540 lines
20 KiB
Python
540 lines
20 KiB
Python
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from __future__ import annotations
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import math
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from collections import Counter
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from dataclasses import dataclass
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from typing import Iterable
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from OCC.Core.BRepAdaptor import BRepAdaptor_Surface
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from OCC.Core.BRepGProp import brepgprop
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from OCC.Core.GeomAbs import GeomAbs_Cylinder, GeomAbs_Plane
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from OCC.Core.GProp import GProp_GProps
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from OCC.Core.TopAbs import TopAbs_EDGE
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from OCC.Core.TopExp import topexp
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from OCC.Core.TopTools import TopTools_IndexedMapOfShape
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from OCC.Core.TopoDS import TopoDS_Shape
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from .geometry_utils import (
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_axis_parameter,
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_direction_dot,
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_point_axis_distance,
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_shape_axis_interval,
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_shape_diagonal,
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_surface_center,
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)
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ANGULAR_TOLERANCE = 1.0e-7
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COVERAGE_TOLERANCE = 0.82
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EXTERNAL_COAXIAL_CONFIDENCE_BOOST = 0.08
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EXTERNAL_TANGENT_CONFIDENCE_BOOST = 0.03
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EXTERNAL_OPENING_PLANE_CONFIDENCE_BOOST = 0.04
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@dataclass(frozen=True)
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class RecognitionFace:
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face_id: int
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solid_id: int
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surface_type: str
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area: float
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centroid: tuple[float, float, float]
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boundary_edge_ids: tuple[int, ...]
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adjacent_face_ids: tuple[int, ...]
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axis_point: object | None = None
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axis_direction: object | None = None
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radius: float | None = None
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axis_interval: tuple[float, float] | None = None
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angular_span: float | None = None
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plane_parameter: float | None = None
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@dataclass(frozen=True)
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class RecognitionRelation:
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relation_type: str
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face_ids: tuple[int, ...]
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residual: float
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@dataclass(frozen=True)
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class RecognitionGraph:
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solid_id: int
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face_ids: tuple[int, ...]
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faces: tuple[RecognitionFace, ...]
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relation_counts: dict[str, int]
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relations: tuple[RecognitionRelation, ...]
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def face(self, face_id: int) -> RecognitionFace | None:
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for item in self.faces:
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if item.face_id == int(face_id):
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return item
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return None
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@dataclass(frozen=True)
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class ThroughHoleRegion:
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face_ids: tuple[int, ...]
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solid_id: int
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diameter: float
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axis_interval: tuple[float, float]
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angular_coverage: float
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opening_face_ids: tuple[int, ...]
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confidence: float
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def build_recognition_graph(model: object, solid_id: int) -> RecognitionGraph:
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face_ids = tuple(
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face_id
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for face_id, item in enumerate(getattr(model, "face_solid_ids", ()))
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if int(item) == int(solid_id)
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)
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faces: list[RecognitionFace] = []
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for face_id in face_ids:
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face = getattr(model, "faces")[face_id]
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boundary_edge_ids = tuple(_face_boundary_edge_ids(model, face_id))
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adjacent_face_ids = tuple(sorted(_adjacent_face_ids(model, boundary_edge_ids, face_id)))
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surf = BRepAdaptor_Surface(face)
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surface_type = "other"
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axis_point = None
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axis_direction = None
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radius: float | None = None
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axis_interval: tuple[float, float] | None = None
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angular_span: float | None = None
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plane_parameter: float | None = None
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if surf.GetType() == GeomAbs_Cylinder:
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surface_type = "cylinder"
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cylinder = surf.Cylinder()
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axis = cylinder.Axis()
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axis_point = axis.Location()
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axis_direction = axis.Direction()
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radius = float(cylinder.Radius())
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axis_interval = _shape_axis_interval(face, axis_point, axis_direction)
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angular_span = abs(float(surf.LastUParameter()) - float(surf.FirstUParameter()))
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elif surf.GetType() == GeomAbs_Plane:
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surface_type = "plane"
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plane = surf.Plane()
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axis_point = plane.Location()
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axis_direction = plane.Axis().Direction()
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plane_parameter = _axis_parameter(axis_point, axis_direction, plane.Location())
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area, centroid = _surface_metrics(face)
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faces.append(
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RecognitionFace(
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face_id=face_id,
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solid_id=int(solid_id),
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surface_type=surface_type,
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area=area,
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centroid=centroid,
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boundary_edge_ids=boundary_edge_ids,
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adjacent_face_ids=adjacent_face_ids,
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axis_point=axis_point,
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axis_direction=axis_direction,
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radius=radius,
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axis_interval=axis_interval,
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angular_span=angular_span,
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plane_parameter=plane_parameter,
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)
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)
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relations = infer_recognition_relations(faces, _recognition_tolerance(model))
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relations.extend(_external_recognition_relations(model, face_ids))
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relation_counts = dict(Counter(item.relation_type for item in relations))
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return RecognitionGraph(
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solid_id=int(solid_id),
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face_ids=face_ids,
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faces=tuple(faces),
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relation_counts=relation_counts,
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relations=tuple(relations),
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)
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def infer_recognition_relations(
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faces: Iterable[RecognitionFace],
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tolerance: float,
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) -> list[RecognitionRelation]:
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items = list(faces)
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relations: list[RecognitionRelation] = []
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for face in items:
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for adjacent_id in face.adjacent_face_ids:
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if face.face_id < adjacent_id:
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relations.append(RecognitionRelation("adjacent", (face.face_id, adjacent_id), 0.0))
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for index, left in enumerate(items):
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for right in items[index + 1 :]:
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if left.surface_type == "plane" and right.surface_type == "plane":
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relation = _plane_relation(left, right, tolerance)
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if relation is not None:
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relations.append(relation)
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if left.surface_type == "cylinder" and right.surface_type == "cylinder":
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relation = _cylinder_relation(left, right, tolerance)
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if relation is not None:
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relations.append(relation)
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return relations
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def recognize_through_hole_regions(model: object, solid_id: int | None = None) -> list[ThroughHoleRegion]:
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solid_ids = _solid_ids(model, solid_id)
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cache_key = ("all", solid_ids) if solid_id is None else ("solid", int(solid_id))
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cache = getattr(model, "_through_hole_regions_cache", None)
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if isinstance(cache, dict) and cache_key in cache:
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return list(cache[cache_key])
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regions: list[ThroughHoleRegion] = []
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for current_solid_id in solid_ids:
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graph = _cached_recognition_graph(model, current_solid_id)
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regions.extend(_recognize_graph_through_hole_regions(model, graph))
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result = _dedupe_regions(regions)
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if isinstance(cache, dict):
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cache[cache_key] = list(result)
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return result
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def recognition_summary(model: object) -> dict[str, object]:
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solid_ids = _solid_ids(model, None)
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relation_counts: Counter[str] = Counter()
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hole_count = 0
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face_count = 0
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for solid_id in solid_ids:
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graph = _cached_recognition_graph(model, solid_id)
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relation_counts.update(graph.relation_counts)
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face_count += len(graph.face_ids)
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hole_count += len(recognize_through_hole_regions(model, solid_id))
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return {
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"source": "internal-recognition-graph",
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"solid_count": len(solid_ids),
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"face_count": face_count,
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"relation_counts": dict(relation_counts),
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"through_hole_region_count": hole_count,
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}
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def _cached_recognition_graph(model: object, solid_id: int) -> RecognitionGraph:
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cache = getattr(model, "_recognition_graph_cache", None)
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if isinstance(cache, dict) and int(solid_id) in cache:
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return cache[int(solid_id)]
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graph = build_recognition_graph(model, int(solid_id))
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if isinstance(cache, dict):
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cache[int(solid_id)] = graph
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return graph
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def _recognize_graph_through_hole_regions(model: object, graph: RecognitionGraph) -> list[ThroughHoleRegion]:
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cylinders = [face for face in graph.faces if face.surface_type == "cylinder" and face.radius and face.radius > 0]
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if not cylinders:
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return []
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tolerance = _recognition_tolerance(model)
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visited: set[int] = set()
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regions: list[ThroughHoleRegion] = []
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for source in cylinders:
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if source.face_id in visited:
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continue
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group = _cocylindrical_interval_group(model, cylinders, source, tolerance)
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visited.update(face.face_id for face in group)
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if not group:
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continue
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coverage = sum(min(abs(float(face.angular_span or 0.0)), math.tau) for face in group)
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if coverage < math.tau * COVERAGE_TOLERANCE:
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continue
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intervals = [face.axis_interval for face in group if face.axis_interval is not None]
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if not intervals:
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continue
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v_min = min(float(item[0]) for item in intervals)
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v_max = max(float(item[1]) for item in intervals)
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opening_face_ids = _opening_plane_face_ids(graph, group, tolerance)
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confidence = 0.72
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if coverage >= math.tau * 0.98:
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confidence += 0.12
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if len(opening_face_ids) >= 2:
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confidence += 0.12
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if len(group) > 1:
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confidence += 0.04
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if _has_external_relation(model, (face.face_id for face in group), {"coaxial"}):
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confidence += EXTERNAL_COAXIAL_CONFIDENCE_BOOST
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if _has_external_relation(model, (face.face_id for face in group), {"tangent"}):
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confidence += EXTERNAL_TANGENT_CONFIDENCE_BOOST
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if len(opening_face_ids) >= 2 and _has_external_relation(
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model,
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opening_face_ids,
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{"coplanar", "parallel"},
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):
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confidence += EXTERNAL_OPENING_PLANE_CONFIDENCE_BOOST
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regions.append(
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ThroughHoleRegion(
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face_ids=tuple(sorted(face.face_id for face in group)),
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solid_id=graph.solid_id,
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diameter=float(group[0].radius or 0.0) * 2.0,
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axis_interval=(v_min, v_max),
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angular_coverage=coverage,
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opening_face_ids=tuple(sorted(opening_face_ids)),
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confidence=min(confidence, 0.99),
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)
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)
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return regions
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def _external_recognition_relations(model: object, face_ids: Iterable[int]) -> list[RecognitionRelation]:
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cache = getattr(model, "_asitus_geometric_relation_cache", None)
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if not isinstance(cache, dict):
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return []
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valid_face_ids = {int(item) for item in face_ids}
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relations: list[RecognitionRelation] = []
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for pair, items in cache.items():
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try:
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face_pair = tuple(sorted(int(item) for item in pair))
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except (TypeError, ValueError):
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continue
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if len(face_pair) != 2 or face_pair[0] not in valid_face_ids or face_pair[1] not in valid_face_ids:
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continue
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if not isinstance(items, (tuple, list)):
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continue
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for item in items:
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if not isinstance(item, dict):
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continue
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relation_type = str(item.get("relation_type") or "").strip()
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if not relation_type:
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continue
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relations.append(
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RecognitionRelation(
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f"external_{relation_type}",
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face_pair,
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_float_or_zero(item.get("residual")),
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)
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)
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return relations
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def _has_external_relation(model: object, face_ids: Iterable[int], relation_types: set[str]) -> bool:
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return _external_relation(model, face_ids, relation_types) is not None
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def _external_relation(
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model: object,
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face_ids: Iterable[int],
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relation_types: set[str],
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) -> dict[str, object] | None:
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cache = getattr(model, "_asitus_geometric_relation_cache", None)
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if not isinstance(cache, dict):
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return None
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face_id_set = {int(item) for item in face_ids}
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if len(face_id_set) < 2:
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return None
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for pair, items in cache.items():
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try:
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face_pair = tuple(sorted(int(item) for item in pair))
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except (TypeError, ValueError):
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continue
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if len(face_pair) != 2 or face_pair[0] not in face_id_set or face_pair[1] not in face_id_set:
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continue
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if not isinstance(items, (tuple, list)):
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continue
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for item in items:
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if isinstance(item, dict) and str(item.get("relation_type") or "").strip() in relation_types:
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return item
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return None
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def _float_or_zero(value: object) -> float:
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try:
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return float(value)
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except (TypeError, ValueError):
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return 0.0
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def _cocylindrical_interval_group(
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model: object,
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cylinders: list[RecognitionFace],
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source: RecognitionFace,
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tolerance: float,
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) -> list[RecognitionFace]:
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pending = [source]
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visited = {source.face_id}
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result: list[RecognitionFace] = []
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while pending:
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current = pending.pop(0)
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result.append(current)
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for candidate in cylinders:
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if candidate.face_id in visited:
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continue
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if candidate.solid_id != source.solid_id:
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continue
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if not _recognition_faces_are_cocylindrical(source, candidate, tolerance) and not (
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|
_external_cocylindrical_hint(model, source, candidate, tolerance)
|
||
|
|
):
|
||
|
|
continue
|
||
|
|
if not _intervals_overlap_or_touch(current.axis_interval, candidate.axis_interval, tolerance * 50.0):
|
||
|
|
continue
|
||
|
|
visited.add(candidate.face_id)
|
||
|
|
pending.append(candidate)
|
||
|
|
return result
|
||
|
|
|
||
|
|
|
||
|
|
def _external_cocylindrical_hint(
|
||
|
|
model: object,
|
||
|
|
left: RecognitionFace,
|
||
|
|
right: RecognitionFace,
|
||
|
|
tolerance: float,
|
||
|
|
) -> bool:
|
||
|
|
relation = _external_relation(model, (left.face_id, right.face_id), {"coaxial"})
|
||
|
|
if relation is None:
|
||
|
|
return False
|
||
|
|
if left.radius is None or right.radius is None:
|
||
|
|
return False
|
||
|
|
radius_tolerance = max(tolerance, max(left.radius, right.radius) * 1e-6)
|
||
|
|
radius_delta = abs(float(left.radius) - float(right.radius))
|
||
|
|
residual = _float_or_zero(relation.get("residual"))
|
||
|
|
return radius_delta <= radius_tolerance or residual <= radius_tolerance
|
||
|
|
|
||
|
|
|
||
|
|
def _recognition_faces_are_cocylindrical(left: RecognitionFace, right: RecognitionFace, tolerance: float) -> bool:
|
||
|
|
if left.axis_point is None or left.axis_direction is None or right.axis_point is None or right.axis_direction is None:
|
||
|
|
return False
|
||
|
|
if left.radius is None or right.radius is None:
|
||
|
|
return False
|
||
|
|
radius_tolerance = max(tolerance, max(left.radius, right.radius) * 1e-6)
|
||
|
|
if abs(left.radius - right.radius) > radius_tolerance:
|
||
|
|
return False
|
||
|
|
if abs(_direction_dot(left.axis_direction, right.axis_direction)) < 1.0 - 1e-6:
|
||
|
|
return False
|
||
|
|
return _point_axis_distance(left.axis_point, left.axis_direction, right.axis_point) <= max(tolerance, radius_tolerance)
|
||
|
|
|
||
|
|
|
||
|
|
def _opening_plane_face_ids(
|
||
|
|
graph: RecognitionGraph,
|
||
|
|
group: list[RecognitionFace],
|
||
|
|
tolerance: float,
|
||
|
|
) -> set[int]:
|
||
|
|
if not group or group[0].axis_point is None or group[0].axis_direction is None:
|
||
|
|
return set()
|
||
|
|
axis_point = group[0].axis_point
|
||
|
|
axis_direction = group[0].axis_direction
|
||
|
|
intervals = [face.axis_interval for face in group if face.axis_interval is not None]
|
||
|
|
if not intervals:
|
||
|
|
return set()
|
||
|
|
v_min = min(float(item[0]) for item in intervals)
|
||
|
|
v_max = max(float(item[1]) for item in intervals)
|
||
|
|
end_tolerance = max(tolerance * 80.0, abs(v_max - v_min) * 1e-4, 1e-4)
|
||
|
|
side_ids = {face.face_id for face in group}
|
||
|
|
adjacent_ids: set[int] = set()
|
||
|
|
for face in group:
|
||
|
|
adjacent_ids.update(face.adjacent_face_ids)
|
||
|
|
openings: set[int] = set()
|
||
|
|
by_id = {face.face_id: face for face in graph.faces}
|
||
|
|
for adjacent_id in adjacent_ids - side_ids:
|
||
|
|
adjacent = by_id.get(adjacent_id)
|
||
|
|
if adjacent is None or adjacent.surface_type != "plane" or adjacent.axis_direction is None:
|
||
|
|
continue
|
||
|
|
if abs(_direction_dot(adjacent.axis_direction, axis_direction)) < 1.0 - ANGULAR_TOLERANCE:
|
||
|
|
continue
|
||
|
|
try:
|
||
|
|
parameter = _axis_parameter(axis_point, axis_direction, _gp_point(adjacent.centroid))
|
||
|
|
except Exception:
|
||
|
|
continue
|
||
|
|
if abs(parameter - v_min) <= end_tolerance or abs(parameter - v_max) <= end_tolerance:
|
||
|
|
openings.add(adjacent_id)
|
||
|
|
return openings
|
||
|
|
|
||
|
|
|
||
|
|
def _plane_relation(left: RecognitionFace, right: RecognitionFace, tolerance: float) -> RecognitionRelation | None:
|
||
|
|
if left.axis_direction is None or right.axis_direction is None:
|
||
|
|
return None
|
||
|
|
dot = abs(_direction_dot(left.axis_direction, right.axis_direction))
|
||
|
|
if dot >= 1.0 - ANGULAR_TOLERANCE:
|
||
|
|
residual = abs(_plane_offset(left, right))
|
||
|
|
if residual <= tolerance:
|
||
|
|
return RecognitionRelation("coplanar", (left.face_id, right.face_id), residual)
|
||
|
|
return RecognitionRelation("parallel", (left.face_id, right.face_id), residual)
|
||
|
|
if dot <= ANGULAR_TOLERANCE:
|
||
|
|
return RecognitionRelation("perpendicular", (left.face_id, right.face_id), dot)
|
||
|
|
return None
|
||
|
|
|
||
|
|
|
||
|
|
def _cylinder_relation(left: RecognitionFace, right: RecognitionFace, tolerance: float) -> RecognitionRelation | None:
|
||
|
|
if not _recognition_faces_are_cocylindrical(left, right, tolerance):
|
||
|
|
if left.axis_point is not None and left.axis_direction is not None and right.axis_direction is not None:
|
||
|
|
if abs(_direction_dot(left.axis_direction, right.axis_direction)) >= 1.0 - ANGULAR_TOLERANCE:
|
||
|
|
return RecognitionRelation("parallel_axis", (left.face_id, right.face_id), 0.0)
|
||
|
|
return None
|
||
|
|
residual = 0.0
|
||
|
|
if left.axis_point is not None and left.axis_direction is not None and right.axis_point is not None:
|
||
|
|
residual = _point_axis_distance(left.axis_point, left.axis_direction, right.axis_point)
|
||
|
|
return RecognitionRelation("coaxial", (left.face_id, right.face_id), residual)
|
||
|
|
|
||
|
|
|
||
|
|
def _plane_offset(left: RecognitionFace, right: RecognitionFace) -> float:
|
||
|
|
if left.axis_point is None or left.axis_direction is None or right.axis_point is None:
|
||
|
|
return math.inf
|
||
|
|
return float(_axis_parameter(left.axis_point, left.axis_direction, right.axis_point))
|
||
|
|
|
||
|
|
|
||
|
|
def _surface_metrics(shape: TopoDS_Shape) -> tuple[float, tuple[float, float, float]]:
|
||
|
|
props = GProp_GProps()
|
||
|
|
try:
|
||
|
|
brepgprop.SurfaceProperties(shape, props)
|
||
|
|
center = props.CentreOfMass()
|
||
|
|
return float(props.Mass()), (float(center.X()), float(center.Y()), float(center.Z()))
|
||
|
|
except Exception:
|
||
|
|
center = _surface_center(shape)
|
||
|
|
return 0.0, (float(center.X()), float(center.Y()), float(center.Z()))
|
||
|
|
|
||
|
|
|
||
|
|
def _face_boundary_edge_ids(model: object, face_id: int) -> list[int]:
|
||
|
|
if hasattr(model, "_face_boundary_edge_ids"):
|
||
|
|
return list(model._face_boundary_edge_ids(face_id)) # noqa: SLF001
|
||
|
|
edges = TopTools_IndexedMapOfShape()
|
||
|
|
topexp.MapShapes(getattr(model, "faces")[face_id], TopAbs_EDGE, edges)
|
||
|
|
return list(range(edges.Size()))
|
||
|
|
|
||
|
|
|
||
|
|
def _adjacent_face_ids(model: object, edge_ids: Iterable[int], face_id: int) -> set[int]:
|
||
|
|
adjacent: set[int] = set()
|
||
|
|
if hasattr(model, "_adjacent_face_ids_for_edges"):
|
||
|
|
adjacent.update(model._adjacent_face_ids_for_edges(edge_ids, face_id)) # noqa: SLF001
|
||
|
|
else:
|
||
|
|
edge_face_ids = getattr(model, "_edge_face_ids_cache", {})
|
||
|
|
for edge_id in edge_ids:
|
||
|
|
adjacent.update(int(item) for item in edge_face_ids.get(int(edge_id), ()) if int(item) != int(face_id))
|
||
|
|
return adjacent
|
||
|
|
|
||
|
|
|
||
|
|
def _recognition_tolerance(model: object) -> float:
|
||
|
|
try:
|
||
|
|
diagonal = _shape_diagonal(getattr(model, "shape"))
|
||
|
|
except Exception:
|
||
|
|
diagonal = 1.0
|
||
|
|
return min(max(float(diagonal) * 1e-7, 1e-6), 1e-3)
|
||
|
|
|
||
|
|
|
||
|
|
def _solid_ids(model: object, solid_id: int | None) -> tuple[int, ...]:
|
||
|
|
if solid_id is not None:
|
||
|
|
return (int(solid_id),)
|
||
|
|
face_solid_ids = sorted({int(item) for item in getattr(model, "face_solid_ids", ()) if int(item) >= 0})
|
||
|
|
if face_solid_ids:
|
||
|
|
return tuple(face_solid_ids)
|
||
|
|
return tuple(range(len(getattr(model, "solids", ()) or ())))
|
||
|
|
|
||
|
|
|
||
|
|
def _intervals_overlap_or_touch(
|
||
|
|
left: tuple[float, float] | None,
|
||
|
|
right: tuple[float, float] | None,
|
||
|
|
tolerance: float,
|
||
|
|
) -> bool:
|
||
|
|
if left is None or right is None:
|
||
|
|
return True
|
||
|
|
left_min, left_max = min(left), max(left)
|
||
|
|
right_min, right_max = min(right), max(right)
|
||
|
|
return max(left_min, right_min) <= min(left_max, right_max) + max(tolerance, 0.0)
|
||
|
|
|
||
|
|
|
||
|
|
def _dedupe_regions(regions: Iterable[ThroughHoleRegion]) -> list[ThroughHoleRegion]:
|
||
|
|
result: list[ThroughHoleRegion] = []
|
||
|
|
seen: set[tuple[int, ...]] = set()
|
||
|
|
for region in sorted(regions, key=lambda item: (item.solid_id, item.face_ids)):
|
||
|
|
if region.face_ids in seen:
|
||
|
|
continue
|
||
|
|
seen.add(region.face_ids)
|
||
|
|
result.append(region)
|
||
|
|
return result
|
||
|
|
|
||
|
|
|
||
|
|
def _gp_point(values: tuple[float, float, float]):
|
||
|
|
from OCC.Core.gp import gp_Pnt
|
||
|
|
|
||
|
|
return gp_Pnt(float(values[0]), float(values[1]), float(values[2]))
|