feat(worker): 接口1 四庭七眼测量真实实现（替换 Mock）

worker 侧从 Mock 替换为真实算法：
- face_analysis 包：detector(MediaPipe 478点) / pose(solvePnP 姿态) /
  calibration(虹膜直径法) / hair_segmenter+bisenet_model(方案B 头发分割) /
  measure(方案A兜底+B/A决策+七眼+换算) / annotation(numpy渐变线+中文标注)
- app.py：/api/v1/face/measure 接真实实现，返回 annotated_image_base64
  （不落盘不拼URL，落盘由网关做）；加 X-Internal-Token 鉴权、/health 就绪态、
  可配置分辨率门槛、异常兜底
- 部署：start.sh/run_worker.sh/hair-worker.service 监听 8187；worker_config 示例
- 测试 tests/：Tier1合成真值<1e-6 + Tier2缩放不变 + Tier3叠加 + 错误码集成 +
  数值回归，pytest 24 项全绿
- 文档补实测基线表 + RTX5090/torch 说明

注：worker 为 RTX 5090(sm_120)，pinned torch 2.2.2(cu121) 只到 sm_90，
BiSeNet 已自动回退 CPU（方案B 正常）；要用 GPU 需换 torch cu128(≥2.7)。

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tests/test_segmenter_logic.py

@@ -0,0 +1,33 @@
+"""方案 B 定位逻辑的真值测试（合成 mask，纯 numpy，无需 torch）。"""
+import numpy as np
+
+from face_analysis.hair_segmenter import locate_hairline_by_segmentation
+
+
+def test_locate_on_synthetic_mask():
+    """已知头发上沿 row=10、中轴线发际线 row=80，应被精确定位。"""
+    H, W = 200, 100
+    cx = W // 2
+    mask = np.zeros((H, W), dtype=bool)
+    mask[10:51, :] = True               # 顶部头发块，最高点 row=10
+    mask[10:81, cx - 1:cx + 2] = True   # 中轴线碎发延伸到 row=80
+    res = locate_hairline_by_segmentation(mask, cx, H)
+    assert res is not None
+    hairline_y, hair_top_y = res
+    assert hairline_y == 80
+    assert hair_top_y == 10
+    assert hair_top_y < hairline_y
+
+
+def test_locate_none_on_empty():
+    assert locate_hairline_by_segmentation(None, 50, 200) is None
+    assert locate_hairline_by_segmentation(np.zeros((200, 100), bool), 50, 200) is None
+
+
+def test_locate_handles_out_of_range_x():
+    """brow_center_x 越界应被夹回，不抛异常。"""
+    H, W = 100, 60
+    mask = np.zeros((H, W), dtype=bool)
+    mask[5:30, :] = True
+    assert locate_hairline_by_segmentation(mask, 9999, H) is not None
+    assert locate_hairline_by_segmentation(mask, -50, H) is not None