Neha's profile - activity

I'm new to opencv and visual studio and still learning its basics.I'm also doing face recognition project using opencv2.4.3 and visual studio 2010.I have read the tutorial on Face recognition in videos using opencv and implemented the code.the code is as follows with name main.cpp

#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect/objdetect.hpp"

#include <iostream>
#include <fstream>
#include <sstream>

using namespace cv;
using namespace std;

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(int argc, const char *argv[]) {
    // Check for valid command line arguments, print usage
    // if no arguments were given.
    if (argc != 4) {
        cout << "usage: " << argv[0] << " C:\opencv243\data\haarcascades\haarcascade_frontalface_default.xml C:\att\att1.txt 0" << endl;
        cout << "\t C:\opencv243\data\haarcascades\haarcascade_frontalface_default.xml -- Path to the Haar Cascade for face detection." << endl;
        cout << "\t C:\att\att1.txt -- Path to the CSV file with the face database." << endl;
        cout << "\t 0 -- The webcam device id to grab frames from." << endl;
        exit(1);
    }
    // Get the path to your CSV:
    string fn_haar = C:\opencv243\data\haarcascades\haarcascade_frontalface_default.xml ;
    string fn_csv = C:\att\att1.txt ;
    int deviceId = 0
    // 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);
    }
    // Get the height from the first image. We'll need this
    // later in code to reshape the images to their original
    // size AND we need to reshape incoming faces to this size:
    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);
    // That's it for learning the Face Recognition model. You now
    // need to create the classifier for the task of Face Detection.
    // We are going to use the haar cascade you have specified in the
    // command line arguments:
    //
    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 ...