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

Example 46 with Model

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

the class TablesGetModel method getModel.

// Demonstrates using the AutoML client to get model details.
public static void getModel(String projectId, String computeRegion, String modelId) throws IOException, StatusRuntimeException {
    // 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, computeRegion, modelId);
        // Get complete detail of the model.
        Model model = client.getModel(modelFullId);
        // Display the model information.
        System.out.format("Model name: %s%n", model.getName());
        System.out.format("Model Id: %s\n", model.getName().split("/")[model.getName().split("/").length - 1]);
        System.out.format("Model display name: %s%n", model.getDisplayName());
        System.out.format("Dataset Id: %s%n", model.getDatasetId());
        System.out.println("Tables Model Metadata: ");
        System.out.format("\tTraining budget: %s%n", model.getTablesModelMetadata().getTrainBudgetMilliNodeHours());
        System.out.format("\tTraining cost: %s%n", model.getTablesModelMetadata().getTrainBudgetMilliNodeHours());
        DateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSSZ");
        String createTime = dateFormat.format(new java.util.Date(model.getCreateTime().getSeconds() * 1000));
        System.out.format("Model create time: %s%n", createTime);
        System.out.format("Model deployment state: %s%n", model.getDeploymentState());
        // Get features of top importance
        for (TablesModelColumnInfo info : model.getTablesModelMetadata().getTablesModelColumnInfoList()) {
            System.out.format("Column: %s - Importance: %.2f%n", info.getColumnDisplayName(), info.getFeatureImportance());
        }
    }
}

Example 47 with Model

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

the class LanguageEntityExtractionCreateModel 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.
        TextExtractionModelMetadata metadata = TextExtractionModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextExtractionModelMetadata(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 48 with Model

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

the class LanguageEntityExtractionPredict method predict.

static void predict(String projectId, String modelId, String content) throws IOException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient client = PredictionServiceClient.create()) {
        // Get the full path of the model.
        ModelName name = ModelName.of(projectId, "us-central1", modelId);
        // For available mime types, see:
        // https://cloud.google.com/automl/docs/reference/rest/v1/projects.locations.models/predict#textsnippet
        TextSnippet textSnippet = TextSnippet.newBuilder().setContent(content).setMimeType(// Types: text/plain, text/html
        "text/plain").build();
        ExamplePayload payload = ExamplePayload.newBuilder().setTextSnippet(textSnippet).build();
        PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).build();
        PredictResponse response = client.predict(predictRequest);
        for (AnnotationPayload annotationPayload : response.getPayloadList()) {
            System.out.format("Text Extract Entity Type: %s\n", annotationPayload.getDisplayName());
            System.out.format("Text score: %.2f\n", annotationPayload.getTextExtraction().getScore());
            TextSegment textSegment = annotationPayload.getTextExtraction().getTextSegment();
            System.out.format("Text Extract Entity Content: %s\n", textSegment.getContent());
            System.out.format("Text Start Offset: %s\n", textSegment.getStartOffset());
            System.out.format("Text End Offset: %s\n\n", textSegment.getEndOffset());
        }
    }
}

Example 49 with Model

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

the class LanguageSentimentAnalysisPredict method predict.

static void predict(String projectId, String modelId, String content) throws IOException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient client = PredictionServiceClient.create()) {
        // Get the full path of the model.
        ModelName name = ModelName.of(projectId, "us-central1", modelId);
        // For available mime types, see:
        // https://cloud.google.com/automl/docs/reference/rest/v1/projects.locations.models/predict#textsnippet
        TextSnippet textSnippet = TextSnippet.newBuilder().setContent(content).setMimeType(// Types: text/plain, text/html
        "text/plain").build();
        ExamplePayload payload = ExamplePayload.newBuilder().setTextSnippet(textSnippet).build();
        PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).build();
        PredictResponse response = client.predict(predictRequest);
        for (AnnotationPayload annotationPayload : response.getPayloadList()) {
            System.out.format("Predicted class name: %s\n", annotationPayload.getDisplayName());
            System.out.format("Predicted sentiment score: %d\n", annotationPayload.getTextSentiment().getSentiment());
        }
    }
}

Example 50 with Model

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

the class LanguageTextClassificationCreateModel 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.
        TextClassificationModelMetadata metadata = TextClassificationModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextClassificationModelMetadata(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...");
    }
}