Sadhya_Analyser 🍛🟩 Basic Details Team Name: NOVA SPARKS Team Members

Team Lead: Neeraj Sukumaran – Sree Buddha College of Engineering, Pattoor, Alappuzha

Member 2: Kalidas V.S. – Sree Buddha College of Engineering, Pattoor, Alappuzha

Project Description

An AI-powered app that checks if your Sadhya is arranged correctly on a banana leaf — because, of course, that matters more than taste. The Problem (that doesn't exist)

People are eating Sadhya chaotic style — avial near the banana, payasam on the left, and pappadam chilling in the middle like it's the DJ. This is an existential threat to Onam aesthetics. The Solution (that nobody asked for)

We trained an AI model to analyze banana leaf symmetry and judge your Sadhya plate. It tells you if your Vishu vibe is off or if you're ready for the culinary catwalk. Technical Details Technologies/Components Used

For Software:

Languages: TypeScript, JavaScript

Frameworks: React, Vite

Libraries: Tailwind CSS, Lucide Icons, react-hot-toast

Tools: GitHub, Vercel

For Hardware:

🥲 Banana leaf (virtual)

Eyes of the AI (YOLOv8 model or placeholder logic)

Camera (optional, but for best accuracy, use DSLR... joking)

Implementation

For Software: Installation

git clone https://github.com/Neeraj2303/Sadhya_Analyser.git
cd Sadhya_Analyser
npm install

Run

npm run dev

Deploy

Deployed on Vercel LINK: https://sadhya-analyser.vercel.app/

Project Documentation Screenshots

 Main analysis UI with mock leaf and items detected

For Hardware: (if future integration happens)

[Add demo video link here] Shows uploading an image, analyzing, and getting judged by an AI with no culinary training Additional Demos

Team Contributions

Neeraj Sukumaran: Frontend UI, AI logic integration, model prompt engineer, cultural accuracy expert

Kalidas V.S. : Model prompt engineer, cultural accuracy

Made with ❤️ (and banana leaves) at TinkerHub Useless Projects