for( int qIdx = 0; qIdx < queryDescriptors.rows; qIdx++ )
{
- if( maskedOut( masks, qIdx ) )
+ if( isMaskedOut( masks, qIdx ) )
{
if( !compactResult ) // push empty vector
matches.push_back( vector<DMatch>() );
for( int qIdx = 0; qIdx < queryDescriptors.rows; qIdx++ )
{
- if( maskedOut( masks, qIdx ) )
+ if( isMaskedOut( masks, qIdx ) )
{
if( !compactResult ) // push empty vector
matches.push_back( vector<DMatch>() );
assert( e_allDists[iIdx].rows() == trainDescCollection[iIdx].rows );
for( int tIdx = 0; tIdx < e_allDists[iIdx].rows(); tIdx++ )
{
- if( masks.empty() || possibleMatch(masks[iIdx], qIdx, tIdx) )
+ if( masks.empty() || isPossibleMatch(masks[iIdx], qIdx, tIdx) )
{
float d = sqrt((-2)*e_allDists[iIdx](tIdx) + queryNorm2);
if( d < maxDistance )