docstr: Applies necessary transformations to the image prior to segmentation.
  
  Parameters
  ----------
  image
      A grayscale or RGB image.
  
  Returns
  -------
  A preprocessed image.
docstr_tok: ["Applies","necessary","transformations","to","the","image","prior","to","segmentation",".","Parameters","--","--","--","--","--","image","A","grayscale","or","RGB","image",".","Returns","--","--","--","-","A","preprocessed","image","."]
code: def _preprocess_img(self, image: np.ndarray) -> np.ndarray:
      """
      Applies necessary transformations to the image prior to segmentation.
  
      Parameters
      ----------
      image
          A grayscale or RGB image.
  
      Returns
      -------
      A preprocessed image.
      """
  
      # Grayscale images are repeated across channels
      if not self.custom_segmentation and image.shape[-1] == 1:
          image_preproc = np.repeat(image, 3, axis=2)
      else:
          image_preproc = image.copy()
  
      return image_preproc
  
imports: import copy
  import logging
  from functools import partial
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
  import numpy
  from skimage.segmentation import felzenszwalb, quickshift, slic
  from alibi.api.defaults import DEFAULT_DATA_ANCHOR_IMG, DEFAULT_META_ANCHOR
  from alibi.api.interfaces import Explainer, Explanation
  from alibi.exceptions import PredictorCallError, PredictorReturnTypeError
  from alibi.utils.wrappers import ArgmaxTransformer
  from .anchor_base import AnchorBaseBeam
  from .anchor_explanation import AnchorExplanation
label_desc: Use image node_id 7 for calling the AnchorImageSampler obj's underlying member method code with example usage: obj._preprocess_img(image) and returns: image_preproc