torchosr - A PyTorch extension package for Open Set Recognition models evaluation in Python

The article presents the torchosr module - a Python package compatible with PyTorch library - offering functionality and models dedicated to Open Set Recognition in Deep Neural Networks. Included software offers two frequently used base recognition methods in the field and a set of functions for handling datasets, enabling the generation of derived datasets, where some classes are considered unknown and used only in the testing process. Code base is enhanced with a set of helper functions, facilitating model validation process. The main goal of the proposal is to simplify and promote the correct experimental evaluation, where experiments are carried out on a large number of derivative sets with various Openness, related to the cardinality of known and unknown classes, and class-to-category assignments. The authors hope that methods available in the package will become a source of a correct and open-source implementation of the relevant baseline and state-of-the-art solutions in the domain.