Metadata-Version: 2.1
Name: geospaitial-lab-aviary
Version: 0.3.1
Summary: Composable inference and postprocessing pipeline for remote sensing data
Author-email: Marius Maryniak <marius.maryniak@w-hs.de>
Maintainer-email: Marius Maryniak <marius.maryniak@w-hs.de>, Alexander Roß <alexander.ross@w-hs.de>
License: GPL-3.0
Project-URL: Homepage, https://www.github.com/geospaitial-lab/aviary
Project-URL: Documentation, https://geospaitial-lab.github.io/aviary
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: GIS
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: geopandas==1.0.1
Requires-Dist: huggingface_hub==0.25.1
Requires-Dist: numpy==1.26.4
Requires-Dist: onnxruntime==1.19.2
Requires-Dist: pydantic==2.9.2
Requires-Dist: pyyaml==6.0.2
Requires-Dist: rasterio==1.4.1
Requires-Dist: requests==2.32.3
Requires-Dist: rich==13.9.2
Requires-Dist: shapely==2.0.6
Requires-Dist: simplification==0.7.12
Requires-Dist: topojson==1.9
Requires-Dist: typer==0.12.5

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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.<br />
Besides the pipelines, aviary also provides task-specific models for remote sensing applications.

aviary is designed upon the following concepts:

- **High-level Python API**<br />
  Abstract components for building pipelines without boilerplate code

- **Command-line interface (CLI)**<br />
  Run the pre-built pipelines easily without writing any code

- **Customizable pipelines**<br />
  Compose your own pipelines with the provided components

- **Extensible components**<br />
  Add your own components to the pipeline

- **Support for large datasets**<br />
  Tile-based processing for large datasets (local, remote or web services)

- **Support for geospatial data**<br />
  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.

### Installation with pip

```
pip install geospaitial-lab-aviary
```

Note that aviary requires Python 3.10 or later.

Have a look at the [installation guide](https://geospaitial-lab.github.io/aviary/how_to_guides/installation/how_to_install_aviary_with_pip)
for further information.

### Installation with Docker

```
docker pull ghcr.io/geospaitial-lab/aviary
```

Have a look at the [installation guide](https://geospaitial-lab.github.io/aviary/how_to_guides/installation/how_to_install_aviary_with_docker)
for further information.

## Next steps

Have a look at the [how-to guides](https://geospaitial-lab.github.io/aviary/how_to_guides)
to get started.

## Documentation

The full documentation is available at [geospaitial-lab.github.io/aviary](https://geospaitial-lab.github.io/aviary).

## About

aviary is developed by the [geospaitial lab](https://www.github.com/geospaitial-lab)
at the [Westfälische Hochschule - Westphalian University of Applied Sciences](https://www.w-hs.de)
in Gelsenkirchen, Germany.
