Designed for surveillance over long periods of time

movementDetector.py

"""
TODO:
* only do caclulation if cooldown is finished
* make directory (opencv doesn't cast exceptions on write errors)
* sort from biggest to smallest area, and save the image with the biggest detection area of that frame shown.
"""
import argparse
import datetime
import time
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser(description="When movement is detected, an image is save (with indication of the movement area). ")
ap.add_argument("-a", "--min-area", type=int, default = 200, help="minimum area size")
ap.add_argument("-c", "--cool-down", type=int, default = 10, help="the lowest time interval (in sec) between two images")
args = vars(ap.parse_args())
 

#load camera
# initialize the camera and grab a reference to the raw camera capture
#camera = PiCamera()
camera = cv2.VideoCapture(0)

#init the background substractor
fgbg = cv2.BackgroundSubtractorMOG2(history = 1000, varThreshold = 100, bShadowDetection = False)

lastDetection = time.time()

# loop over the frames of the video
#for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):

while True:
        
        currentTime = time.time()
        ret, frame = camera.read()
 
        #resize, grayscale and blur
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (11, 11), 0)

        #bg substract method
        bg = fgbg.apply(gray, learningRate = 1.0/150)

        #dialate some more
        bg = cv2.dilate(bg, None, iterations=2)

        (cnts, _) = cv2.findContours(bg.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

	# 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,
                (x, y, w, h) = cv2.boundingRect(c)
                cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)

                # sace image if no cooldown
                if lastDetection + args["cool_down"] < currentTime:
                        lastDetection = currentTime
                        nameString = "detected/" + time.ctime() + ".jpg"
                        cv2.imwrite(nameString, frame)
                        print("saving to: " + nameString)
                        
        cv2.waitKey(1)