EmoQuest
EmoQuest is a gamified application developed to help individuals, especially those on the autism spectrum or with social communication disorders, enhance their emotional intelligence skills. The application utilizes computer vision technology to analyze facial expressions and guide users in recognizing and understanding complex emotions.
Features
Upload photos of friends and family to analyze their facial expressions. Deep Face computer vision library analyzes the emotions displayed in the uploaded photos. Engaging multiple-choice game challenges users to recognize emotions based on facial expressions. Progression system with levels that gradually increase the complexity of emotions to identify. User-friendly interface developed using Tkinter. Installation
Clone the EmoQuest repository. Create a Python virtual environment. Activate the virtual environment. Install the required dependencies: arduino Copy code pip install opencv-python matplotlib tensorflow git+https://github.com/serengil/deepface.git Usage
Run the EmoQuest application. Upload photos of friends and family members. Start the game mode to recognize emotions based on facial expressions. Level up by improving your recognition abilities and identifying more subtle emotions. Challenges
Learning Tkinter for creating the user interface. Integrating various packages and managing dependencies. Combining front-end design with back-end logic for a seamless experience. Developing a game and all its components. Accomplishments
Successfully learning and implementing Tkinter for the user interface. Achieving a basic version of the frontend design and user experience. Implementing the game's basic flow and progression system. Maintaining an efficient and well-organized team dynamic. Next Steps
Implement a progress bar and level-up system. Introduce higher levels with more complex emotions and multiple-answer format. Create a nonverbal communication skills game with a live camera feature. Expand real-world scenarios to enhance emotional intelligence skills. Team Members
Harrison Parshana Sophie Elise