# libfacedetection

**Repository Path**: alexwell/libfacedetection

## Basic Information

- **Project Name**: libfacedetection
- **Description**: An open source library for face detection in images. The face detection speed can reach 1500FPS. 
- **Primary Language**: C++
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-10-12
- **Last Updated**: 2024-10-23

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# libfacedetection

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.

![Examples](/images/cnnresult.png "Detection example")

How to Compile
-------------
* 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.

CNN-based Face Detection on Windows
-------------

| Method             |Time          | FPS         |Time          | FPS         |
|--------------------|--------------|-------------|--------------|-------------|
|                    |  X64         |X64          |  X64         |X64          |
|                    |Single-thread |Single-thread|Multi-thread  |Multi-thread |
|OpenCV Haar+AdaBoost (640x480)|   --         | --          | 12.33ms      |   81.1      |
|cnn (CPU, 640x480)  |  64.21ms     | 15.57       | 15.59ms      |   64.16     |
|cnn (CPU, 320x240)  |  15.23ms     | 65.68       |  3.99ms      |  250.40     |
|cnn (CPU, 160x120)  |   3.47ms     | 288.08      |  0.95ms      | 1052.20     |
|cnn (CPU, 128x96)   |   2.35ms     | 425.95      |  0.64ms      | 1562.10     |

* 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.

CNN-based Face Detection on ARM Linux (Raspberry Pi 3 B+)
-------------

| Method             |Time          | FPS         |Time          | FPS         |
|--------------------|--------------|-------------|--------------|-------------|
|                    |Single-thread |Single-thread|Multi-thread  |Multi-thread |
|cnn (CPU, 640x480)  |  512.04ms    |  1.95       |  174.89ms    |   5.72      |
|cnn (CPU, 320x240)  |  123.47ms    |  8.10       |   42.13ms    |  23.74      |
|cnn (CPU, 160x120)  |   27.42ms    | 36.47       |    9.75ms    | 102.58      |
|cnn (CPU, 128x96)   |   17.78ms    | 56.24       |    6.12ms    | 163.50      |

* 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


Author
-------------
* Shiqi Yu, <shiqi.yu@gmail.com>

Contributors
-------------
* Jia Wu
* Shengyin Wu
* Dong Xu

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