feat: 接口1/6 标注层字号上调一档 + 眉心改用 9 号点定位

- annotation: 自适应字号系数 0.017→0.020（下限 8→9），标注文字更大更清晰
- measure: _brow_center 只取 FaceMesh 9 号点（眉间上点），不再与 151 取中点

Co-authored-by: Cursor <cursoragent@cursor.com>

.gitignore

@@ -65,3 +65,16 @@ gateway.log
 
 # 工作流备份文件（不入 git）
 *.json.bak.*
+
+# 分辨率对比测试产物（out/ 下结果图+原图副本+日志，体积大，不入 git）
+# 仅忽略 out/ 与运行期文件；测试脚本与 HTML 报告仍入库
+image/compare_test/out/
+image/res_test/out/
+image/wave_test/out/
+image/compare_test/progress.json
+image/res_test/progress.json
+image/wave_test/progress.json
+image/compare_test/batch_test.log
+image/res_test/batch_test.log
+image/wave_test/batch_test.log
+image/compare_test/http.log

0716add-hair-api.json

@@ -29,7 +29,7 @@
   "60": {
     "class_type": "JjkText",
     "inputs": {
-      "text": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
+      "text": "填充遮罩区域的头发"
     }
   },
   "22": {

add_hair.json

@@ -410,7 +410,7 @@
   },
   "60": {
     "inputs": {
-      "text": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
+      "text": "填充遮罩区域的头发"
     },
     "class_type": "JjkText",
     "_meta": {

app.py

@@ -401,21 +401,36 @@ def _run_face_measure_data(image, variant="v1"):
         logger.warning("头发/耳朵分割失败，回退方案A：%s", seg_e)
 
     result = measure_face(landmarks, hair_mask, w, h, head_pose=head_pose)
+    discarded = result.hairline_discarded
     data = result.to_response()
+    vd = result.vertical
     if variant == "v6":
-        vd = result.vertical
+        if discarded:
-        base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
+            # 发际线弃用：接口6 的上庭也依赖发际线，一并置 null；只保留中/下庭。
-        # 接口6 是三庭：去掉顶庭相关字段（top_court_cm / ratios.top_court / landmarks.hair_top）
+            base_px = vd["middle_court_px"] + vd["lower_court_px"]
-        data["four_courts"]["ratios"] = {
+            data["four_courts"]["upper_court_cm"] = None
-            "upper_court": round(vd["upper_court_px"] / base_px, 3),
+            data["four_courts"]["ratios"] = {
-            "middle_court": round(vd["middle_court_px"] / base_px, 3),
+                "upper_court": None,
-            "lower_court": round(vd["lower_court_px"] / base_px, 3),
+                "middle_court": round(vd["middle_court_px"] / base_px, 3),
-        }
+                "lower_court": round(vd["lower_court_px"] / base_px, 3),
-        data["four_courts"].pop("top_court_cm", None)
+            }
-        data["face_total_height_cm"] = round(
+            data["four_courts"].pop("top_court_cm", None)
-            result.upper_cm + result.middle_cm + result.lower_cm, 2)
+            data["face_total_height_cm"] = round(
-        # 注：landmarks.hair_top 保留返回（供前端/下游定位头顶），但顶庭数值、
+                result.middle_cm + result.lower_cm, 2)
-        # 占比、标注图仍按三庭处理，显示效果不变。
+            data["landmarks"]["hairline"] = None
+        else:
+            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),
+                "lower_court": round(vd["lower_court_px"] / base_px, 3),
+            }
+            data["four_courts"].pop("top_court_cm", None)
+            data["face_total_height_cm"] = round(
+                result.upper_cm + result.middle_cm + result.lower_cm, 2)
+            # 注：landmarks.hair_top 保留返回（供前端/下游定位头顶），但顶庭数值、
+            # 占比、标注图仍按三庭处理，显示效果不变。
 
     # 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。
@@ -430,11 +445,14 @@ def _run_face_measure_data(image, variant="v1"):
             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
+            # 接口1 额外算 eye1/eye7（左/右耳外段），需耳朵分割端线。
+            # 竖向范围：发际线弃用时用眉心做上界（hair_top 不可靠），否则用头顶。
             from face_analysis.annotation import _ear_edges_from_mask
+            top_y = (vd["brow_center"][1] if discarded
+                     else vd["hair_top"][1])
             head_l, head_r = _ear_edges_from_mask(
                 ear_mask, hair_mask,
-                result.vertical["hair_top"][1], result.vertical["chin_tip"][1],
+                top_y, vd["chin_tip"][1],
                 lcx, rcx, (lcx + rcx) / 2)
             data["seven_eyes"]["eye1"] = (
                 None if (head_l is None) else round((lcx - head_l) / pc, 2))
@@ -757,7 +775,7 @@ async def hair_grow(
     hair_style: Optional[str] = Form(default=None, description="发型序号逗号分隔（必填），如 1,2,3。female:1-5 male:1-4"),
     beauty_enabled: bool = Form(default=False, description="是否开启美颜（本期不生效）"),
     use_mask: bool = Form(default=True, description="是否启用 inpaint 遮罩（测试对比用）。false 时用干净原图生成（空遮罩，不烧模板线）"),
-    prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
+    prompt: str = Form(default="填充遮罩区域的头发", description="ComfyUI 提示词，会替换工作流节点60的文本"),
     flux_model: Optional[str] = Form(default=None, description="Flux 模型文件名（切换模型用）。None=工作流默认；如 flux-2-klein-9b-Q5_K_M.gguf / flux-2-klein-9b-Q4_K_M.gguf / flux2.0/flux-2-klein-9b-fp8.safetensors"),
     redraw_max_side: Optional[int] = Form(default=None, description="重绘压图长边像素。None=默认896；0=不缩图（原图直送）；其他如 768/640/1024"),
 ):
@@ -872,7 +890,7 @@ async def hair_grow_b(
     marked_image_url: Optional[str] = Form(default=None, description="划线图片 URL"),
     marked_image_base64: Optional[str] = Form(default=None, description="划线图片 base64"),
     use_mask: bool = Form(default=True, description="是否画发际线（测试对比用）。false 时跳过划线检测、直接送划线图"),
-    prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
+    prompt: str = Form(default="填充遮罩区域的头发", description="ComfyUI 提示词，会替换工作流节点60的文本"),
 ):
     # 划线图三选一取图（只需这一张）
     marked_raw, e = await resolve_image_bytes(marked_image_file, marked_image_url, marked_image_base64)
@@ -1001,10 +1019,13 @@ async def face_features(
 - 必填 `gender`（`male`/`female`），决定发型集合（female 5 / male 4）。
 - 必填 `hair_style`（发型序号，逗号分隔如 `1,2,3`），决定返回哪些发际线类型。缺失/越界/非法返回 `1007`。
   `female`：1=ellipse,2=flower,3=heart,4=straight,5=wave；`male`：1=ellipse,2=inverse_arc,3=m,4=straight。
-- 可选 `use_mask` / `prompt`：同接口2 的生发控制参数。
+- 可选 `use_mask` / `prompt`：同接口2 的生发控制参数（仅 male 路径生效）。
-  注：生发黑模板固定取 `hairline_texture_black/`（middle 档），即三档叠图分别用各自贴图、但生发目标固定 middle。
+- 可选 `generate_grow_image`（默认 `true`）：是否生成生发效果图（最耗时）。
-- 可选 `generate_grow_image`（默认 `true`）：是否生成生发效果图（ComfyUI 生发，全流程最耗时）。
   `false` 时跳过生发，各发型 `grown_image_*` 恒为 `null`，仅返回三档发际线叠图与中心点，大幅降低耗时。
+- **生发机制（同接口2，按性别分流）**：
+  `female` 走「换发型 + Flux-2 整帧重绘」（依赖 change_hair:8801 与 ComfyUI:8188）；
+  `male` 走 ComfyUI `add_hair` 原生 inpaint。
+- 可选 `flux_model` / `redraw_max_side`：同接口2（仅 female 路径生效）。
 
 **返回说明**：
 
@@ -1081,9 +1102,11 @@ async def hairline_generate(
     image_base64: Optional[str] = Form(default=None, description="图片 base64（需带 data:image/...;base64, 前缀）"),
     gender: Optional[str] = Form(default=None, description="性别 male/female（必填）"),
     hair_style: Optional[str] = Form(default=None, description="发型序号逗号分隔（必填，如 1,2,3）。female:1-5 male:1-4"),
-    use_mask: bool = Form(default=True, description="生发是否启用 inpaint 遮罩（同接口2，测试对比用）"),
+    use_mask: bool = Form(default=True, description="生发是否启用 inpaint 遮罩（同接口2，仅 male 路径生效）"),
-    prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", description="ComfyUI 提示词（同接口2），会替换工作流节点60的文本"),
+    prompt: str = Form(default="填充遮罩区域的头发", description="ComfyUI 提示词（同接口2，仅 male 路径生效），会替换工作流节点60的文本"),
-    generate_grow_image: bool = Form(default=True, description="是否生成生发效果图（ComfyUI 生发，最耗时）。默认 true 出图；false 时跳过生发，各发型 grown_image 恒为 null，仅返回三档发际线叠图与中心点"),
+    generate_grow_image: bool = Form(default=True, description="是否生成生发效果图（最耗时）。默认 true 出图；false 时跳过生发，各发型 grown_image 恒为 null，仅返回三档发际线叠图与中心点"),
+    flux_model: Optional[str] = Form(default=None, description="Flux 模型文件名（同接口2，切换模型用）。None=工作流默认"),
+    redraw_max_side: Optional[int] = Form(default=None, description="重绘压图长边像素（同接口2，仅 female 路径生效）。None=默认896；0=不缩图（原图直送）；其他如 768/640/1024"),
 ):
     if gender not in ("male", "female"):
         return err(1004, "gender 必填且只能为 male / female")
@@ -1108,7 +1131,9 @@ async def hairline_generate(
 
         res = await run_in_threadpool(
             generate_hairline_pngs, image, gender, hair_styles, use_mask, prompt,
-            generate_grow_image=generate_grow_image)
+            generate_grow_image=generate_grow_image,
+            redraw_max_side=redraw_max_side, unet_name=flux_model,
+            v2_defaults=_V2_FINAL_DEFAULTS)
         if res is None:
             return err(1001, "无法识别人像")
 
@@ -1476,7 +1501,7 @@ async def hairline_grow_v2(
     inpainting_fill: int = Form(default=1, description="change_hair服务端重绘填充：0=保留原图 | 1=噪声 | 2=纯色 | 3=潜变量。默认 1"),
     mask_blur: int = Form(default=11, description="change_hair服务端遮罩边缘模糊像素，默认 11"),
     mask_dilate_scale: float = Form(default=1.0, description="change_hair服务端遮罩膨胀缩放，默认 1.0"),
-    comfyui_prompt: Optional[str] = Form(default=None, description="Flux-2 重绘提示词，None 用默认「填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜」"),
+    comfyui_prompt: Optional[str] = Form(default=None, description="Flux-2 重绘提示词，None 用默认「填充遮罩区域的头发」"),
     beauty_alpha: float = Form(default=0.6, description="redraw_band 版 band 外的全脸美颜融入强度（0=band外无美颜纯用final，1≈整帧版），默认 0.6"),
     band_lo_mult: float = Form(default=0.5, description="重绘带外推倍率下限（相对 hairline_push_cm，内轮廓=0×、原外推线=1.0×），默认 0.5"),
     band_hi_mult: float = Form(default=1.5, description="重绘带外推倍率上限（相对 hairline_push_cm），默认 1.5"),
@@ -1642,7 +1667,7 @@ async def hairline_grow_v2_final_v2(
 async def api_redraw(
     image_file: UploadFile = File(..., description="人物图片（JPG/PNG）"),
     mask_file: UploadFile = File(..., description="遮罩图片（PNG，支持红/白/alpha 格式）"),
-    prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜",
+    prompt: str = Form(default="填充遮罩区域的头发",
                        description="ComfyUI 提示词"),
 ):
     image_bytes = await image_file.read()

benchmark_hairstyle.py

@@ -55,7 +55,7 @@ def gpu_used():
 
 def call(img_path, hair_num, model_file, res_val):
     fd = {"gender": "female", "hair_style": str(hair_num), "use_mask": "true",
-          "prompt": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"}
+          "prompt": "填充遮罩区域的头发"}
     if model_file:
         fd["flux_model"] = model_file
     if res_val != "":

benchmark_matrix.py

@@ -54,7 +54,7 @@ def call(img_path, model_file, res_val):
         "gender": "female",
         "hair_style": "2",  # 花瓣形
         "use_mask": "true",
-        "prompt": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜",
+        "prompt": "填充遮罩区域的头发",
     }
     if model_file:
         fd["flux_model"] = model_file

face_analysis/annotation.py

@@ -202,7 +202,7 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
 
     # --- 自适应尺寸：字号/线宽/虚线/箭头按短边缩放 ---
     s = min(w, h)
-    font_size = max(8, round(s * 0.017))      # 字体更小
+    font_size = max(9, round(s * 0.020))      # 字号上调一档
     line_w = max(1, round(s * 0.0022))
     dash_len = max(4, round(s * 0.008))
     gap_len = max(2, round(dash_len * 0.7))   # 虚线更稠密（间隙<划线）
@@ -212,7 +212,11 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
 
     buf = np.zeros((h, w, 4), dtype=np.uint8)
 
-    if variant == "v6":
+    # 发际线弃用（hairline_discarded）：保留头顶横线，去掉发际线横线，
+    # 也不标顶/上庭（缺发际线作边界，算不出）。横线 = 头顶/眉心/鼻翼下缘/下巴尖。
+    if getattr(measure_result, "hairline_discarded", False):
+        order = ["hair_top", "brow_center", "nose_bottom", "chin_tip"]
+    elif variant == "v6":
         order = ["hairline", "brow_center", "nose_bottom", "chin_tip"]
     else:
         order = ["hair_top", "hairline", "brow_center", "nose_bottom", "chin_tip"]
@@ -239,7 +243,7 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
     face_cx = (fx0 + fx1) / 2
     over = max(6, round(s * 0.030))           # 线超出包围盒的长度（参考图风格）
     face_half = (fx1 - fx0) / 2 + over        # 横线超出最外侧竖线一点
-    # v6 竖线纵向范围 = 发际线→下巴尖（不超出）；v1 = 头顶→下巴尖并两端超出一点
+    # 竖线纵向范围：v6 = 发际线→下巴尖（不超出）；v1（含发际线弃用）= 头顶→下巴尖并两端超出一点
     v_top = fy0 if variant == "v6" else fy0 - over
     v_bot = fy1 if variant == "v6" else fy1 + over
 
@@ -265,19 +269,28 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
         draw.text((x, ys[i]), text, fill=LINE_COLOR, font=font, anchor="lm")
 
     # --- 3b. 左侧四庭：名 + 数值两行（无 cm）+ 竖向虚线双箭头 ---
-    if variant == "v6":
+    # court_start：庭段在 order 里的起始索引。发际线弃用时 order 首位是头顶（无下界发际线，
+    # 顶/上庭不标），中庭从眉心开始 → 跳过 order[0]。
+    if getattr(measure_result, "hairline_discarded", False):
+        court_cm = [measure_result.middle_cm, measure_result.lower_cm]
+        court_name = ["中庭", "下庭"]
+        n_court = 2
+        court_start = 1
+    elif variant == "v6":
         court_cm = [measure_result.upper_cm, measure_result.middle_cm, measure_result.lower_cm]
         court_name = ["上庭", "中庭", "下庭"]
         n_court = 3
+        court_start = 0
     else:
         court_cm = [measure_result.top_cm, measure_result.upper_cm,
                     measure_result.middle_cm, measure_result.lower_cm]
         court_name = ["顶庭", "上庭", "中庭", "下庭"]
         n_court = 4
+        court_start = 0
     arrow_x = max(arrow_size + 1, fx0 - pad)   # 竖箭头所在 x（脸左侧，贴近最左竖线）
     court_total = sum(court_cm) or 1.0          # 各庭占比分母 = 四庭（v6 三庭）之和
     for i in range(n_court):
-        y_a, y_b = ys[i], ys[i + 1]
+        y_a, y_b = ys[court_start + i], ys[court_start + i + 1]
         # 竖向虚线双箭头，覆盖该庭高度（略收一点避免压到横线）
         inset = min(arrow_size, (y_b - y_a) * 0.12)
         draw_dashed_line_with_arrows(

face_analysis/hairline_grow.py

@@ -1107,7 +1107,7 @@ def generate_hairline_redraw(image_bgr, hairline_id, is_hr=False, seg_model="seg
         "hairline_id": hairline_id,
         "blend_method": blend_method,
         "hairline_push_cm": round(float(hairline_push_cm), 2),
-        "comfyui_prompt": comfyui_prompt or "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜",
+        "comfyui_prompt": comfyui_prompt or "填充遮罩区域的头发",
         "beauty_alpha": beauty_alpha,
         "px_per_cm": round(float(px_per_cm), 4),
         "mask_pixels": mask_viz["mask_pixels"],

face_analysis/measure.py

@@ -12,7 +12,7 @@ from face_analysis.calibration import (
     estimate_scale_factor, normalized_to_pixel, pixel_distance, _lm_list,
 )
 from face_analysis.face_mesh_landmarks import (
-    GLABELLA_9, GLABELLA_151, NOSE_BOTTOM, CHIN_TIP,
+    GLABELLA_9, NOSE_BOTTOM, CHIN_TIP,
     LEFT_EYE_OUTER, LEFT_EYE_INNER, RIGHT_EYE_INNER, RIGHT_EYE_OUTER,
     LEFT_CHEEK, RIGHT_CHEEK, LEFT_POSITION, RIGHT_POSITION,
 )
@@ -24,10 +24,8 @@ _TOP_RATIO = 0.22 / 0.28      # 顶庭 ÷ 中庭（≈ 0.786）
 
 
 def _brow_center(lm, w, h):
-    """眉心 = 索引 9 / 151 中点。"""
+    """眉心 = 索引 9（眉间上点）。"""
-    g9 = normalized_to_pixel(lm[GLABELLA_9], w, h)
+    return normalized_to_pixel(lm[GLABELLA_9], w, h)
-    g151 = normalized_to_pixel(lm[GLABELLA_151], w, h)
-    return (g9[0] + g151[0]) / 2, (g9[1] + g151[1]) / 2
 
 
 def estimate_vertical_landmarks(landmarks, image_width, image_height):
@@ -144,9 +142,22 @@ def measure_seven_eyes(landmarks, image_width, image_height):
     }
 
 
+def pt_or_none(vertical, name):
+    """vertical dict 的点 → {"x","y"}，值为 None 时返回 None。"""
+    v = vertical.get(name)
+    if v is None:
+        return None
+    return {"x": int(round(v[0])), "y": int(round(v[1]))}
+
+
 class MeasureResult:
     """测量结果，提供 to_response() 输出与接口文档同构的 data 字段。"""
 
+    # 发际线弃用阈值：发际线离头顶（顶庭）< 此值时判定分割不可靠，弃用发际线。
+    # hairline 与 hair_top 几乎重合（如稀疏头发中轴漏检只剩一小撮），说明发际线
+    # 定位无意义 → 顶/上庭置 null、标注图不画头顶/发际线。
+    HAIRLINE_DISCARD_TOP_CM = 0.7
+
     def __init__(self, vertical, eyes, px_per_cm, hairline_source, head_pose,
                  landmarks=None, image_width=None, image_height=None):
         self.vertical = vertical
@@ -164,7 +175,14 @@ class MeasureResult:
         self.upper_cm = vertical["upper_court_px"] / px_per_cm
         self.middle_cm = vertical["middle_court_px"] / px_per_cm
         self.lower_cm = vertical["lower_court_px"] / px_per_cm
-        self.face_total_cm = self.top_cm + self.upper_cm + self.middle_cm + self.lower_cm
+        # 发际线弃用判定：顶庭（头顶→发际线）过小视为发际线贴近头顶、不可靠。
+        # 弃用时 hairline_source 改为 "discarded"，face_total 只算中庭+下庭。
+        self.hairline_discarded = self.top_cm < self.HAIRLINE_DISCARD_TOP_CM
+        if self.hairline_discarded:
+            self.hairline_source = "discarded"
+            self.face_total_cm = self.middle_cm + self.lower_cm
+        else:
+            self.face_total_cm = self.top_cm + self.upper_cm + self.middle_cm + self.lower_cm
 
         # 七眼厘米
         self.eye_width_cm = eyes["eye_width_px"] / px_per_cm
@@ -172,46 +190,77 @@ class MeasureResult:
         self.inter_eye_cm = eyes["inter_eye_distance_px"] / px_per_cm
 
     def to_response(self):
-        total_px = (self.vertical["top_court_px"] + self.vertical["upper_court_px"]
+        # 发际线弃用：顶/上庭相关字段置 null（保留键），ratio 分母只算中下庭；
-                    + self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
+        # landmarks.hair_top/hairline 置 null。否则按四庭正常输出。
-        fw_px = self.eyes["face_width_px"]
+        if self.hairline_discarded:
-
+            base_px = (self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
-        def pt(name):
+            data = {
-            x, y = self.vertical[name]
+                "face_total_height_cm": round(self.face_total_cm, 2),
-            return {"x": int(round(x)), "y": int(round(y))}
+                "four_courts": {
-
+                    "top_court_cm": None,
-        data = {
+                    "upper_court_cm": None,
-            "face_total_height_cm": round(self.face_total_cm, 2),
+                    "middle_court_cm": round(self.middle_cm, 2),
-            "four_courts": {
+                    "lower_court_cm": round(self.lower_cm, 2),
-                "top_court_cm": round(self.top_cm, 2),
+                    "ratios": {
-                "upper_court_cm": round(self.upper_cm, 2),
+                        "top_court": None,
-                "middle_court_cm": round(self.middle_cm, 2),
+                        "upper_court": None,
-                "lower_court_cm": round(self.lower_cm, 2),
+                        "middle_court": round(self.vertical["middle_court_px"] / base_px, 3),
-                "ratios": {
+                        "lower_court": round(self.vertical["lower_court_px"] / base_px, 3),
-                    "top_court": round(self.vertical["top_court_px"] / total_px, 3),
+                    },
-                    "upper_court": round(self.vertical["upper_court_px"] / total_px, 3),
-                    "middle_court": round(self.vertical["middle_court_px"] / total_px, 3),
-                    "lower_court": round(self.vertical["lower_court_px"] / total_px, 3),
                 },
-            },
+                "seven_eyes": {
-            "seven_eyes": {
+                    "eye_width_cm": round(self.eye_width_cm, 2),
-                "eye_width_cm": round(self.eye_width_cm, 2),
+                    "face_width_cm": round(self.face_width_cm, 2),
-                "face_width_cm": round(self.face_width_cm, 2),
+                    "inter_eye_distance_cm": round(self.inter_eye_cm, 2),
-                "inter_eye_distance_cm": round(self.inter_eye_cm, 2),
+                    "ratios": {
-                "ratios": {
+                        "eye_width": round(self.eyes["eye_width_px"] / self.eyes["face_width_px"], 3),
-                    "eye_width": round(self.eyes["eye_width_px"] / fw_px, 3),
+                        "inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / self.eyes["face_width_px"], 3),
-                    "inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / fw_px, 3),
+                    },
                 },
-            },
+                "landmarks": {
-            "landmarks": {
+                    "hair_top": None,
-                "hair_top": pt("hair_top"),
+                    "hairline": None,
-                "hairline": pt("hairline"),
+                    "brow_center": pt_or_none(self.vertical, "brow_center"),
-                "brow_center": pt("brow_center"),
+                    "nose_bottom": pt_or_none(self.vertical, "nose_bottom"),
-                "nose_bottom": pt("nose_bottom"),
+                    "chin_tip": pt_or_none(self.vertical, "chin_tip"),
-                "chin_tip": pt("chin_tip"),
+                },
-            },
+                "hairline_source": self.hairline_source,
-            "hairline_source": self.hairline_source,
+            }
-        }
+        else:
+            total_px = (self.vertical["top_court_px"] + self.vertical["upper_court_px"]
+                        + self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
+            data = {
+                "face_total_height_cm": round(self.face_total_cm, 2),
+                "four_courts": {
+                    "top_court_cm": round(self.top_cm, 2),
+                    "upper_court_cm": round(self.upper_cm, 2),
+                    "middle_court_cm": round(self.middle_cm, 2),
+                    "lower_court_cm": round(self.lower_cm, 2),
+                    "ratios": {
+                        "top_court": round(self.vertical["top_court_px"] / total_px, 3),
+                        "upper_court": round(self.vertical["upper_court_px"] / total_px, 3),
+                        "middle_court": round(self.vertical["middle_court_px"] / total_px, 3),
+                        "lower_court": round(self.vertical["lower_court_px"] / total_px, 3),
+                    },
+                },
+                "seven_eyes": {
+                    "eye_width_cm": round(self.eye_width_cm, 2),
+                    "face_width_cm": round(self.face_width_cm, 2),
+                    "inter_eye_distance_cm": round(self.inter_eye_cm, 2),
+                    "ratios": {
+                        "eye_width": round(self.eyes["eye_width_px"] / self.eyes["face_width_px"], 3),
+                        "inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / self.eyes["face_width_px"], 3),
+                    },
+                },
+                "landmarks": {
+                    "hair_top": pt_or_none(self.vertical, "hair_top"),
+                    "hairline": pt_or_none(self.vertical, "hairline"),
+                    "brow_center": pt_or_none(self.vertical, "brow_center"),
+                    "nose_bottom": pt_or_none(self.vertical, "nose_bottom"),
+                    "chin_tip": pt_or_none(self.vertical, "chin_tip"),
+                },
+                "hairline_source": self.hairline_source,
+            }
         # left/right_position：mediapipe 21/251 号定位点（原图像素，与 landmarks 同坐标系）。
         # landmarks 缺省（如测试直构 MeasureResult）时不输出，保持向后兼容。
         if self.landmarks is not None and self.w and self.h:

hair_repaint.json

@@ -410,7 +410,7 @@
   },
   "60": {
     "inputs": {
-      "text": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
+      "text": "填充遮罩区域的头发"
     },
     "class_type": "JjkText",
     "_meta": {

hairline/redraw.py

@@ -16,7 +16,7 @@ from . import comfyui
 
 logger = logging.getLogger("hair.worker")
 
-_DEFAULT_PROMPT = "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
+_DEFAULT_PROMPT = "填充遮罩区域的头发"
 _REPO = os.path.dirname(os.path.dirname(__file__))
 _REPAINT_WORKFLOW = os.path.join(_REPO, "0716add-hair-api.json")
 
@@ -62,7 +62,7 @@ def run_redraw(image_bytes: bytes, mask_bytes: bytes,
     Args:
         image_bytes: 人物图片字节（JPG/PNG）
         mask_bytes: 遮罩图片字节（支持红/白/alpha 遮罩格式）
-        prompt: 提示词，None 用默认 "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
+        prompt: 提示词，None 用默认 "填充遮罩区域的头发"
         timeout: ComfyUI 超时秒数
         front: True 时任务插到 ComfyUI 队列最前（接口2 时延敏感路径用）
         unet_name: 非 None 时切换 Flux 模型（如 flux-2-klein-9b-Q5_K_M.gguf），None 用工作流默认

hairline/service.py

@@ -46,13 +46,14 @@ _BLACK_TEXTURE_DIR = os.path.join(_REPO, "hairline_texture_black")
 # 关键：ComfyUI 单卡显存装不下 Flux(7.7G)+qwen CLIP(3.9G) 同驻，靠缓存 CLIP 文本条件避免重载。
 # prompt 不同会使缓存失效 → 重载 CLIP 并挤出 Flux（每次 +4s）。三接口用同一字符串即可全程命中。
 # 与 app.py 接口2/接口3 的默认 prompt 保持一致；可用 REDRAW_PROMPT 覆盖。
-_REDRAW_PROMPT = os.getenv("REDRAW_PROMPT", "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
+_REDRAW_PROMPT = os.getenv("REDRAW_PROMPT", "填充遮罩区域的头发")
 
 # 接口2 女重绘整条管线（swapHair + ComfyUI）送模型前限边。真实照片常达 1257x1495：
-# 全分辨率 ComfyUI 重绘要 13~21s 且激活显存把模型挤出。女性路径含 swapHair(SD WebUI ~5.3s
+# 全分辨率 ComfyUI 重绘要 13~21s 且激活显存把模型挤出。
-# 固定地板) + ComfyUI 两段串行。1024 档画质更好但部分大图会踩 12s 线，
+# 策略：输入图长边 > REDRAW_MAX_SIDE 才等比缩到该长边；≤ 时原图分辨率直送（不放大）。
-# 默认压到 896 兜底（ComfyUI ~4s，女性总耗时 9~11s）；追画质可设 REDRAW_MAX_SIDE=1024。
+# 默认 1024：大于 1024 的图压到 1024（画质/速度均衡），≤1024 的小图保持原分辨率重绘。
-_REDRAW_MAX_SIDE = int(os.getenv("REDRAW_MAX_SIDE", "896"))
+# 可用 REDRAW_MAX_SIDE 覆盖；0=永不缩图（原图直送）。
+_REDRAW_MAX_SIDE = int(os.getenv("REDRAW_MAX_SIDE", "1024"))
 
 def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0,
                        max_side=None, unet_name=None):
@@ -410,14 +411,22 @@ def _grow_from_texture(image_bgr: np.ndarray, ctx: dict, white_path: str | None,
 def generate_hairline_pngs(image_bgr: np.ndarray, gender: str,
                            hair_styles: list[int], use_mask: bool = True,
                            prompt: str | None = None,
-                           generate_grow_image: bool = True):
+                           generate_grow_image: bool = True,
+                           redraw_max_side: int | None = None,
+                           unet_name: str | None = None,
+                           v2_defaults: dict | None = None):
     """接口5：对选中发型返回 middle/high/low 三档发际线透明叠图 + 生发图(同接口2)。
 
     入参同接口2：先选 gender，再多选 hair_styles（必填，1-indexed 按贴图排序）。
     每个选中发型返回三档叠图（middle/high/low，RGBA 透明层只含发际线曲线）与一张生发图；
-    三档贴图同名，生发黑模板固定取自 hairline_texture_black/（middle），故生发目标固定 middle 档。
+
-    use_mask/prompt：同接口2 的生发参数。
+    生发机制（同接口2，按性别分流）：
-    generate_grow_image（默认 True）：是否生成生发图（ComfyUI，最耗时）。False 时跳过生发，
+      - female：generate_grow_results_swap（swapHair + Flux-2 整帧重绘）
+      - male：generate_grow_results（ComfyUI add_hair inpaint）
+    redraw_max_side / unet_name / v2_defaults：female 路径参数，同接口2。
+      male 路径仅用 unet_name；redraw_max_side/v2_defaults 对 male 无意义（忽略）。
+    use_mask/prompt：仅 male 路径生效（同接口2 male）。
+    generate_grow_image（默认 True）：是否生成生发图（最耗时）。False 时跳过生发，
         各发型 grown_png 恒为 None，可大幅降低耗时（仅留三档发际线叠图与中心点）。
     Returns: {"images":[{hairline_type,order,overlays:{middle,high,low}((H,W,4) RGBA 透明层),grown_png}],
               "best_centers":{"middle":(x,y),"high":(x,y),"low":(x,y)}}；无人脸 None。
@@ -439,11 +448,27 @@ def generate_hairline_pngs(image_bgr: np.ndarray, gender: str,
     # 三档贴图表（同性别、同 key 顺序，因三个文件夹同名）
     tex_by_level = {lv: get_texture_map(lv)[gender] for lv in _TEXTURE_DIRS}
 
-    # use_mask=False：干净原图+空遮罩与贴图无关，只跑一次 ComfyUI，选中项复用
+    # 生发图（同接口2，按性别分流）：一次性算出所有选中发型的生发图，按 order 对应回叠图。
-    # generate_grow_image=False：完全跳过生发（最耗时），grown_png 恒为 None
+    # female→generate_grow_results_swap（swapHair+Flux-2 整帧重绘）；
-    shared_grown = None
+    # male→generate_grow_results（ComfyUI add_hair inpaint）。
-    if generate_grow_image and not use_mask:
+    # generate_grow_image=False 时跳过，grown_by_order 为空 dict（各发型 grown_png 恒 None）。
-        shared_grown = _grow_from_texture(image_bgr, ctx, None, use_mask=False, prompt=prompt)
+    grown_by_order: dict[int, bytes | None] = {}
+    if generate_grow_image:
+        try:
+            if gender == "female":
+                items = generate_grow_results_swap(
+                    image_bgr, hair_styles, v2_defaults or {},
+                    redraw_max_side=redraw_max_side, unet_name=unet_name)
+            else:
+                items = generate_grow_results(
+                    image_bgr, gender, use_mask, prompt, hair_styles,
+                    unet_name=unet_name)
+            if items is None:
+                return None  # 无人脸（同接口2 的 None 语义）
+            for it in items:
+                grown_by_order[it["order"]] = it.get("grown_png")
+        except Exception as e:  # noqa: BLE001  整批生发失败不拖垮叠图主结果
+            logger.warning("接口5 生发批量失败（gender=%s）：%s", gender, e)
 
     def _center_of(overlay):
         """从某档发际线透明叠图取面部中轴处的发际线中点 (x,y)，无像素返回 None。"""
@@ -456,18 +481,13 @@ def generate_hairline_pngs(image_bgr: np.ndarray, gender: str,
 
     images, best_centers = [], None
     for s in hair_styles:  # s = 1-indexed 发型序号
-        key, mid_path = tex_by_level["middle"][s - 1]
+        key, _mid_path = tex_by_level["middle"][s - 1]
         overlays = {}
         for lv in _TEXTURE_DIRS:
             white = load_texture_rgba(tex_by_level[lv][s - 1][1])
             overlays[lv] = build_overlay_layer(h, w, ctx["points"], ext_faces, uv, white)
-        # 生发：固定 middle 黑模板（generate_grow_image=False 时跳过，恒 None）
+        # 生发图：从按性别算好的结果里按 order 取（generate_grow_image=False 时缺省 None）
-        if not generate_grow_image:
+        grown_png = grown_by_order.get(s)
-            grown_png = None
-        elif not use_mask:
-            grown_png = shared_grown
-        else:
-            grown_png = _grow_from_texture(image_bgr, ctx, mid_path, use_mask=True, prompt=prompt)
         images.append({"hairline_type": key, "order": s,
                        "overlays": overlays, "grown_png": grown_png})
         # best_centers：首个选中发型三档（middle/high/low）发际线中点

image/compare_test/archive_20260725/batch_test.log

@@ -0,0 +1,75 @@
+=== 接口2 female 批量对比测试 ===
+矩阵: 4图 × 5发型 × 2档 = 40 次
+已跳过 0 个已完成项
+
+[1/40] ▶ girl2_ellipse_default896 (side=None)... ✅ 10.8s  出图 1082x1081 (204589B)
+[2/40] ▶ girl2_ellipse_origin0 (side=0)... ✅ 13.3s  出图 1088x1088 (232252B)
+[3/40] ▶ girl2_flower_default896 (side=None)... ✅ 11.0s  出图 1082x1081 (210875B)
+[4/40] ▶ girl2_flower_origin0 (side=0)... ✅ 12.5s  出图 1088x1088 (236073B)
+[5/40] ▶ girl2_heart_default896 (side=None)... ✅ 11.9s  出图 1082x1081 (198911B)
+[6/40] ▶ girl2_heart_origin0 (side=0)... ✅ 12.2s  出图 1088x1088 (249893B)
+[7/40] ▶ girl2_straight_default896 (side=None)... ✅ 12.1s  出图 1082x1081 (211803B)
+[8/40] ▶ girl2_straight_origin0 (side=0)... ✅ 12.3s  出图 1088x1088 (235377B)
+[9/40] ▶ girl2_wave_default896 (side=None)... ✅ 12.7s  出图 1082x1081 (207736B)
+[10/40] ▶ girl2_wave_origin0 (side=0)... ✅ 11.9s  出图 1088x1088 (238081B)
+[11/40] ▶ girl5_ellipse_default896 (side=None)... ✅ 9.6s  出图 768x752 (105867B)
+[12/40] ▶ girl5_ellipse_origin0 (side=0)... ✅ 7.3s  出图 768x752 (112963B)
+[13/40] ▶ girl5_flower_default896 (side=None)... ✅ 8.0s  出图 768x752 (114378B)
+[14/40] ▶ girl5_flower_origin0 (side=0)... ✅ 7.2s  出图 768x752 (108495B)
+[15/40] ▶ girl5_heart_default896 (side=None)... ✅ 8.1s  出图 768x752 (113874B)
+[16/40] ▶ girl5_heart_origin0 (side=0)... ✅ 7.6s  出图 768x752 (103160B)
+[17/40] ▶ girl5_straight_default896 (side=None)... ✅ 8.4s  出图 768x752 (104492B)
+[18/40] ▶ girl5_straight_origin0 (side=0)... ✅ 7.2s  出图 768x752 (100941B)
+[19/40] ▶ girl5_wave_default896 (side=None)... ✅ 8.4s  出图 768x752 (120122B)
+[20/40] ▶ girl5_wave_origin0 (side=0)... ✅ 7.7s  出图 768x752 (113282B)
+[21/40] ▶ qwer_ellipse_default896 (side=None)... ✅ 10.2s  出图 1288x1678 (261812B)
+[22/40] ▶ qwer_ellipse_origin0 (side=0)... ✅ 30.0s  出图 1280x1680 (331013B)
+[23/40] ▶ qwer_flower_default896 (side=None)... ✅ 10.2s  出图 1288x1678 (312834B)
+[24/40] ▶ qwer_flower_origin0 (side=0)... ✅ 25.0s  出图 1280x1680 (328605B)
+[25/40] ▶ qwer_heart_default896 (side=None)... ✅ 11.1s  出图 1288x1678 (331337B)
+[26/40] ▶ qwer_heart_origin0 (side=0)... ✅ 25.0s  出图 1280x1680 (355982B)
+[27/40] ▶ qwer_straight_default896 (side=None)... ✅ 10.7s  出图 1288x1678 (281665B)
+[28/40] ▶ qwer_straight_origin0 (side=0)... ✅ 23.4s  出图 1280x1680 (322183B)
+[29/40] ▶ qwer_wave_default896 (side=None)... ✅ 11.1s  出图 1288x1678 (289322B)
+[30/40] ▶ qwer_wave_origin0 (side=0)... ✅ 25.8s  出图 1280x1680 (351719B)
+[31/40] ▶ asdf_ellipse_default896 (side=None)... ✅ 11.2s  出图 1254x1666 (285362B)
+[32/40] ▶ asdf_ellipse_origin0 (side=0)... ✅ 25.7s  出图 1248x1664 (286768B)
+[33/40] ▶ asdf_flower_default896 (side=None)... ✅ 10.7s  出图 1254x1666 (266946B)
+[34/40] ▶ asdf_flower_origin0 (side=0)... ✅ 22.9s  出图 1248x1664 (353668B)
+[35/40] ▶ asdf_heart_default896 (side=None)... ✅ 10.4s  出图 1254x1666 (271975B)
+[36/40] ▶ asdf_heart_origin0 (side=0)... ✅ 22.9s  出图 1248x1664 (291983B)
+[37/40] ▶ asdf_straight_default896 (side=None)... ✅ 9.8s  出图 1254x1666 (258665B)
+[38/40] ▶ asdf_straight_origin0 (side=0)... ✅ 24.0s  出图 1248x1664 (279883B)
+[39/40] ▶ asdf_wave_default896 (side=None)... ✅ 11.9s  出图 1254x1666 (286515B)
+[40/40] ▶ asdf_wave_origin0 (side=0)... ✅ 24.3s  出图 1248x1664 (295694B)
+
+======================================================================
+汇总报告
+======================================================================
+
+--- 速度对比（秒，✓=成功 ✗=失败）---
+图       发型               默认896         原图0        差值
+girl2   ellipse          10.8✓       13.3✓      +2.5
+girl2   flower           11.0✓       12.5✓      +1.5
+girl2   heart            11.9✓       12.2✓      +0.3
+girl2   straight         12.1✓       12.3✓      +0.2
+girl2   wave             12.7✓       11.9✓      -0.8
+girl5   ellipse           9.6✓        7.3✓      -2.3
+girl5   flower            8.0✓        7.2✓      -0.8
+girl5   heart             8.1✓        7.6✓      -0.5
+girl5   straight          8.4✓        7.2✓      -1.2
+girl5   wave              8.4✓        7.7✓      -0.7
+qwer    ellipse          10.2✓       30.0✓     +19.8
+qwer    flower           10.2✓       25.0✓     +14.8
+qwer    heart            11.1✓       25.0✓     +13.9
+qwer    straight         10.7✓       23.4✓     +12.7
+qwer    wave             11.1✓       25.8✓     +14.7
+asdf    ellipse          11.2✓       25.7✓     +14.5
+asdf    flower           10.7✓       22.9✓     +12.2
+asdf    heart            10.4✓       22.9✓     +12.5
+asdf    straight          9.8✓       24.0✓     +14.2
+asdf    wave             11.9✓       24.3✓     +12.4
+
+结果图: /home/ubuntu/hair/image/compare_test/out/
+CSV报告: /home/ubuntu/hair/image/compare_test/out/report.csv
+JSON明细: /home/ubuntu/hair/image/compare_test/out/report.json

image/compare_test/archive_20260725/report.csv

@@ -0,0 +1,41 @@
+img,style,side,ok,elapsed_s,out_w,out_h,err
+girl2,ellipse,default896,True,10.8,1082,1081,
+girl2,ellipse,origin0,True,13.3,1088,1088,
+girl2,flower,default896,True,11.0,1082,1081,
+girl2,flower,origin0,True,12.5,1088,1088,
+girl2,heart,default896,True,11.9,1082,1081,
+girl2,heart,origin0,True,12.2,1088,1088,
+girl2,straight,default896,True,12.1,1082,1081,
+girl2,straight,origin0,True,12.3,1088,1088,
+girl2,wave,default896,True,12.7,1082,1081,
+girl2,wave,origin0,True,11.9,1088,1088,
+girl5,ellipse,default896,True,9.6,768,752,
+girl5,ellipse,origin0,True,7.3,768,752,
+girl5,flower,default896,True,8.0,768,752,
+girl5,flower,origin0,True,7.2,768,752,
+girl5,heart,default896,True,8.1,768,752,
+girl5,heart,origin0,True,7.6,768,752,
+girl5,straight,default896,True,8.4,768,752,
+girl5,straight,origin0,True,7.2,768,752,
+girl5,wave,default896,True,8.4,768,752,
+girl5,wave,origin0,True,7.7,768,752,
+qwer,ellipse,default896,True,10.2,1288,1678,
+qwer,ellipse,origin0,True,30.0,1280,1680,
+qwer,flower,default896,True,10.2,1288,1678,
+qwer,flower,origin0,True,25.0,1280,1680,
+qwer,heart,default896,True,11.1,1288,1678,
+qwer,heart,origin0,True,25.0,1280,1680,
+qwer,straight,default896,True,10.7,1288,1678,
+qwer,straight,origin0,True,23.4,1280,1680,
+qwer,wave,default896,True,11.1,1288,1678,
+qwer,wave,origin0,True,25.8,1280,1680,
+asdf,ellipse,default896,True,11.2,1254,1666,
+asdf,ellipse,origin0,True,25.7,1248,1664,
+asdf,flower,default896,True,10.7,1254,1666,
+asdf,flower,origin0,True,22.9,1248,1664,
+asdf,heart,default896,True,10.4,1254,1666,
+asdf,heart,origin0,True,22.9,1248,1664,
+asdf,straight,default896,True,9.8,1254,1666,
+asdf,straight,origin0,True,24.0,1248,1664,
+asdf,wave,default896,True,11.9,1254,1666,
+asdf,wave,origin0,True,24.3,1248,1664,

image/compare_test/archive_20260725/report.json

@@ -0,0 +1,562 @@
+[
+ {
+  "key": "girl2_ellipse_default896",
+  "img": "girl2",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 10.8,
+  "err": "",
+  "out_w": 1082,
+  "out_h": 1081,
+  "bytes": 204589
+ },
+ {
+  "key": "girl2_ellipse_origin0",
+  "img": "girl2",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 13.3,
+  "err": "",
+  "out_w": 1088,
+  "out_h": 1088,
+  "bytes": 232252
+ },
+ {
+  "key": "girl2_flower_default896",
+  "img": "girl2",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 11.0,
+  "err": "",
+  "out_w": 1082,
+  "out_h": 1081,
+  "bytes": 210875
+ },
+ {
+  "key": "girl2_flower_origin0",
+  "img": "girl2",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 12.5,
+  "err": "",
+  "out_w": 1088,
+  "out_h": 1088,
+  "bytes": 236073
+ },
+ {
+  "key": "girl2_heart_default896",
+  "img": "girl2",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 11.9,
+  "err": "",
+  "out_w": 1082,
+  "out_h": 1081,
+  "bytes": 198911
+ },
+ {
+  "key": "girl2_heart_origin0",
+  "img": "girl2",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 12.2,
+  "err": "",
+  "out_w": 1088,
+  "out_h": 1088,
+  "bytes": 249893
+ },
+ {
+  "key": "girl2_straight_default896",
+  "img": "girl2",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 12.1,
+  "err": "",
+  "out_w": 1082,
+  "out_h": 1081,
+  "bytes": 211803
+ },
+ {
+  "key": "girl2_straight_origin0",
+  "img": "girl2",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 12.3,
+  "err": "",
+  "out_w": 1088,
+  "out_h": 1088,
+  "bytes": 235377
+ },
+ {
+  "key": "girl2_wave_default896",
+  "img": "girl2",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 12.7,
+  "err": "",
+  "out_w": 1082,
+  "out_h": 1081,
+  "bytes": 207736
+ },
+ {
+  "key": "girl2_wave_origin0",
+  "img": "girl2",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 11.9,
+  "err": "",
+  "out_w": 1088,
+  "out_h": 1088,
+  "bytes": 238081
+ },
+ {
+  "key": "girl5_ellipse_default896",
+  "img": "girl5",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 9.6,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 105867
+ },
+ {
+  "key": "girl5_ellipse_origin0",
+  "img": "girl5",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 7.3,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 112963
+ },
+ {
+  "key": "girl5_flower_default896",
+  "img": "girl5",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 8.0,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 114378
+ },
+ {
+  "key": "girl5_flower_origin0",
+  "img": "girl5",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 7.2,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 108495
+ },
+ {
+  "key": "girl5_heart_default896",
+  "img": "girl5",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 8.1,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 113874
+ },
+ {
+  "key": "girl5_heart_origin0",
+  "img": "girl5",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 7.6,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 103160
+ },
+ {
+  "key": "girl5_straight_default896",
+  "img": "girl5",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 8.4,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 104492
+ },
+ {
+  "key": "girl5_straight_origin0",
+  "img": "girl5",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 7.2,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 100941
+ },
+ {
+  "key": "girl5_wave_default896",
+  "img": "girl5",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 8.4,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 120122
+ },
+ {
+  "key": "girl5_wave_origin0",
+  "img": "girl5",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 7.7,
+  "err": "",
+  "out_w": 768,
+  "out_h": 752,
+  "bytes": 113282
+ },
+ {
+  "key": "qwer_ellipse_default896",
+  "img": "qwer",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 10.2,
+  "err": "",
+  "out_w": 1288,
+  "out_h": 1678,
+  "bytes": 261812
+ },
+ {
+  "key": "qwer_ellipse_origin0",
+  "img": "qwer",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 30.0,
+  "err": "",
+  "out_w": 1280,
+  "out_h": 1680,
+  "bytes": 331013
+ },
+ {
+  "key": "qwer_flower_default896",
+  "img": "qwer",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 10.2,
+  "err": "",
+  "out_w": 1288,
+  "out_h": 1678,
+  "bytes": 312834
+ },
+ {
+  "key": "qwer_flower_origin0",
+  "img": "qwer",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 25.0,
+  "err": "",
+  "out_w": 1280,
+  "out_h": 1680,
+  "bytes": 328605
+ },
+ {
+  "key": "qwer_heart_default896",
+  "img": "qwer",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 11.1,
+  "err": "",
+  "out_w": 1288,
+  "out_h": 1678,
+  "bytes": 331337
+ },
+ {
+  "key": "qwer_heart_origin0",
+  "img": "qwer",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 25.0,
+  "err": "",
+  "out_w": 1280,
+  "out_h": 1680,
+  "bytes": 355982
+ },
+ {
+  "key": "qwer_straight_default896",
+  "img": "qwer",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 10.7,
+  "err": "",
+  "out_w": 1288,
+  "out_h": 1678,
+  "bytes": 281665
+ },
+ {
+  "key": "qwer_straight_origin0",
+  "img": "qwer",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 23.4,
+  "err": "",
+  "out_w": 1280,
+  "out_h": 1680,
+  "bytes": 322183
+ },
+ {
+  "key": "qwer_wave_default896",
+  "img": "qwer",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 11.1,
+  "err": "",
+  "out_w": 1288,
+  "out_h": 1678,
+  "bytes": 289322
+ },
+ {
+  "key": "qwer_wave_origin0",
+  "img": "qwer",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 25.8,
+  "err": "",
+  "out_w": 1280,
+  "out_h": 1680,
+  "bytes": 351719
+ },
+ {
+  "key": "asdf_ellipse_default896",
+  "img": "asdf",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 11.2,
+  "err": "",
+  "out_w": 1254,
+  "out_h": 1666,
+  "bytes": 285362
+ },
+ {
+  "key": "asdf_ellipse_origin0",
+  "img": "asdf",
+  "style": "ellipse",
+  "style_idx": 1,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 25.7,
+  "err": "",
+  "out_w": 1248,
+  "out_h": 1664,
+  "bytes": 286768
+ },
+ {
+  "key": "asdf_flower_default896",
+  "img": "asdf",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 10.7,
+  "err": "",
+  "out_w": 1254,
+  "out_h": 1666,
+  "bytes": 266946
+ },
+ {
+  "key": "asdf_flower_origin0",
+  "img": "asdf",
+  "style": "flower",
+  "style_idx": 2,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 22.9,
+  "err": "",
+  "out_w": 1248,
+  "out_h": 1664,
+  "bytes": 353668
+ },
+ {
+  "key": "asdf_heart_default896",
+  "img": "asdf",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 10.4,
+  "err": "",
+  "out_w": 1254,
+  "out_h": 1666,
+  "bytes": 271975
+ },
+ {
+  "key": "asdf_heart_origin0",
+  "img": "asdf",
+  "style": "heart",
+  "style_idx": 3,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 22.9,
+  "err": "",
+  "out_w": 1248,
+  "out_h": 1664,
+  "bytes": 291983
+ },
+ {
+  "key": "asdf_straight_default896",
+  "img": "asdf",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 9.8,
+  "err": "",
+  "out_w": 1254,
+  "out_h": 1666,
+  "bytes": 258665
+ },
+ {
+  "key": "asdf_straight_origin0",
+  "img": "asdf",
+  "style": "straight",
+  "style_idx": 4,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 24.0,
+  "err": "",
+  "out_w": 1248,
+  "out_h": 1664,
+  "bytes": 279883
+ },
+ {
+  "key": "asdf_wave_default896",
+  "img": "asdf",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "default896",
+  "side_val": null,
+  "ok": true,
+  "elapsed": 11.9,
+  "err": "",
+  "out_w": 1254,
+  "out_h": 1666,
+  "bytes": 286515
+ },
+ {
+  "key": "asdf_wave_origin0",
+  "img": "asdf",
+  "style": "wave",
+  "style_idx": 5,
+  "side": "origin0",
+  "side_val": 0,
+  "ok": true,
+  "elapsed": 24.3,
+  "err": "",
+  "out_w": 1248,
+  "out_h": 1664,
+  "bytes": 295694
+ }
+]

image/compare_test/batch_test.py

@@ -0,0 +1,162 @@
+#!/usr/bin/env python3
+"""接口2 female 批量对比测试：4图 × 5发型 × 3分辨率档位 = 60次请求。
+串行执行，记录耗时与成败，结果图按 图_发型_档位 命名保存。
+用法: python3 batch_test.py
+支持断点续跑（progress.json）；新增档位时只会补跑未完成项。
+"""
+import base64, csv, json, os, sys, time, traceback
+import requests
+
+API = "http://127.0.0.1:8187/api/v1/hair/grow"
+TOKEN = "dev-shared-secret-2026"
+TIMEOUT = 600
+OUT = "/home/ubuntu/hair/image/compare_test/out"
+PROGRESS = "/home/ubuntu/hair/image/compare_test/progress.json"
+
+IMG_DIR = "/home/ubuntu/hair/image"
+IMAGES = [
+    ("girl2",  f"{IMG_DIR}/girl_img/girl2.jpg"),
+    ("girl5",  f"{IMG_DIR}/girl_img/girl5.jpg"),
+    ("qwer",   f"{IMG_DIR}/qwer.jpg"),
+    ("asdf",   f"{IMG_DIR}/asdf.jpg"),
+]
+# female: 1=ellipse 2=flower 3=heart 4=straight 5=wave
+STYLES = [
+    (1, "ellipse"), (2, "flower"), (3, "heart"), (4, "straight"), (5, "wave"),
+]
+# 三档: 默认896 / 显式1024 / 原图直送0
+SIDES = [
+    ("default896", None),   # 不传 → 后端默认896
+    ("side1024",   1024),   # 长边压到 1024
+    ("origin0",    0),      # 原图直送
+]
+SIDE_LABEL = {
+    "default896": "默认896",
+    "side1024": "1024",
+    "origin0": "原图0",
+}
+
+def load_progress():
+    if os.path.exists(PROGRESS):
+        try:
+            return json.load(open(PROGRESS))
+        except Exception:
+            pass
+    return {"done": [], "results": []}
+
+def save_progress(prog):
+    json.dump(prog, open(PROGRESS, "w"), ensure_ascii=False, indent=1)
+
+def run_one(img_name, img_path, style_idx, style_key, side_name, side_val):
+    """跑单次请求，返回 dict 结果。"""
+    key = f"{img_name}_{style_key}_{side_name}"
+    with open(img_path, "rb") as f:
+        img_b64 = base64.b64encode(f.read()).decode()
+    data = {
+        "image_base64": "data:image/jpeg;base64," + img_b64,
+        "gender": "female",
+        "hair_style": str(style_idx),
+    }
+    if side_val is not None:
+        data["redraw_max_side"] = str(side_val)
+    t0 = time.time()
+    rec = {"key": key, "img": img_name, "style": style_key, "style_idx": style_idx,
+           "side": side_name, "side_val": side_val, "ok": False,
+           "elapsed": 0.0, "err": "", "out_w": 0, "out_h": 0}
+    try:
+        r = requests.post(API, data=data, headers={"X-Internal-Token": TOKEN}, timeout=TIMEOUT)
+        rec["elapsed"] = round(time.time() - t0, 1)
+        d = r.json()
+        if d.get("code") != 0:
+            rec["err"] = f"code={d.get('code')} {d.get('message','')}"[:200]
+            return rec
+        results = (d.get("data") or {}).get("results") or []
+        if not results:
+            rec["err"] = "空结果"
+            return rec
+        it = results[0]
+        grown = it.get("grown_image_base64")
+        if not grown:
+            rec["err"] = "无生发图(grown_png=None, 重绘失败)"
+            return rec
+        raw = base64.b64decode(grown)
+        from PIL import Image
+        import io as _io
+        im = Image.open(_io.BytesIO(raw))
+        rec["out_w"], rec["out_h"] = im.size
+        out_path = f"{OUT}/{key}.jpg"
+        with open(out_path, "wb") as fo:
+            fo.write(raw)
+        rec["ok"] = True
+        rec["bytes"] = len(raw)
+    except requests.exceptions.Timeout:
+        rec["elapsed"] = round(time.time() - t0, 1)
+        rec["err"] = f"超时(>{TIMEOUT}s)"
+    except Exception as e:
+        rec["elapsed"] = round(time.time() - t0, 1)
+        rec["err"] = f"{type(e).__name__}: {str(e)[:180]}"
+    return rec
+
+def main():
+    os.makedirs(OUT, exist_ok=True)
+    prog = load_progress()
+    done_keys = set(prog["done"])
+    total = len(IMAGES) * len(STYLES) * len(SIDES)
+    print(f"=== 接口2 female 批量对比测试 ===")
+    print(f"矩阵: {len(IMAGES)}图 × {len(STYLES)}发型 × {len(SIDES)}档 = {total} 次")
+    print(f"已跳过 {len(done_keys)} 个已完成项\n")
+
+    idx = 0
+    for img_name, img_path in IMAGES:
+        for style_idx, style_key in STYLES:
+            for side_name, side_val in SIDES:
+                idx += 1
+                key = f"{img_name}_{style_key}_{side_name}"
+                if key in done_keys:
+                    print(f"[{idx}/{total}] ⏭  跳过已完成 {key}")
+                    continue
+                print(f"[{idx}/{total}] ▶ {key} (side={side_val})...", end=" ", flush=True)
+                rec = run_one(img_name, img_path, style_idx, style_key, side_name, side_val)
+                prog["results"].append(rec)
+                prog["done"].append(key)
+                save_progress(prog)
+                if rec["ok"]:
+                    print(f"✅ {rec['elapsed']}s  出图 {rec['out_w']}x{rec['out_h']} ({rec['bytes']}B)")
+                else:
+                    print(f"❌ {rec['elapsed']}s  {rec['err']}")
+                time.sleep(2)  # 串行间隔，避免队列堆积
+
+    # 汇总
+    print("\n" + "="*70)
+    print("汇总报告")
+    print("="*70)
+    write_report(prog["results"])
+    print(f"\n结果图: {OUT}/")
+    print(f"CSV报告: {OUT}/report.csv")
+    print(f"JSON明细: {OUT}/report.json")
+
+def write_report(results):
+    # CSV
+    csv_path = f"{OUT}/report.csv"
+    with open(csv_path, "w", newline="") as f:
+        w = csv.writer(f)
+        w.writerow(["img","style","side","ok","elapsed_s","out_w","out_h","err"])
+        for r in results:
+            w.writerow([r["img"],r["style"],r["side"],r["ok"],r["elapsed"],
+                        r["out_w"],r["out_h"],r["err"]])
+    # JSON
+    json.dump(results, open(f"{OUT}/report.json","w"), ensure_ascii=False, indent=1)
+    # 控制台速度对比表
+    print("\n--- 速度对比（秒，✓=成功 ✗=失败）---")
+    headers = ["图", "发型"] + [SIDE_LABEL[s] for s, _ in SIDES]
+    print(f"{headers[0]:<8}{headers[1]:<10}" + "".join(f"{h:>12}" for h in headers[2:]))
+    for img_name, _ in IMAGES:
+        for _, style_key in STYLES:
+            cells = []
+            for side_name, _ in SIDES:
+                r = next((x for x in results if x["img"]==img_name and x["style"]==style_key and x["side"]==side_name), None)
+                cells.append(f"{r['elapsed']}{'✓' if r['ok'] else '✗'}" if r else "-")
+            print(f"{img_name:<8}{style_key:<10}" + "".join(f"{c:>12}" for c in cells))
+
+if __name__ == "__main__":
+    main()

image/compare_test/gen_report.py

@@ -0,0 +1,244 @@
+#!/usr/bin/env python3
+"""把 report.json + 结果图生成为自包含 HTML 报告（支持 896 / 1024 / 原图0 三档）。"""
+import json, os, html
+
+OUT = "/home/ubuntu/hair/image/compare_test/out"
+REPORT_HTML = os.path.join(OUT, "report.html")
+results = json.load(open(os.path.join(OUT, "report.json")))
+
+IMAGES = ["girl2", "girl5", "qwer", "asdf"]
+STYLES = ["ellipse", "flower", "heart", "straight", "wave"]
+SIDES = [
+    ("default896", "默认 896", "#2563eb", "d"),
+    ("side1024",   "1024",     "#10b981", "m"),
+    ("origin0",    "原图直送 0", "#f59e0b", "o"),
+]
+IMG_LONGSIDE = {"girl2": 1082, "girl5": 767, "qwer": 1678, "asdf": 1666}
+STYLE_CN = {"ellipse": "椭圆", "flower": "花瓣", "heart": "心形", "straight": "直线", "wave": "波浪"}
+
+def get(img, style, side):
+    for r in results:
+        if r["img"] == img and r["style"] == style and r["side"] == side:
+            return r
+    return None
+
+# 总览统计（>60s 视为冷启动/异常，不进均值）
+total = len(results)
+ok = sum(1 for r in results if r["ok"])
+COLD_S = 60.0
+
+def avg(seq):
+    seq = [x for x in seq if x is not None]
+    return sum(seq) / len(seq) if seq else 0
+
+def times(side, img=None):
+    out = []
+    for r in results:
+        if not r["ok"] or r["side"] != side:
+            continue
+        if img is not None and r["img"] != img:
+            continue
+        if r["elapsed"] >= COLD_S:
+            continue
+        out.append(r["elapsed"])
+    return out
+
+cold_n = sum(1 for r in results if r["ok"] and r["elapsed"] >= COLD_S)
+side_avgs = {sid: avg(times(sid)) for sid, *_ in SIDES}
+all_times = [t for sid, *_ in SIDES for t in times(sid)]
+max_bar = max(all_times + [1])
+
+# 构造速度对比图数据：每图 × 三档
+chart_rows = []
+for img in IMAGES:
+    chart_rows.append((img, IMG_LONGSIDE[img], [avg(times(sid, img)) for sid, *_ in SIDES]))
+
+def bar_svg():
+    bar_h = 22
+    gap = 12
+    label_w = 78
+    chart_w = 760
+    n_bars = len(SIDES)
+    rows = len(chart_rows)
+    h = rows * (bar_h * n_bars + gap) + 40
+    parts = [f'<svg viewBox="0 0 {label_w + chart_w + 80} {h}" class="chart">']
+    y = 10
+    for img, longside, avgs in chart_rows:
+        base = avgs[0] if avgs and avgs[0] else 1
+        for i, ((sid, label, color, _), a) in enumerate(zip(SIDES, avgs)):
+            yi = y + i * bar_h
+            w = int(a / max_bar * chart_w) if a else 0
+            warn = "⚠" if (i > 0 and a > base * 1.8) else ""
+            parts.append(f'<rect x="{label_w}" y="{yi}" width="{w}" height="{bar_h-4}" rx="3" fill="{color}"/>')
+            parts.append(f'<text x="{label_w + w + 6}" y="{yi + bar_h - 10}" class="barlabel">{a:.1f}s {warn}</text>')
+            parts.append(f'<text x="{label_w-8}" y="{yi + bar_h - 10}" class="rowlabel" text-anchor="end">{html.escape(label)}</text>')
+        parts.append(f'<text x="0" y="{y + bar_h - 2}" class="imglabel">{img}<tspan class="imgside">长边{longside}</tspan></text>')
+        y += bar_h * n_bars + gap
+    parts.append("</svg>")
+    return "".join(parts)
+
+def img_cell(r, cls):
+    if not r:
+        return f'<td class="{cls} fail">缺失</td>'
+    fname = r["key"] + ".jpg"
+    status = "✅" if r["ok"] else "❌"
+    t = f'{r["elapsed"]}s'
+    dim = f'{r["out_w"]}×{r["out_h"]}'
+    err = f'<div class="err">{html.escape(r["err"])}</div>' if r["err"] else ""
+    img_tag = (f'<img loading="lazy" src="{fname}" onclick="openImg(this.src)" alt="{html.escape(r["key"])}">'
+               if r["ok"] else '<div class="noimg">无图</div>')
+    return (f'<td class="{cls}"><div class="thumb">{img_tag}</div>'
+            f'<div class="meta">{status} {t} · {dim}</div>{err}</td>')
+
+def compare_cards():
+    out = []
+    for img in IMAGES:
+        out.append(f'<div class="card"><div class="card-h">📷 {html.escape(img)} <span class="tag">原图长边 {IMG_LONGSIDE[img]}px</span></div><div class="card-b">')
+        heads = "".join(f'<th class="{cls}">{html.escape(label)}</th>' for _, label, _, cls in SIDES)
+        out.append(f'<table class="cmp"><thead><tr><th>发型</th>{heads}</tr></thead><tbody>')
+        for style in STYLES:
+            sc = STYLE_CN[style]
+            cells = "".join(img_cell(get(img, style, sid), cls) for sid, _, _, cls in SIDES)
+            out.append(f'<tr><td class="sname">{html.escape(style)}<span>{sc}</span></td>{cells}</tr>')
+        out.append("</tbody></table></div></div>")
+    return "".join(out)
+
+# 结论
+small = [img for img in IMAGES if IMG_LONGSIDE[img] <= 1100]
+large = [img for img in IMAGES if IMG_LONGSIDE[img] > 1100]
+def ratio_range(num_side, den_side="default896"):
+    ratios = []
+    for img in large:
+        den = avg(times(den_side, img))
+        num = avg(times(num_side, img))
+        if den:
+            ratios.append(num / den)
+    if not ratios:
+        return 0, 0
+    return min(ratios), max(ratios)
+
+r1024_lo, r1024_hi = ratio_range("side1024")
+r0_lo, r0_hi = ratio_range("origin0")
+cold_note = f"冷启动 {cold_n} 次（≥{COLD_S:.0f}s）已从均值剔除。" if cold_n else ""
+conclusion = (
+    f"原图长边 ≤ 1100（{'/'.join(small)}）时三档耗时接近；"
+    f"长边 > 1600（{'/'.join(large)}）时相对默认896："
+    f"<b>1024 约 {r1024_lo:.1f}~{r1024_hi:.1f}×</b>，"
+    f"<b>原图直送约 {r0_lo:.1f}~{r0_hi:.1f}×</b>。"
+    f"{cold_note}画质对比见下方三列并排，点击可放大。"
+)
+
+avg896 = side_avgs.get("default896", 0)
+avg1024 = side_avgs.get("side1024", 0)
+avg0 = side_avgs.get("origin0", 0)
+ratio1024 = avg1024 / avg896 if avg896 else 0
+ratio0 = avg0 / avg896 if avg896 else 0
+
+legend = "".join(
+    f'<span><i style="background:{color}"></i>{html.escape(label)}</span>'
+    for _, label, color, _ in SIDES
+)
+
+html_doc = f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>接口2 分辨率对比测试报告</title>
+<style>
+  * {{ box-sizing: border-box; margin: 0; padding: 0; }}
+  body {{ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "PingFang SC", "Microsoft YaHei", sans-serif; background: #f3f4f6; color: #1f2937; line-height: 1.5; padding: 20px; }}
+  .wrap {{ max-width: 1400px; margin: 0 auto; }}
+  h1 {{ font-size: 24px; margin-bottom: 4px; }}
+  .sub {{ color: #6b7280; font-size: 13px; margin-bottom: 20px; }}
+  .summary {{ display: grid; grid-template-columns: repeat(5, 1fr); gap: 12px; margin-bottom: 24px; }}
+  .stat {{ background: #fff; border-radius: 10px; padding: 16px; box-shadow: 0 1px 3px rgba(0,0,0,.06); }}
+  .stat .num {{ font-size: 26px; font-weight: 700; }}
+  .stat .lbl {{ font-size: 12px; color: #6b7280; margin-top: 2px; }}
+  .stat.d .num {{ color: #2563eb; }}
+  .stat.m .num {{ color: #10b981; }}
+  .stat.o .num {{ color: #f59e0b; }}
+  .card {{ background: #fff; border-radius: 12px; box-shadow: 0 1px 4px rgba(0,0,0,.07); margin-bottom: 20px; overflow: hidden; }}
+  .card-h {{ padding: 12px 18px; background: #fafafa; border-bottom: 1px solid #f0f0f0; font-weight: 700; font-size: 15px; display: flex; align-items: center; gap: 8px; }}
+  .card-h .tag {{ font-size: 11px; font-weight: 500; color: #6b7280; background: #f3f4f6; padding: 2px 8px; border-radius: 10px; }}
+  .card-b {{ padding: 16px; }}
+  .chart {{ width: 100%; height: auto; max-width: 920px; }}
+  .barlabel {{ font-size: 12px; fill: #374151; font-weight: 600; }}
+  .rowlabel {{ font-size: 11px; fill: #6b7280; }}
+  .imglabel {{ font-size: 14px; fill: #111; font-weight: 700; }}
+  .imgside {{ font-size: 10px; fill: #9ca3af; font-weight: 400; }}
+  table.cmp {{ width: 100%; border-collapse: collapse; table-layout: fixed; }}
+  table.cmp th {{ font-size: 12px; color: #6b7280; font-weight: 600; padding: 8px; text-align: center; border-bottom: 2px solid #f0f0f0; }}
+  table.cmp td {{ padding: 8px; border-bottom: 1px solid #f6f6f6; vertical-align: top; text-align: center; }}
+  table.cmp th.d, table.cmp td.d {{ background: #eff6ff; }}
+  table.cmp th.m, table.cmp td.m {{ background: #ecfdf5; }}
+  table.cmp th.o, table.cmp td.o {{ background: #fffbeb; }}
+  td.sname {{ font-weight: 600; text-align: left; width: 90px; }}
+  td.sname span {{ display: block; font-size: 11px; color: #9ca3af; font-weight: 400; }}
+  .thumb {{ background: #222; border-radius: 6px; overflow: hidden; margin-bottom: 4px; cursor: zoom-in; }}
+  .thumb img {{ width: 100%; height: 200px; object-fit: contain; display: block; }}
+  .noimg {{ color: #d1d5db; font-size: 12px; padding: 40px 0; }}
+  .meta {{ font-size: 11px; color: #6b7280; }}
+  .err {{ font-size: 10px; color: #dc2626; margin-top: 2px; }}
+  .note {{ background: #fef3c7; border-left: 3px solid #f59e0b; padding: 12px 16px; border-radius: 6px; font-size: 13px; margin-bottom: 20px; }}
+  .legend {{ display: flex; gap: 20px; font-size: 12px; color: #6b7280; margin-bottom: 12px; flex-wrap: wrap; }}
+  .legend span {{ display: inline-flex; align-items: center; gap: 5px; }}
+  .legend i {{ width: 12px; height: 12px; border-radius: 2px; display: inline-block; }}
+  .overlay {{ display: none; position: fixed; inset: 0; background: rgba(0,0,0,.9); z-index: 999; justify-content: center; align-items: center; cursor: zoom-out; padding: 30px; }}
+  .overlay.active {{ display: flex; }}
+  .overlay img {{ max-width: 95%; max-height: 95%; object-fit: contain; border-radius: 4px; }}
+  @media (max-width: 900px) {{
+    .summary {{ grid-template-columns: repeat(2, 1fr); }}
+    .thumb img {{ height: 160px; }}
+  }}
+</style>
+</head>
+<body>
+<div class="wrap">
+  <h1>接口2 生发 · 分辨率对比测试报告</h1>
+  <p class="sub">POST /api/v1/hair/grow · female · 4 张图 × 5 发型 × 3 档分辨率 = {total} 次 · 串行</p>
+
+  <div class="summary">
+    <div class="stat"><div class="num">{ok}/{total}</div><div class="lbl">成功 / 总数</div></div>
+    <div class="stat d"><div class="num">{avg896:.1f}s</div><div class="lbl">默认896 平均</div></div>
+    <div class="stat m"><div class="num">{avg1024:.1f}s</div><div class="lbl">1024 平均 · ×{ratio1024:.2f}</div></div>
+    <div class="stat o"><div class="num">{avg0:.1f}s</div><div class="lbl">原图直送 平均 · ×{ratio0:.2f}</div></div>
+    <div class="stat"><div class="num" style="color:{'#dc2626' if ratio0>1.3 else '#16a34a'}">×{ratio0:.2f}</div><div class="lbl">原图/默认 倍率</div></div>
+  </div>
+
+  <div class="note">
+    <b>结论：</b>{conclusion}
+  </div>
+
+  <div class="card">
+    <div class="card-h">平均耗时对比（按图分组，单位：秒）</div>
+    <div class="card-b">
+      <div class="legend">{legend}</div>
+      {bar_svg()}
+    </div>
+  </div>
+
+  <h2 style="font-size:18px;margin:8px 0 14px">画质对比（左→右：默认896 · 1024 · 原图直送）</h2>
+  {compare_cards()}
+
+</div>
+<div class="overlay" id="overlay" onclick="this.classList.remove('active')">
+  <img id="overlayImg" src="">
+</div>
+<script>
+function openImg(src) {{
+  document.getElementById('overlayImg').src = src;
+  document.getElementById('overlay').classList.add('active');
+}}
+</script>
+</body>
+</html>
+"""
+
+with open(REPORT_HTML, "w") as f:
+    f.write(html_doc)
+# 同步首页
+with open(os.path.join(OUT, "index.html"), "w") as f:
+    f.write(html_doc)
+print(f"已生成: {REPORT_HTML}")
+print(f"图片目录: {OUT}")

image/compare_test/report-server.service

@@ -0,0 +1,15 @@
+[Unit]
+Description=接口2 分辨率对比测试报告 HTTP 服务 (8848)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=ubuntu
+WorkingDirectory=/home/ubuntu/hair/image/compare_test/out
+ExecStart=/home/ubuntu/miniconda3/envs/my_hair/bin/python -m http.server 8848 --bind 0.0.0.0
+Restart=on-failure
+RestartSec=5
+
+[Install]
+WantedBy=multi-user.target

image/reports/index.html

@@ -0,0 +1,47 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>测试报告索引</title>
+<style>
+  * { box-sizing: border-box; margin: 0; padding: 0; }
+  body { font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "PingFang SC", "Microsoft YaHei", sans-serif; background: #f3f4f6; color: #1f2937; padding: 40px 20px; }
+  .wrap { max-width: 720px; margin: 0 auto; }
+  h1 { font-size: 24px; margin-bottom: 4px; }
+  .sub { color: #6b7280; font-size: 13px; margin-bottom: 28px; }
+  .card { display: block; background: #fff; border-radius: 12px; box-shadow: 0 1px 4px rgba(0,0,0,.07); padding: 20px 24px; margin-bottom: 14px; text-decoration: none; color: inherit; transition: .15s; border-left: 4px solid #2563eb; }
+  .card:hover { transform: translateX(4px); box-shadow: 0 4px 12px rgba(0,0,0,.1); }
+  .card .title { font-size: 16px; font-weight: 700; margin-bottom: 4px; }
+  .card .desc { font-size: 13px; color: #6b7280; }
+  .card .url { font-size: 11px; color: #9ca3af; margin-top: 6px; font-family: monospace; }
+  .card.wave { border-left-color: #16a34a; }
+  .card.v2 { border-left-color: #f59e0b; }
+  .card.v1 { border-left-color: #2563eb; }
+</style>
+</head>
+<body>
+<div class="wrap">
+  <h1>📊 测试报告索引</h1>
+  <p class="sub">接口2 / 接口5 分辨率对比测试报告合集</p>
+
+  <a class="card wave" href="wave/">
+    <div class="title">💇 wave发型 · 5档分辨率对比（最新）</div>
+    <div class="desc">21图 × 5档(原图/1024/896/768/640) = 105次 · wave发型 · female</div>
+    <div class="url">/wave/</div>
+  </a>
+
+  <a class="card v2" href="v2/">
+    <div class="title">💄 5图 · 5档分辨率对比 v2</div>
+    <div class="desc">5图 × 3发型(花瓣/心形/波浪) × 5档 = 75次 · female</div>
+    <div class="url">/v2/</div>
+  </a>
+
+  <a class="card v1" href="v1/">
+    <div class="title">💄 4图 · 2档分辨率对比 v1</div>
+    <div class="desc">4图 × 5发型 × 2档(默认896/原图) = 40次 · female</div>
+    <div class="url">/v1/</div>
+  </a>
+</div>
+</body>
+</html>

image/reports/report-server.service

@@ -0,0 +1,15 @@
+[Unit]
+Description=测试报告统一HTTP服务 (8850, 路径区分: /wave /v2 /v1)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=ubuntu
+WorkingDirectory=/home/ubuntu/hair/image/reports
+ExecStart=/home/ubuntu/miniconda3/envs/my_hair/bin/python -m http.server 8850 --bind 0.0.0.0
+Restart=on-failure
+RestartSec=5
+
+[Install]
+WantedBy=multi-user.target

image/reports/v1

@@ -0,0 +1 @@
+/home/ubuntu/hair/image/compare_test/out

image/reports/v2

@@ -0,0 +1 @@
+/home/ubuntu/hair/image/res_test/out

image/reports/wave

@@ -0,0 +1 @@
+/home/ubuntu/hair/image/wave_test/out

image/res_test/batch_test.py

@@ -0,0 +1,148 @@
+#!/usr/bin/env python3
+"""接口2 female 分辨率对比测试 v2: 5图 × 3发型 × 5档 = 75次。
+串行执行，记录耗时与成败，结果图按 图_发型_档位 命名保存。
+支持断点续跑（progress.json）。
+"""
+import base64, csv, json, os, sys, time, io
+import requests
+from PIL import Image
+
+API = "http://127.0.0.1:8187/api/v1/hair/grow"
+TOKEN = "dev-shared-secret-2026"
+TIMEOUT = 600
+OUT = "/home/ubuntu/hair/image/res_test/out"
+PROGRESS = "/home/ubuntu/hair/image/res_test/progress.json"
+
+IMG_DIR = "/home/ubuntu/hair/image"
+IMAGES = [
+    ("girl2", f"{IMG_DIR}/girl_img/girl2.jpg"),
+    ("girl5", f"{IMG_DIR}/girl_img/girl5.jpg"),
+    ("qwer",  f"{IMG_DIR}/qwer.jpg"),
+    ("asdf",  f"{IMG_DIR}/asdf.jpg"),
+    ("girl7", f"{IMG_DIR}/girl_img/girl7.jpg"),
+]
+# female: 2=flower(花瓣) 3=heart(心形) 5=wave(波浪)
+STYLES = [(2, "flower"), (3, "heart"), (5, "wave")]
+# 5档: 原图(0) / 1024 / 896 / 768 / 640
+SIDES = [
+    ("origin",  0),
+    ("s1024",   1024),
+    ("s896",    896),
+    ("s768",    768),
+    ("s640",    640),
+]
+
+def load_progress():
+    if os.path.exists(PROGRESS):
+        try:
+            return json.load(open(PROGRESS))
+        except Exception:
+            pass
+    return {"done": [], "results": []}
+
+def save_progress(prog):
+    json.dump(prog, open(PROGRESS, "w"), ensure_ascii=False, indent=1)
+
+def run_one(img_name, img_path, style_idx, style_key, side_name, side_val):
+    key = f"{img_name}_{style_key}_{side_name}"
+    with open(img_path, "rb") as f:
+        img_b64 = base64.b64encode(f.read()).decode()
+    data = {
+        "image_base64": "data:image/jpeg;base64," + img_b64,
+        "gender": "female",
+        "hair_style": str(style_idx),
+        "redraw_max_side": str(side_val),  # 含原图档=0
+    }
+    t0 = time.time()
+    rec = {"key": key, "img": img_name, "style": style_key, "style_idx": style_idx,
+           "side": side_name, "side_val": side_val, "ok": False,
+           "elapsed": 0.0, "err": "", "out_w": 0, "out_h": 0, "bytes": 0}
+    try:
+        r = requests.post(API, data=data, headers={"X-Internal-Token": TOKEN}, timeout=TIMEOUT)
+        rec["elapsed"] = round(time.time() - t0, 1)
+        d = r.json()
+        if d.get("code") != 0:
+            rec["err"] = f"code={d.get('code')} {d.get('message','')}"[:200]
+            return rec
+        results = (d.get("data") or {}).get("results") or []
+        if not results:
+            rec["err"] = "空结果"
+            return rec
+        it = results[0]
+        grown = it.get("grown_image_base64")
+        if not grown:
+            rec["err"] = "无生发图(重绘失败/OOM?)"
+            return rec
+        raw = base64.b64decode(grown)
+        im = Image.open(io.BytesIO(raw))
+        rec["out_w"], rec["out_h"] = im.size
+        out_path = f"{OUT}/{key}.jpg"
+        with open(out_path, "wb") as fo:
+            fo.write(raw)
+        rec["ok"] = True
+        rec["bytes"] = len(raw)
+    except requests.exceptions.Timeout:
+        rec["elapsed"] = round(time.time() - t0, 1)
+        rec["err"] = f"超时(>{TIMEOUT}s)"
+    except Exception as e:
+        rec["elapsed"] = round(time.time() - t0, 1)
+        rec["err"] = f"{type(e).__name__}: {str(e)[:180]}"
+    return rec
+
+def main():
+    prog = load_progress()
+    done_keys = set(prog["done"])
+    total = len(IMAGES) * len(STYLES) * len(SIDES)
+    print(f"=== 接口2 female 分辨率对比测试 v2 ===")
+    print(f"矩阵: {len(IMAGES)}图 × {len(STYLES)}发型 × {len(SIDES)}档 = {total} 次")
+    print(f"已跳过 {len(done_keys)} 个已完成项\n")
+
+    idx = 0
+    for img_name, img_path in IMAGES:
+        for style_idx, style_key in STYLES:
+            for side_name, side_val in SIDES:
+                idx += 1
+                key = f"{img_name}_{style_key}_{side_name}"
+                if key in done_keys:
+                    print(f"[{idx}/{total}] ⏭  跳过 {key}")
+                    continue
+                print(f"[{idx}/{total}] ▶ {key} (side={side_val})...", end=" ", flush=True)
+                rec = run_one(img_name, img_path, style_idx, style_key, side_name, side_val)
+                prog["results"].append(rec)
+                prog["done"].append(key)
+                save_progress(prog)
+                if rec["ok"]:
+                    print(f"✅ {rec['elapsed']}s  {rec['out_w']}x{rec['out_h']} ({rec['bytes']}B)")
+                else:
+                    print(f"❌ {rec['elapsed']}s  {rec['err']}")
+                time.sleep(2)
+
+    print("\n" + "=" * 70)
+    print("汇总")
+    print("=" * 70)
+    write_report(prog["results"])
+    print(f"\n结果图: {OUT}/")
+    print(f"CSV: {OUT}/report.csv   JSON: {OUT}/report.json")
+
+def write_report(results):
+    with open(f"{OUT}/report.csv", "w", newline="") as f:
+        w = csv.writer(f)
+        w.writerow(["img", "style", "side", "side_val", "ok", "elapsed_s", "out_w", "out_h", "bytes", "err"])
+        for r in results:
+            w.writerow([r["img"], r["style"], r["side"], r["side_val"], r["ok"],
+                        r["elapsed"], r["out_w"], r["out_h"], r["bytes"], r["err"]])
+    json.dump(results, open(f"{OUT}/report.json", "w"), ensure_ascii=False, indent=1)
+
+    # 控制台速度表：按 图×发型 分行，5档列
+    print("\n--- 速度对比（秒）---")
+    print(f"{'图·发型':<18}{'原图0':>8}{'1024':>8}{'896':>8}{'768':>8}{'640':>8}")
+    for img_name, _ in IMAGES:
+        for _, style_key in STYLES:
+            cells = []
+            for side_name, _ in SIDES:
+                r = next((x for x in results if x["img"] == img_name and x["style"] == style_key and x["side"] == side_name), None)
+                cells.append(f"{r['elapsed']}✓" if r and r["ok"] else (f"{r['elapsed']}✗" if r else "-"))
+            print(f"{img_name+'·'+style_key:<18}{cells[0]:>8}{cells[1]:>8}{cells[2]:>8}{cells[3]:>8}{cells[4]:>8}")
+
+if __name__ == "__main__":
+    main()

image/res_test/gen_report.py

@@ -0,0 +1,204 @@
+#!/usr/bin/env python3
+"""生成 v2 分辨率对比报告：每行=原图+5档，按图×发型组织15行。"""
+import json, os, html
+
+OUT = "/home/ubuntu/hair/image/res_test/out"
+REPORT = os.path.join(OUT, "report.html")
+results = json.load(open(os.path.join(OUT, "report.json")))
+
+IMAGES = ["girl2", "girl5", "qwer", "asdf", "girl7"]
+STYLES = [("flower", "花瓣"), ("heart", "心形"), ("wave", "波浪")]
+SIDES = [("origin", "原图直送", 0), ("s1024", "1024", 1024),
+         ("s896", "896", 896), ("s768", "768", 768), ("s640", "640", 640)]
+LONGSIDE = {"girl2": 1082, "girl5": 767, "qwer": 1678, "asdf": 1666, "girl7": 925}
+
+def get(img, style, side):
+    for r in results:
+        if r["img"] == img and r["style"] == style and r["side"] == side:
+            return r
+    return None
+
+# 统计
+total = len(results)
+ok = sum(1 for r in results if r["ok"])
+
+# 每档平均耗时（排除冷启动异常值：girl2_flower_origin=135s 明显是冷启动）
+def avg(side, exclude_first_cold=False):
+    ts = []
+    for r in results:
+        if r["side"] == side and r["ok"]:
+            if exclude_first_cold and r["key"] == "girl2_flower_origin":
+                continue  # 跳过冷启动
+            ts.append(r["elapsed"])
+    return sum(ts) / len(ts) if ts else 0
+
+avg_origin = avg("origin", exclude_first_cold=True)
+avg_1024 = avg("s1024")
+avg_896 = avg("s896")
+avg_768 = avg("s768")
+avg_640 = avg("s640")
+avgs = [("origin", "原图直送", avg_origin, 0),
+        ("s1024", "1024", avg_1024, 1024),
+        ("s896", "896", avg_896, 896),
+        ("s768", "768", avg_768, 768),
+        ("s640", "640", avg_640, 640)]
+
+# 速度色阶：以全部耗时的 min-max 映射颜色（绿→黄→红）
+all_t = sorted([r["elapsed"] for r in results if r["ok"] and r["key"] != "girl2_flower_origin"])
+tmin, tmax = all_t[0], all_t[-1]
+def speed_color(t):
+    if tmax == tmin:
+        return "#16a34a"
+    ratio = (t - tmin) / (tmax - tmin)  # 0=最快(绿) 1=最慢(红)
+    if ratio < 0.33:
+        return "#16a34a"  # 绿
+    elif ratio < 0.66:
+        return "#f59e0b"  # 橙
+    else:
+        return "#dc2626"  # 红
+
+# 表格行
+rows_html = []
+for img in IMAGES:
+    for style_key, style_cn in STYLES:
+        # 原图格
+        orig_cell = (f'<td class="cell orig">'
+                     f'<div class="thumb"><img loading="lazy" src="orig_{img}.jpg" '
+                     f'onclick="openImg(this.src)" alt="原图"></div>'
+                     f'<div class="meta">📷 原图</div></td>')
+        # 5档格
+        side_cells = []
+        for side_name, side_lbl, side_val in SIDES:
+            r = get(img, style_key, side_name)
+            if r and r["ok"]:
+                col = speed_color(r["elapsed"])
+                cell = (f'<td class="cell">'
+                        f'<div class="thumb"><img loading="lazy" src="{r["key"]}.jpg" '
+                        f'onclick="openImg(this.src)" alt="{html.escape(r["key"])}"></div>'
+                        f'<div class="meta"><b style="color:{col}">{r["elapsed"]}s</b> · '
+                        f'{r["out_w"]}×{r["out_h"]}</div></td>')
+            elif r:
+                cell = (f'<td class="cell fail"><div class="thumb noimg">❌</div>'
+                        f'<div class="meta err">{html.escape(r["err"][:30])}</div></td>')
+            else:
+                cell = '<td class="cell fail"><div class="thumb noimg">—</div></td>'
+            side_cells.append(cell)
+        row_label = (f'<td class="rowlabel">'
+                     f'<div class="rimg">{html.escape(img)}</div>'
+                     f'<div class="rs">{html.escape(style_cn)}</div>'
+                     f'<div class="rl">长边 {LONGSIDE[img]}</div></td>')
+        rows_html.append("<tr>" + row_label + orig_cell + "".join(side_cells) + "</tr>")
+
+# 顶部平均耗时卡
+def stat_card(lbl, val, col, sub=""):
+    return (f'<div class="stat" style="border-left:3px solid {col}">'
+            f'<div class="num" style="color:{col}">{val:.1f}s</div>'
+            f'<div class="lbl">{lbl}{sub}</div></div>')
+
+stat_cards = "".join([
+    stat_card("原图直送", avg_origin, "#dc2626", "<br><span class='dim'>排除冷启动</span>"),
+    stat_card("1024", avg_1024, "#f59e0b"),
+    stat_card("896 (默认)", avg_896, "#2563eb"),
+    stat_card("768", avg_768, "#16a34a"),
+    stat_card("640", avg_640, "#0d9488"),
+])
+
+html_doc = f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>接口2 分辨率对比测试 v2</title>
+<style>
+  * {{ box-sizing: border-box; margin: 0; padding: 0; }}
+  body {{ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "PingFang SC", "Microsoft YaHei", sans-serif; background: #f3f4f6; color: #1f2937; line-height: 1.5; padding: 16px; }}
+  .wrap {{ max-width: 100%; margin: 0 auto; }}
+  h1 {{ font-size: 22px; margin-bottom: 4px; }}
+  .sub {{ color: #6b7280; font-size: 12px; margin-bottom: 16px; }}
+  .stats {{ display: flex; gap: 10px; margin-bottom: 16px; flex-wrap: wrap; }}
+  .stat {{ background: #fff; border-radius: 8px; padding: 12px 14px; box-shadow: 0 1px 3px rgba(0,0,0,.06); flex: 1; min-width: 110px; }}
+  .stat .num {{ font-size: 22px; font-weight: 700; }}
+  .stat .lbl {{ font-size: 11px; color: #6b7280; margin-top: 2px; }}
+  .stat .dim {{ color: #9ca3af; font-size: 10px; }}
+  .summary-bar {{ background: #fff; border-radius: 8px; padding: 12px 16px; margin-bottom: 16px; box-shadow: 0 1px 3px rgba(0,0,0,.06); font-size: 13px; }}
+  .summary-bar b {{ color: #dc2626; }}
+  .table-wrap {{ overflow-x: auto; background: #fff; border-radius: 10px; box-shadow: 0 1px 4px rgba(0,0,0,.07); }}
+  table {{ border-collapse: collapse; min-width: 100%; }}
+  th, td {{ vertical-align: top; }}
+  thead th {{ position: sticky; top: 0; background: #f9fafb; z-index: 2; padding: 10px 8px; font-size: 12px; color: #374151; border-bottom: 2px solid #e5e7eb; text-align: center; }}
+  thead th.orig-h {{ background: #fef3c7; }}
+  tbody td {{ border-bottom: 1px solid #f3f4f6; padding: 8px; }}
+  tbody tr:hover {{ background: #f9fafb; }}
+  td.rowlabel {{ text-align: left; padding: 8px 12px; position: sticky; left: 0; background: #fff; z-index: 1; min-width: 90px; box-shadow: 2px 0 4px rgba(0,0,0,.04); }}
+  tbody tr:hover td.rowlabel {{ background: #f9fafb; }}
+  .rimg {{ font-weight: 700; font-size: 14px; }}
+  .rs {{ font-size: 12px; color: #6b7280; }}
+  .rl {{ font-size: 10px; color: #9ca3af; margin-top: 2px; }}
+  .cell {{ width: 180px; min-width: 180px; text-align: center; }}
+  .cell.orig {{ width: 180px; background: #fffbeb; }}
+  .thumb {{ background: #1f2937; border-radius: 6px; overflow: hidden; margin-bottom: 4px; cursor: zoom-in; }}
+  .thumb img {{ width: 100%; height: 240px; object-fit: contain; display: block; }}
+  .thumb.noimg {{ color: #d1d5db; font-size: 16px; padding: 100px 0; text-align: center; }}
+  .meta {{ font-size: 11px; color: #6b7280; }}
+  .meta.err {{ color: #dc2626; }}
+  .legend {{ display: inline-flex; gap: 12px; font-size: 11px; color: #6b7280; margin-left: 12px; }}
+  .legend span {{ display: inline-flex; align-items: center; gap: 4px; }}
+  .legend i {{ width: 10px; height: 10px; border-radius: 2px; display: inline-block; }}
+  .overlay {{ display: none; position: fixed; inset: 0; background: rgba(0,0,0,.92); z-index: 999; justify-content: center; align-items: center; cursor: zoom-out; padding: 24px; }}
+  .overlay.active {{ display: flex; }}
+  .overlay img {{ max-width: 96%; max-height: 96%; object-fit: contain; border-radius: 4px; }}
+</style>
+</head>
+<body>
+<div class="wrap">
+  <h1>💄 接口2 生发 · 5档分辨率对比报告</h1>
+  <p class="sub">POST /api/v1/hair/grow · female · 5 图 × 3 发型(花瓣/心形/波浪) × 5 档分辨率 = 75 次 · 串行 · 4090 (24G)</p>
+
+  <div class="stats">
+    <div class="stat" style="border-left:3px solid #16a34a"><div class="num" style="color:#16a34a">{ok}/{total}</div><div class="lbl">成功 / 总数</div></div>
+    {stat_cards}
+  </div>
+
+  <div class="summary-bar">
+    📊 <b>结论：</b>耗时随送图分辨率单调下降。<b>大图(qwer/asdf 长边~1670) 原图直送需 ~27-30s，是 896 档(10s) 的近 3 倍</b>；
+    中小图(girl2/girl5/girl7 长边 767-1082)各档差异较小(6-15s)。
+    <b>4090 24G 全程无 OOM</b>，75/75 成功。<b>画质对比</b>见下表（横向滑动），点击任意图可放大。
+    <span class="legend">
+      <span><i style="background:#16a34a"></i>快(&lt;{tmin+ (tmax-tmin)*0.33:.0f}s)</span>
+      <span><i style="background:#f59e0b"></i>中等</span>
+      <span><i style="background:#dc2626"></i>慢(&gt;{tmin+ (tmax-tmin)*0.66:.0f}s)</span>
+    </span>
+  </div>
+
+  <div class="table-wrap">
+    <table>
+      <thead>
+        <tr>
+          <th>图 · 发型</th>
+          <th class="orig-h">📷 原图</th>
+          <th>原图直送 (0)<br><span class="dim">不缩放</span></th>
+          <th>1024</th>
+          <th>896<br><span class="dim">默认</span></th>
+          <th>768</th>
+          <th>640</th>
+        </tr>
+      </thead>
+      <tbody>
+        {"".join(rows_html)}
+      </tbody>
+    </table>
+  </div>
+</div>
+<div class="overlay" id="overlay" onclick="this.classList.remove('active')"><img id="overlayImg" src=""></div>
+<script>
+function openImg(src) {{
+  document.getElementById('overlayImg').src = src;
+  document.getElementById('overlay').classList.add('active');
+}}
+</script>
+</body>
+</html>
+"""
+with open(REPORT, "w") as f:
+    f.write(html_doc)
+print(f"已生成: {REPORT}")

image/res_test/report-server-v2.service

@@ -0,0 +1,15 @@
+[Unit]
+Description=接口2 5档分辨率对比报告 v2 (8849)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=ubuntu
+WorkingDirectory=/home/ubuntu/hair/image/res_test/out
+ExecStart=/home/ubuntu/miniconda3/envs/my_hair/bin/python -m http.server 8849 --bind 0.0.0.0
+Restart=on-failure
+RestartSec=5
+
+[Install]
+WantedBy=multi-user.target

image/wave_test/batch_test.py

@@ -0,0 +1,143 @@
+#!/usr/bin/env python3
+"""接口2 female wave发型 分辨率对比测试 v3: 21图 × 5档 = 105次。
+串行执行，记录耗时与成败，结果图按 图_档位 命名保存。支持断点续跑。
+"""
+import base64, csv, json, os, time, io
+import requests
+from PIL import Image
+
+API = "http://127.0.0.1:8187/api/v1/hair/grow"
+TOKEN = "dev-shared-secret-2026"
+TIMEOUT = 600
+OUT = "/home/ubuntu/hair/image/wave_test/out"
+PROGRESS = "/home/ubuntu/hair/image/wave_test/progress.json"
+
+IMG_DIR = "/home/ubuntu/hair/image"
+# 21张图：19张girl_img + asdf + qwer
+IMAGES = []
+for f in sorted(os.listdir(os.path.join(IMG_DIR, "girl_img"))):
+    if f.lower().endswith((".jpg", ".jpeg", ".png")):
+        IMAGES.append((os.path.splitext(f)[0], os.path.join(IMG_DIR, "girl_img", f)))
+IMAGES.append(("asdf", os.path.join(IMG_DIR, "asdf.jpg")))
+IMAGES.append(("qwer", os.path.join(IMG_DIR, "qwer.jpg")))
+
+# wave = female hair_style 5
+STYLE_IDX = 5
+# 5档: 原图(0) / 1024 / 896 / 768 / 640
+SIDES = [
+    ("origin", 0),
+    ("s1024",  1024),
+    ("s896",   896),
+    ("s768",   768),
+    ("s640",   640),
+]
+
+def load_progress():
+    if os.path.exists(PROGRESS):
+        try:
+            return json.load(open(PROGRESS))
+        except Exception:
+            pass
+    return {"done": [], "results": []}
+
+def save_progress(prog):
+    json.dump(prog, open(PROGRESS, "w"), ensure_ascii=False, indent=1)
+
+def run_one(img_name, img_path, side_name, side_val):
+    key = f"{img_name}_{side_name}"
+    with open(img_path, "rb") as f:
+        img_b64 = base64.b64encode(f.read()).decode()
+    data = {
+        "image_base64": "data:image/jpeg;base64," + img_b64,
+        "gender": "female",
+        "hair_style": str(STYLE_IDX),
+        "redraw_max_side": str(side_val),
+    }
+    t0 = time.time()
+    rec = {"key": key, "img": img_name, "side": side_name, "side_val": side_val,
+           "ok": False, "elapsed": 0.0, "err": "", "out_w": 0, "out_h": 0, "bytes": 0}
+    try:
+        r = requests.post(API, data=data, headers={"X-Internal-Token": TOKEN}, timeout=TIMEOUT)
+        rec["elapsed"] = round(time.time() - t0, 1)
+        d = r.json()
+        if d.get("code") != 0:
+            rec["err"] = f"code={d.get('code')} {d.get('message','')}"[:200]
+            return rec
+        results = (d.get("data") or {}).get("results") or []
+        if not results:
+            rec["err"] = "空结果"
+            return rec
+        it = results[0]
+        grown = it.get("grown_image_base64")
+        if not grown:
+            rec["err"] = "无生发图(重绘失败/OOM?)"
+            return rec
+        raw = base64.b64decode(grown)
+        im = Image.open(io.BytesIO(raw))
+        rec["out_w"], rec["out_h"] = im.size
+        out_path = f"{OUT}/{key}.jpg"
+        with open(out_path, "wb") as fo:
+            fo.write(raw)
+        rec["ok"] = True
+        rec["bytes"] = len(raw)
+    except requests.exceptions.Timeout:
+        rec["elapsed"] = round(time.time() - t0, 1)
+        rec["err"] = f"超时(>{TIMEOUT}s)"
+    except Exception as e:
+        rec["elapsed"] = round(time.time() - t0, 1)
+        rec["err"] = f"{type(e).__name__}: {str(e)[:180]}"
+    return rec
+
+def main():
+    prog = load_progress()
+    done_keys = set(prog["done"])
+    total = len(IMAGES) * len(SIDES)
+    print(f"=== 接口2 female wave 分辨率对比测试 v3 ===")
+    print(f"矩阵: {len(IMAGES)}图 × {len(SIDES)}档 = {total} 次 (发型固定 wave)")
+    print(f"已跳过 {len(done_keys)} 个已完成项\n")
+
+    idx = 0
+    for img_name, img_path in IMAGES:
+        for side_name, side_val in SIDES:
+            idx += 1
+            key = f"{img_name}_{side_name}"
+            if key in done_keys:
+                print(f"[{idx}/{total}] ⏭  跳过 {key}")
+                continue
+            print(f"[{idx}/{total}] ▶ {key} (side={side_val})...", end=" ", flush=True)
+            rec = run_one(img_name, img_path, side_name, side_val)
+            prog["results"].append(rec)
+            prog["done"].append(key)
+            save_progress(prog)
+            if rec["ok"]:
+                print(f"✅ {rec['elapsed']}s  {rec['out_w']}x{rec['out_h']} ({rec['bytes']}B)")
+            else:
+                print(f"❌ {rec['elapsed']}s  {rec['err']}")
+            time.sleep(2)
+
+    print("\n" + "=" * 70)
+    print("汇总")
+    print("=" * 70)
+    write_report(prog["results"])
+    print(f"\n结果图: {OUT}/")
+    print(f"CSV: {OUT}/report.csv   JSON: {OUT}/report.json")
+
+def write_report(results):
+    with open(f"{OUT}/report.csv", "w", newline="") as f:
+        w = csv.writer(f)
+        w.writerow(["img", "side", "side_val", "ok", "elapsed_s", "out_w", "out_h", "bytes", "err"])
+        for r in results:
+            w.writerow([r["img"], r["side"], r["side_val"], r["ok"],
+                        r["elapsed"], r["out_w"], r["out_h"], r["bytes"], r["err"]])
+    json.dump(results, open(f"{OUT}/report.json", "w"), ensure_ascii=False, indent=1)
+
+    # 各档平均耗时
+    print("\n--- 各档平均耗时（秒）---")
+    for side_name, side_val in SIDES:
+        ts = [r["elapsed"] for r in results if r["side"] == side_name and r["ok"]]
+        if ts:
+            avg = sum(ts) / len(ts)
+            print(f"  {side_name:8s} (={side_val:>4}): 平均 {avg:5.1f}s  [{min(ts):.1f}~{max(ts):.1f}]  成功 {len(ts)}")
+
+if __name__ == "__main__":
+    main()

image/wave_test/gen_report.py

@@ -0,0 +1,176 @@
+#!/usr/bin/env python3
+"""生成 v3 wave发型 分辨率对比报告：每行=原图+5档，21行；含各档耗时统计。"""
+import json, os, html
+
+OUT = "/home/ubuntu/hair/image/wave_test/out"
+REPORT = os.path.join(OUT, "report.html")
+results = json.load(open(os.path.join(OUT, "report.json")))
+
+SIDES = [("origin", "原图直送", 0), ("s1024", "1024", 1024),
+         ("s896", "896", 896), ("s768", "768", 768), ("s640", "640", 640)]
+
+# 图片顺序（与测试脚本一致）：girl_img 排序 + asdf + qwer
+IMG_DIR = "/home/ubuntu/hair/image"
+IMAGES = []
+for f in sorted(os.listdir(os.path.join(IMG_DIR, "girl_img"))):
+    if f.lower().endswith((".jpg", ".jpeg", ".png")):
+        IMAGES.append(os.path.splitext(f)[0])
+IMAGES.append("asdf")
+IMAGES.append("qwer")
+
+def get(img, side):
+    for r in results:
+        if r["img"] == img and r["side"] == side:
+            return r
+    return None
+
+# 统计
+total = len(results)
+ok = sum(1 for r in results if r["ok"])
+
+# 各档统计
+def avg(side):
+    ts = [r["elapsed"] for r in results if r["side"] == side and r["ok"]]
+    return sum(ts)/len(ts) if ts else 0
+avgs = {s[0]: avg(s[0]) for s in SIDES}
+
+# 速度色阶
+all_t = sorted(r["elapsed"] for r in results if r["ok"])
+tmin, tmax = all_t[0], all_t[-1]
+def speed_color(t):
+    if tmax == tmin: return "#16a34a"
+    ratio = (t - tmin) / (tmax - tmin)
+    if ratio < 0.33: return "#16a34a"
+    elif ratio < 0.66: return "#f59e0b"
+    else: return "#dc2626"
+
+# 表格行
+rows_html = []
+for img in IMAGES:
+    orig_cell = (f'<td class="cell orig">'
+                 f'<div class="thumb"><img loading="lazy" src="orig_{img}.jpg" '
+                 f'onclick="openImg(this.src)" alt="原图"></div>'
+                 f'<div class="meta">📷 原图</div></td>')
+    side_cells = []
+    for side_name, side_lbl, side_val in SIDES:
+        r = get(img, side_name)
+        if r and r["ok"]:
+            col = speed_color(r["elapsed"])
+            cell = (f'<td class="cell">'
+                    f'<div class="thumb"><img loading="lazy" src="{r["key"]}.jpg" '
+                    f'onclick="openImg(this.src)" alt="{html.escape(r["key"])}"></div>'
+                    f'<div class="meta"><b style="color:{col}">{r["elapsed"]}s</b></div></td>')
+        elif r:
+            cell = (f'<td class="cell fail"><div class="thumb noimg">❌</div>'
+                    f'<div class="meta err">{html.escape(r["err"][:30])}</div></td>')
+        else:
+            cell = '<td class="cell fail"><div class="thumb noimg">—</div></td>'
+        side_cells.append(cell)
+    rows_html.append("<tr>" + orig_cell + "".join(side_cells) + "</tr>")
+
+# 各档统计卡
+def stat_card(lbl, val, col, rng=""):
+    return (f'<div class="stat" style="border-left:3px solid {col}">'
+            f'<div class="num" style="color:{col}">{val:.1f}s</div>'
+            f'<div class="lbl">{lbl}{rng}</div></div>')
+
+stat_cards = "".join([
+    stat_card("原图直送(0)", avgs["origin"], "#dc2626"),
+    stat_card("1024", avgs["s1024"], "#f59e0b"),
+    stat_card("896", avgs["s896"], "#2563eb"),
+    stat_card("768", avgs["s768"], "#16a34a"),
+    stat_card("640", avgs["s640"], "#0d9488"),
+])
+
+html_doc = f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>wave发型 5档分辨率对比</title>
+<style>
+  * {{ box-sizing: border-box; margin: 0; padding: 0; }}
+  body {{ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "PingFang SC", "Microsoft YaHei", sans-serif; background: #f3f4f6; color: #1f2937; line-height: 1.5; padding: 16px; }}
+  .wrap {{ max-width: 100%; margin: 0 auto; }}
+  h1 {{ font-size: 22px; margin-bottom: 4px; }}
+  .sub {{ color: #6b7280; font-size: 12px; margin-bottom: 16px; }}
+  .stats {{ display: flex; gap: 10px; margin-bottom: 16px; flex-wrap: wrap; }}
+  .stat {{ background: #fff; border-radius: 8px; padding: 12px 14px; box-shadow: 0 1px 3px rgba(0,0,0,.06); flex: 1; min-width: 110px; }}
+  .stat .num {{ font-size: 22px; font-weight: 700; }}
+  .stat .lbl {{ font-size: 11px; color: #6b7280; margin-top: 2px; }}
+  .summary-bar {{ background: #fff; border-radius: 8px; padding: 12px 16px; margin-bottom: 16px; box-shadow: 0 1px 3px rgba(0,0,0,.06); font-size: 13px; }}
+  .summary-bar b {{ color: #dc2626; }}
+  .legend {{ display: inline-flex; gap: 12px; font-size: 11px; color: #6b7280; margin-left: 12px; }}
+  .legend span {{ display: inline-flex; align-items: center; gap: 4px; }}
+  .legend i {{ width: 10px; height: 10px; border-radius: 2px; display: inline-block; }}
+  .table-wrap {{ overflow-x: auto; background: #fff; border-radius: 10px; box-shadow: 0 1px 4px rgba(0,0,0,.07); }}
+  table {{ border-collapse: collapse; min-width: 100%; }}
+  th, td {{ vertical-align: top; }}
+  thead th {{ position: sticky; top: 0; background: #f9fafb; z-index: 2; padding: 10px 8px; font-size: 12px; color: #374151; border-bottom: 2px solid #e5e7eb; text-align: center; }}
+  thead th.orig-h {{ background: #fef3c7; }}
+  tbody td {{ border-bottom: 1px solid #f3f4f6; padding: 8px; }}
+  tbody tr:hover {{ background: #f9fafb; }}
+  .cell {{ width: 200px; min-width: 200px; text-align: center; }}
+  .cell.orig {{ background: #fffbeb; }}
+  .thumb {{ background: #1f2937; border-radius: 6px; overflow: hidden; margin-bottom: 4px; cursor: zoom-in; }}
+  .thumb img {{ width: 100%; height: 260px; object-fit: contain; display: block; }}
+  .thumb.noimg {{ color: #d1d5db; font-size: 16px; padding: 110px 0; text-align: center; }}
+  .meta {{ font-size: 11px; color: #6b7280; }}
+  .meta.err {{ color: #dc2626; }}
+  .overlay {{ display: none; position: fixed; inset: 0; background: rgba(0,0,0,.92); z-index: 999; justify-content: center; align-items: center; cursor: zoom-out; padding: 24px; }}
+  .overlay.active {{ display: flex; }}
+  .overlay img {{ max-width: 96%; max-height: 96%; object-fit: contain; border-radius: 4px; }}
+</style>
+</head>
+<body>
+<div class="wrap">
+  <h1>💇 wave发型 · 5档分辨率对比报告</h1>
+  <p class="sub">POST /api/v1/hair/grow · female · wave(波浪) · 21 图 × 5 档分辨率 = 105 次 · 串行 · 4090 (24G)</p>
+
+  <div class="stats">
+    <div class="stat" style="border-left:3px solid #16a34a"><div class="num" style="color:#16a34a">{ok}/{total}</div><div class="lbl">成功 / 总数</div></div>
+    {stat_cards}
+  </div>
+
+  <div class="summary-bar">
+    📊 <b>结论：</b>耗时随分辨率单调下降。<b>大图(asdf 1666/qwer 1678) 原图直送需 24~26s，是 1024 档(11s) 的 2.3 倍</b>；
+    中小图(≤1024) 各档差异较小(6~13s)，因小图本身不触发缩图。
+    <b>4090 24G 全程无 OOM</b>，105/105 成功。<b>画质对比</b>见下表（横向滑动），点击任意图可放大。
+    <span class="legend">
+      <span><i style="background:#16a34a"></i>快(&lt;{(tmin+(tmax-tmin)*0.33):.0f}s)</span>
+      <span><i style="background:#f59e0b"></i>中等</span>
+      <span><i style="background:#dc2626"></i>慢(&gt;{(tmin+(tmax-tmin)*0.66):.0f}s)</span>
+    </span>
+  </div>
+
+  <div class="table-wrap">
+    <table>
+      <thead>
+        <tr>
+          <th class="orig-h">📷 原图</th>
+          <th>原图直送 (0)<br><span class="dim">不缩放</span></th>
+          <th>1024</th>
+          <th>896<br><span class="dim">默认</span></th>
+          <th>768</th>
+          <th>640</th>
+        </tr>
+      </thead>
+      <tbody>
+        {"".join(rows_html)}
+      </tbody>
+    </table>
+  </div>
+</div>
+<div class="overlay" id="overlay" onclick="this.classList.remove('active')"><img id="overlayImg" src=""></div>
+<script>
+function openImg(src) {{
+  document.getElementById('overlayImg').src = src;
+  document.getElementById('overlay').classList.add('active');
+}}
+</script>
+</body>
+</html>
+"""
+with open(REPORT, "w") as f:
+    f.write(html_doc)
+print(f"已生成: {REPORT}")

image/wave_test/report-server-wave.service

@@ -0,0 +1,15 @@
+[Unit]
+Description=wave发型5档分辨率对比报告 (8850)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=ubuntu
+WorkingDirectory=/home/ubuntu/hair/image/wave_test/out
+ExecStart=/home/ubuntu/miniconda3/envs/my_hair/bin/python -m http.server 8850 --bind 0.0.0.0
+Restart=on-failure
+RestartSec=5
+
+[Install]
+WantedBy=multi-user.target

local_test/app.py

@@ -206,7 +206,7 @@ def generate():
             return jsonify({"error": msg}), 400
         image_file = request.files["image"]
         mask_file = request.files["mask"]
-        prompt_text = request.form.get("prompt", "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
+        prompt_text = request.form.get("prompt", "填充遮罩区域的头发")
         log.info(
             "收到请求: image=%s mask=%s prompt=%r",
             image_file.filename, mask_file.filename, prompt_text,

local_test/bench.py

@@ -27,7 +27,7 @@ def prep_and_upload():
 
 
 def run_once(fname, model, dtype, steps):
-    wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
+    wf = A.build_workflow(fname, "填充遮罩区域的头发")
     wf["16"]["inputs"]["unet_name"] = model
     wf["16"]["inputs"]["weight_dtype"] = dtype
     wf["1"]["inputs"]["steps"] = steps

local_test/bench2.py

@@ -33,7 +33,7 @@ def upload(scale=1.0):
 
 
 def run(fname, steps):
-    wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
+    wf = A.build_workflow(fname, "填充遮罩区域的头发")
     wf["16"]["inputs"]["unet_name"] = MODEL
     wf["16"]["inputs"]["weight_dtype"] = DTYPE
     wf["1"]["inputs"]["steps"] = steps

local_test/bench_quality.py

@@ -30,7 +30,7 @@ SEED = 123456789
 imgs = []
 labels = []
 for steps in [2, 3, 4, 6]:
-    wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", seed=SEED)
+    wf = A.build_workflow(fname, "填充遮罩区域的头发", seed=SEED)
     wf["16"]["inputs"]["unet_name"] = MODEL
     wf["16"]["inputs"]["weight_dtype"] = DTYPE
     wf["1"]["inputs"]["steps"] = steps

local_test/index.html

@@ -55,7 +55,7 @@ button { padding: 10px 24px; border: none; border-radius: 6px; cursor: pointer;
         </div>
         <div class="controls" style="margin-top:16px">
             <label>提示词:</label>
-            <input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜">
+            <input type="text" id="promptInput" value="填充遮罩区域的头发">
         </div>
         <div style="text-align:center; margin-top:16px">
             <button class="btn-generate" id="generateBtn" disabled>🚀 生成</button>

local_test/test_api.py

@@ -25,7 +25,7 @@ resp = requests.post(
         "image": ("original.jpg", img_data, "image/jpeg"),
         "mask": ("mask.png", mask_data, "image/png"),
     },
-    data={"prompt": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"},
+    data={"prompt": "填充遮罩区域的头发"},
     timeout=600,
 )
 

static/test_interface12.html

@@ -69,7 +69,7 @@
     </div>
     <div class="upload-row" style="margin-top:10px">
       <label style="font-size:13px;font-weight:600;white-space:nowrap">重绘提示词</label>
-      <input type="text" id="localTestPrompt" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
+      <input type="text" id="localTestPrompt" value="填充遮罩区域的头发" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
     </div>
     <div class="upload-row" style="margin-top:10px">
       <label style="font-size:13px;font-weight:600;white-space:nowrap">X-Internal-Token</label>
@@ -354,7 +354,7 @@ function dataUriToBlob(dataUri) {
 
 async function runLocalRedraw() {
   if (!_finalDataUri || !_maskDataUri) { setStatus('缺少 final 或遮罩，请先生成', 'error'); return; }
-  const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜';
+  const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发';
   const btn = $('redrawBtn');
   btn.disabled = true; btn.textContent = '⏳ 重绘中...';
   flog('===== 调后端重绘 =====', 'info');

static/test_interface12_final.html

@@ -56,7 +56,7 @@
     </div>
     <div class="upload-row" style="margin-top:10px">
       <label style="font-size:13px;font-weight:600;white-space:nowrap">重绘提示词</label>
-      <input type="text" id="localTestPrompt" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
+      <input type="text" id="localTestPrompt" value="填充遮罩区域的头发" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
     </div>
     <div class="params">
       <div class="pf">
@@ -169,7 +169,7 @@ async function submitTest() {
 
 async function runLocalRedraw() {
   if (!_finalDataUri || !_maskDataUri) { setStatus('缺少 final 或遮罩，请先生成', 'error'); return; }
-  const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜';
+  const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发';
   const btn = $('redrawBtn');
   btn.disabled = true; btn.textContent = '⏳ 重绘中...';
 

static/test_interface2.html

@@ -101,13 +101,23 @@
             <option value="false">⬜ 关闭 — 空遮罩，不烧模板线</option>
           </select>
         </div>
+        <div class="form-group" id="redrawSideGroup">
+          <label>重绘分辨率</label>
+          <select id="redrawMaxSide" title="仅 Female 生效：图长边超过该值才缩到该值，不超过则原图直送。默认1024=大于1024压到1024，小图保持原分辨率">
+            <option value="" selected>默认 1024（&gt;1024 才缩）</option>
+            <option value="0">0 — 永不缩图（原图直送）</option>
+            <option value="1280">1280（更高清，慢）</option>
+            <option value="768">768（快）</option>
+            <option value="640">640（最快，糊）</option>
+          </select>
+        </div>
         <button class="btn btn-primary" id="submitBtn" onclick="submitTest()">🚀 提交</button>
         <button class="btn btn-outline btn-sm" onclick="clearResults()">清除</button>
       </div>
       <div class="hint">JPG/PNG &nbsp;|&nbsp; 生发图生成较慢（数十秒~数分钟），请耐心等待</div>
       <div style="margin-top:10px;display:flex;align-items:center;gap:8px">
         <label style="font-size:13px;font-weight:600;color:#374151;white-space:nowrap">💬 提示词</label>
-        <input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
+        <input type="text" id="promptInput" value="填充遮罩区域的头发" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
       </div>
       <div id="statusBar" class="status hidden"></div>
     </div>
@@ -155,6 +165,11 @@ async function submitTest() {
   fd.append('hair_style', checked.join(','));
   fd.append('use_mask', $('useMask').value);
   fd.append('prompt', $('promptInput').value);
+  // 重绘分辨率：仅 female 传给后端（male 路径不接受此参数）
+  if ($('gender').value === 'female') {
+    const side = $('redrawMaxSide').value;
+    if (side !== '') fd.append('redraw_max_side', side);  // 空串=不传→后端默认896
+  }
   const _reqStart = performance.now();
   try {
     const r = await fetch(API_BASE + '/api/v1/hair/grow', { method:'POST', headers:{ 'X-Internal-Token': 'dev-shared-secret-2026' }, body:fd });
@@ -258,6 +273,8 @@ function onGenderChange() {
     lb.appendChild(document.createTextNode(' ' + s.label));
     div.appendChild(lb);
   });
+  // 重绘分辨率选项仅 female 生效：male 时隐藏
+  $('redrawSideGroup').style.display = (g === 'female') ? '' : 'none';
 }
 
 function selectAllHair(select) {

static/test_interface3.html

@@ -94,7 +94,7 @@
       </div>
       <div class="upload-group" style="margin-top:14px">
         <div class="label">💬 提示词（prompt）</div>
-        <input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="width:100%;padding:8px 12px;border:1px solid #d1d5db;border-radius:8px;font-size:14px;max-width:500px">
+        <input type="text" id="promptInput" value="填充遮罩区域的头发" style="width:100%;padding:8px 12px;border:1px solid #d1d5db;border-radius:8px;font-size:14px;max-width:500px">
       </div>
       <div style="margin-top:14px;display:flex;gap:12px;align-items:center">
         <button class="btn btn-primary" id="submitBtn" onclick="submitTest()">🚀 提交</button>

static/test_interface7.html

@@ -104,7 +104,7 @@
       <div class="hint">JPG/PNG &nbsp;|&nbsp; 生发图生成较慢（数十秒~数分钟），请耐心等待 &nbsp;|&nbsp; 工作流: add_hair2.json</div>
       <div style="margin-top:10px;display:flex;align-items:center;gap:8px">
         <label style="font-size:13px;font-weight:600;color:#374151;white-space:nowrap">💬 提示词</label>
-        <input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
+        <input type="text" id="promptInput" value="填充遮罩区域的头发" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
       </div>
       <div id="statusBar" class="status hidden"></div>
     </div>