Welcome to interpret-segmentation’s documentation!

interpret-segmentation is a one-stop shop for the interpretability of image segmentation models. This code was extracted from the code of my bachelor thesis: https://github.com/andef4/thesis-code.

The PDF of the thesis is available here: https://github.com/andef4/thesis-doc/releases/download/release/thesis.pdf. It contains detailed explanations of the methods used here.

The following methods are currently implemented:


For pip based environments:
pip install interpret_segmentation
For anaconda users:
conda install interpret_segmentation

All dependencies except pytorch and torchvisison are installed automatically. Please install pytorch and torchvision manually as described on https://pytorch.org/get-started/locally/.


Examples how to use the two algorithms are provided in the examples subdirectory in the git repository. The examples use the testnet dataset, which was specifically built as a showcase for these algorithms.