Diff: include/opencv2/flann/flann_base.hpp

Revision:

0:0e0631af0305

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+++ b/include/opencv2/flann/flann_base.hpp	Fri Jan 29 04:53:38 2021 +0000
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+/***********************************************************************
+ * Software License Agreement (BSD License)
+ *
+ * Copyright 2008-2009  Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
+ * Copyright 2008-2009  David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
+ *
+ * THE BSD LICENSE
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions
+ * are met:
+ *
+ * 1. Redistributions of source code must retain the above copyright
+ *    notice, this list of conditions and the following disclaimer.
+ * 2. Redistributions in binary form must reproduce the above copyright
+ *    notice, this list of conditions and the following disclaimer in the
+ *    documentation and/or other materials provided with the distribution.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
+ * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
+ * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
+ * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
+ * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
+ * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+ * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+ * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
+ * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *************************************************************************/
+
+#ifndef OPENCV_FLANN_BASE_HPP_
+#define OPENCV_FLANN_BASE_HPP_
+
+#include <vector>
+#include <cassert>
+#include <cstdio>
+
+#include "general.h"
+#include "matrix.h"
+#include "params.h"
+#include "saving.h"
+
+#include "all_indices.h"
+
+namespace cvflann
+{
+
+/**
+ * Sets the log level used for all flann functions
+ * @param level Verbosity level
+ */
+inline void log_verbosity(int level)
+{
+    if (level >= 0) {
+        Logger::setLevel(level);
+    }
+}
+
+/**
+ * (Deprecated) Index parameters for creating a saved index.
+ */
+struct SavedIndexParams : public IndexParams
+{
+    SavedIndexParams(cv::String filename)
+    {
+        (* this)["algorithm"] = FLANN_INDEX_SAVED;
+        (*this)["filename"] = filename;
+    }
+};
+
+
+template<typename Distance>
+NNIndex<Distance>* load_saved_index(const Matrix<typename Distance::ElementType>& dataset, const cv::String& filename, Distance distance)
+{
+    typedef typename Distance::ElementType ElementType;
+
+    FILE* fin = fopen(filename.c_str(), "rb");
+    if (fin == NULL) {
+        return NULL;
+    }
+    IndexHeader header = load_header(fin);
+    if (header.data_type != Datatype<ElementType>::type()) {
+        throw FLANNException("Datatype of saved index is different than of the one to be created.");
+    }
+    if ((size_t(header.rows) != dataset.rows)||(size_t(header.cols) != dataset.cols)) {
+        throw FLANNException("The index saved belongs to a different dataset");
+    }
+
+    IndexParams params;
+    params["algorithm"] = header.index_type;
+    NNIndex<Distance>* nnIndex = create_index_by_type<Distance>(dataset, params, distance);
+    nnIndex->loadIndex(fin);
+    fclose(fin);
+
+    return nnIndex;
+}
+
+
+template<typename Distance>
+class Index : public NNIndex<Distance>
+{
+public:
+    typedef typename Distance::ElementType ElementType;
+    typedef typename Distance::ResultType DistanceType;
+
+    Index(const Matrix<ElementType>& features, const IndexParams& params, Distance distance = Distance() )
+        : index_params_(params)
+    {
+        flann_algorithm_t index_type = get_param<flann_algorithm_t>(params,"algorithm");
+        loaded_ = false;
+
+        if (index_type == FLANN_INDEX_SAVED) {
+            nnIndex_ = load_saved_index<Distance>(features, get_param<cv::String>(params,"filename"), distance);
+            loaded_ = true;
+        }
+        else {
+            nnIndex_ = create_index_by_type<Distance>(features, params, distance);
+        }
+    }
+
+    ~Index()
+    {
+        delete nnIndex_;
+    }
+
+    /**
+     * Builds the index.
+     */
+    void buildIndex()
+    {
+        if (!loaded_) {
+            nnIndex_->buildIndex();
+        }
+    }
+
+    void save(cv::String filename)
+    {
+        FILE* fout = fopen(filename.c_str(), "wb");
+        if (fout == NULL) {
+            throw FLANNException("Cannot open file");
+        }
+        save_header(fout, *nnIndex_);
+        saveIndex(fout);
+        fclose(fout);
+    }
+
+    /**
+     * \brief Saves the index to a stream
+     * \param stream The stream to save the index to
+     */
+    virtual void saveIndex(FILE* stream)
+    {
+        nnIndex_->saveIndex(stream);
+    }
+
+    /**
+     * \brief Loads the index from a stream
+     * \param stream The stream from which the index is loaded
+     */
+    virtual void loadIndex(FILE* stream)
+    {
+        nnIndex_->loadIndex(stream);
+    }
+
+    /**
+     * \returns number of features in this index.
+     */
+    size_t veclen() const
+    {
+        return nnIndex_->veclen();
+    }
+
+    /**
+     * \returns The dimensionality of the features in this index.
+     */
+    size_t size() const
+    {
+        return nnIndex_->size();
+    }
+
+    /**
+     * \returns The index type (kdtree, kmeans,...)
+     */
+    flann_algorithm_t getType() const
+    {
+        return nnIndex_->getType();
+    }
+
+    /**
+     * \returns The amount of memory (in bytes) used by the index.
+     */
+    virtual int usedMemory() const
+    {
+        return nnIndex_->usedMemory();
+    }
+
+
+    /**
+     * \returns The index parameters
+     */
+    IndexParams getParameters() const
+    {
+        return nnIndex_->getParameters();
+    }
+
+    /**
+     * \brief Perform k-nearest neighbor search
+     * \param[in] queries The query points for which to find the nearest neighbors
+     * \param[out] indices The indices of the nearest neighbors found
+     * \param[out] dists Distances to the nearest neighbors found
+     * \param[in] knn Number of nearest neighbors to return
+     * \param[in] params Search parameters
+     */
+    void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
+    {
+        nnIndex_->knnSearch(queries, indices, dists, knn, params);
+    }
+
+    /**
+     * \brief Perform radius search
+     * \param[in] query The query point
+     * \param[out] indices The indinces of the neighbors found within the given radius
+     * \param[out] dists The distances to the nearest neighbors found
+     * \param[in] radius The radius used for search
+     * \param[in] params Search parameters
+     * \returns Number of neighbors found
+     */
+    int radiusSearch(const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params)
+    {
+        return nnIndex_->radiusSearch(query, indices, dists, radius, params);
+    }
+
+    /**
+     * \brief Method that searches for nearest-neighbours
+     */
+    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
+    {
+        nnIndex_->findNeighbors(result, vec, searchParams);
+    }
+
+    /**
+     * \brief Returns actual index
+     */
+    FLANN_DEPRECATED NNIndex<Distance>* getIndex()
+    {
+        return nnIndex_;
+    }
+
+    /**
+     * \brief Returns index parameters.
+     * \deprecated use getParameters() instead.
+     */
+    FLANN_DEPRECATED  const IndexParams* getIndexParameters()
+    {
+        return &index_params_;
+    }
+
+private:
+    /** Pointer to actual index class */
+    NNIndex<Distance>* nnIndex_;
+    /** Indices if the index was loaded from a file */
+    bool loaded_;
+    /** Parameters passed to the index */
+    IndexParams index_params_;
+};
+
+/**
+ * Performs a hierarchical clustering of the points passed as argument and then takes a cut in the
+ * the clustering tree to return a flat clustering.
+ * @param[in] points Points to be clustered
+ * @param centers The computed cluster centres. Matrix should be preallocated and centers.rows is the
+ *  number of clusters requested.
+ * @param params Clustering parameters (The same as for cvflann::KMeansIndex)
+ * @param d Distance to be used for clustering (eg: cvflann::L2)
+ * @return number of clusters computed (can be different than clusters.rows and is the highest number
+ * of the form (branching-1)*K+1 smaller than clusters.rows).
+ */
+template <typename Distance>
+int hierarchicalClustering(const Matrix<typename Distance::ElementType>& points, Matrix<typename Distance::ResultType>& centers,
+                           const KMeansIndexParams& params, Distance d = Distance())
+{
+    KMeansIndex<Distance> kmeans(points, params, d);
+    kmeans.buildIndex();
+
+    int clusterNum = kmeans.getClusterCenters(centers);
+    return clusterNum;
+}
+
+}
+#endif /* OPENCV_FLANN_BASE_HPP_ */