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https://github.com/openvinotoolkit/stable-diffusion-webui.git
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Merge pull request #12023 from AUTOMATIC1111/create_infotext_fix
Create infotext fix
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@ -600,8 +600,12 @@ def program_version():
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return res
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def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False):
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index = position_in_batch + iteration * p.batch_size
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def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False, index=None, all_negative_prompts=None):
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if index is None:
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index = position_in_batch + iteration * p.batch_size
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if all_negative_prompts is None:
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all_negative_prompts = p.all_negative_prompts
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clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
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enable_hr = getattr(p, 'enable_hr', False)
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@ -617,12 +621,12 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
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"Sampler": p.sampler_name,
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"CFG scale": p.cfg_scale,
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"Image CFG scale": getattr(p, 'image_cfg_scale', None),
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"Seed": all_seeds[index],
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"Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index],
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"Face restoration": (opts.face_restoration_model if p.restore_faces else None),
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"Size": f"{p.width}x{p.height}",
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"Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
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"Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra),
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"Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
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"Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])),
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"Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
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"Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
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"Denoising strength": getattr(p, 'denoising_strength', None),
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@ -642,7 +646,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
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generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
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prompt_text = p.prompt if use_main_prompt else all_prompts[index]
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negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""
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negative_prompt_text = f"\nNegative prompt: {all_negative_prompts[index]}" if all_negative_prompts[index] else ""
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return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip()
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@ -716,29 +720,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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else:
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p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
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def infotext(iteration=0, position_in_batch=0, use_main_prompt=False):
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all_prompts = p.all_prompts[:]
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all_negative_prompts = p.all_negative_prompts[:]
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all_seeds = p.all_seeds[:]
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all_subseeds = p.all_subseeds[:]
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# apply changes to generation data
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all_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.prompts
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all_negative_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.negative_prompts
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all_seeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.seeds
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all_subseeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.subseeds
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# update p.all_negative_prompts in case extensions changed the size of the batch
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# create_infotext below uses it
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old_negative_prompts = p.all_negative_prompts
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p.all_negative_prompts = all_negative_prompts
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try:
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return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
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finally:
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# restore p.all_negative_prompts in case extensions changed the size of the batch
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p.all_negative_prompts = old_negative_prompts
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if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
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model_hijack.embedding_db.load_textual_inversion_embeddings()
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@ -826,9 +807,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if p.scripts is not None:
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p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
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postprocess_batch_list_args = scripts.PostprocessBatchListArgs(list(x_samples_ddim))
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p.scripts.postprocess_batch_list(p, postprocess_batch_list_args, batch_number=n)
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x_samples_ddim = postprocess_batch_list_args.images
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p.prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
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p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
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batch_params = scripts.PostprocessBatchListArgs(list(x_samples_ddim))
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p.scripts.postprocess_batch_list(p, batch_params, batch_number=n)
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x_samples_ddim = batch_params.images
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def infotext(index=0, use_main_prompt=False):
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return create_infotext(p, p.prompts, p.seeds, p.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=p.negative_prompts)
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for i, x_sample in enumerate(x_samples_ddim):
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p.batch_index = i
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@ -838,7 +825,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if p.restore_faces:
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if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
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images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
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images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-face-restoration")
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devices.torch_gc()
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@ -855,15 +842,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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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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image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
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images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
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images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-color-correction")
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image = apply_color_correction(p.color_corrections[i], image)
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image = apply_overlay(image, p.paste_to, i, p.overlay_images)
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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, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p)
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images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p)
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text = infotext(n, i)
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text = infotext(i)
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infotexts.append(text)
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if opts.enable_pnginfo:
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image.info["parameters"] = text
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@ -874,10 +861,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA')
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if opts.save_mask:
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images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
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images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask")
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if opts.save_mask_composite:
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images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
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images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask-composite")
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if opts.return_mask:
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output_images.append(image_mask)
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@ -918,7 +905,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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p,
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images_list=output_images,
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seed=p.all_seeds[0],
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info=infotext(),
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info=infotexts[0],
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comments="".join(f"{comment}\n" for comment in comments),
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subseed=p.all_subseeds[0],
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index_of_first_image=index_of_first_image,
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