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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_NNINDEX_H
-#define OPENCV_FLANN_NNINDEX_H
-
-#include <string>
-
-#include "general.h"
-#include "matrix.h"
-#include "result_set.h"
-#include "params.h"
-
-namespace cvflann
-{
-
-/**
- * Nearest-neighbour index base class
- */
-template <typename Distance>
-class NNIndex
-{
- typedef typename Distance::ElementType ElementType;
- typedef typename Distance::ResultType DistanceType;
-
-public:
-
- virtual ~NNIndex() {}
-
- /**
- * \brief Builds the index
- */
- virtual void buildIndex() = 0;
-
- /**
- * \brief implementation for algorithms of addable indexes after that.
- */
- virtual void addIndex(const Matrix<ElementType>& wholeData, const Matrix<ElementType>& additionalData) = 0;
-
- /**
- * \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
- */
- virtual void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
- {
- assert(queries.cols == veclen());
- assert(indices.rows >= queries.rows);
- assert(dists.rows >= queries.rows);
- assert(int(indices.cols) >= knn);
- assert(int(dists.cols) >= knn);
-
-#if 0
- KNNResultSet<DistanceType> resultSet(knn);
- for (size_t i = 0; i < queries.rows; i++) {
- resultSet.init(indices[i], dists[i]);
- findNeighbors(resultSet, queries[i], params);
- }
-#else
- KNNUniqueResultSet<DistanceType> resultSet(knn);
- for (size_t i = 0; i < queries.rows; i++) {
- resultSet.clear();
- findNeighbors(resultSet, queries[i], params);
- if (get_param(params,"sorted",true)) resultSet.sortAndCopy(indices[i], dists[i], knn);
- else resultSet.copy(indices[i], dists[i], knn);
- }
-#endif
- }
-
- /**
- * \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
- */
- virtual int radiusSearch(const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params)
- {
- if (query.rows != 1) {
- fprintf(stderr, "I can only search one feature at a time for range search\n");
- return -1;
- }
- assert(query.cols == veclen());
- assert(indices.cols == dists.cols);
-
- int n = 0;
- int* indices_ptr = NULL;
- DistanceType* dists_ptr = NULL;
- if (indices.cols > 0) {
- n = (int)indices.cols;
- indices_ptr = indices[0];
- dists_ptr = dists[0];
- }
-
- RadiusUniqueResultSet<DistanceType> resultSet((DistanceType)radius);
- resultSet.clear();
- findNeighbors(resultSet, query[0], params);
- if (n>0) {
- if (get_param(params,"sorted",true)) resultSet.sortAndCopy(indices_ptr, dists_ptr, n);
- else resultSet.copy(indices_ptr, dists_ptr, n);
- }
-
- return (int)resultSet.size();
- }
-
- /**
- * \brief Saves the index to a stream
- * \param stream The stream to save the index to
- */
- virtual void saveIndex(FILE* stream) = 0;
-
- /**
- * \brief Loads the index from a stream
- * \param stream The stream from which the index is loaded
- */
- virtual void loadIndex(FILE* stream) = 0;
-
- /**
- * \returns number of features in this index.
- */
- virtual size_t size() const = 0;
-
- /**
- * \returns The dimensionality of the features in this index.
- */
- virtual size_t veclen() const = 0;
-
- /**
- * \returns The amount of memory (in bytes) used by the index.
- */
- virtual int usedMemory() const = 0;
-
- /**
- * \returns The index type (kdtree, kmeans,...)
- */
- virtual flann_algorithm_t getType() const = 0;
-
- /**
- * \returns The index parameters
- */
- virtual IndexParams getParameters() const = 0;
-
-
- /**
- * \brief Method that searches for nearest-neighbours
- */
- virtual void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) = 0;
-};
-
-}
-
-#endif //OPENCV_FLANN_NNINDEX_H
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