在Android中使用opencv將檢測到的面部與現有面部數組進行比較

Question

我正在通過opencv制作人臉識別應用程序。 我可以檢測到面孔，並且資源中幾乎沒有面孔。 我在這個地方堆放：

// These vectors hold the images and corresponding labels.
vector<Mat> images;
vector<int> labels;

Mat testSample = images[images.size() - 1];
    int testLabel = labels[labels.size() - 1];
    images.pop_back();
    labels.pop_back();


    Ptr<FaceRecognizer> model = createEigenFaceRecognizer();
    model->train(images, labels);

    string result_message = format("Predicted class = %d / Actual class = %d.", predictedLabel, testLabel);
    cout << result_message << endl;
    // Here is how to get the eigenvalues of this Eigenfaces model:
    Mat eigenvalues = model->getMat("eigenvalues");
    // And we can do the same to display the Eigenvectors (read Eigenfaces):
    Mat W = model->getMat("eigenvectors");
    // Get the sample mean from the training data
    Mat mean = model->getMat("mean");

有人可以向我解釋一下，我應該將檢測到的人臉准確放在哪里，並將其與數據庫進行比較？ 我必須將它們全部放在vector<Mat> images; 要不然是啥？ 字段vector<int> labels;也如何工作vector<int> labels; ？ 我應該在那寫些什么？ 如果有人可以給我寫一個簡單的例子，那就太好了。 我將檢測到的人臉作為參數從Java類傳遞過來。

謝謝！

Answer 1

您需要導入javacv庫（com.googlecode.javacv.cpp.opencv_contrib.FaceRecognizer）隨附的類FaceRecognizer：

以下是類代碼，它包含訓練和測試面部所需的所有功能

package org.opencv.javacv.facerecognition;

import static  com.googlecode.javacv.cpp.opencv_highgui.*;
import static  com.googlecode.javacv.cpp.opencv_core.*;
import static  com.googlecode.javacv.cpp.opencv_imgproc.*;
import static com.googlecode.javacv.cpp.opencv_contrib.*;
import java.io.File;
import java.io.FileOutputStream;
import java.io.FilenameFilter;
import java.util.ArrayList;
import org.opencv.android.Utils;
import org.opencv.core.Mat;
import com.googlecode.javacv.cpp.opencv_imgproc;
import com.googlecode.javacv.cpp.opencv_contrib.FaceRecognizer;
import com.googlecode.javacv.cpp.opencv_core.IplImage;
import com.googlecode.javacv.cpp.opencv_core.MatVector;
import android.graphics.Bitmap;
import android.os.Environment;
import android.util.Log;
import android.widget.Toast;

public  class PersonRecognizer {

public final static int MAXIMG = 100;
FaceRecognizer faceRecognizer;
String mPath;
int count=0;
labels labelsFile;

 static  final int WIDTH= 128;
 static  final int HEIGHT= 128;;
 private int mProb=999;


PersonRecognizer(String path)
{
  faceRecognizer =  com.googlecode.javacv.cpp.opencv_contrib.createLBPHFaceRecognizer(2,8,8,8,200);
 // path=Environment.getExternalStorageDirectory()+"/facerecog/faces/";
 mPath=path;
 labelsFile= new labels(mPath);


}

void changeRecognizer(int nRec)
{
    switch(nRec) {
    case 0: faceRecognizer = com.googlecode.javacv.cpp.opencv_contrib.createLBPHFaceRecognizer(1,8,8,8,100);
            break;
    case 1: faceRecognizer = com.googlecode.javacv.cpp.opencv_contrib.createFisherFaceRecognizer();
            break;
    case 2: faceRecognizer = com.googlecode.javacv.cpp.opencv_contrib.createEigenFaceRecognizer();
            break;
    }
    train();

}

void add(Mat m, String description) {
    Bitmap bmp= Bitmap.createBitmap(m.width(), m.height(), Bitmap.Config.ARGB_8888);

    Utils.matToBitmap(m,bmp);
    bmp= Bitmap.createScaledBitmap(bmp, WIDTH, HEIGHT, false);

    FileOutputStream f;
    try {
        f = new FileOutputStream(mPath+description+"-"+count+".jpg",true);
        count++;
        bmp.compress(Bitmap.CompressFormat.JPEG, 100, f);
        f.close();

    } catch (Exception e) {
        Log.e("error",e.getCause()+" "+e.getMessage());
        e.printStackTrace();

    }
}

public boolean train() {

    File root = new File(mPath);
    Log.i("mPath",mPath);
    FilenameFilter pngFilter = new FilenameFilter() {
        public boolean accept(File dir, String name) {
            return name.toLowerCase().endsWith(".jpg");

    };
    };

    File[] imageFiles = root.listFiles(pngFilter);

    MatVector images = new MatVector(imageFiles.length);

    int[] labels = new int[imageFiles.length];

    int counter = 0;
    int label;

    IplImage img=null;
    IplImage grayImg;

    int i1=mPath.length();


    for (File image : imageFiles) {
        String p = image.getAbsolutePath();
        img = cvLoadImage(p);

        if (img==null)
            Log.e("Error","Error cVLoadImage");
        Log.i("image",p);

        int i2=p.lastIndexOf("-");
        int i3=p.lastIndexOf(".");
        int icount=Integer.parseInt(p.substring(i2+1,i3)); 
        if (count<icount) count++;

        String description=p.substring(i1,i2);

        if (labelsFile.get(description)<0)
            labelsFile.add(description, labelsFile.max()+1);

        label = labelsFile.get(description);

        grayImg = IplImage.create(img.width(), img.height(), IPL_DEPTH_8U, 1);

        cvCvtColor(img, grayImg, CV_BGR2GRAY);

        images.put(counter, grayImg);

        labels[counter] = label;

        counter++;
    }
    if (counter>0)
        if (labelsFile.max()>1)
            faceRecognizer.train(images, labels);
    labelsFile.Save();
return true;
}

public boolean canPredict()
{
    if (labelsFile.max()>1)
        return true;
    else
        return false;

}

public String predict(Mat m) {
    if (!canPredict())
        return "";
    int n[] = new int[1];
    double p[] = new double[1];
    IplImage ipl = MatToIplImage(m,WIDTH, HEIGHT);

    faceRecognizer.predict(ipl, n, p);

    if (n[0]!=-1)
     mProb=(int)p[0];
    else
        mProb=-1;
    if (n[0] != -1)
        return labelsFile.get(n[0]);
    else
        return "Unkown";
}

  IplImage MatToIplImage(Mat m,int width,int heigth)
  {


       Bitmap bmp=Bitmap.createBitmap(m.width(), m.height(), Bitmap.Config.ARGB_8888);


       Utils.matToBitmap(m, bmp);
       return BitmapToIplImage(bmp,width, heigth);

  }

IplImage BitmapToIplImage(Bitmap bmp, int width, int height) {

    if ((width != -1) || (height != -1)) {
        Bitmap bmp2 = Bitmap.createScaledBitmap(bmp, width, height, false);
        bmp = bmp2;
    }

    IplImage image = IplImage.create(bmp.getWidth(), bmp.getHeight(),
            IPL_DEPTH_8U, 4);

    bmp.copyPixelsToBuffer(image.getByteBuffer());

    IplImage grayImg = IplImage.create(image.width(), image.height(),
            IPL_DEPTH_8U, 1);

    cvCvtColor(image, grayImg, opencv_imgproc.CV_BGR2GRAY);

    return grayImg;
}



protected void SaveBmp(Bitmap bmp,String path)
  {
        FileOutputStream file;
        try {
            file = new FileOutputStream(path , true);

        bmp.compress(Bitmap.CompressFormat.JPEG,100,file);  
        file.close();
        }
        catch (Exception e) {
            // TODO Auto-generated catch block
            Log.e("",e.getMessage()+e.getCause());
            e.printStackTrace();
        }

  }


public void load() {
    train();

}

 public int getProb() {
    // TODO Auto-generated method stub
    return mProb;
 }

}