DeFooocus
We are glad to introduce DeFooocus - it is a fork of the Fooocus interface, it combines some other forks and adds some convenient features.
This is just a fork (and a fork of forks), we are not the authors of this creation, all thanks to [llyasviel](https://github.com/lllyasviel).
[>>> DeFooocus on CivitAI <<<](https://civitai.com/models/519557)
## Additional features included in this fork:
### Add Photopea:
### Add rembg:
### Add Online (demos & tools):
### Others add:
- Fast presets choice (in dropdown)
- More presets (including SD1.5)
- Sound after render
- Metadata
- Special theme
- Optimize parameters and UI
- Default model is FluentlyXL v4
---
DeFooocus is an image generating software (based on [Gradio](https://www.gradio.app/)).
DeFooocus 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](#tech_list). 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 “defooocus”. Do not trust those – here is the only official source of DeFooocus.**
## [Installing DeFooocus](#download)
# Moving from Midjourney to DeFooocus
Using Fooocus is as easy as (probably easier than) Midjourney – but this does not mean we lack functionality. Below are the details.
| Midjourney | DeFooocus |
| - | - |
| 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".](https://github.com/lllyasviel/Fooocus/discussions/679)
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 | DeFooocus |
| - | - |
| 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 "defooocus-only" features for advanced users to get perfect results. [Click here to browse the advanced features.](https://github.com/lllyasviel/Fooocus/discussions/117)
# Download
### Windows
You can directly download Fooocus with:
**[>>> Click here to download <<<](https://github.com/ehristoforu/DeFooocus/releases/download/portable-release/DeFooocus_win64_portable.7z)**
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](#models) to the folder "DeFooocus\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](https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/inpaint_v26.fooocus.patch) as the file "DeFooocus\models\inpaint\inpaint_v26.fooocus.patch" (the size of this file is 1.28GB).
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](https://www.nvidia.com/download/driverResults.aspx/199991/en-us/) or [Nvidia Driver 531 Desktop](https://www.nvidia.com/download/driverResults.aspx/199990/en-us/).
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](#minimal-requirement) for different platforms is different.
See also the common problems and troubleshoots [here](troubleshoot.md).
### Switching from Fooocus to DeFooocus
1. open a terminal in your Fooocus folder (the one with your config.txt)
2. execute `git status`. You should see the following:
```
On branch main
Your branch is up to date with 'origin/main'.
nothing to commit, working tree clean
```
If not, execute `git reset --hard origin/main` and check `git status` again.
3. execute
```
git remote set-url origin https://github.com/ehristoforu/DeFooocus.git
git pull
```
6. activate your venv (not necessary when installed from 7z) and update your python packages depending on your environment (7z, venv, conda, etc.)
Example for Windows (7z): `..\python_embeded\python.exe -m pip install -r "requirements_versions.txt"`
8. start Fooocus either by opening the run.bat or corresponding entrypoint (same as before)
OR
Windows: download the [7z file](#download), extract it and run `run.bat`. You may want to copy over already downloaded checkpoints / LoRAs / etc.
### Colab
| Colab | Info
| --- | --- |
[](https://colab.research.google.com/github/ehristoforu/DeFooocus/blob/main/DeFooocus_colab.ipynb) | DeFooocus Official
### Linux (Using Anaconda)
If you want to use Anaconda/Miniconda, you can
git clone https://github.com/ehristoforu/DeFooocus.git
cd DeFooocus
conda env create -f environment.yaml
conda activate defooocus
pip install -r requirements_versions.txt
Then download the models: download [default models](#models) to the folder "DeFooocus\models\checkpoints". **Or let DeFooocus automatically download the models** using the launcher:
conda activate defooocus
python entry_with_update.py
Or, if you want to open a remote port, use
conda activate defooocus
python entry_with_update.py --listen
### Linux (Using Python Venv)
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/ehristoforu/DeFooocus.git
cd DeFooocus
python3 -m venv defooocus_env
source defooocus_env/bin/activate
pip install -r requirements_versions.txt
See the above sections for model downloads. You can launch the software with:
source defooocus_env/bin/activate
python entry_with_update.py
Or, if you want to open a remote port, use
source defooocus_env/bin/activate
python entry_with_update.py --listen
### Linux (Using native system Python)
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/ehristoforu/DeFooocus.git
cd DeFooocus
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
### Linux (AMD GPUs)
Note that the [minimal requirement](#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.
### Windows (AMD GPUs)
Note that the [minimal requirement](#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 DeFooocus\entry_with_update.py --directml
pause
Then run the `run.bat`.
AMD is not intensively tested, however. The AMD support is in beta.
### Mac
Note that the [minimal requirement](#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](https://github.com/lllyasviel/Fooocus/pull/129).
You can install DeFooocus on Apple Mac silicon (M1 or M2) with macOS 'Catalina' or a newer version. Fooocus runs on Apple silicon computers via [PyTorch](https://pytorch.org/get-started/locally/) 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](https://developer.apple.com/metal/pytorch/) Apple Developer guide for instructions. Make sure pytorch recognizes your MPS device.
1. Open the macOS Terminal app and clone this repository with `git clone https://github.com/ehristoforu/DeFooocus.git`.
1. Change to the new DeFooocus directory, `cd DeFooocus`.
1. Create a new conda environment, `conda env create -f environment.yaml`.
1. Activate your new conda environment, `conda activate defooocus`.
1. Install the packages required by Fooocus, `pip install -r requirements_versions.txt`.
1. 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 DeFooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant amount of time, depending on your internet connection.
### Docker
See [docker.md](docker.md)
## Minimal Requirement
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 DeFooocus still works.)
| Operating System | GPU | Minimal GPU Memory | Minimal System Memory | [System Swap](troubleshoot.md) | 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.*
## Troubleshoot
See the common problems [here](troubleshoot.md).
## Default Models
Given different goals, the default models and configs of Fooocus are different:
| Task | Windows | Linux args | Main Model | Refiner | Config |
| --- | --- | --- | --- | --- |--------------------------------------------------------------------------------|
| General | run.bat | | juggernautXL_v9Rundiffusion | not used | [here](https://github.com/ehristoforu/DeFooocus/blob/main/presets/default.json) |
| Realistic | run_realistic.bat | --preset realistic | realisticStockPhoto_v20 | not used | [here](https://github.com/ehristoforu/DeFooocus/blob/main/presets/realistic.json) |
| Anime | run_anime.bat | --preset anime | animaPencilXL_v100 | not used | [here](https://github.com/ehristofour/DeFooocus/blob/main/presets/anime.json) |
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.
## UI Access and Authentication
In addition to running on localhost, DeFooocus 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](./auth-example.json)).
## List of "Hidden" Tricks
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".](https://github.com/lllyasviel/Fooocus/discussions/117#raw) (similar to Midjourney's hidden pre-processsing 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]( https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12371) 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](https://apps.apple.com/us/app/draw-things-ai-generation/id6444050820) 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"](https://arxiv.org/pdf/2210.00939.pdf). 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](https://github.com/lllyasviel/Fooocus/discussions/117#sharpness)). 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.
## Customization
After the first time you run Fooocus, a config file will be generated at `DeFooocus\config.txt`. This file can be edited to change the model path or default parameters.
For example, an edited `DeFooocus\config.txt` (this file will be generated after the first launch) may look like this:
```json
{
"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 `DeFooocus\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 `DeFooocus\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.)
### All CMD Flags
```
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]
```
## Advanced Features
[Click here to browse the advanced features.](https://github.com/lllyasviel/Fooocus/discussions/117)
Fooocus also has many community forks, just like SD-WebUI's [vladmandic/automatic](https://github.com/vladmandic/automatic) and [anapnoe/stable-diffusion-webui-ux](https://github.com/anapnoe/stable-diffusion-webui-ux), for enthusiastic users who want to try!
| Fooocus' forks |
| - |
| [fenneishi/Fooocus-Control](https://github.com/fenneishi/Fooocus-Control) [runew0lf/RuinedFooocus](https://github.com/runew0lf/RuinedFooocus) [MoonRide303/Fooocus-MRE](https://github.com/MoonRide303/Fooocus-MRE) [metercai/SimpleSDXL](https://github.com/metercai/SimpleSDXL) and so on ... |
See also [About Forking and Promotion of Forks](https://github.com/lllyasviel/Fooocus/discussions/699).
## Thanks
Special thanks to [twri](https://github.com/twri) and [3Diva](https://github.com/3Diva) and [Marc K3nt3L](https://github.com/K3nt3L) for creating additional SDXL styles available in Fooocus. Thanks [daswer123](https://github.com/daswer123) for contributing the Canvas Zoom!
## Update Log
The log is [here](update_log.md).
## Localization/Translation/I18N
**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 `DeFooocus/language/example.json`:
```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 `DeFooocus/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 DeFooocus\entry_with_update.py --language example
Or `run_anime.bat` as
.\python_embeded\python.exe -s DeFooocus\entry_with_update.py --language example --preset anime
Or `run_realistic.bat` as
.\python_embeded\python.exe -s DeFooocus\entry_with_update.py --language example --preset realistic
For practical translation, you may create your own file like `DeFooocus/language/jp.json` or `DeFooocus/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 `DeFooocus/language/default.json` exists, Fooocus will always load `DeFooocus/language/default.json` for translation. By default, the file `DeFooocus/language/default.json` does not exist.