# USAGE
# python motion_detector.py
# python motion_detector.py --video videos/example_01.mp4

# import the necessary packages
from imutils.video import VideoStream
import argparse
import datetime
import imutils
import time
import cv2
import yagmail
import os
import subprocess

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the video file")
ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
args = vars(ap.parse_args())

# if the video argument is None, then we are reading from webcam
if args.get("video", None) is None:
    vs = VideoStream(src=0).start()
    time.sleep(2.0)

# otherwise, we are reading from a video file
else:
	vs = cv2.VideoCapture(args["video"])

# initialize the first frame in the video stream
firstFrame = None
frames_array = []
# firstFrame = cv2.imread('2.png', 0)
# firstFrame = imutils.resize(firstFrame, width=500)
# firstFrame = cv2.GaussianBlur(firstFrame, (21, 21), 0)
lastUploaded = datetime.datetime.now()
motionCounter = 0
writer = None
(h, w) = (None, None)
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'DIVX')
# out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))

# loop over the frames of the video
while True:
    # grab the current frame and initialize the occupied/unoccupied
    # text
    frame = vs.read()
    frame = frame if args.get("video", None) is None else frame[1]
    text = "Unoccupied"
    timestamp = datetime.datetime.now()

    # if the frame could not be grabbed, then we have reached the end
    # of the video
    if frame is None:
        break

    # resize the frame, convert it to grayscale, and blur it
    frame = imutils.resize(frame, width=500)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21, 21), 0)

    # if the first frame is None, initialize it
    if firstFrame is None:
    	firstFrame = gray
    	continue

    # compute the absolute difference between the current frame and
    # first frame
    frameDelta = cv2.absdiff(firstFrame, gray)
    thresh = cv2.threshold(frameDelta, 100, 255, cv2.THRESH_BINARY)[1]

    # dilate the thresholded image to fill in holes, then find contours
    # on thresholded image
    thresh = cv2.dilate(thresh, None, iterations=2)
    cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
        cv2.CHAIN_APPROX_SIMPLE)
    cnts = imutils.grab_contours(cnts)

    # loop over the contours
    for c in cnts:
        # if the contour is too small, ignore it
        if cv2.contourArea(c) < args["min_area"]:
            continue

        # compute the bounding box for the contour, draw it on the frame,
        # and update the text
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
        text = "Occupied"

    if text == "Occupied":
            # check to see if enough time has passed between uploads
        if (timestamp - lastUploaded).seconds >= 4:
                # increment the motion counter
                motionCounter += 1
                print("inside occupied",motionCounter)
                # write the flipped frame
                # frame = imutils.resize(frame, width=300)
                (h, w) = frame.shape[:2]
                frames_array.append(frame)
                

                # check to see if the number of frames with consistent motion is
                # high enough
                if motionCounter >= 4:
                    # check to see if dropbox sohuld be used
                        # write the image to temporary file
                        cv2.imwrite('messigray.png',frame)
                        print("limit exceeded",motionCounter)
                        lastUploaded = timestamp
                        motionCounter = 0
                        # out.release()

                    # update the last uploaded timestamp and reset the motion
                    # counter
                    
    # otherwise, the room is not occupied
    else:
        motionCounter = 0

    # draw the text and timestamp on the frame
    cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2)
    cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
        (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)



    # show the frame and record if the user presses a key
    cv2.imshow("Security Feed", frame)
    cv2.imshow("Thresh", thresh)
    cv2.imshow("Frame Delta", frameDelta)
    key = cv2.waitKey(1) & 0xFF

    # if the `q` key is pressed, break from the lop
    if key == ord("q"):
        break


# os.system('spd-say "Suspicious activity detected"')
#subprocess.call(['/usr/bin/snap/vlc', ""])
writer = cv2.VideoWriter("custom.avi", fourcc, 20,(w , h ), True)
key = cv2.waitKey(1) & 0xFF
print(frames_array)
for i in range(len(frames_array)):
    # writing to a image array
    writer.write(frames_array[i])  
writer.release()
# cleanup the camera and close any open windows
vs.stop() if args.get("video", None) is None else vs.release()
cv2.destroyAllWindows()