docs: def facial_features(image, cloud=None, batch=False, api_key=None, version=None, **kwargs):
      """
      Given an grayscale input image of a face, returns a 48 dimensional feature vector explaining that face.
      Useful as a form of feature engineering for face oriented tasks.
      Input should be in a list of list format, resizing will be attempted internally but for best
      performance, images should be already sized at 48x48 pixels.
  
      Example usage:
  
      .. code-block:: python
  
         >>> from indicoio import facial_features
         >>> import numpy as np
         >>> face = np.zeros((48,48))
         >>> features = facial_features(face)
         >>> len(features)
         48
  
      :param image: The image to be analyzed.
      :type image: list of lists
      :rtype: List containing feature responses
      """
      image = data_preprocess(image, batch=batch, size=None if kwargs.get("detect") else (48, 48))
      url_params = {"batch": batch, "api_key": api_key, "version": version}
      return api_handler(image, cloud=cloud, api="facialfeatures", url_params=url_params, **kwargs)