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Pix2text Table Rec
A table structure recognition model developed based on Microsoft's Table Transformer for table detection and recognition tasks in documents
Downloads 1,124
Release Time : 3/29/2024
Model Overview
This model is a Table Transformer trained on the PubTables1M and FinTabNet.c datasets, specifically designed for recognizing table structures in documents.
Model Features
Transformer-based Architecture
Utilizes the same Transformer architecture as DETR, providing robust table structure recognition capabilities
Multi-Dataset Training
Trained on PubTables1M and FinTabNet.c datasets for superior recognition performance
Continuous Optimization
Ongoing iterative improvements based on Microsoft's original model
Model Capabilities
Table Detection
Table Structure Recognition
Document Analysis
Use Cases
Document Processing
PDF Table Extraction
Automatically identifies and extracts table structures from PDF documents
Accurately recognizes the row and column structures of tables
Financial Document Analysis
Processes financial reports and other documents containing complex tables
Identifies various data relationships within financial tables
Office Automation
Spreadsheet Conversion
Converts tables in scanned documents into editable spreadsheet formats
Maintains the structural integrity of the original tables
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