code: def scale_point_to_transformed_image(
      x: float, y: float, scale_factor: float
  ) -> List[int]:
      x_scaled = original_to_transformed_w_coords(
          np.array([x / 2]), scale_factor
      )[0]
      y_scaled = original_to_transformed_h_coords(
          np.array([y / 2]), scale_factor
      )[0]
      return [x_scaled, y_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 10 for calling a global function with example usage: scale_point_to_transformed_image(x, y, scale_factor) and returns: list