[API][Feature] - Add img2img API endpoint (a7c213d0) · Commits · github_fork / Stable Diffusion Webui

modules/api/api.py

+53 −5

Original line number	Diff line number	Diff line
		from modules.api.processing import StableDiffusionProcessingAPI
		from modules.processing import StableDiffusionProcessingTxt2Img, process_images
		from modules.api.processing import StableDiffusionTxt2ImgProcessingAPI, StableDiffusionImg2ImgProcessingAPI
		from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
		from modules.sd_samplers import all_samplers
		from modules.extras import run_pnginfo
		import modules.shared as shared
		@@ -10,6 +10,7 @@ from pydantic import BaseModel, Field, Json
		import json
		import io
		import base64
		from PIL import Image

		sampler_to_index = lambda name: next(filter(lambda row: name.lower() == row[1].name.lower(), enumerate(all_samplers)), None)

		@@ -18,6 +19,11 @@ class TextToImageResponse(BaseModel):
		parameters: Json
		info: Json

		class ImageToImageResponse(BaseModel):
		images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
		parameters: Json
		info: Json


		class Api:
		def __init__(self, app, queue_lock):
		@@ -25,8 +31,9 @@ class Api:
		self.app = app
		self.queue_lock = queue_lock
		self.app.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"])
		self.app.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"])

		def text2imgapi(self, txt2imgreq: StableDiffusionProcessingAPI ):
		def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
		sampler_index = sampler_to_index(txt2imgreq.sampler_index)

		if sampler_index is None:
		@@ -54,8 +61,49 @@ class Api:



		def img2imgapi(self):
		raise NotImplementedError
		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")


		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
		}
		)
		p = StableDiffusionProcessingImg2Img(**vars(populate))

		imgs = []
		for img in init_images:
		# if has a comma, deal with prefix
		if "," in img:
		img = img.split(",")[1]
		# convert base64 to PIL image
		img = base64.b64decode(img)
		img = Image.open(io.BytesIO(img))
		imgs = [img] * p.batch_size

		p.init_images = imgs
		# Override object param
		with self.queue_lock:
		processed = process_images(p)

		b64images = []
		for i in processed.images:
		buffer = io.BytesIO()
		i.save(buffer, format="png")
		b64images.append(base64.b64encode(buffer.getvalue()))

		return ImageToImageResponse(images=b64images, parameters=json.dumps(vars(img2imgreq)), info=json.dumps(processed.info))

		def extrasapi(self):
		raise NotImplementedError

modules/api/processing.py

+9 −2

Original line number	Diff line number	Diff line
		from array import array
		from inflection import underscore
		from typing import Any, Dict, Optional
		from pydantic import BaseModel, Field, create_model
		from modules.processing import StableDiffusionProcessingTxt2Img
		from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
		import inspect


		@@ -92,8 +93,14 @@ class PydanticModelGenerator:
		DynamicModel.__config__.allow_mutation = True
		return DynamicModel

		StableDiffusionProcessingAPI = PydanticModelGenerator(
		StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
		"StableDiffusionProcessingTxt2Img",
		StableDiffusionProcessingTxt2Img,
		[{"key": "sampler_index", "type": str, "default": "Euler"}]
		).generate_model()

		StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
		"StableDiffusionProcessingImg2Img",
		StableDiffusionProcessingImg2Img,
		[{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}]
		).generate_model()
		No newline at end of file

modules/processing.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -623,7 +623,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
		class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
		sampler = None

		def __init__(self, init_images=None, resize_mode=0, denoising_strength=0.75, mask=None, mask_blur=4, inpainting_fill=0, inpaint_full_res=True, inpaint_full_res_padding=0, inpainting_mask_invert=0, **kwargs):
		def __init__(self, init_images: list=None, resize_mode: int=0, denoising_strength: float=0.75, mask: str=None, mask_blur: int=4, inpainting_fill: int=0, inpaint_full_res: bool=True, inpaint_full_res_padding: int=0, inpainting_mask_invert: int=0, **kwargs):
		super().__init__(**kwargs)

		self.init_images = init_images

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