lipan
29f1d45d66
算法更新: delivery v1.2.1、平整度v1.5、测距v2.2、整车配准v1.3 适配器: vehicle-registration 新增、各算法 manifest 和 adapter 更新 后端: taskCadFiles/source 字段迁移、derivedPointClouds 注册、取消任务联动 前端: ElapsedTime 时长显示、两步算法流程、canRun 逻辑修复 文档: 新增5份算法性能分析报告
149 lines
4.4 KiB
Python
149 lines
4.4 KiB
Python
"""Result dataclasses for coupler_panel.
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These types form the **stable public schema** of the package; their
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field names and semantics are guarded by ``SCHEMA_VERSION`` (see
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``_version.py``).
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All numeric units are **mm** for distances and **degree** for angles
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unless otherwise noted.
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"""
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from __future__ import annotations
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from dataclasses import asdict, dataclass, field
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from typing import Any
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import numpy as np
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# ---------------------------------------------------------------------------
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# Building blocks
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# ---------------------------------------------------------------------------
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@dataclass(frozen=True)
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class Hole:
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"""A single detected (or GT) circular hole on the panel."""
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center: tuple[float, float, float] # (x, y, z), mm
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radius_mm: float
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fit_residual_rms_mm: float # 0 for GT
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role: str # "locating" | "central" | "unknown"
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@dataclass(frozen=True)
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class HoleSet:
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"""The four locating holes plus an optional central hole.
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``locating`` is ordered consistently between GT and detection so that
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Kabsch pairing is index-aligned.
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"""
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locating: tuple[Hole, Hole, Hole, Hole]
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central: Hole | None = None
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def locating_centers(self) -> np.ndarray:
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"""Return a (4, 3) ndarray of locating-hole centres."""
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return np.asarray([h.center for h in self.locating], dtype=np.float64)
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@dataclass(frozen=True)
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class PanelPlane:
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"""The fitted (or GT) panel plane."""
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normal: tuple[float, float, float] # unit vector, n_x > 0 enforced
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point_on_plane: tuple[float, float, float]
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d_offset: float # n . x + d = 0
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inlier_ratio: float # 1.0 for GT
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inlier_residual_rms_mm: float # 0 for GT
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@dataclass(frozen=True)
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class ReferenceFrame:
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"""Reference geometry derived from the four-hole panel centre."""
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center_C: tuple[float, float, float]
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# Reference line L = C + lam * e_x (always parallel to the +x axis).
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line_direction: tuple[float, float, float] = (1.0, 0.0, 0.0)
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# Reference plane: z = C_z. Stored as plane normal + offset.
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reference_plane_z: float = 0.0
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# Longitudinal mid-plane: y = C_y.
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longitudinal_mid_y: float = 0.0
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@dataclass(frozen=True)
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class StageTiming:
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"""Per-stage wall-clock and peak-memory cost."""
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stage: str
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seconds: float
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peak_kib: float
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# ---------------------------------------------------------------------------
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# Top-level result
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# ---------------------------------------------------------------------------
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@dataclass
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class CouplerMeasurement:
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"""Top-level result of the coupler-panel measurement pipeline.
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See ``docs/USAGE.md`` for the stable-API contract.
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"""
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schema_version: str
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algorithm_version: str
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# --- Primary measurands ---
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theta_right_deg: float # atan2(n_y, n_x), with right_axis_sign applied
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theta_ref_deg: float # atan2(n_z, n_x)
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D_y_max_mm: float # max |y_i - C_y| over panel ROI
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D_z_max_mm: float # max |z_i - C_z| over panel ROI
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dx_y_max_mm: float # |A| * D_y_max, A = -n_y / n_x
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dx_z_max_mm: float # |B| * D_z_max, B = -n_z / n_x
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# --- Geometry ---
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center_C: tuple[float, float, float]
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normal: tuple[float, float, float] # n_x > 0
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holes: HoleSet
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plane: PanelPlane
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frame: ReferenceFrame
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# --- Diagnostics ---
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quality_flags: list[str] = field(default_factory=list)
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timings: list[StageTiming] = field(default_factory=list)
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report: dict[str, Any] = field(default_factory=dict)
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def to_dict(self) -> dict[str, Any]:
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"""Return a fully JSON-serialisable dict."""
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return _to_jsonable(asdict(self))
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _to_jsonable(obj: Any) -> Any:
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"""Recursively convert numpy / tuple structures into plain Python types."""
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if isinstance(obj, dict):
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return {k: _to_jsonable(v) for k, v in obj.items()}
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if isinstance(obj, (list, tuple)):
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return [_to_jsonable(v) for v in obj]
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if isinstance(obj, np.ndarray):
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return obj.tolist()
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if isinstance(obj, (np.floating, np.integer)):
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return obj.item()
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return obj
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__all__ = [
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"Hole",
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"HoleSet",
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"PanelPlane",
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"ReferenceFrame",
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"StageTiming",
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"CouplerMeasurement",
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]
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