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

Example 1 with PredictRequest

use of com.google.cloud.automl.v1beta1.PredictRequest 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 2 with PredictRequest

use of com.google.cloud.automl.v1beta1.PredictRequest 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 3 with PredictRequest

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

the class LanguageTextClassificationPredict 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: %.2f\n\n", annotationPayload.getClassification().getScore());
        }
    }
}

Example 4 with PredictRequest

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

the class VisionClassificationPredict method predict.

static void predict(String projectId, String modelId, String filePath) 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);
        ByteString content = ByteString.copyFrom(Files.readAllBytes(Paths.get(filePath)));
        Image image = Image.newBuilder().setImageBytes(content).build();
        ExamplePayload payload = ExamplePayload.newBuilder().setImage(image).build();
        PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).putParams("score_threshold", // [0.0-1.0] Only produce results higher than this value
        "0.8").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 class score: %.2f\n", annotationPayload.getClassification().getScore());
        }
    }
}

Example 5 with PredictRequest

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

the class VisionObjectDetectionPredict method predict.

static void predict(String projectId, String modelId, String filePath) 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);
        ByteString content = ByteString.copyFrom(Files.readAllBytes(Paths.get(filePath)));
        Image image = Image.newBuilder().setImageBytes(content).build();
        ExamplePayload payload = ExamplePayload.newBuilder().setImage(image).build();
        PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).putParams("score_threshold", // [0.0-1.0] Only produce results higher than this value
        "0.5").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 class score: %.2f\n", annotationPayload.getImageObjectDetection().getScore());
            BoundingPoly boundingPoly = annotationPayload.getImageObjectDetection().getBoundingBox();
            System.out.println("Normalized Vertices:");
            for (NormalizedVertex vertex : boundingPoly.getNormalizedVerticesList()) {
                System.out.format("\tX: %.2f, Y: %.2f\n", vertex.getX(), vertex.getY());
            }
        }
    }
}