Face Replace

face_replace.py

#!/usr/bin/python
# face_replace.py
# Usage: python face_replace.py <image_file> [face index]

import sys
import cv2

def detectObjects(image):
	"""Converts an image to grayscale and returns the locations of any faces found"""
	grayscale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
	cascade = cv2.CascadeClassifier(
		'haarcascade_frontalface_alt2.xml')

	scalefactor = 1.09  # How much to increase window size each pass
	minNeighbours = 5  # Smallest face to detect. Up this if you have small falsepositives
	faces = cascade.detectMultiScale(grayscale, scalefactor, minNeighbours)


	return [(x, y, x + w, y + h) for (x,y,w,h) in faces]


def main():
	inputfile = sys.argv[1]
	print inputfile
	replacefile = sys.argv[2]
	image = cv2.imread(inputfile)
	replaceimage = cv2.imread(replacefile)
	print "Detecting faces..."
	faceboxes = detectObjects(image)
	print len(faceboxes), "faces found"
	print "Detecting replace faces..."
	replacefaceboxes = detectObjects(replaceimage)
	print len(replacefaceboxes), "replace faces found"
	mask = cv2.imread("circlemask.png")
	replacebox=replacefaceboxes[0]
	newreplaceimage=replaceimage[replacebox[1]:replacebox[3], replacebox[0]:replacebox[2]]
	#cv2.imshow("Output1",newreplaceimage)
	#cv2.waitKey(0)
	box=faceboxes[1]
	size = (box[2] - box[0], box[3] - box[1])
	scalednewface = cv2.resize(newreplaceimage,size, interpolation = cv2.INTER_CUBIC)
	scaledmask = cv2.resize(mask,size, interpolation = cv2.INTER_CUBIC)
	op=cv2.seamlessClone(scalednewface,image, scaledmask, (box[0]+(size[0]/2), box[1]+(size[1]/2)),cv2.NORMAL_CLONE)
	cv2.imshow("Output",op)
	cv2.waitKey(0)
if __name__ == "__main__":
	main()