🥗 Nutrition Tracker

Nutrition Tracker is a full-stack web application that helps users analyze daily nutrition intake by scanning food labels.
It uses Tesseract OCR to extract data from nutrition labels and a Flask backend to process and analyze the information.
The frontend is built with React, providing a clean and interactive interface for users to upload, view, and explore nutritional insights.

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Features

• OCR Scanning – Upload a photo of a nutrition label and extract text automatically using Tesseract.
• Smart Analysis – Parse calories, and calculate macronutrients and micronutrients from text for structured display.
• Backend API – Flask backend processes OCR data and handles business logic.
• Interactive Frontend – React UI for uploading images, displaying results, and managing analysis history.
• Real-time Feedback – See nutritional summaries instantly after label upload.

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Tech Stack

Frontend

• React (TypeScript)
  • React Router
  • Tanstack Query
  • Recharts

Backend

• Flask (Python)
• Tesseract OCR (pytesseract) for text recognition
• Flask-SQLAlchemy
• PostgreSQL
• Google Gemini to provide users with feedback about their intake

Installation & Setup

Backend Setup (Flask)

cd flask-backend
python -m venv venv
source venv/bin/activate      # (or venv\Scripts\activate on Windows)
pip install -r requirements.txt
flask run

The backend will start at http://localhost:5000

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Frontend Setup (React)

Open a new terminal:

cd frontend
npm install
npm run dev

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Connect Frontend ↔ Backend

The frontend sends API requests to:

http://localhost:5000/api/

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How It Works

1. User uploads an image of a food label.
2. The image is sent to the Flask API.
3. Flask uses pytesseract to extract text from the image.
4. Extracted data is parsed into structured nutritional info (calories, fat, protein, etc.).
5. The frontend displays an easy-to-read summary.