java opencv4.40图片实现人脸识别（2）

在之前博客中我们介绍了opencv4.4的安装:​

我们利用opencv4.4中提供的算法实现一个人脸识别

先不说那么多直接上代码：

package org.opencv.test;

import java.awt.Graphics;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

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

import org.junit.Test;
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.core.Size;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;

public class FaceDemo extends JPanel {

    /**
     * 
     */
    private static final long serialVersionUID = 1L;

    protected Mat dst;
    protected Mat truth;

    protected Scalar colorBlack;
    protected Scalar colorWhite;

    protected static final int matSize = 10;
    protected static final double EPS = 0.001;
    protected static final double weakEPS = 0.5;
    
    
    private BufferedImage mImg;
    
    
    @Override
    public void paint(Graphics g){
        if(mImg!=null){
            g.drawImage(mImg, 0, 0, mImg.getWidth(),mImg.getHeight(),this);
        }
    }

    @Test
    public void mainTest() {
        try {

            String opencvDllName = "D:\\opencv\\opencv-4.4.0\\build\\install\\java\\opencv_java440.dll";
            System.load(opencvDllName);
            // System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
        } catch (SecurityException e) {
            System.out.println(e.toString());
            System.exit(-1);
        } catch (UnsatisfiedLinkError e) {
            System.out.println(e.toString());
            System.exit(-1);
        }

        Core.setErrorVerbosity(false);

        String pwd;
        try {
            pwd = new File(".").getCanonicalPath() + File.separator;
        } catch (IOException e) {
            System.out.println(e);
            return;
        }

        OpenCVTestRunner.LENA_PATH = pwd + "res/drawable/OIP.jpg";
        OpenCVTestRunner.CHESS_PATH = pwd + "res/drawable/chessboard.jpg";
        OpenCVTestRunner.LBPCASCADE_FRONTALFACE_PATH = pwd + "res/raw/lbpcascade_frontalface.xml";
        JFrame frame = new JFrame("camera");
        frame.setDefaultCloseOperation(WindowConstants.DISPOSE_ON_CLOSE);
        FaceDemo panel = new FaceDemo();
        frame.setContentPane(panel);
        frame.setVisible(true);
        frame.setSize(500+frame.getInsets().left+frame.getInsets().right,500+frame.getInsets().top+frame.getInsets().bottom);
        CascadeClassifier faceDetector = new CascadeClassifier("D:\\opencv\\opencv-4.4.0\\data\\haarcascades\\haarcascade_frontalface_alt2.xml");
        //CascadeClassifier eyeDetector = new CascadeClassifier("D:\\opencv\\opencv-4.4.0\\data\\haarcascades\\lbpcascade_frontalface.xml");
        MatOfRect faceDetections = new MatOfRect();

        Mat lena = Imgcodecs.imread(OpenCVTestRunner.LENA_PATH);

        faceDetector.detectMultiScale(lena, faceDetections);
        // 转为图像显示
        Rect[] rects = faceDetections.toArray();
            
        if(rects != null && rects.length >= 1){  
            for (Rect rect : rects) {
                //画矩形
                Imgproc.rectangle(lena, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 0, 255), 2);
            }
        }
        panel.mImg = panel.mat2BI(lena);
        panel.repaint();
        int i=1000;
        while(i>100) {
            try {
                Thread.currentThread().sleep(1000);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            i--;
        }
    }
    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;
    }
}

程序运行效果:

希望对你有所帮助