diff --git a/1.mp4 b/1.mp4 new file mode 100644 index 0000000..985c209 Binary files /dev/null and b/1.mp4 differ diff --git a/motion_detector.py b/motion_detector.py new file mode 100644 index 0000000..588dcf7 --- /dev/null +++ b/motion_detector.py @@ -0,0 +1,72 @@ +from imutils.video import VideoStream +import argparse +import datetime +import imutils +import time +import cv2 + + +import traceback +import _thread + + + +def compare(): + try: + url = "1.mp4" + + min_area = 100 + max_area = 30000 + + threashold = 10 + + # initialize the first frame in the video stream + vs = cv2.VideoCapture(url) + + res = vs.read()[0] + firstFrame = None + # loop over the frames of the video + while res: + + res, frame = vs.read() + + # resize the frame, convert it to grayscale, and blur it + frame = imutils.resize(frame, width=500) + cv2.imshow( "frame", frame ) + gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) + gray = cv2.GaussianBlur(gray, (31, 31), 0) + + # if the first frame is None, initialize it + if firstFrame is None: + firstFrame = gray + continue + + frameDelta = cv2.absdiff(gray, firstFrame) + + thresh = cv2.threshold(frameDelta, threashold, 255, cv2.THRESH_BINARY)[1] + + + # dilate the thresholded image to fill in holes, then find contours + thresh = cv2.dilate(thresh, None, iterations=3) + 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 cv2.contourArea(c) < min_area or cv2.contourArea(c) > max_area: + continue + + (x, y, w, h) = cv2.boundingRect(c) + cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2) + text = "Occupied" + + + cv2.imshow( "annotated", frame ) + print("1") + + cv2.waitKey(10) & 0XFF + + except Exception as e: + traceback.print_exc() + +compare()