Face Recognition with Python

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

pathImages = "ImagesAttendance"
myImgList = os.listdir(pathImages)
imagesObjKnown = []
nameList = []

for x, img in enumerate(myImgList):
	imgCur = cv2.imread(f'{pathImages}/{img}')
	imagesObjKnown.append(imgCur)
	nameList.append(os.path.splitext(img)[0])

def findEncodeList(imageList):
	encodeList = []
	for image in imageList:
		img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
		encode = face_recognition.face_encodings(img)[0]
		encodeList.append(encode)
	return encodeList

encodeListKnown = findEncodeList(imagesObjKnown)
print("Encode Complete")

def markAttendance(name):
	with open('Attendance.csv', 'r+') as f:
		now = datetime.now()
		strTime = now.strftime('%d-%m-%Y %H:%M')
		f.readlines()
		f.writelines(f'\n{name}, {strTime}')


cap = cv2.VideoCapture(0)
while True:
	success, imgWebcam = cap.read()
	imgFrame = cv2.cvtColor(imgWebcam, cv2.COLOR_BGR2RGB)
	imgFrameLoc = face_recognition.face_locations(imgFrame)
	imgFrameEncode = face_recognition.face_encodings(imgFrame, imgFrameLoc)
	for imgLoc, imgEncode in zip(imgFrameLoc, imgFrameEncode):
		matches = face_recognition.compare_faces(encodeListKnown, imgEncode)
		faceDis = face_recognition.face_distance(encodeListKnown, imgEncode)
		matchIndex = np.argmin(faceDis)
		if matches[matchIndex]:
			name = nameList[matchIndex]
			y1, x2, y2, x1 = imgLoc
			cv2.rectangle(imgWebcam, (x1, y1), (x2, y2), (0, 255, 0), 2)
			cv2.rectangle(imgWebcam, (x1, y2-30), (x2+200, y2), (0, 255, 0), cv2.FILLED)
			cv2.putText(imgWebcam, f'{name}: {round(faceDis[matchIndex], 2)}', (x1+10, y2-5), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
			markAttendance(name)
	cv2.imshow("Webcam", imgWebcam)
	if cv2.waitKey(1) & 0xFF == ord("q"):
		break