Loading multiple pipelines and trainers #161
Description
@ttsesm
You can add multiple objects to the scene graph like this:
from wisp.framework import WispState
from wisp.renderer.core.api import add_to_scene_graph
wisp_state = WispState() # Your global shared info here.. Created once per app
nerf_pipeline1 = Pipeline(nef=nef1, tracer=tracer1) # See main_nerf.py for an example of creating a Pipeline..
nerf_pipeline2 = Pipeline(nef=nef2, tracer=tracer2) # See main_nerf.py for an example of creating a Pipeline..
# Optional NeRF args are args that NeuralRadianceFieldPackedRenderer.__init__ takes as input:
# https://github.com/NVIDIAGameWorks/kaolin-wisp/blob/main/wisp/renderer/core/renderers/radiance_pipeline_renderer.py#L26
# batch_size is an optional setup arg here which hints the visualizer how many rays can be processed at once
# e.g. this is the pipeline's batch_size used for inference time
nerf_specific_args = dict(batch_size=2**14)
# Add object to scene graph: if interactive mode is on, this will make sure the visualizer can display it.
add_to_scene_graph(state=wisp_state, name="My NeRF", obj=nerf_pipeline1, **nerf_specific_args)
add_to_scene_graph(state=wisp_state, name="Another NeRF", obj=nerf_pipeline2, **nerf_specific_args)Each object has its own ObjectTransform so you can control their orientation, dimensions and location around the scene.
Some more explanation about the scene graph and NeuralRadianceFieldPackedRenderer is available in the docs:
https://kaolin-wisp.readthedocs.io/en/latest/pages/renderer.html#the-scenegraph
Keep in mind that the app runs in an infinite loop, add_to_scene_graph is an async request. The object actually gets added to the scene graph when the next frame is drawn.
If you have further questions please open a separate issue, it makes it easier for me to track :)
Originally posted by @orperel in #35 (comment)