Motion Detection in Python.py

from pickle import NONE
import cv2
import time
from cv2 import cvtColorTwoPlane
import pandas
from datetime import datetime

from numpy import get_array_wrap
status_list=[None,None]
times=[]
df=pandas.DataFrame(columns=["Start","End"])
video=cv2.VideoCapture(0,cv2.CAP_DSHOW)
first_frame=NONE
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(gray,first_frame)
    thresh_frame=cv2.threshold(delta_frame,30,255,cv2.THRESH_BINARY)[1]
    thesh_frame=cv2.dilate(thresh_frame,None,iterations=2)

    (cnts,_)=cv2.findContours(thresh_frame.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    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("video",gray)
    cv2.imshow("delta_frame",delta_frame)
    cv2.imshow("Threshold",thresh_frame)
    cv2.imshow("Frame",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):
    if i==len(times):
        break
    df=df.append({"Start":times[i],"End":times[i+1]},ignore_index=True)
df.to_csv("Times.csv")
video.release()
cv2.destroyAllWindows()