OPENCV+JAVA 人脸识别

http://opencv.org/releases.html 

官方下载 安装文件 ，以win7为例，下载opencv-2.4.13.3-vc14.exe

安装后，在build目录下 D:\opencv\build\java，获取opencv-2413.jar，copy至项目目录

同时需要dll文件 与 各 识别xml文件，进行不同特征的识别（人脸，侧脸，眼睛等）

dll目录：D:\opencv\build\java\x64\opencv_java2413.dll

xml目录：D:\opencv\sources\data\haarcascades\haarcascade_frontalface_alt.xml（目录中有各类识别文件）

项目结构：

具体代码：由于需要用到 opencv 的dll文件，故要么放在java library path 中，或放在jre lib 中，windows下可放在System32目录下

也可以在代码中 动态加载，如下：

package opencv;import com.sun.scenario.effect.ImageData;import org.opencv.core.*;import org.opencv.core.Point;import org.opencv.highgui.Highgui;import org.opencv.imgproc.Imgproc;import org.opencv.objdetect.CascadeClassifier;import javax.imageio.ImageIO;import javax.swing.*;import java.awt.*;import java.awt.image.BufferedImage;import java.io.File;import java.io.IOException;import java.util.Arrays;import java.util.Vector;/** * Created by Administrator on 2017/8/17. */public class Test {    static{        // 导入opencv的库        String opencvpath = System.getProperty("user.dir") + "\\opencv\\x64\\";        String libPath = System.getProperty("java.library.path");        String a = opencvpath + Core.NATIVE_LIBRARY_NAME + ".dll";        System.load(opencvpath + Core.NATIVE_LIBRARY_NAME + ".dll");    }    public static String getCutPath(String filePath){        String[] splitPath = filePath.split("\\.");        return splitPath[0]+"Cut"+"."+splitPath[1];    }    public static void process(String original,String target) throws Exception {        String originalCut = getCutPath(original);        String targetCut = getCutPath(target);        if(detectFace(original,originalCut) && detectFace(target,targetCut)){        }    }    public static boolean detectFace(String imagePath,String outFile) throws Exception    {        System.out.println("\nRunning DetectFaceDemo");        // 从配置文件lbpcascade_frontalface.xml中创建一个人脸识别器，该文件位于opencv安装目录中        CascadeClassifier faceDetector = new CascadeClassifier(                "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_frontalface_alt.xml");        Mat image = Highgui.imread(imagePath);        // 在图片中检测人脸        MatOfRect faceDetections = new MatOfRect();        faceDetector.detectMultiScale(image, faceDetections);        System.out.println(String.format("Detected %s faces",                faceDetections.toArray().length));        Rect[] rects = faceDetections.toArray();        if(rects != null && rects.length > 1){            throw new RuntimeException("超过一个脸");        }        // 在每一个识别出来的人脸周围画出一个方框        Rect rect = rects[0];        Core.rectangle(image, new Point(rect.x-2, rect.y-2), new Point(rect.x                + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));        Mat sub = image.submat(rect);        Mat mat = new Mat();        Size size = new Size(300, 300);        Imgproc.resize(sub, mat, size);//将人脸进行截图并保存        return Highgui.imwrite(outFile, mat);        // 将结果保存到文件//        String filename = "C:\\Users\\Administrator\\Desktop\\opencv\\faceDetection.png";//        System.out.println(String.format("Writing %s", filename));//        Highgui.imwrite(filename, image);    }    public static void setAlpha(String imagePath,String outFile) {        /**         * 增加测试项         * 读取图片，绘制成半透明         */        try {            ImageIcon imageIcon = new ImageIcon(imagePath);            BufferedImage bufferedImage = new BufferedImage(imageIcon.getIconWidth(),imageIcon.getIconHeight()                    , BufferedImage.TYPE_4BYTE_ABGR);            Graphics2D g2D = (Graphics2D) bufferedImage.getGraphics();            g2D.drawImage(imageIcon.getImage(), 0, 0,                    imageIcon.getImageObserver());            //循环每一个像素点，改变像素点的Alpha值            int alpha = 100;            for (int j1 = bufferedImage.getMinY(); j1 < bufferedImage.getHeight(); j1++) {                for (int j2 = bufferedImage.getMinX(); j2 < bufferedImage.getWidth(); j2++) {                    int rgb = bufferedImage.getRGB(j2, j1);                    rgb = ( (alpha + 1) << 24) | (rgb & 0x00ffffff);                    bufferedImage.setRGB(j2, j1, rgb);                }            }            g2D.drawImage(bufferedImage, 0, 0, imageIcon.getImageObserver());            //生成图片为PNG            ImageIO.write(bufferedImage, "png",  new File(outFile));        }        catch (Exception e) {            e.printStackTrace();        }    }    private static void watermark(String a,String b,String outFile, float alpha) throws IOException {        // 获取底图                 BufferedImage buffImg = ImageIO.read(new File(a));                 // 获取层图                 BufferedImage waterImg = ImageIO.read(new File(b));                 // 创建Graphics2D对象，用在底图对象上绘图                 Graphics2D g2d = buffImg.createGraphics();                 int waterImgWidth = waterImg.getWidth();// 获取层图的宽度                 int waterImgHeight = waterImg.getHeight();// 获取层图的高度                 // 在图形和图像中实现混合和透明效果                 g2d.setComposite(AlphaComposite.getInstance(AlphaComposite.SRC_ATOP, alpha));                 // 绘制                 g2d.drawImage(waterImg, 0, 0, waterImgWidth, waterImgHeight, null);                 g2d.dispose();// 释放图形上下文使用的系统资源        //生成图片为PNG        ImageIO.write(buffImg, "png",  new File(outFile));    }    public static boolean mergeSimple(BufferedImage image1, BufferedImage image2, int posw, int posh, File fileOutput) {        //合并两个图像        int w1 = image1.getWidth();        int h1 = image1.getHeight();        int w2 = image2.getWidth();        int h2 = image2.getHeight();        BufferedImage imageSaved = new BufferedImage(w1, h1, BufferedImage.TYPE_INT_ARGB);        Graphics2D g2d = imageSaved.createGraphics();        // 增加下面代码使得背景透明        g2d.drawImage(image1, null, 0, 0);        image1 = g2d.getDeviceConfiguration().createCompatibleImage(w1, w2, Transparency.TRANSLUCENT);        g2d.dispose();        g2d = image1.createGraphics();        // 背景透明代码结束//        for (int i = 0; i < w2; i++) {//            for (int j = 0; j < h2; j++) {//                int rgb1 = image1.getRGB(i + posw, j + posh);//                int rgb2 = image2.getRGB(i, j);////                if (rgb1 != rgb2) {//                    //rgb2 = rgb1 & rgb2;//                }//                imageSaved.setRGB(i + posw, j + posh, rgb2);//            }//        }        boolean b = false;        try {            b = ImageIO.write(imageSaved, "png", fileOutput);        } catch (IOException ie) {            ie.printStackTrace();        }        return b;    }    public static void main(String[] args) throws Exception {        String a,b,c,d;        a = "C:\\Users\\Administrator\\Desktop\\opencv\\zzl.jpg";        d = "C:\\Users\\Administrator\\Desktop\\opencv\\cgx.jpg";        //process(a,d);        a = "C:\\Users\\Administrator\\Desktop\\opencv\\zzlCut.jpg";        d = "C:\\Users\\Administrator\\Desktop\\opencv\\cgxCut.jpg";        CascadeClassifier faceDetector = new CascadeClassifier(                "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_frontalface_alt.xml");        CascadeClassifier eyeDetector1 = new CascadeClassifier(                "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_eye.xml");        CascadeClassifier eyeDetector2 = new CascadeClassifier(                "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_eye_tree_eyeglasses.xml");        Mat image = Highgui.imread("C:\\Users\\Administrator\\Desktop\\opencv\\gakki.jpg");        // 在图片中检测人脸        MatOfRect faceDetections = new MatOfRect();        //eyeDetector2.detectMultiScale(image, faceDetections);        Vector<Rect> objects;        eyeDetector1.detectMultiScale(image, faceDetections, 2.0,1,1,new Size(20,20),new Size(20,20));        Rect[] rects = faceDetections.toArray();        Rect eyea,eyeb;        eyea = rects[0];eyeb = rects[1];         System.out.println("a-中心坐标 " + eyea.x + " and " + eyea.y);        System.out.println("b-中心坐标 " + eyeb.x + " and " + eyeb.y);        //获取两个人眼的角度        double dy=(eyeb.y-eyea.y);        double dx=(eyeb.x-eyea.x);        double len=Math.sqrt(dx*dx+dy*dy);        System.out.println("dx is "+dx);        System.out.println("dy is "+dy);        System.out.println("len is "+len);        double angle=Math.atan2(Math.abs(dy),Math.abs(dx))*180.0/Math.PI;        System.out.println("angle is "+angle);        for(Rect rect:faceDetections.toArray()) {            Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x                    + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));        }        String filename = "C:\\Users\\Administrator\\Desktop\\opencv\\ouput.png";        System.out.println(String.format("Writing %s", filename));        Highgui.imwrite(filename, image);//        watermark(a,d,"C:\\Users\\Administrator\\Desktop\\opencv\\zzlTm2.jpg",0.7f);////        // 读取图像，不改变图像的原始信息//        Mat image1 = Highgui.imread(a);//        Mat image2 = Highgui.imread(d);//        Mat mat1 = new Mat();Mat mat2 = new Mat();//        Size size = new Size(300, 300);//        Imgproc.resize(image1, mat1, size);//        Imgproc.resize(image2, mat2, size);//        Mat mat3 = new Mat(size,CvType.CV_64F);//        //Core.addWeighted(mat1, 0.5, mat2, 1, 0, mat3);////        //Highgui.imwrite("C:\\Users\\Administrator\\Desktop\\opencv\\add.jpg", mat3);////        mergeSimple(ImageIO.read(new File(a)),//                ImageIO.read(new File(d)),0,0,//                new File("C:\\Users\\Administrator\\Desktop\\opencv\\add.jpg"));    }}

最终效果：人脸旁有绿色边框，可以将绿色边框图片截取，生成人脸图