https://github.com/fboulnois/stable-diffusion-docker

Run the official Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint.
https://github.com/fboulnois/stable-diffusion-docker

dall-e dalle diffusion docker generative-art huggingface image-generation inpainting midjourney pytorch stable-diffusion tensorflow text-to-image

Last synced: 9 days ago
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Run the official Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint.

• Host: GitHub
• URL: https://github.com/fboulnois/stable-diffusion-docker
• Owner: fboulnois
• License: agpl-3.0
• Created: 2022-08-23T01:57:45.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-12-29T01:36:15.000Z (10 months ago)
• Last Synced: 2024-10-20T19:50:10.307Z (18 days ago)
• Topics: dall-e, dalle, diffusion, docker, generative-art, huggingface, image-generation, inpainting, midjourney, pytorch, stable-diffusion, tensorflow, text-to-image
• Language: Python
• Homepage:
• Size: 666 KB
• Stars: 732
• Watchers: 10
• Forks: 126
• Open Issues: 7
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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• awesome-ai-painting - https://github.com/fboulnois/stable-diffusion-docker

README

        
# Stable Diffusion in Docker

Run the official [Stable Diffusion](https://huggingface.co/CompVis/stable-diffusion)

releases on [Huggingface](https://huggingface.co/) in a GPU accelerated Docker

container.

```sh

./build.sh run 'An impressionist painting of a parakeet eating spaghetti in the desert'

```

![An impressionist painting of a parakeet eating spaghetti in the desert 1](https://raw.githubusercontent.com/fboulnois/repository-assets/main/assets/stable-diffusion-docker/An_impressionist_painting_of_a_parakeet_eating_spaghetti_in_the_desert_s1.png)

![An impressionist painting of a parakeet eating spaghetti in the desert 2](https://raw.githubusercontent.com/fboulnois/repository-assets/main/assets/stable-diffusion-docker/An_impressionist_painting_of_a_parakeet_eating_spaghetti_in_the_desert_s2.png)

```sh

./build.sh run --image parakeet_eating_spaghetti.png --strength 0.6 'Bouquet of roses'

```

![Bouquet of roses 1](https://raw.githubusercontent.com/fboulnois/repository-assets/main/assets/stable-diffusion-docker/Bouquet_of_roses_s1.png)

![Bouquet of roses 2](https://raw.githubusercontent.com/fboulnois/repository-assets/main/assets/stable-diffusion-docker/Bouquet_of_roses_s2.png)

## Before you start

### Minimum requirements

By default, the pipeline uses the full model and weights which requires a CUDA

capable GPU with 8GB+ of VRAM. It should take a few seconds to create one image.

On less powerful GPUs you may need to modify some of the options; see the

[Examples](#examples) section for more details. If you lack a suitable GPU you

can set the options `--device cpu` and `--onnx` instead.

### Huggingface token

Since it uses the official model, you will need to create a [user access token](https://huggingface.co/docs/hub/security-tokens)

in your [Huggingface account](https://huggingface.co/settings/tokens). Save the

user access token in a file called `token.txt` and make sure it is available

when building the container. The token content should begin with `hf_...`

## Quickstart

The pipeline is managed using a single [`build.sh`](build.sh) script.

Pull the latest version of `stable-diffusion-docker` using `./build.sh pull`.

You will need to use the option `--token` to specify a valid [user access token](#huggingface-token)

when using [`./build run`](#run).

Alternately, build the image locally before running it.

## Build

Make sure your [user access token](#huggingface-token) is saved in a file called

`token.txt`.

To build:

```sh

./build.sh build  # or just ./build.sh

```

## Run

### Text-to-Image (`txt2img`)

Create an image from a text prompt.

To run:

```sh

./build.sh run 'Andromeda galaxy in a bottle'

```

### Image-to-Image (`img2img`)

Create an image from an existing image and a text prompt.

First, copy an image to the `input` folder. Next, to run:

```sh

./build.sh run --image image.png 'Andromeda galaxy in a bottle'

```

### Depth-Guided Diffusion (`depth2img`)

Modify an existing image with its depth map and a text prompt.

First, copy an image to the `input` folder. Next, to run:

```sh

./build.sh run --model 'stabilityai/stable-diffusion-2-depth' \

  --image image.png 'A detailed description of the objects to change'

```

### Instruct Pix2Pix (`pix2pix`)

Modify an existing image with a text prompt.

First, copy an image to the `input` folder. Next, to run:

```sh

./build.sh run --model 'timbrooks/instruct-pix2pix' \

  --image image.png 'A detailed description of the objects to change'

```

### Stable UnCLIP Variations (`unclip`)

Create different versions of an image with a text prompt.

First, copy an image to the `input` folder. Next, to run:

```sh

./build.sh run --model 'stabilityai/stable-diffusion-2-1-unclip-small' \

  --image image.png 'A detailed description of the image'

```

### Image Upscaling (`upscale4x`)

Create a high resolution image from an existing image with a text prompt.

First, copy an image to the `input` folder. Next, to run:

```sh

./build.sh run --model 'stabilityai/stable-diffusion-x4-upscaler' \

  --image image.png 'Andromeda galaxy in a bottle'

```

### Diffusion Inpainting (`inpaint`)

Modify specific areas of an existing image with an image mask and a text prompt.

First, copy an image and an image mask to the `input` folder. White areas of the

mask will be diffused and black areas will be kept untouched. Next, to run:

```sh

./build.sh run --model 'runwayml/stable-diffusion-inpainting' \

  --image image.png --mask mask.png 'Andromeda galaxy in a bottle'

```

## Options

The following are the most common options:

* `--prompt [PROMPT]`: the prompt to render into an image

* `--model [MODEL]`: the model used to render images (default is

`CompVis/stable-diffusion-v1-4`)

* `--height [HEIGHT]`: image height in pixels (default 512, must be divisible by 64)

* `--width [WIDTH]`: image width in pixels (default 512, must be divisible by 64)

* `--iters [ITERS]`: number of times to run pipeline (default 1)

* `--samples [SAMPLES]`: number of images to create per run (default 1)

* `--scale [SCALE]`: how closely the image should follow the prompt (default 7.5)

* `--scheduler [SCHEDULER]`: override the scheduler used to denoise the image

(default `None`)

* `--seed [SEED]`: RNG seed for repeatability (default is a random seed)

* `--steps [STEPS]`: number of sampling steps (default 50)

Other options:

* `--attention-slicing`: use less memory but decrease inference speed (default

is no attention slicing)

* `--device [DEVICE]`: the cpu or cuda device to use to render images (default

`cuda`)

* `--half`: use float16 tensors instead of float32 (default `float32`)

* `--image [IMAGE]`: the input image to use for image-to-image diffusion

(default `None`)

* `--image-scale [IMAGE_SCALE]`: how closely the image should follow the

original image (default `None`)

* `--mask [MASK]`: the input mask to use for diffusion inpainting (default

`None`)

* `--negative-prompt [NEGATIVE_PROMPT]`: the prompt to not render into an image

(default `None`)

* `--onnx`: use the onnx runtime for inference (default is off)

* `--skip`: skip safety checker (default is the safety checker is on)

* `--strength [STRENGTH]`: diffusion strength to apply to the input image

(default 0.75)

* `--token [TOKEN]`: specify a Huggingface user access token at the command line

instead of reading it from a file (default is a file)

* `--vae-slicing`: use less memory when creating large batches of images

(default is no vae slicing)

* `--vae-tiling`: use less memory when creating ultra-high resolution images but

massively decrease inference speed (default is no vae tiling)

* `--xformers-memory-efficient-attention`: use less memory but require the

xformers library (default is that xformers is not required)

Some of the original `txt2img.py` options [have been renamed](https://github.com/fboulnois/stable-diffusion-docker/issues/49)

for easy-of-use and compatibility with other pipelines:

| txt2img | stable-diffusion-docker |

|---------|-------------------------|

| `--H` | `--height` |

| `--W` | `--width` |

| `--n_iter` | `--iters` |

| `--n_samples` | `--samples` |

| `--ddim_steps` | `--steps` |

## Examples

These commands are both identical:

```sh

./build.sh run 'abstract art'

./build.sh run --prompt 'abstract art'

```

Set the seed to 42:

```sh

./build.sh run --seed 42 'abstract art'

```

Options can be combined:

```sh

./build.sh run --scale 7.0 --seed 42 'abstract art'

```

Many popular models are supported out-of-the-box:

| Model Name | Option using `--model` |

|------------|------------------------|

| [Stable Diffusion 1.4](https://huggingface.co/CompVis/stable-diffusion-v1-4) | `'CompVis/stable-diffusion-v1-4'` |

| [Stable Diffusion 1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) | `'runwayml/stable-diffusion-v1-5'` |

| [Stable Diffusion 2.0](https://huggingface.co/stabilityai/stable-diffusion-2) | `'stabilityai/stable-diffusion-2'` |

| [Stable Diffusion 2.1](https://huggingface.co/stabilityai/stable-diffusion-2-1) | `'stabilityai/stable-diffusion-2-1'` |

| [Stable Diffusion XL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) | `'stabilityai/stable-diffusion-xl-base-1.0'` |

| [OpenJourney 1.0](https://huggingface.co/prompthero/openjourney) | `'prompthero/openjourney'` |

| [Dreamlike Diffusion 1.0](https://huggingface.co/dreamlike-art/dreamlike-diffusion-1.0) | `'dreamlike-art/dreamlike-diffusion-1.0'` |

| [and more!](https://huggingface.co/models?other=stable-diffusion&sort=likes) | ... |

```sh

./build.sh run --model 'prompthero/openjourney' --prompt 'abstract art'

```

On systems without enough GPU VRAM, you can try mixing and matching options:

* Give Docker Desktop more resources by increasing the CPU, memory, and swap in

the Settings -> Resources section if the container is terminated

* Make images smaller than 512x512 using `--height` and `--width` to decrease

memory use and increase image creation speed

* Use `--half` to decrease memory use but slightly decrease image quality

* Use `--attention-slicing` to decrease memory use but also decrease image

creation speed

* Use `--xformers-memory-efficient-attention` to decrease memory use if the

pipeline and the hardware supports the option

* Decrease the number of samples and increase the number of iterations with

`--samples` and `--iters` to decrease overall memory use

* Skip the safety checker with `--skip` to run less code

```sh

./build.sh run --height 256 --width 256 --half \

  --attention-slicing --xformers-memory-efficient-attention \

  --samples 1 --iters 1 --skip --prompt 'abstract art'

```

On Windows, if you aren't using WSL2 and instead use MSYS, MinGW, or Git Bash,

prefix your commands with `MSYS_NO_PATHCONV=1` (or export it beforehand):

```sh

MSYS_NO_PATHCONV=1 ./build.sh run --half --prompt 'abstract art'

```

## Outputs

### Model

The model and other files are cached in a volume called `huggingface`. The

models are stored in `/diffusers//snapshots//unet/`.

Checkpoint files (`ckpt`s) are unofficial versions of the official models, and

so these are not part of the official release.

### Images

The images are saved as PNGs in the `output` folder using the prompt text. The

`build.sh` script creates and mounts this folder as a volume in the container.

## Contributing

See the [CONTRIBUTING.md](CONTRIBUTING.md) file for more details. In short,

follow the style guidelines, agree to the Developer Certificate of Origin, and

submit a PR.