AshishSalaskar1/TableNet_Implementation
Extract Tabular data from scanned document images and save the tabular data into CSV files. Used a Encoder-Decoder based architecture for building the model
This tool helps you automatically extract structured data from tables found within scanned document images. You provide scanned documents or images, and it outputs the detected tables as separate images and their content organized into CSV files. It's designed for anyone who needs to convert information trapped in image-based tables into an editable, analyzable format.
No commits in the last 6 months.
Use this if you regularly work with scanned documents, PDFs, or image files containing tables and need to efficiently get that tabular data into spreadsheets for analysis or record-keeping.
Not ideal if your documents are already in a digital, machine-readable format like native PDFs where text can be easily copied, or if you only need to detect tables without extracting their content.
Stars
9
Forks
5
Language
Jupyter Notebook
License
—
Category
Last pushed
Apr 04, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AshishSalaskar1/TableNet_Implementation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Psarpei/Multi-Type-TD-TSR
Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and...
Layout-Parser/layout-parser
A Unified Toolkit for Deep Learning Based Document Image Analysis
Sudhanshu1304/table-transformer
🔍 Table Extraction Tool: A powerful open-source solution combining OCR and computer vision for...
ses4255/Versatile-OCR-Program
Multi-modal OCR pipeline optimized for ML training (text, figure, math, tables, diagrams)
asagar60/TableNet-pytorch
Pytorch Implementation of TableNet