A near-autonomous gameplay assistant developed for educational and technical skill-building purposes. Powered by real-time computer vision and automation techniques.
This project uses computer vision to detect the position of the player's character in Brawlhalla and makes real-time movement decisions based on screen analysis. Designed as a beta-stage automation system, it showcases visual tracking, control flow, and gameplay adaptation through image processing.
🧪 Built to experiment with character tracking, visual input recognition, and motion automation.
- Detects the player's character using visual recognition
- Tracks the character’s position in real-time
- Performs automated directional movements based on location
- Modular code for experimentation and extension
- Works with various screen resolutions
- Python
- OpenCV – for image processing
- MSS – for real-time screen capture
- NumPy – for matrix calculations
- PyAutoGUI / PyWin32 / PyAutoIt – for keyboard/mouse automation
- Pillow – for image manipulation
- Keyboard / Playsound – for interaction and feedback
pip install opencv-python numpy mss pyautogui pywin32 -U pyautoit playsound keyboard Pillow