def __init__(self, sim: Simulator, agent: Agent, sensor_id: str) -> None:
self._sim = sim
self._agent = agent
# sensor is an attached object to the scene node
# store such "attached object" in _sensor_object
self._sensor_object = self._agent._sensors[sensor_id]
self._spec = self._sensor_object.specification()
self._sim.renderer.bind_render_target(self._sensor_object)
if self._spec.gpu2gpu_transfer:
assert cuda_enabled, "Must build habitat sim with cuda for gpu2gpu-transfer"
assert _HAS_TORCH
device = torch.device("cuda", self._sim.gpu_device) # type: ignore[attr-defined]
torch.cuda.set_device(device)
resolution = self._spec.resolution
if self._spec.sensor_type == SensorType.SEMANTIC:
self._buffer: Union[np.ndarray, "Tensor"] = torch.empty(
resolution[0], resolution[1], dtype=torch.int32, device=device
)
elif self._spec.sensor_type == SensorType.DEPTH:
self._buffer = torch.empty(
resolution[0], resolution[1], dtype=torch.float32, device=device
)
else:
self._buffer = torch.empty(
resolution[0], resolution[1], 4, dtype=torch.uint8, device=device
)
else:
if self._spec.sensor_type == SensorType.SEMANTIC:
self._buffer = np.empty(
(self._spec.resolution[0], self._spec.resolution[1]),
dtype=np.uint32,
)
elif self._spec.sensor_type == SensorType.DEPTH:
self._buffer = np.empty(
(self._spec.resolution[0], self._spec.resolution[1]),
dtype=np.float32,
)
else:
self._buffer = np.empty(
(
self._spec.resolution[0],
self._spec.resolution[1],
self._spec.channels,
),
dtype=np.uint8,
)
noise_model_kwargs = self._spec.noise_model_kwargs
self._noise_model = make_sensor_noise_model(
self._spec.noise_model,
{"gpu_device_id": self._sim.gpu_device, **noise_model_kwargs},
)
assert self._noise_model.is_valid_sensor_type(
self._spec.sensor_type
), "Noise model '{}' is not valid for sensor '{}'".format(
self._spec.noise_model, self._spec.uuid
)
def __init__(self, sim, agent, sensor_id):
global torch
self._sim = sim
self._agent = agent
# sensor is an attached object to the scene node
# store such "attached object" in _sensor_object
self._sensor_object = self._agent._sensors.get(sensor_id)
self._spec = self._sensor_object.specification()
self._sim.renderer.bind_render_target(self._sensor_object)
if self._spec.gpu2gpu_transfer:
assert (hsim.cuda_enabled
), "Must build habitat sim with cuda for gpu2gpu-transfer"
if torch is None:
import torch
device = torch.device("cuda", self._sim.gpu_device)
torch.cuda.set_device(device)
resolution = self._spec.resolution
if self._spec.sensor_type == hsim.SensorType.SEMANTIC:
self._buffer = torch.empty(resolution[0],
resolution[1],
dtype=torch.int32,
device=device)
elif self._spec.sensor_type == hsim.SensorType.DEPTH:
self._buffer = torch.empty(resolution[0],
resolution[1],
dtype=torch.float32,
device=device)
else:
self._buffer = torch.empty(resolution[0],
resolution[1],
4,
dtype=torch.uint8,
device=device)
else:
if self._spec.sensor_type == hsim.SensorType.SEMANTIC:
self._buffer = np.empty(
(self._spec.resolution[0], self._spec.resolution[1]),
dtype=np.uint32,
)
elif self._spec.sensor_type == hsim.SensorType.DEPTH:
self._buffer = np.empty(
(self._spec.resolution[0], self._spec.resolution[1]),
dtype=np.float32,
)
else:
self._buffer = np.empty(
(
self._spec.resolution[0],
self._spec.resolution[1],
self._spec.channels,
),
dtype=np.uint8,
)
noise_model_kwargs = self._spec.noise_model_kwargs
self._noise_model = make_sensor_noise_model(
self._spec.noise_model,
{
"gpu_device_id": self._sim.gpu_device,
**noise_model_kwargs
},
)
assert self._noise_model.is_valid_sensor_type(
self._spec.sensor_type
), "Noise model '{}' is not valid for sensor '{}'".format(
self._spec.noise_model, self._spec.uuid)
