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- import os
- from modules.modelloader import load_file_from_url
- from modules.upscaler import Upscaler, UpscalerData
- from ldsr_model_arch import LDSR
- from modules import shared, script_callbacks, errors
- import sd_hijack_autoencoder # noqa: F401
- import sd_hijack_ddpm_v1 # noqa: F401
- class UpscalerLDSR(Upscaler):
- def __init__(self, user_path):
- self.name = "LDSR"
- self.user_path = user_path
- self.model_url = "https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1"
- self.yaml_url = "https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1"
- super().__init__()
- scaler_data = UpscalerData("LDSR", None, self)
- self.scalers = [scaler_data]
- def load_model(self, path: str):
- # Remove incorrect project.yaml file if too big
- yaml_path = os.path.join(self.model_path, "project.yaml")
- old_model_path = os.path.join(self.model_path, "model.pth")
- new_model_path = os.path.join(self.model_path, "model.ckpt")
- local_model_paths = self.find_models(ext_filter=[".ckpt", ".safetensors"])
- local_ckpt_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("model.ckpt")]), None)
- local_safetensors_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("model.safetensors")]), None)
- local_yaml_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("project.yaml")]), None)
- if os.path.exists(yaml_path):
- statinfo = os.stat(yaml_path)
- if statinfo.st_size >= 10485760:
- print("Removing invalid LDSR YAML file.")
- os.remove(yaml_path)
- if os.path.exists(old_model_path):
- print("Renaming model from model.pth to model.ckpt")
- os.rename(old_model_path, new_model_path)
- if local_safetensors_path is not None and os.path.exists(local_safetensors_path):
- model = local_safetensors_path
- else:
- model = local_ckpt_path or load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name="model.ckpt")
- yaml = local_yaml_path or load_file_from_url(self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml")
- return LDSR(model, yaml)
- def do_upscale(self, img, path):
- try:
- ldsr = self.load_model(path)
- except Exception:
- errors.report(f"Failed loading LDSR model {path}", exc_info=True)
- return img
- ddim_steps = shared.opts.ldsr_steps
- return ldsr.super_resolution(img, ddim_steps, self.scale)
- def on_ui_settings():
- import gradio as gr
- shared.opts.add_option("ldsr_steps", shared.OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}, section=('upscaling', "Upscaling")))
- shared.opts.add_option("ldsr_cached", shared.OptionInfo(False, "Cache LDSR model in memory", gr.Checkbox, {"interactive": True}, section=('upscaling', "Upscaling")))
- script_callbacks.on_ui_settings(on_ui_settings)
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