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這篇文章主要講解了“怎么用Java+OpenCV實現人臉檢測并自動拍照”,文中的講解內容簡單清晰,易于學習與理解,下面請大家跟著小編的思路慢慢深入,一起來研究和學習“怎么用Java+OpenCV實現人臉檢測并自動拍照”吧!
java+opencv實現人臉檢測,調用筆記本攝像頭實時抓拍,人臉會用紅色邊框標識出來,并且將抓拍的目錄存放在src下,圖片名稱是時間戳。
環境配置: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;/** * 動態人臉檢測并裁剪 * @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();//創建Opencv中的視頻捕捉對象 camera.open(0);//open函數中的0代表當前計算機中索引為0的攝像頭,如果你的計算機有多個攝像頭,那么一次1,2,3…… if (!camera.isOpened()) {//isOpened函數用來判斷攝像頭調用是否成功 System.out.println("Camera Error");//如果攝像頭調用失敗,輸出錯誤信息 } else { Mat frame = new Mat();//創建一個輸出幀 while (flag == 0) { camera.read(frame);//read方法讀取攝像頭的當前幀// 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("檢測到 %s 個人臉! ", 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); } } //轉換圖像格式并輸出 label.setIcon(new ImageIcon(mat2BufferedImage.matToBufferedImage(frame))); try { Thread.sleep(500);//線程暫停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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