def METHOD_NAME(ibs, aid_list, verbose=VERBOSE_AZURE, **kwargs):
    """Classify aid_list with azure.
    Args:
        aid_list (list of int): the list of IBEIS annotation rowids that need classifying
    Kwargs (optional): refer to the Azure documentation for configuration settings
    Yields:
        tuple: (gid, gpath, result_list)
    """
    # Get new gpaths if downsampling
    chip_filepath_list = ibs.get_annot_chip_fpath(aid_list, ensure=True)
    # Run detection
    results_iter = label(chip_filepath_list, verbose=verbose, **kwargs)
    # Package the results
    for chip_filepath, result_dict in results_iter:
        species_list = ut.take_column(result_dict, 'species_common')
        confidence_list = np.array(ut.take_column(result_dict, 'confidence'))
        confidence_list *= 0.01
        index = np.argmax(confidence_list)
        species = species_list[index]
        confidence = confidence_list[index]
        viewpoint = const.UNKNOWN
        quality = const.QUAL_UNKNOWN
        orientation = 0.0
        probability_dict = dict(zip(species_list, confidence_list))
        yield confidence, species, viewpoint, quality, orientation, probability_dict