a d@@sfddlZddlmmZddlmZmZejejejdddZ d ejejeje ejddd Z dS) N)convert_points_from_homogeneousconvert_points_to_homogeneous)point_3d camera_matrixreturnc Cst|tjstdt|t|tjs>> _ = torch.manual_seed(0) >>> X = torch.rand(1, 3) >>> K = torch.eye(3)[None] >>> project_points(X, K) tensor([[5.6088, 8.6827]]) z/Input point_3d type is not a torch.Tensor. Got 4Input camera_matrix type is not a torch.Tensor. Got -Input tensors must be all in the same device.z6Input points_3d must be in the shape of (*, 3). Got {}Nr r 6Input camera_matrix must be in the shape of (*, 3, 3)..r..rr.rr.r.rrdim) isinstancetorchTensor TypeErrortypedevice ValueErrorshapeformatrstack) rrZ xy_coordsx_coordy_coordfxfycxcyu_coordv_coordr*k/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/kornia/geometry/camera/perspective.pyproject_pointss(     r,F)point_2ddepthr normalizerc CsTt|tjstdt|t|tjs>> _ = torch.manual_seed(0) >>> x = torch.rand(1, 2) >>> depth = torch.ones(1, 1) >>> K = torch.eye(3)[None] >>> unproject_points(x, depth, K) tensor([[0.4963, 0.7682, 1.0000]]) z/Input point_2d type is not a torch.Tensor. Got z,Input depth type is not a torch.Tensor. Got rrr rz6Input points_2d must be in the shape of (*, 2). Got {}rz2Input depth must be in the shape of (*, 1). Got {}r Nr r rrrrrrrg@)rp) rrrrrrrrr r!rFr/) r-r.rr/r(r)r$r%r&r'r"r#Zxyzr*r*r+unproject_points?s6     r2)F) rZtorch.nn.functionalnnZ functionalr1Zkornia.geometry.conversionsrrrr,boolr2r*r*r*r+s9