v0.15.1

Changed

• Better filter tuning of client.list_jobs(args) method

Added

• Dataset method to filter jobs, and statistics on running jobs
  Example:

>>> client = nucleus.NucleusClient(API_KEY)
>>> ds = client.get_dataset(ds_id)
>>> ds.jobs(show_completed=True, stats_only=True)
{'autotagInference': {'Cancelled': 1, 'Completed': 11},
 'modelRunCommit': {'Completed': 7, 'Errored_Server': 1, 'Running': 1},
 'sliceQuery': {'Completed': 40, 'Running': 2}}

Detailed Example

>>> from nucleus.job import CustomerJobTypes
>>> client = nucleus.NucleusClient(API_KEY)
>>> ds = client.get_dataset(ds_id)
>>> from_date = "2022-12-20"; to_date = "2023-01-15"
>>> job_types = [CustomerJobTypes.MODEL_INFERENCE_RUN, CustomerJobTypes.UPLOAD_DATASET_ITEMS]
>>> ds.jobs(
  from_date=from_date,
  to_date=to_date,
  show_completed=True,
  job_types=job_types,
  limit=150
)
# ... returns list of AsyncJob objects

v0.15.0

Changed

• dataset.slices now returns a list of Slice objects instead of a list of IDs

Added

dataset.get_slices(name: str, slice_type: SliceType): List[Slice]

• Retrieve a slice from a dataset by its name, or
• Retrive all slices of a particular type from. Where type is one of ["dataset_item", "object", "scene"].

from nucleus.slice import SliceType
dataset.get_slices(name="My Slice")  # if slice exists, this will return an array with a single item.
dataset.get_slices(slice_type=SliceType.DATASET_ITEM)

v0.14.30

• Support for uploading track-level metrics to external evaluation functions using track_ref_ids

v0.14.29

Added

• Support for Tracks, enabling ground truth annotations and model predictions to be grouped across dataset items and scenes
• Helpers to update track metadata, as well as to create and delete tracks at the dataset level

v0.14.28

Added

• Support for appending to slice with Scene reference IDs
• Better error handling when appending to a slice with non-existent reference IDs

v0.14.27

• Support for scene-level external evaluation functions
• Support for uploading custom scene-level metrics

v0.14.26

Added

• Support for fetching scene from a DatasetItem.reference_id. Example:

dataset = client.get_dataset("<dataset_id>")
assert dataset.is_scene  # only works on scene datasets
some_item = dataset.iloc(0)
dataset.get_scene_from_item_ref_id(some_item['item'].reference_id) 

v0.14.25

Updated

• Items of a slice can be retrieved by Slice property .item
• The type of items returned from .items is based on the slice type:
  • slice.type == 'dataset_item' => list of DatasetItem objects
  • slice.type == 'object' => list of Annotation/Prediction objects
  • slice.type == 'scene' => list of Scene objects

v0.14.24

• Late imports for seldomly used heavy libraries. Sped up CLI invocation and autocomplation. If you had shell completions installed before we recommend removeing them from your .(bash|zsh)rc file and reinstalling with nu install-completions.

v0.14.23

Added support for building slices via Nucleus' Smart Sample