code: def preprocess_input(self, inp):
      return np.array(imagenet_utils.get_resize_transform()(inp))
  
file_path: tensorwatch/tensorwatch/saliency/lime_image_explainer.py
imports: from skimage.segmentation import mark_boundaries
  from torchvision import transforms
  import torch
  from .lime import lime_image
  import numpy
  from ..None import imagenet_utils, pytorch_utils, utils
label_desc: Use image node_id 3 for calling the LimeImagenetExplainer obj's underlying member method code with example usage: obj.preprocess_input(inp) and returns: np