use of com.google.cloud.automl.v1.AutoMlClient in project java-automl by googleapis.
the class VisionObjectDetectionPredictTest method setUp.
@Before
public void setUp() throws IOException, ExecutionException, InterruptedException {
// Verify that the model is deployed for prediction
try (AutoMlClient client = AutoMlClient.create()) {
ModelName modelFullId = ModelName.of(PROJECT_ID, "us-central1", MODEL_ID);
Model model = client.getModel(modelFullId);
if (model.getDeploymentState() == Model.DeploymentState.UNDEPLOYED) {
// Deploy the model if not deployed
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
client.deployModelAsync(request).get();
}
}
bout = new ByteArrayOutputStream();
out = new PrintStream(bout);
originalPrintStream = System.out;
System.setOut(out);
}
use of com.google.cloud.automl.v1.AutoMlClient in project java-automl by googleapis.
the class PredictionApiIT method setUp.
@Before
public void setUp() throws IOException, ExecutionException, InterruptedException, TimeoutException {
// Verify that the model is deployed for prediction
try (AutoMlClient client = AutoMlClient.create()) {
ModelName modelFullId = ModelName.of(PROJECT_ID, "us-central1", modelId);
Model model = client.getModel(modelFullId);
if (model.getDeploymentState() == Model.DeploymentState.UNDEPLOYED) {
// Deploy the model if not deployed
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
Future future = client.deployModelAsync(request);
future.get(30, TimeUnit.MINUTES);
}
}
bout = new ByteArrayOutputStream();
out = new PrintStream(bout);
originalPrintStream = System.out;
System.setOut(out);
}
use of com.google.cloud.automl.v1.AutoMlClient in project java-automl by googleapis.
the class PredictionApiIT method setUp.
@Before
public void setUp() throws IOException, ExecutionException, InterruptedException, TimeoutException {
// Verify that the model is deployed for prediction
try (AutoMlClient client = AutoMlClient.create()) {
ModelName modelFullId = ModelName.of(PROJECT_ID, "us-central1", modelId);
Model model = client.getModel(modelFullId);
if (model.getDeploymentState() == Model.DeploymentState.UNDEPLOYED) {
// Deploy the model if not deployed
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
Future future = client.deployModelAsync(request);
future.get(30, TimeUnit.MINUTES);
}
}
bout = new ByteArrayOutputStream();
out = new PrintStream(bout);
System.setOut(out);
}
use of com.google.cloud.automl.v1.AutoMlClient 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.automl.v1.AutoMlClient in project java-automl by googleapis.
the class VisionObjectDetectionDeployModelNodeCount method visionObjectDetectionDeployModelNodeCount.
// Deploy a model for prediction with a specified node count (can be used to redeploy a model)
static void visionObjectDetectionDeployModelNodeCount(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
ImageObjectDetectionModelDeploymentMetadata metadata = ImageObjectDetectionModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).setImageObjectDetectionModelDeploymentMetadata(metadata).build();
OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
future.get();
System.out.println("Model deployment finished");
}
}
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