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An open source ML pipeline for overhead imagery by CosmiQ Works

PyPI python version PyPI build docs license

This is a beta version of Solaris which may continue to develop. Please report any bugs through issues!

This repository provides the source code for the CosmiQ Works solaris project, which provides software tools for:

  • Tiling large-format overhead images and vector labels
  • Converting between geospatial raster and vector formats and machine learning-compatible formats
  • Performing semantic and instance segmentation, object detection, and related tasks using deep learning models designed specifically for overhead image analysis
  • Evaluating performance of deep learning model predictions


The full documentation for solaris can be found at, and includes:

  • A summary of solaris
  • Installation instructions
  • API Documentation
  • Tutorials for common uses

The documentation is still being improved, so if a tutorial you need isn't there yet, check back soon or post an issue!

Installation Instructions

coming soon: One-command installation from conda-forge.

We recommend creating a conda environment with the dependencies defined in environment.yml before installing solaris. After cloning the repository:

cd solaris

If you're installing on a system with GPU access:

conda env create -n solaris -f environment-gpu.yml


conda env create -n solaris -f environment.yml

Finally, regardless of your installation environment:

conda activate solaris
pip install .


The package also exists on PyPI, but note that some of the dependencies, specifically rtree and gdal, are challenging to install without anaconda. We therefore recommend installing at least those dependencies using conda before installing from PyPI.

conda install -c conda-forge rtree gdal=2.4.1
pip install solaris

If you don't want to use conda, you can install libspatialindex, then pip install rtree. Installing GDAL without conda can be very difficult and approaches vary dramatically depending upon the build environment and version, but the rasterio install documentation provides OS-specific install instructions. Simply follow their install instructions, replacing pip install rasterio with pip install solaris at the end.


All dependencies can be found in the requirements file ./requirements.txt or environment.yml