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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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Save properly processed image before color correction
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dd25722d6c
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@ -46,6 +46,20 @@ def apply_color_correction(correction, image):
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return image
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def apply_overlay(overlay_exists, overlay, paste_loc, image):
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if overlay_exists:
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if paste_loc is not None:
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x, y, w, h = paste_loc
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base_image = Image.new('RGBA', (overlay.width, overlay.height))
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image = images.resize_image(1, image, w, h)
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base_image.paste(image, (x, y))
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image = base_image
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image = image.convert('RGBA')
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image.alpha_composite(overlay)
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image = image.convert('RGB')
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return image
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def get_correct_sampler(p):
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if isinstance(p, modules.processing.StableDiffusionProcessingTxt2Img):
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@ -446,25 +460,14 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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devices.torch_gc()
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image = Image.fromarray(x_sample)
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if p.color_corrections is not None and i < len(p.color_corrections):
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if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction:
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images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
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image_without_cc = apply_overlay(p.overlay_images is not None and i < len(p.overlay_images), p.overlay_images[i], p.paste_to, image)
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images.save_image(image_without_cc, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
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image = apply_color_correction(p.color_corrections[i], image)
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if p.overlay_images is not None and i < len(p.overlay_images):
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overlay = p.overlay_images[i]
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if p.paste_to is not None:
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x, y, w, h = p.paste_to
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base_image = Image.new('RGBA', (overlay.width, overlay.height))
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image = images.resize_image(1, image, w, h)
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base_image.paste(image, (x, y))
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image = base_image
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image = image.convert('RGBA')
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image.alpha_composite(overlay)
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image = image.convert('RGB')
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image = apply_overlay(p.overlay_images is not None and i < len(p.overlay_images), p.overlay_images[i], p.paste_to, image)
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if opts.samples_save and not p.do_not_save_samples:
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images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p)
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