# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved. # # 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 asyncio import base64 import io import mimetypes import re import tempfile import threading import uuid from functools import partial from typing import Awaitable, Callable, List, Optional, Tuple, TypeVar, Union, overload from urllib.parse import parse_qs, urlparse import numpy as np import pandas as pd import requests from PIL import Image from typing_extensions import Literal, ParamSpec, TypeAlias, assert_never from ....utils.deps import function_requires_deps, is_dep_available from .models import ImageInfo, PDFInfo, PDFPageInfo if is_dep_available("aiohttp"): import aiohttp if is_dep_available("opencv-contrib-python"): import cv2 if is_dep_available("filetype"): import filetype if is_dep_available("pypdfium2"): import pypdfium2 as pdfium if is_dep_available("yarl"): import yarl __all__ = [ "FileType", "generate_log_id", "is_url", "infer_file_type", "infer_file_ext", "image_bytes_to_array", "image_bytes_to_image", "image_to_bytes", "image_array_to_bytes", "csv_bytes_to_data_frame", "data_frame_to_bytes", "base64_encode", "read_pdf", "file_to_images", "get_image_info", "write_to_temp_file", "get_raw_bytes", "get_raw_bytes_async", "call_async", ] FileType: TypeAlias = Literal["IMAGE", "PDF", "VIDEO", "AUDIO"] P = ParamSpec("P") R = TypeVar("R") def generate_log_id() -> str: return str(uuid.uuid4()) # TODO: # 1. Use Pydantic to validate the URL and Base64-encoded string types for both # input and output data instead of handling this manually. # 2. Define a `File` type for global use; this will be part of the contract. # 3. Consider using two separate fields instead of a union of URL and Base64, # even though they are both strings. Backward compatibility should be # maintained. def is_url(s: str) -> bool: if not (s.startswith("http://") or s.startswith("https://")): # Quick rejection return False result = urlparse(s) return all([result.scheme, result.netloc]) and result.scheme in ("http", "https") def infer_file_type(url: str) -> Optional[FileType]: url_parts = urlparse(url) filename = url_parts.path.split("/")[-1] file_type = mimetypes.guess_type(filename)[0] if file_type is None: # HACK: The support for BOS URLs with query params is implementation-based, # not interface-based. is_bos_url = re.fullmatch(r"\w+\.bcebos\.com", url_parts.netloc) is not None if is_bos_url and url_parts.query: params = parse_qs(url_parts.query) if ( "responseContentDisposition" in params and len(params["responseContentDisposition"]) == 1 ): match_ = re.match( r"attachment;filename=(.*)", params["responseContentDisposition"][0] ) if match_: file_type = mimetypes.guess_type(match_.group(1))[0] if file_type is None: return None if file_type.startswith("image/"): return "IMAGE" elif file_type == "application/pdf": return "PDF" elif file_type.startswith("video/"): return "VIDEO" elif file_type.startswith("audio/"): return "AUDIO" else: return None @function_requires_deps("filetype") def infer_file_ext(file: str) -> Optional[str]: if is_url(file): url_parts = urlparse(file) filename = url_parts.path.split("/")[-1] mime_type = mimetypes.guess_type(filename)[0] if mime_type is None: return None return mimetypes.guess_extension(mime_type) else: bytes_ = base64.b64decode(file) return "." + filetype.guess_extension(bytes_) @function_requires_deps("opencv-contrib-python") def image_bytes_to_array(data: bytes) -> np.ndarray: return cv2.imdecode(np.frombuffer(data, np.uint8), cv2.IMREAD_COLOR) def image_bytes_to_image(data: bytes) -> Image.Image: return Image.open(io.BytesIO(data)) def image_to_bytes(image: Image.Image, format: str = "JPEG") -> bytes: with io.BytesIO() as f: image.save(f, format=format) img_bytes = f.getvalue() return img_bytes @function_requires_deps("opencv-contrib-python") def image_array_to_bytes(image: np.ndarray, ext: str = ".jpg") -> bytes: image = cv2.imencode(ext, image)[1] return image.tobytes() def csv_bytes_to_data_frame(data: bytes) -> pd.DataFrame: with io.StringIO(data.decode("utf-8")) as f: df = pd.read_csv(f) return df def data_frame_to_bytes(df: pd.DataFrame) -> bytes: return df.to_csv().encode("utf-8") def base64_encode(data: bytes) -> str: return base64.b64encode(data).decode("ascii") _lock = threading.Lock() @function_requires_deps("pypdfium2", "opencv-contrib-python") def read_pdf( bytes_: bytes, max_num_imgs: Optional[int] = None ) -> Tuple[List[np.ndarray], PDFInfo]: images: List[np.ndarray] = [] page_info_list: List[PDFPageInfo] = [] with _lock: doc = pdfium.PdfDocument(bytes_) try: for page in doc: if max_num_imgs is not None and len(images) >= max_num_imgs: break # TODO: Do not always use zoom=2.0 zoom = 2.0 deg = 0 image = page.render(scale=zoom, rotation=deg).to_pil() image = image.convert("RGB") image = np.array(image) image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) images.append(image) page_info = PDFPageInfo( width=image.shape[1], height=image.shape[0], ) page_info_list.append(page_info) finally: doc.close() pdf_info = PDFInfo( numPages=len(page_info_list), pages=page_info_list, ) return images, pdf_info @overload def file_to_images( file_bytes: bytes, file_type: Literal["IMAGE"], *, max_num_imgs: Optional[int] = ..., ) -> Tuple[List[np.ndarray], ImageInfo]: ... @overload def file_to_images( file_bytes: bytes, file_type: Literal["PDF"], *, max_num_imgs: Optional[int] = ..., ) -> Tuple[List[np.ndarray], PDFInfo]: ... @overload def file_to_images( file_bytes: bytes, file_type: Literal["IMAGE", "PDF"], *, max_num_imgs: Optional[int] = ..., ) -> Union[Tuple[List[np.ndarray], ImageInfo], Tuple[List[np.ndarray], PDFInfo]]: ... def file_to_images( file_bytes: bytes, file_type: Literal["IMAGE", "PDF"], *, max_num_imgs: Optional[int] = None, ) -> Union[Tuple[List[np.ndarray], ImageInfo], Tuple[List[np.ndarray], PDFInfo]]: if file_type == "IMAGE": images = [image_bytes_to_array(file_bytes)] data_info = get_image_info(images[0]) elif file_type == "PDF": images, data_info = read_pdf(file_bytes, max_num_imgs=max_num_imgs) else: assert_never(file_type) return images, data_info def get_image_info(image: np.ndarray) -> ImageInfo: return ImageInfo(width=image.shape[1], height=image.shape[0]) def write_to_temp_file(file_bytes: bytes, suffix: str) -> str: with tempfile.NamedTemporaryFile("wb", suffix=suffix, delete=False) as f: f.write(file_bytes) return f.name def get_raw_bytes(file: str) -> bytes: if is_url(file): resp = requests.get(file, timeout=5) resp.raise_for_status() return resp.content else: return base64.b64decode(file) @function_requires_deps("aiohttp", "yarl") async def get_raw_bytes_async(file: str, session: "aiohttp.ClientSession") -> bytes: if is_url(file): async with session.get(yarl.URL(file, encoded=True)) as resp: return await resp.read() else: return base64.b64decode(file) def call_async( func: Callable[P, R], /, *args: P.args, **kwargs: P.kwargs ) -> Awaitable[R]: return asyncio.get_running_loop().run_in_executor( None, partial(func, *args, **kwargs) )