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。

stable-diffusion-webui/modules/textual_inversion/saving_settings.py

@@ -0,0 +1,64 @@
+import datetime
+import json
+import os
+
+saved_params_shared = {
+    "batch_size",
+    "clip_grad_mode",
+    "clip_grad_value",
+    "create_image_every",
+    "data_root",
+    "gradient_step",
+    "initial_step",
+    "latent_sampling_method",
+    "learn_rate",
+    "log_directory",
+    "model_hash",
+    "model_name",
+    "num_of_dataset_images",
+    "steps",
+    "template_file",
+    "training_height",
+    "training_width",
+}
+saved_params_ti = {
+    "embedding_name",
+    "num_vectors_per_token",
+    "save_embedding_every",
+    "save_image_with_stored_embedding",
+}
+saved_params_hypernet = {
+    "activation_func",
+    "add_layer_norm",
+    "hypernetwork_name",
+    "layer_structure",
+    "save_hypernetwork_every",
+    "use_dropout",
+    "weight_init",
+}
+saved_params_all = saved_params_shared | saved_params_ti | saved_params_hypernet
+saved_params_previews = {
+    "preview_cfg_scale",
+    "preview_height",
+    "preview_negative_prompt",
+    "preview_prompt",
+    "preview_sampler_index",
+    "preview_seed",
+    "preview_steps",
+    "preview_width",
+}
+
+
+def save_settings_to_file(log_directory, all_params):
+    now = datetime.datetime.now()
+    params = {"datetime": now.strftime("%Y-%m-%d %H:%M:%S")}
+
+    keys = saved_params_all
+    if all_params.get('preview_from_txt2img'):
+        keys = keys | saved_params_previews
+
+    params.update({k: v for k, v in all_params.items() if k in keys})
+
+    filename = f'settings-{now.strftime("%Y-%m-%d-%H-%M-%S")}.json'
+    with open(os.path.join(log_directory, filename), "w") as file:
+        json.dump(params, file, indent=4)