BatchRenderer#

A high-throughput renderer that renders many parallel environments together on the GPU, for large-scale data collection and reinforcement-learning observation generation. Enable it with gs.Scene(renderer=gs.renderers.BatchRenderer(use_rasterizer=True)); set use_rasterizer=False to path-trace instead. It requires the gs-madrona package.

With n_envs > 1, camera outputs gain a leading batch dimension, for example rgb with shape (n_envs, height, width, 3). It takes its lights at runtime through scene.add_light(...) rather than from VisOptions. For installation, lighting, and a runnable example, see Rendering.

Options#

class genesis.options.renderers.BatchRenderer(*, use_rasterizer: bool = False) → None[source]#

BatchRenderer renderer.

Note

This renderer is used to render the scene in a batch.

Parameters:

use_rasterizer (bool, optional) – Whether to use the rasterizer renderer. Defaults to False.

Implementation#

class genesis.vis.batch_renderer.BatchRenderer(visualizer, renderer_options, vis_options)[source]#

Bases: RBC

This class is used to manage batch rendering

add_light(pos, dir, color, intensity, directional, castshadow, cutoff, attenuation)[source]#
build()[source]#

Build all cameras in the batch and initialize Moderona renderer

update_scene(force_render: bool = False)[source]#
render(rgb=True, depth=False, segmentation=False, normal=False, antialiasing=False, force_render=False)[source]#

Render all cameras in the batch.

Parameters:

  • rgb (bool, optional) – Whether to render the rgb image.

  • depth (bool, optional) – Whether to render the depth image.

  • segmentation (bool, optional) – Whether to render the segmentation image.

  • normal (bool, optional) – Whether to render the normal image.

  • antialiasing (bool, optional) – Whether to apply anti-aliasing.

  • force_render (bool, optional) – Whether to force render the scene.

Returns:

  • rgb_arr (tuple of arrays) – The sequence of rgb images associated with each camera.

  • depth_arr (tuple of arrays) – The sequence of depth images associated with each camera.

  • segmentation_arr (tuple of arrays) – The sequence of segmentation images associated with each camera.

  • normal_arr (tuple of arrays) – The sequence of normal images associated with each camera.

colorize_seg_idxc_arr(seg_idxc_arr)[source]#
destroy()[source]#
reset()[source]#
property lights#
property cameras#
property seg_idxc_map#

See also#

  • Rasterizer: the standard single-scene rasterizer.

  • Examples: rendering observations for RL.