54. SiaPy – a User Friendly Python Software for Hyperspectral Image Segmentation

Commercial software is often prohibitively expensive, and therefore inaccessible for most users. Open-source software can facilitate analysis, but is usually less user friendly. The objective of this research was to develop, debug, and test SiaPy (Spectral imaging analysis for Python) software for image segmentation. It was evaluated on a hyperspectral dataset portraying one potato (Solanum tuberosum L.) cultivar with tolerance to drought. Pilot-case results confirm the efficacy of SiaPy utilization in the agricultural domain, especially in cases where multiple hyperspectral images need to be processed. Furthermore, it can be a great substitution for enterprise software, which are used to perform hyperspectral image segmentation.