77 lines
3.3 KiB
Python
77 lines
3.3 KiB
Python
import os
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import sys
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import traceback
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from basicsr.utils.download_util import load_file_from_url
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from modules.upscaler import Upscaler, UpscalerData
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from ldsr_model_arch import LDSR
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from modules import shared, script_callbacks
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import sd_hijack_autoencoder # noqa: F401
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import sd_hijack_ddpm_v1 # noqa: F401
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class UpscalerLDSR(Upscaler):
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def __init__(self, user_path):
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self.name = "LDSR"
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self.user_path = user_path
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self.model_url = "https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1"
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self.yaml_url = "https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1"
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super().__init__()
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scaler_data = UpscalerData("LDSR", None, self)
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self.scalers = [scaler_data]
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def load_model(self, path: str):
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# Remove incorrect project.yaml file if too big
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yaml_path = os.path.join(self.model_path, "project.yaml")
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old_model_path = os.path.join(self.model_path, "model.pth")
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new_model_path = os.path.join(self.model_path, "model.ckpt")
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local_model_paths = self.find_models(ext_filter=[".ckpt", ".safetensors"])
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local_ckpt_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("model.ckpt")]), None)
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local_safetensors_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("model.safetensors")]), None)
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local_yaml_path = next(iter([local_model for local_model in local_model_paths if local_model.endswith("project.yaml")]), None)
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if os.path.exists(yaml_path):
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statinfo = os.stat(yaml_path)
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if statinfo.st_size >= 10485760:
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print("Removing invalid LDSR YAML file.")
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os.remove(yaml_path)
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if os.path.exists(old_model_path):
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print("Renaming model from model.pth to model.ckpt")
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os.rename(old_model_path, new_model_path)
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if local_safetensors_path is not None and os.path.exists(local_safetensors_path):
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model = local_safetensors_path
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else:
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model = local_ckpt_path if local_ckpt_path is not None else load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="model.ckpt", progress=True)
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yaml = local_yaml_path if local_yaml_path is not None else load_file_from_url(url=self.yaml_url, model_dir=self.model_path, file_name="project.yaml", progress=True)
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try:
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return LDSR(model, yaml)
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except Exception:
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print("Error importing LDSR:", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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return None
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def do_upscale(self, img, path):
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ldsr = self.load_model(path)
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if ldsr is None:
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print("NO LDSR!")
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return img
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ddim_steps = shared.opts.ldsr_steps
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return ldsr.super_resolution(img, ddim_steps, self.scale)
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def on_ui_settings():
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import gradio as gr
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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")))
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shared.opts.add_option("ldsr_cached", shared.OptionInfo(False, "Cache LDSR model in memory", gr.Checkbox, {"interactive": True}, section=('upscaling', "Upscaling")))
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script_callbacks.on_ui_settings(on_ui_settings)
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