Skip to content
Snippets Groups Projects
Commit 3b49c568 authored by Thomas Feuvrier's avatar Thomas Feuvrier
Browse files

Suppression de variable de classe non utilisées: 

Sample
VectorLabel
parent db009d21
Branches
Tags
No related merge requests found
Hide whitespace changes
Inline Side-by-side
Code/Learning/otbSVMClassifier.h
+ 3
− 27
View file @ 3b49c568
......@@ -74,34 +74,15 @@ public:
typedef typename Superclass::MembershipFunctionPointerVector
MembershipFunctionPointerVector ;
// FIXME : typedef TLabel ClassLabelType ;
typedef unsigned int ClassLabelType ;
typedef std::vector< ClassLabelType > ClassLabelVectorType ;
/** typedef for label type */
typedef TLabel ClassLabelType ;
// /** Sets the target data that will be classified by this */
// void SetSample(const TSample* sample) ;
// /** Returns the target data */
// const TSample* GetSample() const;
// /** Sets the user given class labels for membership functions.
// * If users do not provide class labels for membership functions by calling
// * this function, then the index of the membership function vector for a
// * membership function will be used as class label of measurement vectors
// * belong to the membership function */
// void SetMembershipFunctionClassLabels( ClassLabelVectorType& labels) ;
// /** Gets the user given class labels */
// ClassLabelVectorType& GetMembershipFunctionClassLabels()
// { return m_ClassLabels ; }
// /** Returns the classification result */
/** Returns the classification result */
OutputType* GetOutput() ;
/** Type definitions for the SVM Model. */
typedef SVMModel< InputPixelType, TLabel > SVMModelType;
typedef typename SVMModelType::Pointer SVMModelPointer;
......@@ -123,15 +104,10 @@ protected:
void DoClassification() ;
private:
/** Target data sample pointer*/
const TSample* m_Sample ;
/** Output pointer (MembershipSample) */
typename OutputType::Pointer m_Output ;
/** User given class labels for membership functions */
ClassLabelVectorType m_ClassLabels ;
SVMModelPointer m_Model;
} ; // end of class
......
Code/Learning/otbSVMClassifier.txx
+ 12
− 160
View file @ 3b49c568
......@@ -27,7 +27,6 @@ template< class TSample, class TLabel >
SVMClassifier< TSample, TLabel >
::SVMClassifier()
{
m_Sample = 0 ;
m_Output = OutputType::New() ;
m_Model = SVMModelType::New();
}
......@@ -38,51 +37,8 @@ SVMClassifier< TSample, TLabel >
::PrintSelf(std::ostream& os, itk::Indent indent) const
{
Superclass::PrintSelf(os,indent);
// os << indent << "Sample: " ;
// if ( m_Sample != 0 )
// {
// os << m_Sample << std::endl;
// }
// else
// {
// os << "not set." << std::endl ;
// }
// os << indent << "Output: " << m_Output << std::endl;
}
// template< class TSample, class TLabel >
// void
// SVMClassifier< TSample, TLabel >
// ::SetSample(const TSample* sample)
// {
// otbMsgDebugMacro( << "SVMClassifier::SetSample enter" );
// if ( m_Sample != sample )
// {
// m_Sample = sample ;
// m_Output->SetSample(sample) ;
// }
// otbMsgDebugMacro( << "SVMClassifier::SetSample exit" );
// }
// template< class TSample, class TLabel >
// const TSample*
// SVMClassifier< TSample, TLabel >
// ::GetSample() const
// {
// return m_Sample ;
// }
// template< class TSample, class TLabel >
// void
// SVMClassifier< TSample, TLabel >
// ::SetMembershipFunctionClassLabels(ClassLabelVectorType& labels)
// {
// m_ClassLabels = labels ;
// }
template< class TSample, class TLabel >
void
SVMClassifier< TSample, TLabel >
......@@ -99,26 +55,18 @@ SVMClassifier< TSample, TLabel >
::GenerateData()
{
// otbMsgDebugMacro( << "Before Resize 0" );
/* unsigned int i ;
typename TSample::ConstIterator iter = this->GetSample()->Begin() ;
typename TSample::ConstIterator end = this->GetSample()->End() ;
typename TSample::MeasurementVectorType measurements ;
*/
// otbMsgDebugMacro( << "Before Resize " );
m_Output->SetSample(this->GetSample()) ;
otbMsgDebugMacro( << "m_Output " << m_Output );
otbMsgDevMacro( << "m_Output " << m_Output );
m_Output->Resize( this->GetSample()->Size() ) ;
otbMsgDebugMacro( << "Resize to " << this->GetSample()->Size() );
otbMsgDebugMacro( << "Resize to " << m_Output->GetSample()->Size() );
otbMsgDevMacro( << "Resize to " << this->GetSample()->Size() );
otbMsgDevMacro( << "Resize to " << m_Output->GetSample()->Size() );
//std::vector< double > discriminantScores ;
unsigned int numberOfClasses = this->GetNumberOfClasses() ;
otbMsgDebugMacro( << "NbClass " << numberOfClasses );
otbMsgDevMacro( << "NbClass " << numberOfClasses );
//discriminantScores.resize(numberOfClasses) ;
//unsigned int classLabel ;
......@@ -128,41 +76,10 @@ SVMClassifier< TSample, TLabel >
/*typename Superclass::DecisionRuleType::Pointer rule =
this->GetDecisionRule() ;*/
otbMsgDebugMacro( << "Do Classif " );
otbMsgDevMacro( << "Do Classif " );
this->DoClassification();
otbMsgDebugMacro( << "End of classif" );
// if ( m_ClassLabels.size() != this->GetNumberOfMembershipFunctions() )
// {
// while (iter != end)
// {
// measurements = iter.GetMeasurementVector() ;
// for (i = 0 ; i < numberOfClasses ; i++)
// {
// discriminantScores[i] =
// (this->GetMembershipFunction(i))->Evaluate(measurements) ;
// }
// classLabel = rule->Evaluate(discriminantScores) ;
// m_Output->AddInstance(classLabel, iter.GetInstanceIdentifier()) ;
// ++iter ;
// }
// }
// else
// {
// while (iter != end)
// {
// measurements = iter.GetMeasurementVector() ;
// for (i = 0 ; i < numberOfClasses ; i++)
// {
// discriminantScores[i] =
// (this->GetMembershipFunction(i))->Evaluate(measurements) ;
// }
// classLabel = rule->Evaluate(discriminantScores) ;
// m_Output->AddInstance(m_ClassLabels[classLabel],
// iter.GetInstanceIdentifier()) ;
// ++iter ;
// }
// }
otbMsgDevMacro( << "End of classif" );
}
template< class TSample, class TLabel >
......@@ -203,7 +120,7 @@ SVMClassifier< TSample, TLabel >
x = new svm_node[numberOfComponentsPerSample+1];//m_Model->GetXSpace();
otbMsgDebugMacro( << "XSpace Allocated" );
otbMsgDevMacro( << "XSpace Allocated" );
if(svm_check_probability_model(model)==0)
{
throw itk::ExceptionObject(__FILE__, __LINE__,
......@@ -212,10 +129,10 @@ SVMClassifier< TSample, TLabel >
}
int svm_type=svm_get_svm_type(model);
otbMsgDebugMacro( << "SVM Type = " << svm_type );
otbMsgDevMacro( << "SVM Type = " << svm_type );
int nr_class=svm_get_nr_class(model);
otbMsgDebugMacro( << "SVM nr_class = " << nr_class );
otbMsgDevMacro( << "SVM nr_class = " << nr_class );
int *labels=(int *) malloc(nr_class*sizeof(int));
double *prob_estimates=NULL;
......@@ -231,109 +148,52 @@ SVMClassifier< TSample, TLabel >
prob_estimates = (double *) malloc(nr_class*sizeof(double));
}
/*fprintf(output,"labels");
for(j=0;j<nr_class;j++)
fprintf(output," %d",labels[j]);
fprintf(output,"\n");*/
}
// while(1)
otbMsgDebugMacro( << "Starting iterations " );
otbMsgDevMacro( << "Starting iterations " );
while (iter != end && iterO != endO)
{
int i = 0;
double v;
/*
double target;
int c;
if (fscanf(input,"%lf",&target)==EOF)
break;*/
// while(1)
// {
// if(i>=max_nr_attr-1) // need one more for index = -1
// {
// max_nr_attr *= 2;
// x = (struct svm_node *) realloc(x,max_nr_attr*sizeof(struct svm_node));
// }
// do {
// c = getc(input);
// if(c=='\n' || c==EOF) goto out2;
// } while(isspace(c));
// ungetc(c,input);
// fscanf(input,"%d:%lf",&x[i].index,&x[i].value);
// ++i;
// }
// out2:
// x[i++].index = -1;
measurements = iter.GetMeasurementVector() ;
// otbMsgDebugMacro( << "Loop on components " << svm_type );
// otbMsgDevMacro( << "Loop on components " << svm_type );
for(i=0; i<numberOfComponentsPerSample; i++)
{
// otbMsgDebugMacro( << i << " " << measurements[i] );
// otbMsgDebugMacro( << "Index "<< x[i].index );
// otbMsgDebugMacro( << "Value "<< x[i].value );
x[i].index = i+1 ;
x[i].value = measurements[i];
// otbMsgDebugMacro( << "Index "<< x[i].index );
// otbMsgDebugMacro( << "Value "<< x[i].value );
// otbMsgDebugMacro( << "-------------------" );
}
x[i].index = -1;
// otbMsgDebugMacro( << "Starting prediction" );
if (predict_probability && (svm_type==C_SVC || svm_type==NU_SVC))
{
// otbMsgDebugMacro( << "With predict" );
v = svm_predict_probability(model,x,prob_estimates);
// otbMsgDebugMacro( << "Value : " << v );
/*fprintf(output,"%g ",v);
for(j=0;j<nr_class;j++)
fprintf(output,"%g ",prob_estimates[j]);
fprintf(output,"\n");*/
}
else
{
// otbMsgDebugMacro( << "Without predict" );
v = svm_predict(model,x);
// otbMsgDebugMacro( << "Value : " << v );
//fprintf(output,"%g\n",v);
}
ClassLabelType classLabel;
// if(nr_class == 2)
// classLabel = static_cast<ClassLabelType>(v+2);
// else
classLabel = static_cast<ClassLabelType>(v);
// otbMsgDebugMacro( << "Add instance " << classLabel );
// otbMsgDebugMacro( << "Add instance ident " << iterO.GetInstanceIdentifier() );
m_Output->AddInstance(classLabel, iterO.GetInstanceIdentifier()) ;
// otbMsgDebugMacro( << "After add instance " << iterO.GetClassLabel() );
++iter;
++iterO;
}
// otbMsgDebugMacro( << "End of iterations " );
if(predict_probability)
{
free(prob_estimates);
free(labels);
}
// otbMsgDebugMacro( << "End of iterations and free" );
// free(x);
delete [] x;
}
......@@ -341,11 +201,3 @@ delete [] x;
} // end of namespace otb
#endif
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment