# import the necessary packages
import imutils
import cv2

class BasicMotionDetector:
	def __init__(self, accumWeight=0.5, deltaThresh=5, minArea=5000):

		self.isv2 = imutils.is_cv2()
		self.accumWeight = accumWeight
		self.deltaThresh = deltaThresh
		self.minArea = minArea


		self.avg = None

	def update(self, image):

		locs = []

		# if the average image is None, initialize it
		if self.avg is None:
			self.avg = image.astype("float")
			return locs


		cv2.accumulateWeighted(image, self.avg, self.accumWeight)
		frameDelta = cv2.absdiff(image, cv2.convertScaleAbs(self.avg))


		thresh = cv2.threshold(frameDelta, self.deltaThresh, 255,
			cv2.THRESH_BINARY)[1]
		thresh = cv2.dilate(thresh, None, iterations=2)

		cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL,
			cv2.CHAIN_APPROX_SIMPLE)
		cnts = cnts[0] if self.isv2 else cnts[1]


		for c in cnts:
			if cv2.contourArea(c) > self.minArea:
				locs.append(c)
		return locs

7e709675bfeb9b4a3662471cbb09bfb1546adcc0
<mask token>


class BasicMotionDetector:
    <mask token>
    <mask token>

<mask token>


class BasicMotionDetector:
    <mask token>

    def update(self, image):
        locs = []
        if self.avg is None:
            self.avg = image.astype('float')
            return locs
        cv2.accumulateWeighted(image, self.avg, self.accumWeight)
        frameDelta = cv2.absdiff(image, cv2.convertScaleAbs(self.avg))
        thresh = cv2.threshold(frameDelta, self.deltaThresh, 255, cv2.
            THRESH_BINARY)[1]
        thresh = cv2.dilate(thresh, None, iterations=2)
        cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.
            CHAIN_APPROX_SIMPLE)
        cnts = cnts[0] if self.isv2 else cnts[1]
        for c in cnts:
            if cv2.contourArea(c) > self.minArea:
                locs.append(c)
        return locs

<mask token>


class BasicMotionDetector:

    def __init__(self, accumWeight=0.5, deltaThresh=5, minArea=5000):
        self.isv2 = imutils.is_cv2()
        self.accumWeight = accumWeight
        self.deltaThresh = deltaThresh
        self.minArea = minArea
        self.avg = None

    def update(self, image):
        locs = []
        if self.avg is None:
            self.avg = image.astype('float')
            return locs
        cv2.accumulateWeighted(image, self.avg, self.accumWeight)
        frameDelta = cv2.absdiff(image, cv2.convertScaleAbs(self.avg))
        thresh = cv2.threshold(frameDelta, self.deltaThresh, 255, cv2.
            THRESH_BINARY)[1]
        thresh = cv2.dilate(thresh, None, iterations=2)
        cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.
            CHAIN_APPROX_SIMPLE)
        cnts = cnts[0] if self.isv2 else cnts[1]
        for c in cnts:
            if cv2.contourArea(c) > self.minArea:
                locs.append(c)
        return locs

import imutils
import cv2


class BasicMotionDetector:

    def __init__(self, accumWeight=0.5, deltaThresh=5, minArea=5000):
        self.isv2 = imutils.is_cv2()
        self.accumWeight = accumWeight
        self.deltaThresh = deltaThresh
        self.minArea = minArea
        self.avg = None

    def update(self, image):
        locs = []
        if self.avg is None:
            self.avg = image.astype('float')
            return locs
        cv2.accumulateWeighted(image, self.avg, self.accumWeight)
        frameDelta = cv2.absdiff(image, cv2.convertScaleAbs(self.avg))
        thresh = cv2.threshold(frameDelta, self.deltaThresh, 255, cv2.
            THRESH_BINARY)[1]
        thresh = cv2.dilate(thresh, None, iterations=2)
        cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.
            CHAIN_APPROX_SIMPLE)
        cnts = cnts[0] if self.isv2 else cnts[1]
        for c in cnts:
            if cv2.contourArea(c) > self.minArea:
                locs.append(c)
        return locs

# import the necessary packages
import imutils
import cv2

class BasicMotionDetector:
	def __init__(self, accumWeight=0.5, deltaThresh=5, minArea=5000):

		self.isv2 = imutils.is_cv2()
		self.accumWeight = accumWeight
		self.deltaThresh = deltaThresh
		self.minArea = minArea


		self.avg = None

	def update(self, image):

		locs = []

		# if the average image is None, initialize it
		if self.avg is None:
			self.avg = image.astype("float")
			return locs


		cv2.accumulateWeighted(image, self.avg, self.accumWeight)
		frameDelta = cv2.absdiff(image, cv2.convertScaleAbs(self.avg))


		thresh = cv2.threshold(frameDelta, self.deltaThresh, 255,
			cv2.THRESH_BINARY)[1]
		thresh = cv2.dilate(thresh, None, iterations=2)

		cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL,
			cv2.CHAIN_APPROX_SIMPLE)
		cnts = cnts[0] if self.isv2 else cnts[1]


		for c in cnts:
			if cv2.contourArea(c) > self.minArea:
				locs.append(c)
		return locs
