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

Example 16 with ModelName

use of com.google.cloud.automl.v1beta1.ModelName in project java-automl by googleapis.

the class PredictionApi method predict.

// [START automl_vision_predict]
/**
 * Demonstrates using the AutoML client to predict an image.
 *
 * @param projectId the Id of the project.
 * @param computeRegion the Region name.
 * @param modelId the Id of the model which will be used for text classification.
 * @param filePath the Local text file path of the content to be classified.
 * @param scoreThreshold the Confidence score. Only classifications with confidence score above
 *     scoreThreshold are displayed.
 */
static void predict(String projectId, String computeRegion, String modelId, String filePath, String scoreThreshold) throws IOException {
    // Instantiate client for prediction service.
    try (PredictionServiceClient predictionClient = PredictionServiceClient.create()) {
        // Get the full path of the model.
        ModelName name = ModelName.of(projectId, computeRegion, modelId);
        // Read the image and assign to payload.
        ByteString content = ByteString.copyFrom(Files.readAllBytes(Paths.get(filePath)));
        Image image = Image.newBuilder().setImageBytes(content).build();
        ExamplePayload examplePayload = ExamplePayload.newBuilder().setImage(image).build();
        // Additional parameters that can be provided for prediction e.g. Score Threshold
        Map<String, String> params = new HashMap<>();
        if (scoreThreshold != null) {
            params.put("score_threshold", scoreThreshold);
        }
        // Perform the AutoML Prediction request
        PredictResponse response = predictionClient.predict(name, examplePayload, params);
        System.out.println("Prediction results:");
        for (AnnotationPayload annotationPayload : response.getPayloadList()) {
            System.out.println("Predicted class name :" + annotationPayload.getDisplayName());
            System.out.println("Predicted class score :" + annotationPayload.getClassification().getScore());
        }
    }
}

Example 17 with ModelName

use of com.google.cloud.automl.v1beta1.ModelName in project java-automl by googleapis.

the class BatchPredict method batchPredict.

static void batchPredict(String projectId, String modelId, String inputUri, String outputUri) throws IOException, ExecutionException, InterruptedException {
    // 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);
        GcsSource gcsSource = GcsSource.newBuilder().addInputUris(inputUri).build();
        BatchPredictInputConfig inputConfig = BatchPredictInputConfig.newBuilder().setGcsSource(gcsSource).build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(outputUri).build();
        BatchPredictOutputConfig outputConfig = BatchPredictOutputConfig.newBuilder().setGcsDestination(gcsDestination).build();
        BatchPredictRequest request = BatchPredictRequest.newBuilder().setName(name.toString()).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
        OperationFuture<BatchPredictResult, OperationMetadata> future = client.batchPredictAsync(request);
        System.out.println("Waiting for operation to complete...");
        BatchPredictResult response = future.get();
        System.out.println("Batch Prediction results saved to specified Cloud Storage bucket.");
    }
}

Example 18 with ModelName

use of com.google.cloud.automl.v1beta1.ModelName in project java-automl by googleapis.

the class DeployModel method deployModel.

// Deploy a model for prediction
static void deployModel(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);
        DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
        OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
        future.get();
        System.out.println("Model deployment finished");
    }
}

Example 19 with ModelName

use of com.google.cloud.automl.v1beta1.ModelName in project java-automl by googleapis.

the class TablesPredictTest 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 20 with ModelName

use of com.google.cloud.automl.v1beta1.ModelName in project java-automl by googleapis.

the class LanguageSentimentAnalysisPredictTest 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);
}