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from datetime import datetime | |
import urllib.request | |
import base64 | |
import json | |
import time | |
import os | |
webui_server_url = 'http://127.0.0.1:7860' | |
out_dir = 'api_out' | |
out_dir_t2i = os.path.join(out_dir, 'txt2img') | |
out_dir_i2i = os.path.join(out_dir, 'img2img') | |
os.makedirs(out_dir_t2i, exist_ok=True) | |
os.makedirs(out_dir_i2i, exist_ok=True) | |
def timestamp(): | |
return datetime.fromtimestamp(time.time()).strftime("%Y%m%d-%H%M%S") | |
def encode_file_to_base64(path): | |
with open(path, 'rb') as file: | |
return base64.b64encode(file.read()).decode('utf-8') | |
def decode_and_save_base64(base64_str, save_path): | |
with open(save_path, "wb") as file: | |
file.write(base64.b64decode(base64_str)) | |
def call_api(api_endpoint, **payload): | |
data = json.dumps(payload).encode('utf-8') | |
request = urllib.request.Request( | |
f'{webui_server_url}/{api_endpoint}', | |
headers={'Content-Type': 'application/json'}, | |
data=data, | |
) | |
response = urllib.request.urlopen(request) | |
return json.loads(response.read().decode('utf-8')) | |
def call_txt2img_api(**payload): | |
response = call_api('sdapi/v1/txt2img', **payload) | |
for index, image in enumerate(response.get('images')): | |
save_path = os.path.join(out_dir_t2i, f'txt2img-{timestamp()}-{index}.png') | |
decode_and_save_base64(image, save_path) | |
def call_img2img_api(**payload): | |
response = call_api('sdapi/v1/img2img', **payload) | |
for index, image in enumerate(response.get('images')): | |
save_path = os.path.join(out_dir_i2i, f'img2img-{timestamp()}-{index}.png') | |
decode_and_save_base64(image, save_path) | |
if __name__ == '__main__': | |
payload = { | |
"prompt": "masterpiece, (best quality:1.1), 1girl <lora:lora_model:1>", # extra networks also in prompts | |
"negative_prompt": "", | |
"seed": 1, | |
"steps": 20, | |
"width": 512, | |
"height": 512, | |
"cfg_scale": 7, | |
"sampler_name": "DPM++ 2M", | |
"n_iter": 1, | |
"batch_size": 1, | |
# example args for x/y/z plot | |
# "script_name": "x/y/z plot", | |
# "script_args": [ | |
# 1, | |
# "10,20", | |
# [], | |
# 0, | |
# "", | |
# [], | |
# 0, | |
# "", | |
# [], | |
# True, | |
# True, | |
# False, | |
# False, | |
# 0, | |
# False | |
# ], | |
# example args for Refiner and ControlNet | |
# "alwayson_scripts": { | |
# "ControlNet": { | |
# "args": [ | |
# { | |
# "batch_images": "", | |
# "control_mode": "Balanced", | |
# "enabled": True, | |
# "guidance_end": 1, | |
# "guidance_start": 0, | |
# "image": { | |
# "image": encode_file_to_base64(r"B:\path\to\control\img.png"), | |
# "mask": None # base64, None when not need | |
# }, | |
# "input_mode": "simple", | |
# "is_ui": True, | |
# "loopback": False, | |
# "low_vram": False, | |
# "model": "control_v11p_sd15_canny [d14c016b]", | |
# "module": "canny", | |
# "output_dir": "", | |
# "pixel_perfect": False, | |
# "processor_res": 512, | |
# "resize_mode": "Crop and Resize", | |
# "threshold_a": 100, | |
# "threshold_b": 200, | |
# "weight": 1 | |
# } | |
# ] | |
# }, | |
# "Refiner": { | |
# "args": [ | |
# True, | |
# "sd_xl_refiner_1.0", | |
# 0.5 | |
# ] | |
# } | |
# }, | |
# "enable_hr": True, | |
# "hr_upscaler": "R-ESRGAN 4x+ Anime6B", | |
# "hr_scale": 2, | |
# "denoising_strength": 0.5, | |
# "styles": ['style 1', 'style 2'], | |
# "override_settings": { | |
# 'sd_model_checkpoint': "sd_xl_base_1.0", # this can use to switch sd model | |
# }, | |
} | |
call_txt2img_api(**payload) | |
init_images = [ | |
encode_file_to_base64(r"B:\path\to\img_1.png"), | |
# encode_file_to_base64(r"B:\path\to\img_2.png"), | |
# "https://image.can/also/be/a/http/url.png", | |
] | |
batch_size = 2 | |
payload = { | |
"prompt": "1girl, blue hair", | |
"seed": 1, | |
"steps": 20, | |
"width": 512, | |
"height": 512, | |
"denoising_strength": 0.5, | |
"n_iter": 1, | |
"init_images": init_images, | |
"batch_size": batch_size if len(init_images) == 1 else len(init_images), | |
# "mask": encode_file_to_base64(r"B:\path\to\mask.png") | |
} | |
# if len(init_images) > 1 then batch_size should be == len(init_images) | |
# else if len(init_images) == 1 then batch_size can be any value int >= 1 | |
call_img2img_api(**payload) | |
# there exist a useful extension that allows converting of webui calls to api payload | |
# particularly useful when you wish setup arguments of extensions and scripts | |
# https://github.com/huchenlei/sd-webui-api-payload-display |
@mack
You would use prompts from a file for a program that already has descriptions of images ready to be created for the user, for example, an on-the-fly dungeon crawler game. The point of an API is that it allows for divergent use, allowing you to apply entirely different interfaces and use cases to SD, it's not always about "write description, create image."
you misunderstood what he's asking what he's asking, he's asking about the parameters to use for the Prompts from file or textbox
script a buit-in script similer to XYZ grid
basically the function of the script is to let user generate multiple images with different parameters, parameters such as prompts samplers sd model
I don't see a use case of this when using this script when using webui via API, Prompts from file or textbox
, only gives you control of a handful of different parameters, while if you use API directly you have control over everything including parameters of extensions, using Prompts from file or textbox
only adds an extra layer of complexity while giving you less control
he is not asking about reading prompts from a predetermined file/preset/configuration/template
he's asking about a script
@vincent-dl
Hi. Thanks for your great contributions and tutorials. Do you have example payloads for processing multiple images, each with different prompts (batch processing)? I noticed that each sample takes around 10 seconds, and each run takes 3GB of RAM at max. My GPU has 24GB of RAM and I wanna exploit batch processing for higher throughputs. I tried the txt2img API but it only handles 1 request at a time despite receiving many at the same time. I wonder if batch processing is possible or not? Or I have to implement some task processing scheduler such as Celery and use multiple workers at the same time ?
first you have to understand that there is a difference between batch processing and processing two jobs at once
and with batch processing there's two types of batches batch size and batch count
batch_size
is how many images it will process in parallel, using the exact same parameters
(batch count
) or in api n_iter
is running multiple times for increasing the seed
processing multiple jobs at once
it's not supported by webui
lots of parts of the code are only designed for you to only have one job being processed at a time
such as we allows a job to request switching of the current model
just think what chaos what happened if the model is unloaded doing one job by another job
if you really want to do so you could launch multiple instances of webui server, but it doesn't really make much sense doing so on single GPU system
in general when generating "normal size images" your GPU core utilization is basically already at Max
the bottleneck is the processing not the VRAM
while setting a batch size of batch count could reduce job some overhead
it is unlikely that you will see a big performance difference if you use a bigger batch size
but you have multiple GPUs then it may make sense
you just have to distribute it your request among your werbui instances
or use an extension that chains multiple webui toughter https://github.com/papuSpartan/stable-diffusion-webui-distributed
I answered a similar question just recently regarding performance AUTOMATIC1111/stable-diffusion-webui#14784 (comment)
@w-e-w thanks for your response
Hello, I would like to ask what the parameters for redrawing the area are. I would like to use redrawing only to mask the area, but it has not taken effect and has been redrawing the entire image
Hello, I would like to ask what the parameters for redrawing the area are. I would like to use redrawing only to mask the area, but it has not taken effect and has been redrawing the entire image
are you asking about Inpaint area
only masked
irrc the payload are is inpaint_full_res
: True
Is it possible to add Adetailer to the payload
Is it possible to add Adetailer to the payload
yes read the last section
Hi, trying it out on 19th April on Windows 11, Python 3.10.11 and I'm getting a HTTP Error 404: Not Found running the above example script. However when I use the requests
module instead of urllib
I can get the correct response.
Letting people know in case someone faces a similar issue
Hi, trying it out on 19th April on Windows 11, Python 3.10.11 and I'm getting a HTTP Error 404: Not Found running the above example script. However when I use the
requests
module instead ofurllib
I can get the correct response. Letting people know in case someone faces a similar issue
hey, can you share your updated code
Hi, trying it out on 19th April on Windows 11, Python 3.10.11 and I'm getting a HTTP Error 404: Not Found running the above example script. However when I use the
requests
module instead ofurllib
I can get the correct response. Letting people know in case someone faces a similar issue
Hi, I used requests but still got empty response object showing 404. Could you share you code here? Many thanks.
Hello, you have shown an example args for 'x/y/z plot' in this demo, May I ask if you can give me an example args for 'Prompts from file and textbox'
but to be honest I don't know why you would ever use
Prompts from file and textbox
in api just used API and send multiple requests to generate the images with the parameters you want, you have more freedom
Hi, this script is not working anymore. Possible updates?
When I make request at http://127.0.0.1:7860/sdapi/v1/txt2img directly using postman or using the above script (with or without requests module) I am getting 404 error. Anyone know how to fix this?
Did they remove the txt2img & img2img APIs? Please anyone gives us confirmation, thanks.
Did they remove the txt2img & img2img APIs? Please anyone gives us confirmation, thanks.
api works
... HTTP Error 404: Not Found ...
the API error message is not that descripted, we use 404 for lots of things "not found"
txt2img and img2img
- Sampler not found
img2img - Init image not found
interrogate - Image not found
- Model not found
in particular there was some change to the sampler scheduler in 1.9
we did not have the foresight to implement backwards compatibility and result in a 404 if you try to generate an image with a non-existent sampler scheduler
@w-e-w
I created a request using Postman and it says "Not found". Can you tell me what is wrong here?
Moreover, at "http://127.0.0.1:7860/docs#/" I cannot see the description for that above 2 APIs. I installed Automatic1111 v1.9.3
Moreover, at "http://127.0.0.1:7860/docs#/" I cannot see the description for that above 2 APIs. I installed Automatic1111 v1.9.3
that's odd, it's showing on mine
but since you give me practically zero information I can't really help
if I think your experiencing an issue don't ask here make an issue post
Got the same issue: "... HTTP Error 404: Not Found ..."
I searched the http://127.0.0.1:7860/docs#/, no /sdapi/v1/txt2img was found.
restart for several times, still not working.
So I search all the webui process use the following cmd:
ps -ef | grep webui.sh | grep -v grep | gawk '{ print $2 }' and kill all the pids
then I search the 7860 port use the following cmd:
netstat -antlp | grep LISTEN | grep 7860 and kill the pid again.
then I start webui again, and finally the /sdapi/v1/txt2img was shown and the api test code worked.
I don't know why.
if you guys have the same issue, try to clean all the process and restart with --api.
To whom they couldn't find /sdapi/v1/txt2img
and /sdapi/v1/img2img
endpoint in http://127.0.0.1:7860/docs:
I solved the problem by adding --api
to COMMANDLINE_ARGS
in webui-user.bat file.
To whom they couldn't find
/sdapi/v1/txt2img
and/sdapi/v1/img2img
endpoint in http://127.0.0.1:7860/docs: I solved the problem by adding--api
toCOMMANDLINE_ARGS
in webui-user.bat file.
i want to kiss u
Hi. Thanks for your great contributions and tutorials. Do you have example payloads for processing multiple images, each with different prompts (batch processing)? I noticed that each sample takes around 10 seconds, and each run takes 3GB of RAM at max. My GPU has 24GB of RAM and I wanna exploit batch processing for higher throughputs. I tried the txt2img API but it only handles 1 request at a time despite receiving many at the same time. I wonder if batch processing is possible or not? Or I have to implement some task processing scheduler such as Celery and use multiple workers at the same time ?