use of com.google.cloud.speech.v1p1beta1.LocationName in project java-automl by googleapis.
the class VisionClassificationCreateDataset 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 classification type
// Types:
// MultiLabel: Multiple labels are allowed for one example.
// MultiClass: At most one label is allowed per example.
ClassificationType classificationType = ClassificationType.MULTILABEL;
ImageClassificationDatasetMetadata metadata = ImageClassificationDatasetMetadata.newBuilder().setClassificationType(classificationType).build();
Dataset dataset = Dataset.newBuilder().setDisplayName(displayName).setImageClassificationDatasetMetadata(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);
}
}
use of com.google.cloud.speech.v1p1beta1.LocationName in project java-automl by googleapis.
the class VisionObjectDetectionCreateDataset 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");
ImageObjectDetectionDatasetMetadata metadata = ImageObjectDetectionDatasetMetadata.newBuilder().build();
Dataset dataset = Dataset.newBuilder().setDisplayName(displayName).setImageObjectDetectionDatasetMetadata(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);
}
}
use of com.google.cloud.speech.v1p1beta1.LocationName in project java-automl by googleapis.
the class LanguageSentimentAnalysisCreateModel 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.
System.out.println(datasetId);
TextSentimentModelMetadata metadata = TextSentimentModelMetadata.newBuilder().build();
Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextSentimentModelMetadata(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...");
}
}
use of com.google.cloud.speech.v1p1beta1.LocationName in project java-automl by googleapis.
the class DeleteDatasetTest method setUp.
@Before
public void setUp() throws IOException {
// Create a fake dataset to be deleted
// Create a random dataset name with a length of 32 characters (max allowed by AutoML)
// To prevent name collisions when running tests in multiple java versions at once.
// AutoML doesn't allow "-", but accepts "_"
String datasetName = String.format("test_%s", UUID.randomUUID().toString().replace("-", "_").substring(0, 26));
try (AutoMlClient client = AutoMlClient.create()) {
LocationName projectLocation = LocationName.of(PROJECT_ID, "us-central1");
TextExtractionDatasetMetadata metadata = TextExtractionDatasetMetadata.newBuilder().build();
Dataset dataset = Dataset.newBuilder().setDisplayName(datasetName).setTextExtractionDatasetMetadata(metadata).build();
Dataset createdDataset = client.createDataset(projectLocation, dataset);
String[] names = createdDataset.getName().split("/");
datasetId = names[names.length - 1];
}
bout = new ByteArrayOutputStream();
out = new PrintStream(bout);
originalPrintStream = System.out;
System.setOut(out);
}
use of com.google.cloud.speech.v1p1beta1.LocationName in project java-automl by googleapis.
the class ListModels method listModels.
// List the models available in the specified location
static void listModels(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");
// Create list models request.
ListModelsRequest listModelsRequest = ListModelsRequest.newBuilder().setParent(projectLocation.toString()).setFilter("").build();
// List all the models available in the region by applying filter.
System.out.println("List of models:");
for (Model model : client.listModels(listModelsRequest).iterateAll()) {
// Display the model information.
System.out.format("Model name: %s%n", model.getName());
// To get the model id, you have to parse it out of the `name` field. As models Ids are
// required for other methods.
// Name Format: `projects/{project_id}/locations/{location_id}/models/{model_id}`
String[] names = model.getName().split("/");
String retrievedModelId = names[names.length - 1];
System.out.format("Model id: %s%n", retrievedModelId);
System.out.format("Model display name: %s%n", model.getDisplayName());
System.out.println("Model create time:");
System.out.format("\tseconds: %s%n", model.getCreateTime().getSeconds());
System.out.format("\tnanos: %s%n", model.getCreateTime().getNanos());
System.out.format("Model deployment state: %s%n", model.getDeploymentState());
}
}
}
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