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aviary provides composable components for building inference and postprocessing pipelines for remote sensing 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

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.

pip install geospaitial-lab-aviary

Note that aviary requires Python 3.10 or later.

Have a look at the installation guide for further information.

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.

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.

About

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