AI:OPENCV实现人脸的自动识别

依赖jar包：

faceRecognition.java

package opencv;

import java.awt.Graphics;
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.MatOfDouble;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.objdetect.HOGDescriptor;
import org.opencv.videoio.VideoCapture;
import org.opencv.videoio.Videoio;

@SuppressWarnings("serial")
public class faceRecognition extends JPanel {

    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 void paintComponent(Graphics g) {
        if (mImg != null) {
            g.drawImage(mImg, 0, 0, mImg.getWidth(), mImg.getHeight(), this);
        }
    }

    public static void main(String[] args) {
        try {
            System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

            Mat capImg = new Mat();
            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("未发现摄像头！");
            }

            // 创建jframe
            JFrame frame = new JFrame("摄像头");
            frame.setDefaultCloseOperation(WindowConstants.DISPOSE_ON_CLOSE);
            faceRecognition panel = new faceRecognition();
            // 添加鼠标监听器
            // panel.addMouseListener(new MouseAdapter() {
            // @Override
            // public void mouseClicked(MouseEvent arg0) {
            // System.out.println("鼠标点击");
            // }
            //
            // @Override
            // public void mouseMoved(MouseEvent arg0) {
            // System.out.println("鼠标移开");
            //
            // }
            //
            // @Override
            // public void mouseReleased(MouseEvent arg0) {
            // System.out.println("鼠标释放");
            // }
            //
            // @Override
            // public void mousePressed(MouseEvent arg0) {
            // System.out.println("鼠标按下");
            // }
            //
            // @Override
            // public void mouseExited(MouseEvent arg0) {
            // System.out.println("鼠标出界");
            // // System.out.println(arg0.toString());
            // }
            //
            // @Override
            // public void mouseDragged(MouseEvent arg0) {
            // System.out.println("mouseDragged");
            // // System.out.println(arg0.toString());
            // }
            // });
            frame.setContentPane(panel);
            frame.setVisible(true);
            frame.setSize(width + frame.getInsets().left + frame.getInsets().right,
                    height + frame.getInsets().top + frame.getInsets().bottom);
            int n = 1;
            Mat temp = new Mat();
            // while (frame.isShowing() && n <= 500) {
            while (frame.isShowing()) {
                // System.out.println("第" + n + "张");
                capture.read(capImg); // 载入图片
                Imgproc.cvtColor(capImg, temp, Imgproc.COLOR_RGB2GRAY);
                // Imgcodecs.imwrite("E:/opencv/wzg/picture_" + n + ".png", temp); // 存储图片到本地
                panel.mImg = panel.mat2BI(detectFace(capImg)); // 调用人脸识别方法
                panel.repaint();
                // n++;
                // break; // 识别500存入本地
            }
            capture.release();
            frame.dispose();
        } 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 Mat detectFace(Mat img) throws Exception {

        // System.out.println("开始人像识别 ... ");
        // 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("E:\\my_dev\\haarcascade_frontalface_alt.xml");

        // 在图片中检测人脸
        MatOfRect faceDetections = new MatOfRect();

        faceDetector.detectMultiScale(img, faceDetections);

        if (faceDetections.toArray().length == 0) {
//            System.out.println("no face");
        } else {
            System.out.println(String.format("检测到  %s 个人像", faceDetections.toArray().length));
        }

        Rect[] rects = faceDetections.toArray();
        if (rects != null && rects.length >= 1) {
            for (Rect rect : rects) {
                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);
            }
        }
        return img;
    }

    /**
     * opencv实现人型识别，hog默认的分类器。所以效果不好。
     * 
     * @param img
     */
    public static Mat detectPeople(Mat img) {
        // System.out.println("detectPeople...");
        if (img.empty()) {
            System.out.println("image is exist");
        }
        HOGDescriptor hog = new HOGDescriptor();
        hog.setSVMDetector(HOGDescriptor.getDefaultPeopleDetector());
        System.out.println(HOGDescriptor.getDefaultPeopleDetector());
        hog.setSVMDetector(HOGDescriptor.getDaimlerPeopleDetector());
        MatOfRect regions = new MatOfRect();
        MatOfDouble foundWeights = new MatOfDouble();
        System.out.println(foundWeights.toString());
        hog.detectMultiScale(img, regions, foundWeights);
        for (Rect rect : regions.toArray()) {
            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);
        }
        return img;
    }

}