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A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018.

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Video2X: A machine learning-based video super resolution and frame interpolation framework.

🌟 Version 6.0.0

Video2X 6.0.0 highlights:

  • Complete rewrite of the Video2X project in C/C++.
  • Faster and more efficient architecture.
  • Cross-platform support for Windows and Linux.
  • Vastly improved output quality.
  • New GUI and installer for easy setup on Windows.
Click to see more details

Version 6.0.0 is a complete rewrite of this project in C/C++. It:

  • genuinely works this time, with much less hassle compared to the 5.0.0 beta;
  • is blazing fast, thanks to the new optimized pipeline and the efficiency of C/C++;
  • is cross-platform, available now for both Windows and Linux;
  • offers significantly better output quality with Anime4K v4, RealESRGAN, RealCUGAN, and RIFE;
  • supports two modes: filtering (upscaling) and frame interpolation;
  • supports Anime4K v4 and all custom MPV-compatible GLSL shaders;
  • supports RealESRGAN, RealCUGAN, and RIFE (all models) via ncnn and Vulkan;
  • requires zero additional disk space during processing, just space for the final output.

6.3.0-screenshot

Download the Latest Windows Installer Executable (6.3.1)

You can download the latest Windows release on the releases page. For basic GUI usage, refer to the documentation. If you're unable to download directly from GitHub, try the mirror site. The GUI currently supports the following languages:

  • English (United States)
  • 简体中文(中国)
  • 日本語(日本)
  • Português (Portugal)
  • Français (France)

You can install Video2X on Arch Linux using the video2x-git AUR package or on Ubuntu/Debian using the .deb package from the releases page. If you'd like to build from source, refer to the PKGBUILD file for a general overview of the required packages and commands. If you'd prefer not to compile the program from source, consider using the container image below.

Video2X container images are available on the GitHub Container Registry for easy deployment on Linux and macOS. If you already have Docker/Podman installed, only one command is needed to start upscaling a video. For more information on how to use Video2X's Docker image, please refer to the documentation.

You can use Video2X on Google Colab for free if you don't have a powerful GPU of your own. You can borrow a powerful GPU (NVIDIA T4, L4, or A100) on Google's server for free for a maximum of 12 hours per session. Please use the free resource fairly and do not create sessions back-to-back and run upscaling 24/7. This might result in you getting banned. You can get Colab Pro/Pro+ if you'd like to use better GPUs and get longer runtimes. Usage instructions are embedded in the Colab Notebook.

Join our Telegram discussion group to ask any questions you have about Video2X, chat directly with the developers, or discuss super resolution, frame interpolation technologies, or the future of Video2X in general.

Comprehensive documentation for Video2X is available at https://docs.video2x.org/. It offers detailed instructions on how to build, install, use, and develop with this program.

📽️ Video Demos (Outdated)

Spirited Away Demo
Upscale demo: Spirited Away's movie trailer

  • Spirited Away: YouTube | Bilibili
    • 360P to 4K
    • The original video's copyright belongs to 株式会社スタジオジブリ
  • Bad Apple!!: YouTube | Bilibili
    • 384P 30 FPS to 4K 120 FPS with waifu2x and DAIN
    • The original video's copyright belongs to あにら
  • The Pet Girl of Sakurasou: YouTube | Bilibili
    • 240P 29.97 to 1080P 60 FPS with waifu2x and DAIN
    • The original video's copyright belongs to ASCII Media Works

Standard Test Clip

The following clip can be used to test if your setup works properly. This is also the standard clip used for running performance benchmarks.

The original clip came from the anime "さくら荘のペットな彼女."
Copyright of this clip belongs to 株式会社アニプレックス.

⚖️ License

This project is licensed under GNU AGPL version 3.
Copyright (C) 2018-2024 K4YT3X and contributors.

AGPLv3

This project includes or depends on these following projects:

Project License
FFmpeg/FFmpeg LGPLv2.1, GPLv2
Tencent/ncnn BSD 3-Clause
bloc97/Anime4K MIT License
nihui/realcugan-ncnn-vulkan MIT License
nihui/rife-ncnn-vulkan MIT License
xinntao/Real-ESRGAN-ncnn-vulkan MIT License

More licensing information can be found in the NOTICE file.

🌺 Special Thanks

Special thanks to the following individuals for their significant contributions to the project, listed in alphabetical order.