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Donut Demo
D
Donut Demo
Developed by lucky-verma
A Transformer model based on the Donut architecture, specifically designed for extracting structured information from driver's license images
Downloads 45
Release Time : 1/4/2023
Model Overview
This model adopts the Donut (Document Understanding Transformer) architecture, capable of automatically recognizing and extracting key field information such as name, ID number, validity period, etc., from driver's license images, enabling automated processing of document information.
Model Features
End-to-End Document Understanding
No OCR preprocessing required, directly processes image input and outputs structured information
High-Precision Extraction
Optimized for the driver's license domain, achieving high accuracy in key field extraction
Multi-Field Recognition
Capable of simultaneously recognizing multiple fields such as name, ID number, validity period, etc.
Model Capabilities
Text recognition in images
Structured information extraction
Driver's license field parsing
End-to-end document processing
Use Cases
Document Processing Automation
Driver's License Information Entry System
Automatically extracts information from user-uploaded driver's license photos, reducing manual entry
Improves data entry efficiency and reduces human error rates
Identity Verification Process
Quickly retrieves driver's license information during user registration or verification processes
Simplifies verification processes and enhances user experience
Data Organization and Analysis
Driver's License Database Construction
Batch processes large volumes of driver's license images to build a structured database
Enables digital management of document data
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