Examples with InputConfig com.google.cloud.automl.v1.InputConfig used on opensource projects

Example 11 with InputConfig

use of com.google.cloud.automl.v1.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());
                            }
                        }
                    }
                }
            }
        }
    }
}

Example 12 with InputConfig

use of com.google.cloud.automl.v1.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));
    }
}

Example 13 with InputConfig

use of com.google.cloud.automl.v1.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());
    }
}

Example 14 with InputConfig

use of com.google.cloud.automl.v1.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());
    }
}

Example 15 with InputConfig

use of com.google.cloud.automl.v1.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());
        }
    }
}