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.
