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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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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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