Hand Gesture Controlled Tic-Tac-Toe

Table of Contents

• Introduction
• Features
• Technologies Used
• Installation
• Usage
• Demo
• Challenges
• Author
• License

Introduction

I developed a Hand Gesture Controlled Tic-Tac-Toe game using Python, OpenCV, and Mediapipe. This project allows users to play Tic-Tac-Toe by using hand gestures, enhancing the interactivity and providing a unique gaming experience.

Starting from scratch, I delved into computer vision and machine learning, leveraging numerous tutorials and videos to guide me through the process. This project not only enhanced my programming skills but also provided hands-on experience with real-time gesture recognition and interactive game design.

Features

• Real-Time Hand Gesture Detection: Utilizes Mediapipe for accurate and swift hand gesture recognition.
• Interactive GUI: Built with OpenCV, providing a seamless and responsive user interface.
• Dynamic Game Logic: Enables users to compete against the computer with intelligent move selections.
• Symbol Selection: Allows users to choose their preferred symbol (X or O) before starting the game.
• Responsive Feedback: Provides visual cues and instructions to guide users during gameplay.

Technologies Used

• Python 3.10
• OpenCV: For image and video processing.
• Mediapipe: For real-time hand gesture recognition.
• NumPy: For numerical operations.

Installation

Prerequisites

• Python 3.7 to 3.11 (64-bit): Mediapipe supports these Python versions. You can download Python from the official website.
• Git: To clone the repository. Download from here.

Steps

1. Clone the Repository:

   git clone https://github.com/YOUR_GITHUB_USERNAME/hand-gesture-tic-tac-toe.git

Navigate to the Project Directory:

bash Copy code cd hand-gesture-tic-tac-toe Create a Virtual Environment:

bash Copy code python -m venv myenv Activate the Virtual Environment:

Windows:

bash Copy code myenv\Scripts\activate macOS/Linux:

bash Copy code source myenv/bin/activate Upgrade pip:

bash Copy code python -m pip install --upgrade pip Install Required Packages:

bash Copy code pip install -r requirements.txt If requirements.txt is not provided, install the packages manually:

bash Copy code pip install opencv-python mediapipe numpy Usage Activate the Virtual Environment:

Ensure you're in the project directory and the virtual environment is activated.

Windows:

bash Copy code myenv\Scripts\activate macOS/Linux:

bash Copy code source myenv/bin/activate Run the Game:

bash Copy code python tic_tac_toe.py Gameplay Instructions:

Start Screen: Press 'S' to start the game. Choose Symbol: Press 'O' for Circle or 'X' for Cross. Place Symbol: Point your finger inside a cell for 1 second to place your chosen symbol. Winning the Game: The game will declare the winner and provide options to restart or quit. Demo

You can also include a GIF or link to a video demonstration here.

Challenges Hand Gesture Recognition: Ensuring accurate and swift recognition of gestures in real-time was challenging. Mediapipe's robust algorithms were instrumental in overcoming this. GUI Development: Creating an intuitive and responsive interface using OpenCV required a good understanding of image processing techniques. Compatibility Issues: Encountered issues with Python version compatibility, specifically with Mediapipe not supporting Python 3.13. Switching to Python 3.10 resolved this. Author Shon Pasis

LinkedIn GitHub Email License This project is licensed under the MIT License.

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