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Table Detection And Extraction

Developed by foduucom
A table detection model based on YOLOv8s, capable of accurately identifying bordered and borderless tables in images.
Downloads 55.45k
Release Time : 8/5/2023

Model Overview

This model is specifically designed to detect tables in images, regardless of whether they have borders or not. It has been fine-tuned on extensive datasets and achieves high accuracy in detecting tables and distinguishing between bordered and borderless tables.

Model Features

High-precision table detection
The model achieves a mAP@0.5 accuracy of 0.962 in detecting tables, effectively identifying both bordered and borderless tables.
Unstructured document processing
Capable of processing tables in complex unstructured documents by isolating table regions using bounding box techniques.
OCR integration capability
Seamlessly integrates with OCR technology to not only detect table locations but also extract text data from tables.
Diverse table recognition
Can recognize tables of various designs and styles, adapting to different document layouts.

Model Capabilities

Table detection
Table classification (bordered/borderless)
Document analysis
Unstructured table extraction
Structured table extraction

Use Cases

Document processing
Table data extraction
Extract table data from scanned documents or images
Automatically extract table data in combination with OCR technology
Document analysis
Analyze table layouts and structures in documents
Aid in understanding document content and organizational structure
Data management
Unstructured data conversion
Convert tables in unstructured documents into structured data
Facilitate subsequent data analysis and processing
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