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EyeFeatures is an end-to-end Python library for eye-tracking data analysis, designed to make eye-tracking research accessible to developers and scientists alike. From raw gaze preprocessing to complex feature engineering and deep learning, eyefeatures provides a unified, production-ready framework.
Key Features
Scikit-learn Integration: All transformers follow the fit/transform API and work seamlessly with sklearn.Pipeline.
PyTorch-Ready: Native PyTorch Dataset classes and neural network modules (CNN, LSTM, GNN, ViT) for gaze-based classification.
Scanpath Visualizations: Static and animated scanpath plots, heatmaps, and AOI overlays.
50+ Methods: Extensive library of preprocessing, statistical, complexity, and distance-based features.
Group Analysis: Built-in support for individual normalization and group-level comparisons.
Installation
pip install eyefeatures
Check Contribution page in the documentation for installation with poetry.
Documentation & Tutorials
Check out our Full Documentation and the following interactive tutorials: