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

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pixpark/gpupixel

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Build · Examples · Integration

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pixpark%2Fgpupixel | Trendshift


Welcome to join us to make GPUPixel better by participating discussions, opening issues, submitting PRs 👏.

Introduction

⛰️ GPUPixel is a real-time, high-performance image and video filter library, extremely easy to compile and integrate with small library size.

🔑 GPUPixel is written in C++11 and is based on OpenGL/ES, incorporating a built-in beauty face filter that achieves commercial-grade beauty effects.

🔌 GPUPixel supports platforms including iOS, Android, Mac, Win and Linux. It can theoretically be ported to any platform that supports OpenGL/ES.

Effects Preview

👉 Video: YouTube | BiliBili

Origin Smooth White ThinFace
BigEye Lipstick Blusher ON-OFF

Architecture

Features

This table compares the features supported by GPUPixel and 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 - - -

Lib Size

iOS(.framework) MacOS(.framework) Android(.aar)
Size 2.4 MB 2.6 MB 2.1 MB

Before You Start

⭐️ Star us on GitHub, and be instantly notified for new releases!

Getting Started

See the doc: Introduction | Build | Examples | Integrated

Contributing

Welcome to join us to make GPUPixel better by participating discussions, opening issues, submitting PRs.

At the same time, please consider supporting GPUPixel by sharing it on social media and at events and conferences.

Contributors

Contact & Support

  • Doc : Online documentation.
  • Issues : 👉 Github Issues.
  • Mail : 👉 Send email to us.
  • WeChat

wechat

Acknowledgement

Reference Project

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

License

This repository is available under the MIT License.