Cloud Storage ファイルのコンテンツの分類

コレクションでコンテンツを整理 必要に応じて、コンテンツの保存と分類を行います。

Google Cloud Storage に保存されているファイルを分析し、ドキュメント内で検出されたテキストに適用されるコンテンツ カテゴリのリストを返します。

もっと見る

このコードサンプルを含む詳細なドキュメントについては、以下をご覧ください。

コードサンプル

Go


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.v1.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

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

/**
 * @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
    $response = $languageServiceClient->classifyText($document);
    $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("Category name: {}".format(category.name))
        # Get the confidence. Number representing how certain the classifier
        # is that this category represents the provided text.
        print("Confidence: {}".format(category.confidence))

次のステップ

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