[OpenCV C++] Program for Face Detection

This program uses the OpenCV library to detect faces in a live stream from webcam or in a video file stored in the local machine. This program detects faces in real time and tracks it. It uses pre-trained XML classifiers for the same. The classifiers used in this program have facial features trained in them. Different classifiers can be used to detect different objects.
Requirements for running the program:
1) OpenCV must be installed on the local machine.
2) Paths to the classifier XML files must be given before the execution of the program. These XML files can be found in the OpenCV directory “opencv/data/haarcascades”.

Download 2 files and put it in folder of your project.
3) Use 0 in capture.open(0) to play webcam feed.
4) For detection in a local video provide the path to the video.(capture.open(“path_to_video”)).

Implementation:

// CPP program to detects face in a video    // Include required header files from OpenCV directory #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=1;        // Load classifiers from "opencv/data/haarcascades" directory      nestedCascade.load( "haarcascade_eye_tree_eyeglasses.xml" ) ;        // Change path before execution      cascade.load( "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(1)         {             capture >> frame;             if( frame.empty() )                 break;             Mat frame1 = frame.clone();             detectAndDraw( frame1, cascade, nestedCascade, scale );              char c = (char)waitKey(10);                        // 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, cvPoint(cvRound(r.x*scale), cvRound(r.y*scale)),                     cvPoint(cvRound((r.x + r.width-1)*scale),                      cvRound((r.y + r.height-1)*scale)), 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 );  }