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FRUDRERA - AI Recipe Recommender

Overview

FRUDRERA is an AI-powered recipe recommender that suggests recipes based on the ingredients detected in a photo of your fridge. It utilizes object detection and OCR to identify ingredients and recommend recipes accordingly.

Features

  • Upload an image of your fridge to detect ingredients.
  • Get recipe recommendations based on detected ingredients.
  • View detailed recipe information including ingredients, steps, and cooking time.

Technologies Used

  • Flask: Web framework for building the application.
  • YOLOv5: Object detection model for identifying ingredients.
  • EasyOCR: Optical Character Recognition for detecting text in images.
  • FuzzyWuzzy: For matching ingredients with recipe names.

Setup

  1. Clone the repository:

    git clone https://github.com/moscardino1/frudrera.git
cd frudrera

  2. Create a virtual environment:

    python3 -m venv venv

  3. Activate the virtual environment:

    • On macOS/Linux: 
      source venv/bin/activate
    • On Windows: 
      venv\Scripts\activate

  4. Install the required packages:

    pip install -r requirements.txt

Running the Application

To run the application in development mode: python frudrera/app.py Visit http://127.0.0.1:5000 in your web browser to access the application.

Deployment

To deploy the application:

  1. Navigate to the frudrera directory:

    cd frudrera

  2. Deploy using Vercel:

    vercel deploy

  3. For production deployment:

    vercel --prod

Additional Notes

  • Ensure to add charts and results interacting with input for better user experience.
  • The layout should be user-friendly for easier navigation and understanding.
  • Costs and rent expenses should be monthly and autopopulated.

License

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

Acknowledgments

  • Thanks to the contributors and libraries that made this project possible.