9iq1SSKrSSKJr SSKJr SSKJr SSKJ r SSK r SSK J r SSK Jr SS KJr S r\4S jrS r\ R*"5S SS.Sj5rg)N)sparse)spsolve)laplace)utils)label)_build_matrix_innercr[R"X- S5n[R"X-S-U5nX44$)Nrr )npmaximumminimum)nd_idxradiusnd_shape bounds_lo bounds_his [/var/www/html/land-doc-ocr/venv/lib/python3.13/site-packages/skimage/restoration/inpaint.py_get_neighborhoodr s4 6?A.I 6?Q.9I  c[R"XS9nSX1'[[U55n[R"U5nX4n[R"USS9nX4U4$)Ndtyper raxis)r zerosrwherestack)shapecenterr neigh_coefcoef_idx coef_valss r_get_neigh_coefr$sZ%-JJ,-Jxx #H$Ixxq)H  **rc. URSnURSS-n[R"UR[S9nSU[ Xw*54UR -'X-n U)U-n [R "U 5n [R"U 5n [R"U 5n [R"X45n[R "U 5n[[X5VVs/sHunn[R"UU45PM snn5nUS:gn[R"UU[RSS9nUUR5n[R"U5n[R"U5nU[R"UU:H5- n[R "U[R"S9n[R$"UU4UR&S9n[R "U[R"S9n[R "U[R"S9n[R "UUR&S9n0nUR)S5n[R*"UR)SU455n Sn!Sn"Sn#[R,"U SS9n [/U 5GHun#n$[1U$XqR5un%n&[U&U%- 5n'[U$U%- 5n(UR3U'U(4S 5un)n*U)c"[5U'U(UR&S9un+n)n*U)U*4UU'U(4'U)U%S S 2[R64-n)[R8"U)UR5n,Sn-[U*U,5HFun.n/UU/(aU#UU"'U/UU"'U.UU"'U"S- n"M&UU!S S 24==U.U U/S S 24--ss'U-S- n-MH U-(dGMU#UU!'U!S- n!GM" U#S-n0U!n1U"n2[;U0U1U2U UUUU UUUUU5 n3US U3nUS U32S S 24nUUR<4n4[>R@"UUU44U4S 9n5U5S S 2U4n5[R$"UU4UR&S9n6UU6US S 24'[CU5U6S S S9n7U7R S:XaU7S S 2[R64n7U7UU'U$s snnf)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. rrrconstant)outputmoder r)NNN)rFMMD_ATA) use_umfpack permc_spec)"rr onesboolslicendimr flatnonzero concatenatetuplezipndiconvolveuint8sum count_nonzeroemptyintprrreshapeascontiguousarrayr enumeratergetr$newaxisravel_multi_indexr sizer csr_arrayr)8imagemaskoutneigh_coef_fullr#raveled_offsets n_channelsr edge_mask boundary_mask center_mask boundary_pts boundary_icenter_imask_i center_ptsbcmask_pts structuretmp nnz_matrixn_maskn_structnnz_rhs_vector_max row_idx_known data_knownrow_idx_unknowncol_idx_unknown data_unknown coef_cache mask_flatout_flat idx_known idx_unknown mask_pt_nrb_lob_hi coef_shape coef_centerr"coefs_index1dnvalscoefi row_startknown_start_idxunknown_start_idxnnz_rhssp_shapematrix_unknownrhsresults8 r!_inpaint_biharmonic_single_regionrx!sD2J  " "1 % *F $/I78IuVW%'$))34$M*t#K88M*L .J~~k*H ^^Z2 3F+&J\9VW9VAbnnaV,9VWXH 1$I ,,tYrxxj ICTJ  d #F *H""2"23(?"CCHH/rww?M-z:#))LJhhz9Ohhz9O88Jcii8LJ R I##CKKZ0@$ABHIKI88Lq1L&|4 6&vvzzB d4$;' FTM* $..*k)BLQ%  !0Ksyy" Ax6>u4EJ K0 1d1bjj=11&&x<5'*GD!|/8 ,/0 ,,0 [)q 9a<(D8AqD>,AA( + 5'0M) $ NI?5DA IO#!!G("(7+MHWHaK(J!H%% 9:(N $AvI.N ((FJ'syy 9C&C q^Se RF {{a2:: &CM JcXs.%R F)split_into_regions channel_axisc ^URS:a [S5eUSLnU(aURSSO URnXQR:wa [S5e[RR U5(a [ S5e[R"U5n[R"UR5nURUSS9nUR[SS9nU(dUS [R4n[R"US S 9nS mS T-S-4UR-nT4UR-n [!XURS 9upn UR"Sn U T- nX)nUR%SS9UR'SS94nU(Ga@[(R*"URS5n[(R,"UUS9n[/U5nUU-n[(R0"U5n[3US5Hunn[5U4Sj[7UUR555nUUU:HnU[9S54- nUUR5n[R:"USR"Vs/sHnUU -PM sn5n[R<"UUS [R4-SS9n[?UUUUU U U5 UUU'M Op[R:"USR"Vs/sHnUU -PM sn5n[R<"UUS [R4-SS9n[?XXzU U5 [R@"UUSUSUS9 U(dUSnU$s snfs snf)a\Inpaint 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) r z!Input array has to be at least 1DNr&z&Input arrays have to be the same shapezMasked arrays are not supportedF)copy.C)orderrrrr)rUc3># UHAup[[URT- S5[URT-U55v MC g7f)rN)r/maxstartminstop).0slrBrs r %inpaint_biharmonic..*sD AHBc"((V+Q/RWWv5Et1LMM AsA A ).r)a_mina_maxrF)!r0 ValueErrorrr ma isMaskedArray TypeErrorskimage img_as_floatr_supported_float_typerastyper.r@r|r$stridesrrr5generate_binary_structurebinary_dilationr find_objectsr>r3r4r/arrayr8rxclip)rDrEryrz multichannel img_baseshape float_dtyperFrhrirGr"r#channel_stride_bytesoffsets known_pointslimitskernel mask_dilated mask_labeled bbox_slices idx_regionbb_sliceroi_sl mask_regionotmpsostridesrHrs @rinpaint_biharmonicrsTd zzA~<==t+L(4EKK$%++M "ABB uu5!!9::   'E--ekk:K LL5L 1E ;;t%; (D c2::o& ''%s #CFf*q."TYY.J)dii'K+:syy,(Oy ;;r?G>88F @S@ST@S1Q"66@STU&&8CO+D!D1M) y/ GGCvayq s; &k J;J Us 7M0 6M5)numpyr scipyrscipy.sparse.linalgr scipy.ndimagendimager5rr_sharedrmeasurer_inpaintr rfloatr$rxchannel_as_last_axisrrrrsZ'!) */ +aH:?dNNr