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

Example 6 with ModelName

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

the class UndeployModel method undeployModel.

// Undeploy a model from prediction
static void undeployModel(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);
        UndeployModelRequest request = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
        OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(request);
        future.get();
        System.out.println("Model undeployment finished");
    }
}

Example 7 with ModelName

use of com.google.cloud.automl.v1.ModelName 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 8 with ModelName

use of com.google.cloud.automl.v1.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 9 with ModelName

use of com.google.cloud.automl.v1.ModelName 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 10 with ModelName

use of com.google.cloud.automl.v1.ModelName 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");
    }
}