code: def scale_intrinsics(
      camera_matrix: Tensor, scale_factor: Union[float, Tensor]
  ) -> Tensor:
      r"""Scale a camera matrix containing the intrinsics.
  
      Applies the scaling factor to the focal length and center of projection.
  
      Args:
          camera_matrix: the camera calibration matrix containing the intrinsic
            parameters. The expected shape for the tensor is :math:`(B, 3, 3)`.
          scale_factor: the scaling factor to be applied.
  
      Returns:
          The scaled camera matrix with shame shape as input :math:`(B, 3, 3)`.
      """
      K_scale = camera_matrix.clone()
      K_scale[..., 0, 0] *= scale_factor
      K_scale[..., 1, 1] *= scale_factor
      K_scale[..., 0, 2] *= scale_factor
      K_scale[..., 1, 2] *= scale_factor
      return K_scale
  
file_path: kornia/kornia/geometry/epipolar/projection.py
imports: from typing import Tuple, Union
  import torch
  from torch.linalg import qr
  from kornia.core import Tensor, concatenate, ones_like, pad, stack, zeros_like
  from kornia.utils import eye_like, vec_like
  from kornia.utils.helpers import _torch_svd_cast
  from .numeric import cross_product_matrix
label_desc: Use image node_id 3 for calling a global function with example usage: scale_intrinsics(camera_matrix, scale_factor) and returns: K_scale