OPENCV+JAVA实现人脸识别

本文实例为大家分享了JAVA实现人脸识别的具体代码，供大家参考，具体内容如下

官方下载 安装文件 ，以win7为例，下载opencv-2.4.13.3-vc14.exe
安装后，在build目录下 D:\opencv\build\java，获取opencv-2413.jar，copy至项目目录
同时需要dll文件 与 各 识别xml文件，进行不同特征的识别（人脸，侧脸，眼睛等）
dll目录：D:\opencv\build\java\x64\opencv_java2413.dll
xml目录：D:\opencv\sources\data\haarcascades\haarcascade_frontalface_alt.xml（目录中有各类识别文件）

项目结构：

具体代码：由于需要用到 opencv 的dll文件，故要么放在java library path 中，或放在jre lib 中，windows下可放在System32目录下，也可以在代码中动态加载，如下：

package opencv; 
 
import com.sun.scenario.effect.ImageData; 
import org.opencv.core.*; 
import org.opencv.core.Point; 
import org.opencv.highgui.Highgui; 
import org.opencv.imgproc.Imgproc; 
import org.opencv.objdetect.CascadeClassifier; 
 
import javax.imageio.ImageIO; 
import javax.swing.*; 
import java.awt.*; 
import java.awt.image.BufferedImage; 
import java.io.File; 
import java.io.IOException; 
import java.util.Arrays; 
import java.util.Vector; 
 
/** 
 * Created by Administrator on 2017/8/17. 
 */ 
public class Test { 
 
 static{ 
 // 导入opencv的库 
 String opencvpath = System.getProperty("user.dir") + "\\opencv\\x64\\"; 
 String libPath = System.getProperty("java.library.path"); 
 String a = opencvpath + Core.NATIVE_LIBRARY_NAME + ".dll"; 
 System.load(opencvpath + Core.NATIVE_LIBRARY_NAME + ".dll"); 
 } 
 
 public static String getCutPath(String filePath){ 
 String[] splitPath = filePath.split("\\."); 
 return splitPath[0]+"Cut"+"."+splitPath[1]; 
 } 
 
 public static void process(String original,String target) throws Exception { 
 String originalCut = getCutPath(original); 
 String targetCut = getCutPath(target); 
 if(detectFace(original,originalCut) && detectFace(target,targetCut)){ 
 
 } 
 } 
 
 public static boolean detectFace(String imagePath,String outFile) throws Exception 
 { 
 
 System.out.println("\nRunning DetectFaceDemo"); 
 // 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( 
  "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_frontalface_alt.xml"); 
 Mat image = Highgui.imread(imagePath); 
 
 // 在图片中检测人脸 
 MatOfRect faceDetections = new MatOfRect(); 
 faceDetector.detectMultiScale(image, faceDetections); 
 
 System.out.println(String.format("Detected %s faces", 
  faceDetections.toArray().length)); 
 
 Rect[] rects = faceDetections.toArray(); 
 if(rects != null && rects.length > 1){ 
  throw new RuntimeException("超过一个脸"); 
 } 
 // 在每一个识别出来的人脸周围画出一个方框 
 Rect rect = rects[0]; 
 Core.rectangle(image, new Point(rect.x-2, rect.y-2), new Point(rect.x 
  + rect.width, rect.y + rect.height), new Scalar(0, 255, 0)); 
 Mat sub = image.submat(rect); 
 Mat mat = new Mat(); 
 Size size = new Size(300, 300); 
 Imgproc.resize(sub, mat, size);//将人脸进行截图并保存 
 return Highgui.imwrite(outFile, mat); 
 
 
 // 将结果保存到文件 
// String filename = "C:\\Users\\Administrator\\Desktop\\opencv\\faceDetection.png"; 
// System.out.println(String.format("Writing %s", filename)); 
// Highgui.imwrite(filename, image); 
 } 
 
 public static void setAlpha(String imagePath,String outFile) { 
 /** 
  * 增加测试项 
  * 读取图片，绘制成半透明 
  */ 
 try { 
 
  ImageIcon imageIcon = new ImageIcon(imagePath); 
  BufferedImage bufferedImage = new BufferedImage(imageIcon.getIconWidth(),imageIcon.getIconHeight() 
   , BufferedImage.TYPE_4BYTE_ABGR); 
  Graphics2D g2D = (Graphics2D) bufferedImage.getGraphics(); 
  g2D.drawImage(imageIcon.getImage(), 0, 0, 
   imageIcon.getImageObserver()); 
  //循环每一个像素点，改变像素点的Alpha值 
  int alpha = 100; 
  for (int j1 = bufferedImage.getMinY(); j1 < bufferedImage.getHeight(); j1++) { 
  for (int j2 = bufferedImage.getMinX(); j2 < bufferedImage.getWidth(); j2++) { 
   int rgb = bufferedImage.getRGB(j2, j1); 
   rgb = ( (alpha + 1) << 24) | (rgb & 0x00ffffff); 
   bufferedImage.setRGB(j2, j1, rgb); 
  } 
  } 
  g2D.drawImage(bufferedImage, 0, 0, imageIcon.getImageObserver()); 
 
  //生成图片为PNG 
 
  ImageIO.write(bufferedImage, "png", new File(outFile)); 
 } 
 catch (Exception e) { 
  e.printStackTrace(); 
 } 
 
 } 
 
 private static void watermark(String a,String b,String outFile, float alpha) throws IOException { 
 // 获取底图 
   BufferedImage buffImg = ImageIO.read(new File(a)); 
   // 获取层图 
   BufferedImage waterImg = ImageIO.read(new File(b)); 
   // 创建Graphics2D对象，用在底图对象上绘图 
   Graphics2D g2d = buffImg.createGraphics(); 
   int waterImgWidth = waterImg.getWidth();// 获取层图的宽度 
   int waterImgHeight = waterImg.getHeight();// 获取层图的高度 
   // 在图形和图像中实现混合和透明效果 
   g2d.setComposite(AlphaComposite.getInstance(AlphaComposite.SRC_ATOP, alpha)); 
   // 绘制 
   g2d.drawImage(waterImg, 0, 0, waterImgWidth, waterImgHeight, null); 
   g2d.dispose();// 释放图形上下文使用的系统资源 
 //生成图片为PNG 
 
 ImageIO.write(buffImg, "png", new File(outFile)); 
 } 
 
 public static boolean mergeSimple(BufferedImage image1, BufferedImage image2, int posw, int posh, File fileOutput) { 
 
 //合并两个图像 
 int w1 = image1.getWidth(); 
 int h1 = image1.getHeight(); 
 int w2 = image2.getWidth(); 
 int h2 = image2.getHeight(); 
 
 BufferedImage imageSaved = new BufferedImage(w1, h1, BufferedImage.TYPE_INT_ARGB); 
 Graphics2D g2d = imageSaved.createGraphics(); 
 
 
 // 增加下面代码使得背景透明 
 
 g2d.drawImage(image1, null, 0, 0); 
 image1 = g2d.getDeviceConfiguration().createCompatibleImage(w1, w2, Transparency.TRANSLUCENT); 
 g2d.dispose(); 
 g2d = image1.createGraphics(); 
 // 背景透明代码结束 
 
// for (int i = 0; i < w2; i++) { 
//  for (int j = 0; j < h2; j++) { 
//  int rgb1 = image1.getRGB(i + posw, j + posh); 
//  int rgb2 = image2.getRGB(i, j); 
// 
//  if (rgb1 != rgb2) { 
//   //rgb2 = rgb1 & rgb2; 
//  } 
//  imageSaved.setRGB(i + posw, j + posh, rgb2); 
//  } 
// } 
 
 boolean b = false; 
 try { 
  b = ImageIO.write(imageSaved, "png", fileOutput); 
 } catch (IOException ie) { 
  ie.printStackTrace(); 
 } 
 return b; 
 } 
 
 public static void main(String[] args) throws Exception { 
 String a,b,c,d; 
 a = "C:\\Users\\Administrator\\Desktop\\opencv\\zzl.jpg"; 
 d = "C:\\Users\\Administrator\\Desktop\\opencv\\cgx.jpg"; 
 //process(a,d); 
 a = "C:\\Users\\Administrator\\Desktop\\opencv\\zzlCut.jpg"; 
 d = "C:\\Users\\Administrator\\Desktop\\opencv\\cgxCut.jpg"; 
 
 CascadeClassifier faceDetector = new CascadeClassifier( 
  "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_frontalface_alt.xml"); 
 
 CascadeClassifier eyeDetector1 = new CascadeClassifier( 
  "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_eye.xml"); 
 
 CascadeClassifier eyeDetector2 = new CascadeClassifier( 
  "C:\\Users\\Administrator\\Desktop\\opencv\\haarcascade_eye_tree_eyeglasses.xml"); 
 
 Mat image = Highgui.imread("C:\\Users\\Administrator\\Desktop\\opencv\\gakki.jpg"); 
 // 在图片中检测人脸 
 MatOfRect faceDetections = new MatOfRect(); 
 //eyeDetector2.detectMultiScale(image, faceDetections); 
 Vector<Rect> objects; 
 eyeDetector1.detectMultiScale(image, faceDetections, 2.0,1,1,new Size(20,20),new Size(20,20)); 
 
 Rect[] rects = faceDetections.toArray(); 
 Rect eyea,eyeb; 
 eyea = rects[0];eyeb = rects[1]; 
 
 
  System.out.println("a-中心坐标 " + eyea.x + " and " + eyea.y); 
 System.out.println("b-中心坐标 " + eyeb.x + " and " + eyeb.y); 
 
 //获取两个人眼的角度 
 double dy=(eyeb.y-eyea.y); 
 double dx=(eyeb.x-eyea.x); 
 double len=Math.sqrt(dx*dx+dy*dy); 
 System.out.println("dx is "+dx); 
 System.out.println("dy is "+dy); 
 System.out.println("len is "+len); 
 
 double angle=Math.atan2(Math.abs(dy),Math.abs(dx))*180.0/Math.PI; 
 System.out.println("angle is "+angle); 
 
 for(Rect rect:faceDetections.toArray()) { 
  Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x 
   + rect.width, rect.y + rect.height), new Scalar(0, 255, 0)); 
 } 
 String filename = "C:\\Users\\Administrator\\Desktop\\opencv\\ouput.png"; 
 System.out.println(String.format("Writing %s", filename)); 
 Highgui.imwrite(filename, image); 
 
// watermark(a,d,"C:\\Users\\Administrator\\Desktop\\opencv\\zzlTm2.jpg",0.7f); 
// 
// // 读取图像，不改变图像的原始信息 
// Mat image1 = Highgui.imread(a); 
// Mat image2 = Highgui.imread(d); 
// Mat mat1 = new Mat();Mat mat2 = new Mat(); 
// Size size = new Size(300, 300); 
// Imgproc.resize(image1, mat1, size); 
// Imgproc.resize(image2, mat2, size); 
// Mat mat3 = new Mat(size,CvType.CV_64F); 
// //Core.addWeighted(mat1, 0.5, mat2, 1, 0, mat3); 
// 
// //Highgui.imwrite("C:\\Users\\Administrator\\Desktop\\opencv\\add.jpg", mat3); 
// 
// mergeSimple(ImageIO.read(new File(a)), 
//  ImageIO.read(new File(d)),0,0, 
//  new File("C:\\Users\\Administrator\\Desktop\\opencv\\add.jpg")); 
 } 
} 

最终效果：人脸旁有绿色边框，可以将绿色边框图片截取，生成人脸图

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呐喊教程。

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