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

Example 56 with Image

use of com.google.cloud.automl.v1.Image 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 57 with Image

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

the class ListDatasets method listDatasets.

// List the datasets
static void listDatasets(String projectId) throws IOException {
    // 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");
        ListDatasetsRequest request = ListDatasetsRequest.newBuilder().setParent(projectLocation.toString()).build();
        // List all the datasets available in the region by applying filter.
        System.out.println("List of datasets:");
        for (Dataset dataset : client.listDatasets(request).iterateAll()) {
            // Display the dataset information
            System.out.format("\nDataset name: %s\n", dataset.getName());
            // To get the dataset id, you have to parse it out of the `name` field. As dataset Ids are
            // required for other methods.
            // Name Form: `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`
            String[] names = dataset.getName().split("/");
            String retrievedDatasetId = names[names.length - 1];
            System.out.format("Dataset id: %s\n", retrievedDatasetId);
            System.out.format("Dataset display name: %s\n", dataset.getDisplayName());
            System.out.println("Dataset create time:");
            System.out.format("\tseconds: %s\n", dataset.getCreateTime().getSeconds());
            System.out.format("\tnanos: %s\n", dataset.getCreateTime().getNanos());
            // [END automl_language_sentiment_analysis_list_datasets]
            // [END automl_language_text_classification_list_datasets]
            // [END automl_translate_list_datasets]
            // [END automl_vision_classification_list_datasets]
            // [END automl_vision_object_detection_list_datasets]
            System.out.format("Text extraction dataset metadata: %s\n", dataset.getTextExtractionDatasetMetadata());
            // [END automl_language_entity_extraction_list_datasets]
            // [START automl_language_sentiment_analysis_list_datasets]
            System.out.format("Text sentiment dataset metadata: %s\n", dataset.getTextSentimentDatasetMetadata());
            // [END automl_language_sentiment_analysis_list_datasets]
            // [START automl_language_text_classification_list_datasets]
            System.out.format("Text classification dataset metadata: %s\n", dataset.getTextClassificationDatasetMetadata());
            // [END automl_language_text_classification_list_datasets]
            // [START automl_translate_list_datasets]
            System.out.println("Translation dataset metadata:");
            System.out.format("\tSource language code: %s\n", dataset.getTranslationDatasetMetadata().getSourceLanguageCode());
            System.out.format("\tTarget language code: %s\n", dataset.getTranslationDatasetMetadata().getTargetLanguageCode());
            // [END automl_translate_list_datasets]
            // [START automl_vision_classification_list_datasets]
            System.out.format("Image classification dataset metadata: %s\n", dataset.getImageClassificationDatasetMetadata());
            // [END automl_vision_classification_list_datasets]
            // [START automl_vision_object_detection_list_datasets]
            System.out.format("Image object detection dataset metadata: %s\n", dataset.getImageObjectDetectionDatasetMetadata());
        // [START automl_language_entity_extraction_list_datasets]
        // [START automl_language_sentiment_analysis_list_datasets]
        // [START automl_language_text_classification_list_datasets]
        // [START automl_translate_list_datasets]
        // [START automl_vision_classification_list_datasets]
        }
    }
}

Example 58 with Image

use of com.google.cloud.automl.v1.Image in project openstack4j by ContainX.

the class ImageV2Tests method testCreateImage.

public void testCreateImage() throws IOException {
    respondWith(IMAGE_JSON);
    String id = "8a2ea42d-06b5-42c2-a54d-97105420f2bb";
    String name = "amphora-x64-haproxy";
    ContainerFormat cf = ContainerFormat.BARE;
    DiskFormat df = DiskFormat.QCOW2;
    Long mindisk = 0L;
    Long minram = 0L;
    Image.ImageVisibility vis = Image.ImageVisibility.PUBLIC;
    String key1 = "test-key1";
    String key2 = "test-key2";
    String key3 = "id";
    String value1 = "test-value1";
    String value2 = "test-value2";
    String value3 = "test-value3";
    Image im = Builders.imageV2().id(id).name(name).containerFormat(cf).diskFormat(df).minDisk(mindisk).minRam(minram).visibility(vis).additionalProperty(key1, value1).additionalProperty(key2, value2).additionalProperty(key3, value3).build();
    Image image = osv3().imagesV2().create(im);
    assertNotNull(image);
    assertEquals(image.getId(), id);
    assertEquals(image.getName(), name);
    assertEquals(image.getContainerFormat(), cf);
    assertEquals(image.getDiskFormat(), df);
    assertEquals(image.getVisibility(), vis);
    assertEquals(image.getMinDisk(), mindisk);
    assertEquals(image.getMinRam(), minram);
    assertEquals(image.getAdditionalPropertyValue(key1), value1);
    assertEquals(image.getAdditionalPropertyValue(key2), value2);
    assertNull(image.getAdditionalPropertyValue(key3));
}

Example 59 with Image

use of com.google.cloud.automl.v1.Image in project openstack4j by ContainX.

the class ImageV2Tests method testGetImageWithLocations.

public void testGetImageWithLocations() throws IOException {
    respondWith(IMAGE_WIHT_LOCATION_JSON);
    String id = "c73056d6-c583-4d6c-9f70-04f3bfd8dff4";
    Image image = osv3().imagesV2().get(id);
    assertNotNull(image);
    assertNotNull(image.getId());
    assertEquals(image.getId(), id);
    assertEquals(2, image.getLocations().size());
}

Example 60 with Image

use of com.google.cloud.automl.v1.Image in project openstack4j by ContainX.

the class ImageServiceImpl method update.

/**
 * {@inheritDoc}
 */
@Override
public Image update(Image image) {
    checkNotNull(image);
    ObjectMapper objectMapper = new ObjectMapper();
    Image origImage = get(image.getId());
    ObjectNode origJson;
    ObjectNode newJson;
    try {
        String oImg = objectMapper.writeValueAsString(origImage);
        origJson = (ObjectNode) objectMapper.readTree(oImg);
        String img = objectMapper.writeValueAsString(image);
        newJson = (ObjectNode) objectMapper.readTree(img);
        JsonNode jsonDiff = JsonDiff.asJson(origJson, newJson);
        GlanceImageUpdate giu = new GlanceImageUpdate(jsonDiff);
        return update(image.getId(), giu);
    } catch (IOException e) {
        e.printStackTrace();
        return null;
    }
}