Class BatchPredictRequest.Builder (2.27.0)

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

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictRequest.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

build()

public BatchPredictRequest build()
Returns
TypeDescription
BatchPredictRequest

buildPartial()

public BatchPredictRequest buildPartial()
Returns
TypeDescription
BatchPredictRequest

clear()

public BatchPredictRequest.Builder clear()
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

clearField(Descriptors.FieldDescriptor field)

public BatchPredictRequest.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

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
TypeDescription
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
TypeDescription
BatchPredictRequest.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public BatchPredictRequest.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

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
TypeDescription
BatchPredictRequest.Builder

clearParams()

public BatchPredictRequest.Builder clearParams()
Returns
TypeDescription
BatchPredictRequest.Builder

clone()

public BatchPredictRequest.Builder clone()
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

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_imp<span>ortan</span>ce - (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
NameDescription
keyString
Returns
TypeDescription
boolean

getDefaultInstanceForType()

public BatchPredictRequest getDefaultInstanceForType()
Returns
TypeDescription
BatchPredictRequest

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

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
TypeDescription
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
TypeDescription
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
TypeDescription
BatchPredictInputConfigOrBuilder

getMutableParams()

public Map<String,String> getMutableParams()

Use alternate mutation accessors instead.

Returns
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
BatchPredictOutputConfigOrBuilder

getParams()

public Map<String,String> getParams()

Use #getParamsMap() instead.

Returns
TypeDescription
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_imp<span>ortan</span>ce - (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
TypeDescription
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_imp<span>ortan</span>ce - (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
TypeDescription
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_imp<span>ortan</span>ce - (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
NameDescription
keyString
defaultValueString
Returns
TypeDescription
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_imp<span>ortan</span>ce - (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
NameDescription
keyString
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
boolean

Whether the outputConfig field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

internalGetMapField(int number)

protected MapField internalGetMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(BatchPredictRequest other)

public BatchPredictRequest.Builder mergeFrom(BatchPredictRequest other)
Parameter
NameDescription
otherBatchPredictRequest
Returns
TypeDescription
BatchPredictRequest.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public BatchPredictRequest.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides
Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public BatchPredictRequest.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

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
NameDescription
valueBatchPredictInputConfig
Returns
TypeDescription
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
NameDescription
valueBatchPredictOutputConfig
Returns
TypeDescription
BatchPredictRequest.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictRequest.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

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_imp<span>ortan</span>ce - (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
NameDescription
valuesMap<String,String>
Returns
TypeDescription
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_imp<span>ortan</span>ce - (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
NameDescription
keyString
valueString
Returns
TypeDescription
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_imp<span>ortan</span>ce - (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
NameDescription
keyString
Returns
TypeDescription
BatchPredictRequest.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictRequest.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

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
NameDescription
valueBatchPredictInputConfig
Returns
TypeDescription
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
NameDescription
builderForValueBatchPredictInputConfig.Builder
Returns
TypeDescription
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
NameDescription
valueString

The name to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for name to set.

Returns
TypeDescription
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
NameDescription
valueBatchPredictOutputConfig
Returns
TypeDescription
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
NameDescription
builderForValueBatchPredictOutputConfig.Builder
Returns
TypeDescription
BatchPredictRequest.Builder

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

public BatchPredictRequest.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides

setUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictRequest.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
BatchPredictRequest.Builder
Overrides