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98 lines
2.8 KiB
Python
98 lines
2.8 KiB
Python
#!/usr/bin/env python
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# coding=utf-8
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# USAGE
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# python motion_detector.py
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# python motion_detector.py --video videos/example_01.mp4
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# import the necessary packages
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import imutils
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from imutils.video import VideoStream
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import argparse
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import datetime
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import time, sys
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from time import sleep
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import cv2
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# construct the argument parser and parse the arguments
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ap = argparse.ArgumentParser()
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ap.add_argument("-a", "--min-area", type=int, default=6000, help="minimum area size")
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args = vars(ap.parse_args())
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# if the video argument is None, then we are reading from webcam
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vs = VideoStream(usePiCamera=True).start()
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sleep(2.0)
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# initialize the first frame in the video stream
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firstFrame = None
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occupied = False
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# loop over the frames of the video
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while True:
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# grab the current frame and initialize the occupied/unoccupied
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# text
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frame = vs.read()
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frame = frame if args.get("video", None) is None else frame[1]
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text = "Unoccupied"
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# if the frame could not be grabbed, then we have reached the end
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# of the video
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if frame is None:
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break
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# resize the frame, convert it to grayscale, and blur it
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frame = imutils.resize(frame, width=500)
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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gray = cv2.GaussianBlur(gray, (21, 21), 0)
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# if the first frame is None, initialize it
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if firstFrame is None:
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firstFrame = gray
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continue
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# compute the absolute difference between the current frame and
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# first frame
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frameDelta = cv2.absdiff(firstFrame, gray)
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thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
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# dilate the thresholded image to fill in holes, then find contours
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# on thresholded image
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thresh = cv2.dilate(thresh, None, iterations=2)
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cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
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cv2.CHAIN_APPROX_SIMPLE)
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cnts = cnts[0] if imutils.is_cv2() else cnts[1]
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# loop over the contours
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for c in cnts:
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# if the contour is too small, ignore it
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if cv2.contourArea(c) < args["min_area"]:
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continue
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# compute the bounding box for the contour, draw it on the frame,
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# and update the text
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(x, y, w, h) = cv2.boundingRect(c)
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cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
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text = "Occupied"
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if not occupied:
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occupied = True
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print ('occupied')
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sys.exit()
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if occupied and text == "Unoccupied":
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occupied = False
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print ("Unoccupied")
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# # show the frame and record if the user presses a key
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# # cv2.imshow("Security Feed", frame)
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# cv2.imwrite('security.jpg', frame)
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# #cv2.imshow("Thresh", thresh)
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# cv2.imwrite('threshold.jpg', thresh)
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# #cv2.imshow("Frame Delta", frameDelta)
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# cv2.imwrite('blured.jpg', frameDelta)
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# #key = cv2.waitKey(1) & 0xFF
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#
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# # if the `q` key is pressed, break from the lop
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# #if key == ord("q"):
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# # break
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# cleanup the camera and close any open windows
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vs.stop() if args.get("video", None) is None else vs.release()
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#cv2.destroyAllWindows()
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