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。
2026-07-11 18:11:49 +08:00
commit 0eb61f3e60
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+from modules import modelloader, devices, errors
+from modules.shared import opts
+from modules.upscaler import Upscaler, UpscalerData
+from modules.upscaler_utils import upscale_with_model
+
+
+class UpscalerESRGAN(Upscaler):
+    def __init__(self, dirname):
+        self.name = "ESRGAN"
+        self.model_url = "https://github.com/cszn/KAIR/releases/download/v1.0/ESRGAN.pth"
+        self.model_name = "ESRGAN_4x"
+        self.scalers = []
+        self.user_path = dirname
+        super().__init__()
+        model_paths = self.find_models(ext_filter=[".pt", ".pth"])
+        scalers = []
+        if len(model_paths) == 0:
+            scaler_data = UpscalerData(self.model_name, self.model_url, self, 4)
+            scalers.append(scaler_data)
+        for file in model_paths:
+            if file.startswith("http"):
+                name = self.model_name
+            else:
+                name = modelloader.friendly_name(file)
+
+            scaler_data = UpscalerData(name, file, self, 4)
+            self.scalers.append(scaler_data)
+
+    def do_upscale(self, img, selected_model):
+        try:
+            model = self.load_model(selected_model)
+        except Exception:
+            errors.report(f"Unable to load ESRGAN model {selected_model}", exc_info=True)
+            return img
+        model.to(devices.device_esrgan)
+        return esrgan_upscale(model, img)
+
+    def load_model(self, path: str):
+        if path.startswith("http"):
+            # TODO: this doesn't use `path` at all?
+            filename = modelloader.load_file_from_url(
+                url=self.model_url,
+                model_dir=self.model_download_path,
+                file_name=f"{self.model_name}.pth",
+            )
+        else:
+            filename = path
+
+        return modelloader.load_spandrel_model(
+            filename,
+            device=('cpu' if devices.device_esrgan.type == 'mps' else None),
+            expected_architecture='ESRGAN',
+        )
+
+
+def esrgan_upscale(model, img):
+    return upscale_with_model(
+        model,
+        img,
+        tile_size=opts.ESRGAN_tile,
+        tile_overlap=opts.ESRGAN_tile_overlap,
+    )