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Otsu threshold

Goal

Wrap the crop step as a Common Workflow Language CommandLineTool and exectute it with a CWL runner.

Lab

This step has a dedicated lab at practice-labs/3-CWL-CommandLineTools/otsu.ipynb.

CWL CommandLineTool wrapping the step

The CWL document below shows the crop step wrapped as a CWL CommandLineTool:

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cwlVersion: v1.2
$namespaces:
  s: https://schema.org/
# Training-example authors and creation date mirror codemeta.json.
s:name: Otsu threshold
s:description: Detect water bodies by applying the Otsu threshold to a water index raster.
s:dateCreated: '2022-09-01'
s:license:
  s:name: Creative Commons Attribution-ShareAlike 4.0 International
  s:url: https://creativecommons.org/licenses/by-sa/4.0/
  s:identifier: CC-BY-SA-4.0
s:softwareHelp:
  s:name: Mastering Earth Observation Application Packaging with CWL
  s:url: https://eoap.github.io/mastering-app-package
s:publisher:
  s:name: EO Application Packaging
  s:identifier: https://github.com/eoap
s:author:
  - s:givenName: Jane
    s:familyName: Doe
    s:email: jane.doe@acme.earth
    s:affiliation:
      s:name: ACME
  - s:givenName: John
    s:familyName: Doe
    s:email: john.doe@acme.earth
    s:affiliation:
      s:name: ACME
s:softwareRequirements:
  - container runtime
  - cwl runner
s:softwareVersion: 2.0.2

class: CommandLineTool
id: otsu
requirements:
  InlineJavascriptRequirement: {}
  EnvVarRequirement:
    envDef:
      PATH: /app/venv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
  ResourceRequirement:
    coresMax: 1
    ramMin: 1024
    ramMax: 1024
  NetworkAccess:
    networkAccess: false
  DockerRequirement:
    dockerPull: localhost/otsu:latest
baseCommand: otsu
arguments: []
inputs:
  raster:
    type: File
    inputBinding:
      position: 1
      prefix: --raster
    label: Water index raster
    doc: Normalized difference water index raster to threshold.
outputs:
  binary_mask_item:
    outputBinding:
      glob: '*.tif'
    type: File
    label: Water body mask
    doc: Binary raster mask identifying detected water bodies.

Steps

Run the CWL document using the cwltool CWL runner to execute the otsu step with:

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export WORKSPACE=/workspace/mastering-app-package
export RUNTIME=${WORKSPACE}/runs
mkdir -p ${RUNTIME}
cd ${RUNTIME}

cwltool \
    --podman \
    --outdir ${WORKSPACE}/runs \
    ${WORKSPACE}/cwl-cli/otsu.cwl \
    --raster \
    ${WORKSPACE}/runs/norm_diff.tif

sh -x ${WORKSPACE}/scripts/cwl-cli-otsu.sh

Expected outcome

The folder /workspace/mastering-app-package/runs contains: 

(base) jovyan@coder-mrossi:~/runs$ tree .
.
├── crop_green.tif
├── crop_nir.tif
├── norm_diff.tif
└── otsu.tif

0 directories, 4 files