java opencv五官识别

最新推荐文章于 2021-08-25 12:39:38 发布

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本文介绍了一个使用OpenCV进行实时人脸检测的应用程序。程序通过摄像头捕获视频流，并应用多种特征分类器来识别面部、眼睛、嘴巴、鼻子及耳朵。此外，还实现了人体检测功能。

package test;

import java.io.File;
import java.io.IOException;
import java.net.URL;

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;

public class testc extends JPanel{

   public static void main(String[] args) {
       // TODO Auto-generated method stub
       //System.out.print(9999999999999999*9999999999999999);
       testc muDemo = new testc();
try {
muDemo.showURL();
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}

try{
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

Mat capImg=new Mat();
VideoCapture capture=new VideoCapture(3);
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("camera not found!");
}

JFrame frame=new JFrame("camera");
frame.setDefaultCloseOperation(WindowConstants.DISPOSE_ON_CLOSE);
testc panel=new testc();

frame.setContentPane(panel);
frame.setVisible(true);
frame.setSize(width+frame.getInsets().left+frame.getInsets().right,
height+frame.getInsets().top+frame.getInsets().bottom);
int n=0;
Mat temp=new Mat();
while(frame.isShowing()&& n<500){
//System.out.println("第"+n+"张");
capture.read(capImg);
Imgproc.cvtColor(capImg, temp, Imgproc.COLOR_RGB2GRAY);
//Imgcodecs.imwrite("G:/opencv/lw/neg/back"+n+".png", temp);
panel.mImg=panel.mat2BI(detectFace(capImg));
panel.repaint();
//n++;
//break;
//Mat dst = capImg.clone();
//Imgproc.Canny(capImg,dst,40.0,200.0);

}
capture.release();
frame.dispose();
}catch(Exception e){
System.out.println("例外：" + e);
}finally{
System.out.println("--done--");
}


   }

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);
}
}

/**
* opencv实现人脸识别
* @param img
*/
public static Mat detectFace(Mat img) throws Exception
{

System.out.println("Running DetectFace ... ");
// 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:\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml");
CascadeClassifier faceDetector1 = new CascadeClassifier("e:\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml");
CascadeClassifier faceDetector2 = new CascadeClassifier("e:\\opencv\\sources\\data\\haarcascades\\haarcascade_mcs_mouth.xml");
CascadeClassifier faceDetector3 = new CascadeClassifier("e:\\opencv\\sources\\data\\haarcascades\\haarcascade_mcs_nose.xml");
CascadeClassifier faceDetector4 = new CascadeClassifier("e:\\opencv\\sources\\data\\haarcascades\\haarcascade_mcs_leftear.xml");
CascadeClassifier faceDetector5 = new CascadeClassifier("e:\\opencv\\sources\\data\\haarcascades\\haarcascade_mcs_rightear.xml");

// 在图片中检测人脸
MatOfRect faceDetections = new MatOfRect();
MatOfRect faceDetections1 = new MatOfRect();
MatOfRect faceDetections2 = new MatOfRect();
MatOfRect faceDetections3 = new MatOfRect();
MatOfRect faceDetections4 = new MatOfRect();
MatOfRect faceDetections5 = new MatOfRect();

faceDetector.detectMultiScale(img, faceDetections);
faceDetector1.detectMultiScale(img, faceDetections1);
faceDetector2.detectMultiScale(img, faceDetections2);
faceDetector3.detectMultiScale(img, faceDetections3);
faceDetector4.detectMultiScale(img, faceDetections4);
faceDetector5.detectMultiScale(img, faceDetections5);

//System.out.println(String.format("Detected %s faces", 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);
}
}

Rect[] rects1 = faceDetections1.toArray();
if(rects1 != null && rects1.length >= 1){
for (Rect rect : rects1) {
Imgproc.rectangle(img, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(0, 255, 0), 2);
}
}

Rect[] rects2 = faceDetections2.toArray();
if(rects2 != null && rects2.length >= 1){
for (Rect rect : rects2) {
Imgproc.rectangle(img, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(255, 0, 0), 2);
}
}

Rect[] rects3 = faceDetections3.toArray();
if(rects3 != null && rects3.length >= 1){
for (Rect rect : rects3) {
Imgproc.rectangle(img, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(0, 255, 255), 2);
}
}

Rect[] rects4 = faceDetections4.toArray();
if(rects4 != null && rects4.length >= 1){
for (Rect rect : rects4) {
Imgproc.rectangle(img, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(255, 0, 255), 2);
}
}

Rect[] rects5 = faceDetections5.toArray();
if(rects5 != null && rects5.length >= 1){
for (Rect rect : rects5) {
Imgproc.rectangle(img, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(255, 255, 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;
}

   public void showURL() throws IOException {

// 第一种：获取类加载的根路径 D:\git\daotie\daotie\target\classes
File f = new File(this.getClass().getResource("/").getPath());
System.out.println(f);

// 获取当前类的所在工程路径; 如果不加“/” 获取当前类的加载目录 D:\git\daotie\daotie\target\classes\my
File f2 = new File(this.getClass().getResource("").getPath());
System.out.println(f2);

// 第二种：获取项目路径 D:\git\daotie\daotie
File directory = new File("");// 参数为空
String courseFile = directory.getCanonicalPath();
System.out.println(courseFile);

// 第三种： file:/D:/git/daotie/daotie/target/classes/
URL xmlpath = this.getClass().getClassLoader().getResource("");
System.out.println(xmlpath);

// 第四种： D:\git\daotie\daotie
System.out.println(System.getProperty("user.dir"));
/*
* 结果： C:\Documents and Settings\Administrator\workspace\projectName
* 获取当前工程路径
*/

// 第五种：获取所有的类路径包括jar包的路径
System.out.println(System.getProperty("java.class.path"));

}