Emotion Tracker is a project developed for the ConUHacks hackathon that focuses on tracking and analyzing emotional states through user interaction data.
This project aims to provide insights into emotional patterns by capturing user emotions in real-time or through periodic assessments. It leverages computer vision techniques and machine learning models to classify emotions from visual input.
- Real-time emotion detection using OpenCV for facial recognition and feature extraction
- Emotion classification powered by trained machine learning models to accurately identify emotional states
- Visualization of emotional trends to help users better understand their mood changes
- Responsive and intuitive web interface for smooth user experience
- Clone this repository:
git clone https://github.com/kunwar45/conuhacks.git
- Run the application and allow access to your webcam for real-time emotion tracking.
This project is licensed under the MIT License.