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;

     }

 }