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FlannBasedMatcher(LshIndex) in the feature2d optimization for continuance additional train()

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Current implementation of miniflann is releasing the trained index, and
rebuilding the index from the beginning.
But, some indexing algorithms like the LSH are able to add the indexing
data after that.
This branch is implementation of that optimization for LshIndex
FlannBasedMatcher in the feature2d.
This commit is contained in:
ippei ito
2015-03-14 04:38:07 +09:00
parent 29e7eb7719
commit cd42e38013
14 changed files with 133 additions and 26 deletions
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14
modules/features2d/src/matchers.cpp
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@@ -531,10 +531,20 @@ void FlannBasedMatcher::clear()
void FlannBasedMatcher::train()
{
if( flannIndex.empty() || mergedDescriptors.size() < addedDescCount )
int trained = mergedDescriptors.size();
if (flannIndex.empty() || trained < addedDescCount)
{
mergedDescriptors.set( trainDescCollection );
flannIndex = new flann::Index( mergedDescriptors.getDescriptors(), *indexParams );
// construct flannIndex class, if empty or Algorithm not equal FLANN_INDEX_LSH
if (flannIndex.empty() || flannIndex->getAlgorithm() != cvflann::FLANN_INDEX_LSH)
{
flannIndex = new flann::Index(mergedDescriptors.getDescriptors(), *indexParams);
}
else
{
flannIndex->build(mergedDescriptors.getDescriptors(), mergedDescriptors.getDescriptors().rowRange(trained, mergedDescriptors.size()), *indexParams, cvflann::FLANN_DIST_HAMMING);
}
}
}