main.py

import cv2
import numpy as np
import face_recognition
import os
from datetime import datetime
import mysql.connector
from mysql.connector import Error

connection = mysql.connector.connect(host='localhost',
                                     database='absence',
                                     user='root',
                                     password='')

date = datetime.now()
newdate = str(date.year)+"-"+str(date.month)+"-"+str(date.day)

hour = date.hour

interval = '10h12h'


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

    firstname = name.split(" ",1)[1]
    lastname = name.split(" ",1)[0]

    test = """ INSERT INTO abs
            SELECT %s, %s, %s,%s,'justif'
                FROM dual
                WHERE NOT EXISTS (SELECT * FROM abs
                                     WHERE  
                                     Date =%s and Heure= %s and Prenom=%s and Nom=%s)"""
    cursor = connection.cursor()
    cursor.execute(test,(newdate,interval,firstname,lastname,newdate,interval,firstname,lastname))
    connection.commit()
    print(cursor.rowcount, "Record inserted successfully into Laptop table")
    cursor.close()



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('Webcam', img)
    cv2.waitKey(1)