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@foreach (var u in Model.Usings)
{
    <div>using @(u);</div>
}

@foreach (var ns in Model.Namespaces)
{
    <div>@ns.GenerateCode()</div>
    
    
}
generated by cgit v1.3.1 (git 2.54.0) at 2026-07-29 15:37:57 +0000
#include "CardProcessor.h"

using namespace cv;
using namespace std;

// Creation of Intermediate 'Image' Objects required later

double angleOf(Point2f p1, Point2f p2);
double lengthOf(Point2f p1, Point2f p2);
Point2f scale_line(Point2f p1, Point2f p2, double newlength);

const int DBG = 1;

bool isRectChildOf(Rect rect, Rect parent)
{
	cv::Rect rectsIntersecion = parent & rect;
	return (rectsIntersecion.area() == rect.area());
}

Ptr<aruco::Dictionary> dictionary = aruco::getPredefinedDictionary(aruco::DICT_4X4_50);

CardProcessor::CardProcessor()
{
	isInitialized = false;
}

CardProcessor::~CardProcessor()
{
}

vector<Point> CardProcessor::GetQRVertices4(Mat image)
{
	if (!isInitialized)
	{
		Initialize(image);
		isInitialized = true;
	}

	vector<Point> result;

	traces = Scalar(0, 0, 0);
	qr_raw = Mat::zeros(100, 100, CV_8UC3);
	qr = Mat::zeros(100, 100, CV_8UC3);
	qr_gray = Mat::zeros(100, 100, CV_8UC1);
	qr_thres = Mat::zeros(100, 100, CV_8UC1);

	cvtColor(image, gray, CV_RGB2GRAY);		// Convert Image captured from Image Input to GrayScale	
	Canny(gray, edges, 100, 200, 3);		// Apply Canny edge detection on the gray image


	findContours(edges, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE); // Find contours with hierarchy

	mark = 0;								// Reset all detected marker count for this frame

											// Get Moments for all Contours and the mass centers
	vector<Moments> mu(contours.size());
	vector<Point2f> mc(contours.size());

	for (int i = 0; i < contours.size(); i++)
	{
		mu[i] = moments(contours[i], false);
		mc[i] = Point2f(mu[i].m10 / mu[i].m00, mu[i].m01 / mu[i].m00);
	}


	// Start processing the contour data

	// Find Three repeatedly enclosed contours A,B,C
	// NOTE: 1. Contour enclosing other contours is assumed to be the three Alignment markings of the QR code.
	// 2. Alternately, the Ratio of areas of the "concentric" squares can also be used for identifying base Alignment markers.
	// The below demonstrates the first method

	vector<int> indeces;

	for (int i = 0; i < contours.size(); i++)
	{
		//Find the approximated polygon of the contour we are examining
		approxPolyDP(contours[i], pointsseq, arcLength(contours[i], true)*0.02, true);
		if (pointsseq.size() == 4)      // only quadrilaterals contours are examined
		{
			int k = i;
			int c = 0;

			while (hierarchy[k][2] != -1)
			{
				k = hierarchy[k][2];
				c = c + 1;
			}
			if (hierarchy[k][2] != -1)
				c = c + 1;

			if (c == 5)
			{
				if (mark == 0)		A = i;
				else if (mark == 1)	B = i;		// i.e., A is already found, assign current contour to B
				else if (mark == 2)	C = i;		// i.e., A and B are already found, assign current contour to C
				else if (mark == 3)	D = i;		// i.e., A and B are already found, assign current contour to C

				indeces.push_back(i);

				mark = mark + 1;
			}
			else if (c == 6)
			{
				F = i;
			}
		}
	}


	if (mark >= 4)		// Ensure we have (atleast 3; namely A,B,C) 'Alignment Markers' discovered
	{
		// We have found the 3 markers for the QR code; Now we need to determine which of them are 'top', 'right' and 'bottom' markers

		// Determining the 'top' marker
		// Vertex of the triangle NOT involved in the longest side is the 'outlier'

		int minIndex = A;

		for (size_t i = 0; i < indeces.size(); i++)
		{
			if (isRectChildOf(boundingRect(contours[indeces[i]]), boundingRect(contours[F])))
			{
				minIndex = indeces[i];
				break;
			}
		}

		for (size_t i = 0; i < indeces.size(); i++)
		{
			if (indeces[i] == minIndex)
			{
				indeces.erase(indeces.begin() + i);
				break;
			}
		}

		A = indeces[0];
		B = indeces[1];
		C = indeces[2];

		AB = cv_distance(mc[A], mc[B]);
		BC = cv_distance(mc[B], mc[C]);
		CA = cv_distance(mc[C], mc[A]);

		if (AB > BC && AB > CA)
		{
			outlier = C; median1 = A; median2 = B;
		}
		else if (CA > AB && CA > BC)
		{
			outlier = B; median1 = A; median2 = C;
		}
		else if (BC > AB && BC > CA)
		{
			outlier = A;  median1 = B; median2 = C;
		}

		top = outlier;							// The obvious choice

		dist = cv_lineEquation(mc[median1], mc[median2], mc[outlier]);	// Get the Perpendicular distance of the outlier from the longest side			
		slope = cv_lineSlope(mc[median1], mc[median2], align);		// Also calculate the slope of the longest side

																	// Now that we have the orientation of the line formed median1 & median2 and we also have the position of the outlier w.r.t. the line
																	// Determine the 'right' and 'bottom' markers

		if (align == 0)
		{
			bottom = median1;
			right = median2;
		}
		else if (slope < 0 && dist < 0)		// Orientation - North
		{
			bottom = median1;
			right = median2;
			orientation = CV_QR_NORTH;
		}
		else if (slope > 0 && dist < 0)		// Orientation - East
		{
			right = median1;
			bottom = median2;
			orientation = CV_QR_EAST;
		}
		else if (slope < 0 && dist > 0)		// Orientation - South			
		{
			right = median1;
			bottom = median2;
			orientation = CV_QR_SOUTH;
		}

		else if (slope > 0 && dist > 0)		// Orientation - West
		{
			bottom = median1;
			right = median2;
			orientation = CV_QR_WEST;
		}


		// To ensure any unintended values do not sneak up when QR code is not present
		float area_top, area_right, area_bottom;

		if (top < contours.size() && right < contours.size() && bottom < contours.size() && contourArea(contours[top]) > 10 && contourArea(contours[right]) > 10 && contourArea(contours[bottom]) > 10)
		{

			vector<Point2f> L, M, O, tempL, tempM, tempO;
			Point2f N;

			vector<Point2f> src, dst;		// src - Source Points basically the 4 end co-ordinates of the overlay image
											// dst - Destination Points to transform overlay image	

			Mat warp_matrix;

			cv_getVertices(contours, top, slope, tempL);
			cv_getVertices(contours, right, slope, tempM);
			cv_getVertices(contours, bottom, slope, tempO);

			cv_updateCornerOr(orientation, tempL, L); 			// Re-arrange marker corners w.r.t orientation of the QR code
			cv_updateCornerOr(orientation, tempM, M); 			// Re-arrange marker corners w.r.t orientation of the QR code
			cv_updateCornerOr(orientation, tempO, O); 			// Re-arrange marker corners w.r.t orientation of the QR code

			Point2f p1(M[1].x, M[1].y);
			Point2f p2(M[2].x, (M[2].y - M[1].y) / 2);
			Point2f p3(O[3].x, O[3].y);
			Point2f p4(O[2].x, O[2].y);

			int iflag = getIntersectionPoint(M[1], M[2], O[3], O[2], N);

			// Insert Debug instructions here
			if (DBG == 1)
			{
				//Draw contours on the image
				drawContours(image, contours, top, Scalar(255, 200, 0), 2, 8, hierarchy, 0);
				drawContours(image, contours, right, Scalar(0, 0, 255), 2, 8, hierarchy, 0);
				drawContours(image, contours, bottom, Scalar(255, 0, 100), 2, 8, hierarchy, 0);

				// Debug Prints
				// Visualizations for ease of understanding
				if (slope > 5)
					circle(traces, Point(10, 20), 5, Scalar(0, 0, 255), -1, 8, 0);
				else if (slope < -5)
					circle(traces, Point(10, 20), 5, Scalar(255, 255, 255), -1, 8, 0);

				// Draw contours on Trace image for analysis	
				drawContours(traces, contours, top, Scalar(255, 0, 100), 1, 8, hierarchy, 0);
				drawContours(traces, contours, right, Scalar(255, 0, 100), 1, 8, hierarchy, 0);
				drawContours(traces, contours, bottom, Scalar(255, 0, 100), 1, 8, hierarchy, 0);

				// Draw points (4 corners) on Trace image for each Identification marker	
				circle(traces, L[0], 2, Scalar(255, 255, 0), -1, 8, 0);
				circle(traces, L[1], 2, Scalar(0, 255, 0), -1, 8, 0);
				circle(traces, L[2], 2, Scalar(0, 0, 255), -1, 8, 0);
				circle(traces, L[3], 2, Scalar(128, 128, 128), -1, 8, 0);

				circle(traces, M[0], 2, Scalar(255, 255, 0), -1, 8, 0);
				circle(traces, M[1], 2, Scalar(0, 255, 0), -1, 8, 0);
				circle(traces, M[2], 2, Scalar(0, 0, 255), -1, 8, 0);
				circle(traces, M[3], 2, Scalar(128, 128, 128), -1, 8, 0);

				circle(traces, O[0], 2, Scalar(255, 255, 0), -1, 8, 0);
				circle(traces, O[1], 2, Scalar(0, 255, 0), -1, 8, 0);
				circle(traces, O[2], 2, Scalar(0, 0, 255), -1, 8, 0);
				circle(traces, O[3], 2, Scalar(128, 128, 128), -1, 8, 0);

				// Draw point of the estimated 4th Corner of (entire) QR Code
				circle(traces, N, 2, Scalar(255, 255, 255), -1, 8, 0);

				// Draw the lines used for estimating the 4th Corner of QR Code
				line(traces, M[1], N, Scalar(0, 0, 255), 1, 8, 0);
				line(traces, O[3], N, Scalar(0, 0, 255), 1, 8, 0);


				// Show the Orientation of the QR Code wrt to 2D Image Space
				int fontFace = FONT_HERSHEY_PLAIN;

				if (orientation == CV_QR_NORTH)
				{
					putText(traces, "NORTH", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}
				else if (orientation == CV_QR_EAST)
				{
					putText(traces, "EAST", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}
				else if (orientation == CV_QR_SOUTH)
				{
					putText(traces, "SOUTH", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}
				else if (orientation == CV_QR_WEST)
				{
					putText(traces, "WEST", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}

				// Debug Prints
			}

			vector<Point2f> forthPoly;
			cv_getVertices(contours, F, slope, forthPoly);

			if (forthPoly.size() == 4)
			{
				if (orientation == CV_QR_NORTH)
				{
					N = forthPoly[2];
				}
				else if (orientation == CV_QR_EAST)
				{
					N = forthPoly[3];
				}
				else if (orientation == CV_QR_SOUTH)
				{
					N = forthPoly[0];
				}
				else if (orientation == CV_QR_WEST)
				{
					N = forthPoly[1];
				}

				result.push_back(L[0]);
				result.push_back(M[1]);
				result.push_back(N);
				result.push_back(O[3]);
			}
		}
	}

	return result;
}

vector<Point> CardProcessor::GetQRVertices(Mat image)
{
	if (!isInitialized)
	{
		Initialize(image);
		isInitialized = true;
	}

	vector<Point> result;

	traces = Scalar(0, 0, 0);
	qr_raw = Mat::zeros(100, 100, CV_8UC3);
	qr = Mat::zeros(100, 100, CV_8UC3);
	qr_gray = Mat::zeros(100, 100, CV_8UC1);
	qr_thres = Mat::zeros(100, 100, CV_8UC1);

	cvtColor(image, gray, CV_RGB2GRAY);		// Convert Image captured from Image Input to GrayScale	
	Canny(gray, edges, 100, 200, 3);		// Apply Canny edge detection on the gray image


	findContours(edges, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE); // Find contours with hierarchy

	mark = 0;								// Reset all detected marker count for this frame

											// Get Moments for all Contours and the mass centers
	vector<Moments> mu(contours.size());
	vector<Point2f> mc(contours.size());

	for (int i = 0; i < contours.size(); i++)
	{
		mu[i] = moments(contours[i], false);
		mc[i] = Point2f(mu[i].m10 / mu[i].m00, mu[i].m01 / mu[i].m00);
	}


	// Start processing the contour data

	// Find Three repeatedly enclosed contours A,B,C
	// NOTE: 1. Contour enclosing other contours is assumed to be the three Alignment markings of the QR code.
	// 2. Alternately, the Ratio of areas of the "concentric" squares can also be used for identifying base Alignment markers.
	// The below demonstrates the first method

	for (int i = 0; i < contours.size(); i++)
	{
		//Find the approximated polygon of the contour we are examining
		approxPolyDP(contours[i], pointsseq, arcLength(contours[i], true)*0.02, true);
		if (pointsseq.size() == 4)      // only quadrilaterals contours are examined
		{
			int k = i;
			int c = 0;

			while (hierarchy[k][2] != -1)
			{
				k = hierarchy[k][2];
				c = c + 1;
			}
			if (hierarchy[k][2] != -1)
				c = c + 1;

			if (c >= 5)
			{
				if (mark == 0)		A = i;
				else if (mark == 1)	B = i;		// i.e., A is already found, assign current contour to B
				else if (mark == 2)	C = i;		// i.e., A and B are already found, assign current contour to C
				mark = mark + 1;
			}
		}
	}


	if (mark >= 3)		// Ensure we have (atleast 3; namely A,B,C) 'Alignment Markers' discovered
	{
		// We have found the 3 markers for the QR code; Now we need to determine which of them are 'top', 'right' and 'bottom' markers

		// Determining the 'top' marker
		// Vertex of the triangle NOT involved in the longest side is the 'outlier'

		AB = cv_distance(mc[A], mc[B]);
		BC = cv_distance(mc[B], mc[C]);
		CA = cv_distance(mc[C], mc[A]);

		if (AB > BC && AB > CA)
		{
			outlier = C; median1 = A; median2 = B;
		}
		else if (CA > AB && CA > BC)
		{
			outlier = B; median1 = A; median2 = C;
		}
		else if (BC > AB && BC > CA)
		{
			outlier = A;  median1 = B; median2 = C;
		}

		top = outlier;							// The obvious choice

		dist = cv_lineEquation(mc[median1], mc[median2], mc[outlier]);	// Get the Perpendicular distance of the outlier from the longest side			
		slope = cv_lineSlope(mc[median1], mc[median2], align);		// Also calculate the slope of the longest side

																	// Now that we have the orientation of the line formed median1 & median2 and we also have the position of the outlier w.r.t. the line
																	// Determine the 'right' and 'bottom' markers

		if (align == 0)
		{
			bottom = median1;
			right = median2;
		}
		else if (slope < 0 && dist < 0)		// Orientation - North
		{
			bottom = median1;
			right = median2;
			orientation = CV_QR_NORTH;
		}
		else if (slope > 0 && dist < 0)		// Orientation - East
		{
			right = median1;
			bottom = median2;
			orientation = CV_QR_EAST;
		}
		else if (slope < 0 && dist > 0)		// Orientation - South			
		{
			right = median1;
			bottom = median2;
			orientation = CV_QR_SOUTH;
		}

		else if (slope > 0 && dist > 0)		// Orientation - West
		{
			bottom = median1;
			right = median2;
			orientation = CV_QR_WEST;
		}


		// To ensure any unintended values do not sneak up when QR code is not present
		float area_top, area_right, area_bottom;

		if (top < contours.size() && right < contours.size() && bottom < contours.size() && contourArea(contours[top]) > 10 && contourArea(contours[right]) > 10 && contourArea(contours[bottom]) > 10)
		{

			vector<Point2f> L, M, O, tempL, tempM, tempO;
			Point2f N;

			vector<Point2f> src, dst;		// src - Source Points basically the 4 end co-ordinates of the overlay image
											// dst - Destination Points to transform overlay image	

			Mat warp_matrix;

			cv_getVertices(contours, top, slope, tempL);
			cv_getVertices(contours, right, slope, tempM);
			cv_getVertices(contours, bottom, slope, tempO);

			cv_updateCornerOr(orientation, tempL, L); 			// Re-arrange marker corners w.r.t orientation of the QR code
			cv_updateCornerOr(orientation, tempM, M); 			// Re-arrange marker corners w.r.t orientation of the QR code
			cv_updateCornerOr(orientation, tempO, O); 			// Re-arrange marker corners w.r.t orientation of the QR code

			Point2f p1(M[1].x, M[1].y);
			Point2f p2(M[2].x, (M[2].y - M[1].y) / 2);
			Point2f p3(O[3].x, O[3].y);
			Point2f p4(O[2].x, O[2].y);

			int iflag = getIntersectionPoint(M[1], M[2], O[3], O[2], N);

			// Insert Debug instructions here
			if (DBG == 1)
			{
				//Draw contours on the image
				drawContours(image, contours, top, Scalar(255, 200, 0), 2, 8, hierarchy, 0);
				drawContours(image, contours, right, Scalar(0, 0, 255), 2, 8, hierarchy, 0);
				drawContours(image, contours, bottom, Scalar(255, 0, 100), 2, 8, hierarchy, 0);

				// Debug Prints
				// Visualizations for ease of understanding
				if (slope > 5)
					circle(traces, Point(10, 20), 5, Scalar(0, 0, 255), -1, 8, 0);
				else if (slope < -5)
					circle(traces, Point(10, 20), 5, Scalar(255, 255, 255), -1, 8, 0);

				// Draw contours on Trace image for analysis	
				drawContours(traces, contours, top, Scalar(255, 0, 100), 1, 8, hierarchy, 0);
				drawContours(traces, contours, right, Scalar(255, 0, 100), 1, 8, hierarchy, 0);
				drawContours(traces, contours, bottom, Scalar(255, 0, 100), 1, 8, hierarchy, 0);

				// Draw points (4 corners) on Trace image for each Identification marker	
				circle(traces, L[0], 2, Scalar(255, 255, 0), -1, 8, 0);
				circle(traces, L[1], 2, Scalar(0, 255, 0), -1, 8, 0);
				circle(traces, L[2], 2, Scalar(0, 0, 255), -1, 8, 0);
				circle(traces, L[3], 2, Scalar(128, 128, 128), -1, 8, 0);

				circle(traces, M[0], 2, Scalar(255, 255, 0), -1, 8, 0);
				circle(traces, M[1], 2, Scalar(0, 255, 0), -1, 8, 0);
				circle(traces, M[2], 2, Scalar(0, 0, 255), -1, 8, 0);
				circle(traces, M[3], 2, Scalar(128, 128, 128), -1, 8, 0);

				circle(traces, O[0], 2, Scalar(255, 255, 0), -1, 8, 0);
				circle(traces, O[1], 2, Scalar(0, 255, 0), -1, 8, 0);
				circle(traces, O[2], 2, Scalar(0, 0, 255), -1, 8, 0);
				circle(traces, O[3], 2, Scalar(128, 128, 128), -1, 8, 0);

				// Draw point of the estimated 4th Corner of (entire) QR Code
				circle(traces, N, 2, Scalar(255, 255, 255), -1, 8, 0);

				// Draw the lines used for estimating the 4th Corner of QR Code
				line(traces, M[1], N, Scalar(0, 0, 255), 1, 8, 0);
				line(traces, O[3], N, Scalar(0, 0, 255), 1, 8, 0);


				// Show the Orientation of the QR Code wrt to 2D Image Space
				int fontFace = FONT_HERSHEY_PLAIN;

				if (orientation == CV_QR_NORTH)
				{
					putText(traces, "NORTH", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}
				else if (orientation == CV_QR_EAST)
				{
					putText(traces, "EAST", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}
				else if (orientation == CV_QR_SOUTH)
				{
					putText(traces, "SOUTH", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}
				else if (orientation == CV_QR_WEST)
				{
					putText(traces, "WEST", Point(20, 30), fontFace, 1, Scalar(0, 255, 0), 1, 8);
				}

				// Debug Prints
			}

			//double angle1 = angleOf(L[0], O[0]);
			//double angle2 = angleOf(M[1], N);

			//double length1 = lengthOf(L[0], O[3]);
			//double length2 = lengthOf(M[1], N);

			//double length3 = lengthOf(L[0], M[1]);
			//double length4 = lengthOf(O[3], N);

			//if (angle1 == angle2)
			//{
			//	if (length1 != length2 || length3 != length4)
			//	{
			//		N = scale_line(M[1], N, length1);
			//		N = scale_line(O[3], N, length3);

					result.push_back(L[0]);
					result.push_back(M[1]);
					result.push_back(N);
					result.push_back(O[3]);
			//	}
			//}
		}
	}

	return result;
}

vector<Point2f> sortPoints(vector<Point2f> unsorted) {
	vector<Point2f> sorted;
	for (int i = 0; i < 4; i++)sorted.push_back(Point2f(0, 0));
	int middleX = (unsorted[0].x + unsorted[1].x + unsorted[2].x + unsorted[3].x) / 4;
	int middleY = (unsorted[0].y + unsorted[1].y + unsorted[2].y + unsorted[3].y) / 4;
	for (int i = 0; i < unsorted.size(); i++) {
		if (unsorted.at(i).x < middleX && unsorted.at(i).y < middleY)sorted[0] = unsorted.at(i);
		if (unsorted.at(i).x > middleX && unsorted.at(i).y < middleY)sorted[1] = unsorted.at(i);
		if (unsorted.at(i).x < middleX && unsorted.at(i).y > middleY)sorted[2] = unsorted.at(i);
		if (unsorted.at(i).x > middleX && unsorted.at(i).y > middleY)sorted[3] = unsorted.at(i);
	}
	return sorted;
}

vector<Point> sortPoints(vector<Point> unsorted) {
	vector<Point> sorted;
	for (int i = 0; i < 4; i++)sorted.push_back(Point(0, 0));
	int middleX = (unsorted[0].x + unsorted[1].x + unsorted[2].x + unsorted[3].x) / 4;
	int middleY = (unsorted[0].y + unsorted[1].y + unsorted[2].y + unsorted[3].y) / 4;
	for (int i = 0; i < unsorted.size(); i++) {
		if (unsorted.at(i).x < middleX && unsorted.at(i).y < middleY)sorted[0] = unsorted.at(i);
		if (unsorted.at(i).x > middleX && unsorted.at(i).y < middleY)sorted[1] = unsorted.at(i);
		if (unsorted.at(i).x < middleX && unsorted.at(i).y > middleY)sorted[2] = unsorted.at(i);
		if (unsorted.at(i).x > middleX && unsorted.at(i).y > middleY)sorted[3] = unsorted.at(i);
	}
	return sorted;
}

vector<Point> CardProcessor::GetArcusVertices(Mat image)
{
	vector<Point> vertices;

	vector<int> ids;
	vector<vector<Point2f>> corners;

	aruco::DetectorParameters* params = new aruco::DetectorParameters();
	params->cornerRefinementMethod = aruco::CORNER_REFINE_SUBPIX;
	params->perspectiveRemovePixelPerCell = 50;
	

	aruco::detectMarkers(image, dictionary, corners, ids, &(*params));
	if (corners.size() == 4)
	{
		//aruco::drawDetectedMarkers(image, corners, ids);

		vertices =
		{
			Point(0,0),
			Point(0,0),
			Point(0,0),
			Point(0,0)
		};

		InputArrayOfArrays _corners = corners;
		InputArray _ids = ids;

		int nMarkers = (int)_corners.total();

		for (int i = 0; i < nMarkers; i++) {

			Mat currentMarker = _corners.getMat(i);
			int id = _ids.getMat().ptr< int >(0)[i] - 1;

			switch (id)
			{
				case 0:
					vertices[0] = currentMarker.ptr< Point2f >(0)[0];
					break;
				case 1:
					vertices[1] = currentMarker.ptr< Point2f >(0)[1];
					break;
				case 2:
					vertices[2] = currentMarker.ptr< Point2f >(0)[2];
					break;
				case 3:
					vertices[3] = currentMarker.ptr< Point2f >(0)[3];
					break;
			}
		}
	}

	return vertices;
}

double angleOf(Point2f p1, Point2f p2) {
	float angle = atan2(p1.y - p2.y, p1.x - p2.x);
	return angle * 180 / 3.14;
}

double lengthOf(Point2f p1, Point2f p2)
{
	return sqrt(pow((p1.x - p2.x), 2) + pow((p1.y - p2.y), 2));
}

Point2f scale_line(Point2f p1, Point2f p2, double newlength)
{
	double length = lengthOf(p1, p2);
	return Point2f(p1.x + (newlength / length) * (p2.x - p1.x), p1.y + (newlength / length) * (p2.y - p1.y));
}

Mat CardProcessor::ApplyHomography(Mat image, vector<Point> vertices, Size destination_size)
{
	Mat im_dst = Mat::zeros(destination_size, CV_8UC3);

	vector<Point2f> pts_dst;

	pts_dst.push_back(Point2f(0, 0));
	pts_dst.push_back(Point2f(destination_size.width - 1, 0));
	pts_dst.push_back(Point2f(destination_size.width - 1, destination_size.height - 1));
	pts_dst.push_back(Point2f(0, destination_size.height - 1));

	Mat im_temp = image.clone();

	Mat tform = findHomography(vertices, pts_dst);
	warpPerspective(image, im_dst, tform, destination_size);
	return im_dst;
}

Rect CardProcessor::CropRect(Rect rect, Size size)
{
	Point center = (rect.br() + rect.tl())*0.5;

	Rect cropped(center.x - size.width / 2, center.y - size.height / 2, size.width, size.height);

	//Inflate Rectangle ??
	//cv::Point inflationPoint(-20, -20);
	//cv::Size inflationSize(20, 20);
	//croped += inflationPoint;
	//croped += inflationSize;

	return cropped;
}

Scalar CardProcessor::GetRectMeanColor(Mat image, Rect rect)
{
	Point pts[1][4];
	pts[0][0] = Point(rect.x, rect.y);
	pts[0][1] = Point(rect.x + rect.width, rect.y);
	pts[0][2] = Point(rect.x + rect.width, rect.y + rect.height);
	pts[0][3] = Point(rect.x, rect.y + rect.height);

	const Point* points[1] = { pts[0] };
	int npoints = 4;

	// Create the mask with the polygon
	Mat1b mask(image.rows, image.cols, uchar(0));

	fillPoly(mask, points, &npoints, 1, Scalar(255));

	// Compute the mean with the computed mask
	Scalar average = mean(image, mask);

	return average;
}

Mat CardProcessor::GetImageRect(Mat image, Rect rect)
{
	Mat rectImage(rect.size(), CV_8UC3);
	Rect dst(0, 0, rect.width, rect.height);
	image(rect).copyTo(rectImage(dst));
	return rectImage;
}

Mat CardProcessor::Diff(Mat image, int k)
{
	int origRows = image.rows;
	Mat colVec = image.reshape(1, image.rows*image.cols); // change to a Nx3 column vector
	Mat colVecD, bestLabels, centers, clustered;
	int attempts = 2;
	int clusts = 2;
	double eps = 1.0;
	colVec.convertTo(colVecD, CV_32FC3, 1.0 / 255.0); // convert to floating point
	double compactness = kmeans(colVecD, clusts, bestLabels, TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, attempts, eps), attempts, KMEANS_PP_CENTERS, centers);
	Mat labelsImg = bestLabels.reshape(1, origRows); // single channel image of labels

	return centers;
}

void CardProcessor::DrawImage(Mat image, Mat draw, Rect rect)
{
	// Take a sub-view of the large image
	cv::Mat subView = image(rect);

	// Copy contents of the small image to large
	draw.copyTo(subView);
}

void CardProcessor::DrawHistogram(Mat image)
{
	/// Separate the image in 3 places ( B, G and R )
	vector<Mat> bgr_planes;
	split(image, bgr_planes);

	/// Establish the number of bins
	int histSize = image.cols;

	/// Set the ranges ( for B,G,R) )
	float range[] = { 0, 256 };
	const float* histRange = { range };

	bool uniform = true; bool accumulate = false;

	Mat b_hist, g_hist, r_hist;

	/// Compute the histograms:
	calcHist(&bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate);
	calcHist(&bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate);
	calcHist(&bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRange, uniform, accumulate);

	/// Normalize the result to [ 0, histImage.rows ]
	normalize(b_hist, b_hist, 0, image.rows, NORM_MINMAX, -1, Mat());
	normalize(g_hist, g_hist, 0, image.rows, NORM_MINMAX, -1, Mat());
	normalize(r_hist, r_hist, 0, image.rows, NORM_MINMAX, -1, Mat());

	// Draw the histograms for B, G and R
	int hist_w = image.cols;
	int hist_h = image.rows;
	int bin_w = cvRound((double)hist_w / histSize);

	/// Draw for each channel
	for (int i = 1; i < histSize; i++)
	{
		line(image, Point(bin_w*(i - 1), hist_h - cvRound(b_hist.at<float>(i - 1))),
			Point(bin_w*(i), hist_h - cvRound(b_hist.at<float>(i))),
			Scalar(255, 0, 0), 2, 8, 0);
		line(image, Point(bin_w*(i - 1), hist_h - cvRound(g_hist.at<float>(i - 1))),
			Point(bin_w*(i), hist_h - cvRound(g_hist.at<float>(i))),
			Scalar(0, 255, 0), 2, 8, 0);
		line(image, Point(bin_w*(i - 1), hist_h - cvRound(r_hist.at<float>(i - 1))),
			Point(bin_w*(i), hist_h - cvRound(r_hist.at<float>(i))),
			Scalar(0, 0, 255), 2, 8, 0);
	}
}

Point CardProcessor::GetRectCenter(Rect rect)
{
	Point center = (rect.br() + rect.tl())*0.5;
	return center;
}

void CardProcessor::Initialize(Mat image)
{
	// Creation of Intermediate 'Image' Objects required later
	Mat gray(image.size(), CV_MAKETYPE(image.depth(), 1));			// To hold Grayscale Image
	Mat edges(image.size(), CV_MAKETYPE(image.depth(), 1));			// To hold Grayscale Image
	Mat traces(image.size(), CV_8UC3);								// For Debug Visuals
	Mat qr, qr_raw, qr_gray, qr_thres;

	vector<vector<Point> > contours;
	vector<Vec4i> hierarchy;
	vector<Point> pointsseq;    //used to save the approximated sides of each contour
}

// Function: Routine to get Distance between two points
// Description: Given 2 points, the function returns the distance
float CardProcessor::cv_distance(Point2f P, Point2f Q)
{
	return sqrt(pow(abs(P.x - Q.x), 2) + pow(abs(P.y - Q.y), 2));
}

// Function: Perpendicular Distance of a Point J from line formed by Points L and M; Equation of the line ax+by+c=0
// Description: Given 3 points, the function derives the line quation of the first two points,
//	  calculates and returns the perpendicular distance of the the 3rd point from this line.
float CardProcessor::cv_lineEquation(Point2f L, Point2f M, Point2f J)
{
	float a, b, c, pdist;

	a = -((M.y - L.y) / (M.x - L.x));
	b = 1.0;
	c = (((M.y - L.y) / (M.x - L.x)) * L.x) - L.y;

	// Now that we have a, b, c from the equation ax + by + c, time to substitute (x,y) by values from the Point J

	pdist = (a * J.x + (b * J.y) + c) / sqrt((a * a) + (b * b));
	return pdist;
}

// Function: Slope of a line by two Points L and M on it; Slope of line, S = (x1 -x2) / (y1- y2)
// Description: Function returns the slope of the line formed by given 2 points, the alignement flag
//	  indicates the line is vertical and the slope is infinity.
float CardProcessor::cv_lineSlope(Point2f L, Point2f M, int& alignement)
{
	float dx, dy;
	dx = M.x - L.x;
	dy = M.y - L.y;

	if (dy != 0)
	{
		alignement = 1;
		return (dy / dx);
	}
	else				// Make sure we are not dividing by zero; so use 'alignement' flag
	{
		alignement = 0;
		return 0.0;
	}
}

// Function: Routine to calculate 4 Corners of the Marker in Image Space using Region partitioning
// Theory: OpenCV Contours stores all points that describe it and these points lie the perimeter of the polygon.
//	The below function chooses the farthest points of the polygon since they form the vertices of that polygon,
//	exactly the points we are looking for. To choose the farthest point, the polygon is divided/partitioned into
//	4 regions equal regions using bounding box. Distance algorithm is applied between the centre of bounding box
//	every contour point in that region, the farthest point is deemed as the vertex of that region. Calculating
//	for all 4 regions we obtain the 4 corners of the polygon ( - quadrilateral).
void CardProcessor::cv_getVertices(vector<vector<Point> > contours, int c_id, float slope, vector<Point2f>& quad)
{
	Rect box;
	box = boundingRect(contours[c_id]);

	Point2f M0, M1, M2, M3;
	Point2f A, B, C, D, W, X, Y, Z;

	A = box.tl();
	B.x = box.br().x;
	B.y = box.tl().y;
	C = box.br();
	D.x = box.tl().x;
	D.y = box.br().y;


	W.x = (A.x + B.x) / 2;
	W.y = A.y;

	X.x = B.x;
	X.y = (B.y + C.y) / 2;

	Y.x = (C.x + D.x) / 2;
	Y.y = C.y;

	Z.x = D.x;
	Z.y = (D.y + A.y) / 2;

	float dmax[4];
	dmax[0] = 0.0;
	dmax[1] = 0.0;
	dmax[2] = 0.0;
	dmax[3] = 0.0;

	float pd1 = 0.0;
	float pd2 = 0.0;

	if (slope > 5 || slope < -5)
	{

		for (int i = 0; i < contours[c_id].size(); i++)
		{
			pd1 = cv_lineEquation(C, A, contours[c_id][i]);	// Position of point w.r.t the diagonal AC 
			pd2 = cv_lineEquation(B, D, contours[c_id][i]);	// Position of point w.r.t the diagonal BD

			if ((pd1 >= 0.0) && (pd2 > 0.0))
			{
				cv_updateCorner(contours[c_id][i], W, dmax[1], M1);
			}
			else if ((pd1 > 0.0) && (pd2 <= 0.0))
			{
				cv_updateCorner(contours[c_id][i], X, dmax[2], M2);
			}
			else if ((pd1 <= 0.0) && (pd2 < 0.0))
			{
				cv_updateCorner(contours[c_id][i], Y, dmax[3], M3);
			}
			else if ((pd1 < 0.0) && (pd2 >= 0.0))
			{
				cv_updateCorner(contours[c_id][i], Z, dmax[0], M0);
			}
			else
				continue;
		}
	}
	else
	{
		int halfx = (A.x + B.x) / 2;
		int halfy = (A.y + D.y) / 2;

		for (int i = 0; i < contours[c_id].size(); i++)
		{
			if ((contours[c_id][i].x < halfx) && (contours[c_id][i].y <= halfy))
			{
				cv_updateCorner(contours[c_id][i], C, dmax[2], M0);
			}
			else if ((contours[c_id][i].x >= halfx) && (contours[c_id][i].y < halfy))
			{
				cv_updateCorner(contours[c_id][i], D, dmax[3], M1);
			}
			else if ((contours[c_id][i].x > halfx) && (contours[c_id][i].y >= halfy))
			{
				cv_updateCorner(contours[c_id][i], A, dmax[0], M2);
			}
			else if ((contours[c_id][i].x <= halfx) && (contours[c_id][i].y > halfy))
			{
				cv_updateCorner(contours[c_id][i], B, dmax[1], M3);
			}
		}
	}

	quad.push_back(M0);
	quad.push_back(M1);
	quad.push_back(M2);
	quad.push_back(M3);

}

// Function: Compare a point if it more far than previously recorded farthest distance
// Description: Farthest Point detection using reference point and baseline distance
void CardProcessor::cv_updateCorner(Point2f P, Point2f ref, float& baseline, Point2f& corner)
{
	float temp_dist;
	temp_dist = cv_distance(P, ref);

	if (temp_dist > baseline)
	{
		baseline = temp_dist;			// The farthest distance is the new baseline
		corner = P;						// P is now the farthest point
	}

}

// Function: Sequence the Corners wrt to the orientation of the QR Code
void CardProcessor::cv_updateCornerOr(int orientation, vector<Point2f> IN, vector<Point2f> &OUT)
{
	Point2f M0, M1, M2, M3;
	if (orientation == CV_QR_NORTH)
	{
		M0 = IN[0];
		M1 = IN[1];
		M2 = IN[2];
		M3 = IN[3];
	}
	else if (orientation == CV_QR_EAST)
	{
		M0 = IN[1];
		M1 = IN[2];
		M2 = IN[3];
		M3 = IN[0];
	}
	else if (orientation == CV_QR_SOUTH)
	{
		M0 = IN[2];
		M1 = IN[3];
		M2 = IN[0];
		M3 = IN[1];
	}
	else if (orientation == CV_QR_WEST)
	{
		M0 = IN[3];
		M1 = IN[0];
		M2 = IN[1];
		M3 = IN[2];
	}

	OUT.push_back(M0);
	OUT.push_back(M1);
	OUT.push_back(M2);
	OUT.push_back(M3);
}

// Function: Get the Intersection Point of the lines formed by sets of two points
bool CardProcessor::getIntersectionPoint(Point2f a1, Point2f a2, Point2f b1, Point2f b2, Point2f& intersection)
{
	Point2f p = a1;
	Point2f q = b1;
	Point2f r(a2 - a1);
	Point2f s(b2 - b1);

	if (cross(r, s) == 0) { return false; }

	float t = cross(q - p, s) / cross(r, s);

	intersection = p + t*r;
	return true;
}

float CardProcessor::cross(Point2f v1, Point2f v2)
{
	return v1.x*v2.y - v1.y*v2.x;
}
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