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.

• 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.

• 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.

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

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

To deploy the application:

1. Navigate to the frudrera directory:

   cd frudrera

2. Deploy using Vercel:

   vercel deploy

3. For production deployment:

   vercel --prod

• 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.

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

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