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https://github.com/openvinotoolkit/stable-diffusion-webui.git
synced 2024-12-14 14:45:06 +03:00
Fixed outpainting_mk2 output cropping
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91efe138b3
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@ -183,6 +183,7 @@ class Script(scripts.Script):
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pixels_vert = expand_pixels if is_vert else 0
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images_to_process = []
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output_images = []
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for n in range(count):
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res_w = init[n].width + pixels_horiz
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res_h = init[n].height + pixels_vert
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@ -203,7 +204,7 @@ class Script(scripts.Script):
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np_image = (np.asarray(img) / 255.0).astype(np.float64)
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np_mask = (np.asarray(mask) / 255.0).astype(np.float64)
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noised = get_matched_noise(np_image, np_mask, noise_q, color_variation)
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out = Image.fromarray(np.clip(noised * 255., 0., 255.).astype(np.uint8), mode="RGB")
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output_images.append(Image.fromarray(np.clip(noised * 255., 0., 255.).astype(np.uint8), mode="RGB"))
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target_width = min(process_width, init[n].width + pixels_horiz) if is_horiz else img.width
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target_height = min(process_height, init[n].height + pixels_vert) if is_vert else img.height
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@ -211,15 +212,15 @@ class Script(scripts.Script):
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p.height = target_height if is_vert else img.height
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crop_region = (
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0 if is_left else out.width - target_width,
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0 if is_top else out.height - target_height,
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target_width if is_left else out.width,
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target_height if is_top else out.height,
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0 if is_left else output_images[n].width - target_width,
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0 if is_top else output_images[n].height - target_height,
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target_width if is_left else output_images[n].width,
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target_height if is_top else output_images[n].height,
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)
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mask = mask.crop(crop_region)
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p.image_mask = mask
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image_to_process = out.crop(crop_region)
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image_to_process = output_images[n].crop(crop_region)
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images_to_process.append(image_to_process)
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p.init_images = images_to_process
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@ -240,11 +241,11 @@ class Script(scripts.Script):
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initial_seed_and_info[0] = proc.seed
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initial_seed_and_info[1] = proc.info
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for proc_img in proc.images:
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out.paste(proc_img, (0 if is_left else out.width - proc_img.width, 0 if is_top else out.height - proc_img.height))
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out = out.crop((0, 0, res_w, res_h))
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for n in range(count):
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output_images[n].paste(proc.images[n], (0 if is_left else output_images[n].width - proc.images[n].width, 0 if is_top else output_images[n].height - proc.images[n].height))
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output_images[n] = output_images[n].crop((0, 0, res_w, res_h))
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return proc.images
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return output_images
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batch_count = p.n_iter
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batch_size = p.batch_size
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