import cv2,time,pandas
from datetime import datetime

df=pandas.DataFrame(columns=["Entered","Left"])
video=cv2.VideoCapture(0)
times=[]
key=""
first_frame=None
status_list=[None,None]
while key!=ord("s"):
    status=0
    check, frame=video.read()
    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)

    (conts,_) =cv2.findContours(thresh_frame.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    
    for contour in conts:
        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("Capturing",frame)
    cv2.imshow("Delta",delta_frame)
    cv2.imshow("Thresh",thresh_frame)

    key=cv2.waitKey(1)


if status==1:
    times.append(datetime.now())

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

df.to_csv("log.csv")

print(times)
video.release()
cv2.destroyAllWindows()