• 一小时,从零实现Java人脸识别
  • 1. 安装OpenCv环境
  • 2. 进入开发
  • 3. 主函数调用

一小时,从零实现Java人脸识别

本案例成功与2021，09，02

此样图在本教程基础可实现，并非完全次教程实例图。

1. 安装OpenCv环境

opencv官网(点我进入)

实验环境为win，自行选择

下载成功后，安装即可

2. 进入开发

本案例使用Maven搭建

pom.xml(注意maven的opencv和自己下载的opencv版本需一致)

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <groupId>Opencv</groupId>
    <artifactId>Opencv</artifactId>
    <version>1.0-SNAPSHOT</version>
    <dependencies>
        <dependency>
            <groupId>org.bytedeco</groupId>
            <artifactId>opencv</artifactId>
            <version>4.5.3-1.5.6</version>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.13.2</version>
        </dependency>
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.2.2</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.25</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.25</version>
        </dependency>
    </dependencies>
</project>

编写实体类

/**
 * @Author: 王居三木超
 * @Description: TODO
 * @DateTime: 2021/9/2 19:54
 **/
public class CvtMatEntity {
    //原图Mat
    public Mat img;
    //灰度图Mat
    public Mat gray;
    public static CvtMatEntity cvtR2G(Mat img){
        CvtMatEntity cvtMatEntity = new CvtMatEntity();
        Mat rgb = new Mat();
        //实现图片灰度转换
        Imgproc.cvtColor(img, rgb, Imgproc.COLOR_BGR2RGB);
        Mat gray = new Mat();
        Imgproc.cvtColor(rgb, gray, Imgproc.COLOR_RGB2GRAY);
        //赋值
        cvtMatEntity.img = img;
        cvtMatEntity.gray = gray;
        //返回
        return cvtMatEntity;
    }
}

编写核心类

/**
 * @Author: 王居三木超
 * @Description: TODO
 * @DateTime: 2021/9/2 17:41
 **/
public class InitInstance {
   
    private static Logger logger = LoggerFactory.getLogger(InitInstance.class);
        //脸部识别实例
    private static CascadeClassifier faceDetector;
    
    
    
    //此类加载人脸识别模块
       public static void init(String dllAbsPath, String facexmlAbsPath, String eyexmlAbsPath) {
        logger.info("开始读取脸部识别实例");
           //加载dll文件
        System.load(dllAbsPath);
        faceDetector = new CascadeClassifier(facexmlAbsPath);
        if (faceDetector.empty()) {
            logger.error("人脸识别模块读取失败");
        } else logger.info("人脸识别模块读取成功");
       }
    
    
    
    //此类实现打开视频，识别人脸
       public static void videoDetectorModel() {
           //打开摄像头
        VideoCapture videoCapture = new VideoCapture(0);
           //判断摄像头是否打开
        if (!videoCapture.open(0)) {
            logger.error("相机打开失败");
            return;
        }
           
        while (true) {
            //创建图片Mat
            Mat img = new Mat();
            //读取摄像头下的图像
            if (!videoCapture.read(img)) return;
            //为保证教程详细度，此处不调用实体方法，大家可自行选择
            //图片灰度转化
            Mat rgb = new Mat();
            Imgproc.cvtColor(img, rgb, Imgproc.COLOR_BGR2RGB);
            Mat gray = new Mat();
            Imgproc.cvtColor(rgb, gray, Imgproc.COLOR_RGB2GRAY);
            //创建人脸识别出的矩形变量
            MatOfRect faveRect = new MatOfRect();
            //检测人脸
            faceDetector.detectMultiScale(gray, faveRect);
            //图形面勾选人脸
              for (Rect re : faveRect.toArray()) {
            Imgproc.rectangle(img, new Point(re.x, re.y), new Point(re.x + re.width, re.y + re.height), new Scalar(0, 0, 255), 2);
        }
            //显示在屏幕
            HighGui.imshow("人脸识别", img);
            //按'q'退出
            if (HighGui.waitKey(1) == 81) break;
        }
           //释放资源
        videoCapture.release();
        HighGui.destroyAllWindows();
    }
    
    
    //以下内容为对比人脸模块。与打开视频，识别人脸完全分离
        /**
     * 获取灰度人脸
     */
    public static Mat conv_Mat(String img) {
        //读取图片Mat
        Mat imgInfo = Imgcodecs.imread(img);
        //此处调用了实体方法，实现灰度转化
        CvtMatEntity cvtMatEntity = CvtMatEntity.cvtR2G(imgInfo);
        //创建Mat矩形
        MatOfRect faceMat = new MatOfRect();
        //识别人人脸
        faceDetector.detectMultiScale(cvtMatEntity.gray, faceMat);
        for (Rect rect : faceMat.toArray()) {
            //选出灰度人脸
            Mat face = new Mat(cvtMatEntity.gray, rect);
            return face;
        }
        return null;
    }

    /**
     * 图片对比人脸
     */
    public static double compare_image(String img_1, String img_2) {
        //获得灰度人脸
        Mat mat_1 = conv_Mat(img_1);
        Mat mat_2 = conv_Mat(img_2);
        Mat hist_1 = new Mat();
        Mat hist_2 = new Mat();
        //参数定义
        MatOfFloat ranges = new MatOfFloat(0f, 256f);
        MatOfInt histSize = new MatOfInt(10000000);
        //实现图片计算
        Imgproc.calcHist(Arrays.asList(mat_1), new MatOfInt(0), new Mat(), hist_1, histSize, ranges);
        Imgproc.calcHist(Arrays.asList(mat_2), new MatOfInt(0), new Mat(), hist_2, histSize, ranges);
        // 相关系数，获得相似度
        double res = Imgproc.compareHist(hist_1, hist_2, Imgproc.CV_COMP_CORREL);
        //返回相似度
        return res;
    }
}

3. 主函数调用

/**
 * @Author: 王居三木超
 * @Description: TODO
 * @DateTime: 2021/9/2 17:32
 **/
public class openapiMainApplication {
    public static void main(String[] args) throws UnsupportedEncodingException {
        //此为opencv的opencv_java453.dll
        //位置在opencv安装目录下的build\\java\\x64\\位置
        String dllAbsPath = "D:\\Users\\86159\\Desktop\\CloudPool\\opencv\\opencv\\build\\java\\x64\\opencv_java453.dll";
         //位置在opencv安装目录下的sources\\data\\haarcascades\\位置
        String facexmlAbsPath = "D:\\Users\\86159\\Desktop\\CloudPool\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
        //必须加载
        InitInstance.init(dllAbsPath, facexmlAbsPath,eyexmlAbsPath);
        //        InitInstance.videoDetectorModel();
        //        System.out.println(InitInstance.compare_image("D:\\Users\\86159\\Desktop\\TEST\\2.png", "D:\\Users\\86159\\Desktop\\TEST\\2.png"));
    }
}