import cv2
import numpy as np
import os
face_dascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

eye_dascade = cv2.CascadeClassifier('haarcascade_eye.xml')
smile_dascade = cv2.CascadeClassifier('haarcascade_smile.xml')

cap = cv2.VideoCapture(0)
# temp = cv2.imread('dat.jpg',0)
# temp_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
a = 0
while a != 1:
	ret, img = cap.read()
	hinh = np.copy(img)
	gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
	faces = face_dascade.detectMultiScale(gray, 1.3, 5) 
	for (x,y,w,h) in faces:
		cv2.rectangle(img, (x,y), (x+w, y+h), (255,0,0), 2)
		face_gray = gray[y:y+h, x:x+h]
		face_color = img[y:y+h, x:x+h]
		smile = smile_dascade.detectMultiScale(face_gray, 1.3, 5)
		for (x2,y2,w2,h2) in smile:
			if((((h*1.0*w)/(w2*h2))<11) and len(smile)==len(faces)):
				cv2.rectangle(face_color, (x2,y2), (x2+w2, y2+h2), (150,0,0), 2)
				cv2.imwrite('hinh1.jpg',hinh)
				a = 1
		eyes = eye_dascade.detectMultiScale(face_gray)
		for (xe,ye,we,he) in eyes:
			cv2.rectangle(face_color, (xe,ye), (xe+we, ye+he), (0,0,255), 2)
	cv2.imshow('img',img)
	if cv2.waitKey(1) == 27:
		break
cap.release()
cv2.destroyAllWindows()