Metadata-Version: 2.4
Name: orthoseg
Version: 0.7.0
Summary: Package to make it easier to segment orthophotos.
Home-page: https://github.com/orthoseg/orthoseg
Author: Pieter Roggemans
Author-email: pieter.roggemans@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE.MD
Requires-Dist: gdal
Requires-Dist: gdown
Requires-Dist: geofileops>=0.10
Requires-Dist: geopandas>=1.0
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: owslib
Requires-Dist: pillow
Requires-Dist: pycron
Requires-Dist: pygeoops>=0.4
Requires-Dist: rasterio
Requires-Dist: segmentation-models<1.1,>=1.0
Requires-Dist: shapely>=2
Requires-Dist: simplification
Requires-Dist: tensorflow>=2.8
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# 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)

A python package that makes it (relatively) easy to segment orthophotos. Any type of
georeferenced images should work, e.g. satellite, aerial or drone images, (historical)
maps, hillshades,...

No programming is needed, everything is managed via configuration files.

The typical steps:
1. create a training dataset for a topic of your choice, e.g. in QGIS
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, simplify,...

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)

This is an example of how the output of a tree detection on aerial images can look:

![Result of a tree detection on aerial images](docs/_static/images/trees.jpg)
