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| import base64 | |
| import io | |
| import time | |
| import uvicorn | |
| from threading import Lock | |
| from io import BytesIO | |
| from gradio.processing_utils import decode_base64_to_file | |
| from fastapi import APIRouter, Depends, FastAPI, HTTPException | |
| from fastapi.security import HTTPBasic, HTTPBasicCredentials | |
| from secrets import compare_digest | |
| import modules.shared as shared | |
| from modules import sd_samplers, deepbooru | |
| from modules.api.models import * | |
| from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images | |
| from modules.extras import run_extras, run_pnginfo | |
| from PIL import PngImagePlugin,Image | |
| from modules.sd_models import checkpoints_list | |
| from modules.realesrgan_model import get_realesrgan_models | |
| from typing import List | |
| def upscaler_to_index(name: str): | |
| try: | |
| return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) | |
| except: | |
| raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}") | |
| def validate_sampler_name(name): | |
| config = sd_samplers.all_samplers_map.get(name, None) | |
| if config is None: | |
| raise HTTPException(status_code=404, detail="Sampler not found") | |
| return name | |
| def setUpscalers(req: dict): | |
| reqDict = vars(req) | |
| reqDict['extras_upscaler_1'] = upscaler_to_index(req.upscaler_1) | |
| reqDict['extras_upscaler_2'] = upscaler_to_index(req.upscaler_2) | |
| reqDict.pop('upscaler_1') | |
| reqDict.pop('upscaler_2') | |
| return reqDict | |
| def decode_base64_to_image(encoding): | |
| if encoding.startswith("data:image/"): | |
| encoding = encoding.split(";")[1].split(",")[1] | |
| return Image.open(BytesIO(base64.b64decode(encoding))) | |
| def encode_pil_to_base64(image): | |
| with io.BytesIO() as output_bytes: | |
| # Copy any text-only metadata | |
| use_metadata = False | |
| metadata = PngImagePlugin.PngInfo() | |
| for key, value in image.info.items(): | |
| if isinstance(key, str) and isinstance(value, str): | |
| metadata.add_text(key, value) | |
| use_metadata = True | |
| image.save( | |
| output_bytes, "PNG", pnginfo=(metadata if use_metadata else None) | |
| ) | |
| bytes_data = output_bytes.getvalue() | |
| return base64.b64encode(bytes_data) | |
| class Api: | |
| def __init__(self, app: FastAPI, queue_lock: Lock): | |
| if shared.cmd_opts.api_auth: | |
| self.credenticals = dict() | |
| for auth in shared.cmd_opts.api_auth.split(","): | |
| user, password = auth.split(":") | |
| self.credenticals[user] = password | |
| self.router = APIRouter() | |
| self.app = app | |
| self.queue_lock = queue_lock | |
| self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse) | |
| self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse) | |
| self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse) | |
| self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse) | |
| self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse) | |
| self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse) | |
| self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"]) | |
| self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"]) | |
| self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"]) | |
| self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel) | |
| self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"]) | |
| self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=FlagsModel) | |
| self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem]) | |
| self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem]) | |
| self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem]) | |
| self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem]) | |
| self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem]) | |
| self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem]) | |
| self.add_api_route("/sdapi/v1/prompt-styles", self.get_promp_styles, methods=["GET"], response_model=List[PromptStyleItem]) | |
| self.add_api_route("/sdapi/v1/artist-categories", self.get_artists_categories, methods=["GET"], response_model=List[str]) | |
| self.add_api_route("/sdapi/v1/artists", self.get_artists, methods=["GET"], response_model=List[ArtistItem]) | |
| def add_api_route(self, path: str, endpoint, **kwargs): | |
| if shared.cmd_opts.api_auth: | |
| return self.app.add_api_route(path, endpoint, dependencies=[Depends(self.auth)], **kwargs) | |
| return self.app.add_api_route(path, endpoint, **kwargs) | |
| def auth(self, credenticals: HTTPBasicCredentials = Depends(HTTPBasic())): | |
| if credenticals.username in self.credenticals: | |
| if compare_digest(credenticals.password, self.credenticals[credenticals.username]): | |
| return True | |
| raise HTTPException(status_code=401, detail="Incorrect username or password", headers={"WWW-Authenticate": "Basic"}) | |
| def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): | |
| populate = txt2imgreq.copy(update={ # Override __init__ params | |
| "sd_model": shared.sd_model, | |
| "sampler_name": validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index), | |
| "do_not_save_samples": True, | |
| "do_not_save_grid": True | |
| } | |
| ) | |
| if populate.sampler_name: | |
| populate.sampler_index = None # prevent a warning later on | |
| 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): | |
| init_images = img2imgreq.init_images | |
| if init_images is None: | |
| 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, | |
| "sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index), | |
| "do_not_save_samples": True, | |
| "do_not_save_grid": True, | |
| "mask": mask | |
| } | |
| ) | |
| if populate.sampler_name: | |
| populate.sampler_index = None # prevent a warning later on | |
| p = StableDiffusionProcessingImg2Img(**vars(populate)) | |
| imgs = [] | |
| for img in init_images: | |
| img = decode_base64_to_image(img) | |
| imgs = [img] * p.batch_size | |
| p.init_images = imgs | |
| 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): | |
| reqDict = setUpscalers(req) | |
| reqDict['image'] = decode_base64_to_image(reqDict['image']) | |
| with self.queue_lock: | |
| result = run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", **reqDict) | |
| return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1]) | |
| def extras_batch_images_api(self, req: ExtrasBatchImagesRequest): | |
| reqDict = setUpscalers(req) | |
| def prepareFiles(file): | |
| file = decode_base64_to_file(file.data, file_path=file.name) | |
| file.orig_name = file.name | |
| return file | |
| reqDict['image_folder'] = list(map(prepareFiles, reqDict['imageList'])) | |
| reqDict.pop('imageList') | |
| with self.queue_lock: | |
| 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, 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) | |
| shared.state.set_current_image() | |
| 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 interrogateapi(self, interrogatereq: InterrogateRequest): | |
| image_b64 = interrogatereq.image | |
| if image_b64 is None: | |
| raise HTTPException(status_code=404, detail="Image not found") | |
| img = decode_base64_to_image(image_b64) | |
| img = img.convert('RGB') | |
| # Override object param | |
| with self.queue_lock: | |
| if interrogatereq.model == "clip": | |
| processed = shared.interrogator.interrogate(img) | |
| elif interrogatereq.model == "deepdanbooru": | |
| processed = deepbooru.model.tag(img) | |
| else: | |
| raise HTTPException(status_code=404, detail="Model not found") | |
| return InterrogateResponse(caption=processed) | |
| def interruptapi(self): | |
| shared.state.interrupt() | |
| return {} | |
| def skip(self): | |
| shared.state.skip() | |
| def get_config(self): | |
| options = {} | |
| for key in shared.opts.data.keys(): | |
| metadata = shared.opts.data_labels.get(key) | |
| if(metadata is not None): | |
| options.update({key: shared.opts.data.get(key, shared.opts.data_labels.get(key).default)}) | |
| else: | |
| options.update({key: shared.opts.data.get(key, None)}) | |
| return options | |
| def set_config(self, req: Dict[str, Any]): | |
| for k, v in req.items(): | |
| shared.opts.set(k, v) | |
| shared.opts.save(shared.config_filename) | |
| return | |
| def get_cmd_flags(self): | |
| return vars(shared.cmd_opts) | |
| def get_samplers(self): | |
| return [{"name": sampler[0], "aliases":sampler[2], "options":sampler[3]} for sampler in sd_samplers.all_samplers] | |
| def get_upscalers(self): | |
| upscalers = [] | |
| for upscaler in shared.sd_upscalers: | |
| u = upscaler.scaler | |
| upscalers.append({"name":u.name, "model_name":u.model_name, "model_path":u.model_path, "model_url":u.model_url}) | |
| return upscalers | |
| def get_sd_models(self): | |
| return [{"title":x.title, "model_name":x.model_name, "hash":x.hash, "filename": x.filename, "config": x.config} for x in checkpoints_list.values()] | |
| def get_hypernetworks(self): | |
| return [{"name": name, "path": shared.hypernetworks[name]} for name in shared.hypernetworks] | |
| def get_face_restorers(self): | |
| return [{"name":x.name(), "cmd_dir": getattr(x, "cmd_dir", None)} for x in shared.face_restorers] | |
| def get_realesrgan_models(self): | |
| return [{"name":x.name,"path":x.data_path, "scale":x.scale} for x in get_realesrgan_models(None)] | |
| def get_promp_styles(self): | |
| styleList = [] | |
| for k in shared.prompt_styles.styles: | |
| style = shared.prompt_styles.styles[k] | |
| styleList.append({"name":style[0], "prompt": style[1], "negative_prompt": style[2]}) | |
| return styleList | |
| def get_artists_categories(self): | |
| return shared.artist_db.cats | |
| def get_artists(self): | |
| return [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists] | |
| def launch(self, server_name, port): | |
| self.app.include_router(self.router) | |
| uvicorn.run(self.app, host=server_name, port=port) | |