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Java+OpenCV实现人脸检测并自动拍照

作者:大数据菜鸟001

这篇文章主要为大家详细介绍了Java+OpenCV实现人脸检测,并调用笔记本摄像头实时抓拍,具有一定的参考价值,感兴趣的小伙伴们可以参考一下

java+opencv实现人脸检测,调用笔记本摄像头实时抓拍,人脸会用红色边框标识出来,并且将抓拍的目录存放在src下,图片名称是时间戳。

环境配置:win7 64位,jdk1.8

CameraBasic.java

package com.njupt.zhb.test;

import java.awt.EventQueue;

import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;

import org.opencv.core.*;
import org.opencv.highgui.Highgui;
import org.opencv.highgui.VideoCapture;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
/**
 * 动态人脸检测并裁剪
 * @author hyj
 *
 */
public class CameraBasic {
 static {
  System.out.println(System.getProperty("java.library.path")); 
  System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
 }
 private JFrame frame;
 private static JLabel label;
 private static int flag = 0;

 public static void main(String[] args) {
  EventQueue.invokeLater(new Runnable() {
   @Override
   public void run() {
    try {
     CameraBasic window = new CameraBasic();
     window.frame.setVisible(true);
    } catch (Exception e) {
     e.printStackTrace();
    }
   }
  });

  VideoCapture camera = new VideoCapture();//创建Opencv中的视频捕捉对象
  camera.open(0);//open函数中的0代表当前计算机中索引为0的摄像头,如果你的计算机有多个摄像头,那么一次1,2,3……
  if (!camera.isOpened()) {//isOpened函数用来判断摄像头调用是否成功
   System.out.println("Camera Error");//如果摄像头调用失败,输出错误信息
  } else {
   Mat frame = new Mat();//创建一个输出帧
   while (flag == 0) {
    camera.read(frame);//read方法读取摄像头的当前帧
//    CascadeClassifier faceDetector = new CascadeClassifier("src/com/njupt/zhb/test/lbpcascade_frontalface.xml");
    CascadeClassifier faceDetector = new CascadeClassifier("src/com/njupt/zhb/test/haarcascade_frontalface_alt.xml");
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(frame, faceDetections);
    Rect [] rectArray = faceDetections.toArray();
    if (rectArray.length > 0) {
     
     for (int i=0;i<rectArray.length;i++) {
      Rect rect = rectArray[i];
      Rect rectCrop = new Rect(rect.x, rect.y, rect.width, rect.height);
      if (rect.width + rect.height > rectCrop.height + rectCrop.width) {
       rectCrop = new Rect(rect.x, rect.y, rect.width, rect.height);
      }
       System.out.println(String.format("检测到 %s 个人脸! ", rectArray.length));
       Mat imageRoi = new Mat(frame, rectCrop);
       String name = System.currentTimeMillis()+".png";
       Highgui.imwrite(name, imageRoi);
       
      
      Core.rectangle(frame, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 0, 255), 2);
     }
    }
    

    //转换图像格式并输出
    label.setIcon(new ImageIcon(mat2BufferedImage.matToBufferedImage(frame)));

    try {
     Thread.sleep(500);//线程暂停500ms
    } catch (InterruptedException e) {
     // TODO Auto-generated catch block
     e.printStackTrace();
    }

    
    
    
//    if (faceCount > 0) {
//     faceSerialCount++;
//     System.out.println(faceSerialCount);
//    } else {
//     faceSerialCount = 0;
//    }
//
//    if (faceSerialCount > 6) {
//     Mat imageRoi = new Mat(frame, rectCrop);
//     Highgui.imwrite("haha.png", imageRoi);
//     faceSerialCount = 0;
//    }
   }
  }
 }

 private CameraBasic() {
  initialize();
 }

 private void initialize() {
  frame = new JFrame();
  frame.setBounds(100, 100, 1000, 600);
  frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
  frame.getContentPane().setLayout(null);
  label = new JLabel("");
  label.setBounds(0, 0, 1000, 500);
  frame.getContentPane().add(label);
 }
 
 
}

完整源码下载地址:Java+OpenCV实现人脸检测并拍照

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持脚本之家。

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