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chore: moving vision automl samples (#373)
* chore: moving vision automl samples * refactored printout stream * fixed the lint * lint
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‎automl/snippets/resources/dandelion.jpg

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‎automl/snippets/src/main/java/com/google/cloud/vision/ClassificationDeployModel.java

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/*
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* Copyright 2019 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;
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// [START automl_vision_classification_deploy_model]
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import com.google.api.gax.longrunning.OperationFuture;
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import com.google.cloud.automl.v1beta1.AutoMlClient;
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import com.google.cloud.automl.v1beta1.DeployModelRequest;
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import com.google.cloud.automl.v1beta1.ModelName;
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import com.google.cloud.automl.v1beta1.OperationMetadata;
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import com.google.protobuf.Empty;
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import java.io.IOException;
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import java.util.concurrent.ExecutionException;
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class ClassificationDeployModel {
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// Deploy a model
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static void classificationDeployModel(String projectId, String modelId)
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throws IOException, ExecutionException, InterruptedException {
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// String projectId = "YOUR_PROJECT_ID";
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// String modelId = "YOUR_MODEL_ID";
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests. After completing all of your requests, call
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// the "close" method on the client to safely clean up any remaining background resources.
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try (AutoMlClient client = AutoMlClient.create()) {
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// Get the full path of the model.
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ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
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// Build deploy model request.
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DeployModelRequest deployModelRequest =
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DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
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// Deploy a model with the deploy model request.
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OperationFuture<Empty, OperationMetadata> future =
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client.deployModelAsync(deployModelRequest);
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future.get();
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// Display the deployment details of model.
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System.out.println("Model deployment finished");
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}
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}
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}
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// [END automl_vision_classification_deploy_model]

‎automl/snippets/src/main/java/com/google/cloud/vision/ClassificationDeployModelNodeCount.java

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/*
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* Copyright 2019 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;
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// [START automl_vision_classification_deploy_model_node_count]
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import com.google.api.gax.longrunning.OperationFuture;
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import com.google.cloud.automl.v1beta1.AutoMlClient;
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import com.google.cloud.automl.v1beta1.DeployModelRequest;
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import com.google.cloud.automl.v1beta1.ImageClassificationModelDeploymentMetadata;
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import com.google.cloud.automl.v1beta1.ModelName;
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import com.google.cloud.automl.v1beta1.OperationMetadata;
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import com.google.protobuf.Empty;
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import java.io.IOException;
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import java.util.concurrent.ExecutionException;
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class ClassificationDeployModelNodeCount {
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// Deploy a model with a specified node count
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static void classificationDeployModelNodeCount(String projectId, String modelId)
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throws IOException, ExecutionException, InterruptedException {
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// String projectId = "YOUR_PROJECT_ID";
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// String modelId = "YOUR_MODEL_ID";
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests. After completing all of your requests, call
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// the "close" method on the client to safely clean up any remaining background resources.
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try (AutoMlClient client = AutoMlClient.create()) {
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// Get the full path of the model.
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ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
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// Set how many nodes the model is deployed on
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ImageClassificationModelDeploymentMetadata deploymentMetadata =
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ImageClassificationModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
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DeployModelRequest request =
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DeployModelRequest.newBuilder()
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.setName(modelFullId.toString())
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.setImageClassificationModelDeploymentMetadata(deploymentMetadata)
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.build();
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// Deploy the model
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OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
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future.get();
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System.out.println("Model deployment on 2 nodes finished");
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}
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}
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}
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// [END automl_vision_classification_deploy_model_node_count]

‎automl/snippets/src/main/java/com/google/cloud/vision/ClassificationUndeployModel.java

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/*
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* Copyright 2019 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;
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// [START automl_vision_classification_undeploy_model]
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import com.google.api.gax.longrunning.OperationFuture;
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import com.google.cloud.automl.v1beta1.AutoMlClient;
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import com.google.cloud.automl.v1beta1.ModelName;
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import com.google.cloud.automl.v1beta1.OperationMetadata;
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import com.google.cloud.automl.v1beta1.UndeployModelRequest;
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import com.google.protobuf.Empty;
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import java.io.IOException;
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import java.util.concurrent.ExecutionException;
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class ClassificationUndeployModel {
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// Deploy a model
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static void classificationUndeployModel(String projectId, String modelId)
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throws IOException, ExecutionException, InterruptedException {
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// String projectId = "YOUR_PROJECT_ID";
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// String modelId = "YOUR_MODEL_ID";
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests. After completing all of your requests, call
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// the "close" method on the client to safely clean up any remaining background resources.
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try (AutoMlClient client = AutoMlClient.create()) {
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// Get the full path of the model.
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ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
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// Build deploy model request.
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UndeployModelRequest undeployModelRequest =
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UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
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// Deploy a model with the deploy model request.
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OperationFuture<Empty, OperationMetadata> future =
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client.undeployModelAsync(undeployModelRequest);
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future.get();
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// Display the deployment details of model.
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System.out.println("Model undeploy finished");
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}
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}
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}
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// [END automl_vision_classification_undeploy_model]

‎automl/snippets/src/main/java/com/google/cloud/vision/ModelApi.java

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/*
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* Copyright 2018 Google Inc.
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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;
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// Imports the Google Cloud client library
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import com.google.api.gax.longrunning.OperationFuture;
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import com.google.cloud.automl.v1beta1.AutoMlClient;
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import com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics;
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import com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry;
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import com.google.cloud.automl.v1beta1.ImageClassificationModelMetadata;
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import com.google.cloud.automl.v1beta1.ListModelEvaluationsRequest;
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import com.google.cloud.automl.v1beta1.ListModelsRequest;
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import com.google.cloud.automl.v1beta1.LocationName;
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import com.google.cloud.automl.v1beta1.Model;
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import com.google.cloud.automl.v1beta1.ModelEvaluation;
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import com.google.cloud.automl.v1beta1.ModelEvaluationName;
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import com.google.cloud.automl.v1beta1.ModelName;
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import com.google.cloud.automl.v1beta1.OperationMetadata;
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import com.google.longrunning.Operation;
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import com.google.protobuf.Empty;
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import java.io.IOException;
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import java.util.List;
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import java.util.concurrent.ExecutionException;
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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.ModelApi' -Dexec.args='create_model
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* [datasetId] test_model'
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*/
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public class ModelApi {
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// [START automl_vision_create_model]
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/**
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* Demonstrates using the AutoML client to create a model.
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*
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* @param projectId the Id of the project.
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* @param computeRegion the Region name.
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* @param dataSetId the Id of the dataset to which model is created.
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* @param modelName the Name of the model.
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* @param trainBudget the Budget for training the model.
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*/
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static void createModel(
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String projectId,
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String computeRegion,
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String dataSetId,
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String modelName,
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String trainBudget) {
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// Instantiates a client
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try (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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// Set model metadata.
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ImageClassificationModelMetadata imageClassificationModelMetadata =
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Long.valueOf(trainBudget) == 0
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? ImageClassificationModelMetadata.newBuilder().build()
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: ImageClassificationModelMetadata.newBuilder()
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.setTrainBudget(Long.valueOf(trainBudget))
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.build();
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// Set model name and model metadata for the image dataset.
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Model myModel =
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Model.newBuilder()
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.setDisplayName(modelName)
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.setDatasetId(dataSetId)
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.setImageClassificationModelMetadata(imageClassificationModelMetadata)
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.build();
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// Create a model with the model metadata in the region.
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OperationFuture<Model, OperationMetadata> response =
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client.createModelAsync(projectLocation, myModel);
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System.out.println(
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String.format(
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"Training operation name: %s", response.getInitialFuture().get().getName()));
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System.out.println("Training started...");
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} catch (IOException | ExecutionException | InterruptedException e) {
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e.printStackTrace();
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}
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}
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// [END automl_vision_create_model]
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public static void main(String[] args) {
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argsHelper(args);
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}
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static void argsHelper(String[] args) {
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ArgumentParser parser =
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ArgumentParsers.newFor("ModelApi")
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.build()
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.defaultHelp(true)
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.description("Model API operations.");
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Subparsers subparsers = parser.addSubparsers().dest("command");
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Subparser createModelParser = subparsers.addParser("create_model");
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createModelParser.addArgument("datasetId");
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createModelParser.addArgument("modelName");
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createModelParser.addArgument("trainBudget");
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String projectId = System.getenv("GOOGLE_CLOUD_PROJECT");
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String computeRegion = System.getenv("REGION_NAME");
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if (projectId == null || computeRegion == null) {
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System.out.println("Set `GOOGLE_CLOUD_PROJECT` and `REGION_NAME` as specified in the README");
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System.exit(-1);
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}
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try {
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Namespace ns = parser.parseArgs(args);
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if (ns.get("command").equals("create_model")) {
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createModel(
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projectId,
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computeRegion,
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ns.getString("datasetId"),
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ns.getString("modelName"),
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ns.getString("trainBudget"));
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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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}

‎automl/snippets/src/main/java/com/google/cloud/vision/ObjectDetectionDeployModelNodeCount.java

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/*
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* Copyright 2019 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,
12+
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13+
* 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;
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// [START automl_vision_object_detection_deploy_model_node_count]
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import com.google.api.gax.longrunning.OperationFuture;
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import com.google.cloud.automl.v1beta1.AutoMlClient;
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import com.google.cloud.automl.v1beta1.DeployModelRequest;
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import com.google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata;
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import com.google.cloud.automl.v1beta1.ModelName;
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import com.google.cloud.automl.v1beta1.OperationMetadata;
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import com.google.protobuf.Empty;
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import java.io.IOException;
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import java.util.concurrent.ExecutionException;
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class ObjectDetectionDeployModelNodeCount {
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static void objectDetectionDeployModelNodeCount(String projectId, String modelId)
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throws IOException, ExecutionException, InterruptedException {
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// String projectId = "YOUR_PROJECT_ID";
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// String modelId = "YOUR_MODEL_ID";
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests. After completing all of your requests, call
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// the "close" method on the client to safely clean up any remaining background resources.
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try (AutoMlClient client = AutoMlClient.create()) {
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// Get the full path of the model.
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ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
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// Set how many nodes the model is deployed on
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ImageObjectDetectionModelDeploymentMetadata deploymentMetadata =
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ImageObjectDetectionModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
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DeployModelRequest request =
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DeployModelRequest.newBuilder()
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.setName(modelFullId.toString())
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.setImageObjectDetectionModelDeploymentMetadata(deploymentMetadata)
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.build();
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// Deploy the model
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OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
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future.get();
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System.out.println("Model deployment on 2 nodes finished");
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}
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}
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}
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// [END automl_vision_object_detection_deploy_model_node_count]

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