Export specifications: image | video | text | documents | geospatial/tiled imagery | audio | conversational text | HTML | DICOM

Developer guide: Export labels via Python SDK

There are three ways you can export data from Labelbox: export from Catalog, export from a model run, and export from a labeling project. This guide explains how to select and export annotations from a labeling project.

How to export via the app UI

To export annotations from a labeling project via the UI, go to Annotate > select a project > Data Rows tab. From the Data Rows tab, you can narrow down your data rows by label status, metadata, batch, annotations, and workflow history.

Then, when you export from a project, you may choose to include or exclude certain attributes in your export. Note that excluding fields from your export will make the export process faster and the export file smaller.

Please note that Export data v2 is not supported for projects that use a custom editor. Instead, you must go to the Export tab within the project and select v1 in the Export version dropdown.

Option 1: Export all data rows

Click on All (X number of data rows), then click the Export data v2 (beta) in the drop-down menu.

Option 2: Specify label status

If you only want to export data rows that have a certain status, you can use the pre-generated filters to easily select data rows by label status.

1. On the left side of the Data Rows tab, select a label status (To Label, In review, In rework, or Done).
2. Specify the fields you want to include in the export.
3. Click Export data v2 to export those data rows.

Option 3: Filter data rows

After selecting the label status, you can build your filters in the Data Rows tab to query for data rows of the desired context. See more in Data Rows tab.

Then click the Done (X number of data rows) dropdown, and click Export data v2 to export the data rows.

Option 4: Select specific data rows

1. Hand-select data rows to export by using the check boxes next to each data row.
2. Then, click the drop-down on the right side X selected, and click Export data.

3. Once you hit Export data, you will see a panel with additional date range queries and filters.

   1. Choose the fields to include or exclude in your final NDJSON export. See the export specifications in the Developer guides.
   2. When you are done, click Export JSON.

4. After you click Export JSON, you will see a notification banner telling you that you can track the progress of the export job in the Notifications center.

5. Once the job is complete, download the export file by clicking the Download link.

How to view video and DICOM exports

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Export v1 only

This section does not apply to exports V2. Export V2 will include the entire payload in the export file.

Due to size, exports for video and DICOM projects will contain a URL for each video that links to an NDJSON file containing the annotations. You have two options for accessing the annotations in your video and DICOM exports.

Option 1: Python SDK

To learn how to retrieve your video and DICOM annotations via the Python SDK, view this page.

Option 2: Postman

You can also access your video annotations using the Postman UI. Watch this video to learn how to do so.

1. Open Postman and create a new basic API request.

2. Copy the URL for frames and paste it as the request URL.

3. Go to the Headers tab.

4. Select Authorization as the key.

5. Paste your API key as the Authorization value.

6. Click Send.