app.py

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

video_capture=cv2.VideoCapture(0)

sir_image=face_recognition.load_image_file("photos/sir.jpeg")
sir_encoding=face_recognition.face_encodings(sir_image)[0]

vikas_image=face_recognition.load_image_file("photos/vikas.jpg")
vikas_encoding=face_recognition.face_encodings(vikas_image)[0]

known_face_encoding=[sir_encoding,vikas_encoding]

known_faces_names=["Sarwan Sir","Vikas"]

students=known_faces_names.copy()

face_locations=[]
face_encodings=[]
face_names=[]
s=True



now=datetime.now()
current_date=now.strftime("%Y-%m-%d")


f=open(current_date+'.csv','w+',newline='')
lnwriter=csv.writer(f)

while True:
    _,frame=video_capture.read()
    small_frame=cv2.resize(frame,(0,0),fx=0.25,fy=0.25)
    rgb_small_frame=small_frame[:,:,::-1]
    if s:
        face_locations=face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(small_frame, face_locations)
        face_names=[]
        for face_encoding in face_encodings:
            matches=face_recognition.compare_faces(known_face_encoding,face_encoding)
            name=""
            face_distance=face_recognition.face_distance(known_face_encoding,face_encoding)
            best_match_index=np.argmin(face_distance)
            if matches[best_match_index]:
                name=known_faces_names[best_match_index]

            face_names.append(name)
            if name in known_faces_names:
                if name in students:
                    students.remove(name)
                    print(students)
                    current_time=now.strftime("%H-%M-%S")
                    lnwriter.writerow([name,current_time,"Present"])
    cv2.imshow("attendence system",frame)
    if cv2.waitKey(1) & 0xFF==ord('q'):
        break
video_capture.release()
cv2.destroyAllWindows()
f.close()