Merge branch 'master' into feat/progress-api (7f5212fb) · Commits · github_fork / Stable Diffusion Webui

CODEOWNERS

+12 −0

Original line number	Diff line number	Diff line
		* @AUTOMATIC1111
		/localizations/ar_AR.json @xmodar @blackneoo
		/localizations/de_DE.json @LunixWasTaken
		/localizations/es_ES.json @innovaciones
		/localizations/fr_FR.json @tumbly
		/localizations/it_IT.json @EugenioBuffo
		/localizations/ja_JP.json @yuuki76
		/localizations/ko_KR.json @36DB
		/localizations/pt_BR.json @M-art-ucci
		/localizations/ru_RU.json @kabachuha
		/localizations/tr_TR.json @camenduru
		/localizations/zh_CN.json @dtlnor @bgluminous
		/localizations/zh_TW.json @benlisquare

localizations/fr-FR.json→localizations/fr_FR.json

+0 −0

File moved.

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modules/api/api.py

+10 −4

Original line number	Diff line number	Diff line
		@@ -37,7 +37,7 @@ 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
		from modules.extras import run_extras, run_pnginfo

		# copy from wrap_gradio_gpu_call of webui.py
		# because queue lock will be acquired in api handlers
		@@ -90,6 +90,7 @@ class Api:
		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"])

		def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
		@@ -188,6 +189,14 @@ class Api:

		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):
		# copy from check_progress_call of ui.py

		@@ -210,9 +219,6 @@ class Api:

		return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.js())

		def pnginfoapi(self):
		raise NotImplementedError

		def launch(self, server_name, port):
		self.app.include_router(self.router)
		uvicorn.run(self.app, host=server_name, port=port)

modules/api/models.py

+7 −0

Original line number	Diff line number	Diff line
		import inspect
		from click import prompt
		from pydantic import BaseModel, Field, create_model
		from typing import Any, Optional
		from typing_extensions import Literal
		@@ -150,6 +151,12 @@ class ExtrasBatchImagesRequest(ExtrasBaseRequest):
		class ExtrasBatchImagesResponse(ExtraBaseResponse):
		images: list[str] = Field(title="Images", description="The generated images in base64 format.")

		class PNGInfoRequest(BaseModel):
		image: str = Field(title="Image", description="The base64 encoded PNG image")

		class PNGInfoResponse(BaseModel):
		info: str = Field(title="Image info", description="A string with all the info the image had")

		class ProgressResponse(BaseModel):
		progress: float
		eta_relative: float

modules/processing.py

+9 −3

Original line number	Diff line number	Diff line
		@@ -478,7 +478,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
		model_hijack.embedding_db.load_textual_inversion_embeddings()

		if p.scripts is not None:
		p.scripts.run_alwayson_scripts(p)
		p.scripts.process(p)

		infotexts = []
		output_images = []
		@@ -501,7 +501,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
		seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
		subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]

		if (len(prompts) == 0):
		if len(prompts) == 0:
		break

		with devices.autocast():
		@@ -590,7 +590,13 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
		images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)

		devices.torch_gc()
		return Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], all_prompts=p.all_prompts, all_seeds=p.all_seeds, all_subseeds=p.all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts)

		res = Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], all_prompts=p.all_prompts, all_seeds=p.all_seeds, all_subseeds=p.all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts)

		if p.scripts is not None:
		p.scripts.postprocess(p, res)

		return res


		class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):

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