Face detector using Opencv Python version 2.4 and frontal face cascade features

LiveFaceDetector.py

import cv2
import sys



video_capture = cv2.VideoCapture(0)
#video_capture.set(3,320)
#video_capture.set(4,240)
face_cascade = cv2.CascadeClassifier('haar_frontalface_alt2.xml')


if __name__ == "__main__":
    try:
        while(True):
            # Capture frame-by-frame
            ret, frame = video_capture.read()
            if ret==True:
                #just to remove mirror effect in camera
                frame = cv2.flip(frame,2)
                # Our operations on the frame come here
                gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

                faces = face_cascade.detectMultiScale(
                    gray,
                    scaleFactor=1.1,
                    minNeighbors=5,
                    minSize=(30, 30),
                    flags=cv2.cv.CV_HAAR_SCALE_IMAGE
                )

                # Draw a rectangle around the faces
                for (x, y, w, h) in faces:
                    cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), thickness=cv2.cv.CV_FILLED)
                    cv2.rectangle(frame, (x, y), (x+w+3, y+h+3), (0, 0, 0), 2)


                
                # Display the resulting frame
                cv2.imshow('frame',frame)
                if cv2.waitKey(1) & 0xFF == ord('q'):
                    break
            else:
                break

    except KeyboardInterrupt as k:
        sys.stderr.write("program will exit\nBye!\n")
        
    except Exception, e:
        sys.stderr.write(str(e) + "\n")


# When everything done, release the capture
video_capture.release()
cv2.destroyAllWindows()        
sys.exit(0)

cv2.VideoCapture(0, cv2.CAP_DSHOW)