How to run the postprocessing pipeline

Follow along this step-by-step guide to run the postprocessing pipeline with the command-line interface (CLI).

In this example, we will postprocess the resulting geodataframe of the segmentation pipeline, as described in the previous how-to guide.

Step 1: Create a configuration file

Create a configuration file (.yaml file) named config.yaml.

In the next steps, we will add the configuration of each component of the pipeline to this file.

---

Step 2: Configure the path to the geodataframe

config.yaml

gdf: path/to/your/output.gpkg

---

Step 3: Configure the geodata postprocessor

To postprocess the geodata, we will use the CompositePostprocessor with the following configuration:

config.yaml

geodata_postprocessor:
  name: CompositePostprocessor
  config:
    geodata_postprocessors_configs:
      - name: FillPostprocessor
        config:
          max_area: 2
      - name: SievePostprocessor
        config:
          min_area: 2
      - name: SimplifyPostprocessor
        config:
          tolerance: 0.2
      - name: FieldNamePostprocessor
        config:
          mapping:
            class: type
      - name: ValuePostprocessor
        config:
          mapping:
            1: buildings
            2: impervious surfaces
          field_name: type

This configuration will postprocess the geodataframe by:

• Filling holes in the polygons with an area of up to 2 square meters
• Sieving the polygons with an area of less than 2 square meters
• Simplifying the polygons with a tolerance of 0.2 meters
• Renaming the field class to type
• Mapping the values 1 and 2 to buildings and impervious surfaces as stated in the mapping of the values of the model

Note that there are alternative ways to postprocess the geodata. You can choose from a collection of geodata postprocessors and compose them as needed.

Have a look at the API reference for more details on the configuration options.

---

Step 4: Configure the output path to the postprocessed geodataframe

config.yaml

path: path/to/your/postprocessed_output.gpkg

---

Step 5: Run the postprocessing pipeline

The final configuration file should look like this:

config.yaml

gdf: path/to/your/output.gpkg

geodata_postprocessor:
  name: CompositePostprocessor
  config:
    geodata_postprocessors_configs:
      - name: FillPostprocessor
        config:
          max_area: 2
      - name: SievePostprocessor
        config:
          min_area: 2
      - name: SimplifyPostprocessor
        config:
          tolerance: 0.2
      - name: FieldNamePostprocessor
        config:
          mapping:
            class: type
      - name: ValuePostprocessor
        config:
          mapping:
            1: buildings
            2: impervious surfaces
          field_name: type

path: path/to/your/postprocessed_output.gpkg

To run the postprocessing pipeline, run the following command:

pipDocker

aviary postprocessing-pipeline path/to/config.yaml

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

After successfully running the postprocessing pipeline, you will find the postprocessed geodataframe of the impervious surfaces at the specified output path as a geopackage named postprocessed_output.gpkg.