feat(接口3): B端生发-马克笔发际线检测+生发(替换Mock)

医生在额头用马克笔画规划发际线 → 检测该线 → 生发。检测算法源自 /home/xsl/headmark。

- hairline/marker_detect.py: 黑帽响应图(MORPH_BLACKHAT)+鬓角锚点(MediaPipe 21/251吸附)
  +skimage route_through_array 最小路径检测画线；路径平均响应阈值拒识无画线
  (headmark 调研：全局灰度阈值不可用，黑帽+Dijkstra 实测误差≤0.5px)
- hairline/mask.py: 抽出 mask_from_curve(曲线+ROI闭合)，接口2/3共用
- hairline/service.py: generate_grow_b——检测→遮罩→原图重画干净线→ComfyUI生发
- app.py: /hair/grow-b 真实实现，marked+original各三选一+校验；输出
  best_hairline_image_base64(=原图)/hair_growth_image_base64/hairline_type="custom"；
  无人脸或未检测到画线→1001；重活进线程池
- requirements: scikit-image==0.24.0 (⚠️锁0.24，0.25+强依赖numpy>=2会顶掉mediapipe的numpy<2)
- 文档: docs/接口3-B端生发-技术实现方案.md
- 测试: test_marker.py(检测/拒识/辅助) + test_api grow-b(mock ComfyUI)，42全绿

实测(5090): grow-b ~6.4s，生发图把额头发际线补到医生画线、清除划线、人物保持。

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

hairline/mask.py

@@ -83,27 +83,29 @@ def _clean_mask(mask: np.ndarray, w: int) -> np.ndarray:
     return out
 
 
+def mask_from_curve(curve_mask: np.ndarray, landmarks_mp: np.ndarray,
+                    parse_map: np.ndarray) -> np.ndarray:
+    """由发际线曲线 + ROI(额头上部 ∩ 头部) 围成"曲线以上"闭合遮罩（uint8 0..255）。
+
+    接口2(模板渲染曲线) 与 接口3(检测路径曲线) 共用。
+    """
+    h, w = curve_mask.shape[:2]
+    roi = cv2.bitwise_and(forehead_upper_region(landmarks_mp, w, h),
+                          head_silhouette(parse_map))
+    above = _above_curve_region(curve_mask, h, w)
+    return _clean_mask(cv2.bitwise_and(roi, above), w)
+
+
 def build_inpaint_mask(photo_bgr: np.ndarray, landmarks_mp: np.ndarray,
                        parse_map: np.ndarray, points502: np.ndarray,
                        black_texture_rgba: np.ndarray):
-    """返回 (marked_bgr 划线图, mask uint8 0..255 重绘区)。"""
+    """接口2：返回 (marked_bgr 划线图, mask uint8 0..255 重绘区)。"""
     h, w = photo_bgr.shape[:2]
     uv, ext_faces = load_ext_mesh()
-
-    # ④ 渲染黑线：marked = 烧进照片；curve_mask = 曲线像素
     marked = render_hairline_overlay(photo_bgr, points502, ext_faces, uv, black_texture_rgba)
     overlay = build_overlay_layer(h, w, points502, ext_faces, uv, black_texture_rgba)
     curve_mask = (overlay[:, :, 3] > 40).astype(np.uint8) * 255
-
-    # ①②③ ROI
-    upper = forehead_upper_region(landmarks_mp, w, h)
-    head = head_silhouette(parse_map)
-    roi = cv2.bitwise_and(upper, head)
-
-    # ⑤ ROI ∩ 曲线以上 → 清理
-    above = _above_curve_region(curve_mask, h, w)
-    mask = cv2.bitwise_and(roi, above)
-    mask = _clean_mask(mask, w)
+    mask = mask_from_curve(curve_mask, landmarks_mp, parse_map)
     return marked, mask