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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2025-08-04 03:10:21 +00:00
Holy $hit.
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.
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@@ -66,29 +66,28 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
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info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n"
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image = res
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if upscaling_resize != 1.0:
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def upscale(image, scaler_index, resize):
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small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
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pixels = tuple(np.array(small).flatten().tolist())
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key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
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def upscale(image, scaler_index, resize):
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small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
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pixels = tuple(np.array(small).flatten().tolist())
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key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
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c = cached_images.get(key)
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if c is None:
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upscaler = shared.sd_upscalers[scaler_index]
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c = upscaler.upscale(image, image.width * resize, image.height * resize)
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cached_images[key] = c
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c = cached_images.get(key)
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if c is None:
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upscaler = shared.sd_upscalers[scaler_index]
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c = upscaler.scaler.upscale(image, resize, upscaler.data_path)
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cached_images[key] = c
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return c
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return c
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info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"
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res = upscale(image, extras_upscaler_1, upscaling_resize)
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info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"
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res = upscale(image, extras_upscaler_1, upscaling_resize)
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if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
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res2 = upscale(image, extras_upscaler_2, upscaling_resize)
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info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n"
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res = Image.blend(res, res2, extras_upscaler_2_visibility)
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if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
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res2 = upscale(image, extras_upscaler_2, upscaling_resize)
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info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n"
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res = Image.blend(res, res2, extras_upscaler_2_visibility)
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image = res
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image = res
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while len(cached_images) > 2:
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del cached_images[next(iter(cached_images.keys()))]
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