face_recognizer.py

import numpy as np
import cv2 as cv

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

people = ['Ben Afflek', 'Elton John', 'Jerry Seinfield', 'Madonna', 'Mindy Kaling','Unknown']

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

img = cv.imread(r'E:\OpenCV\Lab\Faces\val\ben_afflek\2.jpg')

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Person', gray)

# Detect the face in the image
faces_rect = haar_cascade.detectMultiScale(gray, 1.1, 4)
flag =1
for (x,y,w,h) in faces_rect:
    faces_roi = gray[y:y+h,x:x+w]

    label, loss = face_recognizer.predict(faces_roi)
    print(f'Label = {people[label]} with a loss of {loss}')
    if loss>100:
        flag=0
        label=5
    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)


if(flag==0):
    print("Not in database")


cv.imshow('Detected Face', img)
cv.waitKey(0)