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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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 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)