motion_detector.py

import cv2 ,time
import pandas as pd 
from datetime import datetime

# face_cascade=cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
video=cv2.VideoCapture(0)
# video=cv2.VideoCapture(0,cv2.CAP_DSHOW)
# video=cv2.VideoCapture("anna.mp4")
video.read()
time.sleep(2)

times=[]
status_list=[None,None]
first_frame=None

df=pd.DataFrame(columns=["Start","End"])




while True:
 check, frame= video.read()
 status=0
 
 gray= cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
 gray=cv2.GaussianBlur(gray,(21,21),0) #### Convert for more resolution and accuracy to Gaussian 

 if first_frame is None:
 first_frame=gray
 continue
 # Delta frame difference between furst frame anthe current frame this differne will give another image 
 delta_frame=cv2.absdiff(first_frame,gray)
 thresh_frame=cv2.threshold(delta_frame, 30 , 255, cv2.THRESH_BINARY)[1]
 
 #to remove the black area and smooth the images
 thresh_frame=cv2.dilate(thresh_frame,None,iterations=2)

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


 '''
 The function dilates the source image using the specified structuring element that determines the .
 shape of a pixel neighborhood over which the maximum is taken
 The contours
 are a useful tool for shape analysis and object detection and recognition
 '''

 for contour in cnts:
 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)

 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('Color Frame',frame)
 cv2.imshow("delta",delta_frame)
 cv2.imshow("Threshold frame",thresh_frame)

 key=cv2.waitKey(1)

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