PCA + SVM using C ++ syntax in OpenCV 2.2

Question

I'm having problems working with PCA and Eigenfaces using the latest C ++ syntax with Mat and PCA classes. The older C syntax took the IplImage * array as a parameter for processing it, and the current API accepts only Mat, which is formatted by a column or row. I took the Row approach using the reshape function to fit my image matrix so that it matches a single row. Ultimately, I want to use this data and then use the SVM algorithm to perform the discovery, but when I do this, all my data is just a 0s stream. Can someone please help me? What am I doing wrong? Thank!

I saw this question and it is somewhat related, but I'm not sure what the solution is.

This is basically what I have:

vector<Mat> images; //This variable will be loaded with a set of images to perform PCA on.
Mat values(images.size(), 1, CV_32SC1); //Values are the corresponding values to each of my images.

int nEigens = images.size() - 1; //Number of Eigen Vectors.

//Load the images into a Matrix
Mat desc_mat(images.size(), images[0].rows * images[0].cols, CV_32FC1);
for (int i=0; i<images.size(); i++) {
  desc_mat.row(i) = images[i].reshape(1, 1);
}

Mat average;
PCA pca(desc_mat, average, CV_PCA_DATA_AS_ROW, nEigens);

Mat data(desc_mat.rows, nEigens, CV_32FC1); //This Mat will contain all the Eigenfaces that will be used later with SVM for detection

//Project the images onto the PCA subspace
for(int i=0; i<images.size(); i++) {
  Mat projectedMat(1, nEigens, CV_32FC1);
  pca.project(desc_mat.row(i), projectedMat);

  data.row(i) = projectedMat.row(0);
}

CvMat d1 = (CvMat)data;
CvMat d2 = (CvMat)values;

CvSVM svm;
svm.train(&d1, &d2);
svm.save("svmdata.xml");

Answer 1

What etarion said is correct.

To copy a column or row, you should always write:

Mat B = mat.col(i);
A.copyTo(B);

The following program shows how to run PCA in OpenCV. It will display the middle image and the first three Eigenfaces. The images I used there are available from http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html :

#include "cv.h"
#include "highgui.h"

using namespace std;
using namespace cv;

Mat normalize(const Mat& src) {
    Mat srcnorm;
    normalize(src, srcnorm, 0, 255, NORM_MINMAX, CV_8UC1);
    return srcnorm;
}

int main(int argc, char *argv[]) {
    vector<Mat> db;

    // load greyscale images (these are from http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html)
    db.push_back(imread("s1/1.pgm",0));
    db.push_back(imread("s1/2.pgm",0));
    db.push_back(imread("s1/3.pgm",0));

    db.push_back(imread("s2/1.pgm",0));
    db.push_back(imread("s2/2.pgm",0));
    db.push_back(imread("s2/3.pgm",0));

    db.push_back(imread("s3/1.pgm",0));
    db.push_back(imread("s3/2.pgm",0));
    db.push_back(imread("s3/3.pgm",0));

    db.push_back(imread("s4/1.pgm",0));
    db.push_back(imread("s4/2.pgm",0));
    db.push_back(imread("s4/3.pgm",0));

    int total = db[0].rows * db[0].cols;

    // build matrix (column)
    Mat mat(total, db.size(), CV_32FC1);
    for(int i = 0; i < db.size(); i++) {
        Mat X = mat.col(i);
        db[i].reshape(1, total).col(0).convertTo(X, CV_32FC1, 1/255.);
    }

    // Change to the number of principal components you want:
    int numPrincipalComponents = 12;

    // Do the PCA:
    PCA pca(mat, Mat(), CV_PCA_DATA_AS_COL, numPrincipalComponents);

    // Create the Windows:
    namedWindow("avg", 1);
    namedWindow("pc1", 1);
    namedWindow("pc2", 1);
    namedWindow("pc3", 1);

    // Mean face:
    imshow("avg", pca.mean.reshape(1, db[0].rows));

    // First three eigenfaces:
    imshow("pc1", normalize(pca.eigenvectors.row(0)).reshape(1, db[0].rows));
    imshow("pc2", normalize(pca.eigenvectors.row(1)).reshape(1, db[0].rows));
    imshow("pc3", normalize(pca.eigenvectors.row(2)).reshape(1, db[0].rows));

    // Show the windows:
    waitKey(0);
}

and if you want to build a matrix on a row (for example, in the original question above), use this instead:

// build matrix
Mat mat(db.size(), total, CV_32FC1);
for(int i = 0; i < db.size(); i++) {
    Mat X = mat.row(i);
    db[i].reshape(1, 1).row(0).convertTo(X, CV_32FC1, 1/255.);
}

and set the flag in PCA:

CV_PCA_DATA_AS_ROW

. OpenCV ++ API, , Vector Vector Machines. , : http://www.bytefish.de/pdf/machinelearning.pdf.

Answer 2

data.row(i) = projectedMat.row(0);

. operator= , .

cv::Mat sample = data.row(i); // also a shallow copy, points to old data!
projectedMat.row(0).copyTo(sample);

:

desc_mat.row(i) = images[i].reshape(1, 1);

Answer 3

svn head

modules/core/test/test_mat.cpp

: https://code.ros.org/svn/opencv/trunk/opencv/modules/core/test/test_mat.cpp

PCA c ++

, !