# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from typing import Final, List, Literal, Optional, Tuple import numpy as np from fastapi import FastAPI, HTTPException from numpy.typing import ArrayLike from pydantic import BaseModel, Field from typing_extensions import Annotated, TypeAlias from .....utils import logging from ...layout_parsing import LayoutParsingPipeline from ..storage import SupportsGetURL, Storage, create_storage from .. import utils as serving_utils from ..app import AppConfig, create_app from ..models import Response, ResultResponse _DEFAULT_MAX_IMG_SIZE: Final[Tuple[int, int]] = (2000, 2000) _DEFAULT_MAX_NUM_IMGS: Final[int] = 10 FileType: TypeAlias = Literal[0, 1] class InferenceParams(BaseModel): maxLongSide: Optional[Annotated[int, Field(gt=0)]] = None class InferRequest(BaseModel): file: str fileType: Optional[FileType] = None useImgOrientationCls: bool = True useImgUnwrapping: bool = True useSealTextDet: bool = True inferenceParams: Optional[InferenceParams] = None BoundingBox: TypeAlias = Annotated[List[float], Field(min_length=4, max_length=4)] class LayoutElement(BaseModel): bbox: BoundingBox label: str text: str layoutType: Literal["single", "double"] image: Optional[str] = None class LayoutParsingResult(BaseModel): layoutElements: List[LayoutElement] class InferResult(BaseModel): layoutParsingResults: List[LayoutParsingResult] def _postprocess_image( img: ArrayLike, request_id: str, filename: str, file_storage: Optional[Storage], ) -> str: key = f"{request_id}/{filename}" ext = os.path.splitext(filename)[1] img = np.asarray(img) img_bytes = serving_utils.image_array_to_bytes(img, ext=ext) if file_storage is not None: file_storage.set(key, img_bytes) if isinstance(file_storage, SupportsGetURL): return file_storage.get_url(key) return serving_utils.base64_encode(img_bytes) def create_pipeline_app( pipeline: LayoutParsingPipeline, app_config: AppConfig ) -> FastAPI: app, ctx = create_app( pipeline=pipeline, app_config=app_config, app_aiohttp_session=True ) if ctx.config.extra and "file_storage" in ctx.config.extra: ctx.extra["file_storage"] = create_storage(ctx.config.extra["file_storage"]) else: ctx.extra["file_storage"] = None ctx.extra.setdefault("max_img_size", _DEFAULT_MAX_IMG_SIZE) ctx.extra.setdefault("max_num_imgs", _DEFAULT_MAX_NUM_IMGS) @app.post( "/layout-parsing", operation_id="infer", responses={422: {"model": Response}}, response_model_exclude_none=True, ) async def _infer( request: InferRequest, ) -> ResultResponse[InferResult]: pipeline = ctx.pipeline aiohttp_session = ctx.aiohttp_session request_id = serving_utils.generate_request_id() if request.fileType is None: if serving_utils.is_url(request.file): try: file_type = serving_utils.infer_file_type(request.file) except Exception as e: logging.exception(e) raise HTTPException( status_code=422, detail="The file type cannot be inferred from the URL. Please specify the file type explicitly.", ) else: raise HTTPException(status_code=422, detail="Unknown file type") else: file_type = "PDF" if request.fileType == 0 else "IMAGE" if request.inferenceParams: max_long_side = request.inferenceParams.maxLongSide if max_long_side: raise HTTPException( status_code=422, detail="`max_long_side` is currently not supported.", ) try: file_bytes = await serving_utils.get_raw_bytes( request.file, aiohttp_session ) images = await serving_utils.call_async( serving_utils.file_to_images, file_bytes, file_type, max_img_size=ctx.extra["max_img_size"], max_num_imgs=ctx.extra["max_num_imgs"], ) result = await pipeline.infer( images, use_doc_image_ori_cls_model=request.useImgOrientationCls, use_doc_image_unwarp_model=request.useImgUnwrapping, use_seal_text_det_model=request.useSealTextDet, ) layout_parsing_results: List[LayoutParsingResult] = [] for i, item in enumerate(result): layout_elements: List[LayoutElement] = [] for j, subitem in enumerate( item["layout_parsing_result"]["parsing_result"] ): dyn_keys = subitem.keys() - {"input_path", "layout_bbox", "layout"} if len(dyn_keys) != 1: raise RuntimeError(f"Unexpected result: {subitem}") label = next(iter(dyn_keys)) if label in ("image", "figure", "img", "fig"): image_ = await serving_utils.call_async( _postprocess_image, subitem[label]["img"], request_id=request_id, filename=f"image_{i}_{j}.jpg", file_storage=ctx.extra["file_storage"], ) text = subitem[label]["image_text"] else: image_ = None text = subitem[label] layout_elements.append( LayoutElement( bbox=subitem["layout_bbox"], label=label, text=text, layoutType=subitem["layout"], image=image_, ) ) layout_parsing_results.append( LayoutParsingResult(layoutElements=layout_elements) ) return ResultResponse( logId=serving_utils.generate_log_id(), errorCode=0, errorMsg="Success", result=InferResult( layoutParsingResults=layout_parsing_results, ), ) except Exception as e: logging.exception(e) raise HTTPException(status_code=500, detail="Internal server error") return app