Mat, training data in ml opencv - c++

Question

I'm beginner in opencv. I have not gotten main concepts of opencv in details.
So maybe my code it's too dumb;
Out of my curiosity I want to try machine learning functions like a KNN, ANN.
I have the set of images with size 28*28 pixels. I want to do train cassifier for digit recognition. So first I need to assemble train set and train classes;
Mat train_data = Mat(rows, cols, CV_32FC1);
Mat train_classes = Mat(rows, 1, CV_32SC1);
Mat img = imread(image);
Mat float_data(1, cols, CV_32FC1);
img.convertTo(float_data, CV_32FC1);
How to fill train_data with float_data ?
I thought It was smth like this:
for (int i = 0; i < train_data.rows; ++i)
{
... // image is a string which contains next image path
image = imread(image);
img.convertTo(float_data, CV_32FC1);
for( int x = 0; x < train_data.cols; x++ ){
train_data.at<float> (i, x) = float_data.at<float>( x);;
}
}
KNearest knn;
knn.train(train_data, train_classes);
but it's of course doesn't work . . .
Please, tell me how to do it right. Or at least suggest the books for dummies :)

Answer 1

Mat train_data; // initially empty
Mat train_labels; // empty, too.
// for each img in the train set :
Mat img = imread("image_path");
Mat float_data;
img.convertTo(float_data, CV_32FC1); // to float
train_data.push_back( float_data.reshape(1,1) ); // add 1 row (flattened image)
train_labels.push_back( label_for_image ); // add 1 item
KNearest knn;
knn.train(train_data, train_labels);
it's all the same for other ml algos !