TicTacToeWithEmotionAI is an innovative game that combines classic Tic-Tac-Toe with real-time emotion recognition. Using machine learning, the game analyzes player emotions and adapts gameplay, creating a unique, interactive experience.
- Emotion recognition via AI models
- Adaptive gameplay based on player emotions
- Multiple model architectures (basic, random, transfer learning)
- Intuitive graphical user interface
- Tools for data preprocessing and export
- Python
- Machine Learning (Transfer Learning, Custom Models)
- GUI Development
- Data Processing
This project demonstrates practical skills in machine learning, computer vision, and software engineering. It showcases end-to-end development: data preprocessing, model training, UI design, and game logic integration.
- Install dependencies from
requirements.txt - Run the game with
run.py - Explore emotion model training and dataset tools in the
src/directory
- End-to-end ML pipeline implementation
- Real-time emotion analysis and integration
- Modular, well-documented codebase
- Experience with transfer learning and custom model development