geode-ml 1.0.0

Classes and methods to help with the creation of geospatial training datasets and deep-learning models.

How to install geode-ml

The geode-ml package depends on GDAL for most of its functionality. It is easiest to install GDAL using the conda package manager:

conda create -n "geode_env" python>=3.7
conda activate geode_env
conda install gdal

After activating an environment which has GDAL, use pip to install geode-ml:

pip install geode-ml

The geode.datasets module

The datasets module currently contains the class:

1. SemanticSegmentation
   • creates and processes pairs of imagery and label rasters for scenes

The geode.generators module

The generators module currently contains the class:

1. TrainingGenerator
   • supplies batches of imagery/label pairs for model training
   • from_tiles() method reads from generated tile files
   • from_source() method (in development) reads from the larger source rasters

The geode.losses module

The losses module contains custom loss functions for model training; these may be removed in the future when implemented in Tensorflow.

The geode.metrics module

The metrics module contains useful metrics for testing model performance.

The geode.models module

The models module contains the classes:

1. Segmentation
   • subset of the tensorflow.keras.Model class to be used for image segmentation
2. Unet
   • subset of the Segmentation class which instantiates a Unet architecture.

The geode.utilities module

The utilities module currently contains functions to process, single examples of geospatial data. The datasets module imports these functions to apply to batches of data; however, this module exists so they they can be used by themselves.