初始化：换发型/换发色/训练发型服务

包含：
- hair_service_sd: 主服务（换发型/换发色/生发，端口8801）
- photo_service: LoRA调度+训练（端口32678）
- hair_grow_service: 调试测试页（端口8888，含4个测试页）
- 批量训练脚本（batch_train_hairstyles.py）
- 发际线mask自动识别（hairline_mask.py，4种方案）
- 手绘mask换发型（hair_swap_manual.py）
- 文档：README.md + LARGE_FILES.md + docs/

大文件（模型权重200G、训练数据123G）已排除，见 LARGE_FILES.md
OSS/COS密钥已脱敏为环境变量，原文件备份在本地

gen_template_material.py

@@ -0,0 +1,99 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""为新发型生成 hair_template_material（first##_matting.png + .pkl）
+
+换发型功能4 需要：
+  hair_template_material/<hair_id>/first##<name>.png       原图
+  hair_template_material/<hair_id>/first##<name>_matting.png  头发抠图mask
+  hair_template_material/<hair_id>/first##<name>.pkl       1k关键点
+
+用法:
+  cd /home/xsl/change_hair/project/hair_service_sd
+  python gen_template_material.py --hair-id new_test_001 --img /path/to/template.jpg
+"""
+import os
+import sys
+import ssl
+import uuid
+import pickle
+import argparse
+
+ssl._create_default_https_context = ssl._create_unverified_context
+HAIR_SERVICE_DIR = "/home/xsl/change_hair/project/hair_service_sd"
+os.chdir(HAIR_SERVICE_DIR)
+sys.path.insert(0, HAIR_SERVICE_DIR)
+os.environ.setdefault("HF_HUB_OFFLINE", "1")
+
+import cv2
+import numpy as np
+import torch
+
+_orig_torch_load = torch.load
+def _patched_torch_load(*args, **kwargs):
+    if 'map_location' in kwargs and callable(kwargs['map_location']) and not isinstance(kwargs['map_location'], str):
+        kwargs['map_location'] = 'cpu'
+    return _orig_torch_load(*args, **kwargs)
+torch.load = _patched_torch_load
+
+from models.detector import RetinaFaceDetector
+from models.MomocvFaceAlignment1K import MomocvFaceAlignment1K
+from utils.landmark_processor import get_max_rect
+from core.process_modules import Generator_Matte
+from common.logger import config
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--hair-id", required=True)
+    parser.add_argument("--img", required=True, help="模板图(发型图)")
+    args = parser.parse_args()
+
+    template_dir = config.get('default', 'hair_template_material_dir')
+    out_dir = os.path.join(template_dir, args.hair_id)
+    os.makedirs(out_dir, exist_ok=True)
+
+    img = cv2.imread(args.img)
+    if img is None:
+        print(f"✗ 读取失败: {args.img}"); sys.exit(1)
+    print(f"模板图: {img.shape}")
+
+    # 1. 人脸检测 + 1k关键点
+    print("加载模型...")
+    detector = RetinaFaceDetector(gpu_id=0)
+    aligner = MomocvFaceAlignment1K(gpu_id=0)
+    matte_gen = Generator_Matte(gpu=True, device_id=0)
+    print("模型加载完成")
+
+    dets, landms = detector.forward(img)
+    if len(dets) == 0:
+        print("✗ 未检测到人脸"); sys.exit(1)
+    det = dets[get_max_rect(dets)]
+    landmarks_1k = aligner.stable_forward(img.copy(), [det])
+    pt1k = landmarks_1k[0]
+
+    # 2. 头发抠图
+    with torch.no_grad():
+        _, alpha, _ = matte_gen.matte_inference(img, pt1k)
+    if alpha.shape != img.shape[:2]:
+        alpha = cv2.resize(alpha, (img.shape[1], img.shape[0]))
+
+    # 3. 保存三个文件（first##前缀）
+    file_uuid = f"first##{uuid.uuid4()}"
+    png_path = os.path.join(out_dir, f"{file_uuid}.png")
+    matting_path = os.path.join(out_dir, f"{file_uuid}_matting.png")
+    pkl_path = os.path.join(out_dir, f"{file_uuid}.pkl")
+
+    cv2.imwrite(png_path, img)
+    cv2.imwrite(matting_path, alpha)
+    with open(pkl_path, 'wb') as f:
+        # 存 numpy array（不能用 tolist()，代码用 landmarks[index, :] 索引需要 ndarray）
+        pickle.dump({'human_pt1k': np.asarray(pt1k, dtype=np.float32)}, f)
+
+    print(f"✓ 生成完成:")
+    print(f"  {png_path}")
+    print(f"  {matting_path}")
+    print(f"  {pkl_path}")
+
+
+if __name__ == "__main__":
+    main()