use of com.google.cloud.translate.v3.InputConfig in project java-vision by googleapis.
the class BatchAnnotateFilesGcs method batchAnnotateFilesGcs.
public static void batchAnnotateFilesGcs(String gcsUri) throws IOException {
// the "close" method on the client to safely clean up any remaining background resources.
try (ImageAnnotatorClient imageAnnotatorClient = ImageAnnotatorClient.create()) {
// You can send multiple files to be annotated, this sample demonstrates how to do this with
// one file. If you want to use multiple files, you have to create a `AnnotateImageRequest`
// object for each file that you want annotated.
// First specify where the vision api can find the image
GcsSource gcsSource = GcsSource.newBuilder().setUri(gcsUri).build();
// Specify the input config with the file's uri and its type.
// Supported mime_type: application/pdf, image/tiff, image/gif
// https://cloud.google.com/vision/docs/reference/rpc/google.cloud.vision.v1#inputconfig
InputConfig inputConfig = InputConfig.newBuilder().setMimeType("application/pdf").setGcsSource(gcsSource).build();
// Set the type of annotation you want to perform on the file
// https://cloud.google.com/vision/docs/reference/rpc/google.cloud.vision.v1#google.cloud.vision.v1.Feature.Type
Feature feature = Feature.newBuilder().setType(Feature.Type.DOCUMENT_TEXT_DETECTION).build();
// Build the request object for that one file. Note: for additional file you have to create
// additional `AnnotateFileRequest` objects and store them in a list to be used below.
// Since we are sending a file of type `application/pdf`, we can use the `pages` field to
// specify which pages to process. The service can process up to 5 pages per document file.
// https://cloud.google.com/vision/docs/reference/rpc/google.cloud.vision.v1#google.cloud.vision.v1.AnnotateFileRequest
AnnotateFileRequest fileRequest = AnnotateFileRequest.newBuilder().setInputConfig(inputConfig).addFeatures(feature).addPages(// Process the first page
1).addPages(// Process the second page
2).addPages(// Process the last page
-1).build();
// Add each `AnnotateFileRequest` object to the batch request.
BatchAnnotateFilesRequest request = BatchAnnotateFilesRequest.newBuilder().addRequests(fileRequest).build();
// Make the synchronous batch request.
BatchAnnotateFilesResponse response = imageAnnotatorClient.batchAnnotateFiles(request);
// sample.
for (AnnotateImageResponse imageResponse : response.getResponsesList().get(0).getResponsesList()) {
System.out.format("Full text: %s%n", imageResponse.getFullTextAnnotation().getText());
for (Page page : imageResponse.getFullTextAnnotation().getPagesList()) {
for (Block block : page.getBlocksList()) {
System.out.format("%nBlock confidence: %s%n", block.getConfidence());
for (Paragraph par : block.getParagraphsList()) {
System.out.format("\tParagraph confidence: %s%n", par.getConfidence());
for (Word word : par.getWordsList()) {
System.out.format("\t\tWord confidence: %s%n", word.getConfidence());
for (Symbol symbol : word.getSymbolsList()) {
System.out.format("\t\t\tSymbol: %s, (confidence: %s)%n", symbol.getText(), symbol.getConfidence());
}
}
}
}
}
}
}
}
use of com.google.cloud.translate.v3.InputConfig in project java-automl by googleapis.
the class DatasetApi method importData.
// [START automl_translate_import_data]
/**
* Import sentence pairs to the dataset.
*
* @param projectId the Google Cloud Project ID.
* @param computeRegion the Region name. (e.g., "us-central1").
* @param datasetId the Id of the dataset.
* @param path the remote Path of the training data csv file.
*/
public static void importData(String projectId, String computeRegion, String datasetId, String path) throws IOException, InterruptedException, ExecutionException {
// Instantiates a client
try (AutoMlClient client = AutoMlClient.create()) {
// Get the complete path of the dataset.
DatasetName datasetFullId = DatasetName.of(projectId, computeRegion, datasetId);
GcsSource.Builder gcsSource = GcsSource.newBuilder();
// Get multiple Google Cloud Storage URIs to import data from
String[] inputUris = path.split(",");
for (String inputUri : inputUris) {
gcsSource.addInputUris(inputUri);
}
// Import data from the input URI
InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).build();
System.out.println("Processing import...");
Empty response = client.importDataAsync(datasetFullId, inputConfig).get();
System.out.println(String.format("Dataset imported. %s", response));
}
}
use of com.google.cloud.translate.v3.InputConfig in project java-translate by googleapis.
the class BatchTranslateTextWithModel method batchTranslateTextWithModel.
// Batch translate text using AutoML Translation model
public static void batchTranslateTextWithModel(String projectId, String sourceLanguage, String targetLanguage, String inputUri, String outputUri, 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 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).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());
}
}
use of com.google.cloud.translate.v3.InputConfig in project java-translate by googleapis.
the class BatchTranslateText method batchTranslateText.
// Batch translate text
public static void batchTranslateText(String projectId, String sourceLanguage, String targetLanguage, String inputUri, String outputUri) 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: `us-central1`
LocationName parent = LocationName.of(projectId, "us-central1");
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();
GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(outputUri).build();
OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).build();
BatchTranslateTextRequest request = BatchTranslateTextRequest.newBuilder().setParent(parent.toString()).setSourceLanguageCode(sourceLanguage).addTargetLanguageCodes(targetLanguage).addInputConfigs(inputConfig).setOutputConfig(outputConfig).build();
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);
System.out.printf("Total Characters: %s\n", response.getTotalCharacters());
System.out.printf("Translated Characters: %s\n", response.getTranslatedCharacters());
}
}
use of com.google.cloud.translate.v3.InputConfig in project java-document-ai by googleapis.
the class ParseWithModelBeta method parseWithModel.
public static void parseWithModel(String projectId, String location, String autoMlModel, String gcsUri) throws IOException {
// the "close" method on the client to safely clean up any remaining background resources.
try (DocumentUnderstandingServiceClient client = DocumentUnderstandingServiceClient.create()) {
// Configure the request for processing the PDF
String parent = String.format("projects/%s/locations/%s", projectId, location);
AutoMlParams params = AutoMlParams.newBuilder().setModel(autoMlModel).build();
GcsSource uri = GcsSource.newBuilder().setUri(gcsUri).build();
// mime_type can be application/pdf, image/tiff,
// and image/gif, or application/json
InputConfig config = InputConfig.newBuilder().setGcsSource(uri).setMimeType("application/pdf").build();
ProcessDocumentRequest request = ProcessDocumentRequest.newBuilder().setParent(parent).setAutomlParams(params).setInputConfig(config).build();
// Recognizes text entities in the PDF document
Document response = client.processDocument(request);
// Process the output
for (Document.Label label : response.getLabelsList()) {
System.out.printf("Label detected: %s\n", label.getName());
System.out.printf("Confidence: %s\n", label.getConfidence());
}
}
}
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