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代码示例

Java

如需了解如何安装和使用 Data Labeling Service 客户端库，请参阅 Data Labeling Service 客户端库。 有关详情，请参阅 Data Labeling Service Java API 参考文档。

如需向 Data Labeling Service 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

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.LabelTextRequest;
import com.google.cloud.datalabeling.v1beta1.LabelTextRequest.Feature;
import com.google.cloud.datalabeling.v1beta1.SentimentConfig;
import com.google.cloud.datalabeling.v1beta1.TextClassificationConfig;
import java.io.IOException;
import java.util.concurrent.ExecutionException;

class LabelText {

  // Start a Text Labeling Task
  static void labelText(
      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")
              .setLanguageCode("en-us")
              .setInstruction(formattedInstructionName)
              .build();

      SentimentConfig sentimentConfig =
          SentimentConfig.newBuilder().setEnableLabelSentimentSelection(false).build();

      TextClassificationConfig textClassificationConfig =
          TextClassificationConfig.newBuilder()
              .setAnnotationSpecSet(formattedAnnotationSpecSetName)
              .setSentimentConfig(sentimentConfig)
              .build();

      LabelTextRequest labelTextRequest =
          LabelTextRequest.newBuilder()
              .setParent(formattedDatasetName)
              .setBasicConfig(humanAnnotationConfig)
              .setTextClassificationConfig(textClassificationConfig)
              .setFeature(Feature.TEXT_CLASSIFICATION)
              .build();

      OperationFuture<AnnotatedDataset, LabelOperationMetadata> operation =
          dataLabelingServiceClient.labelTextAsync(labelTextRequest);

      // 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

如需了解如何安装和使用 Data Labeling Service 客户端库，请参阅 Data Labeling Service 客户端库。 如需了解详情，请参阅 Data Labeling Service Python API 参考文档。

如需向 Data Labeling Service 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

def label_text(
    dataset_resource_name, instruction_resource_name, annotation_spec_set_resource_name
):
    """Labels a text 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.LabelTextRequest.Feature.TEXT_ENTITY_EXTRACTION

    config = datalabeling.TextEntityExtractionConfig(
        annotation_spec_set=annotation_spec_set_resource_name
    )

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

    print(f"Label_text operation name: {response.operation.name}")
    return response

后续步骤

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