To obtain a handle to a
DataLabeling object, you call the
DataLabeling() constructor. The default compartment is the same compartment as the notebook session, but the
compartment_id parameter can be used to select a different compartment.
To work with the labeled data, you need a snapshot of the dataset. The
export() method copies the labeled data from the Data Labeling service into a bucket in Object Storage. The
.export() method has the following parameters:
dataset_id: The OCID of the Data Labeling dataset to take a snapshot of.
path: The Object Storage path to store the generated snapshot.
The export process creates a JSONL file that contains metadata about the labeled dataset in the specified bucket. There is also a record JSONL file that stores the image, text, or document file path of each record and its label.
export() method returns the path to the metadata file that was created in the export operation.
from ads.data_labeling import DataLabeling dls = DataLabeling() metadata_path = dls.export( dataset_id="<dataset_id>", path="oci://<bucket_name>@<namespace>/<prefix>" )