Graph Detect task

auv_task.cpp

@@ -0,0 +1,162 @@
+#include "opencv2/highgui/highgui.hpp"
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/core/core.hpp>
+#include <iostream>
+
+using namespace cv;
+
+using namespace std;
+int main(int argc, char *argv[])
+{
+	Mat img = imread(argv[1], 1);
+	Mat img1 = imread(argv[1],1 );
+	Mat grayimg= imread(argv[1], 0);
+	Mat canny_output;
+	int low_threshold=50;
+	int high_threshold=100;
+  Mat img_output;
+	namedWindow("Output Image", WINDOW_AUTOSIZE);
+	namedWindow("Canny", WINDOW_AUTOSIZE);
+	Canny(img, canny_output, low_threshold, high_threshold);
+	vector<Vec2f> lines;
+	std::vector<Vec2f> o_lines;
+	HoughLines(canny_output, lines, 0.01, CV_PI/180, 120);
+	int count=0;
+	for( size_t i = 0; i < lines.size(); i++ )
+	{
+  		float rho = lines[i][0], theta = lines[i][1];
+  		double a = cos(theta), b = sin(theta);
+
+  		float alpha=theta*180/CV_PI;
+			if((fabs(alpha)==0 or fabs(alpha)==90 )){
+				if (rho>7 and rho<img.rows-7) {
+				o_lines.push_back(lines[i]);
+				// cout<<"The lines parallel to axes have rho and angle: "<<o_lines[i]<<'\n';
+				count++;
+			}
+	}
+}
+
+// The crux of the code lies in here.
+// We separated the borders lines from the image which hampered in the processing of the HoughLines.
+// Then we minimized the X coordinates of lines (Provided the lines have slope either Infinity or O)
+// to find the X-axis and maximized the Y coordinates of lines to find the Y-axis. Hence we found the
+// Origin.
+
+Point pt1, pt2;
+Point px1, py1, px2, py2;
+Point origin;
+px1.x=999999;
+px1.y=1000;
+py1.x=1000;
+py1.y=-923;
+	for( size_t i = 0; i<o_lines.size(); i++){
+
+			float rho = o_lines[i][0], theta = o_lines[i][1];
+			int j= (int)i;
+			double a = cos(theta), b = sin(theta);
+
+			float alpha=theta*180/CV_PI;
+			double x0 = a*rho, y0 = b*rho;
+  		pt1.x = cvRound(x0 + 1000*(-b));
+  		pt1.y = cvRound(y0 + 1000*(a));
+  		pt2.x = cvRound(x0 - 1000*(-b));
+ 			pt2.y = cvRound(y0 - 1000*(a));
+ 			//cout<<"This is x coord: "<<pt1<<'\n';
+  		// cout<<"This is y coord: "<< pt2<<'\n';
+			if(alpha==0){
+				if(px1.x>pt1.x){
+					px1.x=pt1.x;
+				}
+			}
+				if(alpha==90){
+					if(py1.y<pt2.y){
+						py1.y=pt2.y;
+						cout<<py1<<'\n';
+					}
+				}
+			}
+
+		px2.x=px1.x;
+		px2.y=-1000;
+		py2.y=py1.y;
+		py2.x=-1000;
+		cout<<py1<<'\n';
+		cout<<px1<<'\n';
+   	line( img1, px1, px2, Scalar(0,0,255), 1, 8);
+		line(img1, py1, py2, Scalar(0,255,0), 1, 8);
+		origin.x=px2.x;
+		origin.y=py2.y;
+		cout<<origin<<'\n';
+		vector<vector<Point> > contours;
+  	vector<Vec4i> hierarchy;
+		if (origin.x>500){
+			origin.x=img.cols/5;
+		}
+		if (origin.y<=0){
+			origin.y=img.rows-img.rows/5;
+		}
+ 		//  This Part of code was used to detect and print contours in an image.
+		// 	This code is commented to show the flow of code.
+
+		findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
+		Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );
+  	for( int i = 0; i< contours.size(); i++ )
+     {
+       Scalar color = Scalar( 0, 255, 0 );
+       drawContours( drawing, contours, i, color, 2, 8, hierarchy, 0, Point() );
+     }
+		 for(size_t i=0; i<contours.size(); i++){
+		 cout<<contours[i]<<'\n';
+	 }
+	 Mat connect;
+
+	 for(int i=0; i<contours.size(); i++ ){
+		 int flag=0;
+		 for(int j=0; j<contours[i].size(); j++){
+			 if(contours[i][j].x-2>origin.x or contours[i][j].x==1 or contours[i][j].x+1==img.cols ){//contours[i][j].y<origin.y  ){
+				// cout<<"This is the x coordinate of the contour points:  "<<contours[i][j].x<<'\n';
+				//  cout<<"This is the y coordinate of the contour points:  "<<contours[i][j].y<<'\n';
+				//  cout<< "This is the y coordinate of the origin point : "<<origin.y<<'\n';
+				 //  cout<<"This is the x coordinate of the origin point :  "<<origin.x<<'\n';
+				 flag=1;
+				 break;
+			 }
+		 }
+		 if(flag==0 ){
+			 Rect boundRect= boundingRect( Mat(contours[i]) );
+			 cout<<"This is the hierarchy matrix"<<hierarchy[i]<<'\n';
+			 Scalar color= Scalar(0,255,0);
+			 rectangle( img1, boundRect.tl(), boundRect.br(), color, 1, 8, 0 );
+		 }
+	 }
+
+	 for(int i=0; i<contours.size(); i++ ){
+		 int flag=0;
+		 for(int j=0; j<contours[i].size(); j++){
+			 if(contours[i][j].y+2<origin.y or contours[i][j].y==1 or contours[i][j].y+1==img.rows ){//contours[i][j].y<origin.y  ){
+				 //cout<<"This is the x coordinate of the contour points:  "<<contours[i][j].x<<'\n';
+				 //cout<<"This is the y coordinate of the contour points:  "<<contours[i][j].y<<'\n';
+				//  cout<< "This is the y coordinate of the origin point : "<<origin.y<<'\n';
+				 //  cout<<"This is the x coordinate of the origin point :  "<<origin.x<<'\n';
+				 flag=1;
+				 break;
+			 }
+		 }
+		 if(flag==0 ){
+
+			 Rect boundRect= boundingRect( Mat(contours[i]) );
+			 cout<<"This is the hierarchy matrix"<<hierarchy[i]<<'\n';
+
+			 Scalar color= Scalar(0,255,0);
+			 rectangle( img1, boundRect.tl(), boundRect.br(), color, 1 );
+		 }
+	 }
+
+	imshow("Contours", drawing);
+	imshow("Original", grayimg);
+	imshow("Canny", canny_output);
+	imshow("Output Image", img1);
+	waitKey(0);
+	return 0;
+}