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.
-
Clone the repository:
git clone https://github.com/moscardino1/frudrera.git cd frudrera
-
Create a virtual environment:
python3 -m venv venv
-
Activate the virtual environment:
- On macOS/Linux:
source venv/bin/activate
- On Windows:
venv\Scripts\activate
- On macOS/Linux:
-
Install the required packages:
pip install -r requirements.txt
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.
To deploy the application:
-
Navigate to the
frudrera
directory:cd frudrera
-
Deploy using Vercel:
vercel deploy
-
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.