ELocator Class
EasyLocate tool - axis aligned bounding box version.
The ELocator locates and classifies objects (or defects). With this class, an object is defined by the axis-aligned bounding box that surrounds it and a label (see ELocatorObject class). The tool must be trained using a dataset with annotated objects.
The minimum size resolution supported by the tool is 128. The maximum size of the image supported is 500 000 pixels.
The tool has 5 main parameters:
- A set of anchors, i.e. pre-defined object size that it must be able to detect. The anchors can be automatically determined from the training dataset, specified manually using ELocator, or generated according to size information about the objects (see ELocator::GenerateAnchors).
- A detection threshold (ELocatorBase::DetectionThreshold) to accept or reject predicted objects based on their score.
- The maximum number of objects in an image (ELocatorBase::MaxNumberOfObjects)
- The maximum overlap between predicted objects with the same label (ELocator::SameLabelMaxOverlap, ELocatorBase::SameLabelMaxObjectProximity)
- The maximum overlap between predicted objects regardless of their label (ELocator::AbsoluteMaxOverlap, ELocatorBase::AbsoluteMaxObjectProximity).
Except for the anchors, all the parameters can be changed before and after training the tool.
Base Class:ELocatorBase
Namespace: Euresys::Open_eVision::EasyDeepLearning
Methods
The value of the parameter must be between 0 (no overlap allowed between two predicted objects with different labels) and 1 (full overlap allowed between two predicted objects with different labels).
Default value: 1.
The value of the parameter must be between 0 (no overlap allowed between two predicted objects with the same label) and 1 (full overlap allowed between two predicted objects with the same label). 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.
Default value: 0.5
The value of the parameter must be between 0 (no overlap allowed between two predicted objects with different labels) and 1 (full overlap allowed between two predicted objects with different labels).
Default value: 1.
The value of the parameter must be between 0 (no overlap allowed between two predicted objects with the same label) and 1 (full overlap allowed between two predicted objects with the same label). 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.
Default value: 0.5
ELocator Class
EasyLocate tool - axis aligned bounding box version.
The ELocator locates and classifies objects (or defects). With this class, an object is defined by the axis-aligned bounding box that surrounds it and a label (see ELocatorObject class). The tool must be trained using a dataset with annotated objects.
The minimum size resolution supported by the tool is 128. The maximum size of the image supported is 500 000 pixels.
The tool has 5 main parameters:
- A set of anchors, i.e. pre-defined object size that it must be able to detect. The anchors can be automatically determined from the training dataset, specified manually using ELocator, or generated according to size information about the objects (see ELocator::GenerateAnchors).
- A detection threshold (ELocatorBase::DetectionThreshold) to accept or reject predicted objects based on their score.
- The maximum number of objects in an image (ELocatorBase::MaxNumberOfObjects)
- The maximum overlap between predicted objects with the same label (ELocator::SameLabelMaxOverlap, ELocatorBase::SameLabelMaxObjectProximity)
- The maximum overlap between predicted objects regardless of their label (ELocator::AbsoluteMaxOverlap, ELocatorBase::AbsoluteMaxObjectProximity).
Except for the anchors, all the parameters can be changed before and after training the tool.
Base Class:ELocatorBase
Namespace: Euresys.Open_eVision.EasyDeepLearning
Properties
The value of the parameter must be between 0 (no overlap allowed between two predicted objects with different labels) and 1 (full overlap allowed between two predicted objects with different labels).
Default value: 1.
The value of the parameter must be between 0 (no overlap allowed between two predicted objects with the same label) and 1 (full overlap allowed between two predicted objects with the same label). 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.
Default value: 0.5
Methods