- 化繁为简 AI的本质应该是化繁为简，让操作更简洁，让想法更易达成。SimpleSDXL保持Fooocus的易用性，以SDXL模型生态为核心，朝着开源可控，简洁易用，功能完善的方向更进一步。
- 中文适配 中文环境与英语环境有很多差异。不仅仅在语言文字上，包括思维习惯、操作方式和网络环境都有很多不同。让中文用户使用更简单，用的更爽，也是SimpleSDXL的原始初衷。
- 场景定制 文生图和图生图有非常多的使用场景，需要更好的配置定制能力。SimpleSDXL以预置包和嵌参图片为基础，面向场景提升Fooocus的开放性和可定制性，发挥出SDXL的强大能力。
在Fooocus基础上增强功能，可无缝升级，同步迭代，并行使用。而且经过了手机适配，PC和手机也可同步操作。
Enhanced features base on Fooocus, seamless upgrading and dual versions available synchronous iteration and parallel use. Adapted to mobile, PC and phone can be used synchronously.
- 中英文混编提示词: 在线离线自主选择，支持翻译后再编辑，更适于提示词表达。
Chinese English mixed prompts: Offline and online autonomous selection, support editing after translation, more suitable for Prompt. - 图片集浏览和管理: 原生版仅能浏览当前生成的图片集，已生成图片管理非常简陋。
Finished image sets browsing and management: Fooocus only can browse the current generated image set. Finished images management is very simple. - 嵌参图片和提参重生: 增强的参数管理，可即时查看可嵌入图片，也可提取参数回填界面，二次生成。
Embeded images and extract regeneration: Enhanced parameter management for instant viewing and embedding of images, and can also extract parameters to backfill for secondary generation. - 增强预置包和模型下载: 预置包可通过界面切换和生成，模型下载会根据IP自动选择内外源。
Enhanced preset and adapted for download: The preset can be switched and generated through UI, and the model download will automatically select sources based on the access IP.
- [2023.01.20] 预置包优化版：预置包导航重构，实现session based的预置包加载，没有浏览器重载过程，更轻量更快速。预置包、嵌参图片和提参重生接口优化，扩充可预置和嵌参的范围，支持Turbo类模型和自定义风格样式的嵌参和预置。
- [2023.01.16] 新年第三版：嵌参图片上线，可以生成嵌参图片，可以上传识别嵌参图片。从参数查看到提参重生，从预置包导航到预置包生成，最后到嵌参图片，这一些列简化参数配置和使用的功能终于闭环了。启动流程优化，平行升级版支持自动获取主线配置，免配置模型目录和出图目录，新增国内下载源。界面多处优化，混编翻译器增加不翻译选项等。
- [2024.01.08] 新年第二版：图片工具增加新特性：浏览图片可自动回填提示词，联动删除坏图文件和日志记录。混编翻译器启动稳定性修补，增加不翻译模式。同步主线v2.1.861，新增风格选择浮层示意图。
- [2024.01.01] 新年新版本：界面交互优化，状态信息迁移到会话(session)，多浏览器访问互不干扰。优化了手机访问界面，PC和手机可同步使用。生成图片过程中禁止预置包切换，保障出图过程的完整。增加相册缓存，提升历史图片索引切换速度。修复模型路径bug，同步主线版本v2.1.859。
- [2023.12.30] 提示词翻译器升级：支持中英文混合编辑，支持翻译后再编辑，可自主选择本地模型翻译还是第三方接口翻译，提升提示词翻译器的总体可用性和可控性，翻译质量也能得到保障，应该是目前文生图提示词翻译器的最佳实践了。同步主线v2.1.856。
- [2023.12.28] 重要更新：底层代码结构重构，相册图集、顶部导航、右侧工具箱解耦。预置包生成流程和加载流程优化，启用MUID模型文件标识，文件名不同自动转换，本地无模型文件自动下载，自动识别embeddings模型，模型MUID标识同步改手动触发。顶部导航视觉优化，新增日志消息提示层，提取和展示Fooocus和SimpleSDXL的最新更新日志，增强互动。本次更新为由预置包和嵌参图片组成的开放系统打下基础，以实现多场景适配的定制能力。同步主线v2.1.855。
- [2023.12.20] 下载优化：启动流程针对国内网络进行优化，包括启动器瘦身，以及PyPI包索引库、项目代码库和模型库等全都选用国内源进行更新和下载。一键启动器(75M): SimpleSDXL_win64_in，提供从零开始的安装过程引导。SimpleSDXL升级包(40M): SimpleSDXL_win64_upgrade_in，提供在Fooocus已有环境上的升级，保持两个版本同时可用。同步主线版本v2.1.853，并适配了新的log.html格式。
- [2023.12.12] 新增特性：将当前环境的配置和参数生成自己的预置包，自动上到顶部导航。对接统一模型标识信息库，为预置包和带参图片分享的可用性提供基础支撑。同步主线版本v2.1.830。
- [2023.12.01] 新增特性：提取历史图片的生成参数，自动回填输入界面，可编辑后二次做生成。
- [2023.11.30] 重要更新：新增图片参数工具箱，实现图片浏览过程中对生成参数的及时查看，数据源来自于图片目录的
log.html，可以与主线版本无缝衔接。 - [2023.11.26] 重要更新：新增顶部工具条，实现了场景预置包的切换和背景切换。优化界面布局，将“出图数量”选项提高到首屏，默认中文界面、夜黑背景和高级选项打开，常用操作尽可能快捷。同步主线最新版本v2.1.824。
- [2023.11.20] 完善历史图片索引功能，新增一天内的图片分页，避免组内图片数量过大；修复其他已知bug。
- [2023.11.18] 将大部分汉化翻译移到
language/cn.json；界面上新增历史图片浏览功能，可以按照日期分组快速浏览历史生成的图片，每次进入会默认加载最新一组的最新一张。同步最新版本v2.1.821。 - [2023.11.14] 风格名称汉化，里面有太多西方专属词汇，中文用户比较少用，待改进。同步版本到v2.1.805，看到测试中的FaceSwap了 。
- [2023.11.12] 同步Fooocus最新版到v2.1.789，修订界面汉化文字，新增离线多语言翻译器：nllb-200，Prompt支持中英文混编，自动识别中文并统一翻译到英文。此功能需提前下载翻译模型到
models/translator/目录，源地址：https://huggingface.co/facebook/nllb-200-distilled-600M 。注：需要整目录下载，保留目录名。 - [2023.10.16] 初始版本，界面文字汉化，新增
--webroot参数，设定云端URL访问的根路径。如云端访问地址为：http://hostname/sdxl/ ，启动参数中需追加--webroot /sdxl。
- 中英文混合编辑 对提示词文本进行中英文切分后分别翻译再合并，适配提示词类的表达场景。
- 在线和离线翻译器 可自动安装Meta(Facebook)的离线翻译大模型，也可选择第三方翻译接口。离线模型需自身算力支持，第三方接口接入便捷成本低，但增加了接口依赖。用户可根据情况自主配置选择。
- 支持翻译后再编辑 机器翻译的结果质量都不可控，存在翻译质量差导致生成内容偏差的现象。翻译后再编辑可以显性化翻译质量，提供用户再优化调整处理的空间。
- 多大厂接口随机选 选择国内大厂（百度、阿里和搜狗）的稳定接口，每次启动时随机选择，运行态相对固定。既避免对接口冲击又保持翻译的一致性。
- 已出图片检索 对已出图片可以按照出图日期进行检索。单天出图量过大，则按照28张一个子目录分别索引，避免撑爆相册组件。
- 已出图片删除 对崩坏的已出图片可以即时删除，联动删除出图参数日志，确保图片和参数日志保持一致性。删除图片的操作入口放在了“参数工具箱”。
- 自动回填提示词 在浏览已出图片集过程中，可选择自动回填图片提示词，方便提示词的对照和修改，及图片的重生。
- 图片集交互优化 已出图片集索引栏可根据状态适配，自动收起和调整，避免目录过多挤占页面空间，干扰图片生成创作。
- 查看参数 从出图日志文件中提取当前图片的生成参数并用浮层完整展示。图集切换过程中，浮层内容跟随切换。
- 提参重生 用当前图片的生成参数覆盖默认预置包的参数，提示词回填，可以修改参数或提示词后重新出图。
- 生成预置包 将当前出图环境参数打包保存为新的预置包，将预置包文件存入presets目录下，顶部导航跟随切换。
- 扩展预置参数 扩展主线的预置包参数范围，补充开发者模式的参数，以及风格样式的定义和通配符的定义。
- 嵌参图片 将当前出图环境参数打包嵌入图片文件中，保存到专属的嵌参图片目录。嵌参图片可通过图片描述工具提取参数形成新的出图环境配置。
- 预置包导航 将presets目录下的预置包配置文件生成顶部导航入口，样式上适配明亮/暗黑两种背景。
- 背景样式导航 在顶部导航可自主切换明亮/暗黑两种背景样式。
- 预置包加载 用户点击顶部预置包导航后，调取对应配置文件，重置出图环境参数和相关配置。
- 统一模型ID和下载 对接模型信息库，使用以模型文件哈希为基础的统一模型MUID。可自动检测预置包出图环境的可用性，缺失模型文件可自动下载补齐。
- 出图保护 当系统环境进入出图状态时，顶部导航不可点击，禁止加载预置包冲击出图环境。
- 启动流程优化 对接国内模型下载源，根据接入位置区分语言和下载源。国内IP默认中文，国内源；国外IP默认英文，国外源。提供启动参数可自定义覆盖默认值，满足科学魔法的适配需求。
- 启动包瘦身 用最小必备组件进行打包，生成一键安装包，从Fooocus主线的1.8G瘦身到75M。
- 平行升级包 构建与Fooocus主线平行目录的升级包，直接读取主线的模型配置文件，免配置直接运行。升级包瘦身到40M。
- 日志消息 每次启动自动检测Fooocus主线和SimpleSDXL的更新日志，将更新消息显示到顶部消息浮层。
- 版本标识 以发布日期和版本哈希值作为SimpleSDXL的版本标识，方便定位排错。
- 云化适配 增加访问根路径启动参数，
--webroot。当在云端服务器部署，并配置前置转发后，需要配置根路径参数，避免URL路径的混乱。 - 主线同步 SimpleSDXL的增强代码保持良好的结构，与Fooocus主线版本保持良好的兼容性和扩展性，可以及时同步主线的新增能力和Bug修复。
- 算力云化 前后端分离，本机的出图算力后端可支持远程的前端出图调用，实现前端操控和出图计算的分离，让无GPU卡设备也可使用SDXL模型出图。
分两种情况:
一，在现有Fooocus环境下安装，两个版本可同时使用:
点击下载一键升级包(40M,可执行压缩包): SimpleSDXL_win64_upgrade_in。下载后点击运行将包内文件解压到现有Fooocus目录的父目录，即保证SimpleSDXL目录与Fooocus目录同级。然后启动命令行窗口cmd，进入到这个同级目录，用命令行运行run_SimpleSDXL.bat。在第一次启动后，会自动读取Fooocus的配置文件，两个版本共享相同的模型目录和图片输出目录，不用再次配置即可使用。
二，全新安装SimpleSDXL:
1, 点击下载一键启动包(75M,可执行压缩包): SimpleSDXL_win64_in。
2, 解压缩到工作目录后，点击运行：run.bat 。第一次运行会下载项目代码，然后自动安装所需的各种PyPI模块.程序启动后，还会下载基础大模型文件。虽然下载源已全部更新为国内源，但模型尺寸比较大，总体时间较长，需耐心等待。
3, 启动成功后，会自动打开浏览器，进入主界面。
一，在现有Fooocus环境下安装，两个版本可同时使用:
1, 进入与现有Fooocus目录的父目录，即保证新建的SimpleSDXL目录与Fooocus目录同级。
git clone https://github.com/metercai/SimpleSDXL.git
#国内用户可换用gitee源: https://gitee.com/metercai/SimpleSDXL.git
cd SimpleSDXL
python entry_with_update.py
# 云端部署可以配置： ip, port, webroot 等参数
# python entry_with_update.py --listen 0.0.0.0 --port 8889 --webroot /sdxl --preset realistic
# Enter English UI : --language en
# python entry_with_update.py --language en
二，全新安装SimpleSDXL:
1, 安装 Anaconda
curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
2, 安装应用环境
git clone https://github.com/metercai/SimpleSDXL.git
#国内用户可换用gitee源: https://gitee.com/metercai/SimpleSDXL.git
cd SimpleSDXL
conda env create -f environment.yaml
conda activate fooocus
pip install -r requirements_versions.txt
3, 启动服务
python entry_with_update.py
# 云端部署可以配置： ip, port, webroot 等参数
# python entry_with_update.py --listen 0.0.0.0 --port 8889 --webroot /sdxl --preset realistic
# Enter English UI : --language en
# python entry_with_update.py --language en
模型库文件同步: 条件允许的可以直接同步模型库，不用一个个下载了。
git lfs install
git clone https://huggingface.co/metercai/SimpleSDXL models
# 国内用户可以换魔搭社区的源
# git clone https://www.modelscope.cn/metercai/SimpleSDXL-models.git models
Non-cherry-picked random batch by just typing two words "forest elf",
without any parameter tweaking, without any strange prompt tags.
See also non-cherry-picked generalization and diversity tests here and here and here.
In the entire open source community, only Fooocus can achieve this level of non-cherry-picked quality.
Fooocus is an image generating software (based on Gradio).
Fooocus is a rethinking of Stable Diffusion and Midjourney’s designs:
-
Learned from Stable Diffusion, the software is offline, open source, and free.
-
Learned from Midjourney, the manual tweaking is not needed, and users only need to focus on the prompts and images.
Fooocus has included and automated lots of inner optimizations and quality improvements. Users can forget all those difficult technical parameters, and just enjoy the interaction between human and computer to "explore new mediums of thought and expanding the imaginative powers of the human species" [1].
Fooocus has simplified the installation. Between pressing "download" and generating the first image, the number of needed mouse clicks is strictly limited to less than 3. Minimal GPU memory requirement is 4GB (Nvidia).
[1] David Holz, 2019.
Recently many fake websites exist on Google when you search “fooocus”. Do not trust those – here is the only official source of Fooocus.
Using Fooocus is as easy as (probably easier than) Midjourney – but this does not mean we lack functionality. Below are the details.
| Midjourney | Fooocus |
|---|---|
| High-quality text-to-image without needing much prompt engineering or parameter tuning. (Unknown method) |
High-quality text-to-image without needing much prompt engineering or parameter tuning. (Fooocus has an offline GPT-2 based prompt processing engine and lots of sampling improvements so that results are always beautiful, no matter if your prompt is as short as “house in garden” or as long as 1000 words) |
| V1 V2 V3 V4 | Input Image -> Upscale or Variation -> Vary (Subtle) / Vary (Strong) |
| U1 U2 U3 U4 | Input Image -> Upscale or Variation -> Upscale (1.5x) / Upscale (2x) |
| Inpaint / Up / Down / Left / Right (Pan) | Input Image -> Inpaint or Outpaint -> Inpaint / Up / Down / Left / Right (Fooocus uses its own inpaint algorithm and inpaint models so that results are more satisfying than all other software that uses standard SDXL inpaint method/model) |
| Image Prompt | Input Image -> Image Prompt (Fooocus uses its own image prompt algorithm so that result quality and prompt understanding are more satisfying than all other software that uses standard SDXL methods like standard IP-Adapters or Revisions) |
| --style | Advanced -> Style |
| --stylize | Advanced -> Advanced -> Guidance |
| --niji | Multiple launchers: "run.bat", "run_anime.bat", and "run_realistic.bat". Fooocus support SDXL models on Civitai (You can google search “Civitai” if you do not know about it) |
| --quality | Advanced -> Quality |
| --repeat | Advanced -> Image Number |
| Multi Prompts (::) | Just use multiple lines of prompts |
| Prompt Weights | You can use " I am (happy:1.5)". Fooocus uses A1111's reweighting algorithm so that results are better than ComfyUI if users directly copy prompts from Civitai. (Because if prompts are written in ComfyUI's reweighting, users are less likely to copy prompt texts as they prefer dragging files) To use embedding, you can use "(embedding:file_name:1.1)" |
| --no | Advanced -> Negative Prompt |
| --ar | Advanced -> Aspect Ratios |
| InsightFace | Input Image -> Image Prompt -> Advanced -> FaceSwap |
| Describe | Input Image -> Describe |
We also have a few things borrowed from the best parts of LeonardoAI:
| LeonardoAI | Fooocus |
|---|---|
| Prompt Magic | Advanced -> Style -> Fooocus V2 |
| Advanced Sampler Parameters (like Contrast/Sharpness/etc) | Advanced -> Advanced -> Sampling Sharpness / etc |
| User-friendly ControlNets | Input Image -> Image Prompt -> Advanced |
Fooocus also developed many "fooocus-only" features for advanced users to get perfect results. Click here to browse the advanced features.
You can directly download Fooocus with:
>>> Click here to download <<<
After you download the file, please uncompress it and then run the "run.bat".
The first time you launch the software, it will automatically download models:
- It will download default models to the folder "Fooocus\models\checkpoints" given different presets. You can download them in advance if you do not want automatic download.
- Note that if you use inpaint, at the first time you inpaint an image, it will download Fooocus's own inpaint control model from here as the file "Fooocus\models\inpaint\inpaint_v26.fooocus.patch" (the size of this file is 1.28GB).
After Fooocus 2.1.60, you will also have run_anime.bat and run_realistic.bat. They are different model presets (and require different models, but they will be automatically downloaded). Check here for more details.
If you already have these files, you can copy them to the above locations to speed up installation.
Note that if you see "MetadataIncompleteBuffer" or "PytorchStreamReader", then your model files are corrupted. Please download models again.
Below is a test on a relatively low-end laptop with 16GB System RAM and 6GB VRAM (Nvidia 3060 laptop). The speed on this machine is about 1.35 seconds per iteration. Pretty impressive – nowadays laptops with 3060 are usually at very acceptable price.
Besides, recently many other software report that Nvidia driver above 532 is sometimes 10x slower than Nvidia driver 531. If your generation time is very long, consider download Nvidia Driver 531 Laptop or Nvidia Driver 531 Desktop.
Note that the minimal requirement is 4GB Nvidia GPU memory (4GB VRAM) and 8GB system memory (8GB RAM). This requires using Microsoft’s Virtual Swap technique, which is automatically enabled by your Windows installation in most cases, so you often do not need to do anything about it. However, if you are not sure, or if you manually turned it off (would anyone really do that?), or if you see any "RuntimeError: CPUAllocator", you can enable it here:
Click here to see the image instructions.
And make sure that you have at least 40GB free space on each drive if you still see "RuntimeError: CPUAllocator" !
Please open an issue if you use similar devices but still cannot achieve acceptable performances.
Note that the minimal requirement for different platforms is different.
See also the common problems and troubleshoots here.
(Last tested - 2023 Dec 12)
| Colab | Info |
|---|---|
 |
Fooocus Official |
In Colab, you can modify the last line to !python entry_with_update.py --share or !python entry_with_update.py --preset anime --share or !python entry_with_update.py --preset realistic --share for Fooocus Default/Anime/Realistic Edition.
Note that this Colab will disable refiner by default because Colab free's resources are relatively limited (and some "big" features like image prompt may cause free-tier Colab to disconnect). We make sure that basic text-to-image is always working on free-tier Colab.
Thanks to camenduru!
If you want to use Anaconda/Miniconda, you can
git clone https://github.com/lllyasviel/Fooocus.git
cd Fooocus
conda env create -f environment.yaml
conda activate fooocus
pip install -r requirements_versions.txt
Then download the models: download default models to the folder "Fooocus\models\checkpoints". Or let Fooocus automatically download the models using the launcher:
conda activate fooocus
python entry_with_update.py
Or, if you want to open a remote port, use
conda activate fooocus
python entry_with_update.py --listen
Use python entry_with_update.py --preset anime or python entry_with_update.py --preset realistic for Fooocus Anime/Realistic Edition.
Your Linux needs to have Python 3.10 installed, and let's say your Python can be called with the command python3 with your venv system working; you can
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
See the above sections for model downloads. You can launch the software with:
source fooocus_env/bin/activate
python entry_with_update.py
Or, if you want to open a remote port, use
source fooocus_env/bin/activate
python entry_with_update.py --listen
Use python entry_with_update.py --preset anime or python entry_with_update.py --preset realistic for Fooocus Anime/Realistic Edition.
If you know what you are doing, and your Linux already has Python 3.10 installed, and your Python can be called with the command python3 (and Pip with pip3), you can
git clone https://github.com/lllyasviel/Fooocus.git
cd Fooocus
pip3 install -r requirements_versions.txt
See the above sections for model downloads. You can launch the software with:
python3 entry_with_update.py
Or, if you want to open a remote port, use
python3 entry_with_update.py --listen
Use python entry_with_update.py --preset anime or python entry_with_update.py --preset realistic for Fooocus Anime/Realistic Edition.
Note that the minimal requirement for different platforms is different.
Same with the above instructions. You need to change torch to the AMD version
pip uninstall torch torchvision torchaudio torchtext functorch xformers
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.6
AMD is not intensively tested, however. The AMD support is in beta.
Use python entry_with_update.py --preset anime or python entry_with_update.py --preset realistic for Fooocus Anime/Realistic Edition.
Note that the minimal requirement for different platforms is different.
Same with Windows. Download the software and edit the content of run.bat as:
.\python_embeded\python.exe -m pip uninstall torch torchvision torchaudio torchtext functorch xformers -y
.\python_embeded\python.exe -m pip install torch-directml
.\python_embeded\python.exe -s Fooocus\entry_with_update.py --directml
pause
Then run the run.bat.
AMD is not intensively tested, however. The AMD support is in beta.
For AMD, use .\python_embeded\python.exe entry_with_update.py --directml --preset anime or .\python_embeded\python.exe entry_with_update.py --directml --preset realistic for Fooocus Anime/Realistic Edition.
Note that the minimal requirement for different platforms is different.
Mac is not intensively tested. Below is an unofficial guideline for using Mac. You can discuss problems here.
You can install Fooocus on Apple Mac silicon (M1 or M2) with macOS 'Catalina' or a newer version. Fooocus runs on Apple silicon computers via PyTorch MPS device acceleration. Mac Silicon computers don't come with a dedicated graphics card, resulting in significantly longer image processing times compared to computers with dedicated graphics cards.
- Install the conda package manager and pytorch nightly. Read the Accelerated PyTorch training on Mac Apple Developer guide for instructions. Make sure pytorch recognizes your MPS device.
- Open the macOS Terminal app and clone this repository with
git clone https://github.com/lllyasviel/Fooocus.git. - Change to the new Fooocus directory,
cd Fooocus. - Create a new conda environment,
conda env create -f environment.yaml. - Activate your new conda environment,
conda activate fooocus. - Install the packages required by Fooocus,
pip install -r requirements_versions.txt. - Launch Fooocus by running
python entry_with_update.py. (Some Mac M2 users may needpython entry_with_update.py --disable-offload-from-vramto speed up model loading/unloading.) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant amount of time, depending on your internet connection.
Use python entry_with_update.py --preset anime or python entry_with_update.py --preset realistic for Fooocus Anime/Realistic Edition.
See the guidelines here.
Below is the minimal requirement for running Fooocus locally. If your device capability is lower than this spec, you may not be able to use Fooocus locally. (Please let us know, in any case, if your device capability is lower but Fooocus still works.)
| Operating System | GPU | Minimal GPU Memory | Minimal System Memory | System Swap | Note |
|---|---|---|---|---|---|
| Windows/Linux | Nvidia RTX 4XXX | 4GB | 8GB | Required | fastest |
| Windows/Linux | Nvidia RTX 3XXX | 4GB | 8GB | Required | usually faster than RTX 2XXX |
| Windows/Linux | Nvidia RTX 2XXX | 4GB | 8GB | Required | usually faster than GTX 1XXX |
| Windows/Linux | Nvidia GTX 1XXX | 8GB (* 6GB uncertain) | 8GB | Required | only marginally faster than CPU |
| Windows/Linux | Nvidia GTX 9XX | 8GB | 8GB | Required | faster or slower than CPU |
| Windows/Linux | Nvidia GTX < 9XX | Not supported | / | / | / |
| Windows | AMD GPU | 8GB (updated 2023 Dec 30) | 8GB | Required | via DirectML (* ROCm is on hold), about 3x slower than Nvidia RTX 3XXX |
| Linux | AMD GPU | 8GB | 8GB | Required | via ROCm, about 1.5x slower than Nvidia RTX 3XXX |
| Mac | M1/M2 MPS | Shared | Shared | Shared | about 9x slower than Nvidia RTX 3XXX |
| Windows/Linux/Mac | only use CPU | 0GB | 32GB | Required | about 17x slower than Nvidia RTX 3XXX |
* AMD GPU ROCm (on hold): The AMD is still working on supporting ROCm on Windows.
* Nvidia GTX 1XXX 6GB uncertain: Some people report 6GB success on GTX 10XX, but some other people report failure cases.
Note that Fooocus is only for extremely high quality image generating. We will not support smaller models to reduce the requirement and sacrifice result quality.
See the common problems here.
Given different goals, the default models and configs of Fooocus are different:
| Task | Windows | Linux args | Main Model | Refiner | Config |
|---|---|---|---|---|---|
| General | run.bat | juggernautXL v6_RunDiffusion | not used | here | |
| Realistic | run_realistic.bat | --preset realistic | realistic_stock_photo | not used | here |
| Anime | run_anime.bat | --preset anime | bluepencil_v50 | dreamsharper_v8 (SD1.5) | here |
Note that the download is automatic - you do not need to do anything if the internet connection is okay. However, you can download them manually if you (or move them from somewhere else) have your own preparation.
List of "Hidden" Tricks
The below things are already inside the software, and users do not need to do anything about these.
- GPT2-based prompt expansion as a dynamic style "Fooocus V2". (similar to Midjourney's hidden pre-processsing and "raw" mode, or the LeonardoAI's Prompt Magic).
- Native refiner swap inside one single k-sampler. The advantage is that the refiner model can now reuse the base model's momentum (or ODE's history parameters) collected from k-sampling to achieve more coherent sampling. In Automatic1111's high-res fix and ComfyUI's node system, the base model and refiner use two independent k-samplers, which means the momentum is largely wasted, and the sampling continuity is broken. Fooocus uses its own advanced k-diffusion sampling that ensures seamless, native, and continuous swap in a refiner setup. (Update Aug 13: Actually, I discussed this with Automatic1111 several days ago, and it seems that the “native refiner swap inside one single k-sampler” is merged into the dev branch of webui. Great!)
- Negative ADM guidance. Because the highest resolution level of XL Base does not have cross attentions, the positive and negative signals for XL's highest resolution level cannot receive enough contrasts during the CFG sampling, causing the results to look a bit plastic or overly smooth in certain cases. Fortunately, since the XL's highest resolution level is still conditioned on image aspect ratios (ADM), we can modify the adm on the positive/negative side to compensate for the lack of CFG contrast in the highest resolution level. (Update Aug 16, the IOS App Drawing Things will support Negative ADM Guidance. Great!)
- We implemented a carefully tuned variation of Section 5.1 of "Improving Sample Quality of Diffusion Models Using Self-Attention Guidance". The weight is set to very low, but this is Fooocus's final guarantee to make sure that the XL will never yield an overly smooth or plastic appearance (examples here). This can almost eliminate all cases for which XL still occasionally produces overly smooth results, even with negative ADM guidance. (Update 2023 Aug 18, the Gaussian kernel of SAG is changed to an anisotropic kernel for better structure preservation and fewer artifacts.)
- We modified the style templates a bit and added the "cinematic-default".
- We tested the "sd_xl_offset_example-lora_1.0.safetensors" and it seems that when the lora weight is below 0.5, the results are always better than XL without lora.
- The parameters of samplers are carefully tuned.
- Because XL uses positional encoding for generation resolution, images generated by several fixed resolutions look a bit better than those from arbitrary resolutions (because the positional encoding is not very good at handling int numbers that are unseen during training). This suggests that the resolutions in UI may be hard coded for best results.
- Separated prompts for two different text encoders seem unnecessary. Separated prompts for the base model and refiner may work, but the effects are random, and we refrain from implementing this.
- The DPM family seems well-suited for XL since XL sometimes generates overly smooth texture, but the DPM family sometimes generates overly dense detail in texture. Their joint effect looks neutral and appealing to human perception.
- A carefully designed system for balancing multiple styles as well as prompt expansion.
- Using automatic1111's method to normalize prompt emphasizing. This significantly improves results when users directly copy prompts from civitai.
- The joint swap system of the refiner now also supports img2img and upscale in a seamless way.
- CFG Scale and TSNR correction (tuned for SDXL) when CFG is bigger than 10.
After the first time you run Fooocus, a config file will be generated at Fooocus\config.txt. This file can be edited to change the model path or default parameters.
For example, an edited Fooocus\config.txt (this file will be generated after the first launch) may look like this:
{
"path_checkpoints": "D:\\Fooocus\\models\\checkpoints",
"path_loras": "D:\\Fooocus\\models\\loras",
"path_embeddings": "D:\\Fooocus\\models\\embeddings",
"path_vae_approx": "D:\\Fooocus\\models\\vae_approx",
"path_upscale_models": "D:\\Fooocus\\models\\upscale_models",
"path_inpaint": "D:\\Fooocus\\models\\inpaint",
"path_controlnet": "D:\\Fooocus\\models\\controlnet",
"path_clip_vision": "D:\\Fooocus\\models\\clip_vision",
"path_fooocus_expansion": "D:\\Fooocus\\models\\prompt_expansion\\fooocus_expansion",
"path_outputs": "D:\\Fooocus\\outputs",
"default_model": "realisticStockPhoto_v10.safetensors",
"default_refiner": "",
"default_loras": [["lora_filename_1.safetensors", 0.5], ["lora_filename_2.safetensors", 0.5]],
"default_cfg_scale": 3.0,
"default_sampler": "dpmpp_2m",
"default_scheduler": "karras",
"default_negative_prompt": "low quality",
"default_positive_prompt": "",
"default_styles": [
"Fooocus V2",
"Fooocus Photograph",
"Fooocus Negative"
]
}Many other keys, formats, and examples are in Fooocus\config_modification_tutorial.txt (this file will be generated after the first launch).
Consider twice before you really change the config. If you find yourself breaking things, just delete Fooocus\config.txt. Fooocus will go back to default.
A safer way is just to try "run_anime.bat" or "run_realistic.bat" - they should already be good enough for different tasks.
Note that (Edit: it is already removed.)user_path_config.txt is deprecated and will be removed soon.
entry_with_update.py [-h] [--listen [IP]] [--port PORT]
[--disable-header-check [ORIGIN]]
[--web-upload-size WEB_UPLOAD_SIZE]
[--external-working-path PATH [PATH ...]]
[--output-path OUTPUT_PATH] [--temp-path TEMP_PATH]
[--cache-path CACHE_PATH] [--in-browser]
[--disable-in-browser] [--gpu-device-id DEVICE_ID]
[--async-cuda-allocation | --disable-async-cuda-allocation]
[--disable-attention-upcast] [--all-in-fp32 | --all-in-fp16]
[--unet-in-bf16 | --unet-in-fp16 | --unet-in-fp8-e4m3fn | --unet-in-fp8-e5m2]
[--vae-in-fp16 | --vae-in-fp32 | --vae-in-bf16]
[--clip-in-fp8-e4m3fn | --clip-in-fp8-e5m2 | --clip-in-fp16 | --clip-in-fp32]
[--directml [DIRECTML_DEVICE]] [--disable-ipex-hijack]
[--preview-option [none,auto,fast,taesd]]
[--attention-split | --attention-quad | --attention-pytorch]
[--disable-xformers]
[--always-gpu | --always-high-vram | --always-normal-vram |
--always-low-vram | --always-no-vram | --always-cpu]
[--always-offload-from-vram] [--disable-server-log]
[--debug-mode] [--is-windows-embedded-python]
[--disable-server-info] [--share] [--preset PRESET]
[--language LANGUAGE] [--disable-offload-from-vram]
[--theme THEME] [--disable-image-log]
Click here to browse the advanced features.
Fooocus also has many community forks, just like SD-WebUI's vladmandic/automatic and anapnoe/stable-diffusion-webui-ux, for enthusiastic users who want to try!
| Fooocus' forks |
|---|
| fenneishi/Fooocus-Control runew0lf/RuinedFooocus MoonRide303/Fooocus-MRE metercai/SimpleSDXL and so on ... |
See also About Forking and Promotion of Forks.
Special thanks to twri and 3Diva and Marc K3nt3L for creating additional SDXL styles available in Fooocus. Thanks daswer123 for contributing the Canvas Zoom!
The log is here.
We need your help! Please help translate Fooocus into international languages.
You can put json files in the language folder to translate the user interface.
For example, below is the content of Fooocus/language/example.json:
{
"Generate": "生成",
"Input Image": "入力画像",
"Advanced": "고급",
"SAI 3D Model": "SAI 3D Modèle"
}If you add --language example arg, Fooocus will read Fooocus/language/example.json to translate the UI.
For example, you can edit the ending line of Windows run.bat as
.\python_embeded\python.exe -s Fooocus\entry_with_update.py --language example
Or run_anime.bat as
.\python_embeded\python.exe -s Fooocus\entry_with_update.py --language example --preset anime
Or run_realistic.bat as
.\python_embeded\python.exe -s Fooocus\entry_with_update.py --language example --preset realistic
For practical translation, you may create your own file like Fooocus/language/jp.json or Fooocus/language/cn.json and then use flag --language jp or --language cn. Apparently, these files do not exist now. We need your help to create these files!
Note that if no --language is given and at the same time Fooocus/language/default.json exists, Fooocus will always load Fooocus/language/default.json for translation. By default, the file Fooocus/language/default.json does not exist.