fastdev.geom.warp_meshes
========================

.. py:module:: fastdev.geom.warp_meshes




Module Contents
---------------

.. py:class:: WarpMeshes(warp_meshes: List[warp.Mesh], warp_meshes_first_idx: jaxtyping.Int[torch.Tensor, num_scenes])

   A lightweight wrapper for batched warp meshes.


   .. py:method:: from_files(filenames: List[str], filenames_first_idx: jaxtyping.Int[torch.Tensor, num_scenes], device: Device = 'cpu')
      :staticmethod:



   .. py:method:: from_trimesh_meshes(meshes: List[trimesh.Trimesh], meshes_first_idx: jaxtyping.Int[torch.Tensor, num_scenes], device: Device = 'cpu') -> WarpMeshes
      :staticmethod:



   .. py:property:: num_scenes
      :type: int



   .. py:property:: num_meshes
      :type: int



   .. py:method:: query_signed_distances(query_points: jaxtyping.Float[torch.Tensor, num_points 3], query_points_first_idx: jaxtyping.Int[torch.Tensor, num_scenes], mesh_poses: Optional[jaxtyping.Float[torch.Tensor, num_meshes 4 4]] = None, mesh_scales: Optional[jaxtyping.Float[torch.Tensor, num_meshes]] = None, max_dist: float = 1000000.0) -> Tuple[jaxtyping.Float[torch.Tensor, num_points], jaxtyping.Float[torch.Tensor, num_points 3], jaxtyping.Float[torch.Tensor, num_points 3]]

      Query signed distances.

      :returns: differentiable signed distances (num_points).
                torch.Tensor: normals (num_points, 3).
                torch.Tensor: closest points (num_points, 3).
      :rtype: torch.Tensor



   .. py:method:: __repr__() -> str


   .. py:method:: __str__() -> str