public static final class BoundingBoxMetricsEntry.Builder extends GeneratedMessageV3.Builder<BoundingBoxMetricsEntry.Builder> implements BoundingBoxMetricsEntryOrBuilder
Bounding box matching model metrics for a single intersection-over-union
threshold and multiple label match confidence thresholds.
Protobuf type google.cloud.automl.v1beta1.BoundingBoxMetricsEntry
Static Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns
Methods
addAllConfidenceMetricsEntries(Iterable<? extends BoundingBoxMetricsEntry.ConfidenceMetricsEntry> values)
public BoundingBoxMetricsEntry.Builder addAllConfidenceMetricsEntries(Iterable<? extends BoundingBoxMetricsEntry.ConfidenceMetricsEntry> values)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Name | Description |
values | Iterable<? extends com.google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry>
|
Returns
addConfidenceMetricsEntries(BoundingBoxMetricsEntry.ConfidenceMetricsEntry value)
public BoundingBoxMetricsEntry.Builder addConfidenceMetricsEntries(BoundingBoxMetricsEntry.ConfidenceMetricsEntry value)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Returns
addConfidenceMetricsEntries(BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder builderForValue)
public BoundingBoxMetricsEntry.Builder addConfidenceMetricsEntries(BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder builderForValue)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Returns
addConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry value)
public BoundingBoxMetricsEntry.Builder addConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry value)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameters
Returns
addConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder builderForValue)
public BoundingBoxMetricsEntry.Builder addConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder builderForValue)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameters
Returns
addConfidenceMetricsEntriesBuilder()
public BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder addConfidenceMetricsEntriesBuilder()
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Returns
addConfidenceMetricsEntriesBuilder(int index)
public BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder addConfidenceMetricsEntriesBuilder(int index)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Returns
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public BoundingBoxMetricsEntry.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
build()
public BoundingBoxMetricsEntry build()
Returns
buildPartial()
public BoundingBoxMetricsEntry buildPartial()
Returns
clear()
public BoundingBoxMetricsEntry.Builder clear()
Returns
Overrides
clearConfidenceMetricsEntries()
public BoundingBoxMetricsEntry.Builder clearConfidenceMetricsEntries()
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Returns
clearField(Descriptors.FieldDescriptor field)
public BoundingBoxMetricsEntry.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Returns
Overrides
clearIouThreshold()
public BoundingBoxMetricsEntry.Builder clearIouThreshold()
Output only. The intersection-over-union threshold value used to compute
this metrics entry.
float iou_threshold = 1;
Returns
clearMeanAveragePrecision()
public BoundingBoxMetricsEntry.Builder clearMeanAveragePrecision()
Output only. The mean average precision, most often close to au_prc.
float mean_average_precision = 2;
Returns
clearOneof(Descriptors.OneofDescriptor oneof)
public BoundingBoxMetricsEntry.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Returns
Overrides
clone()
public BoundingBoxMetricsEntry.Builder clone()
Returns
Overrides
getConfidenceMetricsEntries(int index)
public BoundingBoxMetricsEntry.ConfidenceMetricsEntry getConfidenceMetricsEntries(int index)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Returns
getConfidenceMetricsEntriesBuilder(int index)
public BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder getConfidenceMetricsEntriesBuilder(int index)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Returns
getConfidenceMetricsEntriesBuilderList()
public List<BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder> getConfidenceMetricsEntriesBuilderList()
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Returns
getConfidenceMetricsEntriesCount()
public int getConfidenceMetricsEntriesCount()
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Returns
getConfidenceMetricsEntriesList()
public List<BoundingBoxMetricsEntry.ConfidenceMetricsEntry> getConfidenceMetricsEntriesList()
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Returns
getConfidenceMetricsEntriesOrBuilder(int index)
public BoundingBoxMetricsEntry.ConfidenceMetricsEntryOrBuilder getConfidenceMetricsEntriesOrBuilder(int index)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Returns
getConfidenceMetricsEntriesOrBuilderList()
public List<? extends BoundingBoxMetricsEntry.ConfidenceMetricsEntryOrBuilder> getConfidenceMetricsEntriesOrBuilderList()
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Returns
Type | Description |
List<? extends com.google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntryOrBuilder> | |
getDefaultInstanceForType()
public BoundingBoxMetricsEntry getDefaultInstanceForType()
Returns
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Returns
Overrides
getIouThreshold()
public float getIouThreshold()
Output only. The intersection-over-union threshold value used to compute
this metrics entry.
float iou_threshold = 1;
Returns
Type | Description |
float | The iouThreshold.
|
getMeanAveragePrecision()
public float getMeanAveragePrecision()
Output only. The mean average precision, most often close to au_prc.
float mean_average_precision = 2;
Returns
Type | Description |
float | The meanAveragePrecision.
|
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Overrides
isInitialized()
public final boolean isInitialized()
Returns
Overrides
mergeFrom(BoundingBoxMetricsEntry other)
public BoundingBoxMetricsEntry.Builder mergeFrom(BoundingBoxMetricsEntry other)
Parameter
Returns
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public BoundingBoxMetricsEntry.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Overrides
Exceptions
mergeFrom(Message other)
public BoundingBoxMetricsEntry.Builder mergeFrom(Message other)
Parameter
Returns
Overrides
mergeUnknownFields(UnknownFieldSet unknownFields)
public final BoundingBoxMetricsEntry.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides
removeConfidenceMetricsEntries(int index)
public BoundingBoxMetricsEntry.Builder removeConfidenceMetricsEntries(int index)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameter
Returns
setConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry value)
public BoundingBoxMetricsEntry.Builder setConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry value)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameters
Returns
setConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder builderForValue)
public BoundingBoxMetricsEntry.Builder setConfidenceMetricsEntries(int index, BoundingBoxMetricsEntry.ConfidenceMetricsEntry.Builder builderForValue)
Output only. Metrics for each label-match confidence_threshold from
0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is
derived from them.
repeated .google.cloud.automl.v1beta1.BoundingBoxMetricsEntry.ConfidenceMetricsEntry confidence_metrics_entries = 3;
Parameters
Returns
setField(Descriptors.FieldDescriptor field, Object value)
public BoundingBoxMetricsEntry.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
setIouThreshold(float value)
public BoundingBoxMetricsEntry.Builder setIouThreshold(float value)
Output only. The intersection-over-union threshold value used to compute
this metrics entry.
float iou_threshold = 1;
Parameter
Name | Description |
value | float
The iouThreshold to set.
|
Returns
setMeanAveragePrecision(float value)
public BoundingBoxMetricsEntry.Builder setMeanAveragePrecision(float value)
Output only. The mean average precision, most often close to au_prc.
float mean_average_precision = 2;
Parameter
Name | Description |
value | float
The meanAveragePrecision to set.
|
Returns
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public BoundingBoxMetricsEntry.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
Returns
Overrides
setUnknownFields(UnknownFieldSet unknownFields)
public final BoundingBoxMetricsEntry.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides