From ae36e0899fe912cd701fc4bae5c9d0ce9a5b3e41 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 26 Jul 2023 06:36:06 +0300 Subject: [PATCH] alternative solution for infotext issue --- modules/processing.py | 62 +++++++++++++++++++------------------------ modules/scripts.py | 6 ++++- 2 files changed, 32 insertions(+), 36 deletions(-) diff --git a/modules/processing.py b/modules/processing.py index 6dc178e16..146e409a3 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -600,8 +600,12 @@ def program_version(): return res -def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False): - index = position_in_batch + iteration * p.batch_size +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): + if index is None: + index = position_in_batch + iteration * p.batch_size + + if all_negative_prompts is None: + all_negative_prompts = p.all_negative_prompts clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers) enable_hr = getattr(p, 'enable_hr', False) @@ -642,7 +646,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter 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]) prompt_text = p.prompt if use_main_prompt else all_prompts[index] - negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else "" + negative_prompt_text = f"\nNegative prompt: {all_negative_prompts[index]}" if all_negative_prompts[index] else "" return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip() @@ -716,29 +720,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: else: p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))] - def infotext(iteration=0, position_in_batch=0, use_main_prompt=False): - all_prompts = p.all_prompts[:] - all_negative_prompts = p.all_negative_prompts[:] - all_seeds = p.all_seeds[:] - all_subseeds = p.all_subseeds[:] - - # apply changes to generation data - all_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.prompts - all_negative_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.negative_prompts - all_seeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.seeds - all_subseeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.subseeds - - # update p.all_negative_prompts in case extensions changed the size of the batch - # create_infotext below uses it - old_negative_prompts = p.all_negative_prompts - p.all_negative_prompts = all_negative_prompts - - try: - return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch, use_main_prompt) - finally: - # restore p.all_negative_prompts in case extensions changed the size of the batch - p.all_negative_prompts = old_negative_prompts - if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings: model_hijack.embedding_db.load_textual_inversion_embeddings() @@ -826,9 +807,20 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.scripts is not None: p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n) - postprocess_batch_list_args = scripts.PostprocessBatchListArgs(list(x_samples_ddim)) - p.scripts.postprocess_batch_list(p, postprocess_batch_list_args, batch_number=n) - x_samples_ddim = postprocess_batch_list_args.images + batch_params = scripts.PostprocessBatchListArgs( + list(x_samples_ddim), + p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size], + p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size], + p.seeds, + p.subseeds, + ) + + if p.scripts is not None: + p.scripts.postprocess_batch_list(p, batch_params, batch_number=n) + x_samples_ddim = batch_params.images + + def infotext(index=0, use_main_prompt=False): + return create_infotext(p, batch_params.prompts, batch_params.seeds, batch_params.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=batch_params.negative_prompts) for i, x_sample in enumerate(x_samples_ddim): p.batch_index = i @@ -838,7 +830,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.restore_faces: if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration: - 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") + 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") devices.torch_gc() @@ -855,15 +847,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.color_corrections is not None and i < len(p.color_corrections): if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction: image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images) - 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") + 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") image = apply_color_correction(p.color_corrections[i], image) image = apply_overlay(image, p.paste_to, i, p.overlay_images) if opts.samples_save and not p.do_not_save_samples: - images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p) + images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p) - text = infotext(n, i) + text = infotext(i) infotexts.append(text) if opts.enable_pnginfo: image.info["parameters"] = text @@ -874,10 +866,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: 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') if opts.save_mask: - 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") + images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask") if opts.save_mask_composite: - 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") + 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") if opts.return_mask: output_images.append(image_mask) diff --git a/modules/scripts.py b/modules/scripts.py index 5b4edcac3..1049740d5 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -17,8 +17,12 @@ class PostprocessImageArgs: class PostprocessBatchListArgs: - def __init__(self, images): + def __init__(self, images, prompts, negative_prompts, seeds, subseeds): self.images = images + self.prompts = prompts + self.negative_prompts = negative_prompts + self.seeds = seeds + self.subseeds = subseeds class Script: