noise_models module
Library of Sensor noise models
A library of noise models to close the gap between simulated observations and observations from real sensors.
A noise model can be applied to a sensor by specifying the name of the noise
model in the sensor.SensorSpec.noise_model field.
Arguments can be passed to the noise model constructor as keyword arguments using
the sensor.SensorSpec.noise_model_kwargs field. For instance, to use the RedwoodDepthNoiseModel
with a noise_multiplier of 5
sensor_spec.noise_model = "RedwoodDepthNoiseModel" sensor_spec.noise_model_kwargs = dict(noise_multiplier=5)
These noise models are commonly the result of contributions from various research projects. If you use a noise model in your research, please cite the relevant work specified by the documentation
Depth Noise Models
- Redwood Noise Model for PrimSense depth cameras: RedwoodDepthNoiseModel
Classes
- class SensorNoiseModel
- Base class for all sensor noise models
- class RedwoodDepthNoiseModel
- Redwood Noise Model for PrimSense depth cameras
- class NoSensorNoiseModel
- No noise noise model. Simply returns a copy of the input
- class GaussianNoiseModel
- class SaltAndPepperNoiseModel
- class PoissonNoiseModel
- class SpeckleNoiseModel
Functions
- def make_sensor_noise_model(name: str, kwargs: typing.Dict[str, typing.Any]) -> SensorNoiseModel
- Constructs a noise model using the given name and keyword arguments
Function documentation
def habitat_sim.
Constructs a noise model using the given name and keyword arguments
| Parameters | |
|---|---|
| name | The name of the noise model in the habitat_sim.registry |
| kwargs | The keyword arguments to be passed to the constructor of the noise model |