修改发型为最终发型
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@@ -655,6 +655,11 @@ async def face_measure_v2(
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- 发际线类型 `hairline_type`（英文 key）
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- 顺序 `order`（本期固定 `1..N`，不排序）
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> **female 走「换发型」模式**：生发图 `grown_image_base64` 由换发型（change_hair）
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> + Flux-2 整帧重绘（= 接口12 final 管线，整帧美颜+整帧重绘）生成，其余参数用固化默认值。
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> **male 仍走原生发（ComfyUI add_hair）管线**。入参与返回结构不变。
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> female 依赖 change_hair 与 ComfyUI(:8188) 均在跑。
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{_image_fields_desc}
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图片同时支持 `multipart/form-data` 文件上传（字段名 `image_file`）。
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@@ -734,10 +739,17 @@ async def hair_grow(
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try:
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from fastapi.concurrency import run_in_threadpool
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from hairline.service import generate_grow_results
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# 预览 + 生发(ComfyUI) 都是阻塞且较慢，放线程池避免卡住事件循环
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items = await run_in_threadpool(generate_grow_results, image, gender, use_mask, prompt, hair_styles)
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# 预览 + 生发/换发型 都是阻塞且较慢，放线程池避免卡住事件循环。
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# female：换发型 + Flux-2 整帧重绘（= 接口12 final 管线）；male：仍走原生发管线。
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if gender == "female":
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from hairline.service import generate_grow_results_swap
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items = await run_in_threadpool(
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generate_grow_results_swap, image, hair_styles, _V2_FINAL_DEFAULTS)
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else:
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from hairline.service import generate_grow_results
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items = await run_in_threadpool(
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generate_grow_results, image, gender, use_mask, prompt, hair_styles)
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if items is None:
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return err(1001, "无法识别人像")
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@@ -20,11 +20,22 @@ from .render import load_ext_mesh, load_texture_rgba, render_hairline_overlay, b
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from .mask import build_inpaint_mask, compose_comfy_rgba, mask_from_curve
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from .marker_detect import detect_marker_hairline, path_to_curve_mask
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import base64
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import io
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import logging
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logger = logging.getLogger("hair.worker")
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# 接口2 女性发型 key → change_hair hair_id（chang_*）映射：换发型+Flux-2 整帧重绘用。
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# 与接口12 final 的 5 型一一对应。
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_FEMALE_KEY_TO_CHANG = {
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"ellipse": "chang_tuoyuan", # 椭圆
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"flower": "chang_huaban", # 花瓣
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"heart": "chang_xinxing", # 心形
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"straight": "chang_zhixian", # 直线
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"wave": "chang_bolang", # 波浪
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}
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_REPO = os.path.dirname(os.path.dirname(__file__))
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_TEXTURE_DIR = os.path.join(_REPO, "hairline_texture")
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_BLACK_TEXTURE_DIR = os.path.join(_REPO, "hairline_texture_black")
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@@ -202,6 +213,60 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
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return results
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def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | None,
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redraw_defaults: dict):
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"""接口2 女性专用：发际线透明叠图（同 generate_grow_results）+ 换发型+Flux-2 整帧重绘图。
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与 generate_grow_results 的差异仅在 grown 图的来源：这里对每个选中发型把 female key 映射到
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change_hair 的 chang_* hair_id，调 face_analysis.hairline_grow.generate_hairline_redraw
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（= 接口12 final 管线，参数用 redraw_defaults），取 `redraw_full`（整帧重绘）作为生发图。
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overlay 仍是发际线曲线透明层（与 generate_grow_results 完全一致）。
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Returns: list[dict] {"hairline_type","order","overlay","grown_png"(jpg bytes 或 None)}；
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无人脸返回 None。单个发型换发型/重绘失败时 grown_png=None，不抛异常。
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"""
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from face_analysis.hairline_grow import generate_hairline_redraw, NoFaceError
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ctx = extract_context(image_bgr)
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if ctx is None:
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return None
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uv, ext_faces = load_ext_mesh()
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textures = get_texture_map()["female"] # [(key, path), ...] 已排序
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if hair_styles is not None:
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items = [(s, textures[s - 1]) for s in hair_styles]
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else:
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items = list(enumerate(textures, start=1))
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results = []
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h, w = image_bgr.shape[:2]
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for order, (key, white_path) in items:
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white = load_texture_rgba(white_path)
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overlay = build_overlay_layer(h, w, ctx["points"], ext_faces, uv, white)
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grown_png = None
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chang_id = _FEMALE_KEY_TO_CHANG.get(key)
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if chang_id is None:
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logger.warning("接口2 换发型：female key=%s 无对应 chang_id，跳过生发图", key)
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else:
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try:
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data = generate_hairline_redraw(image_bgr, chang_id, **redraw_defaults)
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b64 = (data.get("steps") or {}).get("redraw_full_base64") or ""
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if b64.startswith("data:"):
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b64 = b64.split(",", 1)[1]
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grown_png = base64.b64decode(b64) if b64 else None
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if grown_png is None:
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logger.warning("接口2 换发型：type=%s 整帧重绘为空（可能 ComfyUI 未生效）", key)
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except NoFaceError:
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logger.warning("接口2 换发型：type=%s 未检出人脸", key)
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except Exception as e: # noqa: BLE001 单张失败不拖垮整请求
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logger.warning("接口2 换发型图失败 type=%s：%s", key, e)
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results.append({"hairline_type": key, "order": order,
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"overlay": overlay, "grown_png": grown_png})
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return results
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def _grow_from_texture(image_bgr: np.ndarray, ctx: dict, white_path: str | None,
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use_mask: bool, prompt: str | None):
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"""对单个发际线做生发(ComfyUI)。黑模板固定取 hairline_texture_black/（middle），
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@@ -156,7 +156,7 @@ async function submitTest() {
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fd.append('prompt', $('promptInput').value);
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const _reqStart = performance.now();
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try {
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const r = await fetch(API_BASE + '/api/v1/hair/grow', { method:'POST', body:fd });
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const r = await fetch(API_BASE + '/api/v1/hair/grow', { method:'POST', headers:{ 'X-Internal-Token': 'dev-shared-secret-2026' }, body:fd });
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const json = await r.json();
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const _elapsed = ((performance.now() - _reqStart) / 1000).toFixed(2);
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$('jsonContent').textContent = JSON.stringify(json, null, 2);
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@@ -179,6 +179,9 @@ function renderSchemes(results) {
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let html = '';
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results.forEach((r, i) => {
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const lb = TYPE_LABELS[r.hairline_type] || r.hairline_type;
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// 直连 worker 时后端返回 base64（网关才会改写为 *_url），URL 缺失则回退 data URI
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const overlaySrc = r.image_url || (r.image_base64 ? 'data:image/png;base64,' + r.image_base64 : '');
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const grownSrc = r.grown_image_url || (r.grown_image_base64 ? 'data:image/jpeg;base64,' + r.grown_image_base64 : '');
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// 原图
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const origSlot = '<div class="img-slot">'+
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@@ -190,15 +193,15 @@ function renderSchemes(results) {
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'<div class="label"><span class="dot preview"></span>原图+发际线叠加</div>'+
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'<div class="thumb"><div class="img-stack">'+
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'<img class="layer-base" src="'+_origUrl+'" alt="原图">'+
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'<img class="layer-anno" src="'+r.image_url+'" alt="叠加">'+
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'<img class="layer-anno" src="'+overlaySrc+'" alt="叠加">'+
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'</div></div></div>';
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// 生发效果
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let grownSlot;
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if (r.grown_image_url) {
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if (grownSrc) {
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grownSlot = '<div class="img-slot">'+
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'<div class="label"><span class="dot grown"></span>生发效果</div>'+
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'<div class="thumb"><img src="'+r.grown_image_url+'" alt="生发"></div></div>';
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'<div class="thumb"><img src="'+grownSrc+'" alt="生发"></div></div>';
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} else {
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grownSlot = '<div class="img-slot">'+
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'<div class="label"><span class="dot grown"></span>生发效果</div>'+
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