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    :Î®c   ã                   @   sJ   d dl mZ d dlmZ d dl mZ d dlmZ d dlZi i fdd„Z	dS )é    )Úsanity_check_image)Úlkm_laplacian)Útrimap_split)ÚcgNc                    s–   t | ƒ t| fi |¤Ž\‰ }t|ƒ\}}}}d}	|	| ‰|	| }
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    Estimate alpha from an input image and an input trimap as described in Fast Matting Using Large Kernel Matting Laplacian Matrices by :cite:`he2010fast`.

    Parameters
    ----------
    image: numpy.ndarray
        Image with shape :math:`h \times  w \times d` for which the alpha matte should be estimated
    trimap: numpy.ndarray
        Trimap with shape :math:`h \times  w` of the image
    laplacian_kwargs: dictionary
        Arguments passed to the :code:`lkm_laplacian` function
    cg_kwargs: dictionary
        Arguments passed to the :code:`cg` solver

    Returns
    -------
    alpha: numpy.ndarray
        Estimated alpha matte

    Example
    -------
    >>> from pymatting import *
    >>> image = load_image("data/lemur/lemur.png", "RGB")
    >>> trimap = load_image("data/lemur/lemur_trimap.png", "GRAY")
    >>> alpha = estimate_alpha_lkm(
    ...     image,
    ...     trimap,
    ...     laplacian_kwargs={"epsilon": 1e-6, "radius": 15},
    ...     cg_kwargs={"maxiter":2000})

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inv_diag_Ar   r   Újacobi9   s   z"estimate_alpha_lkm.<locals>.jacobiÚMr   é   )r   r   r   r   ÚnpÚclipÚreshapeÚshape)ÚimageÚtrimapÚlaplacian_kwargsÚ	cg_kwargsÚdiag_LÚis_fgÚis_bgÚis_knownÚ
is_unknownÚlambda_valueÚbr   r   r	   Úalphar   )r
   r   r   r   Úestimate_alpha_lkm   s   !r"   )
Úpymatting.util.utilr   Ú!pymatting.laplacian.lkm_laplacianr   r   Úpymatting.solver.cgr   Únumpyr   r"   r   r   r   r   Ú<module>   s    