From c44b55c82b42b466a2eeb2f70e0e4c8239608790 Mon Sep 17 00:00:00 2001 From: new-sankaku Date: Tue, 16 Apr 2024 00:01:02 +0900 Subject: [PATCH 1/7] Transparent image saving process that reflects modifications made by Extension MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ・Added saving process for transparent images created by Layerdiffuse. ・Save transparent images that reflect modifications made by Extensions (Hires, ADtailer). Note: Does Hires cause an error if the image size after enlargement is not a multiple of 256? We recommend multiplying 1024*1024 by 1.5 to 1536x1536. ・When Batch count is set to 2 or more, the previous image is always included in the Image List returned by the webui side. Also, since the order is different in ascending/descending order, initialization processing is added to Layerdiffuse. It might cause some problems. --- lib_layerdiffusion/models.py | 22 ++++++++- scripts/forge_layerdiffusion.py | 80 ++++++++++++++++++++++++++++++++- 2 files changed, 99 insertions(+), 3 deletions(-) diff --git a/lib_layerdiffusion/models.py b/lib_layerdiffusion/models.py index 3d0cf82..8140c29 100644 --- a/lib_layerdiffusion/models.py +++ b/lib_layerdiffusion/models.py @@ -3,6 +3,7 @@ import cv2 import numpy as np +from PIL import Image from tqdm import tqdm from typing import Optional, Tuple from diffusers.configuration_utils import ConfigMixin, register_to_config @@ -11,6 +12,8 @@ import ldm_patched.modules.model_management as model_management from ldm_patched.modules.model_patcher import ModelPatcher +from modules import images, processing +from modules.shared import opts def zero_module(module): """ @@ -260,7 +263,7 @@ def wrapper(func, latent): fg = y[..., 1:] B, H, W, C = fg.shape - cb = checkerboard(shape=(H // 64, W // 64)) + cb = checkerboard(shape=(H // 1, W // 1)) cb = cv2.resize(cb, (W, H), interpolation=cv2.INTER_NEAREST) cb = (0.5 + (cb - 0.5) * 0.1)[None, ..., None] cb = torch.from_numpy(cb).to(fg) @@ -270,6 +273,23 @@ def wrapper(func, latent): png = torch.cat([fg, alpha], dim=3)[0] png = (png * 255.0).detach().cpu().float().numpy().clip(0, 255).astype(np.uint8) + + # Save transparent image code. + xpng = Image.fromarray(png) + + infotext = processing.Processed(p, []).infotext(p, i) + images.save_image( + image=xpng, + path=p.outpath_samples, + basename="", + seed=p.seeds[i], + prompt=p.prompts[i], + extension=getattr(opts, 'samples_format', 'png'), + info=infotext, + p=p, + suffix="-transparent" + ) + p.extra_result_images.append(png) vis_list = torch.cat(vis_list, dim=0) diff --git a/scripts/forge_layerdiffusion.py b/scripts/forge_layerdiffusion.py index d08e71b..ad6df5b 100644 --- a/scripts/forge_layerdiffusion.py +++ b/scripts/forge_layerdiffusion.py @@ -5,6 +5,9 @@ import numpy as np import copy +from PIL import Image +from modules import images +from modules import script_callbacks, shared from modules import scripts from modules.processing import StableDiffusionProcessing from lib_layerdiffusion.enums import ResizeMode @@ -19,6 +22,7 @@ from lib_layerdiffusion.attention_sharing import AttentionSharingPatcher from ldm_patched.modules import model_management +from modules.shared import opts def is_model_loaded(model): return any(model == m.model for m in current_loaded_models) @@ -50,6 +54,7 @@ def load_layer_model_state_dict(filename): class LayerDiffusionForForge(scripts.Script): + def title(self): return "LayerDiffuse" @@ -59,6 +64,7 @@ def show(self, is_img2img): def ui(self, *args, **kwargs): with gr.Accordion(open=False, label=self.title()): enabled = gr.Checkbox(label='Enabled', value=False) + enabledSaveRebuild = gr.Checkbox(label='Save rebuild image', value=True) method = gr.Dropdown(choices=[e.value for e in LayerMethod], value=LayerMethod.FG_ONLY_ATTN.value, label="Method", type='value') gr.HTML('
') # some strange gradio problems @@ -106,7 +112,7 @@ def method_changed(m): method.change(method_changed, inputs=method, outputs=[fg_image, bg_image, blend_image, resize_mode, fg_additional_prompt, bg_additional_prompt, blend_additional_prompt], show_progress=False, queue=False) - return enabled, method, weight, ending_step, fg_image, bg_image, blend_image, resize_mode, output_origin, fg_additional_prompt, bg_additional_prompt, blend_additional_prompt + return enabled, enabledSaveRebuild, method, weight, ending_step, fg_image, bg_image, blend_image, resize_mode, output_origin, fg_additional_prompt, bg_additional_prompt, blend_additional_prompt def process_before_every_sampling(self, p: StableDiffusionProcessing, *script_args, **kwargs): global vae_transparent_decoder, vae_transparent_encoder @@ -114,7 +120,7 @@ def process_before_every_sampling(self, p: StableDiffusionProcessing, *script_ar # This will be called before every sampling. # If you use highres fix, this will be called twice. - enabled, method, weight, ending_step, fg_image, bg_image, blend_image, resize_mode, output_origin, fg_additional_prompt, bg_additional_prompt, blend_additional_prompt = script_args + enabled, enabledSaveRebuild, method, weight, ending_step, fg_image, bg_image, blend_image, resize_mode, output_origin, fg_additional_prompt, bg_additional_prompt, blend_additional_prompt = script_args if not enabled: return @@ -151,6 +157,8 @@ def process_before_every_sampling(self, p: StableDiffusionProcessing, *script_ar vae = p.sd_model.forge_objects.vae.clone() clip = p.sd_model.forge_objects.clip + + if method in [LayerMethod.FG_ONLY_ATTN, LayerMethod.FG_ONLY_CONV, LayerMethod.BG_BLEND_TO_FG]: if vae_transparent_decoder is None: model_path = load_file_from_url( @@ -357,3 +365,71 @@ def conditioning_modifier(model, x, timestep, uncond, cond, cond_scale, model_op p.sd_model.forge_objects.unet = unet p.sd_model.forge_objects.vae = vae return + + + def postprocess(self, p, processed, *script_args): + """ + This function is called after processing ends for AlwaysVisible scripts. + args contains all values returned by components from ui() + + p + processed + """ + + enabled, enabledSaveRebuild, method, weight, ending_step, fg_image, bg_image, blend_image, resize_mode, output_origin, fg_additional_prompt, bg_additional_prompt, blend_additional_prompt = script_args + + if not enabled or not enabledSaveRebuild: + return + + print( f"processed:{processed}" ) + print( f"processed images :{processed.images}" ) + + + if processed.images is not None and len(processed.images) > 0: + images_copy = processed.images[:] + + if len(processed.extra_images) != len(processed.images): + # Batch Process. + images_copy.pop(0) + # if self.generatedCount % 2 == 0: + # images_copy.reverse() + # print("reverse.") + + extra_images = processed.extra_images + pil_images = [Image.fromarray(img, 'RGBA') for img in extra_images] + + for image_a, image_b in zip(pil_images, images_copy): + + image_b = image_b.convert("RGBA") + + # Create alpha mask with strict threshold + alpha_mask = image_a.getchannel('A').point(lambda x: 255 if x > 30 else 0) + + # Extract RGB channels and Alpha from image_a + r_a, g_a, b_a, a_a = image_a.split() + + # Extract RGB channels from image_b + r_b, g_b, b_b, a_b = image_b.split() + + # Use the strict alpha mask to apply image_a's RGB only where alpha is 255 + r_final = Image.composite(r_b, r_a, alpha_mask) + g_final = Image.composite(g_b, g_a, alpha_mask) + b_final = Image.composite(b_b, b_a, alpha_mask) + + # Combine the new RGB channels with the original alpha channel of image_b + final_image = Image.merge("RGBA", (r_final, g_final, b_final, a_a)) + + # Save the result + images.save_image( + image=final_image, + path=p.outpath_samples, + basename="", + extension=getattr(opts, 'samples_format', 'png'), + p=p, + suffix="-rebuild" + ) + + processed.images = [] + else: + print("processed.images is null or zero index.") + From 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Extensions (Hires, ADtailer) + Note: Does Hires cause an error if the image size after enlargement is not a multiple of 256? We recommend multiplying 1024*1024 by 1.5 to 1536x1536. + - When Batch count is set to 2 or more, the previous image is always included in the Image List returned by the webui side. Also, + since the order is different in ascending/descending order, initialization processing is added to Layerdiffuse. It might cause some problems. + - The black and white check pattern in the non-transparent image has been changed to 1pixel*1pixel for the convenience of merging corrections. + + - Layerdiffuseの作成した透過画像の保存処理を追加 + - Extensionによる修正を反映した透過画像を保存（Hires、ADetailer） + 注意：Hiresは拡大後の画像サイズが256の倍数じゃないとエラーになる？1024*1024を1.5倍して1536x1536がオススメ。 + - Batch countを2以上にするとwebui側が返すImage Listに以前のイメージが常に入る。 + また順序が昇順／降順バラバラにくるのでLayerdiffuse内に初期化処理を追加。何か問題を引き起こすかも。 + - 非透過画像の白黒のチェック柄は修正をマージする都合上、1pixel*1pixelに変更しています。 + # sd-forge-layerdiffuse Transparent Image Layer Diffusion using Latent Transparency From 98b369c769ffd94c7e8c7a50af79b83e1ce21eaa Mon Sep 17 00:00:00 2001 From: new-sankaku <133557155+new-sankaku@users.noreply.github.com> Date: Tue, 16 Apr 2024 00:16:21 +0900 Subject: [PATCH 3/7] Update README.md --- README.md | 37 +++++++++++++++++++++---------------- 1 file changed, 21 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index f8e56b8..35551cc 100644 --- a/README.md +++ b/README.md @@ -1,23 +1,28 @@ -Transparent image saving process that reflects modifications made by Extension. -Extensionによる修正を反映した透過画像の保存処理 +![image](https://github.com/new-sankaku/sd-forge-layerdiffuse/blob/main/2024-04-16%20000652.png) + +> [!IMPORTANT] +> Transparent image saving process that reflects modifications made by Extension. +> Extensionによる修正を反映した透過画像の保存処理 The following files are additionally output. XXXXXXX-transparent.png XXXXXXX--rebuild.png - - - Added saving process for transparent images created by Layerdiffuse - - Save transparent images that reflect modifications made by Extensions (Hires, ADtailer) - Note: Does Hires cause an error if the image size after enlargement is not a multiple of 256? We recommend multiplying 1024*1024 by 1.5 to 1536x1536. - - When Batch count is set to 2 or more, the previous image is always included in the Image List returned by the webui side. Also, - since the order is different in ascending/descending order, initialization processing is added to Layerdiffuse. It might cause some problems. - - The black and white check pattern in the non-transparent image has been changed to 1pixel*1pixel for the convenience of merging corrections. - - - Layerdiffuseの作成した透過画像の保存処理を追加 - - Extensionによる修正を反映した透過画像を保存（Hires、ADetailer） - 注意：Hiresは拡大後の画像サイズが256の倍数じゃないとエラーになる？1024*1024を1.5倍して1536x1536がオススメ。 - - Batch countを2以上にするとwebui側が返すImage Listに以前のイメージが常に入る。 - また順序が昇順／降順バラバラにくるのでLayerdiffuse内に初期化処理を追加。何か問題を引き起こすかも。 - - 非透過画像の白黒のチェック柄は修正をマージする都合上、1pixel*1pixelに変更しています。 + +> [!TIP] +> - Added saving process for transparent images created by Layerdiffuse +> - Save transparent images that reflect modifications made by Extensions (Hires, ADtailer) +> Note: Does Hires cause an error if the image size after enlargement is not a multiple of 256? We recommend multiplying 1024*1024 by 1.5 to 1536x1536. +> - When Batch count is set to 2 or more, the previous image is always included in the Image List returned by the webui side. Also, +> since the order is different in ascending/descending order, initialization processing is added to Layerdiffuse. It might cause some problems. +> - The black and white check pattern in the non-transparent image has been changed to 1pixel*1pixel for the convenience of merging corrections. + +> [!TIP] +> - Layerdiffuseの作成した透過画像の保存処理を追加 +> - Extensionによる修正を反映した透過画像を保存（Hires、ADetailer） +> 注意：Hiresは拡大後の画像サイズが256の倍数じゃないとエラーになる？1024*1024を1.5倍して1536x1536がオススメ。 +> - Batch countを2以上にするとwebui側が返すImage Listに以前のイメージが常に入る。 +> また順序が昇順／降順バラバラにくるのでLayerdiffuse内に初期化処理を追加。何か問題を引き起こすかも。 +> - 非透過画像の白黒のチェック柄は修正をマージする都合上、1pixel*1pixelに変更しています。 # sd-forge-layerdiffuse From 2424080530150ed87de4943bbeadb356941000dc Mon Sep 17 00:00:00 2001 From: new-sankaku Date: Tue, 16 Apr 2024 00:17:37 +0900 Subject: [PATCH 4/7] size change, --- 2024-04-16 000652.png | Bin 28183 -> 17677 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/2024-04-16 000652.png b/2024-04-16 000652.png index f5277c71e7decc57b8c01bee56f588a982aebf72..2e30ef1d66107722cf0d4d8b6676be56158f3e51 100644 GIT binary patch literal 17677 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zI6ij16k1H~%$c*jat3|35c=0xS}v2BB**#c(xw(!HDC8>t3>p*N<@*U^<3P08&KBd z`yKh+5>koKasA{R3$s6b2JggKs>(C)(SsMEw41wjn1PHRu+Hf#YgwO^Hc~tN-iqf(KyWK`(pu zen*Jo32VQZZwVzQn05b_PSkQIf7mO zwedFze*e8`sAH|;Fa6T<;9UTF+4Lw`H{r%(__gFG4Eyx$rabUyL+6)IjH!`vtA@MNY8A?=5=}eXj)$>;F=q zS3l?f`-|t(;+-B;X3HK!xXs@(e|wquo&Ct4(#L*efBj!2AR*Z_#WKY@#U{nR*}6b~ z%<=zVw0dkY=XT=6iK(PD8bSYoj$Plj zzi3O-!XvgUA@bMnS3g|vagoiuFfrl$UGbF7)3Qtn%g#uAOcSw$74$_-LY& z_50|)hn;f=$$x?d0KWM@k1Dh6yamcJohkcIwv7F3Q`YY{_y1!D`@ag-KIv7g@4&_N VU(%{sYuh-ZOXg6sk_$H?{|kfTDNz6b From a5ae5de0499e532320eb7c99961c0093de04e8ba Mon Sep 17 00:00:00 2001 From: new-sankaku Date: Tue, 16 Apr 2024 01:44:47 +0900 Subject: [PATCH 5/7] Problem where rebuild image is not created due to an error in Controlnet (I tried to prevent the error from occurring, but it does not become a transparent image. Only the error is avoided once) --- scripts/forge_layerdiffusion.py | 18 ++++++++++++------ 1 file changed, 12 insertions(+), 6 deletions(-) diff --git a/scripts/forge_layerdiffusion.py b/scripts/forge_layerdiffusion.py index ad6df5b..ba9ad04 100644 --- a/scripts/forge_layerdiffusion.py +++ b/scripts/forge_layerdiffusion.py @@ -388,18 +388,23 @@ def postprocess(self, p, processed, *script_args): if processed.images is not None and len(processed.images) > 0: images_copy = processed.images[:] - if len(processed.extra_images) != len(processed.images): + if len(processed.extra_images) != len(processed.images) and len(images_copy) != 1 : # Batch Process. images_copy.pop(0) - # if self.generatedCount % 2 == 0: - # images_copy.reverse() - # print("reverse.") extra_images = processed.extra_images - pil_images = [Image.fromarray(img, 'RGBA') for img in extra_images] - for image_a, image_b in zip(pil_images, images_copy): + pil_images = [] + for img in extra_images: + if img.shape[2] == 3: # RGB + pil_image = Image.fromarray(img, 'RGB') + pil_image = pil_image.convert("RGBA") + elif img.shape[2] == 4: # RGBA + pil_image = Image.fromarray(img, 'RGBA') + pil_images.append(pil_image) + + for image_a, image_b in zip(pil_images, images_copy): image_b = image_b.convert("RGBA") # Create alpha mask with strict threshold @@ -419,6 +424,7 @@ def postprocess(self, p, processed, *script_args): # Combine the new RGB channels with the original alpha channel of image_b final_image = Image.merge("RGBA", (r_final, g_final, b_final, a_a)) + print("save rebuild.") # Save the result images.save_image( image=final_image, From 3202ff8475563cfa4ce063310631025741a3dad6 Mon Sep 17 00:00:00 2001 From: new-sankaku Date: Tue, 16 Apr 2024 22:18:22 +0900 Subject: [PATCH 6/7] Controle net rebuild. --- lib_layerdiffusion/models.py | 4 +++- scripts/forge_layerdiffusion.py | 33 +++++++++++++++++++-------------- 2 files changed, 22 insertions(+), 15 deletions(-) diff --git a/lib_layerdiffusion/models.py b/lib_layerdiffusion/models.py index 8140c29..59866ec 100644 --- a/lib_layerdiffusion/models.py +++ b/lib_layerdiffusion/models.py @@ -237,7 +237,7 @@ def estimate_augmented(self, pixel, latent): median = torch.median(result, dim=0).values return median - def patch(self, p, vae_patcher, output_origin): + def patch(self, p, vae_patcher, output_origin, transparentImages): @torch.no_grad() def wrapper(func, latent): pixel = func(latent).movedim(-1, 1).to(device=self.load_device, dtype=self.dtype) @@ -278,6 +278,8 @@ def wrapper(func, latent): xpng = Image.fromarray(png) infotext = processing.Processed(p, []).infotext(p, i) + + transparentImages.append(xpng) images.save_image( image=xpng, path=p.outpath_samples, diff --git a/scripts/forge_layerdiffusion.py b/scripts/forge_layerdiffusion.py index ba9ad04..25df429 100644 --- a/scripts/forge_layerdiffusion.py +++ b/scripts/forge_layerdiffusion.py @@ -55,6 +55,8 @@ def load_layer_model_state_dict(filename): class LayerDiffusionForForge(scripts.Script): + transparentImages = [] + def title(self): return "LayerDiffuse" @@ -167,7 +169,7 @@ def process_before_every_sampling(self, p: StableDiffusionProcessing, *script_ar file_name='vae_transparent_decoder.safetensors' ) vae_transparent_decoder = TransparentVAEDecoder(load_torch_file(model_path)) - vae_transparent_decoder.patch(p, vae.patcher, output_origin) + vae_transparent_decoder.patch(p, vae.patcher, output_origin, self.transparentImages) if vae_transparent_encoder is None: model_path = load_file_from_url( @@ -190,7 +192,7 @@ def process_before_every_sampling(self, p: StableDiffusionProcessing, *script_ar vae_transparent_decoder.mod_number = 3 if method == LayerMethod.BG_TO_FG_SD15: vae_transparent_decoder.mod_number = 2 - vae_transparent_decoder.patch(p, vae.patcher, output_origin) + vae_transparent_decoder.patch(p, vae.patcher, output_origin, self.transparentImages) if vae_transparent_encoder is None: model_path = load_file_from_url( @@ -381,30 +383,31 @@ def postprocess(self, p, processed, *script_args): if not enabled or not enabledSaveRebuild: return - print( f"processed:{processed}" ) + # print( f"processed:{processed}" ) print( f"processed images :{processed.images}" ) + print( f"self.transparentImages :{self.transparentImages}" ) if processed.images is not None and len(processed.images) > 0: images_copy = processed.images[:] - if len(processed.extra_images) != len(processed.images) and len(images_copy) != 1 : + if len(self.transparentImages) != len(processed.images) and len(images_copy) != 1 : # Batch Process. images_copy.pop(0) - extra_images = processed.extra_images + # extra_images = processed.extra_images - pil_images = [] - for img in extra_images: - if img.shape[2] == 3: # RGB - pil_image = Image.fromarray(img, 'RGB') - pil_image = pil_image.convert("RGBA") - elif img.shape[2] == 4: # RGBA - pil_image = Image.fromarray(img, 'RGBA') - pil_images.append(pil_image) + # pil_images = [] + # for img in extra_images: + # if img.shape[2] == 3: # RGB + # pil_image = Image.fromarray(img, 'RGB') + # pil_image = pil_image.convert("RGBA") + # elif img.shape[2] == 4: # RGBA + # pil_image = Image.fromarray(img, 'RGBA') + # pil_images.append(pil_image) - for image_a, image_b in zip(pil_images, images_copy): + for image_a, image_b in zip(self.transparentImages, images_copy): image_b = image_b.convert("RGBA") # Create alpha mask with strict threshold @@ -435,7 +438,9 @@ def postprocess(self, p, processed, *script_args): suffix="-rebuild" ) + self.transparentImages =[] processed.images = [] else: print("processed.images is null or zero index.") + From fe21e676c78f9c876be3b0568d0e7853c8867f71 Mon Sep 17 00:00:00 2001 From: new-sankaku <133557155+new-sankaku@users.noreply.github.com> Date: Sun, 21 Apr 2024 17:25:11 +0900 Subject: [PATCH 7/7] Update README.md --- README.md | 26 -------------------------- 1 file changed, 26 deletions(-) diff --git a/README.md b/README.md index 35551cc..2b6f142 100644 --- a/README.md +++ b/README.md @@ -1,29 +1,3 @@ -![image](https://github.com/new-sankaku/sd-forge-layerdiffuse/blob/main/2024-04-16%20000652.png) - -> [!IMPORTANT] -> Transparent image saving process that reflects modifications made by Extension. -> Extensionによる修正を反映した透過画像の保存処理 - -The following files are additionally output. -XXXXXXX-transparent.png -XXXXXXX--rebuild.png - -> [!TIP] -> - Added saving process for transparent images created by Layerdiffuse -> - Save transparent images that reflect modifications made by Extensions (Hires, ADtailer) -> Note: Does Hires cause an error if the image size after enlargement is not a multiple of 256? We recommend multiplying 1024*1024 by 1.5 to 1536x1536. -> - When Batch count is set to 2 or more, the previous image is always included in the Image List returned by the webui side. Also, -> since the order is different in ascending/descending order, initialization processing is added to Layerdiffuse. It might cause some problems. -> - The black and white check pattern in the non-transparent image has been changed to 1pixel*1pixel for the convenience of merging corrections. - -> [!TIP] -> - Layerdiffuseの作成した透過画像の保存処理を追加 -> - Extensionによる修正を反映した透過画像を保存（Hires、ADetailer） -> 注意：Hiresは拡大後の画像サイズが256の倍数じゃないとエラーになる？1024*1024を1.5倍して1536x1536がオススメ。 -> - Batch countを2以上にするとwebui側が返すImage Listに以前のイメージが常に入る。 -> また順序が昇順／降順バラバラにくるのでLayerdiffuse内に初期化処理を追加。何か問題を引き起こすかも。 -> - 非透過画像の白黒のチェック柄は修正をマージする都合上、1pixel*1pixelに変更しています。 - # sd-forge-layerdiffuse Transparent Image Layer Diffusion using Latent Transparency