A collection of functions to extract pixels and metadata using geojson and georeferenced imagery.
In a virtualenv or conda virtual environment:
pip install dataextractors
A conda environment is preferred because the installation of gdal is straightforward:
conda create -n myenv -c conda-forge gdal
source activate myenv
Clone the repo:
git clone https://github.com/digitalglobe/dataextractors
cd dataextractors
Install the requirements:
pip install -r requirements.txt
Please follow this python style guide. 80-90 columns is fine.
To create a new version:
bumpversion ( major | minor | patch )
git push --tags
Then upload to pypi.