mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2024-06-07 21:20:49 +00:00
115 lines
4.5 KiB
Python
115 lines
4.5 KiB
Python
from modules.api.processing import StableDiffusionProcessingAPI
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from modules.processing import StableDiffusionProcessingTxt2Img, process_images
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from modules.sd_samplers import all_samplers
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import modules.shared as shared
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import uvicorn
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from fastapi import APIRouter, HTTPException
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import json
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import io
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import base64
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from modules.api.models import *
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from PIL import Image
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from modules.extras import run_extras
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from gradio import processing_utils
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def upscaler_to_index(name: str):
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try:
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return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
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except:
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raise HTTPException(status_code=400, detail="Upscaler not found")
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sampler_to_index = lambda name: next(filter(lambda row: name.lower() == row[1].name.lower(), enumerate(all_samplers)), None)
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def img_to_base64(img: str):
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buffer = io.BytesIO()
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img.save(buffer, format="png")
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return base64.b64encode(buffer.getvalue())
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def base64_to_bytes(base64Img: str):
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if "," in base64Img:
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base64Img = base64Img.split(",")[1]
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return io.BytesIO(base64.b64decode(base64Img))
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def base64_to_images(base64Imgs: list[str]):
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imgs = []
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for img in base64Imgs:
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img = Image.open(base64_to_bytes(img))
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imgs.append(img)
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return imgs
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class Api:
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def __init__(self, app, queue_lock):
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self.router = APIRouter()
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self.app = app
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self.queue_lock = queue_lock
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self.app.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse)
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self.app.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse)
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self.app.add_api_route("/sdapi/v1/extra-batch-image", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
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def text2imgapi(self, txt2imgreq: StableDiffusionProcessingAPI ):
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sampler_index = sampler_to_index(txt2imgreq.sampler_index)
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if sampler_index is None:
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raise HTTPException(status_code=404, detail="Sampler not found")
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populate = txt2imgreq.copy(update={ # Override __init__ params
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"sd_model": shared.sd_model,
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"sampler_index": sampler_index[0],
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"do_not_save_samples": True,
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"do_not_save_grid": True
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}
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)
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p = StableDiffusionProcessingTxt2Img(**vars(populate))
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# Override object param
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with self.queue_lock:
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processed = process_images(p)
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b64images = list(map(img_to_base64, processed.images))
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return TextToImageResponse(images=b64images, parameters=json.dumps(vars(txt2imgreq)), info=json.dumps(processed.info))
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def img2imgapi(self):
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raise NotImplementedError
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def extras_single_image_api(self, req: ExtrasSingleImageRequest):
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upscaler1Index = upscaler_to_index(req.upscaler_1)
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upscaler2Index = upscaler_to_index(req.upscaler_2)
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reqDict = vars(req)
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reqDict.pop('upscaler_1')
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reqDict.pop('upscaler_2')
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reqDict['image'] = processing_utils.decode_base64_to_file(reqDict['image'])
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with self.queue_lock:
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result = run_extras(**reqDict, extras_upscaler_1=upscaler1Index, extras_upscaler_2=upscaler2Index, extras_mode=0, image_folder="", input_dir="", output_dir="")
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return ExtrasSingleImageResponse(image=processing_utils.encode_pil_to_base64(result[0]), html_info_x=result[1], html_info=result[2])
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def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
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upscaler1Index = upscaler_to_index(req.upscaler_1)
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upscaler2Index = upscaler_to_index(req.upscaler_2)
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reqDict = vars(req)
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reqDict.pop('upscaler_1')
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reqDict.pop('upscaler_2')
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reqDict['image_folder'] = list(map(processing_utils.decode_base64_to_file, reqDict['imageList']))
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reqDict.pop('imageList')
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with self.queue_lock:
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result = run_extras(**reqDict, extras_upscaler_1=upscaler1Index, extras_upscaler_2=upscaler2Index, extras_mode=1, image="", input_dir="", output_dir="")
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return ExtrasBatchImagesResponse(images=list(map(processing_utils.encode_pil_to_base64, result[0])), html_info_x=result[1], html_info=result[2])
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def extras_folder_processing_api(self):
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raise NotImplementedError
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def pnginfoapi(self):
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raise NotImplementedError
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def launch(self, server_name, port):
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self.app.include_router(self.router)
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uvicorn.run(self.app, host=server_name, port=port)
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