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Difference between revisions of "Maintained BasicSR Forks"
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== Currently Maintained BasicSR Forks == | == Currently Maintained BasicSR Forks == | ||
| − | === [https://github.com/ | + | === [https://github.com/muslll/neosr NeoSR] === |
| − | + | The latest Fork by musl, it has AMP training support, and an opinionated choice of losses and architectures integrated to avoid those losses and architectures that don't add a meaningful benefit to the training process. It supports all of the relevant modern architectures and as such is the recommended fork as of September 2023. | |
| + | |||
| + | === [https://github.com/FlotingDream/traiNNer-redux-FJ traiNNer-redux FJ] === | ||
| + | A fork of Joey's fork, adding additional architectures, ... | ||
| + | |||
| + | === [https://github.com/joeyballentine/traiNNer-redux traiNNer-redux] === | ||
| + | A fork of BasicSR made by Joey to add some additional losses such as the CX Loss and Color loss, as well as adding a few additional architectures such as swinirgan, 2c2esrgan, RealSwinIRGAN, compact-2c2, OmniSR and a few augmentations. | ||
| − | === [https://github.com/ | + | === [https://github.com/xinntao/BasicSR Xinntao's Original BasicSR] === |
| − | This | + | This is the original BasicSR repository. It was updated to v1 officially, however, it is not recommended as it lacks many of the features the community generally finds useful, and only creates x4 scale [[ESRGAN new-arch|new-arch models]] |
| − | === [https://github.com/ | + | === [https://github.com/styler00dollar/Colab-traiNNer Colab-traiNNer] === |
| − | + | Sudo's fork that contains a ton of architectures and losses, you can see him experimenting and expanding it on our discord. | |
== Dead BasicSR Forks == | == Dead BasicSR Forks == | ||
| − | === [https://github.com/victorca25/BasicSR Victorca25's Fork] === | + | === [https://github.com/victorca25/BasicSR Victorca25's traiNNer] === |
| − | This fork | + | This used to be the recommended fork, It includes many features including contextual loss, enhanced degredation pipelines (augmentations), and support for many architectures (SOFVSR, for example). |
| + | |||
| + | === [https://github.com/BlueAmulet/BasicSR BlueAmulet's Fork] === | ||
| + | This fork added many features like auto-backups, YAML training configs, and Frequency Separation. | ||
| + | |||
| + | It is no longer maintained. | ||
| + | |||
| + | === [https://github.com/DinJerr/BasicSR DinJerr's Fork] === | ||
| + | This fork has lots of cool [[On The Fly training]] options added through ImageMagick. This includes different types of dithering and a Kuwahara filter. | ||
| + | |||
| + | It seems to be unmaintained as of late 2021. | ||
Latest revision as of 08:35, 17 September 2023
Contents
Currently Maintained BasicSR Forks
NeoSR
The latest Fork by musl, it has AMP training support, and an opinionated choice of losses and architectures integrated to avoid those losses and architectures that don't add a meaningful benefit to the training process. It supports all of the relevant modern architectures and as such is the recommended fork as of September 2023.
traiNNer-redux FJ
A fork of Joey's fork, adding additional architectures, ...
traiNNer-redux
A fork of BasicSR made by Joey to add some additional losses such as the CX Loss and Color loss, as well as adding a few additional architectures such as swinirgan, 2c2esrgan, RealSwinIRGAN, compact-2c2, OmniSR and a few augmentations.
Xinntao's Original BasicSR
This is the original BasicSR repository. It was updated to v1 officially, however, it is not recommended as it lacks many of the features the community generally finds useful, and only creates x4 scale new-arch models
Colab-traiNNer
Sudo's fork that contains a ton of architectures and losses, you can see him experimenting and expanding it on our discord.
Dead BasicSR Forks
Victorca25's traiNNer
This used to be the recommended fork, It includes many features including contextual loss, enhanced degredation pipelines (augmentations), and support for many architectures (SOFVSR, for example).
BlueAmulet's Fork
This fork added many features like auto-backups, YAML training configs, and Frequency Separation.
It is no longer maintained.
DinJerr's Fork
This fork has lots of cool On The Fly training options added through ImageMagick. This includes different types of dithering and a Kuwahara filter.
It seems to be unmaintained as of late 2021.
