#include "stdafx.h"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>

using namespace std;
using namespace cv;

//! [declare]
/// Global Variables
bool use_mask;
Mat img; Mat templ; Mat mask; Mat result;
const char* image_window = "Source Image";
const char* result_window = "Result window";

int match_method;
int max_Trackbar = 5;
//! [declare]

/// Function Headers
void MatchingMethod(int, void*);

/**
* @function main
*/
int main(int argc, char** argv)
{
	/*if (argc < 2)
	{
		cout << "Not enough parameters" << endl;
		cout << "Usage:\n./MatchTemplate_Demo <image_name> " << endl;
		return -1;
	}*/

	//! [load_image]
	/// Load image and template
	img = imread("2.jpg", IMREAD_COLOR);
	templ = imread("temp.jpg", IMREAD_COLOR);

	/*if (argc > 3) {
		use_mask = true;
		mask = imread(argv[3], IMREAD_COLOR);
	}*/

	if (img.empty() || templ.empty() || (use_mask && mask.empty()))
	{
		cout << "Can't read one of the images" << endl;
		return -1;
	}
	//! [load_image]

	//! [create_windows]
	/// Create windows
	namedWindow(image_window, WINDOW_AUTOSIZE);
	namedWindow(result_window, WINDOW_AUTOSIZE);
	//! [create_windows]

	//! [create_trackbar]
	/// Create Trackbar
	const char* trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED";
	createTrackbar(trackbar_label, image_window, &match_method, max_Trackbar, MatchingMethod);
	//! [create_trackbar]

	MatchingMethod(0, 0);

	//! [wait_key]
	waitKey(0);
	return 0;
	//! [wait_key]
}

/**
* @function MatchingMethod
* @brief Trackbar callback
*/
void MatchingMethod(int, void*)
{
	//! [copy_source]
	/// Source image to display
	Mat img_display;
	img.copyTo(img_display);
	//! [copy_source]

	//! [create_result_matrix]
	/// Create the result matrix
	int result_cols = img.cols - templ.cols + 1;
	int result_rows = img.rows - templ.rows + 1;

	result.create(result_rows, result_cols, CV_32FC1);
	//! [create_result_matrix]

	//! [match_template]
	/// Do the Matching and Normalize
	bool method_accepts_mask = (TM_SQDIFF == match_method || match_method == TM_CCORR_NORMED);
	if (use_mask && method_accepts_mask)
	{
		matchTemplate(img, templ, result, match_method, mask);
	}
	else
	{
		matchTemplate(img, templ, result, match_method);
	}
	//! [match_template]

	//! [normalize]
	normalize(result, result, 0, 1, NORM_MINMAX, -1, Mat());
	//! [normalize]

	//! [best_match]
	/// Localizing the best match with minMaxLoc
	double minVal; double maxVal; Point minLoc; Point maxLoc;
	Point matchLoc;

	minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, Mat());
	//! [best_match]

	//! [match_loc]
	/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
	if (match_method == TM_SQDIFF || match_method == TM_SQDIFF_NORMED)
	{
		matchLoc = minLoc;
	}
	else
	{
		matchLoc = maxLoc;
	}
	//! [match_loc]

	//! [imshow]
	/// Show me what you got
	rectangle(img_display, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar::all(0), 2, 8, 0);
	rectangle(result, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar::all(0), 2, 8, 0);

	imshow(image_window, img_display);
	imshow(result_window, result);
	//! [imshow]

	return;
}