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