This package is under active development. Check back soon for updates!
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
We recommend creating a
conda environment with the dependencies defined in environment.yml before installing
solaris. After cloning the repository:
cd solaris conda env create -n solaris -f environment.yml 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 dependency using
conda before installing from PyPI.
conda install -c conda-forge rtree gdal=2.4.1
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 online resources may help with specific use cases.
Once you have that dependency set up, install as usual using
pip install solaris