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It' difficult to help without any hint, but probably you'll have to convert the image data to your training data format. Something like:

vector<vector<uchar>> training_data;
vector<int> training_labels;
vector<Mat> images;
for(int i=0;i<images.size();i++){
    vector<uchar> data;
    for(int y=0;y<images[i].rows;y++){
        uchar *p=images[i].ptr(y);
        for(int x=0;x<images[i].cols;x++){
            data.push_back(p[i]);
        }
    }
    training_data.push_back(data);
}
mynetwork.train(train_data,train_labels);

It' difficult to help without any hint, but probably you'll have to convert the image data to your training data format. Something like:

vector<vector<uchar>> training_data;
vector<int> training_labels;
vector<Mat> images;
for(int i=0;i<images.size();i++){
    vector<uchar> data;
    for(int y=0;y<images[i].rows;y++){
        uchar *p=images[i].ptr(y);
        for(int x=0;x<images[i].cols;x++){
            data.push_back(p[i]);
data.push_back(p[x]);
        }
    }
    training_data.push_back(data);
}
mynetwork.train(train_data,train_labels);