Merge branch 'master' into feat/progress-api
This commit is contained in:
commit
7f5212fb5f
12
CODEOWNERS
12
CODEOWNERS
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@ -1 +1,13 @@
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* @AUTOMATIC1111
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/localizations/ar_AR.json @xmodar @blackneoo
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/localizations/de_DE.json @LunixWasTaken
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/localizations/es_ES.json @innovaciones
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/localizations/fr_FR.json @tumbly
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/localizations/it_IT.json @EugenioBuffo
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/localizations/ja_JP.json @yuuki76
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/localizations/ko_KR.json @36DB
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/localizations/pt_BR.json @M-art-ucci
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/localizations/ru_RU.json @kabachuha
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/localizations/tr_TR.json @camenduru
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/localizations/zh_CN.json @dtlnor @bgluminous
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/localizations/zh_TW.json @benlisquare
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@ -37,7 +37,7 @@ from modules import devices
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from modules.api.models import *
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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_extras
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from modules.extras import run_extras, run_pnginfo
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# copy from wrap_gradio_gpu_call of webui.py
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# because queue lock will be acquired in api handlers
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@ -90,6 +90,7 @@ class Api:
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self.app.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse)
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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-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
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self.app.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
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self.app.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"])
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def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
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@ -188,6 +189,14 @@ class Api:
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return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
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def pnginfoapi(self, req: PNGInfoRequest):
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if(not req.image.strip()):
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return PNGInfoResponse(info="")
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result = run_pnginfo(decode_base64_to_image(req.image.strip()))
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return PNGInfoResponse(info=result[1])
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def progressapi(self):
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# copy from check_progress_call of ui.py
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@ -210,9 +219,6 @@ class Api:
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return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.js())
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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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@ -1,4 +1,5 @@
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import inspect
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from click import prompt
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from pydantic import BaseModel, Field, create_model
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from typing import Any, Optional
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from typing_extensions import Literal
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@ -150,6 +151,12 @@ class ExtrasBatchImagesRequest(ExtrasBaseRequest):
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class ExtrasBatchImagesResponse(ExtraBaseResponse):
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images: list[str] = Field(title="Images", description="The generated images in base64 format.")
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class PNGInfoRequest(BaseModel):
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image: str = Field(title="Image", description="The base64 encoded PNG image")
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class PNGInfoResponse(BaseModel):
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info: str = Field(title="Image info", description="A string with all the info the image had")
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class ProgressResponse(BaseModel):
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progress: float
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eta_relative: float
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@ -478,7 +478,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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model_hijack.embedding_db.load_textual_inversion_embeddings()
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if p.scripts is not None:
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p.scripts.run_alwayson_scripts(p)
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p.scripts.process(p)
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infotexts = []
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output_images = []
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@ -501,7 +501,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
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subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
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if (len(prompts) == 0):
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if len(prompts) == 0:
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break
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with devices.autocast():
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@ -590,7 +590,13 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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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)
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devices.torch_gc()
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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)
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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)
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if p.scripts is not None:
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p.scripts.postprocess(p, res)
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return res
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class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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@ -64,7 +64,16 @@ class Script:
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def process(self, p, *args):
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"""
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This function is called before processing begins for AlwaysVisible scripts.
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scripts. You can modify the processing object (p) here, inject hooks, etc.
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You can modify the processing object (p) here, inject hooks, etc.
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args contains all values returned by components from ui()
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"""
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pass
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def postprocess(self, p, processed, *args):
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"""
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This function is called after processing ends for AlwaysVisible scripts.
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args contains all values returned by components from ui()
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"""
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pass
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@ -289,13 +298,22 @@ class ScriptRunner:
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return processed
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def run_alwayson_scripts(self, p):
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def process(self, p):
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for script in self.alwayson_scripts:
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try:
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script_args = p.script_args[script.args_from:script.args_to]
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script.process(p, *script_args)
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except Exception:
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print(f"Error running alwayson script: {script.filename}", file=sys.stderr)
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print(f"Error running process: {script.filename}", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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def postprocess(self, p, processed):
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for script in self.alwayson_scripts:
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try:
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script_args = p.script_args[script.args_from:script.args_to]
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script.postprocess(p, processed, *script_args)
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except Exception:
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print(f"Error running postprocess: {script.filename}", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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def reload_sources(self, cache):
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