This Charter states the project’s mission, scope, principles and contribution guidelines to help our community understand how it all fits together.
- satproc: 🛰️ Python library and CLI tools for processing geospatial imagery for ML
- unetseg: U-Net semantic segmentation for satellite imagery
- labfunctions: A workflow platform which allows you to run parameterized notebooks programmatically
- platform: Dymaxion Labs MLaaS platform repository, containing the web UI application and backend API
The Dymaxion Labs Toolkit is a collection of open source libraries that leverage AI and Computer Vision to understand the physical world, by analyzing large scale geospatial data. The Toolkit removes the barriers to geospatial deep learning, providing easy to use tools and a standardized workflow.
The Dymaxion Labs Toolkit Project (the “Project”) develops software under an open source license, supporting the geospatial deep learning lifecycle with tools for data pre-processing, neural network training and prediction, and post-processing to turn model results into standard geospatial formats. Currently the toolkit does not cover data acquisition (i.e. downloading satellite imagery for a given area of interest).
When we talk about our culture, we talk about the way we interact with each other, every single day, at the office or remotely. We have two non-negotiable values: cooperation and execution. Cooperation means to be always ready to help your teammates; Execution means to have always-on the ability to deliver to our stakeholders.
We love transparency and hard fact evidence, and we are committed to the United Nations' Sustainable Development Goals. As active open source developers, we produce source code, blueprints, and documentation that are freely available to the public.
Participation in the Project through interaction with our code repositories is open to anyone so long as they abide by the terms of this Charter. Bug reports and pull requests are welcome on GitHub at the issues page. This Project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.
Our governance model relies on a formal committer group that reviews and accepts pull requests, and can grant committing privileges to new contributors. Current committer group members are:
All inbound code contributions to the Project must be made under the Apache License, Version 2.0 All outbound code will be made available under the Project License.
Documentation will be received and made available by the Project under the Creative Commons Attribution 4.0 International License.