Artificial Intelligence final project in San Diego State University designed to evaluate the nutritional quality of food products and suggest healthier alternatives using Machine Learning methods.
Our goal is to help users make more informed dieatary choices by automatically assesing products through scoring formula and machine learning clustering models (K-means).
First of all, download or clone the repo:
git clone https://github.com/skyscrabble/NutritionalRater
cd yourprojectCreate a virtual environment (optional):
python -m venv venv
source venv/bin/activate # macOS/Linux
venv\Scripts\activate # WindowsThen, install dependencies:
pip install -r requirements.txtSimply execute the main.py file to run the program:
python main.pyOnce in the main menu interface, input the barcode of the product you want to scan and analyze:
Once scanned, the program will ouptut a detailed analysis of the product plus 5 better related options (if there are):
In section 3 there can be found the summarized output information:
For detailed info about the project, visualization of the k-means clusters and the utilized formulas, check the 'doc' folder within the repo.