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🚀 Quickstart

Welcome to the Quickstart Guide for Meteors! This guide will walk you through the basic steps to get started with using Meteors for explaining your hyperspectral and multispectral image models.

📋 Prerequisites

Before you begin, make sure you have the following installed:

  • Python >= 3.9
  • PyTorch >= 1.10
  • Captum >= 0.7.0

📥 Installation

To install Meteors, simply run the following command:

pip install meteors

For conda users, we will provide a conda installation method in the near future. We promise!🤞

🌟 Basic Hyperspectral or Multispectral Data Object

Meteors provide an easy-to-use object for handling hyperspectral and multispectral images. The HSI object is a simple way to process and manipulate your data.

from meteors import HSI

Remember, when providing data to the model, make sure it is in the final format that the model expects, without the batch dimension. The HSI object will handle the rest. We also recommend providing the image data channel orientation, height, width, and the number of channels in the format (CHW). For example:

  • Number of channels: C
  • Height: H
  • Width: W

🔍 Explanation Methods

Meteors provides several explanation methods for hyperspectral and multispectral images, including:

To use a specific explanation method in tutorials we provide for each method, example code.

🎨 Visualization Options

Meteors offers various visualization options to help you understand and interpret the explanations in package meteors.visualize.

from meteors.visualize import visualize_spectral_attributes, visualize_spatial_attributes

📚 Tutorials

We have several tutorials to help get you off the ground with Meteors. The tutorials are Jupyter notebooks and cover the basics along with demonstrating usage of Meteors .

View the tutorials page here.

📖 API Reference

For an in-depth reference of the various Meteors internals, see our API Reference.

🙌 Contributing

We welcome contributions to Meteors! Please refer to our Contributing Guide for more information on how to get involved.