Basic classification.
Project description
(Disclaimer: work in progress…)
A collection of Machine Learning (ML) Tools for object detection and classification on DG imagery.
mltools is MIT licenced.
Installation is easy:
pip install mltools
ML Algorithms (MLAs) (either supervised or unsupervised) are implemented using standard ML libraries such as scikit-learn and tensorflow. MLAs also utilize open source libraries which can read from and write to georeferenced satellite images such as gdal.
The purpose of this repository is to enable fast prototyping of object detection and classification solutions employing one of the existing algorithms or by constructing new ones based on the provided modular tools.
The input of a MLA is one or more of the following:
one or more images;
a job.json specifying the parameters of the MLA;
a train.geojson containing a collection of features, each feature consisting of (at least) a geometry, a class and a unique image identifier;
a target.geojson containing a collection of geometries, each feature consisting of (at least) a geometry, a class and a unique image identifier;
The output of a MLA is one or more of the following:
one or more processed images
an output.geojson containing a collection of features, each feature consisting of (at least) a geometry, a class and a unique image identifier;
Requirements
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Comments
mltools is developed as part of an effort to standardize MLA design and implementation.
Here is a slide with some ideas:
https://docs.google.com/drawings/d/1tKSgFMp0lLd7Abne8CdOhb1PbdJfgCz5x9XkLwDeET0/edit?usp=sharing
The vision is to employ MLA as part of a Crowd+Machine system along the lines of this document:
https://docs.google.com/document/d/1hf82I_jDNGc0NdopXxW9RkbQjLOOGkV4lU5kdM5tqlA/edit?usp=sharing
Imagery in the format required by a MLA (e.g., pansharpened, multi-spectral or orthorectified) can be obtained with the gbdxtools package (https://github.com/kostasthebarbarian/gbdxtools). You need GBDX credentials to use gbdxtools.