ELocatorBase::GetSameLabelMaxObjectProximity

ELocatorBase::SetSameLabelMaxObjectProximity

Maximum proximity between two predicted objects with the same label.
The value of the parameter can be between
- 0 when the two objects are completely outside their respective zone of influence; and
- 1 when the two predicted objects are the same.
The actual implementation of the proximity depends on the type of locator tool.
A low value will reduce the amount of falsely detected objects but may increase the number of missed objects. A high value will increase the number of falsely detected objects and reduce the number of missed objects.
See also ELocator::SameLabelMaxOverlap and EInterestPointLocator::SameLabelMinDistance. Default value: 0.5

Namespace: Euresys::Open_eVision::EasyDeepLearning

[C++]

float GetSameLabelMaxObjectProximity() const

void SetSameLabelMaxObjectProximity(float val)

Remarks

This parameter is also used to compute the matching between ground truth and predicted objects during evaluation.
This parameter can be changed before and after training.

ELocatorBase.SameLabelMaxObjectProximity

Maximum proximity between two predicted objects with the same label.
The value of the parameter can be between
- 0 when the two objects are completely outside their respective zone of influence; and
- 1 when the two predicted objects are the same.
The actual implementation of the proximity depends on the type of locator tool.
A low value will reduce the amount of falsely detected objects but may increase the number of missed objects. A high value will increase the number of falsely detected objects and reduce the number of missed objects.
See also ELocator::SameLabelMaxOverlap and EInterestPointLocator::SameLabelMinDistance. Default value: 0.5

Namespace: Euresys.Open_eVision.EasyDeepLearning

[C#]

float SameLabelMaxObjectProximity

{ get; set; }

Remarks

This parameter is also used to compute the matching between ground truth and predicted objects during evaluation.
This parameter can be changed before and after training.