<filename>faces_recognition.py
import numpy as np
import cv2 as cv

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

people = ['<NAME>', '<NAME>', '<NAME>', 'Madonna', '<NAME>']

# features = np.load('features.npy')
# labels = np.load('labels.npy')

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

img = cv.imread(r'D:\OpenCV\Faces\val\elton_john\1.jpg')

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow("Gray", gray)

# Detect the face in the image

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+w]

    label, confidence = face_recognizer.predict(faces_roi)
    print(f'Label = {people[label]} with a confidence of {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)

cv.imshow('Detected face', img)

cv.waitKey(0)
<filename>faces_recognition.py
import numpy as np
import cv2 as cv

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

people = ['<NAME>', '<NAME>', '<NAME>', 'Madonna', '<NAME>']

# features = np.load('features.npy')
# labels = np.load('labels.npy')

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

img = cv.imread(r'D:\OpenCV\Faces\val\elton_john\1.jpg')

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow("Gray", gray)

# Detect the face in the image

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+w]

    label, confidence = face_recognizer.predict(faces_roi)
    print(f'Label = {people[label]} with a confidence of {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)

cv.imshow('Detected face', img)

cv.waitKey(0)
# features = np.load('features.npy') # labels = np.load('labels.npy') # Detect the face in the image