opencvmultitracking.zip_OpenCV3 识别_opencv MultiTracker_opencv 多目

#include <sstream> #include <string> #include <iostream> #include <opencv\highgui.h> #include <opencv\cv.h> #include <cv.h> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/imgproc/imgproc.hpp> #include <opencv2/core/core.hpp> #include <opencv2/opencv.hpp> #include <iostream> #include "imgproc/imgproc.hpp" #include "video/tracking.hpp" #include "core/core.hpp" #include "cxcore.h" #include <string> #include <vector> #include <sstream> #include <highgui.h> #include <sstream> #include <string> #include <iostream> #include <opencv\highgui.h> #include <opencv\cv.h> using namespace std; using namespace cv; #include <sstream> #include <string> #include <iostream> #include <vector> #include "Fruit.h" //initial min and max HSV filter values. //these will be changed using trackbars int H_MIN = 0; int H_MAX = 256; int S_MIN = 0; int S_MAX = 256; int V_MIN = 0; int V_MAX = 256; //default capture width and height const int FRAME_WIDTH = 640; const int FRAME_HEIGHT = 480; //max number of objects to be detected in frame const int MAX_NUM_OBJECTS = 50; //minimum and maximum object area const int MIN_OBJECT_AREA = 20 * 20; const int MAX_OBJECT_AREA = FRAME_HEIGHT*FRAME_WIDTH / 1.5; //names that will appear at the top of each window const string windowName = "Original Image"; const string windowName1 = "HSV Image"; const string windowName2 = "Thresholded Image"; const string windowName3 = "After Morphological Operations"; const string trackbarWindowName = "Trackbars"; void on_trackbar(int, void*) {//This function gets called whenever a // trackbar position is changed } string intToString(int number){ std::stringstream ss; ss << number; return ss.str(); } void createTrackbars(){ //create window for trackbars namedWindow(trackbarWindowName, 0); //create memory to store trackbar name on window char TrackbarName[50]; sprintf(TrackbarName, "H_MIN", H_MIN); sprintf(TrackbarName, "H_MAX", H_MAX); sprintf(TrackbarName, "S_MIN", S_MIN); sprintf(TrackbarName, "S_MAX", S_MAX); sprintf(TrackbarName, "V_MIN", V_MIN); sprintf(TrackbarName, "V_MAX", V_MAX); //create trackbars and insert them into window //3 parameters are: the address of the variable that is changing when the trackbar is moved(eg.H_LOW), //the max value the trackbar can move (eg. H_HIGH), //and the function that is called whenever the trackbar is moved(eg. on_trackbar) // ----> ----> ----> createTrackbar("H_MIN", trackbarWindowName, &H_MIN, H_MAX, on_trackbar); createTrackbar("H_MAX", trackbarWindowName, &H_MAX, H_MAX, on_trackbar); createTrackbar("S_MIN", trackbarWindowName, &S_MIN, S_MAX, on_trackbar); createTrackbar("S_MAX", trackbarWindowName, &S_MAX, S_MAX, on_trackbar); createTrackbar("V_MIN", trackbarWindowName, &V_MIN, V_MAX, on_trackbar); createTrackbar("V_MAX", trackbarWindowName, &V_MAX, V_MAX, on_trackbar); } void drawObject(vector<Fruit> theFruits, Mat &frame){ for (int i = 0; i<theFruits.size(); i++){ cv::circle(frame, cv::Point(theFruits.at(i).getXPos(), theFruits.at(i).getYPos()), 10, cv::Scalar(0, 0, 255)); cv::putText(frame, intToString(theFruits.at(i).getXPos()) + " , " + intToString(theFruits.at(i).getYPos()), cv::Point(theFruits.at(i).getXPos(), theFruits.at(i).getYPos() + 20), 1, 1, Scalar(0, 255, 0)); cv::putText(frame, theFruits.at(i).getType(), cv::Point(theFruits.at(i).getXPos(), theFruits.at(i).getYPos() - 30), 1, 2, theFruits.at(i).getColour()); } } void morphOps(Mat &thresh){ //create structuring element that will be used to "dilate" and "erode" image. //the element chosen here is a 3px by 3px rectangle Mat erodeElement = getStructuringElement(MORPH_RECT, Size(3, 3)); //dilate with larger element so make sure object is nicely visible Mat dilateElement = getStructuringElement(MORPH_RECT, Size(8, 8)); erode(thresh, thresh, erodeElement); erode(thresh, thresh, erodeElement); dilate(thresh, thresh, dilateElement); dilate(thresh, thresh, dilateElement); } void trackFilteredObject(Mat threshold, Mat HSV, Mat &cameraFeed){ vector <Fruit> apples; Mat temp; threshold.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); //use moments method to find our filtered object double refArea = 0; bool objectFound = false; if (hierarchy.size() > 0) { int numObjects = hierarchy.size(); //if number of objects greater than MAX_NUM_OBJECTS we have a noisy filter if (numObjects<MAX_NUM_OBJECTS){ for (int index = 0; index >= 0; index = hierarchy[index][0]) { Moments moment = moments((cv::Mat)contours[index]); double area = moment.m00; //if the area is less than 20 px by 20px then it is probably just noise //if the area is the same as the 3/2 of the image size, probably just a bad filter //we only want the object with the largest area so we safe a reference area each //iteration and compare it to the area in the next iteration. if (area>MIN_OBJECT_AREA){ Fruit apple; apple.setXPos(moment.m10 / area); apple.setYPos(moment.m01 / area); apples.push_back(apple); objectFound = true; } else objectFound = false; } //let user know you found an object if (objectFound == true){ //draw object location on screen drawObject(apples, cameraFeed); } } else putText(cameraFeed, "TOO MUCH NOISE! ADJUST FILTER", Point(0, 50), 1, 2, Scalar(0, 0, 255), 2); } } void trackFilteredObject(Fruit theFruit, Mat threshold, Mat HSV, Mat &cameraFeed){ vector <Fruit> apples; Mat temp; threshold.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); //use moments method to find our filtered object double refArea = 0; bool objectFound = false; if (hierarchy.size() > 0) { int numObjects = hierarchy.size(); //if number of objects greater than MAX_NUM_OBJECTS we have a noisy filter if (numObjects<MAX_NUM_OBJECTS){ for (int index = 0; index >= 0; index = hierarchy[index][0]) { Moments moment = moments((cv::Mat)contours[index]); double area = moment.m00; //if the area is less than 20 px by 20px then it is probably just noise //if the area is the same as the 3/2 of the image size, probably just a bad filter //we only want the object with the largest area so we safe a reference area each //iteration and compare it to the area in the next iteration. if (area>MIN_OBJECT_AREA){ Fruit apple; apple.setXPos(moment.m10 / area); apple.setYPos(moment.m01 / area); apple.setType(theFruit.getType()); apple.setColour(theFruit.getColour()); apples.push_back(apple); objectFound = true; } else objectFound = false; } //let user know you found an object if (objectFound == true){ //draw object location on screen drawObject(apples, cameraFeed); } } else putText(cameraFeed, "TOO MUCH NOISE! ADJUST FILTER", Point(0, 50), 1, 2, Scalar(0, 0, 255), 2); } } int main(int argc, char* argv[]) { //if we would like to calibrate our filter values, set to true. bool calibrationMode = false; //Matrix to store each frame of the webcam feed Mat cameraFeed; Mat threshold; Mat HSV; if (calibrationMode){ //create slider bars for HSV filtering createTrackbars(); } //vid