motion_detector.py

import cv2,time,pandas
from datetime import datetime

first_frame = None
status_list = [None,None]
times = []
df=pandas.DataFrame(columns=["start","End"])
video = cv2.VideoCapture(0)
while True:
    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_delta = cv2.threshold(delta_frame,30,255,cv2.THRESH_BINARY)
     thresh_delta = cv2.dilate(thresh_delta,None, iterations=0)
     (_,cnts,_) = cv2.findContours(thresh_delta.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
     key = cv2.waitKey(1)
     if key == ord('q'):
         break
for contour in cnts :
    if cv2.contourArea(contour) < 1000:
        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('frame',frame)
      cv2.imshow('capturing',gray)
      cv2.imshow('delta',delta_frame)
      cv2.imshow('thresh',thresh_delta)

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()