torchdrivesim.rendering.base
============================

.. py:module:: torchdrivesim.rendering.base

.. autoapi-nested-parse::

   Base class for renderers producing rasterized birdview images from given background meshes and agent positions.



Attributes
----------

.. autoapisummary::

   torchdrivesim.rendering.base.logger


Classes
-------

.. autoapisummary::

   torchdrivesim.rendering.base.RendererConfig
   torchdrivesim.rendering.base.DummyRendererConfig
   torchdrivesim.rendering.base.Cameras
   torchdrivesim.rendering.base.BirdviewRenderer
   torchdrivesim.rendering.base.DummyRenderer


Functions
---------

.. autoapisummary::

   torchdrivesim.rendering.base.get_default_rendering_levels
   torchdrivesim.rendering.base.get_default_color_map


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

.. py:data:: logger
   :value: None


.. py:class:: RendererConfig

   Determines behavior of the renderer.
   Subclasses determine renderer class used.


   .. py:attribute:: backend
      :type:  str
      :value: 'default'



   .. py:attribute:: render_agent_direction
      :type:  bool
      :value: True



   .. py:attribute:: left_handed_coordinates
      :type:  bool
      :value: False



   .. py:attribute:: highlight_ego_vehicle
      :type:  bool
      :value: False



   .. py:attribute:: shift_mesh_by_camera_before_rendering
      :type:  bool
      :value: True



   .. py:attribute:: device
      :type:  Optional[str]
      :value: None



.. py:class:: DummyRendererConfig

   Bases: :py:obj:`RendererConfig`


   For DummyRenderer.


   .. py:attribute:: backend
      :type:  str
      :value: 'dummy'



.. py:class:: Cameras(xy: torch.Tensor, sc: torch.Tensor, scale: float)

   Lightweight version of pytorch3d.renderer.FoVOrthographicCameras.
   Used to define an interface that works without pytorch3d.


   .. py:attribute:: xy


   .. py:attribute:: sc


   .. py:attribute:: scale


   .. py:attribute:: world_to_clip_transform


   .. py:method:: get_camera_center() -> torch.Tensor


   .. py:method:: get_world_to_view_transform() -> torch.Tensor


   .. py:method:: get_view_to_proj_transform() -> torch.Tensor


   .. py:method:: project_world_to_clip_space(points: torch.Tensor) -> torch.Tensor


   .. py:method:: transform_points_screen(points: torch.Tensor, res: torchdrivesim.utils.Resolution) -> torch.Tensor


   .. py:method:: reverse_transform_points_screen(points: torch.Tensor, res: torchdrivesim.utils.Resolution) -> torch.Tensor


.. py:class:: BirdviewRenderer(cfg: RendererConfig, color_map: Optional[Dict[str, Tuple[int, int, int]]] = None, rendering_levels: Optional[Dict[str, float]] = None, res: torchdrivesim.utils.Resolution = Resolution(64, 64), fov: float = 35)

   Bases: :py:obj:`abc.ABC`


   A renderer producing simple 2D birdview images based on static background meshes and rectangular agents.
   Currently only square resolutions are supported. The renderer always operates in batch mode,
   with a single batch dimension on the left.

   :param cfg: configuration object, usually subclassed
   :param color_map: a dictionary of RGB tuples in 0-255 range specifying colors of different rendered elements
   :param res: default resolution


   .. py:attribute:: cfg
      :type:  RendererConfig


   .. py:attribute:: res


   .. py:attribute:: scale
      :value: 0.05714285714285714



   .. py:attribute:: color_map
      :value: None



   .. py:attribute:: rendering_levels
      :value: None



   .. py:method:: copy()


   .. py:method:: get_color(element_type: str) -> Tuple[int, int, int]


   .. py:method:: render_frame(rgb_mesh: torchdrivesim.mesh.RGBMesh, camera_xy: torch.Tensor, camera_sc: torch.Tensor, res: Optional[torchdrivesim.utils.Resolution] = None, fov: Optional[float] = None)

      Renders a given rgb mesh according the camera position and rotation.

      :param rgb_mesh: the given rgb mesh to render which should be already expanded to match the number of cameras.
      :param camera_xy: BxNcx2 tensor of camera positions, by default one camera placed on each agent
      :param camera_sc: BxNcx2 tensor of camera orientations (sine and cosine), by default matching agent orientations
      :param res: resolution HxW of the resulting image, currently only square resolutions are supported
      :param fov: Field of view in meters

      :returns: tensor image of float RGB values in [0,255] range with shape shape (B*Nc)xCxHxW



   .. py:method:: render_rgb_mesh(mesh: torchdrivesim.mesh.RGBMesh, res: torchdrivesim.utils.Resolution, cameras: Cameras) -> torch.Tensor
      :abstractmethod:


      Renders a given mesh, producing BxHxWxC tensor image of float RGB values in [0,255] range.



   .. py:method:: construct_cameras(xy: torch.Tensor, sc: torch.Tensor, scale: Optional[float] = None) -> Cameras

      Create PyTorch3D cameras object for given positions and orientations.
      Input tensor dimensions should be Bx2.



.. py:class:: DummyRenderer(cfg: RendererConfig, color_map: Optional[Dict[str, Tuple[int, int, int]]] = None, rendering_levels: Optional[Dict[str, float]] = None, res: torchdrivesim.utils.Resolution = Resolution(64, 64), fov: float = 35)

   Bases: :py:obj:`BirdviewRenderer`


   Produces a black image of the required size. Mostly used for debugging and benchmarking.


   .. py:method:: render_rgb_mesh(mesh: torchdrivesim.mesh.RGBMesh, res: torchdrivesim.utils.Resolution, cameras: Cameras) -> torch.Tensor

      Renders a given mesh, producing BxHxWxC tensor image of float RGB values in [0,255] range.



.. py:function:: get_default_rendering_levels() -> Dict[str, float]

   Produces the default rendering levels, mapping object categories
   to their rendering level. Lower level renders on top,
   but levels lower than 0 don't render at all.


.. py:function:: get_default_color_map() -> Dict[str, Tuple[int, int, int]]

   Produces the default color map, mapping object categories
   to RGB 3-tuples in [0,255] range.