diffCheck.dfb_segmentation module

A submodule for the semantic segmentation methods.

class diffCheck.diffcheck_bindings.dfb_segmentation.DFSegmentation

Bases: pybind11_object

A static class for the segmentation methods.

static associate_clusters(is_roundwood: bool, discriminate_points: bool, reference_mesh: collections.abc.Sequence[diffCheck.diffcheck_bindings.dfb_geometry.DFMesh], unassociated_clusters: collections.abc.Sequence[diffCheck.diffcheck_bindings.dfb_geometry.DFPointCloud], angle_threshold: SupportsFloat | SupportsIndex = 0.1, association_threshold: SupportsFloat | SupportsIndex = 0.1, maximum_face_segment_distance: SupportsFloat | SupportsIndex = 0.05) → list[diffCheck.diffcheck_bindings.dfb_geometry.DFPointCloud]

static clean_unassociated_clusters(is_roundwood: bool, discriminate_points: bool, unassociated_clusters: collections.abc.Sequence[diffCheck.diffcheck_bindings.dfb_geometry.DFPointCloud], associated_clusters: collections.abc.Sequence[collections.abc.Sequence[diffCheck.diffcheck_bindings.dfb_geometry.DFPointCloud]], reference_mesh: collections.abc.Sequence[collections.abc.Sequence[diffCheck.diffcheck_bindings.dfb_geometry.DFMesh]], angle_threshold: SupportsFloat | SupportsIndex = 0.1, association_threshold: SupportsFloat | SupportsIndex = 0.1, maximum_face_segment_distance: SupportsFloat | SupportsIndex = 0.05) → None

static segment_by_normal(point_cloud: diffCheck.diffcheck_bindings.dfb_geometry.DFPointCloud, normal_threshold_degree: SupportsFloat | SupportsIndex = 20.0, min_cluster_size: SupportsInt | SupportsIndex = 10, use_knn_neighborhood: bool = True, knn_neighborhood_size: SupportsInt | SupportsIndex = 10, radius_neighborhood_size: SupportsFloat | SupportsIndex = 0.1, color_clusters: bool = False) → list[diffCheck.diffcheck_bindings.dfb_geometry.DFPointCloud]