face.py

import face_recognition, cv2, csv, os
import numpy as np
import datetime as datetime

video_capture = cv2.VideoCapture(0)

kachkol_image = face_recognition.load_image_file("photos/kachkol.jpg")
kachkol_encoding = face_recognition.face_encodings(kachkol_image)[0]

asa_image = face_recognition.load_image_file("photos/asa.jpg")
asa_encoding = face_recognition.face_encodings(asa_image)[0]

known_face_encoding = [
    kachkol_image, 
    asa_encoding
]

known_faces_names = [
    "Kachkol",
    "Asa"
]

people = 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(rgb_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 people:
                    people.remove(name)
                    print(people)
                    current_time = now.strftime("%H-%M-%S")
                    lnwriter.writerow([name, current_time])
    cv2.imshow("attendence system", frame)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

video_capture.release()
cv2.destroyAllWindows()
f.close()