Examples with InputConfig com.google.cloud.documentai.v1beta2.InputConfig used on opensource projects

Example 1 with InputConfig

use of com.google.cloud.documentai.v1beta2.InputConfig in project google-cloud-java by GoogleCloudPlatform.

the class TranslateSnippetsBeta method batchTranslateText.

// [END translate_translate_text_beta]
/**
 * Translates a batch of texts on GCS and stores the result in a GCS location.
 *
 * @param projectId - Id of the project.
 * @param location - location name.
 * @param sourceUri - Google Cloud Storage URI. Location where text is stored.
 * @param destinationUri - Google Cloud Storage URI where result will be stored.
 */
// [START translate_batch_translate_text_beta]
static BatchTranslateResponse batchTranslateText(String projectId, String location, String sourceUri, String destinationUri) {
    try (TranslationServiceClient translationServiceClient = TranslationServiceClient.create()) {
        LocationName locationName = LocationName.newBuilder().setProject(projectId).setLocation(location).build();
        GcsSource gcsSource = GcsSource.newBuilder().setInputUri(sourceUri).build();
        InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).setMimeType("text/plain").build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(destinationUri).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).build();
        BatchTranslateTextRequest batchTranslateTextRequest = BatchTranslateTextRequest.newBuilder().setParent(locationName.toString()).setSourceLanguageCode("en").addTargetLanguageCodes("sr").addInputConfigs(inputConfig).setOutputConfig(outputConfig).build();
        // Call the API
        BatchTranslateResponse response = translationServiceClient.batchTranslateTextAsync(batchTranslateTextRequest).get(300, TimeUnit.SECONDS);
        System.out.printf("Total Characters: %d\n", response.getTotalCharacters());
        System.out.printf("Translated Characters: %d\n", response.getTranslatedCharacters());
        return response;
    } catch (Exception e) {
        throw new RuntimeException("Couldn't create client.", e);
    }
}

Example 2 with InputConfig

use of com.google.cloud.documentai.v1beta2.InputConfig in project spring-cloud-gcp by spring-cloud.

the class DocumentOcrTemplate method runOcrForDocument.

/**
 * Runs OCR processing for a specified {@code document} and generates OCR output files
 * under the path specified by {@code outputFilePathPrefix}.
 *
 * <p>
 * For example, if you specify an {@code outputFilePathPrefix} of
 * "gs://bucket_name/ocr_results/myDoc_", all the output files of OCR processing will be
 * saved under prefix, such as:
 *
 * <ul>
 * <li>gs://bucket_name/ocr_results/myDoc_output-1-to-5.json
 * <li>gs://bucket_name/ocr_results/myDoc_output-6-to-10.json
 * <li>gs://bucket_name/ocr_results/myDoc_output-11-to-15.json
 * </ul>
 *
 * <p>
 * Note: OCR processing operations may take several minutes to complete, so it may not be
 * advisable to block on the completion of the operation. One may use the returned
 * {@link ListenableFuture} to register callbacks or track the status of the operation.
 *
 * @param document The {@link GoogleStorageLocation} of the document to run OCR processing
 * @param outputFilePathPrefix The {@link GoogleStorageLocation} of a file, folder, or a
 *     bucket describing the path for which all output files shall be saved under
 *
 * @return A {@link ListenableFuture} allowing you to register callbacks or wait for the
 * completion of the operation.
 */
public ListenableFuture<DocumentOcrResultSet> runOcrForDocument(GoogleStorageLocation document, GoogleStorageLocation outputFilePathPrefix) {
    Assert.isTrue(document.isFile(), "Provided document location is not a valid file location: " + document);
    GcsSource gcsSource = GcsSource.newBuilder().setUri(document.uriString()).build();
    String contentType = extractContentType(document);
    InputConfig inputConfig = InputConfig.newBuilder().setMimeType(contentType).setGcsSource(gcsSource).build();
    GcsDestination gcsDestination = GcsDestination.newBuilder().setUri(outputFilePathPrefix.uriString()).build();
    OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).setBatchSize(this.jsonOutputBatchSize).build();
    AsyncAnnotateFileRequest request = AsyncAnnotateFileRequest.newBuilder().addFeatures(DOCUMENT_OCR_FEATURE).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
    OperationFuture<AsyncBatchAnnotateFilesResponse, OperationMetadata> result = imageAnnotatorClient.asyncBatchAnnotateFilesAsync(Collections.singletonList(request));
    return extractOcrResultFuture(result);
}

Example 3 with InputConfig

use of com.google.cloud.documentai.v1beta2.InputConfig in project java-translate by googleapis.

the class BatchTranslateTextWithGlossaryAndModel method batchTranslateTextWithGlossaryAndModel.

// Batch translate text with Model and Glossary
public static void batchTranslateTextWithGlossaryAndModel(String projectId, String sourceLanguage, String targetLanguage, String inputUri, String outputUri, String glossaryId, String modelId) throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (TranslationServiceClient client = TranslationServiceClient.create()) {
        // Supported Locations: `global`, [glossary location], or [model location]
        // Glossaries must be hosted in `us-central1`
        // Custom Models must use the same location as your model. (us-central1)
        String location = "us-central1";
        LocationName parent = LocationName.of(projectId, location);
        // Configure the source of the file from a GCS bucket
        GcsSource gcsSource = GcsSource.newBuilder().setInputUri(inputUri).build();
        // Supported Mime Types: https://cloud.google.com/translate/docs/supported-formats
        InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).setMimeType("text/plain").build();
        // Configure where to store the output in a GCS bucket
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(outputUri).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).build();
        // Configure the glossary used in the request
        GlossaryName glossaryName = GlossaryName.of(projectId, location, glossaryId);
        TranslateTextGlossaryConfig glossaryConfig = TranslateTextGlossaryConfig.newBuilder().setGlossary(glossaryName.toString()).build();
        // Configure the model used in the request
        String modelPath = String.format("projects/%s/locations/%s/models/%s", projectId, location, modelId);
        // Build the request that will be sent to the API
        BatchTranslateTextRequest request = BatchTranslateTextRequest.newBuilder().setParent(parent.toString()).setSourceLanguageCode(sourceLanguage).addTargetLanguageCodes(targetLanguage).addInputConfigs(inputConfig).setOutputConfig(outputConfig).putGlossaries(targetLanguage, glossaryConfig).putModels(targetLanguage, modelPath).build();
        // Start an asynchronous request
        OperationFuture<BatchTranslateResponse, BatchTranslateMetadata> future = client.batchTranslateTextAsync(request);
        System.out.println("Waiting for operation to complete...");
        // random number between 300 - 450 (maximum allowed seconds)
        long randomNumber = ThreadLocalRandom.current().nextInt(450, 600);
        BatchTranslateResponse response = future.get(randomNumber, TimeUnit.SECONDS);
        // Display the translation for each input text provided
        System.out.printf("Total Characters: %s\n", response.getTotalCharacters());
        System.out.printf("Translated Characters: %s\n", response.getTranslatedCharacters());
    }
}

Example 4 with InputConfig

use of com.google.cloud.documentai.v1beta2.InputConfig in project java-translate by googleapis.

the class BatchTranslateTextWithGlossary method batchTranslateTextWithGlossary.

// Batch Translate Text with a Glossary.
public static void batchTranslateTextWithGlossary(String projectId, String sourceLanguage, String targetLanguage, String inputUri, String outputUri, String glossaryId) throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (TranslationServiceClient client = TranslationServiceClient.create()) {
        // Supported Locations: `global`, [glossary location], or [model location]
        // Glossaries must be hosted in `us-central1`
        // Custom Models must use the same location as your model. (us-central1)
        String location = "us-central1";
        LocationName parent = LocationName.of(projectId, location);
        // Configure the source of the file from a GCS bucket
        GcsSource gcsSource = GcsSource.newBuilder().setInputUri(inputUri).build();
        // Supported Mime Types: https://cloud.google.com/translate/docs/supported-formats
        InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).setMimeType("text/plain").build();
        // Configure where to store the output in a GCS bucket
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(outputUri).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).build();
        // Configure the glossary used in the request
        GlossaryName glossaryName = GlossaryName.of(projectId, location, glossaryId);
        TranslateTextGlossaryConfig glossaryConfig = TranslateTextGlossaryConfig.newBuilder().setGlossary(glossaryName.toString()).build();
        // Build the request that will be sent to the API
        BatchTranslateTextRequest request = BatchTranslateTextRequest.newBuilder().setParent(parent.toString()).setSourceLanguageCode(sourceLanguage).addTargetLanguageCodes(targetLanguage).addInputConfigs(inputConfig).setOutputConfig(outputConfig).putGlossaries(targetLanguage, glossaryConfig).build();
        // Start an asynchronous request
        OperationFuture<BatchTranslateResponse, BatchTranslateMetadata> future = client.batchTranslateTextAsync(request);
        System.out.println("Waiting for operation to complete...");
        // random number between 300 - 450 (maximum allowed seconds)
        long randomNumber = ThreadLocalRandom.current().nextInt(450, 600);
        BatchTranslateResponse response = future.get(randomNumber, TimeUnit.SECONDS);
        // Display the translation for each input text provided
        System.out.printf("Total Characters: %s\n", response.getTotalCharacters());
        System.out.printf("Translated Characters: %s\n", response.getTranslatedCharacters());
    }
}

Example 5 with InputConfig

use of com.google.cloud.documentai.v1beta2.InputConfig in project java-automl by googleapis.

the class ImportDataset method importDataset.

// Import a dataset
static void importDataset(String projectId, String datasetId, String path) throws IOException, ExecutionException, InterruptedException, TimeoutException {
    Duration totalTimeout = Duration.ofMinutes(45);
    RetrySettings retrySettings = RetrySettings.newBuilder().setTotalTimeout(totalTimeout).build();
    AutoMlSettings.Builder builder = AutoMlSettings.newBuilder();
    builder.importDataSettings().setRetrySettings(retrySettings).build();
    AutoMlSettings settings = builder.build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create(settings)) {
        // Get the complete path of the dataset.
        DatasetName datasetFullId = DatasetName.of(projectId, "us-central1", datasetId);
        // Get multiple Google Cloud Storage URIs to import data from
        GcsSource gcsSource = GcsSource.newBuilder().addAllInputUris(Arrays.asList(path.split(","))).build();
        // Import data from the input URI
        InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).build();
        System.out.println("Processing import...");
        // Start the import job
        OperationFuture<Empty, OperationMetadata> operation = client.importDataAsync(datasetFullId, inputConfig);
        System.out.format("Operation name: %s%n", operation.getName());
        // If you want to wait for the operation to finish, adjust the timeout appropriately. The
        // operation will still run if you choose not to wait for it to complete. You can check the
        // status of your operation using the operation's name.
        Empty response = operation.get(45, TimeUnit.MINUTES);
        System.out.format("Dataset imported. %s%n", response);
    } catch (TimeoutException e) {
        System.out.println("The operation's polling period was not long enough.");
        System.out.println("You can use the Operation's name to get the current status.");
        System.out.println("The import job is still running and will complete as expected.");
        throw e;
    }
}