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geospaitial-lab-aviary

Python Framework for tile-based processing of geospatial data

https://github.com/geospaitial-lab/aviary

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
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    Academic publication links
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  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.2%) to scientific vocabulary

Keywords

aerial-imagery artificial-intelligence computer-vision deep-learning machine-learning orthophotos python remote-sensing
Last synced: 7 months ago · JSON representation ·

Repository

Python Framework for tile-based processing of geospatial data

Basic Info
Statistics
  • Stars: 9
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 12
Topics
aerial-imagery artificial-intelligence computer-vision deep-learning machine-learning orthophotos python remote-sensing
Created almost 2 years ago · Last pushed 7 months ago
Metadata Files
Readme License Code of conduct Citation Codeowners

README.md

aviary
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aviary provides composable components for tile-based processing of geospatial data. This enables you to easily run models on large datasets, export the predictions in a georeferenced file format and postprocess them for further downstream tasks.
Besides the pipelines, aviary also provides task-specific models for remote sensing applications.

aviary is designed upon the following concepts:

  • High-level Python API
    Abstract components for building pipelines without boilerplate code

  • Command-line interface (CLI)
    Run the pre-built pipelines easily without writing any code

  • Customizable pipelines
    Compose your own pipelines with the provided components

  • Extensible components
    Add your own components to the pipeline

  • Support for large datasets
    Tile-based processing for large datasets (local, remote or web services)

  • Support for geospatial data
    Export predictions as geodata, ready for downstream tasks

  • Task-agnostic
    Process geospatial data with a range of machine learning tasks

  • ML-framework agnostic
    Use your favorite machine learning framework

Installation

You can choose between two installation methods, whether you need access to the Python API or the command-line interface (CLI) only. If you just want to use the pre-built pipelines with the command-line interface, you can use the Docker image.

Installation with pip

⚠️ Note: aviary is currently released as a pre-release version. To install the latest version, you need to add the --pre flag.

pip install geospaitial-lab-aviary

Note that aviary requires Python 3.10 or later.

Have a look at the installation guide for further information.

Installation with uv

uv pip install geospaitial-lab-aviary

Note that aviary requires Python 3.10 or later.

Have a look at the installation guide for further information.

Installation with Docker

docker pull ghcr.io/geospaitial-lab/aviary

Have a look at the installation guide for further information.

Next steps

Have a look at the how-to guides to get started.

Documentation

The full documentation is available at geospaitial-lab.github.io/aviary.

About

aviary is developed by the geospaitial lab at the Westfälische Hochschule - Westphalian University of Applied Sciences in Gelsenkirchen, Germany.

Owner

  • Name: geospaitial-lab: Forschungsteam KI und kommunale Geoinformationen
  • Login: geospaitial-lab
  • Kind: organization
  • Email: christian.kuhlmann@w-hs.de

Künstliche Intelligenz und kommunale Geoinformationen an der Westfälischen Hochschule

Citation (CITATION.cff) 

cff-version: 1.2.0
title: aviary
type: software
authors:
  - given-names: Marius
    family-names: Maryniak
    email: marius.maryniak@w-hs.de
  - name: geospaitial lab
repository-code: 'https://www.github.com/geospaitial-lab/aviary'
abstract: >-
  Composable inference and postprocessing pipeline for
  remote sensing data
keywords:
  - python
  - artificial-intelligence
  - deep-learning
  - machine-learning
  - computer-vision
  - remote-sensing
  - aerial-imagery
  - orthophotos
license: GPL-3.0
version: 1.0.0b3
date-released: 2025-05-09

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 12
  • Total pull requests: 517
  • Average time to close issues: 2 days
  • Average time to close pull requests: 1 day
  • Total issue authors: 5
  • Total pull request authors: 5
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.49
  • Merged pull requests: 416
  • Bot issues: 5
  • Bot pull requests: 270
Past Year
  • Issues: 10
  • Pull requests: 351
  • Average time to close issues: 2 days
  • Average time to close pull requests: 1 day
  • Issue authors: 5
  • Pull request authors: 5
  • Average comments per issue: 0.4
  • Average comments per pull request: 0.42
  • Merged pull requests: 265
  • Bot issues: 5
  • Bot pull requests: 215
View more stats
Top Authors
Issue Authors
  • mrsmrynk (5)
  • dependabot[bot] (4)
  • sfanghaenel (1)
  • MKKraemer (1)
  • github-actions[bot] (1)
Pull Request Authors
  • dependabot[bot] (262)
  • mrsmrynk (245)
  • github-actions[bot] (8)
  • AlexRoss-WHS (1)
  • stefan-kuepper (1)
Top Labels
Issue Labels
build (4) docs (2) ci (1) feat (1) breaking (1) refactor (1)
Pull Request Labels
build (262) docs (53) refactor (29) feat (24) ci (23) ignore for release (21) breaking (19) dependencies (19) python (19) cli (16) chore (16) cd (15) enhancement (12) test (6) fix (6) feature (3) style (3)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 120 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 19
  • Total maintainers: 1
pypi.org: geospaitial-lab-aviary

Composable inference and postprocessing pipeline for remote sensing data

  • Versions: 19
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 120 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.5%
Dependent repos count: 60.4%
Maintainers (1)
mrsmrynk
Last synced: 7 months ago

Dependencies

.github/workflows/ci.yaml actions
  • actions/checkout v4 composite
  • actions/setup-python v4 composite
  • codecov/codecov-action v4 composite
dev/requirements.txt pypi
  • geopandas ==0.14.3 development
  • numpy ==1.26.4 development
  • pyproj ==3.6.1 development
  • pytest ==8.1.1 development
  • pytest-cov ==5.0.0 development
  • ruff ==0.3.7 development
  • shapely ==2.0.3 development
pyproject.toml pypi
requirements.txt pypi
  • geopandas ==0.14.3
  • numpy ==1.26.4
  • pyproj ==3.6.1
  • shapely ==2.0.3