cloudViewer.t.pipelines.slac.save_correspondences_for_pointclouds#

cloudViewer.t.pipelines.slac.save_correspondences_for_pointclouds(fnames_processed, fragment_pose_graph, params=SLACOptimizerParams(max_iterations=5, voxel_size=5.000000e-02, distance_threshold=7.000000e-02, fitness_threshold=3.000000e-01, regularizer_weight=1.000000e+00, device=cloudViewer.core.Device('CPU:0'), slac_folder=''), debug_option=SLACDebugOption(debug=False, debug_start_node_idx=0))#

Read pose graph containing loop closures and odometry to compute correspondences. Uses aggressive pruning – reject any suspicious pair.

Parameters:

  • fnames_processed (collections.abc.Sequence[str]) – List of filenames (str) for pre-processed pointcloud fragments.

  • fragment_pose_graph (cloudViewer::pipelines::registration::PoseGraph) – PoseGraph for pointcloud fragments

  • (cloudViewer.t.pipelines.slac.slac_optimizer_params (params) – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • optional – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • default=SLACOptimizerParams(max_iterations=5 – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • voxel_size=5.000000e-02 – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • distance_threshold=7.000000e-02 – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • fitness_threshold=3.000000e-01 – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • regularizer_weight=1.000000e+00 – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • device=cloudViewer.core.Device("CPU – 0”), slac_folder=””)): slac_optimizer_params Parameters to tune in optimization.

  • debug_option (cloudViewer.t.pipelines.slac.slac_debug_option, optional, default=SLACDebugOption(debug=False, debug_start_node_idx=0)) – debug options.

Returns:

None