一、效果展示

image.png

二、技术实现思路

1、人脸检测与画框

  • 图片转为灰色（降低为一维的灰度，降低计算强度）
  • 图片画上矩阵
  • 使用训练分类器找人脸

2、人脸性别识别

  • 加载性别识别网络模型dnn
  • 遍历图片上检测到的人脸，逐一检测性别
  • 在人脸矩形框上方显示性别

3、显示性别

因为opencv 原生的 Imgproc.putText 方法在图片上显示中文会 乱码，具体做法是，需要将性别文字制作成水印添加到图片上，这个过程中需要先将图片二位矩阵Mat转化成Image，添加完水印后再将Image转回成二位矩阵Mat

三、实现步骤

1、人脸识别

  1.     /**
  2.      * 图片人脸检测
  3.      * @return
  4.      */
  5.     private static MatOfRect facePick(Mat img) {
  6.         // 存放灰度图
  7.         Mat tempImg = new Mat();
  8.         // 摄像头获取的是彩色图像，所以先灰度化下
  9.         Imgproc.cvtColor(img, tempImg, Imgproc.COLOR_BGRA2GRAY);
  10.         // OpenCV人脸识别分类器
  11.         CascadeClassifier classifier = new CascadeClassifier("D:\\workspace\\opencv\\data\\haarcascades\\haarcascade_frontalface_default.xml");
  12.         // # 调用识别人脸
  13.         MatOfRect faceRects = new MatOfRect();
  14.         // 特征检测点的最小尺寸, 根据实际照片尺寸来选择， 不然测量结果可能不准确。
  15.         Size minSize = new Size(140, 140);
  16.         // 图像缩放比例，可理解为相机的X倍镜
  17.         double scaleFactor = 1.2;
  18.         // 对特征检测点周边多少有效点同时检测，这样可避免因选取的特征检测点太小而导致遗漏
  19.         int minNeighbors = 3;
  20.         // 人脸检测
  21.         // CV_HAAR_DO_CANNY_PRUNING
  22.         classifier.detectMultiScale(tempImg, faceRects, scaleFactor, minNeighbors, 0, minSize);
  23.         return faceRects;
  24.     }

2、人脸画框

  1.     /**
  2.      * 在图片上的人脸区域画上矩形框
  3.      * @param rect
  4.      * @param img
  5.      * @param color
  6.      */
  7.     private static void drawRect(Rect rect, Mat img, Scalar color) {
  8.         int x = rect.x;
  9.         int y = rect.y;
  10.         int w = rect.width;
  11.         int h = rect.height;
  12.         Imgproc.rectangle(img, new Point(x, y), new Point(x + h, y + w), color, 2);
  13.     }

3、性别识别

  1.     /**
  2.      * 性别检测
  3.      * @param img
  4.      * @param rect
  5.      * @param genderNet
  6.      * @return
  7.      */
  8.     private static String getGender(Mat img, Rect rect, Net genderNet) {
  9.         Mat face = new Mat(img, rect);
  10.         // Resizing pictures to resolution of Caffe model
  11.         Imgproc.resize(face, face, new Size(140, 140));
  12.         // 颜色空间转换
  13.         Imgproc.cvtColor(face, face, Imgproc.COLOR_RGBA2BGR);
  14.         // blob输入网络进行性别的检测
  15.         Mat inputBlob = Dnn.blobFromImage(face, 1.0f, new Size(227, 227), MODEL_MEAN_VALUES, false, false);
  16.         genderNet.setInput(inputBlob, "data");
  17.         // 性别检测进行前向传播
  18.         Mat probs = genderNet.forward("prob").reshape(1, 1);
  19.         Core.MinMaxLocResult mm = Core.minMaxLoc(probs);
  20.         // Result of gender recognition prediction. 1 = FEMALE, 0 = MALE
  21.         double index = mm.maxLoc.x;
  22.         return  genderList.get((int) index);
  23.     }

4、图片上显示中文

这一步主要是解决opencv中文显示乱码的问题

  1.     /**
  2.      * 在图片上显示中文
  3.      * @param img
  4.      * @param gender
  5.      * @param x
  6.      * @param y
  7.      * @return
  8.      */
  9.     private static Mat putChineseTxt(Mat img, String gender, int x, int y) {
  10.         Font font = new Font("微软雅黑", Font.PLAIN, 20);
  11.         BufferedImage bufImg = matToImg(img,".png");
  12.         Graphics2D g = bufImg.createGraphics();
  13.         g.drawImage(bufImg, 0, 0, bufImg.getWidth(), bufImg.getHeight(), null);
  14.         // 设置字体
  15.         g.setColor(new Color(255, 10, 52));
  16.         g.setFont(font);
  17.         // 设置水印的坐标
  18.         g.drawString(gender, x, y);
  19.         g.dispose();
  20.         // 加完水印再转换回来
  21.         return imgToMat(bufImg, BufferedImage.TYPE_3BYTE_BGR, CvType.CV_8UC3);
  22.     }
  25.     /**
  26.      * Mat二维矩阵转Image
  27.      * @param matrix
  28.      * @param fileExtension
  29.      * @return
  30.      */
  31.     public static BufferedImage matToImg(Mat matrix, String fileExtension) {
  32.         // convert the matrix into a matrix of bytes appropriate for
  33.         // this file extension
  34.         MatOfByte mob = new MatOfByte();
  35.         Imgcodecs.imencode(fileExtension, matrix, mob);
  36.         // convert the "matrix of bytes" into a byte array
  37.         byte[] byteArray = mob.toArray();
  38.         BufferedImage bufImage = null;
  39.         try {
  40.             InputStream in = new ByteArrayInputStream(byteArray);
  41.             bufImage = ImageIO.read(in);
  42.         } catch (Exception e) {
  43.             e.printStackTrace();
  44.         }
  45.         return bufImage;
  46.     }
  49.     /**
  50.      * BufferedImage转换成 Mat
  51.      * @param original
  52.      * @param imgType
  53.      * @param matType
  54.      * @return
  55.      */
  56.     public static Mat imgToMat(BufferedImage original, int imgType, int matType) {
  57.         if (original == null) {
  58.             throw new IllegalArgumentException("original == null");
  59.         }
  60.         if (original.getType() != imgType){
  61.             // Create a buffered image
  62.             BufferedImage image = new BufferedImage(original.getWidth(), original.getHeight(), imgType);
  63.             // Draw the image onto the new buffer
  64.             Graphics2D g = image.createGraphics();
  65.             try {
  66.                 g.setComposite(AlphaComposite.Src);
  67.                 g.drawImage(original, 0, 0, null);
  68.             } finally {
  69.                 g.dispose();
  70.             }
  71.         }
  72.         byte[] pixels = ((DataBufferByte) original.getRaster().getDataBuffer()).getData();
  73.         Mat mat = Mat.eye(original.getHeight(), original.getWidth(), matType);
  74.         mat.put(0, 0, pixels);
  75.         return mat;
  76.     }

四、完成代码

  1. package com.biubiu.example;
  2. import java.awt.*;
  3. import java.awt.image.BufferedImage;
  4. import java.awt.image.DataBufferByte;
  5. import java.io.ByteArrayInputStream;
  6. import java.io.InputStream;
  7. import java.util.ArrayList;
  8. import java.util.Arrays;
  9. import java.util.List;
  11. import javax.imageio.ImageIO;
  13. import org.opencv.core.Core;
  14. import org.opencv.core.CvType;
  15. import org.opencv.core.Mat;
  16. import org.opencv.core.MatOfByte;
  17. import org.opencv.core.MatOfRect;
  18. import org.opencv.core.Point;
  19. import org.opencv.core.Rect;
  20. import org.opencv.core.Scalar;
  21. import org.opencv.core.Size;
  22. import org.opencv.dnn.Dnn;
  23. import org.opencv.dnn.Net;
  24. import org.opencv.highgui.HighGui;
  25. import org.opencv.imgcodecs.Imgcodecs;
  26. import org.opencv.imgproc.Imgproc;
  27. import org.opencv.objdetect.CascadeClassifier;
  28. /**
  29.  * @author ：张音乐
  30.  * @date ：Created in 2021/4/17 上午8:01
  31.  * @description：图片人脸性别识别
  32.  * @email: zhangyule1993@sina.com
  33.  * @version: 1.0
  34.  */
  35. public class ImageGenderDetect {
  37.     static {
  38.         System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
  39.     }
  41.     /**
  42.      * 性别识别模型
  43.      */
  44.     private final static String genderProto = "D:/workspace/opencv/data/models/gender_deploy.prototxt";
  45.     private final static String genderModel = "D:/workspace/opencv/data/models/gender_net.caffemodel";
  47.     /**
  48.      * 性别预测返回的是一个二分类结果 Male, Female
  49.      */
  50.     private final static List<String> genderList = new ArrayList<>(Arrays.asList("男", "女"));
  52.     /**
  53.      * 模型均值
  54.      */
  55.     private final static Scalar MODEL_MEAN_VALUES = new Scalar(78.4263377603, 87.7689143744, 114.895847746);
  57.     public static void main(String[] args) {
  58.         // 加载网络模型
  59.         Net genderNet = Dnn.readNetFromCaffe(genderProto, genderModel);
  60.         if (genderNet.empty()) {
  61.             System.out.println("无法打开网络模型...\n");
  62.             return;
  63.         }
  64.         // 加载图片矩阵
  65.         String filePath = "D:\\upload\\gather.png";
  66.         Mat img = Imgcodecs.imread(filePath);
  67.         // 人脸检测
  68.         MatOfRect faceRects = facePick(img);
  69.         // 定义一个颜色
  70.         Scalar color = new Scalar(0, 0, 255);
  71.         // 遍历检测到的图片
  72.         for(Rect rect : faceRects.toArray()) {
  73.             // 人脸画矩形框
  74.             drawRect(rect, img, color);
  75.             // 检测性别
  76.             String gender = getGender(img, rect, genderNet);
  77.             // 图片上显示中文的性别 ，因为原生的 opencv putText 显示中文会乱码， 所以需要特殊处理一下
  78.             img = putChineseTxt(img, gender, rect.x + rect.width / 2 - 5, rect.y - 10);
  79.             // Imgproc.putText(img, new String(gender.getBytes(StandardCharsets.UTF_8)), new Point(x, y), 2, 2, color);
  80.         }
  81.         // 显示图像
  82.         HighGui.imshow("预览", img);
  83.         HighGui.waitKey(0);
  84.         // 释放所有的窗体资源
  85.         HighGui.destroyAllWindows();
  86.     }
  88.     /**
  89.      * 在图片上的人脸区域画上矩形框
  90.      * @param rect
  91.      * @param img
  92.      * @param color
  93.      */
  94.     private static void drawRect(Rect rect, Mat img, Scalar color) {
  95.         int x = rect.x;
  96.         int y = rect.y;
  97.         int w = rect.width;
  98.         int h = rect.height;
  99.         Imgproc.rectangle(img, new Point(x, y), new Point(x + h, y + w), color, 2);
  100.     }
  102.     /**
  103.      * 性别检测
  104.      * @param img
  105.      * @param rect
  106.      * @param genderNet
  107.      * @return
  108.      */
  109.     private static String getGender(Mat img, Rect rect, Net genderNet) {
  110.         Mat face = new Mat(img, rect);
  111.         // Resizing pictures to resolution of Caffe model
  112.         Imgproc.resize(face, face, new Size(140, 140));
  113.         // 灰度化
  114.         Imgproc.cvtColor(face, face, Imgproc.COLOR_RGBA2BGR);
  115.         // blob输入网络进行性别的检测
  116.         Mat inputBlob = Dnn.blobFromImage(face, 1.0f, new Size(227, 227), MODEL_MEAN_VALUES, false, false);
  117.         genderNet.setInput(inputBlob, "data");
  118.         // 性别检测进行前向传播
  119.         Mat probs = genderNet.forward("prob").reshape(1, 1);
  120.         Core.MinMaxLocResult mm = Core.minMaxLoc(probs);
  121.         // Result of gender recognition prediction. 1 = FEMALE, 0 = MALE
  122.         double index = mm.maxLoc.x;
  123.         return  genderList.get((int) index);
  124.     }
  126.     /**
  127.      * 图片人脸检测
  128.      * @return
  129.      */
  130.     private static MatOfRect facePick(Mat img) {
  131.         // 存放灰度图
  132.         Mat tempImg = new Mat();
  133.         // 摄像头获取的是彩色图像，所以先灰度化下
  134.         Imgproc.cvtColor(img, tempImg, Imgproc.COLOR_BGRA2GRAY);
  135.         // OpenCV人脸识别分类器
  136.         CascadeClassifier classifier = new CascadeClassifier("D:\\workspace\\opencv\\data\\haarcascades\\haarcascade_frontalface_default.xml");
  137.         // # 调用识别人脸
  138.         MatOfRect faceRects = new MatOfRect();
  139.         // 特征检测点的最小尺寸, 根据实际照片尺寸来选择， 不然测量结果可能不准确。
  140.         Size minSize = new Size(140, 140);
  141.         // 图像缩放比例，可理解为相机的X倍镜
  142.         double scaleFactor = 1.2;
  143.         // 对特征检测点周边多少有效点同时检测，这样可避免因选取的特征检测点太小而导致遗漏
  144.         int minNeighbors = 3;
  145.         // 人脸检测
  146.         // CV_HAAR_DO_CANNY_PRUNING
  147.         classifier.detectMultiScale(tempImg, faceRects, scaleFactor, minNeighbors, 0, minSize);
  148.         return faceRects;
  149.     }
  151.     /**
  152.      * Mat二维矩阵转Image
  153.      * @param matrix
  154.      * @param fileExtension
  155.      * @return
  156.      */
  157.     public static BufferedImage matToImg(Mat matrix, String fileExtension) {
  158.         // convert the matrix into a matrix of bytes appropriate for
  159.         // this file extension
  160.         MatOfByte mob = new MatOfByte();
  161.         Imgcodecs.imencode(fileExtension, matrix, mob);
  162.         // convert the "matrix of bytes" into a byte array
  163.         byte[] byteArray = mob.toArray();
  164.         BufferedImage bufImage = null;
  165.         try {
  166.             InputStream in = new ByteArrayInputStream(byteArray);
  167.             bufImage = ImageIO.read(in);
  168.         } catch (Exception e) {
  169.             e.printStackTrace();
  170.         }
  171.         return bufImage;
  172.     }
  174.     /**
  175.      * BufferedImage转换成 Mat
  176.      * @param original
  177.      * @param imgType
  178.      * @param matType
  179.      * @return
  180.      */
  181.     public static Mat imgToMat(BufferedImage original, int imgType, int matType) {
  182.         if (original == null) {
  183.             throw new IllegalArgumentException("original == null");
  184.         }
  185.         if (original.getType() != imgType){
  186.             // Create a buffered image
  187.             BufferedImage image = new BufferedImage(original.getWidth(), original.getHeight(), imgType);
  188.             // Draw the image onto the new buffer
  189.             Graphics2D g = image.createGraphics();
  190.             try {
  191.                 g.setComposite(AlphaComposite.Src);
  192.                 g.drawImage(original, 0, 0, null);
  193.             } finally {
  194.                 g.dispose();
  195.             }
  196.         }
  197.         byte[] pixels = ((DataBufferByte) original.getRaster().getDataBuffer()).getData();
  198.         Mat mat = Mat.eye(original.getHeight(), original.getWidth(), matType);
  199.         mat.put(0, 0, pixels);
  200.         return mat;
  201.     }
  203.     /**
  204.      * 在图片上显示中文
  205.      * @param img
  206.      * @param gender
  207.      * @param x
  208.      * @param y
  209.      * @return
  210.      */
  211.     private static Mat putChineseTxt(Mat img, String gender, int x, int y) {
  212.         Font font = new Font("微软雅黑", Font.PLAIN, 20);
  213.         BufferedImage bufImg = matToImg(img,".png");
  214.         Graphics2D g = bufImg.createGraphics();
  215.         g.drawImage(bufImg, 0, 0, bufImg.getWidth(), bufImg.getHeight(), null);
  216.         // 设置字体
  217.         g.setColor(new Color(255, 10, 52));
  218.         g.setFont(font);
  219.         // 设置水印的坐标
  220.         g.drawString(gender, x, y);
  221.         g.dispose();
  222.         // 加完水印再转换回来
  223.         return imgToMat(bufImg, BufferedImage.TYPE_3BYTE_BGR, CvType.CV_8UC3);
  224.     }
  225. }