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siapy

🥷 A Python package for efficient processing of spectral images

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

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (20.8%) to scientific vocabulary

Keywords

hyperspectral-images machine-learning multispectral-images python spectral-analysis spectral-data spectral-imaging
Last synced: 6 months ago · JSON representation ·

Repository

🥷 A Python package for efficient processing of spectral images

Basic Info
Statistics
  • Stars: 111
  • Watchers: 4
  • Forks: 6
  • Open Issues: 3
  • Releases: 47
Topics
hyperspectral-images machine-learning multispectral-images python spectral-analysis spectral-data spectral-imaging
Created almost 4 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog Contributing Funding License Code of conduct Citation Security

README.md

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/

📚 Overview

SiaPy is a versatile Python library designed for processing and analyzing spectral images. It is particularly useful for scientific and academic purposes, but it also serves well for quick prototyping.

Key Features

  • Image Processing: Easily read, display, and manipulate spectral image data.
  • Data Analysis: Perform in-depth analysis of spectral signatures using advanced analytical techniques.
  • Machine Learning Integration: Select image regions for training models and segment images using pre-trained models.
  • Camera Co-registration: Align multiple cameras and compute transformations across different camera spaces.
  • Radiometric Conversion: Convert radiance to reflectance using reference panels.

To make some of the functionality more easily accessible, a command line interface (CLI) is also provided. See siapy-cli. However, the full functionality can be exploited by using the library directly.

💡 Installation

To install the siapy library, use the following command:

bash pip install siapy

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

💻 Examples

``` python from pathlib import Path from siapy.entities import SpectralImageSet

data_dir = "~/data"

headerpaths = sorted(Path(datadir).rglob(".hdr")) imagepaths = sorted(Path(datadir).rglob(".img"))

imageset = SpectralImageSet.spyopen( headerpaths=headerpaths, imagepaths=image_paths, ) print(imageset) ```

For an overview of the key concepts and functionalities of the SiaPy library, please refer to the documentation. Additionally, explore the use cases that demonstrate the library's capabilities here.

🔍 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.

Owner

  • Name: siapy
  • Login: siapy
  • Kind: organization
  • Email: janez.lapajne@kis.si
  • Location: Slovenia

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: SiaPy
message: >-
    If you use this software, please cite it using the
    metadata from this file.
type: software
authors:
    - given-names: Janez
      family-names: Lapajne
      email: janez.lapajne@kis.si
      orcid: "https://orcid.org/0000-0003-2609-700X"
identifiers:
    - type: url
      value: "https://doi.org/10.3920/978-90-8686-947-3_54"
      description: Conference paper
    - type: url
      value: "https://zenodo.org/doi/10.5281/zenodo.7409193"
      description: Zenodo repository
repository-code: "https://github.com/siapy/siapy-lib"
abstract: >-
    A tool for efficient processing of spectral images with
    Python.
keywords:
    - siapy
    - spectral imaging analysis
    - python
license: MIT

GitHub Events

Total
  • Release event: 14
  • Watch event: 85
  • Delete event: 3
  • Issue comment event: 17
  • Push event: 268
  • Pull request event: 110
  • Fork event: 6
  • Create event: 21
Last Year
  • Release event: 14
  • Watch event: 85
  • Delete event: 3
  • Issue comment event: 17
  • Push event: 268
  • Pull request event: 110
  • Fork event: 6
  • Create event: 21

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 76
  • Total Committers: 1
  • Avg Commits per committer: 76.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 4
  • Committers: 1
  • Avg Commits per committer: 4.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Janez Lapajne l****z@g****m 76

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 0
  • Total pull requests: 251
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 day
  • Total issue authors: 0
  • Total pull request authors: 4
  • Average comments per issue: 0
  • Average comments per pull request: 0.23
  • Merged pull requests: 211
  • Bot issues: 0
  • Bot pull requests: 38
Past Year
  • Issues: 0
  • Pull requests: 124
  • Average time to close issues: N/A
  • Average time to close pull requests: 2 days
  • Issue authors: 0
  • Pull request authors: 3
  • Average comments per issue: 0
  • Average comments per pull request: 0.18
  • Merged pull requests: 115
  • Bot issues: 0
  • Bot pull requests: 21
View more stats
Top Authors
Issue Authors
  • janezlapajne (4)
  • Anana-S (1)
  • pre-commit-ci[bot] (1)
Pull Request Authors
  • janezlapajne (353)
  • pre-commit-ci[bot] (39)
  • dependabot[bot] (25)
  • imgbot[bot] (3)
Top Labels
Issue Labels
stale (4) autorelease: pending (1) bug (1) needs triage (1)
Pull Request Labels
needs triage (195) autorelease: pending (64) autorelease: tagged (46) dependencies (25) python (19)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 195 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 43
  • Total maintainers: 1
pypi.org: siapy

A python library for efficient processing of spectral images.

  • Versions: 43
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 195 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.5%
Dependent repos count: 60.3%
Maintainers (1)
janezlapajne
Last synced: 6 months ago

Dependencies

Dockerfile docker
  • ubuntu $UBUNTU_VERSION build
docker-compose.yml docker
  • siapy-api latest
requirements.txt pypi
  • dill ==0.3.5.1
  • hydra_colorlog ==1.2.0
  • hydra_core ==1.2.0
  • inpoly ==0.1.2
  • matplotlib ==3.5.2
  • numba ==0.55.1
  • opencv_python ==4.5.3.56
  • pandas ==1.4.3
  • rich ==12.5.1
  • scikit_image ==0.19.3
  • scikit_learn ==1.1.2
  • spectral ==0.22.4