o oi @sddlmZddlZddlmZmZmZmZmZddej dej de dej fd d Z dd ej d ej d ej deej dej f ddZ dS))OptionalN)cos ones_likesinstack zeros_likeFtauxtauyreturn_inversereturnc Cs|j|jkrtd|jd|jd|}|d}|d}t|}t|}t|}t|}t|}t|} t| ||||||| |g dddd} t||| || ||||g dddd} | | } |rd| d} t| || d| || | d | ||| g dddd}| dd |}|d krt |}|St| d|| d || d| d  ||| g dddd}|| dd }|d krt |}|S) aEstimate the tilt projection matrix or the inverse tilt projection matrix. Args: taux: Rotation angle in radians around the :math:`x`-axis with shape :math:`(*, 1)`. tauy: Rotation angle in radians around the :math:`y`-axis with shape :math:`(*, 1)`. return_inverse: False to obtain the tilt projection matrix. True for the inverse matrix. Returns: torch.Tensor: Inverse tilt projection matrix with shape :math:`(*, 3, 3)`. zShape of taux z and tauy z do not match.).r).rr).rrr) shape ValueErrordimreshaperrrrr transposetorchsqueeze)rr r ndimcTxsTxcTysTyzerooneRxRyRinvR22invPzinv_tiltPztiltr'W/home/ubuntu/.local/lib/python3.10/site-packages/kornia/geometry/calibration/distort.pytilt_projections@   (( &  0 r)pointsKdistnew_KcCs|dkr|jddkrtd|jd|jdddkr(td|jd|dur/|}n|jdddkrAtd |jd|jdd vrRtd |jd|jdd krhtjj|d d |jdg}|dd ddf}|ddddf}|dd dd f}|ddddf}|d||}|d||} ||| | } d|dd df| |dddf| | |dddf| dd|dddf| |dddf| | |dddf| d} || d|dddf|| |dddf| d|||dddf| |dddf| | } | | |dddf| d| | d|dddf|| |dddf| |dddf| | } t|dd kspt|dd krt|d|d}t | | t | gd| dd}|d|d} |d|d} |dd ddf}|ddddf}|dd dd f}|ddddf}|| |}|| |} t || gdS)a~Distortion of a set of 2D points based on the lens distortion model. Radial :math:`(k_1, k_2, k_3, k_4, k_4, k_6)`, tangential :math:`(p_1, p_2)`, thin prism :math:`(s_1, s_2, s_3, s_4)`, and tilt :math:`(\tau_x, \tau_y)` distortion models are considered in this function. Args: points: Input image points with shape :math:`(*, N, 2)`. K: Intrinsic camera matrix with shape :math:`(*, 3, 3)`. dist: Distortion coefficients :math:`(k_1,k_2,p_1,p_2[,k_3[,k_4,k_5,k_6[,s_1,s_2,s_3,s_4[,\tau_x,\tau_y]]]])`. This is a vector with 4, 5, 8, 12 or 14 elements with shape :math:`(*, n)`. new_K: Intrinsic camera matrix of the distorted image. By default, it is the same as K but you may additionally scale and shift the result by using a different matrix. Shape: :math:`(*, 3, 3)`. Default: None. Returns: Undistorted 2D points with shape :math:`(*, N, 2)`. Example: >>> points = torch.rand(1, 1, 2) >>> K = torch.eye(3)[None] >>> dist_coeff = torch.rand(1, 4) >>> points_dist = distort_points(points, K, dist_coeff) rr zpoints shape is invalid. Got .rN)r r zK matrix shape is invalid. Got z#new_K matrix shape is invalid. Got ) z/Invalid number of distortion coefficients. Got r3r.r).r).rr/r0r r1 r2).r2). ).r) rrrrnn functionalpadanyr)rrr)r*r+r,r-new_cxnew_cynew_fxnew_fyxyr2rad_polyxdydr& points_untiltcxcyfxfyr'r'r(distort_pointsOslFF(    rM)F)N) typingrr kornia.corerrrrrTensorboolr)rMr'r'r'r(s "6