OPENCV+JAVA 人脸识别

骑猪看日落 2021-06-11 15:10 683阅读 0赞

[http://opencv.org/releases.html][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：

![Center][]

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

[http_opencv.org_releases.html]: http://opencv.org/releases.html
[Center]: /images/20210527/57b2d36b6dbc4a1fa58c88099a930ffc.png