官方下载opencv安装文件: http://opencv.org/releases.html，以windows版本为例，下载opencv-3.1.0.exe
安装后，在build目录下 D:\opencv\opencv\build\java，获取opencv-310.jar，copy至项目opncv目录（需要新建）
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\opencv\build\java\x64\opencv_java2413.dll （dll库）
xml目录：D:\opencv\opencv\sources\data\haarcascades\haarcascade_frontalface_alt.xml（目录中有各类识别文件）
下面给出图片的各种操作的源码和运行结果，源码中有各个操作的解释，看代码就可以理解，java代码如下
package com.zmx.opencvtest;import org.opencv.core.*;import org.opencv.core.Point;import org.opencv.imgcodecs.Imgcodecs;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;/** * Created by Administrator on 2017/8/17. */public class DetectFaceTest { static{ // 载入opencv的库 String opencvpath = System.getProperty("user.dir") + "\\opencv\\x64\\"; String opencvDllName = opencvpath + Core.NATIVE_LIBRARY_NAME + ".dll"; System.load(opencvDllName); } /** * opencv实现人脸识别 * @param imagePath * @param outFile * @throws Exception */ public static void detectFace(String imagePath, String outFile) throws Exception { System.out.println("Running DetectFace ... "); // 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( "D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml"); Mat image = Imgcodecs.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]; Imgproc.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)); Imgcodecs.imwrite(outFile, image); System.out.println(String.format("人脸识别成功，人脸图片文件为： %s", outFile)); } /** * opencv实现人眼识别 * @param imagePath * @param outFile * @throws Exception */ public static void detectEye(String imagePath, String outFile) throws Exception { CascadeClassifier eyeDetector = new CascadeClassifier( "D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml"); Mat image = Imgcodecs.imread(imagePath); //读取图片 // 在图片中检测人脸 MatOfRect faceDetections = new MatOfRect(); eyeDetector.detectMultiScale(image, faceDetections, 2.0,1,1,new Size(20,20),new Size(20,20)); System.out.println(String.format("Detected %s eyes", faceDetections.toArray().length)); Rect[] rects = faceDetections.toArray(); if(rects != null && rects.length <2){ throw new RuntimeException("不是一双眼睛"); } Rect eyea = rects[0]; Rect 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()) { Imgproc.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0)); } Imgcodecs.imwrite(outFile, image); System.out.println(String.format("人眼识别成功，人眼图片文件为： %s", outFile)); } /** * 裁剪图片并重新装换大小 * @param imagePath * @param posX * @param posY * @param width * @param height * @param outFile */ public static void imageCut(String imagePath,String outFile, int posX,int posY,int width,int height ){ //原始图像 Mat image = Imgcodecs.imread(imagePath); //截取的区域：参数,坐标X,坐标Y,截图宽度,截图长度 Rect rect = new Rect(posX,posY,width,height); //两句效果一样 Mat sub = image.submat(rect); //Mat sub = new Mat(image,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 Imgcodecs.imwrite(outFile, mat); System.out.println(String.format("图片裁切成功，裁切后图片文件为： %s", outFile)); } /** * * @param imagePath * @param outFile */ 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)); System.out.println(String.format("绘制图片半透明成功，图片文件为： %s", outFile)); } catch (Exception e) { e.printStackTrace(); } } /** * 为图像添加水印 * @param buffImgFile 底图 * @param waterImgFile 水印 * @param outFile 输出图片 * @param alpha 透明度 * @throws IOException */ private static void watermark(String buffImgFile,String waterImgFile,String outFile, float alpha) throws IOException { // 获取底图 BufferedImage buffImg = ImageIO.read(new File(buffImgFile)); // 获取层图 BufferedImage waterImg = ImageIO.read(new File(waterImgFile)); // 创建Graphics2D对象，用在底图对象上绘图 Graphics2D g2d = buffImg.createGraphics(); int waterImgWidth = waterImg.getWidth();// 获取水印层图的宽度 int waterImgHeight = waterImg.getHeight();// 获取水印层图的高度 // 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)); System.out.println(String.format("图片添加水印成功，图片文件为： %s", outFile)); } /** * 图片合成 * @param image1 * @param image2 * @param posw * @param posh * @param outFile * @return */ public static void simpleMerge(String image1, String image2, int posw, int posh, String outFile) throws IOException{ // 获取底图 BufferedImage buffImg1 = ImageIO.read(new File(image1)); // 获取层图 BufferedImage buffImg2 = ImageIO.read(new File(image2)); //合并两个图像 int w1 = buffImg1.getWidth(); int h1 = buffImg1.getHeight(); int w2 = buffImg2.getWidth(); int h2 = buffImg2.getHeight(); BufferedImage imageSaved = new BufferedImage(w1, h1, BufferedImage.TYPE_INT_ARGB); //创建一个新的内存图像 Graphics2D g2d = imageSaved.createGraphics(); g2d.drawImage(buffImg1, null, 0, 0); //绘制背景图像 for (int i = 0; i < w2; i++) { for (int j = 0; j < h2; j++) { int rgb1 = buffImg1.getRGB(i + posw, j + posh); int rgb2 = buffImg2.getRGB(i, j); /*if (rgb1 != rgb2) { rgb2 = rgb1 & rgb2; }*/ imageSaved.setRGB(i + posw, j + posh, rgb2); //修改像素值 } } ImageIO.write(imageSaved, "png", new File(outFile)); System.out.println(String.format("图片合成成功，合成图片文件为： %s", outFile)); } public static void main(String[] args) throws Exception { //人脸识别 detectFace("E:\\person.jpg", "E:\\personFaceDetect.png"); //人眼识别 detectEye("E:\\person.jpg", "E:\\personEyeDetect.png"); //图片裁切 imageCut("E:\\person.jpg","E:\\personCut.png", 50, 50,100,100); //设置图片为半透明 setAlpha("E:\\person.jpg", "E:\\personAlpha.png"); //为图片添加水印 watermark("E:\\person.jpg","E:\\ling.jpg","E:\\personWaterMark.png", 0.2f); //图片合成 simpleMerge("E:\\person.jpg", "E:\\ling.jpg", 45, 50, "E:\\personMerge.png"); }}上述运行的结果如下：
（1）原图： E:\person.jpg 水印的图片：E:\ling.jpg
Running DetectFace ...
Detected 1 faces
（2）人脸识别成功，人脸图片文件为： E:\personFaceDetect.png
（3）Detected 4 eyes
a-中心坐标 93 and 102
b-中心坐标 59 and 107
dx is -34.0
dy is 5.0
len is 34.36568055487916
angle is 8.36588612403259
人眼识别成功，人眼图片文件为： E:\personEyeDetect.png
图片裁切成功，裁切后图片文件为： E:\personCut.png
绘制图片半透明成功，图片文件为： E:\personAlpha.png
图片添加水印成功，图片文件为： E:\personWaterMark.png
图片合成成功，合成图片文件为： E:\personMerge.png
总结一下，opencv检测眼睛的还是有一些瑕疵，但是人脸检测效果还可以，我的测试就是如此，大家可以参考实现自己的代码。