完善部署并训练5个新发型 + 换发型集成文档

部署修复：
- torch.load 增加 weights_only=False patch，兼容 PyTorch 2.6+ 加载旧权重
- OSS 改为懒加载，本地用 output_format=base64 无需配凭证即可启动
- 补全被 gitignore 误排除的必需代码：core/models/layers/data、models/layers/data、keypoints/lib
- webui 训练命令 --xformers 改 --sdpa（修复 xformers 无 CUDA 支持报错）

功能调整：
- hair_grow_service 端口改 8899、preview 路由修复（send_file）
- list_hairstyles 增加发型白名单，测试页只展示当前5个发型

新增脚本：
- train_lora_parallel.py：直接调 kohya 并行训练 LoRA（绕过 photo_service 串行限制）
- train_hairstyles_parallel.py / train_batch_stepC.py：批量训练辅助脚本
- scripts/sync_data_to_server.sh：大文件断点续传到云服务器

文档：
- docs/换发型集成文档.md：换发型完整流程、服务架构、资源依赖、训练方法、集成步骤

train_batch_stepC.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""阶段C：为已训练的发型生成 ref材质 + 模板材质 + 预览图
+
+前置：LoRA 已训练完成，webui/photo_service/hair_service_sd 已启动。
+
+对每个发型依次：
+  step3: 调 hair_service_sd trainCallBack 回调生成 ref 材质
+  step4: 生成模板材质
+  step5: 生成预览图
+"""
+import os
+import sys
+import time
+import json
+import shutil
+
+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")
+os.environ.setdefault("TRANSFORMERS_OFFLINE", "1")
+os.environ.setdefault("CRYPTOGRAPHY_OPENSSL_NO_LEGACY", "1")
+
+import requests as req
+
+# (hair_id, gender, template_img)
+HAIRSTYLES = [
+    ("chang_tuoyuan", "girl", "/home/xsl/change_hair/hair_type_images/chang_tuoyuan/chang_tuoyuan.jpg"),
+    ("chang_bolang",  "girl", "/home/xsl/change_hair/hair_type_images/chang_bolang/chang_bolang.jpg"),
+    ("chang_zhixian", "girl", "/home/xsl/change_hair/hair_type_images/chang_zhixian/chang_zhixian.jpg"),
+    ("chang_huaban",  "girl", "/home/xsl/change_hair/hair_type_images/chang_huaban/chang_huaban.jpg"),
+    ("chang_xinxing", "girl", "/home/xsl/change_hair/hair_type_images/chang_xinxing/chang_xinxing.jpg"),
+]
+
+HAIR_CALLBACK = "http://127.0.0.1:8801/api/hair/trainCallBack"
+UPLOAD_TRAIN_DIR = "/home/xsl/change_hair/project/data/upload_train_imgs"
+
+# 导入 step4/step5 函数（会触发模型加载）
+from train_hairstyle_full import step4_template_material, step5_preview
+from common.logger import config
+
+
+def log(msg):
+    print(f"[{time.strftime('%H:%M:%S')}] {msg}", flush=True)
+
+
+def step3_callback(hair_id, template_img):
+    """调 trainCallBack 生成 ref 材质。需要先把模板图放到 upload_train_imgs"""
+    log(f"  --- step3: {hair_id} 生成 ref 材质 ---")
+    # 准备 upload_train_imgs/<hair_id>/first##<hair_id>.jpg
+    src_dir = os.path.join(UPLOAD_TRAIN_DIR, hair_id)
+    os.makedirs(src_dir, exist_ok=True)
+    dst = os.path.join(src_dir, f"first##{hair_id}.jpg")
+    shutil.copy(template_img, dst)
+
+    try:
+        r = req.post(HAIR_CALLBACK, json={
+            "task_id": f"train_{hair_id}", "hair_id": hair_id,
+            "state": 0, "msg": "头发lora训练成功", "is_tj": "1"
+        }, timeout=300)
+        d = r.json()
+        ref_dir = os.path.join(config.get('default', 'hairstyleDir'), hair_id)
+        ok = d.get("state") == 0 and os.path.exists(os.path.join(ref_dir, "ref_rgb_8uc3_768.png"))
+        log(f"  {'✓' if ok else '✗'} {hair_id} ref材质 {'成功' if ok else '失败: ' + str(d.get('msg'))}")
+        return ok
+    except Exception as e:
+        log(f"  ✗ {hair_id} ref材质异常: {e}")
+        return False
+
+
+def main():
+    t0 = time.time()
+    log(f"阶段C: 为 {len(HAIRSTYLES)} 个发型生成材质和预览")
+
+    results = {}
+    for hair_id, gender, template_img in HAIRSTYLES:
+        log(f"\n{'='*50}")
+        log(f"处理: {hair_id}")
+        log(f"{'='*50}")
+        ok3 = step3_callback(hair_id, template_img)
+        ok4 = step4_template_material(hair_id, template_img)
+        ok5 = step5_preview(hair_id, gender)
+        results[hair_id] = (ok3, ok4, ok5)
+        log(f"  {hair_id}: ref={'✓' if ok3 else '✗'} 模板={'✓' if ok4 else '✗'} 预览={'✓' if ok5 else '✗'}")
+
+    log(f"\n{'='*60}")
+    log(f"阶段C完成，耗时 {time.time()-t0:.0f}s")
+    log(f"{'='*60}")
+    for hair_id, (ok3, ok4, ok5) in results.items():
+        status = "✓全部成功" if (ok3 and ok4 and ok5) else f"⚠️ ref={'✓' if ok3 else '✗'} 模板={'✓' if ok4 else '✗'} 预览={'✓' if ok5 else '✗'}"
+        log(f"  {hair_id}: {status}")
+
+
+if __name__ == "__main__":
+    main()