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  pretty_name: PatFig
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  pretty_name: PatFig
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  size_categories:
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+ ---
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+ # PatFig Dataset
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+
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+ ## Table of Contents
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+ - [Introduction](#introduction)
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+ - [Dataset Description](#dataset-description)
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+ - [Overview](#overview)
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+ - [Structure](#structure)
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+ - [Categories](#categories)
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+ - [Access](#access)
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+ - [Usage](#usage)
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+ - [Challenges and Considerations](#challenges-and-considerations)
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+ - [License and Usage Guidelines](#license-and-usage-guidelines)
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+
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+ ## Introduction
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+ The PatFig Dataset is a curated collection of over 18,000 patent images from more than 7,000 European patent applications, spanning the year 2020. It aims to provide a comprehensive resource for research and applications in computer vision, patent analysis, and automated documentation processing.
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+
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+ ## Dataset Description
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+ ### Overview
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+ This dataset includes patent figures accompanied by short and long captions, reference numerals, corresponding terms, and a minimal set of claims, offering a detailed insight into the depicted inventions.
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+ ### Structure
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+ - **Image Files**: Technical drawings, block diagrams, flowcharts, plots, and grayscale photographs.
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+ - **Captions**: Each figure is accompanied by a short and long caption describing its content and context.
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+ - **Reference Numerals and Terms**: Key components in the figures are linked to their descriptions through reference numerals.
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+ - **Minimal Set of Claims**: Claims sentences summarizing the interactions among elements within each figure.
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+ - **Metadata**: Includes image names, publication numbers, titles, figure identifiers, and more.
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+
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+ ### Categories
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+ The dataset is categorized according to the International Patent Classification (IPC) system, ensuring a diverse representation of technological domains.
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+
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+ ## Access
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+ The PatFig Dataset is available for download on Hugging Face. Please follow the platform's guidelines for accessing and downloading datasets.
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+ ## Usage
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+ The PatFig Dataset is intended for use in patent image analysis, automated documentation processing, visual question answering tasks, and image captioning in technical contexts. Users are encouraged to explore innovative applications in related fields.
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+ ## Challenges and Considerations
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+ Users should be aware of challenges such as interpreting compound figures and aligning textual descriptions with visual data. Advanced processing techniques may be required for effective utilization.
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+ ## License and Usage Guidelines
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+ The dataset is released under a Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0) License. It is intended for non-commercial use, and users must adhere to the license terms.
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