AI Mental Health Companion

Inspiration

We wanted to create a simple way to support mental health. Many people feel lonely or stressed, and not everyone has access to help. So, we built a web app that acts like a caring friend.

What it does

Our web application detects emotions from facial expressions and provides real-time, friendly conversations. It helps reduce stress, motivates the user, and makes them feel supported.

How we built it

We used Python, Streamlit, and AI/ML models for emotion detection. The front-end runs on Streamlit for easy web access, and the backend processes facial inputs and generates human-like responses.

Challenges we ran into

1. Difficulty in making accurate facial emotion detection.
2. Managing real-time interaction without freezing. ## Accomplishments that we're proud of
3. Successfully built a working web prototype.
4. Created a smooth, simple interface that anyone can use.
5. Made a privacy-first system that doesn’t share user data. ## What we learned
6. How to integrate AI/ML with a web framework like Streamlit.
7. The importance of user-friendly design in mental health tools.
8. How real-time AI responses can make people feel heard. ## What's next for AI Mental Health Companion
9. Improving accuracy of emotion detection.
10. Adding more engaging conversation styles.
11. Expanding it into a mobile app for wider accessibility.

Built With

• css
• javascript
• opencv
• python
• pytorch
• tensorflow