samuelbutler/stable-diffusion-docker

Runs the official Stable Diffusion release in a Docker container.

Stable Diffusion in Docker

Runs the official Stable Diffusion v1.4 release on Huggingface in a GPU accelerated Docker container.

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

Before you start

The pipeline uses the full model and weights which requires 8GB+ of GPU RAM. It should take a few seconds to create one image. On smaller GPUs you may need to modify some of the parameters, see the Examples section for more details.

Since it uses the official model, you will need to create a user access token in your Huggingface account. Save the user access token in a file called token.txt and make sure it is available when building the container.

Quickstart

The pipeline is managed using a single build.sh script. You must build the image before it can be run.

Build

Make sure your user access token is saved in a file called token.txt. The token content should begin with hf_...

To build:

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

Run

To run:

./build.sh run 'A high tech solarpunk utopia in the Amazon rainforest'

Options

Some of the options from txt2img.py are implemented for compatibility:

• --prompt [PROMPT]: the prompt to render into an image
• --n_samples [N_SAMPLES]: number of images to create per run (default 1)
• --n_iter [N_ITER]: number of times to run pipeline (default 1)
• --H [H]: image height in pixels (default 512, must be divisible by 64)
• --W [W]: image width in pixels (default 512, must be divisible by 64)
• --scale [SCALE]: unconditional guidance scale (default 7.5)
• --seed [SEED]: RNG seed for repeatability (default is a random seed)
• --ddim_steps [DDIM_STEPS]: number of sampling steps (default 50)

Other options:

• --attention-slicing: use less memory at the expense of inference speed (default is no attention slicing)
• --half: use float16 tensors instead of float32 (default float32)
• --skip: skip safety checker (default is the safety checker is on)
• --token [TOKEN]: specify a Huggingface user access token at the command line instead of reading it from a file (default is a file)

Examples

These commands are both identical:

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

Set the seed to 42:

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

Options can be combined:

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

On systems with <8GB of GPU RAM, you can try mixing and matching options:

• Make images smaller than 512x512 using --W and --H 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
• Skip the safety checker with --skip to run less code

./build.sh run --W 256 --H 256 --half --attention-slicing --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):

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.

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.