gradient orientation for 0-180 histogram bins in opencv 2.4.9 visual studio 2013 [closed]

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I am trying to develop a facial emotion system using OpenCV 2.4.9 and C++ in Visual Studio 2013. I need to extract shape based facial features using pyramid HOG, i used cv::phase() for gradient orientation in range of 0-360... i tried to use cv::fastAtan2() for gradient 0-180 by first making the -ve gradient to be positive, but there are some dimension problem and code end with exception..if possible for anyone..kindly help me to solve this..thanks in advance. code i am using is as follows:

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdlib.h>
#include <stdio.h>
#include <iostream>
#include <fstream>  // library that contains file input/output functions
#include <math.h>
#include <stdio.h>
using namespace cv;
using namespace std;


/** @function main */
int main(int argc, char** argv)
{

    Mat src, src_gray;
    Mat grad;
    char* window_name = "Sobel  Edge Detector";
    int scale = 1;
    int delta = 0;
    int ddepth = CV_16S;//16S for 0-360 degree; 8U for 0-90 degree;16U for 0-90

    int c;

    /// Load an image
    src = imread( "whole_face_0.jpg");


    if (!src.data)
    {
        return -1;
    }

    //GaussianBlur(src, src, Size(3, 3), 0, 0, BORDER_DEFAULT);

    /// Convert it to gray
    //cvtColor(src, src_gray, CV_RGB2GRAY);
    src_gray = src;
    /// Create window
    namedWindow(window_name, CV_WINDOW_AUTOSIZE);

    /// Generate grad_x and grad_y
    Mat grad_x, grad_y;
    //The absolute values need to be computed for displaying the gradients (as you cannot display values <0), but they shouldn't be used for further processing.
    Mat abs_grad_x, abs_grad_y;//

    //to calculate the gradient in x direction we use : x_order  = 1 and y_ order  = 0. We do analogously for the y direction

    /// Gradient X
    //Scharr( src_gray, grad_x, ddepth, 1, 0, scale, delta, BORDER_DEFAULT );
    //Sobel(src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT);

    src_gray = src;

    //Scharr(src_gray, grad_x, CV_16S, 1, 0, scale, delta, BORDER_DEFAULT);
    Sobel(src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT);
    convertScaleAbs(grad_x, abs_grad_x); //CV_8U type for Sobel output. It is unsigned integer 8 bit. So it can store only positive values.

    /// Gradient Y
    //Scharr(src_gray, grad_y, CV_16S, 0, 1, scale, delta, BORDER_DEFAULT);//ddepth=CV_16S
    Sobel(src_gray, grad_y, ddepth, 0, 1, 3, scale, delta, BORDER_DEFAULT);

    //Calculates an absolute value of each matrix element
    convertScaleAbs(grad_y, abs_grad_y);

    //we try to approximate the gradient by adding both directional gradients
    //(note that this is not an exact calculation at all! but it is good for our purposes).
    /// Total Gradient (approximate)
    addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad);


    /////////////// gradient angle computation //////////////////
    Mat orientation = Mat::zeros(abs_grad_x.rows, abs_grad_y.cols, CV_32F); //to store the gradients grad_x.convertTo(grad_x,CV_32F);

    Mat angle;


    for (int g = 0; g < grad_x.rows;g++)
    for (int k = 0; k < grad_x.cols; k++){
        if (grad_x.at<float>(g, k) < 0)
            grad_x.at<float>(g, k) = grad_x.at<float>(g, k)*(-1);
        if (grad_y.at<float>(g, k) < 0)
            grad_y.at<float>(g, k) = grad_y.at<float>(g, k)*(-1);
        }

    for (int g = 0; g < grad_x.rows; g++)
    for (int k = 0; k < grad_x.cols; k++){
        angle.at<float>(g, k) = cv::fastAtan2(grad_y.at ...