diff options
Diffstat (limited to 'modules/api')
| -rw-r--r-- | modules/api/api.py | 88 | ||||
| -rw-r--r-- | modules/api/models.py | 38 |
2 files changed, 95 insertions, 31 deletions
diff --git a/modules/api/api.py b/modules/api/api.py index 49c213ea..6c06d449 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -1,11 +1,14 @@ +import time import uvicorn from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image -from fastapi import APIRouter, HTTPException +from fastapi import APIRouter, Depends, HTTPException import modules.shared as shared +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 + def upscaler_to_index(name: str): try: @@ -13,8 +16,10 @@ def upscaler_to_index(name: str): except: raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}") + sampler_to_index = lambda name: next(filter(lambda row: name.lower() == row[1].name.lower(), enumerate(all_samplers)), None) + def setUpscalers(req: dict): reqDict = vars(req) reqDict['extras_upscaler_1'] = upscaler_to_index(req.upscaler_1) @@ -23,6 +28,7 @@ def setUpscalers(req: dict): reqDict.pop('upscaler_2') return reqDict + class Api: def __init__(self, app, queue_lock): self.router = APIRouter() @@ -32,15 +38,17 @@ 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"], response_model=ProgressResponse) def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): sampler_index = sampler_to_index(txt2imgreq.sampler_index) - + if sampler_index is None: - raise HTTPException(status_code=404, detail="Sampler not found") - + raise HTTPException(status_code=404, detail="Sampler not found") + populate = txt2imgreq.copy(update={ # Override __init__ params - "sd_model": shared.sd_model, + "sd_model": shared.sd_model, "sampler_index": sampler_index[0], "do_not_save_samples": True, "do_not_save_grid": True @@ -48,34 +56,39 @@ class Api: ) p = StableDiffusionProcessingTxt2Img(**vars(populate)) # Override object param + + shared.state.begin() + with self.queue_lock: processed = process_images(p) - + + shared.state.end() + b64images = list(map(encode_pil_to_base64, processed.images)) - + return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) 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") + 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") + raise HTTPException(status_code=404, detail="Init image not found") mask = img2imgreq.mask if mask: mask = decode_base64_to_image(mask) - + populate = img2imgreq.copy(update={ # Override __init__ params - "sd_model": shared.sd_model, + "sd_model": shared.sd_model, "sampler_index": sampler_index[0], "do_not_save_samples": True, - "do_not_save_grid": True, + "do_not_save_grid": True, "mask": mask } ) @@ -87,16 +100,20 @@ class Api: imgs = [img] * p.batch_size p.init_images = imgs - # Override object param + + shared.state.begin() + with self.queue_lock: processed = process_images(p) - + + shared.state.end() + b64images = list(map(encode_pil_to_base64, processed.images)) if (not img2imgreq.include_init_images): img2imgreq.init_images = None img2imgreq.mask = None - + return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js()) def extras_single_image_api(self, req: ExtrasSingleImageRequest): @@ -124,9 +141,40 @@ class Api: result = run_extras(extras_mode=1, image="", input_dir="", output_dir="", **reqDict) return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1]) - - def pnginfoapi(self): - raise NotImplementedError + + 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, req: ProgressRequest = Depends()): + # copy from check_progress_call of ui.py + + if shared.state.job_count == 0: + return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict()) + + # avoid dividing zero + progress = 0.01 + + if shared.state.job_count > 0: + progress += shared.state.job_no / shared.state.job_count + if shared.state.sampling_steps > 0: + progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps + + time_since_start = time.time() - shared.state.time_start + eta = (time_since_start/progress) + eta_relative = eta-time_since_start + + progress = min(progress, 1) + + current_image = None + if shared.state.current_image and not req.skip_current_image: + current_image = encode_pil_to_base64(shared.state.current_image) + + return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image) def launch(self, server_name, port): self.app.include_router(self.router) diff --git a/modules/api/models.py b/modules/api/models.py index dd122321..9ee42a17 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -1,4 +1,5 @@ import inspect +from click import prompt from pydantic import BaseModel, Field, create_model from typing import Any, Optional from typing_extensions import Literal @@ -51,17 +52,17 @@ class PydanticModelGenerator: # field_type = str if not overrides.get(k) else overrides[k]["type"] # print(k, v.annotation, v.default) field_type = v.annotation - + return Optional[field_type] - + def merge_class_params(class_): all_classes = list(filter(lambda x: x is not object, inspect.getmro(class_))) parameters = {} for classes in all_classes: parameters = {**parameters, **inspect.signature(classes.__init__).parameters} return parameters - - + + self._model_name = model_name self._class_data = merge_class_params(class_instance) self._model_def = [ @@ -73,11 +74,11 @@ class PydanticModelGenerator: ) for (k,v) in self._class_data.items() if k not in API_NOT_ALLOWED ] - + for fields in additional_fields: self._model_def.append(ModelDef( - field=underscore(fields["key"]), - field_alias=fields["key"], + field=underscore(fields["key"]), + field_alias=fields["key"], field_type=fields["type"], field_value=fields["default"], field_exclude=fields["exclude"] if "exclude" in fields else False)) @@ -94,15 +95,15 @@ class PydanticModelGenerator: DynamicModel.__config__.allow_population_by_field_name = True DynamicModel.__config__.allow_mutation = True return DynamicModel - + StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator( - "StableDiffusionProcessingTxt2Img", + "StableDiffusionProcessingTxt2Img", StableDiffusionProcessingTxt2Img, [{"key": "sampler_index", "type": str, "default": "Euler"}] ).generate_model() StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator( - "StableDiffusionProcessingImg2Img", + "StableDiffusionProcessingImg2Img", StableDiffusionProcessingImg2Img, [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}, {"key": "mask", "type": str, "default": None}, {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}] ).generate_model() @@ -148,4 +149,19 @@ class ExtrasBatchImagesRequest(ExtrasBaseRequest): imageList: list[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings") class ExtrasBatchImagesResponse(ExtraBaseResponse): - images: list[str] = Field(title="Images", description="The generated images in base64 format.")
\ No newline at end of file + 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 ProgressRequest(BaseModel): + skip_current_image: bool = Field(default=False, title="Skip current image", description="Skip current image serialization") + +class ProgressResponse(BaseModel): + progress: float = Field(title="Progress", description="The progress with a range of 0 to 1") + eta_relative: float = Field(title="ETA in secs") + state: dict = Field(title="State", description="The current state snapshot") + current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.") |