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optimise-f
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40f52fbf03 | ||
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3 changed files with 151 additions and 125 deletions
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@ -23,6 +23,7 @@ target_link_libraries(papillon ${catkin_LIBRARIES})
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set_property (TARGET papillon APPEND PROPERTY INCLUDE_DIRECTORIES ${OpenCV_INCLUDE_DIRS})
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set_property (TARGET papillon APPEND PROPERTY INCLUDE_DIRECTORIES ${OpenCV_INCLUDE_DIRS})
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set_property (TARGET papillon APPEND PROPERTY INCLUDE_DIRECTORIES ${catkin_INCLUDE_DIRS})
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set_property (TARGET papillon APPEND PROPERTY INCLUDE_DIRECTORIES ${catkin_INCLUDE_DIRS})
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set_property (TARGET papillon APPEND PROPERTY LINK_LIBRARIES ${OpenCV_LIBRARIES})
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set_property (TARGET papillon APPEND PROPERTY LINK_LIBRARIES ${OpenCV_LIBRARIES})
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set( CMAKE_EXPORT_COMPILE_COMMANDS 1 )
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install(TARGETS papillon DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION})
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install(TARGETS papillon DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION})
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1
commands
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1
commands
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@ -0,0 +1 @@
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catkin_make -DCMAKE_BUILD_TYPE=Debug
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166
src/papillon.cpp
166
src/papillon.cpp
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@ -3,6 +3,7 @@
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#include <cv_bridge/cv_bridge.h>
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#include <cv_bridge/cv_bridge.h>
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#include <sensor_msgs/image_encodings.h>
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#include <sensor_msgs/image_encodings.h>
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#include <geometry_msgs/Twist.h>
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#include <geometry_msgs/Twist.h>
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#include <typeinfo>
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#include <opencv/cv.h>
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#include <opencv/cv.h>
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@ -13,13 +14,26 @@ using namespace std;
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class Traite_image {
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class Traite_image {
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public:
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public:
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const static int SENSITIVITY_VALUE = 30;
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const static int THRESHOLD_DETECT_SENSITIVITY = 10;
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const static int BLUR_SIZE = 10;
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const static int BLUR_SIZE = 5;
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const static int THRESHOLD_MOV = 5;
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constexpr static float MOVEMENT_THRES = 0.05;
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constexpr static float FLOW_MIN_QUAL = 0.01;
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const static int FLOW_MIN_DIST = 20;
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Mat prev;
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Mat prev;
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Mat last_T;
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// Stabilisation transformation matrices
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Mat T, last_T;
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bool first = true;
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bool first = true;
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// Features vectors
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vector <Point2f> prev_ftr, cur_ftr;
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// Downsize factor
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int resize_f = 1;
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int resize_f = 1;
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int theObject[2] = {0,0};
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int theObject[2] = {0,0};
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@ -66,11 +80,14 @@ class Traite_image {
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}
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}
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Mat next_stab;
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Mat next_stab;
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stabiliseImg(prev, next, next_stab);
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trackFeatures(prev, next);
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Rect myROI(next_stab.size().width/8, next_stab.size().height/8, next_stab.size().width*3/4, next_stab.size().height*3/4);
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stabiliseImg(next, next_stab);
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Mat next_stab_cropped = next_stab(myROI);
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trackingOptFlow(prev, next_stab, next_stab);
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Mat prev_cropped = prev(myROI);
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Mat next_stab2;
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searchForMovement(prev_cropped, next_stab_cropped, output);
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trackFeatures(prev, next);
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stabiliseImg(next, next_stab2);
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trackingOptFlow(prev, next_stab2, output);
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//searchForMovementOptFlow(prev_cropped, next_stab_cropped, output);
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pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
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pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
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@ -83,42 +100,38 @@ class Traite_image {
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prev = next.clone();
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prev = next.clone();
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}
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}
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//int to string helper function
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string intToString(int number){
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//this function has a number input and string output
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void trackFeatures(Mat prev, Mat cur) {
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std::stringstream ss;
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ss << number;
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return ss.str();
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}
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void stabiliseImg(Mat prev, Mat cur, Mat &output){
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Mat cur_grey, prev_grey;
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Mat cur_grey, prev_grey;
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cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
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cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
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cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
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cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
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// vector from prev to cur
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// vector from prev to cur
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vector <Point2f> prev_corner, cur_corner;
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vector <Point2f> prev_corner, cur_corner;
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vector <Point2f> prev_corner2, cur_corner2;
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vector <uchar> status;
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vector <uchar> status;
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vector <float> err;
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vector <float> err;
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goodFeaturesToTrack(prev_grey, prev_corner, 200, 0.01, 30);
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goodFeaturesToTrack(prev_grey, prev_corner, 200, FLOW_MIN_QUAL, FLOW_MIN_DIST);
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calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err);
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calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err);
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// weed out bad matches
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// weed out bad matches
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prev_ftr.resize(0);
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cur_ftr.resize(0);
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for(size_t i=0; i < status.size(); i++) {
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for(size_t i=0; i < status.size(); i++) {
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if(status[i]) {
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if(status[i]) {
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prev_corner2.push_back(prev_corner[i]);
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prev_ftr.push_back(prev_corner[i]);
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cur_corner2.push_back(cur_corner[i]);
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cur_ftr.push_back(cur_corner[i]);
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}
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}
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}
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}
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}
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Mat T = estimateRigidTransform(prev_corner2, cur_corner2, true); // false = rigid transform, no scaling/shearing
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if(T.data == NULL) {
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void stabiliseImg(Mat cur, Mat &output){
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T = estimateRigidTransform(prev_ftr, cur_ftr, true); // false = rigid transform, no scaling/shearing
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if(T.data == NULL)
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last_T.copyTo(T);
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last_T.copyTo(T);
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}
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else
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T.copyTo(last_T);
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T.copyTo(last_T);
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Mat cur2;
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Mat cur2;
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@ -128,58 +141,59 @@ class Traite_image {
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cur2.copyTo(output);
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cur2.copyTo(output);
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}
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}
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void searchForMovement(Mat prev, Mat cur, Mat &output){
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Mat cur_grey, prev_grey;
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void warpPoints(vector<Point2f> p, vector<Point2f> &p_warp, Mat T, bool invert=false) {
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Mat H;
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if(invert)
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invertAffineTransform(T, H);
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p_warp.clear();
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for(size_t i=0; i < p.size(); ++i) {
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Mat src(3/*rows*/,1 /* cols */,CV_64F);
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src.at<double>(0,0)=p[i].x;
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src.at<double>(1,0)=p[i].y;
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src.at<double>(2,0)=1.0;
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Mat dst = H*src; //USE MATRIX ALGEBRA
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p_warp.push_back(Point2f(dst.at<double>(0,0),dst.at<double>(1,0)));
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}
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}
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void trackingOptFlow(Mat prev, Mat cur, Mat &output) {
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cur.copyTo(output);
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cur.copyTo(output);
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cvtColor(prev, prev_grey, COLOR_BGR2GRAY);
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vector <Point2f> cur_ftr_stab;
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cvtColor(cur, cur_grey, COLOR_BGR2GRAY);
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// Subtract the 2 last frames and threshold them
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//T = estimateRigidTransform(prev_ftr, cur_ftr, true); // false = rigid transform, no scaling/shearing
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Mat thres;
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//if(T.data == NULL)
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absdiff(prev_grey,cur_grey,thres);
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// last_T.copyTo(T);
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threshold(thres, thres, SENSITIVITY_VALUE, 255, THRESH_BINARY);
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//else
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// Blur to eliminate noise
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// T.copyTo(last_T);
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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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//notice how we use the '&' operator for objectDetected and output. This is because we wish
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warpPoints(cur_ftr, cur_ftr_stab, T, true);
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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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//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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//find contours of filtered image using openCV findContours function
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//findContours(temp,contours,hierarchy,CV_RETR_CCOMP,CV_CHAIN_APPROX_SIMPLE );// retrieves all contours
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findContours(temp,contours,hierarchy,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE );// retrieves external contours
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//if contours vector is not empty, we have found some objects
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vector <Point2f> objects;
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if(contours.size()>0)objectDetected=true;
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vector <float> flow_norm;
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else objectDetected = false;
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for(size_t i=0; i < prev_ftr.size(); ++i) {
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flow_norm.push_back(norm(prev_ftr[i] - cur_ftr_stab[i]) / prev.size().height);
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if(objectDetected){
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line(output, prev_ftr[i], cur_ftr[i], Scalar(200,0,0),1);
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//the largest contour is found at the end of the contours vector
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line(output, prev_ftr[i], cur_ftr_stab[i], Scalar(0,200,0),1);
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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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//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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}
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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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//draw a rectangle around the object
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for(size_t i=0; i < flow_norm.size(); ++i) {
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rectangle(output, Point(x,y), Point(x+width, y+height), Scalar(0, 255, 0), 2);
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if(flow_norm[i] > MOVEMENT_THRES) {
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objects.push_back(cur_ftr_stab[i]);
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//write the position of the object to the screen
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prev_ftr.erase(prev_ftr.begin() + i);
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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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cur_ftr.erase(cur_ftr.begin() + i);
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}
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}
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}
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for(size_t i=0; i < objects.size(); ++i) {
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circle(output, objects[i], 5, Scalar(0, 200, 0), 1);
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}
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}
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inline bool isFlowCorrect(Point2f u)
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inline bool isFlowCorrect(Point2f u)
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{
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{
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@ -194,17 +208,27 @@ class Traite_image {
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geometry_msgs::Twist twist = geometry_msgs::Twist();
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geometry_msgs::Twist twist = geometry_msgs::Twist();
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if(centre_rect.x < centre_image.x)
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if(centre_rect.x < centre_image.x-THRESHOLD_MOV)
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{
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{
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twist.angular.z = 0.2;
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twist.angular.z = 0.2;
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}
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}
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else if(centre_rect.x > centre_image.x)
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else if(centre_rect.x > centre_image.x+THRESHOLD_MOV)
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{
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{
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twist.angular.z = -0.2;
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twist.angular.z = -0.2;
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}
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}
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pub_cmd.publish(twist);
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pub_cmd.publish(twist);
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}
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}
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//int to string helper function
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string intToString(int number){
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//this function has a number input and string output
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std::stringstream ss;
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ss << number;
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return ss.str();
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}
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};
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};
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