| # Fooocus on Docker |
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| The docker image is based on NVIDIA CUDA 12.4 and PyTorch 2.1, see [Dockerfile](Dockerfile) and [requirements_docker.txt](requirements_docker.txt) for details. |
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| ## Requirements |
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| - A computer with specs good enough to run Fooocus, and proprietary Nvidia drivers |
| - Docker, Docker Compose, or Podman |
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|
| ## Quick start |
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| **More information in the [notes](#notes).** |
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| ### Running with Docker Compose |
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| 1. Clone this repository |
| 2. Run the docker container with `docker compose up`. |
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| ### Running with Docker |
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|
| ```sh |
| docker run -p 7865:7865 -v fooocus-data:/content/data -it \ |
| --gpus all \ |
| -e CMDARGS=--listen \ |
| -e DATADIR=/content/data \ |
| -e config_path=/content/data/config.txt \ |
| -e config_example_path=/content/data/config_modification_tutorial.txt \ |
| -e path_checkpoints=/content/data/models/checkpoints/ \ |
| -e path_loras=/content/data/models/loras/ \ |
| -e path_embeddings=/content/data/models/embeddings/ \ |
| -e path_vae_approx=/content/data/models/vae_approx/ \ |
| -e path_upscale_models=/content/data/models/upscale_models/ \ |
| -e path_inpaint=/content/data/models/inpaint/ \ |
| -e path_controlnet=/content/data/models/controlnet/ \ |
| -e path_clip_vision=/content/data/models/clip_vision/ \ |
| -e path_fooocus_expansion=/content/data/models/prompt_expansion/fooocus_expansion/ \ |
| -e path_outputs=/content/app/outputs/ \ |
| ghcr.io/lllyasviel/fooocus |
| ``` |
| ### Running with Podman |
|
|
| ```sh |
| podman run -p 7865:7865 -v fooocus-data:/content/data -it \ |
| --security-opt=no-new-privileges --cap-drop=ALL --security-opt label=type:nvidia_container_t --device=nvidia.com/gpu=all \ |
| -e CMDARGS=--listen \ |
| -e DATADIR=/content/data \ |
| -e config_path=/content/data/config.txt \ |
| -e config_example_path=/content/data/config_modification_tutorial.txt \ |
| -e path_checkpoints=/content/data/models/checkpoints/ \ |
| -e path_loras=/content/data/models/loras/ \ |
| -e path_embeddings=/content/data/models/embeddings/ \ |
| -e path_vae_approx=/content/data/models/vae_approx/ \ |
| -e path_upscale_models=/content/data/models/upscale_models/ \ |
| -e path_inpaint=/content/data/models/inpaint/ \ |
| -e path_controlnet=/content/data/models/controlnet/ \ |
| -e path_clip_vision=/content/data/models/clip_vision/ \ |
| -e path_fooocus_expansion=/content/data/models/prompt_expansion/fooocus_expansion/ \ |
| -e path_outputs=/content/app/outputs/ \ |
| ghcr.io/lllyasviel/fooocus |
| ``` |
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| When you see the message `Use the app with http://0.0.0.0:7865/` in the console, you can access the URL in your browser. |
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| Your models and outputs are stored in the `fooocus-data` volume, which, depending on OS, is stored in `/var/lib/docker/volumes/` (or `~/.local/share/containers/storage/volumes/` when using `podman`). |
|
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| ## Building the container locally |
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| Clone the repository first, and open a terminal in the folder. |
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| Build with `docker`: |
| ```sh |
| docker build . -t fooocus |
| ``` |
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| Build with `podman`: |
| ```sh |
| podman build . -t fooocus |
| ``` |
|
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| ## Details |
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| ### Update the container manually (`docker compose`) |
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| When you are using `docker compose up` continuously, the container is not updated to the latest version of Fooocus automatically. |
| Run `git pull` before executing `docker compose build --no-cache` to build an image with the latest Fooocus version. |
| You can then start it with `docker compose up` |
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| ### Import models, outputs |
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| If you want to import files from models or the outputs folder, you can add the following bind mounts in the [docker-compose.yml](docker-compose.yml) or your preferred method of running the container: |
| ``` |
| #- ./models:/import/models # Once you import files, you don't need to mount again. |
| #- ./outputs:/import/outputs # Once you import files, you don't need to mount again. |
| ``` |
| After running the container, your files will be copied into `/content/data/models` and `/content/data/outputs` |
| Since `/content/data` is a persistent volume folder, your files will be persisted even when you re-run the container without the above mounts. |
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|
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| ### Paths inside the container |
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| |Path|Details| |
| |-|-| |
| |/content/app|The application stored folder| |
| |/content/app/models.org|Original 'models' folder.<br> Files are copied to the '/content/app/models' which is symlinked to '/content/data/models' every time the container boots. (Existing files will not be overwritten.) | |
| |/content/data|Persistent volume mount point| |
| |/content/data/models|The folder is symlinked to '/content/app/models'| |
| |/content/data/outputs|The folder is symlinked to '/content/app/outputs'| |
|
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| ### Environments |
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| You can change `config.txt` parameters by using environment variables. |
| **The priority of using the environments is higher than the values defined in `config.txt`, and they will be saved to the `config_modification_tutorial.txt`** |
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| Docker specified environments are there. They are used by 'entrypoint.sh' |
| |Environment|Details| |
| |-|-| |
| |DATADIR|'/content/data' location.| |
| |CMDARGS|Arguments for [entry_with_update.py](entry_with_update.py) which is called by [entrypoint.sh](entrypoint.sh)| |
| |config_path|'config.txt' location| |
| |config_example_path|'config_modification_tutorial.txt' location| |
| |HF_MIRROR| huggingface mirror site domain| |
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| You can also use the same json key names and values explained in the 'config_modification_tutorial.txt' as the environments. |
| See examples in the [docker-compose.yml](docker-compose.yml) |
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| ## Notes |
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| - Please keep 'path_outputs' under '/content/app'. Otherwise, you may get an error when you open the history log. |
| - Docker on Mac/Windows still has issues in the form of slow volume access when you use "bind mount" volumes. Please refer to [this article](https://docs.docker.com/storage/volumes/#use-a-volume-with-docker-compose) for not using "bind mount". |
| - The MPS backend (Metal Performance Shaders, Apple Silicon M1/M2/etc.) is not yet supported in Docker, see https://github.com/pytorch/pytorch/issues/81224 |
| - You can also use `docker compose up -d` to start the container detached and connect to the logs with `docker compose logs -f`. This way you can also close the terminal and keep the container running. |
