o oi}; @sddlZddlmZmZddlZddlmZddlmZddl m Z m Z m Z ddl mZddlmZmZdd lmZdd lmZeeefZd0d edededededef ddZd0d edededededef ddZd1dededededef ddZ d2dejdejdeejd edejf d!d"Z $d3dededed%ed&edef d'd(Zdededefd)d*Z d4dededeedefd+d,Z! $d5dededed%ed&edef d.d/Z"dS)6N)OptionalTuple)Tensor)KORNIA_CHECK_SHAPE)_extract_device_dtypesafe_inverse_with_masksafe_solve_with_mask)_torch_svd_cast)convert_points_from_homogeneousconvert_points_to_homogeneous)normalize_points)transform_pointsT:0yE>pts1pts2HsquaredepsreturncCsnt|gd|ddkrt|}|ddkrt|}t||}||djdd}|r1|S||S)aeReturn transfer error in image 2 for correspondences given the homography matrix. Args: pts1: correspondences from the left images with shape (B, N, 2 or 3). If they are homogeneous, converted automatically. pts2: correspondences from the right images with shape (B, N, 2 or 3). If they are homogeneous, converted automatically. H: Homographies with shape :math:`(B, 3, 3)`. squared: if True (default), the squared distance is returned. eps: Small constant for safe sqrt. Returns: the computed distance with shape :math:`(B, N)`. B3rdim)rsizer rpowsumsqrt)rrrrr pts1_in_2 error_squaredr$N/home/ubuntu/.local/lib/python3.10/site-packages/kornia/geometry/homography.pyoneway_transfer_error#s  r&c Cst|gd|ddkrt|}|ddkrt|}t|jj}t|\}}t|||d|}t|||d|} | dd |} || | |j||  |j} |rZ| S| | S)adReturn Symmetric transfer error for correspondences given the homography matrix. Args: pts1: correspondences from the left images with shape (B, N, 2 or 3). If they are homogeneous, converted automatically. pts2: correspondences from the right images with shape (B, N, 2 or 3). If they are homogeneous, converted automatically. H: Homographies with shape :math:`(B, 3, 3)`. squared: if True (default), the squared distance is returned. eps: Small constant for safe sqrt. Returns: the computed distance with shape :math:`(B, N)`. rrrTr ) rrr torchfinfodtypemaxrr&view expand_astor!) rrrrrmax_numH_invgood_Htherebackgood_H_reshapeoutr$r$r%symmetric_transfer_errorDs & r5Fls1ls2cCst|gdt|gdt|gd|jdd\}}tj|ddd\}}tj|ddd\}} t|} t| } tjj| | dd} tt||} tt||}| | dd  || }| |dd  || }d ||}|ry|d}|S) aReturn transfer error in image 2 for line segment correspondences given the homography matrix. Line segment end points are reprojected into image 2, and point-to-line error is calculated w.r.t. line, induced by line segment in image 2. See :cite:`homolines2001` for details. Args: ls1: line segment correspondences from the left images with shape (B, N, 2, 2). ls2: line segment correspondences from the right images with shape (B, N, 2, 2). H: Homographies with shape :math:`(B, 3, 3)`. squared: if True (default is False), the squared distance is returned. Returns: the computed distance with shape :math:`(B, N)`. rrN2r:Nrrchunksrrrg?) rshaper'chunkr linalgcrossr transposer+abs)r6r7rrrr9ps1pe1ps2pe2ps2_hpe2_hln2ps1_in2pe1_in2er_st1er_end1errorr$r$r%#line_segment_transfer_error_one_wayis" rPlupoints1points2weightssolverc Cs|j|jkr t|j|jddkrt|jt|gdt|gdt||g\}}d}t|\}}t|\} } tj|ddd\} } tj| ddd\} }t| t| }}tj |||| | | || || |g dd}tj | | ||||| | | | | g dd}tj ||fdd |jd d|jd}|d ur| d d|}n*t |jdkr|j|jd dkst|j|j dddd}| d d||}|d kr z t|\}}}Wn tytjd tddtj|d ddf||dYSw|dddd}n&|dkr0tj|jd |jd||d}t||\}}}| ddd}ntt| d ||}||ddd dd f|}|S)aICompute the homography matrix using the DLT formulation. The linear system is solved by using the Weighted Least Squares Solution for the 4 Points algorithm. Args: points1: A set of points in the first image with a tensor shape :math:`(B, N, 2)`. points2: A set of points in the second image with a tensor shape :math:`(B, N, 2)`. weights: Tensor containing the weights per point correspondence with a shape of :math:`(B, N)`. solver: variants: svd, lu. Returns: the computed homography matrix with shape :math:`(B, 3, 3)`. r )rr9r:rrrr;rrNr=svdSVD did not converge stacklevelrdevicer).rrQ.)r>AssertionErrorrrr r'r? ones_like zeros_likecatreshaperBlenrepeat_interleave unsqueezer RuntimeErrorwarningswarnRuntimeWarningemptyrr+onesrNotImplementedErrorr)rRrSrTrUr\r)r points1_norm transform1 points2_norm transform2x1y1x2y2rkzerosaxayAw_full_VrrsolH_normr$r$r%find_homography_dltsL     ..("    r~@ soft_inl_thn_iterc CTt|||}t|dD]}t|||d}t| d|d}t|||}q |S)aCompute the homography matrix using the iteratively-reweighted least squares (IRWLS). The linear system is solved by using the Reweighted Least Squares Solution for the 4 Points algorithm. Args: points1: A set of points in the first image with a tensor shape :math:`(B, N, 2)`. points2: A set of points in the second image with a tensor shape :math:`(B, N, 2)`. weights: Tensor containing the weights per point correspondence with a shape of :math:`(B, N)`. Used for the first iteration of the IRWLS. soft_inl_th: Soft inlier threshold used for weight calculation. n_iter: number of iterations. Returns: the computed homography matrix with shape :math:`(B, 3, 3)`. r F@r)r~ranger5r'exp) rRrSrTrrrrzerrors weights_newr$r$r%find_homography_dlt_iterated rc Csj|j|jkr t|jt|gdt|gd|j}tjgdgdgdgdgtj|d}t|}t|}|dd|f}|dd|f}tjj |dd d ddf|dd d ddfd d |ddd ddf dd d d  }tjj |dd d ddf|dd d ddfd d |ddd ddf dd d d  } || k d dj d d d} | S)aImplement oriented constraint check from :cite:`Marquez-Neila2015`. Analogous to https://github.com/opencv/opencv/blob/4.x/modules/calib3d/src/usac/degeneracy.cpp#L88 Args: points1: A set of points in the first image with a tensor shape :math:`(B, 4, 2)`. points2: A set of points in the second image with a tensor shape :math:`(B, 4, 2)`. Returns: Mask with the minimal sample is good for homography estimation:math:`(B, 3, 3)`. )r4r:)rr r)rr r)rrr)r rr)r)r\N.r rrrrrrV)r>r^rr\r'tensorlongr r@rApermutesignr+min) rRrSr\idx_perm points_src_h points_dst_hsrc_permdst_perm left_sign right_signsample_is_validr$r$r%sample_is_valid_for_homographys, *4 4 rc$ Cst|jdkr |d}t|jdkr|d}t|gdt|gd|jdd\}}t||g\}}||d|d}||d|d}t|\} } t|\} } tj| ddd\} }tj| ddd\}}tj| ddd\}}tj|ddd\}}tj|ddd\}}tj|ddd\}}||}||}||||}d}tj|||||||||||||||g dd }tj|||||||||||||||g dd }tj||fdd |jd d|jd}|dur| d d|}n7t|jdkr |j|jddkst |jt |j dd  ddd|jd d}| d d||}z t|\} } }!Wn tyZtjd tdd tj| d ddf||dYSw|!dddd}"t| d |"| }"|"|"dddddf|}#|#S)aCompute the homography matrix using the DLT formulation for line correspondences. See :cite:`homolines2001` for details. The linear system is solved by using the Weighted Least Squares Solution for the 4 Line correspondences algorithm. Args: ls1: A set of line segments in the first image with a tensor shape :math:`(B, N, 2, 2)`. ls2: A set of line segments in the second image with a tensor shape :math:`(B, N, 2, 2)`. weights: Tensor containing the weights per point correspondence with a shape of :math:`(B, N)`. Returns: the computed homography matrix with shape :math:`(B, 3, 3)`. rNr8rr r;rrrrr=rXrYr[r].)rcr>rrrbr r'r?rarBr^ diag_embedrerepeatr rfrgrhrirjrr+r)$r6r7rTBSr9r\r)rRrSrmrnrorplst1le1lst2le2xs1ys1xs2ys2xe1ye1xe2ye2rxrCrrvrww_diagrzr{rr}r$r$r%find_homography_lines_dltsR  88(& * r@c Cr)a Compute the homography matrix using the iteratively-reweighted least squares (IRWLS) from line segments. The linear system is solved by using the Reweighted Least Squares Solution for the 4 line segments algorithm. Args: ls1: A set of line segments in the first image with a tensor shape :math:`(B, N, 2, 2)`. ls2: A set of line segments in the second image with a tensor shape :math:`(B, N, 2, 2)`. weights: Tensor containing the weights per point correspondence with a shape of :math:`(B, N)`. Used for the first iteration of the IRWLS. soft_inl_th: Soft inlier threshold used for weight calculation. n_iter: number of iterations. Returns: the computed homography matrix with shape :math:`(B, 3, 3)`. r Frr)rrrPr'r) r6r7rTrrrrzrrr$r$r%"find_homography_lines_dlt_iteratedYrr)Tr)F)NrQ)rr)N)rr)#rgtypingrrr' kornia.corerkornia.core.checkr kornia.utilsrrrkornia.utils.helpersr conversionsr r epipolarr r@r TupleTensorboolfloatr&r5rPstrr~intrrrrr$r$r$r%sp      $$! %& E  %H