l5kit.rasterization.sem_box_rasterizer module

class l5kit.rasterization.sem_box_rasterizer.SemBoxRasterizer(render_context: l5kit.rasterization.render_context.RenderContext, filter_agents_threshold: float, history_num_frames: int, semantic_map_path: str, world_to_ecef: numpy.ndarray, render_ego_history: bool = True)

Bases: l5kit.rasterization.rasterizer.Rasterizer

Combine a Semantic Map and a Box Rasterizers into a single class

num_channels() → int

rasterize(history_frames: numpy.ndarray, history_agents: List[numpy.ndarray], history_tl_faces: List[numpy.ndarray], agent: Optional[numpy.ndarray] = None) → numpy.ndarray

to_rgb(in_im: numpy.ndarray, **kwargs: dict) → numpy.ndarray