void face_train()
{

// Training Images for me
images.push_back(imread("me/me1.jpeg", CV_LOAD_IMAGE_GRAYSCALE)); labels.push_back(0);
images.push_back(imread("me/me2.jpeg", CV_LOAD_IMAGE_GRAYSCALE)); labels.push_back(0);
images.push_back(imread("me/me3.jpeg", CV_LOAD_IMAGE_GRAYSCALE)); labels.push_back(0);
// Training Images for Brad Pitt
images.push_back(imread("Pitt/Brad_Pitt_1.jpeg", CV_LOAD_IMAGE_GRAYSCALE)); labels.push_back(1);
images.push_back(imread("Pitt/Brad_Pitt_2.jpeg", CV_LOAD_IMAGE_GRAYSCALE)); labels.push_back(1);
images.push_back(imread("Pitt/Brad_Pitt_3.jpeg", CV_LOAD_IMAGE_GRAYSCALE)); labels.push_back(1);
}

void face_detect()
{
    Mat image1;
    Mat gray;



    //G E T   I M A G E

    if ( r_c % 2 == 0 )
        image1 = imread("Cam_Pic1.jpeg", CV_LOAD_IMAGE_GRAYSCALE);
    else if ( r_c % 2 != 0 )
        image1 = imread("Cam_Pic2.jpeg", CV_LOAD_IMAGE_GRAYSCALE);


    if (image1.empty())
    {
        cout << "!!! Failed imread(): image not found" << endl;
    }


    // D E T E C T   F A C E

    cvtColor(image1, gray, CV_BGR2GRAY);
    //equalizeHist(gray, gray);


    vector<Rect_<int>> faces;

    face_cascade.load("haarcascade_frontalface_alt.xml");  // xml file with facial features algorithm
    face_cascade.detectMultiScale(gray, faces);

    // T R A I N  R E C O G N I Z E R

    face_train();

    int im_width = images[0].cols;
    int im_height = images[0].rows;

    model_fisher =  createFisherFaceRecognizer();
    model_fisher->train(images, labels);

    Mat original = image1.clone();

    // look for all faces on the image
    for(unsigned int i = 0; i < faces.size(); i++)
        {

            Rect face_i = faces[i];
            Mat face = gray(face_i);

            Mat face_resized;
            resize(face, face_resized, Size(im_width, im_height), 1.0, 1.0, INTER_CUBIC);

            int prediction = model_fisher->predict(face_resized);

            // Draw rectangle around faces
            rectangle(original , face_i, CV_RGB(0, 255,0), 1);

            //Point pt1(faces[i].x + faces[i].width, faces[i].y + faces[i].height);
            //Point pt2(faces[i].x, faces[i].y);

            string box_text = format("Match found = %d", prediction);
            //string box_text = "Match Found: Alan Alban";
            // text position and output
            int pos_x = max(face_i.tl().x - 4, 0);
            int pos_y = max(face_i.tl().y - 4, 0);

            putText(original, box_text, Point(pos_x, pos_y), FONT_HERSHEY_PLAIN, 1.0, CV_RGB(0,255,0), 2.0);
        }

    // S H O W    I M A G E

    if ( r_c % 2 == 0 )
        imwrite("Detected_image1.jpeg", image1);
    else if ( r_c % 2 != 0 )
        imwrite("Detected_image2.jpeg", image1);

    r_c++;

}

model_fisher->train(images, labels);