lhark/papillon
1
0
Fork 0
Code Issues Pull requests Releases Wiki Activity

changed detection to opt flow

Browse source
This commit is contained in:
samilyjcc 2016-06-01 17:09:28 +02:00
parent d1687fb7cb
commit ce831fb167
1 changed files with 65 additions and 3 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

68
src/papillon.cpp
View file

@ -3,6 +3,7 @@
#include <cv_bridge/cv_bridge.h>
#include <sensor_msgs/image_encodings.h>
#include <geometry_msgs/Twist.h>
#include <typeinfo>
#include <opencv/cv.h>
@ -13,8 +14,8 @@ using namespace std;
class Traite_image {
public:
const static int SENSITIVITY_VALUE = 30;
const static int BLUR_SIZE = 10;
const static int SENSITIVITY_VALUE = 10;
const static int BLUR_SIZE = 5;
Mat prev;
@ -70,7 +71,7 @@ class Traite_image {
Rect myROI(next_stab.size().width/8, next_stab.size().height/8, next_stab.size().width*3/4, next_stab.size().height*3/4);
Mat next_stab_cropped = next_stab(myROI);
Mat prev_cropped = prev(myROI);
searchForMovement(prev_cropped, next_stab_cropped, output);
searchForMovementOptFlow(prev_cropped, next_stab_cropped, output);
pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
@ -180,6 +181,67 @@ class Traite_image {
//write the position of the object to the screen
putText(output,"Tracking object at (" + intToString(x)+","+intToString(y)+")",Point(x,y),1,1,Scalar(255,0,0),2);
}
void searchForMovementOptFlow(Mat prev, Mat cur, Mat &output){
Mat cur_grey, prev_grey;
cur.copyTo(output);
cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
Mat flow;
calcOpticalFlowFarneback(prev_grey, cur_grey, flow, 0.5, 3, 15, 3, 5, 1.2, 0);
vector<Mat> flow_coord(2);
Mat flow_norm, angle;
split(flow, flow_coord);
cartToPolar(flow_coord[0], flow_coord[1], flow_norm, angle);
//threshold(flow_norm, flow_norm, SENSITIVITY_VALUE, 255, THRESH_BINARY);
// Blur to eliminate noise
blur(flow_norm, flow_norm, Size(BLUR_SIZE, BLUR_SIZE));
threshold(flow_norm, flow_norm, SENSITIVITY_VALUE, 255, THRESH_BINARY);
flow_norm.convertTo(flow_norm, CV_8U);
bool objectDetected = false;
Mat temp;
flow_norm.copyTo(temp);
//these two vectors needed for output of findContours
vector< vector<Point> > contours;
vector<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
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;
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 estimated position.
objectBoundingRectangle = boundingRect(largestContourVec.at(0));
}
//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), 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,Scalar(255,0,0),2);
}
void get_norm(Mat coord, Mat &norm)
{
//for(i=0; i<
}
inline bool isFlowCorrect(Point2f u)
{