import cv2 as cv
from system.shared import LastErrorHolder
import imutils
import numpy as np
import datetime
class MotionDetectorBase(LastErrorHolder):
"""
Base class for motion detection support
"""
def __init__(self):
LastErrorHolder.__init__(self)
# previous frame
self.prevFrame = None
# DTS (date & time) of moment when last motion was detected
self.motionDetectionDts = None
self.resizeBeforeDetect = True
self.multiFrameDetection = False
def preprocessInputFrame(self, newFrame):
if self.resizeBeforeDetect:
return imutils.resize(newFrame, width=500, height=500)
return newFrame.copy()
def checkMotionDetected(self, frame):
"""
Checks that motion detected.
:param frame: new frame from camera
:return: True when motion detected, otherwise False
"""
return False
def updateMotionDetectionDts(self):
self.motionDetectionDts = datetime.datetime.utcnow()
class MotionDetectorV1(MotionDetectorBase):
def __init__(self):
MotionDetectorBase.__init__(self)
self.threshold = 8
def motionDetected(self, new_frame):
frame = self.preprocessInputFrame(new_frame)
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (21, 21), 0)
if self.prevFrame is None:
self.prevFrame = gray
return False
# compute the absolute difference between the current frame and
# first frame
frameDelta = cv.absdiff(gray, self.prevFrame)
thresh = cv.threshold(frameDelta, 25, 255, cv.THRESH_BINARY)[1]
# dilate the thresholded image to fill in holes, then find contours
# on thresholded image
thresh = cv.dilate(thresh, None, iterations=2)
(cnts, _, _) = cv.findContours(thresh.copy(), cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
height = np.size(gray, 0)
width = np.size(gray, 1)
nb = height * width
qty = 0
for c in cnts:
a = cv.boundingRect(c)
(x, y, w, h) = a
s = w * h
pcs = (float(s) / float(nb)) * 100
if pcs < self.threshold:
continue
# cv.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
qty += 1
break
# cv.imshow("frame", frame)
self.prevFrame = gray
ret = (qty > 0)
if ret:
self.updateMotionDetectionDts()
return ret
class MotionDetectorV2(MotionDetectorBase):
def __init__(self):
MotionDetectorBase.__init__(self)
self.threshold = 1
def motionDetected(self, new_frame):
frame = self.preprocessInputFrame(new_frame)
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (21, 21), 0)
if self.prevFrame is None:
self.prevFrame = gray
return False
frameDiff = cv.absdiff(gray, self.prevFrame)
# kernel = np.ones((5, 5), np.uint8)
opening = cv.morphologyEx(frameDiff, cv.MORPH_OPEN, None) # noqa
closing = cv.morphologyEx(frameDiff, cv.MORPH_CLOSE, None) # noqa
ret1, th1 = cv.threshold(frameDiff, 10, 255, cv.THRESH_BINARY)
height = np.size(th1, 0)
width = np.size(th1, 1)
nb = cv.countNonZero(th1)
avg = (nb * 100) / (height * width) # Calculate the average of black pixel in the image
self.prevFrame = gray
# cv.DrawContours(currentframe, self.currentcontours, (0, 0, 255), (0, 255, 0), 1, 2, cv.CV_FILLED)
# cv.imshow("frame", current_frame)
ret = avg > self.threshold # If over the ceiling trigger the alarm
if ret:
self.updateMotionDetectionDts()
return ret
class MotionDetectorV3(MotionDetectorBase):
def __init__(self):
MotionDetectorBase.__init__(self)
self.threshold = 1000
self.prevPrevFrame = None
def diffImg(self, t0, t1, t2):
d1 = cv.absdiff(t2, t1)
d2 = cv.absdiff(t1, t0)
return cv.bitwise_and(d1, d2)
def motionDetected(self, new_frame):
frame = self.preprocessInputFrame(new_frame)
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (11, 11), 0)
if self.prevPrevFrame is None:
self.prevPrevFrame = gray
return False
if self.prevFrame is None:
self.prevFrame = gray
return False
cv.normalize(gray, gray, 0, 255, cv.NORM_MINMAX)
frameDiff = self.diffImg(self.prevPrevFrame, self.prevFrame, gray)
ret1, th1 = cv.threshold(frameDiff, 10, 255, cv.THRESH_BINARY)
cv.dilate(th1, None, iterations=15)
cv.erode(th1, None, iterations=1)
delta_count = cv.countNonZero(th1)
cv.imshow("frame_th1", th1)
self.prevPrevFrame = self.prevFrame
self.prevFrame = gray
ret = delta_count > self.threshold
if ret:
self.updateMotionDetectionDts()
return ret
class MotionDetector(MotionDetectorBase):
def __init__(self):
MotionDetectorBase.__init__(self)
self.threshold = 1500
self.prevPrevFrame = None
def diffImg(self, t0, t1, t2):
if not self.multiFrameDetection:
return cv.absdiff(t2, t1)
d1 = cv.absdiff(t2, t1)
d2 = cv.absdiff(t1, t2)
return cv.bitwise_and(d1, d2)
def motionDetected(self, new_frame):
frame = self.preprocessInputFrame(new_frame)
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (11, 11), 0)
if (self.multiFrameDetection) and (self.prevPrevFrame is None):
self.prevPrevFrame = gray
return False
if self.prevFrame is None:
self.prevFrame = gray
return False
cv.normalize(gray, gray, 0, 255, cv.NORM_MINMAX)
frameDiff = self.diffImg(self.prevPrevFrame, self.prevFrame, gray)
ret1, th1 = cv.threshold(frameDiff, 10, 255, cv.THRESH_BINARY)
th1 = cv.dilate(th1, None, iterations=8)
th1 = cv.erode(th1, None, iterations=4)
delta_count = cv.countNonZero(th1)
if self.multiFrameDetection:
self.prevPrevFrame = self.prevFrame
self.prevFrame = gray
if delta_count < self.threshold:
return False
if self.multiFrameDetection:
self.prevPrevFrame = self.prevFrame
self.prevFrame = gray
self.updateMotionDetectionDts()
return True
class MotionDetectorV3Traced(MotionDetectorBase):
def __init__(self):
MotionDetectorBase.__init__(self)
self.threshold = 1500
self.prevPrevFrame = None
self.produceContoursFrame = False
self.contoursFrame = None
self.productDiffFrame1 = False
self.diffFrame1 = None
self.productDiffFrame2 = False
self.diffFrame2 = None
def diffImg(self, t0, t1, t2):
if not self.multiFrameDetection:
return cv.absdiff(t2, t1)
d1 = cv.absdiff(t2, t1)
d2 = cv.absdiff(t1, t2)
return cv.bitwise_and(d1, d2)
def motionDetected(self, new_frame):
frame = self.preprocessInputFrame(new_frame)
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (11, 11), 0)
if (self.multiFrameDetection) and (self.prevPrevFrame is None):
self.prevPrevFrame = gray
return False
if self.prevFrame is None:
self.prevFrame = gray
return False
cv.normalize(gray, gray, 0, 255, cv.NORM_MINMAX)
frameDiff = self.diffImg(self.prevPrevFrame, self.prevFrame, gray)
ret1, th1 = cv.threshold(frameDiff, 10, 255, cv.THRESH_BINARY)
if self.productDiffFrame1:
self.diffFrame1 = th1.copy()
th1 = cv.dilate(th1, None, iterations=8)
th1 = cv.erode(th1, None, iterations=4)
if self.productDiffFrame2:
self.diffFrame2 = th1.copy()
delta_count = cv.countNonZero(th1)
if self.multiFrameDetection:
self.prevPrevFrame = self.prevFrame
self.prevFrame = gray
if delta_count < self.threshold:
return False
if self.produceContoursFrame:
self.contoursFrame = frame.copy()
im2, contours, hierarchy = cv.findContours(th1, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
for c in contours:
cv.drawContours(self.contoursFrame, [c], 0, (0, 0, 255), 2)
# (x, y, w, h) = cv.boundingRect(c)
# cv.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
if self.multiFrameDetection:
self.prevPrevFrame = self.prevFrame
self.prevFrame = gray
self.updateMotionDetectionDts()
return True
class MotionDetectorV4(MotionDetectorBase):
def __init__(self):
MotionDetectorBase.__init__(self)
self.threshold = 10
self.prevPrevFrame = None
def diffImg(self, t0, t1, t2):
d1 = cv.absdiff(t2, t1)
d2 = cv.absdiff(t1, t0)
return cv.bitwise_and(d1, d2)
def motionDetected(self, new_frame):
frame = self.preprocessInputFrame(new_frame)
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (11, 11), 0)
if self.prevPrevFrame is None:
self.prevPrevFrame = gray
return False
if self.prevFrame is None:
self.prevFrame = gray
return False
cv.normalize(gray, gray, 0, 255, cv.NORM_MINMAX)
frameDiff = self.diffImg(self.prevPrevFrame, self.prevFrame, gray)
ret1, th1 = cv.threshold(frameDiff, 10, 255, cv.THRESH_BINARY)
cv.dilate(th1, None, iterations=4)
cv.erode(th1, None, iterations=2)
totalArea = 0
im2, contours, hierarchy = cv.findContours(th1, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
for c in contours:
totalArea += cv.contourArea(c)
cv.drawContours(frame, [c], 0, (0, 0, 255), 2)
if totalArea < self.threshold:
return False
cv.imshow("frame_th1", frame)
self.prevPrevFrame = self.prevFrame
self.prevFrame = gray
self.updateMotionDetectionDts()
return True
