Giter Club home page Giter Club logo

Sublime's custom image

Spectral imaging analysis for Python (SiaPy) is a tool for efficient processing of spectral images

Test Coverage Package version DOI Supported Python versions


Source Code: https://github.com/siapy/siapy-lib

Bug Report / Feature Request: https://github.com/siapy/siapy-lib/issues/new/choose

Documentation: https://siapy.github.io/siapy-lib/


Note: The library is currently under development!

💡 Installation

To install the siapy library, use the following command:

pip install siapy

For detailed information and additional options, please refer to the guide.

🔍 Contribution guidelines

We always welcome small improvements or fixes. If you’re considering making more significant contributions to the source code, please contact us via email.

Contributing to SiaPy isn’t limited to coding. You can also:

  • Help us manage and resolve issues, both new and existing.
  • Create tutorials, presentations, and other educational resources.
  • Propose new features.

Not sure where to start or how your skills might fit in? Don’t hesitate to reach out! You can contact us via email, or connect with us directly on GitHub by opening a new issue or commenting on an existing one.

If you’re new to open-source contributions, check out our guide for helpful tips on getting started.

🕐 Issues and new features

Encountered a problem with the library? Please report it by creating an issue on GitHub.

Interested in fixing an issue or enhancing the library’s functionality? Fork the repository, make your changes, and submit a pull request on GitHub.

Have a question? First, ensure that the setup process was completed successfully and resolve any related issues. If you’ve pulled in newer code, you might need to delete and recreate your SiaPy environment to ensure all the necessary packages are correctly installed.

🤝 License

This project is licensed under the MIT License. See LICENSE for more details.

siapy's Projects

siapy-lib icon siapy-lib

🖼️ A tool for efficient processing of spectral images with Python.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.