双目测距方案重构与其他小修改

2026-09-10 16:16:05 +08:00
parent 3325465359
commit 538ae4c6c7
39 changed files with 2285 additions and 1444 deletions
@@ -0,0 +1,82 @@
+"""左右匹配器（§6.2）：硬约束 + 代价升序贪心一一配对；接口注入。
+
+默认 GreedyMatcher 为纯函数（§4 构件表）；调用方可通过
+StereoRanger(matcher=...) 注入匈牙利等替换实现而不动调用方（§10.3）。
+
+硬约束（任一不满足直接拒绝配对，不进代价排序）：类别一致、|Δy| ≤ τ_y、
+框高相对差 ≤ τ_h。视差域 [D_min, D_max] 不参与配对：越界属有效性门
+（§6.2 已回填，与 §5 失败路径表/§6.3/§6.4/§2.3 一致）。
+"""
+
+from dataclasses import dataclass
+from typing import List, Protocol, Sequence
+
+from .config import StereoConfig
+from .sampling import SamplePoint
+
+
+@dataclass(frozen=True)
+class MatchPair:
+    """一一配对结果：左右下标 + 匹配代价（§6.2）。"""
+
+    left_index: int
+    right_index: int
+    cost: float
+
+
+class Matcher(Protocol):
+    """匹配器接口（§4：接口注入，默认贪心）。"""
+
+    def match(
+        self,
+        left: Sequence[SamplePoint],
+        right: Sequence[SamplePoint],
+        config: StereoConfig,
+    ) -> List[MatchPair]:
+        ...
+
+
+class GreedyMatcher:
+    """硬约束过滤 + 代价升序贪心：cost < 1 才接受，一一配对。"""
+
+    def match(
+        self,
+        left: Sequence[SamplePoint],
+        right: Sequence[SamplePoint],
+        config: StereoConfig,
+    ) -> List[MatchPair]:
+        tau_y = config.tau_y_px
+        tau_h = config.tau_h_ratio
+        candidates = []
+        for i, point_l in enumerate(left):
+            if not point_l.finite:
+                continue
+            for j, point_r in enumerate(right):
+                if not point_r.finite:
+                    continue
+                if point_l.box.class_id != point_r.box.class_id:
+                    continue
+                dy = abs(point_l.center_y - point_r.center_y)
+                if dy > tau_y:
+                    continue
+                height_max = max(point_l.box.height, point_r.box.height)
+                if height_max <= 0.0:
+                    continue
+                dh_ratio = abs(point_l.box.height - point_r.box.height) / height_max
+                if dh_ratio > tau_h:
+                    continue
+                cost = dy / tau_y + dh_ratio / tau_h
+                if cost >= 1.0:
+                    continue
+                candidates.append((cost, i, j))
+        candidates.sort(key=lambda item: (item[0], item[1], item[2]))
+        used_left = set()
+        used_right = set()
+        pairs: List[MatchPair] = []
+        for cost, i, j in candidates:
+            if i in used_left or j in used_right:
+                continue
+            pairs.append(MatchPair(left_index=i, right_index=j, cost=cost))
+            used_left.add(i)
+            used_right.add(j)
+        return pairs