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Inhalte einer Cloud Storage-Datei klassifizieren

Analysiert eine in Google Cloud Storage gespeicherte Datei und gibt eine Liste der Inhaltskategorien zurück, die auf den im Dokument enthaltenen Text zutreffen.

Weitere Informationen

Eine ausführliche Dokumentation, die dieses Codebeispiel enthält, finden Sie hier:

Inhaltsklassifizierung

Codebeispiel

Go

Informationen zum Installieren und Verwenden der Clientbibliothek für Natural Language finden Sie unter Natural Language-Clientbibliotheken. Weitere Informationen finden Sie in der Referenzdokumentation zur Natural Language Go API.

Richten Sie für die Authentifizierung bei Natural Language Standardanmeldedaten für Anwendungen ein. Weitere Informationen finden Sie unter Authentifizierung für eine lokale Entwicklungsumgebung einrichten.


func classifyTextFromGCS(ctx context.Context, gcsURI string) (*languagepb.ClassifyTextResponse, error) {
	return client.ClassifyText(ctx, &languagepb.ClassifyTextRequest{
		Document: &languagepb.Document{
			Source: &languagepb.Document_GcsContentUri{
				GcsContentUri: gcsURI,
			},
			Type: languagepb.Document_PLAIN_TEXT,
		},
	})
}

Java

// Instantiate the Language client com.google.cloud.language.v2.LanguageServiceClient
try (LanguageServiceClient language = LanguageServiceClient.create()) {
  // Set the GCS content URI path
  Document doc =
      Document.newBuilder().setGcsContentUri(gcsUri).setType(Type.PLAIN_TEXT).build();
  ClassifyTextRequest request = ClassifyTextRequest.newBuilder().setDocument(doc).build();
  // Detect categories in the given file
  ClassifyTextResponse response = language.classifyText(request);

  for (ClassificationCategory category : response.getCategoriesList()) {
    System.out.printf(
        "Category name : %s, Confidence : %.3f\n",
        category.getName(), category.getConfidence());
  }
}

Node.js

// Imports the Google Cloud client library.
const language = require('@google-cloud/language');

// Creates a client.
const client = new language.LanguageServiceClient();

/**
 * TODO(developer): Uncomment the following lines to run this code
 */
// const bucketName = 'Your bucket name, e.g. my-bucket';
// const fileName = 'Your file name, e.g. my-file.txt';

// Prepares a document, representing a text file in Cloud Storage
const document = {
  gcsContentUri: `gs://${bucketName}/${fileName}`,
  type: 'PLAIN_TEXT',
};

// Classifies text in the document
const [classification] = await client.classifyText({document});

console.log('Categories:');
classification.categories.forEach(category => {
  console.log(`Name: ${category.name}, Confidence: ${category.confidence}`);
});

PHP

Informationen zum Installieren und Verwenden der Clientbibliothek für Natural Language finden Sie unter Natural Language-Clientbibliotheken.

use Google\Cloud\Language\V1\ClassifyTextRequest;
use Google\Cloud\Language\V1\Client\LanguageServiceClient;
use Google\Cloud\Language\V1\Document;
use Google\Cloud\Language\V1\Document\Type;

/**
 * @param string $uri The cloud storage object to analyze (gs://your-bucket-name/your-object-name)
 */
function classify_text_from_file(string $uri): void
{
    $languageServiceClient = new LanguageServiceClient();

    // Create a new Document, pass GCS URI and set type to PLAIN_TEXT
    $document = (new Document())
        ->setGcsContentUri($uri)
        ->setType(Type::PLAIN_TEXT);

    // Call the analyzeSentiment function
    $request = (new ClassifyTextRequest())
        ->setDocument($document);
    $response = $languageServiceClient->classifyText($request);
    $categories = $response->getCategories();
    // Print document information
    foreach ($categories as $category) {
        printf('Category Name: %s' . PHP_EOL, $category->getName());
        printf('Confidence: %s' . PHP_EOL, $category->getConfidence());
        print(PHP_EOL);
    }
}

Python

from google.cloud import language_v1

def sample_classify_text(gcs_content_uri):
    """
    Classifying Content in text file stored in Cloud Storage

    Args:
      gcs_content_uri Google Cloud Storage URI where the file content is located.
      e.g. gs://[Your Bucket]/[Path to File]
      The text file must include at least 20 words.
    """

    client = language_v1.LanguageServiceClient()

    # gcs_content_uri = 'gs://cloud-samples-data/language/classify-entertainment.txt'

    # Available types: PLAIN_TEXT, HTML
    type_ = language_v1.Document.Type.PLAIN_TEXT

    # Optional. If not specified, the language is automatically detected.
    # For list of supported languages:
    # https://cloud.google.com/natural-language/docs/languages
    language = "en"
    document = {
        "gcs_content_uri": gcs_content_uri,
        "type_": type_,
        "language": language,
    }

    response = client.classify_text(request={"document": document})
    # Loop through classified categories returned from the API
    for category in response.categories:
        # Get the name of the category representing the document.
        # See the predefined taxonomy of categories:
        # https://cloud.google.com/natural-language/docs/categories
        print(f"Category name: {category.name}")
        # Get the confidence. Number representing how certain the classifier
        # is that this category represents the provided text.
        print(f"Confidence: {category.confidence}")

Nächste Schritte

Informationen zum Suchen und Filtern von Codebeispielen für andere Google Cloud-Produkte finden Sie im Google Cloud-Beispielbrowser.