# USAGE
# python multi_cam_motion.py

# import the necessary packages
from __future__ import print_function
from pyimagesearch.basicmotiondetector import BasicMotionDetector
from imutils.video import VideoStream
import numpy as np
import datetime
import imutils
import time
import cv2

# initialize the video streams and allow them to warmup
print("[INFO] starting cameras...")
webcam1 = VideoStream(src=0).start()
webcam2 = VideoStream(src=1).start()

time.sleep(2.0)

# initialize the two motion detectors, along with the total
# number of frames read
camMotion = BasicMotionDetector()
piMotion = BasicMotionDetector()
total = 0

# loop over frames from the video streams
while True:
    # initialize the list of frames that have been processed
    frames = []

    # loop over the frames and their respective motion detectors
    for (stream, motion) in zip((webcam1, webcam2), (camMotion, piMotion)):
        # read the next frame from the video stream and resize
        # it to have a maximum width of 400 pixels
        frame = stream.read()
        frame = imutils.resize(frame, width=400)
        roomText = "Unoccupied"

        # convert the frame to grayscale, blur it slightly, update
        # the motion detector
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (21, 21), 0)
        locs = motion.update(gray)

        # we should allow the motion detector to "run" for a bit
        # and accumulate a set of frames to form a nice average
        if total < 32:
            frames.append(frame)
            continue

        # otherwise, check to see if motion was detected
        if len(locs) > 0:
            # initialize the minimum and maximum (x, y)-coordinates,
            # respectively
            (minX, minY) = (np.inf, np.inf)
            (maxX, maxY) = (-np.inf, -np.inf)

            # loop over the locations of motion and accumulate the
            # minimum and maximum locations of the bounding boxes
            for l in locs:
                (x, y, w, h) = cv2.boundingRect(l)
                (minX, maxX) = (min(minX, x), max(maxX, x + w))
                (minY, maxY) = (min(minY, y), max(maxY, y + h))

            # draw the bounding box
            cv2.rectangle(frame, (minX, minY), (maxX, maxY),
                (0, 0, 255), 3)
            roomText = "Occupied"
        if roomText == "Occupied":
                        print("Recording...")
                        cv2.VideoWriter.write(frames)

        # update the frames list
        frames.append(frame)

    # increment the total number of frames read and grab the
    # current timestamp
    total += 1
    timestamp = datetime.datetime.now()
    ts = timestamp.strftime("%A %d %B %Y %I:%M:%S%p")

    # loop over the frames a second time
    for (frame, name) in zip(frames, ("Camera1", "Camera2")):
        # draw the timestamp on the frame and display it
        cv2.putText(frame, ts, (10, frame.shape[0] - 10),
            cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
        cv2.putText(frame, "Room Status: {}".format(roomText), (10, 20),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
        cv2.imshow(name, frame)

    # check to see if a key was pressed
    key = cv2.waitKey(1) & 0xFF

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

# do a bit of cleanup
print("[INFO] cleaning up...")
cv2.destroyAllWindows()
webcam1.stop()
webcam2.stop()