// =================
// || Worksheet 3
// || In this example, we are going to apply convolution filters to an image..
// =================

// for comparison, see:
// http://docs.opencv.org/doc/tutorials/core/mat-mask-operations/mat-mask-operations.html#maskoperationsfilter
// more at
// https://github.com/Itseez/opencv/blob/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp

#include "program.h"

using namespace std;
using namespace cv;
 
 int worksheetthree( Mat& colorImage )
 {
     char my_window_name[] = "My Image";
     
     cv::namedWindow( my_window_name, WINDOW_AUTOSIZE );
     
     // display our output image.
     cv::imshow( my_window_name, colorImage);
     
     cv::waitKey();
     
     cv::Mat outputImage;
     outputImage.create(colorImage.size(), colorImage.type());
 
     // now, we are going to create a convolution kernel.
     // this should do a small blurring.
     // the syntax here is a little confusing.
     // we are going to need to create a 3x3 matrix.
     //and store the following values
     // 0 1 0
     // 1 2 1
     // 0 1 0
     cv::Mat kernel = (cv::Mat_<float>(3,3) <<  0,  1,  0,
                                               1,  2,  1,
                                               0,  1,  0);
     
     // now that we have our kernel, we want to apply it to our input image.
     // the arguments are
     // filter2D(input, output, depth, kernel)
     cv::filter2D(colorImage, outputImage, colorImage.depth(), 0.1666f*kernel);


     // display our output image.
     cv::imshow( my_window_name, outputImage);
 
     cv::waitKey();
 
     return 0;
 }