multipleObjectTracking.cpp

#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 = 150;
//minimum and maximum object area
const int MIN_OBJECT_AREA = 0.5 * 0.5;
const int MAX_OBJECT_AREA = 20 * 20;
//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_ELLIPSE, Size( 2, 2 ) );
	//dilate with larger element so make sure object is nicely visible
	Mat dilateElement = getStructuringElement( MORPH_ELLIPSE, Size( 6, 6 ) );

	erode( thresh, thresh, erodeElement );
	erode( thresh, thresh, erodeElement );

	dilate( thresh, thresh, dilateElement );
	dilate( thresh, thresh, dilateElement );
}

int 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 );
	}
	return objects.size();
}

int 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 );
	}
	return objects.size();
}

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 sourceFeed;
	Mat cameraFeed;
	Mat threshold;
	Rect crop( 70, 0, 500, 480 );
	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)
	const auto CAMERA_ID = 1;

	capture.open( CAMERA_ID );
	//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( sourceFeed );

		if( !sourceFeed.data ) {
			sourceFeed = imread( "kugle.jpg" );;
			cameraFeed = sourceFeed;
		} else
			cameraFeed = sourceFeed( crop );

		src = cameraFeed;

		//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 );
			//createTrackbar("Crop Width", windowName, 0, FRAME_WIDTH);
			//createTrackbar("Crop Height", windowName, 0, FRAME_HEIGHT);
			/// Show the image
			trackFilteredObject( threshold, HSV, cameraFeed );
		} else {
			//create some temp fruit objects so that
			//we can use their member functions/information
			Object black( "black" ), red( "red" ), green( "green" ), yellow( "yellow" );

			//first find black objects
			inRange( HSV, black.getHSVmin(), black.getHSVmax(), threshold );
			morphOps( threshold );
			auto black_count = trackFilteredObject( black, threshold, HSV, cameraFeed );
			//then reds
			inRange( HSV, red.getHSVmin(), red.getHSVmax(), threshold );
			morphOps( threshold );
			auto red_count = trackFilteredObject( red, threshold, HSV, cameraFeed );
			//then greens
			inRange( HSV, green.getHSVmin(), green.getHSVmax(), threshold );
			morphOps( threshold );
			auto green_count = trackFilteredObject( green, threshold, HSV, cameraFeed );
			//then yellow
			inRange( HSV, yellow.getHSVmin(), yellow.getHSVmax(), threshold );
			morphOps( threshold );
			auto yellow_count = trackFilteredObject( yellow, threshold, HSV, cameraFeed );

			std::cout << "Black: " << black_count << " Red: " << red_count << " Green: " << green_count
					<< " Yellow: " << yellow_count << std::endl;

		}
		//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( 100 );
	}
	return 0;
}