Spectral Imaging Made Easy: A Powerful Python Library

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

Judoscale - Save 47% on cloud hosting with autoscaling that just works
Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
judoscale.com
featured
CodeRabbit: AI Code Reviews for Developers
Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
coderabbit.ai
featured
  1. siapy-lib

    🖼️ A Python package for efficient processing of spectral images

  2. Judoscale

    Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.

    Judoscale logo
  3. isofit

    Imaging Spectrometer Optimal FITting (ISOFIT) contains a set of routines and utilities for fitting surface, atmosphere and instrument models to imaging spectrometer data.

    Related: A python package for atmospheric correction of imaging spectroscopy radiance data: https://github.com/isofit/isofit

  4. matlabHyperspectralToolbox

    MATLAB Hyperspectral Toolbox

  5. hyperspy

    Multidimensional data analysis

    Interesting - I'm curious whether you feel that Xarray covers these use cases already?

    https://xarray.dev/

    Especially as I've said before that Hyperspy shares so many features in common with Xarray that Hyperspy should just use Xarray under the hood.

    https://github.com/hyperspy/hyperspy/discussions/3405

  6. xarray

    N-D labeled arrays and datasets in Python

    Interesting - I'm curious whether you feel that Xarray covers these use cases already?

    https://xarray.dev/

    Especially as I've said before that Hyperspy shares so many features in common with Xarray that Hyperspy should just use Xarray under the hood.

    https://github.com/hyperspy/hyperspy/discussions/3405

  7. CodeRabbit

    CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.

    CodeRabbit logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts

  • Show HN: NumPy+Jax Except with Named Axes

    2 projects | news.ycombinator.com | 25 Feb 2025
  • Xarray: N-D labeled arrays and datasets in Python

    1 project | news.ycombinator.com | 20 Oct 2024
  • Introducing Flama for Robust Machine Learning APIs

    11 projects | dev.to | 18 Dec 2023
  • Potential of the Julia programming language for high energy physics computing

    10 projects | news.ycombinator.com | 4 Dec 2023
  • Building an efficient sparse keyword index in Python

    5 projects | dev.to | 17 Aug 2023