add close feature
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ff44b1eb13
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1 changed files with 35 additions and 16 deletions
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@ -14,7 +14,7 @@ using namespace std;
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class Traite_image {
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public:
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const static int SENSITIVITY_VALUE = 40;
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const static int BLUR_SIZE = 10;
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const static int BLUR_SIZE = 15;
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Mat prev;
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@ -78,7 +78,7 @@ class Traite_image {
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searchForMovement(prev_cropped, next_stab_cropped, output);
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pub_img.publish(cv_bridge::CvImage(msg->header, "mono8", output).toImageMsg());
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pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
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// bridge_input is handled by a smart-pointer. No explicit delete needed.
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//droneTracking(Rect(Point(0,0), output.size()));
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@ -138,8 +138,8 @@ class Traite_image {
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cur.copyTo(output);
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cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
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cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
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GaussianBlur(prev_grey, prev_grey, Size(15,15), 3.0);
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GaussianBlur(cur_grey, cur_grey, Size(15,15), 3.0);
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GaussianBlur(prev_grey, prev_grey, Size(BLUR_SIZE,BLUR_SIZE), 3.0);
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GaussianBlur(cur_grey, cur_grey, Size(BLUR_SIZE,BLUR_SIZE), 3.0);
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//blur(prev_grey, prev_grey, Size(BLUR_SIZE, BLUR_SIZE));
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//blur(cur_grey, cur_grey, Size(BLUR_SIZE, BLUR_SIZE));
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@ -149,15 +149,30 @@ class Traite_image {
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// threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY);
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// // Blur to eliminate noise
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// blur(thres, thres, Size(BLUR_SIZE, BLUR_SIZE));
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// threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY);
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thres.copyTo(output);
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threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY);
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//~ int dilation_size = 2;
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//~ Mat element = getStructuringElement( MORPH_ELLIPSE,
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//~ Size( 2*dilation_size + 1, 2*dilation_size+1 ),
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//~ Point( dilation_size, dilation_size ) );
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//~ // Apply the dilation operation
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//~ Mat dilated_thres;
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//~ dilate(thres, dilated_thres, element );
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//~
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//~ dilated_thres.copyTo(output);
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Mat closed_thres;
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Mat structuringElement = getStructuringElement(MORPH_ELLIPSE, Size(40, 40));
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morphologyEx( thres, closed_thres, MORPH_CLOSE, structuringElement );
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//closed_thres.copyTo(output);
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//notice how we use the '&' operator for objectDetected and output. This is because we wish
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//to take the values passed into the function and manipulate them, rather than just working with a copy.
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//eg. we draw to the output to be displayed in the main() function.
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bool objectDetected = false;
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Mat temp;
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thres.copyTo(temp);
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closed_thres.copyTo(temp);
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//these two vectors needed for output of findContours
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vector< vector<Point> > contours;
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vector<Vec4i> hierarchy;
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@ -172,23 +187,27 @@ class Traite_image {
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if(objectDetected){
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//the largest contour is found at the end of the contours vector
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//we will simply assume that the biggest contour is the object we are looking for.
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vector< vector<Point> > largestContourVec;
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largestContourVec.push_back(contours.at(contours.size()-1));
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//vector< vector<Point> > largestContourVec;
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//largestContourVec.push_back(contours.at(contours.size()-1));
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//make a bounding rectangle around the largest contour then find its centroid
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//this will be the object's final estimated position.
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objectBoundingRectangle = boundingRect(largestContourVec.at(0));
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for(int i=0; i<contours.size();i++)
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{
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objectBoundingRectangle = boundingRect(contours[i]);
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rectangle(output, objectBoundingRectangle, Scalar(0, 255, 0), 2);
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}
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}
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//make some temp x and y variables so we dont have to type out so much
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int x = objectBoundingRectangle.x;
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int y = objectBoundingRectangle.y;
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int width = objectBoundingRectangle.width;
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int height = objectBoundingRectangle.height;
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//~ int x = objectBoundingRectangle.x;
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//~ int y = objectBoundingRectangle.y;
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//~ int width = objectBoundingRectangle.width;
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//~ int height = objectBoundingRectangle.height;
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//draw a rectangle around the object
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rectangle(output, Point(x,y), Point(x+width, y+height), Scalar(0, 255, 0), 2);
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//rectangle(output, Point(x,y), Point(x+width, y+height), Scalar(0, 255, 0), 2);
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//write the position of the object to the screen
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putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2);
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//putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2);
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}
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inline bool isFlowCorrect(Point2f u)
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