X-Boost  2.3.8
Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 123]
 Ndetail
 Nheatmap
 Nsprint
 Ntraits
 CAbsDecisionStumpA Weak Classifier based on a Feature Extractor policy
 CAdaBoost
 CAdaBoost< BoostableClassifier< WeakClassifier > >
 CAdaBoostMetricAdaBoost W+ metric (or any metric based on weighted pattern sum) for DecisionStumpPolicy (in this case only used as container for the param recovered) using PatternResponse
 CAdaBoostPatternAggregatorAggregagtor specific for AdaBoost, with a WeightedPattern PatternType
 CAdaBoostTrainer
 CBaseHaarFeatureGeneratorBase Feature Generator for Haar Bases using FeatureGenerator_t
 CBaseIntegralChannelFeatureGeneratorBase Feature Generator for IntegralChannelFeatureGenerators
 CBayesianStump
 CBayesianStumpOracle
 CBinaryClassifierA classifier composed by a Feature Extractor and an Evaluation Policy A "Second Level" classifier, merging a feature extractor algorithm with a feature evaluation classifier
 CBinaryClassifierOracle
 CBinaryWeightedPatternResponse
 CBoostableClassifier
 CBoostClassifier
 CBootStrapParamsParameters for BootStrapProcedure
 CBruteForceFeatureGeneratorA library able to generate any Haar Feature
 CBruteForceIntegralChannelFeatureGeneratorA library able to generate any IC Feature
 CCandidateObject reported by classifier
 CClassificationError
 CClassifierDetectHelper
 CClassifierDetectHelper< IntegralChannelImagePreprocessor, _Instance >Policy for ICHN
 CClassifierDetectHelper< IntegralImagePreprocessor, _Instance >IntegralImage detector, based on the multiple instance allocator with multiscale instance
 CCollapsedHaarFeatureOptimized HaarFeature
 CCollapsedHaarNodePrecomputed HaarNode in order to boost evaluation performance
 CComputeResponseOperator
 CCounter
 CDataSet
 CDataSetHandle
 CdatasetinVirtual pure pattern list reader
 CdatasetitemItem used for positive
 CdatasetobjectItem for positive/multiclass
 CDecisionStumpA Weak Classifier based on a Feature Extractor policy
 CDecisionTree
 CDecisionTreeLearnerA Decision Tree builder
 CDiscreteAdaBoostCommon
 CDTResponse
 CEntropy
 CFeatureDescription
 CFeatureGenerator
 CGentleAdaBoostMetric
 CGiniIndex
 CHaarFeatureAn haar Feature: a collection of weighted HaarNode
 CHaarNode
 CHardCascade
 CHardCascadeStage
 CHeatmapColorGenerator
 CHoGFeature
 CHoGParams
 CHoGPreprocessorPolicy to convert an Image in a HoG descriptor Input: BW Image | Output: RawData n scalar
 Chuman_readable_time
 CHyperPlaneClassifier
 CImageStructure to hold image data (memory)
 CImageClassifier"Binary" Classifier, virtual class
 CImageClassifierOperatorOperator used to collect pattern from the ProcessSet operator
 CImageClassifierWrapperBridge for ImageClassifier
 CImageHandle
 CImageResampler
 CIndirectBinaryClassifierA classifier composed by an index of a feature and an Evaluation Policy
 CIndirectDecisionTree
 CIntegerPolicyDiscrete policy
 CIntegralChannelFeatureSum of a rectangular area, implemented on top of Integral Image
 CIntegralChannelImageParamsParameters required to address a channel params
 CIntegralChannelImagePreprocessor
 CIntegralImage
 CIntegralImageDataIl dato IntegralImage e' pressoche' equivalente a quello di RawData < uint32_t >
 CIntegralImageHandle
 CIntegralImageParamsParameters required to access to integral image and to create features
 CIntegralImagePreprocessor
 Cjit
 CJITHaarFeature
 CJointSparseGranularFeatureGeneratorThis generator, instead of exhaustive, use a Random sampling approach
 Cmetric_cacheUna metrica che calcola la cache
 Cmetric_linearDot product
 CMultiClassClassifierA Multi-Class Classifier based on a Feature Extractor policy
 CMultiClassDataSet
 CMultiClassDataSetHandle
 CMultiClassDecisionStumpMultiThreshold
 CMultiClassDecisionStumpSingleThresholdA simple decision stump for multiclass problem using only one threshold for all problems
 CNaiveDecisionStump
 CNaiveDecisionStumpOracle
 CNormalizedHaarFeatureA rationale haar feature
 CObjectDetector
 CObjectDetectorGlobalParamsOver-Classifier params
 CObjectDetectorParams
 CObjectDetectorWrapper
 CObjectDetectorWrapperBaseSome common method that can be used to inner detector
 COptimizedIntegralChannelFeatureOptimized SumAreaFeature
 COptimizedSumAreaFeatureOptimized SumAreaFeature
 CPattern
 CPatternAggregatorHelp declaring some traits
 CPrecomputedPatternBinaryClassifierOracle
 CPrecomputedPatternResponse
 Crandom_bit_setExclusive random generator
 CRandomFeatureGeneratorThis generator, instead of exhaustive, use a Random sampling approach
 CRandomIntegralChannelFeatureGeneratorThis generator, instead of exhaustive, use a Random sampling approach
 CRawData
 CRealAdaBoostMetric
 CRealDecisionStumpA Weak Classifier based on a Feature Extractor policy
 CRealDecisionStumpOracle
 CRealToDiscrete
 CrectRectangle structure
 CReportTest
 CsdfinSDF file reader
 CSimpleDecisionStump
 CSingleTree
 CsizeImage/size TODO namespace
 CSoftCascadeClassifier
 CSoftCascadeStage
 CSourceDataSet
 CStatisticCompute timing statistics
 CStoredFeatureGeneratorThis generator uses a stored feature list
 CSumAreaFeatureSum of a rectangular area, implemented on top of Integral Image
 Csvm_trainSVM trainer
 CTimer
 CWeightedPattern
 CWeightedPatternResponse
 CWeightedPolicyWeighted policy
 CWindowEventManagerA generic Window object