Facial-recognition-system

Face recognition matches faces from images with a database. Real-time processing is a challenge. Two variants: digital onboarding (registering faces) and authentication (verifying users).

Segments-

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

from PIL import ImageGrab

path = 'Training_images' 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): 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}')

FOR CAPTURING SCREEN RATHER THAN WEBCAM

def captureScreen(bbox=(300,300,690+300,530+300)):

capScr = np.array(ImageGrab.grab(bbox))

capScr = cv2.cvtColor(capScr, cv2.COLOR_RGB2BGR)

return capScr

encodeListKnown = findEncodings(images) print('Encoding Complete')

cap = cv2.VideoCapture(0)

while True: success, img = cap.read()

img = captureScreen()

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)