python

#!/usr/bin/python
# -*- coding: UTF-8 -*-

# face_detect.py

# Face Detection using OpenCV. Based on sample code from:
# http://python.pastebin.com/m76db1d6b

# Usage: python face_detect.py

import sys, os
from opencv.cv import *
from opencv.highgui import *
from PIL import Image, ImageDraw
from math import sqrt

def detectObjects(image):
    """Converts an image to grayscale and prints the locations of any faces found"""
    grayscale = cvCreateImage(cvSize(image.width, image.height), 8 , 1 )
    cvCvtColor(image, grayscale, CV_BGR2GRAY)

    storage = cvCreateMemStorage( 0 )
    cvClearMemStorage(storage)
    cvEqualizeHist(grayscale, grayscale)

    cascade = cvLoadHaarClassifierCascade(
        \ '/usr/share/opencv/haarcascades/haarcascade_frontalface_default.xml\' ,
        cvSize( 1 , 1 ))
    faces = cvHaarDetectObjects(grayscale, cascade, storage, 1.1 , 2 ,
        CV_HAAR_DO_CANNY_PRUNING, cvSize( 20 , 20 ))

    result = []
    for f in faces:
        result.append((f.x, f.y, f.x + f.width, f.y + f.height))

    return result

def grayscale(r, g, b):
    return int (r * . 3 + g * . 59 + b * . 11 )

def process(infile, outfile):

    image = cvLoadImage(infile);
    if image:
        faces = detectObjects(image)

    im = Image. open (infile)

    if faces:
        draw = ImageDraw.Draw(im)
        for f in faces:
            draw.rectangle(f, outline = ( 255 , 0 , 255 ))

        im.save(outfile, "JPEG" , quality = 100 )
    else :
        print "Error: cannot detect faces on %s" % infile

if __name__ = = "__main__" :
    process(\ 'input.jpg\', \'output.jpg\' )