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:

Below is a glossary of the fields that can appear in an export.

Export fields

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.
`media_attributes`	Optional	See Media attributes
`attachments`	Optional	See Attachments
`metadata_fields`	Optional	See Metadata
`embeddings`	Optional	A list of dictionaries containing precomputed and custom embeddings

`data_row`

Field	Included	Description
`id`	Always	The ID of the data row.
`global_key`	If utilized	The global key of the data row.
`external_id`	If utilized	The external ID of the data row.
`row_data`	Always	The URL to your cloud-hosted file
`details`	Optional	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`.

`details`

Field	Included	Description
`dataset_id`	Always	The ID of the dataset to which the data row belongs.
`created_at`	Always	A timestamp that indicates when the data row was created.
`updated_at`	Always	A timestamp indicating when the data row was most recently updated.
`last_activity_at`	Always*	A timestamp indicating the last time any activity was performed on the data row.
`created_by`	Always	The email address of the user that created the data row.

* The last_activity_at field is not included in exports from a model run.

`projects`

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
`project_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` table below.
`project_details`	Optional	A dictionary containing the fields explained in the `project_details` table below.

`labels`

Field	Included	Description
`label_kind`	Always	For labels made on assets of most media types, the value is `Default`. For frame-based assets, the value is `Video`.
`version`	Always	Used to track updates made to export formats. At present, the value will always be `1.0.0`.
`id`	Always	The ID of the label.
`label_details`	Optional	A dictionary containing the fields explained in the `label_details` table below.
`performance_details`	Optional	A dictionary containing the fields explained in the `performance_details` table below.
`annotations`	Always	See the annotation export formats broken down by asset type, beginning here with images.

`label_details`

Field	Included	Description
`created_at`	Always	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_history` here. 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.

`reviews`(for legacy only)

Field	Included	Description
`reviewed_at`	Situational	A timestamp that indicates when the review was created.
`reviewed_by`	Situational	The email address of the user that created the review.
`review_action`	Situational	The type of review created; either `Approve` or `Reject`.

`performance_details`

Field	Included	Description
`seconds_to_create`	Always	The number of seconds spent creating the label. After label submission, there could be a 30-minute delay before this field gets updated.
`seconds_to_review`	Always	The number of seconds spent reviewing the label. After completing reviewing, there could be a 30-minute delay before this field gets updated.
`skipped`	Always	A boolean value expressing whether or not the asset was skipped. A value of `true` indicates the asset was skipped.
`benchmark_reference_label`	Situational	The ID of the "gold standard" benchmark label to which this label is compared.
`benchmark_score`	Situational	The agreement score between the label and the associated benchmark label. After label submission or updates, there could be a 30-minute delay before this field gets updated.
`consensus_score`	Situational	The agreement score between the label and the associated consensus labels made on the same data row. After label submission or updates, there could be a 30-minute delay before this field gets updated.
`consensus_label_count`	Situational	The number of labels created on this data row in this project.
`consensus_labels`	Situational	The IDs of the labels created on this data row in this project.

`annotations`

Field	Included	Description
`objects`	Always	Tool annotations (e.g., bounding box, masks, polygon, etc ..)
`classifications`	Always	Classification annotations (radio, checklist)
`frames`	Videos only	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."

`project_details`

Field	Included	Description
`ontology_id`	Always	The ID of the ontology connected to the project.
`task_id`	Always	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.

`workflow_history`

Field	Included	Description
`action`	Always	The action that was performed on the data row in this specific step. Typical actions are: `Move` : change of task queue `Accept`or `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.

`experiments`

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.

`runs`

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`, or`Test`. When exporting through the SDK, these fields are included by setting the `model_run_details` parameter to `True`.

`predictions`

Field	Included	Description
`label_kind`	Always	For labels made on assets of most media types, the value is `Default`. For frame-based assets, the value is `Video`.
`version`	Always	Used to track updates made to export formats. At present, the value will always be `1.0.0`.
`id`	Always	The ID of the set of predictions.
`annotations`	Always	See the annotation export formats broken down by asset type, beginning here with images.

Export fields

data_row

details

projects

labels

label_details

reviews(for legacy only)

performance_details

annotations

project_details

workflow_history

experiments

runs

predictions