Face recognition script that can run in the background

help_jarvis.py

import os
from threading import Thread

import cv2
import face_recognition


class Face(Thread):
    def __init__(self):
        super(Face, self).__init__()
        self.training_dataset = "train"
        self.learning_rate = 0.6
        self.model = "hog"  # model using which the images are matched
        self.train_faces, self.train_names = [], []
        for character_dir in os.listdir(self.training_dataset):  # loads the training dataset
            try:
                for file_name in os.listdir(f'{self.training_dataset}/{character_dir}'):
                    # loads all the files within the named repo
                    img = face_recognition.load_image_file(f'{self.training_dataset}/{character_dir}/{file_name}')
                    encoded = face_recognition.face_encodings(img)[0]  # generates face encoding matrix
                    self.train_faces.append(encoded)
                    self.train_names.append(character_dir)
            except (IndexError, NotADirectoryError):
                pass

    def run(self):
        while True:
            validation_video = cv2.VideoCapture(1)
            ret, img = validation_video.read()
            identifier = face_recognition.face_locations(img, model=self.model)
            encoded_ = face_recognition.face_encodings(img, identifier)
            for face_encoding, face_location in zip(encoded_, identifier):
                results = face_recognition.compare_faces(self.train_faces, face_encoding, self.learning_rate)
                if True in results:
                    match = self.train_names[results.index(True)]
                    print(match)
                    return match


if __name__ == '__main__':
    Face().start()