OpenCV ARM - Face Detect

Here's another application that uses opencv libraries in the Debian disto. It performs face detection using Haar cascade.

The code below continuously captures frames with a USB web-camera. (In this demo, I displayed a sample picture on a separate laptop but this will also work for actual faces). Using the input frames and a loaded Haar classifier cascade, vector of rectangles containing the detected faces is returned to the user. A bounding box is drawn to each face to show successful detection.

face_detect.py

import cv2.cv as cv

HAAR_CASCADE = "/usr/local/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml"

cv.NamedWindow( "mycamera" )
capture = cv.CreateCameraCapture(0)
storage = cv.CreateMemStorage()
cascade = cv.Load(HAAR_CASCADE)

while True:
    image = cv.QueryFrame(capture)
    faces = cv.HaarDetectObjects(image, cascade, storage, 1.1, 3, cv.CV_HAAR_DO_CANNY_PRUNING, (100,100))
    for((x,y,w,h),i) in faces:
        cv.Rectangle(image, (x,y), (x+w, y+h), (0,255,0), 3)
    cv.ShowImage( "mycamera", image )
    if cv.WaitKey(5) > 0:
        break

cv.DestroyWindow( "mycamera" )

Below is the C/C++ equivalent of the above python script. (The code appears lengthy due to the comments and cleanup routines.)

face_detect.cpp

#include <opencv2/highgui/highgui.hpp>
#include <opencv2/objdetect/objdetect.hpp>
using namespace cv;

#define HAAR_CASCADE "/usr/local/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml"

int main(int argc, const char ** argv)
{
    cvNamedWindow( "mycamera" /*, CV_WINDOW_AUTOSIZE*/); // create camera window, 1=CV_WINDOW_AUTOSIZE(default,the user cannot resize the window)
    CvCapture *capture = cvCreateCameraCapture(0); // start capturing frames from camera (i.e. /dev/video0 device)
    CvMemStorage *storage = cvCreateMemStorage(); // create new memory storage
    CvHaarClassifierCascade *cascade = (CvHaarClassifierCascade *)cvLoad(HAAR_CASCADE); // load frontal face detector

    while (1){
        IplImage *image = cvQueryFrame(capture); // grab and retrieve frame
        CvSeq *faces = cvHaarDetectObjects(image, cascade, storage, 1.1, 3, CV_HAAR_DO_CANNY_PRUNING, cvSize(100,100)); // find rectangular regions that contain faces
        for(int i=0; i < faces->total; i++){
            CvRect *r = (CvRect *)cvGetSeqElem(faces, i); // get bounding rectangle of the detected face
            cvRectangle(image, cvPoint(r->x, r->y), cvPoint(r->x + r->width, r->y + r->height), cvScalar(0,255,0), 3); // draw a green rectangle
        }
        cvShowImage( "mycamera", image ); // display image within window
        if (cvWaitKey(5) > 0) // press any key to exit
            break;
    }
    // cleanups
    cvReleaseHaarClassifierCascade( &cascade ); // release cascade
    cvReleaseMemStorage( &storage ); // release memory storage
    cvReleaseCapture( &capture ); // stop capturing/reading
    cvDestroyWindow( "mycamera" ); // end camera window
    return 0;
}