Awesome GitHub RepositoriesGeospatial Machine Learning

MMSegmentation is an open-source semantic segmentation toolbox built on PyTorch that provides a modular, configurable framework for building, training, evaluating, and deploying segmentation models. At its core, it offers a config-driven pipeline that assembles training, evaluation, and inference workflows by parsing hierarchical configuration files, with a modular component registry that enables plug-and-play composition of neural network modules, optimizers, datasets, and metrics. The framework supports the full model lifecycle through a unified runner interface that controls training, testi

TorchGeo is a PyTorch library designed for deep learning on geospatial data, providing a framework for building and training neural networks for tasks such as semantic segmentation, object detection, and change detection. It serves as a comprehensive pipeline for remote sensing, featuring specialized dataset loaders and multispectral image preprocessing tools. The library is distinguished by a dedicated remote sensing model zoo and extensive support for transfer learning, allowing users to integrate pre-trained weights optimized for specific satellite sensors. It also includes support for sel

Segment Geospatial ist ein Python-Toolkit zur Isolierung geografischer Merkmale in Fernerkundungsbildern unter Verwendung des Segment Anything Model. Es fungiert als Fernerkundungs-Bildprozessor, der Kartenkacheln in georeferenzierte Formate konvertiert, um Segmentierungsmasken aus Satellitendaten zu generieren. Das System ermöglicht die Extraktion geografischer Objekte durch automatische Maskengenerierung oder manuelle Prompts, wie Textbeschreibungen, Bounding-Boxes und interaktive Marker. Es unterstützt die Segmentierung von Zeitreihenbildern, um Objekte über Sequenzen von Bildern an verschiedenen Daten hinweg zu verfolgen oder zu identifizieren, und bietet einen Geodaten-Masken-Visualisierer für das Rendern von Ergebnissen auf interaktiven Karten. Das Projekt deckt ein breites Spektrum an räumlichen Operationen ab, einschließlich Kartenkachel-Akquise, Raster-zu-Vektor-Konvertierung und Feature-Edge-Rekonstruktion zur Verfeinerung von Objektgrenzen. Es enthält zudem eine REST-API, die diese Segmentierungs- und Datenverarbeitungsfunktionen für Remote-Anwendungen bereitstellt. Exportfunktionen unterstützen georeferenzierte Rasterbilder und Standard-Vektorformate, einschließlich GeoJSON, Shapefile und GeoPackage.

SNIPER / AutoFocus is an efficient multi-scale object detection training / inference algorithm

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

Earth observation processing framework for machine learning in Python

Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

Python Package for Airborne RGB machine learning

Data Preparation for Satellite Machine Learning

CosmiQ Works Geospatial Machine Learning Analysis Toolkit

TorchSat is an open-source deep learning framework for satellite imagery analysis based on PyTorch.

You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery

The Satellite Imagery Multiscale Rapid Detection with Windowed Networks (SIMRDWN) codebase combines some of the leading object detection algorithms into a unified framework designed to detect objects both large and small in overhead imagery. This work seeks to extend the YOLT modification of…