Toolbox for experimenting with (Overcomplete) Dictionary Learning for Vision model
Project description
Overcomplete is a compact research library in Pytorch designed to study (Overcomplete)-Dictionary learning methods to extract concepts from large Vision models. In addition, this repository also introduces various visualization methods, attribution and metrics. However, Overcomplete emphasizes experimentation.
🚀 Getting Started with Overcomplete
Overcomplete requires Python 3.8 or newer and several dependencies, including Numpy. It supports both only Torch. Installation is straightforward with Pypi:
pip install overcomplete
With Overcomplete installed, you can dive into any optimisation based dictionary learning method to extract visual features. The API is designed to be intuitive, requiring only a few hyperparameters to get started.
Example usage:
import torch
import overcomplete
todo
Notebooks
Citation
@article{todo,
}
Authors
- Thomas Fel - thomas_fel@brown.edu, PhD Student, Brown University & DEEL (ANITI)
- Remi Cadène - todo
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