How to calculate active hours of an employee using face_recognition for attendance tracking

Question

I am working on face recognition system for my academic project. I want to set the first time an employee was recognized as his first active time and the next time he is being recognized should be recorded as his last active time and then calculate the total active hours based on first active and last active time.

I tried with the following code but I'm getting only the current system time as the start time. can someone help me on what I am doing wrong.

Code:

data = pickle.loads(open(args["encodings"], "rb").read())

vs = VideoStream(src=0).start()

writers = None

time.sleep(2.0)

while True:

frame = vs.read()

rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

rgb = imutils.resize(frame, width=750)

r = frame.shape[1] / float(rgb.shape[1])

boxes = face_recognition.face_locations(rgb)

encodings = face_recognition.face_encodings(rgb, boxes)

names = []

face_names = []

for encoding in encodings:

    matches = face_recognition.compare_faces(data["encodings"],

      encoding)

    name = "Unknown"

if True in matches:

        matchedIdxs = [i for (i, b) in enumerate(matches) if b]

        counts = {}

        for i in matchedIdxs:

            name = data["names"][i]

            counts[name] = counts.get(name, 0) + 1

        name = max(counts, key=counts.get)

    names.append(name)

if names != []:
    for i in names:
        first_active_time = datetime.now().strftime('%H:%M')
        last_active_time = datetime.now().strftime('%H:%M')

        difference = datetime.strptime(first_active_time, '%H:%M') - datetime.strptime(last_active_time, '%H:%M')
        difference = difference.total_seconds()

        total_hours = time.strftime("%H:%M", time.gmtime(difference))
        face_names.append([i, first_active_time, last_active_time, total_hours])