#include "opencv2/objdetect.hpp" #include "opencv2/highgui.hpp" #include "opencv2/imgproc.hpp" #include using namespace std; using namespace cv; /** Function Headers */ void detectAndDisplay( Mat frame ); /** Global variables */ CascadeClassifier face_cascade; CascadeClassifier eyes_cascade; /** @function main */ int main( int argc, const char** argv ) { CommandLineParser parser(argc, argv, "{help h||}" "{face_cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|Path to face cascade.}" "{eyes_cascade|../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|Path to eyes cascade.}" "{camera|0|Camera device number.}"); parser.about( "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n" "You can use Haar or LBP features.\n\n" ); parser.printMessage(); String face_cascade_name = parser.get("face_cascade"); String eyes_cascade_name = parser.get("eyes_cascade"); //-- 1. Load the cascades if( !face_cascade.load( face_cascade_name ) ) { cout << "--(!)Error loading face cascade\n"; return -1; }; if( !eyes_cascade.load( eyes_cascade_name ) ) { cout << "--(!)Error loading eyes cascade\n"; return -1; }; int camera_device = parser.get("camera"); VideoCapture capture; //-- 2. Read the video stream capture.open( camera_device ); if ( ! capture.isOpened() ) { cout << "--(!)Error opening video capture\n"; return -1; } Mat frame; while ( capture.read(frame) ) { if( frame.empty() ) { cout << "--(!) No captured frame -- Break!\n"; break; } //-- 3. Apply the classifier to the frame detectAndDisplay( frame ); if( waitKey(10) == 27 ) { break; // escape } } return 0; } /** @function detectAndDisplay */ void detectAndDisplay( Mat frame ) { Mat frame_gray; cvtColor( frame, frame_gray, COLOR_BGR2GRAY ); equalizeHist( frame_gray, frame_gray ); //-- Detect faces std::vector faces; face_cascade.detectMultiScale( frame_gray, faces ); for ( size_t i = 0; i < faces.size(); i++ ) { Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 ); ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4 ); Mat faceROI = frame_gray( faces[i] ); //-- In each face, detect eyes std::vector eyes; eyes_cascade.detectMultiScale( faceROI, eyes ); for ( size_t j = 0; j < eyes.size(); j++ ) { Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 ); int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 ); circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4 ); } } //-- Show what you got imshow( "Capture - Face detection", frame ); }