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April 3, 2023

about 1 year ago by Alex

Release notes

App

  • You can now upload up to 10 custom embeddings to Labelbox. Custom embeddings are helpful for improving data exploration and similarity search experience. To learn more, visit this page.
  • In Catalog, you can use the new find text filter to narrow down text, conversational text, documents, and HTML data rows by keyword. To learn more, visit this page.
  • With the new natural language search filter in Catalog and Annotate, you can now describe the data rows you're looking for in plain English and Labelbox will surface the relevant data rows. Note: this functionality currently works for images and geospatial data. For more information, visit this page.
  • We added a brush tool to the video & DICOM editors. You can use the brush tool to quickly draw segmentation masks. This feature is in beta. To learn more about the brush tool, see brush tool in video editor and brush tool in DICOM editor.
  • When you export from a project, you'll get a new and improved export format that gives you more flexibility to retrieve the most valuable information from your data rows. Exports v2 enables you to use filters to select and export a subset of data rows. You can also choose to exclude parameters from the export that you do not need. This feature is in beta. For more information, see Export from project.
  • You can now export data from a model run. Use the filters to query data row label status, metadata, batch, annotations, and workflow history. You can also choose to exclude parameters from the export that you do not need. This feature is in beta. For more information, see Export model run data.
  • You can now export everything about a data row from the Catalog UI including slice information, dataset name, annotations, and model run data. To learn more, visit Export from catalog.
  • You can now send model predictions that are stored in a model run to a labeling project as pre-labels. This allows you to inspect the model predictions before sending them to a labeling project. For more information, see this page.
  • If you are browsing your data rows in the Model product and you discover data rows that contain labeling mistakes, you can now send those data from a model run to a labeling project for re-labeling. To learn more, read this page.
  • We enabled the ability to turn off linear interpolation in the video editor at the organization level. When interpolation is disabled, objects will maintain the geometry of a keyframe until the next keyframe, instead of linear transitions between keyframes. To enable this for your organization, contact [email protected].
  • We enabled three new filters in the Data Rows tab: Has review (legacy), Reviewed by (legacy), and Reviewed at (legacy). These filters allow you to see your legacy review information in the new Data Rows tab. For more information, visit this page.
  • All of your projects that have been migrated to the new workflows/batch queue/data row tab paradigm are marked with a “legacy” tag. To learn more, visit this page.
  • In the Workflows tab, the “send to task” functionality now supports up to 10,000 data rows.
  • The zoom experience in the labeling editor is less sensitive and is much easier to achieve specific zoom levels than before.
  • We introduced a new, simplified two-step process for importing annotations to Labelbox. Now, you can upload data rows and annotations in one call using global keys. For more information, visit this page.
  • When importing metadata, you can now import multiple enum options.
  • When you are in the Model product, the URL now contains the state of filters, slices, and splits so you can more easily share exact views of the Model tab with your team.
  • AI-based bounding box tracking in video is now available as GA. To learn more about bounding box tracking, visit this page.
  • We enabled support for Select all on the Data Rows tab With this feature you can now perform this bulk action with a single click.
  • You can now bulk add metadata to data rows via the Catalog UI. For instructions, visit this page.
  • Word selection is now available in the text editor. This feature allows you to hover over and annotate full words with one click, rather than labeling text characters. For more information, see this page.

Python SDK

The latest version of our Python SDK is v3.42.0. See our full changelog in Github for more details on what was added recently.

Version 3.42.0 (2023-03-22)

Added

  • Message based classifications with annotation types for conversations
  • Video and raster segmentation annotation types
  • Global key support to ConversationEntity, DocumentEntity and DicomSegments
  • DICOM polyline annotation type
  • Confidence attribute to classification annotations

Changed

  • Increased metadata string size limit to 4096 chars
  • Removed deletedDataRowGlobalKey from get_data_row_ids_for_global_keys()

Fixed

  • Annotation data type coercion by Pydantic
  • Error message when end point coordinates are smaller than start point coordinates
  • Some typos in error messages

Notebooks

  • Refactored video notebook to include annotation types
  • Replaced data row ids with global keys in notebooks
  • Replaced create_data_row with create_data_rows in notebooks

Version 3.41.0 (2023-03-15)

Added

  • New data classes for creating labels: AudioData, ConversationData, DicomData, DocumentData, HTMLData
  • New DocumentEntity annotation type class
  • New parameter last_activity_end to Project.export_labels()

Notebooks

  • Updated annotation_import/pdf.ipynb with example use of DocumentEntity class

Version 3.40.1 (2023-03-10)

Fixed

  • Fixed issue where calling create_batch() on exported data rows wasn't working

Version 3.40.0 (2023-03-10)

Added

  • Support Global keys to reference data rows in Project.create_batch(), ModelRun.assign_data_rows_to_split()
  • Support upserting labels via project_id in model_run.upsert_labels()
  • media_type_override param to export_v2
  • last_activity_at and label_created_at params to export_v2
  • New client method is_feature_schema_archived()
  • New client method unarchive_feature_schema_node()
  • New client method delete_feature_schema_from_ontology()

Changed

  • Removed default task names for export_v2

Fixed

  • process_label() for COCO panoptic dataset

Notebooks

  • Updated annotation_import/pdf.ipynb with more examples
  • Added integrations/huggingface/huggingface.ipynb
  • Fixed broken links for detectron notebooks in README
  • Added Dataset QueueMode during project creation in integrations/detectron2/coco_object.ipynb
  • Removed metadata and updated ontology in annotation_import/text.ipynb
  • Removed confidence scores in annotation_import/image.ipynb
  • Updated custom embedding tutorial links in basics/data_row_metadata.ipynb