code: def Resize_rotated_box(transform, rotated_boxes):
      """
      Apply the resizing transform on rotated boxes. For details of how these (approximation)
      formulas are derived, please refer to :meth:`RotatedBoxes.scale`.
  
      Args:
          rotated_boxes (ndarray): Nx5 floating point array of
              (x_center, y_center, width, height, angle_degrees) format
              in absolute coordinates.
      """
      scale_factor_x = transform.new_w * 1.0 / transform.w
      scale_factor_y = transform.new_h * 1.0 / transform.h
      rotated_boxes[:, 0] *= scale_factor_x
      rotated_boxes[:, 1] *= scale_factor_y
      theta = rotated_boxes[:, 4] * np.pi / 180.0
      c = np.cos(theta)
      s = np.sin(theta)
      rotated_boxes[:, 2] *= np.sqrt(
          np.square(scale_factor_x * c) + np.square(scale_factor_y * s)
      )
      rotated_boxes[:, 3] *= np.sqrt(
          np.square(scale_factor_x * s) + np.square(scale_factor_y * c)
      )
      rotated_boxes[:, 4] = (
          np.arctan2(scale_factor_x * s, scale_factor_y * c)
          * 180
          / np.pi
      )
  
      return rotated_boxes
  
imports: import numpy
  import torch
  import torch.nn.functional
  from fvcore.transforms.transform import CropTransform, HFlipTransform, NoOpTransform, Transform, TransformList
  from PIL import Image
label_desc: Use image node_id 2 for calling a global function with example usage: Resize_rotated_box(transform, rotated_boxes) and returns: rotated_boxes