main.py

import cv2
import pickle
import numpy as np

face_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainner.yml")

labels = {}
with open("labels.pickle", 'rb') as f:
    og_labels = pickle.load(f)
    labels = {v: k for k, v in og_labels.items()}

cap = cv2.VideoCapture(0)

while (True):
    ret, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.5, minNeighbors=5)
    for (x, y, w, h) in faces:
        roi_gray = gray[y:y + h, x:x + w]
        roi_color = frame[y:y + h, x:x + w]

        id_, conf = recognizer.predict(roi_gray)
        if conf >= 50:
            font = cv2.FONT_HERSHEY_SIMPLEX
            name = labels[id_]
            color = (255, 255, 255)
            stroke = 2
            cv2.putText(frame, name, (x, y), font, 1, color, stroke, cv2.LINE_AA)

        img_item = "my_image.png"
        cv2.imwrite(img_item, roi_gray)
        color = (0, 0,255)
        if labels[id_] == 'alek':
            color = (255, 0, 0)
        stroke = 2
        cv2.rectangle(frame, (x, y), (x + w, y + h), color, stroke)

    cv2.imshow('frame', frame)
    if cv2.waitKey(20) & 0xFF == ord('q'):
        break