Explore the innovative AI projects developed by Synapse, the official AI club of MIT WPU.
A real-time computer vision application that transforms ordinary webcam footage into interactive depth maps using the MiDaS neural network. The system estimates distances of objects from the camera and visualizes them through intuitive color coding - with warm colors indicating nearby objects and cool colors showing distant ones. Features include switchable indoor and outdoor modes, real-time distance measurements, and an interactive color legend. Built with Python, OpenCV, and PyTorch, this project demonstrates practical applications of monocular depth estimation for robotics, AR prototyping, and computer vision research.
Led by Charitra Jain
An innovative application that simulates the neurological phenomenon of synesthesia by converting colors into musical notes in real-time. Using computer vision to analyze webcam input, the system maps color properties to musical characteristics - hue determines the note, brightness controls the octave, and saturation selects the instrument timbre (piano, violin, or trumpet). The grid-based analysis system allows users to explore how different colors in their environment translate into unique soundscapes. This project combines OpenCV for visual processing with Pygame for audio synthesis, offering an engaging way to experience the intersection of perception, AI, and creative expression.
An interactive gesture-controlled pong game that replaces traditional keyboard controls with hand tracking technology. Players control their paddles using real-time hand movements detected through a webcam, creating an immersive gaming experience that bridges physical motion with digital gameplay. The system uses computer vision to track both left and right hands simultaneously, allowing for two-player matches where hand positions translate directly to paddle movements on screen. Features include real-time score tracking, collision detection, game restart functionality, and a split-screen view showing both the gameplay and the raw webcam feed. This project demonstrates practical applications of hand tracking and gesture recognition in interactive entertainment.
Led by Huzefa Pishori