Python API client for AUTOMATIC1111/stable-diffusion-webui
Project description
sdwebuiapi
API client for AUTOMATIC1111/stable-diffusion-webui
Supports txt2img, img2img, extra-single-image, extra-batch-images API calls.
API support have to be enabled from webui. Add --api when running webui. It's explained here.
You can use --api-auth user1:pass1,user2:pass2 option to enable authentication for api access. (Since it's basic http authentication the password is transmitted in cleartext)
API calls are (almost) direct translation from http://127.0.0.1:7860/docs as of 2022/11/21.
Install
pip install webuiapi
Usage
webuiapi_demo.ipynb contains example code with original images. Images are compressed as jpeg in this document.
create API client
import webuiapi
# create API client
api = webuiapi.WebUIApi()
# create API client with custom host, port
#api = webuiapi.WebUIApi(host='127.0.0.1', port=7860)
# create API client with custom host, port and https
#api = webuiapi.WebUIApi(host='webui.example.com', port=443, use_https=True)
# create API client with default sampler, steps.
#api = webuiapi.WebUIApi(sampler='Euler a', steps=20)
# optionally set username, password when --api-auth is set on webui.
api.set_auth('username', 'password')
txt2img
result1 = api.txt2img(prompt="cute squirrel",
negative_prompt="ugly, out of frame",
seed=1003,
styles=["anime"],
cfg_scale=7,
# sampler_index='DDIM',
# steps=30,
# enable_hr=True,
# hr_scale=2,
# hr_upscaler=webuiapi.HiResUpscaler.Latent,
# hr_second_pass_steps=20,
# hr_resize_x=1536,
# hr_resize_y=1024,
# denoising_strength=0.4,
)
# images contains the returned images (PIL images)
result1.images
# image is shorthand for images[0]
result1.image
# info contains text info about the api call
result1.info
# info contains paramteres of the api call
result1.parameters
result1.image
img2img
result2 = api.img2img(images=[result1.image], prompt="cute cat", seed=5555, cfg_scale=6.5, denoising_strength=0.6)
result2.image
img2img inpainting
from PIL import Image, ImageDraw
mask = Image.new('RGB', result2.image.size, color = 'black')
# mask = result2.image.copy()
draw = ImageDraw.Draw(mask)
draw.ellipse((210,150,310,250), fill='white')
draw.ellipse((80,120,160,120+80), fill='white')
mask
inpainting_result = api.img2img(images=[result2.image],
mask_image=mask,
inpainting_fill=1,
prompt="cute cat",
seed=104,
cfg_scale=5.0,
denoising_strength=0.7)
inpainting_result.image
extra-single-image
result3 = api.extra_single_image(image=result2.image,
upscaler_1=webuiapi.Upscaler.ESRGAN_4x,
upscaling_resize=1.5)
print(result3.image.size)
result3.image
(768, 768)
extra-batch-images
result4 = api.extra_batch_images(images=[result1.image, inpainting_result.image],
upscaler_1=webuiapi.Upscaler.ESRGAN_4x,
upscaling_resize=1.5)
result4.images[0]
result4.images[1]
Scripts support
Scripts from AUTOMATIC1111's Web UI are supported, but there aren't official models that define a script's interface.
To find out the list of arguments that are accepted by a particular script look up the associated python file from
AUTOMATIC1111's repo scripts/[script_name].py
. Search for its run(p, **args)
function and the arguments that come
after 'p' is the list of accepted arguments
Example for X/Y Plot script:
(scripts/xy_grid.py file from AUTOMATIC1111's repo)
def run(self, p, x_type, x_values, y_type, y_values, draw_legend, include_lone_images, no_fixed_seeds):
...
List of accepted arguments:
- x_type: Index of the axis for X axis. Indexes start from [0: Nothing]
- x_values: String of comma-separated values for the X axis
- y_type: Index of the axis type for Y axis. As the X axis, indexes start from [0: Nothing]
- y_values: String of comma-separated values for the Y axis
- draw_legend: "True" or "False". IMPORTANT: It needs to be a string and not a Boolean value
- include_lone_images: "True" or "False". IMPORTANT: It needs to be a string and not a Boolean value
- no_fixed_seeds: "True" or "False". IMPORTANT: It needs to be a string and not a Boolean value
# Available Axis options
XYPlotAvailableScripts = [
"Nothing",
"Seed",
"Var. seed",
"Var. strength",
"Steps",
"CFG Scale",
"Prompt S/R",
"Prompt order",
"Sampler",
"Checkpoint Name",
"Hypernetwork",
"Hypernet str.",
"Sigma Churn",
"Sigma min",
"Sigma max",
"Sigma noise",
"Eta",
"Clip skip",
"Denoising",
"Hires upscaler",
"Cond. Image Mask Weight",
"VAE",
"Styles"
]
# Example call
XAxisType = "Steps"
XAxisValues = "8,16,32,64"
YAxisType = "Sampler"
YAxisValues = "k_euler_a, k_euler, k_lms, plms, k_heun, ddim, k_dpm_2, k_dpm_2_a"
drawLegend = "True"
includeSeparateImages = "False"
keepRandomSeed = "False"
result = api.txt2img(
prompt="cute squirrel",
negative_prompt="ugly, out of frame",
seed=1003,
styles=["anime"],
cfg_scale=7,
script_name="X/Y Plot",
script_args=[
XYPlotAvailableScripts.index(XAxisType),
XAxisValues,
XYPlotAvailableScripts.index(YAxisType),
YAxisValues,
drawLegend,
includeSeparateImages,
keepRandomSeed
]
)
Configuration APIs
# return map of current options
options = api.get_options()
# change sd model
options = {}
options['sd_model_checkpoint'] = 'model.ckpt [7460a6fa]'
api.set_options(options)
# when calling set_options, do not pass all options returned by get_options().
# it makes webui unusable (2022/11/21).
# get available sd models
api.get_sd_models()
# misc get apis
api.get_samplers()
api.get_cmd_flags()
api.get_hypernetworks()
api.get_face_restorers()
api.get_realesrgan_models()
api.get_prompt_styles()
api.get_artist_categories()
api.get_artists()
Utility methods
# save current model name
old_model = api.util_get_current_model()
# get list of available models
models = api.util_get_model_names()
# set model (use exact name)
api.util_set_model(models[0])
# set model (find closest match)
api.util_set_model('robodiffusion')
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
File details
Details for the file webuiapi-0.2.1-py3-none-any.whl
.
File metadata
- Download URL: webuiapi-0.2.1-py3-none-any.whl
- Upload date:
- Size: 8.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 54ecc13550adfc8f314ea0d0860c8e7d76d4a26c4824c5735dc9a9aae29f8cef |
|
MD5 | fb52cb42eee754f19b004bcb25003e92 |
|
BLAKE2b-256 | ccd43447326d0cc0030ae560899a91d9e3da7a95ac53e681d41976456d0a0ce1 |