main.py

# Importing the libraries
import cv2
import numpy as np
import face_recognition
import os
from datetime import datetime

# Image Loading and Encoding
path = 'Training_images'
images = []
Names = []
myList = os.listdir(path)
print(myList)
for cl in myList:
    curImg = cv2.imread(f'{path}/{cl}')
    images.append(curImg)
    Names.append(os.path.splitext(cl)[0])
print(Names)


# Encoding function
def findEncodings(images):
    encodeList = []
    for img in images:
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        encode = face_recognition.face_encodings(img)[0]
        encodeList.append(encode)
    return encodeList

# main function
def main():
    encodeListKnown = findEncodings(images)
    print('Encoding Complete')
    cap = cv2.VideoCapture(0)
    cv2.namedWindow('Face Detection')
    while True:
        _, img = cap.read()
        imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
        # Converting the video to RGB
        imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
        facesCurFrame = face_recognition.face_locations(imgS)
        encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)

        # Comparing the encodings
        for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
            matches = face_recognition.compare_faces(
                encodeListKnown, encodeFace)
            faceDis = face_recognition.face_distance(
                encodeListKnown, encodeFace)
            matchIndex = np.argmin(faceDis)

            # If the face matches
            if matches[matchIndex]:
                name = Names[matchIndex].split("_")[0].upper()
                number = Names[matchIndex].split("_")[1]
                y1, x2, y2, x1 = faceLoc
                y1, x2, y2, x1 = y1*4, x2*4, y2*4, x1*4
                cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 4)
                cv2.rectangle(img, (x1, y2-35), (x2, y2),
                              (0, 255, 0), cv2.FILLED)
                cv2.putText(img, name, (x1+6, y2-6),
                            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
        # Displaying the video
        cv2.imshow('Face Detection', img)
        if cv2.waitKey(1) == ord('q'):
            break

    # Releasing the video
    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    main()