134 lines
4.7 KiB
Python
134 lines
4.7 KiB
Python
from modules.api.models import StableDiffusionTxt2ImgProcessingAPI, StableDiffusionImg2ImgProcessingAPI
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from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
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from modules.sd_samplers import all_samplers
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from modules.extras import run_pnginfo
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import modules.shared as shared
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import uvicorn
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from fastapi import Body, APIRouter, HTTPException
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from fastapi.responses import JSONResponse
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from pydantic import BaseModel, Field, Json
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from typing import List
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import json
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import io
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import base64
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from PIL import Image
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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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class TextToImageResponse(BaseModel):
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images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
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parameters: Json
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info: Json
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class ImageToImageResponse(BaseModel):
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images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
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parameters: Json
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info: Json
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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"])
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self.app.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"])
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def __base64_to_image(self, base64_string):
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# if has a comma, deal with prefix
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if "," in base64_string:
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base64_string = base64_string.split(",")[1]
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imgdata = base64.b64decode(base64_string)
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# convert base64 to PIL image
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return Image.open(io.BytesIO(imgdata))
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def __processed_info_to_json(self, processed):
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return json.dumps(processed.info)
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def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
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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 = []
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for i in processed.images:
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buffer = io.BytesIO()
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i.save(buffer, format="png")
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b64images.append(base64.b64encode(buffer.getvalue()))
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return TextToImageResponse(images=b64images, parameters=json.dumps(vars(txt2imgreq)), info=processed.js())
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def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI):
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sampler_index = sampler_to_index(img2imgreq.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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init_images = img2imgreq.init_images
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if init_images is None:
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raise HTTPException(status_code=404, detail="Init image not found")
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mask = img2imgreq.mask
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if mask:
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mask = self.__base64_to_image(mask)
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populate = img2imgreq.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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"mask": mask
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}
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)
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p = StableDiffusionProcessingImg2Img(**vars(populate))
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imgs = []
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for img in init_images:
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img = self.__base64_to_image(img)
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imgs = [img] * p.batch_size
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p.init_images = imgs
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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 = []
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for i in processed.images:
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buffer = io.BytesIO()
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i.save(buffer, format="png")
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b64images.append(base64.b64encode(buffer.getvalue()))
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if (not img2imgreq.include_init_images):
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# remove img2imgreq.init_images and img2imgreq.mask
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img2imgreq.init_images = None
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img2imgreq.mask = None
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return ImageToImageResponse(images=b64images, parameters=json.dumps(vars(img2imgreq)), info=processed.js())
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def extrasapi(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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