https://github.com/orthoseg/orthoseg

OrthoSeg makes it easy to train neural networks to segment orthophotos.
https://github.com/orthoseg/orthoseg

aerial-imagery convolutional-neural-networks deep-learning drone image-classification image-segmentation keras-tensorflow machine-learning neural-network python remote-sensing satellite-imagery segment-orthophotos segmentation tensorflow wms

Last synced: 3 months ago
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OrthoSeg makes it easy to train neural networks to segment orthophotos.

• Host: GitHub
• URL: https://github.com/orthoseg/orthoseg
• Owner: orthoseg
• License: gpl-3.0
• Created: 2018-09-05T11:25:22.000Z (almost 7 years ago)
• Default Branch: main
• Last Pushed: 2025-03-30T11:22:34.000Z (3 months ago)
• Last Synced: 2025-04-03T02:09:17.812Z (3 months ago)
• Topics: aerial-imagery, convolutional-neural-networks, deep-learning, drone, image-classification, image-segmentation, keras-tensorflow, machine-learning, neural-network, python, remote-sensing, satellite-imagery, segment-orthophotos, segmentation, tensorflow, wms
• Language: Python
• Homepage: https://orthoseg.readthedocs.io/
• Size: 4.4 MB
• Stars: 32
• Watchers: 3
• Forks: 5
• Open Issues: 20
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE.MD
  • Citation: CITATION.cff

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README

        
# Orthophoto segmentation

[![Actions Status](https://github.com/orthoseg/orthoseg/actions/workflows/tests.yml/badge.svg?branch=main)](https://github.com/orthoseg/orthoseg/actions?query=workflow%3ATests)

[![Coverage Status](https://codecov.io/gh/orthoseg/orthoseg/branch/main/graph/badge.svg)](https://codecov.io/gh/orthoseg/orthoseg)

[![PyPI version](https://img.shields.io/pypi/v/orthoseg.svg)](https://pypi.org/project/orthoseg)

[![DOI](https://zenodo.org/badge/147507046.svg)](https://zenodo.org/doi/10.5281/zenodo.10340584)

This project provides a procedure and software to make it easy to:

1. create a training dataset for a topic of your choice

2. train a neural network to segment orthophotos

3. run the segmentation on a larger area + vectorize the result

4. apply some basic postprocessing like dissolve,...

Only open source software is needed, eg. QGIS and tensorflow.

Installation and usage instructions can be found in the [orthoseg docs](https://orthoseg.readthedocs.io)