This is an open source library for CNN-based face detection in images. The CNN model has been converted to stastic variales in C source files. The source code does not depend on any other libraries. What you need is just a C++ compiler. You can compile the source code under Windows, Linux, ARM and any platform with a C++ compiler.

SIMD instructions are used to speedup the detection. You can enable AVX2 if you use Intel CPU or NEON for ARM.

The model file has also been provided in directory ./models/.

examples/libfacedetectcnn-example.cpp shows how to use the library.

• Please add -O3 to turn on optimizations when you compile the source code using g++.
• Please choose 'Maximize Speed/-O2' when you compile the source code using Microsoft Visual Studio.

• OpenCV Haar+AdaBoost runs with minimal face size 48x48
• Face detection only, and no landmark detection included.
• Minimal face size ~12x12
• Intel(R) Core(TM) i7-7700 CPU @ 3.6GHz.

• Face detection only, and no landmark detection included.
• Minimal face size ~12x12
• Raspberry Pi 3 B+, Broadcom BCM2837B0, Cortex-A53 (ARMv8) 64-bit SoC @ 1.4GHz

• Shiqi Yu, [email protected]

• Jia Wu
• Shengyin Wu
• Dong Xu

The work is partyly supported by the Science Foundation of Shenzhen (Grant No. JCYJ20150324141711699).

• git clone [email protected]:mhsszm/test_libfacedetection.git
• cd test_libfacedetection
• mkdir build && cd build
• cmake ..
• make
• ./face_detect ../images/keliamoniz2.jpg