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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Misc; latest version of waifu2x; 2D video to stereo 3D video conversion
| Date | Stars |
|---|---|
| 2026-07-24 | 3345 |
| 2026-07-25 | 3346 |
| 2026-07-28 | 3346 |
| 2026-07-30 | 3346 |
| 2026-08-06 | 3346 |
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My playground. For the time being, I will make incompatible changes. ## waifu2x [waifu2x/README.md](./waifu2x/README.md) waifu2x: Image Super-Resolution for Anime-Style Art. Also it supports photo models (GAN based models) The repository contains waifu2x pytorch implementation and pretrained models, started with porting the original [waifu2x](https://github.com/nagadomi/waifu2x). The demo application can be found at - https://waifu2x.udp.jp/ (Cloud version) - https://unlimited.waifu2x.net/ (In-Browser version). ## iw3 [iw3/README.md](./iw3/README.md) I want to watch any 2D video as 3D video on my VR device, so I developed this very personal tool. iw3 provides the ability to convert any 2D image/video into side-by-side 3D image/video. ### iw3-desktop [iw3/docs/desktop.md](./iw3/docs/desktop.md) iw3.desktop is a tool that converts your PC desktop screen into 3D and streaming over WiFi. You can watch any image and video/live displayed on your PC as 3D in realtime. ### iw3-player [iw3/player/README.md](./iw3/player/README.md) iw3-player is a self-hosted, specialized viewing environment for stereoscopic media. It allows you to stream media that has been pre-converted to 3D with iw3 from your PC and enjoy it on VR devices through a WebXR application. ## stilizer [stlizer/README.md](./stlizer/README.md) stlizer is a fast conservative video stabilizer. ## cliqa [cliqa/README.md](./cliqa/README.md) `cliqa` provides low-vision image quality scores that are more consistent across different images. It is useful for filtering low-quality images with a threshold value when creating image datasets. Currently, the following two models are supported. - JPEGQuality: Predicts JPEG Quality from image content - GrainNoiseLeve: Predicts Noise Level related to photograph and PSNR degraded by that noise CLI tools are also available to filter out low quality images using these results. ## Install ### Installer for Windows users - [nunif windows package](windows_package/docs/README.md) - [nunif windows package (日本語)](windows_package/docs/README_ja.md) ### For developers #### Dependencies - Python 3 (Works with Python 3.10 or later, developed with 3.10) - [PyTorch](https://pytorch.org/get-started/locally/) - See requirements.txt We usually support the latest version. If there are bugs or compatibility issues, we will specify the version. - [INSTALL-ubuntu](INSTALL-ubuntu.md) - [INSTALL-windows](INSTALL-windows.md) - [INSTALL-macos](INSTALL-macos.md) For Intel GPUs, additionally see section [INSTALL-xpu](INSTALL-xpu.md). For older NVIDIA GPUs, additionally see section [INSTALL-cu126](INSTALL-cu126.md). For container, packages, or special hardware builds, see [extra_build](extra_build). #### About NUNIF_HOME If the environment variable `NUNIF_HOME` is defined, downloaded pretrained models, configuration files, cache, temporary files, and lock files will be saved under `NUNIF_HOME`. This may be useful when packaging or in situations where the source directory does not have write permissions. The `~` character at the beginning of a path string is expanded to the home directory. ### License Notes Note that if you distribute binary builds, it is possible that it will be GPL. This is due to PyAV(av) wheel package containing the GPL version of ffmpeg library. You can build PyAV with the LGPL version of ffmpeg library. If you load this repository with torch.hub.load for waifu2x Python API etc, this problem does not exist because PyAV is not a dependent package.
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:9b083960865c06b4, topic:super-resolution, readme:super resolution