save code

app.py

@@ -365,6 +365,7 @@ def _run_face_measure_data(image, variant="v1"):
     if variant == "v6":
         vd = result.vertical
         base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
+        # 接口6 是三庭：去掉顶庭相关字段（top_court_cm / ratios.top_court / landmarks.hair_top）
         data["four_courts"]["ratios"] = {
             "upper_court": round(vd["upper_court_px"] / base_px, 3),
             "middle_court": round(vd["middle_court_px"] / base_px, 3),
@@ -375,27 +376,31 @@ def _run_face_measure_data(image, variant="v1"):
             result.upper_cm + result.middle_cm + result.lower_cm, 2)
         data["landmarks"].pop("hair_top", None)
 
-    # 七眼：从左到右共 7 段宽度（cm），仅接口1（v1）含人头最左/最右端线段。
-    # eye1=左耳外段 eye2=左脸颊段 eye3=左眼 eye4=两眼间距 eye5=右眼 eye6=右脸颊段 eye7=右耳外段
-    # 端线取自耳朵分割外缘（与标注图同源）；某侧耳朵不可见 → 该侧端线缺失 → 对应 eye 置 null（保留键）。
-    if variant != "v6":
-        try:
+    # 七眼段宽度（cm）。eye1=左耳外段 eye2=左脸颊 eye3=左眼 eye4=两眼间距 eye5=右眼 eye6=右脸颊 eye7=右耳外段。
+    # eye2~eye6（5段）只用内部分点，接口1/6 共用；eye1/eye7 需耳朵分割端线，仅接口1 有。
+    try:
+        epts = result.eyes["points"]
+        lcx, rcx = epts["left_cheek"][0], epts["right_cheek"][0]
+        pc = result.px_per_cm
+        inner_xs = [lcx, epts["left_outer"][0], epts["left_inner"][0],
+                    epts["right_inner"][0], epts["right_outer"][0], rcx]
+        for i in range(5):
+            a, b = inner_xs[i], inner_xs[i + 1]
+            data["seven_eyes"][f"eye{i + 2}"] = (
+                None if (a is None or b is None) else round((b - a) / pc, 2))
+        if variant != "v6":
+            # 接口1 额外算 eye1/eye7（左/右耳外段），需耳朵分割端线
             from face_analysis.annotation import _ear_edges_from_mask
-            epts = result.eyes["points"]
-            lcx, rcx = epts["left_cheek"][0], epts["right_cheek"][0]
             head_l, head_r = _ear_edges_from_mask(
                 ear_mask, hair_mask,
                 result.vertical["hair_top"][1], result.vertical["chin_tip"][1],
                 lcx, rcx, (lcx + rcx) / 2)
-            xs = [head_l, lcx, epts["left_outer"][0], epts["left_inner"][0],
-                  epts["right_inner"][0], epts["right_outer"][0], rcx, head_r]
-            pc = result.px_per_cm
-            for i in range(7):
-                a, b = xs[i], xs[i + 1]
-                data["seven_eyes"][f"eye{i + 1}"] = (
-                    None if (a is None or b is None) else round((b - a) / pc, 2))
-        except Exception as seg_e:  # noqa: BLE001
-            logger.warning("七眼段宽度计算失败：%s", seg_e)
+            data["seven_eyes"]["eye1"] = (
+                None if (head_l is None) else round((lcx - head_l) / pc, 2))
+            data["seven_eyes"]["eye7"] = (
+                None if (head_r is None) else round((head_r - rcx) / pc, 2))
+    except Exception as seg_e:  # noqa: BLE001
+        logger.warning("七眼段宽度计算失败：%s", seg_e)
 
     return data, result, hair_mask, ear_mask
 
@@ -547,13 +552,13 @@ async def face_measure(
 输入用户正面照，返回：
 - 标注好四庭七眼数据的 **PNG 图片**（仅标注图层，不含人物）
 - 三庭（上庭/中庭/下庭）各段**厘米数值及占比**（**不含顶庭**）
-- 七眼（眼宽/脸宽/两眼间距）**厘米数值及占比**
+- 五眼段宽（eye2~eye6：左脸颊/左眼/两眼间距/右眼/右脸颊）**厘米数值**，另含眼宽/脸宽/两眼间距
 - 四个关键分界点的**原图像素坐标**（发际线/眉心/鼻翼下缘/下巴尖）
 
 基于接口1 的变体，与接口1 的差异：
 - **去顶庭**：不画头顶横线、不返回顶庭数据；`face_total_height_cm` 为三庭之和
 - **竖线范围**：纵向竖线从发际线画到下巴尖（接口1 为头顶→下巴尖）
-- **不画人头最左/最右端线**：仅七眼 6 点共 5 段标尺，不取头发轮廓端线（接口1 为 8 线 7 段）
+- **不画人头最左/最右端线**：仅七眼 6 点共 5 段标尺（eye2~eye6），不取头发轮廓端线（接口1 为 8 线 7 段 eye1~eye7）
 
 其余（箭头/虚线/字体/单位cm/七眼数据）与接口1 一致。
 
@@ -598,6 +603,7 @@ async def face_measure(
                                 "face_width_cm": 24.08,
                                 "inter_eye_distance_cm": 3.44,
                                 "ratios": {"eye_width": 0.143, "inter_eye_distance": 0.143},
+                                "eye2": 3.44, "eye3": 3.44, "eye4": 3.44, "eye5": 3.44, "eye6": 3.44,
                             },
                             "landmarks": {
                                 "hairline": {"x": 540, "y": 430},
@@ -1050,8 +1056,10 @@ async def face_features(
   - `grown_image_url`：该发型的**生发图**（生发失败时为 `null`）。
   - `hairline_type`：发际线类型 key。
   worker 返回 `*_base64`，网关落盘后改写为 `*_url`。
-- `best_hairline_center_point`：**首个选中发型**的 middle 档发际线曲线**面部中间点**坐标，
+- `best_hairline_center_point`：**首个选中发型**的 **middle 档**发际线曲线**面部中间点**坐标，
   以**原图像素**为基准（左上角为原点，x 向右，y 向下）。
+- `high_hairline_center_point`：同上，**high 档**发际线中点。
+- `low_hairline_center_point`：同上，**low 档**发际线中点。
 """,
     responses={
         200: {
@@ -1068,6 +1076,8 @@ async def face_features(
                                 {"hairline_type": "flower", "image_middle_base64": "iVBORw0KGgo...", "image_high_base64": "iVBORw0KGgo...", "image_low_base64": "iVBORw0KGgo...", "grown_image_base64": None, "order": 2},
                             ],
                             "best_hairline_center_point": {"x": 540, "y": 430},
+                            "high_hairline_center_point": {"x": 540, "y": 380},
+                            "low_hairline_center_point": {"x": 540, "y": 480},
                             "face_measure": {
                                 "face_total_height_cm": 13.76,
                                 "four_courts": {
@@ -1155,10 +1165,14 @@ async def hairline_generate(
                                        if it.get("grown_png") else None),
                 "order": it["order"],
             })
-        c = res["best_center"]
+        c = res.get("best_centers") or {}
+        def _pt(p):
+            return ({"x": p[0], "y": p[1]} if p else None)
         data = {
             "hairline_images": hairline_images,
-            "best_hairline_center_point": ({"x": c[0], "y": c[1]} if c else None),
+            "best_hairline_center_point": _pt(c.get("middle")),
+            "high_hairline_center_point": _pt(c.get("high")),
+            "low_hairline_center_point": _pt(c.get("low")),
         }
 
         # face_measure：复用接口1测量数值（四庭/七眼 eye1~eye7/landmarks/姿态），不含标注图。
@@ -1395,8 +1409,18 @@ async def hairline_grow(
     edge_erode_px: int = Form(default=3, description="贴图前遮罩内缩像素（防边缘露皮/光晕），默认 3"),
     denoising_strength: float = Form(default=0.6, description="换发型 webui 重绘强度（越大生发越激进），默认 0.6"),
     mb_levels: int = Form(default=5, description="多频段金字塔层数（2~6，越大低频色差抹得越宽），默认 5"),
+    blend_method: str = Form(default="multiband", description="接缝融合方法：multiband(多频段金字塔,默认) | seamless(泊松无缝克隆) | two_stage(泊松→多频段两段式,大色差场景) | feather(高斯羽化) | alpha_gradient(距离变换内渐变)"),
+    color_match: bool = Form(default=True, description="融合前 Reinhard 颜色迁移消除整体色差（对 multiband/feather/alpha_gradient 有效；seamless/two_stage 自带调色故跳过），默认 True"),
+    color_match_strength: float = Form(default=1.0, description="颜色迁移强度（0~1，1=全迁移，<1 只迁移部分防过度改色），默认 1.0"),
+    mb_feather_px: int = Form(default=1, description="多频段最细层掩码轻羽化像素（0=不羽化，消除发丝边缘锯齿），默认 1"),
+    transition_band_px: int = Form(default=-1, description="keep-region 过渡带边距（-1=自动按层数 2**n，>=0 用绝对像素与层数解耦），默认 -1"),
+    redraw: bool = Form(default=False, description="发际线带重绘开关：开启后额外跑一条分支——外推↔发际线带重绘，final输入，swapHair/Flux-2两路对比，结果单独展示（不替换final），默认 False"),
+    inpainting_fill: int = Form(default=1, description="change_hair服务端重绘填充：0=保留原图(治染绿) | 1=填充噪声(默认/原始) | 2=纯色 | 3=潜变量噪声。默认 1"),
+    mask_blur: int = Form(default=11, description="change_hair服务端遮罩边缘模糊像素（原始11，越大颜色越易从边缘渗透），默认 11"),
+    mask_dilate_scale: float = Form(default=1.0, description="change_hair服务端遮罩膨胀缩放（1.0=原始核尺寸，<1收缩防越界），默认 1.0"),
+    comfyui_prompt: Optional[str] = Form(default=None, description="redraw Flux-2路提示词，None用默认「补充遮罩区域的头发，加一点美颜」"),
 ):
-    """接口11：发际线生发 + 分步可视化。遮罩固定 pushed、融合固定 multiband。"""
+    """接口11：发际线生发 + 分步可视化。遮罩固定 pushed，融合默认 multiband（可选 seamless/two_stage/feather）。"""
     raw, e = await resolve_image_bytes(image_file, image_url, image_base64)
     if e is not None:
         return e
@@ -1410,8 +1434,12 @@ async def hairline_grow(
         from face_analysis.hairline_grow import generate_hairline_grow, NoFaceError, SwapError
         from uuid import uuid4 as _uuid4
         rid = _uuid4().hex[:8]
-        logger.info("[%s] 接口11 收到请求: hairline_push_cm=%s hairline_edge=%s mb_levels=%s",
-                    rid, hairline_push_cm, hairline_edge, mb_levels)
+        logger.info("[%s] 接口11 收到请求: hairline_push_cm=%s hairline_edge=%s mb_levels=%s "
+                    "blend=%s color_match=%s cm_strength=%s mb_feather_px=%s transition_band_px=%s redraw=%s "
+                    "inpainting_fill=%s mask_blur=%s mask_dilate_scale=%s",
+                    rid, hairline_push_cm, hairline_edge, mb_levels, blend_method,
+                    color_match, color_match_strength, mb_feather_px, transition_band_px, redraw,
+                    inpainting_fill, mask_blur, mask_dilate_scale)
         try:
             data = await run_in_threadpool(
                 generate_hairline_grow, image, hairline_id,
@@ -1419,7 +1447,11 @@ async def hairline_grow(
                 edge_erode_px=edge_erode_px, denoising_strength=denoising_strength,
                 gen_backend=gen_backend, hairgrow_strength=hairgrow_strength,
                 mb_levels=mb_levels, hairline_push_cm=hairline_push_cm,
-                hairline_edge=hairline_edge, rid=rid)
+                hairline_edge=hairline_edge, blend_method=blend_method,
+                color_match=color_match, color_match_strength=color_match_strength,
+                mb_feather_px=mb_feather_px, transition_band_px=transition_band_px,
+                redraw=redraw, inpainting_fill=inpainting_fill, mask_blur=mask_blur,
+                mask_dilate_scale=mask_dilate_scale, comfyui_prompt=comfyui_prompt, rid=rid)
         except NoFaceError:
             return err(1001, "无法识别人像")
         except SwapError as se: