docs: def facial_localization(image, cloud=None, batch=False, api_key=None, version=None, **kwargs):
      """
      Given an image, returns a list of faces found within the image.
      For each face, we return a dictionary containing the upper left corner and lower right corner.
      If crop is True, the cropped face is included in the dictionary.
      Input should be in a numpy ndarray or a filename.
  
      Example usage:
  
      .. code-block:: python
  
         >>> from indicoio import facial_localization
         >>> import numpy as np
         >>> img = np.zeros([image of a face])
         >>> faces = facial_localization(img)
         >>> len(faces)
         1
  
      :param image: The image to be analyzed.
      :type image: filepath or ndarray
      :rtype: List of faces (dict) found.
      """
      image = data_preprocess(image, batch=batch)
      url_params = {"batch": batch, "api_key": api_key, "version": version}
      return api_handler(image, cloud=cloud, api="faciallocalization", url_params=url_params, **kwargs)