mvos-hsi 0.1.0

Hyperspectral imagery (HSI) preprocessing utilities for Machine Learning applications

mvos_hsi

MVOS Hyperspectral Imaging Utilities
Python package for calibration, clipping, and augmentation of hyperspectral leaf images, ported from MATLAB scripts.

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Features

• Calibration

  • Single image or batch folder calibration
  • Dark and white reference correction
  • Spectral binning & spatial binning options
  • Outputs calibrated reflectance and fluorescence cubes
  • Saves calibrated cubes as .mat files (*_R.mat, *_F.mat)

• Clipping

  • Detect leaves using vegetation indices:
    • NDVI (Normalized Difference Vegetation Index)
    • CI-RedEdge (Chlorophyll Index Red-Edge)
    • GCI (Green Chlorophyll Index)
  • Thresholding via Otsu (auto) or manual (e.g., NDVI > 0.45)
  • Flexible cropping:
    • Square windows (fixed size, e.g., 30×30 pixels)
    • Tight bounding boxes fit to each leaf
  • Saves clipped cubes as ENVI files (.hdr + .img) in clipped_hypercubes/

• Augmentation

  • Apply data augmentation to calibrated or clipped cubes
  • Options:
    • Per image (single .mat or .hdr)
    • Per folder
    • Per class (each subfolder = class label)
  • User-defined number of augmentations
  • Saves augmented cubes in augmented_hypercubes/

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Installation

Clone this repository and install in editable mode:

conda activate hyperspectral
pip install -e .