fix(发际线): 修正不对称刘海导致的模板叠加倾斜

按 MediaPipe 左右对应额头点协调模板延伸距离，保留人脸姿态与头部轮廓钳制，统一预览白线和生发遮罩的几何。补充对齐回归测试并更新贴图顺序测试及实现说明。

验证：13 项相关测试通过；两张用户图片完成前后对比，新图男性 7 型接口与生发图均成功返回。

hairline/constants.py

@@ -20,6 +20,13 @@ MP_TOP_ANCHORS: list[int] = [
 ]
 N_ANCHORS = len(MP_TOP_ANCHORS)  # 17
 
+# Anatomical left/right pairs, in MediaPipe indices. The anchor list is
+# NOT mirror-ordered at its ends: 127 pairs with 356, 234 with 454.
+MP_TOP_ANCHOR_PAIRS = [
+    (127, 356), (234, 454), (162, 389), (21, 251),
+    (54, 284), (103, 332), (67, 297), (109, 338),
+]
+
 # Vertex ID layout in the extended array of length 468 + 2*N_ANCHORS.
 #   [0       .. 468)         : MediaPipe canonical landmarks
 #   [468     .. 468+N)       : middle row (between MP boundary and hairline)

hairline/hairline_2d.py

@@ -124,6 +124,46 @@ def build_hairline_mask(parse_map: np.ndarray) -> np.ndarray:
     return build_hair_mask(parse_map)
 
 
+def align_hairline_for_template(
+    landmarks_norm: np.ndarray,
+    hairline_norm: np.ndarray,
+    valid: np.ndarray,
+    image_shape: tuple[int, int],
+) -> np.ndarray:
+    """Keep a designed template aligned with the face rather than the fringe.
+
+    Uneven bangs can make the detected hair boundary much higher on one
+    side, shearing an otherwise balanced template. Average the upward
+    extension of each anatomical anchor pair, measured in image pixels.
+    Keep the face anchors and the perpendicular component unchanged so
+    facial roll/perspective remain visible; do not level the curve in the
+    image. Missing ray hits retain their fallback and never influence a
+    valid partner. Call silhouette clamping afterwards to bound the result.
+
+    This is for template placement only, not measurement of the real hairline.
+    """
+    h, w = image_shape
+    scale = np.array([w, h], dtype=np.float64)
+    up = face_up_vector(landmarks_norm) * scale
+    length = np.linalg.norm(up)
+    if length < 1e-9:
+        return hairline_norm.copy()
+    up /= length
+
+    anchors = landmarks_norm[C.MP_TOP_ANCHORS, :2] * scale
+    points = hairline_norm * scale
+    distances = (points - anchors) @ up
+    indices = {mp_idx: i for i, mp_idx in enumerate(C.MP_TOP_ANCHORS)}
+    for left, right in C.MP_TOP_ANCHOR_PAIRS:
+        i, j = indices[left], indices[right]
+        if not (valid[i] and valid[j]):
+            continue
+        mean_distance = (distances[i] + distances[j]) / 2.0
+        for k in (i, j):
+            points[k] += (mean_distance - distances[k]) * up
+    return (points / scale).astype(np.float32)
+
+
 def smooth_hairline(
     hairline_norm: np.ndarray,
     valid: np.ndarray,

hairline/service.py

@@ -15,7 +15,8 @@ from . import comfyui
 from .face_landmarks import FaceLandmarker
 from .face_parsing import FaceParser
 from .hairline_2d import (
-    smooth_hairline, sample_hairline_clamped,
+    smooth_hairline, sample_hairline, align_hairline_for_template,
+    clamp_hairline_to_silhouette,
 )
 from .lift_3d import lift_hairline_to_3d, build_middle_row, assemble_full
 from .render import load_ext_mesh, load_texture_rgba, render_hairline_overlay, build_overlay_layer
@@ -180,17 +181,21 @@ def extract_502(image_bgr: np.ndarray):
 def extract_context(image_bgr: np.ndarray):
     """照片(BGR) → {landmarks, parse_map, points, valid}。无人脸返回 None。
 
-    发际线几何检测固定用 `sample_hairline_clamped`（射线检测 + 头部轮廓钳制）：
+    发际线几何使用射线检测 + 人脸对应点对齐 + 头部轮廓钳制：
+    左右刘海高低不同时，协调对应锚点的延伸距离，避免把设计模板拉歪；
+    保留人脸本身的倾斜。预览白线与生发黑线/遮罩共用同一套 points。
     短发/剃光头照片（如 man_test.jpg）中间锚点检测失效时，纯射线检测的固定 fallback
     偏移会把点顶到头部轮廓外面的背景，产生"发际线贴到头部外面"的视觉 bug；钳制兜底后
-    fallback 点不会再跑出头部轮廓，正常长发照片结果与旧行为一致。
+    fallback 点不会再跑出头部轮廓。
     """
     rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)
     landmarks = get_landmarker().detect(rgb)
     if landmarks is None:
         return None
     parse_map = get_parser().parse(rgb)
-    hairline_2d, valid = sample_hairline_clamped(landmarks, parse_map)
+    hairline_2d, valid = sample_hairline(landmarks, parse_map)
+    hairline_2d = align_hairline_for_template(landmarks, hairline_2d, valid, parse_map.shape)
+    hairline_2d = clamp_hairline_to_silhouette(hairline_2d, parse_map)
     hairline_2d = smooth_hairline(hairline_2d, valid)
     hairline_3d = lift_hairline_to_3d(landmarks, hairline_2d)
     middle_3d = build_middle_row(landmarks, hairline_3d)