Examples with AutoMlClient com.google.cloud.automl.v1beta1.AutoMlClient used on opensource projects

Example 31 with AutoMlClient

use of com.google.cloud.automl.v1beta1.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);
}

Example 32 with AutoMlClient

use of com.google.cloud.automl.v1beta1.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);
}

Example 33 with AutoMlClient

use of com.google.cloud.automl.v1beta1.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);
}

Example 34 with AutoMlClient

use of com.google.cloud.automl.v1beta1.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);
    }
}

Example 35 with AutoMlClient

use of com.google.cloud.automl.v1beta1.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");
    }
}