Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry.
Bounding box matching model metrics for a single intersection-over-union threshold and multiple label match confidence thresholds.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#confidence_metrics_entries
def confidence_metrics_entries() -> ::Array<::Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>
Returns
- (::Array<::Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>) — 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.
#confidence_metrics_entries=
def confidence_metrics_entries=(value) -> ::Array<::Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>
Parameter
- value (::Array<::Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>) — 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.
Returns
- (::Array<::Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>) — 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.
#iou_threshold
def iou_threshold() -> ::Float
Returns
- (::Float) — Output only. The intersection-over-union threshold value used to compute this metrics entry.
#iou_threshold=
def iou_threshold=(value) -> ::Float
Parameter
- value (::Float) — Output only. The intersection-over-union threshold value used to compute this metrics entry.
Returns
- (::Float) — Output only. The intersection-over-union threshold value used to compute this metrics entry.
#mean_average_precision
def mean_average_precision() -> ::Float
Returns
- (::Float) — Output only. The mean average precision, most often close to au_prc.
#mean_average_precision=
def mean_average_precision=(value) -> ::Float
Parameter
- value (::Float) — Output only. The mean average precision, most often close to au_prc.
Returns
- (::Float) — Output only. The mean average precision, most often close to au_prc.