face_recognition.py

# pylint:disable=no-member

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"]
# features = np.load('features.npy', allow_pickle=True)
# labels = np.load('labels.npy')

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

img = cv.imread(r"Faces\val\elton_john/1.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)

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)