Motion_Detector.py

import cv2 , time
import pandas
from datetime import datetime

status_list = [None , None]
times = []
first_frame = None
df = pandas.DataFrame(columns = ["Start" , "End"])

video = cv2.VideoCapture(0)

a = 0
while True:
    a = a + 1
    check , frame = video.read()
    status = 0
    gray = cv2.cvtColor(frame , cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21,21), 0)

    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, hierarchy = cv2.findContours(thresh_frame.copy() , cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    for contour in contours:
        if cv2.contourArea(contour) < 10000:
            continue
        status = 1
        (x, y, w, h)=cv2.boundingRect(contour)
        cv2.rectangle(frame, (x, y), (x+w, y+h), (0,255,0), 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("Gray Frame" , gray)
    cv2.imshow("Delta Frame", delta_frame)
    cv2.imshow("ThreshHold", thresh_frame)
    cv2.imshow("Color Frame", frame)

    key = cv2.waitKey(1)

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

print(status_list)
print(times)

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


df.to_csv("Times.csv")
video.release()
cv2.destroyAllWindows()