Swift-Eye: Towards Anti-blink Pupil Tracking for Precise and Robust High-Frequency Near-Eye Movement Analysis with Event Cameras

fast_forward_video.mp4

This is the implementation code for Swift-Eye, which was built upon MMRotate: A Rotated Object Detection Benchmark using PyTorch.

Setup

For a smooth setup, we kindly suggest referring to mmrotate to install mmrotate and the requirements.txt file in our project to set up the environment.

Data

A test dataset is available for download here. After downloading, please unzip the folder and place it in the Swift_Eye/mmrotate/train_swift_eye directory. If you require additional data, consider checking EV-Eye and utilizing the code from timelens in the other folder.

Model Weights

You can access the model weights from this link. After downloading, kindly place the weighst in the Swift_Eye/mmrotate/train_swift_eye/swift_eye directory.

Execution

To generate results and the corresponding videos, execute /Swift-Eye/Swift-Eye/test_interpolated.py.