【opencv】Java实现opencv 调用本地摄像头，实现人脸识别、人形识别、人眼识别

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效果预览：（没办法，为了效果只能上像了，丑别介意。哈哈。。）

上代码：

  1 package com.lw.test;
  2
  3 import java.awt.Graphics;
  4 import java.awt.event.MouseAdapter;
  5 import java.awt.event.MouseEvent;
  6 import java.awt.image.BufferedImage;
  7
  8 import javax.swing.JFrame;
  9 import javax.swing.JPanel;
 10 import javax.swing.WindowConstants;
 11
 12 import org.opencv.core.Core;
 13 import org.opencv.core.Mat;
 14 import org.opencv.core.MatOfDouble;
 15 import org.opencv.core.MatOfRect;
 16 import org.opencv.core.Point;
 17 import org.opencv.core.Rect;
 18 import org.opencv.core.Scalar;
 19 import org.opencv.imgproc.Imgproc;
 20 import org.opencv.ml.SVM;
 21 import org.opencv.objdetect.CascadeClassifier;
 22 import org.opencv.objdetect.HOGDescriptor;
 23 import org.opencv.videoio.VideoCapture;
 24 import org.opencv.videoio.Videoio;
 25
 26 public class CaptureBasic extends JPanel {
 27
 28     private BufferedImage mImg;
 29
 30     private BufferedImage mat2BI(Mat mat){
 31         int dataSize =mat.cols()*mat.rows()*(int)mat.elemSize();
 32         byte[] data=new byte[dataSize];
 33         mat.get(0, 0,data);
 34         int type=mat.channels()==1?
 35                 BufferedImage.TYPE_BYTE_GRAY:BufferedImage.TYPE_3BYTE_BGR;
 36
 37         if(type==BufferedImage.TYPE_3BYTE_BGR){
 38             for(int i=0;i<dataSize;i+=3){
 39                 byte blue=data[i+0];
 40                 data[i+0]=data[i+2];
 41                 data[i+2]=blue;
 42             }
 43         }
 44         BufferedImage image=new BufferedImage(mat.cols(),mat.rows(),type);
 45         image.getRaster().setDataElements(0, 0, mat.cols(), mat.rows(), data);
 46
 47         return image;
 48     }
 49
 50     public void paintComponent(Graphics g){
 51         if(mImg!=null){
 52             g.drawImage(mImg, 0, 0, mImg.getWidth(),mImg.getHeight(),this);
 53         }
 54     }
 55
 56     public static void main(String[] args) {
 57         try{
 58             System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
 59
 60             Mat capImg=new Mat();
 61             VideoCapture capture=new VideoCapture(0);
 62             int height = (int)capture.get(Videoio.CAP_PROP_FRAME_HEIGHT);
 63             int width = (int)capture.get(Videoio.CAP_PROP_FRAME_WIDTH);
 64             if(height==0||width==0){
 65                 throw new Exception("camera not found!");
 66             }
 67
 68             JFrame frame=new JFrame("camera");
 69             frame.setDefaultCloseOperation(WindowConstants.DISPOSE_ON_CLOSE);
 70             CaptureBasic panel=new CaptureBasic();
 71             panel.addMouseListener(new MouseAdapter() {
 72                 @Override
 73                 public void mouseClicked(MouseEvent arg0) {
 74                      System.out.println("click");
 75                 }
 76                 @Override
 77                 public void mouseMoved(MouseEvent arg0) {
 78                     System.out.println("move");
 79
 80                 }
 81                 @Override
 82                 public void mouseReleased(MouseEvent arg0) {
 83                     System.out.println("mouseReleased");
 84                 }
 85                 @Override
 86                 public void mousePressed(MouseEvent arg0) {
 87                     System.out.println("mousePressed");
 88                 }
 89                 @Override
 90                 public void mouseExited(MouseEvent arg0) {
 91                     System.out.println("mouseExited");
 92                     //System.out.println(arg0.toString());
 93                 }
 94                 @Override
 95                 public void mouseDragged(MouseEvent arg0) {
 96                     System.out.println("mouseDragged");
 97                     //System.out.println(arg0.toString());
 98                 }
 99
100     　　});
101             frame.setContentPane(panel);
102             frame.setVisible(true);
103             frame.setSize(width+frame.getInsets().left+frame.getInsets().right,
104                     height+frame.getInsets().top+frame.getInsets().bottom);
105             int n=0;
106             Mat temp=new Mat();
107             while(frame.isShowing()&& n<500){
108                 //System.out.println("第"+n+"张");
109                 capture.read(capImg);
110                 Imgproc.cvtColor(capImg, temp, Imgproc.COLOR_RGB2GRAY);
111                 //Imgcodecs.imwrite("G:/opencv/lw/neg/back"+n+".png", temp);
112                 panel.mImg=panel.mat2BI(detectFace(capImg));
113                 panel.repaint();
114                 //n++;
115                 //break;
116             }
117             capture.release();
118             frame.dispose();
119         }catch(Exception e){
120             System.out.println("例外：" + e);
121         }finally{
122             System.out.println("--done--");
123         }
124
125     }
126     /**
127      * opencv实现人脸识别
128      * @param img
129      */
130     public static Mat detectFace(Mat img) throws Exception
131     {
132
133         System.out.println("Running DetectFace ... ");
134         // 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
135         CascadeClassifier faceDetector = new CascadeClassifier("D:\\TDDOWNLOAD\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml");
136
137
138         // 在图片中检测人脸
139         MatOfRect faceDetections = new MatOfRect();
140
141         faceDetector.detectMultiScale(img, faceDetections);
142
143         //System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
144
145         Rect[] rects = faceDetections.toArray();
146         if(rects != null && rects.length >= 1){
147             for (Rect rect : rects) {
148                 Imgproc.rectangle(img, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
149                         new Scalar(0, 0, 255), 2);
150             }
151         }
152         return img;
153     }
154
155
156     /**
157      * opencv实现人型识别，hog默认的分类器。所以效果不好。
158      * @param img
159      */
160     public static Mat detectPeople(Mat img) {
161         //System.out.println("detectPeople...");
162         if (img.empty()) {
163             System.out.println("image is exist");
164         }
165         HOGDescriptor hog = new HOGDescriptor();
166         hog.setSVMDetector(HOGDescriptor.getDefaultPeopleDetector());
167         System.out.println(HOGDescriptor.getDefaultPeopleDetector());
168         //hog.setSVMDetector(HOGDescriptor.getDaimlerPeopleDetector());
169         MatOfRect regions = new MatOfRect();
170         MatOfDouble foundWeights = new MatOfDouble();
171         //System.out.println(foundWeights.toString());
172         hog.detectMultiScale(img, regions, foundWeights);
173         for (Rect rect : regions.toArray()) {
174             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);
175         }
176         return img;
177     }
178
179 }