初始化换发型项目：3个微服务代码 + 部署脚本

包含：
- hair_service_sd: 换发型/换发色算法服务 (端口 8801)
- photo_service: LoRA 训练调度服务 (端口 32678)
- stable-diffusion-webui: SD WebUI 推理服务 (端口 57860)
- kohya_ss_home: 训练环境代码
- meidaojia: 监控测试脚本
- setup.sh: 一键部署脚本 (conda环境恢复 + 配置生成 + 完整性检查)
- start_all_services.sh: 启动3个服务
- configure.ini.template: 路径模板化 (BASE_DIR自动推导)
- conda_envs/py310.yml: py310 环境定义

大文件 (weights/, models/, data/, conda_envs/*.tar.gz 等) 通过 .gitignore 排除，
由网盘单独上传。

hair_service_sd/utils/model_io.py

@@ -0,0 +1,25 @@
+import os
+import torch
+
+def load_model_by_path(model_save_path, model, gpu_id = None):
+    if not os.path.exists(model_save_path): return
+    loc = 'cpu' if gpu_id is None else 'cuda:{}'.format(gpu_id)
+    pretrained_dict = torch.load(model_save_path, map_location=loc)
+    if 'state_dict' in pretrained_dict: pretrained_dict = pretrained_dict['state_dict']
+    model_dict = model.state_dict()
+    # pretrained_dict.pop('netG.model.1.weight', '404')
+    pretrained_dict_new = {k: v for k, v in pretrained_dict.items()
+                       if (k in model_dict and model_dict[k].data.shape == v.data.shape)}
+    # if 'netG.model.1.weight' not in pretrained_dict_new and 'netG.model.1.weight' in model_dict:
+    #     pretrained_dict_new['netG.model.1.weight'] = model_dict['netG.model.1.weight']
+    #     pretrained_dict_new['netG.model.1.weight'][:,:12] = pretrained_dict['netG.model.1.weight']
+
+    model_dict.update(pretrained_dict_new)
+    model.load_state_dict(model_dict)
+    print("load model: ", model_save_path)
+
+def save_model_by_path(model_save_path, model):
+    save_dir, _ = os.path.split(model_save_path)
+    if not os.path.isdir(save_dir): os.makedirs(save_dir)
+    model_dic={k.replace('.module', ''):v for k,v in model.state_dict().items()}
+    torch.save(model_dic, model_save_path)