motion_detector.py

from datetime import datetime

import cv2
import pandas

first_frame = None
video = cv2.VideoCapture(0)
status_list = [None, None]
times = []
df = pandas.DataFrame(columns=['Start', 'End'])

while True:
    check, frame = video.read()
    status = 0
    try:
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (21, 21), 0)
    except cv2.error:
        print('Your camera was not detected')
        quit()

    if first_frame is None:
        first_frame = gray
        continue

    delta_frame = cv2.absdiff(first_frame, gray)
    thresh_frame = cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
    thresh_frame = cv2.dilate(thresh_frame, None, iterations=2)

    (_, contours, _) = cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    for contour in contours:
        if cv2.contourArea(contour) < 3000:
            continue
        status = 1
        (x, y, width, height) = cv2.boundingRect(contour)
        cv2.rectangle(frame, (x, y), (x + width, y + height), (255, 255, 0), 3)
    status_list.append(status)

    status_list = status_list[-2:]

    if status_list[-1] == 1 and status_list[-2] == 0:
        times.append(datetime.now())
    if status_list[-1] == 0 and status_list[-2] == 1:
        times.append(datetime.now())

    cv2.imshow('Motion Detector', frame)

    key = cv2.waitKey(1)
    if key == ord('q'):
        if status == 1:
            times.append(datetime.now())
        break

for i in range(0, len(times), 2):
    df = df.append({'Start': times[i], 'End': times[i + 1]}, ignore_index=True)

df.to_csv('results/Times.csv')
video.release()
cv2.destroyAllWindows()