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This project utilizes computer vision techniques to recognize and interpret hand gestures, allowing for a more intuitive and natural way of interacting with computers. The project includes a Jupyter notebook that contains the code for detecting and tracking hand landmarks using the MediaPipe Hands library and OpenCV.