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:
    # python capture the first frame
    check, frame = video.read()
    status=0
    # converts to gray
    gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    # blur the gray, apply gaussianblur
    gray=cv2.GaussianBlur(gray,(21,21),0)

    # store the first frame to first_name
    if first_frame is None:
        first_frame=gray
        continue
        
    # calculate the difference between the first frame and the current frame
    delta_frame=cv2.absdiff(first_frame,gray)
    tresh_frame=cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
    tresh_frame=cv2.dilate(tresh_frame, None, iterations=2)

    # find contours
    (cnts,_) = cv2.findContours(tresh_frame.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    

    for contour in cnts:
        # if loop finds contours greater than 10000
        # changes status 0 to 1
        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)

    # save only the last 2
    status_list=status_list[-2:]

    # compare the last 2 items in the list
    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("Capturing", gray)
    cv2.imshow("Delta Frame", delta_frame)
    cv2.imshow("Threshold Frame", tresh_frame)
    cv2.imshow("Color Frame", frame)

    key=cv2.waitKey(1)

    # print(gray)
    # print(delta_frame)

    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()