https://github.com/spectralpython/spectral

Python module for hyperspectral image processing
https://github.com/spectralpython/spectral

anomaly-detection hyperspectral hyperspectral-image-classification image-processing python remote-sensing target-detection visualization

Last synced: 13 days ago
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Python module for hyperspectral image processing

• Host: GitHub
• URL: https://github.com/spectralpython/spectral
• Owner: spectralpython
• License: mit
• Created: 2014-02-06T03:36:54.000Z (almost 11 years ago)
• Default Branch: master
• Last Pushed: 2024-08-09T19:28:43.000Z (3 months ago)
• Last Synced: 2024-08-16T23:22:36.147Z (3 months ago)
• Topics: anomaly-detection, hyperspectral, hyperspectral-image-classification, image-processing, python, remote-sensing, target-detection, visualization
• Language: Python
• Size: 1.38 MB
• Stars: 569
• Watchers: 36
• Forks: 139
• Open Issues: 21
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.txt

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README

        
Spectral Python (SPy)

---------------------

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Spectral Python (SPy) is a pure Python module for processing hyperspectral image

data (imaging spectroscopy data). It has functions for reading, displaying,

manipulating, and classifying hyperspectral imagery. Full details about the

package are on the `web site `_.

Installation Instructions

=========================

The latest release is always hosted on `PyPI `_,

so if you have `pip` installed, you can install SPy from the command line with

.. code::

    pip install spectral

Packaged distributions are also hosted at `PyPI `_

and `GitHub `_

so you can download and unpack the latest zip/tarball, then type

.. code::

    python setup.py install

To install the latest development version, download or clone the git repository

and install as above. No explicit installation is required so you can simply

access (or symlink) the `spectral` module within the source tree.

**Finally**, up-to-date guidance on how to install via the popular conda package 

and environment management system can be found at official `conda-forge documentation `_.

Unit Tests

==========

To run the suite of unit tests, you must have `numpy` installed and you must

have the `sample data files `_

downloaded to the current directory (or one specified by the `SPECTRAL_DATA`

environment variable). To run the unit tests, type

.. code::

    python -m spectral.tests.run

Dependencies

============

Using SPy interactively with its visualization capabilities requires `IPython` and

several other packages (depending on the features used). See the

`web site `_ for details.