Face-Recognition-with-Masks/AttendanceProject.py at main · yudhisteer/Face-Recognition-with-Masks · GitHub

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

path = 'ImagesAttendance'
images = []     # LIST CONTAINING ALL THE IMAGES
className = []    # LIST CONTAINING ALL THE CORRESPONDING CLASS Names
myList = os.listdir(path)
print(myList)
print("Total Classes Detected:",len(myList))

for x,cl in enumerate(myList):
        curImg = cv2.imread(f'{path}/{cl}')
        images.append(curImg)
        className.append(os.path.splitext(cl)[0])

print(className)

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):
    #reading and writing csv at the same time
    with open('Attendance.csv','r+') as f:
        myDataList = f.readlines()
        nameList =[]
        for line in myDataList:
            entry = line.split(',')
            nameList.append(entry[0]) #append only names in list

        if name not in  line:
            now = datetime.now()
            dt_string = now.strftime("%H:%M:%S")
            f.writelines(f'\n{name},{dt_string}')

encodeListKnown = findEncodings(images)
print(len(encodeListKnown))
print('Encodings Complete')

cap = cv2.VideoCapture(0)

while True:
    # Webcam Image
    success, img = cap.read()
    imgS = cv2.resize(img, (0, 0), fx=0.25, fy=0.25)
    imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)

    #Webcam Encoding
    facesCurFrame = face_recognition.face_locations(imgS)
    encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)

    #Find Matches
    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 = className[matchIndex].upper()
            print(name)
            y1, x2, y2, x1 = faceLoc
            y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4 #Because we reduced size of image above
            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_DUPLEX, 1.0, (255, 255, 255), 1)
            markAttendance(name)

        # if faceDis[matchIndex] < 0.50:
        #     name = classNames[matchIndex].upper()
        #     markAttendance(name)
        # else:
        #     name = 'Unknown'
        # # 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)


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