Now that we have learned how to make our system learn, it's time to use that learned data and recognize the face. So without much talking, let's go ahead and understand how this would be done:

import numpy as np
import cv2

faceDetect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

cam = cv2.VideoCapture(0)
rec = cv2.face.LBPHFaceRecognizer_create()

rec.read("recognizer/trainningData.yml")
id = 0
font = cv2.FONT_HERSHEY_SIMPLEX

while True:

   ret, img = cam.read()
   gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
   faces = faceDetect.detectMultiScale(gray,1.3,5)

   for (x,y,w,h) in faces:
       cv2.rectangle(img, (x,y), (x+w, y+h), (0,0,255), 2)
       id, conf = rec.predict(gray[y:y+h, x:x+w])

       if id==1:
           id = "BEN"
       cv2.putText(img, str(id), (x,y+h),font,2, (255,0,0),1,)

    cv2.imshow("face", img)

    if cv2.waitKey(1)==ord('q'):
       break

cam.release()
cv2.destroyAllWindows()

In this code, there are not a lot of new things...