轻量级人脸检测+关键点检测

ncnn部署轻量级人脸检测模型 rhttps://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB，和insightface人脸关键点检测模型 https://github.com/deepinsight/insightface。 人脸检测的输入分辨率为320x240，人脸检测+关键点在rk3566设备单线程CPU能达15-18FPS。rk3588/MT8195设备单线程能达30FPS以上。（占用低、速度快，Linzaer大佬的模型非常好用）

This is a sample ncnn android project, it depends on ncnn library and opencv

https://github.com/Tencent/ncnn

https://github.com/nihui/opencv-mobile

how to build and run

step1

https://github.com/Tencent/ncnn/releases

• Download ncnn-YYYYMMDD-android-vulkan.zip or build ncnn for android yourself
• Extract ncnn-YYYYMMDD-android-vulkan.zip into app/src/main/jni and change the ncnn_DIR path to yours in app/src/main/jni/CMakeLists.txt

step2

https://github.com/nihui/opencv-mobile

• Download opencv-mobile-XYZ-android.zip
• Extract opencv-mobile-XYZ-android.zip into app/src/main/jni and change the OpenCV_DIR path to yours in app/src/main/jni/CMakeLists.txt

step3

• Open this project with Android Studio, build it and enjoy!

screenshot

reference

https://github.com/nihui/ncnn-android-mobilenetssd

https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB

https://github.com/deepinsight/insightface