Create a data labeling job for images

Creates a data labeling job for images using the create_data_labeling_job method.

Code sample

Python

Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries. For more information, see the Vertex AI Python API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

from google.cloud import aiplatform
from google.protobuf import json_format
from google.protobuf.struct_pb2 import Value


def create_data_labeling_job_images_sample(
    project: str,
    display_name: str,
    dataset: str,
    instruction_uri: str,
    annotation_spec: str,
    location: str = "us-central1",
    api_endpoint: str = "us-central1-aiplatform.googleapis.com",
):
    # The AI Platform services require regional API endpoints.
    client_options = {"api_endpoint": api_endpoint}
    # Initialize client that will be used to create and send requests.
    # This client only needs to be created once, and can be reused for multiple requests.
    client = aiplatform.gapic.JobServiceClient(client_options=client_options)
    inputs_dict = {"annotation_specs": [annotation_spec]}
    inputs = json_format.ParseDict(inputs_dict, Value())

    data_labeling_job = {
        "display_name": display_name,
        # Full resource name: projects/{project_id}/locations/{location}/datasets/{dataset_id}
        "datasets": [dataset],
        # labeler_count must be 1, 3, or 5
        "labeler_count": 1,
        "instruction_uri": instruction_uri,
        "inputs_schema_uri": "gs://google-cloud-aiplatform/schema/datalabelingjob/inputs/image_classification_1.0.0.yaml",
        "inputs": inputs,
        "annotation_labels": {
            "aiplatform.googleapis.com/annotation_set_name": "my_test_saved_query"
        },
    }
    parent = f"projects/{project}/locations/{location}"
    response = client.create_data_labeling_job(
        parent=parent, data_labeling_job=data_labeling_job
    )
    print("response:", response)

What's next

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