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Fixing VS warning

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This commit is contained in:
Vladislav Samsonov
2016-07-25 03:57:23 +03:00
parent 2016e90c7d
commit ab130c76b9
1 changed files with 7 additions and 7 deletions
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14
modules/optflow/src/sparse_matching_gpc.cpp
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@@ -56,7 +56,7 @@ const double thresholdMagnitudeFrac = 0.6666666666;
const int globalIters = 3;
const int localIters = 500;
const unsigned minNumberOfSamples = 2;
const bool debugOutput = true;
//const bool debugOutput = true;
struct Magnitude
{
@@ -116,8 +116,8 @@ void getTrainingSamples( const Mat &from, const Mat &to, const Mat &gt, GPCSampl
for ( int j = patchRadius; j + patchRadius < sz.width; ++j )
mag.push_back( Magnitude( normL2Sqr( gt.at< Vec2f >( i, j ) ), i, j ) );
size_t n = mag.size() * thresholdMagnitudeFrac; // As suggested in the paper, we discard part of the training samples
// with a small displacement and train to better distinguish hard pairs.
size_t n = size_t(mag.size() * thresholdMagnitudeFrac); // As suggested in the paper, we discard part of the training samples
// with a small displacement and train to better distinguish hard pairs.
std::nth_element( mag.begin(), mag.begin() + n, mag.end() );
mag.resize( n );
std::random_shuffle( mag.begin(), mag.end() );
@@ -242,14 +242,14 @@ bool GPCTree::trainNode( size_t nodeId, SIter begin, SIter end, unsigned depth )
node.coef = coef;
node.rhs = median;
if ( debugOutput )
/*if ( debugOutput )
{
printf( "[%u] Updating weights: correct %.2f (%u/%ld)\n", depth, double( correct ) / std::distance( begin, end ), correct,
std::distance( begin, end ) );
for ( unsigned k = 0; k < GPCPatchDescriptor::nFeatures; ++k )
printf( "%.3f ", coef[k] );
printf( "\n" );
}
}*/
}
}
}
@@ -260,8 +260,8 @@ bool GPCTree::trainNode( size_t nodeId, SIter begin, SIter end, unsigned depth )
SIter rightBegin =
std::partition( leftEnd, end, PartitionPredicate2( node.coef, node.rhs ) ); // Separate undefined samples from right subtree samples.
node.left = ( trainNode( nodeId * 2 + 1, begin, leftEnd, depth + 1 ) ) ? nodeId * 2 + 1 : 0;
node.right = ( trainNode( nodeId * 2 + 2, rightBegin, end, depth + 1 ) ) ? nodeId * 2 + 2 : 0;
node.left = ( trainNode( nodeId * 2 + 1, begin, leftEnd, depth + 1 ) ) ? unsigned(nodeId * 2 + 1) : 0;
node.right = ( trainNode( nodeId * 2 + 2, rightBegin, end, depth + 1 ) ) ? unsigned(nodeId * 2 + 2) : 0;
return true;
}