curobo.wrap.model.robot_segmenter module

class RobotSegmenter(
robot_world: RobotWorld,
distance_threshold: float = 0.05,
use_cuda_graph: bool = True,
ops_dtype: dtype = torch.float32,
depth_to_meter: float = 0.001,
)

Bases: object

static from_robot_file(
robot_file: str | Dict,
collision_sphere_buffer: float | None = None,
distance_threshold: float = 0.05,
use_cuda_graph: bool = True,
tensor_args: TensorDeviceType = TensorDeviceType(device=device(type='cuda', index=0), dtype=torch.float32, collision_geometry_dtype=torch.float32, collision_gradient_dtype=torch.float32, collision_distance_dtype=torch.float32),
)
get_pointcloud_from_depth(
camera_obs: CameraObservation,
)
update_camera_projection(
camera_obs: CameraObservation,
)
get_robot_mask(
camera_obs: CameraObservation,
joint_state: JointState,
)

Assumes 1 robot and batch of depth images, batch of poses

get_robot_mask_from_active_js(
camera_obs: CameraObservation,
active_joint_state: JointState,
)
_create_cg_graph(
cam_obs,
q,
)
_call_op(cam_obs, q)
_mask_op(camera_obs, q)
property kinematics: CudaRobotModel
property robot_world: RobotWorld
mask_image(
image: Tensor,
distance: Tensor,
distance_threshold: float,
) → Tuple[Tensor, Tensor]
mask_spheres_image(
image: Tensor,
link_spheres_tensor: Tensor,
points: Tensor,
distance_threshold: float,
) → Tuple[Tensor, Tensor]