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Yolov8n Table Extraction
A table detection model based on YOLOv8, capable of identifying table regions in documents, supporting both bordered and borderless table types.
Downloads 474
Release Time : 1/29/2023
Model Overview
This model is specifically designed for document analysis, efficiently and accurately detecting table regions in documents, suitable for automated document processing and data extraction scenarios.
Model Features
High-precision Table Detection
Achieves 96.7% mAP@0.5 accuracy on the validation set, accurately identifying table regions in documents.
Supports Multiple Table Types
Capable of detecting both bordered and borderless table types.
Based on YOLOv8 Architecture
Utilizes the latest YOLOv8n architecture, achieving a good balance between speed and accuracy.
Model Capabilities
Document Table Detection
Table Region Localization
Table Type Recognition
Use Cases
Document Processing
Automated Table Extraction
Automatically extracts table regions from scanned documents or PDFs for subsequent OCR processing.
Accurately identifies table locations, reducing manual annotation workload.
Document Analysis System
Acts as a preliminary step in the document analysis workflow, first locating tables before content extraction.
Enhances the automation and efficiency of document processing systems.
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