code: def _mask_border_keypoints(image_shape, keypoints, distance):
      """Mask coordinates that are within certain distance from the image border.
  
      Parameters
      ----------
      image_shape : (2,) array_like
          Shape of the image as ``(rows, cols)``.
      keypoints : (N, 2) array
          Keypoint coordinates as ``(rows, cols)``.
      distance : int
          Image border distance.
  
      Returns
      -------
      mask : (N,) bool array
          Mask indicating if pixels are within the image (``True``) or in the
          border region of the image (``False``).
  
      """
  
      rows = image_shape[0]
      cols = image_shape[1]
  
      mask = (
          ((distance - 1) < keypoints[:, 0])
          & (keypoints[:, 0] < (rows - distance + 1))
          & ((distance - 1) < keypoints[:, 1])
          & (keypoints[:, 1] < (cols - distance + 1))
      )
  
      return mask
  
file_path: scikit-image/skimage/feature/util.py
imports: import numpy
  from ..util import img_as_float
  from .._shared.utils import _supported_float_type, check_nD
label_desc: Use image node_id 4 for calling a global function with example usage: _mask_border_keypoints(image_shape, keypoints, distance) and returns: mask