Releases: Labelbox/labelbox-python
Releases · Labelbox/labelbox-python
v.3.26.1
Version 3.26.1 (2022-08-23)
Changed
ModelRun.get_config()
- Modifies get_config to return un-nested Model Run config
Added
ModelRun.update_config()
- Updates model run training metadata
ModelRun.reset_config()
- Resets model run training metadata
ModelRun.get_config()
- Fetches model run training metadata
Changed
Model.create_model_run()
- Add training metadata config as a model run creation param
v.3.26.0
Version 3.26.0 (2022-08-15)
Added
Batch.delete()
which will delete an existingBatch
Batch.delete_labels()
which will delete allLabel
’s created after aProject
’s mode has been set to batch.- Note: Does not include labels that were imported via model-assisted labeling or label imports
- Support for creating model config when creating a model run
RAW_TEXT
andTEXT_FILE
attachment types to replace theTEXT
type.
v.3.25.3
Version 3.25.3 (2022-08-10)
Fixed
- Label export will continue polling if the downloadUrl is None
v.3.25.2
Version 3.25.2 (2022-07-26)
Updated
- Mask downloads now have retries
- Failed
upload_data
now shows more details in the error message
Fixed
- Fixed Metadata not importing with DataRows when bulk importing local files.
- Fixed COCOConverter failing for empty annotations
Documentation
- Notebooks are up-to-date with examples of importing annotations without
schema_id
v.3.25.1
Version 3.25.1 (2022-07-20)
Fix
- Remove extra dependency causing import errors.
v.3.25.0
Version 3.25.0 (2022-07-20)
Added
- Importing annotations with model assisted labeling or label imports using ontology object names instead of schemaId now possible
- In Python dictionaries, you can now use
schemaId
key orname
key for all tools, classifications, options
- In Python dictionaries, you can now use
- Labelbox's Annotation Types now support model assisted labeling or label imports using ontology object names
- Export metadata when using the following methods:
Batch.export_data_rows(include_metadata=True)
Dataset.export_data_rows(include_metadata=True)
Project.export_queued_data_rows(include_metadata=True)
VideoObjectAnnotation
hassegment_index
to group video annotations into video segments
Removed
Project.video_label_generator
. UseProject.label_generator
instead.
Updated
- Model Runs now support unassigned splits
Dataset.create_data_rows
now has the following limits:- 150,000 rows per upload without metadata
- 30,000 rows per upload with metadata
v.3.24.1
Version 3.24.1 (2022-07-07)
Updated
- Added
refresh_ontology()
as part of create/update/delete metadata schema functions
v.3.24.0
Version 3.24.0 (2022-07-06)
Added
DataRowMetadataOntology
class now has functions to create/update/delete metadata schemacreate_schema
- Create custom metadata schemaupdate_schema
- Update name of custom metadata schemaupdate_enum_options
- Update name of an Enum option for an Enum custom metadata schemadelete_schema
- Delete custom metadata schema
ModelRun
class now hasassign_data_rows_to_split
function, which can assign aDataSplit
to a list ofDataRow
sDataset.create_data_rows()
can bulk importconversationalData
v.3.23.3
v.3.23.2
Version 3.23.2 (2022-06-15)
Added
Data Row
object now has a new field,metadata
, which returns metadata associated with data row as a list ofDataRowMetadataField
- Note: When importing Data Rows with metadata, use the existing field,
metadata_fields
- Note: When importing Data Rows with metadata, use the existing field,