class_docstr: build SiamRPNTracker.predicted tracking result.and according to
  tracking result, product window penalty and smooth bbox
  
  Parameters
  ----------
      PENALTY_K : float
          Scale penalty
      WINDOW_INFLUENCE :float
          Window influence
      LR : float
          Interpolation learning rate
      EXEMPLAR_SIZE : int
          EXEMPLAR_SIZE
      INSTANCE_SIZE : int
          INSTANCE_SIZE
      BASE_SIZE : int
          Base size
      CONTEXT_AMOUNT : float
          Context amount
      STRIDE : int
          Anchor stride
      RATIOS : tuple
          Anchor ratios
      SCALES : tuple
          Anchor scales
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docstr: get bbox in image, Make sure the center point of the frame is within the image range
  and boundary
  
  Parameters
  ----------
      center_x : float
          bbox center x location
      center_y : float
          bbox center y location
      width : float
          bbox width location
      height : float
          bbox height location
      boundary : np.ndarray
          img boundary
  
  Returns
  -------
      rejust location within the image range and boundary
docstr_tok: ["get","bbox","in","image",",","Make","sure","the","center","point","of","the","frame","is","within","the","image","range","and","boundary","Parameters","--","--","--","--","--","center_x",":","float","bbox","center","x","location","center_y",":","float","bbox","center","y","location","width",":","float","bbox","width","location","height",":","float","bbox","height","location","boundary",":","np.ndarray","img","boundary","Returns","--","--","--","-","rejust","location","within","the","image","range","and","boundary"]
code: def _bbox_clip(self, center_x, center_y, width, height, boundary):
      """get bbox in image, Make sure the center point of the frame is within the image range
      and boundary
  
      Parameters
      ----------
          center_x : float
              bbox center x location
          center_y : float
              bbox center y location
          width : float
              bbox width location
          height : float
              bbox height location
          boundary : np.ndarray
              img boundary
  
      Returns
      -------
          rejust location within the image range and boundary
      """
      center_x = max(0, min(center_x, boundary[1]))
      center_y = max(0, min(center_y, boundary[0]))
      width = max(10, min(width, boundary[1]))
      height = max(10, min(height, boundary[0]))
      return center_x, center_y, width, height
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import math
  from collections import namedtuple
  import numpy
  import mxnet
  from mxnet import nd
  from gluoncv.utils.filesystem import try_import_cv2
label_desc: Use image node_id 5 for calling the SiamRPNTracker obj's underlying member method code with example usage: obj._bbox_clip(center_x, center_y, width, height, boundary) and returns: center_x,  center_y,  width,  height