Label video

Start a video labeling task.

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To view the code sample used in context, see the following documentation:

Code sample

Java

To learn how to install and use the client library for Data Labeling Service, see Data Labeling Service client libraries. For more information, see the Data Labeling Service Java API reference documentation.

import com.google.api.gax.longrunning.OperationFuture;
import com.google.cloud.datalabeling.v1beta1.AnnotatedDataset;
import com.google.cloud.datalabeling.v1beta1.DataLabelingServiceClient;
import com.google.cloud.datalabeling.v1beta1.DataLabelingServiceSettings;
import com.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig;
import com.google.cloud.datalabeling.v1beta1.LabelOperationMetadata;
import com.google.cloud.datalabeling.v1beta1.LabelVideoRequest;
import com.google.cloud.datalabeling.v1beta1.LabelVideoRequest.Feature;
import com.google.cloud.datalabeling.v1beta1.VideoClassificationConfig;
import com.google.cloud.datalabeling.v1beta1.VideoClassificationConfig.AnnotationSpecSetConfig;
import java.io.IOException;
import java.util.concurrent.ExecutionException;

class LabelVideo {

  // Start a Video Labeling Task
  static void labelVideo(
      String formattedInstructionName,
      String formattedAnnotationSpecSetName,
      String formattedDatasetName)
      throws IOException {
    // String formattedInstructionName = DataLabelingServiceClient.formatInstructionName(
    //      "YOUR_PROJECT_ID", "YOUR_INSTRUCTION_UUID");
    // String formattedAnnotationSpecSetName =
    //     DataLabelingServiceClient.formatAnnotationSpecSetName(
    //         "YOUR_PROJECT_ID", "YOUR_ANNOTATION_SPEC_SET_UUID");
    // String formattedDatasetName = DataLabelingServiceClient.formatDatasetName(
    //      "YOUR_PROJECT_ID", "YOUR_DATASET_UUID");


    DataLabelingServiceSettings settings =
        DataLabelingServiceSettings.newBuilder()
            .build();
    try (DataLabelingServiceClient dataLabelingServiceClient =
        DataLabelingServiceClient.create(settings)) {
      HumanAnnotationConfig humanAnnotationConfig =
          HumanAnnotationConfig.newBuilder()
              .setAnnotatedDatasetDisplayName("annotated_displayname")
              .setAnnotatedDatasetDescription("annotated_description")
              .setInstruction(formattedInstructionName)
              .build();

      AnnotationSpecSetConfig annotationSpecSetConfig =
          AnnotationSpecSetConfig.newBuilder()
              .setAnnotationSpecSet(formattedAnnotationSpecSetName)
              .setAllowMultiLabel(true)
              .build();

      VideoClassificationConfig videoClassificationConfig =
          VideoClassificationConfig.newBuilder()
              .setApplyShotDetection(true)
              .addAnnotationSpecSetConfigs(annotationSpecSetConfig)
              .build();

      LabelVideoRequest labelVideoRequest =
          LabelVideoRequest.newBuilder()
              .setParent(formattedDatasetName)
              .setBasicConfig(humanAnnotationConfig)
              .setVideoClassificationConfig(videoClassificationConfig)
              .setFeature(Feature.CLASSIFICATION)
              .build();

      OperationFuture<AnnotatedDataset, LabelOperationMetadata> operation =
          dataLabelingServiceClient.labelVideoAsync(labelVideoRequest);

      // You'll want to save this for later to retrieve your completed operation.
      System.out.format("Operation Name: %s\n", operation.getName());

      // Cancel the operation to avoid charges when testing.
      dataLabelingServiceClient.getOperationsClient().cancelOperation(operation.getName());
    } catch (IOException | InterruptedException | ExecutionException e) {
      e.printStackTrace();
    }
  }
}

Python

To learn how to install and use the client library for Data Labeling Service, see Data Labeling Service client libraries. For more information, see the Data Labeling Service Python API reference documentation.

def label_video(
    dataset_resource_name, instruction_resource_name, annotation_spec_set_resource_name
):
    """Labels a video dataset."""
    from google.cloud import datalabeling_v1beta1 as datalabeling

    client = datalabeling.DataLabelingServiceClient()

    basic_config = datalabeling.HumanAnnotationConfig(
        instruction=instruction_resource_name,
        annotated_dataset_display_name="YOUR_ANNOTATED_DATASET_DISPLAY_NAME",
        label_group="YOUR_LABEL_GROUP",
        replica_count=1,
    )

    feature = datalabeling.LabelVideoRequest.Feature.OBJECT_TRACKING

    config = datalabeling.ObjectTrackingConfig(
        annotation_spec_set=annotation_spec_set_resource_name
    )

    response = client.label_video(
        request={
            "parent": dataset_resource_name,
            "basic_config": basic_config,
            "feature": feature,
            "object_tracking_config": config,
        }
    )

    print("Label_video operation name: {}".format(response.operation.name))
    return response

What's next

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