Releases: Labelbox/labelbox-python
Releases · Labelbox/labelbox-python
Version 3.6.0
Version 3.6.0 (2021-05-10)
Added
- Bulk export metadata with
DataRowMetadataOntology.bulk_export()
- Add docstring examples of annotation types and a few helper methods
Updated
- Update metadata notebook under examples/basics to include bulk_export
- Allow color to be a single integer when constructing Mask objects
- Allow users to pass int arrays to RasterData and attempt coercion to uint8
Removed
- data_row.metadata was removed in favor of bulk exports
Version 3.5.0
Version 3.5.0 (2021-15-09)
Added
- Diagnostics custom metrics
- Metric annotation types
- Update ndjson converter to be compatible with metric types
- Metric library for computing confusion matrix metrics and iou
- Demo notebooks under
examples/diagnostics
- COCO Converter
- Convert to and from COCO object and panoptic formats
- Detectron2 example integration notebooks
Version 3.4.1
Version 3.4.1 (2021-09-10)
Fix
- Iam validation exception message
Version 3.4.0
Version 3.4.0 (2021-09-10)
Added
- New
IAMIntegration
entity Client.create_dataset()
compatibility with delegated accessOrganization.get_iam_integrations()
to list all iam integrations available to an orgOrganization.get_default_iam_integration()
to retrieve the default iam integration
Version 3.3.0
Version 3.3.0 (2021-09-07)
Added
Dataset.create_data_rows_sync()
for synchronous bulk uploads of data rowsModel.delete()
,ModelRun.delete()
, andModelRun.delete_annotation_groups()
to
Clean up models, model runs, and annotation groups.
Fix
- Increased timeout for label exports since projects with many segmentation masks weren't finishing quickly enough.
Version 3.2.1
Version 3.2.1 (2021-08-31)
Fix
- Resolved issue with
create_data_rows()
not working on amazon linux
Version 3.2.0
Version 3.2.0 (2021-08-26)
Added
- List
BulkImportRequest
s for a project withProject.bulk_import_requests()
- Improvemens to
Dataset.create_data_rows()
- Add attachments when bulk importing data rows
- Provide external ids when creating data rows from local files
- Get more informative error messages when the api rejects an import
Fix
- Bug causing
project.label_generator()
to fail when projects had benchmarks
Version 3.1.0
Version 3.1.0 (2021-08-18)
Added
- Support for new HTML attachment type
- Delete Bulk Import Requests with
BulkImportRequest.delete()
Misc
- Updated MEAPredictionImport class to use latest grapqhql endpoints
Version 3.0.1
Version 3.0.1 (2021-08-13)
Fix
- Issue with inferring text type from export
Version 3.0.0
Version 3.0.0 (2021-08-12)
Added
- Annotation types
- A set of python objects for working with Labelbox data
- Creates a standard interface for both exports and imports
- See example notebooks on how to use under examples/annotation_types
- Note that these types are not yet supported for tiled imagery
- Model Diagnostics Support
- Model Diagnostics beta users can now just use the latest SDK release
- Metadata support
- New metadata features are now fully supported by the SDK
- Easier export
project.export_labels()
accepts a boolean indicating whether or not to download the result- Create annotation objects directly from exports with
project.label_generator()
orproject.video_label_generator()
project.video_label_generator()
asynchronously fetches video annotations
- Retry logic on data uploads
- Bulk creation of data rows will be more reliable
- Datasets
- Determine the number of data rows just by calling
dataset.row_count
. - Updated threading logic in create_data_rows() to make it compatible with aws lambdas
- Determine the number of data rows just by calling
- Ontology
OntologyBuilder
,Classification
,Option
, andTool
can now be imported fromlabelbox
instead oflabelbox.schema.ontology
Removed
- Deprecated:
project.reviews()
project.create_prediction()
project.create_prediction_model()
project.create_label()
Project.predictions()
Project.active_prediction_model
data_row.predictions
PredictionModel
Prediction
- Replaced:
data_row.metadata()
usedata_row.attachments()
insteaddata_row.create_metadata()
usedata_row.create_attachments()
insteadAssetMetadata
useAssetAttachment
instead
Fixes
- Support derived classes of ontology objects when using
from_dict
- Notebooks:
- Video export bug where the code would fail if the exported projects had tools other than bounding boxes
- Model-assisted labeling demos were broken due to an image download failing.
Misc
- Data processing dependencies are not installed by default to for users that only want client functionality.
- To install all dependencies required for the data modules (annotation types and mea metric calculation) use
pip install labelbox[data]
- Decrease wait time between updates for
BulkImportRequest.wait_until_done()
. - Organization is no longer used to create the LFO in
Project.setup()