Overview

A Label is constructed from a Data object and its associated Annotations.

1657

Guides/export examples per asset type

Asset typeGuide/Export sampleColab notebook
ImageExport image annotationsLabel export - Images
VideoExport video annotationsLabel export - Video
TextExport text annotationsLabel export - Text
Geospatial (tiled imagery)Export geospatial annotations-
AudioExport audio annotations-
DocumentsExport document annotations-
Conversational textExport conversational text annotations-
DICOMExport DICOM annotations-
HTMLExport HTML annotations-

JSON export parameters

ParameterDescription
IDLabel ID.
DataRow IDID of the Data Row.
Labeled DataURL to the Asset that was labeled.
Label.frames (video only)URL to the video frame annotations.
Label.frameNumber (video only)Frame number where the annotation is located.
Label.objectsAn array of the Object-type annotations. If there are no Object-type annotations in the Label, the array will be empty. The Object-type annotations are Bounding box, Segmentation mask, Polygon, Point, Polyline, and Text entity. See Annotations section.
Label.classificationsAn array of Classification-type annotations at the global level. Classification-type annotations are Radio, Checklist, Free-form text, and Dropdown. See Annotations section.
Created AtTimestamp indicating when the Label was created. Includes only labeling time. Does not include review time.
Updated AtTimestamp indicating when the Label was updated. If the Label has not been updated since it was created, the timestamp will match the Created At timestamp.
Seconds to LabelNumber of seconds taken to create the Label. Includes review time.
External IDUser-generated filename or ID for the Data Row.
AgreementConsensus agreement score.
Benchmark AgreementBenchmark agreement score.
Benchmark IDID of the Benchmark if enabled for this project.
Dataset NameName of the Dataset containing the Data Row.
Reviews['id']ID of the Label review.
Reviews['score']1 indicates a Reviewer approved the Label. -1 indicates a Reviewer rejected the Label.
Reviews['labelId']Reference to the ID of the Label that was reviewed.
Reviews['createdAt']Timestamp indicating when the Label was reviewed.
Reviews['createdBy']Member that reviewed the Label.
View LabelLink to open the Asset (and Annotations) in the Editor.
Has Open IssuesIndicates whether the Label has any issues that need to be addressed.
Skippedtrue indicates the asset was skipped. false indicates the asset was not skipped.
DataRow Workflow InfoInformation on the progression of the labeled data row through the project's workflow.
DataRow Workflow Info['taskName']Name of the current task in which the data row is located.
DataRow Workflow Info['Workflow History']List of the data row's movements in the project's workflow.
Workflow History['actorId']The ID of the user that actioned on the data row in this specific step.
Workflow History['action']The action performed on the data row in this specific step.
Workflow History['createdAt']Timestamp indicated when this action on the data row occurred.
Workflow History['previousTaskId']The ID of the workflow task in which the data row began this action.
Workflow History['previousTaskName']The name of workflow task in which the data row began this action.
Workflow History['nextTaskId']The ID of the workflow task in which the data row concluded this action.
Workflow History['nextTaskName']The name of the workflow task in which the data row concluded this action.

Python SDK

There are two date range filters available for project export. You can use start and end to indicate the date range of the submitted labels' creation. You can also use last_activity_start and last_activity_end to captures the creation and modification of labels, metadata, status, comments, and reviews.

They should be formatted as "YYYY-MM-DD" or "YYYY-MM-DD hh:mm:ss", or None.

labels = project.label_generator()

# Alternatively you can specify date range to export desired labels from a project
# Date range can be “YYYY-MM-DD” or “YYYY-MM-DD hh:mm:ss”
# labels  range can be “YYYY-MM-DD” or “YYYY-MM-DD hh:mm:ss”

# 
labels = project.label_generator(start="2020-01-01", end="2020-01-02")

for label in labels:
  print(label.annotations)
  
  
#  Export labels that have been updated since a specific date “YYYY-MM-DD”
labels = project.export_labels(last_activity_start = "2023-02-06",last_activity_end="2023-03-06" )

# Updates captured by this filter include: 
# 1. Any label  updated on the data row
# 2. Any label  deleted on the data row 
# 3. Any review  applied to the data row
# 4. Any review through workflow is applied to the data row
# 5. Any issue or comment is created on the data row
# 6. Any issue or comment is updated on the data row
# 7. Any issue or comment is deleted on the data row
# 8. Any time custom metadata is updated on a data row