gpupixel

gpupixel

Real-time image and video processing library similar to GPUImage, with built-in beauty filters, Written in C++11 and based on OpenGL/ES.

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GPUPixel is a real-time, high-performance image and video filter library written in C++11 and based on OpenGL/ES. It incorporates a built-in beauty face filter that achieves commercial-grade beauty effects. The library is extremely easy to compile and integrate with a small size, supporting platforms including iOS, Android, Mac, Windows, and Linux. GPUPixel provides various filters like skin smoothing, whitening, face slimming, big eyes, lipstick, and blush. It supports input formats like YUV420P, RGBA, JPEG, PNG, and output formats like RGBA and YUV420P. The library's performance on devices like iPhone and Android is optimized, with low CPU usage and fast processing times. GPUPixel's lib size is compact, making it suitable for mobile and desktop applications.

README:

English | 简体中文

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🌟 Join us in making GPUPixel better through discussions, issues, and PRs.

📢 Note: VNN face detection library has been replaced with Mars-Face from v1.3.0-beta

Introduction

🚀 GPUPixel is a real-time, high-performance image and video filter library that's extremely easy to compile and integrate with a small footprint.

💻 GPUPixel is written in C++11 and built on OpenGL/ES, featuring built-in beauty face filters that deliver commercial-grade results.

🌐 GPUPixel supports multiple platforms including iOS, Android, Mac, Win and Linux, and can be ported to virtually any platform that supports OpenGL/ES.

Effects Preview

🎬 Video: YouTube

Origin Smooth White ThinFace
BigEye Lipstick Blusher ON-OFF

Architecture

Features

✨ This table compares the features supported by GPUPixel, GPUImage, and Android-GPUImage:

✅: Supported | ❌: Not supported | ✏️: Planning

GPUPixel GPUImage Android-GPUImage
📷 Filters:
Skin Smoothing Filter
Skin Whitening Filter
Face Slimming Filter
Big Eyes Filter
Lipstick Filter
Blush Filter
More Build in Filter
🎬 Input Formats:
YUV420P(I420)
RGBA
JPEG
PNG
NV21(for Android) ✏️
🎥 Output Formats:
RGBA
YUV420P(I420) ✏️
💻 Platform:
iOS
Mac
Android
Win
Linux

⚡ Performance

iPhone

- iPhone 6P iPhone 8 iPhone X iPhone 11 iPhone 14 pro
CPU 5% 5% 3% 3% 3%
Time Taken 10ms 4ms 3ms 3ms 3ms

Android

- Xiaomi 10 Huawei Mate30 Vivo SAMSUNG Google Pixel
CPU 3% 5% - - -
Time Taken 6ms 5ms - - -

Before You Start

⭐ Star us on GitHub to receive instant notifications about new releases!

Getting Started

🔍 See the docs: Introduction | Build | Examples | Integration

Contributing

🤝 Help make GPUPixel better by joining our discussions, opening issues, or submitting PRs. Check our Contributing Guide to get started.

Please also consider supporting GPUPixel by sharing it on social media and at events and conferences.

Contributors

Sponsorship

💖 If you like this project, consider supporting us through the following methods:

☕ Support me on Ko-fi 💝 Support on Open Collective 💰 WeChat Sponsor

Sponsors

🙏 Thank you to the following contributors for their generous support of the project:

@leavenotrace @weiyu666

Contact & Support

  • 📚 Docs : Online documentation
  • 🐛 Issues : Report bugs or request features
  • 📧 Email : Send us a message
  • 📞 Contact : Get in touch with us

Acknowledgements

🔗 Reference Projects

  1. GPUImage
  2. CainCamera
  3. AwemeLike
  4. VNN

License

📄 This repository is available under the MIT License.

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