Face detection using OpenCV

import cv2
import numpy as np
import face_recognition
import os
from datetime import datetime

path = 'ImagesAttendance'
images = []
classNames =[]
myList = os.listdir(path)
print(myList)
for c1 in myList:
    curImg = cv2.imread(f'{path}/{c1}')
    images.append(curImg)
    classNames.append(os.path.splitext(c1)[0])
print(classNames)

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

def markAttendance(name):
    with open('Attendance.csv', 'r+') as f:
        myDataList = f.readlines()
        nameList =[]
        for line in  myDataList:
            entry = line.split(',')
            nameList.append(entry[0])
        if name not in nameList:
            now= datetime.now()
            dtString =now.strftime('%H:%M:%S')
            f.writelines(f'\n{name},{dtString}')

encodeListKnown = findEncodings(images)
print('Encoding Complete')
cap = cv2.VideoCapture(0)

while True:
    success, img = cap.read()
    imgS = cv2.resize(img,(0,0), None, 0.25, 0.25)
    imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)

    facesCurFrame = face_recognition.face_locations(imgS)
    encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)

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

        if matches[matchIndex]:
            name = classNames[matchIndex].upper()
            print(name)
            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), 2)
            cv2.rectangle(img,(x1, y2-35), (x2, y2), (0, 255, 0), cv2.FILLED)
            cv2.putText(img, name, (x1+6, y2-6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
            markAttendance(name)


    cv2.imshow('Webcame', img)
    cv2.waitKey(1)