main_recognizer.py

import numpy as np 
import cv2 as cv
import os

# save np.load
np_load_old = np.load

# modify the default parameters of np.load
np.load = lambda *a,**k: np_load_old(*a, allow_pickle=True, **k)


DIR=r'Faces'
people=[]

for i in os.listdir(DIR):
   people.append(i)

haar_cascade = cv.CascadeClassifier('haar_face.xml')

features = np.load("features.npy")

labels=np.load("labels.npy")

face_recognizer = cv.face.LBPHFaceRecognizer_create()
face_recognizer.read('face_trained.yml')

photo=input("enter the copied path of picture:- ")
img=cv.imread(photo)

gray= cv.cvtColor(img,cv.COLOR_BGR2GRAY)

cv.imshow("Person",gray)
faces_rect= haar_cascade.detectMultiScale(gray,1.1,4)
for(x,y,w,h) in faces_rect:
   faces_roi = gray[y:y+h,x:x+h]

   label,confidence= face_recognizer.predict(faces_roi)
   
   print("Label ="+ people[label] +"with a confidence of"+str(confidence))
   
   cv.putText(img,str(people[label]),(20,20),cv.FONT_HERSHEY_COMPLEX,1.0,(0,255,0), thickness=2)

   cv.rectangle(img,(x,y),(x+w,y+h),(0,255,0),thickness=2)
np.load = np_load_old
cv.imshow("Detected Face",img)
cv.waitKey(0)