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Eye-Tracking with Deep Learning and Real-Time Mouse Control

This project controls the cursor on the screen with real-time eye-tracking using a custom-trained convolutional neural network (CNN) based on eye images captured from a webcam.

Features

  • Real-time eye tracking: Uses a webcam feed to capture images of the eye in real time.
  • CNN-based prediction: A CNN is trained to predict the (x, y) coordinates on the screen where the user is looking.
  • Mouse control: The predicted coordinates are used to move the mouse cursor on the screen.
  • Smoothing and responsiveness: Implements an exponential moving average (EMA) smoothing algorithm with a movement threshold for responsive yet (somewhat) stable cursor control.

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