feat: 算法升级、整车配准集成与性能分析文档

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

alg/delivery_v1.2.1/underframe_deflection/structures.py

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+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+import numpy as np
+
+
+@dataclass(slots=True)
+class FrameHypothesis:
+    name: str
+    axes: np.ndarray
+    origin: np.ndarray
+    score: float
+    bottom_score: float
+    symmetry_score: float
+    flatness_score: float
+    hole_score: float
+    continuity_score: float
+
+
+@dataclass(slots=True)
+class CandidateBand:
+    candidate_id: str
+    slice_index: int
+    x_start: float
+    x_end: float
+    x_center: float
+    y_min: float
+    y_max: float
+    y_center: float
+    z_low: float
+    width: float
+    point_count: int
+    low_point_count: int
+    flatness: float
+    normal_alignment: float
+    score: float
+    edge_ratio: float
+    side: str
+    y_mid: float
+    bin_start: int
+    bin_end: int
+
+
+@dataclass(slots=True)
+class SliceResult:
+    slice_index: int
+    x_start: float
+    x_end: float
+    x_center: float
+    y_mid: float
+    candidate_bands: list[CandidateBand] = field(default_factory=list)
+    left_candidates: list[CandidateBand] = field(default_factory=list)
+    right_candidates: list[CandidateBand] = field(default_factory=list)
+    point_count: int = 0
+
+
+@dataclass(slots=True)
+class TrackSolution:
+    side: str
+    rank: int
+    score: float
+    coverage_ratio: float
+    coverage_count: int
+    candidate_ids: list[str | None]
+    candidates: list[CandidateBand]
+    score_margin: float | None
+    confidence: float
+
+
+@dataclass(slots=True)
+class RepresentativePoint:
+    side: str
+    slice_index: int
+    x: float
+    y: float
+    z: float
+    width: float
+    point_count: int
+    residual: float
+    confidence: float
+    x_start: float
+    x_end: float
+
+
+@dataclass(slots=True)
+class FittedLine:
+    side: str
+    x_support: np.ndarray
+    y_support: np.ndarray
+    z_support: np.ndarray
+    y_spline: Any
+    z_spline: Any
+    y_residual_rms: float
+    z_residual_rms: float
+    low_confidence_segments: list[tuple[float, float]]
+    gaps: list[tuple[float, float]]
+
+
+@dataclass(slots=True)
+class HoleCandidate:
+    side: str
+    region: str
+    axis: str
+    center: np.ndarray
+    radius: float
+    score: float
+    inlier_count: int
+    coverage_ratio: float
+    residual: float
+    confidence: float
+
+
+@dataclass(slots=True)
+class ReferenceLine:
+    side: str
+    available: bool
+    point_front: np.ndarray | None
+    point_back: np.ndarray | None
+    direction: np.ndarray | None
+    confidence: float
+    residual: float | None
+    candidates_front: list[HoleCandidate] = field(default_factory=list)
+    candidates_back: list[HoleCandidate] = field(default_factory=list)
+    alternates: list[dict[str, Any]] = field(default_factory=list)