FlannIndex.h

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/*
Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
 
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.
    * 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.
    * Neither the name of the Universite de Sherbrooke nor the
      names of its contributors may be used to endorse or promote products
      derived from this software without specific prior written permission.
 
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "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 COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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*/
 
#ifndef CORELIB_SRC_FLANNINDEX_H_
#define CORELIB_SRC_FLANNINDEX_H_
 
#include "rtabmap/core/rtabmap_core_export.h" // DLL export/import defines
#include <list>
#include <opencv2/opencv.hpp>
 
namespace rtabmap {
 
class RTABMAP_CORE_EXPORT FlannIndex
{
public:
        FlannIndex();
        virtual ~FlannIndex();
 
        void release();
        size_t indexedFeatures() const;
 
        // return Bytes
        size_t memoryUsed() const;
 
        // Note that useDistanceL1 doesn't have any effect if LSH is used
        void buildLinearIndex(
                        const cv::Mat & features,
                        bool useDistanceL1 = false,
                        float rebalancingFactor = 2.0f);
        void buildKDTreeIndex(
                        const cv::Mat & features,
                        int trees = 4,
                        bool useDistanceL1 = false,
                        float rebalancingFactor = 2.0f);
        void buildKDTreeSingleIndex(
                        const cv::Mat & features,
                        int leafMaxSize = 10,
                        bool reorder = true,
                        bool useDistanceL1 = false,
                        float rebalancingFactor = 2.0f);
        void buildLSHIndex(
                        const cv::Mat & features,
                        unsigned int table_number = 12,
                        unsigned int key_size = 20,
                        unsigned int multi_probe_level = 2,
                        float rebalancingFactor = 2.0f);
 
        bool isBuilt();
 
        int featuresType() const {return featuresType_;}
        int featuresDim() const {return featuresDim_;}
 
        std::vector<unsigned int> addPoints(const cv::Mat & features);
 
        void removePoint(unsigned int index);
 
        // return squared distances (indices should be casted in size_t)
        void knnSearch(
                        const cv::Mat & query,
                        cv::Mat & indices,
                        cv::Mat & dists,
                int knn,
                        int checks = 32,
                        float eps = 0.0,
                        bool sorted = true) const;
 
        // return squared distances
        void radiusSearch(
                        const cv::Mat & query,
                        std::vector<std::vector<size_t> > & indices,
                        std::vector<std::vector<float> > & dists,
                        float radius,
                        int maxNeighbors = 0,
                        int checks = 32,
                        float eps = 0.0,
                        bool sorted = true) const;
 
private:
        void * index_;
        unsigned int nextIndex_;
        int featuresType_;
        int featuresDim_;
        bool isLSH_;
        bool useDistanceL1_; // true=EUCLEDIAN_L2 false=MANHATTAN_L1
        float rebalancingFactor_;
 
        // keep feature in memory until the tree is rebuilt
        // (in case the word is deleted when removed from the VWDictionary)
        std::map<int, cv::Mat> addedDescriptors_;
        std::list<int> removedIndexes_;
};
 
} /* namespace rtabmap */
 
#endif /* CORELIB_SRC_FLANNINDEX_H_ */