ComfyUI_HiDiffusion_Pro
A HiDiffusion node for ComfyUI
HiDiffusion From: link
Update
07/24
--新增社区单体模型支持,单体controlnet模型支持
-- 通过菜单model_category来选择使用不同模型;
--VAE可以填写你喜欢的vae地址
--Added support for community monolithic models and monolithic ControlNet models
--Select different models through the menu “model_category”;
--VAE can fill in your favorite VAE address
--
--增加adapter_style支持,SDXL需求的显存较大,虽然能跑CPU,但是不推荐,会爆显存,SD1.5测试没问题。
--Adding adapter_style support, SDXL requires a large amount of graphics memory. Although it can run on CPU, it is not recommended as it may cause graphics memory "explosion". SD1.5 testing is not a problem.
My ComfyUI node list:
1、ParlerTTS node:ComfyUI_ParlerTTS
2、Llama3_8B node:ComfyUI_Llama3_8B
3、HiDiffusion node:ComfyUI_HiDiffusion_Pro
4、ID_Animator node: ComfyUI_ID_Animator
5、StoryDiffusion node:ComfyUI_StoryDiffusion
6、Pops node:ComfyUI_Pops
7、stable-audio-open-1.0 node :ComfyUI_StableAudio_Open
8、GLM4 node:ComfyUI_ChatGLM_API
9、CustomNet node:ComfyUI_CustomNet
10、Pipeline_Tool node :ComfyUI_Pipeline_Tool
11、Pic2Story node :ComfyUI_Pic2Story
12、PBR_Maker node:ComfyUI_PBR_Maker
13、ComfyUI_Streamv2v_Plus node:ComfyUI_Streamv2v_Plus
14、ComfyUI_MS_Diffusion node:ComfyUI_MS_Diffusion
15、ComfyUI_AnyDoor node: ComfyUI_AnyDoor
16、ComfyUI_Stable_Makeup node: ComfyUI_Stable_Makeup
17、ComfyUI_EchoMimic node: ComfyUI_EchoMimic
18、ComfyUI_FollowYourEmoji node: ComfyUI_FollowYourEmoji
Notice(节点的特殊功能说明 Special Function Description of Nodes)
-- 增加 manne加速Lora
-- 加入controlnet-tile-sdxl的支持,内置图片预处理,默认512尺寸,新增apply_window_attn 条件控制。
--修复节点连接逻辑,现在文生图模式,无需接入image,无controlnet也无需接入control_image
--支持SDXL-lighting\Hyper\LCM\DMD2\的加速Unet,建议适当提高步数;
--基于官方的更新,加入lora支持,需要填关键词;
--加入skip,去掉意义不大的其他参数;
-- add manne lighting lora
--Added support for control net file sdxl, built-in image preprocessing, default size of 512, and added condition control for apply_window_attn.
--Fix node connection logic, now in text-based graphics mode, there is no need to connect to image, no controllnet, and no need to connect to controll_image
--Support acceleration Unet for SDXL lighting, Hyper, LCM, and DMD2. It is recommended to increase the number of steps appropriately;
--Based on official updates, adding support for Lora requires filling in keywords;
--Add skip and remove other parameters that are not significant;
1.Installation
1.1 In the .\ComfyUI \ custom_node directory, run the following:
git clone https://github.com/smthemex/ComfyUI_HiDiffusion_Pro.git
1.2 using it
2.requirements
diffusers >=0.28.0 is best yaml
3 About models
3.1 使用社区单体模型 Using the Community Monomer Model
3.2 填写repo_id 和controlnet_repo_id
可以是stabilityai/stable-diffusion-xl-base-1.0
也可是“x:/xx/xx/stabilityai/stable-diffusion-xl-base-1.0”
controlnet_repo_id 如果使用controlnet_repo_id,本地模型存放示例:
├── your path/
| ├──xinsir/controlnet-openpose-sdxl-1.0
| ├── config.json
| ├── diffusion_pytorch_model.fp16.safetensors
| ├──xinsir/controlnet-scribble-sdxl-1.0
| ├── config.json
| ├── diffusion_pytorch_model.fp16.safetensors
| ├──xinsir/controlnet-tile-sdxl-1.0
| ├── config.json
| ├── diffusion_pytorch_model.fp16.safetensors
| ├──diffusers/controlnet-canny-sdxl-1.0
| ├── config.json
| ├── diffusion_pytorch_model.fp16.safetensors
| ├──diffusers/controlnet-depth-sdxl-1.0
| ├── config.json
| ├── diffusion_pytorch_model.fp16.safetensors
| ├──TheMistoAI/MistoLine
| ├── config.json
| ├── diffusion_pytorch_model.fp16.safetensors
ip_adapter model 模型存放示例:
如果不存放对应,运行时会自动下载。 If the corresponding file is not stored, it will be automatically downloaded at runtime.
├── ComfyUI/models/photomaker
| ├──models/
| ├── ip-adapter_sd15.bin
| ├── image_encoder/
| ├── config.json
| ├── model.safetensors
| ├──sdxl_models/
| ├── ip-adapter_sdxl.bin
| ├── image_encoder/
| ├── config.json
| ├── model.safetensors
4 other
部分支持的模型请查看model.yaml 文件
For partially supported models, please refer to the model.yaml file
5 example
sd1.5 using ip_adapter_style 使用ip_adapter_style

img2img + controlnet 图生图加controlnet

img2img use Hyper unet 图生图加加速unet

6 Citation
@article{zhang2023hidiffusion,
title={HiDiffusion: Unlocking Higher-Resolution Creativity and Efficiency in Pretrained Diffusion Models},
author={Zhang, Shen and Chen, Zhaowei and Zhao, Zhenyu and Chen, Yuhao and Tang, Yao and Liang, Jiajun},
journal={arXiv preprint arXiv:2311.17528},
year={2023}
}
