- ALL OF YOU PLEASE INSTALL PIP PERFECTLY.
Face detection is AI-based computer technology that is used to extract and identify human faces from digital images. When integrated with biometric security systems (particularly, facial recognition ones), this kind of technology is what makes it possible to monitor and track people in real-time.
A facial recognition system uses biometrics to map facial features from a photograph or video. It compares the information with a database of known faces to find a match. Facial recognition can help verify a person's identity, but it also raises privacy issues.
imgElon = face_recognition.load_image_file('Imagesbasic/Elon Musk.jpg')
imgElon = cv2.cvtColor(imgElon,cv2.COLOR_BGR2RGB)
imgTest = face_recognition.load_image_file('Imagesbasic/Elon1.jpg')
imgTest = cv2.cvtColor(imgTest,cv2.COLOR_BGR2RGB)
results = face_recognition.compare_faces([encodeElon],encodeTest)
faceDis = face_recognition.face_distance([encodeElon],encodeTest)
print(results,faceDis)
cv2.putText(imgTest,f'{results} {round(faceDis[0],2)}',(50,50),cv2.FONT_HERSHEY_COMPLEX,1,(0,0,255),2)
import cv2
import numpy as np
import face_recognition
import os
from datetime import datetime
# from PIL import ImageGrab
def markAttendance(name):
with open('Code\Att.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}')