eyetrack.cpp

#include "opencv2/objdetect.hpp" 
#include "opencv2/highgui.hpp" 
#include "opencv2/imgproc.hpp" 
#include <iostream> 



using namespace std;

using namespace cv;


// Function for Face Detection 

void detectAndDraw(Mat& img, CascadeClassifier& cascade,

	CascadeClassifier& nestedCascade, double scale);
string cascadeName, nestedCascadeName;



int main(int argc, const char** argv)
{

	// VideoCapture class for playing video for which faces to be detected 

	VideoCapture capture;

	Mat frame, image;



	// PreDefined trained XML classifiers with facial features 

	CascadeClassifier cascade, nestedCascade;

	double scale = 3;



	// Load classifiers from "opencv/data/haarcascades" directory  

	nestedCascade.load("C:\\Users\\India\\Documents\\opencv\\sources\\data\\haarcascades\\haarcascade_eye_tree_eyeglasses.xml");



	// Change path before execution  

	cascade.load("C:\\Users\\India\\Documents\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalcatface.xml");



	// Start Video..1) 0 for WebCam 2) "Path to Video" for a Local Video 

	capture.open(0);

	if (capture.isOpened())

	{

		// Capture frames from video and detect faces 

		cout << "Face Detection Started...." << endl;

		while (waitKey(35))

		{

			capture >> frame;

			//if (frame.empty())

			//	break;

			Mat frame1 = frame.clone();

			detectAndDraw(frame1, cascade, nestedCascade, scale);

			//char c = (char)waitKey(2);



			/* Press q to exit from window

			if (c == 27 || c == 'q' || c == 'Q')

				break;
				*/
		}

	}

	else

		cout << "Could not Open Camera";

	return 0;
}



void detectAndDraw(Mat& img, CascadeClassifier& cascade,

	CascadeClassifier& nestedCascade,

	double scale)
{

	vector<Rect> faces, faces2;

	Mat gray, smallImg;



	cvtColor(img, gray, COLOR_BGR2GRAY); // Convert to Gray Scale 

	double fx = 1 / scale;



	// Resize the Grayscale Image  

	resize(gray, smallImg, Size(), fx, fx, INTER_LINEAR);

	equalizeHist(smallImg, smallImg);



	// Detect faces of different sizes using cascade classifier  

	cascade.detectMultiScale(smallImg, faces, 1.1,

		2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30));



	// Draw circles around the faces 

	for (size_t i = 0; i < faces.size(); i++)

	{

		Rect r = faces[i];

		Mat smallImgROI;

		vector<Rect> nestedObjects;

		Point center;

		Scalar color = Scalar(255, 0, 0); // Color for Drawing tool 

		int radius;



		double aspect_ratio = (double)r.width / r.height;

		if (0.75 < aspect_ratio && aspect_ratio < 1.3)

		{

			center.x = cvRound((r.x + r.width*0.5)*scale);

			center.y = cvRound((r.y + r.height*0.5)*scale);

			radius = cvRound((r.width + r.height)*0.25*scale);

			circle(img, center, radius, color, 3, 8, 0);

		}

		else

			rectangle(img, r, color, 3, 8, 0);

		if (nestedCascade.empty())

			continue;

		smallImgROI = smallImg(r);



		// Detection of eyes int the input image 

		nestedCascade.detectMultiScale(smallImgROI, nestedObjects, 1.1, 2,

			0 | CASCADE_SCALE_IMAGE, Size(30, 30));



		// Draw circles around eyes 

		for (size_t j = 0; j < nestedObjects.size(); j++)

		{

			Rect nr = nestedObjects[j];

			center.x = cvRound((r.x + nr.x + nr.width*0.5)*scale);

			center.y = cvRound((r.y + nr.y + nr.height*0.5)*scale);

			radius = cvRound((nr.width + nr.height)*0.25*scale);

			circle(img, center, radius, color, 3, 8, 0);

		}

	}



	// Show Processed Image with detected faces 

	imshow("Face Detection", img);
}