finished evaluation

Author: akshaybhatia10

FaceRecognition/testModel.py

@@ -0,0 +1,61 @@
+import cv2
+import numpy as np
+from trainModel import *
+
+cascade_path = 'cascades/haarcascade_frontalface_default.xml'
+face_cascade = cv2.CascadeClassifier(cascade_path)
+
+# Finds face and return the original image and cropped face
+def detect_face(image):
+	gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+	faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+
+	if faces is ():
+		return image
+
+	for (x, y, w, h) in faces:
+		cv2.rectangle(image, (x,y), (x+w, y+h), (0,255,0), 2)
+		cropped_face = image[y:y+h, x:x+w]
+		cropped_face = cv2.resize(cropped_face, (200,200))
+	
+	return cropped_face		
+
+capture = cv2.VideoCapture(0)
+
+while True:
+	response, frame = capture.read()
+	found_face = detect_face(frame)	
+
+	try:
+		gray_face = cv2.cvtColor(found_face, cv2.COLOR_BGR2GRAY)
+
+		# predict using trained model
+		label, score = classifier.predict(gray_face)
+		if score < 500:
+			confidence_score = int(100 * (1 - score/400))
+			message = 'I am {} confident '.format(str(confidence_score))
+
+		cv2.putText(frame, message, (50,50), cv2.FONT_ITALIC, 1, (200,0,200), 2)
+
+		if score > 75:
+			message = 'Sorry! You are not who you say'
+			cv2.putText(frame, message, (150,50), cv2.FONT_ITALIC, 1, (200,200,0), 2)
+			cv2.imshow('I rekognize You', image)
+		else:
+			message = 'You you are finally here'
+			cv2.putText(frame, message, (150,50), cv2.FONT_ITALIC, 1, (0,200,200), 2)	
+			cv2.imshow('I rekognize You', image)
+	
+	except:
+		message = 'No face found!'
+		cv2.putText(frame, message, (150,150), cv2.FONT_ITALIC, 1, (0,200,200), 2)	
+		cv2.imshow('I rekognize You', frame)
+		pass
+
+	if cv2.waitKey(0):
+		break
+
+capture.release()
+cv2.destroyAllWindows()			
+
+