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chore(release): v0.4.0
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examples/pipelines/dextr.yaml

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name: DEXTR
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triggers:
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# Adds a button to the annotator.
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annotatorButton:
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name: 'DEXTR'
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icon: brain
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name: DEXTR
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# Annotator will prompt the user for 4 points before triggering the pipeline
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flow: 4-points
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jobs:
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predict:
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# Properties about the trigger event can be accessed at 'event' property
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steps:
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- action: datatorch/download-file@v1
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cache: true
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- name: Download File
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action: datatorch/download-file@v1
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inputs:
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fileId: ${{ input.fileId }}
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- action: datatorch/download-file@v1
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# Get the file id for the event that triggered this.
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fileId: ${{ event.fileId }}
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- name: Predict Segmentation
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action: datatorch/dextr@latest
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inputs:
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fileId: ${{ input.fileId }}
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# Download file path from the previous action.
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imagePath: ${{ variable.path }}
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# Get the 4 points the user clicked
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points: ${{ event.flowData.points }}
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# Annotation created by the four points. We will insert the
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# segmentation into this annotation
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annotationId: ${{ event.annotationId }}

setup.py

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setup(
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name="datatorch",
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version="0.3.0",
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version="0.4.0",
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description="A CLI and library for interacting with DataTorch",
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author="DataTorch",
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author_email="[email protected]",

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