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import joblib

import cv2

import numpy as np

import matplotlib.pyplot as plt

cam = cv2.VideoCapture(1)

path = "E:\\Coding\\AIML\\haarcascade_frontalface_default.xml"

# face detector

face_detector = cv2.CascadeClassifier(path)

model_path = 'E:\\Coding\\AIML\\data_files\\orl_face_model_2.pkl'

face_model = joblib.load(model_path)

frame=True

count = 0

while(frame):

ret,im = cam.read()

im_new = cv2.resize(im, (512,512))

# covert the color (BGR) into grayscale

gray_im = cv2.cvtColor(im_new,cv2.COLOR_BGR2GRAY)

# run your classifier on the image

faces = face_detector.detectMultiScale(gray_im,scaleFactor=1.1,minNeighbors=10)

# disply the bounding box on all the faces

for (dx,dy,w,h) in faces:

cv2.rectangle(im_new, (dx,dy),(dx+w,dy+h),(0,0,255),2)

cropped_im = cv2.resize((gray_im[dy-20:(dy+h)+40,dx:(dx+w)]),(92,112))

lb = face_model.predict((cropped_im.reshape(1,-1)))

cv2.putText(im_new,'user: '+str(lb[0]),(dx-5,dy-5),cv2.FONT_HERSHEY_SIMPLEX,1,color=(255,0,0),thickness=2)

cv2.imshow('camera live feed', im_new)

# desired button of your choice

if cv2.waitKey(1) & 0xFF == ord('q'):

frame=False

break

cam.release()

cv2.destroyAllWindows()