o :ήc @s6ddlZddlmZmZmZddlmZd ddZdS) N) vec_vec_dot mat_vec_dot vec_vec_outer) boxfilterHz> Tc sBtjdd}||}j\}tdd|}ttdd|}|t||8}tj|||t||t |d|t |tt ddfddfdd} |rtddd} dtdd} | t tdd8} | t | 7} | | fS| S) aCalculates the Laplacian for large kernel matting :cite:`he2010fast` Parameters --------- image: numpy.ndarray Image of shape :math:`h\times w \times 3` epsilons: float Regularization strength, defaults to :math:`10^{-7}` radius: int Radius of local window size, defaults to :math:`10`, i.e. only adjacent pixels are considered. The size of the local window is given as :math:`(2 r + 1)^2`, where :math:`r` denotes the radius. A larger radius might lead to violated color line constraints, but also favors further propagation of information within the image. return_diagonal: bool Whether to also return the diagonal of the laplacian, defaults to True Returns ------- L_matvec: function Function that applies the Laplacian matrix to a vector diag_L: numpy.ndarray Diagonal entries of the matting Laplacian, only returnes if `return_diagonal` is True validmodefullcs|}t|dd}t|ddddtjfdd}|}|ddddtjft|}|tt|dd7}|t|}|t|dd8}|S)Nr r r )reshapernpnewaxisrrflatten)pp_sumspI_sumsp_LtempVVmchimagemVmradiuswH/tmp/pip-target-vg8gfxp4/lib/python/pymatting/laplacian/lkm_laplacian.pyL_matvec.s &&zlkm_laplacian..L_matvecg?) astyperfloat64shaperrlinalginveyerronesr) repsilonrreturn_diagonal window_size window_areadepthmeanscovsr"diag_Lrr rr! lkm_laplacians&   " ( r2)rrT) numpyrpymatting.util.utilrrrpymatting.util.boxfilterrr2r r r r!s