use of com.google.cloudbuild.v1.LocationName 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_video_object_tracking_list_datasets_beta]
// [END automl_tables_list_datasets]
System.out.format("Video classification dataset metadata: %s%n", dataset.getVideoClassificationDatasetMetadata());
// [END automl_video_classification_list_datasets_beta]
// [START automl_video_object_tracking_list_datasets_beta]
System.out.format("Video object tracking dataset metadata: %s%n", dataset.getVideoObjectTrackingDatasetMetadata());
// [END automl_video_object_tracking_list_datasets_beta]
// [START automl_tables_list_datasets]
System.out.format("Tables dataset metadata: %s%n", dataset.getTablesDatasetMetadata());
// [START automl_video_classification_list_datasets_beta]
// [START automl_video_object_tracking_list_datasets_beta]
}
}
}
use of com.google.cloudbuild.v1.LocationName in project java-automl by googleapis.
the class LanguageEntityExtractionCreateModel method createModel.
// Create a model
static void createModel(String projectId, String datasetId, String displayName) throws IOException, ExecutionException, InterruptedException {
// 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");
// Set model metadata.
TextExtractionModelMetadata metadata = TextExtractionModelMetadata.newBuilder().build();
Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextExtractionModelMetadata(metadata).build();
// Create a model with the model metadata in the region.
OperationFuture<Model, OperationMetadata> future = client.createModelAsync(projectLocation, model);
// OperationFuture.get() will block until the model is created, which may take several hours.
// You can use OperationFuture.getInitialFuture to get a future representing the initial
// response to the request, which contains information while the operation is in progress.
System.out.format("Training operation name: %s\n", future.getInitialFuture().get().getName());
System.out.println("Training started...");
}
}
use of com.google.cloudbuild.v1.LocationName in project java-automl by googleapis.
the class LanguageSentimentAnalysisCreateDataset method createDataset.
// Create a dataset
static void createDataset(String projectId, String displayName) throws IOException, ExecutionException, InterruptedException {
// 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");
// Specify the text classification type for the dataset.
TextSentimentDatasetMetadata metadata = TextSentimentDatasetMetadata.newBuilder().setSentimentMax(// Possible max sentiment score: 1-10
4).build();
Dataset dataset = Dataset.newBuilder().setDisplayName(displayName).setTextSentimentDatasetMetadata(metadata).build();
OperationFuture<Dataset, OperationMetadata> future = client.createDatasetAsync(projectLocation, dataset);
Dataset createdDataset = future.get();
// Display the dataset information.
System.out.format("Dataset name: %s\n", createdDataset.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 = createdDataset.getName().split("/");
String datasetId = names[names.length - 1];
System.out.format("Dataset id: %s\n", datasetId);
}
}
use of com.google.cloudbuild.v1.LocationName in project java-automl by googleapis.
the class LanguageTextClassificationCreateModel method createModel.
// Create a model
static void createModel(String projectId, String datasetId, String displayName) throws IOException, ExecutionException, InterruptedException {
// 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");
// Set model metadata.
TextClassificationModelMetadata metadata = TextClassificationModelMetadata.newBuilder().build();
Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextClassificationModelMetadata(metadata).build();
// Create a model with the model metadata in the region.
OperationFuture<Model, OperationMetadata> future = client.createModelAsync(projectLocation, model);
// OperationFuture.get() will block until the model is created, which may take several hours.
// You can use OperationFuture.getInitialFuture to get a future representing the initial
// response to the request, which contains information while the operation is in progress.
System.out.format("Training operation name: %s\n", future.getInitialFuture().get().getName());
System.out.println("Training started...");
}
}
use of com.google.cloudbuild.v1.LocationName 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]
}
}
}
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