text: PNG into a document format that we can use downstream.Using Unstructuredâ€‹#!pip install pdfminerfrom langchain.document_loaders.image import UnstructuredImageLoaderloader = UnstructuredImageLoader("layout-parser-paper-fast.jpg")data = loader.load()data[0]    Document(page_content="LayoutParser: A Unified Toolkit for Deep\nLearning Based Document Image Analysis\n\n\nâ€˜Zxjiang Shen' (F3}, Ruochen Zhangâ€�, Melissa Dell*, Benjamin Charles Germain\nLeet, Jacob Carlson, and Weining LiF\n\n\nsugehen\n\nshangthrows, et\n\nâ€œAbstract. Recent advanocs in document image analysis (DIA) have been\nâ€˜pimarliy driven bythe application of neural networks dell roar\n{uteomer could be aly deployed in production and extended fo farther\n[nvetigtion. However, various factory ke lcely organize codebanee\nsnd sophisticated modal cnigurations compat the ey ree of\nâ€˜erin! innovation by wide sence, Though there have been sng\nâ€˜Hors to improve reuablty and simplify deep lees (DL) mode\nâ€˜aon, sone of them ae optimized for challenge inthe demain of DIA,\nThis roprscte a major gap in the extng fol, sw DIA i eal to\nscademic research acon wie range of dpi in the social ssencee\n[rary for streamlining the sage of DL in DIA research and appicn\nâ€˜tons The core LayoutFaraer brary comes with a sch of simple and\nIntative interfaee or applying and eutomiing DI. odel fr Inyo de\npltfom for sharing both protrined modes an fal document dist\n{ation pipeline We