code: def bounding_box_area(boxes: np.ndarray) -> np.ndarray:
      """Compute areas for a list of boxes.
  
      Args:
       boxes: a numpy array with dimenstion [ <batch_size> , 4+] in corners format
         [LEFT, TOP, RIGHT, BOTTOM]
  
      Returns:
       boxes_areas: a numpy array with dimension len(boxes)
      """
      if boxes.ndim != 2 or boxes.shape[1] < 4:
          raise ValueError(
              "Input boxes list should be a 2d array of shape "
              "( <batch_size> , 4+)"
          )
      # Calculate the height and width for each dimension
      if np.any(boxes[:, RIGHT] - boxes[:, LEFT] < 0):
          raise ValueError(
              "The right boundary is less than the left boundary "
              "right = {}, left = {}.".format(
                  boxes[:, RIGHT], boxes[:, LEFT]
              )
          )
      if np.any(boxes[:, BOTTOM] - boxes[:, TOP] < 0):
          raise ValueError(
              "The BOTTOM boundary is less than the TOP boundary "
              "BOTTOM = {}, TOP = {}.".format(
                  boxes[:, BOTTOM], boxes[:, TOP]
              )
          )
      boxes_width = boxes[:, RIGHT] - boxes[:, LEFT]
      boxes_height = boxes[:, BOTTOM] - boxes[:, TOP]
  
      # Calculate the area of each box
      boxes_areas = boxes_width * boxes_height
      return boxes_areas
  
imports: from typing import Iterable, Tuple
  import warnings
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: bounding_box_area(boxes) and returns: boxes_areas