VideoJaNai

VideoJaNai

Overview

VideoJaNai (previously called AnimeJaNaiConverterGui) provides a Windows and Linux GUI for upscaling videos with ONNX models, including temporal (multi-frame) models, and frame interpolation with RIFE. Upscaling runs entirely on the GPU, with NVIDIA TensorRT or, on Windows, DirectML for AMD and Intel GPUs, through the AnimeJaNai inference engine, the same engine that powers mpv-AnimeJaNai.

On Windows, NVIDIA GeForce RTX 20 / GTX 16 series and newer GPUs upscale with TensorRT-RTX by default, which builds its engines in seconds instead of minutes. Its component (about 230 MB installed) is installed automatically for those GPUs; on other NVIDIA GPUs it's optional, from App Settings > Components. TensorRT stays installed alongside it: TensorRT-RTX output is equivalent to TensorRT's but not bit-identical, and if it can't start or can't build an engine, VideoJaNai falls back to TensorRT automatically and shows a warning in the status bar (and in the preview). To choose a backend yourself, pick TensorRT, TensorRT-RTX or DirectML under Backend in App Settings.

On a PC with more than one GPU the backend can use, App Settings also has a GPU choice. Auto runs DirectML on the GPU Windows ranks for high performance and TensorRT on the NVIDIA GPU CUDA lists first (usually the most powerful); pick a GPU there if Auto chooses the wrong one. Integrated graphics are listed last and marked, and picking them shows a warning, since they upscale much slower than a graphics card. On Auto, the TensorRT components are installed for every NVIDIA GPU in the PC; with a GPU picked, only that GPU's are recommended (none on DirectML), and components you remove for other GPUs stay removed.

Linux

Download either the AppImage or the linux-x64.tar.zst from the latest release. An NVIDIA GPU and driver are required.

• AppImage: make it executable and run it. Run it once with --install to add a menu entry. The TensorRT kernels for your GPU and the RIFE models download on first launch into ~/.local/share/VideoJaNai.
• Tarball: extract it anywhere and run ./install.sh from inside the extracted folder. This adds a menu entry and installs the components for your GPU. The folder stays in place and updates itself in-app.

Command line

videojanai upscales from the command line, with the same engine, components and settings as the GUI. Download videojanai-windows-x64.zip or videojanai-linux-x64.tar.zst from the latest release, unpack it anywhere, run videojanai setup once, then videojanai <video>. See its README for everything else.

Resources

• OpenModelDB: Repository of AI upscaling models.
• chaiNNer: General purpose tool for AI upscaling, which can be used to convert PyTorch (*.pth) models to ONNX models.

Related Projects

• mpv-AnimeJaNai: Real-time anime upscaling in mpv
• MangaJaNai GUI: Upscale manga and images
• yosh: Fast manga, comic and image reader
• traiNNer-redux: Train your own upscaling models

Acknowledgments

• MPV_lazy
• vs-mlrt
• vs_temporalfix: the temporal fix models (Apache-2.0)