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🔭 Real-time Streamlit Facial Emotion Recognition web application to monitor student's mood in a classroom

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🔭 Facial Emotion Recognition App

Welcome to the Facial Emotion Recognition App, a real-time web application designed to monitor students' moods in a classroom. Utilizing a convolutional neural network with Python, Streamlit, and Streamlit WebRTC, this app provides insightful emotion analysis in educational environments.

Features

  • Real-Time Emotion Recognition: Uses advanced CNN to identify and analyze emotions in real-time.
  • Streamlit Integration: Offers a user-friendly web interface for easy interaction and monitoring.
  • Educational Focus: Tailored to understand and improve the classroom experience.

Getting Started 🚀

Prerequisites

  • Docker and Docker Compose

Environment Setup

# Copy environment variables
cp .env.example .env

# Start development containers
docker-compose up

Run tests

Execute tests as described in the Python unittest documentation..

docker-compose exec app python -m unittest -v <test_class_directory>

Collaborators 👥

This project is the result of the collaborative efforts of these fantastic individuals:

We thank them for their invaluable contributions and expertise.

License

This project is open-sourced software licensed unde the MIT license.