video2x - A machine learning-based video super resolution an

项目说明

<p align="center">
<img src="
alt=": A machine learning-based video super resolution and frame interpolation 框架."/>
</br>
<img src="
<img src="
<img src="
<img src="
<img src="
</p>

🌟 6.0.0

6.0.0 highlights:

Complete rewrite of the project in C/C++.

Faster and more efficient architecture.

Cross-platform support for Windows and Linux.

impro quality.

New 界面 and installer for easy setup on Windows.

<details>
<summary>Click to see more details</summary>

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, a 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 MP GLSL shaders;

supports Real-ESRGAN, Real-CUGAN, and RIFE (all models) via ncnn and ;

requires zero additional disk space during processing, just space for the final output.

</details>

!6.4.0-screenshot

🖥️ Hardware Requirements

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

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 .
- 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 界面 usage, refer to the documentation. If you're unable to download directly from GitHub, try the mirror site. The 界面 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

packages are a for the Linux distros listed below. A uni AppImage is also a for other distros. If you'd like to build it from 源码 代码, refer to the PKGBUILD file for a general o of the required dependencies and commands.

Arch Linux: AUR packages, maintained by .

- aur/
- aur/
- aur/
- aur/

Arch Linux (Chinese Mainland): archlinuxcn packages, maintained by -Tech.

- archlinuxcn/
- archlinuxcn/
- archlinuxcn/
- archlinuxcn/

Other distros: .AppImage on the releases page.

📦 Container Image

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

📔 Google Colab

You can use 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 服务端 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 scuss super resolution, frame interpolation technologies, or the future of in general.

📖 Documentation

Comprehensi for is a at 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 mo

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.

Standard Test Clip (240P) 4.54 MiB

Real-CUGAN Upscaled Sample (1704P) 3.5 MiB

Real-ESRGAN Upscaled Sample (1704P) 3.1 MiB

waifu2x Upscaled Sample (1080P) 4.54 MiB

Ground Truth (1080P) 22.2 MiB

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 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- | MIT License |
| nihui/rife-ncnn- | MIT License |
| xinntao/Real-ESRGAN-ncnn- | MIT License |

More licensing information can be found in the NOTICE file.

🌺 Special Thanks

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

-Tech

项目信息

开发语言：C++

Star 数：21975

技术要点

该项目属于黑客技术方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕A machine learning-based video super resolution and frame interpolation 框架. Est. Hack the Valley II, 2018.展开，提供了可运行的实现，对理解相关安全机制、工具原理与攻防技术具有较高的研究价值。

从技术实现角度看，此类项目的核心在于对底层原理的深入理解与工程化落地。开发者在研究过程中可以结合官方文档与社区讨论，梳理项目的初始化流程、核心模块职责与数据流转，逐步掌握其中的技术细节与设计思路。

使用与学习建议

1. 下载源码压缩包，解压到本地环境。

2. 根据项目类型准备对应的运行环境与依赖。

3. 按照 README 中的步骤完成配置与部署。

4. 在隔离的测试环境中运行验证，避免影响生产系统。

免责声明

本资源来源于开源社区，仅供安全研究、技术学习与合法授权范围内的攻防演练使用，请勿用于任何非法或侵害他人权益的用途。使用本项目产生的一切后果由使用者自行承担。