java opencv4.40图片实现人脸识别（2）

怼烎@ 2022-11-29 13:09 166阅读 0赞

在之前博客中我们介绍了opencv4.4的安装: [https://blog.csdn.net/datouniao1/article/details/108072623][https_blog.csdn.net_datouniao1_article_details_108072623]

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:

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2RhdG91bmlhbzE_size_16_color_FFFFFF_t_70][]

希望对你有所帮助

[https_blog.csdn.net_datouniao1_article_details_108072623]: https://blog.csdn.net/datouniao1/article/details/108072623
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2RhdG91bmlhbzE_size_16_color_FFFFFF_t_70]: /images/20221124/6d6be4d40d7c475c86a954a3a578d008.png