Examples with LocationName com.google.cloud.tasks.v2.LocationName used on opensource projects

Example 21 with LocationName

use of com.google.cloud.tasks.v2.LocationName in project java-automl by googleapis.

the class ModelApi method createModel.

// [START automl_vision_create_model]
/**
 * Demonstrates using the AutoML client to create a model.
 *
 * @param projectId the Id of the project.
 * @param computeRegion the Region name.
 * @param dataSetId the Id of the dataset to which model is created.
 * @param modelName the Name of the model.
 * @param trainBudget the Budget for training the model.
 */
static void createModel(String projectId, String computeRegion, String dataSetId, String modelName, String trainBudget) {
    // Instantiates a client
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, computeRegion);
        // Set model metadata.
        ImageClassificationModelMetadata imageClassificationModelMetadata = Long.valueOf(trainBudget) == 0 ? ImageClassificationModelMetadata.newBuilder().build() : ImageClassificationModelMetadata.newBuilder().setTrainBudget(Long.valueOf(trainBudget)).build();
        // Set model name and model metadata for the image dataset.
        Model myModel = Model.newBuilder().setDisplayName(modelName).setDatasetId(dataSetId).setImageClassificationModelMetadata(imageClassificationModelMetadata).build();
        // Create a model with the model metadata in the region.
        OperationFuture<Model, OperationMetadata> response = client.createModelAsync(projectLocation, myModel);
        System.out.println(String.format("Training operation name: %s", response.getInitialFuture().get().getName()));
        System.out.println("Training started...");
    } catch (IOException | ExecutionException | InterruptedException e) {
        e.printStackTrace();
    }
}

Example 22 with LocationName

use of com.google.cloud.tasks.v2.LocationName in project java-automl by googleapis.

the class ListDatasets method listDatasets.

// List the datasets
static void listDatasets(String projectId) throws IOException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, "us-central1");
        ListDatasetsRequest request = ListDatasetsRequest.newBuilder().setParent(projectLocation.toString()).build();
        // List all the datasets available in the region by applying filter.
        System.out.println("List of datasets:");
        for (Dataset dataset : client.listDatasets(request).iterateAll()) {
            // Display the dataset information
            System.out.format("%nDataset name: %s%n", dataset.getName());
            // To get the dataset id, you have to parse it out of the `name` field. As dataset Ids are
            // required for other methods.
            // Name Form: `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`
            String[] names = dataset.getName().split("/");
            String retrievedDatasetId = names[names.length - 1];
            System.out.format("Dataset id: %s%n", retrievedDatasetId);
            System.out.format("Dataset display name: %s%n", dataset.getDisplayName());
            System.out.println("Dataset create time:");
            System.out.format("\tseconds: %s%n", dataset.getCreateTime().getSeconds());
            System.out.format("\tnanos: %s%n", dataset.getCreateTime().getNanos());
            // [END automl_video_object_tracking_list_datasets_beta]
            // [END automl_tables_list_datasets]
            System.out.format("Video classification dataset metadata: %s%n", dataset.getVideoClassificationDatasetMetadata());
            // [END automl_video_classification_list_datasets_beta]
            // [START automl_video_object_tracking_list_datasets_beta]
            System.out.format("Video object tracking dataset metadata: %s%n", dataset.getVideoObjectTrackingDatasetMetadata());
            // [END automl_video_object_tracking_list_datasets_beta]
            // [START automl_tables_list_datasets]
            System.out.format("Tables dataset metadata: %s%n", dataset.getTablesDatasetMetadata());
        // [START automl_video_classification_list_datasets_beta]
        // [START automl_video_object_tracking_list_datasets_beta]
        }
    }
}

Example 23 with LocationName

use of com.google.cloud.tasks.v2.LocationName in project java-automl by googleapis.

the class LanguageEntityExtractionCreateModel method createModel.

// Create a model
static void createModel(String projectId, String datasetId, String displayName) throws IOException, ExecutionException, InterruptedException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, "us-central1");
        // Set model metadata.
        TextExtractionModelMetadata metadata = TextExtractionModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextExtractionModelMetadata(metadata).build();
        // Create a model with the model metadata in the region.
        OperationFuture<Model, OperationMetadata> future = client.createModelAsync(projectLocation, model);
        // OperationFuture.get() will block until the model is created, which may take several hours.
        // You can use OperationFuture.getInitialFuture to get a future representing the initial
        // response to the request, which contains information while the operation is in progress.
        System.out.format("Training operation name: %s\n", future.getInitialFuture().get().getName());
        System.out.println("Training started...");
    }
}

Example 24 with LocationName

use of com.google.cloud.tasks.v2.LocationName in project java-automl by googleapis.

the class LanguageSentimentAnalysisCreateDataset method createDataset.

// Create a dataset
static void createDataset(String projectId, String displayName) throws IOException, ExecutionException, InterruptedException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, "us-central1");
        // Specify the text classification type for the dataset.
        TextSentimentDatasetMetadata metadata = TextSentimentDatasetMetadata.newBuilder().setSentimentMax(// Possible max sentiment score: 1-10
        4).build();
        Dataset dataset = Dataset.newBuilder().setDisplayName(displayName).setTextSentimentDatasetMetadata(metadata).build();
        OperationFuture<Dataset, OperationMetadata> future = client.createDatasetAsync(projectLocation, dataset);
        Dataset createdDataset = future.get();
        // Display the dataset information.
        System.out.format("Dataset name: %s\n", createdDataset.getName());
        // To get the dataset id, you have to parse it out of the `name` field. As dataset Ids are
        // required for other methods.
        // Name Form: `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`
        String[] names = createdDataset.getName().split("/");
        String datasetId = names[names.length - 1];
        System.out.format("Dataset id: %s\n", datasetId);
    }
}

Example 25 with LocationName

use of com.google.cloud.tasks.v2.LocationName in project java-automl by googleapis.

the class LanguageTextClassificationCreateModel method createModel.

// Create a model
static void createModel(String projectId, String datasetId, String displayName) throws IOException, ExecutionException, InterruptedException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, "us-central1");
        // Set model metadata.
        TextClassificationModelMetadata metadata = TextClassificationModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextClassificationModelMetadata(metadata).build();
        // Create a model with the model metadata in the region.
        OperationFuture<Model, OperationMetadata> future = client.createModelAsync(projectLocation, model);
        // OperationFuture.get() will block until the model is created, which may take several hours.
        // You can use OperationFuture.getInitialFuture to get a future representing the initial
        // response to the request, which contains information while the operation is in progress.
        System.out.format("Training operation name: %s\n", future.getInitialFuture().get().getName());
        System.out.println("Training started...");
    }
}