I've been working on siapy-lib, a Python library for processing and analyzing hyperspectral and multispectral images. It’s aimed at researchers, engineers, and developers who want to work with spectral image data without the overhead of large GUI-based tools like ENVI or SNAP.

The library focuses on flexibility and modularity, using a plugin-based architecture to make it easy to extend and integrate into your own pipelines.

Key features: • Spectral Image Handling: Read and visualize ENVI, GeoTIFF, and raw image cubes with ease. • Spectral Analysis: Extract and analyze spectral signatures • Machine Learning Integration: Label image regions, train models, and segment images • Camera Co-registration: Align data from multiple sensors and compute transformations between camera spaces. • Radiometric Conversion: Convert radiance to reflectance using reference panels. • CLI Tool (Experimental): Basic command-line access via siapy-cli for quick prototyping.

The library is still evolving, and I’d love feedback from people working in remote sensing, Earth observation, or spectral imaging—whether academic or applied. Suggestions, bug reports, or contributions are all welcome!

GitHub: https://github.com/siapy/siapy-lib CLI (optional): https://github.com/siapy/siapy-cli