python类BackgroundSubtractorMOG2()的实例源码

def __init__(self):
        super(TargetFilterBGSub, self).__init__()

        # background subtractor
        #self._bgs = cv2.BackgroundSubtractorMOG()
        #self._bgs = cv2.BackgroundSubtractorMOG2()  # not great defaults, and need bShadowDetection to be False
        #self._bgs = cv2.BackgroundSubtractorMOG(history=10, nmixtures=3, backgroundRatio=0.2, noiseSigma=20)

        # varThreshold: higher values detect fewer/smaller changed regions
        self._bgs = cv2.createBackgroundSubtractorMOG2(history=0, varThreshold=8, detectShadows=False)

        # ??? history is ignored?  Only if learning_rate is > 0, or...?  Unclear.

        # Learning rate for background subtractor.
        # 0 = never adapts after initial background creation.
        # A bit above 0 looks good.
        # Lower values are better for detecting slower movement, though it
        # takes a bit of time to learn the background initially.
        self._learning_rate = 0.001

        # elements to reuse in erode/dilate
        # CROSS elimates more horizontal/vertical lines and leaves more
        # blobs with extent in both axes [than RECT].
        self._element_shrink = cv2.getStructuringElement(cv2.MORPH_CROSS,(5,5))
        self._element_grow = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(7,7))

def __init__(self, video_src):
        self.cam = cv2.VideoCapture(video_src)
        ret, self.frame = self.cam.read()
        cv2.namedWindow('gesture_hci')

        # set channel range of skin detection 
        self.mask_lower_yrb = np.array([44, 131, 80])       # [54, 131, 110]
        self.mask_upper_yrb = np.array([163, 157, 155])     # [163, 157, 135]
        # create trackbar for skin calibration
        self.calib_switch = False

        # create background subtractor 
        self.fgbg = cv2.BackgroundSubtractorMOG2(history=120, varThreshold=50, bShadowDetection=True)

        # define dynamic ROI area
        self.ROIx, self.ROIy = 200, 200
        self.track_switch = False
        # record previous positions of the centroid of ROI
        self.preCX = None
        self.preCY = None

        # A queue to record last couple gesture command
        self.last_cmds = FixedQueue()

        # prepare some data for detecting single-finger gesture  
        self.fin1 = cv2.imread('./test_data/index1.jpg')
        self.fin2 = cv2.imread('./test_data/index2.jpg')
        self.fin3 = cv2.imread('./test_data/index3.jpg')

        # switch to turn on mouse input control
        self.cmd_switch = False

        # count loop (frame), for debugging
        self.n_frame = 0


# On-line Calibration for skin detection (bug, not stable)