o &?e~2@sddlZddlmZddlmZddlmZddlm Z ddl Z ddl m Z ddl mZdd lmZd d Zefd d ZddZe dddddZdS)N)sparse)spsolve)laplace)utils)label)_build_matrix_innercCs,t||d}t||d|}||fS)Nrr)npmaximumminimum)nd_idxradiusZnd_shapeZ bounds_loZ bounds_hir\/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/skimage/restoration/inpaint.py_get_neighborhood srcCsLtj||d}d||<tt|}t|}||}tj|dd}|||fS)NdtyperrZaxis)r zerosrwherestack)shapecenterrZ neigh_coefcoef_idx coef_valsrrr_get_neigh_coefs   rc6Cs|jd}|jdd}tj|jtd}d|t|| f|j<||} ||} t| } t| } t| } t| | f}t| }t ddt | |D}|dk}t j ||tj dd}||}t|}t|}|t||k}tj|tjd}tj||f|jd}tj|tjd}tj|tjd}tj||jd}i}|d}t|d|f}d}d} d}!tj| d d } t| D]\}!}"t|"||j\}#}$t |$|#}%t |"|#}&||%|&fd \}'}(|'d urt|%|&|jd\})}'}(|'|(f||%|&f<|'|#d d tjf}'t|'|j}*d}+t |(|*D]4\},}-||-r1|!|| <|-|| <|,|| <| d 7} q||d d f|,||-d d f8<|+d 7}+q|+rV|!||<|d 7}q|!d }.|}/| }0t|.|/|0| ||||||||| }1|d |1}|d |1d d f}||jf}2tj |||ff|2d !}3|3d d |f}3tj||f|jd}4||4|d d f<t"|3|4ddd}5|5jd kr|5d d tjf}5|5||<|S)aSolve a (sparse) linear system corresponding to biharmonic inpainting. This function creates a linear system of the form: ``A @ u = b`` where ``A`` is a sparse matrix, ``b`` is a vector enforcing smoothness and boundary constraints and ``u`` is the vector of inpainted values to be (uniquely) determined by solving the linear system. ``A`` is a sparse matrix of shape (n_mask, n_mask) where ``n_mask`` corresponds to the number of non-zero values in ``mask`` (i.e. the number of pixels to be inpainted). Each row in A will have a number of non-zero values equal to the number of non-zero values in the biharmonic kernel, ``neigh_coef_full``. In practice, biharmonic kernels with reduced extent are used at the image borders. This matrix, ``A`` is the same for all image channels (since the same inpainting mask is currently used for all channels). ``u`` is a dense matrix of shape ``(n_mask, n_channels)`` and represents the vector of unknown values for each channel. ``b`` is a dense matrix of shape ``(n_mask, n_channels)`` and represents the desired output of convolving the solution with the biharmonic kernel. At mask locations where there is no overlap with known values, ``b`` will have a value of 0. This enforces the biharmonic smoothness constraint in the interior of inpainting regions. For regions near the boundary that overlap with known values, the entries in ``b`` enforce boundary conditions designed to avoid discontinuity with the known values. rrrcSsg|] \}}t||fqSr)r concatenate).0bcrrr Qsz5_inpaint_biharmonic_single_region..Zconstant)outputmoderr)NNN)rFZMMD_ATA)Z use_umfpackZ permc_spec)#rr ZonesboolslicendimrZ flatnonzerortuplezipndiZconvolveZuint8sumZ count_nonzeroemptyZintprrZreshapeZascontiguousarrayr enumeratergetrnewaxisZravel_multi_indexr sizerZ coo_matrixZtocsrr)6imagemaskoutneigh_coef_fullrraveled_offsetsZ n_channelsrZ edge_maskZ boundary_maskZ center_maskZ boundary_ptsZ boundary_iZcenter_iZmask_iZ center_ptsZmask_pts structuretmpZ nnz_matrixZn_maskZn_structZnnz_rhs_vector_maxZ row_idx_knownZ data_knownZrow_idx_unknownZcol_idx_unknownZ data_unknownZ coef_cacheZ mask_flatZout_flatZ idx_knownZ idx_unknownZ mask_pt_nr Zb_loZb_hi coef_shape coef_centerrZcoefs_Zindex1dZnvalsZcoefiZ row_startZknown_start_idxZunknown_start_idxZnnz_rhsZsp_shapeZmatrix_unknownrhsresultrrr!_inpaint_biharmonic_single_region!s !               (     r>F)split_into_regions channel_axiscs~|jdkr td|du}|r|jddn|j}||jkr"tdtj|r,tdt|}t |j }|j |dd}|j t dd}|sN|d tjf}tj|d d }d d df|j}f|j} t|| |j d \} } } |jd| } ||}|jdd|jddf}|rt|jd}tj||d}t|}||9}t|}t|dD]R\}}tfddt||jD}|||k}|tdf7}||}tfdd|djD}tj| |d tjfdd}t||||| | ||||<qn&tfdd|djD}tj| |d tjfdd}t|||| | |tj ||d|d|d|s=|d}|S)aInpaint masked points in image with biharmonic equations. Parameters ---------- image : (M[, N[, ..., P]][, C]) ndarray Input image. mask : (M[, N[, ..., P]]) ndarray Array of pixels to be inpainted. Have to be the same shape as one of the 'image' channels. Unknown pixels have to be represented with 1, known pixels - with 0. split_into_regions : boolean, optional If True, inpainting is performed on a region-by-region basis. This is likely to be slower, but will have reduced memory requirements. channel_axis : int or None, optional If None, the image is assumed to be a grayscale (single channel) image. Otherwise, this parameter indicates which axis of the array corresponds to channels. .. versionadded:: 0.19 ``channel_axis`` was added in 0.19. Returns ------- out : (M[, N[, ..., P]][, C]) ndarray Input image with masked pixels inpainted. References ---------- .. [1] S.B.Damelin and N.S.Hoang. "On Surface Completion and Image Inpainting by Biharmonic Functions: Numerical Aspects", International Journal of Mathematics and Mathematical Sciences, Vol. 2018, Article ID 3950312 :DOI:`10.1155/2018/3950312` .. [2] C. K. Chui and H. N. Mhaskar, MRA Contextual-Recovery Extension of Smooth Functions on Manifolds, Appl. and Comp. Harmonic Anal., 28 (2010), 104-113, :DOI:`10.1016/j.acha.2009.04.004` Examples -------- >>> img = np.tile(np.square(np.linspace(0, 1, 5)), (5, 1)) >>> mask = np.zeros_like(img) >>> mask[2, 2:] = 1 >>> mask[1, 3:] = 1 >>> mask[0, 4:] = 1 >>> out = inpaint_biharmonic(img, mask) rz!Input array has to be at least 1DNrz&Input arrays have to be the same shapezMasked arrays are not supportedF)copy.C)orderrrrr)r6c3s6|]\}}tt|jdt|j|VqdS)rN)r&maxstartminstop)rslr0)rrr &s  z%inpaint_biharmonic..cg|]}|qSrrrschannel_stride_bytesrrr"1 z&inpaint_biharmonic..).rcrKrrrLrNrrr">rP)Za_minZa_maxr3)!r' ValueErrorrr maZ isMaskedArray TypeErrorskimageZ img_as_floatrZ_supported_float_typerZastyper%r/rArstridesrGrEr*Zgenerate_binary_structureZbinary_dilationrZ find_objectsr-r(r)r&arrayr+r>Zclip)r1r2r?r@Z multichannelZ img_baseshapeZ float_dtyper3r8r9r4rroffsetsZ known_pointsZlimitsZkernelZ mask_dilatedZ mask_labeledZ bbox_slicesZ idx_regionZbb_sliceZroi_slZ mask_regionZotmpZostridesr5r)rOrrinpaint_biharmonics| 3               rX)numpyr ZscipyrZscipy.sparse.linalgrZ scipy.ndimageZndimager*rrTZ_sharedrmeasurerZ_inpaintr rfloatrr>Zchannel_as_last_axisrXrrrrs