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Labelbox exports give you more flexibility and control to retrieve the most valuable information from your projects. You can now select and export a subselection of the data rows of most interest based on your predefined or new parameters in the Data Rows tab. You can also export more detailed information from these data rows, and include or exclude relevant attributes in your export. We also simplified and standardized the annotation formats.For more details on how to create exports, along with complete samples, please view the following pages:
Export labels from project
Export model run data
Below is a glossary of the fields that can appear in an export.
Labelbox exports aligns with the data-row-centric paradigm, thus every line, regardless of the export time, will include information on each included data row.
Field
Included
Description
data_row
Always
A dictionary containing the fields explained the data_row table below.
A dictionary containing the fields explained in the details table below. When exporting through the SDK, these fields are included by setting the data_row_details parameter to True.
The projects field contains a dictionary in which the keys are project IDs and the values consist of the fields explained below.In a project-based export, there will only be a singular project ID in this dictionary. Yet, when exporting from the Catalog, consider that a data row may have been labeled in multiple projects, and thus the dictionary will have multiple keys.Project IDs are used in favor of project names in order to enforce uniqueness.
Field
Included
Description
name
Always
The name of the project in which the data row was labeled.
labels
Always
Contains a list of dictionaries comprised of the fields explained in the labels section below.
project_details
Optional
A dictionary containing the fields explained in the project_details table below.
A timestamp indicating when the label was created.
updated_at
Always
A timestamp indicating when the label was most recently updated.
created_by
Always
The email address of the user that created the label.
reviews
Always
[Legacy] For projects using Workflows for review, please use workflow_historyhere. Information on the thumbs up/down reviews created on this label. Contains a list of dictionaries comprised of the fields explained in the reviews table below.
Dictionary with per-frame annotations (objects and classifications)
segments
Videos only
A dictionary where each key is a feature_id, and the corresponding value is a list of frame numbers representing the range of frames where that feature exists.
key_frame_feature_map
Videos only
A dictionary where each key is a feature_id, and the corresponding value is a list of frame numbers representing the frames where that feature exists.
feature_id
Always
Unique identifier for an annotation in a label; this id is also present on all classification answers.
feature_schema_id
Always
Unique identifier for an ontology tool or classification; this id is also present on all classification answers.
annotation_kind
Situational
The kind of tool utilized by the annotation (e.g. ImageBoundingBox, ImagePolyline)
name
Always
Name given to the tool or classification
value
Always
Normalized name of the tool or classification: if a user creates a tool named “Apple Pear,” this field will show the normalized version “apple_pear.”
The ID of the task the data row currently is in in the project.
task_name
Always
The name of the task the data row currently is in in the project.
batch_id
Always
The ID of the batch in which the data row was sent to the project.
batch_name
Always
The name of the batch in which the data row was sent to the project.
workflow_status
Always
The status of the data row in the project (either TO_LABEL, IN_REWORK, IN_REVIEW, or DONE)
priority
Always
The priority assigned to the batch.
selected_label_id
If utilized
The ID of the label that was selected as the “winner” amongst the labels made on the data row.
consensus_expected_label_count
Always
The number of labels that were expected to be created on this data row according to the consensus settings.
workflow_history
Always
Information on the progression of the labeled data row through the project’s workflow. Contains a list of dictionaries comprised of the fields explained in the workflow_history table below.
The action that was performed on the data row in this specific step. Typical actions are: Move : change of task queue Acceptor Reject: selection of a review score Rework: follows Reject
created_at
Always
A timestamp that indicates when this action on the data row occurred.
created_by
Always
The email address of the user that performed this action.
previous_task_name
Situational
The name of the workflow task in which the data row began this action.
previous_task_id
Situational
The ID of the workflow task in which the data row began this action.
next_task_name
Situational
The name of the workflow task in which the data row concluded this action.
next_task_id
Situational
The ID of the workflow task in which the data row concluded this action.
The experiments field contains a dictionary in which the keys are model experiment IDs, and the values consist of the name and a dictionary of model runs.In a model-based export, only a singular model ID will be in this dictionary. Yet, when exporting from the Catalog, consider that a data row may be included in multiple models, and thus the dictionary will have multiple keys.Model experiment IDs are used in favor of model names to enforce uniqueness.
Field
Included
Description
name
Always
The name of the model in which the data row appears.
runs
Always
A dictionary where the keys are the IDs of the model runs in which the data row appears.
The model runs field contains a dictionary in which the keys are model run IDs, and the values consist of the fields explained below.Model run IDs are used in favor of model run names to enforce uniqueness.
Field
Included
Description
name
Always
The name of the model run.
run_data_row_id
Always
A unique ID for the data row in the context of the model run.
labels
Situational
Ground truth annotations can optionally be sent to a model run as labels. If present, the labels will appear in the same format as in a project-based export, which is detailed in the labels table above, though the optional label_details and performance_details sections are always excluded in the context of a model run.
predictions
Optional
A dictionary containing the fields explained in the predictions table below.
split
Situational
The value will be included if the data row is assigned to a split. The potential outputs are Training, Validation, orTest. When exporting through the SDK, these fields are included by setting the model_run_details parameter to True.
