# 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
# 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
# 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"
# 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, 25, 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"
# draw the text and timestamp on the frame
cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 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
# cleanup the camera and close any open windows
vs.stop() if args.get("video", None) is None else vs.release()
cv2.destroyAllWindows()
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