Metadata-Version: 2.1
Name: gref4hsi
Version: 0.1.5
Summary: A Python package for for georeferencing and orthorectifying hyperspectral imagery
Home-page: https://github.com/havardlovas/gref4hsi
Author: Haavard Snefjellaa Loevaas
Author-email: havard.s.lovas@ntnu.no
License: EUPL-1.2
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: European Union Public Licence 1.2 (EUPL 1.2)
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >3.7
Description-Content-Type: text/markdown
License-File: LICENCE.MD
Requires-Dist: opencv-python
Requires-Dist: dill
Requires-Dist: geopandas
Requires-Dist: h5py
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: open3d
Requires-Dist: pandas
Requires-Dist: Pillow
Requires-Dist: pymap3d
Requires-Dist: pyproj
Requires-Dist: pyvista
Requires-Dist: pyvistaqt
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: shapely
Requires-Dist: spectral
Requires-Dist: xmltodict
Requires-Dist: pykdtree
Requires-Dist: trimesh
Requires-Dist: rtree
Requires-Dist: embreex
Requires-Dist: ephem

# gref4hsi

The hyperspectral toolchain is a toolbox for the georeferencing and orthorectification of hyperspectral pushbroom data. It was made with a special emphasis on georeferencing and co-registration of underwater hyperspectral data. However, it is equally simple to use for airborne data.

Installation instructions:

Set up a virtual environment with python 3.8. The following has been confirmed to work with anaconda virtual environment with python=3.8 on a windows 10, dell precision

GDAL and rasterio: These are downloaded as wheel (*.whl) files for python 3.8 to the /dependencies folder. Navigate here cd /dependencies and run the following to install these:
for %x in (dir *.whl) do python -m pip install %x

For remaining dependencies, run:
pip install -r requirements.txt

A *.bat script was added for automated installation and testing.

The pyvista function multi_ray_trace depends on the pyembree install and should be tested with /test/test_multi_ray_trace.py. For my machine the test takes 0.35 s. If it does not work, consider installing pyembree with anaconda (for mac and linux):
conda install -c conda-forge pyembree

