3j'XSSKJrJrJrJr SSKrSSKJs Jr SSKJr SSK J r J r J r SSKJr SSKJr SSKJr SS /r"S S\R*5rS \R.S \4S jrS \R.S\R.S \4SjrSS \R.S\\R.S \4Sjjrg))IteratorOptionalTupleUnionN)nn) KORNIA_CHECKKORNIA_CHECK_IS_TENSORKORNIA_CHECK_SHAPE)_torch_svd_cast)batched_dot_product) HyperplaneParametrizedLinefit_linec ^\rSrSrSrS\R S\R SS4U4SjjrS\4Sjr S\4S jr S \ S\R 4S jr S\ \R 4S jr\S\R 4S j5r\S\R 4Sj5rS\ 4Sjr\S\R S\R SS4Sj5rS\\\R 4S\R 4SjrS\R S\R 4SjrS\R S\R 4SjrS\R S\R 4SjrSS\S\S\\R \R 44SjjrSrU=r$)r"zClass that describes a parametrize line. A parametrized line is defined by an origin point :math:`o` and a unit direction vector :math:`d` such that the line corresponds to the set .. math:: l(t) = o + t * d origin directionreturnNc>[TU]5 [R"U5Ul[R"U5Ulg)a,Initialize a parametrized line of direction and origin. Args: origin: any point on the line of any dimension. direction: the normalized vector direction of any dimension. Example: >>> o = torch.tensor([0.0, 0.0]) >>> d = torch.tensor([1.0, 1.0]) >>> l = ParametrizedLine(o, d) N)super__init__r Parameter_origin _direction)selfrr __class__s N/home/wildlama/miniconda3/lib/python3.13/site-packages/kornia/geometry/line.pyrParametrizedLine.__init__-s0 ||F+ ,,y1c:SURSUR3$)NzOrigin: z Direction: rrrs r__str__ParametrizedLine.__str__>s$++mDNN3CDDrc[U5$N)strr"s r__repr__ParametrizedLine.__repr__As 4yridxc>US:Xa UR$UR$)Nrr!)rr*s r __getitem__ParametrizedLine.__getitem__Ds!Qht{{:DNN:rc#P# URUR4ShvN gN7fr&r!r"s r__iter__ParametrizedLine.__iter__GsKK000s &$&cUR$)zReturn the line origin point.)rr"s rrParametrizedLine.originJs||rcUR$)z!Return the line direction vector.)rr"s rrParametrizedLine.directionOsrc4URRS$)z-Return the dimension in which the line holds.)rshaper"s rdimParametrizedLine.dimTs~~##B''rp0p1c F[U[R"X!- SSS95$)ayConstruct a parametrized line going from a point :math:`p0` to :math:`p1`. Args: p0: tensor with first point :math:`(B, D)` where `D` is the point dimension. p1: tensor with second point :math:`(B, D)` where `D` is the point dimension. Example: >>> p0 = torch.tensor([0.0, 0.0]) >>> p1 = torch.tensor([1.0, 1.0]) >>> l = ParametrizedLine.through(p0, p1) r6)pr8)rF normalize)clsr:r;s rthroughParametrizedLine.throughXs  AKKQB$GHHrtc:URURU--$)aGet the point at :math:`t` along this line. Args: t: step along the line. Return: tensor with the point. Example: >>> p0 = torch.tensor([0.0, 0.0]) >>> p1 = torch.tensor([1.0, 1.0]) >>> l = ParametrizedLine.through(p0, p1) >>> p2 = l.point_at(0.1) r!)rrDs rpoint_atParametrizedLine.point_aths {{T^^a///rpointclURURXR- -UR--$)z^Return the projection of a point onto the line. Args: point: the point to be projected. r!rrHs r projectionParametrizedLine.projectionzs,{{dnn 0CDVVVrcXR- n[R"X R-SS9n[R"X"-SS9nXCU-- $)zReturn the squared distance of a point to its projection onte the line. Args: point: the point to calculate the distance onto the line. r6r8)rtorchsumr)rrHdproj sq_norm_ds rsquared_distance!ParametrizedLine.squared_distancesF KK yy^^+4IIae, $;&&rc@URU5R5$)zReturn the distance of a point to its projections onto the line. Args: point: the point to calculate the distance into the line. )rTsqrtrJs rdistanceParametrizedLine.distances $$U+0022rplaneepsc[URRURR5nUR 5U:n[ R "UUR[URRURR5-*U- [ R"U55nURU5nXV4$)a Return the intersection point between the line and a given plane. Args: plane: the plane to compute the intersection point. eps: epsilon for numerical stability. Return: - the lambda value used to compute the look at point. - the intersected point. ) r normaldatarabsrOwhereoffsetr empty_likerF)rrZr[dot_prod dot_prod_mask res_lambda res_points r intersectParametrizedLine.intersects'u||'8'8$..:M:MN #- [[ ll01B1BDKKDTDTUU VYa a   X & MM*- $$r)rr)gư>) __name__ __module__ __qualname____firstlineno____doc__rOTensorrr'r#r(intr,rr/propertyrrr8 classmethodrBrfloatrFrKrTrXr rrg__static_attributes__ __classcell__)rs@rrr"s2u||2 22"EE#;s;u||;1(5<<01 5<<(S( I I5<< IrN?)devicerr=) meanrPrOr` zeros_likecat ones_liketensorrexpandr7normr) ruxyx_meany_meandxdydenomsloperrs r_fit_line_ols_2drs$vAvA VVDV )F VVDV )F B B WMMb$M /E KK rwmmDm&IE&QSXScScdiSj kE    5??5)51r: c3Z 6==fll1oqQI NNr4N@@I YY'R 0F F ..rweightscUSnUSnURSSS9nX-RSSS9U- nX-RSSS9U- nX%- nX6- nX-U-n X-U-n U RSSS9n U RSSS9U - n [R"[R"U 5U [R"U 55n U S:*n [R "[R "U 5U /SS9n[R"SS /URURS 9nXU RS5'XRSSS9- n[R "XV/SS9n[UU5$) Nrwrxr6Trzr|rNr}r~)rdtype) rPrOr`isfiniterrrrrrsqueezerr)rurrrw_sumrrrr weighted_dx2 weighted_dxdyrr is_verticalr replacementrs r_fit_line_weighted_ols_2drsjvAvA KKBK -Ek  2t  4u >> points = torch.rand(2, 10, 3) >>> weights = torch.ones(2, 10) >>> line = fit_line(points, weights) >>> line.direction.shape torch.Size([2, 3]) zpoints must be a tensor)BNDr=Nzweights must be a tensorrrrTr6.) r r r7rrrr transposerO diag_embedr r) rur_B_NrrA_Vrrs rrrs[&6#<=v/ IBA Av   "7,F G wc 3 aGMM!,<< =,V= =#F+ + ;;r4 D Aw(BC7S#J/V\\!_ a(889 KKB %"2"27"; ;a ? KKB ! #a GAq BA#q!) I #q!)_F F ..rr&)typingrrrrrOtorch.nn.functionalr functionalr?kornia.core.checkrr r kornia.core.utilsr kornia.geometry.linalgr kornia.geometry.planer __all__Modulerrnrrrrrrs(43 VV-6, z *Q%ryyQ%h/U\\/.>/./ell/U\\/N^/@5/U\\5/HU\\,B5/N^5/r