PHOENiX.pth)]</small> |
− | | | + | | PHEONiX (?) |
| 4x | | 4x | ||
− | | | + | | |
| ESRGAN | | ESRGAN | ||
− | | | + | | Animation |
− | | | + | | |
− | | | + | | American Dad |
− | | | + | | |
| | | | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://de-next.owncube.com/index.php/s/jYnFtncarkBmpcF FatalimiX] |
+ | | |[[User:Twittman|Twittman]] | ||
| 4x | | 4x | ||
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
| ESRGAN | | ESRGAN | ||
− | | | + | | Animation |
− | | | + | | 2019-10-29 |
− | | | + | | Comic and Cartoon style images |
− | | | + | | 4x_Fatality_MKII_90000_G_02.pth |
| | | | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/open?id=1qjpxp8z4FGLZxieUDEVKd6FDum-8vpvJ Comic Book] |
− | | | + | | |[[User:LyonHrt|LyonHrt]] |
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | | 4x |
− | | ESRGAN | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | + | | ESRGAN |
− | | | + | | Animation |
− | | | + | | |
− | | | + | | Comic / Drawings. Trained on Custom (Spider-Man) dataset |
+ | | none (no interpolation) | ||
| | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | | [https://de-next.owncube.com/index.php/s/x99pKzS7TNaErrC Fatal_Anime] | |
− | | [https:// | + | | |[[User:Twittman|Twittman]] |
− | | | + | | 4x |
− | | | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | | ESRGAN |
− | | ESRGAN | + | | Animation |
− | | | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
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− | |||
− | |||
− | |||
− | |||
| | | | ||
− | | | + | | Trained on Anime and Manga images |
− | + | | none (no interpolation) | |
− | |||
− | |||
− | | | ||
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [ | + | | [http://cloud.mitch.best/index.php/s/iio9SL9BdgWiCoi 4x_AbeScale] |
− | | | + | | |[[User:mitch#1337|mitch#1337]] |
| 4x | | 4x | ||
− | | | + | | GNU |
| ESRGAN | | ESRGAN | ||
− | | | + | | Linework Cartoons |
− | | | + | | |
− | | | + | | Dataset: LR: Clone High DVD, HR: Re-illustrated Vectors from Frames |
− | | | + | | [https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] |
| | | | ||
|- | |- | ||
− | |||
− | + | |- | |
+ | | <small>[https://mega.nz/file/9dJFjYrT#LY4Op8myZGJsh6ytUvF6ITVGXpx8XODN_AG-kzvWg4Y 2x_Loyaldk-SuperPony_370000 V1.0]</small> | ||
+ | | ChaseMMD | ||
+ | | 2x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Animation | ||
+ | | 2021-02-24 | ||
+ | | Upscale MLP episodes | ||
+ | | 2x_ERGAN | ||
+ | | https://imgsli.com/NDIwNTY | ||
+ | |||
+ | https://imgsli.com/NDIwNTg | ||
+ | |||
+ | https://imgsli.com/NDIwNjE | ||
+ | |||
+ | https://imgsli.com/NDIwNjI | ||
− | + | https://imgsli.com/NDIwNjM | |
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | <small>[https://mega.nz/file/RYxGEKRL#nTe0Zy2gB9e9QF5T8UhJSla1oEPQjSCXAB0BpNrTrRk 2x_Loyaldk-LitePony_380500 V1.0]</small> |
− | | | + | | ChaseMMD |
− | | | + | | 2x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
| Animation | | Animation | ||
+ | | 2021-03-01 | ||
+ | | Upscale MLP episodes. Liter version. | ||
+ | | 2x_ESRGAN | ||
| | | | ||
− | + | |- | |
− | |||
− | |||
− | |- | ||
|- | |- | ||
− | | [https:// | + | | <small>[https://mega.nz/file/VM5WmLwb#QvO1n6w6llYRh8qauXXkXy4tElrBCwclCl5VHM3IH8M 2x_Loyaldk-LitePony_500000_V2.0]</small> |
− | | | + | | ChaseMMD#6957 |
− | | | + | | 2x |
− | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | ESRGAN | + | | ESRGAN (NF=32, NB=12) |
| Animation | | Animation | ||
− | | | + | | 2021-04-06 |
− | | | + | | Upscale MLP episodes. Liter version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. |
− | | | + | | none |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | <small>[https://mega.nz/file/YMwm0TbZ#agDBMDkswkpMM7FE1tDRlGX4zIOE4D0WBzcWudkN7Mc 2x_Loyaldk-MediumPony_500000_V2.0]</small> |
− | | | + | | ChaseMMD |
− | | | + | | 2x |
| [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
− | | ESRGAN | + | | ESRGAN (NF=48, NB=18) |
| Animation | | Animation | ||
− | | | + | | 2021-04-11 |
− | | | + | | Upscale MLP episodes. Liter version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. Leaves more blobs when converting detail to blobs compared to litepony |
− | | none | + | | none |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | <small>[https://mega.nz/file/hcoViIQQ#O1cmQ8FsLk5RAIP5lxB3Q2L0suh9IWX_dGHhuSuL9U4 4x_Loyaldk-LitePony_500000_V2.0]</small> |
− | | | + | | ChaseMMD |
| 4x | | 4x | ||
− | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | ESRGAN | + | | ESRGAN (NF=32, NB=12) |
| Animation | | Animation | ||
− | | | + | | 2021-04-12 |
− | | | + | | Good for Vector 2D art however converts detail to blobs. Quality seems weak with this one. However posting anyways to see if a use is found. |
− | | none | + | | none |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | <small>[https://mega.nz/file/IBhElRYJ#C_lVc8Vr2q8X6hEltJKD6I63U7oL_FDLeJgPh72AZmg 2x_Loyaldk-SuperPony_500000_V2.0]</small> |
− | | | + | | ChaseMMD |
− | | | + | | 2x |
− | | [https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Animation |
− | | | + | | 2021-04-30 |
− | | | + | | Upscale MLP episodes. Full version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. |
− | | | + | | none |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [ | + | | <small>[https://mega.nz/file/BMhUCbJZ#kYz0wvc26RW0n0f8AUXekW_ZCuRamKmh2-iWf1eefn0 4x_Loyaldk-SuperPony_500000_V2.0]</small> |
− | | | + | | ChaseMMD |
| 4x | | 4x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Animation |
− | | | + | | 2021-04-30 |
− | + | | Upscale MLP episodes. Full version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. | |
− | | | + | | none |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https://mega.nz/file/ | + | | <small>[https://mega.nz/file/lYo01DRI#HIiJ7M5YaXjwAb3zEbtSLzAI59iljwEX72Ad88CvUf0 4x_Loyaldk-MediumPony_500000_V2.0]</small> |
| ChaseMMD | | ChaseMMD | ||
− | | | + | | 4x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
| Animation | | Animation | ||
− | | 2021- | + | | 2021-04-30 |
− | | Upscale MLP episodes | + | | Upscale MLP episodes. Full version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. |
− | + | | none | |
− | + | | | |
|- | |- | ||
|- | |- | ||
− | | [https://mega.nz/ | + | | [https://mega.nz/folder/5UAlQCRJ#2Bj1lq8PYeB3P9k5UKSvkQ Platoon Model Set] |
| ChaseMMD | | ChaseMMD | ||
− | | | + | | 4x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
| Animation | | Animation | ||
− | | 2021- | + | | 2021-06-07 |
− | | Upscale | + | | 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. |
− | | | + | | Pony Models |
| | | | ||
|- | |- | ||
+ | |} | ||
+ | |||
+ | =====Anime and Cartoon Restoration===== | ||
+ | |||
+ | {| class="wikitable sortable" | ||
|- | |- | ||
− | + | ! Model Name | |
− | + | ! Author | |
− | + | ! Scale | |
− | + | ! License | |
− | + | ! Architecture | |
− | + | ! Purpose (short) | |
− | + | ! Date Posted | |
− | + | ! Purpose (Full) | |
− | + | ! Pretrained_Model_G | |
− | + | ! Sample | |
|- | |- | ||
|- | |- | ||
− | | [https://mega.nz/file/ | + | | [https://mega.nz/file/MZdEja6I#ao8L6INGvzns4IlDpyzjpuzR-kIqm_VrC3Q8pUTZncM 1x_HurrDeblur_SuperUltraCompact] |
− | | | + | | Zarxrax |
− | | | + | | 1x |
− | | | + | |[http://www.wtfpl.net WTFPL] |
− | | | + | | Compact |
+ | [nf:24 nc:8] | ||
| Animation | | Animation | ||
− | | | + | | 2022-06-04 |
− | | | + | | 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. | ||
| | | | ||
− | | | + | | https://imgsli.com/MTEwOTg4 |
+ | https://imgsli.com/MTEwOTY2 | ||
+ | |||
+ | https://imgsli.com/MTEwOTY5 | ||
+ | |||
+ | https://imgsli.com/MTEwOTcx | ||
|- | |- | ||
− | | [https://mega.nz/file/ | + | |
− | | | + | | [https://mega.nz/file/9INFwYLD#KlV11g5yDG6fWWdZDXhztnsqhuLSIUP7-Upq3szgMCQ 1x_AnimeUndeint_Compact] |
− | | | + | | Zarxrax |
− | |[ | + | | 1x |
− | | | + | |[http://www.wtfpl.net WTFPL] |
+ | | Compact | ||
| Animation | | Animation | ||
− | | | + | | 2022-06-05 |
− | | | + | | 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. |
− | |||
| | | | ||
+ | | https://imgsli.com/MTExMTE0 | ||
+ | |||
+ | https://imgsli.com/MTExMTE1 | ||
+ | |||
+ | https://imgsli.com/MTExMTE2 | ||
+ | |||
+ | https://imgsli.com/MTExMTE3 | ||
|- | |- | ||
− | + | | [https://mega.nz/file/lNdTmSKD#R7GIISShx-zsUVwDHw0oosv72ifbB31GClXXV3UtLLo 1x_BleedOut_Compact] | |
− | | [https://mega.nz/file/ | + | | Zarxrax |
− | | | + | | 1x |
− | | | + | |[http://www.wtfpl.net WTFPL] |
− | |[ | + | | Compact |
− | | | ||
| Animation | | Animation | ||
− | | | + | | 2022-07-25 |
− | | | + | | 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. |
− | |||
| | | | ||
− | | | + | | https://imgsli.com/MTE4MjEz |
− | + | https://imgsli.com/MTE4MjE4 | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | https://imgsli.com/MTE4MjE5 | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | | [https://mega.nz/file/VQkDmSgb#dlVuJZQ__yAKdJaWA_4Nx52YU_c2qy_a2oG9_a98dO4 1x_Dotzilla_Compact] | |
− | | [https://mega.nz/ | + | | Zarxrax |
− | | | + | | 1x |
− | | | + | |[http://www.wtfpl.net WTFPL] |
− | |[ | + | | Compact |
− | | | ||
| Animation | | Animation | ||
− | | | + | | 2022-12-09 |
− | | | + | | Wipes out dot crawl and rainbows in animation. |
− | | | + | | 1x_Compact_Pretrain.pth |
− | | https:// | + | | https://imgsli.com/MTM4ODkz |
|- | |- | ||
|} | |} | ||
− | + | ====Digital Animation==== | |
− | ==== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 1,704: | Line 1,781: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https:// | + | | [https://u.pcloud.link/publink/show?code=XZQlqjXZPNgmLRJl5HLLG0M3VRmzmzmHr5hk 4x_DigitalFake-2.1] |
− | | | + | | Joey |
− | | | + | | 4x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Digital Animation |
− | | 2021-02- | + | | 2021-02-18 |
− | | | + | | Replica of DigitalFrames 2.1 but interpolatable |
− | | | + | | RRDB_ESRGAN_x4_old_arch.pth |
− | | | + | | |
|- | |- | ||
− | | [https://mega.nz/ | + | | [https://mega.nz/folder/QsUWWJjb#SIuqcPEzrkpLW0WNSth66g 4X_KCJPUNK_1.0233089 G.pth] |
− | | | + | | KCJPUNK |
| 4x | | 4x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Digital Animation |
− | | 2021-03- | + | | 2021-03-23 |
− | | | + | | Up-scaling Digital Animation |
− | | | + | | 4x_fatal_Anime_500000_G |
− | | | + | | |
|- | |- | ||
− | |||
+ | | [https://mega.nz/folder/4oVRHQaA#vE3Lplfetc9z9SJOxZD6nA 2X_KcjpunkAnime_2.0_Lite_196496_G] | ||
+ | | KCJPUNK | ||
+ | | 2x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN-lite | ||
+ | | Digital Animation | ||
+ | | 2021-03-23 | ||
+ | | Up-scaling Digital Animation | ||
+ | | This is my first attempt to make Light model so I started with 2x version. This model is much faster and give better results than my previous one. | ||
+ | | | ||
+ | |- | ||
− | + | | [https://mega.nz/file/XWpFzRID#398qZx763bMSBsPB2MfgZqROGxdB0VldrIgH_prwa7U 2x_DigitoonLite_216k] | |
− | + | | SaurusX | |
− | + | | 2x | |
− | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |
+ | | ESRGAN-lite | ||
+ | | Digital Animation | ||
+ | | 2022-07-05 | ||
+ | | 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. | ||
+ | | 2x_DigiGradients_Lite_486k.pth | ||
+ | | https://imgsli.com/MTE1Mzg4 | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | | [https://mega.nz/file/PfhxWCRT#R59B_ovEwdiojZbas76SCbUSv-uNd1ZSOdZ0vQp-6w4 2x_DigiGradients_Lite_486k] | |
− | |[https:// | + | | SaurusX |
− | | | + | | 2x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | + | | ESRGAN-lite |
− | | ESRGAN | + | | Digital Animation |
− | | | + | | 2022-08-24 |
− | | | + | | A very focused model meant for upscaling the TMNT 2003 DVDs. Degradations were added via AVISynth in order to match the video on the TMNT 2003 DVDs to correct the source problems. Problems corrected include aliased red chroma, chroma vertical blur, bad deinterlacing, banding, compression "grain", and poor animation line detail. The AVS scripts for the LR's were run through HCEnc to get authentic low bit rate MPEG-2 artifacts for fixing. By design, the final model gives a very digital-looking result and does not do a good job of retaining textures as the style of TMNT 2003 is all flats and gradients. |
− | | | + | | none |
− | | | + | | https://imgsli.com/MTAxNjc1 |
− | | | + | |
+ | https://imgsli.com/ODQ2NzI | ||
|- | |- | ||
− | + | | [https://mega.nz/file/lVUDRQYa#LVyZdRS1c1Vo7IQcDA9ivBplLqPYPWjl39px7mBKuFo 2x_DigitalFlim_SuperUltraCompact] | |
− | |[https:// | + | | Zarxrax |
− | | |[ | + | | 2x |
− | | | + | |[http://www.wtfpl.net WTFPL] |
− | + | | Compact | |
− | | | + | [nf:24 nc:8] |
− | | | + | | Animation |
+ | | 2022-05-14 | ||
+ | | 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. | ||
| | | | ||
− | | | + | | https://imgsli.com/MTA3ODYx |
− | + | ||
− | + | https://imgsli.com/MTA3ODY0 | |
− | |||
+ | https://imgsli.com/MTA3ODY2 | ||
− | + | https://imgsli.com/MTA3ODY3 | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
+ | |} | ||
+ | |||
+ | ====Manga==== | ||
+ | {| class="wikitable sortable" | ||
+ | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | | [https://drive.google.com/file/d/1uraeNuUPx46HKZ77xUI1PCBBoH-LhikY/view?usp=sharing FSMangaV2] | |
− | + | | Jacob_ | |
− | | [https://drive.google.com/ | + | | 4x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | ||
− | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Manga |
− | | | + | | 2020-12-14 |
− | | | + | | Manga-style images with or without dithering - cartoons, maybe pixel art, etc |
− | | | + | | RRDB_PSNR_x4 |
− | | | + | | https://i.imgur.com/oVBVthF.png |
|- | |- | ||
+ | |- | ||
+ | | [https://cdn.discordapp.com/attachments/450036622940045325/936099965300768808/4x_eula_digimanga_bw_v1_860k.pth 4x_eula_digimanga_bw_v1_860k] | ||
+ | | end user license agreement#9756 | ||
+ | | 4x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Manga | ||
+ | | 2022-1-26 | ||
+ | | Black and white digital manga with halftones. | ||
+ | | 4xPSNR | ||
+ | | [https://slow.pics/c/lp9O3GnZ Clean] | ||
− | + | [https://slow.pics/c/AxmHpF3m Heavy Degradation] | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | |- | |
− | |[https:// | + | | [https://cdn.discordapp.com/attachments/894310505622155264/1008498310597857290/4x_eula_digimanga_bw_v2_nc1_307k.pth 4x_eula_digimanga_bw_v2_nc1_307k] |
− | | | + | | end user license agreement#9756 |
− | | | + | | 4x |
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Manga |
− | | | + | | 2022-08-17 |
− | | | + | |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. |
− | | | + | | 4x_eula_digimanga_bw_v1_860k |
+ | | https://slow.pics/c/Asbu0xgz | ||
|- | |- | ||
+ | | [https://mega.nz/file/nR51EYYC#RcAKkxb8hAzvZAj4TLxnAukd9gbrYuUeyjUp2l1ffb8 MangaScaleV3] | ||
+ | | Bunzero++ | ||
+ | | 2x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN+ | ||
+ | | Manga | ||
+ | | 2021-05-24 | ||
+ | | To upscale manga including halftones, instead of trying to smooth them out. | ||
+ | | unreleased model | ||
+ | | https://imgsli.com/NTUyMjg | ||
+ | |- | ||
− | |[ | + | | [http://www.mediafire.com/file/w3jujtm752hvdj1/Manga109Attempt.pth.zip/file Manga109Attempt] |
− | | | + | | Kingdomakrillic |
− | | | + | | 4x |
− | |[https://creativecommons.org/licenses/by | + | | [https://creativecommons.org/licenses/by/4.0/ CC BY 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Anime / Manga |
− | | | + | | |
− | | | + | | Pretrained model: [https://drive.google.com/drive/folders/1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 4xPSNR] |
− | |||
| | | | ||
+ | | Manga109 | ||
|- | |- | ||
+ | |} | ||
− | + | ====Drawings==== | |
− | + | ||
− | + | {| class="wikitable sortable" | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
|- | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
− | | [https:// | + | |- |
− | | | + | | [https://www.dropbox.com/s/52hsqa7ymt5pgga/KDM003_scans_1x.pth KDM003_scans_1x.pth] |
+ | | BoxDrop | ||
| 1x | | 1x | ||
− | | | + | | |
| ESRGAN | | ESRGAN | ||
− | | | + | | Art |
− | | | + | | 2019-07-29 |
− | | | + | | Clean up model for scanned illustrations. - Made to remove moire patterns, reduce small imperfections, and correct mild compression artifacts in scanned Kingdom Death: Monster illustrations. CMYK printing often shifts colors, so this is intended to reverse that color shifting as well. |
− | | | + | | Failed attempts based on ESRGAN_1x_JPEG_80to100 |
| | | | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | | + | | [https://drive.google.com/open?id=103MX2bvd3GW0MYpC53ABU5VYY6v1t99Y DigiPaint] |
− | | | + | | Rastrum |
− | | | + | | 4x |
− | | | + | | CC0 |
− | | | + | | ESRGAN |
+ | | Art | ||
+ | | 2019-09-07 | ||
+ | | Digital Art Upscaler | ||
+ | | 4xfalcoon300(manga).pth | ||
| | | | ||
− | |||
− | |||
− | |||
|- | |- | ||
+ | |} | ||
− | + | ====Cel Animation==== | |
− | + | {| class="wikitable sortable" | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
|- | |- | ||
− | + | ! Model Name | |
− | + | ! Author | |
− | + | ! Scale | |
− | + | ! License | |
− | | | + | ! Architecture |
− | |[https:// | + | ! Purpose (short) |
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
+ | |||
+ | |- | ||
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/812414843939455036/2X_DigitalFilmV5_Lite.pth DigitalFilmV5 Lite] | ||
+ | | OptimusPrimal | ||
+ | | 2x | ||
+ | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Traditional Animation |
− | | | + | | 2021-02-19 |
− | | | + | | Upscaling Dragon Ball Z DBox DVD's. - grainy sources. It keeps some grain, but also doing some cleaning, sharpening, and fixing. |
− | | | + | | none |
− | + | | https://imgsli.com/NDE0MzQ | |
− | + | ||
+ | https://imgsli.com/NDE0MzU | ||
+ | |||
+ | https://imgsli.com/NDE0MzY | ||
+ | |||
+ | https://imgsli.com/NDE0Mzc | ||
+ | https://imgsli.com/NDE0Mzg | ||
− | + | https://imgsli.com/NDE0Mzk | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | | [https://mega.nz/file/GFFkSL5R#C-dDxaxTZpSPUh_heAUw_idGIF8Xizdr0ktyGi05yFk 4x_HellinaCel] | |
− | | [https://mega.nz/ | + | | VGDCKeroro |
− | | | ||
| 4x | | 4x | ||
− | | | + | | fuckin do whatever |
| ESRGAN | | ESRGAN | ||
− | | | + | | Traditional Animation |
− | | 2021- | + | | 2021-03-21 |
− | | ' | + | | 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. |
| 4xESRGAN | | 4xESRGAN | ||
− | | https:// | + | | https://imgsli.com/NDU2MjU |
|- | |- | ||
+ | |} | ||
− | | [https:// | + | ===Image Restoration=== |
− | | |[[User: | + | ====Image Compression==== |
+ | =====JPEG Artifacts===== | ||
+ | {| class="wikitable sortable" | ||
+ | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
+ | |||
+ | |- | ||
+ | |[https://drive.google.com/drive/folders/1HWokMsUwsR_Mw-NOJgc8OdS8mkdIje_C JPG (00-20%)] | ||
+ | | |[[User:BlueAmulet|BlueAmulet]] | ||
| 1x | | 1x | ||
− | | [https://creativecommons.org/licenses/by-nc | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
| JPEG | | JPEG | ||
− | |||
| | | | ||
− | |||
| | | | ||
+ | | Trained on Custom (CC0 Textures) | ||
+ | | JPEG models by Alsa | ||
|- | |- | ||
− | + | |- | |
− | | [https:// | + | |[https://drive.google.com/drive/folders/1HWokMsUwsR_Mw-NOJgc8OdS8mkdIje_C JPG (20-40%)] |
− | | |[[User: | + | | |[[User:BlueAmulet|BlueAmulet]] |
| 1x | | 1x | ||
− | | [https://creativecommons.org/licenses/by-nc | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
| JPEG | | JPEG | ||
− | |||
− | |||
− | |||
| | | | ||
+ | | | ||
+ | | Trained on Custom (CC0 Textures) | ||
+ | | JPEG models by Alsa | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | |
− | | |[[User: | + | |[https://drive.google.com/drive/folders/1HWokMsUwsR_Mw-NOJgc8OdS8mkdIje_C JPG (40-60%)] |
+ | | |[[User:BlueAmulet|BlueAmulet]] | ||
| 1x | | 1x | ||
− | | [https:// | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
| JPEG | | JPEG | ||
− | |||
− | |||
− | |||
| | | | ||
+ | | | ||
+ | | Trained on Custom (CC0 Textures) | ||
+ | | JPEG models by Alsa | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | |[https://drive.google.com/drive/folders/1HWokMsUwsR_Mw-NOJgc8OdS8mkdIje_C JPG (60-80%)] |
− | | | + | | |[[User:BlueAmulet|BlueAmulet]] |
− | | | + | | 1x |
− | | [https:// | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | JPEG | + | | JPEG |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
| | | | ||
− | |||
| | | | ||
+ | | Trained on Custom (CC0 Textures) | ||
+ | | JPEG models by Alsa | ||
|- | |- | ||
− | | [https:// | + | |
− | | |[[User: | + | | [https://drive.google.com/drive/folders/1HWokMsUwsR_Mw-NOJgc8OdS8mkdIje_C JPG (80-100%)] |
+ | | |[[User:BlueAmulet|BlueAmulet]] | ||
| 1x | | 1x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
− | | ESRGAN | + | | ESRGAN |
− | | JPEG | + | | JPEG |
− | + | | | |
− | |||
− | | | ||
| | | | ||
+ | | Trained on Custom (CC0 Textures) | ||
+ | | JPEG models by Alsa | ||
|- | |- | ||
− | | [https:// | + | |
− | | | + | |[https://e.pcloud.link/publink/show?code=XZvmsZo4qORoatgHXm4A1CooSUnuy5YD5X JPG (00-20%)] |
+ | | |[[User:Alsa|Alsa]] | ||
| 1x | | 1x | ||
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
| JPEG | | JPEG | ||
− | | | + | | |
− | | | + | | |
− | | | + | | Trained on Custom (Photos / Manga) |
− | + | | | |
− | | | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | ||
− | | [https:// | + | |[https://e.pcloud.link/publink/show?code=XZimsZmfeBi2HJp9H00wvCRISpnuSRrjgy JPG (20-40%)] |
− | | |[[User: | + | | |[[User:Alsa|Alsa]] |
| 1x | | 1x | ||
− | | [https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
+ | | | ||
| | | | ||
− | | | + | | Trained on Custom (Photos / Manga) |
− | |||
| | | | ||
|- | |- | ||
− | + | ||
− | | [https:// | + | |[https://e.pcloud.link/publink/show?code=XZrmsZbOaINRer4xRn6UWBtGgRK5r7biWy JPG (40-60%)] |
− | | |[[User: | + | | |[[User:Alsa|Alsa]] |
| 1x | | 1x | ||
− | | [https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
+ | | | ||
| | | | ||
− | | | + | | Trained on Custom (Photos / Manga) |
− | |||
| | | | ||
|- | |- | ||
− | + | ||
− | | [https:// | + | |[https://e.pcloud.link/publink/show?code=XZcmsZASeN84hQXCLfhYzUogomG5EdkwPV JPG (60-80%)] |
− | | | + | | |[[User:Alsa|Alsa]] |
| 1x | | 1x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
− | | | + | | |
− | | | + | | |
− | | | + | | Trained on Custom (Photos / Manga) |
− | + | | | |
|- | |- | ||
− | |||
− | + | | [https://e.pcloud.link/publink/show?code=XZomsZwGOr2Jb4lLXGopIwu8UtNQqpuqyX JPG (80-100%)] | |
− | + | | |[[User:Alsa|Alsa]] | |
− | + | | 1x | |
− | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | [https:// | ||
− | | |[[User: | ||
− | | | ||
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
+ | | | ||
| | | | ||
− | | | + | | Trained on Custom (Photos / Manga) |
− | |||
| | | | ||
|- | |- | ||
− | |||
− | + | | [https://mega.nz/file/jcZQ1J6A#qLlSGBFQPWyQ0kUbOcvPN5kEYalPGUu9iR6EkEuS-T4 Kim2091_DeJpeg_v0] | |
− | + | | |[[User:Kim2091|Kim2091]] | |
+ | | 1x | ||
+ | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN Superlite | ||
+ | | JPEG | ||
+ | | | ||
+ | | Model I forgot to release. This doesn't totally remove JPEG artifacts, but it does a decent job at a fast rate. It seemingly does a better job of retaining detail than some other JPEG models. The model is incomplete, I need to train it further on compact rather than ESRGAN. This is just a temporary release | ||
+ | | Custom JPEG dataset | ||
+ | | [https://cdn.discordapp.com/attachments/903415274521374750/1041539960672632832/1668392853.8196685.png Sample 1] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/903415274521374750/1041540021175463956/1668392885.0326388.png Sample 2] | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |- | + | | [https://icedrive.net/1/43GNBihZyi 4x NMKD-PatchySharp] |
− | | [https://drive.google.com/open?id= | + | | nmkd |
+ | | 4x | ||
+ | | WTFPL | ||
+ | | ESRGAN (Old Arch) | ||
+ | | Art/CGI | ||
+ | | 2020-09-12 | ||
+ | | Upscaler for clean images or images with compression artifacts (jpeg quality >75) - Produces very sharp lines/edges due to NN-Filtered HR images. Proven to produce very, very good results on drawings (sharp lines) and CGI, but should also work pretty well for real-world images. | ||
+ | | 4xESRGAN | ||
+ | | https://i.imgur.com/PzFkmAg.png | ||
+ | |- | ||
+ | |||
+ | |||
+ | | [https://drive.google.com/open?id=1HWokMsUwsR_Mw-NOJgc8OdS8mkdIje_C 1x_JPEG (by compression level)] | ||
| |[[User:BlueAmulet|BlueAmulet]] | | |[[User:BlueAmulet|BlueAmulet]] | ||
| 1x | | 1x | ||
|[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
− | | 2019- | + | | 2019-08-01 |
− | | A | + | | A collection of models for jpeg artifact removal, examples are included in the provided link |
− | | | + | | JPEG models by |[[User:Alsa|Alsa]] |
− | | | + | | [https://drive.google.com/open?id=1HWokMsUwsR_Mw-NOJgc8OdS8mkdIje_C Sample Gallery] |
|- | |- | ||
− | + | ||
− | | [https:// | + | | [https://de-next.owncube.com/index.php/s/w82HLrLWmWi4SQ5 DeJpeg Fatality_PlusULTRA!] |
− | | | + | | |[[User:Twittman|Twittman]] |
| 1x | | 1x | ||
− | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
− | | | + | | 2019-10-29 |
− | | | + | | |
+ | | 1x_DeJpeg_Fatality_01_200000_G.pth | ||
+ | | | ||
+ | |- | ||
+ | |||
− | This | + | | [https://mega.nz/folder/vBgGgA5Z#qXsikSiIU8Edemaju91zDA DeCompress] |
+ | | |[[User:Kim2091|Kim2091]] | ||
+ | | 4x | ||
+ | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | JPEG (works on many compression formats) | ||
+ | | 2021-09-07 | ||
+ | | '''USE 4x-UltraSharp INSTEAD''' - This is UniScaleV2, but intended for images with compression. Seems to work best on realistic images. | ||
+ | | 4xESRGAN | ||
+ | | [https://cdn.discordapp.com/attachments/884864597310459996/884952891721383936/unknown.png Sample 1] | ||
− | + | [https://cdn.discordapp.com/attachments/884864597310459996/884957054807179274/unknown.png Sample 2] | |
− | + | [https://cdn.discordapp.com/attachments/884864597310459996/884960697883193354/unknown.png Sample 3] | |
− | + | [https://cdn.discordapp.com/attachments/884864597310459996/884953810097827850/unknown.png Sample 4] | |
− | |||
− | |||
|- | |- | ||
− | + | ||
− | | [https:// | + | | [https://de-next.owncube.com/index.php/s/w82HLrLWmWi4SQ5 JPG PlusULTRA (1x_jpg_PlusULTRA_130000.pth)] |
− | | | + | | |[[User:Twittman|Twittman]] |
| 1x | | 1x | ||
− | | | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
− | | | + | | 2019-10-29 |
− | | | + | | |
− | | | + | | 1x_DeJpeg_Fatality_01_200000_G.pth |
− | | | + | | |
|- | |- | ||
− | + | ||
− | | [https:// | + | | [https://f002.backblazeb2.com/file/ESRGAN/_RELEASE/1x_Saiyajin_DeJPEG_300000_G.pth SaiyaJin DeJpeg] |
− | | | + | | |[[User:Twittman|Twittman]] |
| 1x | | 1x | ||
− | | | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
− | | | + | | 2019-10-29 |
− | | | + | | Dataset: Anime, real life, manga, generated |
− | | | + | | 1x_DeJpeg_Fatality_PlusULTRA_200000_G.pth |
− | | https:// | + | | [https://f002.backblazeb2.com/file/ESRGAN/image_samples/SaiyaJin%20DeJpeg/sample_001.png Example 1] |
+ | |||
+ | [https://f002.backblazeb2.com/file/ESRGAN/image_samples/SaiyaJin%20DeJpeg/sample_002.png Example 2] | ||
+ | |||
+ | [https://f002.backblazeb2.com/file/ESRGAN/image_samples/SaiyaJin%20DeJpeg/sample_006.png Example 3] | ||
|- | |- | ||
− | + | | [https://drive.google.com/file/d/1C0Lnn3PfXrm4UX9trjQIWsmxtspjQjmm/view?usp=drivesdk 1x_JPEGDestroyer] | |
− | | [https:// | + | | |[[User:BlackScout|BlackScout]] |
− | | |[[User: | ||
| 1x | | 1x | ||
− | |[https:// | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG |
− | | | + | | 2020-02-19 |
− | | | + | | This model is meant to reduce or eliminate JPEG Compression without making the original images too smooth or killing detail. It manages to do a fairly good job but don't expect overly compressed images to work with this. |
− | | | + | | 1xESRGAN + previous attempts |
| | | | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/file/d/17k72r01xTkeOzqsaYCN6ZqnAktKqTLyw/view?usp=sharing 4xJaypeg90] |
− | | |[ | + | | Jacob |
− | + | | 4x | |
− | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] | |
| ESRGAN | | ESRGAN | ||
− | | | + | | JPEG compression |
− | | 2020- | + | | 2020-07-20 |
− | | | + | | Photos/realistic 3D with JPEG compression, quality 85-95 and 4:2:0 chroma subsampling. - Created for Myst3 images, since all have 4:2:0 chroma subsampling and existing JPEG models did not give good results. Favors smoothing over over-sharpening. |
− | | | + | | 4xESRGAN |
− | | https:// | + | | https://i.imgur.com/n09m2Rt.png |
|- | |- | ||
− | | [https:// | + | | [https://u.pcloud.link/publink/show?code=kZvfeFXZMyUSYScxAizUmTKjax0JQzTk9Gfk 1x_SBDV-DeJPEG-Lite] |
− | | |[[User: | + | | Joey |
+ | | 1x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN (lite) | ||
+ | | JPEG compression | ||
+ | | 2020-10-10 | ||
+ | | | ||
+ | | 1x_DIV2K-Lite_80k.pth | ||
+ | | | ||
+ | |- | ||
+ | |||
+ | | [https://icedrive.net/1/43GNBihZyi NMKD Jaywreck3 & Jaywreck3-Soft (Lite)] | ||
+ | | |[[User:nmkd|Nmkd]] | ||
| 1x | | 1x | ||
| WTFPL | | WTFPL | ||
− | | ESRGAN | + | | ESRGAN Lite [nf=32 nb=12] |
− | | | + | | JPEG compression |
− | | | + | | 2020-10-13 |
− | | | + | | 1xESRGAN |
| 1xESRGAN | | 1xESRGAN | ||
| | | | ||
|- | |- | ||
+ | |||
+ | | [https://mega.nz/folder/fAg21TRI#kBk0synXgNqTGaXiW6nSZA MangaJPEG] | ||
+ | | Bunzero++ | ||
+ | | 1x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | JPEG | ||
+ | | 2021-06-17 | ||
+ | | Remove JPEG artifacts from manga without destroying screentone and other details | ||
+ | | none | ||
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/855269193762865152/Example_LQ_Input-comparison.png Sample] | ||
|} | |} | ||
− | ===== | + | =====Aliasing===== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,234: | Line 2,360: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
− | + | |- | |
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/open?id=11nMqVF9sUN2jRRagYc3wdWNX5acEy0MJ SS Anti Alias 9x] |
− | | [[User: | + | | |[[User:BlueAmulet|BlueAmulet]] |
| 1x | | 1x | ||
− | |[https://creativecommons.org/licenses/by-nc | + | | [https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Anti aliasing |
| | | | ||
− | | | + | | Dataset: Custom (9x Supersampling AA) |
− | | | + | | none (no interpolation) |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://de-next.owncube.com/index.php/s/mmYCcK4H3rQQR5Y Anti Aliasing] |
− | | | + | | |[[User:Twittman|Twittman]] |
− | | | + | | 1x |
− | | | + | | [https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Anti aliasing / Images with pixelated edges |
− | | | + | | |
− | | | + | | Dataset: Custom (?) |
− | | | + | | none (no interpolation) |
− | | | + | | |
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/folder/yg0lHQoJ#sP8_BfDk2YlshFjOL9Qrtg 1x_GainRESV3 (Aggro,Natural,Passive)] |
− | | | + | | CF2lter |
− | | | + | | 1x |
− | | | + | | WTFPL |
− | | ESRGAN | + | | ESRGAN |
− | | | + | | Anti aliasing / Deblur |
− | | | + | | 2022-02-26 |
− | | | + | | To eliminate aliasing and general artifacts caused by not enough resolution while bringing out details Im stopping its training here because it's getting worse, i think of some aligment issues by game's rendering pipeline + downscaling... Dataset: 5K resolution shots from paladins rendered by 200% for hr and 37.5%(1080p) for lr then downscaled to 1080 |
− | + | | BCGONE_DetailedV2 | |
− | + | | [https://cdn.discordapp.com/attachments/579685650824036387/947132730313949184/cmp2.png Sample 1] | |
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/947132731056324668/cmp.png Sample 2] | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|} | |} | ||
− | ==== | + | =====GIF===== |
− | |||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,325: | Line 2,418: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
− | |||
|- | |- | ||
− | | [https:// | + | | [https://icedrive.net/1/43GNBihZyi DeGif] |
− | | | + | | |[[User:nmkd|nmkd]] |
− | | | + | | 2x |
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | GIF Restoration |
− | | | + | | |
− | | | + | | GIF Restoration |
− | | | + | | [https://mega.nz/#!vtgSWKQT!K7Asn2zKe4N70R2aV89KEMTKhH3aiyGAAiuQDJF09qs 2xESRGAN] |
− | | | + | | |
|- | |- | ||
+ | |} | ||
+ | =====DDS (BC1/DXT1, BC3/DXT5 Compression)===== | ||
+ | {| class="wikitable sortable" | ||
+ | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/open?id=1LHplsPRqhmjR28jGgRlEekeP_bvx3nUC 1x_BC1-smooth2.pth] |
− | | | + | | |[[User:BlueAmulet|BlueAmulet]] |
| 1x | | 1x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | BC1 Compression |
− | | | + | | 2019-09-05 |
− | | | + | | A model to help remove compression artifacts in BC1-BC3/DXT1-DXT5 compressed images (these all have color encoded the same way) |
− | | | + | | none |
− | | | + | | |
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/drive/folders/1y-QoWGAnF8YiX764rWrDOGzndWtpCfF3?usp=sharing x1_ITF_SkinDiffDDS_v1] |
+ | | intheflesh#3116 | ||
| 1x | | 1x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | BC1 Compression |
− | | | + | | 2022-08-24 |
− | | | + | | Removes banding, blocking, dithering, aliasing, noise and color tint on DDS Compressed Skin Diffuse Textures. |
− | | | + | |
− | | | + | This should work extremely well on most modern DDS compression types. The training set was compressed with BC3/DXT5, BC3/DXT5 Fast, BC2/DXT3, BC2/DXT3 Fast, and a small number of JPEG compressed images to cover outliers. |
+ | |||
+ | This model is trained to remove the slight green color tint that DDS compression tends to add to skin textures, so the model output will not match the original color tone of the input image. This is the desired result though, as DDS compression shifts the colors to a sickly green tint and this model corrects that to more natural color tones. | ||
+ | |||
+ | The training set included faces, body parts, eyes, mouths and hair in a variety of skin types and tones so it should work well on most related diffuse textures. | ||
+ | |||
+ | However it's not just limited to skin, many other images and textures can be cleaned with this model. Designed to be used as a first step cleaning pass before applying additional models after. Check out the other ITF Models. | ||
+ | | 1x_BC1-smooth2.pth | ||
+ | | https://imgsli.com/MTIyMzE5 | ||
+ | |||
+ | https://imgsli.com/MTIyMzIw | ||
+ | |||
+ | https://imgsli.com/MTIyMzIx | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/file/d/1WXBNdlqDWV10a3L1_U7zuNkSpN9aBF0M/view?usp=sharing 1x_DXTDecompressor_Source_V3-300000_G] |
+ | | JosephtheKP | ||
| 1x | | 1x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | DXT1 Compression |
− | | 2021- | + | | 2021-12-21 |
− | | | + | | Removing compression artifacts from DXT1 compressed textures. This model was created to remove DXT1 compression artifacts from textures imported into the Source Engine. Compressed textures in the engine sometimes have a green-tint which this model also corrects. The data for this model contained a good mix of diffuse textures and normal maps which means this model is pretty good at removing compression from normals as well. Creating this model was a real learning experience for me and I hope someone finds a good use for it. |
− | | | + | | |
− | | https://imgsli.com/ | + | | https://imgsli.com/ODcwNDg |
+ | |||
+ | https://imgsli.com/ODcwNDk | ||
+ | |||
+ | https://imgsli.com/ODcwNTA | ||
+ | |||
+ | https://imgsli.com/ODcwNTE | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://mega.nz/file/TltS1TQY#CW3zaI24pxFXggeRjgnXb4bSfjnQsY_ch1bogCjMCmU 1x_DEDXT] |
+ | | CF2lter | ||
| 1x | | 1x | ||
| WTFPL | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | DXT compression |
− | | | + | | 2022-02-26 |
− | | | + | | To retain details while removing artifacts caused by dxt compression on textures |
− | |||
| | | | ||
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/947116367205793882/cmp.png Sample] | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | | [https://e.pcloud.link/publink/show?code=XZXbsZK03Y0UsmtR0W7wRMHWGvYkzgPII7 1x_artifacts_bc1_free_alsa.pth] | |
− | | [https:// | + | | |[[User:Alsa|Alsa]] |
− | | |[[User: | ||
| 1x | | 1x | ||
− | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | BC1 Compression |
+ | | | ||
| | | | ||
− | | | + | | [https://mega.nz/#!r2hEAAAb!zdk-Ka6VCqVnKThtfJVYM0NnVBSUyeqsjYs-NgKjLkc BC1 take 2] |
− | |||
− | |||
− | |||
| | | | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/drive/u/1/folders/1pnyPklpLPtMAHeNC5NVU1mV_Qh61wWnx 1x_BCGone_Smooth_110000_G] |
− | | |[[User: | + | | |[[User:Mutin_Choler|Mutin_Choler]] |
| 1x | | 1x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | BC1 Compression |
− | | | + | | 2020-08-02 |
− | | | + | | Attempts to remove the damages done by BC1 compression. |
| 1xESRGAN | | 1xESRGAN | ||
− | | | + | | https://imgsli.com/MjU5MzQ/4/3 |
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/drive/folders/1pnyPklpLPtMAHeNC5NVU1mV_Qh61wWnx?usp=sharing 1x_BCGone-DetailedV2_40-60_115000_G] |
− | | |[[User: | + | | |[[User:Mutin_Choler|Mutin_Choler]] |
| 1x | | 1x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | BC1 Compression |
− | | | + | | 2021-03-18 |
− | |||
− | |||
− | |||
| | | | ||
− | | | + | | 1xESRGAN |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
| | | | ||
|- | |- | ||
− | |||
|} | |} | ||
− | ==== | + | =====Dithering===== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,468: | Line 2,567: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
+ | |||
|- | |- | ||
− | | [https:// | + | | [https://e.pcloud.link/publink/show?code=XZ5bsZtd0ldzEF2UFLSYqIBNhqNH21slxX 1x_artifacts_dithering_alsa.pth (pcloud)][https://mega.nz/file/IsABVIJb#ljH6JDvFahi6KLWpaeQ_G9DOSQlvhwjbitlPBbSHcuo (mega)] |
− | + | | [[User:Alsa|Alsa]] | |
| 1x | | 1x | ||
− | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Dithering |
− | | | + | | |
− | | | + | | Dithered Images |
− | | | + | | [https://mega.nz/#!7io2gSQR!UB9u2k51daixTgC2H0LdOWzNlkDyIDHwxBX4BVY2J3k JPG (0-20%)] |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/file/d/1H4KQyhcknOoExjvDdsoxAgTBMO7JuJ3w/view 4xFSDedither] |
− | | | + | | Jacob |
− | | | + | | 4x |
− | | | + | | GNU GPL3 |
| ESRGAN | | ESRGAN | ||
− | | | + | | Dithering |
− | | | + | | 2020-01-29 |
− | | | + | | 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. |
− | | | + | | RRDB_ESRGAN_x4 |
− | | https://imgsli.com/ | + | | https://imgsli.com/MTI1NTY/ |
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/open?id=1Vtwt9kgnmju1edibl07WI6Rg7CrAlHIx 4xFSDedither_Manga] |
− | | | + | | Jacob |
− | | | + | | 4x |
− | | [https:// | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
− | | ESRGAN | + | | ESRGAN-FS |
− | | | + | | Dithering |
− | | | + | | 2020-04-21 |
− | | | + | | Cartoons/pixel art/other non-realistic stuff with dithering |
− | | | + | | RRDB_ESRGAN_x4.pth |
− | | | + | | https://imgsli.com/MTQ3Nzc |
|- | |- | ||
− | | | + | | [https://buildism.net/files/4xFSDedither_Riven.pth 4xFSDedither_Riven] |
− | + | | Jacob | |
− | + | | 4x | |
− | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] | |
+ | | ESRGAN-FS | ||
+ | | Dithering | ||
+ | | 2020-07-11 | ||
+ | | 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. | ||
+ | | 4xESRGAN | ||
+ | | https://imgsli.com/MTg5NTM | ||
+ | |||
+ | https://imgsli.com/MTg5NTQ | ||
+ | |||
+ | https://imgsli.com/MTg5NTU | ||
+ | |||
+ | https://i.imgur.com/j7Wtn0G.png | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
+ | | [https://drive.google.com/drive/folders/1XKREcpHnaYz_dcmkMPDbyETcXzDcQsR2?usp=sharing 1x_DitherDeleter-Smooth_104000_G] | ||
+ | | |[[User:Mutin_Choler|Mutin_Choler]] | ||
+ | | 1x | ||
+ | | WTFPL | ||
+ | | ESRGAN | ||
+ | | Dithering | ||
+ | | 2021-01-23 | ||
+ | | 1xESRGAN | ||
+ | | | ||
+ | | https://imgsli.com/Mzg0MTk/1/2 | ||
|- | |- | ||
− | | [https://drive.google.com/drive | + | |
+ | | [https://drive.google.com/drive/folders/1XKREcpHnaYz_dcmkMPDbyETcXzDcQsR2?usp=sharing 1x_DitherDeleterV3-Smooth] | ||
| |[[User:Mutin_Choler|Mutin_Choler]] | | |[[User:Mutin_Choler|Mutin_Choler]] | ||
| 1x | | 1x | ||
| WTFPL | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Dithering |
− | | | + | | 2021-04-18 |
− | | | + | | Attempts to remove the damages done by dithering. For this model, I downscaled all of the HR images to make their pixel size closer to 1000x1000 using the Box filter and then downscaled them again by 50% using the Point filter. Afterwards, I applied 32-bit Riemersma to every image in the dataset. |
| 1xESRGAN | | 1xESRGAN | ||
− | | https://imgsli.com/ | + | | https://imgsli.com/NTA5MjU/1/0 |
|- | |- | ||
|} | |} | ||
− | ==== | + | ====Blurring==== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
Line 2,552: | Line 2,665: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/file/CYoXCAKR#eRKwpP9rCL9vFCsO41oVImvmVwAEOtYUlp2CquX0Fw8 1x_ThePi7on-Solidd_Deborutify_UltraLite_260k_G] |
− | | | + | | ThePi7on |
− | | | + | | 1x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Deblur |
− | | | + | | 2021-05-09 |
− | | | + | | Sharpening, line darkening and slight line thinning, specifically made for the Boruto anime. |
− | | | + | | |
− | | | + | | |
|- | |- | ||
− | | [https:// | + | |
− | | | + | |- |
+ | | [https://mega.nz/file/zcBRHRbJ#iLStv-F5ax-vQBPG7N6OaRv_xBhRHux3pdnSG43GuMg 1x_DeBLR] | ||
+ | | BlackScout | ||
| 1x | | 1x | ||
− | | | + | | Unknown or None |
| ESRGAN | | ESRGAN | ||
− | | | + | | Deblur |
− | | | + | | 2020-02-19 |
− | | | + | | General Deblurring |
− | | | + | | |
− | | | + | | |
|- | |- | ||
− | | [https:// | + | | [https://cloud.owncube.com/s/p3w7M2sfaWWYCK9/download?path=%2F&files=1x_mdeblur.pth mdeblur] |
− | | | + | | LyonHrt |
| 1x | | 1x | ||
− | | | + | |UNKNOWN |
| ESRGAN | | ESRGAN | ||
− | | | + | | Blurring |
− | | | + | | |
+ | | Strong deblurring model | ||
+ | | | ||
| | | | ||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | [https://1drv.ms/u/s!Aip-EMByJHY27TDhiFPB39jM0pwq?e=5zAFtO 1x_PixelSharpen_100000] |
− | + | | [[User:DinJerr|DinJerr]] | |
| 1x | | 1x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Pixel Art |
− | | | + | | 2021-03-19 |
− | | | + | | Restores blurry/upscaled pixel art. |
| 1xESRGAN | | 1xESRGAN | ||
− | | https://imgsli.com/ | + | | https://imgsli.com/NDUxNDQ/5/4 |
|- | |- | ||
− | + | | [https://1drv.ms/u/s!Aip-EMByJHY28w0Zkd9fdANYH3j6?e=9zwxII 1x_ArtClarity] | |
− | | [https:// | + | | [[User:DinJerr|DinJerr]] |
− | | | ||
| 1x | | 1x | ||
| WTFPL | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Pixel Art |
− | | | + | | 2021-08-05 |
− | | | + | | Texture retaining denoiser and sharpener for digital artwork. Helps resized/generated artwork look more like it is in 'native' resolution. |
− | | | + | | 4xPSNR |
+ | | [https://1drv.ms/u/s!Aip-EMByJHY28xKFp93VIGydNsoN?e=vN2WYh Sample Gallery] | ||
+ | |- | ||
− | + | | [https://de-next.owncube.com/index.php/s/aAojXwLTPZto8rP 1x_Fatality_DeBlur] | |
− | + | | |[[User:Twittman|Twittman]] | |
− | | [https:// | ||
− | | | ||
| 1x | | 1x | ||
− | | | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Deblur |
− | | | + | | 2019-10-16 |
− | | | + | | Dataset: Mix of anime, manga, and photos |
− | | | + | | 1x_DeJpeg_Fatality_01_175000_G.pth |
+ | | | ||
+ | |- | ||
+ | | [https://de-next.owncube.com/index.php/s/nmNfcd33mnLLwEC UnResize V3 (1x_UnResize_V3_200000_G.pth)] | ||
+ | | |[[User:Twittman|Twittman]] | ||
+ | | 1x | ||
+ | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) | ||
+ | | ESRGAN | ||
+ | | Deblur / Unresize | ||
+ | | | ||
+ | | Dataset: Anime, manga, and photos - | ||
+ | Purpose: Fix images that have been arbitrarily / poorly resized, such as non-integer nearest-neighbor upscaling/downscaling - | ||
+ | Also acts as an image sharpener/deblur when used on slightly soft inputs | ||
+ | | 1x_UnResize_MKII_030000_G.pth | ||
| | | | ||
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://mega.nz/folder/OVomUZyT#vDyNntGY1MirBEACNjpqVg 1x-Focus and 1x-Focus_Moderate] |
+ | | |[[User:Kim2091|Kim2091]] | ||
| 1x | | 1x | ||
− | | | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Deblur |
− | |||
− | |||
− | |||
| | | | ||
− | | | + | | These models deblur most images. It was trained mostly on aniso2 and iso blurring (BSRGAN augmentation) with some gaussian mixed in. It performs well on most blurry images, but I'd recommend using something like Fatality_Deblur for very strong gaussian blur. Dataset: The UniScale Dataset + My Fabric dataset |
+ | | 1xESRGAN | ||
+ | | [https://cdn.discordapp.com/attachments/893483065664483338/893483645803847690/unknown.png Sample 1] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/893483065664483338/893497416207188028/unknown.png Sample 2] | ||
+ | [https://cdn.discordapp.com/attachments/893483065664483338/893483280895193118/unknown.png Sample 3] | ||
− | + | [https://cdn.discordapp.com/attachments/893483065664483338/893496207832408135/unknown.png Sample 4] | |
− | |||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |- | + | | [https://de-next.owncube.com/index.php/s/HyygDgXEB45JqBH ReFocus V3 (1x_ReFocus_V3_140000_G.pth)] |
− | | [https:// | + | | |[[User:Twittman|Twittman]] |
− | | | + | | 1x |
+ | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Deblur / ReFocus | ||
+ | | 2022-03-12 | ||
+ | | Dataset: Photos, Anime, and manga - | ||
+ | Purpose: DeBlur, ReFocus, Sharpen Real life style images, but will work on Anime images too. | ||
+ | | 1x_Saiyajin_DeJPEG_300000_G.pth | ||
+ | | | ||
+ | |- | ||
+ | |||
+ | | [https://de-next.owncube.com/index.php/s/GjbBw7pcgm5gmYm ReFocus Cleanly (1x_ReFocus_Cleanly_100000_G.pth)] | ||
+ | | |[[User:Twittman|Twittman]] | ||
| 1x | | 1x | ||
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Deblur / ReFocus |
− | | | + | | 2022-01-21 |
− | | | + | | Dataset: Anime, manga, and photos - |
− | | | + | Purpose: DeBlur, ReFocus, Sharpen Manga, Anime and cartoon style images, but will work on real life images too. |
+ | | 1x_ReFocus_V3_110000_G.pth | ||
| | | | ||
|- | |- | ||
+ | |||
|} | |} | ||
− | ==== | + | ====Banding==== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,681: | Line 2,814: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
− | |||
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/file/d/1GNguVMV4E5t_4dn23w6UMXVKN6Ff9XPt/view?usp=sharing 1x_N64clean] |
− | | |[[User: | + | | |[[User:BlueAmulet|BlueAmulet]] |
− | | | + | | 1x |
− | | | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Banding |
− | | | + | | 2020-07-16 |
− | | | + | | N64 textures use a color depth of 5-bits per channel, this model attempts to clean them, restoring smooth gradients in textures |
− | | | + | | 1x_BC1-smooth2.pth |
| | | | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | |- |
− | | | + | | [https://drive.google.com/drive/folders/1WD2RqtER_jk0QkPFUySeXhDV2aAO8_nr?usp=sharing 1x_Bandage-Smooth] |
+ | | |[[User:Mutin_Choler|Mutin_Choler]] | ||
| 1x | | 1x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | Banding |
− | | | + | | 2021-04-16 |
− | | | + | | Attempts to remove the damages done by color banding. For this model, I downscaled all of the HR images to make their pixel size closer to 1000x1000 using the Box filter and then downscaled them again by 50% using the Point filter. Afterwards, I applied 64-bit color banding to every image in the dataset. |
| 1xESRGAN | | 1xESRGAN | ||
+ | | https://imgsli.com/NTA1NTk/1/0 | ||
+ | |- | ||
+ | |||
+ | |- | ||
+ | | [https://f002.backblazeb2.com/file/ESRGAN/_RELEASE/1x_Debandurh_FS_lite_140000_G.pth Debandurh_FS Ultra-lite (1x_Debandurh_FS_lite_140000_G.pth)] | ||
+ | | |[[User:Twittman|Twittman]] | ||
+ | | 1x | ||
+ | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) | ||
+ | | ESRGAN | ||
+ | | Debanding images | ||
+ | | | ||
+ | | Dataset: Anime, real life, manga | ||
+ | | None | ||
| | | | ||
|- | |- | ||
+ | |||
|} | |} | ||
− | + | ====Halo Removal==== | |
− | |||
− | |||
− | ==== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,725: | Line 2,869: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/drive/u/1/folders/1pT75GdIU4JAH75eJzpxsaHfIoJ1a_gXB 1x_DeEdge_105000_G] |
− | | |[[User: | + | | |[[User:Mutin_Choler|Mutin_Choler]] |
| 1x | | 1x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | Halo remover |
− | | 2020- | + | | 2020-11-03 |
− | | | + | | |
| 1xESRGAN | | 1xESRGAN | ||
− | | | + | | https://imgsli.com/MjgxMDU/3/0 |
|- | |- | ||
+ | |} | ||
− | + | ====Noise==== | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,779: | Line 2,898: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https://drive.google.com/file/d/ | + | | [https://drive.google.com/file/d/1GoUY7t5kE0Ubi-NDvlMB8lUs-_u_f6tS/view?usp=sharing LADDIER1] |
− | | | + | | Alexander Syring |
| 4x | | 4x | ||
− | | | + | | Unknown |
| ESRGAN | | ESRGAN | ||
− | | | + | | Denoise |
− | | | + | | 2019-11-13 |
− | | | + | | Remove noise, grain, box blur, lens blur and gaussian blur and increase overall image quality. |
− | | | + | | RRDB_ESRGAN_x4.pth |
| | | | ||
|- | |- | ||
+ | | [https://drive.google.com/drive/u/1/folders/12j6BvuR7SU48ui9DHjBPB1vzPpQri9bD 1x_NoiseToner-Poisson-Detailed_108000_G] | ||
+ | | |[[User:Mutin_Choler|Mutin_Choler]] | ||
+ | | 1x | ||
+ | | WTFPL | ||
+ | | ESRGAN | ||
+ | | Noise remover | ||
+ | | 2021-10-08 | ||
+ | | Attempts to remove the damages done from noise. Successor of sorts to Noisetoner_Poisson_150000_G | ||
+ | | 1xESRGAN | ||
+ | | https://imgsli.com/NzQ5MzM/2/0 | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | |
− | | | + | | [https://drive.google.com/drive/u/1/folders/12j6BvuR7SU48ui9DHjBPB1vzPpQri9bD 1x_NoiseToner_Poisson_150000_G] |
+ | | |[[User:Mutin_Choler|Mutin_Choler]] | ||
| 1x | | 1x | ||
− | | | + | | WTFPL |
− | | ESRGAN | + | | ESRGAN |
− | | | + | | Noise remover |
− | | | + | | 2020-10-14 |
− | | | + | | |
− | | | + | | 1xESRGAN |
− | | | + | | https://imgsli.com/MjU1ODU/3/1 |
+ | |- | ||
− | + | | [https://drive.google.com/drive/u/1/folders/12j6BvuR7SU48ui9DHjBPB1vzPpQri9bD 1x_NoiseToner_Uniform_100000_G] | |
− | + | | |[[User:Mutin_Choler|Mutin_Choler]] | |
− | + | | 1x | |
− | + | | WTFPL | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | [https://drive.google.com/ | ||
− | | |[[User: | ||
− | | | ||
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Noise remover |
− | | 2020- | + | | 2020-10-14 |
− | |||
− | |||
| | | | ||
− | + | | 1xESRGAN | |
+ | | https://imgsli.com/MjU1Nzg/2/1 | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1f5kIr3gG5GjbN_EM96CCB0nqu_2_56gh/view 1x_ISO_denoise_v1] |
− | | | + | | Alpha |
− | | | + | | 1x |
| WTFPL | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | denoise |
− | | | + | | not on discord |
− | | | + | | Remove high ISO noise |
− | | | + | | 1xESRGAN |
+ | |||
+ | | | ||
+ | |- | ||
+ | | [https://drive.google.com/file/d/1HSUvnQm56_CmVAAMjTfVn_Hi6a4Bm2h0/view 1x_ISO_denoise_v2] | ||
+ | | Alpha | ||
+ | | 1x | ||
+ | | WTFPL | ||
+ | | ESRGAN | ||
+ | | denoise | ||
+ | | not on discord | ||
+ | | Remove high ISO noise | ||
+ | | ISO denoise v1 | ||
+ | |||
+ | | | ||
+ | |- | ||
+ | | [https://drive.google.com/file/d/1kO3fx9FL5rKhoDk2n4kiiPWuCNHojkIR/view Film-Degrainer_1-000] | ||
+ | | Tika | ||
+ | | 1x | ||
+ | | CC0 | ||
+ | | ESRGAN | ||
+ | | denoise | ||
+ | | not on discord | ||
+ | | Remove film grain/noise | ||
+ | | none | ||
+ | | | ||
+ | |||
|- | |- | ||
+ | | [https://1drv.ms/u/s!Aip-EMByJHY2gYQUcbSTFgrdwtMjQA?e=A5p6lH 1x_Fatality_NoiseToner] | ||
+ | | [https://upscale.wiki/wiki/User:DinJerr DinJerr] | ||
+ | | 1x | ||
+ | | WTFPL | ||
+ | | ESRGAN | ||
+ | | sharpen & denoise | ||
+ | | 2023-04-16 | ||
+ | | Interpolation of Mutin_Choler's various 1x_NoiseToner_Poisson with Twittman's 1x_Fatality_DeBlur | ||
+ | | none | ||
+ | | | ||
|} | |} | ||
− | === | + | ====Oversharpening==== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,873: | Line 3,010: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/#!qRZD3SLL!RqP7cISIcoW5YakPya9CXEWSEHWqUSKdWLQSdYKGa14 1x_DeSharpen] |
− | | | + | | Loinne |
| 1x | | 1x | ||
− | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Denoise |
− | | | + | | 2019-06-03 |
− | | | + | | Made for rare particular cases when the image was destroyed by applying noise, i.e. game textures or any badly exported photos. If your image does not have any oversharpening, it won't hurt them, leaving as is. In theory, this model knows when to activate and when to skip, also can successfully remove artifacts if only some parts of the image are oversharpened, for example in image consisting of several combined images, 1 of them with sharpen noise. |
− | | | + | | 1st attempt on random sharpening with the same dataset at 200000 iterations, which was trained on non-random desharp model, total ~600000 iterations on 3 models. |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
| | | | ||
− | |||
− | |||
|- | |- | ||
− | |||
|} | |} | ||
− | === | + | ====DeToon==== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,914: | Line 3,038: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
+ | |||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/open?id=1uJvdx3g3GEY0VxMnHb0ItBvoc6pmGvuH detoon] |
− | | |[[User: | + | | |[[User:LyonHrt|LyonHrt]] |
− | | | + | | |
− | | | + | | |
| ESRGAN | | ESRGAN | ||
− | | | + | | Detooning |
− | | | + | | 2019-06-24 |
− | | | + | | A toon to realistic shading style model to wiki under drawings |
− | | | + | | |
− | | [https:// | + | | |
− | + | |- | |
− | |} | + | |
+ | | [https://drive.google.com/file/d/12vkDn35cuVnq2KYpkaA3XfCmk6zY_u4_/view?usp=sharing 1xDoubleDetoon] | ||
+ | | Joey | ||
+ | | 1x | ||
+ | | CC BY-NC-SA | ||
+ | | ESRGAN | ||
+ | | Detooning | ||
+ | | 2020-07-31 | ||
+ | | An attempt to detoon images/drawings of people | ||
+ | | 1xESRGAN | ||
+ | | | ||
+ | |- | ||
+ | |} | ||
+ | |||
− | === | + | |
+ | ====Image De/Colorization==== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 2,943: | Line 3,082: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | |[https://drive.google.com/ | + | | [https://drive.google.com/file/d/1UgxnymTfLaVhY3aaDuBRnTZ9ehckKVKJ BS_Colorizer/Vapourizer] |
− | | |[[User: | + | | |[[User:BlackScout|BlackScout]] |
− | | | + | | 1x |
− | |[https:// | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Colorization |
− | | | + | | 2020-01-30 |
− | | | + | | Colorize Grayscale or Desaturated images. - This model is a partially failed attempt at restoring color from Grayscale | B/W | 100% Desaturated images. It mostly results in Blue and Yellow images with slight hints of Green, Orange and Magenta. You are free to use this as a pretrain to achieve better results. |
− | | | + | | 1xESRGAN |
| | | | ||
|- | |- | ||
− | | [https://u.pcloud.link/publink/show?code= | + | | [https://u.pcloud.link/publink/show?code=kZpAGFXZARxWIu9Pp4YDLUSIN8I8aFuJ5TKV 1x_SpongeColor-Lite] |
| Joey | | Joey | ||
− | | | + | | 1x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
− | | ESRGAN | + | | ESRGAN (lite) [nf=32 nb=12] |
− | | | + | | Colorization |
− | | 2020- | + | | 2020-10-15 |
− | | | + | | The first attempt at ESRGAN colorization that produces more than 2 colors. Doesn't work that great but it was a neat experiment. |
| none | | none | ||
| | | | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/open?id=1-mxmDF1Dh-PnQqRz_PeCrvsTkHjYCbi3 Deoldify] |
− | | | + | | Rastrum |
− | | | + | | 4x |
+ | | CC0 | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Photos |
− | | | + | | 2019-08-29 |
− | | | + | | Old black and white photo restoration. |
− | | | + | | Falcon Fanart |
| | | | ||
|- | |- | ||
+ | |} | ||
− | + | ===Stylization=== | |
− | + | ====Images==== | |
− | + | {| class="wikitable sortable" | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
|- | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/file/d/1AR2KhmJ23woifnpe1dr0BXkmF7WLG2pS/view?usp=sharing Rek's Effeks Photoanime v2] |
+ | | Rek | ||
| 4x | | 4x | ||
− | | | + | | GNU GPL3 |
| ESRGAN | | ESRGAN | ||
− | | | + | | Stylization |
− | | | + | | 2020-10-17 |
− | | | + | | Photo stylization from JPEGs. Trained on images upscaled by ISO Denoise v2 -> DeJPEG Fatality PlusULTRA -> NMKD Yan2. Essentially a combination of that model chain into one. Use if you're looking for a stylized output, not photo quality. |
− | + | | NMKD Yandere2 | |
+ | | | ||
+ | |- | ||
+ | |||
+ | |- | ||
+ | | [https://drive.google.com/file/d/1URPhkwgraCzWAIkB8Pk4ZPr1LTdfdwxJ/view?usp=sharing Ghibli_Grain.pth] | ||
+ | | nonogamester#3975 | ||
+ | | 1x | ||
+ | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Realistic Ghibli Grain | ||
+ | | 2022-11-16 | ||
+ | | Text or Anime. Attempt to get the nostalgic grain feel of classically animated Ghibli movies. Got the idea from researching the making of Ronin's :PKT_blue: 1x_AnimeFilmGrain28k. This was made running Nate video denoising with the preset "more denoising" on kiki's delivery service then overlaying it 66.65 percent over the original with DaVinci. On digital drawn anime it gives a slightly [10%] more organic/sharp feel to black lines. Matches well with content that already has a light digital grain. Run Twice for heavy grain. Eternal Thanks to all that indulge all my :psyduck: Wonderings :element_fire_neon: | ||
| | | | ||
+ | | https://slow.pics/c/M6dNTu6G | ||
+ | |||
+ | https://imgsli.com/MTM0Nzcw/9/8 | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://1drv.ms/u/s!Aip-EMByJHY282MGb4GvQh-BO-SH?e=Hm49eo 1x_ReDetail_v2_126000_G] |
− | | | + | | [[User:DinJerr|DinJerr]] |
− | | | + | | 1x |
+ | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Digital Illustration |
+ | | 2021-02-11 | ||
+ | | A failed model that's supposed to insert details into paintings. It's actual use is to interpolate with other 1x models such as with 1x_DoubleDetoon to reduce its colour warping, or with 1x_ArtClarity to emphasize more on feature extraction. | ||
+ | | 1x_ArtClarity | ||
| | | | ||
− | + | ||
− | |||
− | |||
− | |||
|} | |} | ||
− | === | + | ==Specialized Models== |
+ | ===Text=== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,031: | Line 3,193: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
+ | |||
|- | |- | ||
− | + | | [https://drive.google.com/file/d/15ovbadCoYs7q8nSd5Mq02PqBOpwiBkoS/view 2x_BSTexty] | |
− | | [https://drive.google.com/ | + | | |[[User:BlackScout|BlackScout]] |
− | | | + | | 2x |
− | | | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
− | |[https:// | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Text |
− | | | + | | 2020-03-04 |
− | | | + | | 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. |
− | | | + | | 2x_ESRGAN |
− | | | + | | |
+ | |||
|- | |- | ||
− | + | | [https://mega.nz/folder/rdpkjZzC#eUXPed_vntJKLrB0wpeJ-w 4x-TextSharpV1] | |
− | | [https:// | + | | |[[User:Kim2091|Kim2091]] |
− | | | ||
| 4x | | 4x | ||
− | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Text |
− | | | + | | 2021-12-28 |
− | | | + | | Text or Anime |
− | | | + | | Interpolation between 4x-UltraSharp and 4x-TextSharp-v0.5. This is a duplicate listing of '''4x-AnimeSharp''' |
− | + | | [https://media.discordapp.net/attachments/556604553424928768/925526934555881532/unknown.png Sample 1] | |
− | + | ||
+ | [https://cdn.discordapp.com/attachments/903415274521374750/925533775616696340/unknown.png Sample 2] | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | | [https://icedrive.net/1/43GNBihZyi NMKD Typescale] | |
− | | [https:// | + | | |[[User:nmkd|Nmkd]] |
− | | | + | | 8x |
− | | | + | | WTFPL |
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Text |
− | | 2020- | + | | 2020-11-04 |
− | | | + | | Low-resolution text/typography and symbols |
− | + | | 8xESRGAN | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
|} | |} | ||
− | === | + | ===Inpainting=== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,108: | Line 3,247: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
− | |||
|- | |- | ||
− | | [https:// | + | | [https://e.pcloud.link/publink/show?code=kZQOu7ZldzmFyMPUcFNGkEvwqOxQ8Bl3CeX 1x_sudo_inpaint_PartialConv2D_424000_G.pth] |
− | | | + | | sudo rm -rf / --no-preserve-root#8353 |
| 1x | | 1x | ||
− | | [https:// | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Inpainting |
− | | 2020- | + | | 2020-12-05 |
− | | | + | | Experimental PartialConv2D attempt to paint with ESRGAN. Took ~10.4 days of training on a P100 and around 1.5 months in total due to Colab limits. Not sure if I will continue training it since training is very slow, but may get better.. Warning: Result can vary with different tilesizes. Try not to tile your data. |
− | | | + | | None |
− | | | + | | [https://e.pcloud.link/publink/show?code=kZQOu7ZldzmFyMPUcFNGkEvwqOxQ8Bl3CeX Samples] |
+ | |||
|- | |- | ||
− | + | | [https://icedrive.net/1/43GNBihZyi 1x_NMKD-YandereInpaint_375000_G.pth] | |
− | | [https:// | + | | [[User:nmkd|Nmkd]] |
− | |||
| 1x | | 1x | ||
− | | | + | | Unknown |
| ESRGAN | | ESRGAN | ||
− | | | + | | Inpainting |
− | | | + | | Unknown |
− | |||
− | |||
| | | | ||
+ | | None | ||
+ | | [https://icedrive.net/1/43GNBihZyi Samples] | ||
|- | |- | ||
+ | |||
|} | |} | ||
− | === | + | ===Fabric/Cloth=== |
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,149: | Line 3,288: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | + | | [https://mega.nz/folder/6EJjwADL#oDvv9p0z1t9nQvObbvBRBQ 4x-Fabric and Fabric-Alt] | |
− | | |[[User: | + | | |[[User:Kim2091|Kim2091]] |
| 4x | | 4x | ||
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Fabric |
− | | | + | | 2021-09-15 |
− | | | + | | 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. |
− | | | + | | 4xESRGAN |
− | + | | [https://cdn.discordapp.com/attachments/887850596214902835/887852703873638410/unknown.png Sample 1] | |
− | + | ||
+ | [https://cdn.discordapp.com/attachments/887850596214902835/887852170156847124/unknown.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/887850596214902835/887856392269094952/unknown.png Sample 3] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/887850596214902835/887853344545194084/unknown.png Sample 4] | ||
+ | |||
|} | |} | ||
− | === | + | |
+ | ===Alphas=== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,177: | Line 3,323: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https://drive.google.com/ | + | |[https://drive.google.com/open?id=192Mw2_yUwCgqt3tAJ2sRxZ8hYHe4CKrZ FireAlpha] |
− | | | + | | |[[User:BlueAmulet|BlueAmulet]] |
| 4x | | 4x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Alpha (4 channel) |
− | | | + | | 2019-11-12 |
− | | | + | | |
− | | | + | | none |
| | | | ||
|- | |- | ||
− | |||
− | = | + | | [https://u.pcloud.link/publink/show?code=kZQfN4XZmIrkODabBWhtmmA95c0GMb19WUuy 4x_1ch-Alpha-Lite] |
− | + | | Joey | |
+ | | 4x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Alpha | ||
+ | | 2020-12-15 | ||
+ | | Obsoleted by Joey's Fork - Alpha channels of PNGs | ||
+ | | none | ||
+ | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | | [https://u.pcloud.link/publink/show?code=kZkR7hXZhfCA4WvVQvbxXkNN50tazuxj73uX 2x_Gen5-Alpha] | |
− | | [https:// | + | | Joey |
− | | |[ | + | | 2x |
− | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |
− | + | | ESRGAN | |
− | | ESRGAN | + | | Pixel Art with Tranparency / Alpha Channel |
− | | | + | | 2021-02-03 |
− | | | ||
− | |||
− | |||
| | | | ||
− | | | + | | 4xFireAlpha |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
| | | | ||
|- | |- | ||
− | + | | [https://u.pcloud.link/publink/show?code=kZeNFhXZbuw2jGJOGqQnKecb8Moo1ha47W57 8x_Sphax-Alpha-NN] | |
− | | [https:// | + | | Joey |
− | | | + | | 8x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Pixel Art with Tranparency / Alpha Channel |
− | | | + | | 2021-02-04 |
− | | | + | | Replica of sphax with transparency |
− | | | + | | 4xFireAlpha |
| | | | ||
|- | |- | ||
− | + | | [https://u.pcloud.link/publink/show?code=kZrIFhXZxnpi72FuwgLz7FIDw8kdrp2suIEk 4x_PocketMonsters-Alpha] | |
− | | [https:// | + | | Joey |
− | | | ||
| 4x | | 4x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | Art/ | + | | Pixel Art with Tranparency / Alpha Channel |
− | | | + | | 2021-02-04 |
− | | | + | | upscaling pixel art with alpha channels that should perform better than any other. It should work well on both cartoon and 3D styled content. |
− | | | + | | 4xFireAlpha |
− | | | + | | |
|- | |- | ||
− | + | | [https://drive.google.com/file/d/1trYs4AuC9s2JWAbryHdNyy5cgYV-V8cH/view Skyrim Alpha] | |
− | | [https:// | + | | Deorder |
− | | | ||
| 4x | | 4x | ||
− | |[https://creativecommons.org/ | + | |[https://creativecommons.org/publicdomain/zero/1.0/ CC0] |
| ESRGAN | | ESRGAN | ||
− | | Art/ | + | | Pixel Art with Tranparency / Alpha Channel |
− | | | + | | |
+ | | Dataset: Alpha Channels from Skyrim | ||
+ | | Unknown | ||
| | | | ||
− | |||
− | |||
|- | |- | ||
+ | |} | ||
+ | ===CGI=== | ||
+ | {| class="wikitable sortable" | ||
|- | |- | ||
− | + | ! Model Name | |
− | + | ! Author | |
− | + | ! Scale | |
− | + | ! License | |
− | + | ! Architecture | |
− | + | ! Purpose (short) | |
− | + | ! Date Posted | |
− | + | ! Purpose (Full) | |
− | + | ! Pretrained_Model_G | |
− | + | ! Sample | |
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/drive/folders/1m7fO9ywNNRc2FZBKycJiC556rBJpbGoH 1xRedImage10000.pth] |
− | | |[[User:DinJerr|DinJerr]] | + | | 3majsie1995 |
+ | | 1x | ||
+ | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
+ | | ESRGAN | ||
+ | | Correct old color photos that are tinted red | ||
+ | | 2022-08-04 | ||
+ | | Correct old color photos that are tinted red. Model only tested in nature. | ||
+ | | 1xESRGAN | ||
+ | | https://i.imgur.com/5O74rRL.png | ||
+ | |- | ||
+ | |||
+ | | [https://1drv.ms/u/s!Aip-EMByJHY20wpGoLuSRzjdqh0T WaifuGAN_v3_30000] | ||
+ | | [[User:DinJerr|DinJerr]] | ||
| 4x | | 4x | ||
|[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | CGI |
− | | 2019- | + | | 2019-07-12 |
− | | | + | | Upscaling CG-painted anime with variable outlines. |
− | | | + | | Manga109v2.pth |
| | | | ||
|- | |- | ||
− | | [https://drive.google.com/file/d/ | + | |
+ | | [https://drive.google.com/file/d/1zlc8BWOcpCbSZpwf7ArMCqpb0Tf9DlZk/view?usp=drivesdk 2xBS_Wolly] | ||
| |[[User:BlackScout|BlackScout]] | | |[[User:BlackScout|BlackScout]] | ||
− | | | + | | 2x |
| [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | CGI Animation |
− | | 2020-07 | + | | 2020-02-07 |
− | | | + | | Pixar Movies or Wall-E pictures/frames |
− | | | + | | 2xESRGAN |
| | | | ||
|- | |- | ||
− | + | | [https://drive.google.com/file/d/1kNSz5f2_krdlsJ700DwH78OEPYkkcjW5/view?usp=sharing 4xSGI] | |
− | | [https://drive.google.com/file/d/ | + | | ChrisNonyminus |
− | | | ||
| 4x | | 4x | ||
− | | | + | | GNU GPL3 |
| ESRGAN | | ESRGAN | ||
− | | | + | | CGI |
− | | | + | | 2020-12-17 |
− | | | + | | Upscaling and dedithering pre-rendered sprites, images and textures made in the 90s. Basically vintage CGI. |
− | | | + | | 4xESRGAN |
− | | | + | | https://imgur.com/a/iwLTjeB |
|- | |- | ||
− | + | | [https://lbry.tv/@Madiator2011:e/x2_CGIMaster_v1:6 CGIMaster_v1] | |
− | | [https:// | + | | Madiator |
− | | | + | | 2x |
− | | | + | | GNU GPL3 |
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | CGI Animation |
− | | | + | | 2021-01-14 |
− | | | + | | mixed 3D/2D CGI animations on some 2D animations it might sharpen the edges. General usage is to upscale CGI animations compressed by YouTube. |
− | | | + | | Sharp_Anime_v2 |
− | | | + | | https://imgsli.com/Mzc1NTM |
|- | |- | ||
|} | |} | ||
− | + | ===Luminance/Chroma=== | |
− | === | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,349: | Line 3,488: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/file/d/1FDb9H6GOmE3aRvZbx_-kTiCLS77WyjgL/view 1x_BSLuma] |
− | | | + | | |[[User:BlackScout|BlackScout]] |
| 1x | | 1x | ||
− | | | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Luma |
+ | | 2020-02-28 | ||
+ | | Fix Luminance issues?? LumaSharpen ESRGAN Edition? - This model mostly does what "Lumasharpen" algorithms do. It may help fixing images with Luminance images issues? Like old DVD rips? I am not sure, didn't test. | ||
+ | | none | ||
| | | | ||
− | | | + | |- |
− | + | | [https://drive.google.com/file/d/12v_2OwrB_rr6_0tMshHaHgD_XWRNgIyF/view 1x_BSChroma] | |
− | + | | |[[User:BlackScout|BlackScout]] | |
− | + | | 1x | |
− | | | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
+ | | ESRGAN | ||
+ | | Sharpen | ||
+ | | 2020-02-29 | ||
+ | | ChromaSharpen - makes the colors slightly more vibrant with a sideeffect of possibly adding Chromatic Abberation to the image. I am not sure about the usage of this model on real case scenarios but anything blurry or with fuzzy colors could work | ||
+ | | none | ||
| | | | ||
|- | |- | ||
− | + | | [https://drive.google.com/file/d/1JLyZZbnb06BddjNMXZ_CAyyoMpWCDHq0/view?usp=sharing/view 1x_3mChroma] | |
+ | | |[[User:3majsie1995|3majsie1995]] | ||
+ | | 1x | ||
+ | | [https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] | ||
+ | | ESRGAN | ||
+ | | Chroma | ||
+ | | 2023-01-04 | ||
+ | | Improves chromatic aberration. It's not as good as 1x_BSchroma, but I recommend you to test it! | ||
+ | | 1xESRGAN | ||
+ | | https://i.imgur.com/oSub859.png | ||
+ | |- | ||
|} | |} | ||
− | + | ===Cats=== | |
− | === | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,385: | Line 3,541: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https:// | + | | |[https://f002.backblazeb2.com/file/ESRGAN/_RELEASE/4x_cat_patch_325000_G.pth Cat_Patch] |
− | | | + | | |[[User:Twittman|Twittman]] |
− | | | + | | 4x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
| ESRGAN | | ESRGAN | ||
− | | | + | | Cats |
− | | | + | | not on discord |
− | | | + | | |
− | | | + | | previous attempt |
− | | | + | | |
|- | |- | ||
+ | |} | ||
− | | [https://drive.google.com/file/d/ | + | ===Coins=== |
− | | | + | {| class="wikitable sortable" |
+ | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
+ | |||
+ | |- | ||
+ | | [https://drive.google.com/file/d/1zC97RLUg5ejqb5-4Dj5q-SzdLPLiMozH/view 4x_Nickelfront] | ||
+ | | BlackScout | ||
| 4x | | 4x | ||
− | | | + | | GNU GPLv3 |
| ESRGAN | | ESRGAN | ||
− | | | + | | Coins |
− | | | + | | 2020-02-13 |
− | | | + | | Upscale coins. That's it. If you were mad at me because Nickelback doesn't make any sense. Now you have the perfect solution to your problems. If you want to upscale nickels or anything with similar texture made out of metal, now you can. It works pretty well for a joke. |
− | | | + | | 4xESRGAN |
| | | | ||
|- | |- | ||
|} | |} | ||
− | === | + | ===Faces=== |
− | |||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,426: | Line 3,597: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https:// | + | | [https://de-next.owncube.com/index.php/s/PF5GTJ9jix4Log8 4x_Faces_N_250000.pth] |
− | | |[[User: | + | | |[[User:Twittman|Twittman]] |
| 4x | | 4x | ||
− | | | + | | |
| ESRGAN | | ESRGAN | ||
− | | | + | | Faces |
− | | | + | | 2019-07-18 |
− | | Upscales | + | | Upscales images of faces of different scales, sometimes resulting in monsters. |
− | | 4xESRGAN | + | | 4xESRGAN |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://de-next.owncube.com/index.php/s/PF5GTJ9jix4Log8 4x_Faces_04_N_180000_G] |
− | | | + | | |[[User:Twittman|Twittman]] |
| 4x | | 4x | ||
− | | | + | | |
| ESRGAN | | ESRGAN | ||
− | | | + | | Faces |
− | | | + | | 2019-07-23 |
− | | | + | | Upscale faces both pixelized and real |
− | | | + | | 4x_Faces_N_250000.pth |
− | | | + | | |
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://de-next.owncube.com/index.php/s/mZRG4HB3KdP2iP6 Face-Ality V1 (4x_Fatality_Faces_310000_G.pth)] |
− | | |[[User: | + | | |[[User:Twittman|Twittman]] |
| 4x | | 4x | ||
− | | CC BY-NC-SA 4.0 | + | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
− | | ESRGAN | + | | ESRGAN |
− | | | + | | Faces |
− | | | + | | |
− | | | + | | Dataset: Custom (Faces) |
− | | | + | | 4x_Faces_04_N_180000_G.pth |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://1drv.ms/f/s!Aip-EMByJHY29BRdcYSnTpgx0LWd?e=nX92z1 4x_SmolFace_200k] |
− | + | | [[User:DinJerr|DinJerr]] | |
| 4x | | 4x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Art/People |
− | | 2022- | + | | 2022-08-19 |
− | | | + | | A sharp upscaler trained specifically for small sprite faces. Does not blend, so avoid using on painted/photo portraits unless you were trying to retain more of the outlines somehow. The _clean version has denoising/dedithering training on top of it. |
− | | | + | | 4x_NMKD-UltraYandere_300k |
− | | https:// | + | | SmolFace: https://imgsli.com/MTIxNjU1/8/9 |
+ | SmolFace_clean: [https://1drv.ms/i/s!Aip-EMByJHY2-TNPYE5i1apNxRPn?e=B4tBsW Sample 1] [https://1drv.ms/i/s!Aip-EMByJHY2gYVZac1TWZP2A52_tw?e=Wrfnjo Sample 2] [https://1drv.ms/i/s!Aip-EMByJHY2-TSVRq30c_KUe1Mc?e=GE1TO9 Comparison with anime models] | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://1drv.ms/u/s!Aip-EMByJHY27CHg3-1Uue5KgbtK?e=6k0COU BigFace_v3, BigFace_V3_Blend, BigFace_V3_Clear] |
+ | | [[User:DinJerr|DinJerr]] | ||
| 4x | | 4x | ||
− | |[https://creativecommons.org/licenses/by-nc | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Art/People |
− | | 2020- | + | | 2020-07-22 |
− | | | + | | Pixel art upscaler for faces drawn in digital painting style. Best for game portraits with multiple shades (not cel-shaded). |
− | | | + | | 4x_BigFace |
− | | | + | | |
|- | |- | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/open?id=1OyOJIW224hBhb-aTCbuUQb0qzKmE4oH6 TGHQFace8x] |
− | | | + | | tg |
+ | | 8x | ||
+ | | GNU GPL3 | ||
+ | | ESRGAN | ||
+ | | Faces | ||
+ | | 2019-11-27 | ||
+ | | Upscales blurry 128px faces, usefull for enhancing that someone in a small picture. | ||
+ | | 8xESRGAN | ||
+ | | https://imgsli.com/OTM1NQ | ||
+ | |- | ||
+ | |||
+ | | [https://1drv.ms/u/s!Aip-EMByJHY211Vcr3fF39ZOaPk-?e=BQajTd FArtFace] | ||
+ | | |[[User:DinJerr|DinJerr]] | ||
| 4x | | 4x | ||
− | | [https:// | + | |[https://creativecommons.org/licenses/by-nc/4.0/ CC BY-NC 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Faces |
− | | | + | | 2019-11-28 |
− | | | + | | Rather old pixel art face upscaler. I suggest using BigFace_v3 or SmolFace instead. Sometimes produces better results though. |
− | | | + | | |
| | | | ||
|- | |- | ||
− | + | | [https://drive.google.com/file/d/14daAyYuoX-nZ_Lo1U6oekbFqrZTQlQkG/view?usp=drivesdk 4x_BS_SbeveHarvey] | |
− | | [https://drive.google.com/file/d/ | ||
| |[[User:BlackScout|BlackScout]] | | |[[User:BlackScout|BlackScout]] | ||
| 4x | | 4x | ||
− | | | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Faces |
− | | 2020- | + | | 2020-07-24 |
− | | | + | | Upscale Steve Harvey, but maybe other things, somehow?? |
− | | | + | | 4xESRGAN |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https://drive.google.com/file/d/ | + | | [https://drive.google.com/file/d/19ICMKNuS4PbhmtA7Be9lUE6v8NHDDEzP/view Face Focus] |
− | | |[[User: | + | | |[[User:LyonHrt|LyonHrt]] |
| 4x | | 4x | ||
− | | CC BY-NC-SA | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | + | | ESRGAN |
− | | | + | | Faces |
− | | | + | | not on discord |
− | | | + | | Face De-blur - slightly out of focus / blurred images of faces. It is aimed at faces / hair |
− | | | + | | 4xPSNR |
+ | | | ||
+ | |- | ||
+ | |||
+ | |- | ||
+ | | [https://drive.google.com/file/d/1OyOJIW224hBhb-aTCbuUQb0qzKmE4oH6/view TGHQFace8x] | ||
+ | | |[[User:Torrentguy|Torrentguy]] | ||
+ | | 8x | ||
+ | | [https://www.gnu.org/licenses/gpl-3.0.en.html [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3]] | ||
+ | | ESRGAN | ||
+ | | Face Upscaling | ||
+ | | | ||
+ | | | ||
+ | | 8xESRGAN | ||
| | | | ||
|- | |- | ||
|} | |} | ||
− | ==== | + | ===Skin=== |
− | |||
− | |||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,546: | Line 3,741: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
+ | |||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/drive/folders/1VkT6tpbCPn2gKZYPtawDJGMpLg6EyRpO?usp=sharing x1_ITF_SkinDiffDetail_Lite_v1] |
− | | | + | | intheflesh#3116 |
| 1x | | 1x | ||
− | | | + | | CC BY-NC-SA 4.0 |
− | | ESRGAN | + | | ESRGAN |
− | | | + | | Skin Upscaling |
− | | | + | | |
− | | | + | | Adds plausible high frequency detail and removes subtle blur. This is an early unfinished attempt at a x1 Lite model designed specifically for enhancing detail on skin diffuse textures of 3d characters. Even in its current state it works quite well. |
− | + | ||
− | + | Best suited for uncompressed or cleaned textures - otherwise it may just enhance any existing compression artefacts too. The training set included faces, body parts, eyes and hair in a variety of skin types and tones so it should work well on most related diffuse textures. | |
− | |||
− | + | However it's not just limited to skin, many other images and textures can be enhanced with this model. The results are subtle, so run multiple times if desired. | |
− | + | | 50/50 Interpolation of DIV2K-Lite and SpongeBC1-Lite | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
| | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|} | |} | ||
− | === | + | |
+ | ===Foliage/Ground=== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
Line 3,599: | Line 3,777: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
− | |||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/drive/folders/1ZcMD3hy1YCm-hsrT6xYGvhboxSzhrJKg 1x_Plants_400000_G.pth] |
− | | | + | | Muf |
− | | | + | | 1x |
− | | | + | | Public Domain |
| ESRGAN | | ESRGAN | ||
− | | | + | | bad upscale |
− | | | + | | 2021-06-23 |
− | | | + | | Images of plants, trees or other foliage upscaled with Photoshop Preserve Details 2.0. Sharpens and "subdivides" details and noise so it doesn't look upscaled. |
− | | | + | | 1x_NMKD-h264Texturize_500k.pth |
− | | | + | | https://imgsli.com/NTg2MDk https://imgsli.com/NTg2MDg https://imgsli.com/NTg2MTA |
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1dGmhHUPmb3lO9buX_Bt2nq97Nk5MCTb4/view Ground] |
− | | | + | | tldr_coder |
| 4x | | 4x | ||
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | Upscales ground textures |
− | | | + | | 2021-06-23 |
− | | | + | | Dataset: Custom (Ground textures Google) |
− | | | + | | |
| | | | ||
|- | |- | ||
+ | |} | ||
+ | ===Video Games=== | ||
+ | ====Game Screenshots==== | ||
+ | {| class="wikitable sortable" | ||
+ | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
− | | [https://drive.google.com/file/d/ | + | |- |
− | | | + | | [https://drive.google.com/file/d/1DbbM4saRpJu0dmgvccQFwfF4zI2rjiQ_ Minepack] |
+ | | |[[User:BlackScout|BlackScout]] | ||
| 4x | | 4x | ||
− | | | + | | CC BY-NC-SA |
| ESRGAN | | ESRGAN | ||
− | | | + | | Upscaling pack.png |
− | | 2020- | + | | 2020-01-26 |
− | | | + | | Upscales Minecraft screenshots by 4x. May suffer from haloing, weird patterns on blocks and JPEG-like artifacts. |
− | | | + | | 4xESRGAN.pth |
− | | | + | | |
|- | |- | ||
− | + | |- | |
− | | [https://drive.google.com/ | + | | [https://drive.google.com/drive/u/0/folders/1zM07-eMja0PISoUz0dWGqx8b_YspU-gl 4x_Link] |
− | | | + | | Fielran#1024 |
| 4x | | 4x | ||
− | | | + | | GNU GPL3 |
| ESRGAN | | ESRGAN | ||
− | | | + | | Chainmail game textures. Alternatively, it can be used to turn plain images into chainmail. |
− | | | + | | 2022-10-06 |
− | | | + | | A highly generative model for chainmail game textures. Works fairly well on items without visible chainmail texture (ie just a grey area) or items with clear chainmail texture, less well on items with present but poorly defined chainmail texture. I'm not 100% happy with it but it is still an improvement over existing models in enough situations to be worth releasing. |
− | | | + | | 4x_Nickelfront_14000G.pth |
− | | https:// | + | | [https://cdn.discordapp.com/attachments/579685650824036387/1027685415756509265/4x_Link_500000_G-TestImage-0x9F6EFFE0.png Sample 1] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/1027685416180121722/4x_Link_500000_G-TestImage-CMMM_Knight_Templar_ID2_DiffuseMap.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/1027685416528261203/4x_Link_500000_G-TestImage-Crest_Venetian_DiffuseMap.png Sample 3] | ||
|- | |- | ||
− | | [https://mega.nz/folder/ | + | |- |
+ | | [https://mega.nz/folder/zRYh3SII#QIm6T-rzhxjBLeYF1zSDpg 4x-FatePlus-lite] | ||
| |[[User:Kim2091|Kim2091]] | | |[[User:Kim2091|Kim2091]] | ||
| 4x | | 4x | ||
| CC BY-NC-SA 4.0 | | CC BY-NC-SA 4.0 | ||
− | | ESRGAN | + | | ESRGAN-lite |
− | | | + | | Anime PSP games, Fate Extra |
− | | | + | | 2022-07-03 |
− | | This model | + | | This model was trained as a favor to Demon and the Fate Extra community. It leaves a nice grain on the images and upscales lines and details accurately without looking odd. This model works on most anime-style PSP games. Enjoy! It works best on content with dithering and quantization. '''NOTICE:''' I have included both NCNN and ONNX models to make upscaling easier if you rely on either of these. For NCNN, there's two versions. One is FP16 and the other is FP32. FP16 works best on RTX GPUs. Choose FP32 if in doubt about compatibility, or if FP16 doesn't work for you. To use ONNX, download chaiNNer and upscale through there with the ONNX nodes. |
− | | | + | | 4x-AnimeSharp-lite |
− | | | + | | |
+ | |- | ||
+ | |||
|- | |- | ||
+ | | [https://drive.google.com/file/d/15KhApV05F8nEqTa5ZjLE821rhe1k8VOg/view?usp=sharing 4x_GameAI_2.0] [https://drive.google.com/file/d/1-s7iSK9ivJaoyvTXwDZvMjuyGG72bTQA/view?usp=sharing 4x_GameAI_1.0] | ||
+ | | Tal | ||
+ | | 4x | ||
+ | | WTFPL | ||
+ | | ESRGAN | ||
+ | | PS2 textures, cartoonish and realistic game textures. | ||
+ | | 2022-02-27 | ||
+ | | 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. Dataset: I used textures from, "(A Hat in Time, Kingdom Hearts 3 and World of Final Fantasy) for GameAI_2.0" "(Skyrim, The Witcher 3, Resident Evil 4, Final Fantasy XV and Tales of Vesperia ) for GameAI_1.0" Dataset_size: 21.9k to 70k textures , up to 1024x1024 per texture | ||
+ | | 4x_GameAI_1.0 | ||
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/947610558981632040/2ea384c8dc05593e-55207ec648ad52a4-00006213_2-comparison.png Sample 1] | ||
+ | [https://cdn.discordapp.com/attachments/579685650824036387/947610559497510922/65aac3d41ce0297c-5ff21b7095173a35-00006213_2-comparison.png Sample 2] | ||
− | + | [https://cdn.discordapp.com/attachments/579685650824036387/947610560005033984/a6518186b4e88a86-ddbb8bd9666cd975-00006213_2-comparison.png Sample 3] | |
− | + | ||
− | + | [https://cdn.discordapp.com/attachments/579685650824036387/947610560369950740/ae6ae340a472b13d-2ade3b7d0cf4a09f-00005dd3_2-comparison.png Sample 4] | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1Xe1JorGFJzPClR9tUuGmpuMyLhTA-d2T/view?usp=sharing 4xPackCraft_v4] |
| Joey | | Joey | ||
− | | | + | | 4x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
− | | ESRGAN | + | | ESRGAN |
− | | | + | | Upscaling pack.png |
− | | 2020- | + | | 2020-09-05 |
− | | | + | | Designed to upscale one specific minecraft screenshot. Results on dissimilar screenshots may be poor. |
− | | | + | | 4xESRGAN/previous versions |
− | | | + | | [https://cdn.discordapp.com/attachments/436411385673547787/750481717307113543/pack.png Sample] |
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://drive.google.com/drive/folders/1XsOFqGx_cGMWQTBuE9K9smwULg_wiaWc?usp=sharing MinecraftAlphaUpscaler with Good data] |
− | | | + | | Washed Up |
− | |[https:// | + | | 4x |
− | | ESRGAN | + | | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
− | | | + | | ESRGAN |
− | | 2020- | + | | Upscaling pack.png |
− | | | + | | 2020-01-29 |
− | | | + | | Designed to upscale one specific minecraft screenshot. Results on dissimilar screenshots may be poor. |
+ | | RRDB_PNSR_x4.pth | ||
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1MkqAuELmbhrEGcD55IUJhDFFNniOmNWN ScreenBooster V2] |
− | | | + | | |[[User:BlackScout|BlackScout]] |
| 4x | | 4x | ||
− | | CC BY-NC-SA | + | | CC BY-NC-SA |
| ESRGAN | | ESRGAN | ||
− | | | + | | CGI |
− | | | + | | 2020-01-29 |
− | | | + | | Game Screenshots |
− | | | + | | none |
− | | | + | | |
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1JI8VZSSHpH9u7HzE8MvuNG351Dgn4jwU/view?usp=sharing BS_ScreenBooster_SPSR] |
− | | | + | | |[[User:BlackScout|BlackScout]] |
| 4x | | 4x | ||
− | | | + | | CC BY-NC-SA |
− | | | + | | SPSR |
− | | | + | | CGI |
− | | | + | | 2020-07-18 |
− | | | + | | This model is designed to upscale game screenshots (3D Games) by 4 times. The SPSR version is an improvement over the ESRGAN based V2. |
− | | | + | | Screenbooster V2 |
− | | | + | | |
|- | |- | ||
+ | |} | ||
− | + | ====Normal Map/Bump Map Generation==== | |
− | + | You may want to use this instead: https://github.com/JoeyBallentine/Material-Map-Generator | |
− | + | ||
− | + | {| class="wikitable sortable" | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
− | | [https:// | + | |- |
− | | | + | | [https://u.pcloud.link/publink/show?code=kZEdNHXZ3bpVwUoge94d9igFWxbjQQrcbpny 1x_NormalMapGenerator-CX-Lite] |
− | | | + | | Joey |
+ | | 1x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
− | | ESRGAN | + | | ESRGAN Lite [nf=32 nb=12] |
− | | | + | | Map Generation - normal maps |
− | | | + | | 2020-11-04 |
− | | | + | | Generating normal maps from textures |
− | | | + | | 1x_DIV2K-Lite_450k.pth |
+ | | | ||
+ | |- | ||
+ | |||
+ | | [https://u.pcloud.link/publink/show?code=kZecVzXZEO6fAyO6w25YDc43BkSVHRgFdOwX 1x_FrankenMapGenerator-CX-Lite] | ||
+ | | Joey | ||
+ | | 1x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN Lite [nf=32 nb=12] | ||
+ | | Map Generation - roughness and displacement maps | ||
+ | | 2020-11-07 | ||
+ | | This model generates "Franken Maps" (named after Frankenstein), which is a custom material map combination I made. Basically, the Red channel of RGB is just the texture converted to grayscale, the Green channel is the roughness map, and the Blue channel is the displacement map. I had to do this to get around the current limitation of CX loss where it requires a 3 channel output (otherwise I would have just made a 2 channel model, or separate single channel models). As of right now the channels need to be manually split from each other but I will be making a tool for doing this automatically in the coming days. | ||
+ | | 1x_DIV2K-Lite_450k.pth | ||
| | | | ||
|- | |- | ||
− | | [https:// | + | | [https://drive.google.com/file/d/1uksv1uyyZjQcU4567OrfU0w2NECcG8dY/view 1x_normals_generator_general_215k] |
− | + | | [[User:LyonHrt|LyonHrt]] | |
− | | | + | | 1x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Map Generation - Normal Maps |
− | |||
| | | | ||
− | | | + | | This model generates "Franken Maps" (named after Frankenstein), which is a custom material map combination I made. Basically, the Red channel of RGB is just the texture converted to grayscale, the Green channel is the roughness map, and the Blue channel is the displacement map. I had to do this to get around the current limitation of CX loss where it requires a 3 channel output (otherwise I would have just made a 2 channel model, or separate single channel models). As of right now the channels need to be manually split from each other but I will be making a tool for doing this automatically in the coming days. |
+ | | none (no interpolation) | ||
| | | | ||
|- | |- | ||
+ | |} | ||
− | + | ====Video Game Textures==== | |
− | + | {| class="wikitable sortable" | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
+ | |||
|- | |- | ||
− | | [https:// | + | | [https://1drv.ms/u/s!AiWox1lAWLoTg1bUeJouJNOFZ_Jj Fallout Weapons (Fallout 4 Weapons?)] |
− | | | + | | Bob |
| 4x | | 4x | ||
− | | CC BY-NC-SA 4.0 | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
| Game textures | | Game textures | ||
− | | | + | | 2019-08-05 |
− | | | + | | Video game textures, mostly metal rusty, clean or painted |
− | | | + | | Manga109Attempt |
− | | | + | | |
|- | |- | ||
− | | [https:// | + | | [https://1drv.ms/u/s!AiWox1lAWLoThANuXjxIR-hqA6os Fallout Weapons V2] |
− | | | + | | Bob |
| 4x | | 4x | ||
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
| Game textures | | Game textures | ||
− | | | + | | 2019-08-23 |
− | | | + | | Video game textures, mostly metal rusty, clean or painted |
− | | | + | | Fallout 4 Weapons |
| | | | ||
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://drive.google.com/file/d/1y9nYjuy8vG7_LHpveYTj0ihK_6fE2XKF/view?usp=sharing 4x_ThiefGoldMod_100000] |
+ | | Akven | ||
| 4x | | 4x | ||
− | | | + | | no idea |
| ESRGAN | | ESRGAN | ||
| Game textures | | Game textures | ||
− | | | + | | 2020-05-15 |
− | | | + | | Version of the previous model but based on Manga109 pretrained model and with slightly different dataset. Sometimes gives better results especially for wood and metal, sometimes worse. Sometime generates the same dotted artifacts on very bright/white images. |
− | | | + | | 4x_Manga109Attempt |
− | | | + | | https://imgsli.com/MTYzNjI |
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://drive.google.com/file/d/1L8reADxi5Nt-8Tki0oY5jkQlv6kJg6w4/view?usp=sharing 4x_ThiefGold_110000] |
+ | | Akven | ||
| 4x | | 4x | ||
− | | | + | | no idea |
| ESRGAN | | ESRGAN | ||
| Game textures | | Game textures | ||
− | | | + | | 2020-05-15 |
− | | | + | | Various game textures. Primary wood, metal, stone |
− | | | + | | RRDB_ESRGAN_x4 |
− | | | + | | https://imgsli.com/MTYzNjI |
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/folder/HNh0hLzD#vUuFhp2ZAeNi_5shZfCC0g 4x-VolArt] |
− | | |[[User: | + | | |[[User:Kim2091|Kim2091]] |
| 4x | | 4x | ||
− | | | + | | CC BY-NC-SA 4.0 |
| ESRGAN | | ESRGAN | ||
− | | Game textures | + | | Game textures/Art |
− | | | + | | 2021-09-18 |
− | | | + | | This model upscales artwork for the game Volfoss (2001). The model peaked in quality very quickly. The NR model removes most noise, but has the downside of removing transparent portions. Use the main model in most cases. |
− | | | + | | 4xESRGAN |
− | | | + | | [https://cdn.discordapp.com/attachments/888869052867543060/888869070928248852/unknown.png Sample 1] [https://cdn.discordapp.com/attachments/888869052867543060/888869784169619496/unknown.png Sample 2] |
|- | |- | ||
− | | | + | | [https://drive.google.com/file/d/1Ful_AALrK-gxSwsTeMkzvwX5hh1ah8X8/view?usp=sharing 2xFaithfulSPSR] |
− | + | | Joey | |
− | + | | 2x | |
− | + | | CC BY-NC-SA | |
− | + | | SPSR | |
− | + | | Pixel art | |
+ | | 2020-07-19 | ||
+ | | Mainly just a test for SPSR. Seems to work better than the original 2xFaithful32_1316 that I used as a pretrained, even though it uses the same dataset. | ||
+ | | 2xFaithful32_1316 | ||
+ | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | | [https://u.pcloud.link/publink/show?code=kZUMKFXZUG6BpzHR6wFGack19pvWgbQQ9OA7 2x_FakeFaith-Lite] | |
− | | [https:// | + | | Joey |
− | | | + | | 2x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | | ESRGAN (lite) |
− | | ESRGAN | + | | Pixel Art |
− | | | + | | 2020-10-12 |
− | | | + | | An attempt at recreating the "faithful" style without using the faithful dataset -- aka keeping the "pixel art" style of pixel art. |
− | | | + | | 2x_Faithful-Lite |
− | | | ||
| | | | ||
|- | |- | ||
− | + | | [https://u.pcloud.link/publink/show?code=XZHawFXZhqD7dF4qtYHnqJVPnQd0ey0vW1JX 2x_Faithful-Lite] | |
− | | [https:// | + | | Joey |
− | | | + | | 2x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | |[https:// | + | | ESRGAN (lite) |
− | | ESRGAN | + | | Pixel Art |
− | | | + | | 2020-10-12 |
− | | | + | | A "lite" model version of my Faithful model |
− | | | ||
| none | | none | ||
| | | | ||
Line 3,896: | Line 4,105: | ||
|- | |- | ||
− | | [https:// | + | | [https://github.com/Venomalia/HDcube/tree/main/v3#hdcube-3 4x_HDCube3] |
− | | | + | | Venomalia |
− | | | + | | 4x |
| CC BY-NC-SA 4.0 | | CC BY-NC-SA 4.0 | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Gamecube and Wii textures. |
− | | | + | | 2022-12-13 |
− | | | + | | 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. |
− | | | + | | 4x_HDcube2 |
− | | | + | | https://imgsli.com/MTM5ODE0/0/1 |
− | |||
− | + | [https://github.com/Venomalia/HDcube/tree/main/v3#image-comparison Sample Gallery] | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | |||
|- | |- | ||
− | | [https:// | + | | [https://github.com/Venomalia/HDcube/tree/main/v1#hdcube 4x_HDCube] |
− | | | + | | Venomalia |
− | | | + | | 4x |
− | | | + | | CC0-1.0 |
| ESRGAN | | ESRGAN | ||
− | | | + | | Gamecube and Wii textures. |
− | | | + | | 2022-05-10 |
− | | | + | | Gamecube and Wii textures (mainly DXT and 8bit color compression). Is good for preserving fine details without affecting the original style too much, it is not suitable for pixel art, small icons and text under 16 pixel. |
− | | | + | | 4x_NMKD Siax |
− | | https://imgsli.com/ | + | | https://imgsli.com/MTA3NDQ3 |
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | https://slow.pics/c/rmQsQ6yb | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | [https://u.pcloud.link/publink/show?code=XZTAmsXZzEO8tMJaYAF1MrKKnmOCKu7Ghedy 1x_DXTless_SourceEngine_170000_G] |
− | | | + | | Xeller |
| 1x | | 1x | ||
| WTFPL | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | DTX5 Compression |
− | | | + | | 2021-04-10 |
− | | | + | | This model is made for Source Engine textures. It tries to remove compression artifacts such as blockyness, discoloration, green tint. It does pretty well on a lot of things, realistic stuff as well, but it was mostly made to work on TF2 textures. It's made to keep as much detail as possible, without any unnecessary denoising/sharpening. Huge thanks to Twittman for assisting me along this journey. |
− | | | + | | 1x_Saiyajin_DeJpeg_300000_G |
− | | | + | | https://imgsli.com/NDk1NTk |
+ | |||
+ | https://imgsli.com/NDk1NjA | ||
+ | |||
+ | https://imgsli.com/NDk1NjE | ||
+ | |||
+ | https://imgsli.com/NDk1NjI | ||
|- | |- | ||
− | + | | [https://drive.google.com/file/d/1HIBRKFs7s-XhpN1p7rwAWcMTHwFRqn3n/view Trixie] | |
− | | [https://drive.google.com/ | + | | |[[User:LyonHrt|LyonHrt]] |
− | | | + | | 4x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Faces / Game Textures |
− | | | + | | not on discord |
− | | | + | | character textures for star wars games, including the heroes, rebels, sith and imperial. Plus a few main aliens…Why called trixie? Because jar jars big adventure would be too long of a name… This also provides good upscale for face textures for general purpose as well as basic star wars |
− | | | + | | none |
− | | | + | | |
|- | |- | ||
− | | | + | | [https://e.pcloud.link/publink/show?code=XZGmsZo1yNrot19O4R5SrPVD1GWpRy1MKX Skyrim Armory] |
− | + | | |[[User:Alsa|Alsa]] | |
− | | | ||
| 4x | | 4x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | Game textures/equipment |
+ | | not on discord | ||
| | | | ||
− | | | + | | Manga109Attempt |
− | |||
| | | | ||
|- | |- | ||
− | |||
− | + | | [https://drive.google.com/file/d/1RjVWNUFtVyz4ykqu6Pm9wmO03pPEBGqg/view Skyrim Misc] | |
− | + | | Deorder | |
+ | | 4x | ||
+ | | CC0 | ||
+ | | ESRGAN | ||
+ | | Game textures | ||
+ | | not on discord | ||
+ | | Skyrim Diffuse Textures | ||
+ | | ? | ||
+ | | | ||
|- | |- | ||
− | + | ||
− | + | | [https://drive.google.com/file/d/1RjVWNUFtVyz4ykqu6Pm9wmO03pPEBGqg/view Skyrim Wood] | |
− | + | | Laeris | |
− | + | | 4x | |
− | + | | | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | [https:// | ||
− | | | ||
− | | | ||
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Game textures |
− | | | + | | not on discord |
− | | | + | | Wood |
− | | | + | | ? |
| | | | ||
|- | |- | ||
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/folder/fcp2SLKC#tF3vG7zjvfpnXK7OLUaFRA 4x-SkyrimTexV2.1 and V2_Fabric] |
− | | | + | | [[User:Kim2091|Kim2091]] |
− | | | + | | 4x |
− | | | + | | CC BY-NC-SA 4.0 |
| ESRGAN | | ESRGAN | ||
− | | | + | | Game textures |
− | | | + | | 2021-09-25 |
− | | | + | | This model set upscales most Skyrim textures. I hope it helps 🙂 The base model (2.1) works well on stone, wood, metals, and most other textures. The Fabric model is a 50/50 interpolation with a stronger iteration of this model and my Fabric model. As you can tell by the name, it's intended for Fabric textures. If you want to upscale Alpha textures, use a model dedicated to it. There's an INFO file in the folder, it just explains the extra models |
− | | | + | | 4xESRGAN |
− | | [https:// | + | | [https://cdn.discordapp.com/attachments/891300021453070387/891392169926098974/unknown.png Sample 1] |
+ | |||
+ | [https://cdn.discordapp.com/attachments/891393393849147423/891397870266224731/unknown.png Sample 2] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/891300021453070387/891395469387890738/unknown.png Sample 3] | ||
+ | |||
+ | [https://cdn.discordapp.com/attachments/891393393849147423/891398051325960202/unknown.png Sample 4] | ||
|- | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/file/d/12fR-pWw6YL2ZbS6EDvrAeOVoQHWkWl5L/view Forest] |
− | | | + | | |[[User:LyonHrt|LyonHrt]] |
− | | | + | | 4x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Game textures |
− | | | + | | not on discord |
− | | | + | | Wood / Leaves |
| none | | none | ||
| | | | ||
|- | |- | ||
− | | [https://mega.nz/ | + | | [https://mega.nz/folder/tFhl0L5b#CK4WLHYxjX7KFXU1PLNDuQ Morrowind Mixed] |
− | | | + | | mkultra |
− | | | + | | 4x |
|[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Game textures |
− | | | + | | not on discord |
− | | | + | | Morrowind Mod Textures |
− | | | + | | 4xESRGAN |
− | | | + | | |
|- | |- | ||
− | | | + | | [https://mega.nz/folder/dVQxxITT#Bsloq9G_Xh5tsDMKDQuTTA Morrowind 2.0] |
+ | | mkultra | ||
+ | | 4x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Game textures | ||
+ | | not on discord | ||
+ | | Morrowind Mod Textures | ||
+ | | 4xESRGAN | ||
+ | | | ||
+ | |- | ||
− | = | + | | [https://drive.google.com/file/d/1xPzqzTG5L6y5I0U3W0oQjexwGF5zfG32/view Map] |
− | {| class="wikitable sortable" | + | | |[[User:LyonHrt|LyonHrt]] |
+ | | 4x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | Game textures | ||
+ | | not on discord | ||
+ | | Map / Old Paper with text | ||
+ | | none | ||
+ | | | ||
+ | |- | ||
+ | |||
+ | |||
+ | |} | ||
+ | |||
+ | ==Video Restoration== | ||
+ | ===Video Compression=== | ||
+ | |||
+ | {| class="wikitable sortable" | ||
|- | |- | ||
! Model Name | ! Model Name | ||
Line 4,066: | Line 4,281: | ||
! License | ! License | ||
! Architecture | ! Architecture | ||
− | ! Purpose | + | ! Purpose (short) |
! Date Posted | ! Date Posted | ||
− | ! | + | ! Purpose (Full) |
− | ! | + | ! Pretrained_Model_G |
+ | ! Sample | ||
+ | |||
|- | |- | ||
− | + | | [https://de-next.owncube.com/index.php/s/wKjLmYsq7M5JAmx 1x_cinepak_200000] | |
− | | [https:// | + | | |[[User:Twittman|Twittman]] |
− | | | + | | 1x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] (?) |
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Compression |
− | | | + | | 2019-07-03 |
− | | | + | | Removal of Compression such as Cinepak, msvideo1 and Roq |
+ | | none | ||
| | | | ||
|- | |- | ||
− | | [https:// | + | |- |
− | | | + | | [https://de-next.owncube.com/index.php/s/wKjLmYsq7M5JAmx 1x_cinepak_alt.pth] |
− | | | + | | |buildist |
− | | | + | | 1x |
− | | | + | |[https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] |
− | | | + | | ESRGAN |
− | | | + | | Compression |
− | | | + | | |
+ | | Cinepak (only) | ||
+ | | none | ||
| | | | ||
|- | |- | ||
− | | [https://mega.nz/folder/ | + | |- |
− | | Kim2091 | + | | [https://mega.nz/folder/bYxyWaZI#YQXKPVCSPF4jzHDZUcI27A DeBink v4/v5/v6] |
− | | | + | | |[[User:Kim2091|Kim2091]] |
+ | | 1x | ||
| CC BY-NC-SA 4.0 | | CC BY-NC-SA 4.0 | ||
− | | | + | | ESRGAN |
− | | | + | | Compression |
− | | | + | | 8.6.21 |
− | | This | + | | This model removes early 2000s Bink and other compression artifacts. Works well on almost any image or video compression type. |
+ | | none | ||
| | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | + | | [https://mega.nz/folder/6cxHzIxB#IN6ZgG-S0j3LjM0x5DEqew DeBink_Lite] | |
− | | [https:// | + | | |[[User:Kim2091|Kim2091]] |
− | | | + | | 1x |
− | | | + | | CC BY-NC-SA 4.0 |
− | | | + | | ESRGAN-lite |
− | | | + | | Compression |
− | | | + | | 2021-10-30 |
− | | | + | | This model was trained on lossless video frames of Metal Arms: Glitch in the System, compressed with Bink V1 for the LR frames. It's a lot more efficient than my first DeBink model, and also has less artifacts. It's not quite as robust, but the compression is barely noticeable in videos after processing with this. |
− | | | + | | none |
− | | | + | | [https://cdn.discordapp.com/attachments/903415274521374750/904129653374078976/XB_Demo_Mov-85600_G.mp4 Video Sample] |
+ | |- | ||
+ | |||
+ | |||
|- | |- | ||
+ | | [https://mega.nz/file/rUh0WCQI#rLy6foaaeagDxPKnVCVeMghO-VZr6AtTulrXmZMT6j4 1x-RoQ_nRoll] | ||
+ | | |[[User:Kim2091|Kim2091]] | ||
+ | | 1x | ||
+ | | CC BY-NC-SA 4.0 | ||
+ | | ESRGAN | ||
+ | | Compression | ||
+ | | 2021-11-21 | ||
+ | | This model decompresses images and video compressed using RoQ. Config and presets will be added when Mega decides to let me use their site! | ||
+ | | none | ||
+ | | [https://imgsli.com/ODI5Njg Sample 1] | ||
− | + | [https://cdn.discordapp.com/attachments/911838608879677440/912086092755374200/unknown.png Sample 2] | |
+ | [https://cdn.discordapp.com/attachments/911838608879677440/912084886792314880/unknown.png Sample 3] | ||
− | + | [https://cdn.discordapp.com/attachments/911838608879677440/912085213859954788/unknown.png Sample 4] | |
− | |||
− | + | [https://cdn.discordapp.com/attachments/911838608879677440/912087766366564372/unknown.png Sample 5] | |
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | | [https://mega.nz/# | + | | [https://mega.nz/file/qAY11ZBR#zgLbwfSI2MDYHb0HxehLkq4cppEg-U9bplxHu5hVrgU 1x_DeRoqBeta-lite] |
− | | | + | | |[[User:Kim2091|Kim2091]] |
| 1x | | 1x | ||
− | | | + | | CC BY-NC-SA 4.0 |
| ESRGAN | | ESRGAN | ||
− | | | + | | Compression |
− | | | + | | 2022-07-26 |
− | | | + | | Incomplete lite model to remove ROQ compression |
− | |||
| | | | ||
+ | | [https://cdn.discordapp.com/attachments/579685650824036387/1001671437293207672/1658887461.0522466.png Sample] | ||
|- | |- | ||
− | + | | [https://icedrive.net/1/43GNBihZyi NMKD h264Texturize] | |
− | | [https:// | + | | |[[User:nmkd|Nmkd]] |
− | | | + | | 1x |
− | | | + | | WTFPL |
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Texturizing |
− | | | + | | 2020-10-20 |
− | | | + | | Tries to reverse heavy h264 compression. Fails. Can be used to texturize images though. |
− | | | + | | 4x ESRGAN |
| | | | ||
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://drive.google.com/drive/folders/1ZcMD3hy1YCm-hsrT6xYGvhboxSzhrJKg 1x_Filmify4K_v2_325000_G.pth] |
− | | | + | | Muf |
− | | | + | | 1x |
+ | | Public Domain | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | artifact |
− | | | + | | 2021-07-19 |
− | | | + | | This model attempts to make films upscaled to 4K with Topaz Gaia-HQ look more natural and filmic. It sharpens, adds film grain, and smooths out small artefacts from the upscaling process. I recommend adding a tiny amount of grain to the input to seed the model (you can do this in VEAI), otherwise the film grain will remain static across frames that don't move much. Pretrain model used with permission to relicense from Twittman. |
− | | | + | | 1x_UnResize_V3_110000_G.pth |
− | | | + | | https://imgsli.com/NjE5MTE |
− | |||
+ | https://imgsli.com/NjE5MTI | ||
− | | [https://mega.nz/# | + | https://imgsli.com/NjE5MTM |
− | | | + | |
− | | | + | https://imgsli.com/NjE5MTQ |
− | | | + | |- |
+ | |||
+ | |- | ||
+ | | [https://mega.nz/file/zAIVEaaY#AWHaCZVeIVQ8FiqsDwxQjzhiydSntFVEyGl1cCLxRzg DeIndeo (mirror)] [https://drive.google.com/file/d/1-lfgZ_6vtS9DsWU-57ig8UJExH26XmCv/view?usp=sharing DeIndeo] | ||
+ | | Wild West Quest#7975 | ||
+ | | 4x | ||
+ | | WTFPL | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | Indeo Compression Artifacts |
− | |||
| | | | ||
− | | | + | | Dataset: Custom |
+ | | [https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | ||
| | | | ||
|- | |- | ||
+ | |} | ||
− | + | ===VHS Tapes=== | |
− | + | {| class="wikitable sortable" | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
|- | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
|- | |- | ||
− | | [https:// | + | | [https://icedrive.net/0/d3bwO9Byjo 1xBaldrickVHSFix_180000_G_V0.2] |
− | | | + | | NimRodZorg |
| 1x | | 1x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | VHS |
− | | | + | | 2021-03-03 |
− | | | + | | Fixing minor VHS Chroma and Pattern Noise - NOTE: only works on deinterlaced sources |
− | | | + | | 1xESRGAN |
| | | | ||
|- | |- | ||
+ | |- | ||
+ | | [https://drive.google.com/file/d/1w88lL_XGrE8n9sSIq97nLcVASqQNCtP6/view?usp=sharing ToonVHS] | ||
+ | | Redslam | ||
+ | | 1x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | ESRGAN | ||
+ | | VHS | ||
+ | | 2022-02-06 | ||
+ | | Best when used on cartoons, it can work on anime. Due to the dataset it does struggle a bit with orange colors and grainy dark spots. This model is meant to be used to clean up the image before using it on a 2x or 4x model. | ||
+ | | 1xESRGAN | ||
+ | | [https://imgsli.com/OTQ0NjM/0/1 Examples of ToonVHS + other models] | ||
+ | |||
+ | [https://imgsli.com/OTQ0NjQ/4/5 Examples of ToonVHS by itself] | ||
+ | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/drive/folders/1NVT-5hmcrXc1d_DFjzNf-z-VfOa_xhwI?usp=sharing 2x_VHS-upscale-and-denoise_Film_477000_G] |
− | | | + | | Itewreed |
| 2x | | 2x | ||
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
| ESRGAN | | ESRGAN | ||
− | | | + | | VHS |
− | | | + | | 2021-03-28 |
− | | | + | | VHS captures of Film material, but may work on VHS recorded native SD-TV material as well. Also useable for cleaned up source material |
− | | | + | | none |
| | | | ||
|- | |- | ||
− | + | | [https://mega.nz/file/Z5IXBSrA#bE9VasE60zLqZ_NggOhs40Z9l2z8DapROZb5VX0F3h0 VHS-Sharpen-1x] | |
− | | [https:// | + | | RTX 2080 ti hoarder |
− | | | + | | 1x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | ||
| ESRGAN | | ESRGAN | ||
− | | | + | | VHS |
− | | | + | | 2021-03-19 |
− | | | + | | Make old VHS footage crispy. This model will not work on video and images with noticeable JPEG/Video compression artifacts, noticeable interlacing or haloing, heavy tape distortion/artifacts and scenes with tons of detail. For best results, use a downscaled HD capture of the VHS tape you intend to use it on. |
− | | | + | | 1xESRGAN |
− | | | + | | https://imgsli.com/NDUxNDY/2/3 |
|- | |- | ||
+ | |} | ||
+ | |||
+ | =Model Collections= | ||
+ | {| class="wikitable sortable" | ||
+ | |- | ||
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose | ||
+ | ! Date Posted | ||
+ | ! Description | ||
+ | ! Sample | ||
+ | |- | ||
− | | [https://drive.google.com/ | + | | [https://drive.google.com/drive/folders/1s39goxbCkZIk3KsM1-dJhwZyIx-iQHRy?usp=sharing OptimusPrimal's Collection] |
− | | | + | | OptimusPrimal |
− | | | + | | Various |
− | | | + | | WTFPL |
| ESRGAN | | ESRGAN | ||
− | | | + | | Collection |
− | | | + | | 2022-02-28 |
− | | | + | | I'm dumping all my models here. (I moved my favorites to a favorite folder). Most of these models work well on DVD resolution animation sources. These are all ESRGAN models. Everything is with the WTFPL license. So do whatever you want with them. Credit is not needed, but would be nice if you use them to make something. There's a few that are interpolations with other user's publicly available models, or interpolations of other user's publicly available models (so technically, these are not mine), so credit goes out to them, the only ones I can remember off the top of my head is @twittman with the Fatality model series, which are great, and @cd VSGAN && poetry install with the Sol Levante/American Dad2 models, and if you do 50/50 with those 2 models, you get a really good model that I called Soladad. |
− | |||
| | | | ||
|- | |- | ||
− | + | | [https://mega.nz/folder/WEwUCDSJ#b1eXDT9b7yMKVlOURbR4FQ Kim's Collection] | |
− | | [https:// | + | | Kim2091 |
− | | | + | | Various |
− | | | + | | CC BY-NC-SA 4.0 |
− | | | + | | Various (ESRGAN and ESRGAN-lite) |
− | | | + | | Collection |
− | + | | 2022-02-28 | |
− | | | + | | My (Kim's) main folder for hosting models. Every model of mine on this database links to subsections of this folder. If a link is broken or you just want to see nearly all of the models I've trained, look here. |
− | | | ||
− | |||
| | | | ||
|- | |- | ||
+ | | [https://mega.nz/folder/3Jo2AAAa#4CGEwUM0dKu3kkaJa-qUIA UltraMix Collection] | ||
+ | | Kim2091 | ||
+ | | Various | ||
+ | | CC BY-NC-SA 4.0 | ||
+ | | Various (ESRGAN and ESRGAN-lite) | ||
+ | | Collection | ||
+ | | 2022-06-28 | ||
+ | | This is a mixture of models based around UltraSharp and my other available models. These are usually interpolations that have separate but very helpful uses. As an example, UltraMix_Restore is a combination of UltraSharp and UniScale_Restore, and is great for video game textures. | ||
+ | | | ||
+ | |- | ||
− | | [https:// | + | | [https://icedrive.net/s/43GNBihZyi NMKD's Collection] |
− | | | + | | NMKD |
− | | | + | | Various |
− | | | + | | Various |
− | | | + | | Various (ESRGAN and ESRGAN-lite?) |
− | | | + | | Collection |
− | | 2022- | + | | 2022-02-28 |
− | | | + | | NMKD's main folder for hosting models. Nearly every one of NMKD's models posted on this wiki link to it. |
− | |||
| | | | ||
|- | |- | ||
− | |||
− | ==Pretrained | + | | [https://mega.nz/folder/BAkVjQJK#tFPH9f334BNYqEluwBVZRg Zarxrax's Collection] |
− | {| class="wikitable sortable" | + | | Zarxrax |
+ | | Various | ||
+ | | Various | ||
+ | | Compact | ||
+ | | Collection | ||
+ | | 2023-01-20 | ||
+ | | All of my compact models, including a few variations which might not be linked from elsewhere. | ||
+ | | | ||
+ | |- | ||
+ | |||
+ | | [https://drive.google.com/drive/folders/1R31KChaJiw1hbVhO4NDKHNCktzSrpJpb?usp=sharing Joey's ESRGAN Bot Collection] | ||
+ | | Various | ||
+ | | Various | ||
+ | | Various | ||
+ | | Various | ||
+ | | Collection | ||
+ | | 2022-08-04 | ||
+ | | Here is a dump of all the ESRGAN-Bot models. As it was a un-curated collection, many of the models here were never officially released, but I do not know exactly which ones. If one of your models is included here and you would like me to remove it, please let me know. | ||
+ | | | ||
+ | |- | ||
+ | |||
+ | |} | ||
+ | |||
+ | |||
+ | ==Pretrained Models== | ||
+ | Looking for official models? Look here: https://upscale.wiki/wiki/Official_Research_Models | ||
+ | |||
+ | {| class="wikitable sortable" | ||
|- | |- | ||
! Model Name | ! Model Name | ||
Line 4,301: | Line 4,585: | ||
! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/#!D940CAKR!-BAx7tSj1CgeopGkaMW31VuPsC3hvNBL35TEVAj4LIo 1xESRGAN] |
− | | | + | | victorca25 |
| 1x | | 1x | ||
− | | | + | | Apache License 2.0 |
− | | | + | | ESRGAN |
− | | Pretrained | + | | Pretrained |
− | | | + | | 2019-07-06 |
− | | | + | | |
− | | | + | | RRDB_ESRGAN_x4.pth |
| | | | ||
|- | |- | ||
− | | [https:// | + | | [https://mega.nz/#!vtgSWKQT!K7Asn2zKe4N70R2aV89KEMTKhH3aiyGAAiuQDJF09qs 2xESRGAN] |
− | | | + | | victorca25 |
| 2x | | 2x | ||
− | | | + | | Apache License 2.0 |
− | | | + | | ESRGAN |
− | | Pretrained | + | | Pretrained |
− | | | + | | 2019-07-06 |
− | | | + | | |
− | | | + | | RRDB_ESRGAN_x4.pth |
| | | | ||
|- | |- | ||
− | + | | [https://mega.nz/#!uhAVEaAA!qfwIQ44Ba3rXMAb2-M3aM3zFBCwzmyQ64IO_0O-csJE 4xESRGAN] | |
− | | [https:// | + | | xinntao |
− | | | ||
| 4x | | 4x | ||
− | | | + | | Apache License 2.0 |
− | | | + | | ESRGAN |
− | | Pretrained | + | | Pretrained |
− | | | + | | 2019-07-06 |
− | |||
− | |||
| | | | ||
− | | | + | | RRDB_ESRGAN_x4.pth |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
| | | | ||
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://mega.nz/#!6kwQiCCS!v2uN8R44vVrlzmSqffGaCnzgogkPhhl67myJbuG45SA 8xESRGAN] |
− | | | + | | victorca25 |
− | | | + | | 8x |
− | | ESRGAN | + | | Apache License 2.0 |
+ | | ESRGAN | ||
| Pretrained | | Pretrained | ||
− | | | + | | 2019-07-06 |
− | | | + | | |
− | | | + | | RRDB_ESRGAN_x4.pth |
| | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | + | | [https://mega.nz/#!btwEXAoI!nNxWI89OdQCEkcRoPEFwj6GoFN8uzZyZFaCn1wbhzKY 16xESRGAN] | |
− | + | | victorca25 | |
− | + | | 16x | |
− | + | | Apache License 2.0 | |
− | + | | ESRGAN | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | | [https://mega.nz/ | ||
− | | | ||
− | | | ||
− | | | ||
− | | | ||
| Pretrained | | Pretrained | ||
− | | | + | | 2019-07-06 |
− | |||
| | | | ||
+ | | RRDB_ESRGAN_x4.pth | ||
| | | | ||
|- | |- | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
+ | | [https://drive.google.com/open?id=1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 1x PSNR Pretrained Model] | ||
+ | | BlueAmulet | ||
+ | | 1x | ||
+ | | Apache License 2.0 (ESRGAN's license) | ||
+ | | ESRGAN | ||
+ | | Pretrained | ||
+ | | 2020-04-20 | ||
+ | | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | ||
+ | | RRDB_PSNR_x4.pth | ||
+ | | | ||
+ | |- | ||
+ | |||
− | | [https:// | + | | [https://drive.google.com/open?id=1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 2x PSNR Pretrained Model] |
− | | | + | | BlueAmulet |
| 2x | | 2x | ||
− | | | + | | Apache License 2.0 (ESRGAN's license) |
− | | | + | | ESRGAN |
− | + | | Pretrained | |
− | | | + | | 2020-04-20 |
− | | | + | | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions |
− | | | + | | RRDB_PSNR_x4.pth |
| | | | ||
− | | | + | |- |
− | |||
− | https:// | + | | [https://drive.google.com/open?id=1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 4x PSNR Pretrained Model] |
+ | | BlueAmulet | ||
+ | | 4x | ||
+ | | Apache License 2.0 (ESRGAN's license) | ||
+ | | ESRGAN | ||
+ | | Pretrained | ||
+ | | 2020-04-20 | ||
+ | | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | ||
+ | | RRDB_PSNR_x4.pth | ||
+ | | | ||
+ | |- | ||
− | |||
− | |||
− | | [https:// | + | | [https://drive.google.com/open?id=1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 8x PSNR Pretrained Model] |
− | | | + | | BlueAmulet |
− | | | + | | 8x |
− | | | + | | Apache License 2.0 (ESRGAN's license) |
− | | | + | | ESRGAN |
− | + | | Pretrained | |
− | | | + | | 2020-04-20 |
− | | | + | | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions |
− | | | + | | RRDB_PSNR_x4.pth |
− | |||
− | |||
− | |||
− | |||
| | | | ||
− | | | + | |- |
− | |||
− | https:// | + | | [https://drive.google.com/open?id=1ldwajXL50uC7PCS63B4Wato6Dnk-svNL 16x PSNR Pretrained Model] |
+ | | BlueAmulet | ||
+ | | 16x | ||
+ | | Apache License 2.0 (ESRGAN's license) | ||
+ | | ESRGAN | ||
+ | | Pretrained | ||
+ | | 2020-04-20 | ||
+ | | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | ||
+ | | RRDB_PSNR_x4.pth | ||
+ | | | ||
+ | |- | ||
− | |||
− | |||
− | | [https://mega.nz/file/ | + | | [https://mega.nz/file/Bc0SmIyK#ThTyculaFvrLGMIY8FicUUWBem8O_ZF8LgpPXCn7aVQ Compact Pretrained Models] |
| Zarxrax | | Zarxrax | ||
− | | 1x | + | | 1x-4x |
− | |[http://www.wtfpl.net WTFPL] | + | | [http://www.wtfpl.net WTFPL] |
− | | | + | | Real-ESRGAN "compact" |
− | | | + | | Pretrained |
− | | 2022- | + | | 2022-07-31 |
− | | This | + | | This is a collection of pretrained models for Real-ESRGAN's Compact architecture. There are 1x, 2x, and 4x models, as well as 1x and 2x "UltraCompact" and "SuperUltraCompact" models (think of these as the equivalent to ESRGAN "lite" models). By using these are pretrains for your models, you can ensure that your models are able to be interpolated with other Compact models that were trained from these. These pretrains are compatible with most existing compact models. |
+ | | | ||
| | | | ||
− | | | + | |- |
+ | |} | ||
− | + | ==Pretrained Discriminators== | |
− | + | {| class="wikitable sortable" | |
− | + | |- | |
+ | ! Model Name | ||
+ | ! Author | ||
+ | ! Scale | ||
+ | ! License | ||
+ | ! Architecture | ||
+ | ! Purpose (short) | ||
+ | ! Date Posted | ||
+ | ! Purpose (Full) | ||
+ | ! Pretrained_Model_G | ||
+ | ! Sample | ||
− | |||
|- | |- | ||
− | + | | [https://u.pcloud.link/publink/show?code=kZkLGpXZLPOptIrA1fjXvFdIS0NpdzuWSfkk 1x Pretrained Discriminator Pack] | |
− | | [https:// | + | | Joey |
− | | | ||
| 1x | | 1x | ||
− | |[ | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | + | | VGG |
− | | | + | | Pretrained discriminators |
− | | | + | | 2020-10-26 |
− | | | + | | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. |
+ | | none | ||
| | | | ||
− | | | + | |- |
− | |||
− | https:// | + | | [https://u.pcloud.link/publink/show?code=kZkLGpXZLPOptIrA1fjXvFdIS0NpdzuWSfkk 2x Pretrained Discriminator Pack] |
+ | | Joey | ||
+ | | 2x | ||
+ | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | ||
+ | | VGG | ||
+ | | Pretrained discriminators | ||
+ | | 2020-10-26 | ||
+ | | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. | ||
+ | | none | ||
+ | | | ||
|- | |- | ||
− | | [https:// | + | |
− | | | + | | [https://u.pcloud.link/publink/show?code=kZkLGpXZLPOptIrA1fjXvFdIS0NpdzuWSfkk 4x Pretrained Discriminator Pack] |
− | | | + | | Joey |
− | |[ | + | | 4x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | + | | VGG |
− | | | + | | Pretrained discriminators |
− | | | + | | 2020-10-26 |
− | | | + | | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. |
− | | | + | | none |
+ | | | ||
|- | |- | ||
− | + | | [https://u.pcloud.link/publink/show?code=kZkLGpXZLPOptIrA1fjXvFdIS0NpdzuWSfkk 8x Pretrained Discriminator Pack] | |
− | | [https:// | + | | Joey |
− | | | + | | 8x |
− | | | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | CC BY-NC-SA 4.0 | + | | VGG |
− | | | + | | Pretrained discriminators |
− | | | + | | 2020-10-26 |
− | | | + | | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. |
− | | | + | | none |
− | + | | | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | | | ||
− | | | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
|- | |- | ||
− | | [https:// | + | | [https://u.pcloud.link/publink/show?code=kZPxrYXZOBnSmRzYywHg9heV55yt0JvKC3gk 4x_RRDB-G_ResNet-D (Both G and D)] |
− | | | + | | Joey |
− | | | + | | 4x |
− | | [https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] | + | |[https://creativecommons.org/licenses/by-nc-sa/4.0/ CC BY-NC-SA 4.0] |
− | | | + | | ESRGAN (G) / ResNet (D) |
− | | | + | | Pretrained |
− | | | + | | 2021-01-17 |
− | | | + | | Clean bicubic downscales / Pretrained models (G/D) |
− | | | + | | RRDB_ESRGAN_x4_old_arch.pth |
− | | | + | | |
|- | |- | ||
+ | |} | ||
− | |||
=Official Models= | =Official Models= | ||
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! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
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| upscale IRL videos. Use not recommended by creator | | upscale IRL videos. Use not recommended by creator | ||
| none | | none | ||
− | | https://cdn.discordapp.com/attachments/547949806761410560/813134983236419664/100k_iter.mp4 | + | | [https://cdn.discordapp.com/attachments/547949806761410560/813134983236419664/100k_iter.mp4 Sample Video] |
|- | |- | ||
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! Purpose (Full) | ! Purpose (Full) | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
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! Description | ! Description | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
− | | [https://e1.pcloud.link/publink/show?code=kZfoGRZNuvokO5THhVzVLOt7ocHkR9vDdF7 sudo_rife4_269.662_testV1_scale1.pth] | + | | <small>[https://e1.pcloud.link/publink/show?code=kZfoGRZNuvokO5THhVzVLOt7ocHkR9vDdF7 sudo_rife4_269.662_testV1_scale1.pth]</small> |
| sudo | | sudo | ||
| 2x | | 2x | ||
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| I never really mentioned it in model-releases prior since I think not too many care about interpolation here, but I trained a rife4 model for animation a some months ago, which is better than rife4 and rife4.2 imo. Thought I should also mention it here as well. I also converted it into ncnn. (Nihuis rife ncnn models are only exported with the fastest mode and not the best quality. I exported ncnn models for the most important quality settings. Due to different export/quality settings, there are multiple models. For that reason alone, my ncnn models are much better too, since nihui only exported the fastest one.) My https://github.com/styler00dollar/VSGAN-tensorrt-docker also has the rife ncnn extention, which can use VMAF, dedup, scene detection and so on, which I would recommend. My models are in that extention as well, just select model 10, 11 or 12 and use the dev docker. That test video is done with 2x framerate, enbemble True and FastMode False, combined with scene detection and dedup stuff, tta False. Towards the best quality rife can do. Plz don't steal without credits, k thx. | | I never really mentioned it in model-releases prior since I think not too many care about interpolation here, but I trained a rife4 model for animation a some months ago, which is better than rife4 and rife4.2 imo. Thought I should also mention it here as well. I also converted it into ncnn. (Nihuis rife ncnn models are only exported with the fastest mode and not the best quality. I exported ncnn models for the most important quality settings. Due to different export/quality settings, there are multiple models. For that reason alone, my ncnn models are much better too, since nihui only exported the fastest one.) My https://github.com/styler00dollar/VSGAN-tensorrt-docker also has the rife ncnn extention, which can use VMAF, dedup, scene detection and so on, which I would recommend. My models are in that extention as well, just select model 10, 11 or 12 and use the dev docker. That test video is done with 2x framerate, enbemble True and FastMode False, combined with scene detection and dedup stuff, tta False. Towards the best quality rife can do. Plz don't steal without credits, k thx. | ||
| | | | ||
− | | https://cdn.discordapp.com/attachments/579685650824036387/990345004260151296/ngnl_sudorife.mp4 | + | | [https://cdn.discordapp.com/attachments/579685650824036387/990345004260151296/ngnl_sudorife.mp4 Sample Video] |
|- | |- | ||
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! Description | ! Description | ||
! Pretrained_Model_G | ! Pretrained_Model_G | ||
− | ! | + | ! Sample |
|- | |- | ||
Line 4,736: | Line 5,011: | ||
Plz don't steal without credits, k thx. | Plz don't steal without credits, k thx. | ||
| | | | ||
− | | https://cdn.discordapp.com/attachments/579685650824036387/1002663424695750686/output.mp4 | + | | [https://cdn.discordapp.com/attachments/579685650824036387/1002663424695750686/output.mp4 Sample Video] |
|- | |- | ||
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| 2021-09-14 | | 2021-09-14 | ||
| | | | ||
− | | My ~~first~~ (ok technically second) attempt to create a video frame interpolation model and I like how it turned out. To use it, you can either use https://gitlab.com/hubert.sontowski2007/cainapp, https://github.com/styler00dollar/Colab-CAIN or the bot in [Game Upscale] (model called rvpv1 there, just use --model rvpv1). Some demo videos in pcloud, but you need to download them. The web player seems to playback in low fps. The architecture is mainly the same to the original CAIN, but i modified the padding to be zero padding instead. ``.pt`` means JIT model, `.pth`, means normal pytorch model. Architecture file is in pcloud as well. And no, no cupscale or flowframes. Dataset: Modified Animeinterp dataset | + | | My ~~first~~ (ok technically second) attempt to create a video frame interpolation model and I like how it turned out. To use it, you can either use [https://gitlab.com/hubert.sontowski2007/cainapp cain-App], [https://github.com/styler00dollar/Colab-CAIN Colab-CAIN (no longer available)] or the bot in the [https://discord.gg/cpAUpDK Game Upscale discord] (model called rvpv1 there, just use --model rvpv1). Some demo videos in pcloud, but you need to download them. The web player seems to playback in low fps. The architecture is mainly the same to the original CAIN, but i modified the padding to be zero padding instead. ``.pt`` means JIT model, `.pth`, means normal pytorch model. Architecture file is in pcloud as well. And no, no cupscale or flowframes. Dataset: Modified Animeinterp dataset |
− | | https://files.catbox.moe/xiq9vi.mp4 | + | | [https://files.catbox.moe/xiq9vi.mp4 Sample Video] |
|- | |- | ||
Revision as of 23:41, 27 May 2023
If a model has no license, that means all rights reserved. You will need a private license or explicit permission from the creator to use it commercially or with modifications. However you may use all model here on non-commercial projects, that may not in any way cost money. If you gain permission to use a model in another way including commercially, you should still credit the author and link to the original model source. |
For Datasets to train your models, go here: https://upscale.wiki/wiki/Dataset_Database |
Looking for Official Models (Such as ESRGAN, BSRGAN, or Real-ESRGAN)? Check this page: https://upscale.wiki/wiki/Official_Research_Models |
Contents
- 1 ESRGAN ("old Architecture") Models
- 2 Model Collections
- 3 Official Models
- 4 SOFVSR Models
- 5 RIFE Models
- 6 CAIN Models
- 7 Waifu2x Models
ESRGAN ("old Architecture") Models
These are all models that use the "old" ESRGAN architecture. There are various GUIs available to inference/upscale with these models. The only actively maintained program is chaiNNer by Joey. The others are: IEU by Honh Cupscale by NMKD.
These programs can be used to train your models: BasicSR, the official ESRGAN repository (old arch tag), victorca's traiNNer (https://github.com/victorca25/traiNNer), or sudo's colab-traiNNer (https://github.com/styler00dollar/Colab-traiNNer/).
Image scaling and Video upscaling
Universal Models
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
CountryRoads | EzoGaming | 4x | WTFPL | ESRGAN | Universal Upscaler | 2021-08-26 | Streets with dense foliage in the background. Outdoor scenes. | 4xPSNR | Sample 1 |
Remacri Remacri Backup Mirror | Foolhardy | 4x | CC BY-NC-SA 4.0 | ESRGAN | General Upscaler | 2021-04-09 | A creation of BSRGAN with more details and less smoothing, made by interpolating IRL models such as Siax, Superscale, Superscale Artisoft, Pixel Perfect, etc. This was, things like skin and other details don't become mushy and blurry. | none - interpolated | |
4x-UltraSharp | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Universal Upscaler | 2021-10-27 | This is my best model yet! It generates lots and lots of detail and leaves a nice texture on images. It works on most images, whether compressed or not. It does work best on JPEG compression though, as that's mostly what it was trained on. It has the ability to restore highly compressed images as well! If you want a more balanced output, check out the UltraMix Collection down below. It's a bunch of interpolated models based around UltraSharp and my other models | 4xESRGAN | Sample 1 |
UniScale-Balanced/Strong | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Universal Upscaler | 2021-08-23 | UniScale strikes a nice balance between sharpness and realism. This model can upscale almost anything well. It was originally intended to upscale game textures, but was expanded into a universal upscaler. Interp is these two models interpolated. | 4xESRGAN | https://slow.pics/c/i75q0yN1 |
UniScaleNR-Balanced/Strong | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Universal Upscaler | 2021-08-23 | Version of UniScale trained with camera noise injection (NR = Noise Removal). This model removes noise from images while upscaling. | 4xESRGAN | https://slow.pics/c/UkCwdK13 |
UniScale_Restore | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Universal Upscaler | 2021-08-27 | UniScale_Restore has strong compression removal that helps with restoring heavily compressed or noisy images. It is intended to compete with BSRGAN. Trained with BSRGAN_Resize and Combo_Noise in traiNNer. | 4xESRGAN | Sample 1 |
UniScaleV2_Soft/Moderate/Sharp | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Universal Upscaler | 2021-09-06 | These models work great on game textures when interpolated 50/50 with UniScale_Restore, and work amazingly on uncompressed images. DO NOT USE FOR COMPRESSED IMAGES, use the original UniScale or UltraSharp for that. | 4xESRGAN | Sample 1 |
realesrgan-x4minus | DinJerr | 4x | WTFPL | Real-ESRGAN | General Upscaler | 2022-04-19 | Basically realesrgan-x4plus without the degradation training. Supposed to help retain more details, but unfortunately due to the dataset (I think) still blurs details adjacent to other objects. | realesrgan-x4plus | https://imgsli.com/MTA0OTA2 |
4x_2C2-ESRGAN_Nomos2K_200000_G.pth | Joey | 4x | MIT | 2C2-ESRGAN | General Upscaler | 2022-04-20 | Technically my previous experiment was the pretrained model, but for all intents and purposes this was trained from scratch. Description: Pretrained model for the new architecture modification I made. You can read more about it in the github README. Basically it makes smaller ESRGAN models that theoretically can produce the same level of quality. NOTE: THIS WILL NOT WORK IN CUPSCALE, IEU, OR CHAINNER (yet)! You have to use my fork to use it for now. | ||
FuzzyBox | BlueAmulet | 4x | CC BY-NC 4.0 | ESRGAN | General upscaler | 2020-07-21 | Photographs, Artwork, Textures, Anything really - Tried out a new pixel loss idea based on ensuring the HR downscaled matches the LR. Colors are pretty good as well as edges, but generated details seem slightly fuzzy hence the name. | RRDB_ESRGAN_x4 | |
Lollypop | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | General upscaler | 2020-09-11 | A universal model, that is aimed at prerendered images, but handles realistic faces, manga, pixel art and dedithering as well. Trained using the patchgan discriminator, with cx loss, cutmixup and frequency separation, it produces good results with a slight grain due to patchgan, with some sharpening using cutmixup. | 4X_esrgan.pth | |
UniversalUpscalerV2 | Mutin_Choler | 4x | WTFPL | ESRGAN | General Upscaler | 2021-04-01 | General Upscaler | 1xESRGAN | https://imgsli.com/NDc3ODA/2/1 |
NMKD Siax ("CX") | Nmkd | 4x | WTFPL | ESRGAN | General upscaler | 2020-11-06 | Universal upscaler for clean and slightly compressed images (JPEG quality 75 or better) | 4xPSNR |
Realistic Photos
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
4x_RealisticRescaler_100000_G | Mutin Choler | 4x | WTFPL | Real-ESRGAN | Realistic Photos | 2023-01-01 | This model was made to upscale realistic low-res textures that are compressed by either JPEG or BC1. From my testing, this works rather well on realistic GameCube textures such as the ones from Shrek Extra Large and the board textures from Mario Party 4. This model could also work on some real life images, especially the ones that are taken outdoors. | RealESRGAN_x4plus | https://imgsli.com/MTQ0Mzk1 |
4x-Valar | musl | 4x | CC0 | ESRGAN+ | Realistic Photos | 2021-09-16 | Meant as an experiment to test latest techniques implemented on traiNNer, including: AdaTarget, KernelGAN, UNet discriminator, nESRGAN+ arch, noise patches, camera noise, isotropic/anisotropic/sinc blur, frequency separation, contextual loss, mixup, clipL1 pixel loss, AdamP optimizer, etc. The config file is provided on the download link above. I encourage everybody to mirror the model, distribute and modify it in anywway you want. | 4x_RRDB_ESRGAN | Sample 1 |
4x_Box | buildist | 4x | GNU GPLv3 | ESRGAN | Realistic Photos | 2019-06-20 | RRDB_ESRGAN_x4 replacement for stuff that's supposed to look realistic. | none | |
Nickelback | BlackScout | 4x | GNU GPLv3 | ESRGAN | Realistic Photos | 2020-02-12 | this model aims to improve further on what has been achieved by the regular 4xESRGAN and also 4xBox. It can upscale most pictures/photos (granted they are clean enough) without destroying as much detail as the aforementioned models. It generates less moiré like patterns and keeps details without oversharpening or blurring the image too much. | 4xESRGAN | |
NickelbackFS | BlackScout | 4x | GNU GPLv3 | ESRGAN-FS | Realistic Photos | 2020-07-10 | This model aims to improve further on what has been achieved by the old Nickelback which was an improvement attempt over 4xESRGAN and also 4xBox. It can upscale most pictures/photos (granted they are clean enough) without destroying as much detail as Box and basic ESRGAN. | 4xESRGAN | |
4x NMKD Superscale | Nmkd | 4x | WTFPL | ESRGAN | Clean Real-World Images | 2020-07-22 | Upscaling of realistic images/photos with noise and compression artifacts | 4xESRGAN | |
Misc | Alsa | 4x | CC BY-NC-SA 4.0 | ESRGAN | General Upscaler | The Misc model is trained on various pictures shot by myself (Alsa), including bricks, stone, dirt, grass, plants, wood, bark, metal and a few others. | Manga109Attempt |
Art/Pixel Art
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
4x_xbrz_90k | LyonHrt | 4x | CC BY-NC 4.0 | ESRGAN | Pixel Art | 2019-06-05 | Xbrz style pixel art upscaler | 4xPSNR | |
Rebout | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art/Sprites | 2019-08-04 | For upscaling character sprites | Detoon | |
Rebout Blend | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art/Sprites | Dataset: Custom prepared sprites from kof 94 rebout, which with gradients blending | Detoon | ||
Arzenal (v1.1) | ComputerK | 8x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art | Smooth general pixel art, Minecraft textures | Interpolated from nmkd's pixel art upscaling models with different interpolation settings and de-dithered versions | ||
4x_scalenx_90k | LyonHrt | 4x | CC BY-NC 4.0 | ESRGAN | Pixel Art | 2019-06-15 | Scalenx style pixel art upscaler | 4xPSNR | |
4x_xbrz+dd_260k | LyonHrt | 4x | CC BY-NC 4.0 | ESRGAN | Pixel Art | 2019-06-17 | xbrz plus dedithering style pixel-art upscaling model to wiki under specialised | 4x_xbrz_90k | |
Lady0101_208000.pth | DinJerr | 4x | ESRGAN | Pixel Art/Paintings | 2019-07-25 | Upscale pixel art/paintings to digital painting style | WaifuGAN_v3_30000.pth | ||
Fatality (4x_Fatality_01.pth) | twittman | 4x | ESRGAN | Pixel Art/Sprites | 2019-07-29 | Upscales medium resolution Sprites, dithered or undithered, can also upscale manga/anime and gameboy camera images. | 4x_Faces_04_N_180000_G.pth | ||
Fatality MK2 (4x_Fatality_MKII_90000_G.pth) | twittman | 4x | ESRGAN | Pixel Art/Sprites | Dataset: Anime, Manga and some real life | A previously attempted MK2 | |||
Fatal Pixels (4x_FatalPixels_340000_G.pth) | twittman | 4x | ESRGAN | Pixel Art/Sprites | Dataset: Anime, Manga | Fatality_MKII_90k | |||
Faithful 2x | Joey | 2x | CC-BY-NC 4.0 | ESRGAN | Pixel Art | 2019-09-08 | 2xESRGAN | ||
deviantPixelHD | raulsangonzalo | 4x | You're free to use this model for all non-commercial projects and interpolation, please give credit if featured in any projects | ESRGAN | Pixel Art | 2019-09-09 | Similar to Manga109, can be used as a general digital upscaler as well as with pixel art | RRDB_PSNR_x4 | Video Samples |
4x_BS_Deviance | systemd-resolved/BlackScout | 4x | GNU GPLv3 | ESRGAN | Art | 2020-02-25 | This model upscales Digital Drawings. It was trained on random drawings found on DeviantArt. Mostly Landscape and Scenery and Illustrations of Characters. It does fairly well and works on many different styles. | 4xESRGAN | |
4xSmoothRealism | Joey | 4x | CC BY-NC 4.0 | ESRGAN | Pixel Art | 2020-03-04 | Pixel art, rocky/grainy textures? Quantization smoothing, adding detail. | 4x_RRDB_PSNR_old_arch.pth | |
8x_HugePeeps_v1 | DinJerr | 8x | CC BY-NC 4.0 | ESRGAN | Art/People | 2020-06-16 | Painted humans | TGHQFace8x | |
ArtStation1337 | DinJerr | 4x | CC BY-NC 4.0 | ESRGAN | Digital Art/People | 2019-08-21 | Mainly for digital art, but can be used to upscale pixel art. | ||
4x_BS_DevianceV2 | systemd-resolved/BlackScout | 4x | GNU GPLv3 | ESRGAN-FS | Art | 2020-07-25 | upscales Digital Drawings. It was trained on random drawings found on DeviantArt. Mostly Landscape and Scenery and Illustrations of Characters. It does fairly well and works on many different styles. | 4xESRGAN | |
4x_BS_DevianceMIP | systemd-resolved/BlackScout | 4x | GNU GPLv3 | ESRGAN-FS | Art | 2020-07-25 | upscales Digital Drawings. It was trained on random drawings found on DeviantArt. Mostly Landscape and Scenery and Illustrations of Characters. It does fairly well and works on many different styles. | 4xESRGAN | |
4x_Struzan | Laserschwert | 4x | CC BY-NC-SA 4.0 | ESRGAN | Art | 2020-10-12 | Upscaling airbrush/pencil-based artwork | 4xPSNR | Sample Gallery |
4x_PixelPerfectV4_137000_G | Mutin Choler | 4x | WTFPL | ESRGAN | Pixel Art/Sprites | 2020-11-16 | Sprite Upscaler | 4xESRGAN | https://imgsli.com/MzgxMTc/1/2 |
BigFArt | DinJerr | 4x | CC BY-NC 4.0 | ESRGAN | Pixel art | 2020-15-31 | Larger-scaled pixels to digital painting | Face Focus | |
MS Unpainter | FoolhardyVEVO | 8x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art | 2021-03-24 | Low-resolution MS Paint drawings, general pixel art, and general dithered pixel art, all kinds of pixel art | A mix of: 8x_glasshopper_ArzenalV1.1, 8x_glasshopper_MS-Unpainter, 8x_NMKD-Sphax + Sphax de-dither, and 8x_NMKD-YanderePixelArt4 + Yandere De-Dither, all interpolated with adjustments using the interpolate function in Cupscale | |
MS Unpainter De-Dither | FoolhardyVEVO | 8x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art | 2021-03-24 | Low-resolution MS Paint drawings, general pixel art, and general dithered pixel art, all kinds of pixel art | A mix of: 8x_glasshopper_ArzenalV1.1, 8x_glasshopper_MS-Unpainter, 8x_NMKD-Sphax + Sphax de-dither, and 8x_NMKD-YanderePixelArt4 + Yandere De-Dither, all interpolated with adjustments using the interpolate function in Cupscale | |
UltraFArt_v3 Suite | DinJerr | 4x | CC BY-NC-SA 4.0 | ESRGAN | Art | 2021-05-14 | Illustrations with with larger shaped features (?). | 4x_UltraFArt | |
HugePaint | DinJerr | 8x | CC BY-NC 4.0 | ESRGAN | Digital Illustrations | Trained on a variety of images from ArtStation | HugePeeps | ||
NXbrz | Archerpolation | 4x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art | 2021-06-09 | Basic pixel art upscaling, for people who want a more simpler style and lightweight pixel art upscaling model. | Sample Gallery |
Drawn Material
Anime and Cartoons
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
4x-AnimeSharp | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Anime or Text | 2021-12-28 | 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. | Text Sample | |
4x-AnimeSharp-lite | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN-lite | Anime | 2022-02-11 | This model is a lite version of AnimeSharp. It was trained using student-teacher learning (if i'm using the term properly), where the HRs are LRs upscaled by the full size AnimeSharp ESRGAN model, and the lite model is trained on those outputs as the HR. It works best on clean or slightly blurry anime. Downscale by 50% first in almost all cases | Sample 1 | |
sudo_RealESRGAN2x_3.332.758_G.pth / sudo_RealESRGAN2x_Dropout_ 3.799.042_G.pth (pcloud)
sudo_RealESRGAN2x_3.332.758_G.pth / sudo_RealESRGAN2x_Dropout_ 3.799.042_G.pth (mediafire) |
sudo | 2x | CC BY-NC-SA 4.0 | ESRGAN (6B) | Anime | 2022-06-25 | Tried to make the best 2x model there is for drawings. I think i archived that. And yes, it is nearly 3.8 million iterations (probably a record nobody will beat here), took me nearly half a year to train. It can happen that in one edge is a noisy pattern in edges. You can use padding/crop for that. I aimed for perceptual quality without zooming in like 400%. Since RealESRGAN is 4x, I downscaled these images with bicubic. I would recommend my VSGAN code though and just load the onnx. https://github.com/styler00dollar/VSGAN-tensorrt-docker I just wanted a good 2x model for animations, but that model can also be used for wallpapers and so on. Before I hear people complaining, the dropout model is a modified architecture. Stuff like cupscale or chaiNNer won't work with pth. Load the onnx with VSGAN or chaiNNer. I did add the model before switching to dropout though, which is normal ESRGAN pth, that one should work everywhere. I also converted everything into onnx, jit and ncnn, so pretty much everything there is. If you want to use ncnn, don't use nihuis code (that also includes cupscale), these codes don't include propper tiling in C++, which is very bad for this model. I think chaiNNer should have overlap/padding with ncnn, so use that instead if you really want ncnn. Plz don't steal without credits, k thx. | Pretrained_Model_G: RealESRGAN_x4plus_anime_6B.pth /
RealESRGAN_x4plus_anime_6B.pth (sudo_RealESRGAN2x_ 3.332.758_G.pth) |
Sample 1 |
sudo_UltraCompact_2x_1.121.175_G.pth (pcloud) / sudo_UltraCompact_2x_1.121.175_G.pth (mediafire) | sudo | 2x | CC BY-NC-SA 4.0 | Compact | Realtime animation restauration and doing stuff like deblur and compression artefact removal | 2022-05-29 | My first attempt to make a REALTIME 2x upscaling model while also applying teacher student learning. It beats Anime4k in every way. These benchmarks use a 3060ti and it shows that everything better than a 3060ti should be able to handle 1080p input if you create engine files and use my TensorRT code. You can see in the readme how to convert onnx files into engines. The 2 right bars compare normal Compact2 and Ultracompact in speed, the 2 on the left showcase older apis I used which isn't too important for this showcase. To use this, you need to use my code which is https://github.com/styler00dollar/VSGAN-tensorrt-docker. If you use Manjaro, it is also possible to pipe the data stream directly into mpv, so you can watch it in a video player without rendering a video. Yeah the model does seem a little noisy if you zoom in a lot, but don't forget that the model itself is only 1.2mb. I think it does quite well. I still try to improve on fast models, but this is good enough to share as a first model. Plz don't steal without credits, k thx. | RealESRGANv2-animevideo-xsx2.pth
(Teacher: RealESRGANv2-animevideo-xsx2.pth) |
Sample 1 |
2x_Bubble_AnimeScale_Compact_v1 | Bubblemint#6472 | 2x | CC BY-NC-SA 4.0 | Real-ESRGAN Compact | Anime or Text | 2022-11-13 | 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. | 4x_muy4_035_1.pth | https://imgsli.com/MTM0MzMx |
2x_Bubble_AnimeScale_SwinIR_Small_ v1 | Bubblemint#6472 | 2x | CC BY-NC-SA 4.0 | SwinIR Small | Anime or Text | 2022-11-13 | 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. | None | https://imgsli.com/MTM2MjAx |
escale | katoumegumi_#3231 | 4x | WTFPL | ESRGAN | Anime / Visual Novel Art | 2022-12-17 | Third iteration of my eroge upscaling model. Discriminator: Google Drive | https://slow.pics/c/fqjAhnjH | |
4x_eula_anifilm_v1_225k | eula | 4x | CC BY-NC-SA 4.0 | ESRGAN | Anime or Text | 2022-12-14 | Upscaling cel animation. Trained this more than a year ago, releasing cause I've got a much better v2 and v3 now. | 4xPSNR | https://slow.pics/c/UrnFYuXX |
2x / 4x-anifilm_compact | Kim2091 | 2x and 4x | CC BY-NC-SA 4.0 | Compact | Animation | 2022-08-02 | 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. |
4x_Compact_Pretrain.pth | 2x Comparison:
4x Comparison: |
LD-Anime_Compact | Zarxrax / Skr | 2x | CC BY-NC-SA 4.0 | Compact | Animation | 2022-12-22 | 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. | 2x_Compact_Pretrain.pth | https://imgsli.com/MTQyMzM3/0/1 |
Futsuu Anime | Zarxrax | 2x | WTFPL | Compact | Animation | 2023-1-18 | 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. | 2x_Compact_Pretrain.pth | https://imgsli.com/MTQ4MDM2/ |
2xGT-evA.pth | evA-01 | 2x | CC BY-NC-SA 4.0 | Real-ESRGAN Compact | Anime or Text | 2022-12-14 | 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. | 2x_Compact_Pretrain.pth | Sample 1 |
1xEpsilon-one-compact.pth | evA-01 | 1x | CC BY-NC-SA 4.0 | Real-ESRGAN Compact | Anime or Text | 2022-12-03 | 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. | 1x_Compact_Pretrain.pth | https://imgsli.com/MTM3Mzgz/2/3
https://imgsli.com/MTM3Mzg1/2/3 https://imgsli.com/MTM3Mzg2/0/1
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Sol Levante NTSC2HD | Phoenix | 4x | UNLICENSE | ESRGAN | Anime/Pretrained | 2020-04-08 | NTSC DVD-spec encode x4 scale super-resolution for Anime Drawing style content. The dataset has a LOT of data throughout almost every frame, so it had a lot of stuff to learn. The resulting DVD-spec encode also had some blocking at times so it also learned to fight off blocking. | RRDB_PSNR_x4 | |
2x_AnimeClassics_UltraLite_510K | CG1989 | 2x | CC BY-NC-SA 4.0 | ESRGAN | Anime/Pretrained | 2022-03-08 | 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. | 2X_DigitalFilmV5_Lite.pth | Sample 1 |
600k 650k BooruGan | Tal | 4x | WTFPL | ESRGAN | Anime | 2021-11-26 | This model is designed to mainly upscale anime artworks. If you have issues with chroma then try the 600k iterations release. | 4x_Manga109Attempt | Sample 1 |
2x_Byousoku_5_Centimeter.pth | Mystery_Bullet#0642 (Shady Adel) | 2x | GNU GPLv3 | ESRGAN | Anime/Pretrained | 2020-04-08 | Anime landscape upscale. Trained on Frames from BluRay of Byousoku 5 Centimeter | 2xESRGAN | |
4x_OLDIES_290000_G_FINAL | solidd93110 | 4x | WTFPL | ESRGAN | Anime | 2020-08-16 | i made this model to upscale old anime and denoise. | RRDB_PSNR_x4.pth | |
fidelbd_pokemodel | Neo-Raws#4055 | 2x | WTFPL | ESRGAN | Anime | 2020-08-29 | Made this model to upscale old anime that looks blurry. | 2xESRGAN | https://imgsli.com/MjExMjQ/ |
4x_OLDIES_ALTERNATIVE_FINAL.pth | solidd93110 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Anime | 2020-09-01 | This model was made for my project captain tsubasa anime so i don't know if it works good for anything else. just try it ;) | RRDB_PSNR_x4.pth | https://imgsli.com/MjEzMDU |
2x_SHARP_ANIME_V1 | solidd93110 | 2x | CC BY-NC-SA 4.0 | ESRGAN | Anime | 2020-09-12 | this model has been trained to work on lines and details - works well on animes which have fairly fine lines at the base but also the video must be progressive or deinterlaced | 2xPSNR.pth | https://imgsli.com/MjIwMDY |
MeguUp | katoumegumi_#3231 | GNU GPLv3. | ESRGAN | Anime | 2020-09-16 | Upscaling of lossless (uncompressed) anime art. | Interpolated custom, hence the license. | SYNLA: LyonHrt (bloc97 dataset, MIT license).
Fatal Pixels, Fatality Anime: twittman (CC BY-NC-SA 4.0, acquired special permission to relicense. Screencap). Deviance: BlackScout (GNU GPLv3) | |
NMKD UltraYandere | Nmkd | 4x | WTFPL | ESRGAN | Art/Anime | 2020-10-08 | Highly flexible 2D Art upscaling | 4xESRGAN | |
NMKD UltraYandere Lite | Nmkd | 4x | WTFPL | ESRGAN Lite [nf=32 nb=12] | Anime | 2020-10-15 | Fast Anime/Art upscaling | 4x_DIV2K-Lite | |
2x_pokemodel_lite_100000_G | Neo-Raws#4055 | 2x | WTFPL | ESRGAN | Anime | 2020-11-01 | Upscale old anime like pokemon | none | https://imgsli.com/Mjc3Nzk |
2x_SHARP_ANIME_V2 | solidd93110 | 2x | CC BY-NC-SA 4.0 | ESRGAN | Anime | 2020-12-09 | 2x_PSNR.pth | https://imgsli.com/MzI0MDk | |
2x_BIGOLDIES_415000_G.pth | solidd93110 | 2x | CC BY-NC-SA 4.0 | ESRGAN | Anime | 2020-12-09 | upscaling old anime. help to denoise and find lines and dehalo | 2x_PSNR.pth | https://imgsli.com/MzI0MDc |
NMKD YandereNeo | Nmkd | 2x | WTFPL | ESRGAN (Lite) | Anime | 2021-01-26 | https://i.imgur.com/oxs71v5.png
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NMKD YandereNeo | Nmkd | 4x | WTFPL | ESRGAN (Lite) | Anime | 2021-01-26 | 4x_DIV2K-Lite_1M | https://i.imgur.com/oxs71v5.png | |
2x_Waifaux-NL3-SuperLite | Joey | 2x | CC BY-NC-SA 4.0 | ESRGAN | 2021-02-23 | Trained this model to see how it would work trying to essentially get the same results as Waifu2x but with ESRGAN | none | ||
2x_Waifaux-NL3-SRResNet | Joey | 2x | CC BY-NC-SA 4.0 | EDSR (SRResNet) | 2021-02-25 | Emulating Waifu2x at Noise Level 3 NOTE: You can't use this with regular esrgan forks or the bot, it has to be run through basicsr | none | ||
4x_Training4Melozard_Anime | Joey | 4x | Whatever @B.Melozard2 wants | ESRGAN | Anime | 2021-03-17 | RRDB_ESRGAN_x4_old_arch | ||
2x_LD-Anime_Skr_v1.0 | Skr | 2x | CC BY-NC-SA 4.0 | ESRGAN | Denoise/Dehalo | 2021-04-17 | Denoise, dehalo, derainbow old anime | 2xESRGAN | https://imgsli.com/NTA3MDU/ |
2x_KemonoScale_v2 | EzoGaming | 2x | CC BY-NC-SA 4.0 | ESRGAN | Anime | 2021-06-05 | Upscaling frames from Irodori anime (namely kemono friends) from 540p (the source render resolution) to 1080p, low resolution flat shaded art, de-JPEG of the aforementioned | x2_CGIMaster_v1 | Sample |
4x_muy4_035_1.pth | katoumegumi_ | 4x | WTFPL | ESRGAN | Anime | 2021-07-18 | Upscaling of anime art (Specifically visual novel CG art) | Sample 1
(Hakurei Reimu from Touhou Project illustrated by "okawa friend") (Kitaooji Karen from Making * Lovers developed by SMEE.)(edited) | |
Falcon Fanart | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Anime | not on discord | 4xPSNR | ||
1x_BroadcastToStudioLite_485k | SaurusX | 1x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2022-03-05 | 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. | Sample 1 |
2x_SwatKats_154000_G | SaurusX | 2x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-11-17 | In addition to removing the vertical blur, the model upscales, sharpens and will remove MPEG-2 artifacting and a small amount of rainbowing and dot crawl. Another series afflicted with the vertical blur is Avatar the Last Airbender, which can be repaired by this model. The video fed into the model MUST be 540 vertical for the deblur to work properly. | 2xESRGAN | https://imgsli.com/NzM2MDY |
1x_SwatKatsLite_360000_G.pth | SaurusX | 1x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-11-17 | 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. | 2xESRGAN | https://slow.pics/c/F4ilU8PM |
1x_SheeepIt! | Kim2091 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2022-07-21 | 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. | Sample 1 |
2x-UniScale_CartoonRestore-lite | Kim2091 | 2x | CC BY-NC-SA 4.0 | ESRGAN | Animation, Pixel Art | 2021-08-31 | This model has VERY strong compression removal and line restructuring that allows it to restore any heavily compressed drawings, animation, cartoons, or anime. Also works on games as well as DDS compression. It renders frames very quickly and is very viable for restoring videos. | 4x-MMScale | Comparisons: |
2x_ATLA_KORRA_336200_G.pth | aptitude | 2x | WTFPL | ESRGAN | Animation | 2021-07-22 | Upscaling of Animation based on The Legend of Korra. | 2xESRGAN.pth | https://imgsli.com/NjIzMzU |
8x_BoyMeBob-Redux | Joey | 8x | CC BY-NC-SA 4.0 | ESRGAN+ (Joey's fork, eFonte fork, or iNNfer required to use) | Animation | 2021-08-19 | Upscaling cartoons | 8xBoyMeBob (unreleased) which used 8xESRGAN | Examples |
Spongebob (4x_SpongeBob_235000_G / 4xSpongebob) | Joey | 4x | CC-BY-NC 4.0 | ESRGAN | Animation | 2019-09-12 | 4xESRGAN | ||
Spongebob De-Quantize | Joey | 1x | CC-BY-NC 4.0 | ESRGAN | Animation - Quantized | 2019-11-02 | Removed color quantization/indexing and dithering from cartoon style images and textures | 1x_1xDEDITHER_32_512_126900_G | |
4x Spongebob v6 Deblur | Joey | 4x | CC-BY-NC 4.0 | ESRGAN | Animation | 2019-11-08 | After not being entirely happy with the main Spongebob v6 model, I trained a new one with blurring OTF options and two different downscale types. This one is much better in my opinion. | 4x Spongebob v6 | |
4x Spongebob v6 De-Quantize | Joey | 4x | CC-BY-NC 4.0 | ESRGAN | Animation - Quantized | 2019-11-08 | A model I trained to do both de-quantizing as well as upscaling. The results are pretty blurry but it works decently for what it is. | 4x Spongebob v6 | |
4x Spongebob v6 | Joey | 4x | CC-BY-NC 4.0 | ESRGAN | Animation | 2019-11-08 | New version of the Spongebob model. Ideally it's a lot sharper and cleaner but I'm still not sure if it works better than the old one. From what I can tell it's better in many cases. | 4xESRGAN | |
SpongeBob.CEL.2.HD.125ki.499e-PHOENiX.pth | Phoenix | 4x | GPLv3 - SHARE YOUR CHANGES - If you use this as a pretrained model, share your new model!!! | ESRGAN | Animation | 2019-12-24 | Restorative CEL Animation MPEG-1 and 2 Model specifically crafted for SpongeBob S01. | RRDB_PSNR_x4.pth | |
1x_SpongeBC1-Lite | Joey | 1x | CC BY-NC-SA 4.0 | BC1/DXT1 compression | 2020-11-01 | First ever lite BC1/DXT1 model. Probably only useful for cartoony textures like those in spongebob games or other cartoon licensed games. | 1x_DIV2K-Lite_80k | ||
4x_SpongeBob-Reloaded | Joey | 4x | CC BY-NC-SA 4.0 | ESRGAN | Animation, Pixel Art | 2020-12-11 | 4xSpongeBob | ||
4x_SpongeBob-Reloaded-SWAG | Joey | 4x | CC BY-NC-SA 4.0 | ESRGAN | Animation, Pixel Art | 2020-12-11 | 4xSpongeBob | ||
American Dad 2 (American.Dad.2.HD.150ki.5e-PHOENiX.pth) | PHEONiX (?) | 4x | ESRGAN | Animation | American Dad | ||||
FatalimiX | Twittman | 4x | CC BY-NC-SA 4.0 (?) | ESRGAN | Animation | 2019-10-29 | Comic and Cartoon style images | 4x_Fatality_MKII_90000_G_02.pth | |
Comic Book | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Animation | Comic / Drawings. Trained on Custom (Spider-Man) dataset | none (no interpolation) | ||
Fatal_Anime | Twittman | 4x | CC BY-NC-SA 4.0 (?) | ESRGAN | Animation | Trained on Anime and Manga images | none (no interpolation) | ||
4x_AbeScale | mitch#1337 | 4x | GNU | ESRGAN | Linework Cartoons | Dataset: LR: Clone High DVD, HR: Re-illustrated Vectors from Frames | 4xESRGAN | ||
2x_Loyaldk-SuperPony_370000 V1.0 | ChaseMMD | 2x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-02-24 | Upscale MLP episodes | 2x_ERGAN | https://imgsli.com/NDIwNTY |
2x_Loyaldk-LitePony_380500 V1.0 | ChaseMMD | 2x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-03-01 | Upscale MLP episodes. Liter version. | 2x_ESRGAN | |
2x_Loyaldk-LitePony_500000_V2.0 | ChaseMMD#6957 | 2x | CC BY-NC-SA 4.0 | ESRGAN (NF=32, NB=12) | Animation | 2021-04-06 | Upscale MLP episodes. Liter version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. | none | |
2x_Loyaldk-MediumPony_500000_V2.0 | ChaseMMD | 2x | CC BY-NC-SA 4.0 | ESRGAN (NF=48, NB=18) | Animation | 2021-04-11 | Upscale MLP episodes. Liter version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. Leaves more blobs when converting detail to blobs compared to litepony | none | |
4x_Loyaldk-LitePony_500000_V2.0 | ChaseMMD | 4x | CC BY-NC-SA 4.0 | ESRGAN (NF=32, NB=12) | Animation | 2021-04-12 | Good for Vector 2D art however converts detail to blobs. Quality seems weak with this one. However posting anyways to see if a use is found. | none | |
2x_Loyaldk-SuperPony_500000_V2.0 | ChaseMMD | 2x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-04-30 | Upscale MLP episodes. Full version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. | none | |
4x_Loyaldk-SuperPony_500000_V2.0 | ChaseMMD | 4x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-04-30 | Upscale MLP episodes. Full version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. | none | |
4x_Loyaldk-MediumPony_500000_V2.0 | ChaseMMD | 4x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-04-30 | Upscale MLP episodes. Full version. Able to handle compression better compared to V1.0 and no longer creates halo's/rainbows. Good for Vector 2D art however converts detail to blobs. | none | |
Platoon Model Set | ChaseMMD | 4x | CC BY-NC-SA 4.0 | ESRGAN | Animation | 2021-06-07 | 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. | Pony Models |
Anime and Cartoon Restoration
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_HurrDeblur_SuperUltraCompact | Zarxrax | 1x | WTFPL | Compact
[nf:24 nc:8] |
Animation | 2022-06-04 | This is a sharpening/deblurring model for anime video. It was created with three goals in mind:
Despite that last point, this is not intended to be used on modern anime which makes heavy of use depth-of-field effects. |
https://imgsli.com/MTEwOTg4 | |
1x_AnimeUndeint_Compact | Zarxrax | 1x | WTFPL | Compact | Animation | 2022-06-05 | 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. | https://imgsli.com/MTExMTE0 | |
1x_BleedOut_Compact | Zarxrax | 1x | WTFPL | Compact | Animation | 2022-07-25 | 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. | https://imgsli.com/MTE4MjEz | |
1x_Dotzilla_Compact | Zarxrax | 1x | WTFPL | Compact | Animation | 2022-12-09 | Wipes out dot crawl and rainbows in animation. | 1x_Compact_Pretrain.pth | https://imgsli.com/MTM4ODkz |
Digital Animation
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
4x_DigitalFake-2.1 | Joey | 4x | CC BY-NC-SA 4.0 | ESRGAN | Digital Animation | 2021-02-18 | Replica of DigitalFrames 2.1 but interpolatable | RRDB_ESRGAN_x4_old_arch.pth | |
4X_KCJPUNK_1.0233089 G.pth | KCJPUNK | 4x | CC BY-NC-SA 4.0 | ESRGAN | Digital Animation | 2021-03-23 | Up-scaling Digital Animation | 4x_fatal_Anime_500000_G | |
2X_KcjpunkAnime_2.0_Lite_196496_G | KCJPUNK | 2x | CC BY-NC-SA 4.0 | ESRGAN-lite | Digital Animation | 2021-03-23 | Up-scaling Digital Animation | This is my first attempt to make Light model so I started with 2x version. This model is much faster and give better results than my previous one. | |
2x_DigitoonLite_216k | SaurusX | 2x | CC BY-NC-SA 4.0 | ESRGAN-lite | Digital Animation | 2022-07-05 | 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. | 2x_DigiGradients_Lite_486k.pth | https://imgsli.com/MTE1Mzg4 |
2x_DigiGradients_Lite_486k | SaurusX | 2x | CC BY-NC-SA 4.0 | ESRGAN-lite | Digital Animation | 2022-08-24 | A very focused model meant for upscaling the TMNT 2003 DVDs. Degradations were added via AVISynth in order to match the video on the TMNT 2003 DVDs to correct the source problems. Problems corrected include aliased red chroma, chroma vertical blur, bad deinterlacing, banding, compression "grain", and poor animation line detail. The AVS scripts for the LR's were run through HCEnc to get authentic low bit rate MPEG-2 artifacts for fixing. By design, the final model gives a very digital-looking result and does not do a good job of retaining textures as the style of TMNT 2003 is all flats and gradients. | none | https://imgsli.com/MTAxNjc1 |
2x_DigitalFlim_SuperUltraCompact | Zarxrax | 2x | WTFPL | Compact
[nf:24 nc:8] |
Animation | 2022-05-14 | 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. | https://imgsli.com/MTA3ODYx |
Manga
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
FSMangaV2 | Jacob_ | 4x | CC BY-NC-SA 4.0 | ESRGAN | Manga | 2020-12-14 | Manga-style images with or without dithering - cartoons, maybe pixel art, etc | RRDB_PSNR_x4 | https://i.imgur.com/oVBVthF.png |
4x_eula_digimanga_bw_v1_860k | end user license agreement#9756 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Manga | 2022-1-26 | Black and white digital manga with halftones. | 4xPSNR | Clean |
4x_eula_digimanga_bw_v2_nc1_307k | end user license agreement#9756 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Manga | 2022-08-17 | 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. |
4x_eula_digimanga_bw_v1_860k | https://slow.pics/c/Asbu0xgz |
MangaScaleV3 | Bunzero++ | 2x | CC BY-NC-SA 4.0 | ESRGAN+ | Manga | 2021-05-24 | To upscale manga including halftones, instead of trying to smooth them out. | unreleased model | https://imgsli.com/NTUyMjg |
Manga109Attempt | Kingdomakrillic | 4x | CC BY 4.0 | ESRGAN | Anime / Manga | Pretrained model: 4xPSNR | Manga109 |
Drawings
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample
|
---|---|---|---|---|---|---|---|---|---|
KDM003_scans_1x.pth | BoxDrop | 1x | ESRGAN | Art | 2019-07-29 | Clean up model for scanned illustrations. - Made to remove moire patterns, reduce small imperfections, and correct mild compression artifacts in scanned Kingdom Death: Monster illustrations. CMYK printing often shifts colors, so this is intended to reverse that color shifting as well. | Failed attempts based on ESRGAN_1x_JPEG_80to100 | ||
DigiPaint | Rastrum | 4x | CC0 | ESRGAN | Art | 2019-09-07 | Digital Art Upscaler | 4xfalcoon300(manga).pth |
Cel Animation
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
DigitalFilmV5 Lite | OptimusPrimal | 2x | WTFPL | ESRGAN | Traditional Animation | 2021-02-19 | Upscaling Dragon Ball Z DBox DVD's. - grainy sources. It keeps some grain, but also doing some cleaning, sharpening, and fixing. | none | https://imgsli.com/NDE0MzQ |
4x_HellinaCel | VGDCKeroro | 4x | fuckin do whatever | ESRGAN | Traditional Animation | 2021-03-21 | 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. | 4xESRGAN | https://imgsli.com/NDU2MjU |
Image Restoration
Image Compression
JPEG Artifacts
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
JPG (00-20%) | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | JPEG | Trained on Custom (CC0 Textures) | JPEG models by Alsa | ||
JPG (20-40%) | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | JPEG | Trained on Custom (CC0 Textures) | JPEG models by Alsa | ||
JPG (40-60%) | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | JPEG | Trained on Custom (CC0 Textures) | JPEG models by Alsa | ||
JPG (60-80%) | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | JPEG | Trained on Custom (CC0 Textures) | JPEG models by Alsa | ||
JPG (80-100%) | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | JPEG | Trained on Custom (CC0 Textures) | JPEG models by Alsa | ||
JPG (00-20%) | Alsa | 1x | CC BY-NC-SA 4.0 | ESRGAN | JPEG | Trained on Custom (Photos / Manga) | |||
JPG (20-40%) | Alsa | 1x | CC BY-NC-SA 4.0 | ESRGAN | JPEG | Trained on Custom (Photos / Manga) | |||
JPG (40-60%) | Alsa | 1x | CC BY-NC-SA 4.0 | ESRGAN | JPEG | Trained on Custom (Photos / Manga) | |||
JPG (60-80%) | Alsa | 1x | CC BY-NC-SA 4.0 | ESRGAN | JPEG | Trained on Custom (Photos / Manga) | |||
JPG (80-100%) | Alsa | 1x | CC BY-NC-SA 4.0 | ESRGAN | JPEG | Trained on Custom (Photos / Manga) | |||
Kim2091_DeJpeg_v0 | Kim2091 | 1x | CC BY-NC-SA 4.0 | ESRGAN Superlite | JPEG | Model I forgot to release. This doesn't totally remove JPEG artifacts, but it does a decent job at a fast rate. It seemingly does a better job of retaining detail than some other JPEG models. The model is incomplete, I need to train it further on compact rather than ESRGAN. This is just a temporary release | Custom JPEG dataset | Sample 1 | |
4x NMKD-PatchySharp | nmkd | 4x | WTFPL | ESRGAN (Old Arch) | Art/CGI | 2020-09-12 | Upscaler for clean images or images with compression artifacts (jpeg quality >75) - Produces very sharp lines/edges due to NN-Filtered HR images. Proven to produce very, very good results on drawings (sharp lines) and CGI, but should also work pretty well for real-world images. | 4xESRGAN | https://i.imgur.com/PzFkmAg.png |
1x_JPEG (by compression level) | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | JPEG | 2019-08-01 | A collection of models for jpeg artifact removal, examples are included in the provided link | Alsa | Sample Gallery |
DeJpeg Fatality_PlusULTRA! | Twittman | 1x | CC BY-NC-SA 4.0 (?) | ESRGAN | JPEG | 2019-10-29 | 1x_DeJpeg_Fatality_01_200000_G.pth | ||
DeCompress | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | JPEG (works on many compression formats) | 2021-09-07 | USE 4x-UltraSharp INSTEAD - This is UniScaleV2, but intended for images with compression. Seems to work best on realistic images. | 4xESRGAN | Sample 1 |
JPG PlusULTRA (1x_jpg_PlusULTRA_130000.pth) | Twittman | 1x | CC BY-NC-SA 4.0 (?) | ESRGAN | JPEG | 2019-10-29 | 1x_DeJpeg_Fatality_01_200000_G.pth | ||
SaiyaJin DeJpeg | Twittman | 1x | CC BY-NC-SA 4.0 (?) | ESRGAN | JPEG | 2019-10-29 | Dataset: Anime, real life, manga, generated | 1x_DeJpeg_Fatality_PlusULTRA_200000_G.pth | Example 1 |
1x_JPEGDestroyer | BlackScout | 1x | GNU GPLv3 | ESRGAN | JPEG | 2020-02-19 | This model is meant to reduce or eliminate JPEG Compression without making the original images too smooth or killing detail. It manages to do a fairly good job but don't expect overly compressed images to work with this. | 1xESRGAN + previous attempts | |
4xJaypeg90 | Jacob | 4x | GNU GPLv3 | ESRGAN | JPEG compression | 2020-07-20 | Photos/realistic 3D with JPEG compression, quality 85-95 and 4:2:0 chroma subsampling. - Created for Myst3 images, since all have 4:2:0 chroma subsampling and existing JPEG models did not give good results. Favors smoothing over over-sharpening. | 4xESRGAN | https://i.imgur.com/n09m2Rt.png |
1x_SBDV-DeJPEG-Lite | Joey | 1x | CC BY-NC-SA 4.0 | ESRGAN (lite) | JPEG compression | 2020-10-10 | 1x_DIV2K-Lite_80k.pth | ||
NMKD Jaywreck3 & Jaywreck3-Soft (Lite) | Nmkd | 1x | WTFPL | ESRGAN Lite [nf=32 nb=12] | JPEG compression | 2020-10-13 | 1xESRGAN | 1xESRGAN | |
MangaJPEG | Bunzero++ | 1x | CC BY-NC-SA 4.0 | ESRGAN | JPEG | 2021-06-17 | Remove JPEG artifacts from manga without destroying screentone and other details | none | Sample |
Aliasing
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
SS Anti Alias 9x | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | Anti aliasing | Dataset: Custom (9x Supersampling AA) | none (no interpolation) | ||
Anti Aliasing | Twittman | 1x | CC BY-NC 4.0 | ESRGAN | Anti aliasing / Images with pixelated edges | Dataset: Custom (?) | none (no interpolation) | ||
1x_GainRESV3 (Aggro,Natural,Passive) | CF2lter | 1x | WTFPL | ESRGAN | Anti aliasing / Deblur | 2022-02-26 | To eliminate aliasing and general artifacts caused by not enough resolution while bringing out details Im stopping its training here because it's getting worse, i think of some aligment issues by game's rendering pipeline + downscaling... Dataset: 5K resolution shots from paladins rendered by 200% for hr and 37.5%(1080p) for lr then downscaled to 1080 | BCGONE_DetailedV2 | Sample 1 |
GIF
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
DeGif | nmkd | 2x | WTFPL | ESRGAN | GIF Restoration | GIF Restoration | 2xESRGAN |
DDS (BC1/DXT1, BC3/DXT5 Compression)
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_BC1-smooth2.pth | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | BC1 Compression | 2019-09-05 | A model to help remove compression artifacts in BC1-BC3/DXT1-DXT5 compressed images (these all have color encoded the same way) | none | |
x1_ITF_SkinDiffDDS_v1 | intheflesh#3116 | 1x | CC BY-NC 4.0 | ESRGAN | BC1 Compression | 2022-08-24 | Removes banding, blocking, dithering, aliasing, noise and color tint on DDS Compressed Skin Diffuse Textures.
This should work extremely well on most modern DDS compression types. The training set was compressed with BC3/DXT5, BC3/DXT5 Fast, BC2/DXT3, BC2/DXT3 Fast, and a small number of JPEG compressed images to cover outliers. This model is trained to remove the slight green color tint that DDS compression tends to add to skin textures, so the model output will not match the original color tone of the input image. This is the desired result though, as DDS compression shifts the colors to a sickly green tint and this model corrects that to more natural color tones. The training set included faces, body parts, eyes, mouths and hair in a variety of skin types and tones so it should work well on most related diffuse textures. However it's not just limited to skin, many other images and textures can be cleaned with this model. Designed to be used as a first step cleaning pass before applying additional models after. Check out the other ITF Models. |
1x_BC1-smooth2.pth | https://imgsli.com/MTIyMzE5 |
1x_DXTDecompressor_Source_V3-300000_G | JosephtheKP | 1x | WTFPL | ESRGAN | DXT1 Compression | 2021-12-21 | Removing compression artifacts from DXT1 compressed textures. This model was created to remove DXT1 compression artifacts from textures imported into the Source Engine. Compressed textures in the engine sometimes have a green-tint which this model also corrects. The data for this model contained a good mix of diffuse textures and normal maps which means this model is pretty good at removing compression from normals as well. Creating this model was a real learning experience for me and I hope someone finds a good use for it. | https://imgsli.com/ODcwNDg | |
1x_DEDXT | CF2lter | 1x | WTFPL | ESRGAN | DXT compression | 2022-02-26 | To retain details while removing artifacts caused by dxt compression on textures | Sample | |
1x_artifacts_bc1_free_alsa.pth | Alsa | 1x | CC BY-NC-SA 4.0 | ESRGAN | BC1 Compression | BC1 take 2 | |||
1x_BCGone_Smooth_110000_G | Mutin_Choler | 1x | WTFPL | ESRGAN | BC1 Compression | 2020-08-02 | Attempts to remove the damages done by BC1 compression. | 1xESRGAN | https://imgsli.com/MjU5MzQ/4/3 |
1x_BCGone-DetailedV2_40-60_115000_G | Mutin_Choler | 1x | WTFPL | ESRGAN | BC1 Compression | 2021-03-18 | 1xESRGAN |
Dithering
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample
|
---|---|---|---|---|---|---|---|---|---|
1x_artifacts_dithering_alsa.pth (pcloud)(mega) | Alsa | 1x | CC BY-NC-SA 4.0 | ESRGAN | Dithering | Dithered Images | JPG (0-20%) | ||
4xFSDedither | Jacob | 4x | GNU GPL3 | ESRGAN | Dithering | 2020-01-29 | 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. | RRDB_ESRGAN_x4 | https://imgsli.com/MTI1NTY/ |
4xFSDedither_Manga | Jacob | 4x | GNU GPLv3 | ESRGAN-FS | Dithering | 2020-04-21 | Cartoons/pixel art/other non-realistic stuff with dithering | RRDB_ESRGAN_x4.pth | https://imgsli.com/MTQ3Nzc |
4xFSDedither_Riven | Jacob | 4x | GNU GPLv3 | ESRGAN-FS | Dithering | 2020-07-11 | 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. | 4xESRGAN | https://imgsli.com/MTg5NTM |
1x_DitherDeleter-Smooth_104000_G | Mutin_Choler | 1x | WTFPL | ESRGAN | Dithering | 2021-01-23 | 1xESRGAN | https://imgsli.com/Mzg0MTk/1/2 | |
1x_DitherDeleterV3-Smooth | Mutin_Choler | 1x | WTFPL | ESRGAN | Dithering | 2021-04-18 | Attempts to remove the damages done by dithering. For this model, I downscaled all of the HR images to make their pixel size closer to 1000x1000 using the Box filter and then downscaled them again by 50% using the Point filter. Afterwards, I applied 32-bit Riemersma to every image in the dataset. | 1xESRGAN | https://imgsli.com/NTA5MjU/1/0 |
Blurring
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_ThePi7on-Solidd_Deborutify_UltraLite_260k_G | ThePi7on | 1x | CC BY-NC-SA 4.0 | ESRGAN | Deblur | 2021-05-09 | Sharpening, line darkening and slight line thinning, specifically made for the Boruto anime. | ||
1x_DeBLR | BlackScout | 1x | Unknown or None | ESRGAN | Deblur | 2020-02-19 | General Deblurring | ||
mdeblur | LyonHrt | 1x | UNKNOWN | ESRGAN | Blurring | Strong deblurring model | |||
1x_PixelSharpen_100000 | DinJerr | 1x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art | 2021-03-19 | Restores blurry/upscaled pixel art. | 1xESRGAN | https://imgsli.com/NDUxNDQ/5/4 |
1x_ArtClarity | DinJerr | 1x | WTFPL | ESRGAN | Pixel Art | 2021-08-05 | Texture retaining denoiser and sharpener for digital artwork. Helps resized/generated artwork look more like it is in 'native' resolution. | 4xPSNR | Sample Gallery |
1x_Fatality_DeBlur | Twittman | 1x | CC BY-NC-SA 4.0 | ESRGAN | Deblur | 2019-10-16 | Dataset: Mix of anime, manga, and photos | 1x_DeJpeg_Fatality_01_175000_G.pth | |
UnResize V3 (1x_UnResize_V3_200000_G.pth) | Twittman | 1x | CC BY-NC-SA 4.0 (?) | ESRGAN | Deblur / Unresize | Dataset: Anime, manga, and photos -
Purpose: Fix images that have been arbitrarily / poorly resized, such as non-integer nearest-neighbor upscaling/downscaling - Also acts as an image sharpener/deblur when used on slightly soft inputs |
1x_UnResize_MKII_030000_G.pth | ||
1x-Focus and 1x-Focus_Moderate | Kim2091 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Deblur | These models deblur most images. It was trained mostly on aniso2 and iso blurring (BSRGAN augmentation) with some gaussian mixed in. It performs well on most blurry images, but I'd recommend using something like Fatality_Deblur for very strong gaussian blur. Dataset: The UniScale Dataset + My Fabric dataset | 1xESRGAN | Sample 1 | |
ReFocus V3 (1x_ReFocus_V3_140000_G.pth) | Twittman | 1x | CC BY-NC-SA 4.0 | ESRGAN | Deblur / ReFocus | 2022-03-12 | Dataset: Photos, Anime, and manga -
Purpose: DeBlur, ReFocus, Sharpen Real life style images, but will work on Anime images too. |
1x_Saiyajin_DeJPEG_300000_G.pth | |
ReFocus Cleanly (1x_ReFocus_Cleanly_100000_G.pth) | Twittman | 1x | CC BY-NC-SA 4.0 | ESRGAN | Deblur / ReFocus | 2022-01-21 | Dataset: Anime, manga, and photos -
Purpose: DeBlur, ReFocus, Sharpen Manga, Anime and cartoon style images, but will work on real life images too. |
1x_ReFocus_V3_110000_G.pth |
Banding
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_N64clean | BlueAmulet | 1x | CC BY-NC 4.0 | ESRGAN | Banding | 2020-07-16 | N64 textures use a color depth of 5-bits per channel, this model attempts to clean them, restoring smooth gradients in textures | 1x_BC1-smooth2.pth | |
1x_Bandage-Smooth | Mutin_Choler | 1x | WTFPL | ESRGAN | Banding | 2021-04-16 | Attempts to remove the damages done by color banding. For this model, I downscaled all of the HR images to make their pixel size closer to 1000x1000 using the Box filter and then downscaled them again by 50% using the Point filter. Afterwards, I applied 64-bit color banding to every image in the dataset. | 1xESRGAN | https://imgsli.com/NTA1NTk/1/0 |
Debandurh_FS Ultra-lite (1x_Debandurh_FS_lite_140000_G.pth) | Twittman | 1x | CC BY-NC-SA 4.0 (?) | ESRGAN | Debanding images | Dataset: Anime, real life, manga | None |
Halo Removal
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_DeEdge_105000_G | Mutin_Choler | 1x | WTFPL | ESRGAN | Halo remover | 2020-11-03 | 1xESRGAN | https://imgsli.com/MjgxMDU/3/0 |
Noise
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
LADDIER1 | Alexander Syring | 4x | Unknown | ESRGAN | Denoise | 2019-11-13 | Remove noise, grain, box blur, lens blur and gaussian blur and increase overall image quality. | RRDB_ESRGAN_x4.pth | |
1x_NoiseToner-Poisson-Detailed_108000_G | Mutin_Choler | 1x | WTFPL | ESRGAN | Noise remover | 2021-10-08 | Attempts to remove the damages done from noise. Successor of sorts to Noisetoner_Poisson_150000_G | 1xESRGAN | https://imgsli.com/NzQ5MzM/2/0 |
1x_NoiseToner_Poisson_150000_G | Mutin_Choler | 1x | WTFPL | ESRGAN | Noise remover | 2020-10-14 | 1xESRGAN | https://imgsli.com/MjU1ODU/3/1 | |
1x_NoiseToner_Uniform_100000_G | Mutin_Choler | 1x | WTFPL | ESRGAN | Noise remover | 2020-10-14 | 1xESRGAN | https://imgsli.com/MjU1Nzg/2/1 | |
1x_ISO_denoise_v1 | Alpha | 1x | WTFPL | ESRGAN | denoise | not on discord | Remove high ISO noise | 1xESRGAN | |
1x_ISO_denoise_v2 | Alpha | 1x | WTFPL | ESRGAN | denoise | not on discord | Remove high ISO noise | ISO denoise v1 | |
Film-Degrainer_1-000 | Tika | 1x | CC0 | ESRGAN | denoise | not on discord | Remove film grain/noise | none | |
1x_Fatality_NoiseToner | DinJerr | 1x | WTFPL | ESRGAN | sharpen & denoise | 2023-04-16 | Interpolation of Mutin_Choler's various 1x_NoiseToner_Poisson with Twittman's 1x_Fatality_DeBlur | none |
Oversharpening
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_DeSharpen | Loinne | 1x | CC BY-NC-SA 4.0 | ESRGAN | Denoise | 2019-06-03 | Made for rare particular cases when the image was destroyed by applying noise, i.e. game textures or any badly exported photos. If your image does not have any oversharpening, it won't hurt them, leaving as is. In theory, this model knows when to activate and when to skip, also can successfully remove artifacts if only some parts of the image are oversharpened, for example in image consisting of several combined images, 1 of them with sharpen noise. | 1st attempt on random sharpening with the same dataset at 200000 iterations, which was trained on non-random desharp model, total ~600000 iterations on 3 models. |
DeToon
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample
|
---|---|---|---|---|---|---|---|---|---|
detoon | LyonHrt | ESRGAN | Detooning | 2019-06-24 | A toon to realistic shading style model to wiki under drawings | ||||
1xDoubleDetoon | Joey | 1x | CC BY-NC-SA | ESRGAN | Detooning | 2020-07-31 | An attempt to detoon images/drawings of people | 1xESRGAN |
Image De/Colorization
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
BS_Colorizer/Vapourizer | BlackScout | 1x | GNU GPLv3 | ESRGAN | Colorization | 2020-01-30 | B/W | 100% Desaturated images. It mostly results in Blue and Yellow images with slight hints of Green, Orange and Magenta. You are free to use this as a pretrain to achieve better results. | 1xESRGAN | |
1x_SpongeColor-Lite | Joey | 1x | CC BY-NC-SA 4.0 | ESRGAN (lite) [nf=32 nb=12] | Colorization | 2020-10-15 | The first attempt at ESRGAN colorization that produces more than 2 colors. Doesn't work that great but it was a neat experiment. | none | |
Deoldify | Rastrum | 4x | CC0 | ESRGAN | Photos | 2019-08-29 | Old black and white photo restoration. | Falcon Fanart |
Stylization
Images
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
Rek's Effeks Photoanime v2 | Rek | 4x | GNU GPL3 | ESRGAN | Stylization | 2020-10-17 | Photo stylization from JPEGs. Trained on images upscaled by ISO Denoise v2 -> DeJPEG Fatality PlusULTRA -> NMKD Yan2. Essentially a combination of that model chain into one. Use if you're looking for a stylized output, not photo quality. | NMKD Yandere2 | |
Ghibli_Grain.pth | nonogamester#3975 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Realistic Ghibli Grain | 2022-11-16 | Text or Anime. Attempt to get the nostalgic grain feel of classically animated Ghibli movies. Got the idea from researching the making of Ronin's :PKT_blue: 1x_AnimeFilmGrain28k. This was made running Nate video denoising with the preset "more denoising" on kiki's delivery service then overlaying it 66.65 percent over the original with DaVinci. On digital drawn anime it gives a slightly [10%] more organic/sharp feel to black lines. Matches well with content that already has a light digital grain. Run Twice for heavy grain. Eternal Thanks to all that indulge all my :psyduck: Wonderings :element_fire_neon: | https://slow.pics/c/M6dNTu6G | |
1x_ReDetail_v2_126000_G | DinJerr | 1x | WTFPL | ESRGAN | Digital Illustration | 2021-02-11 | A failed model that's supposed to insert details into paintings. It's actual use is to interpolate with other 1x models such as with 1x_DoubleDetoon to reduce its colour warping, or with 1x_ArtClarity to emphasize more on feature extraction. | 1x_ArtClarity |
Specialized Models
Text
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
2x_BSTexty | BlackScout | 2x | GNU GPLv3 | ESRGAN | Text | 2020-03-04 | 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. | 2x_ESRGAN | |
4x-TextSharpV1 | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Text | 2021-12-28 | Text or Anime | Interpolation between 4x-UltraSharp and 4x-TextSharp-v0.5. This is a duplicate listing of 4x-AnimeSharp | Sample 1
|
NMKD Typescale | Nmkd | 8x | WTFPL | ESRGAN | Text | 2020-11-04 | Low-resolution text/typography and symbols | 8xESRGAN |
Inpainting
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_sudo_inpaint_PartialConv2D_424000_G.pth | sudo rm -rf / --no-preserve-root#8353 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Inpainting | 2020-12-05 | Experimental PartialConv2D attempt to paint with ESRGAN. Took ~10.4 days of training on a P100 and around 1.5 months in total due to Colab limits. Not sure if I will continue training it since training is very slow, but may get better.. Warning: Result can vary with different tilesizes. Try not to tile your data. | None | Samples |
1x_NMKD-YandereInpaint_375000_G.pth | Nmkd | 1x | Unknown | ESRGAN | Inpainting | Unknown | None | Samples |
Fabric/Cloth
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
4x-Fabric and Fabric-Alt | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Fabric | 2021-09-15 | 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. | 4xESRGAN | Sample 1 |
Alphas
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
FireAlpha | BlueAmulet | 4x | CC BY-NC 4.0 | ESRGAN | Alpha (4 channel) | 2019-11-12 | none | ||
4x_1ch-Alpha-Lite | Joey | 4x | CC BY-NC-SA 4.0 | ESRGAN | Alpha | 2020-12-15 | Obsoleted by Joey's Fork - Alpha channels of PNGs | none | |
2x_Gen5-Alpha | Joey | 2x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art with Tranparency / Alpha Channel | 2021-02-03 | 4xFireAlpha | ||
8x_Sphax-Alpha-NN | Joey | 8x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art with Tranparency / Alpha Channel | 2021-02-04 | Replica of sphax with transparency | 4xFireAlpha | |
4x_PocketMonsters-Alpha | Joey | 4x | CC BY-NC-SA 4.0 | ESRGAN | Pixel Art with Tranparency / Alpha Channel | 2021-02-04 | upscaling pixel art with alpha channels that should perform better than any other. It should work well on both cartoon and 3D styled content. | 4xFireAlpha | |
Skyrim Alpha | Deorder | 4x | CC0 | ESRGAN | Pixel Art with Tranparency / Alpha Channel | Dataset: Alpha Channels from Skyrim | Unknown |
CGI
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1xRedImage10000.pth | 3majsie1995 | 1x | CC BY-NC 4.0 | ESRGAN | Correct old color photos that are tinted red | 2022-08-04 | Correct old color photos that are tinted red. Model only tested in nature. | 1xESRGAN | https://i.imgur.com/5O74rRL.png |
WaifuGAN_v3_30000 | DinJerr | 4x | CC BY-NC 4.0 | ESRGAN | CGI | 2019-07-12 | Upscaling CG-painted anime with variable outlines. | Manga109v2.pth | |
2xBS_Wolly | BlackScout | 2x | GNU GPLv3 | ESRGAN | CGI Animation | 2020-02-07 | Pixar Movies or Wall-E pictures/frames | 2xESRGAN | |
4xSGI | ChrisNonyminus | 4x | GNU GPL3 | ESRGAN | CGI | 2020-12-17 | Upscaling and dedithering pre-rendered sprites, images and textures made in the 90s. Basically vintage CGI. | 4xESRGAN | https://imgur.com/a/iwLTjeB |
CGIMaster_v1 | Madiator | 2x | GNU GPL3 | ESRGAN | CGI Animation | 2021-01-14 | mixed 3D/2D CGI animations on some 2D animations it might sharpen the edges. General usage is to upscale CGI animations compressed by YouTube. | Sharp_Anime_v2 | https://imgsli.com/Mzc1NTM |
Luminance/Chroma
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample
|
---|---|---|---|---|---|---|---|---|---|
1x_BSLuma | BlackScout | 1x | GNU GPLv3 | ESRGAN | Luma | 2020-02-28 | Fix Luminance issues?? LumaSharpen ESRGAN Edition? - This model mostly does what "Lumasharpen" algorithms do. It may help fixing images with Luminance images issues? Like old DVD rips? I am not sure, didn't test. | none | |
1x_BSChroma | BlackScout | 1x | GNU GPLv3 | ESRGAN | Sharpen | 2020-02-29 | ChromaSharpen - makes the colors slightly more vibrant with a sideeffect of possibly adding Chromatic Abberation to the image. I am not sure about the usage of this model on real case scenarios but anything blurry or with fuzzy colors could work | none | |
1x_3mChroma | 3majsie1995 | 1x | CC BY-NC 4.0 | ESRGAN | Chroma | 2023-01-04 | Improves chromatic aberration. It's not as good as 1x_BSchroma, but I recommend you to test it! | 1xESRGAN | https://i.imgur.com/oSub859.png |
Cats
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
Cat_Patch | Twittman | 4x | CC BY-NC-SA 4.0 (?) | ESRGAN | Cats | not on discord | previous attempt |
Coins
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
4x_Nickelfront | BlackScout | 4x | GNU GPLv3 | ESRGAN | Coins | 2020-02-13 | Upscale coins. That's it. If you were mad at me because Nickelback doesn't make any sense. Now you have the perfect solution to your problems. If you want to upscale nickels or anything with similar texture made out of metal, now you can. It works pretty well for a joke. | 4xESRGAN |
Faces
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
4x_Faces_N_250000.pth | Twittman | 4x | ESRGAN | Faces | 2019-07-18 | Upscales images of faces of different scales, sometimes resulting in monsters. | 4xESRGAN | ||
4x_Faces_04_N_180000_G | Twittman | 4x | ESRGAN | Faces | 2019-07-23 | Upscale faces both pixelized and real | 4x_Faces_N_250000.pth | ||
Face-Ality V1 (4x_Fatality_Faces_310000_G.pth) | Twittman | 4x | CC BY-NC-SA 4.0 (?) | ESRGAN | Faces | Dataset: Custom (Faces) | 4x_Faces_04_N_180000_G.pth | ||
4x_SmolFace_200k | DinJerr | 4x | CC BY-NC-SA 4.0 | ESRGAN | Art/People | 2022-08-19 | A sharp upscaler trained specifically for small sprite faces. Does not blend, so avoid using on painted/photo portraits unless you were trying to retain more of the outlines somehow. The _clean version has denoising/dedithering training on top of it. | 4x_NMKD-UltraYandere_300k | SmolFace: https://imgsli.com/MTIxNjU1/8/9
SmolFace_clean: Sample 1 Sample 2 Comparison with anime models |
BigFace_v3, BigFace_V3_Blend, BigFace_V3_Clear | DinJerr | 4x | CC BY-NC 4.0 | ESRGAN | Art/People | 2020-07-22 | Pixel art upscaler for faces drawn in digital painting style. Best for game portraits with multiple shades (not cel-shaded). | 4x_BigFace | |
TGHQFace8x | tg | 8x | GNU GPL3 | ESRGAN | Faces | 2019-11-27 | Upscales blurry 128px faces, usefull for enhancing that someone in a small picture. | 8xESRGAN | https://imgsli.com/OTM1NQ |
FArtFace | DinJerr | 4x | CC BY-NC 4.0 | ESRGAN | Faces | 2019-11-28 | Rather old pixel art face upscaler. I suggest using BigFace_v3 or SmolFace instead. Sometimes produces better results though. | ||
4x_BS_SbeveHarvey | BlackScout | 4x | GNU GPLv3 | ESRGAN | Faces | 2020-07-24 | Upscale Steve Harvey, but maybe other things, somehow?? | 4xESRGAN | |
Face Focus | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Faces | not on discord | Face De-blur - slightly out of focus / blurred images of faces. It is aimed at faces / hair | 4xPSNR | |
TGHQFace8x | Torrentguy | 8x | [https://www.gnu.org/licenses/gpl-3.0.en.html GNU GPLv3] | ESRGAN | Face Upscaling | 8xESRGAN |
Skin
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample
|
---|---|---|---|---|---|---|---|---|---|
x1_ITF_SkinDiffDetail_Lite_v1 | intheflesh#3116 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Skin Upscaling | Adds plausible high frequency detail and removes subtle blur. This is an early unfinished attempt at a x1 Lite model designed specifically for enhancing detail on skin diffuse textures of 3d characters. Even in its current state it works quite well.
Best suited for uncompressed or cleaned textures - otherwise it may just enhance any existing compression artefacts too. The training set included faces, body parts, eyes and hair in a variety of skin types and tones so it should work well on most related diffuse textures. However it's not just limited to skin, many other images and textures can be enhanced with this model. The results are subtle, so run multiple times if desired. |
50/50 Interpolation of DIV2K-Lite and SpongeBC1-Lite |
Foliage/Ground
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_Plants_400000_G.pth | Muf | 1x | Public Domain | ESRGAN | bad upscale | 2021-06-23 | Images of plants, trees or other foliage upscaled with Photoshop Preserve Details 2.0. Sharpens and "subdivides" details and noise so it doesn't look upscaled. | 1x_NMKD-h264Texturize_500k.pth | https://imgsli.com/NTg2MDk https://imgsli.com/NTg2MDg https://imgsli.com/NTg2MTA |
Ground | tldr_coder | 4x | WTFPL | ESRGAN | Upscales ground textures | 2021-06-23 | Dataset: Custom (Ground textures Google) |
Video Games
Game Screenshots
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
Minepack | BlackScout | 4x | CC BY-NC-SA | ESRGAN | Upscaling pack.png | 2020-01-26 | Upscales Minecraft screenshots by 4x. May suffer from haloing, weird patterns on blocks and JPEG-like artifacts. | 4xESRGAN.pth | |
4x_Link | Fielran#1024 | 4x | GNU GPL3 | ESRGAN | Chainmail game textures. Alternatively, it can be used to turn plain images into chainmail. | 2022-10-06 | A highly generative model for chainmail game textures. Works fairly well on items without visible chainmail texture (ie just a grey area) or items with clear chainmail texture, less well on items with present but poorly defined chainmail texture. I'm not 100% happy with it but it is still an improvement over existing models in enough situations to be worth releasing. | 4x_Nickelfront_14000G.pth | Sample 1 |
4x-FatePlus-lite | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN-lite | Anime PSP games, Fate Extra | 2022-07-03 | This model was trained as a favor to Demon and the Fate Extra community. It leaves a nice grain on the images and upscales lines and details accurately without looking odd. This model works on most anime-style PSP games. Enjoy! It works best on content with dithering and quantization. NOTICE: I have included both NCNN and ONNX models to make upscaling easier if you rely on either of these. For NCNN, there's two versions. One is FP16 and the other is FP32. FP16 works best on RTX GPUs. Choose FP32 if in doubt about compatibility, or if FP16 doesn't work for you. To use ONNX, download chaiNNer and upscale through there with the ONNX nodes. | 4x-AnimeSharp-lite | |
4x_GameAI_2.0 4x_GameAI_1.0 | Tal | 4x | WTFPL | ESRGAN | PS2 textures, cartoonish and realistic game textures. | 2022-02-27 | 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. Dataset: I used textures from, "(A Hat in Time, Kingdom Hearts 3 and World of Final Fantasy) for GameAI_2.0" "(Skyrim, The Witcher 3, Resident Evil 4, Final Fantasy XV and Tales of Vesperia ) for GameAI_1.0" Dataset_size: 21.9k to 70k textures , up to 1024x1024 per texture | 4x_GameAI_1.0 | Sample 1 |
4xPackCraft_v4 | Joey | 4x | CC BY-NC-SA 4.0 | ESRGAN | Upscaling pack.png | 2020-09-05 | Designed to upscale one specific minecraft screenshot. Results on dissimilar screenshots may be poor. | 4xESRGAN/previous versions | Sample |
MinecraftAlphaUpscaler with Good data | Washed Up | 4x | GNU GPLv3 | ESRGAN | Upscaling pack.png | 2020-01-29 | Designed to upscale one specific minecraft screenshot. Results on dissimilar screenshots may be poor. | RRDB_PNSR_x4.pth | |
ScreenBooster V2 | BlackScout | 4x | CC BY-NC-SA | ESRGAN | CGI | 2020-01-29 | Game Screenshots | none | |
BS_ScreenBooster_SPSR | BlackScout | 4x | CC BY-NC-SA | SPSR | CGI | 2020-07-18 | This model is designed to upscale game screenshots (3D Games) by 4 times. The SPSR version is an improvement over the ESRGAN based V2. | Screenbooster V2 |
Normal Map/Bump Map Generation
You may want to use this instead: https://github.com/JoeyBallentine/Material-Map-Generator
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_NormalMapGenerator-CX-Lite | Joey | 1x | CC BY-NC-SA 4.0 | ESRGAN Lite [nf=32 nb=12] | Map Generation - normal maps | 2020-11-04 | Generating normal maps from textures | 1x_DIV2K-Lite_450k.pth | |
1x_FrankenMapGenerator-CX-Lite | Joey | 1x | CC BY-NC-SA 4.0 | ESRGAN Lite [nf=32 nb=12] | Map Generation - roughness and displacement maps | 2020-11-07 | This model generates "Franken Maps" (named after Frankenstein), which is a custom material map combination I made. Basically, the Red channel of RGB is just the texture converted to grayscale, the Green channel is the roughness map, and the Blue channel is the displacement map. I had to do this to get around the current limitation of CX loss where it requires a 3 channel output (otherwise I would have just made a 2 channel model, or separate single channel models). As of right now the channels need to be manually split from each other but I will be making a tool for doing this automatically in the coming days. | 1x_DIV2K-Lite_450k.pth | |
1x_normals_generator_general_215k | LyonHrt | 1x | CC BY-NC-SA 4.0 | ESRGAN | Map Generation - Normal Maps | This model generates "Franken Maps" (named after Frankenstein), which is a custom material map combination I made. Basically, the Red channel of RGB is just the texture converted to grayscale, the Green channel is the roughness map, and the Blue channel is the displacement map. I had to do this to get around the current limitation of CX loss where it requires a 3 channel output (otherwise I would have just made a 2 channel model, or separate single channel models). As of right now the channels need to be manually split from each other but I will be making a tool for doing this automatically in the coming days. | none (no interpolation) |
Video Game Textures
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample
|
---|---|---|---|---|---|---|---|---|---|
Fallout Weapons (Fallout 4 Weapons?) | Bob | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures | 2019-08-05 | Video game textures, mostly metal rusty, clean or painted | Manga109Attempt | |
Fallout Weapons V2 | Bob | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures | 2019-08-23 | Video game textures, mostly metal rusty, clean or painted | Fallout 4 Weapons | |
4x_ThiefGoldMod_100000 | Akven | 4x | no idea | ESRGAN | Game textures | 2020-05-15 | Version of the previous model but based on Manga109 pretrained model and with slightly different dataset. Sometimes gives better results especially for wood and metal, sometimes worse. Sometime generates the same dotted artifacts on very bright/white images. | 4x_Manga109Attempt | https://imgsli.com/MTYzNjI |
4x_ThiefGold_110000 | Akven | 4x | no idea | ESRGAN | Game textures | 2020-05-15 | Various game textures. Primary wood, metal, stone | RRDB_ESRGAN_x4 | https://imgsli.com/MTYzNjI |
4x-VolArt | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures/Art | 2021-09-18 | This model upscales artwork for the game Volfoss (2001). The model peaked in quality very quickly. The NR model removes most noise, but has the downside of removing transparent portions. Use the main model in most cases. | 4xESRGAN | Sample 1 Sample 2 |
2xFaithfulSPSR | Joey | 2x | CC BY-NC-SA | SPSR | Pixel art | 2020-07-19 | Mainly just a test for SPSR. Seems to work better than the original 2xFaithful32_1316 that I used as a pretrained, even though it uses the same dataset. | 2xFaithful32_1316 | |
2x_FakeFaith-Lite | Joey | 2x | CC BY-NC-SA 4.0 | ESRGAN (lite) | Pixel Art | 2020-10-12 | An attempt at recreating the "faithful" style without using the faithful dataset -- aka keeping the "pixel art" style of pixel art. | 2x_Faithful-Lite | |
2x_Faithful-Lite | Joey | 2x | CC BY-NC-SA 4.0 | ESRGAN (lite) | Pixel Art | 2020-10-12 | A "lite" model version of my Faithful model | none | |
4x_HDCube3 | Venomalia | 4x | CC BY-NC-SA 4.0 | ESRGAN | Gamecube and Wii textures. | 2022-12-13 | 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. | 4x_HDcube2 | https://imgsli.com/MTM5ODE0/0/1 |
4x_HDCube | Venomalia | 4x | CC0-1.0 | ESRGAN | Gamecube and Wii textures. | 2022-05-10 | Gamecube and Wii textures (mainly DXT and 8bit color compression). Is good for preserving fine details without affecting the original style too much, it is not suitable for pixel art, small icons and text under 16 pixel. | 4x_NMKD Siax | https://imgsli.com/MTA3NDQ3 |
1x_DXTless_SourceEngine_170000_G | Xeller | 1x | WTFPL | ESRGAN | DTX5 Compression | 2021-04-10 | This model is made for Source Engine textures. It tries to remove compression artifacts such as blockyness, discoloration, green tint. It does pretty well on a lot of things, realistic stuff as well, but it was mostly made to work on TF2 textures. It's made to keep as much detail as possible, without any unnecessary denoising/sharpening. Huge thanks to Twittman for assisting me along this journey. | 1x_Saiyajin_DeJpeg_300000_G | https://imgsli.com/NDk1NTk |
Trixie | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Faces / Game Textures | not on discord | character textures for star wars games, including the heroes, rebels, sith and imperial. Plus a few main aliens…Why called trixie? Because jar jars big adventure would be too long of a name… This also provides good upscale for face textures for general purpose as well as basic star wars | none | |
Skyrim Armory | Alsa | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures/equipment | not on discord | Manga109Attempt | ||
Skyrim Misc | Deorder | 4x | CC0 | ESRGAN | Game textures | not on discord | Skyrim Diffuse Textures | ? | |
Skyrim Wood | Laeris | 4x | ESRGAN | Game textures | not on discord | Wood | ? | ||
4x-SkyrimTexV2.1 and V2_Fabric | Kim2091 | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures | 2021-09-25 | This model set upscales most Skyrim textures. I hope it helps 🙂 The base model (2.1) works well on stone, wood, metals, and most other textures. The Fabric model is a 50/50 interpolation with a stronger iteration of this model and my Fabric model. As you can tell by the name, it's intended for Fabric textures. If you want to upscale Alpha textures, use a model dedicated to it. There's an INFO file in the folder, it just explains the extra models | 4xESRGAN | Sample 1 |
Forest | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures | not on discord | Wood / Leaves | none | |
Morrowind Mixed | mkultra | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures | not on discord | Morrowind Mod Textures | 4xESRGAN | |
Morrowind 2.0 | mkultra | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures | not on discord | Morrowind Mod Textures | 4xESRGAN | |
Map | LyonHrt | 4x | CC BY-NC-SA 4.0 | ESRGAN | Game textures | not on discord | Map / Old Paper with text | none |
Video Restoration
Video Compression
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x_cinepak_200000 | Twittman | 1x | CC BY-NC-SA 4.0 (?) | ESRGAN | Compression | 2019-07-03 | Removal of Compression such as Cinepak, msvideo1 and Roq | none | |
1x_cinepak_alt.pth | buildist | 1x | GNU GPLv3 | ESRGAN | Compression | Cinepak (only) | none | ||
DeBink v4/v5/v6 | Kim2091 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Compression | 8.6.21 | This model removes early 2000s Bink and other compression artifacts. Works well on almost any image or video compression type. | none | |
DeBink_Lite | Kim2091 | 1x | CC BY-NC-SA 4.0 | ESRGAN-lite | Compression | 2021-10-30 | This model was trained on lossless video frames of Metal Arms: Glitch in the System, compressed with Bink V1 for the LR frames. It's a lot more efficient than my first DeBink model, and also has less artifacts. It's not quite as robust, but the compression is barely noticeable in videos after processing with this. | none | Video Sample |
1x-RoQ_nRoll | Kim2091 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Compression | 2021-11-21 | This model decompresses images and video compressed using RoQ. Config and presets will be added when Mega decides to let me use their site! | none | Sample 1 |
1x_DeRoqBeta-lite | Kim2091 | 1x | CC BY-NC-SA 4.0 | ESRGAN | Compression | 2022-07-26 | Incomplete lite model to remove ROQ compression | Sample | |
NMKD h264Texturize | Nmkd | 1x | WTFPL | ESRGAN | Texturizing | 2020-10-20 | Tries to reverse heavy h264 compression. Fails. Can be used to texturize images though. | 4x ESRGAN | |
1x_Filmify4K_v2_325000_G.pth | Muf | 1x | Public Domain | ESRGAN | artifact | 2021-07-19 | This model attempts to make films upscaled to 4K with Topaz Gaia-HQ look more natural and filmic. It sharpens, adds film grain, and smooths out small artefacts from the upscaling process. I recommend adding a tiny amount of grain to the input to seed the model (you can do this in VEAI), otherwise the film grain will remain static across frames that don't move much. Pretrain model used with permission to relicense from Twittman. | 1x_UnResize_V3_110000_G.pth | https://imgsli.com/NjE5MTE |
DeIndeo (mirror) DeIndeo | Wild West Quest#7975 | 4x | WTFPL | ESRGAN | Indeo Compression Artifacts | Dataset: Custom | 4xESRGAN |
VHS Tapes
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1xBaldrickVHSFix_180000_G_V0.2 | NimRodZorg | 1x | CC BY-NC-SA 4.0 | ESRGAN | VHS | 2021-03-03 | Fixing minor VHS Chroma and Pattern Noise - NOTE: only works on deinterlaced sources | 1xESRGAN | |
ToonVHS | Redslam | 1x | CC BY-NC-SA 4.0 | ESRGAN | VHS | 2022-02-06 | Best when used on cartoons, it can work on anime. Due to the dataset it does struggle a bit with orange colors and grainy dark spots. This model is meant to be used to clean up the image before using it on a 2x or 4x model. | 1xESRGAN | Examples of ToonVHS + other models |
2x_VHS-upscale-and-denoise_Film_477000_G | Itewreed | 2x | CC BY-NC-SA 4.0 | ESRGAN | VHS | 2021-03-28 | VHS captures of Film material, but may work on VHS recorded native SD-TV material as well. Also useable for cleaned up source material | none | |
VHS-Sharpen-1x | RTX 2080 ti hoarder | 1x | CC BY-NC-SA 4.0 | ESRGAN | VHS | 2021-03-19 | Make old VHS footage crispy. This model will not work on video and images with noticeable JPEG/Video compression artifacts, noticeable interlacing or haloing, heavy tape distortion/artifacts and scenes with tons of detail. For best results, use a downscaled HD capture of the VHS tape you intend to use it on. | 1xESRGAN | https://imgsli.com/NDUxNDY/2/3 |
Model Collections
Model Name | Author | Scale | License | Architecture | Purpose | Date Posted | Description | Sample |
---|---|---|---|---|---|---|---|---|
OptimusPrimal's Collection | OptimusPrimal | Various | WTFPL | ESRGAN | Collection | 2022-02-28 | I'm dumping all my models here. (I moved my favorites to a favorite folder). Most of these models work well on DVD resolution animation sources. These are all ESRGAN models. Everything is with the WTFPL license. So do whatever you want with them. Credit is not needed, but would be nice if you use them to make something. There's a few that are interpolations with other user's publicly available models, or interpolations of other user's publicly available models (so technically, these are not mine), so credit goes out to them, the only ones I can remember off the top of my head is @twittman with the Fatality model series, which are great, and @cd VSGAN && poetry install with the Sol Levante/American Dad2 models, and if you do 50/50 with those 2 models, you get a really good model that I called Soladad. | |
Kim's Collection | Kim2091 | Various | CC BY-NC-SA 4.0 | Various (ESRGAN and ESRGAN-lite) | Collection | 2022-02-28 | My (Kim's) main folder for hosting models. Every model of mine on this database links to subsections of this folder. If a link is broken or you just want to see nearly all of the models I've trained, look here. | |
UltraMix Collection | Kim2091 | Various | CC BY-NC-SA 4.0 | Various (ESRGAN and ESRGAN-lite) | Collection | 2022-06-28 | This is a mixture of models based around UltraSharp and my other available models. These are usually interpolations that have separate but very helpful uses. As an example, UltraMix_Restore is a combination of UltraSharp and UniScale_Restore, and is great for video game textures. | |
NMKD's Collection | NMKD | Various | Various | Various (ESRGAN and ESRGAN-lite?) | Collection | 2022-02-28 | NMKD's main folder for hosting models. Nearly every one of NMKD's models posted on this wiki link to it. | |
Zarxrax's Collection | Zarxrax | Various | Various | Compact | Collection | 2023-01-20 | All of my compact models, including a few variations which might not be linked from elsewhere. | |
Joey's ESRGAN Bot Collection | Various | Various | Various | Various | Collection | 2022-08-04 | Here is a dump of all the ESRGAN-Bot models. As it was a un-curated collection, many of the models here were never officially released, but I do not know exactly which ones. If one of your models is included here and you would like me to remove it, please let me know. |
Pretrained Models
Looking for official models? Look here: https://upscale.wiki/wiki/Official_Research_Models
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1xESRGAN | victorca25 | 1x | Apache License 2.0 | ESRGAN | Pretrained | 2019-07-06 | RRDB_ESRGAN_x4.pth | ||
2xESRGAN | victorca25 | 2x | Apache License 2.0 | ESRGAN | Pretrained | 2019-07-06 | RRDB_ESRGAN_x4.pth | ||
4xESRGAN | xinntao | 4x | Apache License 2.0 | ESRGAN | Pretrained | 2019-07-06 | RRDB_ESRGAN_x4.pth | ||
8xESRGAN | victorca25 | 8x | Apache License 2.0 | ESRGAN | Pretrained | 2019-07-06 | RRDB_ESRGAN_x4.pth | ||
16xESRGAN | victorca25 | 16x | Apache License 2.0 | ESRGAN | Pretrained | 2019-07-06 | RRDB_ESRGAN_x4.pth | ||
1x PSNR Pretrained Model | BlueAmulet | 1x | Apache License 2.0 (ESRGAN's license) | ESRGAN | Pretrained | 2020-04-20 | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | RRDB_PSNR_x4.pth | |
2x PSNR Pretrained Model | BlueAmulet | 2x | Apache License 2.0 (ESRGAN's license) | ESRGAN | Pretrained | 2020-04-20 | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | RRDB_PSNR_x4.pth | |
4x PSNR Pretrained Model | BlueAmulet | 4x | Apache License 2.0 (ESRGAN's license) | ESRGAN | Pretrained | 2020-04-20 | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | RRDB_PSNR_x4.pth | |
8x PSNR Pretrained Model | BlueAmulet | 8x | Apache License 2.0 (ESRGAN's license) | ESRGAN | Pretrained | 2020-04-20 | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | RRDB_PSNR_x4.pth | |
16x PSNR Pretrained Model | BlueAmulet | 16x | Apache License 2.0 (ESRGAN's license) | ESRGAN | Pretrained | 2020-04-20 | The original RRDB_PSNR_x4.pth model converted to 1x, 2x, 8x and 16x scales, intended to be used as pretrained models for new models at those scales. These are compatible with victor's 4xESRGAN.pth conversions | RRDB_PSNR_x4.pth | |
Compact Pretrained Models | Zarxrax | 1x-4x | WTFPL | Real-ESRGAN "compact" | Pretrained | 2022-07-31 | This is a collection of pretrained models for Real-ESRGAN's Compact architecture. There are 1x, 2x, and 4x models, as well as 1x and 2x "UltraCompact" and "SuperUltraCompact" models (think of these as the equivalent to ESRGAN "lite" models). By using these are pretrains for your models, you can ensure that your models are able to be interpolated with other Compact models that were trained from these. These pretrains are compatible with most existing compact models. |
Pretrained Discriminators
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
1x Pretrained Discriminator Pack | Joey | 1x | CC BY-NC-SA 4.0 | VGG | Pretrained discriminators | 2020-10-26 | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. | none | |
2x Pretrained Discriminator Pack | Joey | 2x | CC BY-NC-SA 4.0 | VGG | Pretrained discriminators | 2020-10-26 | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. | none | |
4x Pretrained Discriminator Pack | Joey | 4x | CC BY-NC-SA 4.0 | VGG | Pretrained discriminators | 2020-10-26 | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. | none | |
8x Pretrained Discriminator Pack | Joey | 8x | CC BY-NC-SA 4.0 | VGG | Pretrained discriminators | 2020-10-26 | Most of these are my spongebob dataset so they will be more useful for cartoons but I did include my original faithful model discriminator. | none | |
4x_RRDB-G_ResNet-D (Both G and D) | Joey | 4x | CC BY-NC-SA 4.0 | ESRGAN (G) / ResNet (D) | Pretrained | 2021-01-17 | Clean bicubic downscales / Pretrained models (G/D) | RRDB_ESRGAN_x4_old_arch.pth |
Official Models
To cut down on the length of this page and reduce confusion, these models have been moved here: https://upscale.wiki/wiki/Official_Research_Models This page contains models such as: ESRGAN, BSRGAN, Real-ESRGAN, and more.
SOFVSR Models
These models are for SOFVSR, they will not work in Cupscale or the main ESRGAN forks. You need this to use it: https://github.com/JoeyBallentine/Video-Inference
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
3x_Video_TSSM | Joey | 3x | CC BY-NC-SA 4.0 | SOFVSR | Animation | 2020-11-17 | none | ||
3x_Video_TSSM_RRDB | Joey | 3x | CC BY-NC-SA 4.0 | SOFVSR RRDB / VESRGAN | Animation | 2020-11-25 | none | ||
2x_SBS11-RRDB | Joey | 2x | CC BY-NC-SA 4.0 | SOFVSR RRDB / SOFVESRGAN | Animation | 2020-12-03 | none | ||
4x_REDSVAL-7f-RRDB-Lite (both G and D) | Joey | 4x | CC BY-NC-SA 4.0 | SOFVSR RRDB / SOFVESRGAN Lite [nf=32, nb=12] | IRL videos | 2020-12-03 | none | ||
SOFVSR_REDS_F3_V1 | Sunseille | 4x | WTFPL | RRDB | IRL videos | 2021-02-26 | upscale IRL videos. Use not recommended by creator | none | Sample Video |
2x_VimeoScale_Unet | Sazoji | 2x | CC BY-SA 4.0 | SOFVSR-RRDB (light arch, 3 frames, nf=32, nb=12) | Upscaling video content | 2021-09-09 | This model is meant to surpass VEAI 2x while being efficient to run quickly with fp16. The real-esrgan/BSRGAN augmentation and Unet should help with videos where the resolution is not ideal and can reconstruct details without effecting blurs in most cases. This model SHOULD run faster than real-esrgan while matching the resolving and enabling some multiframe feature extraction. No major denoising/compression/blurring effects (or artifacts) should be found. | Self-Trained Base for the Unet finalisation with vgg_fea discrim | Sample 1 Sample 2 Sample 3 |
4x_VimeoScale | Sazoji | 4x | CC BY-SA 4.0 | SOFVSR-RRDB (5 frames) | Upscaling IRL video content | 2021-10-08 | This model is one of the longest I have trained and tuned, includes some noise training but this is not intended for deblocking/decompression. Combined with https://github.com/JoeyBallentine/Video-Inference 's fp16 mode, this should handle most SD and 720p content at or faster than ESRGAN, with a significant bump in quality. | Self-Trained Base for the Unet finalisation with vgg_fea discrim | Sample 1 Sample 2 Sample 3 Sample 4 |
Pretrained SOFVSR Models
Model Name | Author | Scale | License | Architecture | Purpose (short) | Date Posted | Purpose (Full) | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
video_G | victorca25 | 4x | Unknown | SOFVSR net | Trained on REDS' size dataset | none | |||
VESRGAN_G | victorca25 | 4x | Unknown | RRDB | Trained on REDS' size dataset | none |
RIFE Models
Model Name | Author | Scale | License | Architecture | Purpose | Date Posted | Description | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
sudo_rife4_269.662_testV1_scale1.pth | sudo | 2x | CC BY-NC-SA 4.0 | RIFE | Animation interpolation | 2022-06-25 | I never really mentioned it in model-releases prior since I think not too many care about interpolation here, but I trained a rife4 model for animation a some months ago, which is better than rife4 and rife4.2 imo. Thought I should also mention it here as well. I also converted it into ncnn. (Nihuis rife ncnn models are only exported with the fastest mode and not the best quality. I exported ncnn models for the most important quality settings. Due to different export/quality settings, there are multiple models. For that reason alone, my ncnn models are much better too, since nihui only exported the fastest one.) My https://github.com/styler00dollar/VSGAN-tensorrt-docker also has the rife ncnn extention, which can use VMAF, dedup, scene detection and so on, which I would recommend. My models are in that extention as well, just select model 10, 11 or 12 and use the dev docker. That test video is done with 2x framerate, enbemble True and FastMode False, combined with scene detection and dedup stuff, tta False. Towards the best quality rife can do. Plz don't steal without credits, k thx. | Sample Video |
CAIN Models
CAIN is a video frame rate interpolation AI. These models are intended for use with CAIN only. These CANNOT be used with Cupscale or ESRGAN, you need this: https://gitlab.com/hubert.sontowski2007/cainappModel Name | Author | Scale | License | Architecture | Purpose | Date Posted | Description | Pretrained_Model_G | Sample |
---|---|---|---|---|---|---|---|---|---|
explodV1 | hubert | 2x | BSD-3-Clause | CAIN YUV | Animethemes | 2022-07-29 | I think one of sharpest models for anime
Plz don't steal without credits, k thx. |
Sample Video | |
190562_vimeo_enchanced.pth | hubert | 2x | MIT | CAIN | RL videos - interpolation | 2021-07-13 | |||
cainREALTIME | hubert | 2x | MIT | CAIN (CAIN 1 Group) | RL videos - interpolation | 2021-07-13 | Trained mostly on abba music videos | ||
cainliteanime.pth | hubert | 2x | MIT | CAIN | Anime - interpolation | 2021-08-06 | Sample | ||
rvpV1 (pcloud) rvpV1 (mediafire) | sudo rm -rf / --no-preserve-root#8353 | 2x | CC BY-NC-SA 4.0 | CAIN | Video Frame Interpolation for anime openings | 2021-09-14 | My ~~first~~ (ok technically second) attempt to create a video frame interpolation model and I like how it turned out. To use it, you can either use cain-App, Colab-CAIN (no longer available) or the bot in the Game Upscale discord (model called rvpv1 there, just use --model rvpv1). Some demo videos in pcloud, but you need to download them. The web player seems to playback in low fps. The architecture is mainly the same to the original CAIN, but i modified the padding to be zero padding instead. ``.pt`` means JIT model, `.pth`, means normal pytorch model. Architecture file is in pcloud as well. And no, no cupscale or flowframes. Dataset: Modified Animeinterp dataset | Sample Video | |
cvpv6.pth | hubert | 2x | MIT | CAIN | Anime - interpolation | 2021-09-21 |
Waifu2x Models
Some helpful links for Waifu2x, rewritten in PyTorch. The repos contain the pretrained models themselves as well.