Working with single face

main.py

@@ -4,6 +4,7 @@ from picamera import PiCamera
 from io import BytesIO
 import cv2
 import numpy as np
+import os
 
 def init():
 	go = True
@@ -31,35 +32,72 @@ def init():
 		print('closing')
 	
 def start( camera, face_cascade):
+	j = 0
 	while True:
-		try:
-			print('Taking photo')
-			camera.capture('img.jpg')
-			print('Photo Captured')
+		#try:			
+			camera.capture('img.jpg')			
 			img = cv2.imread('img.jpg',1)
-			gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-			print('Photo Converted')
-			faces = face_cascade.detectMultiScale(gray, 1.3, 5)
-			print('Photo Processed')
+			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
-				cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
-				#cv2.imwrite('result.jpg', gray)
+				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
+		#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()
 
+