Segmentation pipeline

The segmentation pipeline is a pre-built pipeline designed to run a segmentation model on your data. It consists of the following components:

• A DataFetcher to fetch data from a source
• A ProcessArea to specify the area of interest
• A DataPreprocessor to preprocess the fetched data
• A SegmentationModel to do the inference on the preprocessed data
• An SegmentationExporter to export the predictions dynamically as geospatial data

These components are set up in a configuration file (.yaml file) that is passed to the pipeline.
The configuration file must have the following structure:

config.yaml

data_fetcher:
  name:
  config:

process_area:

data_preprocessor:
  name:
  config:

model:
  name:
  config:

exporter:
  name:
  config:

batch_size: 1
num_workers: 4

The name field must be the name of the class that you want to use for the component.
The config field must contain its corresponding configuration.
Note that each class has its own configuration, which can be found in the API reference.

To run the segmentation pipeline, run the following command:

pip and uvDocker

aviary segmentation-pipeline path/to/config.yaml

docker run --rm \
  -v path/to/config.yaml:/aviary/config.yaml \
  aviary segmentation-pipeline /aviary/config.yaml

Note that you need to bind mount all directories and files that are referenced in the configuration file, so they're accessible inside the Docker container.
Add the following options to the command for each directory:

-v path/to/directory:/aviary/directory

and for each file:

-v path/to/file:/aviary/file

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Next steps

Have a look at the how-to guide on how to run the segmentation pipeline with an example configuration file.