code: def random_intrinsics(
      low: Union[float, Tensor], high: Union[float, Tensor]
  ) -> Tensor:
      r"""Generate a random camera matrix based on a given uniform distribution.
  
      Args:
          low: lower range (inclusive).
          high: upper range (exclusive).
  
      Returns:
          the random camera matrix with the shape of :math:`(1, 3, 3)`.
      """
      sampler = torch.distributions.Uniform(low, high)
      fx, fy, cx, cy = (
          sampler.sample(torch.Size((1,))) for _ in range(4)
      )
      zeros, ones = zeros_like(fx), ones_like(fx)
      camera_matrix = concatenate(
          [fx, zeros, cx, zeros, fy, cy, zeros, zeros, ones]
      )
      return camera_matrix.view(1, 3, 3)
  
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 2 for calling a global function with example usage: random_intrinsics(low, high) and returns: camera_matrix