def METHOD_NAME(slice_index='centre', backend='tigre', tolerance=0.005, search_range=None, initial_binning=None, **kwargs):
    """This creates a CentreOfRotationCorrector processor.
    The processor will find the centre offset by maximising the sharpness of a reconstructed slice.
    Can be used on single slice parallel-beam, and centre slice cone beam geometry. For use only with datasets that can be reconstructed with FBP/FDK.
    Parameters
    ----------
    slice_index : int, str, default='centre'
        An integer defining the vertical slice to run the algorithm on. The special case slice 'centre' is the default.
    backend : {'tigre', 'astra'}
        The backend to use for the reconstruction
    tolerance : float, default=0.005
        The tolerance of the fit in pixels, the default is 1/200 of a pixel. This is a stopping criteria, not a statement of accuracy of the algorithm.
    search_range : int
        The range in pixels to search either side of the panel centre. If `None` a quarter of the width of the panel is used.  
    initial_binning : int
        The size of the bins for the initial search. If `None` will bin the image to a step corresponding to <128 pixels. The fine search will be on unbinned data.
    Other Parameters
    ----------------
    **kwargs : dict
        FBP : The FBP class to use as the backend imported from `cil.plugins.[backend].FBP`  - This has been deprecated please use 'backend' instead
    Example
    -------
    from cil.processors import CentreOfRotationCorrector
    processor = CentreOfRotationCorrector.image_sharpness('centre', 'tigre')
    processor.set_input(data)
    data_centred = processor.get_output()
    Example
    -------
    from cil.processors import CentreOfRotationCorrector
    processor = CentreOfRotationCorrector.image_sharpness(slice_index=120, 'astra')
    processor.set_input(data)
    processor.get_output(out=data)
    Note
    ----
    For best results data should be 360deg which leads to blurring with incorrect geometry.
    This method is unreliable on half-scan data with 'tuning-fork' style artifacts.
    """
    processor = CofR_image_sharpness(slice_index=slice_index, backend=backend, tolerance=tolerance, search_range=search_range, initial_binning=initial_binning, **kwargs)
    return processor