code: def check_boxes_in_area_range(
      boxes: np.ndarray, area_range: Tuple[float, float]
  ) -> np.ndarray:
      """Check boxes whether their areas fall in a given range.
  
      Args:
       boxes: a numpy array representing the bounding boxes in the following format
         [LEFT, TOP, RIGHT, BOTTOM, CLASS, CONFIDENCE(Optional)]
       area_range: [lowerbound(inclusive), upperbound(inclusive)] of the box area
  
      Returns:
       A numpy array of bool indicates whether the box is in the range.
      """
      if boxes.ndim != 2 or boxes.shape[1] <= 3:
          raise ValueError(
              "Input boxes list should be a 2d array of shape "
              "(<batch_size>,4+)"
          )
  
      if len(area_range) != 2:
          raise ValueError("Invalid shape of area_range")
      if area_range[1] <= area_range[0]:
          raise ValueError(
              "Invalid input of area range: lower bound is greater"
              "or equal to upperbound"
          )
  
      area = bounding_box_area(boxes)
      return (area_range[0] <= area) & (area <= area_range[1])
  
imports: from typing import Iterable, Tuple
  import warnings
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: check_boxes_in_area_range(boxes, area_range) and returns: unknown