  Deep learning computer vision techniques have achieved many successes in
recent years across numerous imaging domains. However, the application of deep
learning to spectral data remains a complex task due to the need for
augmentation routines, specific architectures for spectral data, and
significant memory requirements. Here we present spectrai, an open-source deep
learning framework designed to facilitate the training of neural networks on
spectral data and enable comparison between different methods. Spectrai
provides numerous built-in spectral data pre-processing and augmentation
methods, neural networks for spectral data including spectral (image)
denoising, spectral (image) classification, spectral image segmentation, and
spectral image super-resolution. Spectrai includes both command line and
graphical user interfaces (GUI) designed to guide users through model and
hyperparameter decisions for a wide range of applications.
