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AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.

License: Apache License 2.0

Python 100.00%

aitlas's Introduction

Project Status: Active – The project has reached a stable, usable state and is being actively developed. License: Apache License 2.0 Python 3.7+

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The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite imagery as well as repository of AI-ready Earth Observation (EO) datasets. It can be easily applied for a variety of Earth Observation tasks, such as land use and cover classification, crop type prediction, localization of specific objects (semantic segmentation), etc. The main goal of AiTLAS is to facilitate better usability and adoption of novel AI methods (and models) by EO experts, while offering easy access and standardized format of EO datasets to AI experts which allows benchmarking of various existing and novel AI methods tailored for EO data.

Getting started

AiTLAS Introduction https://youtu.be/-3Son1NhdDg

AiTLAS Software Architecture: https://youtu.be/cLfEZFQQiXc

AiTLAS in a nutshell: https://www.youtube.com/watch?v=lhDjiZg7RwU

AiTLAS examples:

Installation

The best way to install aitlas, is if you create a virtual environment and install the requirements with pip. Here are the steps:

  • Go to the folder where you cloned the repo.
  • Create a virtual environment
conda create -n aitlas python=3.8
  • Use the virtual environment
conda activate aitlas
pip install GDAL-3.4.1-cp38-cp38-win_amd64.whl 
pip install Fiona-1.8.20-cp38-cp38-win_amd64.whl
pip install rasterio-1.2.10-cp38-cp38-win_amd64.whl
  • Install the requirements
pip install -r requirements.txt

And, that's it, you can start using aitlas!

python -m aitlas.run configs/example_config.json

If you want to use aitlas as a package run

pip install .

in the folder where you cloned the repo.


Note: You will have to download dataset from their respective source. You can find a link for each dataset in the respective dataset class in aitlas/datasets/ or use the AiTLAS Semantic Data Catalog


AiTLAS Semantic Data Catalog of Earth Observation (EO) datasets (beta)

A novel semantic data catalog of numerous EO datasets, pertaining to various different EO and ML tasks. The catalog, that includes properties of different datasets and provides further details for their use, is available here

Citation

For attribution in academic contexts, please cite this work as

@article{dimitrovski2022aitlas,
      title={AiTLAS: Artificial Intelligence Toolbox for Earth Observation}, 
      author={Ivica Dimitrovski and Ivan Kitanovski and Panče Panov and Nikola Simidjievski and Dragi Kocev},
      year={2022},
      journal={arXiv preprint arXiv:2201.08789},
}

aitlas's People

Contributors

ivicadimitrovski avatar ivankitanovski avatar elenamer avatar simidjievskin avatar popovstefan avatar

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