from time import sleep
from picamera import PiCamera
from io import BytesIO
import cv2
import numpy as np
import os

def init():
	go = True
	print('Initilizing Camera and cascade components..')
	try:
		camera = PiCamera()
		camera.resolution = (640, 480)
		sleep(2)
		print('[ OK ] Camera')
	except:
		print('[ Error ] Can not initialize PiCamera')
		go = False

	try:
		face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
		sleep(1)
		print('[ OK ] CascadeClassifier')
	except:
		print('[ Error ] Can not load cascade File')
		go = False
	if (go):
		print('Starting Photo loop..')
		start(camera, face_cascade)
	else: 
		print('closing')
	
def start( camera, face_cascade):
	j = 0
	while True:
		#try:			
			camera.capture('img.jpg')			
			img = cv2.imread('img.jpg',1)
			gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)			
			faces = face_cascade.detectMultiScale(gray, 1.3, 5)			
			i = 0;
			for (x,y,w,h) in faces:
				i = i + 1
				j = j + 1 				

				roi_gray = gray[y:y+h, x:x+w]
				roi_color = img[y:y+h, x:x+w]
				try:
					cv2.imwrite('train/'+str(j)+'.jpg',roi_color)
				except Exception as ex:
					print(ex)
				print('Drawing on face ', i)
				
				cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
				cv2.putText(img, recognize(roi_gray), (x, y), cv2.FONT_HERSHEY_PLAIN, 1.7, (255, 0, 0), 2)
			cv2.imshow('image',img) 
			cv2.waitKey(100)
			if cv2.waitKey(1) & 0xFF == ord('q'):
				cv2.destroyAllWindows()
				break
		
		#except:
			#print('[ Error ] Unexpected exception')
			#print('Closing')
			#break
			
def train(number):

	train_path = 'train/'
	face_recognizer = cv2.createLBPHFaceRecognizer()
	images = []
	labels = []
	image_names = os.listdir(train_path)
	for image_name in image_names:
		if image_name.startswith("."):
			continue;
		image_path = train_path + image_name
		image = cv2.imread(image_path)
		gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
		images.append(gray)
		labels.append(number)
	print('training')
	face_recognizer.train(images, np.array(labels))
	face_recognizer.save('faces/hesham')
	

def recognize(image):
	
	subjects = ['','Hesham','Unknown']
	face_recognizer = cv2.createLBPHFaceRecognizer()
	face_recognizer.load('faces/hesham')
	img = image.copy()	
	label= face_recognizer.predict(img)
	if label[0] == 1:
		return 'Hesham'
	else: 
		return 'Unknown'
	
  
init()