Class BatchPredictRequest.Builder (2.42.0)

public static final class BatchPredictRequest.Builder extends GeneratedMessageV3.Builder<BatchPredictRequest.Builder> implements BatchPredictRequestOrBuilder

Request message for PredictionService.BatchPredict.

Protobuf type google.cloud.automl.v1beta1.BatchPredictRequest

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > BatchPredictRequest.Builder

Implements

BatchPredictRequestOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
`Descriptor`

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictRequest.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
`field`	`FieldDescriptor`
`value`	`Object`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public BatchPredictRequest build()

Returns
Type	Description
`BatchPredictRequest`

buildPartial()

public BatchPredictRequest buildPartial()

Returns
Type	Description
`BatchPredictRequest`

clear()

public BatchPredictRequest.Builder clear()

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearField(Descriptors.FieldDescriptor field)

public BatchPredictRequest.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
`field`	`FieldDescriptor`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearInputConfig()

public BatchPredictRequest.Builder clearInputConfig()

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictRequest.Builder`

clearName()

public BatchPredictRequest.Builder clearName()

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

string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
`BatchPredictRequest.Builder`	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public BatchPredictRequest.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
`oneof`	`OneofDescriptor`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearOutputConfig()

public BatchPredictRequest.Builder clearOutputConfig()

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictRequest.Builder`

clearParams()

public BatchPredictRequest.Builder clearParams()

Returns
Type	Description
`BatchPredictRequest.Builder`

clone()

public BatchPredictRequest.Builder clone()

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

containsParams(String key)

public boolean containsParams(String key)

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`key`	`String`

Returns
Type	Description
`boolean`

getDefaultInstanceForType()

public BatchPredictRequest getDefaultInstanceForType()

Returns
Type	Description
`BatchPredictRequest`

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
`Descriptor`

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getInputConfig()

public BatchPredictInputConfig getInputConfig()

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictInputConfig`	The inputConfig.

getInputConfigBuilder()

public BatchPredictInputConfig.Builder getInputConfigBuilder()

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictInputConfig.Builder`

getInputConfigOrBuilder()

public BatchPredictInputConfigOrBuilder getInputConfigOrBuilder()

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictInputConfigOrBuilder`

getMutableParams() (deprecated)

public Map<String,String> getMutableParams()

Use alternate mutation accessors instead.

Returns
Type	Description
`Map<String,String>`

getName()

public String getName()

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

string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
`String`	The name.

getNameBytes()

public ByteString getNameBytes()

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

string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
`ByteString`	The bytes for name.

getOutputConfig()

public BatchPredictOutputConfig getOutputConfig()

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictOutputConfig`	The outputConfig.

getOutputConfigBuilder()

public BatchPredictOutputConfig.Builder getOutputConfigBuilder()

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictOutputConfig.Builder`

getOutputConfigOrBuilder()

public BatchPredictOutputConfigOrBuilder getOutputConfigOrBuilder()

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`BatchPredictOutputConfigOrBuilder`

getParams() (deprecated)

public Map<String,String> getParams()

Use #getParamsMap() instead.

Returns
Type	Description
`Map<String,String>`

getParamsCount()

public int getParamsCount()

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`int`

getParamsMap()

public Map<String,String> getParamsMap()

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`Map<String,String>`

getParamsOrDefault(String key, String defaultValue)

public String getParamsOrDefault(String key, String defaultValue)

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
`key`	`String`
`defaultValue`	`String`

Returns
Type	Description
`String`

getParamsOrThrow(String key)

public String getParamsOrThrow(String key)

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`key`	`String`

Returns
Type	Description
`String`

hasInputConfig()

public boolean hasInputConfig()

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`boolean`	Whether the inputConfig field is set.

hasOutputConfig()

public boolean hasOutputConfig()

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
`boolean`	Whether the outputConfig field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
`FieldAccessorTable`

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

internalGetMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)

Parameter
Name	Description
`number`	`int`

Returns
Type	Description
`com.google.protobuf.MapFieldReflectionAccessor`

Overrides

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

internalGetMutableMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)

Parameter
Name	Description
`number`	`int`

Returns
Type	Description
`com.google.protobuf.MapFieldReflectionAccessor`

Overrides

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
`boolean`

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(BatchPredictRequest other)

public BatchPredictRequest.Builder mergeFrom(BatchPredictRequest other)

Parameter
Name	Description
`other`	`BatchPredictRequest`

Returns
Type	Description
`BatchPredictRequest.Builder`

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public BatchPredictRequest.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
`input`	`CodedInputStream`
`extensionRegistry`	`ExtensionRegistryLite`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions
Type	Description
`IOException`

mergeFrom(Message other)

public BatchPredictRequest.Builder mergeFrom(Message other)

Parameter
Name	Description
`other`	`Message`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeInputConfig(BatchPredictInputConfig value)

public BatchPredictRequest.Builder mergeInputConfig(BatchPredictInputConfig value)

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`value`	`BatchPredictInputConfig`

Returns
Type	Description
`BatchPredictRequest.Builder`

mergeOutputConfig(BatchPredictOutputConfig value)

public BatchPredictRequest.Builder mergeOutputConfig(BatchPredictOutputConfig value)

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`value`	`BatchPredictOutputConfig`

Returns
Type	Description
`BatchPredictRequest.Builder`

mergeUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictRequest.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

putAllParams(Map<String,String> values)

public BatchPredictRequest.Builder putAllParams(Map<String,String> values)

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`values`	`Map<String,String>`

Returns
Type	Description
`BatchPredictRequest.Builder`

putParams(String key, String value)

public BatchPredictRequest.Builder putParams(String key, String value)

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
`key`	`String`
`value`	`String`

Returns
Type	Description
`BatchPredictRequest.Builder`

removeParams(String key)

public BatchPredictRequest.Builder removeParams(String key)

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

For Text 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.
For Image 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.
For Image 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) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
For Video 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. 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. The default is "false". 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. 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. The default is "false".
For Tables:

feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
For Video 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) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

map<string, string> params = 5 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`key`	`String`

Returns
Type	Description
`BatchPredictRequest.Builder`

setField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictRequest.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
`field`	`FieldDescriptor`
`value`	`Object`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setInputConfig(BatchPredictInputConfig value)

public BatchPredictRequest.Builder setInputConfig(BatchPredictInputConfig value)

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`value`	`BatchPredictInputConfig`

Returns
Type	Description
`BatchPredictRequest.Builder`

setInputConfig(BatchPredictInputConfig.Builder builderForValue)

public BatchPredictRequest.Builder setInputConfig(BatchPredictInputConfig.Builder builderForValue)

Required. The input configuration for batch prediction.

.google.cloud.automl.v1beta1.BatchPredictInputConfig input_config = 3 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`builderForValue`	`BatchPredictInputConfig.Builder`

Returns
Type	Description
`BatchPredictRequest.Builder`

setName(String value)

public BatchPredictRequest.Builder setName(String value)

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

string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Parameter
Name	Description
`value`	`String` The name to set.

Returns
Type	Description
`BatchPredictRequest.Builder`	This builder for chaining.

setNameBytes(ByteString value)

public BatchPredictRequest.Builder setNameBytes(ByteString value)

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

string name = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Parameter
Name	Description
`value`	`ByteString` The bytes for name to set.

Returns
Type	Description
`BatchPredictRequest.Builder`	This builder for chaining.

setOutputConfig(BatchPredictOutputConfig value)

public BatchPredictRequest.Builder setOutputConfig(BatchPredictOutputConfig value)

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`value`	`BatchPredictOutputConfig`

Returns
Type	Description
`BatchPredictRequest.Builder`

setOutputConfig(BatchPredictOutputConfig.Builder builderForValue)

public BatchPredictRequest.Builder setOutputConfig(BatchPredictOutputConfig.Builder builderForValue)

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

.google.cloud.automl.v1beta1.BatchPredictOutputConfig output_config = 4 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
`builderForValue`	`BatchPredictOutputConfig.Builder`

Returns
Type	Description
`BatchPredictRequest.Builder`

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public BatchPredictRequest.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters
Name	Description
`field`	`FieldDescriptor`
`index`	`int`
`value`	`Object`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictRequest.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
`unknownFields`	`UnknownFieldSet`

Returns
Type	Description
`BatchPredictRequest.Builder`

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)