colomi
0eb61f3e60
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。
63 lines
2.1 KiB
Python
Executable File
63 lines
2.1 KiB
Python
Executable File
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,
|
|
)
|