asagar60/TableNet-pytorch
Pytorch Implementation of TableNet
This project helps you automatically extract structured data from tables found within images or scanned documents. It takes an image containing a table as input and outputs the identified table's location, its column structure, and the text content of each cell, making it easy to convert visual information into usable data. This is ideal for data entry specialists, researchers, or anyone needing to digitize information locked in image-based tables.
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Use this if you need to reliably extract data from tables embedded in images, like scanned reports or screenshots, and convert it into a structured, editable format.
Not ideal if your tables are already in digital, editable formats like PDFs where text is selectable, or if you only need to identify the presence of a table without extracting its full structure and content.
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66
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24
Language
Jupyter Notebook
License
MIT
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Last pushed
Jul 21, 2021
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