CandidatePointClouds
rendering.CandidatePointClouds(
points,
lengths,
semidense_points,
semidense_length,
occupancy_bounds,
)
Batched candidate point clouds plus fused semi-dense reconstruction.
Attributes
| points |
Tensor[‘B’, ‘P’, 3] padded candidate point clouds (world frame). |
| lengths |
Tensor[‘B’] actual point counts per candidate. |
| semidense_points |
Tensor[‘K’, 3] collapsed semi-dense SLAM point cloud. |
| semidense_length |
Tensor[1] number of valid semi-dense points. |
| occupancy_bounds |
Tensor[6] = [xmin, xmax, ymin, ymax, zmin, zmax] covering snippet + candidates. |
Methods
| to_serializable |
Serialize this point-cloud batch into a cache-friendly CPU payload. |
| from_serializable |
Reconstruct one point-cloud batch from a serialized payload. |
to_serializable
rendering.CandidatePointClouds.to_serializable()
Serialize this point-cloud batch into a cache-friendly CPU payload.
from_serializable
rendering.CandidatePointClouds.from_serializable(payload, *, device)
Reconstruct one point-cloud batch from a serialized payload.
Parameters
| payload |
dict[str, object] |
Serialized payload produced by to_serializable. |
required |
| device |
torch.device |
Destination device for tensors. |
required |
Returns
|
'CandidatePointClouds' |
Reconstructed candidate-pointcloud batch. |