Examples with PredictResponse com.google.cloud.aiplatform.v1.PredictResponse used on opensource projects

Example 1 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-aiplatform by googleapis.

the class PredictCustomTrainedModelSample method predictCustomTrainedModel.

static void predictCustomTrainedModel(String project, String endpointId, String instance) throws IOException {
    PredictionServiceSettings predictionServiceSettings = PredictionServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create(predictionServiceSettings)) {
        String location = "us-central1";
        EndpointName endpointName = EndpointName.of(project, location, endpointId);
        ListValue.Builder listValue = ListValue.newBuilder();
        JsonFormat.parser().merge(instance, listValue);
        List<Value> instanceList = listValue.getValuesList();
        PredictRequest predictRequest = PredictRequest.newBuilder().setEndpoint(endpointName.toString()).addAllInstances(instanceList).build();
        PredictResponse predictResponse = predictionServiceClient.predict(predictRequest);
        System.out.println("Predict Custom Trained model Response");
        System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
        System.out.println("Predictions");
        for (Value prediction : predictResponse.getPredictionsList()) {
            System.out.format("\tPrediction: %s\n", prediction);
        }
    }
}

Example 2 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-aiplatform by googleapis.

the class PredictImageClassificationSample method predictImageClassification.

static void predictImageClassification(String project, String fileName, String endpointId) throws IOException {
    PredictionServiceSettings settings = PredictionServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create(settings)) {
        String location = "us-central1";
        EndpointName endpointName = EndpointName.of(project, location, endpointId);
        byte[] contents = Base64.encodeBase64(Files.readAllBytes(Paths.get(fileName)));
        String content = new String(contents, StandardCharsets.UTF_8);
        ImageClassificationPredictionInstance predictionInstance = ImageClassificationPredictionInstance.newBuilder().setContent(content).build();
        List<Value> instances = new ArrayList<>();
        instances.add(ValueConverter.toValue(predictionInstance));
        ImageClassificationPredictionParams predictionParams = ImageClassificationPredictionParams.newBuilder().setConfidenceThreshold((float) 0.5).setMaxPredictions(5).build();
        PredictResponse predictResponse = predictionServiceClient.predict(endpointName, instances, ValueConverter.toValue(predictionParams));
        System.out.println("Predict Image Classification Response");
        System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
        System.out.println("Predictions");
        for (Value prediction : predictResponse.getPredictionsList()) {
            ClassificationPredictionResult.Builder resultBuilder = ClassificationPredictionResult.newBuilder();
            // Display names and confidences values correspond to
            // IDs in the ID list.
            ClassificationPredictionResult result = (ClassificationPredictionResult) ValueConverter.fromValue(resultBuilder, prediction);
            int counter = 0;
            for (Long id : result.getIdsList()) {
                System.out.printf("Label ID: %d\n", id);
                System.out.printf("Label: %s\n", result.getDisplayNames(counter));
                System.out.printf("Confidence: %.4f\n", result.getConfidences(counter));
                counter++;
            }
        }
    }
}

Example 3 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-aiplatform by googleapis.

the class PredictTabularClassificationSample method predictTabularClassification.

static void predictTabularClassification(String instance, String project, String endpointId) throws IOException {
    PredictionServiceSettings predictionServiceSettings = PredictionServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create(predictionServiceSettings)) {
        String location = "us-central1";
        EndpointName endpointName = EndpointName.of(project, location, endpointId);
        ListValue.Builder listValue = ListValue.newBuilder();
        JsonFormat.parser().merge(instance, listValue);
        List<Value> instanceList = listValue.getValuesList();
        Value parameters = Value.newBuilder().setListValue(listValue).build();
        PredictResponse predictResponse = predictionServiceClient.predict(endpointName, instanceList, parameters);
        System.out.println("Predict Tabular Classification Response");
        System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
        System.out.println("Predictions");
        for (Value prediction : predictResponse.getPredictionsList()) {
            TabularClassificationPredictionResult.Builder resultBuilder = TabularClassificationPredictionResult.newBuilder();
            TabularClassificationPredictionResult result = (TabularClassificationPredictionResult) ValueConverter.fromValue(resultBuilder, prediction);
            for (int i = 0; i < result.getClassesCount(); i++) {
                System.out.printf("\tClass: %s", result.getClasses(i));
                System.out.printf("\tScore: %f", result.getScores(i));
            }
        }
    }
}

Example 4 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse in project java-aiplatform by googleapis.

the class PredictTextSentimentAnalysisSample method predictTextSentimentAnalysis.

static void predictTextSentimentAnalysis(String project, String content, String endpointId) throws IOException {
    PredictionServiceSettings predictionServiceSettings = PredictionServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create(predictionServiceSettings)) {
        String location = "us-central1";
        String jsonString = "{\"content\": \"" + content + "\"}";
        EndpointName endpointName = EndpointName.of(project, location, endpointId);
        Value parameter = Value.newBuilder().setNumberValue(0).setNumberValue(5).build();
        Value.Builder instance = Value.newBuilder();
        JsonFormat.parser().merge(jsonString, instance);
        List<Value> instances = new ArrayList<>();
        instances.add(instance.build());
        PredictResponse predictResponse = predictionServiceClient.predict(endpointName, instances, parameter);
        System.out.println("Predict Text Sentiment Analysis Response");
        System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
        System.out.println("Predictions");
        for (Value prediction : predictResponse.getPredictionsList()) {
            System.out.format("\tPrediction: %s\n", prediction);
        }
    }
}

Example 5 with PredictResponse

use of com.google.cloud.aiplatform.v1.PredictResponse 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());
        }
    }
}