mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2024-06-07 21:20:49 +00:00
0dce0df1ee
Yep. Fix gfpgan_model_arch requirement(s). Add Upscaler base class, move from images. Add a lot of methods to Upscaler. Re-work all the child upscalers to be proper classes. Add BSRGAN scaler. Add ldsr_model_arch class, removing the dependency for another repo that just uses regular latent-diffusion stuff. Add one universal method that will always find and load new upscaler models without having to add new "setup_model" calls. Still need to add command line params, but that could probably be automated. Add a "self.scale" property to all Upscalers so the scalers themselves can do "things" in response to the requested upscaling size. Ensure LDSR doesn't get stuck in a longer loop of "upscale/downscale/upscale" as we try to reach the target upscale size. Add typehints for IDE sanity. PEP-8 improvements. Moar.
46 lines
1.6 KiB
Python
46 lines
1.6 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 modules.ldsr_model_arch import LDSR
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from modules import shared
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from modules.paths import models_path
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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.model_path = os.path.join(models_path, self.name)
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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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model = load_file_from_url(url=self.model_url, model_dir=self.model_path,
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file_name="model.pth", progress=True)
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yaml = load_file_from_url(url=self.model_url, model_dir=self.model_path,
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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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pre_scale = shared.opts.ldsr_pre_down
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return ldsr.super_resolution(img, ddim_steps, self.scale)
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