Given a folder full of jpegs, this gist prints out if you have a face in it which is frontal (not profile), and its ratio between face size and image size. If it finds more than one face, it treats it as if no faces were found. (Use case: profile pictures)

gistfile1.py

import sys, os
from cv import *
from cv2 import *
import glob


def detect_face(image):
    """Converts an image to grayscale and prints the ratio of face to image if _one_ face is found"""
    grayscale = CreateImage((image.width, image.height), 8, 1)
    CvtColor(image, grayscale, CV_BGR2GRAY)
    storage = CreateMemStorage(0)
    EqualizeHist(grayscale, grayscale)
    cascade = Load('/usr/local/Cellar/opencv/2.4.0/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml')
    faces = HaarDetectObjects(grayscale, cascade, storage, 1.2, 2,
                              CV_HAAR_DO_CANNY_PRUNING, (50, 50))

    if len(faces) == 1:
        for f in faces:
            print (f[0][2]*f[0][3], 
            image.width*image.height, 
            (f[0][2]*f[0][3])*100/(image.width*image.height))
    else:
        print 0, image.width*image.height, 0


def main():
    print 'user_id', 'face_area', 'image_area', 'ratio'
    file_list = glob.glob('/path/to/folder/*jpg')
    for f in file_list:
        image = LoadImage(f)
        print os.path.basename(f)[:-4],
        detect_face(image)


if __name__ == "__main__":
    main()