Package com.google.cloud.automl.v1

Class PredictionServiceClient

java.lang.Object

com.google.cloud.automl.v1.PredictionServiceClient

All Implemented Interfaces:

BackgroundResource, AutoCloseable

@Generated("by gapic-generator-java")
public class PredictionServiceClient
extends Object
implements BackgroundResource

Service Description: AutoML Prediction API.

On any input that is documented to expect a string parameter in snake_case or dash-case, either of those cases is accepted.

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:

 // 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);
 }
 

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().

Methods

Method	Description	Method Variants
Predict	Perform an online prediction. The prediction result is directly returned in the response. Available for following ML scenarios, and their expected request payloads: AutoML Vision Classification An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB. AutoML Vision Object Detection An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB. AutoML Natural Language Classification A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB. AutoML Natural Language Entity Extraction A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or .TIFF format with size upto 20MB. AutoML Natural Language Sentiment Analysis A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB. AutoML Translation A TextSnippet up to 25,000 characters, UTF-8 encoded. AutoML Tables A row with column values matching the columns of the model, up to 5MB. Not available for FORECASTING `prediction_type`.	Request object method variants only take one parameter, a request object, which must be constructed before the call. predict(PredictRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. predict(ModelName name, ExamplePayload payload, Map<String, String> params) predict(String name, ExamplePayload payload, Map<String, String> params) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. predictCallable()
BatchPredict	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: AutoML Vision Classification AutoML Vision Object Detection AutoML Video Intelligence Classification AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification AutoML Natural Language Entity Extraction AutoML Natural Language Sentiment Analysis AutoML Tables	Request object method variants only take one parameter, a request object, which must be constructed before the call. batchPredictAsync(BatchPredictRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. batchPredictAsync(ModelName name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) batchPredictAsync(String name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. batchPredictOperationCallable() batchPredictCallable()

See the individual methods for example code.

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.

This class can be customized by passing in a custom instance of PredictionServiceSettings to create(). For example:

To customize credentials:

 // 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);
 

To customize the endpoint:

 // 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);
 

To use REST (HTTP1.1/JSON) transport (instead of gRPC) for sending and receiving requests over the wire:

 // 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);
 

Please refer to the GitHub repository's samples for more quickstart code snippets.

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	PredictionServiceClient(PredictionServiceSettings settings)	Constructs an instance of PredictionServiceClient, using the given settings.
protected	PredictionServiceClient(PredictionServiceStub stub)

Method Summary

Modifier and Type	Method	Description
boolean	awaitTermination(long duration, TimeUnit unit)
final OperationFuture<BatchPredictResult,OperationMetadata>	batchPredictAsync(BatchPredictRequest request)	Perform a batch prediction.
final OperationFuture<BatchPredictResult,OperationMetadata>	batchPredictAsync(ModelName name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String,String> params)	Perform a batch prediction.
final OperationFuture<BatchPredictResult,OperationMetadata>	batchPredictAsync(String name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String,String> params)	Perform a batch prediction.
final UnaryCallable<BatchPredictRequest,Operation>	batchPredictCallable()	Perform a batch prediction.
final OperationCallable<BatchPredictRequest,BatchPredictResult,OperationMetadata>	batchPredictOperationCallable()	Perform a batch prediction.
final void	close()
static final PredictionServiceClient	create()	Constructs an instance of PredictionServiceClient with default settings.
static final PredictionServiceClient	create(PredictionServiceSettings settings)	Constructs an instance of PredictionServiceClient, using the given settings.
static final PredictionServiceClient	create(PredictionServiceStub stub)	Constructs an instance of PredictionServiceClient, using the given stub for making calls.
final OperationsClient	getHttpJsonOperationsClient()	Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.
final OperationsClient	getOperationsClient()	Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.
final PredictionServiceSettings	getSettings()
PredictionServiceStub	getStub()
boolean	isShutdown()
boolean	isTerminated()
final PredictResponse	predict(ModelName name, ExamplePayload payload, Map<String,String> params)	Perform an online prediction.
final PredictResponse	predict(PredictRequest request)	Perform an online prediction.
final PredictResponse	predict(String name, ExamplePayload payload, Map<String,String> params)	Perform an online prediction.
final UnaryCallable<PredictRequest,PredictResponse>	predictCallable()	Perform an online prediction.
void	shutdown()
void	shutdownNow()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

PredictionServiceClient

protected PredictionServiceClient(PredictionServiceSettings settings)
                           throws IOException

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.

Throws:

IOException

PredictionServiceClient

protected PredictionServiceClient(PredictionServiceStub stub)

Method Details

create

public static final PredictionServiceClient create()
                                            throws IOException

Constructs an instance of PredictionServiceClient with default settings.

Throws:

IOException

create

public static final PredictionServiceClient create(PredictionServiceSettings settings)
                                            throws IOException

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.

Throws:

IOException

create

public static final PredictionServiceClient create(PredictionServiceStub stub)

Constructs an instance of PredictionServiceClient, using the given stub for making calls. This is for advanced usage - prefer using create(PredictionServiceSettings).

getSettings

public final PredictionServiceSettings getSettings()

getStub

public PredictionServiceStub getStub()

getOperationsClient

public final OperationsClient getOperationsClient()

Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.

getHttpJsonOperationsClient

@BetaApi
public final OperationsClient getHttpJsonOperationsClient()

Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.

predict

public final PredictResponse predict(ModelName name,
 ExamplePayload payload,
 Map<String,String> params)

Perform an online prediction. The prediction result is directly returned in the response. Available for following ML scenarios, and their expected request payloads:

AutoML Vision Classification

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Vision Object Detection

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Natural Language Classification

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Natural Language Entity Extraction

• A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or .TIFF format with size upto 20MB.

AutoML Natural Language Sentiment Analysis

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Translation

• A TextSnippet up to 25,000 characters, UTF-8 encoded.

AutoML Tables

• A row with column values matching the columns of the model, up to 5MB. Not available for FORECASTING `prediction_type`.

Sample 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);
 }
 

Parameters:

name - Required. Name of the model requested to serve the prediction.

payload - Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.

params - Additional domain-specific parameters, any string must be up to 25000 characters long.

AutoML Vision Classification

`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.

AutoML Vision Object Detection

`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.

`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.

AutoML Tables

`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:

ApiException - if the remote call fails

predict

public final PredictResponse predict(String name,
 ExamplePayload payload,
 Map<String,String> params)

Perform an online prediction. The prediction result is directly returned in the response. Available for following ML scenarios, and their expected request payloads:

AutoML Vision Classification

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Vision Object Detection

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Natural Language Classification

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Natural Language Entity Extraction

• A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or .TIFF format with size upto 20MB.

AutoML Natural Language Sentiment Analysis

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Translation

• A TextSnippet up to 25,000 characters, UTF-8 encoded.

AutoML Tables

• A row with column values matching the columns of the model, up to 5MB. Not available for FORECASTING `prediction_type`.

Sample 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);
 }
 

Parameters:

name - Required. Name of the model requested to serve the prediction.

payload - Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.

params - Additional domain-specific parameters, any string must be up to 25000 characters long.

AutoML Vision Classification

`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.

AutoML Vision Object Detection

`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.

`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.

AutoML Tables

`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:

ApiException - if the remote call fails

predict

public final PredictResponse predict(PredictRequest request)

Perform an online prediction. The prediction result is directly returned in the response. Available for following ML scenarios, and their expected request payloads:

AutoML Vision Classification

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Vision Object Detection

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Natural Language Classification

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Natural Language Entity Extraction

• A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or .TIFF format with size upto 20MB.

AutoML Natural Language Sentiment Analysis

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Translation

• A TextSnippet up to 25,000 characters, UTF-8 encoded.

AutoML Tables

• A row with column values matching the columns of the model, up to 5MB. Not available for FORECASTING `prediction_type`.

Sample 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);
 }
 

Parameters:

request - The request object containing all of the parameters for the API call.

Throws:

ApiException - if the remote call fails

predictCallable

public final UnaryCallable<PredictRequest,PredictResponse> predictCallable()

Perform an online prediction. The prediction result is directly returned in the response. Available for following ML scenarios, and their expected request payloads:

AutoML Vision Classification

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Vision Object Detection

• An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.

AutoML Natural Language Classification

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Natural Language Entity Extraction

• A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document in .PDF, .TIF or .TIFF format with size upto 20MB.

AutoML Natural Language Sentiment Analysis

• A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in .PDF, .TIF or .TIFF format with size upto 2MB.

AutoML Translation

• A TextSnippet up to 25,000 characters, UTF-8 encoded.

AutoML Tables

• A row with column values matching the columns of the model, up to 5MB. Not available for FORECASTING `prediction_type`.

Sample 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();
 }
 

batchPredictAsync

public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(ModelName name,
 BatchPredictInputConfig inputConfig,
 BatchPredictOutputConfig outputConfig,
 Map<String,String> params)

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:

• AutoML Vision Classification
• AutoML Vision Object Detection
• AutoML Video Intelligence Classification
• AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
• AutoML Natural Language Entity Extraction
• AutoML Natural Language Sentiment Analysis
• AutoML Tables

Sample 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();
 }
 

Parameters:

name - Required. Name of the model requested to serve the batch prediction.

inputConfig - Required. The input configuration for batch prediction.

outputConfig - Required. The Configuration specifying where output predictions should be written.

params - Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long.

AutoML Natural Language Classification

`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.

AutoML Vision Classification

`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.

AutoML Vision Object Detection

`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.

`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

`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.

`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.

`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.

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.

`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.

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.

AutoML Video Intelligence Object Tracking

`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.

`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.

`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:

ApiException - if the remote call fails

batchPredictAsync

public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(String name,
 BatchPredictInputConfig inputConfig,
 BatchPredictOutputConfig outputConfig,
 Map<String,String> params)

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:

• AutoML Vision Classification
• AutoML Vision Object Detection
• AutoML Video Intelligence Classification
• AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
• AutoML Natural Language Entity Extraction
• AutoML Natural Language Sentiment Analysis
• AutoML Tables

Sample 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();
 }
 

Parameters:

name - Required. Name of the model requested to serve the batch prediction.

inputConfig - Required. The input configuration for batch prediction.

outputConfig - Required. The Configuration specifying where output predictions should be written.

params - Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long.

AutoML Natural Language Classification

`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.

AutoML Vision Classification

`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.

AutoML Vision Object Detection

`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.

`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

`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.

`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.

`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.

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.

`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.

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.

AutoML Video Intelligence Object Tracking

`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.

`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.

`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:

ApiException - if the remote call fails

batchPredictAsync

public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(BatchPredictRequest request)

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:

• AutoML Vision Classification
• AutoML Vision Object Detection
• AutoML Video Intelligence Classification
• AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
• AutoML Natural Language Entity Extraction
• AutoML Natural Language Sentiment Analysis
• AutoML Tables

Sample 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();
 }
 

Parameters:

request - The request object containing all of the parameters for the API call.

Throws:

ApiException - if the remote call fails

batchPredictOperationCallable

public final OperationCallable<BatchPredictRequest,BatchPredictResult,OperationMetadata> batchPredictOperationCallable()

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:

• AutoML Vision Classification
• AutoML Vision Object Detection
• AutoML Video Intelligence Classification
• AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
• AutoML Natural Language Entity Extraction
• AutoML Natural Language Sentiment Analysis
• AutoML Tables

Sample 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();
 }
 

batchPredictCallable

public final UnaryCallable<BatchPredictRequest,Operation> batchPredictCallable()

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:

• AutoML Vision Classification
• AutoML Vision Object Detection
• AutoML Video Intelligence Classification
• AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification
• AutoML Natural Language Entity Extraction
• AutoML Natural Language Sentiment Analysis
• AutoML Tables

Sample 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();
 }
 

close

public final void close()

Specified by:

close in interface AutoCloseable

shutdown

public void shutdown()

Specified by:

shutdown in interface BackgroundResource

isShutdown

public boolean isShutdown()

Specified by:

isShutdown in interface BackgroundResource

isTerminated

public boolean isTerminated()

Specified by:

isTerminated in interface BackgroundResource

shutdownNow

public void shutdownNow()

Specified by:

shutdownNow in interface BackgroundResource

awaitTermination

public boolean awaitTermination(long duration,
 TimeUnit unit)
                         throws InterruptedException

Specified by:

awaitTermination in interface BackgroundResource

Throws:

InterruptedException