Examples with AutoMlClient com.google.cloud.automl.v1.AutoMlClient used on opensource projects

Example 1 with AutoMlClient

use of com.google.cloud.automl.v1.AutoMlClient in project java-automl by googleapis.

the class CancelOperation method cancelOperation.

static void cancelOperation(String operationFullId) throws IOException, InterruptedException, StatusRuntimeException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
        client.getOperationsClient().cancelOperation(operationFullId);
        System.out.println("Operation cancelled");
    }
}

Example 2 with AutoMlClient

use of com.google.cloud.automl.v1.AutoMlClient in project java-automl by googleapis.

the class DeleteModel method deleteModel.

// Delete a model
static void deleteModel(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);
        // Delete a model.
        Empty response = client.deleteModelAsync(modelFullId).get();
        System.out.println("Model deletion started...");
        System.out.println(String.format("Model deleted. %s", response));
    }
}

Example 3 with AutoMlClient

use of com.google.cloud.automl.v1.AutoMlClient in project java-automl by googleapis.

the class VisionObjectDetectionCreateModel 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.
        ImageObjectDetectionModelMetadata metadata = ImageObjectDetectionModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setImageObjectDetectionModelMetadata(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 4 with AutoMlClient

use of com.google.cloud.automl.v1.AutoMlClient in project java-automl by googleapis.

the class ModelApi method listModels.

// [START automl_translate_list_models]
/**
 * Demonstrates using the AutoML client to list all models.
 *
 * @param projectId the Id of the project.
 * @param computeRegion the Region name.
 * @param filter the filter expression.
 * @throws IOException on Input/Output errors.
 */
public static void listModels(String projectId, String computeRegion, String filter) throws IOException {
    // Instantiates a client
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, computeRegion);
        // Create list models request.
        ListModelsRequest listModlesRequest = ListModelsRequest.newBuilder().setParent(projectLocation.toString()).setFilter(filter).build();
        // List all the models available in the region by applying filter.
        System.out.println("List of models:");
        for (Model model : client.listModels(listModlesRequest).iterateAll()) {
            // Display the model information.
            System.out.println(String.format("Model name: %s", model.getName()));
            System.out.println(String.format("Model id: %s", model.getName().split("/")[model.getName().split("/").length - 1]));
            System.out.println(String.format("Model display name: %s", model.getDisplayName()));
            System.out.println("Model create time:");
            System.out.println(String.format("\tseconds: %s", model.getCreateTime().getSeconds()));
            System.out.println(String.format("\tnanos: %s", model.getCreateTime().getNanos()));
            System.out.println(String.format("Model deployment state: %s", model.getDeploymentState()));
        }
    }
}

Example 5 with AutoMlClient

use of com.google.cloud.automl.v1.AutoMlClient 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();
    }
}