import cv2                                            //1
import sys

faceCascadeObject = 
  cv2.CascadeClassifier("haarcascade_frontalface_default.xml") //2

image = cv2.imread(sys.argv[1])                       //3 Image file
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)        //4

faces = faceCascade.detectMultiScale(       //5
    gray,                                   //grayscale image
    scaleFactor=1.1,                        //some faces may be closer to camera
                                            // they would appear bigger than faces at back. 
                                            // scale factor compensates for this.
    minNeighbors=5,                         //how many objects are detected near the 
                                            // current one using moving Window
    minSize=(30, 30),                       //gives the size of each window
    flags = cv2.cv.CV_HAAR_SCALE_IMAGE
)

print("Found {0} faces!".format(len(faces)))

# Draw a rectangle around the faces
for (x, y, w, h) in faces:
    cv2.rectangle(                    //6
      image,                          //It is the image on which rectangle is to be drawn.
      (x, y),                         //Starting coordinates of rectangle. 
                                      // (X coordinate value, Y coordinate value).
      (x+w, y+h),                     //Ending coordinates of rectangle. 
                                      //(X coordinate value, Y coordinate value).
      (0, 255, 0),                    //Color of border line of rectangle. 
                                      //For BGR, we pass a tuple. eg: (255, 0, 0) 
                                      //for blue color.
      2)                              //Thickness of the rectangle border line in px.

cv2.imshow("Faces found", image)
cv2.waitKey(0)