code: def scale_bbox_to_transformed_image(
      top: float,
      left: float,
      bottom: float,
      right: float,
      scale_factor: float,
  ) -> List[int]:
      top_scaled = original_to_transformed_w_coords(
          np.array([top / 2]), scale_factor
      )[0]
      left_scaled = original_to_transformed_h_coords(
          np.array([left / 2]), scale_factor
      )[0]
      bottom_scaled = original_to_transformed_w_coords(
          np.array([bottom / 2]), scale_factor
      )[0]
      right_scaled = original_to_transformed_h_coords(
          np.array([right / 2]), scale_factor
      )[0]
      return [top_scaled, left_scaled, bottom_scaled, right_scaled]
  
imports: import re
  from typing import Dict, List, Optional, Tuple, Union
  import numpy
  from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import PaddingStrategy, TruncationStrategy
  from ...utils import TensorType, is_torch_available, logging, requires_backends
label_desc: Use image node_id 11 for calling a global function with example usage: scale_bbox_to_transformed_image(top, left, bottom, right, scale_factor) and returns: list