| # Fooocus on Docker | |
| 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. | |
| ## Requirements | |
| - A computer with specs good enough to run Fooocus, and proprietary Nvidia drivers | |
| - Docker, Docker Compose, or Podman | |
| ## Quick start | |
| **More information in the [notes](#notes).** | |
| ### Running with Docker Compose | |
| 1. Clone this repository | |
| 2. Run the docker container with `docker compose up`. | |
| ### Running with Docker | |
| ```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 | |
| ``` | |
| 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. | |
| 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`). | |
| ## Building the container locally | |
| Clone the repository first, and open a terminal in the folder. | |
| Build with `docker`: | |
| ```sh | |
| docker build . -t fooocus | |
| ``` | |
| Build with `podman`: | |
| ```sh | |
| podman build . -t fooocus | |
| ``` | |
| ## Details | |
| ### Update the container manually (`docker compose`) | |
| 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` | |
| ### Import models, outputs | |
| 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. | |
| ### Paths inside the container | |
| |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'| | |
| ### Environments | |
| 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`** | |
| 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| | |
| 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) | |
| ## Notes | |
| - 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. |