Build · Examples · Integration
Welcome to join us to make GPUPixel better by participating discussions, opening issues, submitting PRs 👏.
Replace the VNN face detection library with Mars-Face from v1.3.0-beta
🍔 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.
👉 Video: YouTube
Origin | Smooth | White | ThinFace |
---|---|---|---|
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BigEye | Lipstick | Blusher | ON-OFF |
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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 | ✅ | ❌ | ❌ |
- | iPhone 6P | iPhone 8 | iPhone X | iPhone 11 | iPhone 14 pro |
---|---|---|---|---|---|
CPU | 5% | 5% | 3% | 3% | 3% |
Time Taken | 10ms | 4ms | 3ms | 3ms | 3ms |
- | Xiaomi 10 | Huawei Mate30 | Vivo | SAMSUNG | Google Pixel |
---|---|---|---|---|---|
CPU | 3% | 5% | - | - | - |
Time Taken | 6ms | 5ms | - | - | - |
iOS(.framework) | MacOS(.framework) | Android(.aar) | |
---|---|---|---|
Size | 2.4 MB | 2.6 MB | 2.1 MB |
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See the doc: Introduction | Build | Examples | Integrated
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.
If you like this project, you can consider supporting me through the following methods:
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Thank you to the following friends for their contributions and support to the project.
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- Doc : Online documentation.
- Issues : 👉 Github Issues.
- Mail : 👉 Send email to us.
- Contact : 👉 Contact us.
This repository is available under the MIT License.