import cv2, time, pandas
from datetime import datetime


first_frame = None
status_list=[None, None]
times = []
video=cv2.VideoCapture(0)
df = pandas.DataFrame(columns=["Start","End"])
while True:
 
    check, frame = video.read()
    status=0
    # print(check)
    # print(frame)

    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)

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

    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),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("Capturing",gray)
    cv2.imshow("Delta Frame",delta_frame)
    cv2.imshow("Thresh 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)
df.to_csv("Times.csv")



video.release()
cv2.destroyAllWindows

