Meal Classifier
A simple Streamlit app that uses computer vision to determine if a meal is healthy or unhealthy based on its image.
Role: Developer & ML Enthusiast | Focus: Streamlit, Computer Vision
Project Highlights
- Developed a quick and easy meal classification tool for healthy vs. unhealthy food detection.
- Built a lightweight Streamlit interface for real-time predictions.
- Applied a pre-trained CNN model to classify meal images with minimal training data.
- Used OpenCV for simple image preprocessing and resizing.
- Designed for easy experimentation and potential integration into larger health tracking apps.
Key Takeaways
- Streamlit is ideal for quickly turning ML models into usable web apps.
- Lightweight image preprocessing can work well for basic classification tasks.
- Transfer learning greatly reduces the need for large custom datasets.
- Single-page ML apps are a great starting point for broader AI-driven platforms.
Project Links
App Preview
