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AI-Assisted Rice Grading (PNS/BAFS-290:2019)

A web-based tool for automated rice quality grading using Convolutional Neural Networks (CNN) and Near-Infrared (NIR) imaging, aligned with Philippine National Standards for Grains (PNS/BAFS-290:2019).

Features

  • Upload rice grain images (RGB + NIR)
  • Live camera capture and device selection
  • Automated grading using mock CNN model output
  • Visual report card with radar chart for key metrics
  • Compliance with PNS/BAFS-290:2019 standards
  • Exportable JSON reports

Technologies

  • React + Vite
  • Tailwind CSS
  • Recharts (Radar chart visualization)
  • TypeScript

Usage

  1. Clone the repository
  2. Install dependencies: npm install
  3. Start the dev server: npm run dev
  4. Upload or capture rice sample images
  5. View grading results and export reports

Project Description (for GitHub)

Automated rice grading web app using CNN and NIR imaging, designed for Philippine rice standards (PNS/BAFS-290:2019). Upload or capture rice images, get instant grading, and visualize results with radar charts.

License

MIT

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Automated rice grading web app using CNN and NIR imaging, designed for Philippine rice standards (PNS/BAFS-290:2019). Upload or capture rice images, get instant grading, and visualize results with radar charts.

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