import cv2, time, pandas
import numpy as np
from datetime import datetime

first_frame=None
status_list=[None,None]
times=[]
df=pandas.DataFrame(columns=["Start","End"])

video=cv2.VideoCapture("C://Users//anjali patil//Downloads//input.mp4") #capture video

while True:
    check, frame = video.read()
    status=0
    gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    gray=cv2.GaussianBlur(gray,(21,21),0)


    #this is used to store the first frame of video
    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)

    (cnts,_)=cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)#define the contour area. basically, add the bourders

    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)

    status_list=status_list[-2:]

    #record datetime in a list when change in a list when change occurs
    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("Gray Frame",gray)
    cv2.imshow("Delta Frame",delta_frame)
    cv2.imshow("Threshold Frame",thresh_frame)
    cv2.imshow("Color Frame",frame)

    key=cv2.waitKey(1)

    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) #store time values in a dataframe

df.to_csv("Times.csv") #write the dataframe to a CSV file

video.release()
cv2.destroyAllWindows()
