Collection of metrics used to evaluate the results of a ELocator tool. More...

Inheritance diagram for eVision.EasyDeepLearning.ELocatorMetrics:

Collaboration diagram for eVision.EasyDeepLearning.ELocatorMetrics:

Public Member Functions
	ELocatorMetrics ()
	Constructs an ELocatorMetrics object.
	ELocatorMetrics (eVision.EasyDeepLearning.ELocatorMetrics other)
	Copy constructor of an ELocatorMetrics object.
void	Load (string path)
	Loads a locator metric. The given ESerializer must have been created for reading.
void	Load (eVision.ESerializer serializer)
	Loads a locator metric. The given ESerializer must have been created for reading.
void	Save (string path)
	Saves a locator metric. The given ESerializer must have been created for writing.
void	Save (eVision.ESerializer serializer)
	Saves a locator metric. The given ESerializer must have been created for writing.
bool	IsValid ()
	Indicates whether the object contains at least one result.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetWeightedPrecisionRecallPoint ()
	Weighted precision and recall metrics for the current or specified threshold.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetWeightedPrecisionRecallPoint (float threshold)
	Weighted precision and recall metrics for the current or specified threshold.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetWeightedPrecisionRecallPoint (float[] weights)
	Weighted precision and recall metrics for the current or specified threshold.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetWeightedPrecisionRecallPoint (float threshold, float[] weights)
	Weighted precision and recall metrics for the current or specified threshold.
float	GetWeightedRecall ()
	Weighted average of the recall (true positive rate) for each label.
float	GetWeightedRecall (float[] weights)
	Weighted average of the recall (true positive rate) for each label.
float	GetLabelRecall (string label)
	Recall for the given label.
float	GetLabelRecall (int labelId)
	Recall for the given label.
float	GetBestWeightedRecall ()
	Best weighted recall achievable by changing the detection threshold.
float	GetBestWeightedRecall (float[] weights)
	Best weighted recall achievable by changing the detection threshold.
float	GetBestWeightedRecallThreshold ()
	Detection threshold that gives the best weighted recall (ELocatorMetrics.GetWeightedRecall).
float	GetBestWeightedRecallThreshold (float[] weights)
	Detection threshold that gives the best weighted recall (ELocatorMetrics.GetWeightedRecall).
void	GetBestWeightedRecallAndThreshold (ref float recall, ref float threshold)
	Best weighted recall achievable with the corresponding threshold.
void	GetBestWeightedRecallAndThreshold (float[] weights, ref float recall, ref float threshold)
	Best weighted recall achievable with the corresponding threshold.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetBestWeightedRecallPoint ()
	Best weighted recall achievable returned as a weighted precision/recall point.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetBestWeightedRecallPoint (float[] weights)
	Best weighted recall achievable returned as a weighted precision/recall point.
float	GetWeightedPrecision ()
	Weighted average of the precision (proportion of detected objects that are correct) for each label.
float	GetWeightedPrecision (float[] weights)
	Weighted average of the precision (proportion of detected objects that are correct) for each label.
float	GetLabelPrecision (string label)
	Precision for the given label.
float	GetLabelPrecision (int labelId)
	Precision for the given label.
float	GetBestWeightedPrecision ()
	Best weighted precision achievable by changing the detection threshold.
float	GetBestWeightedPrecision (float[] weights)
	Best weighted precision achievable by changing the detection threshold.
float	GetBestWeightedPrecisionThreshold ()
	Detection threshold that gives the best weighted precision (ELocatorMetrics.GetWeightedPrecision).
float	GetBestWeightedPrecisionThreshold (float[] weights)
	Detection threshold that gives the best weighted precision (ELocatorMetrics.GetWeightedPrecision).
void	GetBestWeightedPrecisionAndThreshold (ref float precision, ref float threshold)
	Best weighted precision achievable with the corresponding threshold.
void	GetBestWeightedPrecisionAndThreshold (float[] weights, ref float precision, ref float threshold)
	Best weighted precision achievable with the corresponding threshold.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetBestWeightedPrecisionPoint ()
	Best weighted precision achievable returned as a weighted precision/recall point.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetBestWeightedPrecisionPoint (float[] weights)
	Best weighted precision achievable returned as a weighted precision/recall point.
float	GetWeightedFScore ()
	Weighted average of the F-Score for each label.
float	GetWeightedFScore (float[] weights)
	Weighted average of the F-Score for each label.
float	GetLabelFScore (string label)
	F-Score for the given label.
float	GetLabelFScore (int labelId)
	F-Score for the given label.
float	GetBestWeightedFScore ()
	Best weighted F-Score achievable by changing the detection threshold.
float	GetBestWeightedFScore (float[] weights)
	Best weighted F-Score achievable by changing the detection threshold.
float	GetBestWeightedFScoreThreshold ()
	Detection threshold that gives the best weighted F-Score (ELocatorMetrics.GetWeightedFScore).
float	GetBestWeightedFScoreThreshold (float[] weights)
	Detection threshold that gives the best weighted F-Score (ELocatorMetrics.GetWeightedFScore).
void	GetBestWeightedFScoreAndThreshold (ref float fScore, ref float threshold)
	Best weighted F-Score achievable with the corresponding threshold.
void	GetBestWeightedFScoreAndThreshold (float[] weights, ref float fScore, ref float threshold)
	Best weighted F-Score achievable with the corresponding threshold.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetBestWeightedFScorePoint ()
	Best weighted F-Score achievable returned as a weighted precision/recall point.
eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint	GetBestWeightedFScorePoint (float[] weights)
	Best weighted F-Score achievable returned as a weighted precision/recall point.
uint	GetNumDetectedObjects ()
	Number of detected objects.
uint	GetNumDetectedObjects (string label)
	Number of detected objects.
uint	GetNumDetectedObjects (int labelId)
	Number of detected objects.
uint	GetNumCorrectlyDetectedObjects ()
	Number of correctly detected objects.
uint	GetNumCorrectlyDetectedObjects (string label)
	Number of correctly detected objects.
uint	GetNumCorrectlyDetectedObjects (int labelId)
	Number of correctly detected objects.
uint	GetNumUndetectedObjects ()
	Number of undetected objects.
uint	GetNumUndetectedObjects (string label)
	Number of undetected objects.
uint	GetNumUndetectedObjects (int labelId)
	Number of undetected objects.
float	GetLabelAveragePrecision (int labelIdx)
	Average precision for detection of objects from the given label.
float	GetLabelAverageProximity (int labelIdx)
	Average proximity of the predicted objects of the given label to the ground truth objects.
float	GetLabelIntersectionOverUnion (int labelIdx)
	Same as ELocatorMetrics.GetLabelAverageProximity.
string	GetLabel (int idx)
	Label.

Properties
float	Error `[get]`
	Error of the EasyLocate training algorithm (only available for the training metrics, see ELocatorBase.GetTrainingMetrics).
float	Recall `[get]`
	Recall (true positive rate, proportion of ground truth object that are correctly detected).
float	Precision `[get]`
	Precision (proportion of detected objects that are correct).
float	FScore `[get]`
	F-Score (harmonic mean of ELocatorMetrics.Recall and ELocatorMetrics.Precision).
float	AveragePrecision `[get]`
	Average Precision when matching prediction and ground truth with a minimum proximity of ELocatorBase.SameLabelMaxObjectProximity.
float	AveragePrecision50 `[get]`
	Average precision when matching prediction and ground truth with a minimum "proximity" of 0.5.
float	AverageProximity `[get]`
	Average proximity of the predicted objects to the ground truth objects.
float	IntersectionOverUnion `[get]`
	Same as ELocatorMetrics.AverageProximity.
float	DetectionThreshold `[get, set]`
	Threshold for detected objects.
float	ImageAccuracy `[get]`
	Image accuracy: the proportion of images that are correctly detected to contain or not objects, regardless of their labels.
uint	NumCorrectlyPredictedImagesWithObjects `[get]`
	Number of images containing objects that are correctly predicted as containing objects, regardless of the labels of the objects. This is the number of true positives at the image level.
uint	NumCorrectlyPredictedImagesWithoutObjects `[get]`
	Number of images without objects that are correctly predicted as containing no object. This is the number of true negatives at the image level.
uint	NumBadlyPredictedImagesWithObjects `[get]`
	Number of images with objects that are badly predicted as containing no object. This is the number of false negatives at the image level.
uint	NumBadlyPredictedImagesWithoutObjects `[get]`
	Number of images without objects that are badly predicted as containing objects. This is the number of false positives a the image level.
int	NumLabels `[get]`
	Number of labels recognized by the ELocator tool that produced these metrics.

Detailed Description

Collection of metrics used to evaluate the results of a ELocator tool.

License(s): BasicTypes

Constructor & Destructor Documentation

◆ ELocatorMetrics() [1/2]

eVision.EasyDeepLearning.ELocatorMetrics.ELocatorMetrics ( )

Constructs an ELocatorMetrics object.

◆ ELocatorMetrics() [2/2]

eVision.EasyDeepLearning.ELocatorMetrics.ELocatorMetrics ( eVision.EasyDeepLearning.ELocatorMetrics other )

Copy constructor of an ELocatorMetrics object.

Parameters

other Reference to the ELocatorMetrics object that should be copied

Member Function Documentation

◆ GetBestWeightedFScore() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScore ( )

Best weighted F-Score achievable by changing the detection threshold.

◆ GetBestWeightedFScore() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScore ( float[] weights )

Best weighted F-Score achievable by changing the detection threshold.

Parameters

weights Label weights

◆ GetBestWeightedFScoreAndThreshold() [1/2]

void eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScoreAndThreshold	(	float[]	weights,
		ref float	fScore,
		ref float	threshold )

Best weighted F-Score achievable with the corresponding threshold.

Parameters

weights	Label weights
fScore	Best weighted F-Score achievable
threshold	Threshold that achieves the best weighted F-Score

Deprecated

Use ELocatorMetrics.GetBestWeightedFScorePoint instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ GetBestWeightedFScoreAndThreshold() [2/2]

void eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScoreAndThreshold	(	ref float	fScore,
		ref float	threshold )

Best weighted F-Score achievable with the corresponding threshold.

Parameters

fScore	Best weighted F-Score achievable
threshold	Threshold that achieves the best weighted F-Score

Deprecated

Use ELocatorMetrics.GetBestWeightedFScorePoint instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ GetBestWeightedFScorePoint() [1/2]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScorePoint ( )

Best weighted F-Score achievable returned as a weighted precision/recall point.

◆ GetBestWeightedFScorePoint() [2/2]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScorePoint ( float[] weights )

Best weighted F-Score achievable returned as a weighted precision/recall point.

Parameters

weights Label weights

◆ GetBestWeightedFScoreThreshold() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScoreThreshold ( )

Detection threshold that gives the best weighted F-Score (ELocatorMetrics.GetWeightedFScore).

◆ GetBestWeightedFScoreThreshold() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedFScoreThreshold ( float[] weights )

Detection threshold that gives the best weighted F-Score (ELocatorMetrics.GetWeightedFScore).

Parameters

weights Label weights

◆ GetBestWeightedPrecision() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecision ( )

Best weighted precision achievable by changing the detection threshold.

◆ GetBestWeightedPrecision() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecision ( float[] weights )

Best weighted precision achievable by changing the detection threshold.

Parameters

weights Label weights

◆ GetBestWeightedPrecisionAndThreshold() [1/2]

void eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecisionAndThreshold	(	float[]	weights,
		ref float	precision,
		ref float	threshold )

Best weighted precision achievable with the corresponding threshold.

Parameters

weights	Label weights
precision	Best weighted precision achievable
threshold	Threshold that achieves the best weighted precision

Deprecated

Use ELocatorMetrics.GetBestWeightedPrecisionPoint instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ GetBestWeightedPrecisionAndThreshold() [2/2]

void eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecisionAndThreshold	(	ref float	precision,
		ref float	threshold )

Best weighted precision achievable with the corresponding threshold.

Parameters

precision	Best weighted precision achievable
threshold	Threshold that achieves the best weighted precision

Deprecated

Use ELocatorMetrics.GetBestWeightedPrecisionPoint instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ GetBestWeightedPrecisionPoint() [1/2]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecisionPoint ( )

Best weighted precision achievable returned as a weighted precision/recall point.

◆ GetBestWeightedPrecisionPoint() [2/2]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecisionPoint ( float[] weights )

Best weighted precision achievable returned as a weighted precision/recall point.

Parameters

weights Label weights

◆ GetBestWeightedPrecisionThreshold() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecisionThreshold ( )

Detection threshold that gives the best weighted precision (ELocatorMetrics.GetWeightedPrecision).

◆ GetBestWeightedPrecisionThreshold() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedPrecisionThreshold ( float[] weights )

Detection threshold that gives the best weighted precision (ELocatorMetrics.GetWeightedPrecision).

Parameters

weights Label weights

◆ GetBestWeightedRecall() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecall ( )

Best weighted recall achievable by changing the detection threshold.

◆ GetBestWeightedRecall() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecall ( float[] weights )

Best weighted recall achievable by changing the detection threshold.

Parameters

weights Label weights

◆ GetBestWeightedRecallAndThreshold() [1/2]

void eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecallAndThreshold	(	float[]	weights,
		ref float	recall,
		ref float	threshold )

Best weighted recall achievable with the corresponding threshold.

Parameters

weights	Label weights
recall	Best weighted recall achievable
threshold	Threshold that achieves the best weighted recall

Deprecated

Use ELocatorMetrics.GetBestWeightedRecallPoint instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ GetBestWeightedRecallAndThreshold() [2/2]

void eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecallAndThreshold	(	ref float	recall,
		ref float	threshold )

Best weighted recall achievable with the corresponding threshold.

Parameters

recall	Best weighted recall achievable
threshold	Threshold that achieves the best weighted recall

Deprecated

Use ELocatorMetrics.GetBestWeightedRecallPoint instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ GetBestWeightedRecallPoint() [1/2]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecallPoint ( )

Best weighted recall achievable returned as a weighted precision/recall point.

◆ GetBestWeightedRecallPoint() [2/2]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecallPoint ( float[] weights )

Best weighted recall achievable returned as a weighted precision/recall point.

Parameters

weights Label weights

◆ GetBestWeightedRecallThreshold() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecallThreshold ( )

Detection threshold that gives the best weighted recall (ELocatorMetrics.GetWeightedRecall).

◆ GetBestWeightedRecallThreshold() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetBestWeightedRecallThreshold ( float[] weights )

Detection threshold that gives the best weighted recall (ELocatorMetrics.GetWeightedRecall).

Parameters

weights Label weights

◆ GetLabel()

string eVision.EasyDeepLearning.ELocatorMetrics.GetLabel ( int idx )

Label.

Parameters

idx	Index of the label.

◆ GetLabelAveragePrecision()

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelAveragePrecision ( int labelIdx )

Average precision for detection of objects from the given label.

Parameters

labelIdx Label index

◆ GetLabelAverageProximity()

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelAverageProximity ( int labelIdx )

Average proximity of the predicted objects of the given label to the ground truth objects.

Parameters

labelIdx Index of the label.

Look at the documentation of ELocator and EInterestPointLocator for their definition of proximity.

◆ GetLabelFScore() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelFScore ( int labelId )

F-Score for the given label.

Parameters

labelId Label index

◆ GetLabelFScore() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelFScore ( string label )

F-Score for the given label.

Parameters

label Label

◆ GetLabelIntersectionOverUnion()

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelIntersectionOverUnion ( int labelIdx )

Same as ELocatorMetrics.GetLabelAverageProximity.

Parameters

labelIdx Index of the label.

Deprecated

Use ELocatorMetrics.GetLabelAverageProximity instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ GetLabelPrecision() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelPrecision ( int labelId )

Precision for the given label.

Parameters

labelId Label index

◆ GetLabelPrecision() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelPrecision ( string label )

Precision for the given label.

Parameters

label Label

◆ GetLabelRecall() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelRecall ( int labelId )

Recall for the given label.

Parameters

labelId Label index

◆ GetLabelRecall() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetLabelRecall ( string label )

Recall for the given label.

Parameters

label Label

◆ GetNumCorrectlyDetectedObjects() [1/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumCorrectlyDetectedObjects ( )

Number of correctly detected objects.

A correctly detected object is a predicted object that has a "proximity" higher than ELocatorBase.SameLabelMaxObjectProximity with a ground truth object of the same label.

A label can be specified to obtain the number of correctly detected objects for that label. Otherwise, the number of correctly detected objects is for all the labels.

◆ GetNumCorrectlyDetectedObjects() [2/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumCorrectlyDetectedObjects ( int labelId )

Number of correctly detected objects.

A correctly detected object is a predicted object that has a "proximity" higher than ELocatorBase.SameLabelMaxObjectProximity with a ground truth object of the same label.

A label can be specified to obtain the number of correctly detected objects for that label. Otherwise, the number of correctly detected objects is for all the labels.

Parameters

labelId Index of the label

◆ GetNumCorrectlyDetectedObjects() [3/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumCorrectlyDetectedObjects ( string label )

Number of correctly detected objects.

A correctly detected object is a predicted object that has a "proximity" higher than ELocatorBase.SameLabelMaxObjectProximity with a ground truth object of the same label.

A label can be specified to obtain the number of correctly detected objects for that label. Otherwise, the number of correctly detected objects is for all the labels.

Parameters

label Label

◆ GetNumDetectedObjects() [1/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumDetectedObjects ( )

Number of detected objects.

A label can be specified to obtain the number of detected objects for that label. Otherwise, the number of detected objects is for all the labels.

◆ GetNumDetectedObjects() [2/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumDetectedObjects ( int labelId )

Number of detected objects.

A label can be specified to obtain the number of detected objects for that label. Otherwise, the number of detected objects is for all the labels.

Parameters

labelId Index of the label

◆ GetNumDetectedObjects() [3/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumDetectedObjects ( string label )

Number of detected objects.

A label can be specified to obtain the number of detected objects for that label. Otherwise, the number of detected objects is for all the labels.

Parameters

label Label

◆ GetNumUndetectedObjects() [1/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumUndetectedObjects ( )

Number of undetected objects.

An undetected object is a ground truth object that is not matched to any predicted object of the same label with a proximity higher than ELocatorBase.SameLabelMaxObjectProximity.

A label can be specified to obtain the number of undetected objects for that label. Otherwise, the number of undetected objects is for all the labels.

◆ GetNumUndetectedObjects() [2/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumUndetectedObjects ( int labelId )

Number of undetected objects.

An undetected object is a ground truth object that is not matched to any predicted object of the same label with a proximity higher than ELocatorBase.SameLabelMaxObjectProximity.

A label can be specified to obtain the number of undetected objects for that label. Otherwise, the number of undetected objects is for all the labels.

Parameters

labelId Index of the label

◆ GetNumUndetectedObjects() [3/3]

uint eVision.EasyDeepLearning.ELocatorMetrics.GetNumUndetectedObjects ( string label )

Number of undetected objects.

An undetected object is a ground truth object that is not matched to any predicted object of the same label with a proximity higher than ELocatorBase.SameLabelMaxObjectProximity.

A label can be specified to obtain the number of undetected objects for that label. Otherwise, the number of undetected objects is for all the labels.

Parameters

label Label

◆ GetWeightedFScore() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedFScore ( )

Weighted average of the F-Score for each label.

◆ GetWeightedFScore() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedFScore ( float[] weights )

Weighted average of the F-Score for each label.

Parameters

weights Label weights

◆ GetWeightedPrecision() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedPrecision ( )

Weighted average of the precision (proportion of detected objects that are correct) for each label.

◆ GetWeightedPrecision() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedPrecision ( float[] weights )

Weighted average of the precision (proportion of detected objects that are correct) for each label.

Parameters

weights Label weights

◆ GetWeightedPrecisionRecallPoint() [1/4]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedPrecisionRecallPoint ( )

Weighted precision and recall metrics for the current or specified threshold.

◆ GetWeightedPrecisionRecallPoint() [2/4]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedPrecisionRecallPoint ( float threshold )

Weighted precision and recall metrics for the current or specified threshold.

Parameters

threshold Threshold for which to get the weighted precision/recall point

◆ GetWeightedPrecisionRecallPoint() [3/4]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedPrecisionRecallPoint	(	float	threshold,
		float[]	weights )

Weighted precision and recall metrics for the current or specified threshold.

Parameters

threshold	Threshold for which to get the weighted precision/recall point
weights	Label weights

◆ GetWeightedPrecisionRecallPoint() [4/4]

eVision.EasyDeepLearning.EWeightedPrecisionRecallPoint eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedPrecisionRecallPoint ( float[] weights )

Weighted precision and recall metrics for the current or specified threshold.

Parameters

weights Label weights

◆ GetWeightedRecall() [1/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedRecall ( )

Weighted average of the recall (true positive rate) for each label.

◆ GetWeightedRecall() [2/2]

float eVision.EasyDeepLearning.ELocatorMetrics.GetWeightedRecall ( float[] weights )

Weighted average of the recall (true positive rate) for each label.

Parameters

weights Label weights

◆ IsValid()

bool eVision.EasyDeepLearning.ELocatorMetrics.IsValid ( )

Indicates whether the object contains at least one result.

◆ Load() [1/2]

void eVision.EasyDeepLearning.ELocatorMetrics.Load ( eVision.ESerializer serializer )

Loads a locator metric. The given ESerializer must have been created for reading.

Parameters

serializer The serializer.

◆ Load() [2/2]

void eVision.EasyDeepLearning.ELocatorMetrics.Load ( string path )

Loads a locator metric. The given ESerializer must have been created for reading.

Parameters

path	The file path.

◆ Save() [1/2]

void eVision.EasyDeepLearning.ELocatorMetrics.Save ( eVision.ESerializer serializer )

Saves a locator metric. The given ESerializer must have been created for writing.

Parameters

serializer The ESerializer object that is written to.

◆ Save() [2/2]

void eVision.EasyDeepLearning.ELocatorMetrics.Save ( string path )

Saves a locator metric. The given ESerializer must have been created for writing.

Parameters

path	The file path.

Property Documentation

◆ AveragePrecision

float eVision.EasyDeepLearning.ELocatorMetrics.AveragePrecision

get

Average Precision when matching prediction and ground truth with a minimum proximity of ELocatorBase.SameLabelMaxObjectProximity.

◆ AveragePrecision50

float eVision.EasyDeepLearning.ELocatorMetrics.AveragePrecision50

get

Average precision when matching prediction and ground truth with a minimum "proximity" of 0.5.

◆ AverageProximity

float eVision.EasyDeepLearning.ELocatorMetrics.AverageProximity

get

Average proximity of the predicted objects to the ground truth objects.

This value is the average of ELocatorMetrics.GetLabelAverageProximity over all the labels.

Look at the documentation of ELocator and EInterestPointLocator for their definition of proximity.

◆ DetectionThreshold

float eVision.EasyDeepLearning.ELocatorMetrics.DetectionThreshold

getset

Threshold for detected objects.

◆ Error

float eVision.EasyDeepLearning.ELocatorMetrics.Error

get

Error of the EasyLocate training algorithm (only available for the training metrics, see ELocatorBase.GetTrainingMetrics).

◆ FScore

float eVision.EasyDeepLearning.ELocatorMetrics.FScore

get

F-Score (harmonic mean of ELocatorMetrics.Recall and ELocatorMetrics.Precision).

◆ ImageAccuracy

float eVision.EasyDeepLearning.ELocatorMetrics.ImageAccuracy

get

Image accuracy: the proportion of images that are correctly detected to contain or not objects, regardless of their labels.

◆ IntersectionOverUnion

float eVision.EasyDeepLearning.ELocatorMetrics.IntersectionOverUnion

get

Same as ELocatorMetrics.AverageProximity.

Deprecated

Use ELocatorMetrics.AverageProximity instead.

Deprecated in version 22.8. Scheduled to be removed in version 27.6.

◆ NumBadlyPredictedImagesWithObjects

uint eVision.EasyDeepLearning.ELocatorMetrics.NumBadlyPredictedImagesWithObjects

get

Number of images with objects that are badly predicted as containing no object. This is the number of false negatives at the image level.

◆ NumBadlyPredictedImagesWithoutObjects

uint eVision.EasyDeepLearning.ELocatorMetrics.NumBadlyPredictedImagesWithoutObjects

get

Number of images without objects that are badly predicted as containing objects. This is the number of false positives a the image level.

◆ NumCorrectlyPredictedImagesWithObjects

uint eVision.EasyDeepLearning.ELocatorMetrics.NumCorrectlyPredictedImagesWithObjects

get

Number of images containing objects that are correctly predicted as containing objects, regardless of the labels of the objects. This is the number of true positives at the image level.

◆ NumCorrectlyPredictedImagesWithoutObjects

uint eVision.EasyDeepLearning.ELocatorMetrics.NumCorrectlyPredictedImagesWithoutObjects

get

Number of images without objects that are correctly predicted as containing no object. This is the number of true negatives at the image level.

◆ NumLabels

int eVision.EasyDeepLearning.ELocatorMetrics.NumLabels

get

Number of labels recognized by the ELocator tool that produced these metrics.

◆ Precision

float eVision.EasyDeepLearning.ELocatorMetrics.Precision

get

Precision (proportion of detected objects that are correct).

◆ Recall

float eVision.EasyDeepLearning.ELocatorMetrics.Recall

get

Recall (true positive rate, proportion of ground truth object that are correctly detected).

Public Member Functions

Properties

Detailed Description

Constructor & Destructor Documentation

◆ ELocatorMetrics() [1/2]

◆ ELocatorMetrics() [2/2]

Member Function Documentation

◆ GetBestWeightedFScore() [1/2]

◆ GetBestWeightedFScore() [2/2]

◆ GetBestWeightedFScoreAndThreshold() [1/2]

◆ GetBestWeightedFScoreAndThreshold() [2/2]

◆ GetBestWeightedFScorePoint() [1/2]

◆ GetBestWeightedFScorePoint() [2/2]

◆ GetBestWeightedFScoreThreshold() [1/2]

◆ GetBestWeightedFScoreThreshold() [2/2]

◆ GetBestWeightedPrecision() [1/2]

◆ GetBestWeightedPrecision() [2/2]

◆ GetBestWeightedPrecisionAndThreshold() [1/2]

◆ GetBestWeightedPrecisionAndThreshold() [2/2]

◆ GetBestWeightedPrecisionPoint() [1/2]

◆ GetBestWeightedPrecisionPoint() [2/2]

◆ GetBestWeightedPrecisionThreshold() [1/2]

◆ GetBestWeightedPrecisionThreshold() [2/2]

◆ GetBestWeightedRecall() [1/2]

◆ GetBestWeightedRecall() [2/2]

◆ GetBestWeightedRecallAndThreshold() [1/2]

◆ GetBestWeightedRecallAndThreshold() [2/2]

◆ GetBestWeightedRecallPoint() [1/2]

◆ GetBestWeightedRecallPoint() [2/2]

◆ GetBestWeightedRecallThreshold() [1/2]

◆ GetBestWeightedRecallThreshold() [2/2]

◆ GetLabel()

◆ GetLabelAveragePrecision()

◆ GetLabelAverageProximity()

◆ GetLabelFScore() [1/2]

◆ GetLabelFScore() [2/2]

◆ GetLabelIntersectionOverUnion()

◆ GetLabelPrecision() [1/2]

◆ GetLabelPrecision() [2/2]

◆ GetLabelRecall() [1/2]

◆ GetLabelRecall() [2/2]

◆ GetNumCorrectlyDetectedObjects() [1/3]

◆ GetNumCorrectlyDetectedObjects() [2/3]

◆ GetNumCorrectlyDetectedObjects() [3/3]

◆ GetNumDetectedObjects() [1/3]

◆ GetNumDetectedObjects() [2/3]

◆ GetNumDetectedObjects() [3/3]

◆ GetNumUndetectedObjects() [1/3]

◆ GetNumUndetectedObjects() [2/3]

◆ GetNumUndetectedObjects() [3/3]

◆ GetWeightedFScore() [1/2]

◆ GetWeightedFScore() [2/2]

◆ GetWeightedPrecision() [1/2]

◆ GetWeightedPrecision() [2/2]

◆ GetWeightedPrecisionRecallPoint() [1/4]

◆ GetWeightedPrecisionRecallPoint() [2/4]

◆ GetWeightedPrecisionRecallPoint() [3/4]

◆ GetWeightedPrecisionRecallPoint() [4/4]

◆ GetWeightedRecall() [1/2]

◆ GetWeightedRecall() [2/2]

◆ IsValid()

◆ Load() [1/2]

◆ Load() [2/2]

◆ Save() [1/2]

◆ Save() [2/2]

Property Documentation

◆ AveragePrecision

◆ AveragePrecision50

◆ AverageProximity

◆ DetectionThreshold

◆ Error

◆ FScore

◆ ImageAccuracy

◆ IntersectionOverUnion

◆ NumBadlyPredictedImagesWithObjects

◆ NumBadlyPredictedImagesWithoutObjects

◆ NumCorrectlyPredictedImagesWithObjects

◆ NumCorrectlyPredictedImagesWithoutObjects

◆ NumLabels

◆ Precision