Tracking Daily Food Consumption is a research-based project developed at Ho Chi Minh Open University (HCMOU) from May 2024 to March 2025. The application helps users manage their diet and track daily nutrition intake using machine learning models trained on Vietnamese food data.
- 🥗 Personalized Meal Suggestions: Generates meal recommendations based on height, weight, age, and gender.
- 🔎 Food Database Lookup: Allows users to search for foods and view their detailed nutritional values.
- 🍛 Custom Meal Planning: Users can design their own meals based on dietary needs and preferences.
- 📊 Data Analysis & Clustering: Utilizes machine learning algorithms to classify and recommend food items.
This project is built using the following technologies:
- 💪 Scikit-Learn: Machine learning library for food classification and clustering.
- 🌟 Streamlit: Interactive web framework for visualizing data and building the user interface.
- 📊 K-Means & Decision Tree: Used for calorie clustering and meal classification.
- 📂 Vietnamese Food Dataset: Collected and processed for machine learning model training.
Ensure you have Python 3.8+ and pip installed.
- Clone the repository:
git clone https://github.com/your-username/tracking-daily-food.git cd tracking-daily-food - Install dependencies:
pip install -r requirements.txt
- Run the Streamlit app:
streamlit run app.py
- Open the browser and navigate to
http://localhost:8501
Click here to try out the app!
- Database (if available): Vietnamese food Link
- Research Paper (if available): Paper Link
Developed by Nguyen Lu Hong Phuong as part of a scientific research project at Ho Chi Minh Open University (HCMOU).
- 🔥 Add real-time calorie tracking with user-uploaded meals.
- 📱 Develop a mobile version using React Native.
- 🌎 Expand the food database for global cuisine support.