mirror of
https://github.com/kohya-ss/sd-scripts.git
synced 2026-04-15 00:32:25 +00:00
Update accel_sdxl_gen_img.py
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DKnight54
GitHub
@@ -2120,7 +2120,7 @@ def main(args):
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iter_seed = random.randint(0, 0x7FFFFFFF)
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# バッチ処理の関数
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def process_batch(batch: List[BatchData], highres_fix, highres_1st=False):
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def process_batch(batch: List[BatchData], distributed_state, highres_fix, highres_1st=False):
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batch_size = len(batch)
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# highres_fixの処理
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@@ -2170,7 +2170,7 @@ def main(args):
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batch_1st.append(BatchData(is_1st_latent, global_count, base, ext_1st))
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pipe.set_enable_control_net(True) # 1st stageではControlNetを有効にする
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images_1st = process_batch(batch_1st, True, True)
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images_1st = process_batch(batch_1st, distributed_state, True, True)
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# 2nd stageのバッチを作成して以下処理する
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logger.info("process 2nd stage")
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@@ -2381,60 +2381,72 @@ def main(args):
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return images
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# save image
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highres_prefix = ("0" if highres_1st else "1") if highres_fix else ""
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ds_str = time.strftime("%Y%m%d", time.localtime())
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ts_str = time.strftime("%H%M%S", time.localtime())
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for i, (image, globalcount, prompt, negative_prompts, seed, clip_prompt, raw_prompt) in enumerate(
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zip(images, global_counter, prompts, negative_prompts, seeds, clip_prompts, raw_prompts)
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):
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if highres_fix:
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seed -= 1 # record original seed
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metadata = PngInfo()
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metadata.add_text("prompt", prompt)
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metadata.add_text("seed", str(seed))
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metadata.add_text("sampler", args.sampler)
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metadata.add_text("steps", str(steps))
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metadata.add_text("scale", str(scale))
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if negative_prompt is not None:
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metadata.add_text("negative-prompt", negative_prompt)
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if negative_scale is not None:
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metadata.add_text("negative-scale", str(negative_scale))
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if clip_prompt is not None:
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metadata.add_text("clip-prompt", clip_prompt)
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if raw_prompt is not None:
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metadata.add_text("raw-prompt", raw_prompt)
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metadata.add_text("original-height", str(original_height))
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metadata.add_text("original-width", str(original_width))
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metadata.add_text("original-height-negative", str(original_height_negative))
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metadata.add_text("original-width-negative", str(original_width_negative))
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metadata.add_text("crop-top", str(crop_top))
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metadata.add_text("crop-left", str(crop_left))
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if args.use_original_file_name and init_images is not None:
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if type(init_images) is list:
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fln = os.path.splitext(os.path.basename(init_images[i % len(init_images)].filename))[0] + ".png"
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distributed_state.wait_for_everyone()
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all_images=gather_object(images)
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all_global_counter = gather_object(global_counter)
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all_prompts = gather_object(prompts)
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all_negative_prompts = gather_object(negative_prompts)
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all_seeds = gather_object(seeds)
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all_clip_prompts = gather_object(clip_prompts)
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all_raw_prompts = gather_object(raw_prompts)
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all_init_images = gather_object(init_images)
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if distributed_state.is_main_process:
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highres_prefix = ("0" if highres_1st else "1") if highres_fix else ""
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ds_str = time.strftime("%Y%m%d", time.localtime())
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ts_str = time.strftime("%H%M%S", time.localtime())
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for i, (image, globalcount, prompt, negative_prompts, seed, clip_prompt, raw_prompt) in enumerate(
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zip(all_images, all_global_counter, all_prompts, all_negative_prompts, all_seeds, all_clip_prompts, all_raw_prompts)
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):
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if highres_fix:
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seed -= 1 # record original seed
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metadata = PngInfo()
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metadata.add_text("prompt", prompt)
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metadata.add_text("seed", str(seed))
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metadata.add_text("sampler", args.sampler)
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metadata.add_text("steps", str(steps))
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metadata.add_text("scale", str(scale))
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if negative_prompt is not None:
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metadata.add_text("negative-prompt", negative_prompt)
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if negative_scale is not None:
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metadata.add_text("negative-scale", str(negative_scale))
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if clip_prompt is not None:
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metadata.add_text("clip-prompt", clip_prompt)
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if raw_prompt is not None:
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metadata.add_text("raw-prompt", raw_prompt)
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metadata.add_text("original-height", str(original_height))
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metadata.add_text("original-width", str(original_width))
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metadata.add_text("original-height-negative", str(original_height_negative))
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metadata.add_text("original-width-negative", str(original_width_negative))
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metadata.add_text("crop-top", str(crop_top))
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metadata.add_text("crop-left", str(crop_left))
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if args.use_original_file_name and init_images is not None:
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if type(init_images) is list:
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fln = os.path.splitext(os.path.basename(init_images[i % len(init_images)].filename))[0] + ".png"
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else:
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fln = os.path.splitext(os.path.basename(init_images.filename))[0] + ".png"
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elif args.sequential_file_name:
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fln = f"im_{globalcount:02d}_{highres_prefix}{step_first + i + 1:06d}.png"
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else:
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fln = os.path.splitext(os.path.basename(init_images.filename))[0] + ".png"
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elif args.sequential_file_name:
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fln = f"im_{globalcount:02d}_{highres_prefix}{step_first + i + 1:06d}.png"
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else:
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fln = f"im_{ds_str}_{globalcount:02d}_{ts_str}_{highres_prefix}{i:03d}_{seed}.png"
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image.save(os.path.join(args.outdir, fln), pnginfo=metadata)
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if not args.no_preview and not highres_1st and args.interactive:
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try:
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import cv2
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for prompt, image in zip(prompts, images):
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cv2.imshow(prompt[:128], np.array(image)[:, :, ::-1]) # プロンプトが長いと死ぬ
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cv2.waitKey()
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cv2.destroyAllWindows()
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except ImportError:
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logger.error(
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"opencv-python is not installed, cannot preview / opencv-pythonがインストールされていないためプレビューできません"
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)
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fln = f"im_{ds_str}_{ts_str}_{globalcount:02d}_{highres_prefix}{i:03d}_{seed}.png"
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logger.info(f"Saving image {global_count}: {fln}\nPrompt: {prompt}")
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image.save(os.path.join(args.outdir, fln), pnginfo=metadata)
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if not args.no_preview and not highres_1st and args.interactive:
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try:
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import cv2
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for prompt, image in zip(prompts, images):
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cv2.imshow(prompt[:128], np.array(image)[:, :, ::-1]) # プロンプトが長いと死ぬ
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cv2.waitKey()
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cv2.destroyAllWindows()
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except ImportError:
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logger.error(
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"opencv-python is not installed, cannot preview / opencv-pythonがインストールされていないためプレビューできません"
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)
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distributed_state.wait_for_everyone()
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return images
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# 画像生成のプロンプトが一周するまでのループ
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@@ -2922,7 +2934,7 @@ def main(args):
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logger.info(f"\nLoading batch {j+1}/{len(batches)} of {len(batches[j])} prompts onto device {distributed_state.local_process_index}:\nbatch_list:")
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for i in range(len(batches[j])):
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logger.info(f"Image: {batches[j][i].global_count}\nDevice {distributed_state.device}: Prompt {i+1}: {batches[j][i].base.prompt}\nNegative Prompt: {batches[j][i].base.negative_prompt}\nSeed: {batches[j][i].base.seed}")
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prev_image = process_batch(batch_list[j], highres_fix)[0]
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prev_image = process_batch(batch_list[j], distributed_state, highres_fix)[0]
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distributed_state.wait_for_everyone()
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#for i in range(len(data_loader)):
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