Overview

The Receipt Analyzer is a machine learning project aimed at calculating the carbon footprint of grocery purchases. It processes receipt data to provide insights into the environmental impact of consumer spending.

Features

• Data Extraction: Utilizes Optical Character Recognition (OCR) to extract text from scanned grocery receipts.
• Carbon Footprint Calculation: Analyzes purchased items and calculates their associated carbon emissions based on predefined metrics.
• User-Friendly Dashboard: Presents the results in a clear, interactive dashboard for users to visualize their carbon footprint.
• Export Functionality: Allows users to export their analysis results for personal records or further review.

Technologies Used

• Languages: Python
• Libraries:
  • OCR: PyTesseract for text extraction
  • Data Analysis: Pandas, NumPy
  • Visualization: Matplotlib, Seaborn
• Frameworks: Flask for web application deployment

Installation

To run this project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/yourusername/receipt-analyzer.git

2. Navigate to the project directory:

   cd receipt-analyzer

3. Install the required packages:

   pip install -r requirements.txt

4. Run the application:

   python app.py

Usage

1. Upload a scanned image of your grocery receipt.
2. The application will process the image, extract item details, and calculate the carbon footprint.
3. View your results in the dashboard.

Contribution

Contributions are welcome! Feel free to submit issues or pull requests to improve the project.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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