使用教程/详解视频:【简体中文版ComfyUI来啦!我把界面&常用模块&管理器&风格插件都汉化了!Stable Diffusion | Ai+建筑】
20230816
- 简体中文版整合包正式上线,预装超多模块组(简版5个,标准版25个),下载地址:https://pan.baidu.com/s/11znfR-gm0ieHHEVpOzVhCQ?pwd=e5cu 提取码:e5cu
- 中文云部署全新升级,新增模组下载器,详见:ComfyUI 云部署1.0
20230815
- 编写了一个常用参考网站的主菜单按钮,代码详见:常用艺术库 按钮 双语版
20230814
- 完成ComfyUI Overlay(Layout)节点汉化,代码详见:ComfyUI 排版模块 简体中文版
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完成ComfyUI 20+常用节点汉化,代码详见:ComfyUI 常用节点 简体中文版
节点列表
1.采样器_Zho
2.高级采样器_Zho
3.主模型加载器_Zho
4.VAE加载器_Zho
5.Lora加载器_Zho
6.ControlNet加载器_Zho
7.GLIGEN加载器_Zho
8.提示词_Zho
9.CLIP跳过层_Zho
10.GLIGEN区域设定_Zho
11.ControlNet_Zho
12.初始潜空间_Zho
13.VAE解码器_Zho
14.VAE编码器_Zho
15.VAE编码器_重绘_Zho
16.批次选择_Zho
17.批次复制_Zho
18.潜空间放大_Zho
19.潜空间放大_比例_Zho
20.图像保存_Zho
21.图像预览_Zho
22.图像加载_Zho
23.图像放大_Zho
24.图像放大_比例_Zho
25.图像反转_Zho
20230804
- 完成ComfyUI Styler汉化,代码详见:ComfyUI Styler 简体中文版
20230803
- 完成ComfyUI界面汉化,并新增ZHO主题配色 ,代码详见:ComfyUI 简体中文版界面
- 完成ComfyUI Manager汉化 ,代码详见:ComfyUI Manager 简体中文版
声明:我并不是ComfyUI的作者,我只是对界面做了汉化 + 常用节点汉化 + 新增了一个主题配色,原作者在ComfyUI
本地部署
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简体中文版整合包正式上线,预装超多模块组(简版5个,标准版25个),下载地址:https://pan.baidu.com/s/11znfR-gm0ieHHEVpOzVhCQ?pwd=e5cu 提取码:e5cu
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未部署过的小伙伴: 先下载ComfyUI作者的整合包,然后再把web和custom nodes文件夹下载到本地,覆盖掉原来的web和custom nodes文件夹即可(自己安装的其他模块也放到新的custom nodes文件夹里),运行之后就可看到中文简体版的界面。
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已部署的小伙伴: 只需把web和custom nodes文件夹下载到本地,覆盖掉原来的web和custom nodes文件夹即可(自己安装的其他模块也放到新的custom nodes文件夹里)。
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需要中文版Manager的小伙伴,移步ComfyUI Manager 简体中文版
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需要中文版Styler的小伙伴,移步ComfyUI Styler 简体中文版
Google Colab 云部署:
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我制作的ComfyUI 云部署1.0:已载入简体中文版界面、简体中文版常用节点、简体中文版Manager、简体中文版Styler,同时也支持最新SDXL1.0模型,并且提供了支持中文输入的【SDXL系列标准工作流 -Zho-】
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有自己colab云部署的小伙伴,只需git安装此库即可
基础文生图工作流:Zho_文生图
整合包百度网盘下载:
链接:https://pan.baidu.com/s/11znfR-gm0ieHHEVpOzVhCQ?pwd=e5cu 提取码:e5cu
汉化包百度网盘下载:
链接:https://pan.baidu.com/s/1wck3rvUkzO5GS8mduR6wfQ?pwd=pc1o 提取码:pc1o
直接下载:
web已修复与原始图片加载冲突的问题、汉化默认工作流
ComfyUI-Manager-Zh-Chinese-main.zip
sdxl_prompt_styler-Zh-Chinese-main.zip
This ui will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart based interface. For some workflow examples and see what ComfyUI can do you can check out:
- Nodes/graph/flowchart interface to experiment and create complex Stable Diffusion workflows without needing to code anything.
- Fully supports SD1.x, SD2.x and SDXL
- Asynchronous Queue system
- Many optimizations: Only re-executes the parts of the workflow that changes between executions.
- Command line option:
--lowvram
to make it work on GPUs with less than 3GB vram (enabled automatically on GPUs with low vram) - Works even if you don't have a GPU with:
--cpu
(slow) - Can load ckpt, safetensors and diffusers models/checkpoints. Standalone VAEs and CLIP models.
- Embeddings/Textual inversion
- Loras (regular, locon and loha)
- Hypernetworks
- Loading full workflows (with seeds) from generated PNG files.
- Saving/Loading workflows as Json files.
- Nodes interface can be used to create complex workflows like one for Hires fix or much more advanced ones.
- Area Composition
- Inpainting with both regular and inpainting models.
- ControlNet and T2I-Adapter
- Upscale Models (ESRGAN, ESRGAN variants, SwinIR, Swin2SR, etc...)
- unCLIP Models
- GLIGEN
- Model Merging
- Latent previews with TAESD
- Starts up very fast.
- Works fully offline: will never download anything.
- Config file to set the search paths for models.
Workflow examples can be found on the Examples page
Keybind | Explanation |
---|---|
Ctrl + Enter | Queue up current graph for generation |
Ctrl + Shift + Enter | Queue up current graph as first for generation |
Ctrl + S | Save workflow |
Ctrl + O | Load workflow |
Ctrl + A | Select all nodes |
Ctrl + M | Mute/unmute selected nodes |
Delete/Backspace | Delete selected nodes |
Ctrl + Delete/Backspace | Delete the current graph |
Space | Move the canvas around when held and moving the cursor |
Ctrl/Shift + Click | Add clicked node to selection |
Ctrl + C/Ctrl + V | Copy and paste selected nodes (without maintaining connections to outputs of unselected nodes) |
Ctrl + C/Ctrl + Shift + V | Copy and paste selected nodes (maintaining connections from outputs of unselected nodes to inputs of pasted nodes) |
Shift + Drag | Move multiple selected nodes at the same time |
Ctrl + D | Load default graph |
Q | Toggle visibility of the queue |
H | Toggle visibility of history |
R | Refresh graph |
Double-Click LMB | Open node quick search palette |
Ctrl can also be replaced with Cmd instead for macOS users
There is a portable standalone build for Windows that should work for running on Nvidia GPUs or for running on your CPU only on the releases page.
Simply download, extract with 7-Zip and run. Make sure you put your Stable Diffusion checkpoints/models (the huge ckpt/safetensors files) in: ComfyUI\models\checkpoints
See the Config file to set the search paths for models. In the standalone windows build you can find this file in the ComfyUI directory. Rename this file to extra_model_paths.yaml and edit it with your favorite text editor.
To run it on colab or paperspace you can use my Colab Notebook here: Link to open with google colab
Git clone this repo.
Put your SD checkpoints (the huge ckpt/safetensors files) in: models/checkpoints
Put your VAE in: models/vae
AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
This is the command to install the nightly with ROCm 5.6 that supports the 7000 series and might have some performance improvements:
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm5.6
Nvidia users should install torch and xformers using this command:
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu118 xformers
If you get the "Torch not compiled with CUDA enabled" error, uninstall torch with:
pip uninstall torch
And install it again with the command above.
Install the dependencies by opening your terminal inside the ComfyUI folder and:
pip install -r requirements.txt
After this you should have everything installed and can proceed to running ComfyUI.
You can install ComfyUI in Apple Mac silicon (M1 or M2) with any recent macOS version.
- Install pytorch nightly. For instructions, read the Accelerated PyTorch training on Mac Apple Developer guide (make sure to install the latest pytorch nightly).
- Follow the ComfyUI manual installation instructions for Windows and Linux.
- Install the ComfyUI dependencies. If you have another Stable Diffusion UI you might be able to reuse the dependencies.
- Launch ComfyUI by running
python main.py --force-fp16
. Note that --force-fp16 will only work if you installed the latest pytorch nightly.
Note: Remember to add your models, VAE, LoRAs etc. to the corresponding Comfy folders, as discussed in ComfyUI manual installation.
pip install torch-directml
Then you can launch ComfyUI with: python main.py --directml
I already have another UI for Stable Diffusion installed do I really have to install all of these dependencies?
You don't. If you have another UI installed and working with its own python venv you can use that venv to run ComfyUI. You can open up your favorite terminal and activate it:
source path_to_other_sd_gui/venv/bin/activate
or on Windows:
With Powershell: "path_to_other_sd_gui\venv\Scripts\Activate.ps1"
With cmd.exe: "path_to_other_sd_gui\venv\Scripts\activate.bat"
And then you can use that terminal to run ComfyUI without installing any dependencies. Note that the venv folder might be called something else depending on the SD UI.
python main.py
Try running it with this command if you have issues:
For 6700, 6600 and maybe other RDNA2 or older: HSA_OVERRIDE_GFX_VERSION=10.3.0 python main.py
For AMD 7600 and maybe other RDNA3 cards: HSA_OVERRIDE_GFX_VERSION=11.0.0 python main.py
Only parts of the graph that have an output with all the correct inputs will be executed.
Only parts of the graph that change from each execution to the next will be executed, if you submit the same graph twice only the first will be executed. If you change the last part of the graph only the part you changed and the part that depends on it will be executed.
Dragging a generated png on the webpage or loading one will give you the full workflow including seeds that were used to create it.
You can use () to change emphasis of a word or phrase like: (good code:1.2) or (bad code:0.8). The default emphasis for () is 1.1. To use () characters in your actual prompt escape them like \( or \).
You can use {day|night}, for wildcard/dynamic prompts. With this syntax "{wild|card|test}" will be randomly replaced by either "wild", "card" or "test" by the frontend every time you queue the prompt. To use {} characters in your actual prompt escape them like: \{ or \}.
Dynamic prompts also support C-style comments, like // comment
or /* comment */
.
To use a textual inversion concepts/embeddings in a text prompt put them in the models/embeddings directory and use them in the CLIPTextEncode node like this (you can omit the .pt extension):
embedding:embedding_filename.pt
Make sure you use the regular loaders/Load Checkpoint node to load checkpoints. It will auto pick the right settings depending on your GPU.
You can set this command line setting to disable the upcasting to fp32 in some cross attention operations which will increase your speed. Note that this will very likely give you black images on SD2.x models. If you use xformers this option does not do anything.
--dont-upcast-attention
Use --preview-method auto
to enable previews.
The default installation includes a fast latent preview method that's low-resolution. To enable higher-quality previews with TAESD, download the taesd_decoder.pth (for SD1.x and SD2.x) and taesdxl_decoder.pth (for SDXL) models and place them in the models/vae_approx
folder. Once they're installed, restart ComfyUI to enable high-quality previews.
Matrix space: #comfyui_space:matrix.org (it's like discord but open source).
I wanted to learn how Stable Diffusion worked in detail. I also wanted something clean and powerful that would let me experiment with SD without restrictions.
This is for anyone that wants to make complex workflows with SD or that wants to learn more how SD works. The interface follows closely how SD works and the code should be much more simple to understand than other SD UIs.