Class ImageObjectDetectionEvaluationMetrics.Builder (2.3.15)

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public static final class ImageObjectDetectionEvaluationMetrics.Builder extends GeneratedMessageV3.Builder<ImageObjectDetectionEvaluationMetrics.Builder> implements ImageObjectDetectionEvaluationMetricsOrBuilder

Model evaluation metrics for image object detection problems. Evaluates prediction quality of labeled bounding boxes.

Protobuf type google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetrics

Static Methods

getDescriptor()

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

Methods

addAllBoundingBoxMetricsEntries(Iterable<? extends BoundingBoxMetricsEntry> values)

public ImageObjectDetectionEvaluationMetrics.Builder addAllBoundingBoxMetricsEntries(Iterable<? extends BoundingBoxMetricsEntry> values)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
valuesIterable<? extends com.google.cloud.automl.v1beta1.BoundingBoxMetricsEntry>
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

addBoundingBoxMetricsEntries(BoundingBoxMetricsEntry value)

public ImageObjectDetectionEvaluationMetrics.Builder addBoundingBoxMetricsEntries(BoundingBoxMetricsEntry value)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
valueBoundingBoxMetricsEntry
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

addBoundingBoxMetricsEntries(BoundingBoxMetricsEntry.Builder builderForValue)

public ImageObjectDetectionEvaluationMetrics.Builder addBoundingBoxMetricsEntries(BoundingBoxMetricsEntry.Builder builderForValue)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
builderForValueBoundingBoxMetricsEntry.Builder
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

addBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry value)

public ImageObjectDetectionEvaluationMetrics.Builder addBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry value)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameters
NameDescription
indexint
valueBoundingBoxMetricsEntry
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

addBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry.Builder builderForValue)

public ImageObjectDetectionEvaluationMetrics.Builder addBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry.Builder builderForValue)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameters
NameDescription
indexint
builderForValueBoundingBoxMetricsEntry.Builder
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

addBoundingBoxMetricsEntriesBuilder()

public BoundingBoxMetricsEntry.Builder addBoundingBoxMetricsEntriesBuilder()

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Returns
TypeDescription
BoundingBoxMetricsEntry.Builder

addBoundingBoxMetricsEntriesBuilder(int index)

public BoundingBoxMetricsEntry.Builder addBoundingBoxMetricsEntriesBuilder(int index)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
BoundingBoxMetricsEntry.Builder

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

build()

public ImageObjectDetectionEvaluationMetrics build()
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics

buildPartial()

public ImageObjectDetectionEvaluationMetrics buildPartial()
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics

clear()

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

clearBoundingBoxMeanAveragePrecision()

public ImageObjectDetectionEvaluationMetrics.Builder clearBoundingBoxMeanAveragePrecision()

Output only. The single metric for bounding boxes evaluation: the mean_average_precision averaged over all bounding_box_metrics_entries.

float bounding_box_mean_average_precision = 3;

Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

This builder for chaining.

clearBoundingBoxMetricsEntries()

public ImageObjectDetectionEvaluationMetrics.Builder clearBoundingBoxMetricsEntries()

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

clearEvaluatedBoundingBoxCount()

public ImageObjectDetectionEvaluationMetrics.Builder clearEvaluatedBoundingBoxCount()

Output only. The total number of bounding boxes (i.e. summed over all images) the ground truth used to create this evaluation had.

int32 evaluated_bounding_box_count = 1;

Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

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

clearOneof(Descriptors.OneofDescriptor oneof)

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

clone()

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

getBoundingBoxMeanAveragePrecision()

public float getBoundingBoxMeanAveragePrecision()

Output only. The single metric for bounding boxes evaluation: the mean_average_precision averaged over all bounding_box_metrics_entries.

float bounding_box_mean_average_precision = 3;

Returns
TypeDescription
float

The boundingBoxMeanAveragePrecision.

getBoundingBoxMetricsEntries(int index)

public BoundingBoxMetricsEntry getBoundingBoxMetricsEntries(int index)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
BoundingBoxMetricsEntry

getBoundingBoxMetricsEntriesBuilder(int index)

public BoundingBoxMetricsEntry.Builder getBoundingBoxMetricsEntriesBuilder(int index)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
BoundingBoxMetricsEntry.Builder

getBoundingBoxMetricsEntriesBuilderList()

public List<BoundingBoxMetricsEntry.Builder> getBoundingBoxMetricsEntriesBuilderList()

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Returns
TypeDescription
List<Builder>

getBoundingBoxMetricsEntriesCount()

public int getBoundingBoxMetricsEntriesCount()

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Returns
TypeDescription
int

getBoundingBoxMetricsEntriesList()

public List<BoundingBoxMetricsEntry> getBoundingBoxMetricsEntriesList()

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Returns
TypeDescription
List<BoundingBoxMetricsEntry>

getBoundingBoxMetricsEntriesOrBuilder(int index)

public BoundingBoxMetricsEntryOrBuilder getBoundingBoxMetricsEntriesOrBuilder(int index)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
BoundingBoxMetricsEntryOrBuilder

getBoundingBoxMetricsEntriesOrBuilderList()

public List<? extends BoundingBoxMetricsEntryOrBuilder> getBoundingBoxMetricsEntriesOrBuilderList()

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Returns
TypeDescription
List<? extends com.google.cloud.automl.v1beta1.BoundingBoxMetricsEntryOrBuilder>

getDefaultInstanceForType()

public ImageObjectDetectionEvaluationMetrics getDefaultInstanceForType()
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getEvaluatedBoundingBoxCount()

public int getEvaluatedBoundingBoxCount()

Output only. The total number of bounding boxes (i.e. summed over all images) the ground truth used to create this evaluation had.

int32 evaluated_bounding_box_count = 1;

Returns
TypeDescription
int

The evaluatedBoundingBoxCount.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(ImageObjectDetectionEvaluationMetrics other)

public ImageObjectDetectionEvaluationMetrics.Builder mergeFrom(ImageObjectDetectionEvaluationMetrics other)
Parameter
NameDescription
otherImageObjectDetectionEvaluationMetrics
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

mergeFrom(Message other)

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

mergeUnknownFields(UnknownFieldSet unknownFields)

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

removeBoundingBoxMetricsEntries(int index)

public ImageObjectDetectionEvaluationMetrics.Builder removeBoundingBoxMetricsEntries(int index)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

setBoundingBoxMeanAveragePrecision(float value)

public ImageObjectDetectionEvaluationMetrics.Builder setBoundingBoxMeanAveragePrecision(float value)

Output only. The single metric for bounding boxes evaluation: the mean_average_precision averaged over all bounding_box_metrics_entries.

float bounding_box_mean_average_precision = 3;

Parameter
NameDescription
valuefloat

The boundingBoxMeanAveragePrecision to set.

Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

This builder for chaining.

setBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry value)

public ImageObjectDetectionEvaluationMetrics.Builder setBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry value)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameters
NameDescription
indexint
valueBoundingBoxMetricsEntry
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

setBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry.Builder builderForValue)

public ImageObjectDetectionEvaluationMetrics.Builder setBoundingBoxMetricsEntries(int index, BoundingBoxMetricsEntry.Builder builderForValue)

Output only. The bounding boxes match metrics for each Intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair.

repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry bounding_box_metrics_entries = 2;

Parameters
NameDescription
indexint
builderForValueBoundingBoxMetricsEntry.Builder
Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

setEvaluatedBoundingBoxCount(int value)

public ImageObjectDetectionEvaluationMetrics.Builder setEvaluatedBoundingBoxCount(int value)

Output only. The total number of bounding boxes (i.e. summed over all images) the ground truth used to create this evaluation had.

int32 evaluated_bounding_box_count = 1;

Parameter
NameDescription
valueint

The evaluatedBoundingBoxCount to set.

Returns
TypeDescription
ImageObjectDetectionEvaluationMetrics.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

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

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

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

setUnknownFields(UnknownFieldSet unknownFields)

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