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  • vision/automl/src/main/java/com/google/cloud/vision/samples/automl

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‎vision/automl/src/main/java/com/google/cloud/vision/samples/automl/DatasetApi.java

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/*
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* Copyright 2018 Google LLC.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package com.google.cloud.vision.samples.automl;
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// Imports the Google Cloud client library
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import com.google.cloud.automl.v1beta1.AutoMlClient;
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import com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationType;
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import com.google.cloud.automl.v1beta1.Dataset;
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import com.google.cloud.automl.v1beta1.DatasetName;
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import com.google.cloud.automl.v1beta1.GcsDestination;
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import com.google.cloud.automl.v1beta1.GcsSource;
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import com.google.cloud.automl.v1beta1.ImageClassificationDatasetMetadata;
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import com.google.cloud.automl.v1beta1.InputConfig;
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import com.google.cloud.automl.v1beta1.ListDatasetsRequest;
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import com.google.cloud.automl.v1beta1.LocationName;
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import com.google.cloud.automl.v1beta1.OutputConfig;
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import com.google.protobuf.Empty;
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import java.io.IOException;
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import java.io.PrintStream;
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import net.sourceforge.argparse4j.ArgumentParsers;
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import net.sourceforge.argparse4j.inf.ArgumentParser;
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import net.sourceforge.argparse4j.inf.ArgumentParserException;
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import net.sourceforge.argparse4j.inf.Namespace;
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import net.sourceforge.argparse4j.inf.Subparser;
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import net.sourceforge.argparse4j.inf.Subparsers;
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/**
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* Google Cloud AutoML Vision API sample application. Example usage: mvn package exec:java
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* -Dexec.mainClass ='com.google.cloud.vision.samples.automl.DatasetAPI' -Dexec.args='create_dataset
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* test_dataset'
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*/
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public class DatasetApi {
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// [START automl_vision_create_dataset]
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/**
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* Demonstrates using the AutoML client to create a dataset
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*
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* @param projectId the Google Cloud Project ID.
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* @param computeRegion the Region name. (e.g., "us-central1")
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* @param datasetName the name of the dataset to be created.
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* @param multiLabel the type of classification problem. Set to FALSE by default.
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* @throws IOException on Input/Output errors.
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*/
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public static void createDataset(
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String projectId, String computeRegion, String datasetName, Boolean multiLabel)
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throws IOException {
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// Instantiates a client
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AutoMlClient client = AutoMlClient.create();
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// Resource representing the Google Cloud Platform location
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LocationName projectLocation = LocationName.of(projectId, computeRegion);
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// Classification type assigned based on multiLabel value.
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ClassificationType classificationType =
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multiLabel ? ClassificationType.MULTILABEL : ClassificationType.MULTICLASS;
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// Specify the image classification type for the dataset.
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ImageClassificationDatasetMetadata imageClassificationDatasetMetadata =
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ImageClassificationDatasetMetadata.newBuilder()
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.setClassificationType(classificationType)
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.build();
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// Create a dataset with dataset name and set the dataset metadata.
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Dataset myDataset =
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Dataset.newBuilder()
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.setDisplayName(datasetName)
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.setImageClassificationDatasetMetadata(imageClassificationDatasetMetadata)
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.build();
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// Create dataset with the dataset metadata in the region.
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Dataset dataset = client.createDataset(projectLocation, myDataset);
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// Display the dataset information
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System.out.println(String.format("Dataset name: %s", dataset.getName()));
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System.out.println(
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String.format(
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"Dataset id: %s",
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dataset.getName().split("/")[dataset.getName().split("/").length - 1]));
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System.out.println(String.format("Dataset display name: %s", dataset.getDisplayName()));
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System.out.println("Image classification dataset specification:");
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System.out.print(String.format("\t%s", dataset.getImageClassificationDatasetMetadata()));
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System.out.println(String.format("Dataset example count: %d", dataset.getExampleCount()));
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System.out.println("Dataset create time:");
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System.out.println(String.format("\tseconds: %s", dataset.getCreateTime().getSeconds()));
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System.out.println(String.format("\tnanos: %s", dataset.getCreateTime().getNanos()));
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}
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// [END automl_vision_create_dataset]
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// [START automl_vision_listdatasets]
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/**
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* Demonstrates using the AutoML client to list all datasets.
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*
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* @param projectId - Id of the project.
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* @param computeRegion - Region name.
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* @param filter - Filter expression.
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* @throws IOException on Input/Output errors.
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*/
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public static void listDatasets(String projectId, String computeRegion, String filter)
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throws IOException {
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// Instantiates a client
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AutoMlClient client = AutoMlClient.create();
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// A resource that represents Google Cloud Platform location.
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LocationName projectLocation = LocationName.of(projectId, computeRegion);
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// Build the List datasets request
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ListDatasetsRequest request =
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ListDatasetsRequest.newBuilder()
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.setParent(projectLocation.toString())
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.setFilter(filter)
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.build();
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// List all the datasets available in the region by applying the filter.
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System.out.println("List of datasets:");
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for (Dataset dataset : client.listDatasets(request).iterateAll()) {
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// Display the dataset information
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System.out.println(String.format("\nDataset name: %s", dataset.getName()));
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System.out.println(
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String.format(
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"Dataset id: %s",
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dataset.getName().split("/")[dataset.getName().split("/").length - 1]));
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System.out.println(String.format("Dataset display name: %s", dataset.getDisplayName()));
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System.out.println("Image classification dataset specification:");
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System.out.print(String.format("\t%s", dataset.getImageClassificationDatasetMetadata()));
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System.out.println(String.format("Dataset example count: %d", dataset.getExampleCount()));
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System.out.println("Dataset create time:");
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System.out.println(String.format("\tseconds: %s", dataset.getCreateTime().getSeconds()));
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System.out.println(String.format("\tnanos: %s", dataset.getCreateTime().getNanos()));
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}
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}
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// [END automl_vision_listdatasets]
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// [START automl_vision_getdataset]
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/**
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* Demonstrates using the AutoML client to get a dataset by ID.
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*
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* @param projectId - Id of the project.
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* @param computeRegion - Region name.
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* @param datasetId - Id of the dataset.
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* @throws IOException on Input/Output errors.
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*/
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public static void getDataset(String projectId, String computeRegion, String datasetId)
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throws IOException {
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// Instantiates a client
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AutoMlClient client = AutoMlClient.create();
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// Get the complete path of the dataset.
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DatasetName datasetFullId = DatasetName.of(projectId, computeRegion, datasetId);
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// Get all the information about a given dataset.
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Dataset dataset = client.getDataset(datasetFullId);
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// Display the dataset information.
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System.out.println(String.format("Dataset name: %s", dataset.getName()));
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System.out.println(
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String.format(
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"Dataset id: %s",
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dataset.getName().split("/")[dataset.getName().split("/").length - 1]));
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System.out.println(String.format("Dataset display name: %s", dataset.getDisplayName()));
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System.out.println("Image classification dataset specification:");
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System.out.print(String.format("\t%s", dataset.getImageClassificationDatasetMetadata()));
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System.out.println(String.format("Dataset example count: %d", dataset.getExampleCount()));
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System.out.println("Dataset create time:");
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System.out.println(String.format("\tseconds: %s", dataset.getCreateTime().getSeconds()));
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System.out.println(String.format("\tnanos: %s", dataset.getCreateTime().getNanos()));
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}
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// [END automl_vision_getdataset]
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// [START automl_vision_importdata]
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/**
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* Demonstrates using the AutoML client to import labeled images.
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*
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* @param projectId - Id of the project.
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* @param computeRegion - Region name.
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* @param datasetId - Id of the dataset to which the training data will be imported.
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* @param path - Google Cloud Storage URIs. Target files must be in AutoML vision CSV format.
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* @throws Exception on AutoML Client errors
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*/
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public static void importData(
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String projectId, String computeRegion, String datasetId, String path) throws Exception {
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// Instantiates a client
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AutoMlClient client = AutoMlClient.create();
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// Get the complete path of the dataset.
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DatasetName datasetFullId = DatasetName.of(projectId, computeRegion, datasetId);
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GcsSource.Builder gcsSource = GcsSource.newBuilder();
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// Get multiple training data files to be imported
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String[] inputUris = path.split(",");
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for (String inputUri : inputUris) {
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gcsSource.addInputUris(inputUri);
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}
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// Import data
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InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).build();
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System.out.println("Processing import...");
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Empty response = client.importDataAsync(datasetFullId.toString(), inputConfig).get();
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System.out.println(String.format("Dataset imported. %s", response));
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}
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// [END automl_vision_importdata]
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// [START automl_vision_exportdata]
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/**
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* Demonstrates using the AutoML client to export a dataset to a Google Cloud Storage bucket.
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*
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* @param projectId - Id of the project.
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* @param computeRegion - Region name.
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* @param datasetId - Id of the dataset.
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* @param gcsUri - Destination URI (Google Cloud Storage)
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* @throws Exception on AutoML Client errors
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*/
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public static void exportData(
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String projectId, String computeRegion, String datasetId, String gcsUri) throws Exception {
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// Instantiates a client
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AutoMlClient client = AutoMlClient.create();
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// Get the complete path of the dataset.
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DatasetName datasetFullId = DatasetName.of(projectId, computeRegion, datasetId);
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// Set the output URI
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GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsUri).build();
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// Export the dataset to the output URI.
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OutputConfig outputConfig = OutputConfig.newBuilder().setGcsDestination(gcsDestination).build();
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System.out.println("Processing export...");
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Empty response = client.exportDataAsync(datasetFullId, outputConfig).get();
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System.out.println(String.format("Dataset exported. %s", response));
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}
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// [END automl_vision_exportdata]
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// [START automl_vision_deletedataset]
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/**
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* Delete a dataset.
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*
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* @param projectId - Id of the project.
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* @param computeRegion - Region name.
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* @param datasetId - Id of the dataset.
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* @throws Exception on AutoML Client errors
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*/
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public static void deleteDataset(String projectId, String computeRegion, String datasetId)
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throws Exception {
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// Instantiates a client
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AutoMlClient client = AutoMlClient.create();
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// Get the complete path of the dataset.
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DatasetName datasetFullId = DatasetName.of(projectId, computeRegion, datasetId);
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// Delete a dataset.
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Empty response = client.deleteDatasetAsync(datasetFullId).get();
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System.out.println(String.format("Dataset deleted. %s", response));
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}
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// [END automl_vision_deleteDataset]
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public static void main(String[] args) throws Exception {
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DatasetApi datasetApi = new DatasetApi();
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datasetApi.argsHelper(args, System.out);
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}
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public static void argsHelper(String[] args, PrintStream out) throws Exception {
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ArgumentParser parser =
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ArgumentParsers.newFor("DatasetAPI")
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.build()
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.defaultHelp(true)
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.description("Dataset API operations.");
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Subparsers subparsers = parser.addSubparsers().dest("command");
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Subparser createDatasetParser = subparsers.addParser("create_dataset");
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createDatasetParser.addArgument("datasetName");
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createDatasetParser
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.addArgument("multiLabel")
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.nargs("?")
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.type(Boolean.class)
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.choices(Boolean.FALSE, Boolean.TRUE)
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.setDefault(Boolean.FALSE);
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Subparser listDatasetsParser = subparsers.addParser("list_datasets");
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listDatasetsParser
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.addArgument("filter")
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.nargs("?")
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.setDefault("imageClassificationDatasetMetadata:*");
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Subparser getDatasetParser = subparsers.addParser("get_dataset");
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getDatasetParser.addArgument("datasetId");
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Subparser importDataParser = subparsers.addParser("import_data");
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importDataParser.addArgument("datasetId");
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importDataParser.addArgument("path");
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Subparser exportDataParser = subparsers.addParser("export_data");
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exportDataParser.addArgument("datasetId");
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exportDataParser.addArgument("gcsUri");
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Subparser deleteDatasetParser = subparsers.addParser("delete_dataset");
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deleteDatasetParser.addArgument("datasetId");
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String projectId = System.getenv("PROJECT_ID");
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String computeRegion = System.getenv("REGION_NAME");
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Namespace ns = null;
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try {
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ns = parser.parseArgs(args);
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if (ns.get("command").equals("create_dataset")) {
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createDataset(
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projectId, computeRegion, ns.getString("datasetName"), ns.getBoolean("multiLabel"));
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}
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if (ns.get("command").equals("list_datasets")) {
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listDatasets(projectId, computeRegion, ns.getString("filter"));
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}
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if (ns.get("command").equals("get_dataset")) {
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getDataset(projectId, computeRegion, ns.getString("datasetId"));
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}
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if (ns.get("command").equals("import_data")) {
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importData(projectId, computeRegion, ns.getString("datasetId"), ns.getString("path"));
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}
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if (ns.get("command").equals("export_data")) {
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exportData(projectId, computeRegion, ns.getString("datasetId"), ns.getString("gcsUri"));
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}
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if (ns.get("command").equals("delete_dataset")) {
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deleteDataset(projectId, computeRegion, ns.getString("datasetId"));
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}
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} catch (ArgumentParserException e) {
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parser.handleError(e);
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}
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}
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}

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