cleaned all comments

src/papillon.cpp

@@ -56,17 +56,16 @@ class Traite_image {
 				return;
 			}
 
-			//cv::Mat& input  = const_cast<cv::Mat&>(bridge_input->image);
 			const cv::Mat& input = bridge_input->image;
 			cv::Mat next;
 			resize(input, next, cv::Size(input.size().width/resize_f, input.size().height/resize_f));
-			cv::Mat output;// = input.clone(); //   (input.rows, input.cols, CV_32FC2);
+			cv::Mat output;
 			if (first) {
 				for (int i = 0; i < NB_FRAME_DROP; ++i) {
 					prevs.push_back(next.clone());
 				}
 				first = false;
-				ROS_INFO("first done");
+				ROS_INFO("Ready");
 			}
 
 			cv::Mat next_stab;
@@ -85,22 +84,11 @@ class Traite_image {
 
 			pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
 			pub_thres.publish(cv_bridge::CvImage(msg->header, "mono8", closed_thres).toImageMsg());
-			// bridge_input is handled by a smart-pointer. No explicit delete needed.
 
 			prevs.pop_back();
 			prevs.insert(prevs.begin(), next.clone());
 		}
-
+		
-
-		//int to string helper function
-		string intToString(int number){
-			//this function has a number input and string output
-			std::stringstream ss;
-			ss << number;
-			return ss.str();
-		}
-
-
 		void stabiliseImg(cv::Mat prev, cv::Mat cur, cv::Mat &output){
 			cv::Mat cur_grey, prev_grey;
 			cv::cvtColor(cur, cur_grey, cv::COLOR_BGR2GRAY);
@@ -115,7 +103,7 @@ class Traite_image {
 			cv::goodFeaturesToTrack(prev_grey, prev_corner, 200, 0.01, 30);
 			cv::calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err);
 
-			// weed out bad cv::Matches
+			// weed out bad matches
 			for(size_t i=0; i < status.size(); i++) {
 				if(status[i]) {
 					prev_corner2.push_back(prev_corner[i]);
@@ -144,64 +132,40 @@ class Traite_image {
 			cv::cvtColor(cur, cur_grey, cv::COLOR_BGR2GRAY);
 			cv::GaussianBlur(prev_grey, prev_grey, cv::Size(BLUR_Size,BLUR_Size), 3.0);
 			cv::GaussianBlur(cur_grey, cur_grey, cv::Size(BLUR_Size,BLUR_Size), 3.0);
-			//blur(prev_grey, prev_grey, cv::Size(BLUR_Size, BLUR_Size));
-			//blur(cur_grey, cur_grey, cv::Size(BLUR_Size, BLUR_Size));
 
 			// Subtract the 2 last frames and threshold them
 			cv::Mat thres;
 			cv::absdiff(prev_grey,cur_grey,thres);
-			// threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY);
-			// // Blur to eliminate noise
-			// blur(thres, thres, cv::Size(BLUR_Size, BLUR_Size));
 
 			cv::Mat element = getStructuringElement( cv::MORPH_ELLIPSE,
                                    cv::Size( 2*ERODE_SIZE + 1, 2*ERODE_SIZE+1 ),
                                    cv::Point( ERODE_SIZE, ERODE_SIZE ) );
-			// Apply the dilation operation
+			// Apply the erode operation
 			cv::erode(thres, thres, element );
 
-			thres.copyTo(out2);
-
-
 			cv::threshold(thres, thres, SENSITIVITY_VALUE, 255, cv::THRESH_BINARY);
+			
+			// Intermediate output
+			thres.copyTo(out2);
 
 			cv::Mat closed_thres;
 			cv::Mat structuringElement = getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(CLOSE_SIZE, CLOSE_SIZE));
 			cv::morphologyEx( thres, closed_thres, cv::MORPH_CLOSE, structuringElement );
-			// dilated_thres.copyTo(output);
 
-
-			//closed_thres.copyTo(output);
-
-			//notice how we use the '&' operator for objectDetected and output. This is because we wish
-			//to take the values passed into the function and manipulate them, rather than just working with a copy.
-			//eg. we draw to the output to be displayed in the main() function.
 			bool objectDetected = false;
 			cv::Mat temp;
 			closed_thres.copyTo(temp);
-			//these two vectors needed for output of findContours
 			vector< vector<cv::Point> > contours;
 			vector<cv::Vec4i> hierarchy;
 			//find contours of filtered image using openCV findContours function
-			//findContours(temp,contours,hierarchy,CV_RETR_CCOMP,CV_CHAIN_APPROX_SIMPLE );// retrieves all contours
 			cv::findContours(temp,contours,hierarchy,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE );// retrieves external contours
 
 			//if contours vector is not empty, we have found some objects
-			if(contours.size()>0)objectDetected=true;
+			if(contours.size()>0){
-			else objectDetected = false;
-
-			if(objectDetected){
-				//the largest contour is found at the end of the contours vector
-				//we will simply assume that the biggest contour is the object we are looking for.
-				//vector< vector<Point> > largestContourVec;
-				//largestContourVec.push_back(contours.at(contours.size()-1));
-				//make a bounding rectangle around the largest contour then find its centroid
-				//this will be the object's final esticv::Mated position.
 				vector<cv::Rect> nc_rects; // Non connected rectangles
 				for(size_t i=0; i<contours.size();i++)
 				{
 					nc_rects.push_back(cv::boundingRect(contours[i]));
-					//cv::rectangle(output, objectBoundingRectangle, cv::Scalar(0, 255, 0), 2);
 				}
 
 				vector<cv::Rect> c_rects; // Connected rectangles
@@ -211,7 +175,6 @@ class Traite_image {
 						cv::rectangle(output, rect, cv::Scalar(0, 255, 0), 2);
 
 					cv::Rect objBRect = c_rects.front();
-					//cv::rectangle(output, objBRect, cv::Scalar(0, 255, 0), 2);
 					papillon::BoundingBox bbox = papillon::BoundingBox();
 					bbox.x = objBRect.x / (float)cur.size().width;
 					bbox.y = objBRect.y / (float)cur.size().height;
@@ -220,20 +183,8 @@ class Traite_image {
 					pub_cmd.publish(bbox);
 				}
 			}
-			//make some temp x and y variables so we dont have to type out so much
-			//~ int x = objectBoundingRectangle.x;
-			//~ int y = objectBoundingRectangle.y;
-			//~ int width = objectBoundingRectangle.width;
-			//~ int height = objectBoundingRectangle.height;
-
-			//draw a rectangle around the object
-			//rectangle(output, Point(x,y), Point(x+width, y+height), cv::Scalar(0, 255, 0), 2);
-
-			//write the position of the object to the screen
-			//putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,cv::Scalar(255,0,0),2);
 		}
 
-
 		void cleanBBoxes(vector<cv::Rect> nc_rects, cv::Size img, vector<cv::Rect> &c_rects) {
 			int max = 0;
 			for (auto r : nc_rects) {
@@ -272,4 +223,4 @@ int main(int argc, char **argv)
 	ros::spin();
 
 	return 0;
-}
+}