BUG: Add a workaround to check the model name before serialization.

This workaround is added to avoid a crash in application when build
is made with RelWithDebInfo which is caused by a
boost::archive_exception impossible to be catch.
This workaround break the compatibility with shark model direct
read/write.
It is still possible to read old RF model from OTB.

Modules/Learning/Supervised/include/otbSharkRandomForestsMachineLearningModel.txx

@@ -195,6 +195,8 @@ SharkRandomForestsMachineLearningModel<TInputValue,TOutputValue>
     {
     itkExceptionMacro(<< "Error opening " << filename.c_str() );
     }
+  // Add comment with model file name
+  ofs << "#" << m_RFModel.name() << std::endl;
   shark::TextOutArchive oa(ofs);
   m_RFModel.save(oa,0);
 }
@@ -205,8 +207,25 @@ SharkRandomForestsMachineLearningModel<TInputValue,TOutputValue>
 ::Load(const std::string & filename, const std::string & itkNotUsed(name))
 {
   std::ifstream ifs(filename.c_str());
-  shark::TextInArchive ia(ifs);
-  m_RFModel.load(ia,0);
+  if( ifs.good() )
+    {
+    // Check if the first line is a comment and verify the name of the model in this case.
+    std::string line;
+    getline( ifs, line );
+    if( line.at( 0 ) == '#' )
+      {
+      if( line.find( m_RFModel.name() ) == std::string::npos )
+        itkExceptionMacro( "The model file : " + filename + " cannot be read." );
+      }
+    else
+      {
+      // rewind if first line is not a comment
+      ifs.clear();
+      ifs.seekg( 0, std::ios::beg );
+      }
+    shark::TextInArchive ia( ifs );
+    m_RFModel.load( ia, 0 );
+    }
 }
 
 template <class TInputValue, class TOutputValue>

Modules/Learning/Unsupervised/include/otbSharkKMeansMachineLearningModel.txx

@@ -30,6 +30,7 @@
 #pragma GCC diagnostic ignored "-Wignored-qualifiers"
 #endif
 
+#include "otb_shark.h"
 #include "otbSharkUtils.h"
 #include "shark/Algorithms/Trainers/NormalizeComponentsUnitVariance.h" //normalize
 #include "shark/Algorithms/KMeans.h" //k-means algorithm
@@ -188,9 +189,8 @@ SharkKMeansMachineLearningModel<TInputValue, TOutputValue>
     {
     itkExceptionMacro( << "Error opening " << filename.c_str());
     }
+  ofs << "#" << m_ClusteringModel->name() << std::endl;
   shark::TextOutArchive oa( ofs );
-  std::string name = m_ClusteringModel->name();
-  oa << name;
   m_ClusteringModel->save( oa, 1 );
 }
 
@@ -203,6 +203,7 @@ SharkKMeansMachineLearningModel<TInputValue, TOutputValue>
   std::ifstream ifs( filename.c_str());
   if(ifs.good())
     {
+    // Check if first line contains model name
     std::string line;
     std::getline(ifs, line);
     m_CanRead = line.find(m_ClusteringModel->name()) != std::string::npos;
@@ -211,12 +212,8 @@ SharkKMeansMachineLearningModel<TInputValue, TOutputValue>
   if(!m_CanRead)
     return;
 
-  // Go to the start of the file
-  ifs.seekg(0, std::ios::beg);
   shark::TextInArchive ia( ifs );
-  std::string name;
-  ia & name;
-  m_ClusteringModel->load( ia, 1 );
+  m_ClusteringModel->load( ia, 0 );
   ifs.close();
 }