ELocator Class
EasyLocate tool - axis aligned bounding box version.
The ELocator locates and classifies objects (or defects). With this class, an object In a general content, the term object should be understood with the meaning of a class instance. In EasyObject, an object is a maximally-sized area of adjacent connected pixels belonging to the layer foreground. 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
ELocatorBase::PredictionAnchors, or generated according to size information about the objects (seeELocator::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
License(s): EasyLocate and EasyLocateInference
Constructors
Properties
Type of the deep learning tool.
Maximum overlap (intersection over union) between two predicted objects regardless of their label.
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.
Maximum overlap (intersection over union) between two predicted objects with the same label.
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
Generates anchors based on the objects in the dataset or a formal specification.
For the version that takes a dataset, the properties ELocatorBase::Width and ELocatorBase::Height must be set.
Assignment operator
Serializes the settings of the locator.
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
ELocatorBase.PredictionAnchors, or generated according to size information about the objects (seeELocator.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
License(s): EasyLocate and EasyLocateInference
Constructors
Properties
Maximum overlap (intersection over union) between two predicted objects regardless of their label.
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.
Maximum overlap (intersection over union) between two predicted objects with the same label.
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
Type of the deep learning tool.
Methods
Generates anchors based on the objects in the dataset or a formal specification.
For the version that takes a dataset, the properties ELocatorBase.Width and ELocatorBase.Height must be set.
Serializes the settings of the locator.
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 ELocatorBase.PredictionAnchors, 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
Module: open_evision.EasyDeepLearning
License(s): EasyLocate and EasyLocateInference
Constructors
Properties
Maximum overlap (intersection over union) between two predicted objects regardless of their label.
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.
Maximum overlap (intersection over union) between two predicted objects with the same label.
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
Type of the deep learning tool.
Methods
Generates anchors based on the objects in the dataset or a formal specification.
For the version that takes a dataset, the properties ELocatorBase.Width and ELocatorBase.Height must be set.
Serializes the settings of the locator.