java中的CascadeClassifier无法通过网络摄像头找到人脸

Question

我正在尝试将OpenCV Cascade分类器教程从C翻译成Java。在C中运行良好。这个java教程也运行良好。

但翻译根本就没有检测到人脸。我没有明显的错误。我可以看到网络摄像头对视频输入的处理（灰色/直方图…）和视频显示器。级联加载不会给出错误。但是CascadeClassifier调用不会返回任何面孔。。。因此，您可能可以跳过所有代码，直接转到我的级联分类器调用，直至公共Mat检测（Mat inputframe）。由于我不熟悉Java和OpenCV，所以我会粘贴其余部分（我删除了我认为可能不重要的内容），以防万一，但这并不意味着你要调试它。。。

我也用许多不同的方式尝试过这个电话（和其他部分），但一无所获...

非常感谢。

import java.awt.*;
import java.awt.image.BufferedImage;
import javax.swing.*;

import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.highgui.VideoCapture;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;

class My_Panel extends JPanel{

    private static final long serialVersionUID = 1L;
    private BufferedImage image;
    private CascadeClassifier face_cascade;

    // Create a constructor method
    public My_Panel(){
        super(); 
        String face_cascade_name = "/haarcascade_frontalface_alt.xml";
        //String face_cascade_name = "/lbpcascade_frontalface.xml";
        //-- 1. Load the cascades

        String str;
        str = getClass().getResource(face_cascade_name).getPath();
        str = str.replace("/C:","C:");
        face_cascade_name=str;

        face_cascade=new CascadeClassifier(face_cascade_name);
        if( !face_cascade.empty())
        {
            System.out.println("--(!)Error loading A\n");
            return;
        }
        else
        {
                System.out.println("Face classifier loooaaaaaded up");
        }
    }

    private BufferedImage getimage(){
        return image;
    }

    public void setimage(BufferedImage newimage){
        image=newimage;
        return;
    }

    /**
     * Converts/writes a Mat into a BufferedImage.
     * 
     * @param matrix Mat of type CV_8UC3 or CV_8UC1
     * @return BufferedImage of type TYPE_3BYTE_BGR or TYPE_BYTE_GRAY
     */
    public BufferedImage matToBufferedImage(Mat matrix) {
        int cols = matrix.cols();
        int rows = matrix.rows();
        int elemSize = (int)matrix.elemSize();
        byte[] data = new byte[cols * rows * elemSize];
        int type;

        matrix.get(0, 0, data);

        switch (matrix.channels()) {
            case 1:
                type = BufferedImage.TYPE_BYTE_GRAY;
                break;

            case 3: 
                type = BufferedImage.TYPE_3BYTE_BGR;

                // bgr to rgb
                byte b;
                for(int i=0; i<data.length; i=i+3) {
                    b = data[i];
                    data[i] = data[i+2];
                    data[i+2] = b;
                }
                break;

            default:
                return null;
        }

        BufferedImage image2 = new BufferedImage(cols, rows, type);
        image2.getRaster().setDataElements(0, 0, cols, rows, data);

        return image2;
    }

    public void paintComponent(Graphics g){
         BufferedImage temp=getimage();
         g.drawImage(temp,10,10,temp.getWidth(),temp.getHeight(), this); 
    }

    public Mat detect(Mat inputframe){
        Mat mRgba=new Mat();
        Mat mGrey=new Mat();
        MatOfRect faces = new MatOfRect();
        //MatOfRect eyes = new MatOfRect();

        inputframe.copyTo(mRgba);
        inputframe.copyTo(mGrey);
        Imgproc.cvtColor( mRgba, mGrey, Imgproc.COLOR_BGR2GRAY);
        Imgproc.equalizeHist( mGrey, mGrey );

        face_cascade.detectMultiScale(mGrey, faces);
        //face_cascade.detectMultiScale(mGrey, faces, 1.1, 2, 0|Objdetect.CASCADE_SCALE_IMAGE, new Size(30, 30), new Size(200,200) );
        //face_cascade.detectMultiScale(mGrey, faces, 1.1, 2, 2//CV_HAAR_SCALE_IMAGE,
        //      ,new Size(30, 30), new Size(200,200) );

        System.out.println(String.format("Detected %s faces", faces.toArray().length));

        return mGrey;
        }
}

public class window {
    public static void main(String arg[]){
     // Load the native library.
     System.loadLibrary("opencv_java245");  

     String window_name = "Capture - Face detection";

     JFrame frame = new JFrame(window_name);
     frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
     frame.setSize(400,400);

     My_Panel my_panel = new My_Panel();
     frame.setContentPane(my_panel);          
     frame.setVisible(true);           

     //-- 2. Read the video stream
     BufferedImage temp;
     Mat webcam_image=new Mat();

     VideoCapture capture =new VideoCapture(0); 
     if( capture.isOpened())
        {
          while( true )
          {
              capture.read(webcam_image);
              if( !webcam_image.empty() )
               { 
                   frame.setSize(webcam_image.width()+40,webcam_image.height()+60);

                   //-- 3. Apply the classifier to the captured image
                   // At this point I was wondering where this should be done.
                   // I put it within the panel class, but maybe one could actually
                   // create a processor object...
                   webcam_image=my_panel.detect(webcam_image);

                 //-- 4. Display the image
                   temp=my_panel.matToBufferedImage(webcam_image);
                   my_panel.setimage(temp);
                   my_panel.repaint(); 
               }
               else
               { 
                   System.out.println(" --(!) No captured frame -- Break!"); 
                   break; 
               }
              }
           }
           return;
    }
}

PS.：其他信息，以防万一：

1. mGrey是：Mat[480*640*CV_8UC1， isCont=true， isSubmat=false， nativeObj=0x19d9af48， dataAddr=0x19dc3430]
2. face is： Mat[0*0*CV_8UC1， isCont=false， isSubmat=false， nativeObj=0x194bb048， dataAddr=0x0]

Answer 1

我已经尝试了你的代码，它工作得很好！haarcascade\u frontalface\u alt.xml文件位置只有一个问题。尝试使用文件的完整路径：face\u cascade=new CascadeClassifier（“D:/HelloCV/src/haarcascade\u frontalface\u alt.xml”）；