mirror of
https://github.com/openvinotoolkit/stable-diffusion-webui.git
synced 2024-12-15 07:03:06 +03:00
182 lines
6.8 KiB
Python
182 lines
6.8 KiB
Python
import time
|
|
import uvicorn
|
|
from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image
|
|
from fastapi import APIRouter, Depends, HTTPException
|
|
import modules.shared as shared
|
|
from modules import devices
|
|
from modules.api.models import *
|
|
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
|
|
from modules.sd_samplers import all_samplers
|
|
from modules.extras import run_extras, run_pnginfo
|
|
|
|
|
|
def upscaler_to_index(name: str):
|
|
try:
|
|
return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
|
|
except:
|
|
raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}")
|
|
|
|
|
|
sampler_to_index = lambda name: next(filter(lambda row: name.lower() == row[1].name.lower(), enumerate(all_samplers)), None)
|
|
|
|
|
|
def setUpscalers(req: dict):
|
|
reqDict = vars(req)
|
|
reqDict['extras_upscaler_1'] = upscaler_to_index(req.upscaler_1)
|
|
reqDict['extras_upscaler_2'] = upscaler_to_index(req.upscaler_2)
|
|
reqDict.pop('upscaler_1')
|
|
reqDict.pop('upscaler_2')
|
|
return reqDict
|
|
|
|
|
|
class Api:
|
|
def __init__(self, app, queue_lock):
|
|
self.router = APIRouter()
|
|
self.app = app
|
|
self.queue_lock = queue_lock
|
|
self.app.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse)
|
|
self.app.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse)
|
|
self.app.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse)
|
|
self.app.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
|
|
self.app.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
|
|
self.app.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse)
|
|
|
|
def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
|
|
sampler_index = sampler_to_index(txt2imgreq.sampler_index)
|
|
|
|
if sampler_index is None:
|
|
raise HTTPException(status_code=404, detail="Sampler not found")
|
|
|
|
populate = txt2imgreq.copy(update={ # Override __init__ params
|
|
"sd_model": shared.sd_model,
|
|
"sampler_index": sampler_index[0],
|
|
"do_not_save_samples": True,
|
|
"do_not_save_grid": True
|
|
}
|
|
)
|
|
p = StableDiffusionProcessingTxt2Img(**vars(populate))
|
|
# Override object param
|
|
|
|
shared.state.begin()
|
|
|
|
with self.queue_lock:
|
|
processed = process_images(p)
|
|
|
|
shared.state.end()
|
|
|
|
b64images = list(map(encode_pil_to_base64, processed.images))
|
|
|
|
return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
|
|
|
|
def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI):
|
|
sampler_index = sampler_to_index(img2imgreq.sampler_index)
|
|
|
|
if sampler_index is None:
|
|
raise HTTPException(status_code=404, detail="Sampler not found")
|
|
|
|
|
|
init_images = img2imgreq.init_images
|
|
if init_images is None:
|
|
raise HTTPException(status_code=404, detail="Init image not found")
|
|
|
|
mask = img2imgreq.mask
|
|
if mask:
|
|
mask = decode_base64_to_image(mask)
|
|
|
|
|
|
populate = img2imgreq.copy(update={ # Override __init__ params
|
|
"sd_model": shared.sd_model,
|
|
"sampler_index": sampler_index[0],
|
|
"do_not_save_samples": True,
|
|
"do_not_save_grid": True,
|
|
"mask": mask
|
|
}
|
|
)
|
|
p = StableDiffusionProcessingImg2Img(**vars(populate))
|
|
|
|
imgs = []
|
|
for img in init_images:
|
|
img = decode_base64_to_image(img)
|
|
imgs = [img] * p.batch_size
|
|
|
|
p.init_images = imgs
|
|
|
|
shared.state.begin()
|
|
|
|
with self.queue_lock:
|
|
processed = process_images(p)
|
|
|
|
shared.state.end()
|
|
|
|
b64images = list(map(encode_pil_to_base64, processed.images))
|
|
|
|
if (not img2imgreq.include_init_images):
|
|
img2imgreq.init_images = None
|
|
img2imgreq.mask = None
|
|
|
|
return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
|
|
|
|
def extras_single_image_api(self, req: ExtrasSingleImageRequest):
|
|
reqDict = setUpscalers(req)
|
|
|
|
reqDict['image'] = decode_base64_to_image(reqDict['image'])
|
|
|
|
with self.queue_lock:
|
|
result = run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", **reqDict)
|
|
|
|
return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
|
|
|
|
def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
|
|
reqDict = setUpscalers(req)
|
|
|
|
def prepareFiles(file):
|
|
file = decode_base64_to_file(file.data, file_path=file.name)
|
|
file.orig_name = file.name
|
|
return file
|
|
|
|
reqDict['image_folder'] = list(map(prepareFiles, reqDict['imageList']))
|
|
reqDict.pop('imageList')
|
|
|
|
with self.queue_lock:
|
|
result = run_extras(extras_mode=1, image="", input_dir="", output_dir="", **reqDict)
|
|
|
|
return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
|
|
|
|
def pnginfoapi(self, req: PNGInfoRequest):
|
|
if(not req.image.strip()):
|
|
return PNGInfoResponse(info="")
|
|
|
|
result = run_pnginfo(decode_base64_to_image(req.image.strip()))
|
|
|
|
return PNGInfoResponse(info=result[1])
|
|
|
|
def progressapi(self, req: ProgressRequest = Depends()):
|
|
# copy from check_progress_call of ui.py
|
|
|
|
if shared.state.job_count == 0:
|
|
return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict())
|
|
|
|
# avoid dividing zero
|
|
progress = 0.01
|
|
|
|
if shared.state.job_count > 0:
|
|
progress += shared.state.job_no / shared.state.job_count
|
|
if shared.state.sampling_steps > 0:
|
|
progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
|
|
|
|
time_since_start = time.time() - shared.state.time_start
|
|
eta = (time_since_start/progress)
|
|
eta_relative = eta-time_since_start
|
|
|
|
progress = min(progress, 1)
|
|
|
|
current_image = None
|
|
if shared.state.current_image and not req.skip_current_image:
|
|
current_image = encode_pil_to_base64(shared.state.current_image)
|
|
|
|
return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image)
|
|
|
|
def launch(self, server_name, port):
|
|
self.app.include_router(self.router)
|
|
uvicorn.run(self.app, host=server_name, port=port)
|