PredictionServiceClient.java
/*
* Copyright 2022 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.google.cloud.automl.v1;
import com.google.api.core.BetaApi;
import com.google.api.gax.core.BackgroundResource;
import com.google.api.gax.httpjson.longrunning.OperationsClient;
import com.google.api.gax.longrunning.OperationFuture;
import com.google.api.gax.rpc.OperationCallable;
import com.google.api.gax.rpc.UnaryCallable;
import com.google.cloud.automl.v1.stub.PredictionServiceStub;
import com.google.cloud.automl.v1.stub.PredictionServiceStubSettings;
import com.google.longrunning.Operation;
import java.io.IOException;
import java.util.Map;
import java.util.concurrent.TimeUnit;
import javax.annotation.Generated;
// AUTO-GENERATED DOCUMENTATION AND CLASS.
/**
* Service Description: AutoML Prediction API.
*
* <p>On any input that is documented to expect a string parameter in snake_case or dash-case,
* either of those cases is accepted.
*
* <p>This class provides the ability to make remote calls to the backing service through method
* calls that map to API methods. Sample code to get started:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
* ExamplePayload payload = ExamplePayload.newBuilder().build();
* Map<String, String> params = new HashMap<>();
* PredictResponse response = predictionServiceClient.predict(name, payload, params);
* }
* }</pre>
*
* <p>Note: close() needs to be called on the PredictionServiceClient object to clean up resources
* such as threads. In the example above, try-with-resources is used, which automatically calls
* close().
*
* <p>The surface of this class includes several types of Java methods for each of the API's
* methods:
*
* <ol>
* <li>A "flattened" method. With this type of method, the fields of the request type have been
* converted into function parameters. It may be the case that not all fields are available as
* parameters, and not every API method will have a flattened method entry point.
* <li>A "request object" method. This type of method only takes one parameter, a request object,
* which must be constructed before the call. Not every API method will have a request object
* method.
* <li>A "callable" method. This type of method takes no parameters and returns an immutable API
* callable object, which can be used to initiate calls to the service.
* </ol>
*
* <p>See the individual methods for example code.
*
* <p>Many parameters require resource names to be formatted in a particular way. To assist with
* these names, this class includes a format method for each type of name, and additionally a parse
* method to extract the individual identifiers contained within names that are returned.
*
* <p>This class can be customized by passing in a custom instance of PredictionServiceSettings to
* create(). For example:
*
* <p>To customize credentials:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newBuilder()
* .setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
* .build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }</pre>
*
* <p>To customize the endpoint:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }</pre>
*
* <p>To use REST (HTTP1.1/JSON) transport (instead of gRPC) for sending and receiving requests over
* the wire:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newHttpJsonBuilder().build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }</pre>
*
* <p>Please refer to the GitHub repository's samples for more quickstart code snippets.
*/
@Generated("by gapic-generator-java")
public class PredictionServiceClient implements BackgroundResource {
private final PredictionServiceSettings settings;
private final PredictionServiceStub stub;
private final OperationsClient httpJsonOperationsClient;
private final com.google.longrunning.OperationsClient operationsClient;
/** Constructs an instance of PredictionServiceClient with default settings. */
public static final PredictionServiceClient create() throws IOException {
return create(PredictionServiceSettings.newBuilder().build());
}
/**
* Constructs an instance of PredictionServiceClient, using the given settings. The channels are
* created based on the settings passed in, or defaults for any settings that are not set.
*/
public static final PredictionServiceClient create(PredictionServiceSettings settings)
throws IOException {
return new PredictionServiceClient(settings);
}
/**
* Constructs an instance of PredictionServiceClient, using the given stub for making calls. This
* is for advanced usage - prefer using create(PredictionServiceSettings).
*/
public static final PredictionServiceClient create(PredictionServiceStub stub) {
return new PredictionServiceClient(stub);
}
/**
* Constructs an instance of PredictionServiceClient, using the given settings. This is protected
* so that it is easy to make a subclass, but otherwise, the static factory methods should be
* preferred.
*/
protected PredictionServiceClient(PredictionServiceSettings settings) throws IOException {
this.settings = settings;
this.stub = ((PredictionServiceStubSettings) settings.getStubSettings()).createStub();
this.operationsClient =
com.google.longrunning.OperationsClient.create(this.stub.getOperationsStub());
this.httpJsonOperationsClient = OperationsClient.create(this.stub.getHttpJsonOperationsStub());
}
protected PredictionServiceClient(PredictionServiceStub stub) {
this.settings = null;
this.stub = stub;
this.operationsClient =
com.google.longrunning.OperationsClient.create(this.stub.getOperationsStub());
this.httpJsonOperationsClient = OperationsClient.create(this.stub.getHttpJsonOperationsStub());
}
public final PredictionServiceSettings getSettings() {
return settings;
}
public PredictionServiceStub getStub() {
return stub;
}
/**
* Returns the OperationsClient that can be used to query the status of a long-running operation
* returned by another API method call.
*/
public final com.google.longrunning.OperationsClient getOperationsClient() {
return operationsClient;
}
/**
* Returns the OperationsClient that can be used to query the status of a long-running operation
* returned by another API method call.
*/
@BetaApi
public final OperationsClient getHttpJsonOperationsClient() {
return httpJsonOperationsClient;
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction. The prediction result is directly returned in the response.
* Available for following ML scenarios, and their expected request payloads:
*
* <p>AutoML Vision Classification
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Vision Object Detection
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Natural Language Classification
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Natural Language Entity Extraction
*
* <ul>
* <li>A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or
* .TIFF format with size upto 20MB.
* </ul>
*
* <p>AutoML Natural Language Sentiment Analysis
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Translation
*
* <ul>
* <li>A TextSnippet up to 25,000 characters, UTF-8 encoded.
* </ul>
*
* <p>AutoML Tables
*
* <ul>
* <li>A row with column values matching the columns of the model, up to 5MB. Not available for
* FORECASTING `prediction_type`.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
* ExamplePayload payload = ExamplePayload.newBuilder().build();
* Map<String, String> params = new HashMap<>();
* PredictResponse response = predictionServiceClient.predict(name, payload, params);
* }
* }</pre>
*
* @param name Required. Name of the model requested to serve the prediction.
* @param payload Required. Payload to perform a prediction on. The payload must match the problem
* type that the model was trained to solve.
* @param params Additional domain-specific parameters, any string must be up to 25000 characters
* long.
* <p>AutoML Vision Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for an image, it will only produce results that have at least this confidence score. The
* default is 0.5.
* <p>AutoML Vision Object Detection
* <p>`score_threshold` : (float) When Model detects objects on the image, it will only
* produce bounding boxes which have at least this confidence score. Value in 0 to 1 range,
* default is 0.5.
* <p>`max_bounding_box_count` : (int64) The maximum number of bounding boxes returned. The
* default is 100. The number of returned bounding boxes might be limited by the server.
* <p>AutoML Tables
* <p>`feature_importance` : (boolean) Whether
* [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] is
* populated in the returned list of
* [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] objects. The default is false.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictResponse predict(
ModelName name, ExamplePayload payload, Map<String, String> params) {
PredictRequest request =
PredictRequest.newBuilder()
.setName(name == null ? null : name.toString())
.setPayload(payload)
.putAllParams(params)
.build();
return predict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction. The prediction result is directly returned in the response.
* Available for following ML scenarios, and their expected request payloads:
*
* <p>AutoML Vision Classification
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Vision Object Detection
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Natural Language Classification
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Natural Language Entity Extraction
*
* <ul>
* <li>A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or
* .TIFF format with size upto 20MB.
* </ul>
*
* <p>AutoML Natural Language Sentiment Analysis
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Translation
*
* <ul>
* <li>A TextSnippet up to 25,000 characters, UTF-8 encoded.
* </ul>
*
* <p>AutoML Tables
*
* <ul>
* <li>A row with column values matching the columns of the model, up to 5MB. Not available for
* FORECASTING `prediction_type`.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
* ExamplePayload payload = ExamplePayload.newBuilder().build();
* Map<String, String> params = new HashMap<>();
* PredictResponse response = predictionServiceClient.predict(name, payload, params);
* }
* }</pre>
*
* @param name Required. Name of the model requested to serve the prediction.
* @param payload Required. Payload to perform a prediction on. The payload must match the problem
* type that the model was trained to solve.
* @param params Additional domain-specific parameters, any string must be up to 25000 characters
* long.
* <p>AutoML Vision Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for an image, it will only produce results that have at least this confidence score. The
* default is 0.5.
* <p>AutoML Vision Object Detection
* <p>`score_threshold` : (float) When Model detects objects on the image, it will only
* produce bounding boxes which have at least this confidence score. Value in 0 to 1 range,
* default is 0.5.
* <p>`max_bounding_box_count` : (int64) The maximum number of bounding boxes returned. The
* default is 100. The number of returned bounding boxes might be limited by the server.
* <p>AutoML Tables
* <p>`feature_importance` : (boolean) Whether
* [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] is
* populated in the returned list of
* [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] objects. The default is false.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictResponse predict(
String name, ExamplePayload payload, Map<String, String> params) {
PredictRequest request =
PredictRequest.newBuilder().setName(name).setPayload(payload).putAllParams(params).build();
return predict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction. The prediction result is directly returned in the response.
* Available for following ML scenarios, and their expected request payloads:
*
* <p>AutoML Vision Classification
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Vision Object Detection
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Natural Language Classification
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Natural Language Entity Extraction
*
* <ul>
* <li>A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or
* .TIFF format with size upto 20MB.
* </ul>
*
* <p>AutoML Natural Language Sentiment Analysis
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Translation
*
* <ul>
* <li>A TextSnippet up to 25,000 characters, UTF-8 encoded.
* </ul>
*
* <p>AutoML Tables
*
* <ul>
* <li>A row with column values matching the columns of the model, up to 5MB. Not available for
* FORECASTING `prediction_type`.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* PredictRequest request =
* PredictRequest.newBuilder()
* .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
* .setPayload(ExamplePayload.newBuilder().build())
* .putAllParams(new HashMap<String, String>())
* .build();
* PredictResponse response = predictionServiceClient.predict(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictResponse predict(PredictRequest request) {
return predictCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction. The prediction result is directly returned in the response.
* Available for following ML scenarios, and their expected request payloads:
*
* <p>AutoML Vision Classification
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Vision Object Detection
*
* <ul>
* <li>An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
* </ul>
*
* <p>AutoML Natural Language Classification
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Natural Language Entity Extraction
*
* <ul>
* <li>A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or
* .TIFF format with size upto 20MB.
* </ul>
*
* <p>AutoML Natural Language Sentiment Analysis
*
* <ul>
* <li>A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF
* format with size upto 2MB.
* </ul>
*
* <p>AutoML Translation
*
* <ul>
* <li>A TextSnippet up to 25,000 characters, UTF-8 encoded.
* </ul>
*
* <p>AutoML Tables
*
* <ul>
* <li>A row with column values matching the columns of the model, up to 5MB. Not available for
* FORECASTING `prediction_type`.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* PredictRequest request =
* PredictRequest.newBuilder()
* .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
* .setPayload(ExamplePayload.newBuilder().build())
* .putAllParams(new HashMap<String, String>())
* .build();
* ApiFuture<PredictResponse> future =
* predictionServiceClient.predictCallable().futureCall(request);
* // Do something.
* PredictResponse response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<PredictRequest, PredictResponse> predictCallable() {
return stub.predictCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform a batch prediction. Unlike the online
* [Predict][google.cloud.automl.v1.PredictionService.Predict], batch prediction result won't be
* immediately available in the response. Instead, a long running operation object is returned.
* User can poll the operation result via
* [GetOperation][google.longrunning.Operations.GetOperation] method. Once the operation is done,
* [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned in the
* [response][google.longrunning.Operation.response] field. Available for following ML scenarios:
*
* <ul>
* <li>AutoML Vision Classification
* <li>AutoML Vision Object Detection
* <li>AutoML Video Intelligence Classification
* <li>AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
* <li>AutoML Natural Language Entity Extraction
* <li>AutoML Natural Language Sentiment Analysis
* <li>AutoML Tables
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
* BatchPredictInputConfig inputConfig = BatchPredictInputConfig.newBuilder().build();
* BatchPredictOutputConfig outputConfig = BatchPredictOutputConfig.newBuilder().build();
* Map<String, String> params = new HashMap<>();
* BatchPredictResult response =
* predictionServiceClient.batchPredictAsync(name, inputConfig, outputConfig, params).get();
* }
* }</pre>
*
* @param name Required. Name of the model requested to serve the batch prediction.
* @param inputConfig Required. The input configuration for batch prediction.
* @param outputConfig Required. The Configuration specifying where output predictions should be
* written.
* @param params Additional domain-specific parameters for the predictions, any string must be up
* to 25000 characters long.
* <p>AutoML Natural Language Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for a text snippet, it will only produce results that have at least this confidence score.
* The default is 0.5.
* <p>AutoML Vision Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for an image, it will only produce results that have at least this confidence score. The
* default is 0.5.
* <p>AutoML Vision Object Detection
* <p>`score_threshold` : (float) When Model detects objects on the image, it will only
* produce bounding boxes which have at least this confidence score. Value in 0 to 1 range,
* default is 0.5.
* <p>`max_bounding_box_count` : (int64) The maximum number of bounding boxes returned per
* image. The default is 100, the number of bounding boxes returned might be limited by the
* server. AutoML Video Intelligence Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for a video, it will only produce results that have at least this confidence score. The
* default is 0.5.
* <p>`segment_classification` : (boolean) Set to true to request segment-level
* classification. AutoML Video Intelligence returns labels and their confidence scores for
* the entire segment of the video that user specified in the request configuration. The
* default is true.
* <p>`shot_classification` : (boolean) Set to true to request shot-level classification.
* AutoML Video Intelligence determines the boundaries for each camera shot in the entire
* segment of the video that user specified in the request configuration. AutoML Video
* Intelligence then returns labels and their confidence scores for each detected shot, along
* with the start and end time of the shot. The default is false.
* <p>WARNING: Model evaluation is not done for this classification type, the quality of it
* depends on training data, but there are no metrics provided to describe that quality.
* <p>`1s_interval_classification` : (boolean) Set to true to request classification for a
* video at one-second intervals. AutoML Video Intelligence returns labels and their
* confidence scores for each second of the entire segment of the video that user specified in
* the request configuration. The default is false.
* <p>WARNING: Model evaluation is not done for this classification type, the quality of it
* depends on training data, but there are no metrics provided to describe that quality.
* <p>AutoML Video Intelligence Object Tracking
* <p>`score_threshold` : (float) When Model detects objects on video frames, it will only
* produce bounding boxes which have at least this confidence score. Value in 0 to 1 range,
* default is 0.5.
* <p>`max_bounding_box_count` : (int64) The maximum number of bounding boxes returned per
* image. The default is 100, the number of bounding boxes returned might be limited by the
* server.
* <p>`min_bounding_box_size` : (float) Only bounding boxes with shortest edge at least that
* long as a relative value of video frame size are returned. Value in 0 to 1 range. Default
* is 0.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final OperationFuture<BatchPredictResult, OperationMetadata> batchPredictAsync(
ModelName name,
BatchPredictInputConfig inputConfig,
BatchPredictOutputConfig outputConfig,
Map<String, String> params) {
BatchPredictRequest request =
BatchPredictRequest.newBuilder()
.setName(name == null ? null : name.toString())
.setInputConfig(inputConfig)
.setOutputConfig(outputConfig)
.putAllParams(params)
.build();
return batchPredictAsync(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform a batch prediction. Unlike the online
* [Predict][google.cloud.automl.v1.PredictionService.Predict], batch prediction result won't be
* immediately available in the response. Instead, a long running operation object is returned.
* User can poll the operation result via
* [GetOperation][google.longrunning.Operations.GetOperation] method. Once the operation is done,
* [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned in the
* [response][google.longrunning.Operation.response] field. Available for following ML scenarios:
*
* <ul>
* <li>AutoML Vision Classification
* <li>AutoML Vision Object Detection
* <li>AutoML Video Intelligence Classification
* <li>AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
* <li>AutoML Natural Language Entity Extraction
* <li>AutoML Natural Language Sentiment Analysis
* <li>AutoML Tables
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
* BatchPredictInputConfig inputConfig = BatchPredictInputConfig.newBuilder().build();
* BatchPredictOutputConfig outputConfig = BatchPredictOutputConfig.newBuilder().build();
* Map<String, String> params = new HashMap<>();
* BatchPredictResult response =
* predictionServiceClient.batchPredictAsync(name, inputConfig, outputConfig, params).get();
* }
* }</pre>
*
* @param name Required. Name of the model requested to serve the batch prediction.
* @param inputConfig Required. The input configuration for batch prediction.
* @param outputConfig Required. The Configuration specifying where output predictions should be
* written.
* @param params Additional domain-specific parameters for the predictions, any string must be up
* to 25000 characters long.
* <p>AutoML Natural Language Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for a text snippet, it will only produce results that have at least this confidence score.
* The default is 0.5.
* <p>AutoML Vision Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for an image, it will only produce results that have at least this confidence score. The
* default is 0.5.
* <p>AutoML Vision Object Detection
* <p>`score_threshold` : (float) When Model detects objects on the image, it will only
* produce bounding boxes which have at least this confidence score. Value in 0 to 1 range,
* default is 0.5.
* <p>`max_bounding_box_count` : (int64) The maximum number of bounding boxes returned per
* image. The default is 100, the number of bounding boxes returned might be limited by the
* server. AutoML Video Intelligence Classification
* <p>`score_threshold` : (float) A value from 0.0 to 1.0. When the model makes predictions
* for a video, it will only produce results that have at least this confidence score. The
* default is 0.5.
* <p>`segment_classification` : (boolean) Set to true to request segment-level
* classification. AutoML Video Intelligence returns labels and their confidence scores for
* the entire segment of the video that user specified in the request configuration. The
* default is true.
* <p>`shot_classification` : (boolean) Set to true to request shot-level classification.
* AutoML Video Intelligence determines the boundaries for each camera shot in the entire
* segment of the video that user specified in the request configuration. AutoML Video
* Intelligence then returns labels and their confidence scores for each detected shot, along
* with the start and end time of the shot. The default is false.
* <p>WARNING: Model evaluation is not done for this classification type, the quality of it
* depends on training data, but there are no metrics provided to describe that quality.
* <p>`1s_interval_classification` : (boolean) Set to true to request classification for a
* video at one-second intervals. AutoML Video Intelligence returns labels and their
* confidence scores for each second of the entire segment of the video that user specified in
* the request configuration. The default is false.
* <p>WARNING: Model evaluation is not done for this classification type, the quality of it
* depends on training data, but there are no metrics provided to describe that quality.
* <p>AutoML Video Intelligence Object Tracking
* <p>`score_threshold` : (float) When Model detects objects on video frames, it will only
* produce bounding boxes which have at least this confidence score. Value in 0 to 1 range,
* default is 0.5.
* <p>`max_bounding_box_count` : (int64) The maximum number of bounding boxes returned per
* image. The default is 100, the number of bounding boxes returned might be limited by the
* server.
* <p>`min_bounding_box_size` : (float) Only bounding boxes with shortest edge at least that
* long as a relative value of video frame size are returned. Value in 0 to 1 range. Default
* is 0.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final OperationFuture<BatchPredictResult, OperationMetadata> batchPredictAsync(
String name,
BatchPredictInputConfig inputConfig,
BatchPredictOutputConfig outputConfig,
Map<String, String> params) {
BatchPredictRequest request =
BatchPredictRequest.newBuilder()
.setName(name)
.setInputConfig(inputConfig)
.setOutputConfig(outputConfig)
.putAllParams(params)
.build();
return batchPredictAsync(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform a batch prediction. Unlike the online
* [Predict][google.cloud.automl.v1.PredictionService.Predict], batch prediction result won't be
* immediately available in the response. Instead, a long running operation object is returned.
* User can poll the operation result via
* [GetOperation][google.longrunning.Operations.GetOperation] method. Once the operation is done,
* [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned in the
* [response][google.longrunning.Operation.response] field. Available for following ML scenarios:
*
* <ul>
* <li>AutoML Vision Classification
* <li>AutoML Vision Object Detection
* <li>AutoML Video Intelligence Classification
* <li>AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
* <li>AutoML Natural Language Entity Extraction
* <li>AutoML Natural Language Sentiment Analysis
* <li>AutoML Tables
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* BatchPredictRequest request =
* BatchPredictRequest.newBuilder()
* .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
* .setInputConfig(BatchPredictInputConfig.newBuilder().build())
* .setOutputConfig(BatchPredictOutputConfig.newBuilder().build())
* .putAllParams(new HashMap<String, String>())
* .build();
* BatchPredictResult response = predictionServiceClient.batchPredictAsync(request).get();
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final OperationFuture<BatchPredictResult, OperationMetadata> batchPredictAsync(
BatchPredictRequest request) {
return batchPredictOperationCallable().futureCall(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform a batch prediction. Unlike the online
* [Predict][google.cloud.automl.v1.PredictionService.Predict], batch prediction result won't be
* immediately available in the response. Instead, a long running operation object is returned.
* User can poll the operation result via
* [GetOperation][google.longrunning.Operations.GetOperation] method. Once the operation is done,
* [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned in the
* [response][google.longrunning.Operation.response] field. Available for following ML scenarios:
*
* <ul>
* <li>AutoML Vision Classification
* <li>AutoML Vision Object Detection
* <li>AutoML Video Intelligence Classification
* <li>AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
* <li>AutoML Natural Language Entity Extraction
* <li>AutoML Natural Language Sentiment Analysis
* <li>AutoML Tables
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* BatchPredictRequest request =
* BatchPredictRequest.newBuilder()
* .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
* .setInputConfig(BatchPredictInputConfig.newBuilder().build())
* .setOutputConfig(BatchPredictOutputConfig.newBuilder().build())
* .putAllParams(new HashMap<String, String>())
* .build();
* OperationFuture<BatchPredictResult, OperationMetadata> future =
* predictionServiceClient.batchPredictOperationCallable().futureCall(request);
* // Do something.
* BatchPredictResult response = future.get();
* }
* }</pre>
*/
public final OperationCallable<BatchPredictRequest, BatchPredictResult, OperationMetadata>
batchPredictOperationCallable() {
return stub.batchPredictOperationCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform a batch prediction. Unlike the online
* [Predict][google.cloud.automl.v1.PredictionService.Predict], batch prediction result won't be
* immediately available in the response. Instead, a long running operation object is returned.
* User can poll the operation result via
* [GetOperation][google.longrunning.Operations.GetOperation] method. Once the operation is done,
* [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned in the
* [response][google.longrunning.Operation.response] field. Available for following ML scenarios:
*
* <ul>
* <li>AutoML Vision Classification
* <li>AutoML Vision Object Detection
* <li>AutoML Video Intelligence Classification
* <li>AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
* <li>AutoML Natural Language Entity Extraction
* <li>AutoML Natural Language Sentiment Analysis
* <li>AutoML Tables
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* BatchPredictRequest request =
* BatchPredictRequest.newBuilder()
* .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
* .setInputConfig(BatchPredictInputConfig.newBuilder().build())
* .setOutputConfig(BatchPredictOutputConfig.newBuilder().build())
* .putAllParams(new HashMap<String, String>())
* .build();
* ApiFuture<Operation> future =
* predictionServiceClient.batchPredictCallable().futureCall(request);
* // Do something.
* Operation response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<BatchPredictRequest, Operation> batchPredictCallable() {
return stub.batchPredictCallable();
}
@Override
public final void close() {
stub.close();
}
@Override
public void shutdown() {
stub.shutdown();
}
@Override
public boolean isShutdown() {
return stub.isShutdown();
}
@Override
public boolean isTerminated() {
return stub.isTerminated();
}
@Override
public void shutdownNow() {
stub.shutdownNow();
}
@Override
public boolean awaitTermination(long duration, TimeUnit unit) throws InterruptedException {
return stub.awaitTermination(duration, unit);
}
}