feat(接口2): 支持动态切换Flux模型+分辨率 + 模型对比测试脚本

代码改动:
- comfyui.py: run() 新增 unet_name 参数，提交前自动改写模型节点
  (.gguf→UnetLoaderGGUF, .safetensors→UNETLoader)，并按模型自动同步
  文本编码器(4b→qwen_3_4b, 9b→qwen_3_8b)，避免切换时维度不匹配
- redraw.py: run_redraw() 透传 unet_name
- service.py: generate_grow_results_swap/generate_grow_results 支持
  redraw_max_side(分辨率参数化) 和 unet_name 透传
- app.py: 接口2 新增 flux_model/redraw_max_side 两个 Form 参数(男女路径都加)
- test_interface2.html: 新增 Flux模型/压图长边 下拉选择器
- add_hair.json/0716add-hair-api.json: 工作流默认模型改为 9b

测试脚本:
- benchmark_matrix.py: 4模型×3分辨率×3图×3次 矩阵测试
- benchmark_hairstyle.py: 3图×5发型×10组合 发型对比测试
- benchmark_report.py/benchmark_hairstyle_report.py: HTML报告生成

清理:
- .gitignore: 排除 benchmark_out/、报告HTML、gateway.log、*.bak.*
- 移除 gateway.log 的 git 跟踪

hairline/service.py

@@ -54,21 +54,26 @@ _REDRAW_PROMPT = os.getenv("REDRAW_PROMPT", "填充遮罩区域的头发，皮
 # 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。
 _REDRAW_MAX_SIDE = int(os.getenv("REDRAW_MAX_SIDE", "896"))
 
-def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0):
+def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0,
+                       max_side=None, unet_name=None):
     """直接调 ComfyUI 重绘（替代原 local_test HTTP 服务）。
 
     传 final 图 + 纯红遮罩 PNG，返回重绘后的 PNG bytes。
     失败抛异常（调用方负责 try/except 跳过）。
+
+    max_side：送 ComfyUI 前长边压到多少像素，None 用全局默认 _REDRAW_MAX_SIDE。
+    unet_name：非 None 时切换 Flux 模型，None 用工作流内置默认。
     """
     from .redraw import run_redraw
+    eff_side = _REDRAW_MAX_SIDE if max_side is None else max_side
     img = cv2.imdecode(np.frombuffer(image_png_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
     scale = 1.0
     orig_w = orig_h = 0
     if img is not None:
         orig_h, orig_w = img.shape[:2]
         m = max(orig_h, orig_w)
-        if _REDRAW_MAX_SIDE > 0 and m > _REDRAW_MAX_SIDE:
-            scale = _REDRAW_MAX_SIDE / float(m)
+        if eff_side > 0 and m > eff_side:
+            scale = eff_side / float(m)
             nw, nh = max(1, round(orig_w * scale)), max(1, round(orig_h * scale))
             msk = cv2.imdecode(np.frombuffer(mask_png_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
             img_s = cv2.resize(img, (nw, nh), interpolation=cv2.INTER_AREA)
@@ -76,10 +81,10 @@ def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0):
             image_png_bytes = cv2.imencode(".png", img_s)[1].tobytes()
             mask_png_bytes = cv2.imencode(".png", msk_s)[1].tobytes()
             logger.info("接口2女 缩图送 Comfy: %dx%d → %dx%d (max_side=%d)",
-                        orig_w, orig_h, nw, nh, _REDRAW_MAX_SIDE)
+                        orig_w, orig_h, nw, nh, eff_side)
     # front=True：接口2 时延敏感，插到 ComfyUI 队列最前，避免排在接口3/5 的批量任务后面
     out = run_redraw(image_png_bytes, mask_png_bytes, timeout=timeout,
-                     prompt=_REDRAW_PROMPT, front=True)
+                     prompt=_REDRAW_PROMPT, front=True, unet_name=unet_name)
     if scale < 1.0 and out:
         out = _upscale_png_to(out, orig_w, orig_h)
     return out
@@ -200,7 +205,8 @@ def generate_previews(image_bgr: np.ndarray, gender: str):
 
 def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = True,
                          prompt: str = None, hair_styles: list[int] | None = None,
-                         workflow_path: str | None = None):
+                         workflow_path: str | None = None,
+                         unet_name: str | None = None):
     """指定发际线类型：发际线透明叠图(白线 RGBA) + 生发图(ComfyUI)。
 
     hair_styles（1-indexed 列表）：指定生成哪几张发际线（按贴图排序）。female: 1..5，male: 1..4。
@@ -236,7 +242,8 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
             compose_comfy_rgba(img_s, msk_s).save(buf, format="PNG", compress_level=1)
             # front=True：接口2 时延敏感，插到 ComfyUI 队列最前
             shared_grown = comfyui.run(buf.getvalue(), prompt=prompt,
-                                       workflow_path=workflow_path, front=True)
+                                       workflow_path=workflow_path, front=True,
+                                       unet_name=unet_name)
             if gsc < 1.0 and shared_grown:
                 shared_grown = _upscale_png_to(shared_grown, w, h)
         except Exception as e:  # noqa: BLE001
@@ -261,7 +268,8 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
                 compose_comfy_rgba(m_s, msk_s).save(buf, format="PNG", compress_level=1)
                 # front=True：接口2 时延敏感，插到 ComfyUI 队列最前
                 grown_png = comfyui.run(buf.getvalue(), prompt=prompt,
-                                        workflow_path=workflow_path, front=True)
+                                        workflow_path=workflow_path, front=True,
+                                        unet_name=unet_name)
                 if gsc < 1.0 and grown_png:
                     grown_png = _upscale_png_to(grown_png, w, h)
             except Exception as e:  # noqa: BLE001  单张失败不拖垮整请求
@@ -273,7 +281,9 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
 
 
 def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | None,
-                               redraw_defaults: dict):
+                               redraw_defaults: dict,
+                               redraw_max_side: int | None = None,
+                               unet_name: str | None = None):
     """接口2 女性专用：发际线透明叠图（同 generate_grow_results）+ 换发型重绘图。
 
     grown 图来源（新流程）：对每个选中发型把 female key 映射到 change_hair 的 chang_* hair_id，
@@ -307,16 +317,17 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
 
     # 重绘管线（swapHair + ComfyUI）统一降分辨率：真实照片 swap(SD WebUI)~5s、blend、ComfyUI
     # 均随分辨率线性下降。overlay 预览仍用全分辨率；grown_png 最后放大回原尺寸。
+    eff_side = _REDRAW_MAX_SIDE if redraw_max_side is None else redraw_max_side
     redraw_img = image_bgr
     hair_mask_redraw = hair_mask_reuse
-    if _REDRAW_MAX_SIDE > 0 and max(h, w) > _REDRAW_MAX_SIDE:
-        redraw_img, _rs = _downscale_max_side(image_bgr, _REDRAW_MAX_SIDE)
+    if eff_side > 0 and max(h, w) > eff_side:
+        redraw_img, _rs = _downscale_max_side(image_bgr, eff_side)
         _nh, _nw = redraw_img.shape[:2]
         if hair_mask_redraw is not None:
             hair_mask_redraw = cv2.resize(hair_mask_reuse.astype(np.uint8), (_nw, _nh),
                                           interpolation=cv2.INTER_NEAREST).astype(bool)
         logger.info("接口2女 管线降分辨率: %dx%d → %dx%d (max_side=%d)",
-                    w, h, _nw, _nh, _REDRAW_MAX_SIDE)
+                    w, h, _nw, _nh, eff_side)
 
     for order, (key, white_path) in items:
         white = load_texture_rgba(white_path)
@@ -349,7 +360,9 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
                     mask_bytes = base64.b64decode(mask_b64)
                     # 后端直接调 ComfyUI 重绘，返回重绘后的 PNG
                     _tr0 = _t.perf_counter()
-                    grown_png = _call_local_redraw(final_bytes, mask_bytes)
+                    grown_png = _call_local_redraw(final_bytes, mask_bytes,
+                                                   max_side=redraw_max_side,
+                                                   unet_name=unet_name)
                     _tr1 = _t.perf_counter()
                     _tm = data.get("timings_ms") or {}
                     logger.info("接口2女 分段计时 type=%s: swapHair管线=%.2fs (mask=%dms swap=%dms blend=%dms), ComfyUI重绘=%.2fs",