From: Marius Muja Date: Thu, 27 Sep 2012 10:58:17 +0000 (-0700) Subject: Exposed HierarchicalClusteringIndex in OpenCV wrapper X-Git-Tag: accepted/2.0/20130307.220821~364^2~158 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=7236858bea3c4da1c0cb7c6ccaf62fed184926e1;p=profile%2Fivi%2Fopencv.git Exposed HierarchicalClusteringIndex in OpenCV wrapper --- diff --git a/modules/flann/include/opencv2/flann/defines.h b/modules/flann/include/opencv2/flann/defines.h index 178f07b..13833b3 100644 --- a/modules/flann/include/opencv2/flann/defines.h +++ b/modules/flann/include/opencv2/flann/defines.h @@ -137,6 +137,7 @@ enum flann_distance_t FLANN_DIST_CS = 7, FLANN_DIST_KULLBACK_LEIBLER = 8, FLANN_DIST_KL = 8, + FLANN_DIST_HAMMING = 9, // deprecated constants, should use the FLANN_DIST_* ones instead EUCLIDEAN = 1, diff --git a/modules/flann/include/opencv2/flann/hierarchical_clustering_index.h b/modules/flann/include/opencv2/flann/hierarchical_clustering_index.h index 3b61bd2..a7c6e1b 100644 --- a/modules/flann/include/opencv2/flann/hierarchical_clustering_index.h +++ b/modules/flann/include/opencv2/flann/hierarchical_clustering_index.h @@ -619,13 +619,13 @@ private: if (checks>=maxChecks) { if (result.full()) return; } - checks += node->size; for (int i=0; isize; ++i) { int index = node->indices[i]; if (!checked[index]) { DistanceType dist = distance(dataset[index], vec, veclen_); result.addPoint(dist, index); checked[index] = true; + ++checks; } } } diff --git a/modules/flann/include/opencv2/flann/miniflann.hpp b/modules/flann/include/opencv2/flann/miniflann.hpp index d7fd90f..04249bf 100644 --- a/modules/flann/include/opencv2/flann/miniflann.hpp +++ b/modules/flann/include/opencv2/flann/miniflann.hpp @@ -100,6 +100,12 @@ struct CV_EXPORTS AutotunedIndexParams : public IndexParams float memory_weight = 0, float sample_fraction = 0.1); }; +struct CV_EXPORTS HierarchicalClusteringIndexParams : public IndexParams +{ + HierarchicalClusteringIndexParams(int branching = 32, + cvflann::flann_centers_init_t centers_init = cvflann::FLANN_CENTERS_RANDOM, int trees = 4, int leaf_size = 100 ); +}; + struct CV_EXPORTS KMeansIndexParams : public IndexParams { KMeansIndexParams(int branching = 32, int iterations = 11, diff --git a/modules/flann/src/miniflann.cpp b/modules/flann/src/miniflann.cpp index e1dbe5b..972ae72 100644 --- a/modules/flann/src/miniflann.cpp +++ b/modules/flann/src/miniflann.cpp @@ -256,17 +256,33 @@ KMeansIndexParams::KMeansIndexParams(int branching, int iterations, // cluster boundary index. Used when searching the kmeans tree p["cb_index"] = cb_index; } + +HierarchicalClusteringIndexParams::HierarchicalClusteringIndexParams(int branching , + flann_centers_init_t centers_init, + int trees, int leaf_size) +{ + ::cvflann::IndexParams& p = get_params(*this); + p["algorithm"] = FLANN_INDEX_HIERARCHICAL; + // The branching factor used in the hierarchical clustering + p["branching"] = branching; + // Algorithm used for picking the initial cluster centers + p["centers_init"] = centers_init; + // number of parallel trees to build + p["trees"] = trees; + // maximum leaf size + p["leaf_size"] = leaf_size; +} LshIndexParams::LshIndexParams(int table_number, int key_size, int multi_probe_level) { ::cvflann::IndexParams& p = get_params(*this); p["algorithm"] = FLANN_INDEX_LSH; // The number of hash tables to use - p["table_number"] = (unsigned)table_number; + p["table_number"] = table_number; // The length of the key in the hash tables - p["key_size"] = (unsigned)key_size; + p["key_size"] = key_size; // Number of levels to use in multi-probe (0 for standard LSH) - p["multi_probe_level"] = (unsigned)multi_probe_level; + p["multi_probe_level"] = multi_probe_level; } SavedIndexParams::SavedIndexParams(const std::string& _filename) @@ -317,7 +333,6 @@ typedef ::cvflann::Hamming HammingDistance; #else typedef ::cvflann::HammingLUT HammingDistance; #endif -typedef ::cvflann::LshIndex LshIndex; Index::Index() { @@ -351,14 +366,11 @@ void Index::build(InputArray _data, const IndexParams& params, flann_distance_t featureType = data.type(); distType = _distType; - if( algo == FLANN_INDEX_LSH ) - { - buildIndex_(index, data, params); - return; - } - switch( distType ) { + case FLANN_DIST_HAMMING: + buildIndex< HammingDistance >(index, data, params); + break; case FLANN_DIST_L2: buildIndex< ::cvflann::L2 >(index, data, params); break; @@ -406,15 +418,12 @@ void Index::release() { if( !index ) return; - if( algo == FLANN_INDEX_LSH ) - { - deleteIndex_(index); - } - else + + switch( distType ) { - CV_Assert( featureType == CV_32F ); - switch( distType ) - { + case FLANN_DIST_HAMMING: + deleteIndex< HammingDistance >(index); + break; case FLANN_DIST_L2: deleteIndex< ::cvflann::L2 >(index); break; @@ -440,7 +449,6 @@ void Index::release() #endif default: CV_Error(CV_StsBadArg, "Unknown/unsupported distance type"); - } } index = 0; } @@ -539,18 +547,15 @@ void Index::knnSearch(InputArray _query, OutputArray _indices, OutputArray _dists, int knn, const SearchParams& params) { Mat query = _query.getMat(), indices, dists; - int dtype = algo == FLANN_INDEX_LSH ? CV_32S : CV_32F; + int dtype = distType == FLANN_DIST_HAMMING ? CV_32S : CV_32F; createIndicesDists( _indices, _dists, indices, dists, query.rows, knn, knn, dtype ); - if( algo == FLANN_INDEX_LSH ) - { - runKnnSearch_(index, query, indices, dists, knn, params); - return; - } - switch( distType ) { + case FLANN_DIST_HAMMING: + runKnnSearch(index, query, indices, dists, knn, params); + break; case FLANN_DIST_L2: runKnnSearch< ::cvflann::L2 >(index, query, indices, dists, knn, params); break; @@ -584,7 +589,7 @@ int Index::radiusSearch(InputArray _query, OutputArray _indices, const SearchParams& params) { Mat query = _query.getMat(), indices, dists; - int dtype = algo == FLANN_INDEX_LSH ? CV_32S : CV_32F; + int dtype = distType == FLANN_DIST_HAMMING ? CV_32S : CV_32F; CV_Assert( maxResults > 0 ); createIndicesDists( _indices, _dists, indices, dists, query.rows, maxResults, INT_MAX, dtype ); @@ -593,6 +598,9 @@ int Index::radiusSearch(InputArray _query, OutputArray _indices, switch( distType ) { + case FLANN_DIST_HAMMING: + return runRadiusSearch< HammingDistance >(index, query, indices, dists, radius, params); + case FLANN_DIST_L2: return runRadiusSearch< ::cvflann::L2 >(index, query, indices, dists, radius, params); case FLANN_DIST_L1: @@ -647,15 +655,11 @@ void Index::save(const std::string& filename) const if (fout == NULL) CV_Error_( CV_StsError, ("Can not open file %s for writing FLANN index\n", filename.c_str()) ); - if( algo == FLANN_INDEX_LSH ) - { - saveIndex_(this, index, fout); - fclose(fout); - return; - } - switch( distType ) { + case FLANN_DIST_HAMMING: + saveIndex< HammingDistance >(this, index, fout); + break; case FLANN_DIST_L2: saveIndex< ::cvflann::L2 >(this, index, fout); break; @@ -739,54 +743,51 @@ bool Index::load(InputArray _data, const std::string& filename) return false; } - if( !((algo == FLANN_INDEX_LSH && featureType == CV_8U) || - (algo != FLANN_INDEX_LSH && featureType == CV_32F)) ) + int idistType = 0; + ::cvflann::load_value(fin, idistType); + distType = (flann_distance_t)idistType; + + if( !((distType == FLANN_DIST_HAMMING && featureType == CV_8U) || + (distType != FLANN_DIST_HAMMING && featureType == CV_32F)) ) { fprintf(stderr, "Reading FLANN index error: unsupported feature type %d for the index type %d\n", featureType, algo); fclose(fin); return false; } - int idistType = 0; - ::cvflann::load_value(fin, idistType); - distType = (flann_distance_t)idistType; - if( algo == FLANN_INDEX_LSH ) - { - loadIndex_(this, index, data, fin); - } - else + switch( distType ) { - switch( distType ) - { - case FLANN_DIST_L2: - loadIndex< ::cvflann::L2 >(this, index, data, fin); - break; - case FLANN_DIST_L1: - loadIndex< ::cvflann::L1 >(this, index, data, fin); - break; - #if MINIFLANN_SUPPORT_EXOTIC_DISTANCE_TYPES - case FLANN_DIST_MAX: - loadIndex< ::cvflann::MaxDistance >(this, index, data, fin); - break; - case FLANN_DIST_HIST_INTERSECT: - loadIndex< ::cvflann::HistIntersectionDistance >(index, data, fin); - break; - case FLANN_DIST_HELLINGER: - loadIndex< ::cvflann::HellingerDistance >(this, index, data, fin); - break; - case FLANN_DIST_CHI_SQUARE: - loadIndex< ::cvflann::ChiSquareDistance >(this, index, data, fin); - break; - case FLANN_DIST_KL: - loadIndex< ::cvflann::KL_Divergence >(this, index, data, fin); - break; - #endif - default: - fprintf(stderr, "Reading FLANN index error: unsupported distance type %d\n", distType); - ok = false; - } + case FLANN_DIST_HAMMING: + loadIndex< HammingDistance >(this, index, data, fin); + break; + case FLANN_DIST_L2: + loadIndex< ::cvflann::L2 >(this, index, data, fin); + break; + case FLANN_DIST_L1: + loadIndex< ::cvflann::L1 >(this, index, data, fin); + break; +#if MINIFLANN_SUPPORT_EXOTIC_DISTANCE_TYPES + case FLANN_DIST_MAX: + loadIndex< ::cvflann::MaxDistance >(this, index, data, fin); + break; + case FLANN_DIST_HIST_INTERSECT: + loadIndex< ::cvflann::HistIntersectionDistance >(index, data, fin); + break; + case FLANN_DIST_HELLINGER: + loadIndex< ::cvflann::HellingerDistance >(this, index, data, fin); + break; + case FLANN_DIST_CHI_SQUARE: + loadIndex< ::cvflann::ChiSquareDistance >(this, index, data, fin); + break; + case FLANN_DIST_KL: + loadIndex< ::cvflann::KL_Divergence >(this, index, data, fin); + break; +#endif + default: + fprintf(stderr, "Reading FLANN index error: unsupported distance type %d\n", distType); + ok = false; } - + if( fin ) fclose(fin); return ok;