In this post we’ll look at a surprisingly simple way to get started with face recognition using Python and the open source library OpenCV.

All the code is below.I will explain it later.

# -*- coding:utf-8 -*-
import cv2 
import numpy as np
import cv2.cv as cv
import glob

#cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
def detect(img, cascade):
	rects = cascade.detectMultiScale(img, scaleFactor=1.1, minNeighbors=3, minSize=(10, 10), flags = 	cv.CV_HAAR_SCALE_IMAGE)
	if len(rects) == 0:
		return []
	rects[:,2:] += rects[:,:2]
	return rects
	
def faceCrop(imagePattern,boxScale=1):
	imgList=glob.glob(imagePattern)
	if len(imgList)<=0:
    	print 'No Images Found'
    	return
	i = 0
	for img in imgList:
		print img
    	image = cv2.imread(img)
    	cascade = cv2.CascadeClassifier("./haarcascades/haarcascade_frontalface_alt.xml")
    	gray = cv2.cvtColor(image, cv.CV_BGR2GRAY)
    	gray = cv2.equalizeHist(gray)
    	
    	rects = detect(gray, cascade)
    	x1 = rects[0][1]
    	y1 = rects[0][0]
    	x2 = rects[0][3]
    	y2 = rects[0][2]
    	faceROI = image[x1:x2, y1:y2]
    	cv2.imwrite('./new/' + '%s.jpg'% i, faceROI)
    	i += 1
    	
faceCrop('./data/boss/*.jpg',boxScale=1)