CVB.Net 14.0
Stemmer.Cvb.Polimago Namespace Reference

Classes

class  ClassificationPredictor
 Predictor to classify patterns with. More...
 
struct  ClassificationResult
 Polimago classification result container. More...
 
class  NamespaceDoc
 The namespace and assembly Stemmer.Cvb.Polimago contains the classes and definitions needed for using the Common Vision Blox Polimago tool. More...
 
class  PolimagoExtensions
 Extension methods for the Stemmer.Cvb.Polimago library. More...
 
class  PolimagoFactoryCreatedObject
 Base class for Polimago objects created by one of the factory classes. More...
 
class  PolimagoRefCountedObject
 Base class for Polimago's reference counted objects. More...
 
class  PredictorBase
 Base class for Polimago predictors. More...
 
class  PredictorBaseEx
 Base class for all Polimago predictors. More...
 
class  RegressionPredictor
 Polimago Regression predictor. More...
 
class  SearchPredictor
 Predictor that may be used for searching objects. More...
 
struct  SearchResult
 Search results as provided by a Search Classifier. More...
 
struct  SearchResultInternal
 Search results as provided by a Search Classifier, compatible with native code. More...
 

Enumerations

enum  ClassificationType { None , OneVersusAll , OneVersusOne }
 Determine the classification type to be carried out. More...
 
enum  InterpolationType { None = 0 , Linear = 1 }
 Interpolation to be used when extracting image data for classifier generation. More...
 
enum  InvarianceType { None = 0 , Translation = 1 , RotationScaleTranslation = 2 , AffineGroup = 3 }
 Invariance types that can be defined for training. More...
 

Enumeration Type Documentation

◆ ClassificationType

Determine the classification type to be carried out.

Enumerator
None 

The enum element indicating undefined state.

OneVersusAll 

Quick classification that tests versus all classes simultaneously (but potentially at the cost of result quality, especially if many classes are involved).

OneVersusOne 

Thorough classification that tests all possible pairs of classes (which yields potentially better results if many classes are involved but takes significantly longer than the OneVersusAll approach).

◆ InterpolationType

Interpolation to be used when extracting image data for classifier generation.

Enumerator
None 

Image data is (if necessary) extracted without interpolation.

Linear 

Image data is (if necessary) extracted with linear interpolation.

◆ InvarianceType

Invariance types that can be defined for training.

Enumerator
None 

No invariance (not valid for training!).

Translation 

Translation.

RotationScaleTranslation 

Rotation + Scale + Translation.

AffineGroup 

Affine group (i.e. 2x2 matrix plus translation)