Examples with OperationMetadata com.google.cloud.documentai.v1beta2.OperationMetadata used on opensource projects

Example 26 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata 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");
    }
}

Example 27 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata in project java-automl by googleapis.

the class ClassificationUndeployModel method classificationUndeployModel.

// Deploy a model
static void classificationUndeployModel(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);
        // Build deploy model request.
        UndeployModelRequest undeployModelRequest = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
        // Deploy a model with the deploy model request.
        OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(undeployModelRequest);
        future.get();
        // Display the deployment details of model.
        System.out.println("Model undeploy finished");
    }
}

Example 28 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata in project java-automl by googleapis.

the class ClassificationDeployModel method classificationDeployModel.

// Deploy a model
static void classificationDeployModel(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);
        // Build deploy model request.
        DeployModelRequest deployModelRequest = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
        // Deploy a model with the deploy model request.
        OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(deployModelRequest);
        future.get();
        // Display the deployment details of model.
        System.out.println("Model deployment finished");
    }
}

Example 29 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata in project java-automl by googleapis.

the class VideoObjectTrackingCreateModel 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.
        VideoObjectTrackingModelMetadata metadata = VideoObjectTrackingModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setVideoObjectTrackingModelMetadata(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 30 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata 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);
    }
}