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Java+OpenCV实现图片中的人脸识别

作者：TGITCIC

这篇文章主要介绍了如何利用java opencv实现人脸识别功能,本文给大家介绍的非常详细，对大家的学习或工作具有一定的参考借鉴价值，需要的朋友可以参考下

经过前三个教程，我们可以知道了OpenCV的基本使用了。

今天，我们就要讲OpenCV中认出，这是一个人脸是怎么做的。

MatOfRect.detectMultiScale函数

OpenCV用的是detectMultiScale来认出这是一个脸的。记得，这只是认出这是一个脸，而不是这个脸是谁。

这个脸是谁我们会逐步展开，前面勿求夯实基础。

detectMultiScale需要两个参数(Mat src, MatOfRect objDetections);

实现代码

ImageViewer.java

再上一遍

package org.mk.opencv;
 
import org.mk.opencv.util.OpenCVUtil;
import org.opencv.core.Mat;
import javax.swing.*;
import java.awt.*;
 
public class ImageViewer {
    private JLabel imageView;
    private Mat image;
    private String windowName;
 
    private JFrame frame = null;
 
    public ImageViewer() {
        frame = createJFrame(windowName, 800, 600);
    }
 
    public ImageViewer(Mat image) {
        this.image = image;
    }
 
    /**
     * @param image      要显示的mat
     * @param windowName 窗口标题
     */
    public ImageViewer(Mat image, String windowName) {
        frame = createJFrame(windowName, 1024, 768);
        this.image = image;
        this.windowName = windowName;
    }
 
    public void setTitle(String windowName) {
        this.windowName = windowName;
    }
 
    public void setImage(Mat image) {
        this.image = image;
    }
 
    /**
     * 图片显示
     */
    public void imshow() {
        setSystemLookAndFeel();
        frame.pack();
        frame.setLocationRelativeTo(null);
        frame.setVisible(true);
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);// 用户点击窗口关闭
        if (image != null) {
            Image loadedImage = OpenCVUtil.matToImage(image);
            // JFrame frame = createJFrame(windowName, image.width(), image.height());
            imageView.setIcon(new ImageIcon(loadedImage));
            frame.pack();
            // frame.setLocationRelativeTo(null);
            // frame.setVisible(true);
            // frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);// 用户点击窗口关闭
        }
    }
 
    private void setSystemLookAndFeel() {
        try {
            UIManager.setLookAndFeel(UIManager.getSystemLookAndFeelClassName());
        } catch (ClassNotFoundException e) {
            e.printStackTrace();
        } catch (InstantiationException e) {
            e.printStackTrace();
        } catch (IllegalAccessException e) {
            e.printStackTrace();
        } catch (UnsupportedLookAndFeelException e) {
            e.printStackTrace();
        }
    }
 
    private JFrame createJFrame(String windowName, int width, int height) {
        JFrame frame = new JFrame(windowName);
        imageView = new JLabel();
        final JScrollPane imageScrollPane = new JScrollPane(imageView);
        imageScrollPane.setPreferredSize(new Dimension(width, height));
        frame.add(imageScrollPane, BorderLayout.CENTER);
        frame.setDefaultCloseOperation(WindowConstants.EXIT_ON_CLOSE);
        return frame;
    }
 
}

DetectFace.java

这个是主类。

老三样：

1.加载opencv_java343.dll；

2.加载人脸分拣器；

3.创建Mat对象；

然后我们开始把脸识别出来：

1.使用detectMultiScale把传入的Mat对象中含有脸的那些全部识别出来；

2.识别出来后我们可以使用for (Rect rect : objDetections.toArray())把所有的脸枚举出来；

3.使用Imgproc.rectangle在每个识别出来的脸上用“绿”色把它们一个个框出来；

4.使用ImageViewer的.imgShow显示标识出来的脸；

package org.mk.opencv;
 
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
 
public class DetectFace {
    public static void main(String[] args) {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
        //Mat src = Imgcodecs.imread("/Users/chrishu123126.com/opt/img/detect-face-4.jpg");
        Mat src = Imgcodecs.imread("D:\\opencv-demo\\green-arrow.jpg");
        if (src.empty()) {
            System.out.println("图片路径不正确");
            return;
        }
        Mat dst = dobj(src);
        ImageViewer imageViewer = new ImageViewer(dst, "识脸");
        imageViewer.imshow();
    }
 
    private static Mat dobj(Mat src) {
        Mat dst = src.clone();
 
        CascadeClassifier objDetector = new CascadeClassifier(
                "D:\\opencvinstall\\build\\install\\etc\\lbpcascades\\lbpcascade_frontalface.xml");
 
        MatOfRect objDetections = new MatOfRect();
 
        objDetector.detectMultiScale(dst, objDetections);
 
        if (objDetections.toArray().length <= 0) {
            return src;
        }
 
        for (Rect rect : objDetections.toArray()) {
            Imgproc.rectangle(dst, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.width),
                    new Scalar(0, 255, 0), 1); //new Scalar(0, 255, 0), 1)绿 //new Scalar(0, 0, 255), 1)红 //new Scalar(255, 0, 0), 1)蓝
        }
        return dst;
    }
}

把识别出来的脸存成文件

我们现在把识别出来的5张脸存成5个jpg图片。

制作一个写盘函数，很简单。

    private static void outputFace(String outputDir, Mat face) {
        long millSecs = System.currentTimeMillis();
        int temp = (int) (Math.random() * 10000);
        StringBuffer outputImgName = new StringBuffer();
        outputImgName.append(outputDir).append("/").append(millSecs).append(temp).append(".jpg");
        if (face != null) {
            Imgcodecs.imwrite(outputImgName.toString(), face);
            logger.info(">>>>>>write image into->" + outputDir);
        }
    }

然后我们在我们的原来的代码中加入这个函数

package org.mk.opencv;
 
import org.apache.log4j.Logger;
import org.mk.opencv.face.FaceRecogFromFiles;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
 
public class DetectFace {
 
    private static Logger logger = Logger.getLogger(DetectFace.class);
    private final static String faceOutPutDir = "d://opencv-demo/face";
 
    public static void main(String[] args) {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
 
        // Mat src =
        // Imgcodecs.imread("/Users/chrishu123126.com/opt/img/detect-face-4.jpg");
        Mat src = Imgcodecs.imread("D:\\opencv-demo\\green-arrow.jpg");
        if (src.empty()) {
            System.out.println("图片路径不正确");
            return;
        }
        Mat dst = dobj(src);
        ImageViewer imageViewer = new ImageViewer(dst, "识脸");
        imageViewer.imshow();
    }
 
    private static Mat dobj(Mat src) {
        Mat dst = src.clone();
 
        CascadeClassifier objDetector = new CascadeClassifier(
                "D:\\opencvinstall\\build\\install\\etc\\lbpcascades\\lbpcascade_frontalface.xml");
 
        MatOfRect objDetections = new MatOfRect();
 
        objDetector.detectMultiScale(dst, objDetections);
 
        if (objDetections.toArray().length <= 0) {
            return src;
        }
 
        for (Rect rect : objDetections.toArray()) {
            Imgproc.rectangle(dst, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.width),
                    new Scalar(0, 255, 0), 1); // new Scalar(0, 255, 0), 1)绿 //new Scalar(0, 0, 255), 1)红 //new
                                                // Scalar(255, 0, 0), 1)蓝
            outputFace(faceOutPutDir, src.submat(rect));
        }
        return dst;
    }
 
    private static void outputFace(String outputDir, Mat face) {
        long millSecs = System.currentTimeMillis();
        int temp = (int) (Math.random() * 10000);
        StringBuffer outputImgName = new StringBuffer();
        outputImgName.append(outputDir).append("/").append(millSecs).append(temp).append(".jpg");
        if (face != null) {
            Imgcodecs.imwrite(outputImgName.toString(), face);
            logger.info(">>>>>>write image into->" + outputDir);
        }
    }
}

运行DetectFace.java

到此这篇关于Java+OpenCV实现图片中的人脸识别的文章就介绍到这了,更多相关Java OpenCV人脸识别内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家！

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