habitat_sim.sensors.noise_models.RedwoodDepthNoiseModel class

Redwood Noise Model for PrimSense depth cameras

Accessible from the registry under the name "RedwoodDepthNoiseModel"

Implements the noise model provided by http://redwood-data.org/indoor/dataset.html

If you use this noise model, please cite

@inproceedings{choi2015robust,
  title={Robust reconstruction of indoor scenes},
  author={Choi, Sungjoon and Zhou, Qian-Yi and Koltun, Vladlen},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and
    Pattern Recognition}, pages={5556--5565}, year={2015}
}

Static methods

def is_valid_sensor_type(sensor_type: sensor.SensorType) -> bool

Methods

def apply(self, gt_depth: typing.Union[numpy.ndarray, torch.Tensor]) -> typing.Union[numpy.ndarray, torch.Tensor]: Alias of simulate() to conform to base-class and expected API
def simulate(self, gt_depth: typing.Union[numpy.ndarray, torch.Tensor]) -> typing.Union[numpy.ndarray, torch.Tensor]

Special methods

def __attrs_post_init__(self) -> None
def __call__(self, sensor_observation: typing.Union[numpy.ndarray, torch.Tensor]) -> typing.Union[numpy.ndarray, torch.Tensor]: Alias of apply()
def __init__(self, *, gpu_device_id: typing.Optional[int] = None, noise_multiplier: float = 1.0) -> None: Method generated by attrs for class RedwoodDepthNoiseModel.

Properties

noise_multiplier: float get set del
gpu_device_id: typing.Optional[int] get set del

Method documentation

def habitat_sim.sensors.noise_models.RedwoodDepthNoiseModel.init(self, *, gpu_device_id: typing.Optional[int] = None, noise_multiplier: float = 1.0) -> None

Method generated by attrs for class RedwoodDepthNoiseModel.

Parameters
gpu_device_id	The ID of CUDA device to use (only applicable if habitat-sim was built with `--with-cuda`)
noise_multiplier	Multiplier for the Gaussian random-variables. This reduces or increases the amount of noise