Hey friends, Welcome to CodeWithNepal today in this blog you’ll learn OpenCV C++ Program for Face Detection. This program uses the OpenCV library to detect faces in a video file stored in the local machine or in a live stream from a webcam. This program detects faces in real time and tracks them. It uses trained XML classifiers for the same. The classifiers used on this software have facial capabilities skilled in them. Different classifiers may be used to discover special objects. In the earlier blog, I shared Detect Browser in JavaScript and now it’s time to create an OpenCV C++ Program for Face Detection.
Requirements for running the Face Detection program:
1) OpenCV must be installed on the device.
2) Paths to the classifier XML files must be given before to execution program. These XML files can be found in the OpenCV directory “OpenCV/data/codewithnepal”.
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”)).
You might like this:
Source Code for Face Detection program.
// CPP program to detects face in a video // Include required header files from OpenCV directory #include "/usr/local/include/opencv2/objdetect.hpp" #include "/usr/local/include/opencv2/highgui.hpp" #include "/usr/local/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/codewithnepal" directory nestedCascade.load( "../../codewithnepal_eye_tree_eyeglasses.xml" ) ; // Change path before execution cascade.load( "../../codewithnepal_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 ); }
That’s all, now you’ve successfully built OpenCV C++ Program for Face Detection If your code doesn’t work or you’ve faced any problems, please free to comment down I will provide the source code files.