multipleObjectTracking.cpp

//Written by  Kyle Hounslow 2013

// modified by: Ahmad Kaifi, Hassan Althobaiti

//Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software")
//, to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
//and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
//The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
//THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
//FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
//LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
//IN THE SOFTWARE.

#include <sstream>
#include <string>
#include <iostream>
#include <vector>

#include "Object.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";

//The following for canny edge detec
Mat dst, detected_edges;
Mat src, src_gray;
int edgeThresh = 1;
int lowThreshold;
int const max_lowThreshold = 100;
int ratio = 3;
int kernel_size = 3;
const char* window_name = "Edge Map";

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<Object> theObjects,Mat &frame, Mat &temp, vector< vector<Point> > contours, vector<Vec4i> hierarchy){

	for(int i =0; i<theObjects.size(); i++){
	cv::drawContours(frame,contours,i,theObjects.at(i).getColor(),3,8,hierarchy);
	cv::circle(frame,cv::Point(theObjects.at(i).getXPos(),theObjects.at(i).getYPos()),5,theObjects.at(i).getColor());
	cv::putText(frame,intToString(theObjects.at(i).getXPos())+ " , " + intToString(theObjects.at(i).getYPos()),cv::Point(theObjects.at(i).getXPos(),theObjects.at(i).getYPos()+20),1,1,theObjects.at(i).getColor());
	cv::putText(frame,theObjects.at(i).getType(),cv::Point(theObjects.at(i).getXPos(),theObjects.at(i).getYPos()-20),1,2,theObjects.at(i).getColor());
	}
}

void drawObject(vector<Object> theObjects,Mat &frame){

	for(int i =0; i<theObjects.size(); i++){

	cv::circle(frame,cv::Point(theObjects.at(i).getXPos(),theObjects.at(i).getYPos()),10,cv::Scalar(0,0,255));
	cv::putText(frame,intToString(theObjects.at(i).getXPos())+ " , " + intToString(theObjects.at(i).getYPos()),cv::Point(theObjects.at(i).getXPos(),theObjects.at(i).getYPos()+20),1,1,Scalar(0,255,0));
	cv::putText(frame,theObjects.at(i).getType(),cv::Point(theObjects.at(i).getXPos(),theObjects.at(i).getYPos()-30),1,2,theObjects.at(i).getColor());
	}
}

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 <Object> objects;
	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)
				{
					Object object;

					object.setXPos(moment.m10/area);
					object.setYPos(moment.m01/area);

					objects.push_back(object);

					objectFound = true;

				}
				else objectFound = false;
			}
			//let user know you found an object
			if(objectFound ==true)
			{
				//draw object location on screen
				drawObject(objects,cameraFeed);
			}
		}
		else putText(cameraFeed,"TOO MUCH NOISE! ADJUST FILTER",Point(0,50),1,2,Scalar(0,0,255),2);
	}
}

void trackFilteredObject(Object theObject,Mat threshold,Mat HSV, Mat &cameraFeed){

	vector <Object> objects;
	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){

					Object object;

					object.setXPos(moment.m10/area);
					object.setYPos(moment.m01/area);
					object.setType(theObject.getType());
					object.setColor(theObject.getColor());

					objects.push_back(object);

					objectFound = true;

				}else objectFound = false;
			}
			//let user know you found an object
			if(objectFound ==true){
				//draw object location on screen
				drawObject(objects,cameraFeed,temp,contours,hierarchy);}

		}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 = true;

	//Matrix to store each frame of the webcam feed
	Mat cameraFeed;
	Mat threshold;
	Mat HSV;

	if(calibrationMode){
		//create slider bars for HSV filtering
		createTrackbars();
	}
	//video capture object to acquire webcam feed
	VideoCapture capture;
	//open capture object at location zero (default location for webcam)
	capture.open(0);
	//set height and width of capture frame
	capture.set(CV_CAP_PROP_FRAME_WIDTH,FRAME_WIDTH);
	capture.set(CV_CAP_PROP_FRAME_HEIGHT,FRAME_HEIGHT);
	//start an infinite loop where webcam feed is copied to cameraFeed matrix
	//all of our operations will be performed within this loop
	waitKey(1000);
	while(1){
		//store image to matrix
		capture.read(cameraFeed);

		src = cameraFeed;

  		if( !src.data )
  		{ return -1; }

		//convert frame from BGR to HSV colorspace
		cvtColor(cameraFeed,HSV,COLOR_BGR2HSV);

		if(calibrationMode==true){

		//need to find the appropriate color range values
		// calibrationMode must be false

		//if in calibration mode, we track objects based on the HSV slider values.
			cvtColor(cameraFeed,HSV,COLOR_BGR2HSV);
			inRange(HSV,Scalar(H_MIN,S_MIN,V_MIN),Scalar(H_MAX,S_MAX,V_MAX),threshold);
			morphOps(threshold);
			imshow(windowName2,threshold);

		//the folowing for canny edge detec
			/// Create a matrix of the same type and size as src (for dst)
	  		dst.create( src.size(), src.type() );
	  		/// Convert the image to grayscale
	  		cvtColor( src, src_gray, CV_BGR2GRAY );
	  		/// Create a window
	  		namedWindow( window_name, CV_WINDOW_AUTOSIZE );
	  		/// Create a Trackbar for user to enter threshold
	  		createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold);
	  		/// Show the image
			trackFilteredObject(threshold,HSV,cameraFeed);
		}
		else{
			//create some temp fruit objects so that
			//we can use their member functions/information
			Object blue("blue"), yellow("yellow"), red("red"), green("green");

			//first find blue objects
			cvtColor(cameraFeed,HSV,COLOR_BGR2HSV);
			inRange(HSV,blue.getHSVmin(),blue.getHSVmax(),threshold);
			morphOps(threshold);
			trackFilteredObject(blue,threshold,HSV,cameraFeed);
			//then yellows
			cvtColor(cameraFeed,HSV,COLOR_BGR2HSV);
			inRange(HSV,yellow.getHSVmin(),yellow.getHSVmax(),threshold);
			morphOps(threshold);
			trackFilteredObject(yellow,threshold,HSV,cameraFeed);
			//then reds
			cvtColor(cameraFeed,HSV,COLOR_BGR2HSV);
			inRange(HSV,red.getHSVmin(),red.getHSVmax(),threshold);
			morphOps(threshold);
			trackFilteredObject(red,threshold,HSV,cameraFeed);
			//then greens
			cvtColor(cameraFeed,HSV,COLOR_BGR2HSV);
			inRange(HSV,green.getHSVmin(),green.getHSVmax(),threshold);
			morphOps(threshold);
			trackFilteredObject(green,threshold,HSV,cameraFeed);

		}
		//show frames
		//imshow(windowName2,threshold);

		imshow(windowName,cameraFeed);
		//imshow(windowName1,HSV);

		//delay 30ms so that screen can refresh.
		//image will not appear without this waitKey() command
		waitKey(30);
	}
	return 0;
}