video2x README

The project's README from github.com/k4yt3x/video2x. As one markdown file: README.md.

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

🌟 Version 6.0.0

Video2X 6.0.0 highlights:

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.

🪟 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:

🐧 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

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:

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.

video2x (k4yt3x/video2x)

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22.3K ·GitHub
Video2x
这是做什么的?Video2X 是一个开源的视频超分辨率和补帧工具:它利用机器学习把低分辨率视频放大到更高的画质,并通过插帧让画面动得更流畅。
这是桌面软件,还是得在命令行里运行?两种方式都有:在 Windows 上它是一个带标准安装程序的图形界面软件,在 Linux 上有软件包或 AppImage 可用,另外还有 Docker 镜像,适合在 Linux 和 macOS 上无界面运行。
我的电脑能跑得动吗?需要一颗支持 AVX2 的 CPU(Intel Haswell 2013 年及以后,AMD Excavator 2015 年及以后),以及一块支持 Vulkan 的显卡——NVIDIA GTX 600 系列、AMD HD 7000 系列或 Intel HD 4000 之后的都行。
在 macOS 上能用吗?没有原生的 macOS 版本;macOS 是通过 GitHub Container Registry 上的 Video2X 容器镜像来支持的,和 Linux 一起。
它是免费的吗?许可证有什么要求?它是免费开源的,采用 GNU AGPL v3 许可证——个人使用完全没问题,但修改和衍生项目必须以同样的许可证发布。
我没有好显卡怎么办?可以在 Google Colab 上免费运行 Video2X:能借用 NVIDIA T4、L4 或 A100,每次会话最长 12 小时,但别不停地连着开新会话全天候跑放大,否则 Google 可能会封你的账号。
放大时支持哪些 AI 模型?放大方面内置了 Anime4K v4、Real-ESRGAN 和 Real-CUGAN,补帧方面是 RIFE——全部通过 ncnn 在 Vulkan 上运行。它也支持任意自定义的 MPV 兼容 GLSL 着色器。
它能修复卡顿的低帧率视频,而不只是放大吗?可以——除了放大(滤波)之外,还有一个由 RIFE 驱动的专门补帧模式,所以你既能提高视频的分辨率,也能提高它的帧率。
处理的时候需要很大的剩余磁盘空间吗?不需要。6.x 的处理流程在运行期间不占用任何额外磁盘空间——你只需要留出存放最终输出文件的空间就行。
为什么 6 版整个项目都重写了?作者用 C/C++ 从零重写了 Video2X,为的是让它真正好用,比 5.0.0 beta 省心得多,经过优化的处理流程跑起来飞快,输出质量也明显更好。
What are similar projects?ALH-Pro, Waifu2x-Extension-GUI, dlss5-visual-enhancer, paper2gui, Anime4K, video2dlssnr, waifu2x, KytyPS5
Which topics is it in?anime4k, frame-interpolation, video-upscaling, colab, appimage, super-resolution, neural-networks, vulkan, video-processing, ffmpeg, cpp, c++
Creator
k4yt3x
Size
560.8 MB
Stars
22.3K
Updated
CommitMar 07Release6.4.0Jan 24
Age
8y
Commits · 90 Days