3.b.py

import cv2
import numpy as np
import os,sys 

recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer/trainer.yml')
faceCascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

font = cv2.FONT_HERSHEY_SIMPLEX

cam = cv2.VideoCapture(0)
cam.set(3, 640) 
cam.set(4, 480) 

minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)

cam = cv2.VideoCapture(sys.argv[1]))
 
if (cam.isOpened()== False): 
  print("Error opening video stream or file")

while(cam.isOpened()) :
    ret, img = cam.read()
    if ret == True:
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

        faces = faceCascade.detectMultiScale( 
            gray,
            scaleFactor = 1.2,
            minNeighbors = 5,
            minSize = (int(minW), int(minH)),
            )

        for(x,y,w,h) in faces:

            cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)
            id, confidence = recognizer.predict(gray[y:y+h,x:x+w])
            if (confidence < 50):
                confidence = "  {0}%".format(round(100 - confidence))
            else:
                id = "unknown"
                confidence = "  {0}%".format(round(100 - confidence))
            
            cv2.putText(img, str(id), (x+5,y-5), font, 1, (255,255,255), 2)
            cv2.putText(img, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 1)  
            print(id)
            
        cv2.imshow('camera',img) 

        k = cv2.waitKey(10) & 0xff 
        if k == 27:
            break
    else:
        cam.release()
        cv2.destroyAllWindows()