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这篇文章主要讲解了“怎么用Java+OpenCV实现人脸检测并自动拍照”,文中的讲解内容简单清晰,易于学习与理解,下面请大家跟着小编的思路慢慢深入,一起来研究和学习“怎么用Java+OpenCV实现人脸检测并自动拍照”吧!
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); } }
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