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Multilingual Invoice Data Extraction from Image for C# .NET Applications


🎯 Purpose of the Sample

The Multilingual Invoice Data Extraction Demo illustrates how to leverage the LM-Kit.NET SDK for automatically extracting structured invoice data from images. Using advanced multimodal language models with integrated OCR, this solution simplifies the process of capturing invoice information across multiple languages, reducing manual data entry and boosting operational efficiency.


👥 Industry Target Audience

This demo is highly valuable for developers and businesses involved in:

  • Financial Services & Accounting: Automate invoice processing, significantly reducing manual data entry and human error.
  • Enterprise Software Development: Integrate seamless multilingual invoice extraction into business applications for improved data handling.
  • Supply Chain & Logistics: Quickly and accurately process invoices in diverse languages, streamlining operations.
  • Intelligent Automation Solutions: Enhance autonomous processing capabilities by enabling precise extraction of structured data from multilingual invoices.

🚀 Problem Solved

Manual extraction of invoice data, especially from multilingual sources, is time-consuming, costly, and error-prone. This demo addresses these challenges by automating data extraction from invoice images. It also includes robust vision-language models optimized for CPU execution, eliminating the need for expensive GPU hardware.


💻 Sample Application Description

The Multilingual Invoice Data Extraction Demo is a console application enabling users to select a vision-language model and specify invoice image files. The application extracts structured data based on a predefined JSON schema, providing clear, structured output and performance metrics.

✨ Key Features

  • Flexible Model Selection: Select from multiple CPU-optimized vision-language models or specify a custom model URI.
  • Real-Time Progress Indicators: Visual feedback for model downloading and loading.
  • Structured Invoice Data Extraction: Automatically extracts key invoice fields leveraging integrated OCR and advanced multimodal models.
  • Automatic Language and Orientation Detection: OCR engine detects invoice language and orientation, optimizing extraction accuracy.
  • Performance Insights: Display processing times to evaluate extraction efficiency.

🤖 Benefits for Agentic Solutions

Integrating multilingual invoice data extraction into autonomous workflows provides significant operational advantages:

  • Enhanced Automation: Agents quickly and accurately extract invoice data, streamlining financial operations.
  • Reduced Processing Time: Accelerates workflows by automating data entry and validation tasks.
  • Cost Efficiency: CPU-friendly models ensure cost-effective deployment without specialized hardware.
  • Improved Accuracy: Minimizes errors through precise OCR and structured extraction, enhancing data reliability.

🛠️ Getting Started

📋 Prerequisites

  • .NET Framework 4.6.2 or .NET 6.0

📥 Download the Project

▶️ Running the Application

  1. Clone the repository:
git clone https://github.com/LM-Kit/lm-kit-net-samples.git
  1. Navigate to the project directory:
cd lm-kit-net-samples/console_framework_4.62/multilingual_invoice_data_extraction_from_image

or

cd lm-kit-net-samples/console_net/multilingual_invoice_data_extraction_from_image
  1. Build and run the application:
dotnet build
dotnet run
  1. Follow the on-screen prompts to select a model and provide the invoice image file path.

💡 Example Usage

  1. Select a Vision-Language Model: Choose from available CPU-friendly models or enter a custom URI.
  2. Choose Invoice Image: Input the file path to the invoice image.
  3. Structured Data Extraction: The application processes the image, performs OCR, detects language and orientation, and extracts structured data according to a predefined schema.
  4. Review Extracted Data: Clearly displayed extracted fields and a comprehensive JSON payload.
  5. Process More or Exit: Continue with additional invoices or exit the application.

Incorporating this demo into your projects streamlines invoice data management, improves accuracy, and accelerates financial workflows through intelligent automation using easily deployable CPU-friendly models.