From c0aa9bd39bc800890b465564b78f6aa4002df2af Mon Sep 17 00:00:00 2001
From: Julien Malik <julien.malik@c-s.fr>
Date: Wed, 17 Oct 2012 00:54:30 +0200
Subject: [PATCH] ENH: ListSampleGenerator, reorganize code, remove a useless
member
---
Code/Learning/otbListSampleGenerator.h | 1 -
Code/Learning/otbListSampleGenerator.txx | 54 ++++++++++--------------
2 files changed, 23 insertions(+), 32 deletions(-)
diff --git a/Code/Learning/otbListSampleGenerator.h b/Code/Learning/otbListSampleGenerator.h
index a49c4d05b2..7bb91e3ed9 100644
--- a/Code/Learning/otbListSampleGenerator.h
+++ b/Code/Learning/otbListSampleGenerator.h
@@ -170,7 +170,6 @@ private:
// useful, when dealing with small polygon area (1 or two pixels)
// false by default
std::string m_ClassKey;
- double m_ClassMinSize;
ListSamplePointerType m_TrainingListSample;
ListLabelPointerType m_TrainingListLabel;
diff --git a/Code/Learning/otbListSampleGenerator.txx b/Code/Learning/otbListSampleGenerator.txx
index f022a98079..033d1c90be 100644
--- a/Code/Learning/otbListSampleGenerator.txx
+++ b/Code/Learning/otbListSampleGenerator.txx
@@ -65,8 +65,7 @@ ListSampleGenerator<TImage, TVectorData>
m_MaxValidationSize(-1),
m_ValidationTrainingProportion(0.0),
m_PolygonEdgeInclusion(false),
- m_ClassKey("Class"),
- m_ClassMinSize(-1)
+ m_ClassKey("Class")
{
this->SetNumberOfRequiredInputs(2);
this->SetNumberOfRequiredOutputs(1);
@@ -263,27 +262,6 @@ ListSampleGenerator<TImage, TVectorData>
}
}
- // Compute the class with the minimum number of pixels
- if (!m_ClassesSize.empty())
- {
- double minSize = itk::NumericTraits<double>::max();
-
- for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesSize.begin();
- itmap != m_ClassesSize.end();
- ++itmap)
- {
- if (minSize > itmap->second)
- {
- minSize = itmap->second;
- }
- }
-
- m_ClassMinSize = minSize;
- }
- else
- {
- itkGenericExceptionMacro(<< "No training sample found inside image")
- }
}
template <class TImage, class TVectorData>
@@ -293,16 +271,30 @@ ListSampleGenerator<TImage, TVectorData>
{
m_ClassesProbTraining.clear();
m_ClassesProbValidation.clear();
+
+ // Sanity check
+ if (m_ClassesSize.empty())
+ {
+ itkGenericExceptionMacro(<< "No training sample found inside image");
+ }
- //Go through the classes size to find the smallest one
- double minSizeTraining = m_ClassMinSize;
- double minSizeValidation = minSizeTraining;
+ // Go through the classes size to find the smallest one
+ double minSize = itk::NumericTraits<double>::max();
+ for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesSize.begin();
+ itmap != m_ClassesSize.end();
+ ++itmap)
+ {
+ if (minSize > itmap->second)
+ {
+ minSize = itmap->second;
+ }
+ }
- //Apply the proportion between training and validation samples (all training by default)
- minSizeTraining *= (1.0 - m_ValidationTrainingProportion);
- minSizeValidation *= m_ValidationTrainingProportion;
+ // Apply the proportion between training and validation samples (all training by default)
+ double minSizeTraining = minSize * (1.0 - m_ValidationTrainingProportion);
+ double minSizeValidation = minSize * m_ValidationTrainingProportion;
- //Apply the limit if specified by the user
+ // Apply the limit if specified by the user
if ((m_MaxTrainingSize != -1) && (m_MaxTrainingSize < minSizeTraining))
{
minSizeTraining = m_MaxTrainingSize;
@@ -312,7 +304,7 @@ ListSampleGenerator<TImage, TVectorData>
minSizeValidation = m_MaxValidationSize;
}
- //Compute the probability selection for each class
+ // Compute the probability selection for each class
for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesSize.begin();
itmap != m_ClassesSize.end();
++itmap)
--
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