Machine Vision Balloon Pop Game
Experience an interactive balloon pop game using real-time hand gestures and dynamic difficulty settings.
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Prompt
Project Title: "Machine Vision-Based Balloon Pop Game" Objective: Real-time hand gesture recognition to interact with the game. Dynamic difficulty across 10 levels, based on score. Multimedia feedback (images, sound effects, and jumpscares). Libraries & Tools Used: OpenCV – Image processing and real-time video capture. cvzone – Hand tracking and gesture detection. pygame – Game development (graphics, events, audio). NumPy – Numerical operations for image processing. pygame.mixer – Background music and sound effects. Machine Learning Model: cvzone HandDetector – Tracks hand positions and gestures in real time. Outcome: Interactive gameplay using hand gestures. Escalating difficulty with higher levels. Jumpscare image and audio when the user loses.
