Ben Beilharz
@engramm.ing
295 followers 528 following 252 posts
Cognitive Science PhD student working on (inverse) light transport for sensing, planning & acting @tsawallis.bsky.social's Perception Lab. AI for science. I like my models uncertain. he/him
![Image shows a code example for the Python package introduced in this post.
The code is as following (for screenreaders):
import mitsuba_scene_description as msd
import mitsuba as mi
mi.set_variant("llvm_ad_rgb")
# Define components
diffuse = msd.SmoothDiffuseMaterial(reflectance=msd.RGB([0.8, 0.2, 0.2]))
ball = msd.Sphere(
radius=1.0,
bsdf=diffuse,
to_world=msd.Transform().translate(0, 0, 3).scale(0.4),
)
cam = msd.PerspectivePinholeCamera(
fov=45,
to_world=msd.Transform().look_at(
origin=[0, 1, -6], target=[0, 0, 0], up=[0, 1, 0]
),
)
integrator = msd.PathTracer()
emitter = msd.ConstantEnvironmentEmitter()
# builder pattern
scene = (
msd.SceneBuilder()
.integrator(integrator)
.sensor(cam)
.shape("ball", ball)
.emitter("sun", emitter)
.build()
)
# or
scene = msd.Scene(
integrator=integrator,
sensors=cam, # also accepts a list for multi-sensor setups
shapes={"ball": ball},
emitters={"sun": emitter},
)
mi.load_dict(scene.to_dict())
# will return:
{'ball': {'bsdf': {'reflectance': {'type': 'rgb', 'value': [0.8, 0.2, 0.2]},
'type': 'diffuse'},
'radius': 1.0,
'to_world': Transform[
matrix=[[0.4, 0, 0, 0],
[0, 0.4, 0, 0],
[0, 0, 0.4, 1.2],
[0, 0, 0, 1]],
...
],
'type': 'sphere'},
'integrator': {'type': 'path'},
'sensor': {'fov': 45,
'to_world': Transform[...],
'type': 'perspective'},
'sun': {'type': 'constant'},
'type': 'scene'}](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:kutrsf5pzrkdsgp2vvmlnasx/bafkreieqk6b5gdlehozd4pzzxe5bxxdawec22o7lxdtgj6ulmzt4mzyqwe)
