{"id":25173994,"url":"https://github.com/macorisd/u-cv-ttt","last_synced_at":"2026-05-01T09:31:40.762Z","repository":{"id":213426099,"uuid":"734101199","full_name":"macorisd/U-CV-TTT","owner":"macorisd","description":"A computer vision-powered TicTacToe game where a mobile device camera acts as the player's eyes. 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The application uses Python and OpenCV to recognize and interact with the TicTacToe board.\n\n## Key Features\n- Play against an AI with three difficulty modes: Easy, Medium, and Nightmare.\n- Real-time board recognition via a mobile device camera.\n- Train and test your own symbol classifier for custom configurations.\n\n## Requirements\n- Python (latest version recommended)\n- DroidCam installed on your mobile device\n\n## Installation\nFollow these steps to set up the project:\n\n1. **Clone the Repository**\n   ```bash\n   git clone https://github.com/macorisd/U-CV-TTT.git\n   ```\n\n2. **Install Python**\n   - Go to [python.org/downloads](https://www.python.org/downloads/).\n   - Download and install the latest version of Python.\n\n3. **Install DroidCam on a Mobile Device**\n   - For Android: [Download from Google Play Store](https://play.google.com/store/apps/details?id=com.dev47apps.droidcam\u0026hl=es\u0026gl=US\u0026pli=1).\n\n4. **Install Required Python Packages**\n   - Open the project folder, named `U-CV-TTT`.\n   - Right-click in the folder and select **Open in Terminal**.\n   - Install dependencies using one of the following methods:\n\n     **Option 1:** Run the batch file `install_packages.bat` located in the `Setup` folder.\n\n     **Option 2:** Install packages manually by running the following commands:\n     ```bash\n     pip install opencv-python\n     pip install shapely\n     pip install matplotlib\n     ```\n\n5. **You're ready to play!**\n   - Open the file `U-CV-TTT.pyw` for direct execution, or run `U-CV-TTT.py` to view the Python code.\n\n## How to Play\n\n1. Connect both your mobile device and computer to the same Wi-Fi network (or tether your computer to your mobile data).\n2. Launch DroidCam on your mobile device.\n3. Run the `U-CV-TTT.pyw` file.\n4. Click on the **IP/Port** button in the application window.\n5. Enter the IP and port provided by DroidCam into the corresponding fields.\n6. Select a difficulty mode: Easy, Medium, or Nightmare.\n7. Capture board images by pressing the spacebar. Exit the application by pressing `q`.\n\n## Tips for Optimal Performance\n- Use plain white paper and a black marker for better recognition.\n- Align the TicTacToe board approximately within the provided grid, but avoid placing it too close to the camera.\n- You may choose to draw or not draw the bot's moves on the paper; both approaches work.\n\n## Advanced Features\n\n1. **Train Your Own Symbol Classifier**\n   - Use the `train_classifier.py` script to train a custom symbol classifier.\n\n2. **Test the Symbol Classifier**\n   - Use the `test_classifier.py` script to evaluate your classifier's performance.\n\n## Author\nMade with ❤️ by **Macorís Decena Giménez**.  \n[GitHub Profile](https://github.com/macorisd)\n\n## Reporting Issues\nIf you encounter any bugs or issues, please feel free to contact me at **macorisd@gmail.com**.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmacorisd%2Fu-cv-ttt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmacorisd%2Fu-cv-ttt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmacorisd%2Fu-cv-ttt/lists"}