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Unsupported format or combination of formats while running face recognition from video.

Each time I am trying to run programm I got this error. Can anyone help me with that? What may cause the issu?

OpenCV Error: Unsupported format or combination of formats (In the Fisherfaces method all input samples (training images) must be of equal size! Expected 76800 pixels, but was 0 pixels.) in train, file /hdd1/software/opencv/opencv-2.4.6.1/modules/contrib/src/facerec.cpp, line 455 terminate called after throwing an instance of 'cv::Exception' what(): /hdd1/software/opencv/opencv-2.4.6.1/modules/contrib/src/facerec.cpp:455: error: (-210) In the Fisherfaces method all input samples (training images) must be of equal size! Expected 76800 pixels, but was 0 pixels. in function train

And below is my source code:

>     #include "/usr/local/include/opencv2/core/core.hpp"
>     #include "/usr/local/include/opencv2/contrib/contrib.hpp"
>     #include "/usr/local/include/opencv2/highgui/highgui.hpp"
>     #include "/usr/local/include/opencv2/imgproc/imgproc.hpp"
>     #include "/usr/local/include/opencv2/objdetect/objdetect.hpp"
>     
>     #include <iostream>
>     #include <fstream>
>     #include <sstream>
>     #include <string>
>     
>     using namespace cv;
>     using namespace std;
>     
>     int WriteLabel(int prediction) {
>     ofstream label;
>     label.open("/home/lbobrek/public_html/FaceToLog/src/facerecognizer/label.txt");
>        if (label.fail())
>        {
>           return 1;
>        }
>     label << prediction;
>     label.close();
>     return 0;
>     }
>     
>     static void read_csv(const string& filename, vector<Mat>& images,
> vector<int>& labels, char separator =
> ';') {
>         std::ifstream file(filename.c_str(), ifstream::in);
>         if (!file) {
>             string error_message = "No valid input file was given, please
> check the given filename.";
>             CV_Error(CV_StsBadArg, error_message);
>         }
>         string line, path, classlabel;
>         while (getline(file, line)) {
>             stringstream liness(line);
>             getline(liness, path, separator);
>             getline(liness, classlabel);
>             if(!path.empty() && !classlabel.empty()) {
>                 images.push_back(imread(path, 0));
>                 labels.push_back(atoi(classlabel.c_str()));
>             }
>         }
>     }
>     
>     int main() {
>        //if (argc != 4) {
>        //     cout << "usage: " << argv[0] << " </path/to/haar_cascade>
> </path/to/csv.ext> </path/to/device
> id>" << endl;
>        //     cout << "\t </path/to/haar_cascade> -- Path to the
> Haar Cascade for face detection." <<
> endl;
>        //     cout << "\t </path/to/csv.ext> -- Path to the CSV
> file with the face database." << endl;
>        //     cout << "\t <device id> -- The webcam device id to grab frames from." << endl;
>        //     exit(1);
>        //}
>         // Get the path to your CSV:
>         remove("/home/lbobrek/public_html/FaceToLog/src/facerecognizer/label.txt");
>         string fn_haar = ("/home/lbobrek/public_html/FaceToLog/src/facerecognizer/haarcascade_frontalface_default.xml");
>         string fn_csv = ("/home/lbobrek/public_html/FaceToLog/src/database.csv");
>         string deviceId = ("/home/lbobrek/public_html/FaceToLog/src/video/login.webm");
>         // These vectors hold the images and corresponding labels:
>         vector<Mat> images;
>         vector<int> labels;
>         // Read in the data (fails if no valid input filename is given, but
> you'll get an error message):
>         try {
>             read_csv(fn_csv, images, labels);
>         } catch (cv::Exception& e) {
>             cerr << "Error opening file \"" << fn_csv << "\". Reason: "
> << e.msg << endl;
>             // nothing more we can do
>             exit(1);
>         }
>         int im_width = images[0].cols;
>         int im_height = images[0].rows;
>         // Create a FaceRecognizer and train it on the given images:
>         Ptr<FaceRecognizer> model = createFisherFaceRecognizer();
>         model->train(images, labels);
>         CascadeClassifier haar_cascade;
>         haar_cascade.load(fn_haar);
>         // Get a handle to the Video device:
>         VideoCapture cap(deviceId);
>         // Check if we can use this device at all:
>         if(!cap.isOpened()) {
>             cerr << "Capture Device ID " << deviceId << "cannot be opened."
> << endl;
>             return -1;
>         }
>         // Holds the current frame from the Video device:
>         Mat frame;
>         for(;;) {
>             cap >> frame;
>             // Clone the current frame:
>             Mat original = frame.clone();
>             // Convert the current frame to grayscale:
>             Mat gray;
>             cvtColor(original, gray, CV_BGR2GRAY);
>             // Find the faces in the frame:
>             vector< Rect_<int> > faces;
>             haar_cascade.detectMultiScale(gray,
> faces);
>             // At this point you have the position of the faces in
>             // faces. Now we'll get the faces, make a prediction and
>             // annotate it in the video. Cool or what?
>             for(int i = 0; i < faces.size(); i++) {
>                 // Process face by face:
>                 Rect face_i = faces[i];
>                 // Crop the face from the image. So simple with OpenCV C++:
>                 Mat face = gray(face_i);
>                 Mat face_resized;
>                 cv::resize(face, face_resized, Size(im_width,
> im_height), 1.0, 1.0, INTER_CUBIC);
>                 // Now perform the prediction, see how easy that is:
>                 int prediction = model->predict(face_resized);
>                 if (prediction != -1) {
>                   WriteLabel(prediction);
>                 }
>             }
>         }
>         return 0;
>     }

Cheers! :)