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Video2X

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ML-based video upscaling and frame interpolation using Real-ESRGAN, Real-CUGAN, RIFE and other models to upscale old low-res video or raise frame rates; video2x handles one video per run and is scriptable. Needs a Vulkan GPU; Windows, Linux and Docker builds, no native macOS.

k4yt3x/video2x22.3k
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README

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, Real-ESRGAN, Real-CUGAN, and RIFE;
  • supports two modes: filtering (upscaling) and frame interpolation;
  • supports Anime4K v4 and all custom MPV-compatible GLSL shaders;
  • supports Real-ESRGAN, Real-CUGAN, and RIFE (all models) via ncnn and Vulkan;
  • requires zero additional disk space during processing, just space for the final output.

6.4.0-screenshot

🖥️ Hardware Requirements

Your system must meet the minimum hardware requirements below to run Video2X.

  • CPU
    • The precompiled binaries require CPUs with AVX2 support.
    • Intel: Haswell (Q2 2013) or newer
    • AMD: Excavator (Q2 2015) or newer
  • GPU
    • The GPU must support Vulkan.
    • NVIDIA: Kepler (GTX 600 series, Q2 2012) or newer
    • AMD: GCN 1.0 (Radeon HD 7000 series, Q1 2012) or newer
    • Intel: HD Graphics 4000 (Q2 2012) or newer

🪟 Install on Windows

Download the Latest Windows Installer Executable (6.4.0)

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)
  • Deutsch (Deutschland)

🐧 Install on Linux

Video2X packages are available for the Linux distros listed below. A universal AppImage is also available for other distros. If you'd like to build it from source code, refer to the PKGBUILD file for a general overview of the required dependencies and commands.

📦 Container Image

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.

📔 Google Colab

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.

💬 Telegram Discussion Group

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.

📖 Documentation

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) 2018-2025 K4YT3X and contributors.

AGPLv3

This project includes or depends on these following projects:

ProjectLicense
FFmpeg/FFmpegLGPLv2.1, GPLv2
Tencent/ncnnBSD 3-Clause
bloc97/Anime4KMIT License
nihui/realcugan-ncnn-vulkanMIT License
nihui/rife-ncnn-vulkanMIT License
xinntao/Real-ESRGAN-ncnn-vulkanMIT 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.

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