main.py

import face_recognition
import cv2
import os

KNOWN_FACES_DIR = "images/known_faces"
TOLERANCE = 0.6
FRAME_THICKNESS = 2
FONT_THICKNESS = 1
MODEL = "cnn"

video = cv2.VideoCapture(0)

print("Loading known faces.")
known_faces = []
known_names = []

for name in os.listdir(KNOWN_FACES_DIR):
    for filename in os.listdir(f"{KNOWN_FACES_DIR}/{name}"):
        image = face_recognition.load_image_file(f"{KNOWN_FACES_DIR}/{name}/{filename}")
        encoding = face_recognition.face_encodings(image)[0]
        known_faces.append(encoding)
        known_names.append(name)
print("Loading finished.\n")

print("Starting video capture.")
print("Detection started.\n")

while True:
    ret, frame = video.read()
    frame = cv2.flip(frame, 1)

    locations = face_recognition.face_locations(frame, model=MODEL)
    encodings = face_recognition.face_encodings(frame, locations)

    for face_encoding, face_location in zip(encodings, locations):
        results = face_recognition.compare_faces(known_faces, face_encoding, TOLERANCE)
        match = None
        if True in results:
            match = known_names[results.index(True)]

            top_left = (face_location[3], face_location[0])
            bottom_right = (face_location[1], face_location[2])

            color = [0, 255, 0]
            cv2.rectangle(frame, top_left, bottom_right, color, FRAME_THICKNESS)

            top_left = (face_location[3], face_location[2])
            bottom_right = (face_location[1], face_location[2]+20)

            cv2.rectangle(frame, top_left, bottom_right, color, cv2.FILLED)
            cv2.putText(frame, match, (face_location[3]+10, face_location[2]+15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), FONT_THICKNESS)

    cv2.imshow(filename, frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

print("Video capture stopped. Please wait a few moments for the process to finish.")
video.release()
cv2.destroyAllWindows()