code: def resize_point(point, in_size, out_size):
      """Adapt point coordinates to the rescaled image space.
  
      Args:
          point (~numpy.ndarray or list of arrays): See the table below.
          in_size (tuple): A tuple of length 2. The height and the width
              of the image before resized.
          out_size (tuple): A tuple of length 2. The height and the width
              of the image after resized.
  
      .. csv-table::
          :header: name, shape, dtype, format
  
          :obj:`point`, ":math:`(R, K, 2)` or :math:`[(K, 2)]`", \
          :obj:`float32`, ":math:`(y, x)`"
  
      Returns:
          ~numpy.ndarray or list of arrays:
          Points rescaled according to the given image shapes.
  
      """
      y_scale = float(out_size[0]) / in_size[0]
      x_scale = float(out_size[1]) / in_size[1]
      if isinstance(point, np.ndarray):
          out_point = point.copy()
          out_point[:, :, 0] = y_scale * point[:, :, 0]
          out_point[:, :, 1] = x_scale * point[:, :, 1]
      else:
          out_point = []
          for pnt in point:
              out_pnt = pnt.copy()
              out_pnt[:, 0] = y_scale * pnt[:, 0]
              out_pnt[:, 1] = x_scale * pnt[:, 1]
              out_point.append(out_pnt)
      return out_point
  
label_desc: Use image node_id 1 for calling a global function with example usage: resize_point(point, in_size, out_size) and returns: out_point