  In this paper we introduce a tool called Principal Image Sections Mapping -
PRISM, dedicated for PyTorch, but can be easily ported to other deep learning
frameworks. Presented software relies on Principal Component Analysis to
visualize the most significant features recognized by a given Convolutional
Neural Network. Moreover, it allows to display comparative set features between
images processed in the same batch, therefore PRISM can be a method well
synerging with technique Explanation by Example.
