code: def corner_shi_tomasi(image, sigma=1):
      """Compute Shi-Tomasi (Kanade-Tomasi) corner measure response image.
  
      This corner detector uses information from the auto-correlation matrix A::
  
          A = [(imx**2)   (imx*imy)] = [Axx Axy]
              [(imx*imy)   (imy**2)]   [Axy Ayy]
  
      Where imx and imy are first derivatives, averaged with a gaussian filter.
      The corner measure is then defined as the smaller eigenvalue of A::
  
          ((Axx + Ayy) - sqrt((Axx - Ayy)**2 + 4 * Axy**2)) / 2
  
      Parameters
      ----------
      image : (M, N) ndarray
          Input image.
      sigma : float, optional
          Standard deviation used for the Gaussian kernel, which is used as
          weighting function for the auto-correlation matrix.
  
      Returns
      -------
      response : ndarray
          Shi-Tomasi response image.
  
      References
      ----------
      .. [1] https://en.wikipedia.org/wiki/Corner_detection
  
      Examples
      --------
      >>> from skimage.feature import corner_shi_tomasi, corner_peaks
      >>> square = np.zeros([10, 10])
      >>> square[2:8, 2:8] = 1
      >>> square.astype(int)
      array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
      >>> corner_peaks(corner_shi_tomasi(square), min_distance=1)
      array([[2, 2],
             [2, 7],
             [7, 2],
             [7, 7]])
  
      """
  
      Arr, Arc, Acc = structure_tensor(image, sigma, order="rc")
  
      # minimum eigenvalue of A
      response = (
          (Arr + Acc) - np.sqrt((Arr - Acc) ** 2 + 4 * Arc**2)
      ) / 2
  
      return response
  
imports: import functools
  import math
  from itertools import combinations_with_replacement
  import numpy
  from scipy import ndimage
  from scipy import spatial, stats
  from .._shared.filters import gaussian
  from .._shared.utils import _supported_float_type, safe_as_int, warn
  from ..transform import integral_image
  from ..util import img_as_float
  from ._hessian_det_appx import _hessian_matrix_det
  from .corner_cy import _corner_fast, _corner_moravec, _corner_orientations
  from .peak import peak_local_max
  from .util import _prepare_grayscale_input_2D, _prepare_grayscale_input_nD
label_desc: Use image node_id 13 for calling a global function with example usage: corner_shi_tomasi(image, sigma) and returns: response