Examples with GcsSource com.google.cloud.aiplatform.v1.GcsSource used on opensource projects

Example 41 with GcsSource

use of com.google.cloud.aiplatform.v1.GcsSource in project java-aiplatform by googleapis.

the class CreateBatchPredictionJobTextEntityExtractionSample method createBatchPredictionJobTextEntityExtractionSample.

static void createBatchPredictionJobTextEntityExtractionSample(String project, String location, String displayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix) throws IOException {
    // The AI Platform services require regional API endpoints.
    JobServiceSettings settings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient client = JobServiceClient.create(settings)) {
        try {
            String modelName = ModelName.of(project, location, modelId).toString();
            GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
            BatchPredictionJob.InputConfig inputConfig = BatchPredictionJob.InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
            GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
            BatchPredictionJob.OutputConfig outputConfig = BatchPredictionJob.OutputConfig.newBuilder().setPredictionsFormat("jsonl").setGcsDestination(gcsDestination).build();
            BatchPredictionJob batchPredictionJob = BatchPredictionJob.newBuilder().setDisplayName(displayName).setModel(modelName).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
            LocationName parent = LocationName.of(project, location);
            BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
            System.out.format("response: %s\n", response);
            System.out.format("\tname:%s\n", response.getName());
        } catch (ApiException ex) {
            System.out.format("Exception: %s\n", ex.getLocalizedMessage());
        }
    }
}

Example 42 with GcsSource

use of com.google.cloud.aiplatform.v1.GcsSource in project java-aiplatform by googleapis.

the class CreateBatchPredictionJobVideoActionRecognitionSample method createBatchPredictionJobVideoActionRecognitionSample.

static void createBatchPredictionJobVideoActionRecognitionSample(String project, String displayName, String model, String gcsSourceUri, String gcsDestinationOutputUriPrefix) throws IOException {
    JobServiceSettings settings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    String location = "us-central1";
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient client = JobServiceClient.create(settings)) {
        Value modelParameters = ValueConverter.EMPTY_VALUE;
        GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
        BatchPredictionJob.InputConfig inputConfig = BatchPredictionJob.InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
        BatchPredictionJob.OutputConfig outputConfig = BatchPredictionJob.OutputConfig.newBuilder().setPredictionsFormat("jsonl").setGcsDestination(gcsDestination).build();
        String modelName = ModelName.of(project, location, model).toString();
        BatchPredictionJob batchPredictionJob = BatchPredictionJob.newBuilder().setDisplayName(displayName).setModel(modelName).setModelParameters(modelParameters).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
        LocationName parent = LocationName.of(project, location);
        BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
        System.out.format("response: %s\n", response);
        System.out.format("\tName: %s\n", response.getName());
    }
}

Example 43 with GcsSource

use of com.google.cloud.aiplatform.v1.GcsSource in project java-datalabeling by googleapis.

the class LabelTextIT method setUp.

@Before
public void setUp() {
    System.setOut(new PrintStream(new ByteArrayOutputStream()));
    try (DataLabelingServiceClient dataLabelingServiceClient = DataLabelingServiceClient.create()) {
        // Create the dataset
        CreateDataset.createDataset(PROJECT_ID, datasetName);
        ProjectName projectName = ProjectName.of(PROJECT_ID);
        // Get the Dataset
        ListDatasetsRequest datasetsRequest = ListDatasetsRequest.newBuilder().setParent(projectName.toString()).build();
        ListDatasetsPagedResponse datasetsResponse = dataLabelingServiceClient.listDatasets(datasetsRequest);
        for (Dataset returnedDataset : datasetsResponse.getPage().iterateAll()) {
            if (returnedDataset.getDisplayName().equals("LABEL_TEXT_DATASET_NAME")) {
                dataset = returnedDataset;
            }
        }
        // Import the texts
        GcsSource gcsSource = GcsSource.newBuilder().setInputUri(DATASET_GCS_SOURCE_URI).setMimeType("text/csv").build();
        InputConfig inputConfig = InputConfig.newBuilder().setDataType(// DataTypes: AUDIO, IMAGE, VIDEO, TEXT
        DataType.TEXT).setGcsSource(gcsSource).build();
        ImportDataRequest importDataRequest = ImportDataRequest.newBuilder().setName(dataset.getName()).setInputConfig(inputConfig).build();
        ImportDataOperationResponse response = dataLabelingServiceClient.importDataAsync(importDataRequest).get();
        System.out.format("Imported items: %d\n", response.getImportCount());
        // Create the instruction
        CreateInstruction.createInstruction(PROJECT_ID, INSTRUCTION_GCS_SOURCE_URI);
        // Create the annotation spec set
        CreateAnnotationSpecSet.createAnnotationSpecSet(PROJECT_ID);
        // Get the instruction
        ListInstructionsRequest instructionsRequest = ListInstructionsRequest.newBuilder().setParent(projectName.toString()).build();
        ListInstructionsPagedResponse instructionsResponse = dataLabelingServiceClient.listInstructions(instructionsRequest);
        for (Instruction returnedInstruction : instructionsResponse.getPage().iterateAll()) {
            if (returnedInstruction.getDisplayName().equals("YOUR_INSTRUCTION_DISPLAY_NAME")) {
                instruction = returnedInstruction;
            }
        }
        // Get the annotation spec set
        ListAnnotationSpecSetsRequest annotationRequest = ListAnnotationSpecSetsRequest.newBuilder().setParent(projectName.toString()).build();
        ListAnnotationSpecSetsPagedResponse annotationsResponse = dataLabelingServiceClient.listAnnotationSpecSets(annotationRequest);
        for (AnnotationSpecSet returnedAnnotation : annotationsResponse.getPage().iterateAll()) {
            if (returnedAnnotation.getDisplayName().equals("YOUR_ANNOTATION_SPEC_SET_DISPLAY_NAME")) {
                annotationSpecSet = returnedAnnotation;
            }
        }
    } catch (Exception e) {
        e.printStackTrace();
    }
}

Example 44 with GcsSource

use of com.google.cloud.aiplatform.v1.GcsSource in project google-cloud-java by googleapis.

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 45 with GcsSource

use of com.google.cloud.aiplatform.v1.GcsSource 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());
        }
    }
}