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 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.

We also have a few things borrowed from the best parts of LeonardoAI:

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:

1. 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.
2. 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.

After Fooocus 2.3.0 you can also switch presets directly in the browser. Keep in mind to add these arguments if you want to change the default behavior:

• Use --disable-preset-selection to disable preset selection in the browser.
• Use --always-download-new-model to download missing models on preset switch. Default is fallback to previous_default_models defined in the corresponding preset, also see terminal output.

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:

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 - 2024 Mar 18 by mashb1t)

Colab	Info
	Fooocus Official

In Colab, you can modify the last line to !python entry_with_update.py --share --always-high-vram or !python entry_with_update.py --share --always-high-vram --preset anime or !python entry_with_update.py --share --always-high-vram --preset realistic for Fooocus Default/Anime/Realistic Edition.

You can also change the preset in the UI. Please be aware that this may lead to timeouts after 60 seconds. If this is the case, please wait until the download has finished, change the preset to initial and back to the one you've selected or reload the page.

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.

Using --always-high-vram shifts resource allocation from RAM to VRAM and achieves the overall best balance between performance, flexibility and stability on the default T4 instance. Please find more information here.

Thanks to camenduru for the template!

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.

1. 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.
2. Open the macOS Terminal app and clone this repository with git clone https://github.com/lllyasviel/Fooocus.git.
3. Change to the new Fooocus directory, cd Fooocus.
4. Create a new conda environment, conda env create -f environment.yaml.
5. Activate your new conda environment, conda activate fooocus.
6. Install the packages required by Fooocus, pip install -r requirements_versions.txt.
7. Launch Fooocus by running python entry_with_update.py. (Some Mac M2 users may need python entry_with_update.py --disable-offload-from-vram to 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 docker.md

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.)

* 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:

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.

In addition to running on localhost, Fooocus can also expose its UI in two ways:

• Local UI listener: use --listen (specify port e.g. with --port 8888).
• API access: use --share (registers an endpoint at .gradio.live).

In both ways the access is unauthenticated by default. You can add basic authentication by creating a file called auth.json in the main directory, which contains a list of JSON objects with the keys user and pass (see example in auth-example.json).

The below things are already inside the software, and users do not need to do anything about these.

1. GPT2-based prompt expansion as a dynamic style "Fooocus V2". (similar to Midjourney's hidden pre-processing and "raw" mode, or the LeonardoAI's Prompt Magic).
2. 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!)
3. 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 Draw Things will support Negative ADM Guidance. Great!)
4. 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.)
5. We modified the style templates a bit and added the "cinematic-default".
6. 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.
7. The parameters of samplers are carefully tuned.
8. 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.
9. 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.
10. 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.
11. A carefully designed system for balancing multiple styles as well as prompt expansion.
12. Using automatic1111's method to normalize prompt emphasizing. This significantly improves results when users directly copy prompts from civitai.
13. The joint swap system of the refiner now also supports img2img and upscale in a seamless way.
14. 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 user_path_config.txt is deprecated and will be removed soon. (Edit: it is already removed.)

entry_with_update.py  [-h] [--listen [IP]] [--port PORT]
                      [--disable-header-check [ORIGIN]]
                      [--web-upload-size WEB_UPLOAD_SIZE]
                      [--hf-mirror HF_MIRROR]
                      [--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]
                      [--vae-in-cpu]
                      [--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 [CPU_NUM_THREADS]]
                      [--always-offload-from-vram]
                      [--pytorch-deterministic] [--disable-server-log]
                      [--debug-mode] [--is-windows-embedded-python]
                      [--disable-server-info] [--multi-user] [--share]
                      [--preset PRESET] [--disable-preset-selection]
                      [--language LANGUAGE]
                      [--disable-offload-from-vram] [--theme THEME]
                      [--disable-image-log] [--disable-analytics]
                      [--disable-metadata] [--disable-preset-download]
                      [--enable-auto-describe-image]
                      [--always-download-new-model]
                      [--rebuild-hash-cache [CPU_NUM_THREADS]]

Example prompt: __color__ flower

Processed for positive and negative prompt.

Selects a random wildcard from a predefined list of options, in this case the wildcards/color.txt file. The wildcard will be replaced with a random color (randomness based on seed). You can also disable randomness and process a wildcard file from top to bottom by enabling the checkbox Read wildcards in order in Developer Debug Mode.

Wildcards can be nested and combined, and multiple wildcards can be used in the same prompt (example see wildcards/color_flower.txt).

Example prompt: [[red, green, blue]] flower

Processed only for positive prompt.

Processes the array from left to right, generating a separate image for each element in the array. In this case 3 images would be generated, one for each color. Increase the image number to 3 to generate all 3 variants.

Arrays can not be nested, but multiple arrays can be used in the same prompt. Does support inline LoRAs as array elements!

Example prompt: flower <lora:sunflowers:1.2>

Processed only for positive prompt.

Applies a LoRA to the prompt. The LoRA file must be located in the models/loras directory.

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!

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.