I have this opencv python code for motion detection. A rectangle box will outline the detected motion. Now i want to execute a statement(eg: print("you are standing in the frame for more than a minute"). The statement should be executed only when the person stands for more than 60 seconds.else the loop should run normally. This is my code.

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I have this opencv python code for motion detection. A rectangle box will outline the detected motion. Now i want to execute a statement(eg: print("you are standing in the frame for more than a minute"). The statement should be executed only when the person stands for more than 60 seconds.else the loop should run normally. This is my code.

# import the necessary packages

# 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 = cnts[0] if imutils.is_cv2() else cnts[1]

# 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

link text

I have this opencv python code for motion detection. A rectangle box will outline the detected motion. Now i want to execute a statement(eg: print("you are standing in the frame for more than a minute"). The statement should be executed only when the person stands for more than 60 seconds.else the loop should run normally. This is my code.

# import the necessary packages

from imutils.video import VideoStream import argparse import datetime import imutils import time import cv2

cv2 # construct the argument parser and parse the arguments

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())

vars(ap.parse_args()) # if the video argument is None, then we are reading from webcam

webcam if args.get("video", None) is None: vs = VideoStream(src=0).start() time.sleep(2.0)

time.sleep(2.0) # otherwise, we are reading from a video file

file else: vs = cv2.VideoCapture(args["video"])

cv2.VideoCapture(args["video"]) # initialize the first frame in the video stream

stream firstFrame = None

None # loop over the frames of the video

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"

"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 = cnts[0] if imutils.is_cv2() else cnts[1]

 # 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

windows vs.stop() if args.get("video", None) is None else vs.release() cv2.destroyAllWindows()

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