124 lines
5.3 KiB
Python
124 lines
5.3 KiB
Python
"""StereoConfig 与 JSON 配置加载（§9 配置参数全量表）。
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全部参数配置外置、构造期一次加载并校验：缺项、类型错误、非法取值一律拒绝
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进入运行期（fail-fast）。所有默认值均为 ⚠占位值，未整定前不得用于飞行决策
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（§12.3 红线 1/2）。
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域权威（实现决策）：视差域 disparity_min_px / disparity_max_px 为权威，
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距离域 z_min_m / z_max_m 由 Z = F·B/D 派生为只读属性——域判定使用视差
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（§11.2 直接观测量），两套阈值不再冗余存储、避免互推舍入不一致（§6.4）。
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"""
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import json
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import math
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from dataclasses import dataclass, fields
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from typing import Any, Dict
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# JSON 加载时的整数型字段（其余按数值校验）
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_INT_FIELDS = frozenset({"consistency_N_frames", "consistency_M_frames", "filter_reset_frames"})
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@dataclass
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class StereoConfig:
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# ---- 几何组（来自标定 P1/P2，§9.1；⚠全部为占位值）----
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fx_px: float = 960.0
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fy_px: float = 960.0
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cx_px: float = 960.0
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cy_px: float = 540.0
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baseline_m: float = 0.06
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# ---- 匹配组（§9.2）----
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tau_y_px: float = 2.0
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tau_h_ratio: float = 0.25
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disparity_min_px: float = 3.0
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disparity_max_px: float = 57.6 # ⚠占位：F=960/B=0.06 下 ⇔ 近界 1.0 m
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# ---- 有效性组（§9.3）----
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max_delta_z_m: float = 2.0 # 误差预算 δZ(δD = 1px) 上限
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consistency_N_frames: int = 3 # 连续跳变降置信度的帧数
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consistency_M_frames: int = 5 # 连续异常判 invalid 的帧数
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consistency_jump_px: float = 3.0 # ⚠补充项：§9 未列，§6.7 的视差跳变门限
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# ---- 滤波组（§9.4）----
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smooth_alpha: float = 0.3
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jump_reset_m: float = 5.0
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filter_reset_frames: int = 5
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# ---- 目标隔离（§4：类别 + 框位置最近邻；⚠补充项）----
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isolation_gate_px: float = 50.0
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def __post_init__(self) -> None:
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_require(self.fx_px > 0.0, "fx_px", "必须为正")
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_require(self.fy_px > 0.0, "fy_px", "必须为正")
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_require(self.cx_px >= 0.0, "cx_px", "必须非负")
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_require(self.cy_px >= 0.0, "cy_px", "必须非负")
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_require(self.baseline_m > 0.0, "baseline_m", "必须为正")
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_require(self.tau_y_px > 0.0, "tau_y_px", "必须为正")
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_require(self.tau_h_ratio > 0.0, "tau_h_ratio", "必须为正")
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_require(
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0.0 < self.disparity_min_px < self.disparity_max_px,
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"disparity_min_px/disparity_max_px",
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"须满足 0 < 下限 < 上限",
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)
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_require(self.max_delta_z_m > 0.0, "max_delta_z_m", "必须为正")
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_require(self.consistency_N_frames >= 1, "consistency_N_frames", "必须 ≥ 1")
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_require(
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self.consistency_M_frames >= self.consistency_N_frames,
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"consistency_M_frames",
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"必须 ≥ consistency_N_frames",
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)
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_require(self.consistency_jump_px > 0.0, "consistency_jump_px", "必须为正")
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_require(0.0 < self.smooth_alpha <= 1.0, "smooth_alpha", "须落在 (0, 1]")
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_require(self.jump_reset_m > 0.0, "jump_reset_m", "必须为正")
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_require(self.filter_reset_frames >= 1, "filter_reset_frames", "必须 ≥ 1")
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_require(self.isolation_gate_px > 0.0, "isolation_gate_px", "必须为正")
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@property
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def focal_baseline_px_m(self) -> float:
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"""F·B：构造期一次算好的常量，热路径只做乘除（§11.1）。"""
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return self.fx_px * self.baseline_m
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@property
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def z_min_m(self) -> float:
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"""近界（由 disparity_max_px 派生）。"""
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return self.focal_baseline_px_m / self.disparity_max_px
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@property
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def z_max_m(self) -> float:
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"""远界（由 disparity_min_px 派生）。"""
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return self.focal_baseline_px_m / self.disparity_min_px
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@property
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def z_error_budget_max_m(self) -> float:
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"""误差预算门限对应的最远距离 sqrt(δZ_max·F·B)（δD = 1px，§7.2）。"""
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return math.sqrt(self.max_delta_z_m * self.focal_baseline_px_m)
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def load_from_json(path: str) -> StereoConfig:
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"""从 JSON 文件构建配置；缺项/未知字段/类型错误/非法取值一律抛 ValueError。"""
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with open(path, encoding="utf-8") as handle:
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data: Dict[str, Any] = json.load(handle)
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if not isinstance(data, dict):
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raise ValueError("配置非法: 顶层须为 JSON 对象")
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known = {item.name for item in fields(StereoConfig)}
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unknown = sorted(set(data) - known)
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if unknown:
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raise ValueError(f"未知配置字段: {unknown}")
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missing = sorted(known - set(data))
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if missing:
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raise ValueError(f"缺少配置字段: {missing}")
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for name, value in data.items():
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if isinstance(value, bool):
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raise ValueError(f"配置类型非法: {name} 须为数值")
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if name in _INT_FIELDS:
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if not isinstance(value, int):
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raise ValueError(f"配置类型非法: {name} 须为整数")
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elif not isinstance(value, (int, float)):
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raise ValueError(f"配置类型非法: {name} 须为数值")
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return StereoConfig(**data)
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def _require(condition: bool, field_name: str, message: str) -> None:
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if not condition:
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raise ValueError(f"配置非法: {field_name} {message}")
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