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Fooocus 本地 AI 绘图工具

新上架第 2 版 · 更新于
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概览

lllyasviel 做的开源图像生成软件,离线运行在你自己的电脑上。你写一句提示词,按下 Generate,基本不用调参数。它基于 Stable Diffusion XL,有 Windows、Linux、Mac、Colab 和 Docker 几条安装路线。项目现在只修 bug。

Fooocus 本地 AI 绘图工具 是一款 GitHub 上的开源项目,属于营销类,由 Mindket 上架。可免费获取。当前为第 2 版,最近更新于 。按它的 README 从 GitHub 安装。Mindket 的设置说明可在你的 Mindket 账户获取,以 zip 压缩包下载。

速览

用在
  • Windows with an Nvidia GPU: a downloadable archive and run.bat
  • Windows with an AMD GPU: DirectML, through an edited run.bat, in beta
  • Linux: Anaconda, a Python venv or the system Python
  • Linux with an AMD GPU: ROCm, in beta
先运行
git clone https://github.com/lllyasviel/Fooocus.git
cd Fooocus
python3 -m venv fooocus_env

平台

Docker容器
Windows操作系统
Linux操作系统

关于

它是什么

Fooocus is image generating software you run on your own computer. The README says it is offline, open source and free, and that you only focus on the prompt and the pictures, as with online generators such as Midjourney. Manual tweaking is not needed. It is built on Stable Diffusion XL and Gradio, so you use it in your browser. An offline GPT-2 based prompt engine expands a short prompt such as “house in garden”, so the result still looks good. From the same page you can upscale a picture, make variations, inpaint or outpaint, use an image as a prompt, or ask for a description of an image. The README says the project is in limited long-term support: bug fixes only, and no current plan to move to newer model architectures.

  1. You type a prompt and press Generate
  2. With the Fooocus V2 style, a GPT-2 model expands your prompt
  3. Stable Diffusion XL draws the images on your computer
  4. You upscale, vary or inpaint the one you like
  5. Images are saved in the outputs folder

适合谁

People who want pictures from text on their own computer, offline and free. It suits you if you know Midjourney or Leonardo, because the README maps their features to Fooocus’s. It also suits anyone with an Nvidia card who wants a simple browser interface over Stable Diffusion XL.

Who uses it, and how
IndustryWho uses itHow they use itExample
Digital artPeople who want pictures from textType a prompt, press Generate and pick a style under AdvancedSomeone types “house in garden” and lets the prompt engine fill in the detail.
Midjourney and Leonardo usersPeople moving to a local toolLook up each feature in the README’s two comparison listsA Midjourney user opens Input Image, then Upscale or Variation, and picks Vary (Subtle).
Photo editingPeople who fix or extend a pictureInpaint to change part of an image, Outpaint to extend itSomeone opens Input Image, chooses Inpaint or Outpaint, then picks Up, Down, Left or Right.
Local networkPeople who open the interface to other devicesLaunch with --listen, optionally a port, and add a login fileA user runs python entry_with_update.py --listen, sets a port with --port 8888 as the README suggests, and adds an auth.json file with a user and pass.

Skip it if you need newer models such as Flux. The README sends those users to WebUI Forge and ComfyUI. Skip it too if you have no GPU. The README’s table puts a CPU-only run at about 17 times slower than an Nvidia RTX 3XXX and asks for 32 GB of memory.

用在哪里

The README, and the Docker page it links, have a route for each of these.

  • Windows with an Nvidia GPU: a downloadable archive and run.bat
  • Windows with an AMD GPU: DirectML, through an edited run.bat, in beta
  • Linux: Anaconda, a Python venv or the system Python
  • Linux with an AMD GPU: ROCm, in beta
  • Mac with Apple silicon: an unofficial guide, and much slower
  • Google Colab: the official notebook, with a last line you can edit
  • Docker, Docker Compose and Podman: an image for Nvidia GPUs

如何设置

Get it saves a zip of Minda’s setup notes in your downloads folder, with a page for each platform above, one for models and config, and one for troubleshooting. On Windows with an Nvidia card, the README says to download the archive, uncompress it and run run.bat. On Windows with an AMD card you edit run.bat in the same archive. On Linux and Mac you clone the repository and install its Python packages. Colab runs the official notebook, and Docker or Podman run the ghcr.io/lllyasviel/fooocus image.

What you need first
NeedDetail
A GPUAn Nvidia RTX card with 4 GB of GPU memory is the README’s minimum. A GTX 1XXX or 9XX card needs 8 GB, and older GTX cards are not supported. An AMD card needs 8 GB, and a Mac uses shared memory
System memory8 GB, plus system swap. On Windows the swap is usually automatic. If you still see “RuntimeError: CPUAllocator”, keep 40 GB free on each drive
PythonOnly on the Linux and Mac routes: Python 3.10 for the venv and system routes, and conda for the Anaconda and Mac routes (Mac also needs PyTorch nightly)
Disk spaceRoom for the models. The first launch downloads them, and your first inpaint adds one more file of 1.28 GB
  1. Check your GPU first. Compare it with the README’s table of minimal requirements before you download anything.
  2. Get the code. On Windows, download the archive from the repository. On Linux and Mac, clone the repository.
  3. Install it. On Windows, uncompress the archive and run run.bat. On Linux and Mac, install the packages, in a conda or venv environment unless you use the system Python.
  4. Launch it and wait. The first launch downloads the default models for you.
  5. Type a prompt on its page. Open the page in your browser first.
git clone https://github.com/lllyasviel/Fooocus.git
cd Fooocus
python3 -m venv fooocus_env
source fooocus_env/bin/activate
pip install -r requirements_versions.txt

That is the README’s venv route for Linux. It launches with these two lines.

source fooocus_env/bin/activate
python entry_with_update.py

如何使用

Type a prompt and press Generate. Most other controls sit in two places. Input Image holds what you do with a picture: upscale it, vary it, inpaint or outpaint it, use it as an image prompt or ask for a description. Advanced holds the style, quality, image number, negative prompt, aspect ratios and guidance. The README maps Leonardo’s Prompt Magic to the Fooocus V2 style under Advanced.

Where a Midjourney habit lives in Fooocus
MidjourneyFooocus
V1 to V4Input Image, Upscale or Variation, then Vary (Subtle) or Vary (Strong)
U1 to U4Input Image, Upscale or Variation, then Upscale (1.5x) or Upscale (2x)
Inpaint and PanInput Image, Inpaint or Outpaint, then Inpaint, Up, Down, Left or Right
Image PromptInput Image, Image Prompt
--styleAdvanced, Style
--qualityAdvanced, Quality
--repeatAdvanced, Image Number
--noAdvanced, Negative Prompt
--arAdvanced, Aspect Ratios
DescribeInput Image, Describe

示例

You want one flower in three colors. Type the line below in the prompt box and raise the image number to 3. Fooocus makes one image for red, one for green and one for blue.

[[red, green, blue]] flower

A wildcard works the other way round. The prompt __color__ flower picks one random color from the file wildcards/color.txt, and the pick follows the seed. A LoRA goes in the prompt too: flower <lora:sunflowers:1.2> applies it when its file is in the models/loras folder.

新手与专家

新手:Fooocus is a program, not a website. A model is the file that holds what the drawing system learned, and your graphics card does the work. Fooocus fetches the models it needs when you first start it. The README warns that fake Fooocus sites exist, so get it from the repository. On Windows, run_realistic.bat and run_anime.bat load different models than run.bat. Start with run.bat, write a plain sentence and press Generate. If the console shows “RuntimeError: CPUAllocator”, a crash such as Segmentation Fault or Killed, or closes in a flash, the troubleshooting page blames too little system swap. A “CUDA Out Of Memory” on an Nvidia card with 8 GB, or 4 GB with Float16 support, is a bug to report. On 6 GB it says very likely a bug.

专家:The README lists the sampling work as tricks, and says they are based on SDXL and are not very up to date with the latest models. They include a refiner swap inside a single k-sampler, negative ADM guidance, a tuned form of self-attention guidance, and CFG scale with TSNR correction above 10. Prompt weights use A1111’s reweighting, which the README says suits prompts copied from Civitai. After the first launch, config.txt sets the defaults, and the usage line lists many flags, from --always-high-vram to --preset and --language. The lines below are an excerpt of the README’s example of an edited config.txt.

{
    "default_model": "realisticStockPhoto_v10.safetensors",
    "default_cfg_scale": 3.0,
    "default_sampler": "dpmpp_2m",
    "default_scheduler": "karras"
}

注意事项

Fooocus runs on your machine, and a few paths reach out.

  • Status: the README says it is in limited long-term support, with bug fixes only. For newer models it names WebUI Forge, ComfyUI and SwarmUI
  • Official source: the README says its GitHub page is the only official source. It lists fooocus.com, fooocus.net, fooocus.co, fooocus.ai, fooocus.org, fooocus.pro and fooocus.one as fake sites with no tie to the maker
  • Network: --listen and --share expose the interface, and both are unauthenticated unless you add an auth.json file with a user and a pass for each login
  • Downloads: the first launch downloads models, and the README names a Hugging Face address for the inpaint model. It does not cover the licenses of the models you download
  • Flags: the README’s flag list includes --disable-analytics, --disable-image-log and --disable-metadata, and does not describe them
  • Hardware: Nvidia is the main route. AMD support is in beta, Mac is unofficial, and the troubleshooting page blames too little system swap for most crashes
  • Removal: the README gives no steps. On Windows you delete the folder you extracted
  • License: GPL-3.0. The LICENSE file is the standard GNU General Public License version 3 text, with no copyright line for the maker

README 和文件

README

Fooocus:安装说明

这个工具包里只有安装说明,由 Mindket 编写。Fooocus 本身要从它作者的仓库获取,地址是 https://github.com/lllyasviel/Fooocus

这些说明不是 lllyasviel 写的,也没有得到 lllyasviel 的认可。GitHub 的项目描述是“Focus on prompting and generating”。README 把 Fooocus 称为“an image generating software (based on Gradio)”,并说它“offline, open source, and free”,意思是:一款基于 Gradio 的图像生成软件,离线、开源、免费。

许可证:GPL-3.0。LICENSE 文件(https://github.com/lllyasviel/Fooocus/blob/main/LICENSE)是标准的 GNU 通用公共许可证第 3 版文本,日期为 2007 年 6 月 29 日,文末附录保留着占位行 Copyright (C) <year> <name of author>,所以没有写明版权持有人。这个工具包不含 Fooocus 的任何代码。

先读这里

  • 项目状态。 README 说 Fooocus 基于 Stable Diffusion XL 架构,现在处于“limited long-term support (LTS) with bug fixes only”,也就是有限的长期支持,只修 bug。它说目前没有迁移到新模型架构的计划。需要 Flux 这样的新模型时,它指向 WebUI Forge 和 ComfyUI 或 SwarmUI。
  • 唯一官方来源。 README 说在 Google 上搜“fooocus”会出现很多假网站,GitHub 页面才是唯一官方来源。它把这些列为假网站:fooocus.com、fooocus.net、fooocus.co、fooocus.ai、fooocus.org、fooocus.pro 和 fooocus.one。只从仓库下载。
  • 显卡是主要路线。 README 的最低要求是 4 GB 显存的 Nvidia RTX 显卡和 8 GB 系统内存。AMD 显卡、Apple 芯片和只用 CPU 的运行方式(32 GB 系统内存,大约比 RTX 3XXX 慢 17 倍)也能用,但有限制,见 setup/models-and-config.md。

会安装什么

  • 在 Windows 上,是仓库 Releases 里的一个 .7z 压缩包,里面有程序、它自带的 Python,以及启动文件 run.bat、run_anime.bat 和 run_realistic.bat。来源见 https://github.com/lllyasviel/Fooocus/blob/main/readme.md
  • 在 Linux 和 Mac 上,是用 git clone 得到的仓库代码,再加上 requirements_versions.txt 里的 Python 包。走 Anaconda 和 Mac 路线时,先用 environment.yaml 建好 conda 环境,再把这些包装进去。
  • 在 Colab 上,你的电脑里什么都不装:官方笔记本在 Colab 会话里运行 Fooocus。
  • 用 Docker 或 Podman 的话,是镜像 ghcr.io/lllyasviel/fooocus,或者你用仓库自己构建的镜像。
  • 第一次启动时会下载模型。README 说 Fooocus 会下载你所启动预设的默认模型,第一次局部重绘时还会下载它自己的局部重绘模型。README 给出这个文件的大小是 1.28 GB。

事先需要准备

  • README 的最低要求是 4 GB 显存或更多的 Nvidia RTX 显卡。GTX 1XXX 和 9XX 需要 8 GB,更老的 GTX 显卡不支持。Docker 页面还要求安装专有的 Nvidia 驱动。
  • 8 GB 系统内存。故障排查页要求至少 40 GB 系统交换空间,并说 Windows 10 和 11 会替你建好,所以在那里只要每个磁盘至少留出 40 GB 空闲空间。
  • 不用 conda 的 Linux 需要 Python 3.10。来源见 README 的“Linux (Using Python Venv)”一节。

各平台说明

  • setup/windows.md:压缩包、三个启动文件,以及通过 DirectML 使用 AMD 显卡
  • setup/linux.md:conda、venv、系统 Python,以及通过 ROCm 使用 AMD 显卡
  • setup/mac.md:Apple 芯片,非官方
  • setup/colab.md:官方笔记本
  • setup/docker.md:Docker、Docker Compose 和 Podman
  • setup/models-and-config.md:默认模型、预设、config.txt、参数、网络访问、通配符和数组
  • setup/troubleshooting.md:作者列出的常见错误

更新或卸载

README 没有单独给出更新步骤。它的启动命令用的是 entry_with_update.py,README 没有说这个文件更新什么。想要旧版本的话,README 指向 https://github.com/lllyasviel/Fooocus/discussions/1405,并说更新日志是仓库里的 update_log.md。

README 没有给出卸载步骤。在 Windows 路线上,程序、它的 python_embeded 文件夹和 Fooocus\models 文件夹都在你解压出的那个文件夹里,删掉它就移除了这些。在 Linux 和 Mac 上,删掉你克隆的文件夹和你建的 conda 或 venv 环境。走系统 Python 路线的话,requirements_versions.txt 里的包会留在你的系统 Python 里,README 没有给出移除它们的步骤。你在 config.txt 里把模型或输出路径指到别处的话,那些东西会一直留着,直到你自己删除。

来源

  • README:https://github.com/lllyasviel/Fooocus/blob/main/readme.md
  • Docker 页面:https://github.com/lllyasviel/Fooocus/blob/main/docker.md
  • 故障排查页:https://github.com/lllyasviel/Fooocus/blob/main/troubleshoot.md
  • LICENSE:https://github.com/lllyasviel/Fooocus/blob/main/LICENSE
文件
README.md  5 KB
setup/colab.md  2 KB
setup/docker.md  6 KB
setup/linux.md  3 KB
setup/mac.md  2 KB
setup/models-and-config.md  9 KB
setup/troubleshooting.md  4 KB
setup/windows.md  3 KB

8 个文件,共 33 KB,以 zip 压缩包下载。

更新内容

  • 第 2 版 · 2026-11-09

    Updated by Mindket to the current version of this kit.

  • 第 1 版 · 2026-11-03

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大家怎么说

Hacker News、Bluesky、X、Reddit、Facebook 和 YouTube 上提到这个项目的帖子和评论,来自每周一次的搜索和 Trendshift。它们不是 Mindket 写的,也未经核实,点开即可在原帖处阅读。

somenameformeChatGPT Images 2.5Should probably mention this as a root comment, but various local image gen models like fooocus [1] run on basically any remotely modern hardware, have phenomenal output quality, and cost basically nothing. I think companies trying to sell image gen at this point are just banking on ignorance. [1]…@quon-echosphere.bsky.socialまず褒める側。Fooocus公式は offline, open source, free、初回画像まで3クリック未満・最低4GB VRAM と明記。Ollama公式もローカル実行自体は本当。ここは盛りすぎじゃない。https://github.com/lllyasviel/Fooocus https://docs.ollama.com/faq1 条回复@cyrilXBTAgencies charge $3,000 a month to run an Instagram page. This stack does it for almost NOTHING. 10 open source repos that turn one idea into a posted reel: 1. ComfyUI: generate the visuals https://t.co/xHdCsQKRFV 2. Fooocus: pro images in one prompt https://t.co/plpYUkhvo8 3. ControlNet: lock in…r/StableDiffusionI built a Fooocus-style local studio for Qwen-Image 2.1: masks, annotations, outpainting, OpenPose poses and sketches as references. Looking for honest…somenameformeI love LLMs, I hate hypeSure, for a balance between usability and power I'd recommend fooocus. [1] AmuseAI [2] is an alternative that is extremely plug-and-play which can be especially handy with AMD hardware, but is a bit less powerful and also censored by default. ComfyUI [3] is an advanced tool for rich customization…ChiefGyk3DI just starred lllyasviel/Fooocus on GitHub: https://github.com/lllyasviel/Fooocus1 赞@Crypto_QianXun2. Ollama GPT-4 级别的 AI 模型,直接跑在自己电脑上。 无需调用 API,无需付费。 https://t.co/KVqIgn52LDvunderbaGreatest irony of the AI age: Humans hired to clean AI slopMinor correction. FOOCUS [1] isn't a LoRA - it's a Gradio-based frontend (in the same vein as Automatic1111, Forge, etc.) for image generation. And most SOTA models (Imagen, Qwen 20b, etc) at this point can actually already handle a fair amount of text in a single T2I generation. Flux Dev provided…EUVD Bot🚨 EUVD-2025-210684 📊 9.3/10 🏢 lllyasviel 📝 Fooocus is an image generating software. In versions 2.5.5 and prior, the Fooocus web UI is vulnerable to remote code execution due to the unsafe use... 🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2025-210684 #cybersecurity #infosec #cve #euvd@AsWill11Top 10 Open Creative Media Tools: 1. SD WebUI - https://t.co/bU2MftMMLh 2. ComfyUI - https://t.co/il7DyLf4SY 3. MoneyPrinterTurbo - https://t.co/rCp1zg8WAS 4. VoiceStudio - https://t.co/bHOHpeZJz9 5. HyperFrames - https://t.co/r0ckNK9nRf 6. GPT-SoVITS - https://t.co/8tTq9atGJb 7. whisper.cpp -…ykAI model for near-instant image creation on consumer-grade hardwareFor runtime, I use ComfyUi [0] which is node based and therefore a bit hard to learn. But you can just look at the examples on their github. Foocus [1] also seems to be popular and a bit more conventional perhaps, though I didn't try it. For models, Flux [2] is pretty good and quite…STACKFLAGCVE-2025-31114 - fooocus The Fooocus image generating software has a security issue in its web interface. This means an attacker could potentially take control of the software if they gain access to it.… Too many irrelevant or confusing CVEs? Use stackflag.com #fooocus #lllyasviel #CVE #infosec

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