  M3d-CAM is an easy to use library for generating attention maps of CNN-based
PyTorch models improving the interpretability of model predictions for humans.
The attention maps can be generated with multiple methods like Guided
Backpropagation, Grad-CAM, Guided Grad-CAM and Grad-CAM++. These attention maps
visualize the regions in the input data that influenced the model prediction
the most at a certain layer. Furthermore, M3d-CAM supports 2D and 3D data for
the task of classification as well as for segmentation. A key feature is also
that in most cases only a single line of code is required for generating
attention maps for a model making M3d-CAM basically plug and play.
