OpenCV实现人脸识别

环境搭建：https://blog.csdn.net/colourful_sky/article/details/69487720 
功能：调用系统摄像头检测人脸，检测到一张完整人脸后自动关闭摄像头窗口并将人脸保存到本地，没有检测到人脸或检测到多张人脸给提示继续直到检测到完整人脸

package com.jf,opencv;

import java.awt.image.BufferedImage;

import javax.swing.JFrame;
import javax.swing.JPanel;
import javax.swing.WindowConstants;

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.videoio.VideoCapture;
import org.opencv.videoio.Videoio;


public class OpencvTest extends JPanel {
    static class Haha {
        private Mat mat;
        private int num;
        
        public Mat getMat() {
            return mat;
        }
        public void setMat(Mat mat) {
            this.mat = mat;
        }
        public int getNum() {
            return num;
        }
        public void setNum(int num) {
            this.num = num;
        }
    }
    
    private static final long serialVersionUID = 1L;
    @SuppressWarnings("unused")
    private BufferedImage mImg;
    
    private BufferedImage mat2BI(Mat mat){
        int dataSize = mat.cols()*mat.rows()*(int)mat.elemSize();
        byte[] data = new byte[dataSize];
        mat.get(0, 0,data);
        int type = mat.channels() == 1 ? BufferedImage.TYPE_BYTE_GRAY:BufferedImage.TYPE_3BYTE_BGR;
        if(type == BufferedImage.TYPE_3BYTE_BGR){
            for(int i = 0;i < dataSize;i += 3){
                byte blue = data[i + 0];
                data[i + 0] = data[i + 2];
                data[i + 2] = blue;
            }
        }
        BufferedImage image = new BufferedImage(mat.cols(),mat.rows(),type);
        image.getRaster().setDataElements(0, 0, mat.cols(), mat.rows(), data);
        return image;
    }
    
    public static void main(String[] args) {
        try{
            System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
            Mat capImg = new Mat();
            //启动摄像头
            VideoCapture capture = new VideoCapture(0);
            int height = (int)capture.get(Videoio.CAP_PROP_FRAME_HEIGHT);
            int width = (int)capture.get(Videoio.CAP_PROP_FRAME_WIDTH);
            if(height == 0 || width == 0){
                throw new Exception("camera not found!");
            }
            //使Java实现窗体功能
            JFrame frame = new JFrame("camera");
            //用户单击窗口的关闭按钮时执行的操作
            frame.setDefaultCloseOperation(WindowConstants.DISPOSE_ON_CLOSE); //关闭窗体时，自动隐藏并释放窗体
            OpencvTest panel = new OpencvTest();
            frame.setContentPane(panel); //给窗体加个面板
            frame.setVisible(true); //这个组件显示为可见
            frame.setSize(width+frame.getInsets().left+frame.getInsets().right,
            height+frame.getInsets().top+frame.getInsets().bottom);
            int n = 0;
            while(frame.isShowing() && n != 1){
                capture.read(capImg);//获取视频帧
                //将 capImg 按照 Imgproc.COLOR_RGB2GRAY 的色彩空间转换到 temp
                // Imgproc.cvtColor(capImg, temp, Imgproc.COLOR_RGB2GRAY);
                Imgcodecs.imwrite("D:/opencv/images/back"+ (n + 1) +".png", capImg); //将色彩空间转换后的capImg保存到本地
                Haha haha = detectFace(capImg);
                panel.mImg = panel.mat2BI(haha.getMat()); //人像画红框
                int num = haha.getNum();
                if(num == 1)
                    n = num ;
                else if(num > 1)
                    System.out.println("1个人？");
                else
                    System.out.println("有人吗");
                panel.repaint();//重绘窗口
            }
            capture.release();
            frame.dispose(); //关闭窗口
            frame = null;
        }catch(Exception e){
            System.out.println("例外：" + e);
        }finally{
            System.out.println("--done--");
        }
    }
    
    /**
    * opencv实现人脸识别
    * @param img
    */
    public static Haha detectFace(Mat img) throws Exception{
        Haha haha = new Haha();
        System.out.println("Running DetectFace ... ");
        // 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(System.getProperty("user.dir") + "\\bin\\openccv\\haarcascade_frontalface_alt.xml");        
        
        // 在图片中检测人脸
        MatOfRect faceDetections = new MatOfRect();
        faceDetector.detectMultiScale(img, faceDetections);
                
        Rect[] rects = faceDetections.toArray();
        if(rects != null && rects.length >= 1){
            for (Rect rect : rects) {
                //处理直方图
                Imgproc.rectangle(img, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
                new Scalar(0, 0, 255), 2);
            }
        }
        haha.setMat(img);
        haha.setNum(rects.length);
        return haha;
    }
}