Create a thumbnail of a face photo.

facecrop.py

#!/usr/bin/python

# A small script to create a square thumbnail out of a picture of a human face.
# Written by Miikka Koskinen (http://miikka.me/) on 2012-04-07.

# Based on:
# http://recursive-design.com/blog/2010/12/14/face-detection-with-osx-and-python/

import cv
import sys

from optparse import OptionParser

def crop_face_square(image, cascade, target_size = 100):
	faces = cv.HaarDetectObjects(image, cascade, cv.CreateMemStorage(0))

	if faces:
		# Let's the face with most neighbors
		((x, y, w, h), n) = sorted(faces, key=lambda x: x[1], reverse=True)[0]
	
		# Calculate the center of the face
		xc = x + w/2
		yc = y + h/2

		# Cropping just the detected rectangle is not enough - it probably
		# doesn't containg the whole head.
		size = int(max(w,h) * 1.5)

		# We don't want to scale up

		if size < target_size:
			size = target_size

		if size > image.width or size > image.height:
			size = min(image.width, image.height)

		# The actual top-left point of our ROI
		x2 = xc - size/2
		y2 = yc - size/2

		# Let's keep our ROI rectangle inside the image

		def limit(num, lower, upper):
			return max(lower, min(upper, num))

		x2 = limit(x2, 0, image.width - size)
		y2 = limit(y2, 0, image.height - size)

		# Actually crop the image

		cropped = cv.CreateImage((size, size), 8, 3)
		resized = cv.CreateImage((target_size, target_size), 8, 3)

		cv.SetImageROI(image, (x2, y2, size, size))
		cv.Copy(image, cropped)
		cv.Resize(cropped, resized)

		return resized
	else:
		return None

def main():
	parser = OptionParser(usage = "usage: %prog [options] [input filename] [output filename]")
	parser.add_option("-c", "--cascade",
			action="store",
			dest="cascade",
			type="str",
			help="Haar cascade file, default %default",
			default = "/usr/local/Cellar/opencv/2.3.1a/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml")

	(options, args) = parser.parse_args()

	if len(args) != 2:
		parser.print_help()
		sys.exit(1)

	input_name = args[0]
	output_name = args[1]

	cascade = cv.Load(options.cascade)
	image = cv.LoadImage(input_name, 1)
	face_square = crop_face_square(image, cascade)

	if face_square:
		cv.SaveImage(output_name, face_square)
	else:
		print "No faces found."

if __name__ == '__main__':
	main()