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我们。

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