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easyai-sdwebui-api-0.1.2
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Easy SDWebUI API - Easy API for SDWebUI, forked from mix1009/sdwebuiapi
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | easyai-sdwebui-api-0.1.2 |
| نام | easyai-sdwebui-api |
| نسخه کتابخانه | 0.1.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Freemind Core |
| ایمیل نویسنده | freemindcore@icloud.com |
| آدرس صفحه اصلی | https://github.com/freemindcore/sdwebuiapi |
| آدرس اینترنتی | https://pypi.org/project/easyai-sdwebui-api/ |
| مجوز | - |
# easyai
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](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/API).
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 easyai
```
# Usage
easyai_demo.ipynb contains example code with original images. Images are compressed as jpeg in this document.
## create API client
```
import easyai
# create API client
api = easyai.EasyAPI()
# create API client with custom host, port
#api = easyai.EasyAPI(host='127.0.0.1', port=7860)
# create API client with custom host, port and https
#api = easyai.EasyAPI(host='webui.example.com', port=443, use_https=True)
# create API client with default sampler, steps.
#api = easyai.EasyAPI(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=easyai.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=easyai.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=easyai.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/Z Plot script:
```
(scripts/xyz_grid.py file from AUTOMATIC1111's repo)
def run(self, p, x_type, x_values, y_type, y_values, z_type, z_values, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, margin_size):
...
```
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
* _z_type_: Index of the axis type for Z axis. As the X axis, indexes start from [0: Nothing]
* _z_values_: String of comma-separated values for the Z 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
* _include_sub_grids_: "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
* margin_size: int value
```
# Available Axis options (Different for txt2img and img2img!)
XYZPlotAvailableTxt2ImgScripts = [
"Nothing",
"Seed",
"Var. seed",
"Var. strength",
"Steps",
"Hires steps",
"CFG Scale",
"Prompt S/R",
"Prompt order",
"Sampler",
"Checkpoint name",
"Sigma Churn",
"Sigma min",
"Sigma max",
"Sigma noise",
"Eta",
"Clip skip",
"Denoising",
"Hires upscaler",
"VAE",
"Styles",
]
XYZPlotAvailableImg2ImgScripts = [
"Nothing",
"Seed",
"Var. seed",
"Var. strength",
"Steps",
"CFG Scale",
"Image CFG Scale",
"Prompt S/R",
"Prompt order",
"Sampler",
"Checkpoint name",
"Sigma Churn",
"Sigma min",
"Sigma max",
"Sigma noise",
"Eta",
"Clip skip",
"Denoising",
"Cond. Image Mask Weight",
"VAE",
"Styles",
]
# Example call
XAxisType = "Steps"
XAxisValues = "20,30"
YAxisType = "Sampler"
YAxisValues = "Euler a, LMS"
ZAxisType = "Nothing"
ZAxisValues = ""
drawLegend = "True"
includeLoneImages = "False"
includeSubGrids = "False"
noFixedSeeds = "False"
marginSize = 0
# x_type, x_values, y_type, y_values, z_type, z_values, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, margin_size
result = api.txt2img(
prompt="cute girl with short brown hair in black t-shirt in animation style",
seed=1003,
script_name="X/Y/Z Plot",
script_args=[
XYZPlotAvailableTxt2ImgScripts.index(XAxisType),
XAxisValues,
XYZPlotAvailableTxt2ImgScripts.index(YAxisType),
YAxisValues,
XYZPlotAvailableTxt2ImgScripts.index(ZAxisType),
ZAxisValues,
drawLegend,
includeLoneImages,
includeSubGrids,
noFixedSeeds,
marginSize, ]
)
result.image
```
### 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()
api.get_progress()
```
### 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')
# wait for job complete
api.util_wait_for_ready()
```
### LORA and alwayson_scripts example
```
r = api.txt2img(prompt='photo of a cute girl with green hair <lora:Moxin_10:0.6> shuimobysim __juice__',
seed=1000,
save_images=True,
alwayson_scripts={"Simple wildcards":[]} # wildcards extension doesn't accept more parameters.
)
r.image
```
### Extension support - Model-Keyword
```
# https://github.com/mix1009/model-keyword
mki = easyai.ModelKeywordInterface(api)
mki.get_keywords()
```
ModelKeywordResult(keywords=['nousr robot'], model='robo-diffusion-v1.ckpt', oldhash='41fef4bd', match_source='model-keyword.txt')
### Extension support - Instruct-Pix2Pix
```
# Instruct-Pix2Pix extension is now deprecated and is now part of webui.
# You can use normal img2img with image_cfg_scale when instruct-pix2pix model is loaded.
r = api.img2img(prompt='sunset', images=[pil_img], cfg_scale=7.5, image_cfg_scale=1.5)
r.image
```
### Extension support - ControlNet
```
# https://github.com/Mikubill/sd-webui-controlnet
cn = easyai.ControlNetInterface(api)
cn.model_list()
```
<pre>
['control_canny-fp16 [e3fe7712]',
'control_depth-fp16 [400750f6]',
'control_hed-fp16 [13fee50b]',
'control_mlsd-fp16 [e3705cfa]',
'control_normal-fp16 [63f96f7c]',
'control_openpose-fp16 [9ca67cc5]',
'control_scribble-fp16 [c508311e]',
'control_seg-fp16 [b9c1cc12]']
</pre>
**Use of ControlNetInterface txt2img/img2img is deprecated.** Please use the txt2img and img2img api with controlnet_units parameter.
```
# normal txt2img
r = api.txt2img(prompt="photo of a beautiful girl with blonde hair", height=512, seed=100)
img = r.image
img
```
```
# txt2img with ControlNet
unit1 = easyai.ControlNetUnit(input_image=img, module='canny', model='control_canny-fp16 [e3fe7712]')
r = api.txt2img(prompt="photo of a beautiful girl", controlnet_units=[unit1])
r.image
```
```
# img2img with multiple ControlNets
unit1 = easyai.ControlNetUnit(input_image=img, module='canny', model='control_canny-fp16 [e3fe7712]')
unit2 = easyai.ControlNetUnit(input_image=img, module='depth', model='control_depth-fp16 [400750f6]', weight=0.5)
r2 = api.img2img(prompt="girl",
images=[img],
width=512,
height=512,
controlnet_units=[unit1, unit2],
sampler_name="Euler a",
cfg_scale=7,
)
r2.image
```
```
r2.images[1]
```
```
r2.images[2]
```
نیازمندی
| مقدار | نام |
|---|---|
| - | requests |
| - | Pillow |
| - | autoflake |
| - | pre_commit |
| - | bumpversion==0.6.0 |
| - | pytest |
| - | pytest-cov |
| - | black |
| - | isort |
| - | flake8 |
| - | mypy==0.931 |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl easyai-sdwebui-api-0.1.2:
pip install easyai-sdwebui-api-0.1.2.whl
نصب پکیج tar.gz easyai-sdwebui-api-0.1.2:
pip install easyai-sdwebui-api-0.1.2.tar.gz