Open projects

Fractal Hunter — Robust Image Classification Under Extreme Distortion

## Up the Gain — Electric & Distortion-Ready Blorbos (toon penguins) hide by transforming into distorted, non-intuitive representations. You are given a dataset derived from a small set of source images, transformed through unknown but structure-preserving processes. 📦 Dataset & full documentation: https://github.com/andrewrgarcia/fractal-hunter-dataset 🔬 Kaggle (for experimentation): https://www.kaggle.com/datasets/drandrewgarcia/fractal-hunter-extreme-distortion ### Task Build a model that determines whether an image originated from Blorbo. ### Constraints - Transformation is unknown - No explicit inversion tricks - Must generalize to unseen images and transformations ### Goals - Robust classification under severe distortion - Clear approach + failure analysis ### Evaluation Held-out test set uses unseen transformations ### Stretch - Learn invariant representations - Recover structure without knowing the transform **Stack:** Python · PyTorch / sklearn