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Dedoc is an open universal system for converting documents to a unified output format.
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It extracts a document’s logical structure and content, its tables, text formatting and metadata.
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It extracts a document’s logical structure and content: tables, text formatting and metadata.
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The document’s content is represented as a tree storing headings and lists of any level.
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Dedoc can be integrated in a document contents and structure analysis system as a separate module.
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Workflow description is given [`here`](https://dedoc.readthedocs.io/en/latest/?badge=latest#workflow)
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## Features and advantages
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Dedoc is implemented in Python and works with semi-structured data formats (DOC/DOCX, ODT, XLS/XLSX, CSV, TXT, JSON) and none-structured data formats like images (PNG, JPG etc.), archives (ZIP, RAR etc.), PDF and HTML formats.
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Dedoc is implemented in Python and works with semi-structured data formats (DOC/DOCX, ODT, XLS/XLSX, CSV, TXT, JSON) and unstructured data formats like images (PNG, JPG etc.), archives (ZIP, RAR etc.), PDF and HTML formats.
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Document structure extraction is fully automatic regardless of input data type.
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Metadata and text formatting are also extracted automatically.
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In 2022, the system won a grant to support the development of promising AI projects from the [Innovation Assistance Foundation (Фонд содействия инновациям)](https://fasie.ru/).
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## Dedoc provides:
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* Extensibility due to a flexible addition of new document formats and to an easy change of an output data format.
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* Extensibility due to flexible addition of new document formats and easy change of an output data format.
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* Support for extracting document structure out of nested documents having different formats.
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* Extracting various text formatting features (indentation, font type, size, style etc.).
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* Working with documents of various origin (statements of work, legal documents, technical reports, scientific papers) allowing flexible tuning for new domains.
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## Impact
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This project may be useful as a first step of automatic document analysis pipeline (e.g. before the NLP part).
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This project may be useful as a first step of an automatic document analysis pipeline (e.g. before the NLP part).
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Dedoc is in demand for information analytic systems, information leak monitoring systems, as well as for natural language processing systems.
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The library is intended for application use by developers of systems for automatic analysis and structuring of electronic documents, including for further search in electronic documents.
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# Installation instructions
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This project has REST Api and you can run it in Docker container.
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This project has a REST api and you can run it in Docker container.
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Also, dedoc can be installed as a library via `pip`.
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There are two ways to install and run dedoc as a web application or a library that are described below.
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If you don't want to use docker for running the application, it's possible to run dedoc locally.
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However, it isn't suitable for any operating system (`Ubuntu 20+` is recommended) and
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there may be not enough machine's resources for its work.
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there may be not enough machine resources for its work.
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You should have `python` (`python3.8`, `python3.9` are recommended) and `pip` installed.
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Installation instructions via pip are available [here](https://dedoc.readthedocs.io/en/latest/getting_started/installation.html#install-dedoc-using-pip).
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